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[SPARK-27592][SQL] Set the bucketed data source table SerDe correctly #24486

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[SPARK-27592][SQL] Set the bucketed data source table SerDe correctly #24486

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6ce0a32
Write the write information of this data to metadata.
wangyum Apr 29, 2019
2fdc3a6
Set the bucketed data source table SerDe correctly
wangyum May 4, 2019
4e1dd5c
Spark bucketed data source table always a not bucketed table at Hive …
wangyum May 8, 2019
921bbb0
Merge remote-tracking branch 'upstream/master' into SPARK-27592
wangyum May 23, 2019
26c895a
Check the results.
wangyum May 23, 2019
87b302c
Fix scala style
wangyum May 23, 2019
86e4394
Merge remote-tracking branch 'upstream/master' into SPARK-27592
wangyum Aug 15, 2019
842bd3e
Include the jira id in test name.
wangyum Aug 15, 2019
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11 changes: 8 additions & 3 deletions sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveExternalCatalog.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -358,12 +358,17 @@ private[spark] class HiveExternalCatalog(conf: SparkConf, hadoopConf: Configurat
"Spark SQL specific format, which is NOT compatible with Hive."
(None, message)

// our bucketing is un-compatible with hive(different hash function)
case _ if table.bucketSpec.nonEmpty =>
// our bucketing is un-compatible with hive(different hash function).
// but downstream(Hive/Presto) still can read it as not bucketed table.
// We set the SerDe correctly and bucketing_version to spark.
// The downstream decides how to read it by themselves, a similar implementation:

@gatorsmile gatorsmile May 6, 2019

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What is the impact if the downstream makes a wrong decision?

@wangyum wangyum May 8, 2019

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Sorry. It's not bucketed table at Hive side. Related code:

spark/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveExternalCatalog.scala

Lines 444 to 459 in f9776e3

if (bucketSpec.isDefined) {
val BucketSpec(numBuckets, bucketColumnNames, sortColumnNames) = bucketSpec.get
properties.put(DATASOURCE_SCHEMA_NUMBUCKETS, numBuckets.toString)
properties.put(DATASOURCE_SCHEMA_NUMBUCKETCOLS, bucketColumnNames.length.toString)
bucketColumnNames.zipWithIndex.foreach { case (bucketCol, index) =>
properties.put(s"$DATASOURCE_SCHEMA_BUCKETCOL_PREFIX$index", bucketCol)
}
if (sortColumnNames.nonEmpty) {
properties.put(DATASOURCE_SCHEMA_NUMSORTCOLS, sortColumnNames.length.toString)
sortColumnNames.zipWithIndex.foreach { case (sortCol, index) =>
properties.put(s"$DATASOURCE_SCHEMA_SORTCOL_PREFIX$index", sortCol)
}
}
}

spark/sql/hive/src/main/scala/org/apache/spark/sql/hive/client/HiveClientImpl.scala

Lines 976 to 990 in 33f3c48

table.bucketSpec match {
case Some(bucketSpec) if DDLUtils.isHiveTable(table) =>
hiveTable.setNumBuckets(bucketSpec.numBuckets)
hiveTable.setBucketCols(bucketSpec.bucketColumnNames.toList.asJava)
if (bucketSpec.sortColumnNames.nonEmpty) {
hiveTable.setSortCols(
bucketSpec.sortColumnNames
.map(col => new Order(col, HIVE_COLUMN_ORDER_ASC))
.toList
.asJava
)
}
case _ =>
}

// https://github.com/prestosql/presto/pull/512
case Some(serde) if table.bucketSpec.nonEmpty =>
val message =
s"Persisting bucketed data source table $qualifiedTableName into " +
"Hive metastore in Spark SQL specific format, which is NOT compatible with Hive. "
(None, message)
tableProperties.put("bucketing_version", "spark")
(Some(newHiveCompatibleMetastoreTable(serde)), message)

@gatorsmile gatorsmile May 22, 2019

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Should we set bucketSpec = None?

@wangyum wangyum May 23, 2019

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Not necessary:

spark/sql/hive/src/main/scala/org/apache/spark/sql/hive/client/HiveClientImpl.scala

Lines 1009 to 1023 in fee695d

table.bucketSpec match {
case Some(bucketSpec) if DDLUtils.isHiveTable(table) =>
hiveTable.setNumBuckets(bucketSpec.numBuckets)
hiveTable.setBucketCols(bucketSpec.bucketColumnNames.toList.asJava)
if (bucketSpec.sortColumnNames.nonEmpty) {
hiveTable.setSortCols(
bucketSpec.sortColumnNames
.map(col => new Order(col, HIVE_COLUMN_ORDER_ASC))
.toList
.asJava
)
}
case _ =>
}


case Some(serde) =>
val message =
Expand Down
24 changes: 23 additions & 1 deletion sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala
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Expand Up @@ -23,7 +23,7 @@ import org.apache.spark.sql.catalyst.catalog.CatalogTableType
import org.apache.spark.sql.catalyst.parser.CatalystSqlParser
import org.apache.spark.sql.catalyst.plans.logical.SubqueryAlias
import org.apache.spark.sql.hive.test.TestHiveSingleton
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.internal.{HiveSerDe, SQLConf}
import org.apache.spark.sql.test.{ExamplePointUDT, SQLTestUtils}
import org.apache.spark.sql.types._

Expand Down Expand Up @@ -273,4 +273,26 @@ class DataSourceWithHiveMetastoreCatalogSuite
}

}

test("Set the bucketed data source table SerDe correctly") {

@cloud-fan cloud-fan Aug 15, 2019

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let's include the jira id in test name.

val provider = "parquet"
withTable("t") {
spark.sql(
s"""
|CREATE TABLE t (c1 INT, c2 INT)
|USING $provider
|CLUSTERED BY (c1)
|SORTED BY (c1)
|INTO 2 BUCKETS
""".stripMargin)

val metadata = sessionState.catalog.getTableMetadata(TableIdentifier("t", Some("default")))
assert(metadata.properties.get("bucketing_version") === Some("spark"))

val hiveSerDe = HiveSerDe.sourceToSerDe(provider).get
assert(metadata.storage.serde === hiveSerDe.serde)
assert(metadata.storage.inputFormat === hiveSerDe.inputFormat)
assert(metadata.storage.outputFormat === hiveSerDe.outputFormat)
}
}
}