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Posted to commits@hudi.apache.org by GitBox <gi...@apache.org> on 2022/06/22 22:27:33 UTC
[GitHub] [hudi] CTTY opened a new pull request, #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
CTTY opened a new pull request, #5943:
URL: https://github.com/apache/hudi/pull/5943
## *Tips*
- *Thank you very much for contributing to Apache Hudi.*
- *Please review https://hudi.apache.org/contribute/how-to-contribute before opening a pull request.*
## What is the purpose of the pull request
Support Spark 3.3.0
## Brief change log
*(for example:)*
- *Modify AnnotationLocation checkstyle rule in checkstyle.xml*
## Verify this pull request
*(Please pick either of the following options)*
This pull request is a trivial rework / code cleanup without any test coverage.
*(or)*
This pull request is already covered by existing tests, such as *(please describe tests)*.
(or)
This change added tests and can be verified as follows:
*(example:)*
- *Added integration tests for end-to-end.*
- *Added HoodieClientWriteTest to verify the change.*
- *Manually verified the change by running a job locally.*
## Committer checklist
- [ ] Has a corresponding JIRA in PR title & commit
- [ ] Commit message is descriptive of the change
- [ ] CI is green
- [ ] Necessary doc changes done or have another open PR
- [ ] For large changes, please consider breaking it into sub-tasks under an umbrella JIRA.
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1183955446
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r919516291
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/analysis/HoodieAnalysis.scala:
##########
@@ -413,10 +416,13 @@ case class HoodieResolveReferences(sparkSession: SparkSession) extends Rule[Logi
// Resolve Delete Table
case DeleteFromTable(table, condition)
if sparkAdapter.isHoodieTable(table, sparkSession) && table.resolved =>
- // Resolve condition
- val resolvedCondition = condition.map(resolveExpressionFrom(table)(_))
+ val unwrappedCondition: Expression = condition match {
Review Comment:
[SPARK-38626](https://github.com/apache/spark/pull/35941) Make condition in DeleteFromTable plan required
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1192094190
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1197089899
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931580643
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/parser/HoodieCommonSqlParser.scala:
##########
@@ -57,6 +57,14 @@ class HoodieCommonSqlParser(session: SparkSession, delegate: ParserInterface)
override def parseDataType(sqlText: String): DataType = delegate.parseDataType(sqlText)
+ /* SPARK-37266 Added parseQuery to ParserInterface in Spark 3.3.0. This is a patch to prevent
+ hackers from tampering text with persistent view, it won't be called in older Spark
+ Don't mark this as override for backward compatibility
+ Can't use sparkExtendedParser directly here due to the same reason */
+ def parseQuery(sqlText: String): LogicalPlan = parse(sqlText) { parser =>
Review Comment:
I reused the code flow from `parsePlan` method under the same class here. Calling `parse` might not be needed here. good point
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1183867585
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186305422
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193028433
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[GitHub] [hudi] XuQianJin-Stars commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
XuQianJin-Stars commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928183435
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,12 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
+ .defaultValue("true")
+ .withDocumentation("Sets spark.sql.parquet.fieldId.write.enabled. "
+ + "If enabled, Spark will write out parquet native field ids that are stored inside StructField's metadata as parquet.field.id to parquet files.");
Review Comment:
.sinceVersion("0.12.0")?
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928054937
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/execution/datasources/Spark33NestedSchemaPruning.scala:
##########
@@ -0,0 +1,195 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.datasources
+
+import org.apache.hudi.HoodieBaseRelation
+import org.apache.spark.sql.catalyst.expressions.{And, AttributeReference, AttributeSet, Expression, NamedExpression, ProjectionOverSchema}
+import org.apache.spark.sql.catalyst.planning.PhysicalOperation
+import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.sources.BaseRelation
+import org.apache.spark.sql.types.{ArrayType, DataType, MapType, StructType}
+import org.apache.spark.sql.util.SchemaUtils.restoreOriginalOutputNames
+
+/**
+ * Prunes unnecessary physical columns given a [[PhysicalOperation]] over a data source relation.
+ * By "physical column", we mean a column as defined in the data source format like Parquet format
+ * or ORC format. For example, in Spark SQL, a root-level Parquet column corresponds to a SQL
+ * column, and a nested Parquet column corresponds to a [[StructField]].
+ *
+ * NOTE: This class is borrowed from Spark 3.2.1, with modifications adapting it to handle [[HoodieBaseRelation]],
+ * instead of [[HadoopFsRelation]]
+ */
+class Spark33NestedSchemaPruning extends Rule[LogicalPlan] {
+ import org.apache.spark.sql.catalyst.expressions.SchemaPruning._
+
+ override def apply(plan: LogicalPlan): LogicalPlan =
+ if (conf.nestedSchemaPruningEnabled) {
+ apply0(plan)
+ } else {
+ plan
+ }
+
+ private def apply0(plan: LogicalPlan): LogicalPlan =
+ plan transformDown {
+ case op @ PhysicalOperation(projects, filters,
+ // NOTE: This is modified to accommodate for Hudi's custom relations, given that original
+ // [[NestedSchemaPruning]] rule is tightly coupled w/ [[HadoopFsRelation]]
+ // TODO generalize to any file-based relation
+ l @ LogicalRelation(relation: HoodieBaseRelation, _, _, _))
+ if relation.canPruneRelationSchema =>
+
+ prunePhysicalColumns(l.output, projects, filters, relation.dataSchema,
+ prunedDataSchema => {
+ val prunedRelation =
+ relation.updatePrunedDataSchema(prunedSchema = prunedDataSchema)
+ buildPrunedRelation(l, prunedRelation)
+ }).getOrElse(op)
+ }
+
+ /**
+ * This method returns optional logical plan. `None` is returned if no nested field is required or
+ * all nested fields are required.
+ */
+ private def prunePhysicalColumns(output: Seq[AttributeReference],
+ projects: Seq[NamedExpression],
+ filters: Seq[Expression],
+ dataSchema: StructType,
+ outputRelationBuilder: StructType => LogicalRelation): Option[LogicalPlan] = {
+ val (normalizedProjects, normalizedFilters) =
+ normalizeAttributeRefNames(output, projects, filters)
+ val requestedRootFields = identifyRootFields(normalizedProjects, normalizedFilters)
+
+ // If requestedRootFields includes a nested field, continue. Otherwise,
+ // return op
+ if (requestedRootFields.exists { root: RootField => !root.derivedFromAtt }) {
+ val prunedDataSchema = pruneSchema(dataSchema, requestedRootFields)
+
+ // If the data schema is different from the pruned data schema, continue. Otherwise,
+ // return op. We effect this comparison by counting the number of "leaf" fields in
+ // each schemata, assuming the fields in prunedDataSchema are a subset of the fields
+ // in dataSchema.
+ if (countLeaves(dataSchema) > countLeaves(prunedDataSchema)) {
+ val prunedRelation = outputRelationBuilder(prunedDataSchema)
+ val projectionOverSchema = ProjectionOverSchema(prunedDataSchema,AttributeSet(output))
Review Comment:
This constructor was changed in spark 3.3: https://github.com/apache/spark/pull/36216/files#diff-1164414022404e2b8a8c317d5f13b29715f54fa61d150145cbc9f6107941448f
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193263088
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1192879640
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1189476436
@codope @yihua This is ready to review
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925174999
##########
hudi-spark-datasource/hudi-spark2/src/main/scala/org/apache/hudi/Spark2HoodieFileScanRDD.scala:
##########
@@ -0,0 +1,35 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hudi
+
+import org.apache.hudi.HoodieUnsafeRDD
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.AttributeReference
+import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile}
+import org.apache.spark.sql.types.StructType
+
+class Spark2HoodieFileScanRDD(@transient private val sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ @transient filePartitions: Seq[FilePartition])
+ extends FileScanRDD(sparkSession, readFunction, filePartitions)
+ with HoodieUnsafeRDD {
+
+ override final def collect(): Array[InternalRow] = super[HoodieUnsafeRDD].collect()
+}
Review Comment:
FileScanRDD constructor changed. Split class for Spark2: https://github.com/apache/spark/pull/34575
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925174744
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/procedure/TestCallCommandParser.scala:
##########
@@ -82,7 +82,11 @@ class TestCallCommandParser extends HoodieSparkSqlTestBase {
}
test("Test Call Parse Error") {
- checkParseExceptionContain("CALL cat.system radish kebab")("mismatched input 'CALL' expecting")
+ if (HoodieSparkUtils.gteqSpark3_3_0) {
+ checkParseExceptionContain("CALL cat.system radish kebab")("Syntax error at or near 'CALL'")
+ } else {
+ checkParseExceptionContain("CALL cat.system radish kebab")("mismatched input 'CALL' expecting")
+ }
Review Comment:
Error message changed: https://github.com/apache/spark/pull/35707
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925176179
##########
hudi-spark-datasource/hudi-spark3.2.x/pom.xml:
##########
@@ -0,0 +1,335 @@
+<?xml version="1.0" encoding="UTF-8"?>
Review Comment:
Everything under hudi-spark3.2.x/ are moved from previous hudi-spark3
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193581179
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194742110
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194674788
>
I've added them in hudi-spark-datasource/README.md
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1196043156
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186505737
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r926230911
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/DeleteHoodieTableCommand.scala:
##########
@@ -36,9 +37,13 @@ case class DeleteHoodieTableCommand(deleteTable: DeleteFromTable) extends Hoodie
// Remove meta fields from the data frame
var df = removeMetaFields(Dataset.ofRows(sparkSession, table))
- if (deleteTable.condition.isDefined) {
- df = df.filter(Column(deleteTable.condition.get))
+ // SPARK-38626 DeleteFromTable.condition is changed from Option[Expression] to Expression in Spark 3.3
+ val condition: Expression = deleteTable.condition match {
Review Comment:
If modified like that, I think we would still have to handle the type matching at L133 HoodieAnalysis.scala
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925178178
##########
hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/HoodieSpark3_3SqlUtils.scala:
##########
@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import org.apache.hudi.exception.HoodieException
+import org.apache.spark.sql.catalyst.catalog.BucketSpec
+import org.apache.spark.sql.connector.expressions.{BucketTransform, FieldReference, IdentityTransform, Transform}
+
+import scala.collection.mutable
+
+object HoodieSpark3_3SqlUtils {
+ def convertTransforms(partitions: Seq[Transform]): (Seq[String], Option[BucketSpec]) = {
+ val identityCols = new mutable.ArrayBuffer[String]
+ var bucketSpec = Option.empty[BucketSpec]
+
+ partitions.map {
+ case IdentityTransform(FieldReference(Seq(col))) =>
+ identityCols += col
+
+ case BucketTransform(numBuckets, Seq(FieldReference(Seq(col))), _) =>
+ bucketSpec = Some(BucketSpec(numBuckets, col :: Nil, Nil))
Review Comment:
BucketTransform class changed here. It won't compile if we keep args as before and I'm NOT sure why. Please review this change.
https://github.com/apache/spark/pull/34914
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925174514
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/TestAlterTableDropPartition.scala:
##########
@@ -211,7 +211,7 @@ class TestAlterTableDropPartition extends HoodieSparkSqlTestBase {
// specify duplicate partition columns
checkExceptionContain(s"alter table $tableName drop partition (dt='2021-10-01', dt='2021-10-02')")(
- "Found duplicate keys 'dt'")
+ "Found duplicate keys ")
Review Comment:
error message changed in Spark 3.3: https://github.com/apache/spark/pull/36289
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193263747
@hudi-bot run azure
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193207094
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930240274
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/java/org/apache/spark/sql/execution/datasources/parquet/Spark33HoodieVectorizedParquetRecordReader.java:
##########
@@ -0,0 +1,191 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.datasources.parquet;
+
+import org.apache.hadoop.mapreduce.InputSplit;
+import org.apache.hadoop.mapreduce.TaskAttemptContext;
+import org.apache.hudi.client.utils.SparkInternalSchemaConverter;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.spark.memory.MemoryMode;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.execution.vectorized.OffHeapColumnVector;
+import org.apache.spark.sql.execution.vectorized.OnHeapColumnVector;
+import org.apache.spark.sql.execution.vectorized.WritableColumnVector;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.StructType;
+import org.apache.spark.sql.vectorized.ColumnarBatch;
+
+import java.io.IOException;
+import java.time.ZoneId;
+import java.util.HashMap;
+import java.util.Map;
+
+public class Spark33HoodieVectorizedParquetRecordReader extends VectorizedParquetRecordReader {
Review Comment:
They are copied from spark 3.2 module. Here is the follow-up jira to refactor these code: https://issues.apache.org/jira/browse/HUDI-4466
I'll put some comments here
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1195875778
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186424099
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186096054
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186601547
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[GitHub] [hudi] leesf commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
leesf commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928353409
##########
hudi-spark-datasource/hudi-spark3-common/src/main/scala/org/apache/spark/sql/adapter/BaseSpark3Adapter.scala:
##########
@@ -81,23 +80,12 @@ abstract class BaseSpark3Adapter extends SparkAdapter with Logging {
}
}
- override def createExtendedSparkParser: Option[(SparkSession, ParserInterface) => ParserInterface] = {
- // since spark3.2.1 support datasourceV2, so we need to a new SqlParser to deal DDL statment
- if (SPARK_VERSION.startsWith("3.1")) {
- val loadClassName = "org.apache.spark.sql.parser.HoodieSpark312ExtendedSqlParser"
- Some {
- (spark: SparkSession, delegate: ParserInterface) => {
- val clazz = Class.forName(loadClassName, true, Thread.currentThread().getContextClassLoader)
- val ctor = clazz.getConstructors.head
- ctor.newInstance(spark, delegate).asInstanceOf[ParserInterface]
- }
- }
- } else {
- None
- }
- }
-
override def createInterpretedPredicate(e: Expression): InterpretedPredicate = {
Predicate.createInterpreted(e)
}
+
+ override def getQueryParserFromExtendedSqlParser(session: SparkSession, delegate: ParserInterface,
Review Comment:
can this method defined in `SparkAdapter` and default implement is unsupported ?
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[GitHub] [hudi] leesf commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
leesf commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928353695
##########
hudi-spark-datasource/hudi-spark3.2.x/src/main/scala/org/apache/spark/sql/HoodieSpark32CatalystPlanUtils.scala:
##########
@@ -13,7 +13,7 @@
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
- * limitations under the License.
+ * limitations under the License.a
Review Comment:
please revert this change.
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194727953
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929459679
##########
hudi-spark-datasource/README.md:
##########
@@ -21,17 +21,19 @@ This repo contains the code that integrate Hudi with Spark. The repo is split in
`hudi-spark`
`hudi-spark2`
-`hudi-spark3`
`hudi-spark3.1.x`
+`hudi-spark3.2.x`
+`hudi-spark3.3.x`
Review Comment:
This is in accordance with flink module naming, do we want to clean that as well?
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194678329
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929457545
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/DeleteHoodieTableCommand.scala:
##########
@@ -36,9 +37,13 @@ case class DeleteHoodieTableCommand(deleteTable: DeleteFromTable) extends Hoodie
// Remove meta fields from the data frame
var df = removeMetaFields(Dataset.ofRows(sparkSession, table))
- if (deleteTable.condition.isDefined) {
- df = df.filter(Column(deleteTable.condition.get))
+ // SPARK-38626 DeleteFromTable.condition is changed from Option[Expression] to Expression in Spark 3.3
+ val condition: Expression = deleteTable.condition match {
+ case option: Option[Expression] => option.getOrElse(null)
+ case expr: Expression => expr
+ case _ => throw new IllegalArgumentException(s"DeleteFromTable.condition has to be either Option[Expression] or Expression")
Review Comment:
Yes, in spark 3.3 this was changed from `Optional[Expression]` to `Expression`
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1185118709
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1197094494
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] alexeykudinkin commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931585204
##########
hudi-spark-datasource/hudi-spark2/src/main/scala/org/apache/spark/sql/adapter/Spark2Adapter.scala:
##########
@@ -122,6 +123,30 @@ class Spark2Adapter extends SparkAdapter {
InterpretedPredicate.create(e)
}
+ override def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD = {
+ new Spark2HoodieFileScanRDD(sparkSession, readFunction, filePartitions)
+ }
+
+ override def resolveDeleteFromTable(deleteFromTable: Command,
Review Comment:
I don't see why we can't:
- We get rid of the method completely
- We use `extractCondition` to extract condition and then do everything else (resolution, etc) in the caller
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1197438398
> @yihua @CTTY the last commit disabled `testHoodieFlinkQuickstart`. I don't know why this affects flink tests. Please make a follow up to re-enable it back.
Created this jira to track it: https://issues.apache.org/jira/browse/HUDI-4491
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1182575098
> @CTTY is this still WIP?
Yes, but can we enable Azure CI for this PR? It could expose more potential issues and I can work on them
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193099047
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* d3916394dbdd84d14f0fcebfbeb19c1ed0698921 Azure: [FAILURE](https://dev.azure.com/apache-hudi-ci-org/785b6ef4-2f42-4a89-8f0e-5f0d7039a0cc/_build/results?buildId=10247)
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193658769
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1196274738
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193072785
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194947168
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930242485
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/hudi/analysis/HoodieSpark3Analysis.scala:
##########
@@ -0,0 +1,222 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.hudi.analysis
+
+import org.apache.hudi.{DefaultSource, SparkAdapterSupport}
+import org.apache.hudi.common.table.HoodieTableMetaClient
+import org.apache.spark.sql.catalyst.TableIdentifier
+import org.apache.spark.sql.catalyst.analysis.{ResolvedTable, UnresolvedPartitionSpec}
+import org.apache.spark.sql.catalyst.catalog.{CatalogTable, HoodieCatalogTable}
+import org.apache.spark.sql.catalyst.expressions.{Alias, Attribute}
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.connector.catalog.CatalogV2Implicits.IdentifierHelper
+import org.apache.spark.sql.connector.catalog.{Table, V1Table}
+import org.apache.spark.sql.execution.datasources.LogicalRelation
+import org.apache.spark.sql.execution.datasources.PreWriteCheck.failAnalysis
+import org.apache.spark.sql.execution.datasources.v2.{DataSourceV2Relation, V2SessionCatalog}
+import org.apache.spark.sql.hudi.HoodieSqlCommonUtils.{castIfNeeded, getTableLocation, removeMetaFields, tableExistsInPath}
+import org.apache.spark.sql.hudi.catalog.{HoodieCatalog, HoodieInternalV2Table}
+import org.apache.spark.sql.hudi.command.{AlterHoodieTableDropPartitionCommand, ShowHoodieTablePartitionsCommand, TruncateHoodieTableCommand}
+import org.apache.spark.sql.hudi.{HoodieSqlCommonUtils, ProvidesHoodieConfig}
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.{AnalysisException, SQLContext, SparkSession}
+
+import scala.collection.JavaConverters.mapAsJavaMapConverter
+
+/**
+ * NOTE: PLEASE READ CAREFULLY
+ *
+ * Since Hudi relations don't currently implement DS V2 Read API, we have to fallback to V1 here.
+ * Such fallback will have considerable performance impact, therefore it's only performed in cases
+ * where V2 API have to be used. Currently only such use-case is using of Schema Evolution feature
+ *
+ * Check out HUDI-4178 for more details
+ */
+class HoodieDataSourceV2ToV1Fallback(sparkSession: SparkSession) extends Rule[LogicalPlan]
+ with ProvidesHoodieConfig {
+
+ override def apply(plan: LogicalPlan): LogicalPlan = plan.resolveOperatorsDown {
+ case v2r @ DataSourceV2Relation(v2Table: HoodieInternalV2Table, _, _, _, _) =>
+ val output = v2r.output
+ val catalogTable = v2Table.catalogTable.map(_ => v2Table.v1Table)
+ val relation = new DefaultSource().createRelation(new SQLContext(sparkSession),
+ buildHoodieConfig(v2Table.hoodieCatalogTable), v2Table.hoodieCatalogTable.tableSchema)
+
+ LogicalRelation(relation, output, catalogTable, isStreaming = false)
+ }
+}
+
+class HoodieSpark3Analysis(sparkSession: SparkSession) extends Rule[LogicalPlan] {
Review Comment:
tracking jira: https://issues.apache.org/jira/browse/HUDI-4466
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191943290
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193065542
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193206328
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[GitHub] [hudi] yihua commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
yihua commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929563589
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/antlr4/imports/SqlBase.g4:
##########
@@ -0,0 +1,1908 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+ * This file is an adaptation of Presto's presto-parser/src/main/antlr4/com/facebook/presto/sql/parser/SqlBase.g4 grammar.
+ */
+
+// The parser file is forked from spark 3.2.0's SqlBase.g4.
Review Comment:
Is this going to be compatible with Spark 3.3 and support new SQL features?
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191099779
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r919516736
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/analysis/HoodieAnalysis.scala:
##########
@@ -64,15 +64,18 @@ object HoodieAnalysis {
val spark3ResolveReferences: RuleBuilder =
session => ReflectionUtils.loadClass(spark3ResolveReferencesClass, session).asInstanceOf[Rule[LogicalPlan]]
- val spark32ResolveAlterTableCommandsClass = "org.apache.spark.sql.hudi.ResolveHudiAlterTableCommandSpark32"
- val spark32ResolveAlterTableCommands: RuleBuilder =
- session => ReflectionUtils.loadClass(spark32ResolveAlterTableCommandsClass, session).asInstanceOf[Rule[LogicalPlan]]
+ val resolveAlterTableCommandsClass =
+ if (HoodieSparkUtils.gteqSpark3_3_0)
+ "org.apache.spark.sql.hudi.ResolveHudiAlterTableCommandSpark33"
+ else "org.apache.spark.sql.hudi.ResolveHudiAlterTableCommandSpark32"
+ val resolveAlterTableCommands: RuleBuilder =
+ session => ReflectionUtils.loadClass(resolveAlterTableCommandsClass, session).asInstanceOf[Rule[LogicalPlan]]
// NOTE: PLEASE READ CAREFULLY
//
// It's critical for this rules to follow in this order, so that DataSource V2 to V1 fallback
// is performed prior to other rules being evaluated
- rules ++= Seq(dataSourceV2ToV1Fallback, spark3Analysis, spark3ResolveReferences, spark32ResolveAlterTableCommands)
+ rules ++= Seq(dataSourceV2ToV1Fallback, spark3Analysis, spark3ResolveReferences, resolveAlterTableCommands)
Review Comment:
[SPARK-38939](https://github.com/apache/spark/pull/36252) DropColumns syntax change
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1183869459
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1184871491
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186087014
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1184918189
Most hive sync CI tests are failing. I saw another PR working on this: https://github.com/apache/hudi/pull/6110
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925174999
##########
hudi-spark-datasource/hudi-spark2/src/main/scala/org/apache/hudi/Spark2HoodieFileScanRDD.scala:
##########
@@ -0,0 +1,35 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hudi
+
+import org.apache.hudi.HoodieUnsafeRDD
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.AttributeReference
+import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile}
+import org.apache.spark.sql.types.StructType
+
+class Spark2HoodieFileScanRDD(@transient private val sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ @transient filePartitions: Seq[FilePartition])
+ extends FileScanRDD(sparkSession, readFunction, filePartitions)
+ with HoodieUnsafeRDD {
+
+ override final def collect(): Array[InternalRow] = super[HoodieUnsafeRDD].collect()
+}
Review Comment:
Split class for Spark2: https://github.com/apache/spark/pull/34575
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925171807
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -337,6 +343,11 @@ public Builder parquetOutputTimestampType(String parquetOutputTimestampType) {
return this;
}
+ public Builder parquetFieldIdWrite(String parquetFieldIdWrite) {
+ storageConfig.setValue(PARQUET_FIELD_ID_WRITE_ENABLED, parquetFieldIdWrite);
+ return this;
+ }
+
Review Comment:
See above
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925178549
##########
hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/parser/HoodieSpark3_3ExtendedSqlParser.scala:
##########
@@ -0,0 +1,199 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.parser
+
+import org.antlr.v4.runtime._
+import org.antlr.v4.runtime.atn.PredictionMode
+import org.antlr.v4.runtime.misc.{Interval, ParseCancellationException}
+import org.antlr.v4.runtime.tree.TerminalNodeImpl
+import org.apache.hudi.spark.sql.parser.HoodieSqlBaseParser.{NonReservedContext, QuotedIdentifierContext}
+import org.apache.hudi.spark.sql.parser.{HoodieSqlBaseBaseListener, HoodieSqlBaseLexer, HoodieSqlBaseParser}
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.parser.{ParseErrorListener, ParseException, ParserInterface}
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.trees.Origin
+import org.apache.spark.sql.catalyst.{FunctionIdentifier, TableIdentifier}
+import org.apache.spark.sql.internal.VariableSubstitution
+import org.apache.spark.sql.types._
+import org.apache.spark.sql.{AnalysisException, SparkSession}
+
+import java.util.Locale
+
+class HoodieSpark3_3ExtendedSqlParser(session: SparkSession, delegate: ParserInterface)
+ extends ParserInterface with Logging {
+
+ private lazy val conf = session.sqlContext.conf
+ private lazy val builder = new HoodieSpark3_3ExtendedSqlAstBuilder(conf, delegate)
+ private val substitutor = new VariableSubstitution
+
+ override def parsePlan(sqlText: String): LogicalPlan = {
+ val substitutionSql = substitutor.substitute(sqlText)
+ if (isHoodieCommand(substitutionSql)) {
+ parse(substitutionSql) { parser =>
+ builder.visit(parser.singleStatement()) match {
+ case plan: LogicalPlan => plan
+ case _ => delegate.parsePlan(sqlText)
+ }
+ }
+ } else {
+ delegate.parsePlan(substitutionSql)
+ }
+ }
+
+ // SPARK-37266 Added parseQuery to ParserInterface in Spark 3.3.0
+ // Don't mark this as override for backward compatibility
+ def parseQuery(sqlText: String): LogicalPlan = delegate.parseQuery(sqlText)
Review Comment:
new function here
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1196210232
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[GitHub] [hudi] yihua commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
yihua commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931606491
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/spark/sql/hudi/SparkAdapter.scala:
##########
@@ -143,6 +141,38 @@ trait SparkAdapter extends Serializable {
*/
def createInterpretedPredicate(e: Expression): InterpretedPredicate
+ /**
+ * Create instance of [[HoodieFileScanRDD]]
+ * SPARK-37273 FileScanRDD constructor changed in SPARK 3.3
+ */
+ def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD
+
+ /**
+ * Resolve [[DeleteFromTable]]
+ * SPARK-38626 condition is no longer Option in Spark 3.3
+ */
+ def resolveDeleteFromTable(deleteFromTable: Command,
+ resolveExpression: Expression => Expression): LogicalPlan
+
+ /**
+ * Extract condition in [[DeleteFromTable]]
+ * SPARK-38626 condition is no longer Option in Spark 3.3
+ */
+ def extractCondition(deleteFromTable: Command): Expression
Review Comment:
nit: rename to `extractDeleteCondition`?
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r926234730
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/analysis/HoodieAnalysis.scala:
##########
@@ -64,15 +64,18 @@ object HoodieAnalysis {
val spark3ResolveReferences: RuleBuilder =
session => ReflectionUtils.loadClass(spark3ResolveReferencesClass, session).asInstanceOf[Rule[LogicalPlan]]
- val spark32ResolveAlterTableCommandsClass = "org.apache.spark.sql.hudi.ResolveHudiAlterTableCommandSpark32"
- val spark32ResolveAlterTableCommands: RuleBuilder =
- session => ReflectionUtils.loadClass(spark32ResolveAlterTableCommandsClass, session).asInstanceOf[Rule[LogicalPlan]]
+ val resolveAlterTableCommandsClass =
+ if (HoodieSparkUtils.gteqSpark3_3_0)
+ "org.apache.spark.sql.hudi.ResolveHudiAlterTableCommandSpark33"
Review Comment:
Will do
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925171715
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,12 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
+ .defaultValue("true")
+ .withDocumentation("Sets spark.sql.parquet.fieldId.write.enabled. "
+ + "If enabled, Spark will write out parquet native field ids that are stored inside StructField's metadata as parquet.field.id to parquet files.");
+
Review Comment:
[SPARK-38094](https://github.com/apache/spark/pull/35385) Spark 3.3 checks if this field is enabled. There would be NPE if not provided. default value is true in Spark
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r927037922
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/DeleteHoodieTableCommand.scala:
##########
@@ -36,9 +37,13 @@ case class DeleteHoodieTableCommand(deleteTable: DeleteFromTable) extends Hoodie
// Remove meta fields from the data frame
var df = removeMetaFields(Dataset.ofRows(sparkSession, table))
- if (deleteTable.condition.isDefined) {
- df = df.filter(Column(deleteTable.condition.get))
+ // SPARK-38626 DeleteFromTable.condition is changed from Option[Expression] to Expression in Spark 3.3
+ val condition: Expression = deleteTable.condition match {
Review Comment:
Several things I've tried:
- exctract `Expression` from `condition`
- Embed `condition` to `Option[Expression]`
Both approches above would make `DeleteHoodieTableCommand` cleaner but have the same problem: we have to provide condition back to `DeleteFromTable` around L417 in `HoodieAnalysis`, which means we have to wrap/unwrap it once more for different spark versions.
If we want to also make `DeleteHoodieTableCommand` cleaner, I think the only way might be adding two different methods in `SparkAdapter`: one to `resolveDeleteFromTable`, another to `extractCondition`
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191025844
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[GitHub] [hudi] yihua commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
yihua commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929446058
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/TestAlterTableDropPartition.scala:
##########
@@ -211,7 +211,7 @@ class TestAlterTableDropPartition extends HoodieSparkSqlTestBase {
// specify duplicate partition columns
checkExceptionContain(s"alter table $tableName drop partition (dt='2021-10-01', dt='2021-10-02')")(
- "Found duplicate keys 'dt'")
+ "Found duplicate keys ")
Review Comment:
Could we do strict checks based on Spark version like `TestParquetColumnProjection`, so that each Spark version has different check:
```
// Stats for the reads fetching only _projected_ columns (note how amount of bytes read
// increases along w/ the # of columns)
val projectedColumnsReadStats: Array[(String, Long)] =
if (HoodieSparkUtils.isSpark3)
Array(
("rider", 2363),
("rider,driver", 2463),
("rider,driver,tip_history", 3428))
else if (HoodieSparkUtils.isSpark2)
Array(
("rider", 2474),
("rider,driver", 2614),
("rider,driver,tip_history", 3629))
else
fail("Only Spark 3 and Spark 2 are currently supported")
```
##########
hudi-spark-datasource/hudi-spark2/src/main/scala/org/apache/spark/sql/adapter/Spark2Adapter.scala:
##########
@@ -122,6 +123,26 @@ class Spark2Adapter extends SparkAdapter {
InterpretedPredicate.create(e)
}
+ override def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD = {
+ new Spark2HoodieFileScanRDD(sparkSession, readFunction, filePartitions)
+ }
+
+ override def resolveDeleteFromTable(dft: Command,
Review Comment:
nit: `dft`: better naming across classes?
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/DeleteHoodieTableCommand.scala:
##########
@@ -36,9 +37,13 @@ case class DeleteHoodieTableCommand(deleteTable: DeleteFromTable) extends Hoodie
// Remove meta fields from the data frame
var df = removeMetaFields(Dataset.ofRows(sparkSession, table))
- if (deleteTable.condition.isDefined) {
- df = df.filter(Column(deleteTable.condition.get))
+ // SPARK-38626 DeleteFromTable.condition is changed from Option[Expression] to Expression in Spark 3.3
+ val condition: Expression = deleteTable.condition match {
+ case option: Option[Expression] => option.getOrElse(null)
+ case expr: Expression => expr
+ case _ => throw new IllegalArgumentException(s"DeleteFromTable.condition has to be either Option[Expression] or Expression")
Review Comment:
Is this because of the API compatibility, so both `Option[Expression]` and `Expression` typed value can exist? Nevertheless, looks not clean.
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/analysis/HoodieAnalysis.scala:
##########
@@ -421,12 +433,10 @@ case class HoodieResolveReferences(sparkSession: SparkSession) extends Rule[Logi
UpdateTable(table, resolvedAssignments, resolvedCondition)
// Resolve Delete Table
- case DeleteFromTable(table, condition)
+ case dft @ DeleteFromTable(table, condition)
if sparkAdapter.isHoodieTable(table, sparkSession) && table.resolved =>
- // Resolve condition
- val resolvedCondition = condition.map(resolveExpressionFrom(table)(_))
- // Return the resolved DeleteTable
- DeleteFromTable(table, resolvedCondition)
+ val resolveExpression = resolveExpressionFrom(table, None)_
+ sparkAdapter.resolveDeleteFromTable(dft, resolveExpression)
Review Comment:
Do we want to wrap the whole thing in a SparkAdapter method?
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1195073860
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928200299
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/hudi/catalog/HoodieCatalog.scala:
##########
@@ -355,7 +355,7 @@ object HoodieCatalog {
identityCols += col
- case BucketTransform(numBuckets, FieldReference(Seq(col))) =>
+ case BucketTransform(numBuckets, Seq(FieldReference(Seq(col))), _) =>
bucketSpec = Some(BucketSpec(numBuckets, col :: Nil, Nil))
Review Comment:
[SPARK-37627](https://github.com/apache/spark/pull/34914) API change.
This API hasn't changed a lot but this code change is the only way I found to make compiler happy. Please review this
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[GitHub] [hudi] yihua commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
yihua commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929309926
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/spark/sql/hudi/SparkAdapter.scala:
##########
@@ -138,4 +139,30 @@ trait SparkAdapter extends Serializable {
* TODO move to HoodieCatalystExpressionUtils
*/
def createInterpretedPredicate(e: Expression): InterpretedPredicate
+
+ /**
+ * Create instance of [[HoodieFileScanRDD]]
+ * SPARK-37273 FileScanRDD constructor changed in SPARK 3.3
+ */
+ def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD
+
+ /**
+ * Resolve [[DeleteFromTable]]
+ * SPARK-38626 condition is no longer Option in Spark 3.3
+ */
+ def resolveDeleteFromTable(dft: Command,
+ resolveExpression: Expression => Expression): LogicalPlan
+
+ /**
+ * Get parseQuery from ExtendedSqlParser, only for Spark 3.3+
+ */
+ def getQueryParserFromExtendedSqlParser(session: SparkSession, delegate: ParserInterface,
+ sqlText: String): LogicalPlan = {
+ // unsupported by default
+ throw new UnsupportedOperationException(s"Unsupported parseQuery method in Spark earlier than Spark 3.3.0")
Review Comment:
To clarify, I see that `HoodieCommonSqlParser` uses this API now. Does it affect SQL in pre-Spark 3.3 versions? If not, how is it realized?
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/SparkAdapterSupport.scala:
##########
@@ -27,7 +27,9 @@ import org.apache.spark.sql.hudi.SparkAdapter
trait SparkAdapterSupport {
lazy val sparkAdapter: SparkAdapter = {
- val adapterClass = if (HoodieSparkUtils.isSpark3_2) {
+ val adapterClass = if (HoodieSparkUtils.gteqSpark3_3_0) {
Review Comment:
Similar to above, is `gteqSpark3_3` good enough here?
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/bootstrap/HoodieSparkBootstrapSchemaProvider.java:
##########
@@ -71,11 +72,20 @@ protected Schema getBootstrapSourceSchema(HoodieEngineContext context, List<Pair
}
private static Schema getBootstrapSourceSchemaParquet(HoodieWriteConfig writeConfig, HoodieEngineContext context, Path filePath) {
- MessageType parquetSchema = new ParquetUtils().readSchema(context.getHadoopConf().get(), filePath);
+ Configuration hadoopConf = context.getHadoopConf().get();
+ MessageType parquetSchema = new ParquetUtils().readSchema(hadoopConf, filePath);
+
+ hadoopConf.set(
+ SQLConf.PARQUET_BINARY_AS_STRING().key(),
+ SQLConf.PARQUET_BINARY_AS_STRING().defaultValueString());
+ hadoopConf.set(
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().key(),
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().defaultValueString());
+ hadoopConf.set(
+ SQLConf.CASE_SENSITIVE().key(),
+ SQLConf.CASE_SENSITIVE().defaultValueString());
+ ParquetToSparkSchemaConverter converter = new ParquetToSparkSchemaConverter(hadoopConf);
Review Comment:
nit: For such BWC logic, should we just create a new method in the SparkAdapter for different Spark versions? Then the code and logic for existing supported Spark versions are not changed. I'm a little paranoid about changes to existing Spark versions which have the risk of breaking things that are hard to track.
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/HoodieSparkUtils.scala:
##########
@@ -52,11 +52,14 @@ private[hudi] trait SparkVersionsSupport {
def isSpark3_0: Boolean = getSparkVersion.startsWith("3.0")
def isSpark3_1: Boolean = getSparkVersion.startsWith("3.1")
def isSpark3_2: Boolean = getSparkVersion.startsWith("3.2")
+ def isSpark3_3: Boolean = getSparkVersion.startsWith("3.3")
def gteqSpark3_1: Boolean = getSparkVersion >= "3.1"
def gteqSpark3_1_3: Boolean = getSparkVersion >= "3.1.3"
def gteqSpark3_2: Boolean = getSparkVersion >= "3.2"
def gteqSpark3_2_1: Boolean = getSparkVersion >= "3.2.1"
+ def gteqSpark3_3: Boolean = getSparkVersion >= "3.3"
+ def gteqSpark3_3_0: Boolean = getSparkVersion >= "3.3.0"
Review Comment:
We don't need the patch version level check for Spark 3.3 at this point, right?
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/BaseFileOnlyRelation.scala:
##########
@@ -91,7 +93,9 @@ class BaseFileOnlyRelation(sqlContext: SQLContext,
hadoopConf = HoodieDataSourceHelper.getConfigurationWithInternalSchema(new Configuration(conf), requiredSchema.internalSchema, metaClient.getBasePath, validCommits)
)
- new HoodieFileScanRDD(sparkSession, baseFileReader, fileSplits)
+ // SPARK-37273 FileScanRDD constructor changed in SPARK 3.3
Review Comment:
@CTTY is this resolved?
##########
hudi-spark-datasource/README.md:
##########
@@ -21,17 +21,19 @@ This repo contains the code that integrate Hudi with Spark. The repo is split in
`hudi-spark`
`hudi-spark2`
-`hudi-spark3`
`hudi-spark3.1.x`
+`hudi-spark3.2.x`
+`hudi-spark3.3.x`
Review Comment:
nit: We should have `hudi-spark3.1`, `hudi-spark3.2`, and `hudi-spark3.3` as shorter names. @CTTY Could you create a ticket to track this?
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,12 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
+ .defaultValue("true")
+ .withDocumentation("Sets spark.sql.parquet.fieldId.write.enabled. "
+ + "If enabled, Spark will write out parquet native field ids that are stored inside StructField's metadata as parquet.field.id to parquet files.");
+
Review Comment:
@CTTY could you help me understand where this check is enforced? From the Spark docs, I see that the default value of `spark.sql.parquet.fieldId.write.enabled` is true and I suppose we don't have to set it explicitly?
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[GitHub] [hudi] XuQianJin-Stars commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
XuQianJin-Stars commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928183504
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,12 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
+ .defaultValue("true")
+ .withDocumentation("Sets spark.sql.parquet.fieldId.write.enabled. "
+ + "If enabled, Spark will write out parquet native field ids that are stored inside StructField's metadata as parquet.field.id to parquet files.");
+
Review Comment:
> [SPARK-38094](https://github.com/apache/spark/pull/35385) Spark 3.3 checks if this field is enabled. There would be NPE if not provided. default value is true in Spark
add note for this?
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[GitHub] [hudi] XuQianJin-Stars commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
XuQianJin-Stars commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928183435
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,12 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
+ .defaultValue("true")
+ .withDocumentation("Sets spark.sql.parquet.fieldId.write.enabled. "
+ + "If enabled, Spark will write out parquet native field ids that are stored inside StructField's metadata as parquet.field.id to parquet files.");
Review Comment:
.sinceVersion("0.12.0")? Does this need to be merged in version 0.12.0?
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1192263766
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928297202
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/antlr4/imports/SqlBase.g4:
##########
@@ -0,0 +1,1908 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+ * This file is an adaptation of Presto's presto-parser/src/main/antlr4/com/facebook/presto/sql/parser/SqlBase.g4 grammar.
+ */
+
+// The parser file is forked from spark 3.2.0's SqlBase.g4.
Review Comment:
Those .g4 files have been refactored and changed a lot in Spark 3.3. e.g.: https://github.com/apache/spark/pull/35701
And I don't think it's needed to port those changes back to Hudi as they are going to be removed soon.
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[GitHub] [hudi] alexeykudinkin commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928053904
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/analysis/HoodieAnalysis.scala:
##########
@@ -44,15 +44,26 @@ import scala.collection.mutable.ListBuffer
object HoodieAnalysis {
type RuleBuilder = SparkSession => Rule[LogicalPlan]
- def customOptimizerRules: Seq[RuleBuilder] =
- if (HoodieSparkUtils.gteqSpark3_1) {
- val nestedSchemaPruningClass = "org.apache.spark.sql.execution.datasources.NestedSchemaPruning"
+ def customOptimizerRules: Seq[RuleBuilder] = {
+ if (HoodieSparkUtils.gteqSpark3_3) {
Review Comment:
We can reduce the conditional to just instantiate the actual rule and extract common `Seq(_ => rule)`
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930268271
##########
hudi-examples/hudi-examples-spark/pom.xml:
##########
@@ -190,6 +190,12 @@
<artifactId>spark-sql_${scala.binary.version}</artifactId>
</dependency>
+ <!-- Hadoop -->
+ <dependency>
+ <groupId>org.apache.hadoop</groupId>
+ <artifactId>hadoop-auth</artifactId>
+ </dependency>
+
Review Comment:
Filed this one: https://issues.apache.org/jira/browse/HUDI-4479
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1196094945
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] alexeykudinkin commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931583487
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/parser/HoodieCommonSqlParser.scala:
##########
@@ -57,6 +57,14 @@ class HoodieCommonSqlParser(session: SparkSession, delegate: ParserInterface)
override def parseDataType(sqlText: String): DataType = delegate.parseDataType(sqlText)
+ /* SPARK-37266 Added parseQuery to ParserInterface in Spark 3.3.0. This is a patch to prevent
+ hackers from tampering text with persistent view, it won't be called in older Spark
+ Don't mark this as override for backward compatibility
+ Can't use sparkExtendedParser directly here due to the same reason */
Review Comment:
As discussed on Slack, let's instead of doing parsing in `SparkAdapter` create `ExtendedParserInterface`, where we can place this new `parseQuery` method and that could be used in Hudi's code-base (this is similar to how `HoodieCatalystExpressionUtils` set up)
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[GitHub] [hudi] yihua merged pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
yihua merged PR #5943:
URL: https://github.com/apache/hudi/pull/5943
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[GitHub] [hudi] xushiyan commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
xushiyan commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930496049
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala:
##########
@@ -181,8 +200,6 @@ private[sql] class AvroDeserializer(rootAvroType: Schema,
case b: ByteBuffer =>
val bytes = new Array[Byte](b.remaining)
b.get(bytes)
- // Do not forget to reset the position
- b.rewind()
Review Comment:
why remove? this was a recent fix, right?
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1196276835
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[GitHub] [hudi] alexeykudinkin commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931566562
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/parser/HoodieCommonSqlParser.scala:
##########
@@ -57,6 +57,14 @@ class HoodieCommonSqlParser(session: SparkSession, delegate: ParserInterface)
override def parseDataType(sqlText: String): DataType = delegate.parseDataType(sqlText)
+ /* SPARK-37266 Added parseQuery to ParserInterface in Spark 3.3.0. This is a patch to prevent
+ hackers from tampering text with persistent view, it won't be called in older Spark
+ Don't mark this as override for backward compatibility
+ Can't use sparkExtendedParser directly here due to the same reason */
Review Comment:
Sorry, but i can't understand the java-doc: can you please elaborate on why this is here?
- What exactly are we trying to prevent from happening?
- What BWC are we referring to?
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/analysis/HoodieAnalysis.scala:
##########
@@ -421,12 +433,10 @@ case class HoodieResolveReferences(sparkSession: SparkSession) extends Rule[Logi
UpdateTable(table, resolvedAssignments, resolvedCondition)
// Resolve Delete Table
- case DeleteFromTable(table, condition)
+ case dft @ DeleteFromTable(table, condition)
if sparkAdapter.isHoodieTable(table, sparkSession) && table.resolved =>
- // Resolve condition
- val resolvedCondition = condition.map(resolveExpressionFrom(table)(_))
- // Return the resolved DeleteTable
- DeleteFromTable(table, resolvedCondition)
+ val resolveExpression = resolveExpressionFrom(table, None)_
Review Comment:
I'd suggest we keep syntax as it was (with parenthesis)
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/parser/HoodieCommonSqlParser.scala:
##########
@@ -57,6 +57,14 @@ class HoodieCommonSqlParser(session: SparkSession, delegate: ParserInterface)
override def parseDataType(sqlText: String): DataType = delegate.parseDataType(sqlText)
+ /* SPARK-37266 Added parseQuery to ParserInterface in Spark 3.3.0. This is a patch to prevent
+ hackers from tampering text with persistent view, it won't be called in older Spark
+ Don't mark this as override for backward compatibility
+ Can't use sparkExtendedParser directly here due to the same reason */
+ def parseQuery(sqlText: String): LogicalPlan = parse(sqlText) { parser =>
Review Comment:
Why are we doing double-parsing?
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/adapter/Spark3_3Adapter.scala:
##########
@@ -0,0 +1,80 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.adapter
+
+import org.apache.avro.Schema
+import org.apache.hudi.Spark33HoodieFileScanRDD
+import org.apache.spark.sql.avro._
+import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Expression}
+import org.apache.spark.sql.catalyst.parser.ParserInterface
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile}
+import org.apache.spark.sql.execution.datasources.parquet.{ParquetFileFormat, Spark33HoodieParquetFileFormat}
+import org.apache.spark.sql.parser.HoodieSpark3_3ExtendedSqlParser
+import org.apache.spark.sql.types.{DataType, StructType}
+import org.apache.spark.sql.{HoodieCatalystExpressionUtils, HoodieCatalystPlansUtils, HoodieSpark33CatalystPlanUtils, HoodieSpark33CatalystExpressionUtils, SparkSession}
+
+/**
+ * Implementation of [[SparkAdapter]] for Spark 3.3.x branch
+ */
+class Spark3_3Adapter extends BaseSpark3Adapter {
+
+ override def getCatalystExpressionUtils: HoodieCatalystExpressionUtils = HoodieSpark33CatalystExpressionUtils
+
+ override def getCatalystPlanUtils: HoodieCatalystPlansUtils = HoodieSpark33CatalystPlanUtils
+
+ override def createAvroSerializer(rootCatalystType: DataType, rootAvroType: Schema, nullable: Boolean): HoodieAvroSerializer =
+ new HoodieSpark3_3AvroSerializer(rootCatalystType, rootAvroType, nullable)
+
+ override def createAvroDeserializer(rootAvroType: Schema, rootCatalystType: DataType): HoodieAvroDeserializer =
+ new HoodieSpark3_3AvroDeserializer(rootAvroType, rootCatalystType)
+
+ override def createExtendedSparkParser: Option[(SparkSession, ParserInterface) => ParserInterface] = {
+ Some(
+ (spark: SparkSession, delegate: ParserInterface) => new HoodieSpark3_3ExtendedSqlParser(spark, delegate)
+ )
+ }
+
+ override def createHoodieParquetFileFormat(appendPartitionValues: Boolean): Option[ParquetFileFormat] = {
+ Some(new Spark33HoodieParquetFileFormat(appendPartitionValues))
+ }
+
+ override def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD = {
+ new Spark33HoodieFileScanRDD(sparkSession, readFunction, filePartitions, readDataSchema, metadataColumns)
+ }
+
+ override def resolveDeleteFromTable(deleteFromTable: Command,
+ resolveExpression: Expression => Expression): DeleteFromTable = {
+ val deleteFromTableCommand = deleteFromTable.asInstanceOf[DeleteFromTable]
+ DeleteFromTable(deleteFromTableCommand.table, resolveExpression(deleteFromTableCommand.condition))
+ }
+
+ override def extractCondition(deleteFromTable: Command): Expression = {
+ deleteFromTable.asInstanceOf[DeleteFromTable].condition
+ }
+
+ override def getQueryParserFromExtendedSqlParser(session: SparkSession, delegate: ParserInterface,
+ sqlText: String): LogicalPlan = {
+ new HoodieSpark3_3ExtendedSqlParser(session, delegate).parseQuery(sqlText)
Review Comment:
This is not a query parser -- this is already parsed query
##########
hudi-spark-datasource/hudi-spark2/src/main/scala/org/apache/spark/sql/adapter/Spark2Adapter.scala:
##########
@@ -122,6 +123,30 @@ class Spark2Adapter extends SparkAdapter {
InterpretedPredicate.create(e)
}
+ override def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD = {
+ new Spark2HoodieFileScanRDD(sparkSession, readFunction, filePartitions)
+ }
+
+ override def resolveDeleteFromTable(deleteFromTable: Command,
Review Comment:
Given that we have `extractCondition` we can get rid of `resolveDeleteFromTable`
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1197510513
Created this umbrella jira and linked existing follow-up jiras to it: https://issues.apache.org/jira/browse/HUDI-4492
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1183957927
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186126889
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r919474750
##########
hudi-spark-datasource/hudi-spark3.3/src/main/scala/org/apache/spark/sql/parser/HoodieSpark3_3ExtendedSqlAstBuilder.scala:
##########
@@ -0,0 +1,3351 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.sql.parser
+
+import org.antlr.v4.runtime.tree.{ParseTree, RuleNode, TerminalNode}
+import org.antlr.v4.runtime.{ParserRuleContext, Token}
+import org.apache.hudi.spark.sql.parser.HoodieSqlBaseParser._
+import org.apache.hudi.spark.sql.parser.{HoodieSqlBaseBaseVisitor, HoodieSqlBaseParser}
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.AnalysisException
+import org.apache.spark.sql.catalyst.analysis._
+import org.apache.spark.sql.catalyst.catalog.{BucketSpec, CatalogStorageFormat}
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.{First, Last}
+import org.apache.spark.sql.catalyst.parser.ParserUtils.{EnhancedLogicalPlan, checkDuplicateClauses, checkDuplicateKeys, entry, escapedIdentifier, operationNotAllowed, source, string, stringWithoutUnescape, validate, withOrigin}
+import org.apache.spark.sql.catalyst.parser.{ParseException, ParserInterface}
+import org.apache.spark.sql.catalyst.plans._
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.util.DateTimeUtils._
+import org.apache.spark.sql.catalyst.util.{CharVarcharUtils, DateTimeUtils, IntervalUtils, truncatedString}
+import org.apache.spark.sql.catalyst.{FunctionIdentifier, TableIdentifier}
+import org.apache.spark.sql.connector.catalog.CatalogV2Implicits.BucketSpecHelper
+import org.apache.spark.sql.connector.catalog.TableCatalog
+import org.apache.spark.sql.connector.catalog.TableChange.ColumnPosition
+import org.apache.spark.sql.connector.expressions.{ApplyTransform, BucketTransform, DaysTransform, FieldReference, HoursTransform, IdentityTransform, LiteralValue, MonthsTransform, Transform, YearsTransform, Expression => V2Expression}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.types._
+import org.apache.spark.unsafe.types.{CalendarInterval, UTF8String}
+import org.apache.spark.util.Utils.isTesting
+import org.apache.spark.util.random.RandomSampler
+
+import java.util.Locale
+import java.util.concurrent.TimeUnit
+import javax.xml.bind.DatatypeConverter
+import scala.collection.JavaConverters._
+import scala.collection.mutable.ArrayBuffer
+
+/**
+ * The AstBuilder for HoodieSqlParser to parser the AST tree to Logical Plan.
+ * Here we only do the parser for the extended sql syntax. e.g MergeInto. For
+ * other sql syntax we use the delegate sql parser which is the SparkSqlParser.
+ */
+class HoodieSpark3_3ExtendedSqlAstBuilder(conf: SQLConf, delegate: ParserInterface)
+ extends HoodieSqlBaseBaseVisitor[AnyRef] with Logging {
+
+ protected def typedVisit[T](ctx: ParseTree): T = {
+ ctx.accept(this).asInstanceOf[T]
+ }
+
+ /**
+ * Override the default behavior for all visit methods. This will only return a non-null result
+ * when the context has only one child. This is done because there is no generic method to
+ * combine the results of the context children. In all other cases null is returned.
+ */
+ override def visitChildren(node: RuleNode): AnyRef = {
+ if (node.getChildCount == 1) {
+ node.getChild(0).accept(this)
+ } else {
+ null
+ }
+ }
+
+ /**
+ * Create an aliased table reference. This is typically used in FROM clauses.
+ */
+ override def visitTableName(ctx: TableNameContext): LogicalPlan = withOrigin(ctx) {
+ val tableId = visitMultipartIdentifier(ctx.multipartIdentifier())
+ val relation = UnresolvedRelation(tableId)
+ val table = mayApplyAliasPlan(
+ ctx.tableAlias, relation.optionalMap(ctx.temporalClause)(withTimeTravel))
+ table.optionalMap(ctx.sample)(withSample)
+ }
+
+ private def withTimeTravel(
+ ctx: TemporalClauseContext, plan: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ val v = ctx.version
+ val version = if (ctx.INTEGER_VALUE != null) {
+ Some(v.getText)
+ } else {
+ Option(v).map(string)
+ }
+
+ val timestamp = Option(ctx.timestamp).map(expression)
+ if (timestamp.exists(_.references.nonEmpty)) {
+ throw new ParseException(
+ "timestamp expression cannot refer to any columns", ctx.timestamp)
+ }
+ if (timestamp.exists(e => SubqueryExpression.hasSubquery(e))) {
+ throw new ParseException(
+ "timestamp expression cannot contain subqueries", ctx.timestamp)
+ }
+
+ TimeTravelRelation(plan, timestamp, version)
+ }
+
+ // ============== The following code is fork from org.apache.spark.sql.catalyst.parser.AstBuilder
+ override def visitSingleStatement(ctx: SingleStatementContext): LogicalPlan = withOrigin(ctx) {
+ visit(ctx.statement).asInstanceOf[LogicalPlan]
+ }
+
+ override def visitSingleExpression(ctx: SingleExpressionContext): Expression = withOrigin(ctx) {
+ visitNamedExpression(ctx.namedExpression)
+ }
+
+ override def visitSingleTableIdentifier(
+ ctx: SingleTableIdentifierContext): TableIdentifier = withOrigin(ctx) {
+ visitTableIdentifier(ctx.tableIdentifier)
+ }
+
+ override def visitSingleFunctionIdentifier(
+ ctx: SingleFunctionIdentifierContext): FunctionIdentifier = withOrigin(ctx) {
+ visitFunctionIdentifier(ctx.functionIdentifier)
+ }
+
+ override def visitSingleMultipartIdentifier(
+ ctx: SingleMultipartIdentifierContext): Seq[String] = withOrigin(ctx) {
+ visitMultipartIdentifier(ctx.multipartIdentifier)
+ }
+
+ override def visitSingleDataType(ctx: SingleDataTypeContext): DataType = withOrigin(ctx) {
+ typedVisit[DataType](ctx.dataType)
+ }
+
+ override def visitSingleTableSchema(ctx: SingleTableSchemaContext): StructType = {
+ val schema = StructType(visitColTypeList(ctx.colTypeList))
+ withOrigin(ctx)(schema)
+ }
+
+ /* ********************************************************************************************
+ * Plan parsing
+ * ******************************************************************************************** */
+ protected def plan(tree: ParserRuleContext): LogicalPlan = typedVisit(tree)
+
+ /**
+ * Create a top-level plan with Common Table Expressions.
+ */
+ override def visitQuery(ctx: QueryContext): LogicalPlan = withOrigin(ctx) {
+ val query = plan(ctx.queryTerm).optionalMap(ctx.queryOrganization)(withQueryResultClauses)
+
+ // Apply CTEs
+ query.optionalMap(ctx.ctes)(withCTE)
+ }
+
+ override def visitDmlStatement(ctx: DmlStatementContext): AnyRef = withOrigin(ctx) {
+ val dmlStmt = plan(ctx.dmlStatementNoWith)
+ // Apply CTEs
+ dmlStmt.optionalMap(ctx.ctes)(withCTE)
+ }
+
+ private def withCTE(ctx: CtesContext, plan: LogicalPlan): LogicalPlan = {
+ val ctes = ctx.namedQuery.asScala.map { nCtx =>
+ val namedQuery = visitNamedQuery(nCtx)
+ (namedQuery.alias, namedQuery)
+ }
+ // Check for duplicate names.
+ val duplicates = ctes.groupBy(_._1).filter(_._2.size > 1).keys
+ if (duplicates.nonEmpty) {
+ throw new ParseException(s"CTE definition can't have duplicate names: ${duplicates.mkString("'", "', '", "'")}.", ctx)
+ }
+ UnresolvedWith(plan, ctes.toSeq)
+ }
+
+ /**
+ * Create a logical query plan for a hive-style FROM statement body.
+ */
+ private def withFromStatementBody(
+ ctx: FromStatementBodyContext, plan: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ // two cases for transforms and selects
+ if (ctx.transformClause != null) {
+ withTransformQuerySpecification(
+ ctx,
+ ctx.transformClause,
+ ctx.lateralView,
+ ctx.whereClause,
+ ctx.aggregationClause,
+ ctx.havingClause,
+ ctx.windowClause,
+ plan
+ )
+ } else {
+ withSelectQuerySpecification(
+ ctx,
+ ctx.selectClause,
+ ctx.lateralView,
+ ctx.whereClause,
+ ctx.aggregationClause,
+ ctx.havingClause,
+ ctx.windowClause,
+ plan
+ )
+ }
+ }
+
+ override def visitFromStatement(ctx: FromStatementContext): LogicalPlan = withOrigin(ctx) {
+ val from = visitFromClause(ctx.fromClause)
+ val selects = ctx.fromStatementBody.asScala.map { body =>
+ withFromStatementBody(body, from).
+ // Add organization statements.
+ optionalMap(body.queryOrganization)(withQueryResultClauses)
+ }
+ // If there are multiple SELECT just UNION them together into one query.
+ if (selects.length == 1) {
+ selects.head
+ } else {
+ Union(selects.toSeq)
+ }
+ }
+
+ /**
+ * Create a named logical plan.
+ *
+ * This is only used for Common Table Expressions.
+ */
+ override def visitNamedQuery(ctx: NamedQueryContext): SubqueryAlias = withOrigin(ctx) {
+ val subQuery: LogicalPlan = plan(ctx.query).optionalMap(ctx.columnAliases)(
+ (columnAliases, plan) =>
+ UnresolvedSubqueryColumnAliases(visitIdentifierList(columnAliases), plan)
+ )
+ SubqueryAlias(ctx.name.getText, subQuery)
+ }
+
+ /**
+ * Create a logical plan which allows for multiple inserts using one 'from' statement. These
+ * queries have the following SQL form:
+ * {{{
+ * [WITH cte...]?
+ * FROM src
+ * [INSERT INTO tbl1 SELECT *]+
+ * }}}
+ * For example:
+ * {{{
+ * FROM db.tbl1 A
+ * INSERT INTO dbo.tbl1 SELECT * WHERE A.value = 10 LIMIT 5
+ * INSERT INTO dbo.tbl2 SELECT * WHERE A.value = 12
+ * }}}
+ * This (Hive) feature cannot be combined with set-operators.
+ */
+ override def visitMultiInsertQuery(ctx: MultiInsertQueryContext): LogicalPlan = withOrigin(ctx) {
+ val from = visitFromClause(ctx.fromClause)
+
+ // Build the insert clauses.
+ val inserts = ctx.multiInsertQueryBody.asScala.map { body =>
+ withInsertInto(body.insertInto,
+ withFromStatementBody(body.fromStatementBody, from).
+ optionalMap(body.fromStatementBody.queryOrganization)(withQueryResultClauses))
+ }
+
+ // If there are multiple INSERTS just UNION them together into one query.
+ if (inserts.length == 1) {
+ inserts.head
+ } else {
+ Union(inserts.toSeq)
+ }
+ }
+
+ /**
+ * Create a logical plan for a regular (single-insert) query.
+ */
+ override def visitSingleInsertQuery(
+ ctx: SingleInsertQueryContext): LogicalPlan = withOrigin(ctx) {
+ withInsertInto(
+ ctx.insertInto(),
+ plan(ctx.queryTerm).optionalMap(ctx.queryOrganization)(withQueryResultClauses))
+ }
+
+ /**
+ * Parameters used for writing query to a table:
+ * (UnresolvedRelation, tableColumnList, partitionKeys, ifPartitionNotExists).
+ */
+ type InsertTableParams = (UnresolvedRelation, Seq[String], Map[String, Option[String]], Boolean)
+
+ /**
+ * Parameters used for writing query to a directory: (isLocal, CatalogStorageFormat, provider).
+ */
+ type InsertDirParams = (Boolean, CatalogStorageFormat, Option[String])
+
+ /**
+ * Add an
+ * {{{
+ * INSERT OVERWRITE TABLE tableIdentifier [partitionSpec [IF NOT EXISTS]]? [identifierList]
+ * INSERT INTO [TABLE] tableIdentifier [partitionSpec] [identifierList]
+ * INSERT OVERWRITE [LOCAL] DIRECTORY STRING [rowFormat] [createFileFormat]
+ * INSERT OVERWRITE [LOCAL] DIRECTORY [STRING] tableProvider [OPTIONS tablePropertyList]
+ * }}}
+ * operation to logical plan
+ */
+ private def withInsertInto(
+ ctx: InsertIntoContext,
+ query: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ ctx match {
+ case table: InsertIntoTableContext =>
+ val (relation, cols, partition, ifPartitionNotExists) = visitInsertIntoTable(table)
+ InsertIntoStatement(
+ relation,
+ partition,
+ cols,
+ query,
+ overwrite = false,
+ ifPartitionNotExists)
+ case table: InsertOverwriteTableContext =>
+ val (relation, cols, partition, ifPartitionNotExists) = visitInsertOverwriteTable(table)
+ InsertIntoStatement(
+ relation,
+ partition,
+ cols,
+ query,
+ overwrite = true,
+ ifPartitionNotExists)
+ case dir: InsertOverwriteDirContext =>
+ val (isLocal, storage, provider) = visitInsertOverwriteDir(dir)
+ InsertIntoDir(isLocal, storage, provider, query, overwrite = true)
+ case hiveDir: InsertOverwriteHiveDirContext =>
+ val (isLocal, storage, provider) = visitInsertOverwriteHiveDir(hiveDir)
+ InsertIntoDir(isLocal, storage, provider, query, overwrite = true)
+ case _ =>
+ throw new ParseException("Invalid InsertIntoContext", ctx)
+ }
+ }
+
+ /**
+ * Add an INSERT INTO TABLE operation to the logical plan.
+ */
+ override def visitInsertIntoTable(
+ ctx: InsertIntoTableContext): InsertTableParams = withOrigin(ctx) {
+ val cols = Option(ctx.identifierList()).map(visitIdentifierList).getOrElse(Nil)
+ val partitionKeys = Option(ctx.partitionSpec).map(visitPartitionSpec).getOrElse(Map.empty)
+
+ if (ctx.EXISTS != null) {
+ operationNotAllowed("INSERT INTO ... IF NOT EXISTS", ctx)
+ }
+
+ (createUnresolvedRelation(ctx.multipartIdentifier), cols, partitionKeys, false)
+ }
+
+ /**
+ * Add an INSERT OVERWRITE TABLE operation to the logical plan.
+ */
+ override def visitInsertOverwriteTable(
+ ctx: InsertOverwriteTableContext): InsertTableParams = withOrigin(ctx) {
+ assert(ctx.OVERWRITE() != null)
+ val cols = Option(ctx.identifierList()).map(visitIdentifierList).getOrElse(Nil)
+ val partitionKeys = Option(ctx.partitionSpec).map(visitPartitionSpec).getOrElse(Map.empty)
+
+ val dynamicPartitionKeys: Map[String, Option[String]] = partitionKeys.filter(_._2.isEmpty)
+ if (ctx.EXISTS != null && dynamicPartitionKeys.nonEmpty) {
+ operationNotAllowed("IF NOT EXISTS with dynamic partitions: " +
+ dynamicPartitionKeys.keys.mkString(", "), ctx)
+ }
+
+ (createUnresolvedRelation(ctx.multipartIdentifier), cols, partitionKeys, ctx.EXISTS() != null)
+ }
+
+ /**
+ * Write to a directory, returning a [[InsertIntoDir]] logical plan.
+ */
+ override def visitInsertOverwriteDir(
+ ctx: InsertOverwriteDirContext): InsertDirParams = withOrigin(ctx) {
+ throw new ParseException("INSERT OVERWRITE DIRECTORY is not supported", ctx)
+ }
+
+ /**
+ * Write to a directory, returning a [[InsertIntoDir]] logical plan.
+ */
+ override def visitInsertOverwriteHiveDir(
+ ctx: InsertOverwriteHiveDirContext): InsertDirParams = withOrigin(ctx) {
+ throw new ParseException("INSERT OVERWRITE DIRECTORY is not supported", ctx)
+ }
+
+ private def getTableAliasWithoutColumnAlias(
+ ctx: TableAliasContext, op: String): Option[String] = {
+ if (ctx == null) {
+ None
+ } else {
+ val ident = ctx.strictIdentifier()
+ if (ctx.identifierList() != null) {
+ throw new ParseException(s"Columns aliases are not allowed in $op.", ctx.identifierList())
+ }
+ if (ident != null) Some(ident.getText) else None
+ }
+ }
+
+ override def visitDeleteFromTable(
+ ctx: DeleteFromTableContext): LogicalPlan = withOrigin(ctx) {
+ val table = createUnresolvedRelation(ctx.multipartIdentifier())
+ val tableAlias = getTableAliasWithoutColumnAlias(ctx.tableAlias(), "DELETE")
+ val aliasedTable = tableAlias.map(SubqueryAlias(_, table)).getOrElse(table)
+ val predicate = if (ctx.whereClause() != null) {
+ Some(expression(ctx.whereClause().booleanExpression()))
+ } else {
+ None
+ }
+ DeleteFromTable(aliasedTable, predicate.get)
+ }
+
+ override def visitUpdateTable(ctx: UpdateTableContext): LogicalPlan = withOrigin(ctx) {
+ val table = createUnresolvedRelation(ctx.multipartIdentifier())
+ val tableAlias = getTableAliasWithoutColumnAlias(ctx.tableAlias(), "UPDATE")
+ val aliasedTable = tableAlias.map(SubqueryAlias(_, table)).getOrElse(table)
+ val assignments = withAssignments(ctx.setClause().assignmentList())
+ val predicate = if (ctx.whereClause() != null) {
+ Some(expression(ctx.whereClause().booleanExpression()))
+ } else {
+ None
+ }
+
+ UpdateTable(aliasedTable, assignments, predicate)
+ }
+
+ private def withAssignments(assignCtx: AssignmentListContext): Seq[Assignment] =
+ withOrigin(assignCtx) {
+ assignCtx.assignment().asScala.map { assign =>
+ Assignment(UnresolvedAttribute(visitMultipartIdentifier(assign.key)),
+ expression(assign.value))
+ }.toSeq
+ }
+
+ override def visitMergeIntoTable(ctx: MergeIntoTableContext): LogicalPlan = withOrigin(ctx) {
+ val targetTable = createUnresolvedRelation(ctx.target)
+ val targetTableAlias = getTableAliasWithoutColumnAlias(ctx.targetAlias, "MERGE")
+ val aliasedTarget = targetTableAlias.map(SubqueryAlias(_, targetTable)).getOrElse(targetTable)
+
+ val sourceTableOrQuery = if (ctx.source != null) {
+ createUnresolvedRelation(ctx.source)
+ } else if (ctx.sourceQuery != null) {
+ visitQuery(ctx.sourceQuery)
+ } else {
+ throw new ParseException("Empty source for merge: you should specify a source" +
+ " table/subquery in merge.", ctx.source)
+ }
+ val sourceTableAlias = getTableAliasWithoutColumnAlias(ctx.sourceAlias, "MERGE")
+ val aliasedSource =
+ sourceTableAlias.map(SubqueryAlias(_, sourceTableOrQuery)).getOrElse(sourceTableOrQuery)
+
+ val mergeCondition = expression(ctx.mergeCondition)
+
+ val matchedActions = ctx.matchedClause().asScala.map {
+ clause => {
+ if (clause.matchedAction().DELETE() != null) {
+ DeleteAction(Option(clause.matchedCond).map(expression))
+ } else if (clause.matchedAction().UPDATE() != null) {
+ val condition = Option(clause.matchedCond).map(expression)
+ if (clause.matchedAction().ASTERISK() != null) {
+ UpdateStarAction(condition)
+ } else {
+ UpdateAction(condition, withAssignments(clause.matchedAction().assignmentList()))
+ }
+ } else {
+ // It should not be here.
+ throw new ParseException(s"Unrecognized matched action: ${clause.matchedAction().getText}",
+ clause.matchedAction())
+ }
+ }
+ }
+ val notMatchedActions = ctx.notMatchedClause().asScala.map {
+ clause => {
+ if (clause.notMatchedAction().INSERT() != null) {
+ val condition = Option(clause.notMatchedCond).map(expression)
+ if (clause.notMatchedAction().ASTERISK() != null) {
+ InsertStarAction(condition)
+ } else {
+ val columns = clause.notMatchedAction().columns.multipartIdentifier()
+ .asScala.map(attr => UnresolvedAttribute(visitMultipartIdentifier(attr)))
+ val values = clause.notMatchedAction().expression().asScala.map(expression)
+ if (columns.size != values.size) {
+ throw new ParseException("The number of inserted values cannot match the fields.",
+ clause.notMatchedAction())
+ }
+ InsertAction(condition, columns.zip(values).map(kv => Assignment(kv._1, kv._2)).toSeq)
+ }
+ } else {
+ // It should not be here.
+ throw new ParseException(s"Unrecognized not matched action: ${clause.notMatchedAction().getText}",
+ clause.notMatchedAction())
+ }
+ }
+ }
+ if (matchedActions.isEmpty && notMatchedActions.isEmpty) {
+ throw new ParseException("There must be at least one WHEN clause in a MERGE statement", ctx)
+ }
+ // children being empty means that the condition is not set
+ val matchedActionSize = matchedActions.length
+ if (matchedActionSize >= 2 && !matchedActions.init.forall(_.condition.nonEmpty)) {
+ throw new ParseException("When there are more than one MATCHED clauses in a MERGE " +
+ "statement, only the last MATCHED clause can omit the condition.", ctx)
+ }
+ val notMatchedActionSize = notMatchedActions.length
+ if (notMatchedActionSize >= 2 && !notMatchedActions.init.forall(_.condition.nonEmpty)) {
+ throw new ParseException("When there are more than one NOT MATCHED clauses in a MERGE " +
+ "statement, only the last NOT MATCHED clause can omit the condition.", ctx)
+ }
+
+ MergeIntoTable(
+ aliasedTarget,
+ aliasedSource,
+ mergeCondition,
+ matchedActions.toSeq,
+ notMatchedActions.toSeq)
+ }
+
+ /**
+ * Create a partition specification map.
+ */
+ override def visitPartitionSpec(
+ ctx: PartitionSpecContext): Map[String, Option[String]] = withOrigin(ctx) {
+ val legacyNullAsString =
+ conf.getConf(SQLConf.LEGACY_PARSE_NULL_PARTITION_SPEC_AS_STRING_LITERAL)
+ val parts = ctx.partitionVal.asScala.map { pVal =>
+ val name = pVal.identifier.getText
+ val value = Option(pVal.constant).map(v => visitStringConstant(v, legacyNullAsString))
+ name -> value
+ }
+ // Before calling `toMap`, we check duplicated keys to avoid silently ignore partition values
+ // in partition spec like PARTITION(a='1', b='2', a='3'). The real semantical check for
+ // partition columns will be done in analyzer.
+ if (conf.caseSensitiveAnalysis) {
+ checkDuplicateKeys(parts.toSeq, ctx)
+ } else {
+ checkDuplicateKeys(parts.map(kv => kv._1.toLowerCase(Locale.ROOT) -> kv._2).toSeq, ctx)
+ }
+ parts.toMap
+ }
+
+ /**
+ * Create a partition specification map without optional values.
+ */
+ protected def visitNonOptionalPartitionSpec(
+ ctx: PartitionSpecContext): Map[String, String] = withOrigin(ctx) {
+ visitPartitionSpec(ctx).map {
+ case (key, None) => throw new ParseException(s"Found an empty partition key '$key'.", ctx)
+ case (key, Some(value)) => key -> value
+ }
+ }
+
+ /**
+ * Convert a constant of any type into a string. This is typically used in DDL commands, and its
+ * main purpose is to prevent slight differences due to back to back conversions i.e.:
+ * String -> Literal -> String.
+ */
+ protected def visitStringConstant(
+ ctx: ConstantContext,
+ legacyNullAsString: Boolean): String = withOrigin(ctx) {
+ expression(ctx) match {
+ case Literal(null, _) if !legacyNullAsString => null
+ case l@Literal(null, _) => l.toString
+ case l: Literal =>
+ // TODO For v2 commands, we will cast the string back to its actual value,
+ // which is a waste and can be improved in the future.
+ Cast(l, StringType, Some(conf.sessionLocalTimeZone)).eval().toString
+ case other =>
+ throw new IllegalArgumentException(s"Only literals are allowed in the " +
+ s"partition spec, but got ${other.sql}")
+ }
+ }
+
+ /**
+ * Add ORDER BY/SORT BY/CLUSTER BY/DISTRIBUTE BY/LIMIT/WINDOWS clauses to the logical plan. These
+ * clauses determine the shape (ordering/partitioning/rows) of the query result.
+ */
+ private def withQueryResultClauses(
+ ctx: QueryOrganizationContext,
+ query: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ import ctx._
+
+ // Handle ORDER BY, SORT BY, DISTRIBUTE BY, and CLUSTER BY clause.
+ val withOrder = if (
+ !order.isEmpty && sort.isEmpty && distributeBy.isEmpty && clusterBy.isEmpty) {
+ // ORDER BY ...
+ Sort(order.asScala.map(visitSortItem).toSeq, global = true, query)
+ } else if (order.isEmpty && !sort.isEmpty && distributeBy.isEmpty && clusterBy.isEmpty) {
+ // SORT BY ...
+ Sort(sort.asScala.map(visitSortItem).toSeq, global = false, query)
+ } else if (order.isEmpty && sort.isEmpty && !distributeBy.isEmpty && clusterBy.isEmpty) {
+ // DISTRIBUTE BY ...
+ withRepartitionByExpression(ctx, expressionList(distributeBy), query)
+ } else if (order.isEmpty && !sort.isEmpty && !distributeBy.isEmpty && clusterBy.isEmpty) {
+ // SORT BY ... DISTRIBUTE BY ...
+ Sort(
+ sort.asScala.map(visitSortItem).toSeq,
+ global = false,
+ withRepartitionByExpression(ctx, expressionList(distributeBy), query))
+ } else if (order.isEmpty && sort.isEmpty && distributeBy.isEmpty && !clusterBy.isEmpty) {
+ // CLUSTER BY ...
+ val expressions = expressionList(clusterBy)
+ Sort(
+ expressions.map(SortOrder(_, Ascending)),
+ global = false,
+ withRepartitionByExpression(ctx, expressions, query))
+ } else if (order.isEmpty && sort.isEmpty && distributeBy.isEmpty && clusterBy.isEmpty) {
+ // [EMPTY]
+ query
+ } else {
+ throw new ParseException(
+ "Combination of ORDER BY/SORT BY/DISTRIBUTE BY/CLUSTER BY is not supported", ctx)
+ }
+
+ // WINDOWS
+ val withWindow = withOrder.optionalMap(windowClause)(withWindowClause)
+
+ // LIMIT
+ // - LIMIT ALL is the same as omitting the LIMIT clause
+ withWindow.optional(limit) {
+ Limit(typedVisit(limit), withWindow)
+ }
+ }
+
+ /**
+ * Create a clause for DISTRIBUTE BY.
+ */
+ protected def withRepartitionByExpression(
+ ctx: QueryOrganizationContext,
+ expressions: Seq[Expression],
+ query: LogicalPlan): LogicalPlan = {
+ RepartitionByExpression(expressions, query, None)
+ }
+
+ override def visitTransformQuerySpecification(
+ ctx: TransformQuerySpecificationContext): LogicalPlan = withOrigin(ctx) {
+ val from = OneRowRelation().optional(ctx.fromClause) {
+ visitFromClause(ctx.fromClause)
+ }
+ withTransformQuerySpecification(
+ ctx,
+ ctx.transformClause,
+ ctx.lateralView,
+ ctx.whereClause,
+ ctx.aggregationClause,
+ ctx.havingClause,
+ ctx.windowClause,
+ from
+ )
+ }
+
+ override def visitRegularQuerySpecification(
+ ctx: RegularQuerySpecificationContext): LogicalPlan = withOrigin(ctx) {
+ val from = OneRowRelation().optional(ctx.fromClause) {
+ visitFromClause(ctx.fromClause)
+ }
+ withSelectQuerySpecification(
+ ctx,
+ ctx.selectClause,
+ ctx.lateralView,
+ ctx.whereClause,
+ ctx.aggregationClause,
+ ctx.havingClause,
+ ctx.windowClause,
+ from
+ )
+ }
+
+ override def visitNamedExpressionSeq(
+ ctx: NamedExpressionSeqContext): Seq[Expression] = {
+ Option(ctx).toSeq
+ .flatMap(_.namedExpression.asScala)
+ .map(typedVisit[Expression])
+ }
+
+ override def visitExpressionSeq(ctx: ExpressionSeqContext): Seq[Expression] = {
+ Option(ctx).toSeq
+ .flatMap(_.expression.asScala)
+ .map(typedVisit[Expression])
+ }
+
+ /**
+ * Create a logical plan using a having clause.
+ */
+ private def withHavingClause(
+ ctx: HavingClauseContext, plan: LogicalPlan): LogicalPlan = {
+ // Note that we add a cast to non-predicate expressions. If the expression itself is
+ // already boolean, the optimizer will get rid of the unnecessary cast.
+ val predicate = expression(ctx.booleanExpression) match {
+ case p: Predicate => p
+ case e => Cast(e, BooleanType)
+ }
+ UnresolvedHaving(predicate, plan)
+ }
+
+ /**
+ * Create a logical plan using a where clause.
+ */
+ private def withWhereClause(ctx: WhereClauseContext, plan: LogicalPlan): LogicalPlan = {
+ Filter(expression(ctx.booleanExpression), plan)
+ }
+
+ /**
+ * Add a hive-style transform (SELECT TRANSFORM/MAP/REDUCE) query specification to a logical plan.
+ */
+ private def withTransformQuerySpecification(
+ ctx: ParserRuleContext,
+ transformClause: TransformClauseContext,
+ lateralView: java.util.List[LateralViewContext],
+ whereClause: WhereClauseContext,
+ aggregationClause: AggregationClauseContext,
+ havingClause: HavingClauseContext,
+ windowClause: WindowClauseContext,
+ relation: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ if (transformClause.setQuantifier != null) {
+ throw new ParseException("TRANSFORM does not support DISTINCT/ALL in inputs", transformClause.setQuantifier)
+ }
+ // Create the attributes.
+ val (attributes, schemaLess) = if (transformClause.colTypeList != null) {
+ // Typed return columns.
+ (createSchema(transformClause.colTypeList).toAttributes, false)
+ } else if (transformClause.identifierSeq != null) {
+ // Untyped return columns.
+ val attrs = visitIdentifierSeq(transformClause.identifierSeq).map { name =>
+ AttributeReference(name, StringType, nullable = true)()
+ }
+ (attrs, false)
+ } else {
+ (Seq(AttributeReference("key", StringType)(),
+ AttributeReference("value", StringType)()), true)
+ }
+
+ val plan = visitCommonSelectQueryClausePlan(
+ relation,
+ visitExpressionSeq(transformClause.expressionSeq),
+ lateralView,
+ whereClause,
+ aggregationClause,
+ havingClause,
+ windowClause,
+ isDistinct = false)
+
+ ScriptTransformation(
+ string(transformClause.script),
+ attributes,
+ plan,
+ withScriptIOSchema(
+ ctx,
+ transformClause.inRowFormat,
+ transformClause.recordWriter,
+ transformClause.outRowFormat,
+ transformClause.recordReader,
+ schemaLess
+ )
+ )
+ }
+
+ /**
+ * Add a regular (SELECT) query specification to a logical plan. The query specification
+ * is the core of the logical plan, this is where sourcing (FROM clause), projection (SELECT),
+ * aggregation (GROUP BY ... HAVING ...) and filtering (WHERE) takes place.
+ *
+ * Note that query hints are ignored (both by the parser and the builder).
+ */
+ private def withSelectQuerySpecification(
+ ctx: ParserRuleContext,
+ selectClause: SelectClauseContext,
+ lateralView: java.util.List[LateralViewContext],
+ whereClause: WhereClauseContext,
+ aggregationClause: AggregationClauseContext,
+ havingClause: HavingClauseContext,
+ windowClause: WindowClauseContext,
+ relation: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ val isDistinct = selectClause.setQuantifier() != null &&
+ selectClause.setQuantifier().DISTINCT() != null
+
+ val plan = visitCommonSelectQueryClausePlan(
+ relation,
+ visitNamedExpressionSeq(selectClause.namedExpressionSeq),
+ lateralView,
+ whereClause,
+ aggregationClause,
+ havingClause,
+ windowClause,
+ isDistinct)
+
+ // Hint
+ selectClause.hints.asScala.foldRight(plan)(withHints)
+ }
+
+ def visitCommonSelectQueryClausePlan(
+ relation: LogicalPlan,
+ expressions: Seq[Expression],
+ lateralView: java.util.List[LateralViewContext],
+ whereClause: WhereClauseContext,
+ aggregationClause: AggregationClauseContext,
+ havingClause: HavingClauseContext,
+ windowClause: WindowClauseContext,
+ isDistinct: Boolean): LogicalPlan = {
+ // Add lateral views.
+ val withLateralView = lateralView.asScala.foldLeft(relation)(withGenerate)
+
+ // Add where.
+ val withFilter = withLateralView.optionalMap(whereClause)(withWhereClause)
+
+ // Add aggregation or a project.
+ val namedExpressions = expressions.map {
+ case e: NamedExpression => e
+ case e: Expression => UnresolvedAlias(e)
+ }
+
+ def createProject() = if (namedExpressions.nonEmpty) {
+ Project(namedExpressions, withFilter)
+ } else {
+ withFilter
+ }
+
+ val withProject = if (aggregationClause == null && havingClause != null) {
+ if (conf.getConf(SQLConf.LEGACY_HAVING_WITHOUT_GROUP_BY_AS_WHERE)) {
+ // If the legacy conf is set, treat HAVING without GROUP BY as WHERE.
+ val predicate = expression(havingClause.booleanExpression) match {
+ case p: Predicate => p
+ case e => Cast(e, BooleanType)
+ }
+ Filter(predicate, createProject())
+ } else {
+ // According to SQL standard, HAVING without GROUP BY means global aggregate.
+ withHavingClause(havingClause, Aggregate(Nil, namedExpressions, withFilter))
+ }
+ } else if (aggregationClause != null) {
+ val aggregate = withAggregationClause(aggregationClause, namedExpressions, withFilter)
+ aggregate.optionalMap(havingClause)(withHavingClause)
+ } else {
+ // When hitting this branch, `having` must be null.
+ createProject()
+ }
+
+ // Distinct
+ val withDistinct = if (isDistinct) {
+ Distinct(withProject)
+ } else {
+ withProject
+ }
+
+ // Window
+ val withWindow = withDistinct.optionalMap(windowClause)(withWindowClause)
+
+ withWindow
+ }
+
+ // Script Transform's input/output format.
+ type ScriptIOFormat =
+ (Seq[(String, String)], Option[String], Seq[(String, String)], Option[String])
+
+ protected def getRowFormatDelimited(ctx: RowFormatDelimitedContext): ScriptIOFormat = {
+ // TODO we should use the visitRowFormatDelimited function here. However HiveScriptIOSchema
+ // expects a seq of pairs in which the old parsers' token names are used as keys.
+ // Transforming the result of visitRowFormatDelimited would be quite a bit messier than
+ // retrieving the key value pairs ourselves.
+ val entries = entry("TOK_TABLEROWFORMATFIELD", ctx.fieldsTerminatedBy) ++
+ entry("TOK_TABLEROWFORMATCOLLITEMS", ctx.collectionItemsTerminatedBy) ++
+ entry("TOK_TABLEROWFORMATMAPKEYS", ctx.keysTerminatedBy) ++
+ entry("TOK_TABLEROWFORMATNULL", ctx.nullDefinedAs) ++
+ Option(ctx.linesSeparatedBy).toSeq.map { token =>
+ val value = string(token)
+ validate(
+ value == "\n",
+ s"LINES TERMINATED BY only supports newline '\\n' right now: $value",
+ ctx)
+ "TOK_TABLEROWFORMATLINES" -> value
+ }
+
+ (entries, None, Seq.empty, None)
+ }
+
+ /**
+ * Create a [[ScriptInputOutputSchema]].
+ */
+ protected def withScriptIOSchema(
+ ctx: ParserRuleContext,
+ inRowFormat: RowFormatContext,
+ recordWriter: Token,
+ outRowFormat: RowFormatContext,
+ recordReader: Token,
+ schemaLess: Boolean): ScriptInputOutputSchema = {
+
+ def format(fmt: RowFormatContext): ScriptIOFormat = fmt match {
+ case c: RowFormatDelimitedContext =>
+ getRowFormatDelimited(c)
+
+ case c: RowFormatSerdeContext =>
+ throw new ParseException("TRANSFORM with serde is only supported in hive mode", ctx)
+
+ // SPARK-32106: When there is no definition about format, we return empty result
+ // to use a built-in default Serde in SparkScriptTransformationExec.
+ case null =>
+ (Nil, None, Seq.empty, None)
+ }
+
+ val (inFormat, inSerdeClass, inSerdeProps, reader) = format(inRowFormat)
+
+ val (outFormat, outSerdeClass, outSerdeProps, writer) = format(outRowFormat)
+
+ ScriptInputOutputSchema(
+ inFormat, outFormat,
+ inSerdeClass, outSerdeClass,
+ inSerdeProps, outSerdeProps,
+ reader, writer,
+ schemaLess)
+ }
+
+ /**
+ * Create a logical plan for a given 'FROM' clause. Note that we support multiple (comma
+ * separated) relations here, these get converted into a single plan by condition-less inner join.
+ */
+ override def visitFromClause(ctx: FromClauseContext): LogicalPlan = withOrigin(ctx) {
+ val from = ctx.relation.asScala.foldLeft(null: LogicalPlan) { (left, relation) =>
+ val right = plan(relation.relationPrimary)
+ val join = right.optionalMap(left) { (left, right) =>
+ if (relation.LATERAL != null) {
+ if (!relation.relationPrimary.isInstanceOf[AliasedQueryContext]) {
+ throw new ParseException(s"LATERAL can only be used with subquery", relation.relationPrimary)
+ }
+ LateralJoin(left, LateralSubquery(right), Inner, None)
+ } else {
+ Join(left, right, Inner, None, JoinHint.NONE)
+ }
+ }
+ withJoinRelations(join, relation)
+ }
+ if (ctx.pivotClause() != null) {
+ if (!ctx.lateralView.isEmpty) {
+ throw new ParseException("LATERAL cannot be used together with PIVOT in FROM clause", ctx)
+ }
+ withPivot(ctx.pivotClause, from)
+ } else {
+ ctx.lateralView.asScala.foldLeft(from)(withGenerate)
+ }
+ }
+
+ /**
+ * Connect two queries by a Set operator.
+ *
+ * Supported Set operators are:
+ * - UNION [ DISTINCT | ALL ]
+ * - EXCEPT [ DISTINCT | ALL ]
+ * - MINUS [ DISTINCT | ALL ]
+ * - INTERSECT [DISTINCT | ALL]
+ */
+ override def visitSetOperation(ctx: SetOperationContext): LogicalPlan = withOrigin(ctx) {
+ val left = plan(ctx.left)
+ val right = plan(ctx.right)
+ val all = Option(ctx.setQuantifier()).exists(_.ALL != null)
+ ctx.operator.getType match {
+ case HoodieSqlBaseParser.UNION if all =>
+ Union(left, right)
+ case HoodieSqlBaseParser.UNION =>
+ Distinct(Union(left, right))
+ case HoodieSqlBaseParser.INTERSECT if all =>
+ Intersect(left, right, isAll = true)
+ case HoodieSqlBaseParser.INTERSECT =>
+ Intersect(left, right, isAll = false)
+ case HoodieSqlBaseParser.EXCEPT if all =>
+ Except(left, right, isAll = true)
+ case HoodieSqlBaseParser.EXCEPT =>
+ Except(left, right, isAll = false)
+ case HoodieSqlBaseParser.SETMINUS if all =>
+ Except(left, right, isAll = true)
+ case HoodieSqlBaseParser.SETMINUS =>
+ Except(left, right, isAll = false)
+ }
+ }
+
+ /**
+ * Add a [[WithWindowDefinition]] operator to a logical plan.
+ */
+ private def withWindowClause(
+ ctx: WindowClauseContext,
+ query: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ // Collect all window specifications defined in the WINDOW clause.
+ val baseWindowTuples = ctx.namedWindow.asScala.map {
+ wCtx =>
+ (wCtx.name.getText, typedVisit[WindowSpec](wCtx.windowSpec))
+ }
+ baseWindowTuples.groupBy(_._1).foreach { kv =>
+ if (kv._2.size > 1) {
+ throw new ParseException(s"The definition of window '${kv._1}' is repetitive", ctx)
+ }
+ }
+ val baseWindowMap = baseWindowTuples.toMap
+
+ // Handle cases like
+ // window w1 as (partition by p_mfgr order by p_name
+ // range between 2 preceding and 2 following),
+ // w2 as w1
+ val windowMapView = baseWindowMap.mapValues {
+ case WindowSpecReference(name) =>
+ baseWindowMap.get(name) match {
+ case Some(spec: WindowSpecDefinition) =>
+ spec
+ case Some(ref) =>
+ throw new ParseException(s"Window reference '$name' is not a window specification", ctx)
+ case None =>
+ throw new ParseException(s"Cannot resolve window reference '$name'", ctx)
+ }
+ case spec: WindowSpecDefinition => spec
+ }
+
+ // Note that mapValues creates a view instead of materialized map. We force materialization by
+ // mapping over identity.
+ WithWindowDefinition(windowMapView.map(identity).toMap, query)
+ }
+
+ /**
+ * Add an [[Aggregate]] to a logical plan.
+ */
+ private def withAggregationClause(
+ ctx: AggregationClauseContext,
+ selectExpressions: Seq[NamedExpression],
+ query: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ if (ctx.groupingExpressionsWithGroupingAnalytics.isEmpty) {
+ val groupByExpressions = expressionList(ctx.groupingExpressions)
+ if (ctx.GROUPING != null) {
+ // GROUP BY ... GROUPING SETS (...)
+ // `groupByExpressions` can be non-empty for Hive compatibility. It may add extra grouping
+ // expressions that do not exist in GROUPING SETS (...), and the value is always null.
+ // For example, `SELECT a, b, c FROM ... GROUP BY a, b, c GROUPING SETS (a, b)`, the output
+ // of column `c` is always null.
+ val groupingSets =
+ ctx.groupingSet.asScala.map(_.expression.asScala.map(e => expression(e)).toSeq)
+ Aggregate(Seq(GroupingSets(groupingSets.toSeq, groupByExpressions)),
+ selectExpressions, query)
+ } else {
+ // GROUP BY .... (WITH CUBE | WITH ROLLUP)?
+ val mappedGroupByExpressions = if (ctx.CUBE != null) {
+ Seq(Cube(groupByExpressions.map(Seq(_))))
+ } else if (ctx.ROLLUP != null) {
+ Seq(Rollup(groupByExpressions.map(Seq(_))))
+ } else {
+ groupByExpressions
+ }
+ Aggregate(mappedGroupByExpressions, selectExpressions, query)
+ }
+ } else {
+ val groupByExpressions =
+ ctx.groupingExpressionsWithGroupingAnalytics.asScala
+ .map(groupByExpr => {
+ val groupingAnalytics = groupByExpr.groupingAnalytics
+ if (groupingAnalytics != null) {
+ visitGroupingAnalytics(groupingAnalytics)
+ } else {
+ expression(groupByExpr.expression)
+ }
+ })
+ Aggregate(groupByExpressions.toSeq, selectExpressions, query)
+ }
+ }
+
+ override def visitGroupingAnalytics(
+ groupingAnalytics: GroupingAnalyticsContext): BaseGroupingSets = {
+ val groupingSets = groupingAnalytics.groupingSet.asScala
+ .map(_.expression.asScala.map(e => expression(e)).toSeq)
+ if (groupingAnalytics.CUBE != null) {
+ // CUBE(A, B, (A, B), ()) is not supported.
+ if (groupingSets.exists(_.isEmpty)) {
+ throw new ParseException(s"Empty set in CUBE grouping sets is not supported.", groupingAnalytics)
+ }
+ Cube(groupingSets.toSeq)
+ } else if (groupingAnalytics.ROLLUP != null) {
+ // ROLLUP(A, B, (A, B), ()) is not supported.
+ if (groupingSets.exists(_.isEmpty)) {
+ throw new ParseException(s"Empty set in ROLLUP grouping sets is not supported.", groupingAnalytics)
+ }
+ Rollup(groupingSets.toSeq)
+ } else {
+ assert(groupingAnalytics.GROUPING != null && groupingAnalytics.SETS != null)
+ val groupingSets = groupingAnalytics.groupingElement.asScala.flatMap { expr =>
+ val groupingAnalytics = expr.groupingAnalytics()
+ if (groupingAnalytics != null) {
+ visitGroupingAnalytics(groupingAnalytics).selectedGroupByExprs
+ } else {
+ Seq(expr.groupingSet().expression().asScala.map(e => expression(e)).toSeq)
+ }
+ }
+ GroupingSets(groupingSets.toSeq)
+ }
+ }
+
+ /**
+ * Add [[UnresolvedHint]]s to a logical plan.
+ */
+ private def withHints(
+ ctx: HintContext,
+ query: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ var plan = query
+ ctx.hintStatements.asScala.reverse.foreach { stmt =>
+ plan = UnresolvedHint(stmt.hintName.getText,
+ stmt.parameters.asScala.map(expression).toSeq, plan)
+ }
+ plan
+ }
+
+ /**
+ * Add a [[Pivot]] to a logical plan.
+ */
+ private def withPivot(
+ ctx: PivotClauseContext,
+ query: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ val aggregates = Option(ctx.aggregates).toSeq
+ .flatMap(_.namedExpression.asScala)
+ .map(typedVisit[Expression])
+ val pivotColumn = if (ctx.pivotColumn.identifiers.size == 1) {
+ UnresolvedAttribute.quoted(ctx.pivotColumn.identifier.getText)
+ } else {
+ CreateStruct(
+ ctx.pivotColumn.identifiers.asScala.map(
+ identifier => UnresolvedAttribute.quoted(identifier.getText)).toSeq)
+ }
+ val pivotValues = ctx.pivotValues.asScala.map(visitPivotValue)
+ Pivot(None, pivotColumn, pivotValues.toSeq, aggregates, query)
+ }
+
+ /**
+ * Create a Pivot column value with or without an alias.
+ */
+ override def visitPivotValue(ctx: PivotValueContext): Expression = withOrigin(ctx) {
+ val e = expression(ctx.expression)
+ if (ctx.identifier != null) {
+ Alias(e, ctx.identifier.getText)()
+ } else {
+ e
+ }
+ }
+
+ /**
+ * Add a [[Generate]] (Lateral View) to a logical plan.
+ */
+ private def withGenerate(
+ query: LogicalPlan,
+ ctx: LateralViewContext): LogicalPlan = withOrigin(ctx) {
+ val expressions = expressionList(ctx.expression)
+ Generate(
+ UnresolvedGenerator(visitFunctionName(ctx.qualifiedName), expressions),
+ unrequiredChildIndex = Nil,
+ outer = ctx.OUTER != null,
+ // scalastyle:off caselocale
+ Some(ctx.tblName.getText.toLowerCase),
+ // scalastyle:on caselocale
+ ctx.colName.asScala.map(_.getText).map(UnresolvedAttribute.quoted).toSeq,
+ query)
+ }
+
+ /**
+ * Create a single relation referenced in a FROM clause. This method is used when a part of the
+ * join condition is nested, for example:
+ * {{{
+ * select * from t1 join (t2 cross join t3) on col1 = col2
+ * }}}
+ */
+ override def visitRelation(ctx: RelationContext): LogicalPlan = withOrigin(ctx) {
+ withJoinRelations(plan(ctx.relationPrimary), ctx)
+ }
+
+ /**
+ * Join one more [[LogicalPlan]]s to the current logical plan.
+ */
+ private def withJoinRelations(base: LogicalPlan, ctx: RelationContext): LogicalPlan = {
+ ctx.joinRelation.asScala.foldLeft(base) { (left, join) =>
+ withOrigin(join) {
+ val baseJoinType = join.joinType match {
+ case null => Inner
+ case jt if jt.CROSS != null => Cross
+ case jt if jt.FULL != null => FullOuter
+ case jt if jt.SEMI != null => LeftSemi
+ case jt if jt.ANTI != null => LeftAnti
+ case jt if jt.LEFT != null => LeftOuter
+ case jt if jt.RIGHT != null => RightOuter
+ case _ => Inner
+ }
+
+ if (join.LATERAL != null && !join.right.isInstanceOf[AliasedQueryContext]) {
+ throw new ParseException(s"LATERAL can only be used with subquery", join.right)
+ }
+
+ // Resolve the join type and join condition
+ val (joinType, condition) = Option(join.joinCriteria) match {
+ case Some(c) if c.USING != null =>
+ if (join.LATERAL != null) {
+ throw new ParseException("LATERAL join with USING join is not supported", ctx)
+ }
+ (UsingJoin(baseJoinType, visitIdentifierList(c.identifierList)), None)
+ case Some(c) if c.booleanExpression != null =>
+ (baseJoinType, Option(expression(c.booleanExpression)))
+ case Some(c) =>
+ throw new ParseException(s"Unimplemented joinCriteria: $c", ctx)
+ case None if join.NATURAL != null =>
+ if (join.LATERAL != null) {
+ throw new ParseException("LATERAL join with NATURAL join is not supported", ctx)
+ }
+ if (baseJoinType == Cross) {
+ throw new ParseException("NATURAL CROSS JOIN is not supported", ctx)
+ }
+ (NaturalJoin(baseJoinType), None)
+ case None =>
+ (baseJoinType, None)
+ }
+ if (join.LATERAL != null) {
+ if (!Seq(Inner, Cross, LeftOuter).contains(joinType)) {
+ throw new ParseException(s"Unsupported LATERAL join type ${joinType.toString}", ctx)
+ }
+ LateralJoin(left, LateralSubquery(plan(join.right)), joinType, condition)
+ } else {
+ Join(left, plan(join.right), joinType, condition, JoinHint.NONE)
+ }
+ }
+ }
+ }
+
+ /**
+ * Add a [[Sample]] to a logical plan.
+ *
+ * This currently supports the following sampling methods:
+ * - TABLESAMPLE(x ROWS): Sample the table down to the given number of rows.
+ * - TABLESAMPLE(x PERCENT): Sample the table down to the given percentage. Note that percentages
+ * are defined as a number between 0 and 100.
+ * - TABLESAMPLE(BUCKET x OUT OF y): Sample the table down to a 'x' divided by 'y' fraction.
+ */
+ private def withSample(ctx: SampleContext, query: LogicalPlan): LogicalPlan = withOrigin(ctx) {
+ // Create a sampled plan if we need one.
+ def sample(fraction: Double): Sample = {
+ // The range of fraction accepted by Sample is [0, 1]. Because Hive's block sampling
+ // function takes X PERCENT as the input and the range of X is [0, 100], we need to
+ // adjust the fraction.
+ val eps = RandomSampler.roundingEpsilon
+ validate(fraction >= 0.0 - eps && fraction <= 1.0 + eps,
+ s"Sampling fraction ($fraction) must be on interval [0, 1]",
+ ctx)
+ Sample(0.0, fraction, withReplacement = false, (math.random * 1000).toInt, query)
+ }
+
+ if (ctx.sampleMethod() == null) {
+ throw new ParseException("TABLESAMPLE does not accept empty inputs.", ctx)
+ }
+
+ ctx.sampleMethod() match {
+ case ctx: SampleByRowsContext =>
+ Limit(expression(ctx.expression), query)
+
+ case ctx: SampleByPercentileContext =>
+ val fraction = ctx.percentage.getText.toDouble
+ val sign = if (ctx.negativeSign == null) 1 else -1
+ sample(sign * fraction / 100.0d)
+
+ case ctx: SampleByBytesContext =>
+ val bytesStr = ctx.bytes.getText
+ if (bytesStr.matches("[0-9]+[bBkKmMgG]")) {
+ throw new ParseException(s"TABLESAMPLE(byteLengthLiteral) is not supported", ctx)
+ } else {
+ throw new ParseException(s"$bytesStr is not a valid byte length literal, " +
+ "expected syntax: DIGIT+ ('B' | 'K' | 'M' | 'G')", ctx)
+ }
+
+ case ctx: SampleByBucketContext if ctx.ON() != null =>
+ if (ctx.identifier != null) {
+ throw new ParseException(s"TABLESAMPLE(BUCKET x OUT OF y ON colname) is not supported", ctx)
+ } else {
+ throw new ParseException(s"TABLESAMPLE(BUCKET x OUT OF y ON function) is not supported", ctx)
+ }
+
+ case ctx: SampleByBucketContext =>
+ sample(ctx.numerator.getText.toDouble / ctx.denominator.getText.toDouble)
+ }
+ }
+
+ /**
+ * Create a logical plan for a sub-query.
+ */
+ override def visitSubquery(ctx: SubqueryContext): LogicalPlan = withOrigin(ctx) {
+ plan(ctx.query)
+ }
+
+ /**
+ * Create an un-aliased table reference. This is typically used for top-level table references,
+ * for example:
+ * {{{
+ * INSERT INTO db.tbl2
+ * TABLE db.tbl1
+ * }}}
+ */
+ override def visitTable(ctx: TableContext): LogicalPlan = withOrigin(ctx) {
+ UnresolvedRelation(visitMultipartIdentifier(ctx.multipartIdentifier))
+ }
+
+ /**
+ * Create a table-valued function call with arguments, e.g. range(1000)
+ */
+ override def visitTableValuedFunction(ctx: TableValuedFunctionContext)
+ : LogicalPlan = withOrigin(ctx) {
+ val func = ctx.functionTable
+ val aliases = if (func.tableAlias.identifierList != null) {
+ visitIdentifierList(func.tableAlias.identifierList)
+ } else {
+ Seq.empty
+ }
+ val name = getFunctionIdentifier(func.functionName)
+ if (name.database.nonEmpty) {
+ operationNotAllowed(s"table valued function cannot specify database name: $name", ctx)
+ }
+
+ val tvf = UnresolvedTableValuedFunction(
+ name, func.expression.asScala.map(expression).toSeq, aliases)
+ tvf.optionalMap(func.tableAlias.strictIdentifier)(aliasPlan)
+ }
+
+ /**
+ * Create an inline table (a virtual table in Hive parlance).
+ */
+ override def visitInlineTable(ctx: InlineTableContext): LogicalPlan = withOrigin(ctx) {
+ // Get the backing expressions.
+ val rows = ctx.expression.asScala.map { e =>
+ expression(e) match {
+ // inline table comes in two styles:
+ // style 1: values (1), (2), (3) -- multiple columns are supported
+ // style 2: values 1, 2, 3 -- only a single column is supported here
+ case struct: CreateNamedStruct => struct.valExprs // style 1
+ case child => Seq(child) // style 2
+ }
+ }
+
+ val aliases = if (ctx.tableAlias.identifierList != null) {
+ visitIdentifierList(ctx.tableAlias.identifierList)
+ } else {
+ Seq.tabulate(rows.head.size)(i => s"col${i + 1}")
+ }
+
+ val table = UnresolvedInlineTable(aliases, rows.toSeq)
+ table.optionalMap(ctx.tableAlias.strictIdentifier)(aliasPlan)
+ }
+
+ /**
+ * Create an alias (SubqueryAlias) for a join relation. This is practically the same as
+ * visitAliasedQuery and visitNamedExpression, ANTLR4 however requires us to use 3 different
+ * hooks. We could add alias names for output columns, for example:
+ * {{{
+ * SELECT a, b, c, d FROM (src1 s1 INNER JOIN src2 s2 ON s1.id = s2.id) dst(a, b, c, d)
+ * }}}
+ */
+ override def visitAliasedRelation(ctx: AliasedRelationContext): LogicalPlan = withOrigin(ctx) {
+ val relation = plan(ctx.relation).optionalMap(ctx.sample)(withSample)
+ mayApplyAliasPlan(ctx.tableAlias, relation)
+ }
+
+ /**
+ * Create an alias (SubqueryAlias) for a sub-query. This is practically the same as
+ * visitAliasedRelation and visitNamedExpression, ANTLR4 however requires us to use 3 different
+ * hooks. We could add alias names for output columns, for example:
+ * {{{
+ * SELECT col1, col2 FROM testData AS t(col1, col2)
+ * }}}
+ */
+ override def visitAliasedQuery(ctx: AliasedQueryContext): LogicalPlan = withOrigin(ctx) {
+ val relation = plan(ctx.query).optionalMap(ctx.sample)(withSample)
+ if (ctx.tableAlias.strictIdentifier == null) {
+ // For un-aliased subqueries, use a default alias name that is not likely to conflict with
+ // normal subquery names, so that parent operators can only access the columns in subquery by
+ // unqualified names. Users can still use this special qualifier to access columns if they
+ // know it, but that's not recommended.
+ SubqueryAlias("__auto_generated_subquery_name", relation)
+ } else {
+ mayApplyAliasPlan(ctx.tableAlias, relation)
+ }
+ }
+
+ /**
+ * Create an alias ([[SubqueryAlias]]) for a [[LogicalPlan]].
+ */
+ private def aliasPlan(alias: ParserRuleContext, plan: LogicalPlan): LogicalPlan = {
+ SubqueryAlias(alias.getText, plan)
+ }
+
+ /**
+ * If aliases specified in a FROM clause, create a subquery alias ([[SubqueryAlias]]) and
+ * column aliases for a [[LogicalPlan]].
+ */
+ private def mayApplyAliasPlan(tableAlias: TableAliasContext, plan: LogicalPlan): LogicalPlan = {
+ if (tableAlias.strictIdentifier != null) {
+ val alias = tableAlias.strictIdentifier.getText
+ if (tableAlias.identifierList != null) {
+ val columnNames = visitIdentifierList(tableAlias.identifierList)
+ SubqueryAlias(alias, UnresolvedSubqueryColumnAliases(columnNames, plan))
+ } else {
+ SubqueryAlias(alias, plan)
+ }
+ } else {
+ plan
+ }
+ }
+
+ /**
+ * Create a Sequence of Strings for a parenthesis enclosed alias list.
+ */
+ override def visitIdentifierList(ctx: IdentifierListContext): Seq[String] = withOrigin(ctx) {
+ visitIdentifierSeq(ctx.identifierSeq)
+ }
+
+ /**
+ * Create a Sequence of Strings for an identifier list.
+ */
+ override def visitIdentifierSeq(ctx: IdentifierSeqContext): Seq[String] = withOrigin(ctx) {
+ ctx.ident.asScala.map(_.getText).toSeq
+ }
+
+ /* ********************************************************************************************
+ * Table Identifier parsing
+ * ******************************************************************************************** */
+
+ /**
+ * Create a [[TableIdentifier]] from a 'tableName' or 'databaseName'.'tableName' pattern.
+ */
+ override def visitTableIdentifier(
+ ctx: TableIdentifierContext): TableIdentifier = withOrigin(ctx) {
+ TableIdentifier(ctx.table.getText, Option(ctx.db).map(_.getText))
+ }
+
+ /**
+ * Create a [[FunctionIdentifier]] from a 'functionName' or 'databaseName'.'functionName' pattern.
+ */
+ override def visitFunctionIdentifier(
+ ctx: FunctionIdentifierContext): FunctionIdentifier = withOrigin(ctx) {
+ FunctionIdentifier(ctx.function.getText, Option(ctx.db).map(_.getText))
+ }
+
+ /**
+ * Create a multi-part identifier.
+ */
+ override def visitMultipartIdentifier(ctx: MultipartIdentifierContext): Seq[String] =
+ withOrigin(ctx) {
+ ctx.parts.asScala.map(_.getText).toSeq
+ }
+
+ /* ********************************************************************************************
+ * Expression parsing
+ * ******************************************************************************************** */
+
+ /**
+ * Create an expression from the given context. This method just passes the context on to the
+ * visitor and only takes care of typing (We assume that the visitor returns an Expression here).
+ */
+ protected def expression(ctx: ParserRuleContext): Expression = typedVisit(ctx)
+
+ /**
+ * Create sequence of expressions from the given sequence of contexts.
+ */
+ private def expressionList(trees: java.util.List[ExpressionContext]): Seq[Expression] = {
+ trees.asScala.map(expression).toSeq
+ }
+
+ /**
+ * Create a star (i.e. all) expression; this selects all elements (in the specified object).
+ * Both un-targeted (global) and targeted aliases are supported.
+ */
+ override def visitStar(ctx: StarContext): Expression = withOrigin(ctx) {
+ UnresolvedStar(Option(ctx.qualifiedName()).map(_.identifier.asScala.map(_.getText).toSeq))
+ }
+
+ /**
+ * Create an aliased expression if an alias is specified. Both single and multi-aliases are
+ * supported.
+ */
+ override def visitNamedExpression(ctx: NamedExpressionContext): Expression = withOrigin(ctx) {
+ val e = expression(ctx.expression)
+ if (ctx.name != null) {
+ Alias(e, ctx.name.getText)()
+ } else if (ctx.identifierList != null) {
+ MultiAlias(e, visitIdentifierList(ctx.identifierList))
+ } else {
+ e
+ }
+ }
+
+ /**
+ * Combine a number of boolean expressions into a balanced expression tree. These expressions are
+ * either combined by a logical [[And]] or a logical [[Or]].
+ *
+ * A balanced binary tree is created because regular left recursive trees cause considerable
+ * performance degradations and can cause stack overflows.
+ */
+ override def visitLogicalBinary(ctx: LogicalBinaryContext): Expression = withOrigin(ctx) {
+ val expressionType = ctx.operator.getType
+ val expressionCombiner = expressionType match {
+ case HoodieSqlBaseParser.AND => And.apply _
+ case HoodieSqlBaseParser.OR => Or.apply _
+ }
+
+ // Collect all similar left hand contexts.
+ val contexts = ArrayBuffer(ctx.right)
+ var current = ctx.left
+
+ def collectContexts: Boolean = current match {
+ case lbc: LogicalBinaryContext if lbc.operator.getType == expressionType =>
+ contexts += lbc.right
+ current = lbc.left
+ true
+ case _ =>
+ contexts += current
+ false
+ }
+
+ while (collectContexts) {
+ // No body - all updates take place in the collectContexts.
+ }
+
+ // Reverse the contexts to have them in the same sequence as in the SQL statement & turn them
+ // into expressions.
+ val expressions = contexts.reverseMap(expression)
+
+ // Create a balanced tree.
+ def reduceToExpressionTree(low: Int, high: Int): Expression = high - low match {
+ case 0 =>
+ expressions(low)
+ case 1 =>
+ expressionCombiner(expressions(low), expressions(high))
+ case x =>
+ val mid = low + x / 2
+ expressionCombiner(
+ reduceToExpressionTree(low, mid),
+ reduceToExpressionTree(mid + 1, high))
+ }
+
+ reduceToExpressionTree(0, expressions.size - 1)
+ }
+
+ /**
+ * Invert a boolean expression.
+ */
+ override def visitLogicalNot(ctx: LogicalNotContext): Expression = withOrigin(ctx) {
+ Not(expression(ctx.booleanExpression()))
+ }
+
+ /**
+ * Create a filtering correlated sub-query (EXISTS).
+ */
+ override def visitExists(ctx: ExistsContext): Expression = {
+ Exists(plan(ctx.query))
+ }
+
+ /**
+ * Create a comparison expression. This compares two expressions. The following comparison
+ * operators are supported:
+ * - Equal: '=' or '=='
+ * - Null-safe Equal: '<=>'
+ * - Not Equal: '<>' or '!='
+ * - Less than: '<'
+ * - Less then or Equal: '<='
+ * - Greater than: '>'
+ * - Greater then or Equal: '>='
+ */
+ override def visitComparison(ctx: ComparisonContext): Expression = withOrigin(ctx) {
+ val left = expression(ctx.left)
+ val right = expression(ctx.right)
+ val operator = ctx.comparisonOperator().getChild(0).asInstanceOf[TerminalNode]
+ operator.getSymbol.getType match {
+ case HoodieSqlBaseParser.EQ =>
+ EqualTo(left, right)
+ case HoodieSqlBaseParser.NSEQ =>
+ EqualNullSafe(left, right)
+ case HoodieSqlBaseParser.NEQ | HoodieSqlBaseParser.NEQJ =>
+ Not(EqualTo(left, right))
+ case HoodieSqlBaseParser.LT =>
+ LessThan(left, right)
+ case HoodieSqlBaseParser.LTE =>
+ LessThanOrEqual(left, right)
+ case HoodieSqlBaseParser.GT =>
+ GreaterThan(left, right)
+ case HoodieSqlBaseParser.GTE =>
+ GreaterThanOrEqual(left, right)
+ }
+ }
+
+ /**
+ * Create a predicated expression. A predicated expression is a normal expression with a
+ * predicate attached to it, for example:
+ * {{{
+ * a + 1 IS NULL
+ * }}}
+ */
+ override def visitPredicated(ctx: PredicatedContext): Expression = withOrigin(ctx) {
+ val e = expression(ctx.valueExpression)
+ if (ctx.predicate != null) {
+ withPredicate(e, ctx.predicate)
+ } else {
+ e
+ }
+ }
+
+ /**
+ * Add a predicate to the given expression. Supported expressions are:
+ * - (NOT) BETWEEN
+ * - (NOT) IN
+ * - (NOT) LIKE (ANY | SOME | ALL)
+ * - (NOT) RLIKE
+ * - IS (NOT) NULL.
+ * - IS (NOT) (TRUE | FALSE | UNKNOWN)
+ * - IS (NOT) DISTINCT FROM
+ */
+ private def withPredicate(e: Expression, ctx: PredicateContext): Expression = withOrigin(ctx) {
+ // Invert a predicate if it has a valid NOT clause.
+ def invertIfNotDefined(e: Expression): Expression = ctx.NOT match {
+ case null => e
+ case not => Not(e)
+ }
+
+ def getValueExpressions(e: Expression): Seq[Expression] = e match {
+ case c: CreateNamedStruct => c.valExprs
+ case other => Seq(other)
+ }
+
+ // Create the predicate.
+ ctx.kind.getType match {
+ case HoodieSqlBaseParser.BETWEEN =>
+ // BETWEEN is translated to lower <= e && e <= upper
+ invertIfNotDefined(And(
+ GreaterThanOrEqual(e, expression(ctx.lower)),
+ LessThanOrEqual(e, expression(ctx.upper))))
+ case HoodieSqlBaseParser.IN if ctx.query != null =>
+ invertIfNotDefined(InSubquery(getValueExpressions(e), ListQuery(plan(ctx.query))))
+ case HoodieSqlBaseParser.IN =>
+ invertIfNotDefined(In(e, ctx.expression.asScala.map(expression).toSeq))
+ case HoodieSqlBaseParser.LIKE =>
+ Option(ctx.quantifier).map(_.getType) match {
+ case Some(HoodieSqlBaseParser.ANY) | Some(HoodieSqlBaseParser.SOME) =>
+ validate(!ctx.expression.isEmpty, "Expected something between '(' and ')'.", ctx)
+ val expressions = expressionList(ctx.expression)
+ if (expressions.forall(_.foldable) && expressions.forall(_.dataType == StringType)) {
+ // If there are many pattern expressions, will throw StackOverflowError.
+ // So we use LikeAny or NotLikeAny instead.
+ val patterns = expressions.map(_.eval(EmptyRow).asInstanceOf[UTF8String])
+ ctx.NOT match {
+ case null => LikeAny(e, patterns)
+ case _ => NotLikeAny(e, patterns)
+ }
+ } else {
+ ctx.expression.asScala.map(expression)
+ .map(p => invertIfNotDefined(new Like(e, p))).toSeq.reduceLeft(Or)
+ }
+ case Some(HoodieSqlBaseParser.ALL) =>
+ validate(!ctx.expression.isEmpty, "Expected something between '(' and ')'.", ctx)
+ val expressions = expressionList(ctx.expression)
+ if (expressions.forall(_.foldable) && expressions.forall(_.dataType == StringType)) {
+ // If there are many pattern expressions, will throw StackOverflowError.
+ // So we use LikeAll or NotLikeAll instead.
+ val patterns = expressions.map(_.eval(EmptyRow).asInstanceOf[UTF8String])
+ ctx.NOT match {
+ case null => LikeAll(e, patterns)
+ case _ => NotLikeAll(e, patterns)
+ }
+ } else {
+ ctx.expression.asScala.map(expression)
+ .map(p => invertIfNotDefined(new Like(e, p))).toSeq.reduceLeft(And)
+ }
+ case _ =>
+ val escapeChar = Option(ctx.escapeChar).map(string).map { str =>
+ if (str.length != 1) {
+ throw new ParseException("Invalid escape string. Escape string must contain only one character.", ctx)
+ }
+ str.charAt(0)
+ }.getOrElse('\\')
+ invertIfNotDefined(Like(e, expression(ctx.pattern), escapeChar))
+ }
+ case HoodieSqlBaseParser.RLIKE =>
+ invertIfNotDefined(RLike(e, expression(ctx.pattern)))
+ case HoodieSqlBaseParser.NULL if ctx.NOT != null =>
+ IsNotNull(e)
+ case HoodieSqlBaseParser.NULL =>
+ IsNull(e)
+ case HoodieSqlBaseParser.TRUE => ctx.NOT match {
+ case null => EqualNullSafe(e, Literal(true))
+ case _ => Not(EqualNullSafe(e, Literal(true)))
+ }
+ case HoodieSqlBaseParser.FALSE => ctx.NOT match {
+ case null => EqualNullSafe(e, Literal(false))
+ case _ => Not(EqualNullSafe(e, Literal(false)))
+ }
+ case HoodieSqlBaseParser.UNKNOWN => ctx.NOT match {
+ case null => IsUnknown(e)
+ case _ => IsNotUnknown(e)
+ }
+ case HoodieSqlBaseParser.DISTINCT if ctx.NOT != null =>
+ EqualNullSafe(e, expression(ctx.right))
+ case HoodieSqlBaseParser.DISTINCT =>
+ Not(EqualNullSafe(e, expression(ctx.right)))
+ }
+ }
+
+ /**
+ * Create a binary arithmetic expression. The following arithmetic operators are supported:
+ * - Multiplication: '*'
+ * - Division: '/'
+ * - Hive Long Division: 'DIV'
+ * - Modulo: '%'
+ * - Addition: '+'
+ * - Subtraction: '-'
+ * - Binary AND: '&'
+ * - Binary XOR
+ * - Binary OR: '|'
+ */
+ override def visitArithmeticBinary(ctx: ArithmeticBinaryContext): Expression = withOrigin(ctx) {
+ val left = expression(ctx.left)
+ val right = expression(ctx.right)
+ ctx.operator.getType match {
+ case HoodieSqlBaseParser.ASTERISK =>
+ Multiply(left, right)
+ case HoodieSqlBaseParser.SLASH =>
+ Divide(left, right)
+ case HoodieSqlBaseParser.PERCENT =>
+ Remainder(left, right)
+ case HoodieSqlBaseParser.DIV =>
+ IntegralDivide(left, right)
+ case HoodieSqlBaseParser.PLUS =>
+ Add(left, right)
+ case HoodieSqlBaseParser.MINUS =>
+ Subtract(left, right)
+ case HoodieSqlBaseParser.CONCAT_PIPE =>
+ Concat(left :: right :: Nil)
+ case HoodieSqlBaseParser.AMPERSAND =>
+ BitwiseAnd(left, right)
+ case HoodieSqlBaseParser.HAT =>
+ BitwiseXor(left, right)
+ case HoodieSqlBaseParser.PIPE =>
+ BitwiseOr(left, right)
+ }
+ }
+
+ /**
+ * Create a unary arithmetic expression. The following arithmetic operators are supported:
+ * - Plus: '+'
+ * - Minus: '-'
+ * - Bitwise Not: '~'
+ */
+ override def visitArithmeticUnary(ctx: ArithmeticUnaryContext): Expression = withOrigin(ctx) {
+ val value = expression(ctx.valueExpression)
+ ctx.operator.getType match {
+ case HoodieSqlBaseParser.PLUS =>
+ UnaryPositive(value)
+ case HoodieSqlBaseParser.MINUS =>
+ UnaryMinus(value)
+ case HoodieSqlBaseParser.TILDE =>
+ BitwiseNot(value)
+ }
+ }
+
+ override def visitCurrentLike(ctx: CurrentLikeContext): Expression = withOrigin(ctx) {
+ if (conf.ansiEnabled) {
+ ctx.name.getType match {
+ case HoodieSqlBaseParser.CURRENT_DATE =>
+ CurrentDate()
+ case HoodieSqlBaseParser.CURRENT_TIMESTAMP =>
+ CurrentTimestamp()
+ case HoodieSqlBaseParser.CURRENT_USER =>
+ CurrentUser()
+ }
+ } else {
+ // If the parser is not in ansi mode, we should return `UnresolvedAttribute`, in case there
+ // are columns named `CURRENT_DATE` or `CURRENT_TIMESTAMP`.
+ UnresolvedAttribute.quoted(ctx.name.getText)
+ }
+ }
+
+ /**
+ * Create a [[Cast]] expression.
+ */
+ override def visitCast(ctx: CastContext): Expression = withOrigin(ctx) {
+ val rawDataType = typedVisit[DataType](ctx.dataType())
+ val dataType = CharVarcharUtils.replaceCharVarcharWithStringForCast(rawDataType)
+ val cast = ctx.name.getType match {
+ case HoodieSqlBaseParser.CAST =>
+ Cast(expression(ctx.expression), dataType)
+
+ case HoodieSqlBaseParser.TRY_CAST =>
+ TryCast(expression(ctx.expression), dataType)
+ }
+ cast.setTagValue(Cast.USER_SPECIFIED_CAST, true)
+ cast
+ }
+
+ /**
+ * Create a [[CreateStruct]] expression.
+ */
+ override def visitStruct(ctx: StructContext): Expression = withOrigin(ctx) {
+ CreateStruct.create(ctx.argument.asScala.map(expression).toSeq)
+ }
+
+ /**
+ * Create a [[First]] expression.
+ */
+ override def visitFirst(ctx: FirstContext): Expression = withOrigin(ctx) {
+ val ignoreNullsExpr = ctx.IGNORE != null
+ First(expression(ctx.expression), ignoreNullsExpr).toAggregateExpression()
+ }
+
+ /**
+ * Create a [[Last]] expression.
+ */
+ override def visitLast(ctx: LastContext): Expression = withOrigin(ctx) {
+ val ignoreNullsExpr = ctx.IGNORE != null
+ Last(expression(ctx.expression), ignoreNullsExpr).toAggregateExpression()
+ }
+
+ /**
+ * Create a Position expression.
+ */
+ override def visitPosition(ctx: PositionContext): Expression = withOrigin(ctx) {
+ new StringLocate(expression(ctx.substr), expression(ctx.str))
+ }
+
+ /**
+ * Create a Extract expression.
+ */
+ override def visitExtract(ctx: ExtractContext): Expression = withOrigin(ctx) {
+ val arguments = Seq(Literal(ctx.field.getText), expression(ctx.source))
+ UnresolvedFunction("extract", arguments, isDistinct = false)
+ }
+
+ /**
+ * Create a Substring/Substr expression.
+ */
+ override def visitSubstring(ctx: SubstringContext): Expression = withOrigin(ctx) {
+ if (ctx.len != null) {
+ Substring(expression(ctx.str), expression(ctx.pos), expression(ctx.len))
+ } else {
+ new Substring(expression(ctx.str), expression(ctx.pos))
+ }
+ }
+
+ /**
+ * Create a Trim expression.
+ */
+ override def visitTrim(ctx: TrimContext): Expression = withOrigin(ctx) {
+ val srcStr = expression(ctx.srcStr)
+ val trimStr = Option(ctx.trimStr).map(expression)
+ Option(ctx.trimOption).map(_.getType).getOrElse(HoodieSqlBaseParser.BOTH) match {
+ case HoodieSqlBaseParser.BOTH =>
+ StringTrim(srcStr, trimStr)
+ case HoodieSqlBaseParser.LEADING =>
+ StringTrimLeft(srcStr, trimStr)
+ case HoodieSqlBaseParser.TRAILING =>
+ StringTrimRight(srcStr, trimStr)
+ case other =>
+ throw new ParseException("Function trim doesn't support with " +
+ s"type $other. Please use BOTH, LEADING or TRAILING as trim type", ctx)
+ }
+ }
+
+ /**
+ * Create a Overlay expression.
+ */
+ override def visitOverlay(ctx: OverlayContext): Expression = withOrigin(ctx) {
+ val input = expression(ctx.input)
+ val replace = expression(ctx.replace)
+ val position = expression(ctx.position)
+ val lengthOpt = Option(ctx.length).map(expression)
+ lengthOpt match {
+ case Some(length) => Overlay(input, replace, position, length)
+ case None => new Overlay(input, replace, position)
+ }
+ }
+
+ /**
+ * Create a (windowed) Function expression.
+ */
+ override def visitFunctionCall(ctx: FunctionCallContext): Expression = withOrigin(ctx) {
+ // Create the function call.
+ val name = ctx.functionName.getText
+ val isDistinct = Option(ctx.setQuantifier()).exists(_.DISTINCT != null)
+ // Call `toSeq`, otherwise `ctx.argument.asScala.map(expression)` is `Buffer` in Scala 2.13
+ val arguments = ctx.argument.asScala.map(expression).toSeq match {
+ case Seq(UnresolvedStar(None))
+ if name.toLowerCase(Locale.ROOT) == "count" && !isDistinct =>
+ // Transform COUNT(*) into COUNT(1).
+ Seq(Literal(1))
+ case expressions =>
+ expressions
+ }
+ val filter = Option(ctx.where).map(expression(_))
+ val ignoreNulls =
+ Option(ctx.nullsOption).map(_.getType == HoodieSqlBaseParser.IGNORE).getOrElse(false)
+ val function = UnresolvedFunction(
+ getFunctionMultiparts(ctx.functionName), arguments, isDistinct, filter, ignoreNulls)
+
+ // Check if the function is evaluated in a windowed context.
+ ctx.windowSpec match {
+ case spec: WindowRefContext =>
+ UnresolvedWindowExpression(function, visitWindowRef(spec))
+ case spec: WindowDefContext =>
+ WindowExpression(function, visitWindowDef(spec))
+ case _ => function
+ }
+ }
+
+ /**
+ * Create a function database (optional) and name pair.
+ */
+ protected def visitFunctionName(ctx: QualifiedNameContext): FunctionIdentifier = {
+ visitFunctionName(ctx, ctx.identifier().asScala.map(_.getText).toSeq)
+ }
+
+ /**
+ * Create a function database (optional) and name pair.
+ */
+ private def visitFunctionName(ctx: ParserRuleContext, texts: Seq[String]): FunctionIdentifier = {
+ texts match {
+ case Seq(db, fn) => FunctionIdentifier(fn, Option(db))
+ case Seq(fn) => FunctionIdentifier(fn, None)
+ case other =>
+ throw new ParseException(s"Unsupported function name '${texts.mkString(".")}'", ctx)
+ }
+ }
+
+ /**
+ * Get a function identifier consist by database (optional) and name.
+ */
+ protected def getFunctionIdentifier(ctx: FunctionNameContext): FunctionIdentifier = {
+ if (ctx.qualifiedName != null) {
+ visitFunctionName(ctx.qualifiedName)
+ } else {
+ FunctionIdentifier(ctx.getText, None)
+ }
+ }
+
+ protected def getFunctionMultiparts(ctx: FunctionNameContext): Seq[String] = {
+ if (ctx.qualifiedName != null) {
+ ctx.qualifiedName().identifier().asScala.map(_.getText).toSeq
+ } else {
+ Seq(ctx.getText)
+ }
+ }
+
+ /**
+ * Create an [[LambdaFunction]].
+ */
+ override def visitLambda(ctx: LambdaContext): Expression = withOrigin(ctx) {
+ val arguments = ctx.identifier().asScala.map { name =>
+ UnresolvedNamedLambdaVariable(UnresolvedAttribute.quoted(name.getText).nameParts)
+ }
+ val function = expression(ctx.expression).transformUp {
+ case a: UnresolvedAttribute => UnresolvedNamedLambdaVariable(a.nameParts)
+ }
+ LambdaFunction(function, arguments.toSeq)
+ }
+
+ /**
+ * Create a reference to a window frame, i.e. [[WindowSpecReference]].
+ */
+ override def visitWindowRef(ctx: WindowRefContext): WindowSpecReference = withOrigin(ctx) {
+ WindowSpecReference(ctx.name.getText)
+ }
+
+ /**
+ * Create a window definition, i.e. [[WindowSpecDefinition]].
+ */
+ override def visitWindowDef(ctx: WindowDefContext): WindowSpecDefinition = withOrigin(ctx) {
+ // CLUSTER BY ... | PARTITION BY ... ORDER BY ...
+ val partition = ctx.partition.asScala.map(expression)
+ val order = ctx.sortItem.asScala.map(visitSortItem)
+
+ // RANGE/ROWS BETWEEN ...
+ val frameSpecOption = Option(ctx.windowFrame).map { frame =>
+ val frameType = frame.frameType.getType match {
+ case HoodieSqlBaseParser.RANGE => RangeFrame
+ case HoodieSqlBaseParser.ROWS => RowFrame
+ }
+
+ SpecifiedWindowFrame(
+ frameType,
+ visitFrameBound(frame.start),
+ Option(frame.end).map(visitFrameBound).getOrElse(CurrentRow))
+ }
+
+ WindowSpecDefinition(
+ partition.toSeq,
+ order.toSeq,
+ frameSpecOption.getOrElse(UnspecifiedFrame))
+ }
+
+ /**
+ * Create or resolve a frame boundary expressions.
+ */
+ override def visitFrameBound(ctx: FrameBoundContext): Expression = withOrigin(ctx) {
+ def value: Expression = {
+ val e = expression(ctx.expression)
+ validate(e.resolved && e.foldable, "Frame bound value must be a literal.", ctx)
+ e
+ }
+
+ ctx.boundType.getType match {
+ case HoodieSqlBaseParser.PRECEDING if ctx.UNBOUNDED != null =>
+ UnboundedPreceding
+ case HoodieSqlBaseParser.PRECEDING =>
+ UnaryMinus(value)
+ case HoodieSqlBaseParser.CURRENT =>
+ CurrentRow
+ case HoodieSqlBaseParser.FOLLOWING if ctx.UNBOUNDED != null =>
+ UnboundedFollowing
+ case HoodieSqlBaseParser.FOLLOWING =>
+ value
+ }
+ }
+
+ /**
+ * Create a [[CreateStruct]] expression.
+ */
+ override def visitRowConstructor(ctx: RowConstructorContext): Expression = withOrigin(ctx) {
+ CreateStruct(ctx.namedExpression().asScala.map(expression).toSeq)
+ }
+
+ /**
+ * Create a [[ScalarSubquery]] expression.
+ */
+ override def visitSubqueryExpression(
+ ctx: SubqueryExpressionContext): Expression = withOrigin(ctx) {
+ ScalarSubquery(plan(ctx.query))
+ }
+
+ /**
+ * Create a value based [[CaseWhen]] expression. This has the following SQL form:
+ * {{{
+ * CASE [expression]
+ * WHEN [value] THEN [expression]
+ * ...
+ * ELSE [expression]
+ * END
+ * }}}
+ */
+ override def visitSimpleCase(ctx: SimpleCaseContext): Expression = withOrigin(ctx) {
+ val e = expression(ctx.value)
+ val branches = ctx.whenClause.asScala.map { wCtx =>
+ (EqualTo(e, expression(wCtx.condition)), expression(wCtx.result))
+ }
+ CaseWhen(branches.toSeq, Option(ctx.elseExpression).map(expression))
+ }
+
+ /**
+ * Create a condition based [[CaseWhen]] expression. This has the following SQL syntax:
+ * {{{
+ * CASE
+ * WHEN [predicate] THEN [expression]
+ * ...
+ * ELSE [expression]
+ * END
+ * }}}
+ *
+ * @param ctx the parse tree
+ * */
+ override def visitSearchedCase(ctx: SearchedCaseContext): Expression = withOrigin(ctx) {
+ val branches = ctx.whenClause.asScala.map { wCtx =>
+ (expression(wCtx.condition), expression(wCtx.result))
+ }
+ CaseWhen(branches.toSeq, Option(ctx.elseExpression).map(expression))
+ }
+
+ /**
+ * Currently only regex in expressions of SELECT statements are supported; in other
+ * places, e.g., where `(a)?+.+` = 2, regex are not meaningful.
+ */
+ private def canApplyRegex(ctx: ParserRuleContext): Boolean = withOrigin(ctx) {
+ var parent = ctx.getParent
+ var rtn = false
+ while (parent != null) {
+ if (parent.isInstanceOf[NamedExpressionContext]) {
+ rtn = true
+ }
+ parent = parent.getParent
+ }
+ rtn
+ }
+
+ /**
+ * Create a dereference expression. The return type depends on the type of the parent.
+ * If the parent is an [[UnresolvedAttribute]], it can be a [[UnresolvedAttribute]] or
+ * a [[UnresolvedRegex]] for regex quoted in ``; if the parent is some other expression,
+ * it can be [[UnresolvedExtractValue]].
+ */
+ override def visitDereference(ctx: DereferenceContext): Expression = withOrigin(ctx) {
+ val attr = ctx.fieldName.getText
+ expression(ctx.base) match {
+ case unresolved_attr@UnresolvedAttribute(nameParts) =>
+ ctx.fieldName.getStart.getText match {
+ case escapedIdentifier(columnNameRegex)
+ if conf.supportQuotedRegexColumnName && canApplyRegex(ctx) =>
+ UnresolvedRegex(columnNameRegex, Some(unresolved_attr.name),
+ conf.caseSensitiveAnalysis)
+ case _ =>
+ UnresolvedAttribute(nameParts :+ attr)
+ }
+ case e =>
+ UnresolvedExtractValue(e, Literal(attr))
+ }
+ }
+
+ /**
+ * Create an [[UnresolvedAttribute]] expression or a [[UnresolvedRegex]] if it is a regex
+ * quoted in ``
+ */
+ override def visitColumnReference(ctx: ColumnReferenceContext): Expression = withOrigin(ctx) {
+ ctx.getStart.getText match {
+ case escapedIdentifier(columnNameRegex)
+ if conf.supportQuotedRegexColumnName && canApplyRegex(ctx) =>
+ UnresolvedRegex(columnNameRegex, None, conf.caseSensitiveAnalysis)
+ case _ =>
+ UnresolvedAttribute.quoted(ctx.getText)
+ }
+
+ }
+
+ /**
+ * Create an [[UnresolvedExtractValue]] expression, this is used for subscript access to an array.
+ */
+ override def visitSubscript(ctx: SubscriptContext): Expression = withOrigin(ctx) {
+ UnresolvedExtractValue(expression(ctx.value), expression(ctx.index))
+ }
+
+ /**
+ * Create an expression for an expression between parentheses. This is need because the ANTLR
+ * visitor cannot automatically convert the nested context into an expression.
+ */
+ override def visitParenthesizedExpression(
+ ctx: ParenthesizedExpressionContext): Expression = withOrigin(ctx) {
+ expression(ctx.expression)
+ }
+
+ /**
+ * Create a [[SortOrder]] expression.
+ */
+ override def visitSortItem(ctx: SortItemContext): SortOrder = withOrigin(ctx) {
+ val direction = if (ctx.DESC != null) {
+ Descending
+ } else {
+ Ascending
+ }
+ val nullOrdering = if (ctx.FIRST != null) {
+ NullsFirst
+ } else if (ctx.LAST != null) {
+ NullsLast
+ } else {
+ direction.defaultNullOrdering
+ }
+ SortOrder(expression(ctx.expression), direction, nullOrdering, Seq.empty)
+ }
+
+ /**
+ * Create a typed Literal expression. A typed literal has the following SQL syntax:
+ * {{{
+ * [TYPE] '[VALUE]'
+ * }}}
+ * Currently Date, Timestamp, Interval and Binary typed literals are supported.
+ */
+ override def visitTypeConstructor(ctx: TypeConstructorContext): Literal = withOrigin(ctx) {
+ val value = string(ctx.STRING)
+ val valueType = ctx.identifier.getText.toUpperCase(Locale.ROOT)
+
+ def toLiteral[T](f: UTF8String => Option[T], t: DataType): Literal = {
+ f(UTF8String.fromString(value)).map(Literal(_, t)).getOrElse {
+ throw new ParseException(s"Cannot parse the $valueType value: $value", ctx)
+ }
+ }
+
+ def constructTimestampLTZLiteral(value: String): Literal = {
+ val zoneId = getZoneId(conf.sessionLocalTimeZone)
+ val specialTs = convertSpecialTimestamp(value, zoneId).map(Literal(_, TimestampType))
+ specialTs.getOrElse(toLiteral(stringToTimestamp(_, zoneId), TimestampType))
+ }
+
+ try {
+ valueType match {
+ case "DATE" =>
+ val zoneId = getZoneId(conf.sessionLocalTimeZone)
+ val specialDate = convertSpecialDate(value, zoneId).map(Literal(_, DateType))
+ specialDate.getOrElse(toLiteral(stringToDate, DateType))
+ // SPARK-36227: Remove TimestampNTZ type support in Spark 3.2 with minimal code changes.
+ case "TIMESTAMP_NTZ" if isTesting =>
+ convertSpecialTimestampNTZ(value, getZoneId(conf.sessionLocalTimeZone))
+ .map(Literal(_, TimestampNTZType))
+ .getOrElse(toLiteral(stringToTimestampWithoutTimeZone, TimestampNTZType))
+ case "TIMESTAMP_LTZ" if isTesting =>
+ constructTimestampLTZLiteral(value)
+ case "TIMESTAMP" =>
+ SQLConf.get.timestampType match {
+ case TimestampNTZType =>
+ convertSpecialTimestampNTZ(value, getZoneId(conf.sessionLocalTimeZone))
+ .map(Literal(_, TimestampNTZType))
+ .getOrElse {
+ val containsTimeZonePart =
+ DateTimeUtils.parseTimestampString(UTF8String.fromString(value))._2.isDefined
+ // If the input string contains time zone part, return a timestamp with local time
+ // zone literal.
+ if (containsTimeZonePart) {
+ constructTimestampLTZLiteral(value)
+ } else {
+ toLiteral(stringToTimestampWithoutTimeZone, TimestampNTZType)
+ }
+ }
+
+ case TimestampType =>
+ constructTimestampLTZLiteral(value)
+ }
+
+ case "INTERVAL" =>
+ val interval = try {
+ IntervalUtils.stringToInterval(UTF8String.fromString(value))
+ } catch {
+ case e: IllegalArgumentException =>
+ val ex = new ParseException(s"Cannot parse the INTERVAL value: $value", ctx)
+ ex.setStackTrace(e.getStackTrace)
+ throw ex
+ }
+ if (!conf.legacyIntervalEnabled) {
+ val units = value
+ .split("\\s")
+ .map(_.toLowerCase(Locale.ROOT).stripSuffix("s"))
+ .filter(s => s != "interval" && s.matches("[a-z]+"))
+ constructMultiUnitsIntervalLiteral(ctx, interval, units)
+ } else {
+ Literal(interval, CalendarIntervalType)
+ }
+ case "X" =>
+ val padding = if (value.length % 2 != 0) "0" else ""
+ Literal(DatatypeConverter.parseHexBinary(padding + value))
+ case other =>
+ throw new ParseException(s"Literals of type '$other' are currently not supported.", ctx)
+ }
+ } catch {
+ case e: IllegalArgumentException =>
+ val message = Option(e.getMessage).getOrElse(s"Exception parsing $valueType")
+ throw new ParseException(message, ctx)
+ }
+ }
+
+ /**
+ * Create a NULL literal expression.
+ */
+ override def visitNullLiteral(ctx: NullLiteralContext): Literal = withOrigin(ctx) {
+ Literal(null)
+ }
+
+ /**
+ * Create a Boolean literal expression.
+ */
+ override def visitBooleanLiteral(ctx: BooleanLiteralContext): Literal = withOrigin(ctx) {
+ if (ctx.getText.toBoolean) {
+ Literal.TrueLiteral
+ } else {
+ Literal.FalseLiteral
+ }
+ }
+
+ /**
+ * Create an integral literal expression. The code selects the most narrow integral type
+ * possible, either a BigDecimal, a Long or an Integer is returned.
+ */
+ override def visitIntegerLiteral(ctx: IntegerLiteralContext): Literal = withOrigin(ctx) {
+ BigDecimal(ctx.getText) match {
+ case v if v.isValidInt =>
+ Literal(v.intValue)
+ case v if v.isValidLong =>
+ Literal(v.longValue)
+ case v => Literal(v.underlying())
+ }
+ }
+
+ /**
+ * Create a decimal literal for a regular decimal number.
+ */
+ override def visitDecimalLiteral(ctx: DecimalLiteralContext): Literal = withOrigin(ctx) {
+ Literal(BigDecimal(ctx.getText).underlying())
+ }
+
+ /**
+ * Create a decimal literal for a regular decimal number or a scientific decimal number.
+ */
+ override def visitLegacyDecimalLiteral(
+ ctx: LegacyDecimalLiteralContext): Literal = withOrigin(ctx) {
+ Literal(BigDecimal(ctx.getText).underlying())
+ }
+
+ /**
+ * Create a double literal for number with an exponent, e.g. 1E-30
+ */
+ override def visitExponentLiteral(ctx: ExponentLiteralContext): Literal = {
+ numericLiteral(ctx, ctx.getText, /* exponent values don't have a suffix */
+ Double.MinValue, Double.MaxValue, DoubleType.simpleString)(_.toDouble)
+ }
+
+ /** Create a numeric literal expression. */
+ private def numericLiteral(
+ ctx: NumberContext,
+ rawStrippedQualifier: String,
+ minValue: BigDecimal,
+ maxValue: BigDecimal,
+ typeName: String)(converter: String => Any): Literal = withOrigin(ctx) {
+ try {
+ val rawBigDecimal = BigDecimal(rawStrippedQualifier)
+ if (rawBigDecimal < minValue || rawBigDecimal > maxValue) {
+ throw new ParseException(s"Numeric literal $rawStrippedQualifier does not " +
+ s"fit in range [$minValue, $maxValue] for type $typeName", ctx)
+ }
+ Literal(converter(rawStrippedQualifier))
+ } catch {
+ case e: NumberFormatException =>
+ throw new ParseException(e.getMessage, ctx)
+ }
+ }
+
+ /**
+ * Create a Byte Literal expression.
+ */
+ override def visitTinyIntLiteral(ctx: TinyIntLiteralContext): Literal = {
+ val rawStrippedQualifier = ctx.getText.substring(0, ctx.getText.length - 1)
+ numericLiteral(ctx, rawStrippedQualifier,
+ Byte.MinValue, Byte.MaxValue, ByteType.simpleString)(_.toByte)
+ }
+
+ /**
+ * Create a Short Literal expression.
+ */
+ override def visitSmallIntLiteral(ctx: SmallIntLiteralContext): Literal = {
+ val rawStrippedQualifier = ctx.getText.substring(0, ctx.getText.length - 1)
+ numericLiteral(ctx, rawStrippedQualifier,
+ Short.MinValue, Short.MaxValue, ShortType.simpleString)(_.toShort)
+ }
+
+ /**
+ * Create a Long Literal expression.
+ */
+ override def visitBigIntLiteral(ctx: BigIntLiteralContext): Literal = {
+ val rawStrippedQualifier = ctx.getText.substring(0, ctx.getText.length - 1)
+ numericLiteral(ctx, rawStrippedQualifier,
+ Long.MinValue, Long.MaxValue, LongType.simpleString)(_.toLong)
+ }
+
+ /**
+ * Create a Float Literal expression.
+ */
+ override def visitFloatLiteral(ctx: FloatLiteralContext): Literal = {
+ val rawStrippedQualifier = ctx.getText.substring(0, ctx.getText.length - 1)
+ numericLiteral(ctx, rawStrippedQualifier,
+ Float.MinValue, Float.MaxValue, FloatType.simpleString)(_.toFloat)
+ }
+
+ /**
+ * Create a Double Literal expression.
+ */
+ override def visitDoubleLiteral(ctx: DoubleLiteralContext): Literal = {
+ val rawStrippedQualifier = ctx.getText.substring(0, ctx.getText.length - 1)
+ numericLiteral(ctx, rawStrippedQualifier,
+ Double.MinValue, Double.MaxValue, DoubleType.simpleString)(_.toDouble)
+ }
+
+ /**
+ * Create a BigDecimal Literal expression.
+ */
+ override def visitBigDecimalLiteral(ctx: BigDecimalLiteralContext): Literal = {
+ val raw = ctx.getText.substring(0, ctx.getText.length - 2)
+ try {
+ Literal(BigDecimal(raw).underlying())
+ } catch {
+ case e: AnalysisException =>
+ throw new ParseException(e.message, ctx)
+ }
+ }
+
+ /**
+ * Create a String literal expression.
+ */
+ override def visitStringLiteral(ctx: StringLiteralContext): Literal = withOrigin(ctx) {
+ Literal(createString(ctx))
+ }
+
+ /**
+ * Create a String from a string literal context. This supports multiple consecutive string
+ * literals, these are concatenated, for example this expression "'hello' 'world'" will be
+ * converted into "helloworld".
+ *
+ * Special characters can be escaped by using Hive/C-style escaping.
+ */
+ private def createString(ctx: StringLiteralContext): String = {
+ if (conf.escapedStringLiterals) {
+ ctx.STRING().asScala.map(stringWithoutUnescape).mkString
+ } else {
+ ctx.STRING().asScala.map(string).mkString
+ }
+ }
+
+ /**
+ * Create an [[UnresolvedRelation]] from a multi-part identifier context.
+ */
+ private def createUnresolvedRelation(
+ ctx: MultipartIdentifierContext): UnresolvedRelation = withOrigin(ctx) {
+ UnresolvedRelation(visitMultipartIdentifier(ctx))
+ }
+
+ /**
+ * Construct an [[Literal]] from [[CalendarInterval]] and
+ * units represented as a [[Seq]] of [[String]].
+ */
+ private def constructMultiUnitsIntervalLiteral(
+ ctx: ParserRuleContext,
+ calendarInterval: CalendarInterval,
+ units: Seq[String]): Literal = {
+ var yearMonthFields = Set.empty[Byte]
+ var dayTimeFields = Set.empty[Byte]
+ for (unit <- units) {
+ if (YearMonthIntervalType.stringToField.contains(unit)) {
+ yearMonthFields += YearMonthIntervalType.stringToField(unit)
+ } else if (DayTimeIntervalType.stringToField.contains(unit)) {
+ dayTimeFields += DayTimeIntervalType.stringToField(unit)
+ } else if (unit == "week") {
+ dayTimeFields += DayTimeIntervalType.DAY
+ } else {
+ assert(unit == "millisecond" || unit == "microsecond")
+ dayTimeFields += DayTimeIntervalType.SECOND
+ }
+ }
+ if (yearMonthFields.nonEmpty) {
+ if (dayTimeFields.nonEmpty) {
+ val literalStr = source(ctx)
+ throw new ParseException(s"Cannot mix year-month and day-time fields: $literalStr", ctx)
+ }
+ Literal(
+ calendarInterval.months,
+ YearMonthIntervalType(yearMonthFields.min, yearMonthFields.max)
+ )
+ } else {
+ Literal(
+ IntervalUtils.getDuration(calendarInterval, TimeUnit.MICROSECONDS),
+ DayTimeIntervalType(dayTimeFields.min, dayTimeFields.max))
+ }
+ }
+
+ /**
+ * Create a [[CalendarInterval]] or ANSI interval literal expression.
+ * Two syntaxes are supported:
+ * - multiple unit value pairs, for instance: interval 2 months 2 days.
+ * - from-to unit, for instance: interval '1-2' year to month.
+ */
+ override def visitInterval(ctx: IntervalContext): Literal = withOrigin(ctx) {
+ val calendarInterval = parseIntervalLiteral(ctx)
+ if (ctx.errorCapturingUnitToUnitInterval != null && !conf.legacyIntervalEnabled) {
+ // Check the `to` unit to distinguish year-month and day-time intervals because
+ // `CalendarInterval` doesn't have enough info. For instance, new CalendarInterval(0, 0, 0)
+ // can be derived from INTERVAL '0-0' YEAR TO MONTH as well as from
+ // INTERVAL '0 00:00:00' DAY TO SECOND.
+ val fromUnit =
+ ctx.errorCapturingUnitToUnitInterval.body.from.getText.toLowerCase(Locale.ROOT)
+ val toUnit = ctx.errorCapturingUnitToUnitInterval.body.to.getText.toLowerCase(Locale.ROOT)
+ if (toUnit == "month") {
+ assert(calendarInterval.days == 0 && calendarInterval.microseconds == 0)
+ val start = YearMonthIntervalType.stringToField(fromUnit)
+ Literal(calendarInterval.months, YearMonthIntervalType(start, YearMonthIntervalType.MONTH))
+ } else {
+ assert(calendarInterval.months == 0)
+ val micros = IntervalUtils.getDuration(calendarInterval, TimeUnit.MICROSECONDS)
+ val start = DayTimeIntervalType.stringToField(fromUnit)
+ val end = DayTimeIntervalType.stringToField(toUnit)
+ Literal(micros, DayTimeIntervalType(start, end))
+ }
+ } else if (ctx.errorCapturingMultiUnitsInterval != null && !conf.legacyIntervalEnabled) {
+ val units =
+ ctx.errorCapturingMultiUnitsInterval.body.unit.asScala.map(
+ _.getText.toLowerCase(Locale.ROOT).stripSuffix("s")).toSeq
+ constructMultiUnitsIntervalLiteral(ctx, calendarInterval, units)
+ } else {
+ Literal(calendarInterval, CalendarIntervalType)
+ }
+ }
+
+ /**
+ * Create a [[CalendarInterval]] object
+ */
+ protected def parseIntervalLiteral(ctx: IntervalContext): CalendarInterval = withOrigin(ctx) {
+ if (ctx.errorCapturingMultiUnitsInterval != null) {
+ val innerCtx = ctx.errorCapturingMultiUnitsInterval
+ if (innerCtx.unitToUnitInterval != null) {
+ throw new ParseException("Can only have a single from-to unit in the interval literal syntax", innerCtx.unitToUnitInterval)
+ }
+ visitMultiUnitsInterval(innerCtx.multiUnitsInterval)
+ } else if (ctx.errorCapturingUnitToUnitInterval != null) {
+ val innerCtx = ctx.errorCapturingUnitToUnitInterval
+ if (innerCtx.error1 != null || innerCtx.error2 != null) {
+ val errorCtx = if (innerCtx.error1 != null) innerCtx.error1 else innerCtx.error2
+ throw new ParseException("Can only have a single from-to unit in the interval literal syntax", errorCtx)
+ }
+ visitUnitToUnitInterval(innerCtx.body)
+ } else {
+ throw new ParseException("at least one time unit should be given for interval literal", ctx)
+ }
+ }
+
+ /**
+ * Creates a [[CalendarInterval]] with multiple unit value pairs, e.g. 1 YEAR 2 DAYS.
+ */
+ override def visitMultiUnitsInterval(ctx: MultiUnitsIntervalContext): CalendarInterval = {
+ withOrigin(ctx) {
+ val units = ctx.unit.asScala
+ val values = ctx.intervalValue().asScala
+ try {
+ assert(units.length == values.length)
+ val kvs = units.indices.map { i =>
+ val u = units(i).getText
+ val v = if (values(i).STRING() != null) {
+ val value = string(values(i).STRING())
+ // SPARK-32840: For invalid cases, e.g. INTERVAL '1 day 2' hour,
+ // INTERVAL 'interval 1' day, we need to check ahead before they are concatenated with
+ // units and become valid ones, e.g. '1 day 2 hour'.
+ // Ideally, we only ensure the value parts don't contain any units here.
+ if (value.exists(Character.isLetter)) {
+ throw new ParseException("Can only use numbers in the interval value part for" +
+ s" multiple unit value pairs interval form, but got invalid value: $value", ctx)
+ }
+ if (values(i).MINUS() == null) {
+ value
+ } else {
+ value.startsWith("-") match {
+ case true => value.replaceFirst("-", "")
+ case false => s"-$value"
+ }
+ }
+ } else {
+ values(i).getText
+ }
+ UTF8String.fromString(" " + v + " " + u)
+ }
+ IntervalUtils.stringToInterval(UTF8String.concat(kvs: _*))
+ } catch {
+ case i: IllegalArgumentException =>
+ val e = new ParseException(i.getMessage, ctx)
+ e.setStackTrace(i.getStackTrace)
+ throw e
+ }
+ }
+ }
+
+ /**
+ * Creates a [[CalendarInterval]] with from-to unit, e.g. '2-1' YEAR TO MONTH.
+ */
+ override def visitUnitToUnitInterval(ctx: UnitToUnitIntervalContext): CalendarInterval = {
+ withOrigin(ctx) {
+ val value = Option(ctx.intervalValue.STRING).map(string).map { interval =>
+ if (ctx.intervalValue().MINUS() == null) {
+ interval
+ } else {
+ interval.startsWith("-") match {
+ case true => interval.replaceFirst("-", "")
+ case false => s"-$interval"
+ }
+ }
+ }.getOrElse {
+ throw new ParseException("The value of from-to unit must be a string", ctx.intervalValue)
+ }
+ try {
+ val from = ctx.from.getText.toLowerCase(Locale.ROOT)
+ val to = ctx.to.getText.toLowerCase(Locale.ROOT)
+ (from, to) match {
+ case ("year", "month") =>
+ IntervalUtils.fromYearMonthString(value)
+ case ("day", "hour") | ("day", "minute") | ("day", "second") | ("hour", "minute") |
+ ("hour", "second") | ("minute", "second") =>
+ IntervalUtils.fromDayTimeString(value,
+ DayTimeIntervalType.stringToField(from), DayTimeIntervalType.stringToField(to))
+ case _ =>
+ throw new ParseException(s"Intervals FROM $from TO $to are not supported.", ctx)
+ }
+ } catch {
+ // Handle Exceptions thrown by CalendarInterval
+ case e: IllegalArgumentException =>
+ val pe = new ParseException(e.getMessage, ctx)
+ pe.setStackTrace(e.getStackTrace)
+ throw pe
+ }
+ }
+ }
+
+ /* ********************************************************************************************
+ * DataType parsing
+ * ******************************************************************************************** */
+
+ /**
+ * Resolve/create a primitive type.
+ */
+ override def visitPrimitiveDataType(ctx: PrimitiveDataTypeContext): DataType = withOrigin(ctx) {
+ val dataType = ctx.identifier.getText.toLowerCase(Locale.ROOT)
+ (dataType, ctx.INTEGER_VALUE().asScala.toList) match {
+ case ("boolean", Nil) => BooleanType
+ case ("tinyint" | "byte", Nil) => ByteType
+ case ("smallint" | "short", Nil) => ShortType
+ case ("int" | "integer", Nil) => IntegerType
+ case ("bigint" | "long", Nil) => LongType
+ case ("float" | "real", Nil) => FloatType
+ case ("double", Nil) => DoubleType
+ case ("date", Nil) => DateType
+ case ("timestamp", Nil) => SQLConf.get.timestampType
+ // SPARK-36227: Remove TimestampNTZ type support in Spark 3.2 with minimal code changes.
+ case ("timestamp_ntz", Nil) if isTesting => TimestampNTZType
+ case ("timestamp_ltz", Nil) if isTesting => TimestampType
+ case ("string", Nil) => StringType
+ case ("character" | "char", length :: Nil) => CharType(length.getText.toInt)
+ case ("varchar", length :: Nil) => VarcharType(length.getText.toInt)
+ case ("binary", Nil) => BinaryType
+ case ("decimal" | "dec" | "numeric", Nil) => DecimalType.USER_DEFAULT
+ case ("decimal" | "dec" | "numeric", precision :: Nil) =>
+ DecimalType(precision.getText.toInt, 0)
+ case ("decimal" | "dec" | "numeric", precision :: scale :: Nil) =>
+ DecimalType(precision.getText.toInt, scale.getText.toInt)
+ case ("void", Nil) => NullType
+ case ("interval", Nil) => CalendarIntervalType
+ case (dt, params) =>
+ val dtStr = if (params.nonEmpty) s"$dt(${params.mkString(",")})" else dt
+ throw new ParseException(s"DataType $dtStr is not supported.", ctx)
+ }
+ }
+
+ override def visitYearMonthIntervalDataType(ctx: YearMonthIntervalDataTypeContext): DataType = {
+ val startStr = ctx.from.getText.toLowerCase(Locale.ROOT)
+ val start = YearMonthIntervalType.stringToField(startStr)
+ if (ctx.to != null) {
+ val endStr = ctx.to.getText.toLowerCase(Locale.ROOT)
+ val end = YearMonthIntervalType.stringToField(endStr)
+ if (end <= start) {
+ throw new ParseException(s"Intervals FROM $startStr TO $endStr are not supported.", ctx)
+ }
+ YearMonthIntervalType(start, end)
+ } else {
+ YearMonthIntervalType(start)
+ }
+ }
+
+ override def visitDayTimeIntervalDataType(ctx: DayTimeIntervalDataTypeContext): DataType = {
+ val startStr = ctx.from.getText.toLowerCase(Locale.ROOT)
+ val start = DayTimeIntervalType.stringToField(startStr)
+ if (ctx.to != null) {
+ val endStr = ctx.to.getText.toLowerCase(Locale.ROOT)
+ val end = DayTimeIntervalType.stringToField(endStr)
+ if (end <= start) {
+ throw new ParseException(s"Intervals FROM $startStr TO $endStr are not supported.", ctx)
+ }
+ DayTimeIntervalType(start, end)
+ } else {
+ DayTimeIntervalType(start)
+ }
+ }
+
+ /**
+ * Create a complex DataType. Arrays, Maps and Structures are supported.
+ */
+ override def visitComplexDataType(ctx: ComplexDataTypeContext): DataType = withOrigin(ctx) {
+ ctx.complex.getType match {
+ case HoodieSqlBaseParser.ARRAY =>
+ ArrayType(typedVisit(ctx.dataType(0)))
+ case HoodieSqlBaseParser.MAP =>
+ MapType(typedVisit(ctx.dataType(0)), typedVisit(ctx.dataType(1)))
+ case HoodieSqlBaseParser.STRUCT =>
+ StructType(Option(ctx.complexColTypeList).toSeq.flatMap(visitComplexColTypeList))
+ }
+ }
+
+ /**
+ * Create top level table schema.
+ */
+ protected def createSchema(ctx: ColTypeListContext): StructType = {
+ StructType(Option(ctx).toSeq.flatMap(visitColTypeList))
+ }
+
+ /**
+ * Create a [[StructType]] from a number of column definitions.
+ */
+ override def visitColTypeList(ctx: ColTypeListContext): Seq[StructField] = withOrigin(ctx) {
+ ctx.colType().asScala.map(visitColType).toSeq
+ }
+
+ /**
+ * Create a top level [[StructField]] from a column definition.
+ */
+ override def visitColType(ctx: ColTypeContext): StructField = withOrigin(ctx) {
+ import ctx._
+
+ val builder = new MetadataBuilder
+ // Add comment to metadata
+ Option(commentSpec()).map(visitCommentSpec).foreach {
+ builder.putString("comment", _)
+ }
+
+ StructField(
+ name = colName.getText,
+ dataType = typedVisit[DataType](ctx.dataType),
+ nullable = NULL == null,
+ metadata = builder.build())
+ }
+
+ /**
+ * Create a [[StructType]] from a sequence of [[StructField]]s.
+ */
+ protected def createStructType(ctx: ComplexColTypeListContext): StructType = {
+ StructType(Option(ctx).toSeq.flatMap(visitComplexColTypeList))
+ }
+
+ /**
+ * Create a [[StructType]] from a number of column definitions.
+ */
+ override def visitComplexColTypeList(
+ ctx: ComplexColTypeListContext): Seq[StructField] = withOrigin(ctx) {
+ ctx.complexColType().asScala.map(visitComplexColType).toSeq
+ }
+
+ /**
+ * Create a [[StructField]] from a column definition.
+ */
+ override def visitComplexColType(ctx: ComplexColTypeContext): StructField = withOrigin(ctx) {
+ import ctx._
+ val structField = StructField(
+ name = identifier.getText,
+ dataType = typedVisit(dataType()),
+ nullable = NULL == null)
+ Option(commentSpec).map(visitCommentSpec).map(structField.withComment).getOrElse(structField)
+ }
+
+ /**
+ * Create a location string.
+ */
+ override def visitLocationSpec(ctx: LocationSpecContext): String = withOrigin(ctx) {
+ string(ctx.STRING)
+ }
+
+ /**
+ * Create an optional location string.
+ */
+ protected def visitLocationSpecList(ctx: java.util.List[LocationSpecContext]): Option[String] = {
+ ctx.asScala.headOption.map(visitLocationSpec)
+ }
+
+ /**
+ * Create a comment string.
+ */
+ override def visitCommentSpec(ctx: CommentSpecContext): String = withOrigin(ctx) {
+ string(ctx.STRING)
+ }
+
+ /**
+ * Create an optional comment string.
+ */
+ protected def visitCommentSpecList(ctx: java.util.List[CommentSpecContext]): Option[String] = {
+ ctx.asScala.headOption.map(visitCommentSpec)
+ }
+
+ /**
+ * Create a [[BucketSpec]].
+ */
+ override def visitBucketSpec(ctx: BucketSpecContext): BucketSpec = withOrigin(ctx) {
+ BucketSpec(
+ ctx.INTEGER_VALUE.getText.toInt,
+ visitIdentifierList(ctx.identifierList),
+ Option(ctx.orderedIdentifierList)
+ .toSeq
+ .flatMap(_.orderedIdentifier.asScala)
+ .map { orderedIdCtx =>
+ Option(orderedIdCtx.ordering).map(_.getText).foreach { dir =>
+ if (dir.toLowerCase(Locale.ROOT) != "asc") {
+ operationNotAllowed(s"Column ordering must be ASC, was '$dir'", ctx)
+ }
+ }
+
+ orderedIdCtx.ident.getText
+ })
+ }
+
+ /**
+ * Convert a table property list into a key-value map.
+ * This should be called through [[visitPropertyKeyValues]] or [[visitPropertyKeys]].
+ */
+ override def visitTablePropertyList(
+ ctx: TablePropertyListContext): Map[String, String] = withOrigin(ctx) {
+ val properties = ctx.tableProperty.asScala.map { property =>
+ val key = visitTablePropertyKey(property.key)
+ val value = visitTablePropertyValue(property.value)
+ key -> value
+ }
+ // Check for duplicate property names.
+ checkDuplicateKeys(properties.toSeq, ctx)
+ properties.toMap
+ }
+
+ /**
+ * Parse a key-value map from a [[TablePropertyListContext]], assuming all values are specified.
+ */
+ def visitPropertyKeyValues(ctx: TablePropertyListContext): Map[String, String] = {
+ val props = visitTablePropertyList(ctx)
+ val badKeys = props.collect { case (key, null) => key }
+ if (badKeys.nonEmpty) {
+ operationNotAllowed(
+ s"Values must be specified for key(s): ${badKeys.mkString("[", ",", "]")}", ctx)
+ }
+ props
+ }
+
+ /**
+ * Parse a list of keys from a [[TablePropertyListContext]], assuming no values are specified.
+ */
+ def visitPropertyKeys(ctx: TablePropertyListContext): Seq[String] = {
+ val props = visitTablePropertyList(ctx)
+ val badKeys = props.filter { case (_, v) => v != null }.keys
+ if (badKeys.nonEmpty) {
+ operationNotAllowed(
+ s"Values should not be specified for key(s): ${badKeys.mkString("[", ",", "]")}", ctx)
+ }
+ props.keys.toSeq
+ }
+
+ /**
+ * A table property key can either be String or a collection of dot separated elements. This
+ * function extracts the property key based on whether its a string literal or a table property
+ * identifier.
+ */
+ override def visitTablePropertyKey(key: TablePropertyKeyContext): String = {
+ if (key.STRING != null) {
+ string(key.STRING)
+ } else {
+ key.getText
+ }
+ }
+
+ /**
+ * A table property value can be String, Integer, Boolean or Decimal. This function extracts
+ * the property value based on whether its a string, integer, boolean or decimal literal.
+ */
+ override def visitTablePropertyValue(value: TablePropertyValueContext): String = {
+ if (value == null) {
+ null
+ } else if (value.STRING != null) {
+ string(value.STRING)
+ } else if (value.booleanValue != null) {
+ value.getText.toLowerCase(Locale.ROOT)
+ } else {
+ value.getText
+ }
+ }
+
+ /**
+ * Type to keep track of a table header: (identifier, isTemporary, ifNotExists, isExternal).
+ */
+ type TableHeader = (Seq[String], Boolean, Boolean, Boolean)
+
+ /**
+ * Type to keep track of table clauses:
+ * - partition transforms
+ * - partition columns
+ * - bucketSpec
+ * - properties
+ * - options
+ * - location
+ * - comment
+ * - serde
+ *
+ * Note: Partition transforms are based on existing table schema definition. It can be simple
+ * column names, or functions like `year(date_col)`. Partition columns are column names with data
+ * types like `i INT`, which should be appended to the existing table schema.
+ */
+ type TableClauses = (
+ Seq[Transform], Seq[StructField], Option[BucketSpec], Map[String, String],
+ Map[String, String], Option[String], Option[String], Option[SerdeInfo])
+
+ /**
+ * Validate a create table statement and return the [[TableIdentifier]].
+ */
+ override def visitCreateTableHeader(
+ ctx: CreateTableHeaderContext): TableHeader = withOrigin(ctx) {
+ val temporary = ctx.TEMPORARY != null
+ val ifNotExists = ctx.EXISTS != null
+ if (temporary && ifNotExists) {
+ operationNotAllowed("CREATE TEMPORARY TABLE ... IF NOT EXISTS", ctx)
+ }
+ val multipartIdentifier = ctx.multipartIdentifier.parts.asScala.map(_.getText).toSeq
+ (multipartIdentifier, temporary, ifNotExists, ctx.EXTERNAL != null)
+ }
+
+ /**
+ * Validate a replace table statement and return the [[TableIdentifier]].
+ */
+ override def visitReplaceTableHeader(
+ ctx: ReplaceTableHeaderContext): TableHeader = withOrigin(ctx) {
+ val multipartIdentifier = ctx.multipartIdentifier.parts.asScala.map(_.getText).toSeq
+ (multipartIdentifier, false, false, false)
+ }
+
+ /**
+ * Parse a qualified name to a multipart name.
+ */
+ override def visitQualifiedName(ctx: QualifiedNameContext): Seq[String] = withOrigin(ctx) {
+ ctx.identifier.asScala.map(_.getText).toSeq
+ }
+
+ /**
+ * Parse a list of transforms or columns.
+ */
+ override def visitPartitionFieldList(
+ ctx: PartitionFieldListContext): (Seq[Transform], Seq[StructField]) = withOrigin(ctx) {
+ val (transforms, columns) = ctx.fields.asScala.map {
+ case transform: PartitionTransformContext =>
+ (Some(visitPartitionTransform(transform)), None)
+ case field: PartitionColumnContext =>
+ (None, Some(visitColType(field.colType)))
+ }.unzip
+
+ (transforms.flatten.toSeq, columns.flatten.toSeq)
+ }
+
+ override def visitPartitionTransform(
+ ctx: PartitionTransformContext): Transform = withOrigin(ctx) {
+ def getFieldReference(
+ ctx: ApplyTransformContext,
+ arg: V2Expression): FieldReference = {
+ lazy val name: String = ctx.identifier.getText
+ arg match {
+ case ref: FieldReference =>
+ ref
+ case nonRef =>
+ throw new ParseException(s"Expected a column reference for transform $name: $nonRef.describe", ctx)
+ }
+ }
+
+ def getSingleFieldReference(
+ ctx: ApplyTransformContext,
+ arguments: Seq[V2Expression]): FieldReference = {
+ lazy val name: String = ctx.identifier.getText
+ if (arguments.size > 1) {
+ throw new ParseException(s"Too many arguments for transform $name", ctx)
+ } else if (arguments.isEmpty) {
+ throw
+
+ new ParseException(s"Not enough arguments for transform $name", ctx)
+ } else {
+ getFieldReference(ctx, arguments.head)
+ }
+ }
+
+ ctx.transform match {
+ case identityCtx: IdentityTransformContext =>
+ IdentityTransform(FieldReference(typedVisit[Seq[String]](identityCtx.qualifiedName)))
+
+ case applyCtx: ApplyTransformContext =>
+ val arguments = applyCtx.argument.asScala.map(visitTransformArgument).toSeq
+
+ applyCtx.identifier.getText match {
+ case "bucket" =>
+ val numBuckets: Int = arguments.head match {
+ case LiteralValue(shortValue, ShortType) =>
+ shortValue.asInstanceOf[Short].toInt
+ case LiteralValue(intValue, IntegerType) =>
+ intValue.asInstanceOf[Int]
+ case LiteralValue(longValue, LongType) =>
+ longValue.asInstanceOf[Long].toInt
+ case lit =>
+ throw new ParseException(s"Invalid number of buckets: ${lit.describe}", applyCtx)
+ }
+
+ val fields = arguments.tail.map(arg => getFieldReference(applyCtx, arg))
+
+ BucketTransform(LiteralValue(numBuckets, IntegerType), fields)
+
+ case "years" =>
+ YearsTransform(getSingleFieldReference(applyCtx, arguments))
+
+ case "months" =>
+ MonthsTransform(getSingleFieldReference(applyCtx, arguments))
+
+ case "days" =>
+ DaysTransform(getSingleFieldReference(applyCtx, arguments))
+
+ case "hours" =>
+ HoursTransform(getSingleFieldReference(applyCtx, arguments))
+
+ case name =>
+ ApplyTransform(name, arguments)
+ }
+ }
+ }
+
+ /**
+ * Parse an argument to a transform. An argument may be a field reference (qualified name) or
+ * a value literal.
+ */
+ override def visitTransformArgument(ctx: TransformArgumentContext): V2Expression = {
+ withOrigin(ctx) {
+ val reference = Option(ctx.qualifiedName)
+ .map(typedVisit[Seq[String]])
+ .map(FieldReference(_))
+ val literal = Option(ctx.constant)
+ .map(typedVisit[Literal])
+ .map(lit => LiteralValue(lit.value, lit.dataType))
+ reference.orElse(literal)
+ .getOrElse(throw new ParseException("Invalid transform argument", ctx))
+ }
+ }
+
+ def cleanTableProperties(
+ ctx: ParserRuleContext, properties: Map[String, String]): Map[String, String] = {
+ import TableCatalog._
+ val legacyOn = conf.getConf(SQLConf.LEGACY_PROPERTY_NON_RESERVED)
+ properties.filter {
+ case (PROP_PROVIDER, _) if !legacyOn =>
+ throw new ParseException(s"$PROP_PROVIDER is a reserved table property, please use the USING clause to specify it.", ctx)
+ case (PROP_PROVIDER, _) => false
+ case (PROP_LOCATION, _) if !legacyOn =>
+ throw new ParseException(s"$PROP_LOCATION is a reserved table property, please use the LOCATION clause to specify it.", ctx)
+ case (PROP_LOCATION, _) => false
+ case (PROP_OWNER, _) if !legacyOn =>
+ throw new ParseException(s"$PROP_OWNER is a reserved table property, it will be set to the current user.", ctx)
+ case (PROP_OWNER, _) => false
+ case _ => true
+ }
+ }
+
+ def cleanTableOptions(
+ ctx: ParserRuleContext,
+ options: Map[String, String],
+ location: Option[String]): (Map[String, String], Option[String]) = {
+ var path = location
+ val filtered = cleanTableProperties(ctx, options).filter {
+ case (k, v) if k.equalsIgnoreCase("path") && path.nonEmpty =>
+ throw new ParseException(s"Duplicated table paths found: '${path.get}' and '$v'. LOCATION" +
+ s" and the case insensitive key 'path' in OPTIONS are all used to indicate the custom" +
+ s" table path, you can only specify one of them.", ctx)
+ case (k, v) if k.equalsIgnoreCase("path") =>
+ path = Some(v)
+ false
+ case _ => true
+ }
+ (filtered, path)
+ }
+
+ /**
+ * Create a [[SerdeInfo]] for creating tables.
+ *
+ * Format: STORED AS (name | INPUTFORMAT input_format OUTPUTFORMAT output_format)
+ */
+ override def visitCreateFileFormat(ctx: CreateFileFormatContext): SerdeInfo = withOrigin(ctx) {
+ (ctx.fileFormat, ctx.storageHandler) match {
+ // Expected format: INPUTFORMAT input_format OUTPUTFORMAT output_format
+ case (c: TableFileFormatContext, null) =>
+ SerdeInfo(formatClasses = Some(FormatClasses(string(c.inFmt), string(c.outFmt))))
+ // Expected format: SEQUENCEFILE | TEXTFILE | RCFILE | ORC | PARQUET | AVRO
+ case (c: GenericFileFormatContext, null) =>
+ SerdeInfo(storedAs = Some(c.identifier.getText))
+ case (null, storageHandler) =>
+ operationNotAllowed("STORED BY", ctx)
+ case _ =>
+ throw new ParseException("Expected either STORED AS or STORED BY, not both", ctx)
+ }
+ }
+
+ /**
+ * Create a [[SerdeInfo]] used for creating tables.
+ *
+ * Example format:
+ * {{{
+ * SERDE serde_name [WITH SERDEPROPERTIES (k1=v1, k2=v2, ...)]
+ * }}}
+ *
+ * OR
+ *
+ * {{{
+ * DELIMITED [FIELDS TERMINATED BY char [ESCAPED BY char]]
+ * [COLLECTION ITEMS TERMINATED BY char]
+ * [MAP KEYS TERMINATED BY char]
+ * [LINES TERMINATED BY char]
+ * [NULL DEFINED AS char]
+ * }}}
+ */
+ def visitRowFormat(ctx: RowFormatContext): SerdeInfo = withOrigin(ctx) {
+ ctx match {
+ case serde: RowFormatSerdeContext => visitRowFormatSerde(serde)
+ case delimited: RowFormatDelimitedContext => visitRowFormatDelimited(delimited)
+ }
+ }
+
+ /**
+ * Create SERDE row format name and properties pair.
+ */
+ override def visitRowFormatSerde(ctx: RowFormatSerdeContext): SerdeInfo = withOrigin(ctx) {
+ import ctx._
+ SerdeInfo(
+ serde = Some(string(name)),
+ serdeProperties = Option(tablePropertyList).map(visitPropertyKeyValues).getOrElse(Map.empty))
+ }
+
+ /**
+ * Create a delimited row format properties object.
+ */
+ override def visitRowFormatDelimited(
+ ctx: RowFormatDelimitedContext): SerdeInfo = withOrigin(ctx) {
+ // Collect the entries if any.
+ def entry(key: String, value: Token): Seq[(String, String)] = {
+ Option(value).toSeq.map(x => key -> string(x))
+ }
+
+ // TODO we need proper support for the NULL format.
+ val entries =
+ entry("field.delim", ctx.fieldsTerminatedBy) ++
+ entry("serialization.format", ctx.fieldsTerminatedBy) ++
+ entry("escape.delim", ctx.escapedBy) ++
+ // The following typo is inherited from Hive...
+ entry("colelction.delim", ctx.collectionItemsTerminatedBy) ++
+ entry("mapkey.delim", ctx.keysTerminatedBy) ++
+ Option(ctx.linesSeparatedBy).toSeq.map { token =>
+ val value = string(token)
+ validate(
+ value == "\n",
+ s"LINES TERMINATED BY only supports newline '\\n' right now: $value",
+ ctx)
+ "line.delim" -> value
+ }
+ SerdeInfo(serdeProperties = entries.toMap)
+ }
+
+ /**
+ * Throw a [[ParseException]] if the user specified incompatible SerDes through ROW FORMAT
+ * and STORED AS.
+ *
+ * The following are allowed. Anything else is not:
+ * ROW FORMAT SERDE ... STORED AS [SEQUENCEFILE | RCFILE | TEXTFILE]
+ * ROW FORMAT DELIMITED ... STORED AS TEXTFILE
+ * ROW FORMAT ... STORED AS INPUTFORMAT ... OUTPUTFORMAT ...
+ */
+ protected def validateRowFormatFileFormat(
+ rowFormatCtx: RowFormatContext,
+ createFileFormatCtx: CreateFileFormatContext,
+ parentCtx: ParserRuleContext): Unit = {
+ if (!(rowFormatCtx == null || createFileFormatCtx == null)) {
+ (rowFormatCtx, createFileFormatCtx.fileFormat) match {
+ case (_, ffTable: TableFileFormatContext) => // OK
+ case (rfSerde: RowFormatSerdeContext, ffGeneric: GenericFileFormatContext) =>
+ ffGeneric.identifier.getText.toLowerCase(Locale.ROOT) match {
+ case ("sequencefile" | "textfile" | "rcfile") => // OK
+ case fmt =>
+ operationNotAllowed(
+ s"ROW FORMAT SERDE is incompatible with format '$fmt', which also specifies a serde",
+ parentCtx)
+ }
+ case (rfDelimited: RowFormatDelimitedContext, ffGeneric: GenericFileFormatContext) =>
+ ffGeneric.identifier.getText.toLowerCase(Locale.ROOT) match {
+ case "textfile" => // OK
+ case fmt => operationNotAllowed(
+ s"ROW FORMAT DELIMITED is only compatible with 'textfile', not '$fmt'", parentCtx)
+ }
+ case _ =>
+ // should never happen
+ def str(ctx: ParserRuleContext): String = {
+ (0 until ctx.getChildCount).map { i => ctx.getChild(i).getText }.mkString(" ")
+ }
+
+ operationNotAllowed(
+ s"Unexpected combination of ${str(rowFormatCtx)} and ${str(createFileFormatCtx)}",
+ parentCtx)
+ }
+ }
+ }
+
+ protected def validateRowFormatFileFormat(
+ rowFormatCtx: Seq[RowFormatContext],
+ createFileFormatCtx: Seq[CreateFileFormatContext],
+ parentCtx: ParserRuleContext): Unit = {
+ if (rowFormatCtx.size == 1 && createFileFormatCtx.size == 1) {
+ validateRowFormatFileFormat(rowFormatCtx.head, createFileFormatCtx.head, parentCtx)
+ }
+ }
+
+ override def visitCreateTableClauses(ctx: CreateTableClausesContext): TableClauses = {
+ checkDuplicateClauses(ctx.TBLPROPERTIES, "TBLPROPERTIES", ctx)
+ checkDuplicateClauses(ctx.OPTIONS, "OPTIONS", ctx)
+ checkDuplicateClauses(ctx.PARTITIONED, "PARTITIONED BY", ctx)
+ checkDuplicateClauses(ctx.createFileFormat, "STORED AS/BY", ctx)
+ checkDuplicateClauses(ctx.rowFormat, "ROW FORMAT", ctx)
+ checkDuplicateClauses(ctx.commentSpec(), "COMMENT", ctx)
+ checkDuplicateClauses(ctx.bucketSpec(), "CLUSTERED BY", ctx)
+ checkDuplicateClauses(ctx.locationSpec, "LOCATION", ctx)
+
+ if (ctx.skewSpec.size > 0) {
+ operationNotAllowed("CREATE TABLE ... SKEWED BY", ctx)
+ }
+
+ val (partTransforms, partCols) =
+ Option(ctx.partitioning).map(visitPartitionFieldList).getOrElse((Nil, Nil))
+ val bucketSpec = ctx.bucketSpec().asScala.headOption.map(visitBucketSpec)
+ val properties = Option(ctx.tableProps).map(visitPropertyKeyValues).getOrElse(Map.empty)
+ val cleanedProperties = cleanTableProperties(ctx, properties)
+ val options = Option(ctx.options).map(visitPropertyKeyValues).getOrElse(Map.empty)
+ val location = visitLocationSpecList(ctx.locationSpec())
+ val (cleanedOptions, newLocation) = cleanTableOptions(ctx, options, location)
+ val comment = visitCommentSpecList(ctx.commentSpec())
+ val serdeInfo =
+ getSerdeInfo(ctx.rowFormat.asScala.toSeq, ctx.createFileFormat.asScala.toSeq, ctx)
+ (partTransforms, partCols, bucketSpec, cleanedProperties, cleanedOptions, newLocation, comment,
+ serdeInfo)
+ }
+
+ protected def getSerdeInfo(
+ rowFormatCtx: Seq[RowFormatContext],
+ createFileFormatCtx: Seq[CreateFileFormatContext],
+ ctx: ParserRuleContext): Option[SerdeInfo] = {
+ validateRowFormatFileFormat(rowFormatCtx, createFileFormatCtx, ctx)
+ val rowFormatSerdeInfo = rowFormatCtx.map(visitRowFormat)
+ val fileFormatSerdeInfo = createFileFormatCtx.map(visitCreateFileFormat)
+ (fileFormatSerdeInfo ++ rowFormatSerdeInfo).reduceLeftOption((l, r) => l.merge(r))
+ }
+
+ private def partitionExpressions(
+ partTransforms: Seq[Transform],
+ partCols: Seq[StructField],
+ ctx: ParserRuleContext): Seq[Transform] = {
+ if (partTransforms.nonEmpty) {
+ if (partCols.nonEmpty) {
+ val references = partTransforms.map(_.describe()).mkString(", ")
+ val columns = partCols
+ .map(field => s"${field.name} ${field.dataType.simpleString}")
+ .mkString(", ")
+ operationNotAllowed(
+ s"""PARTITION BY: Cannot mix partition expressions and partition columns:
+ |Expressions: $references
+ |Columns: $columns""".stripMargin, ctx)
+
+ }
+ partTransforms
+ } else {
+ // columns were added to create the schema. convert to column references
+ partCols.map { column =>
+ IdentityTransform(FieldReference(Seq(column.name)))
+ }
+ }
+ }
+
+ /**
+ * Create a table, returning a [[CreateTable]] or [[CreateTableAsSelect]] logical plan.
+ *
+ * Expected format:
+ * {{{
+ * CREATE [TEMPORARY] TABLE [IF NOT EXISTS] [db_name.]table_name
+ * [USING table_provider]
+ * create_table_clauses
+ * [[AS] select_statement];
+ *
+ * create_table_clauses (order insensitive):
+ * [PARTITIONED BY (partition_fields)]
+ * [OPTIONS table_property_list]
+ * [ROW FORMAT row_format]
+ * [STORED AS file_format]
+ * [CLUSTERED BY (col_name, col_name, ...)
+ * [SORTED BY (col_name [ASC|DESC], ...)]
+ * INTO num_buckets BUCKETS
+ * ]
+ * [LOCATION path]
+ * [COMMENT table_comment]
+ * [TBLPROPERTIES (property_name=property_value, ...)]
+ *
+ * partition_fields:
+ * col_name, transform(col_name), transform(constant, col_name), ... |
+ * col_name data_type [NOT NULL] [COMMENT col_comment], ...
+ * }}}
+ */
+ override def visitCreateTable(ctx: CreateTableContext): LogicalPlan = withOrigin(ctx) {
+ val (table, temp, ifNotExists, external) = visitCreateTableHeader(ctx.createTableHeader)
+
+ val columns = Option(ctx.colTypeList()).map(visitColTypeList).getOrElse(Nil)
+ val provider = Option(ctx.tableProvider).map(_.multipartIdentifier.getText)
+ val (partTransforms, partCols, bucketSpec, properties, options, location, comment, serdeInfo) =
+ visitCreateTableClauses(ctx.createTableClauses())
+
+ if (provider.isDefined && serdeInfo.isDefined) {
+ operationNotAllowed(s"CREATE TABLE ... USING ... ${serdeInfo.get.describe}", ctx)
+ }
+
+ if (temp) {
+ val asSelect = if (ctx.query == null) "" else " AS ..."
+ operationNotAllowed(
+ s"CREATE TEMPORARY TABLE ...$asSelect, use CREATE TEMPORARY VIEW instead", ctx)
+ }
+
+ // partition transforms for BucketSpec was moved inside parser
+ // https://issues.apache.org/jira/browse/SPARK-37923
+ val partitioning =
+ partitionExpressions(partTransforms, partCols, ctx) ++ bucketSpec.map(_.asTransform)
+ val tableSpec = TableSpec(properties, provider, options, location, comment,
+ serdeInfo, external)
+
+ Option(ctx.query).map(plan) match {
+ case Some(_) if columns.nonEmpty =>
+ operationNotAllowed(
+ "Schema may not be specified in a Create Table As Select (CTAS) statement",
+ ctx)
+
+ case Some(_) if partCols.nonEmpty =>
+ // non-reference partition columns are not allowed because schema can't be specified
+ operationNotAllowed(
+ "Partition column types may not be specified in Create Table As Select (CTAS)",
+ ctx)
+
+ // CreateTable / CreateTableAsSelect was migrated to v2 in Spark 3.3.0
Review Comment:
Change made according to https://issues.apache.org/jira/browse/SPARK-36850
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186086521
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186094636
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186101984
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1182708368
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## CI report:
* b61dcddad364cf184fef3e642078300699c5c69c Azure: [FAILURE](https://dev.azure.com/apache-hudi-ci-org/785b6ef4-2f42-4a89-8f0e-5f0d7039a0cc/_build/results?buildId=9877)
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r919515661
##########
hudi-spark-datasource/hudi-spark3.3/src/main/scala/org/apache/spark/sql/HoodieSpark3_3SqlUtils.scala:
##########
@@ -0,0 +1,44 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import org.apache.hudi.exception.HoodieException
+import org.apache.spark.sql.catalyst.catalog.BucketSpec
+import org.apache.spark.sql.connector.expressions.{BucketTransform, FieldReference, IdentityTransform, Transform}
+
+import scala.collection.mutable
+
+object HoodieSpark3_3SqlUtils {
+ def convertTransforms(partitions: Seq[Transform]): (Seq[String], Option[BucketSpec]) = {
+ val identityCols = new mutable.ArrayBuffer[String]
+ var bucketSpec = Option.empty[BucketSpec]
+
+ partitions.map {
+ case IdentityTransform(FieldReference(Seq(col))) =>
+ identityCols += col
+
+ case BucketTransform(numBuckets, Seq(FieldReference(Seq(col))), _) =>
Review Comment:
[SPARK-37627](https://github.com/apache/spark/pull/34914) Separate SortedBucketTransform from BucketTransform
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1184867581
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## CI report:
* 9e8f799edd35782847baf7b298294f2c285d7628 Azure: [FAILURE](https://dev.azure.com/apache-hudi-ci-org/785b6ef4-2f42-4a89-8f0e-5f0d7039a0cc/_build/results?buildId=9903)
* 925cca43e07501a3c40d9f2225583826e5cbdd97 UNKNOWN
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[GitHub] [hudi] alexeykudinkin commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1190846928
> Upgrade Parquet version to 1.12.3. [PARQUET-1968](https://issues.apache.org/jira/browse/PARQUET-1968) can simplify current In predicate filter pushdown.
Awesome! Parquet finally released a new version with the fix that should considerably bring down our overhead of writing binary (strings) into it (PARQUET-2106)
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[GitHub] [hudi] alexeykudinkin commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r926119182
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/spark/sql/hudi/SparkAdapter.scala:
##########
@@ -171,12 +170,32 @@ trait SparkAdapter extends Serializable {
}
/**
- * Create instance of [[ParquetFileFormat]]
- */
+ * Create instance of [[ParquetFileFormat]]
+ */
def createHoodieParquetFileFormat(appendPartitionValues: Boolean): Option[ParquetFileFormat]
/**
* Create instance of [[InterpretedPredicate]]
*/
def createInterpretedPredicate(e: Expression): InterpretedPredicate
+
+ /**
+ * Create instance of [[HoodieFileScanRDD]]
+ */
+ def createHoodieFileScanRDD(@transient sparkSession: SparkSession,
Review Comment:
There's no point in annotating `@transient` method params
##########
hudi-spark-datasource/hudi-spark3.2.x/src/main/antlr4/imports/SqlBase.g4:
##########
@@ -0,0 +1,1908 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+ * This file is an adaptation of Presto's presto-parser/src/main/antlr4/com/facebook/presto/sql/parser/SqlBase.g4 grammar.
+ */
+
+// The parser file is forked from spark 3.2.0's SqlBase.g4.
+grammar SqlBase;
Review Comment:
Did this change from Spark 3.2?
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/BaseFileOnlyRelation.scala:
##########
@@ -91,7 +93,9 @@ class BaseFileOnlyRelation(sqlContext: SQLContext,
hadoopConf = HoodieDataSourceHelper.getConfigurationWithInternalSchema(new Configuration(conf), requiredSchema.internalSchema, metaClient.getBasePath, validCommits)
)
- new HoodieFileScanRDD(sparkSession, baseFileReader, fileSplits)
+ // SPARK-37273 FileScanRDD constructor changed in SPARK 3.3
Review Comment:
I think we can spare this comment for just the adapter
##########
hudi-spark-datasource/README.md:
##########
@@ -21,17 +21,19 @@ This repo contains the code that integrate Hudi with Spark. The repo is split in
`hudi-spark`
`hudi-spark2`
-`hudi-spark3`
`hudi-spark3.1.x`
+`hudi-spark3.2.x`
+`hudi-spark3`
Review Comment:
Let's fix naming in this PR to make sure we avoid the need to rename the module and move 10k LOC of code when we'd plan to support next Spark version.
Let's call it in-line with the other modules -- `hudi-spark3.3.x`
##########
hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/adapter/Spark3_3Adapter.scala:
##########
@@ -0,0 +1,92 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.adapter
+
+import org.apache.avro.Schema
+import org.apache.hudi.Spark33HoodieFileScanRDD
+import org.apache.spark.sql.avro._
+import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Expression, Literal}
+import org.apache.spark.sql.catalyst.parser.ParserInterface
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile}
+import org.apache.spark.sql.execution.datasources.parquet.{ParquetFileFormat, Spark33HoodieParquetFileFormat}
+import org.apache.spark.sql.parser.HoodieSpark3_3ExtendedSqlParser
+import org.apache.spark.sql.types.{DataType, StructType}
+import org.apache.spark.sql.{HoodieCatalystExpressionUtils, HoodieSpark3_3CatalystExpressionUtils, SparkSession}
+
+/**
+ * Implementation of [[SparkAdapter]] for Spark 3.3.x branch
+ */
+class Spark3_3Adapter extends BaseSpark3Adapter {
+
+ override def createAvroSerializer(rootCatalystType: DataType, rootAvroType: Schema, nullable: Boolean): HoodieAvroSerializer =
+ new HoodieSpark3_2AvroSerializer(rootCatalystType, rootAvroType, nullable)
+
+ override def createAvroDeserializer(rootAvroType: Schema, rootCatalystType: DataType): HoodieAvroDeserializer =
+ new HoodieSpark3_2AvroDeserializer(rootAvroType, rootCatalystType)
+
+ override def createCatalystExpressionUtils(): HoodieCatalystExpressionUtils = HoodieSpark3_3CatalystExpressionUtils
+
+ /**
+ * if the logical plan is a TimeTravelRelation LogicalPlan.
+ */
+ override def isRelationTimeTravel(plan: LogicalPlan): Boolean = {
+ plan.isInstanceOf[TimeTravelRelation]
+ }
+
+ /**
+ * Get the member of the TimeTravelRelation LogicalPlan.
+ */
+ override def getRelationTimeTravel(plan: LogicalPlan): Option[(LogicalPlan, Option[Expression], Option[String])] = {
+ plan match {
+ case timeTravel: TimeTravelRelation =>
+ Some((timeTravel.table, timeTravel.timestamp, timeTravel.version))
+ case _ =>
+ None
+ }
+ }
+
+ override def createExtendedSparkParser: Option[(SparkSession, ParserInterface) => ParserInterface] = {
+ Some(
+ (spark: SparkSession, delegate: ParserInterface) => new HoodieSpark3_3ExtendedSqlParser(spark, delegate)
+ )
+ }
+
+ override def createHoodieParquetFileFormat(appendPartitionValues: Boolean): Option[ParquetFileFormat] = {
+ Some(new Spark33HoodieParquetFileFormat(appendPartitionValues))
+ }
+
+ override def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD = {
+ new Spark33HoodieFileScanRDD(sparkSession, readFunction, filePartitions, readDataSchema, metadataColumns)
+ }
+
+
+ override def getDeleteFromTable(table: LogicalPlan, condition: Option[Expression]): DeleteFromTable = {
+ DeleteFromTable(table, condition.getOrElse(Literal.TrueLiteral))
+ }
+
+ override def getQueryParserFromExtendedSqlParser(session: SparkSession, delegate: ParserInterface,
+ sqlText: String): LogicalPlan = {
+ new HoodieSpark3_3ExtendedSqlParser(session, delegate).parseQuery(sqlText)
Review Comment:
Why can't we just get leverage existing `createExtendedSparkParser` API instead adding this new one?
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/analysis/HoodieAnalysis.scala:
##########
@@ -64,15 +64,18 @@ object HoodieAnalysis {
val spark3ResolveReferences: RuleBuilder =
session => ReflectionUtils.loadClass(spark3ResolveReferencesClass, session).asInstanceOf[Rule[LogicalPlan]]
- val spark32ResolveAlterTableCommandsClass = "org.apache.spark.sql.hudi.ResolveHudiAlterTableCommandSpark32"
- val spark32ResolveAlterTableCommands: RuleBuilder =
- session => ReflectionUtils.loadClass(spark32ResolveAlterTableCommandsClass, session).asInstanceOf[Rule[LogicalPlan]]
+ val resolveAlterTableCommandsClass =
+ if (HoodieSparkUtils.gteqSpark3_3_0)
+ "org.apache.spark.sql.hudi.ResolveHudiAlterTableCommandSpark33"
Review Comment:
Do you mind cleaning this up and renaming the classes to have Spark3x as prefix (same as other classes)
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/DeleteHoodieTableCommand.scala:
##########
@@ -36,9 +37,13 @@ case class DeleteHoodieTableCommand(deleteTable: DeleteFromTable) extends Hoodie
// Remove meta fields from the data frame
var df = removeMetaFields(Dataset.ofRows(sparkSession, table))
- if (deleteTable.condition.isDefined) {
- df = df.filter(Column(deleteTable.condition.get))
+ // SPARK-38626 DeleteFromTable.condition is changed from Option[Expression] to Expression in Spark 3.3
+ val condition: Expression = deleteTable.condition match {
Review Comment:
Instead of doing that let's modify this class to hold the `Option[Expression]` instead of `DeleteFromCommand`
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/analysis/HoodieAnalysis.scala:
##########
@@ -413,10 +416,13 @@ case class HoodieResolveReferences(sparkSession: SparkSession) extends Rule[Logi
// Resolve Delete Table
case DeleteFromTable(table, condition)
if sparkAdapter.isHoodieTable(table, sparkSession) && table.resolved =>
- // Resolve condition
- val resolvedCondition = condition.map(resolveExpressionFrom(table)(_))
+ val unwrappedCondition: Expression = condition match {
Review Comment:
Let's hide this compatibility juggling w/in the SparkAdapter actually: we can create method like
```
def resolveDeleteFromCommand(dfc: DeleteFromCommand)
```
And handle compatibility in there
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/HoodieSparkSqlTestBase.scala:
##########
@@ -140,8 +140,11 @@ class HoodieSparkSqlTestBase extends FunSuite with BeforeAndAfterAll {
spark.sql(sql)
} catch {
case e: Throwable =>
- assertResult(true)(e.getMessage.contains(errorMsg))
- hasException = true
+ if (e.getMessage.contains(errorMsg)) {
Review Comment:
Why changing this?
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925173187
##########
hudi-examples/hudi-examples-spark/pom.xml:
##########
@@ -190,6 +190,12 @@
<artifactId>spark-sql_${scala.binary.version}</artifactId>
</dependency>
+ <!-- Hadoop -->
+ <dependency>
+ <groupId>org.apache.hadoop</groupId>
+ <artifactId>hadoop-auth</artifactId>
+ </dependency>
+
Review Comment:
SparkQuickStartTest would throw NoSuchMethodError without this
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925173265
##########
hudi-examples/hudi-examples-spark/src/test/java/org/apache/hudi/examples/quickstart/TestHoodieSparkQuickstart.java:
##########
@@ -30,6 +30,7 @@
import org.apache.spark.sql.SparkSession;
import org.apache.spark.util.Utils;
import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Disabled;
Review Comment:
will remove
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r926234429
##########
hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/adapter/Spark3_3Adapter.scala:
##########
@@ -0,0 +1,92 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.adapter
+
+import org.apache.avro.Schema
+import org.apache.hudi.Spark33HoodieFileScanRDD
+import org.apache.spark.sql.avro._
+import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Expression, Literal}
+import org.apache.spark.sql.catalyst.parser.ParserInterface
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile}
+import org.apache.spark.sql.execution.datasources.parquet.{ParquetFileFormat, Spark33HoodieParquetFileFormat}
+import org.apache.spark.sql.parser.HoodieSpark3_3ExtendedSqlParser
+import org.apache.spark.sql.types.{DataType, StructType}
+import org.apache.spark.sql.{HoodieCatalystExpressionUtils, HoodieSpark3_3CatalystExpressionUtils, SparkSession}
+
+/**
+ * Implementation of [[SparkAdapter]] for Spark 3.3.x branch
+ */
+class Spark3_3Adapter extends BaseSpark3Adapter {
+
+ override def createAvroSerializer(rootCatalystType: DataType, rootAvroType: Schema, nullable: Boolean): HoodieAvroSerializer =
+ new HoodieSpark3_2AvroSerializer(rootCatalystType, rootAvroType, nullable)
+
+ override def createAvroDeserializer(rootAvroType: Schema, rootCatalystType: DataType): HoodieAvroDeserializer =
+ new HoodieSpark3_2AvroDeserializer(rootAvroType, rootCatalystType)
+
+ override def createCatalystExpressionUtils(): HoodieCatalystExpressionUtils = HoodieSpark3_3CatalystExpressionUtils
+
+ /**
+ * if the logical plan is a TimeTravelRelation LogicalPlan.
+ */
+ override def isRelationTimeTravel(plan: LogicalPlan): Boolean = {
+ plan.isInstanceOf[TimeTravelRelation]
+ }
+
+ /**
+ * Get the member of the TimeTravelRelation LogicalPlan.
+ */
+ override def getRelationTimeTravel(plan: LogicalPlan): Option[(LogicalPlan, Option[Expression], Option[String])] = {
+ plan match {
+ case timeTravel: TimeTravelRelation =>
+ Some((timeTravel.table, timeTravel.timestamp, timeTravel.version))
+ case _ =>
+ None
+ }
+ }
+
+ override def createExtendedSparkParser: Option[(SparkSession, ParserInterface) => ParserInterface] = {
+ Some(
+ (spark: SparkSession, delegate: ParserInterface) => new HoodieSpark3_3ExtendedSqlParser(spark, delegate)
+ )
+ }
+
+ override def createHoodieParquetFileFormat(appendPartitionValues: Boolean): Option[ParquetFileFormat] = {
+ Some(new Spark33HoodieParquetFileFormat(appendPartitionValues))
+ }
+
+ override def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD = {
+ new Spark33HoodieFileScanRDD(sparkSession, readFunction, filePartitions, readDataSchema, metadataColumns)
+ }
+
+
+ override def getDeleteFromTable(table: LogicalPlan, condition: Option[Expression]): DeleteFromTable = {
+ DeleteFromTable(table, condition.getOrElse(Literal.TrueLiteral))
+ }
+
+ override def getQueryParserFromExtendedSqlParser(session: SparkSession, delegate: ParserInterface,
+ sqlText: String): LogicalPlan = {
+ new HoodieSpark3_3ExtendedSqlParser(session, delegate).parseQuery(sqlText)
Review Comment:
For previous spark versions, we can't call `parseQuery` in a class shared across spark3/2 like `HoodieCommonSqlParser` as it's not in `ParserInterface`. I guess we can call existing `createExtendedSparkParser` in the new method added here but it's basically the same
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191023697
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930242159
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/avro/AvroUtils.scala:
##########
@@ -0,0 +1,117 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.avro
+
+import org.apache.avro.Schema
+import org.apache.spark.sql.internal.SQLConf
+
+import java.util.Locale
+
+import scala.collection.JavaConverters._
+
+/**
+ * NOTE: This code is borrowed from Spark 3.2.1
+ * This code is borrowed, so that we can better control compatibility w/in Spark minor
+ * branches (3.2.x, 3.1.x, etc)
+ *
+ * PLEASE REFRAIN MAKING ANY CHANGES TO THIS CODE UNLESS ABSOLUTELY NECESSARY
+ */
Review Comment:
Technically we need to port from Spark 3.3. There is a list of classes I copied from spark3.2 module. I'll update this jira to track these classes: https://issues.apache.org/jira/browse/HUDI-4467
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1195197364
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930265879
##########
hudi-spark-datasource/README.md:
##########
@@ -21,17 +21,19 @@ This repo contains the code that integrate Hudi with Spark. The repo is split in
`hudi-spark`
`hudi-spark2`
-`hudi-spark3`
`hudi-spark3.1.x`
+`hudi-spark3.2.x`
+`hudi-spark3.3.x`
Review Comment:
https://issues.apache.org/jira/browse/HUDI-4478 created this one. Will put this under hudi-spark-datasource/README.md
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1195948587
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[GitHub] [hudi] alexeykudinkin commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r926899150
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/HoodieSparkSqlTestBase.scala:
##########
@@ -140,8 +140,11 @@ class HoodieSparkSqlTestBase extends FunSuite with BeforeAndAfterAll {
spark.sql(sql)
} catch {
case e: Throwable =>
- assertResult(true)(e.getMessage.contains(errorMsg))
- hasException = true
+ if (e.getMessage.contains(errorMsg)) {
Review Comment:
Nit: I'd suggest to squash match w/ conditional:
```
match {
case e: Throwable if e.getMessage.contains(...) => ...
case _ => fail(...)
}
```
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193081694
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928197802
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/bootstrap/HoodieSparkBootstrapSchemaProvider.java:
##########
@@ -71,11 +72,20 @@ protected Schema getBootstrapSourceSchema(HoodieEngineContext context, List<Pair
}
private static Schema getBootstrapSourceSchemaParquet(HoodieWriteConfig writeConfig, HoodieEngineContext context, Path filePath) {
- MessageType parquetSchema = new ParquetUtils().readSchema(context.getHadoopConf().get(), filePath);
+ Configuration hadoopConf = context.getHadoopConf().get();
+ MessageType parquetSchema = new ParquetUtils().readSchema(hadoopConf, filePath);
+
+ hadoopConf.set(
+ SQLConf.PARQUET_BINARY_AS_STRING().key(),
+ SQLConf.PARQUET_BINARY_AS_STRING().defaultValueString());
+ hadoopConf.set(
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().key(),
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().defaultValueString());
+ hadoopConf.set(
+ SQLConf.CASE_SENSITIVE().key(),
+ SQLConf.CASE_SENSITIVE().defaultValueString());
+ ParquetToSparkSchemaConverter converter = new ParquetToSparkSchemaConverter(hadoopConf);
Review Comment:
Yes, this is calling a constructor shared between all spark versions
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193190410
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[GitHub] [hudi] XuQianJin-Stars commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
XuQianJin-Stars commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928185137
##########
hudi-spark-datasource/README.md:
##########
@@ -53,4 +55,4 @@ has no class since hudi only supports spark 2.4.4 version, and it acts as the pl
### About upgrading Time Travel:
Spark3.3 support time travel syntax link [SPARK-37219](https://issues.apache.org/jira/browse/SPARK-37219).
Once Spark 3.3 released. The files in the following list will be removed:
-* hudi-spark3's `HoodieSpark3_2ExtendedSqlAstBuilder.scala`、`HoodieSpark3_2ExtendedSqlParser.scala`、`TimeTravelRelation.scala`、`SqlBase.g4`、`HoodieSqlBase.g4`
+* hudi-spark3.3.x's `HoodieSpark3_2ExtendedSqlAstBuilder.scala`、`HoodieSpark3_2ExtendedSqlParser.scala`、`TimeTravelRelation.scala`、`SqlBase.g4`、`HoodieSqlBase.g4`
Review Comment:
`HoodieSpark3_2ExtendedSqlParser` -> `HoodieSpark3_3ExtendedSqlParser`
`HoodieSpark3_2ExtendedSqlAstBuilder` -> `HoodieSpark3_3ExtendedSqlAstBuilder`
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[GitHub] [hudi] XuQianJin-Stars commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
XuQianJin-Stars commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928186006
##########
hudi-spark-datasource/README.md:
##########
@@ -53,4 +55,4 @@ has no class since hudi only supports spark 2.4.4 version, and it acts as the pl
### About upgrading Time Travel:
Spark3.3 support time travel syntax link [SPARK-37219](https://issues.apache.org/jira/browse/SPARK-37219).
Once Spark 3.3 released. The files in the following list will be removed:
-* hudi-spark3's `HoodieSpark3_2ExtendedSqlAstBuilder.scala`、`HoodieSpark3_2ExtendedSqlParser.scala`、`TimeTravelRelation.scala`、`SqlBase.g4`、`HoodieSqlBase.g4`
+* hudi-spark3.3.x's `HoodieSpark3_2ExtendedSqlAstBuilder.scala`、`HoodieSpark3_2ExtendedSqlParser.scala`、`TimeTravelRelation.scala`、`SqlBase.g4`、`HoodieSqlBase.g4`
Review Comment:
spark3.3 support `RelationTimeTravel`, `TimeTravelRelation.scala` should be removed and simplified.
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[GitHub] [hudi] yihua commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
yihua commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931509790
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/DeleteHoodieTableCommand.scala:
##########
@@ -36,9 +37,9 @@ case class DeleteHoodieTableCommand(deleteTable: DeleteFromTable) extends Hoodie
// Remove meta fields from the data frame
var df = removeMetaFields(Dataset.ofRows(sparkSession, table))
- if (deleteTable.condition.isDefined) {
- df = df.filter(Column(deleteTable.condition.get))
- }
+ // SPARK-38626 DeleteFromTable.condition is changed from Option[Expression] to Expression in Spark 3.3
Review Comment:
This can be addressed in a separate PR.
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931574811
##########
hudi-spark-datasource/hudi-spark2/src/main/scala/org/apache/spark/sql/adapter/Spark2Adapter.scala:
##########
@@ -122,6 +123,30 @@ class Spark2Adapter extends SparkAdapter {
InterpretedPredicate.create(e)
}
+ override def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD = {
+ new Spark2HoodieFileScanRDD(sparkSession, readFunction, filePartitions)
+ }
+
+ override def resolveDeleteFromTable(deleteFromTable: Command,
Review Comment:
We can't simply reuse the method, `resolveDeleteFromTable` has a different logic that involves `resolveFromExpression`
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1195070276
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[GitHub] [hudi] xushiyan commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
xushiyan commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930123936
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,16 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ // SPARK-38094 Spark 3.3 checks if this field is enabled. Hudi has to provide this or there would be NPE thrown
+ // Would ONLY be effective with Spark 3.3+
+ // default value is true which is in accordance with Spark 3.3
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
Review Comment:
hoodie config keys follow snake case
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1196143917
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[GitHub] [hudi] yihua commented on pull request #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
yihua commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1182095073
@alexeykudinkin @XuQianJin-Stars @YannByron This PR is going to add support for Spark 3.3. In the long term, how should we maintain the support matrix for Spark in Hudi? Do we deprecate the support for older Spark versions as we add new versions? cc @xushiyan @vinothchandar
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[GitHub] [hudi] melin commented on pull request #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
melin commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1167097365
rename column failed:
ALTER TABLE bigdata.test_hudi_dt RENAME COLUMN name TO username
```
Exception in thread "main" scala.MatchError: org.apache.spark.sql.connector.catalog.TableChange$RenameColumn@153b1055 (of class org.apache.spark.sql.connector.catalog.TableChange$RenameColumn)
at org.apache.spark.sql.hudi.catalog.HoodieCatalog.$anonfun$alterTable$4(HoodieCatalog.scala:169)
at scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:36)
at scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:38)
at org.apache.spark.sql.hudi.catalog.HoodieCatalog.$anonfun$alterTable$2(HoodieCatalog.scala:169)
at scala.collection.immutable.Map$Map1.foreach(Map.scala:193)
at org.apache.spark.sql.hudi.catalog.HoodieCatalog.alterTable(HoodieCatalog.scala:158)
at org.apache.spark.sql.hudi.catalog.HoodieCatalog.alterTable(HoodieCatalog.scala:43)
at org.apache.spark.sql.execution.datasources.v2.AlterTableExec.run(AlterTableExec.scala:37)
at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result$lzycompute(V2CommandExec.scala:43)
at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result(V2CommandExec.scala:43)
at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.executeCollect(V2CommandExec.scala:49)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:98)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:109)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:169)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:95)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:98)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:94)
at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:584)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:176)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:584)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:560)
at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:94)
at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:81)
at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:79)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:220)
at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:100)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:97)
at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:622)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:617)
at org.example.hudi.HudiSqlExample$.main(HudiSqlExample.scala:55)
at org.example.hudi.HudiSqlExample.main(HudiSqlExample.scala)
```
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186267831
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186474605
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186600925
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186125041
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[GitHub] [hudi] codope commented on pull request #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
codope commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1181727660
@CTTY is this still WIP?
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1189863769
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925172420
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/bootstrap/HoodieSparkBootstrapSchemaProvider.java:
##########
@@ -71,11 +72,20 @@ protected Schema getBootstrapSourceSchema(HoodieEngineContext context, List<Pair
}
private static Schema getBootstrapSourceSchemaParquet(HoodieWriteConfig writeConfig, HoodieEngineContext context, Path filePath) {
- MessageType parquetSchema = new ParquetUtils().readSchema(context.getHadoopConf().get(), filePath);
+ Configuration hadoopConf = context.getHadoopConf().get();
+ MessageType parquetSchema = new ParquetUtils().readSchema(hadoopConf, filePath);
+
+ hadoopConf.set(
+ SQLConf.PARQUET_BINARY_AS_STRING().key(),
+ SQLConf.PARQUET_BINARY_AS_STRING().defaultValueString());
+ hadoopConf.set(
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().key(),
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().defaultValueString());
+ hadoopConf.set(
+ SQLConf.CASE_SENSITIVE().key(),
+ SQLConf.CASE_SENSITIVE().defaultValueString());
+ ParquetToSparkSchemaConverter converter = new ParquetToSparkSchemaConverter(hadoopConf);
Review Comment:
[SPARK-36935](https://github.com/apache/spark/pull/34199) Constructor is changed for `ParquetToSparkSchemaConverter` in Spark 3.3. Switched to use another constructor that takes conf for bwc
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1192918042
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191060570
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191655589
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1192217509
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[GitHub] [hudi] xushiyan commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
xushiyan commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930121808
##########
pom.xml:
##########
@@ -1307,6 +1308,7 @@
<version>${maven-surefire-plugin.version}</version>
<configuration combine.self="append">
<skip>${skipUTs}</skip>
+ <trimStackTrace>false</trimStackTrace>
Review Comment:
this is already set in
```
<pluginManagement>
<plugins>
<plugin>
```
is it not effective?
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1195995323
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930464958
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/DeleteHoodieTableCommand.scala:
##########
@@ -36,9 +37,13 @@ case class DeleteHoodieTableCommand(deleteTable: DeleteFromTable) extends Hoodie
// Remove meta fields from the data frame
var df = removeMetaFields(Dataset.ofRows(sparkSession, table))
- if (deleteTable.condition.isDefined) {
- df = df.filter(Column(deleteTable.condition.get))
+ // SPARK-38626 DeleteFromTable.condition is changed from Option[Expression] to Expression in Spark 3.3
+ val condition: Expression = deleteTable.condition match {
+ case option: Option[Expression] => option.getOrElse(null)
+ case expr: Expression => expr
+ case _ => throw new IllegalArgumentException(s"DeleteFromTable.condition has to be either Option[Expression] or Expression")
Review Comment:
Added a new method `extractCondition` in `SparkAdapter` to clean this part
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[GitHub] [hudi] alexeykudinkin commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929059483
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/execution/datasources/Spark33NestedSchemaPruning.scala:
##########
@@ -0,0 +1,195 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.datasources
+
+import org.apache.hudi.HoodieBaseRelation
+import org.apache.spark.sql.catalyst.expressions.{And, AttributeReference, AttributeSet, Expression, NamedExpression, ProjectionOverSchema}
+import org.apache.spark.sql.catalyst.planning.PhysicalOperation
+import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.sources.BaseRelation
+import org.apache.spark.sql.types.{ArrayType, DataType, MapType, StructType}
+import org.apache.spark.sql.util.SchemaUtils.restoreOriginalOutputNames
+
+/**
+ * Prunes unnecessary physical columns given a [[PhysicalOperation]] over a data source relation.
+ * By "physical column", we mean a column as defined in the data source format like Parquet format
+ * or ORC format. For example, in Spark SQL, a root-level Parquet column corresponds to a SQL
+ * column, and a nested Parquet column corresponds to a [[StructField]].
Review Comment:
As we've discussed, please create an issue to back-port one from Spark 3.3 and revisit this one
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark33HoodieParquetFileFormat.scala:
##########
@@ -0,0 +1,505 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.datasources.parquet
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.mapred.FileSplit
+import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl
+import org.apache.hadoop.mapreduce.{JobID, TaskAttemptID, TaskID, TaskType}
+import org.apache.hudi.HoodieSparkUtils
+import org.apache.hudi.client.utils.SparkInternalSchemaConverter
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.util.InternalSchemaCache
+import org.apache.hudi.common.util.StringUtils.isNullOrEmpty
+import org.apache.hudi.common.util.collection.Pair
+import org.apache.hudi.internal.schema.InternalSchema
+import org.apache.hudi.internal.schema.action.InternalSchemaMerger
+import org.apache.hudi.internal.schema.utils.{InternalSchemaUtils, SerDeHelper}
+import org.apache.parquet.filter2.compat.FilterCompat
+import org.apache.parquet.filter2.predicate.FilterApi
+import org.apache.parquet.format.converter.ParquetMetadataConverter.SKIP_ROW_GROUPS
+import org.apache.parquet.hadoop.{ParquetInputFormat, ParquetRecordReader}
+import org.apache.spark.TaskContext
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.codegen.GenerateUnsafeProjection
+import org.apache.spark.sql.catalyst.expressions.{Cast, JoinedRow}
+import org.apache.spark.sql.catalyst.util.DateTimeUtils
+import org.apache.spark.sql.execution.datasources.parquet.Spark33HoodieParquetFileFormat._
+import org.apache.spark.sql.execution.datasources.{DataSourceUtils, PartitionedFile, RecordReaderIterator}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.sources._
+import org.apache.spark.sql.types.{AtomicType, DataType, StructField, StructType}
+import org.apache.spark.util.SerializableConfiguration
+
+import java.net.URI
+
+/**
+ * This class is an extension of [[ParquetFileFormat]] overriding Spark-specific behavior
+ * that's not possible to customize in any other way
+ *
+ * NOTE: This is a version of [[AvroDeserializer]] impl from Spark 3.2.1 w/ w/ the following changes applied to it:
Review Comment:
Are there any changes from Spark 3.2? Can we actually revisit all such cases and if there're actually no changes from Spark 3.2 let's just re-use these classes.
If this would be more than just a simple file move (to hoodie-spark3-common), then please create a JIRA ticket to follow-up which you can assign to me
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194435414
Created those Jiras below to follow up on improving the code quality:
- https://issues.apache.org/jira/browse/HUDI-4466 Re-use common code between Spark 3.2/3.3
- https://issues.apache.org/jira/browse/HUDI-4467 Port NestedSchemaPruning from Spark 3.3
- https://issues.apache.org/jira/browse/HUDI-4468 Time travel logic simplification
@alexeykudinkin @XuQianJin-Stars
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194522417
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194675076
> > Created those Jiras below to follow up on improving the code quality:
> > https://issues.apache.org/jira/browse/HUDI-4466 Re-use common code between Spark 3.2/3.3
> > https://issues.apache.org/jira/browse/HUDI-4467 Port NestedSchemaPruning from Spark 3.3
> > https://issues.apache.org/jira/browse/HUDI-4468 Time travel logic simplification
>
> If you haven't done so, could you put the Jira ticket number in the docs / comments of the code so that it won't get lost?
I've added them in hudi-spark-datasource/README.md
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193189907
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1197390727
> Created those Jiras below to follow up on improving the code quality:
>
> * https://issues.apache.org/jira/browse/HUDI-4466 Re-use common code between Spark 3.2/3.3
> * https://issues.apache.org/jira/browse/HUDI-4467 Port borrowed code from Spark 3.3
> * https://issues.apache.org/jira/browse/HUDI-4468 Time travel logic simplification
> * https://issues.apache.org/jira/browse/HUDI-4489 Break down HoodieAnalysis rules into Spark-specific components
> * https://issues.apache.org/jira/browse/HUDI-4481 Refactor HoodieCommonSqlParser
>
> @alexeykudinkin @XuQianJin-Stars @yihua
Updated follow-up jiras
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186631323
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186102412
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186095145
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193451044
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929167248
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/execution/datasources/Spark33NestedSchemaPruning.scala:
##########
@@ -0,0 +1,195 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.datasources
+
+import org.apache.hudi.HoodieBaseRelation
+import org.apache.spark.sql.catalyst.expressions.{And, AttributeReference, AttributeSet, Expression, NamedExpression, ProjectionOverSchema}
+import org.apache.spark.sql.catalyst.planning.PhysicalOperation
+import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.sources.BaseRelation
+import org.apache.spark.sql.types.{ArrayType, DataType, MapType, StructType}
+import org.apache.spark.sql.util.SchemaUtils.restoreOriginalOutputNames
+
+/**
+ * Prunes unnecessary physical columns given a [[PhysicalOperation]] over a data source relation.
+ * By "physical column", we mean a column as defined in the data source format like Parquet format
+ * or ORC format. For example, in Spark SQL, a root-level Parquet column corresponds to a SQL
+ * column, and a nested Parquet column corresponds to a [[StructField]].
Review Comment:
Sounds good, created a jira for this: https://issues.apache.org/jira/browse/HUDI-4467
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194594024
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194589168
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928297354
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/parser/HoodieSpark3_3ExtendedSqlAstBuilder.scala:
##########
@@ -0,0 +1,3351 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.sql.parser
+
+import org.antlr.v4.runtime.tree.{ParseTree, RuleNode, TerminalNode}
+import org.antlr.v4.runtime.{ParserRuleContext, Token}
+import org.apache.hudi.spark.sql.parser.HoodieSqlBaseParser._
+import org.apache.hudi.spark.sql.parser.{HoodieSqlBaseBaseVisitor, HoodieSqlBaseParser}
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.AnalysisException
+import org.apache.spark.sql.catalyst.analysis._
+import org.apache.spark.sql.catalyst.catalog.{BucketSpec, CatalogStorageFormat}
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.{First, Last}
+import org.apache.spark.sql.catalyst.parser.ParserUtils.{EnhancedLogicalPlan, checkDuplicateClauses, checkDuplicateKeys, entry, escapedIdentifier, operationNotAllowed, source, string, stringWithoutUnescape, validate, withOrigin}
+import org.apache.spark.sql.catalyst.parser.{ParseException, ParserInterface}
+import org.apache.spark.sql.catalyst.plans._
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.util.DateTimeUtils._
+import org.apache.spark.sql.catalyst.util.{CharVarcharUtils, DateTimeUtils, IntervalUtils, truncatedString}
+import org.apache.spark.sql.catalyst.{FunctionIdentifier, TableIdentifier}
+import org.apache.spark.sql.connector.catalog.CatalogV2Implicits.BucketSpecHelper
+import org.apache.spark.sql.connector.catalog.TableCatalog
+import org.apache.spark.sql.connector.catalog.TableChange.ColumnPosition
+import org.apache.spark.sql.connector.expressions.{ApplyTransform, BucketTransform, DaysTransform, FieldReference, HoursTransform, IdentityTransform, LiteralValue, MonthsTransform, Transform, YearsTransform, Expression => V2Expression}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.types._
+import org.apache.spark.unsafe.types.{CalendarInterval, UTF8String}
+import org.apache.spark.util.Utils.isTesting
+import org.apache.spark.util.random.RandomSampler
+
+import java.util.Locale
+import java.util.concurrent.TimeUnit
+import javax.xml.bind.DatatypeConverter
+import scala.collection.JavaConverters._
+import scala.collection.mutable.ArrayBuffer
+
+/**
+ * The AstBuilder for HoodieSqlParser to parser the AST tree to Logical Plan.
+ * Here we only do the parser for the extended sql syntax. e.g MergeInto. For
+ * other sql syntax we use the delegate sql parser which is the SparkSqlParser.
+ */
+class HoodieSpark3_3ExtendedSqlAstBuilder(conf: SQLConf, delegate: ParserInterface)
+ extends HoodieSqlBaseBaseVisitor[AnyRef] with Logging {
+
+ protected def typedVisit[T](ctx: ParseTree): T = {
+ ctx.accept(this).asInstanceOf[T]
+ }
+
+ /**
+ * Override the default behavior for all visit methods. This will only return a non-null result
+ * when the context has only one child. This is done because there is no generic method to
+ * combine the results of the context children. In all other cases null is returned.
+ */
+ override def visitChildren(node: RuleNode): AnyRef = {
+ if (node.getChildCount == 1) {
+ node.getChild(0).accept(this)
+ } else {
+ null
+ }
+ }
+
+ /**
+ * Create an aliased table reference. This is typically used in FROM clauses.
+ */
+ override def visitTableName(ctx: TableNameContext): LogicalPlan = withOrigin(ctx) {
+ val tableId = visitMultipartIdentifier(ctx.multipartIdentifier())
+ val relation = UnresolvedRelation(tableId)
+ val table = mayApplyAliasPlan(
+ ctx.tableAlias, relation.optionalMap(ctx.temporalClause)(withTimeTravel))
+ table.optionalMap(ctx.sample)(withSample)
+ }
+
+ private def withTimeTravel(
+ ctx: TemporalClauseContext, plan: LogicalPlan): LogicalPlan = withOrigin(ctx) {
Review Comment:
Same as above. We can file another PR to fix all those logics later
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193372326
@hudi-bot run azure
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193413199
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930237009
##########
pom.xml:
##########
@@ -1307,6 +1308,7 @@
<version>${maven-surefire-plugin.version}</version>
<configuration combine.self="append">
<skip>${skipUTs}</skip>
+ <trimStackTrace>false</trimStackTrace>
Review Comment:
I think it's not effective for me w/ or w/o this change. During Github CI check I still see truncated stacktrace. Will revert this change
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1196184063
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* ca8a1ba779576e7bf217d80f1e455b3ba4058e70 Azure: [FAILURE](https://dev.azure.com/apache-hudi-ci-org/785b6ef4-2f42-4a89-8f0e-5f0d7039a0cc/_build/results?buildId=10377)
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[GitHub] [hudi] yihua commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
yihua commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929566480
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/java/org/apache/spark/sql/execution/datasources/parquet/Spark33HoodieVectorizedParquetRecordReader.java:
##########
@@ -0,0 +1,191 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.datasources.parquet;
+
+import org.apache.hadoop.mapreduce.InputSplit;
+import org.apache.hadoop.mapreduce.TaskAttemptContext;
+import org.apache.hudi.client.utils.SparkInternalSchemaConverter;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.spark.memory.MemoryMode;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.execution.vectorized.OffHeapColumnVector;
+import org.apache.spark.sql.execution.vectorized.OnHeapColumnVector;
+import org.apache.spark.sql.execution.vectorized.WritableColumnVector;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.StructType;
+import org.apache.spark.sql.vectorized.ColumnarBatch;
+
+import java.io.IOException;
+import java.time.ZoneId;
+import java.util.HashMap;
+import java.util.Map;
+
+public class Spark33HoodieVectorizedParquetRecordReader extends VectorizedParquetRecordReader {
Review Comment:
Is this copied from Spark as well? Could you add some docs here?
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/hudi/analysis/HoodieSpark3Analysis.scala:
##########
@@ -0,0 +1,222 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.hudi.analysis
+
+import org.apache.hudi.{DefaultSource, SparkAdapterSupport}
+import org.apache.hudi.common.table.HoodieTableMetaClient
+import org.apache.spark.sql.catalyst.TableIdentifier
+import org.apache.spark.sql.catalyst.analysis.{ResolvedTable, UnresolvedPartitionSpec}
+import org.apache.spark.sql.catalyst.catalog.{CatalogTable, HoodieCatalogTable}
+import org.apache.spark.sql.catalyst.expressions.{Alias, Attribute}
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.connector.catalog.CatalogV2Implicits.IdentifierHelper
+import org.apache.spark.sql.connector.catalog.{Table, V1Table}
+import org.apache.spark.sql.execution.datasources.LogicalRelation
+import org.apache.spark.sql.execution.datasources.PreWriteCheck.failAnalysis
+import org.apache.spark.sql.execution.datasources.v2.{DataSourceV2Relation, V2SessionCatalog}
+import org.apache.spark.sql.hudi.HoodieSqlCommonUtils.{castIfNeeded, getTableLocation, removeMetaFields, tableExistsInPath}
+import org.apache.spark.sql.hudi.catalog.{HoodieCatalog, HoodieInternalV2Table}
+import org.apache.spark.sql.hudi.command.{AlterHoodieTableDropPartitionCommand, ShowHoodieTablePartitionsCommand, TruncateHoodieTableCommand}
+import org.apache.spark.sql.hudi.{HoodieSqlCommonUtils, ProvidesHoodieConfig}
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.{AnalysisException, SQLContext, SparkSession}
+
+import scala.collection.JavaConverters.mapAsJavaMapConverter
+
+/**
+ * NOTE: PLEASE READ CAREFULLY
+ *
+ * Since Hudi relations don't currently implement DS V2 Read API, we have to fallback to V1 here.
+ * Such fallback will have considerable performance impact, therefore it's only performed in cases
+ * where V2 API have to be used. Currently only such use-case is using of Schema Evolution feature
+ *
+ * Check out HUDI-4178 for more details
+ */
+class HoodieDataSourceV2ToV1Fallback(sparkSession: SparkSession) extends Rule[LogicalPlan]
+ with ProvidesHoodieConfig {
+
+ override def apply(plan: LogicalPlan): LogicalPlan = plan.resolveOperatorsDown {
+ case v2r @ DataSourceV2Relation(v2Table: HoodieInternalV2Table, _, _, _, _) =>
+ val output = v2r.output
+ val catalogTable = v2Table.catalogTable.map(_ => v2Table.v1Table)
+ val relation = new DefaultSource().createRelation(new SQLContext(sparkSession),
+ buildHoodieConfig(v2Table.hoodieCatalogTable), v2Table.hoodieCatalogTable.tableSchema)
+
+ LogicalRelation(relation, output, catalogTable, isStreaming = false)
+ }
+}
+
+class HoodieSpark3Analysis(sparkSession: SparkSession) extends Rule[LogicalPlan] {
Review Comment:
For a follow-up PR, for common Spark 3 support classes, should we put them in a common module instead of duplicating code? Could you create a ticket to track that work?
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/avro/AvroUtils.scala:
##########
@@ -0,0 +1,117 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.avro
+
+import org.apache.avro.Schema
+import org.apache.spark.sql.internal.SQLConf
+
+import java.util.Locale
+
+import scala.collection.JavaConverters._
+
+/**
+ * NOTE: This code is borrowed from Spark 3.2.1
+ * This code is borrowed, so that we can better control compatibility w/in Spark minor
+ * branches (3.2.x, 3.1.x, etc)
+ *
+ * PLEASE REFRAIN MAKING ANY CHANGES TO THIS CODE UNLESS ABSOLUTELY NECESSARY
+ */
Review Comment:
Is this class changed? Do we need to update it based on Spark 3.3.0 implementation?
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930269250
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/bootstrap/HoodieSparkBootstrapSchemaProvider.java:
##########
@@ -71,11 +72,20 @@ protected Schema getBootstrapSourceSchema(HoodieEngineContext context, List<Pair
}
private static Schema getBootstrapSourceSchemaParquet(HoodieWriteConfig writeConfig, HoodieEngineContext context, Path filePath) {
- MessageType parquetSchema = new ParquetUtils().readSchema(context.getHadoopConf().get(), filePath);
+ Configuration hadoopConf = context.getHadoopConf().get();
+ MessageType parquetSchema = new ParquetUtils().readSchema(hadoopConf, filePath);
+
+ hadoopConf.set(
+ SQLConf.PARQUET_BINARY_AS_STRING().key(),
+ SQLConf.PARQUET_BINARY_AS_STRING().defaultValueString());
+ hadoopConf.set(
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().key(),
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().defaultValueString());
+ hadoopConf.set(
+ SQLConf.CASE_SENSITIVE().key(),
+ SQLConf.CASE_SENSITIVE().defaultValueString());
Review Comment:
Good point, but I think the original logic is passing default value in this class. Not sure if we should change that
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1195871742
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194517558
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928198507
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,12 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
+ .defaultValue("true")
+ .withDocumentation("Sets spark.sql.parquet.fieldId.write.enabled. "
+ + "If enabled, Spark will write out parquet native field ids that are stored inside StructField's metadata as parquet.field.id to parquet files.");
Review Comment:
Good point. This field is added in Spark 3.3 . It doesn't break older Spark but it would not be effective. I'll add this into `withDocumentation`
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928198507
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,12 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
+ .defaultValue("true")
+ .withDocumentation("Sets spark.sql.parquet.fieldId.write.enabled. "
+ + "If enabled, Spark will write out parquet native field ids that are stored inside StructField's metadata as parquet.field.id to parquet files.");
Review Comment:
Good point. This field is added in Spark 3.3 . It doesn't break older Spark but it would not be effective. I'll note this in`withDocumentation`
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193264779
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] XuQianJin-Stars commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
XuQianJin-Stars commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928185801
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/antlr4/imports/SqlBase.g4:
##########
@@ -0,0 +1,1908 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+ * This file is an adaptation of Presto's presto-parser/src/main/antlr4/com/facebook/presto/sql/parser/SqlBase.g4 grammar.
+ */
+
+// The parser file is forked from spark 3.2.0's SqlBase.g4.
Review Comment:
Need copy spark 3.3's `SqlBaseParser.g4`?
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191103564
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1192220299
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193255526
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1192150133
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931577076
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/parser/HoodieCommonSqlParser.scala:
##########
@@ -57,6 +57,14 @@ class HoodieCommonSqlParser(session: SparkSession, delegate: ParserInterface)
override def parseDataType(sqlText: String): DataType = delegate.parseDataType(sqlText)
+ /* SPARK-37266 Added parseQuery to ParserInterface in Spark 3.3.0. This is a patch to prevent
+ hackers from tampering text with persistent view, it won't be called in older Spark
+ Don't mark this as override for backward compatibility
+ Can't use sparkExtendedParser directly here due to the same reason */
Review Comment:
`parseQuery` is a new method of Spark trait `ParserInterface`. there would be compile issue If we call this method from any class that’s shared across different versions of spark, because older `ParserInterface` doesn’t have this method
Due to the same reason, we can't mark this method with `override` because for older spark there isn't `parseQuery`
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1184914987
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## CI report:
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1182633087
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## CI report:
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r919514634
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/bootstrap/HoodieSparkBootstrapSchemaProvider.java:
##########
@@ -71,11 +72,20 @@ protected Schema getBootstrapSourceSchema(HoodieEngineContext context, List<Pair
}
private static Schema getBootstrapSourceSchemaParquet(HoodieWriteConfig writeConfig, HoodieEngineContext context, Path filePath) {
- MessageType parquetSchema = new ParquetUtils().readSchema(context.getHadoopConf().get(), filePath);
+ Configuration hadoopConf = context.getHadoopConf().get();
+ MessageType parquetSchema = new ParquetUtils().readSchema(hadoopConf, filePath);
+
Review Comment:
Change made according to SPARK-36935. ParquetSchemaConverter change
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1182639310
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## CI report:
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1185152050
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1183927786
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186101474
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929457013
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/spark/sql/hudi/SparkAdapter.scala:
##########
@@ -138,4 +139,30 @@ trait SparkAdapter extends Serializable {
* TODO move to HoodieCatalystExpressionUtils
*/
def createInterpretedPredicate(e: Expression): InterpretedPredicate
+
+ /**
+ * Create instance of [[HoodieFileScanRDD]]
+ * SPARK-37273 FileScanRDD constructor changed in SPARK 3.3
+ */
+ def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD
+
+ /**
+ * Resolve [[DeleteFromTable]]
+ * SPARK-38626 condition is no longer Option in Spark 3.3
+ */
+ def resolveDeleteFromTable(dft: Command,
+ resolveExpression: Expression => Expression): LogicalPlan
+
+ /**
+ * Get parseQuery from ExtendedSqlParser, only for Spark 3.3+
+ */
+ def getQueryParserFromExtendedSqlParser(session: SparkSession, delegate: ParserInterface,
+ sqlText: String): LogicalPlan = {
+ // unsupported by default
+ throw new UnsupportedOperationException(s"Unsupported parseQuery method in Spark earlier than Spark 3.3.0")
Review Comment:
`parseQuery` is added in Spark 3.3 and older spark shouldn't call this method
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929455208
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,12 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
+ .defaultValue("true")
+ .withDocumentation("Sets spark.sql.parquet.fieldId.write.enabled. "
+ + "If enabled, Spark will write out parquet native field ids that are stored inside StructField's metadata as parquet.field.id to parquet files.");
+
Review Comment:
Here: https://github.com/apache/spark/blob/f74867bddfbcdd4d08076db36851e88b15e66556/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala#L464
On master branch of spark this issue is addressed
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929468050
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/bootstrap/HoodieSparkBootstrapSchemaProvider.java:
##########
@@ -71,11 +72,20 @@ protected Schema getBootstrapSourceSchema(HoodieEngineContext context, List<Pair
}
private static Schema getBootstrapSourceSchemaParquet(HoodieWriteConfig writeConfig, HoodieEngineContext context, Path filePath) {
- MessageType parquetSchema = new ParquetUtils().readSchema(context.getHadoopConf().get(), filePath);
+ Configuration hadoopConf = context.getHadoopConf().get();
+ MessageType parquetSchema = new ParquetUtils().readSchema(hadoopConf, filePath);
+
+ hadoopConf.set(
+ SQLConf.PARQUET_BINARY_AS_STRING().key(),
+ SQLConf.PARQUET_BINARY_AS_STRING().defaultValueString());
+ hadoopConf.set(
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().key(),
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().defaultValueString());
+ hadoopConf.set(
+ SQLConf.CASE_SENSITIVE().key(),
+ SQLConf.CASE_SENSITIVE().defaultValueString());
+ ParquetToSparkSchemaConverter converter = new ParquetToSparkSchemaConverter(hadoopConf);
Review Comment:
I'm ok with using adapter. but please correct me, this is a java class, and I don't think we can implement `SparkAdapterSupport` without rewriting its methods again here
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[GitHub] [hudi] alexeykudinkin commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r926897002
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/DeleteHoodieTableCommand.scala:
##########
@@ -36,9 +37,13 @@ case class DeleteHoodieTableCommand(deleteTable: DeleteFromTable) extends Hoodie
// Remove meta fields from the data frame
var df = removeMetaFields(Dataset.ofRows(sparkSession, table))
- if (deleteTable.condition.isDefined) {
- df = df.filter(Column(deleteTable.condition.get))
+ // SPARK-38626 DeleteFromTable.condition is changed from Option[Expression] to Expression in Spark 3.3
+ val condition: Expression = deleteTable.condition match {
Review Comment:
The overarching idea is to limit this compatibility code to live inside Spark-specific domains (SparkAdapter, HoodieCatalystExpressionUtils, etc).
> If modified like that, I think we would still have to handle the type matching at L133 HoodieAnalysis.scala
Good call. We can modify then previous suggestion and instead of `resolveDeleteFromCommand` we can either do `extractCondition(DeleteFromCommand)`
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191057816
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191153002
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[GitHub] [hudi] xushiyan commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
xushiyan commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930070043
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,16 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ // SPARK-38094 Spark 3.3 checks if this field is enabled. Hudi has to provide this or there would be NPE thrown
+ // Would ONLY be effective with Spark 3.3+
+ // default value is true which is in accordance with Spark 3.3
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
Review Comment:
```suggestion
.key("hoodie.parquet.field_id.write.enabled")
```
##########
pom.xml:
##########
@@ -1307,6 +1308,7 @@
<version>${maven-surefire-plugin.version}</version>
<configuration combine.self="append">
<skip>${skipUTs}</skip>
+ <trimStackTrace>false</trimStackTrace>
Review Comment:
this is also set in
<pluginManagement>
<plugins>
<plugin>
is it not effective?
##########
hudi-examples/hudi-examples-spark/pom.xml:
##########
@@ -190,6 +190,12 @@
<artifactId>spark-sql_${scala.binary.version}</artifactId>
</dependency>
+ <!-- Hadoop -->
+ <dependency>
+ <groupId>org.apache.hadoop</groupId>
+ <artifactId>hadoop-auth</artifactId>
+ </dependency>
+
Review Comment:
good find. so can we now re-enable spark 3.2 quickstart test in GH action? check out bot.yml
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/bootstrap/HoodieSparkBootstrapSchemaProvider.java:
##########
@@ -71,11 +72,20 @@ protected Schema getBootstrapSourceSchema(HoodieEngineContext context, List<Pair
}
private static Schema getBootstrapSourceSchemaParquet(HoodieWriteConfig writeConfig, HoodieEngineContext context, Path filePath) {
- MessageType parquetSchema = new ParquetUtils().readSchema(context.getHadoopConf().get(), filePath);
+ Configuration hadoopConf = context.getHadoopConf().get();
+ MessageType parquetSchema = new ParquetUtils().readSchema(hadoopConf, filePath);
+
+ hadoopConf.set(
+ SQLConf.PARQUET_BINARY_AS_STRING().key(),
+ SQLConf.PARQUET_BINARY_AS_STRING().defaultValueString());
+ hadoopConf.set(
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().key(),
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().defaultValueString());
+ hadoopConf.set(
+ SQLConf.CASE_SENSITIVE().key(),
+ SQLConf.CASE_SENSITIVE().defaultValueString());
Review Comment:
dont you want to set those only when they're not set?
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[GitHub] [hudi] xushiyan commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
xushiyan commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930121808
##########
pom.xml:
##########
@@ -1307,6 +1308,7 @@
<version>${maven-surefire-plugin.version}</version>
<configuration combine.self="append">
<skip>${skipUTs}</skip>
+ <trimStackTrace>false</trimStackTrace>
Review Comment:
this is also set in
```
<pluginManagement>
<plugins>
<plugin>
```
is it not effective?
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1189866980
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193205513
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193225503
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193373310
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[GitHub] [hudi] XuQianJin-Stars commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
XuQianJin-Stars commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928186137
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/parser/HoodieSpark3_3ExtendedSqlAstBuilder.scala:
##########
@@ -0,0 +1,3351 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.sql.parser
+
+import org.antlr.v4.runtime.tree.{ParseTree, RuleNode, TerminalNode}
+import org.antlr.v4.runtime.{ParserRuleContext, Token}
+import org.apache.hudi.spark.sql.parser.HoodieSqlBaseParser._
+import org.apache.hudi.spark.sql.parser.{HoodieSqlBaseBaseVisitor, HoodieSqlBaseParser}
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.AnalysisException
+import org.apache.spark.sql.catalyst.analysis._
+import org.apache.spark.sql.catalyst.catalog.{BucketSpec, CatalogStorageFormat}
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.{First, Last}
+import org.apache.spark.sql.catalyst.parser.ParserUtils.{EnhancedLogicalPlan, checkDuplicateClauses, checkDuplicateKeys, entry, escapedIdentifier, operationNotAllowed, source, string, stringWithoutUnescape, validate, withOrigin}
+import org.apache.spark.sql.catalyst.parser.{ParseException, ParserInterface}
+import org.apache.spark.sql.catalyst.plans._
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.util.DateTimeUtils._
+import org.apache.spark.sql.catalyst.util.{CharVarcharUtils, DateTimeUtils, IntervalUtils, truncatedString}
+import org.apache.spark.sql.catalyst.{FunctionIdentifier, TableIdentifier}
+import org.apache.spark.sql.connector.catalog.CatalogV2Implicits.BucketSpecHelper
+import org.apache.spark.sql.connector.catalog.TableCatalog
+import org.apache.spark.sql.connector.catalog.TableChange.ColumnPosition
+import org.apache.spark.sql.connector.expressions.{ApplyTransform, BucketTransform, DaysTransform, FieldReference, HoursTransform, IdentityTransform, LiteralValue, MonthsTransform, Transform, YearsTransform, Expression => V2Expression}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.types._
+import org.apache.spark.unsafe.types.{CalendarInterval, UTF8String}
+import org.apache.spark.util.Utils.isTesting
+import org.apache.spark.util.random.RandomSampler
+
+import java.util.Locale
+import java.util.concurrent.TimeUnit
+import javax.xml.bind.DatatypeConverter
+import scala.collection.JavaConverters._
+import scala.collection.mutable.ArrayBuffer
+
+/**
+ * The AstBuilder for HoodieSqlParser to parser the AST tree to Logical Plan.
+ * Here we only do the parser for the extended sql syntax. e.g MergeInto. For
+ * other sql syntax we use the delegate sql parser which is the SparkSqlParser.
+ */
+class HoodieSpark3_3ExtendedSqlAstBuilder(conf: SQLConf, delegate: ParserInterface)
+ extends HoodieSqlBaseBaseVisitor[AnyRef] with Logging {
+
+ protected def typedVisit[T](ctx: ParseTree): T = {
+ ctx.accept(this).asInstanceOf[T]
+ }
+
+ /**
+ * Override the default behavior for all visit methods. This will only return a non-null result
+ * when the context has only one child. This is done because there is no generic method to
+ * combine the results of the context children. In all other cases null is returned.
+ */
+ override def visitChildren(node: RuleNode): AnyRef = {
+ if (node.getChildCount == 1) {
+ node.getChild(0).accept(this)
+ } else {
+ null
+ }
+ }
+
+ /**
+ * Create an aliased table reference. This is typically used in FROM clauses.
+ */
+ override def visitTableName(ctx: TableNameContext): LogicalPlan = withOrigin(ctx) {
+ val tableId = visitMultipartIdentifier(ctx.multipartIdentifier())
+ val relation = UnresolvedRelation(tableId)
+ val table = mayApplyAliasPlan(
+ ctx.tableAlias, relation.optionalMap(ctx.temporalClause)(withTimeTravel))
+ table.optionalMap(ctx.sample)(withSample)
+ }
+
+ private def withTimeTravel(
+ ctx: TemporalClauseContext, plan: LogicalPlan): LogicalPlan = withOrigin(ctx) {
Review Comment:
Because `TimeTravel` has added a lot of logic here, spark3.3 is now supported, which this class should be greatly simplified here.
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[GitHub] [hudi] XuQianJin-Stars commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
XuQianJin-Stars commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928183435
##########
hudi-client/hudi-client-common/src/main/java/org/apache/hudi/config/HoodieStorageConfig.java:
##########
@@ -130,6 +130,12 @@ public class HoodieStorageConfig extends HoodieConfig {
.defaultValue("TIMESTAMP_MICROS")
.withDocumentation("Sets spark.sql.parquet.outputTimestampType. Parquet timestamp type to use when Spark writes data to Parquet files.");
+ public static final ConfigProperty<String> PARQUET_FIELD_ID_WRITE_ENABLED = ConfigProperty
+ .key("hoodie.parquet.fieldId.write.enabled")
+ .defaultValue("true")
+ .withDocumentation("Sets spark.sql.parquet.fieldId.write.enabled. "
+ + "If enabled, Spark will write out parquet native field ids that are stored inside StructField's metadata as parquet.field.id to parquet files.");
Review Comment:
.sinceVersion("0.12.0")? Does this need to be merged in version 0.12.0? And this change compatible with versions before spark 3.2?
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928200637
##########
hudi-examples/hudi-examples-flink/src/test/java/org/apache/hudi/examples/quickstart/TestHoodieFlinkQuickstart.java:
##########
@@ -45,6 +46,7 @@ void beforeEach() {
@TempDir
File tempFile;
+ @Disabled
Review Comment:
Temporarily disabled flink quickstart test due to it's instablity
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1190050954
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1192876122
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193027471
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191157279
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191238185
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931506367
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/antlr4/imports/SqlBase.g4:
##########
@@ -0,0 +1,1908 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+ * This file is an adaptation of Presto's presto-parser/src/main/antlr4/com/facebook/presto/sql/parser/SqlBase.g4 grammar.
+ */
+
+// The parser file is forked from spark 3.2.0's SqlBase.g4.
Review Comment:
It's gonna be compatible but new SQL feature might not be supported.
This should be solved after simplifying time travel logic, jira: https://issues.apache.org/jira/browse/HUDI-4468
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[GitHub] [hudi] alexeykudinkin commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1197380346
@CTTY please add the Jiras in the description so that they're more easily discoverable
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[GitHub] [hudi] YannByron commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
YannByron commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1196208725
> @alexeykudinkin @XuQianJin-Stars @YannByron This PR is going to add support for Spark 3.3. In the long term, how should we maintain the support matrix for Spark in Hudi? Do we deprecate the support for older Spark versions as we add new versions? cc @xushiyan @vinothchandar
It's not easy to decide.
Like delta lake, its latest version just supports the current latest version of spark, and it never consider to support the new features and the older spark version at its same version. If users need these, port the new features to the version that they own maintain. After all, i think most production users will not follow the Spark release iteration in a timely manner.
maybe we can support the two or three latest spark version to provide some convenience to our users.
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[GitHub] [hudi] melin commented on pull request #5943: [HUDI-4186] [WIP] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
melin commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1168111135
Upgrade Parquet version to 1.12.3.
[PARQUET-1968](https://issues.apache.org/jira/browse/PARQUET-1968) can simplify current In predicate filter pushdown.
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[GitHub] [hudi] CTTY commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1182617871
removed [WIP] tag to unblock Azure CI. **This PR is still under work**
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1182700523
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r926135463
##########
hudi-spark-datasource/hudi-spark3.2.x/src/main/antlr4/imports/SqlBase.g4:
##########
@@ -0,0 +1,1908 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+ * This file is an adaptation of Presto's presto-parser/src/main/antlr4/com/facebook/presto/sql/parser/SqlBase.g4 grammar.
+ */
+
+// The parser file is forked from spark 3.2.0's SqlBase.g4.
+grammar SqlBase;
Review Comment:
Everything under hudi-spark3.2.x are purely moved from previous hudi-spark3. They are not changed
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186110342
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186278547
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925175535
##########
hudi-spark-datasource/hudi-spark3.1.x/src/main/scala/org/apache/hudi/Spark31HoodieFileScanRDD.scala:
##########
@@ -0,0 +1,35 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hudi
+
+import org.apache.hudi.HoodieUnsafeRDD
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.AttributeReference
+import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile}
+import org.apache.spark.sql.types.StructType
+
+class Spark31HoodieFileScanRDD(@transient private val sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ @transient filePartitions: Seq[FilePartition])
+ extends FileScanRDD(sparkSession, readFunction, filePartitions)
+ with HoodieUnsafeRDD {
+
+ override final def collect(): Array[InternalRow] = super[HoodieUnsafeRDD].collect()
+}
Review Comment:
FileScanRDD constructor changed. Split class for Spark31: https://github.com/apache/spark/pull/34575
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[GitHub] [hudi] alexeykudinkin commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
alexeykudinkin commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r926894316
##########
hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/spark/sql/adapter/Spark3_3Adapter.scala:
##########
@@ -0,0 +1,92 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.adapter
+
+import org.apache.avro.Schema
+import org.apache.hudi.Spark33HoodieFileScanRDD
+import org.apache.spark.sql.avro._
+import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Expression, Literal}
+import org.apache.spark.sql.catalyst.parser.ParserInterface
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile}
+import org.apache.spark.sql.execution.datasources.parquet.{ParquetFileFormat, Spark33HoodieParquetFileFormat}
+import org.apache.spark.sql.parser.HoodieSpark3_3ExtendedSqlParser
+import org.apache.spark.sql.types.{DataType, StructType}
+import org.apache.spark.sql.{HoodieCatalystExpressionUtils, HoodieSpark3_3CatalystExpressionUtils, SparkSession}
+
+/**
+ * Implementation of [[SparkAdapter]] for Spark 3.3.x branch
+ */
+class Spark3_3Adapter extends BaseSpark3Adapter {
+
+ override def createAvroSerializer(rootCatalystType: DataType, rootAvroType: Schema, nullable: Boolean): HoodieAvroSerializer =
+ new HoodieSpark3_2AvroSerializer(rootCatalystType, rootAvroType, nullable)
+
+ override def createAvroDeserializer(rootAvroType: Schema, rootCatalystType: DataType): HoodieAvroDeserializer =
+ new HoodieSpark3_2AvroDeserializer(rootAvroType, rootCatalystType)
+
+ override def createCatalystExpressionUtils(): HoodieCatalystExpressionUtils = HoodieSpark3_3CatalystExpressionUtils
+
+ /**
+ * if the logical plan is a TimeTravelRelation LogicalPlan.
+ */
+ override def isRelationTimeTravel(plan: LogicalPlan): Boolean = {
+ plan.isInstanceOf[TimeTravelRelation]
+ }
+
+ /**
+ * Get the member of the TimeTravelRelation LogicalPlan.
+ */
+ override def getRelationTimeTravel(plan: LogicalPlan): Option[(LogicalPlan, Option[Expression], Option[String])] = {
+ plan match {
+ case timeTravel: TimeTravelRelation =>
+ Some((timeTravel.table, timeTravel.timestamp, timeTravel.version))
+ case _ =>
+ None
+ }
+ }
+
+ override def createExtendedSparkParser: Option[(SparkSession, ParserInterface) => ParserInterface] = {
+ Some(
+ (spark: SparkSession, delegate: ParserInterface) => new HoodieSpark3_3ExtendedSqlParser(spark, delegate)
+ )
+ }
+
+ override def createHoodieParquetFileFormat(appendPartitionValues: Boolean): Option[ParquetFileFormat] = {
+ Some(new Spark33HoodieParquetFileFormat(appendPartitionValues))
+ }
+
+ override def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD = {
+ new Spark33HoodieFileScanRDD(sparkSession, readFunction, filePartitions, readDataSchema, metadataColumns)
+ }
+
+
+ override def getDeleteFromTable(table: LogicalPlan, condition: Option[Expression]): DeleteFromTable = {
+ DeleteFromTable(table, condition.getOrElse(Literal.TrueLiteral))
+ }
+
+ override def getQueryParserFromExtendedSqlParser(session: SparkSession, delegate: ParserInterface,
+ sqlText: String): LogicalPlan = {
+ new HoodieSpark3_3ExtendedSqlParser(session, delegate).parseQuery(sqlText)
Review Comment:
> For previous spark versions, we can't call parseQuery in a class shared across spark3/2 like HoodieCommonSqlParser as it's not in ParserInterface. I guess we can call existing createExtendedSparkParser in the new method added here but it's basically the same
I don't think it's the same: we should preserve the coherence of the API -- `parseQuery` should be part of the Parser API, not SparkAdapter API. Let's move it into `ExtendedSqlParser`
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925176816
##########
hudi-spark-datasource/hudi-spark3/src/main/scala/org/apache/hudi/Spark33HoodieFileScanRDD.scala:
##########
@@ -20,14 +20,15 @@ package org.apache.hudi
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.AttributeReference
import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile}
+import org.apache.spark.sql.types.StructType
-case class HoodieBaseFileSplit(filePartition: FilePartition) extends HoodieFileSplit
-
-class HoodieFileScanRDD(@transient private val sparkSession: SparkSession,
+class Spark33HoodieFileScanRDD(@transient private val sparkSession: SparkSession,
readFunction: PartitionedFile => Iterator[InternalRow],
- @transient fileSplits: Seq[HoodieBaseFileSplit])
- extends FileScanRDD(sparkSession, readFunction, fileSplits.map(_.filePartition))
+ @transient filePartitions: Seq[FilePartition],
+ readDataSchema: StructType, metadataColumns: Seq[AttributeReference] = Seq.empty)
+ extends FileScanRDD(sparkSession, readFunction, filePartitions, readDataSchema, metadataColumns)
Review Comment:
FileScanRDD constructor changed in spark3.3
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186489231
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186610615
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186610012
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[GitHub] [hudi] XuQianJin-Stars commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
XuQianJin-Stars commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928186137
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/parser/HoodieSpark3_3ExtendedSqlAstBuilder.scala:
##########
@@ -0,0 +1,3351 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.sql.parser
+
+import org.antlr.v4.runtime.tree.{ParseTree, RuleNode, TerminalNode}
+import org.antlr.v4.runtime.{ParserRuleContext, Token}
+import org.apache.hudi.spark.sql.parser.HoodieSqlBaseParser._
+import org.apache.hudi.spark.sql.parser.{HoodieSqlBaseBaseVisitor, HoodieSqlBaseParser}
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.AnalysisException
+import org.apache.spark.sql.catalyst.analysis._
+import org.apache.spark.sql.catalyst.catalog.{BucketSpec, CatalogStorageFormat}
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.{First, Last}
+import org.apache.spark.sql.catalyst.parser.ParserUtils.{EnhancedLogicalPlan, checkDuplicateClauses, checkDuplicateKeys, entry, escapedIdentifier, operationNotAllowed, source, string, stringWithoutUnescape, validate, withOrigin}
+import org.apache.spark.sql.catalyst.parser.{ParseException, ParserInterface}
+import org.apache.spark.sql.catalyst.plans._
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.util.DateTimeUtils._
+import org.apache.spark.sql.catalyst.util.{CharVarcharUtils, DateTimeUtils, IntervalUtils, truncatedString}
+import org.apache.spark.sql.catalyst.{FunctionIdentifier, TableIdentifier}
+import org.apache.spark.sql.connector.catalog.CatalogV2Implicits.BucketSpecHelper
+import org.apache.spark.sql.connector.catalog.TableCatalog
+import org.apache.spark.sql.connector.catalog.TableChange.ColumnPosition
+import org.apache.spark.sql.connector.expressions.{ApplyTransform, BucketTransform, DaysTransform, FieldReference, HoursTransform, IdentityTransform, LiteralValue, MonthsTransform, Transform, YearsTransform, Expression => V2Expression}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.types._
+import org.apache.spark.unsafe.types.{CalendarInterval, UTF8String}
+import org.apache.spark.util.Utils.isTesting
+import org.apache.spark.util.random.RandomSampler
+
+import java.util.Locale
+import java.util.concurrent.TimeUnit
+import javax.xml.bind.DatatypeConverter
+import scala.collection.JavaConverters._
+import scala.collection.mutable.ArrayBuffer
+
+/**
+ * The AstBuilder for HoodieSqlParser to parser the AST tree to Logical Plan.
+ * Here we only do the parser for the extended sql syntax. e.g MergeInto. For
+ * other sql syntax we use the delegate sql parser which is the SparkSqlParser.
+ */
+class HoodieSpark3_3ExtendedSqlAstBuilder(conf: SQLConf, delegate: ParserInterface)
+ extends HoodieSqlBaseBaseVisitor[AnyRef] with Logging {
+
+ protected def typedVisit[T](ctx: ParseTree): T = {
+ ctx.accept(this).asInstanceOf[T]
+ }
+
+ /**
+ * Override the default behavior for all visit methods. This will only return a non-null result
+ * when the context has only one child. This is done because there is no generic method to
+ * combine the results of the context children. In all other cases null is returned.
+ */
+ override def visitChildren(node: RuleNode): AnyRef = {
+ if (node.getChildCount == 1) {
+ node.getChild(0).accept(this)
+ } else {
+ null
+ }
+ }
+
+ /**
+ * Create an aliased table reference. This is typically used in FROM clauses.
+ */
+ override def visitTableName(ctx: TableNameContext): LogicalPlan = withOrigin(ctx) {
+ val tableId = visitMultipartIdentifier(ctx.multipartIdentifier())
+ val relation = UnresolvedRelation(tableId)
+ val table = mayApplyAliasPlan(
+ ctx.tableAlias, relation.optionalMap(ctx.temporalClause)(withTimeTravel))
+ table.optionalMap(ctx.sample)(withSample)
+ }
+
+ private def withTimeTravel(
+ ctx: TemporalClauseContext, plan: LogicalPlan): LogicalPlan = withOrigin(ctx) {
Review Comment:
Because `TimeTravel` has added a lot of logic here, spark3.3 is now supported, which should be greatly simplified here.
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193264165
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193082268
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r927044414
##########
hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/hudi/command/DeleteHoodieTableCommand.scala:
##########
@@ -36,9 +37,13 @@ case class DeleteHoodieTableCommand(deleteTable: DeleteFromTable) extends Hoodie
// Remove meta fields from the data frame
var df = removeMetaFields(Dataset.ofRows(sparkSession, table))
- if (deleteTable.condition.isDefined) {
- df = df.filter(Column(deleteTable.condition.get))
+ // SPARK-38626 DeleteFromTable.condition is changed from Option[Expression] to Expression in Spark 3.3
+ val condition: Expression = deleteTable.condition match {
Review Comment:
Several things I've tried:
- exctract `Expression` from `condition`
- Embed `condition` to `Option[Expression]`
Both approches above would make `DeleteHoodieTableCommand` cleaner but have the same problem: we have to provide condition back to `DeleteFromTable` around L417 in `HoodieAnalysis`, which means we have to call adapter once more to wrap/unwrap for different spark versions.
If we also want to also make `DeleteHoodieTableCommand` cleaner, I think the only way might be adding two different methods in `SparkAdapter`: one to `resolveDeleteFromTable`, another to `extractCondition`
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r928055213
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/execution/datasources/Spark33NestedSchemaPruning.scala:
##########
@@ -0,0 +1,195 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.datasources
+
+import org.apache.hudi.HoodieBaseRelation
+import org.apache.spark.sql.catalyst.expressions.{And, AttributeReference, AttributeSet, Expression, NamedExpression, ProjectionOverSchema}
+import org.apache.spark.sql.catalyst.planning.PhysicalOperation
+import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.sources.BaseRelation
+import org.apache.spark.sql.types.{ArrayType, DataType, MapType, StructType}
+import org.apache.spark.sql.util.SchemaUtils.restoreOriginalOutputNames
+
+/**
+ * Prunes unnecessary physical columns given a [[PhysicalOperation]] over a data source relation.
+ * By "physical column", we mean a column as defined in the data source format like Parquet format
+ * or ORC format. For example, in Spark SQL, a root-level Parquet column corresponds to a SQL
+ * column, and a nested Parquet column corresponds to a [[StructField]].
+ *
+ * NOTE: This class is borrowed from Spark 3.2.1, with modifications adapting it to handle [[HoodieBaseRelation]],
+ * instead of [[HadoopFsRelation]]
+ */
+class Spark33NestedSchemaPruning extends Rule[LogicalPlan] {
+ import org.apache.spark.sql.catalyst.expressions.SchemaPruning._
+
+ override def apply(plan: LogicalPlan): LogicalPlan =
+ if (conf.nestedSchemaPruningEnabled) {
+ apply0(plan)
+ } else {
+ plan
+ }
+
+ private def apply0(plan: LogicalPlan): LogicalPlan =
+ plan transformDown {
+ case op @ PhysicalOperation(projects, filters,
+ // NOTE: This is modified to accommodate for Hudi's custom relations, given that original
+ // [[NestedSchemaPruning]] rule is tightly coupled w/ [[HadoopFsRelation]]
+ // TODO generalize to any file-based relation
+ l @ LogicalRelation(relation: HoodieBaseRelation, _, _, _))
+ if relation.canPruneRelationSchema =>
+
+ prunePhysicalColumns(l.output, projects, filters, relation.dataSchema,
+ prunedDataSchema => {
+ val prunedRelation =
+ relation.updatePrunedDataSchema(prunedSchema = prunedDataSchema)
+ buildPrunedRelation(l, prunedRelation)
+ }).getOrElse(op)
+ }
+
+ /**
+ * This method returns optional logical plan. `None` is returned if no nested field is required or
+ * all nested fields are required.
+ */
+ private def prunePhysicalColumns(output: Seq[AttributeReference],
+ projects: Seq[NamedExpression],
+ filters: Seq[Expression],
+ dataSchema: StructType,
+ outputRelationBuilder: StructType => LogicalRelation): Option[LogicalPlan] = {
+ val (normalizedProjects, normalizedFilters) =
+ normalizeAttributeRefNames(output, projects, filters)
+ val requestedRootFields = identifyRootFields(normalizedProjects, normalizedFilters)
+
+ // If requestedRootFields includes a nested field, continue. Otherwise,
+ // return op
+ if (requestedRootFields.exists { root: RootField => !root.derivedFromAtt }) {
+ val prunedDataSchema = pruneSchema(dataSchema, requestedRootFields)
Review Comment:
method name was changed from `pruneDataSchema` to `pruneSchema` in spark 3.3: https://github.com/apache/spark/pull/35147/files#diff-5718e2850bdcf5c3696b230e23ef53a22266d823fb092cd2aa9827f97919426a
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930263799
##########
hudi-examples/hudi-examples-spark/pom.xml:
##########
@@ -190,6 +190,12 @@
<artifactId>spark-sql_${scala.binary.version}</artifactId>
</dependency>
+ <!-- Hadoop -->
+ <dependency>
+ <groupId>org.apache.hadoop</groupId>
+ <artifactId>hadoop-auth</artifactId>
+ </dependency>
+
Review Comment:
Highly likely. maybe we need a seperate jira to track that?
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1196212221
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931598774
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/adapter/Spark3_3Adapter.scala:
##########
@@ -0,0 +1,80 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.adapter
+
+import org.apache.avro.Schema
+import org.apache.hudi.Spark33HoodieFileScanRDD
+import org.apache.spark.sql.avro._
+import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Expression}
+import org.apache.spark.sql.catalyst.parser.ParserInterface
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.{FilePartition, FileScanRDD, PartitionedFile}
+import org.apache.spark.sql.execution.datasources.parquet.{ParquetFileFormat, Spark33HoodieParquetFileFormat}
+import org.apache.spark.sql.parser.HoodieSpark3_3ExtendedSqlParser
+import org.apache.spark.sql.types.{DataType, StructType}
+import org.apache.spark.sql.{HoodieCatalystExpressionUtils, HoodieCatalystPlansUtils, HoodieSpark33CatalystPlanUtils, HoodieSpark33CatalystExpressionUtils, SparkSession}
+
+/**
+ * Implementation of [[SparkAdapter]] for Spark 3.3.x branch
+ */
+class Spark3_3Adapter extends BaseSpark3Adapter {
+
+ override def getCatalystExpressionUtils: HoodieCatalystExpressionUtils = HoodieSpark33CatalystExpressionUtils
+
+ override def getCatalystPlanUtils: HoodieCatalystPlansUtils = HoodieSpark33CatalystPlanUtils
+
+ override def createAvroSerializer(rootCatalystType: DataType, rootAvroType: Schema, nullable: Boolean): HoodieAvroSerializer =
+ new HoodieSpark3_3AvroSerializer(rootCatalystType, rootAvroType, nullable)
+
+ override def createAvroDeserializer(rootAvroType: Schema, rootCatalystType: DataType): HoodieAvroDeserializer =
+ new HoodieSpark3_3AvroDeserializer(rootAvroType, rootCatalystType)
+
+ override def createExtendedSparkParser: Option[(SparkSession, ParserInterface) => ParserInterface] = {
+ Some(
+ (spark: SparkSession, delegate: ParserInterface) => new HoodieSpark3_3ExtendedSqlParser(spark, delegate)
+ )
+ }
+
+ override def createHoodieParquetFileFormat(appendPartitionValues: Boolean): Option[ParquetFileFormat] = {
+ Some(new Spark33HoodieParquetFileFormat(appendPartitionValues))
+ }
+
+ override def createHoodieFileScanRDD(sparkSession: SparkSession,
+ readFunction: PartitionedFile => Iterator[InternalRow],
+ filePartitions: Seq[FilePartition],
+ readDataSchema: StructType,
+ metadataColumns: Seq[AttributeReference] = Seq.empty): FileScanRDD = {
+ new Spark33HoodieFileScanRDD(sparkSession, readFunction, filePartitions, readDataSchema, metadataColumns)
+ }
+
+ override def resolveDeleteFromTable(deleteFromTable: Command,
+ resolveExpression: Expression => Expression): DeleteFromTable = {
+ val deleteFromTableCommand = deleteFromTable.asInstanceOf[DeleteFromTable]
+ DeleteFromTable(deleteFromTableCommand.table, resolveExpression(deleteFromTableCommand.condition))
+ }
+
+ override def extractCondition(deleteFromTable: Command): Expression = {
+ deleteFromTable.asInstanceOf[DeleteFromTable].condition
+ }
+
+ override def getQueryParserFromExtendedSqlParser(session: SparkSession, delegate: ParserInterface,
+ sqlText: String): LogicalPlan = {
+ new HoodieSpark3_3ExtendedSqlParser(session, delegate).parseQuery(sqlText)
Review Comment:
> Created those Jiras below to follow up on improving the code quality:
>
> * https://issues.apache.org/jira/browse/HUDI-4466 Re-use common code between Spark 3.2/3.3
> * https://issues.apache.org/jira/browse/HUDI-4467 Port borrowed code from Spark 3.3
> * https://issues.apache.org/jira/browse/HUDI-4468 Time travel logic simplification
> * https://issues.apache.org/jira/browse/HUDI-4489 Break down HoodieAnalysis rules into Spark-specific components
> * https://issues.apache.org/jira/browse/HUDI-4481 Refactor HoodieCommonSqlParser
> @alexeykudinkin @XuQianJin-Stars @yihua
Updated follow-up jiras
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r930502025
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala:
##########
@@ -181,8 +200,6 @@ private[sql] class AvroDeserializer(rootAvroType: Schema,
case b: ByteBuffer =>
val bytes = new Array[Byte](b.remaining)
b.get(bytes)
- // Do not forget to reset the position
- b.rewind()
Review Comment:
Good point, this was reverted by mistake. I've added it back
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1196146015
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## CI report:
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r931503340
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/bootstrap/HoodieSparkBootstrapSchemaProvider.java:
##########
@@ -71,11 +72,20 @@ protected Schema getBootstrapSourceSchema(HoodieEngineContext context, List<Pair
}
private static Schema getBootstrapSourceSchemaParquet(HoodieWriteConfig writeConfig, HoodieEngineContext context, Path filePath) {
- MessageType parquetSchema = new ParquetUtils().readSchema(context.getHadoopConf().get(), filePath);
+ Configuration hadoopConf = context.getHadoopConf().get();
+ MessageType parquetSchema = new ParquetUtils().readSchema(hadoopConf, filePath);
+
+ hadoopConf.set(
+ SQLConf.PARQUET_BINARY_AS_STRING().key(),
+ SQLConf.PARQUET_BINARY_AS_STRING().defaultValueString());
+ hadoopConf.set(
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().key(),
+ SQLConf.PARQUET_INT96_AS_TIMESTAMP().defaultValueString());
+ hadoopConf.set(
+ SQLConf.CASE_SENSITIVE().key(),
+ SQLConf.CASE_SENSITIVE().defaultValueString());
+ ParquetToSparkSchemaConverter converter = new ParquetToSparkSchemaConverter(hadoopConf);
Review Comment:
Even in scala `ParquetToSparkSchemaConverter` defined default values, but those default values can be referred to when it's instantiated in Java. Using the constructor that takes conf obj is good enough here
Reference: https://github.com/scala/bug/issues/4278
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929167902
##########
hudi-spark-datasource/hudi-spark3.3.x/src/main/scala/org/apache/spark/sql/parser/HoodieSpark3_3ExtendedSqlAstBuilder.scala:
##########
@@ -0,0 +1,3351 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.sql.parser
+
+import org.antlr.v4.runtime.tree.{ParseTree, RuleNode, TerminalNode}
+import org.antlr.v4.runtime.{ParserRuleContext, Token}
+import org.apache.hudi.spark.sql.parser.HoodieSqlBaseParser._
+import org.apache.hudi.spark.sql.parser.{HoodieSqlBaseBaseVisitor, HoodieSqlBaseParser}
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.AnalysisException
+import org.apache.spark.sql.catalyst.analysis._
+import org.apache.spark.sql.catalyst.catalog.{BucketSpec, CatalogStorageFormat}
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.{First, Last}
+import org.apache.spark.sql.catalyst.parser.ParserUtils.{EnhancedLogicalPlan, checkDuplicateClauses, checkDuplicateKeys, entry, escapedIdentifier, operationNotAllowed, source, string, stringWithoutUnescape, validate, withOrigin}
+import org.apache.spark.sql.catalyst.parser.{ParseException, ParserInterface}
+import org.apache.spark.sql.catalyst.plans._
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.util.DateTimeUtils._
+import org.apache.spark.sql.catalyst.util.{CharVarcharUtils, DateTimeUtils, IntervalUtils, truncatedString}
+import org.apache.spark.sql.catalyst.{FunctionIdentifier, TableIdentifier}
+import org.apache.spark.sql.connector.catalog.CatalogV2Implicits.BucketSpecHelper
+import org.apache.spark.sql.connector.catalog.TableCatalog
+import org.apache.spark.sql.connector.catalog.TableChange.ColumnPosition
+import org.apache.spark.sql.connector.expressions.{ApplyTransform, BucketTransform, DaysTransform, FieldReference, HoursTransform, IdentityTransform, LiteralValue, MonthsTransform, Transform, YearsTransform, Expression => V2Expression}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.types._
+import org.apache.spark.unsafe.types.{CalendarInterval, UTF8String}
+import org.apache.spark.util.Utils.isTesting
+import org.apache.spark.util.random.RandomSampler
+
+import java.util.Locale
+import java.util.concurrent.TimeUnit
+import javax.xml.bind.DatatypeConverter
+import scala.collection.JavaConverters._
+import scala.collection.mutable.ArrayBuffer
+
+/**
+ * The AstBuilder for HoodieSqlParser to parser the AST tree to Logical Plan.
+ * Here we only do the parser for the extended sql syntax. e.g MergeInto. For
+ * other sql syntax we use the delegate sql parser which is the SparkSqlParser.
+ */
+class HoodieSpark3_3ExtendedSqlAstBuilder(conf: SQLConf, delegate: ParserInterface)
+ extends HoodieSqlBaseBaseVisitor[AnyRef] with Logging {
+
+ protected def typedVisit[T](ctx: ParseTree): T = {
+ ctx.accept(this).asInstanceOf[T]
+ }
+
+ /**
+ * Override the default behavior for all visit methods. This will only return a non-null result
+ * when the context has only one child. This is done because there is no generic method to
+ * combine the results of the context children. In all other cases null is returned.
+ */
+ override def visitChildren(node: RuleNode): AnyRef = {
+ if (node.getChildCount == 1) {
+ node.getChild(0).accept(this)
+ } else {
+ null
+ }
+ }
+
+ /**
+ * Create an aliased table reference. This is typically used in FROM clauses.
+ */
+ override def visitTableName(ctx: TableNameContext): LogicalPlan = withOrigin(ctx) {
+ val tableId = visitMultipartIdentifier(ctx.multipartIdentifier())
+ val relation = UnresolvedRelation(tableId)
+ val table = mayApplyAliasPlan(
+ ctx.tableAlias, relation.optionalMap(ctx.temporalClause)(withTimeTravel))
+ table.optionalMap(ctx.sample)(withSample)
+ }
+
+ private def withTimeTravel(
+ ctx: TemporalClauseContext, plan: LogicalPlan): LogicalPlan = withOrigin(ctx) {
Review Comment:
Created this jira to follow up on this: https://issues.apache.org/jira/browse/HUDI-4468
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194599423
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1194793199
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## CI report:
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r929453394
##########
hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/HoodieSparkUtils.scala:
##########
@@ -52,11 +52,14 @@ private[hudi] trait SparkVersionsSupport {
def isSpark3_0: Boolean = getSparkVersion.startsWith("3.0")
def isSpark3_1: Boolean = getSparkVersion.startsWith("3.1")
def isSpark3_2: Boolean = getSparkVersion.startsWith("3.2")
+ def isSpark3_3: Boolean = getSparkVersion.startsWith("3.3")
def gteqSpark3_1: Boolean = getSparkVersion >= "3.1"
def gteqSpark3_1_3: Boolean = getSparkVersion >= "3.1.3"
def gteqSpark3_2: Boolean = getSparkVersion >= "3.2"
def gteqSpark3_2_1: Boolean = getSparkVersion >= "3.2.1"
+ def gteqSpark3_3: Boolean = getSparkVersion >= "3.3"
+ def gteqSpark3_3_0: Boolean = getSparkVersion >= "3.3.0"
Review Comment:
Correct, I'll remove that
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1193412308
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1185121021
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186439990
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186618741
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/5943#issuecomment-1183865673
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1186424975
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r925173896
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/BaseFileOnlyRelation.scala:
##########
@@ -91,7 +93,10 @@ class BaseFileOnlyRelation(sqlContext: SQLContext,
hadoopConf = HoodieDataSourceHelper.getConfigurationWithInternalSchema(new Configuration(conf), requiredSchema.internalSchema, metaClient.getBasePath, validCommits)
)
- new HoodieFileScanRDD(sparkSession, baseFileReader, fileSplits)
+ // SPARK-37273 FileScanRDD constructor changed in SPARK 3.3
+ // TODO: Critical change introduced in Spark 3.3, need to test manually
+ sparkAdapter.createHoodieFileScanRDD(sparkSession, baseFileReader, fileSplits.map(_.filePartition), requiredSchema.structTypeSchema)
+ .asInstanceOf[HoodieUnsafeRDD]
Review Comment:
FileScanRDD API changed: [SPARK-37273](https://github.com/apache/spark/pull/34575) have to split `HoodieFileScanRDD` for different spark versions
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/hudi/pull/5943#issuecomment-1192092007
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191939855
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[GitHub] [hudi] CTTY commented on a diff in pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
CTTY commented on code in PR #5943:
URL: https://github.com/apache/hudi/pull/5943#discussion_r926134427
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/HoodieSparkSqlTestBase.scala:
##########
@@ -140,8 +140,11 @@ class HoodieSparkSqlTestBase extends FunSuite with BeforeAndAfterAll {
spark.sql(sql)
} catch {
case e: Throwable =>
- assertResult(true)(e.getMessage.contains(errorMsg))
- hasException = true
+ if (e.getMessage.contains(errorMsg)) {
Review Comment:
It makes the unit test eaiser to debug. I was seeing some issues with unittests but previous code only gives out limited info
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[GitHub] [hudi] hudi-bot commented on pull request #5943: [HUDI-4186] Support Hudi with Spark 3.3.0
Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #5943:
URL: https://github.com/apache/hudi/pull/5943#issuecomment-1191880923
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