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[GitHub] [spark] yaooqinn opened a new pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
yaooqinn opened a new pull request #33888:
URL: https://github.com/apache/spark/pull/33888
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Add a config spark.sql.parquet.columnIndexAccessÂ
When true, we access the parquet files by column index instead of catalyst schema mapping at the executor side.
This is useful when the parquet file meta is inconsistent with those in Metastore, e.g. creating a table with existing parquet files with column names renamed, the column names are changed by external systems.
By default, it is off
### Why are the changes needed?
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1. If you propose a new API, clarify the use case for a new API.
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better data accessibility
### Does this PR introduce _any_ user-facing change?
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NO
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newly added test
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[GitHub] [spark] SparkQA commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-937375741
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704922547
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
What's worse, turning off column pruning also changes the result, which definitely violates the principle (query optimization should not change result)
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r701638958
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetReadSupport.scala
##########
@@ -323,9 +327,20 @@ object ParquetReadSupport {
* @return A list of clipped [[GroupType]] fields, which can be empty.
*/
private def clipParquetGroupFields(
- parquetRecord: GroupType, structType: StructType, caseSensitive: Boolean): Seq[Type] = {
+ parquetRecord: GroupType,
+ structType: StructType,
+ caseSensitive: Boolean,
+ columnIndexAccess: Boolean): Seq[Type] = {
val toParquet = new SparkToParquetSchemaConverter(writeLegacyParquetFormat = false)
- if (caseSensitive) {
+ if (columnIndexAccess) {
+ structType.zipWithIndex.map { case (f, i) =>
+ if (i >= parquetRecord.getFieldCount) {
+ toParquet.convertField(f)
Review comment:
shouldn't we call `clipParquetType`?
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URL: https://github.com/apache/spark/pull/33888#issuecomment-910060552
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Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-910195556
**[Test build #142913 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/142913/testReport)** for PR 33888 at commit [`6467608`](https://github.com/apache/spark/commit/6467608133700c39f9dbfb64b52751675bc83e91).
* This patch **fails Spark unit tests**.
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* This patch adds no public classes.
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[GitHub] [spark] cloud-fan commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-912224992
@yaooqinn can you put more details in the PR description? Something like
1. What if the number of columns/inner fields does not match?
2. What if the types are not compatible?
3. What's the concrete use case that requires this feature?
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[GitHub] [spark] yaooqinn commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
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yaooqinn commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-912276639
retest this please
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SparkQA commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-937673661
**[Test build #143942 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143942/testReport)** for PR 33888 at commit [`b989aa3`](https://github.com/apache/spark/commit/b989aa3821dbaf6cacccde886ed1051068d43cf5).
* This patch passes all tests.
* This patch **does not merge cleanly**.
* This patch adds no public classes.
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704921288
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
I don't think that's how by-ordinal access should work. Let's say that the actual parquet schema is [a, b, c], and the catalyst schema is [x, y, z]. If a query reads column `y`, we should read column `b` from Parquet. It's very confusing to the users if `SELECT x`, `SELECT y` and `SELECT z` all return the same value, which is column `a` of the parquet file (assume all columns have the same type).
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[GitHub] [spark] yaooqinn commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-911145513
cc @cloud-fan @maropu
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r702049826
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetReadSupport.scala
##########
@@ -323,15 +344,27 @@ object ParquetReadSupport {
* @return A list of clipped [[GroupType]] fields, which can be empty.
*/
private def clipParquetGroupFields(
- parquetRecord: GroupType, structType: StructType, caseSensitive: Boolean): Seq[Type] = {
+ parquetRecord: GroupType,
+ structType: StructType,
+ caseSensitive: Boolean,
+ accessByColumnOrdinal: Boolean): Seq[Type] = {
val toParquet = new SparkToParquetSchemaConverter(writeLegacyParquetFormat = false)
- if (caseSensitive) {
+ if (accessByColumnOrdinal) {
+ structType.zipWithIndex.map { case (f, i) =>
+ if (i < parquetRecord.getFieldCount) {
+ clipParquetType(
+ parquetRecord.getType(i), f.dataType, caseSensitive, accessByColumnOrdinal)
+ } else {
+ toParquet.convertField(f)
+ }
+ }
+ } else if (caseSensitive) {
val caseSensitiveParquetFieldMap =
parquetRecord.getFields.asScala.map(f => f.getName -> f).toMap
structType.map { f =>
caseSensitiveParquetFieldMap
.get(f.name)
- .map(clipParquetType(_, f.dataType, caseSensitive))
+ .map(clipParquetType(_, f.dataType, caseSensitive, accessByColumnOrdinal))
Review comment:
both accessByColumnOrdinal or `false` are the same
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Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/33888#issuecomment-912203015
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704918391
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
in this test, the user and the parser side requests `b`, but at the execution side we follow `by-ordinal` rule to read the parquet file, so `a` is read actually. If `a` has the same data type, there will be side effects; otherwise, we fail like this test
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704916113
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
But the test here shows we can't, or did I miss something?
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[GitHub] [spark] sunchao commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
sunchao commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r702020262
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetReadSupport.scala
##########
@@ -323,15 +344,27 @@ object ParquetReadSupport {
* @return A list of clipped [[GroupType]] fields, which can be empty.
*/
private def clipParquetGroupFields(
- parquetRecord: GroupType, structType: StructType, caseSensitive: Boolean): Seq[Type] = {
+ parquetRecord: GroupType,
+ structType: StructType,
+ caseSensitive: Boolean,
+ accessByColumnOrdinal: Boolean): Seq[Type] = {
val toParquet = new SparkToParquetSchemaConverter(writeLegacyParquetFormat = false)
- if (caseSensitive) {
+ if (accessByColumnOrdinal) {
+ structType.zipWithIndex.map { case (f, i) =>
+ if (i < parquetRecord.getFieldCount) {
+ clipParquetType(
+ parquetRecord.getType(i), f.dataType, caseSensitive, accessByColumnOrdinal)
+ } else {
+ toParquet.convertField(f)
+ }
+ }
+ } else if (caseSensitive) {
val caseSensitiveParquetFieldMap =
parquetRecord.getFields.asScala.map(f => f.getName -> f).toMap
structType.map { f =>
caseSensitiveParquetFieldMap
.get(f.name)
- .map(clipParquetType(_, f.dataType, caseSensitive))
+ .map(clipParquetType(_, f.dataType, caseSensitive, accessByColumnOrdinal))
Review comment:
why do we need to pass down `accessByColumnOrdinal`? it is always false here right? also it seems we can't do this on nested columns?
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
##########
@@ -200,19 +200,28 @@ private[parquet] class ParquetRowConverter(
// Converters for each field.
private[this] val fieldConverters: Array[Converter with HasParentContainerUpdater] = {
- // (SPARK-31116) Use case insensitive map if spark.sql.caseSensitive is false
- // to prevent throwing IllegalArgumentException when searching catalyst type's field index
- val catalystFieldNameToIndex = if (SQLConf.get.caseSensitiveAnalysis) {
- catalystType.fieldNames.zipWithIndex.toMap
+ if (SQLConf.get.parquetAccessByIndex) {
+ // SPARK-36634: When access parquet file by the idx of columns, we can not ensure 2 types
+ // matched
+ parquetType.getFields.asScala.zip(catalystType).zipWithIndex.map {
Review comment:
what if `len(parquetType.getFields != len(catalystType)`? I think it's not always guaranteed because of `ParquetReadSupport.intersectParquetGroups`? e.g., some fields in catalyst requested schema do not appear in Parquet file schema?
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
##########
@@ -139,7 +139,8 @@ private[parquet] class ParquetRowConverter(
convertTz: Option[ZoneId],
datetimeRebaseMode: LegacyBehaviorPolicy.Value,
int96RebaseMode: LegacyBehaviorPolicy.Value,
- updater: ParentContainerUpdater)
+ updater: ParentContainerUpdater,
+ parquetAccessByOrdinal: Boolean)
Review comment:
nit: `parquetAccessByOrdinal` -> `accessByOrdinal`? parquet seems redundant in this context. Also please update the method comments with the new parameter.
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[GitHub] [spark] yaooqinn commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-912203937
> should this be a per-query option (data source options) or a session config?
It seems to be more ease-to-use in session conf
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r703341729
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
hmm, so this feature breaks column pruning. How useful is this feature then?
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[GitHub] [spark] cloud-fan commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-911740543
should this be a per-query option (data source options) or a session config?
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704921836
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
Think about a user running `SELECT x, y` and `SELECT y`, he/she will see the column `y` has different values in each run, which is kind of a correctness bug.
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[GitHub] [spark] SparkQA commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-912452999
**[Test build #142966 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/142966/testReport)** for PR 33888 at commit [`3177993`](https://github.com/apache/spark/commit/3177993234d669bcd35e45196e94dd6b30912ac6).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704914960
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
we can read `a`, `ab`, or `abc` by ordinal.
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704277499
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
Not 'all the columns' but the resolved project list zipped directly to the fields of parquet data files
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Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/33888#issuecomment-937610617
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704569159
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
I'm a bit confused. Say if a parquet file has 3 columns `a, b, c`. By-ordinal access only works if a query needs to read all the columns (no column pruning). Do I miss something?
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URL: https://github.com/apache/spark/pull/33888#issuecomment-912631178
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[GitHub] [spark] sunchao commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
sunchao commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r702038063
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
##########
@@ -200,19 +200,28 @@ private[parquet] class ParquetRowConverter(
// Converters for each field.
private[this] val fieldConverters: Array[Converter with HasParentContainerUpdater] = {
- // (SPARK-31116) Use case insensitive map if spark.sql.caseSensitive is false
- // to prevent throwing IllegalArgumentException when searching catalyst type's field index
- val catalystFieldNameToIndex = if (SQLConf.get.caseSensitiveAnalysis) {
- catalystType.fieldNames.zipWithIndex.toMap
+ if (SQLConf.get.parquetAccessByIndex) {
+ // SPARK-36634: When access parquet file by the idx of columns, we can not ensure 2 types
+ // matched
+ parquetType.getFields.asScala.zip(catalystType).zipWithIndex.map {
Review comment:
what if `len(parquetType.getFields != len(catalystType)`? I think it's not always guaranteed because of `ParquetReadSupport.intersectParquetGroups`? e.g., some fields in catalyst requested schema do not appear in Parquet file schema.
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704109578
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
Right now by-ordinal access only works if the query selects all the columns. Maybe the column pruning should pass "required column ordinals" to the parquet reader
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github-actions[bot] commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-1013986253
We're closing this PR because it hasn't been updated in a while. This isn't a judgement on the merit of the PR in any way. It's just a way of keeping the PR queue manageable.
If you'd like to revive this PR, please reopen it and ask a committer to remove the Stale tag!
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Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/33888#issuecomment-910381329
**[Test build #142921 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/142921/testReport)** for PR 33888 at commit [`3017e59`](https://github.com/apache/spark/commit/3017e59fee81ef7a3df9d656a0b34493577ff4e5).
* This patch **fails Spark unit tests**.
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r703342039
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
shall we turn off column pruning when access-by-ordinal is enabled?
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Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/33888#issuecomment-912318688
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r701773655
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetReadSupport.scala
##########
@@ -323,9 +327,20 @@ object ParquetReadSupport {
* @return A list of clipped [[GroupType]] fields, which can be empty.
*/
private def clipParquetGroupFields(
- parquetRecord: GroupType, structType: StructType, caseSensitive: Boolean): Seq[Type] = {
+ parquetRecord: GroupType,
+ structType: StructType,
+ caseSensitive: Boolean,
+ columnIndexAccess: Boolean): Seq[Type] = {
val toParquet = new SparkToParquetSchemaConverter(writeLegacyParquetFormat = false)
- if (caseSensitive) {
+ if (columnIndexAccess) {
+ structType.zipWithIndex.map { case (f, i) =>
+ if (i >= parquetRecord.getFieldCount) {
+ toParquet.convertField(f)
Review comment:
addressed, but shall be applied in `else` branch
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[GitHub] [spark] yaooqinn commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-912239963
> @yaooqinn can you put more details in the PR description? Something like
>
> 1. What if the number of columns/inner fields does not match?
> 2. What if the types are not compatible?
> 3. What's the concrete use case that requires this feature?
nice questions, updated accordingly
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704921836
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
Think about a user running `SELECT x, y` and `SELECT y`, he/she will see the column `y` has inconsistent values in each run, which is kind of a correctness bug.
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r703998755
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
I guess they are not conflicting. We are using idx-0 to get data from `file 1(my_id)` and `file 2(myid)` and feed it to my_name. Here the idx is not the final output set but the original input set of raw data
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[GitHub] [spark] SparkQA commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-937960914
**[Test build #143996 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143996/testReport)** for PR 33888 at commit [`b989aa3`](https://github.com/apache/spark/commit/b989aa3821dbaf6cacccde886ed1051068d43cf5).
* This patch **fails Spark unit tests**.
* This patch **does not merge cleanly**.
* This patch adds no public classes.
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[GitHub] [spark] sunchao commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
sunchao commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r700366823
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -903,6 +903,13 @@ object SQLConf {
.intConf
.createWithDefault(4096)
+ val PARQUET_COLUMN_INDEX_ACCESS = buildConf("spark.sql.parquet.columnIndexAccess")
Review comment:
Column index is a special feature in Parquet and this may cause confusion. How about `spark.sql.parquet.accessByIndex`?
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
##########
@@ -4223,6 +4223,52 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
checkAnswer(sql("""SELECT from_json(r'{"a": "\\"}', 'a string')"""), Row(Row("\\")))
checkAnswer(sql("""SELECT from_json(R'{"a": "\\"}', 'a string')"""), Row(Row("\\")))
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
Review comment:
We should test with both `spark.sql.parquet.enableVectorizedReader` enabled or disabled. I think it currently doesn't work for the latter.
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -903,6 +903,13 @@ object SQLConf {
.intConf
.createWithDefault(4096)
+ val PARQUET_COLUMN_INDEX_ACCESS = buildConf("spark.sql.parquet.columnIndexAccess")
+ .doc("When true, we access the parquet files by column index instead of catalyst schema" +
Review comment:
nit: parquet -> Parquet
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
##########
@@ -4223,6 +4223,52 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
checkAnswer(sql("""SELECT from_json(r'{"a": "\\"}', 'a string')"""), Row(Row("\\")))
checkAnswer(sql("""SELECT from_json(R'{"a": "\\"}', 'a string')"""), Row(Row("\\")))
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'kent'")
+ sql("insert into t2 select 2, 'yao'")
+ sql("insert into t2 select 3, 'kyuubi'")
Review comment:
nit: I'd suggest to use more neutral words here :)
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[GitHub] [spark] pan3793 commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
pan3793 commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r700930659
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -903,6 +903,13 @@ object SQLConf {
.intConf
.createWithDefault(4096)
+ val PARQUET_COLUMN_INDEX_ACCESS = buildConf("spark.sql.parquet.columnIndexAccess")
Review comment:
How about using `ordinal` instead of `index`?
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r701640693
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
##########
@@ -4223,6 +4223,55 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
checkAnswer(sql("""SELECT from_json(r'{"a": "\\"}', 'a string')"""), Row(Row("\\")))
checkAnswer(sql("""SELECT from_json(R'{"a": "\\"}', 'a string')"""), Row(Row("\\")))
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
Review comment:
can we move the test to `ParquetQuerySuite`? then we can use `withAllParquetReaders` to test all the parquet readers.
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r700731428
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
##########
@@ -4223,6 +4223,52 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
checkAnswer(sql("""SELECT from_json(r'{"a": "\\"}', 'a string')"""), Row(Row("\\")))
checkAnswer(sql("""SELECT from_json(R'{"a": "\\"}', 'a string')"""), Row(Row("\\")))
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
Review comment:
add support for the latter, thanks for pointing it out
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
##########
@@ -4223,6 +4223,52 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
checkAnswer(sql("""SELECT from_json(r'{"a": "\\"}', 'a string')"""), Row(Row("\\")))
checkAnswer(sql("""SELECT from_json(R'{"a": "\\"}', 'a string')"""), Row(Row("\\")))
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'kent'")
+ sql("insert into t2 select 2, 'yao'")
+ sql("insert into t2 select 3, 'kyuubi'")
Review comment:
addressed
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r702050323
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetReadSupport.scala
##########
@@ -323,15 +344,27 @@ object ParquetReadSupport {
* @return A list of clipped [[GroupType]] fields, which can be empty.
*/
private def clipParquetGroupFields(
- parquetRecord: GroupType, structType: StructType, caseSensitive: Boolean): Seq[Type] = {
+ parquetRecord: GroupType,
+ structType: StructType,
+ caseSensitive: Boolean,
+ accessByColumnOrdinal: Boolean): Seq[Type] = {
val toParquet = new SparkToParquetSchemaConverter(writeLegacyParquetFormat = false)
- if (caseSensitive) {
+ if (accessByColumnOrdinal) {
+ structType.zipWithIndex.map { case (f, i) =>
+ if (i < parquetRecord.getFieldCount) {
+ clipParquetType(
+ parquetRecord.getType(i), f.dataType, caseSensitive, accessByColumnOrdinal)
+ } else {
+ toParquet.convertField(f)
+ }
+ }
+ } else if (caseSensitive) {
val caseSensitiveParquetFieldMap =
parquetRecord.getFields.asScala.map(f => f.getName -> f).toMap
structType.map { f =>
caseSensitiveParquetFieldMap
.get(f.name)
- .map(clipParquetType(_, f.dataType, caseSensitive))
+ .map(clipParquetType(_, f.dataType, caseSensitive, accessByColumnOrdinal))
Review comment:
we support nesting, as you can see from the newly added tests
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[GitHub] [spark] cloud-fan commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r701639602
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
##########
@@ -200,19 +200,28 @@ private[parquet] class ParquetRowConverter(
// Converters for each field.
private[this] val fieldConverters: Array[Converter with HasParentContainerUpdater] = {
- // (SPARK-31116) Use case insensitive map if spark.sql.caseSensitive is false
- // to prevent throwing IllegalArgumentException when searching catalyst type's field index
- val catalystFieldNameToIndex = if (SQLConf.get.caseSensitiveAnalysis) {
- catalystType.fieldNames.zipWithIndex.toMap
+ if (SQLConf.get.parquetAccessByOrdinal) {
Review comment:
can we pass it in as a parameter of `ParquetRowConverter`?
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r704958740
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
##########
@@ -901,6 +901,91 @@ abstract class ParquetQuerySuite extends QueryTest with ParquetTest with SharedS
}
}
}
+
+ test("SPARK-36634: Support access and read parquet file by column index") {
+ withTempDir { dir =>
+ val loc = s"file:///$dir/t"
+
+ withTable("t1", "t2", "t3") {
+ sql(s"create table t1 (my_id int, my_name string) using parquet location '$loc'")
+ sql(s"create table t2 (myid int, myName string) using parquet location '$loc'")
+ sql("insert into t1 select 1, 'apache'")
+ sql("insert into t2 select 2, 'software'")
+ sql("insert into t2 select 3, 'foundation'")
+ sql(s"create table t3 (myid int, myname string, myage int) using parquet location '$loc'")
+
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "false")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(null), Row(null)))
+ checkAnswer(sql("select my_id, my_name from t1"),
+ Seq(Row(1, "apache"), Row(null, null), Row(null, null)))
+ assert(sql("select my_id, my_name from t1 where my_id=2").isEmpty)
+ checkAnswer(sql("select myid, myname, myage from t3"),
+ Seq(Row(2, "software", null),
+ Row(3, "foundation", null),
+ Row(null, null, null)))
+ }
+
+ sql("insert into t3 select 4, 'spark', 11")
+
+ withAllParquetReaders {
+ withSQLConf((SQLConf.PARQUET_ACCESS_BY_ORDINAL.key, "true")) {
+ checkAnswer(sql("select my_id from t1"), Seq(Row(1), Row(2), Row(3)))
+ val e1 = {
+ intercept[SparkException](sql("select my_name from t1").collect())
+ }
+ assert(e1.getCause.getMessage.contains("Parquet column cannot be converted in"))
Review comment:
I see. Let me think it over.
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r700701053
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -903,6 +903,13 @@ object SQLConf {
.intConf
.createWithDefault(4096)
+ val PARQUET_COLUMN_INDEX_ACCESS = buildConf("spark.sql.parquet.columnIndexAccess")
Review comment:
make sense
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[GitHub] [spark] yaooqinn commented on a change in pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on a change in pull request #33888:
URL: https://github.com/apache/spark/pull/33888#discussion_r702049276
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
##########
@@ -200,19 +200,28 @@ private[parquet] class ParquetRowConverter(
// Converters for each field.
private[this] val fieldConverters: Array[Converter with HasParentContainerUpdater] = {
- // (SPARK-31116) Use case insensitive map if spark.sql.caseSensitive is false
- // to prevent throwing IllegalArgumentException when searching catalyst type's field index
- val catalystFieldNameToIndex = if (SQLConf.get.caseSensitiveAnalysis) {
- catalystType.fieldNames.zipWithIndex.toMap
+ if (SQLConf.get.parquetAccessByIndex) {
+ // SPARK-36634: When access parquet file by the idx of columns, we can not ensure 2 types
+ // matched
+ parquetType.getFields.asScala.zip(catalystType).zipWithIndex.map {
Review comment:
I have added test cases for this, for name or idx mapping the output sets for the exceed part result in `nulls`
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[GitHub] [spark] yaooqinn commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-911276204
retest this please
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[GitHub] [spark] yaooqinn commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
yaooqinn commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-912321859
> @yaooqinn should orc support this similar behavior?
yes, we can support other file sources later, if this looks good to the community and gets merged.
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[GitHub] [spark] advancedxy commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
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advancedxy commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-912320394
@yaooqinn should orc support this similar behavior?
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[GitHub] [spark] SparkQA commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column ordinal
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-937505098
**[Test build #143942 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143942/testReport)** for PR 33888 at commit [`b989aa3`](https://github.com/apache/spark/commit/b989aa3821dbaf6cacccde886ed1051068d43cf5).
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[GitHub] [spark] AmplabJenkins commented on pull request #33888: [SPARK-36634][SQL] Support access and read parquet file by column index
Posted by GitBox <gi...@apache.org>.
AmplabJenkins commented on pull request #33888:
URL: https://github.com/apache/spark/pull/33888#issuecomment-910099484
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