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Posted to commits@hudi.apache.org by GitBox <gi...@apache.org> on 2020/07/21 07:07:52 UTC
[GitHub] [hudi] vinothchandar commented on a change in pull request #1848: [HUDI-69] Support Spark Datasource for MOR table - RDD approach
vinothchandar commented on a change in pull request #1848:
URL: https://github.com/apache/hudi/pull/1848#discussion_r457864770
##########
File path: hudi-hadoop-mr/src/main/java/org/apache/hudi/hadoop/utils/HoodieRealtimeRecordReaderUtils.java
##########
@@ -69,6 +71,17 @@ public static Schema readSchema(Configuration conf, Path filePath) {
}
}
+ /**
+ * get the max compaction memory in bytes from JobConf.
+ */
+ public static long getMaxCompactionMemoryInBytes(JobConf jobConf) {
Review comment:
ah ok. its just relocated
##########
File path: hudi-hadoop-mr/src/main/java/org/apache/hudi/hadoop/realtime/AbstractRealtimeRecordReader.java
##########
@@ -147,12 +146,4 @@ public Schema getWriterSchema() {
public Schema getHiveSchema() {
return hiveSchema;
}
-
- public long getMaxCompactionMemoryInBytes() {
Review comment:
why remove this?
##########
File path: hudi-hadoop-mr/src/main/java/org/apache/hudi/hadoop/realtime/RealtimeCompactedRecordReader.java
##########
@@ -40,6 +40,8 @@
import java.io.IOException;
import java.util.Map;
+import static org.apache.hudi.hadoop.utils.HoodieRealtimeRecordReaderUtils.getMaxCompactionMemoryInBytes;
Review comment:
seems good to avoid the static import here and have the reader realize the class its coming from ?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.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.hudi
+
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig}
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS
+
+import org.apache.avro.Schema
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition
Review comment:
lets name the classes `HoodieMergeOn...` not `Hudi..` to be consistent with rest of the code.
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/SnapshotRelation.scala
##########
@@ -0,0 +1,113 @@
+/*
+ * 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.avro.HoodieAvroUtils
+import org.apache.hudi.common.model.HoodieBaseFile
+import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver}
+import org.apache.hudi.common.table.view.HoodieTableFileSystemView
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.utils.HoodieRealtimeInputFormatUtils
+import org.apache.hudi.hadoop.utils.HoodieRealtimeRecordReaderUtils.getMaxCompactionMemoryInBytes
+
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.mapred.JobConf
+import org.apache.spark.internal.Logging
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
+import org.apache.spark.sql.{Row, SQLContext}
+import org.apache.spark.sql.sources.{BaseRelation, TableScan}
+import org.apache.spark.sql.types.StructType
+
+import scala.collection.JavaConverters._
+
+case class HudiMergeOnReadFileSplit(dataFile: PartitionedFile,
+ logPaths: Option[List[String]],
+ latestCommit: String,
+ tablePath: String,
+ maxCompactionMemoryInBytes: Long,
+ skipMerge: Boolean)
+
+class SnapshotRelation (val sqlContext: SQLContext,
+ val optParams: Map[String, String],
+ val userSchema: StructType,
+ val globPaths: Seq[Path],
+ val metaClient: HoodieTableMetaClient)
+ extends BaseRelation with TableScan with Logging{
Review comment:
nit: space after Logging? `Logging {` ?
##########
File path: hudi-hadoop-mr/src/main/java/org/apache/hudi/hadoop/config/HadoopSerializableConfiguration.java
##########
@@ -0,0 +1,43 @@
+/*
+ * 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.hadoop.config;
+
+import org.apache.hadoop.conf.Configuration;
+
+import java.io.IOException;
+import java.io.ObjectInputStream;
+import java.io.ObjectOutputStream;
+import java.io.Serializable;
+
+public class HadoopSerializableConfiguration implements Serializable {
Review comment:
hows this different from the class we already have in `hudi-common` : `SerializableConfiguration` ?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/DataSourceOptions.scala
##########
@@ -110,6 +112,10 @@ object DataSourceReadOptions {
*/
val INCR_PATH_GLOB_OPT_KEY = "hoodie.datasource.read.incr.path.glob"
val DEFAULT_INCR_PATH_GLOB_OPT_VAL = ""
+
+
+ val REALTIME_SKIP_MERGE_KEY = REALTIME_SKIP_MERGE_PROP
Review comment:
should we just make a new datasource level config for this. and translate. mixing raw InputFormat level configs here, feels a bit problematic in terms of long term maitenance>
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/SnapshotRelation.scala
##########
@@ -0,0 +1,113 @@
+/*
+ * 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.avro.HoodieAvroUtils
+import org.apache.hudi.common.model.HoodieBaseFile
+import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver}
+import org.apache.hudi.common.table.view.HoodieTableFileSystemView
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.utils.HoodieRealtimeInputFormatUtils
+import org.apache.hudi.hadoop.utils.HoodieRealtimeRecordReaderUtils.getMaxCompactionMemoryInBytes
+
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.mapred.JobConf
+import org.apache.spark.internal.Logging
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
+import org.apache.spark.sql.{Row, SQLContext}
+import org.apache.spark.sql.sources.{BaseRelation, TableScan}
+import org.apache.spark.sql.types.StructType
+
+import scala.collection.JavaConverters._
+
+case class HudiMergeOnReadFileSplit(dataFile: PartitionedFile,
+ logPaths: Option[List[String]],
+ latestCommit: String,
+ tablePath: String,
+ maxCompactionMemoryInBytes: Long,
+ skipMerge: Boolean)
+
+class SnapshotRelation (val sqlContext: SQLContext,
+ val optParams: Map[String, String],
+ val userSchema: StructType,
+ val globPaths: Seq[Path],
+ val metaClient: HoodieTableMetaClient)
+ extends BaseRelation with TableScan with Logging{
+
+ private val conf = sqlContext.sparkContext.hadoopConfiguration
+
+ // use schema from latest metadata, if not present, read schema from the data file
+ private val latestSchema = {
+ val schemaUtil = new TableSchemaResolver(metaClient)
+ val tableSchema = HoodieAvroUtils.createHoodieWriteSchema(schemaUtil.getTableAvroSchemaWithoutMetadataFields)
+ AvroConversionUtils.convertAvroSchemaToStructType(tableSchema)
+ }
+
+ private val skipMerge = optParams.getOrElse(
+ DataSourceReadOptions.REALTIME_SKIP_MERGE_KEY,
+ DataSourceReadOptions.DEFAULT_REALTIME_SKIP_MERGE_VAL).toBoolean
+ private val maxCompactionMemoryInBytes = getMaxCompactionMemoryInBytes(new JobConf(conf))
+ private val fileIndex = buildFileIndex()
+
+ override def schema: StructType = latestSchema
+
+ override def needConversion: Boolean = false
+
+ override def buildScan(): RDD[Row] = {
+ val parquetReaderFunction = new ParquetFileFormat().buildReaderWithPartitionValues(
Review comment:
from the last PR, it seems the biggest change is calling `ParquetFileFormat()`. and the wrapping as opposed to inheriting the code. Would life be lot simpler if we still defined our own FileFormat and then wrapped `ParquetFileFormat` and the code you have to read logs as `Iterator<InternalRow>` ? Just a thought. https://github.com/apache/spark/blob/8c7d6f9733751503f80d5a1b2463904dfefd6843/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormat.scala#L105
What you are doing is probably valid and makes it consistent with how @umehrot2 is also approaching it. if they are equivalent, then I am fine with it.
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/DefaultSource.scala
##########
@@ -123,4 +120,25 @@ class DefaultSource extends RelationProvider
}
override def shortName(): String = "hudi"
+
+ private def getReadOptimizedView(sqlContext: SQLContext,
Review comment:
rename: getBaseFileOnlyView()
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.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.hudi
+
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig}
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS
+
+import org.apache.avro.Schema
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition
+
+class HudiMergeOnReadRDD(sc: SparkContext,
+ broadcastedConf: Broadcast[HadoopSerializableConfiguration],
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit])
+ extends RDD[InternalRow](sc, Nil) {
+
+ // Broadcast the hadoop Configuration to executors.
+ def this(sc: SparkContext,
+ config: Configuration,
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit]) = {
+ this(
+ sc,
+ sc.broadcast(new HadoopSerializableConfiguration(config))
+ .asInstanceOf[Broadcast[HadoopSerializableConfiguration]],
+ dataReadFunction,
+ dataSchema,
+ hudiRealtimeFileSplits)
+ }
+
+ override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = {
+ val mergeParquetPartition = split.asInstanceOf[HudiMergeOnReadPartition]
+ mergeParquetPartition.split match {
+ case dataFileOnlySplit if dataFileOnlySplit.logPaths.isEmpty =>
+ read(mergeParquetPartition.split.dataFile, dataReadFunction)
+ case unMergeSplit if unMergeSplit.skipMerge =>
+ unMergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case mergeSplit if !mergeSplit.skipMerge =>
+ mergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case _ => throw new HoodieException("Unable to select an Iterator to read the Hudi MOR File Split")
+ }
+ }
+
+ override protected def getPartitions: Array[Partition] = {
+ hudiRealtimeFileSplits.zipWithIndex.map(file => HudiMergeOnReadPartition(file._2, file._1)).toArray
+ }
+
+ private def getConfig(): Configuration = {
+ broadcastedConf.value.config
+ }
+
+ private def read(partitionedFile: PartitionedFile,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] = {
+ val fileIterator = readFileFunction(partitionedFile)
+ val rows = fileIterator.flatMap(_ match {
+ case r: InternalRow => Seq(r)
+ case b: ColumnarBatch => b.rowIterator().asScala
+ })
+ rows
+ }
+
+ private def unMergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var hudiLogRecordsIterator = hudiLogRecords.keySet().iterator().asScala
+
+ override def hasNext: Boolean = {
+ dataFileIterator.hasNext || hudiLogRecordsIterator.hasNext
+ }
+
+ override def next(): InternalRow = {
+ if (dataFileIterator.hasNext) {
+ dataFileIterator.next()
+ } else {
+ val curAvrokey = hudiLogRecordsIterator.next()
+ val curAvroRecord = hudiLogRecords.get(curAvrokey).getData.getInsertValue(logSchema).get()
+ converter.deserialize(curAvroRecord).asInstanceOf[InternalRow]
+ }
+ }
+ }
+
+ private def mergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var parquetFinished = false
+ private var logRecordToRead = hudiLogRecords.keySet()
+ private var hudiLogRecordsIterator: Iterator[String] = _
+
+ override def hasNext: Boolean = {
+ if (dataFileIterator.hasNext) {
+ true
+ } else {
+ if (!parquetFinished) {
+ parquetFinished = true
+ hudiLogRecordsIterator = logRecordToRead.iterator().asScala
+ }
+ hudiLogRecordsIterator.hasNext
+ }
+ }
+
+ override def next(): InternalRow = {
+ if (dataFileIterator.hasNext) {
+ val curRow = dataFileIterator.next()
+ val curKey = curRow.getString(HOODIE_RECORD_KEY_COL_POS)
+ if (hudiLogRecords.keySet().contains(curKey)) {
+ logRecordToRead.remove(curKey)
Review comment:
is the remove needed. this map is often spillable.. we should just make sure the remove does not incur additional I/O or soemethng
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.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.hudi
+
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig}
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS
+
+import org.apache.avro.Schema
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition
+
+class HudiMergeOnReadRDD(sc: SparkContext,
+ broadcastedConf: Broadcast[HadoopSerializableConfiguration],
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit])
+ extends RDD[InternalRow](sc, Nil) {
+
+ // Broadcast the hadoop Configuration to executors.
+ def this(sc: SparkContext,
+ config: Configuration,
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit]) = {
+ this(
+ sc,
+ sc.broadcast(new HadoopSerializableConfiguration(config))
+ .asInstanceOf[Broadcast[HadoopSerializableConfiguration]],
+ dataReadFunction,
+ dataSchema,
+ hudiRealtimeFileSplits)
+ }
+
+ override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = {
+ val mergeParquetPartition = split.asInstanceOf[HudiMergeOnReadPartition]
+ mergeParquetPartition.split match {
+ case dataFileOnlySplit if dataFileOnlySplit.logPaths.isEmpty =>
+ read(mergeParquetPartition.split.dataFile, dataReadFunction)
+ case unMergeSplit if unMergeSplit.skipMerge =>
+ unMergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case mergeSplit if !mergeSplit.skipMerge =>
+ mergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case _ => throw new HoodieException("Unable to select an Iterator to read the Hudi MOR File Split")
+ }
+ }
+
+ override protected def getPartitions: Array[Partition] = {
+ hudiRealtimeFileSplits.zipWithIndex.map(file => HudiMergeOnReadPartition(file._2, file._1)).toArray
+ }
+
+ private def getConfig(): Configuration = {
+ broadcastedConf.value.config
+ }
+
+ private def read(partitionedFile: PartitionedFile,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] = {
+ val fileIterator = readFileFunction(partitionedFile)
+ val rows = fileIterator.flatMap(_ match {
+ case r: InternalRow => Seq(r)
+ case b: ColumnarBatch => b.rowIterator().asScala
+ })
+ rows
+ }
+
+ private def unMergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var hudiLogRecordsIterator = hudiLogRecords.keySet().iterator().asScala
+
+ override def hasNext: Boolean = {
+ dataFileIterator.hasNext || hudiLogRecordsIterator.hasNext
+ }
+
+ override def next(): InternalRow = {
+ if (dataFileIterator.hasNext) {
+ dataFileIterator.next()
+ } else {
+ val curAvrokey = hudiLogRecordsIterator.next()
+ val curAvroRecord = hudiLogRecords.get(curAvrokey).getData.getInsertValue(logSchema).get()
+ converter.deserialize(curAvroRecord).asInstanceOf[InternalRow]
+ }
+ }
+ }
+
+ private def mergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var parquetFinished = false
+ private var logRecordToRead = hudiLogRecords.keySet()
+ private var hudiLogRecordsIterator: Iterator[String] = _
+
+ override def hasNext: Boolean = {
+ if (dataFileIterator.hasNext) {
+ true
+ } else {
+ if (!parquetFinished) {
Review comment:
lets not leak parquet in the naming within this class. we can keep it generic as base vs log files
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.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.hudi
+
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig}
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS
+
+import org.apache.avro.Schema
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition
+
+class HudiMergeOnReadRDD(sc: SparkContext,
+ broadcastedConf: Broadcast[HadoopSerializableConfiguration],
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit])
+ extends RDD[InternalRow](sc, Nil) {
+
+ // Broadcast the hadoop Configuration to executors.
+ def this(sc: SparkContext,
+ config: Configuration,
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit]) = {
+ this(
+ sc,
+ sc.broadcast(new HadoopSerializableConfiguration(config))
+ .asInstanceOf[Broadcast[HadoopSerializableConfiguration]],
+ dataReadFunction,
+ dataSchema,
+ hudiRealtimeFileSplits)
+ }
+
+ override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = {
+ val mergeParquetPartition = split.asInstanceOf[HudiMergeOnReadPartition]
+ mergeParquetPartition.split match {
+ case dataFileOnlySplit if dataFileOnlySplit.logPaths.isEmpty =>
+ read(mergeParquetPartition.split.dataFile, dataReadFunction)
+ case unMergeSplit if unMergeSplit.skipMerge =>
+ unMergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case mergeSplit if !mergeSplit.skipMerge =>
+ mergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case _ => throw new HoodieException("Unable to select an Iterator to read the Hudi MOR File Split")
+ }
+ }
+
+ override protected def getPartitions: Array[Partition] = {
+ hudiRealtimeFileSplits.zipWithIndex.map(file => HudiMergeOnReadPartition(file._2, file._1)).toArray
+ }
+
+ private def getConfig(): Configuration = {
+ broadcastedConf.value.config
+ }
+
+ private def read(partitionedFile: PartitionedFile,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] = {
+ val fileIterator = readFileFunction(partitionedFile)
+ val rows = fileIterator.flatMap(_ match {
+ case r: InternalRow => Seq(r)
+ case b: ColumnarBatch => b.rowIterator().asScala
+ })
+ rows
+ }
+
+ private def unMergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var hudiLogRecordsIterator = hudiLogRecords.keySet().iterator().asScala
+
+ override def hasNext: Boolean = {
+ dataFileIterator.hasNext || hudiLogRecordsIterator.hasNext
+ }
+
+ override def next(): InternalRow = {
+ if (dataFileIterator.hasNext) {
+ dataFileIterator.next()
+ } else {
+ val curAvrokey = hudiLogRecordsIterator.next()
+ val curAvroRecord = hudiLogRecords.get(curAvrokey).getData.getInsertValue(logSchema).get()
+ converter.deserialize(curAvroRecord).asInstanceOf[InternalRow]
+ }
+ }
+ }
+
+ private def mergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var parquetFinished = false
+ private var logRecordToRead = hudiLogRecords.keySet()
+ private var hudiLogRecordsIterator: Iterator[String] = _
+
+ override def hasNext: Boolean = {
+ if (dataFileIterator.hasNext) {
+ true
+ } else {
+ if (!parquetFinished) {
+ parquetFinished = true
+ hudiLogRecordsIterator = logRecordToRead.iterator().asScala
+ }
+ hudiLogRecordsIterator.hasNext
+ }
+ }
+
+ override def next(): InternalRow = {
+ if (dataFileIterator.hasNext) {
+ val curRow = dataFileIterator.next()
+ val curKey = curRow.getString(HOODIE_RECORD_KEY_COL_POS)
+ if (hudiLogRecords.keySet().contains(curKey)) {
+ logRecordToRead.remove(curKey)
+ mergeRowWithLog(curRow)
+ } else {
+ curRow
+ }
+ } else {
+ val curKey = hudiLogRecordsIterator.next()
Review comment:
same comment here about double checking if this is actually ok
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/SnapshotRelation.scala
##########
@@ -0,0 +1,113 @@
+/*
+ * 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.avro.HoodieAvroUtils
+import org.apache.hudi.common.model.HoodieBaseFile
+import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver}
+import org.apache.hudi.common.table.view.HoodieTableFileSystemView
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.utils.HoodieRealtimeInputFormatUtils
+import org.apache.hudi.hadoop.utils.HoodieRealtimeRecordReaderUtils.getMaxCompactionMemoryInBytes
+
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.mapred.JobConf
+import org.apache.spark.internal.Logging
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
+import org.apache.spark.sql.{Row, SQLContext}
+import org.apache.spark.sql.sources.{BaseRelation, TableScan}
+import org.apache.spark.sql.types.StructType
+
+import scala.collection.JavaConverters._
+
+case class HudiMergeOnReadFileSplit(dataFile: PartitionedFile,
+ logPaths: Option[List[String]],
+ latestCommit: String,
+ tablePath: String,
+ maxCompactionMemoryInBytes: Long,
+ skipMerge: Boolean)
+
+class SnapshotRelation (val sqlContext: SQLContext,
+ val optParams: Map[String, String],
+ val userSchema: StructType,
+ val globPaths: Seq[Path],
+ val metaClient: HoodieTableMetaClient)
+ extends BaseRelation with TableScan with Logging{
+
+ private val conf = sqlContext.sparkContext.hadoopConfiguration
+
+ // use schema from latest metadata, if not present, read schema from the data file
+ private val latestSchema = {
+ val schemaUtil = new TableSchemaResolver(metaClient)
+ val tableSchema = HoodieAvroUtils.createHoodieWriteSchema(schemaUtil.getTableAvroSchemaWithoutMetadataFields)
+ AvroConversionUtils.convertAvroSchemaToStructType(tableSchema)
+ }
+
+ private val skipMerge = optParams.getOrElse(
+ DataSourceReadOptions.REALTIME_SKIP_MERGE_KEY,
+ DataSourceReadOptions.DEFAULT_REALTIME_SKIP_MERGE_VAL).toBoolean
+ private val maxCompactionMemoryInBytes = getMaxCompactionMemoryInBytes(new JobConf(conf))
+ private val fileIndex = buildFileIndex()
+
+ override def schema: StructType = latestSchema
+
+ override def needConversion: Boolean = false
+
+ override def buildScan(): RDD[Row] = {
+ val parquetReaderFunction = new ParquetFileFormat().buildReaderWithPartitionValues(
+ sparkSession = sqlContext.sparkSession,
+ dataSchema = latestSchema,
+ partitionSchema = StructType(Nil),
+ requiredSchema = latestSchema,
Review comment:
would n't this read all the fields out? should we not pass `userSchema` here?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/SnapshotRelation.scala
##########
@@ -0,0 +1,113 @@
+/*
+ * 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.avro.HoodieAvroUtils
+import org.apache.hudi.common.model.HoodieBaseFile
+import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver}
+import org.apache.hudi.common.table.view.HoodieTableFileSystemView
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.utils.HoodieRealtimeInputFormatUtils
+import org.apache.hudi.hadoop.utils.HoodieRealtimeRecordReaderUtils.getMaxCompactionMemoryInBytes
+
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.mapred.JobConf
+import org.apache.spark.internal.Logging
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
+import org.apache.spark.sql.{Row, SQLContext}
+import org.apache.spark.sql.sources.{BaseRelation, TableScan}
+import org.apache.spark.sql.types.StructType
+
+import scala.collection.JavaConverters._
+
+case class HudiMergeOnReadFileSplit(dataFile: PartitionedFile,
+ logPaths: Option[List[String]],
+ latestCommit: String,
+ tablePath: String,
+ maxCompactionMemoryInBytes: Long,
+ skipMerge: Boolean)
+
+class SnapshotRelation (val sqlContext: SQLContext,
+ val optParams: Map[String, String],
+ val userSchema: StructType,
+ val globPaths: Seq[Path],
+ val metaClient: HoodieTableMetaClient)
+ extends BaseRelation with TableScan with Logging{
Review comment:
can we file a JIRA for this. and is it possible to target this for 0.6.0 as well?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.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.hudi
+
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig}
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS
+
+import org.apache.avro.Schema
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition
+
+class HudiMergeOnReadRDD(sc: SparkContext,
+ broadcastedConf: Broadcast[HadoopSerializableConfiguration],
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit])
+ extends RDD[InternalRow](sc, Nil) {
+
+ // Broadcast the hadoop Configuration to executors.
+ def this(sc: SparkContext,
+ config: Configuration,
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit]) = {
+ this(
+ sc,
+ sc.broadcast(new HadoopSerializableConfiguration(config))
+ .asInstanceOf[Broadcast[HadoopSerializableConfiguration]],
+ dataReadFunction,
+ dataSchema,
+ hudiRealtimeFileSplits)
+ }
+
+ override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = {
+ val mergeParquetPartition = split.asInstanceOf[HudiMergeOnReadPartition]
+ mergeParquetPartition.split match {
+ case dataFileOnlySplit if dataFileOnlySplit.logPaths.isEmpty =>
+ read(mergeParquetPartition.split.dataFile, dataReadFunction)
+ case unMergeSplit if unMergeSplit.skipMerge =>
+ unMergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case mergeSplit if !mergeSplit.skipMerge =>
+ mergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case _ => throw new HoodieException("Unable to select an Iterator to read the Hudi MOR File Split")
+ }
+ }
+
+ override protected def getPartitions: Array[Partition] = {
+ hudiRealtimeFileSplits.zipWithIndex.map(file => HudiMergeOnReadPartition(file._2, file._1)).toArray
+ }
+
+ private def getConfig(): Configuration = {
+ broadcastedConf.value.config
+ }
+
+ private def read(partitionedFile: PartitionedFile,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] = {
+ val fileIterator = readFileFunction(partitionedFile)
+ val rows = fileIterator.flatMap(_ match {
+ case r: InternalRow => Seq(r)
+ case b: ColumnarBatch => b.rowIterator().asScala
+ })
+ rows
+ }
+
+ private def unMergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var hudiLogRecordsIterator = hudiLogRecords.keySet().iterator().asScala
+
+ override def hasNext: Boolean = {
+ dataFileIterator.hasNext || hudiLogRecordsIterator.hasNext
+ }
+
+ override def next(): InternalRow = {
+ if (dataFileIterator.hasNext) {
+ dataFileIterator.next()
+ } else {
+ val curAvrokey = hudiLogRecordsIterator.next()
+ val curAvroRecord = hudiLogRecords.get(curAvrokey).getData.getInsertValue(logSchema).get()
+ converter.deserialize(curAvroRecord).asInstanceOf[InternalRow]
+ }
+ }
+ }
+
+ private def mergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var parquetFinished = false
+ private var logRecordToRead = hudiLogRecords.keySet()
+ private var hudiLogRecordsIterator: Iterator[String] = _
+
+ override def hasNext: Boolean = {
+ if (dataFileIterator.hasNext) {
+ true
+ } else {
+ if (!parquetFinished) {
+ parquetFinished = true
+ hudiLogRecordsIterator = logRecordToRead.iterator().asScala
+ }
+ hudiLogRecordsIterator.hasNext
+ }
+ }
+
+ override def next(): InternalRow = {
+ if (dataFileIterator.hasNext) {
+ val curRow = dataFileIterator.next()
+ val curKey = curRow.getString(HOODIE_RECORD_KEY_COL_POS)
+ if (hudiLogRecords.keySet().contains(curKey)) {
Review comment:
why not `containsKey`. `keySet()` may create a copy?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.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.hudi
+
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig}
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS
+
+import org.apache.avro.Schema
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition
+
+class HudiMergeOnReadRDD(sc: SparkContext,
+ broadcastedConf: Broadcast[HadoopSerializableConfiguration],
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit])
+ extends RDD[InternalRow](sc, Nil) {
+
+ // Broadcast the hadoop Configuration to executors.
+ def this(sc: SparkContext,
+ config: Configuration,
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit]) = {
+ this(
+ sc,
+ sc.broadcast(new HadoopSerializableConfiguration(config))
+ .asInstanceOf[Broadcast[HadoopSerializableConfiguration]],
+ dataReadFunction,
+ dataSchema,
+ hudiRealtimeFileSplits)
+ }
+
+ override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = {
+ val mergeParquetPartition = split.asInstanceOf[HudiMergeOnReadPartition]
+ mergeParquetPartition.split match {
+ case dataFileOnlySplit if dataFileOnlySplit.logPaths.isEmpty =>
+ read(mergeParquetPartition.split.dataFile, dataReadFunction)
+ case unMergeSplit if unMergeSplit.skipMerge =>
+ unMergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case mergeSplit if !mergeSplit.skipMerge =>
+ mergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case _ => throw new HoodieException("Unable to select an Iterator to read the Hudi MOR File Split")
+ }
+ }
+
+ override protected def getPartitions: Array[Partition] = {
+ hudiRealtimeFileSplits.zipWithIndex.map(file => HudiMergeOnReadPartition(file._2, file._1)).toArray
+ }
+
+ private def getConfig(): Configuration = {
+ broadcastedConf.value.config
+ }
+
+ private def read(partitionedFile: PartitionedFile,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] = {
+ val fileIterator = readFileFunction(partitionedFile)
+ val rows = fileIterator.flatMap(_ match {
+ case r: InternalRow => Seq(r)
+ case b: ColumnarBatch => b.rowIterator().asScala
+ })
+ rows
+ }
+
+ private def unMergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var hudiLogRecordsIterator = hudiLogRecords.keySet().iterator().asScala
+
+ override def hasNext: Boolean = {
+ dataFileIterator.hasNext || hudiLogRecordsIterator.hasNext
+ }
+
+ override def next(): InternalRow = {
+ if (dataFileIterator.hasNext) {
+ dataFileIterator.next()
+ } else {
+ val curAvrokey = hudiLogRecordsIterator.next()
+ val curAvroRecord = hudiLogRecords.get(curAvrokey).getData.getInsertValue(logSchema).get()
+ converter.deserialize(curAvroRecord).asInstanceOf[InternalRow]
+ }
+ }
+ }
+
+ private def mergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var parquetFinished = false
+ private var logRecordToRead = hudiLogRecords.keySet()
+ private var hudiLogRecordsIterator: Iterator[String] = _
+
+ override def hasNext: Boolean = {
+ if (dataFileIterator.hasNext) {
+ true
+ } else {
+ if (!parquetFinished) {
+ parquetFinished = true
+ hudiLogRecordsIterator = logRecordToRead.iterator().asScala
+ }
+ hudiLogRecordsIterator.hasNext
Review comment:
this seems to indicate that we will keep scanning the remaining entries in the log and hand them out if `dataFileIterator` runs out. We need to be careful about how it interplays with split generation. specifically, only works if the each base file has only 1 split..
```
HudiMergeOnReadFileSplit(partitionedFile, logPaths, latestCommit,
metaClient.getBasePath, maxCompactionMemoryInBytes, skipMerge)
```
here `partitionedFile` has to be a single file and not an input Split. otherwise we will face an issue that the log entry belongs to a different split and the ultimate query will have duplicates.
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.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.hudi
+
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig}
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS
+
+import org.apache.avro.Schema
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition
+
+class HudiMergeOnReadRDD(sc: SparkContext,
+ broadcastedConf: Broadcast[HadoopSerializableConfiguration],
+ dataReadFunction: PartitionedFile => Iterator[Any],
Review comment:
rename `baseFileReadFunction`
##########
File path: hudi-spark/src/test/scala/org/apache/hudi/functional/TestCOWDataSource.scala
##########
@@ -67,7 +68,7 @@ class TestDataSource {
// Insert Operation
val records = DataSourceTestUtils.convertToStringList(dataGen.generateInserts("000", 100)).toList
val inputDF: Dataset[Row] = spark.read.json(spark.sparkContext.parallelize(records, 2))
- inputDF.write.format("hudi")
+ inputDF.write.format("org.apache.hudi")
Review comment:
why change this?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/SnapshotRelation.scala
##########
@@ -0,0 +1,113 @@
+/*
+ * 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.avro.HoodieAvroUtils
+import org.apache.hudi.common.model.HoodieBaseFile
+import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver}
+import org.apache.hudi.common.table.view.HoodieTableFileSystemView
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.utils.HoodieRealtimeInputFormatUtils
+import org.apache.hudi.hadoop.utils.HoodieRealtimeRecordReaderUtils.getMaxCompactionMemoryInBytes
+
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.mapred.JobConf
+import org.apache.spark.internal.Logging
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
+import org.apache.spark.sql.{Row, SQLContext}
+import org.apache.spark.sql.sources.{BaseRelation, TableScan}
+import org.apache.spark.sql.types.StructType
+
+import scala.collection.JavaConverters._
+
+case class HudiMergeOnReadFileSplit(dataFile: PartitionedFile,
+ logPaths: Option[List[String]],
+ latestCommit: String,
+ tablePath: String,
+ maxCompactionMemoryInBytes: Long,
+ skipMerge: Boolean)
+
+class SnapshotRelation (val sqlContext: SQLContext,
+ val optParams: Map[String, String],
+ val userSchema: StructType,
+ val globPaths: Seq[Path],
+ val metaClient: HoodieTableMetaClient)
+ extends BaseRelation with TableScan with Logging{
+
+ private val conf = sqlContext.sparkContext.hadoopConfiguration
+
+ // use schema from latest metadata, if not present, read schema from the data file
+ private val latestSchema = {
+ val schemaUtil = new TableSchemaResolver(metaClient)
+ val tableSchema = HoodieAvroUtils.createHoodieWriteSchema(schemaUtil.getTableAvroSchemaWithoutMetadataFields)
+ AvroConversionUtils.convertAvroSchemaToStructType(tableSchema)
+ }
+
+ private val skipMerge = optParams.getOrElse(
+ DataSourceReadOptions.REALTIME_SKIP_MERGE_KEY,
+ DataSourceReadOptions.DEFAULT_REALTIME_SKIP_MERGE_VAL).toBoolean
+ private val maxCompactionMemoryInBytes = getMaxCompactionMemoryInBytes(new JobConf(conf))
+ private val fileIndex = buildFileIndex()
+
+ override def schema: StructType = latestSchema
+
+ override def needConversion: Boolean = false
+
+ override def buildScan(): RDD[Row] = {
+ val parquetReaderFunction = new ParquetFileFormat().buildReaderWithPartitionValues(
+ sparkSession = sqlContext.sparkSession,
+ dataSchema = latestSchema,
+ partitionSchema = StructType(Nil),
+ requiredSchema = latestSchema,
+ filters = Seq.empty,
Review comment:
if we did `PrunedFilteredScan` we can also pass in teh filters? in any case, can we pass in the the options?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.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.hudi
+
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig}
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS
+
+import org.apache.avro.Schema
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition
+
+class HudiMergeOnReadRDD(sc: SparkContext,
+ broadcastedConf: Broadcast[HadoopSerializableConfiguration],
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit])
Review comment:
hudi vs hoodie
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/SnapshotRelation.scala
##########
@@ -0,0 +1,113 @@
+/*
+ * 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.avro.HoodieAvroUtils
+import org.apache.hudi.common.model.HoodieBaseFile
+import org.apache.hudi.common.table.{HoodieTableMetaClient, TableSchemaResolver}
+import org.apache.hudi.common.table.view.HoodieTableFileSystemView
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.utils.HoodieRealtimeInputFormatUtils
+import org.apache.hudi.hadoop.utils.HoodieRealtimeRecordReaderUtils.getMaxCompactionMemoryInBytes
+
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.mapred.JobConf
+import org.apache.spark.internal.Logging
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
+import org.apache.spark.sql.{Row, SQLContext}
+import org.apache.spark.sql.sources.{BaseRelation, TableScan}
+import org.apache.spark.sql.types.StructType
+
+import scala.collection.JavaConverters._
+
+case class HudiMergeOnReadFileSplit(dataFile: PartitionedFile,
+ logPaths: Option[List[String]],
+ latestCommit: String,
+ tablePath: String,
+ maxCompactionMemoryInBytes: Long,
+ skipMerge: Boolean)
+
+class SnapshotRelation (val sqlContext: SQLContext,
+ val optParams: Map[String, String],
+ val userSchema: StructType,
+ val globPaths: Seq[Path],
+ val metaClient: HoodieTableMetaClient)
+ extends BaseRelation with TableScan with Logging{
+
+ private val conf = sqlContext.sparkContext.hadoopConfiguration
+
+ // use schema from latest metadata, if not present, read schema from the data file
+ private val latestSchema = {
+ val schemaUtil = new TableSchemaResolver(metaClient)
+ val tableSchema = HoodieAvroUtils.createHoodieWriteSchema(schemaUtil.getTableAvroSchemaWithoutMetadataFields)
+ AvroConversionUtils.convertAvroSchemaToStructType(tableSchema)
+ }
+
+ private val skipMerge = optParams.getOrElse(
+ DataSourceReadOptions.REALTIME_SKIP_MERGE_KEY,
+ DataSourceReadOptions.DEFAULT_REALTIME_SKIP_MERGE_VAL).toBoolean
+ private val maxCompactionMemoryInBytes = getMaxCompactionMemoryInBytes(new JobConf(conf))
+ private val fileIndex = buildFileIndex()
+
+ override def schema: StructType = latestSchema
+
+ override def needConversion: Boolean = false
+
+ override def buildScan(): RDD[Row] = {
+ val parquetReaderFunction = new ParquetFileFormat().buildReaderWithPartitionValues(
+ sparkSession = sqlContext.sparkSession,
+ dataSchema = latestSchema,
+ partitionSchema = StructType(Nil),
+ requiredSchema = latestSchema,
+ filters = Seq.empty,
+ options = Map.empty,
+ hadoopConf = sqlContext.sparkSession.sessionState.newHadoopConf()
+ )
+ val rdd = new HudiMergeOnReadRDD(sqlContext.sparkContext,
+ sqlContext.sparkSession.sessionState.newHadoopConf(),
+ parquetReaderFunction, latestSchema, fileIndex)
+ rdd.asInstanceOf[RDD[Row]]
+ }
+
+ def buildFileIndex(): List[HudiMergeOnReadFileSplit] = {
+ val inMemoryFileIndex = HudiSparkUtils.createInMemoryFileIndex(sqlContext.sparkSession, globPaths)
+ val fileStatuses = inMemoryFileIndex.allFiles()
+ if (fileStatuses.isEmpty) {
+ throw new HoodieException("No files found for reading in user provided path.")
+ }
+
+ val fsView = new HoodieTableFileSystemView(metaClient,
+ metaClient.getActiveTimeline.getCommitsTimeline
+ .filterCompletedInstants, fileStatuses.toArray)
+ val latestFiles: List[HoodieBaseFile] = fsView.getLatestBaseFiles.iterator().asScala.toList
+ val latestCommit = fsView.getLastInstant.get().getTimestamp
+ val fileGroup = HoodieRealtimeInputFormatUtils.groupLogsByBaseFile(conf, latestFiles.asJava).asScala
+ val FileSplits = fileGroup.map(kv => {
Review comment:
rename variable using camel case?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.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.hudi
+
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig}
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS
+
+import org.apache.avro.Schema
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition
+
+class HudiMergeOnReadRDD(sc: SparkContext,
+ broadcastedConf: Broadcast[HadoopSerializableConfiguration],
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit])
+ extends RDD[InternalRow](sc, Nil) {
+
+ // Broadcast the hadoop Configuration to executors.
+ def this(sc: SparkContext,
+ config: Configuration,
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit]) = {
+ this(
+ sc,
+ sc.broadcast(new HadoopSerializableConfiguration(config))
+ .asInstanceOf[Broadcast[HadoopSerializableConfiguration]],
+ dataReadFunction,
+ dataSchema,
+ hudiRealtimeFileSplits)
+ }
+
+ override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = {
+ val mergeParquetPartition = split.asInstanceOf[HudiMergeOnReadPartition]
+ mergeParquetPartition.split match {
+ case dataFileOnlySplit if dataFileOnlySplit.logPaths.isEmpty =>
+ read(mergeParquetPartition.split.dataFile, dataReadFunction)
+ case unMergeSplit if unMergeSplit.skipMerge =>
+ unMergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case mergeSplit if !mergeSplit.skipMerge =>
+ mergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case _ => throw new HoodieException("Unable to select an Iterator to read the Hudi MOR File Split")
Review comment:
print the `mergeParquetPartition` split variable in the error message?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiMergeOnReadRDD.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.hudi
+
+import org.apache.hudi.common.fs.FSUtils
+import org.apache.hudi.common.table.log.{HoodieMergedLogRecordScanner, LogReaderUtils}
+import org.apache.hudi.exception.HoodieException
+import org.apache.hudi.hadoop.config.{HadoopSerializableConfiguration, HoodieRealtimeConfig}
+import org.apache.hudi.hadoop.utils.HoodieInputFormatUtils.HOODIE_RECORD_KEY_COL_POS
+
+import org.apache.avro.Schema
+import org.apache.hadoop.conf.Configuration
+import org.apache.spark.broadcast.Broadcast
+import org.apache.spark.{Partition, SparkContext, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.avro.{AvroDeserializer, SchemaConverters}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+import scala.collection.JavaConverters._
+import scala.util.Try
+
+case class HudiMergeOnReadPartition(index: Int, split: HudiMergeOnReadFileSplit) extends Partition
+
+class HudiMergeOnReadRDD(sc: SparkContext,
+ broadcastedConf: Broadcast[HadoopSerializableConfiguration],
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit])
+ extends RDD[InternalRow](sc, Nil) {
+
+ // Broadcast the hadoop Configuration to executors.
+ def this(sc: SparkContext,
+ config: Configuration,
+ dataReadFunction: PartitionedFile => Iterator[Any],
+ dataSchema: StructType,
+ hudiRealtimeFileSplits: List[HudiMergeOnReadFileSplit]) = {
+ this(
+ sc,
+ sc.broadcast(new HadoopSerializableConfiguration(config))
+ .asInstanceOf[Broadcast[HadoopSerializableConfiguration]],
+ dataReadFunction,
+ dataSchema,
+ hudiRealtimeFileSplits)
+ }
+
+ override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = {
+ val mergeParquetPartition = split.asInstanceOf[HudiMergeOnReadPartition]
+ mergeParquetPartition.split match {
+ case dataFileOnlySplit if dataFileOnlySplit.logPaths.isEmpty =>
+ read(mergeParquetPartition.split.dataFile, dataReadFunction)
+ case unMergeSplit if unMergeSplit.skipMerge =>
+ unMergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case mergeSplit if !mergeSplit.skipMerge =>
+ mergeFileIterator(mergeParquetPartition.split, dataReadFunction)
+ case _ => throw new HoodieException("Unable to select an Iterator to read the Hudi MOR File Split")
+ }
+ }
+
+ override protected def getPartitions: Array[Partition] = {
+ hudiRealtimeFileSplits.zipWithIndex.map(file => HudiMergeOnReadPartition(file._2, file._1)).toArray
+ }
+
+ private def getConfig(): Configuration = {
+ broadcastedConf.value.config
+ }
+
+ private def read(partitionedFile: PartitionedFile,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] = {
+ val fileIterator = readFileFunction(partitionedFile)
+ val rows = fileIterator.flatMap(_ match {
+ case r: InternalRow => Seq(r)
+ case b: ColumnarBatch => b.rowIterator().asScala
+ })
+ rows
+ }
+
+ private def unMergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var hudiLogRecordsIterator = hudiLogRecords.keySet().iterator().asScala
+
+ override def hasNext: Boolean = {
+ dataFileIterator.hasNext || hudiLogRecordsIterator.hasNext
+ }
+
+ override def next(): InternalRow = {
+ if (dataFileIterator.hasNext) {
+ dataFileIterator.next()
+ } else {
+ val curAvrokey = hudiLogRecordsIterator.next()
+ val curAvroRecord = hudiLogRecords.get(curAvrokey).getData.getInsertValue(logSchema).get()
+ converter.deserialize(curAvroRecord).asInstanceOf[InternalRow]
+ }
+ }
+ }
+
+ private def mergeFileIterator(split: HudiMergeOnReadFileSplit,
+ readFileFunction: PartitionedFile => Iterator[Any]): Iterator[InternalRow] =
+ new Iterator[InternalRow] {
+ private val dataFileIterator = read(split.dataFile, readFileFunction)
+ private val logSchema = getLogAvroSchema(split)
+ private val sparkTypes = SchemaConverters.toSqlType(logSchema).dataType.asInstanceOf[StructType]
+ private val converter = new AvroDeserializer(logSchema, sparkTypes)
+ private val hudiLogRecords = scanLog(split, logSchema).getRecords
+ private var parquetFinished = false
+ private var logRecordToRead = hudiLogRecords.keySet()
+ private var hudiLogRecordsIterator: Iterator[String] = _
+
+ override def hasNext: Boolean = {
+ if (dataFileIterator.hasNext) {
+ true
+ } else {
+ if (!parquetFinished) {
+ parquetFinished = true
+ hudiLogRecordsIterator = logRecordToRead.iterator().asScala
+ }
+ hudiLogRecordsIterator.hasNext
+ }
+ }
+
+ override def next(): InternalRow = {
+ if (dataFileIterator.hasNext) {
+ val curRow = dataFileIterator.next()
+ val curKey = curRow.getString(HOODIE_RECORD_KEY_COL_POS)
+ if (hudiLogRecords.keySet().contains(curKey)) {
+ logRecordToRead.remove(curKey)
+ mergeRowWithLog(curRow)
+ } else {
+ curRow
+ }
+ } else {
+ val curKey = hudiLogRecordsIterator.next()
+ getAvroRecord(curKey)
+ }
+ }
+
+ private def getAvroRecord(curKey: String): InternalRow = {
+ val curAvroRecord = hudiLogRecords.get(curKey).getData.getInsertValue(logSchema).get()
Review comment:
this implicitly assumes `OvewriteWithLatestPayload` ? can we just convert the parquet row as well to Avro and then perform the merge actually calling the right API. `HoodieRecordPayload#combineAndGetUpdateValue()` ? This is a correctness issue we need to resolve in the PR..
ideally, adding a test case as well to go along with this would be good
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