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[SPARK-27407][SQL] File source V2: Invalidate cache data on overwrite/append #24318

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[SPARK-27407][SQL] File source V2: Invalidate cache data on overwrite/append #24318

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30 changes: 23 additions & 7 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/CacheManager.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,8 @@ import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeMap, Subqu
import org.apache.spark.sql.catalyst.plans.logical.{IgnoreCachedData, LogicalPlan, ResolvedHint}
import org.apache.spark.sql.execution.columnar.InMemoryRelation
import org.apache.spark.sql.execution.command.CommandUtils
import org.apache.spark.sql.execution.datasources.{HadoopFsRelation, LogicalRelation}
import org.apache.spark.sql.execution.datasources.{FileIndex, HadoopFsRelation, LogicalRelation}
import org.apache.spark.sql.execution.datasources.v2.{DataSourceV2Relation, FileTable}
import org.apache.spark.storage.StorageLevel
import org.apache.spark.storage.StorageLevel.MEMORY_AND_DISK

Expand Down Expand Up @@ -253,15 +254,30 @@ class CacheManager extends Logging {
plan match {
case lr: LogicalRelation => lr.relation match {
case hr: HadoopFsRelation =>
val prefixToInvalidate = qualifiedPath.toString
val invalidate = hr.location.rootPaths
.map(_.makeQualified(fs.getUri, fs.getWorkingDirectory).toString)
.exists(_.startsWith(prefixToInvalidate))
if (invalidate) hr.location.refresh()
invalidate
refreshFileIndexIfNecessary(hr.location, fs, qualifiedPath)
case _ => false
}

case DataSourceV2Relation(fileTable: FileTable, _, _) =>
refreshFileIndexIfNecessary(fileTable.fileIndex, fs, qualifiedPath)

case _ => false
}
}

/**
* Refresh the given [[FileIndex]] if any of its root paths starts with `qualifiedPath`.
* @return whether the [[FileIndex]] is refreshed.
*/
private def refreshFileIndexIfNecessary(
fileIndex: FileIndex,
fs: FileSystem,
qualifiedPath: Path): Boolean = {
val prefixToInvalidate = qualifiedPath.toString
val needToRefresh = fileIndex.rootPaths
.map(_.makeQualified(fs.getUri, fs.getWorkingDirectory).toString)
.exists(_.startsWith(prefixToInvalidate))
if (needToRefresh) fileIndex.refresh()
needToRefresh
}
}
32 changes: 32 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
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Expand Up @@ -494,6 +494,38 @@ class FileBasedDataSourceSuite extends QueryTest with SharedSQLContext with Befo
}
}

test("Do not use cache on overwrite") {
Seq("", "orc").foreach { useV1SourceReaderList =>
withSQLConf(SQLConf.USE_V1_SOURCE_READER_LIST.key -> useV1SourceReaderList) {
withTempDir { dir =>
val path = dir.toString
spark.range(1000).write.mode("overwrite").orc(path)
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@dongjoon-hyun dongjoon-hyun Apr 9, 2019 •
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@gengliangwang . In this suite, we need to test all available data sources like the following instead of using .orc.

Seq("csv", "orc", "text").foreach { format =>

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@dongjoon-hyun dongjoon-hyun Apr 9, 2019 •
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Could you generalize this test case?
Also, please add JIRA issue for Parquet DSv2 Migration as a TODO comment.

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@gengliangwang gengliangwang Apr 9, 2019

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@dongjoon-hyun The cache invalidation is for all file sources. Testing ORC here is quite sufficient, just like only Parquet is tested in #13566.

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@dongjoon-hyun dongjoon-hyun Apr 9, 2019 •
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If that is the logic, let's hold on this until Parquet is ready to migrate. We don't need to move around the test logic from here to there.

We are going to migrate Parquet anyway, aren't we?

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@dongjoon-hyun dongjoon-hyun Apr 9, 2019 •
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In general, this test suite is designed to verify for all data sources from the beginning.

val df = spark.read.orc(path).cache()
assert(df.count() == 1000)
spark.range(10).write.mode("overwrite").orc(path)
assert(df.count() == 10)
assert(spark.read.orc(path).count() == 10)
}
}
}
}

test("Do not use cache on append") {
Seq("", "orc").foreach { useV1SourceReaderList =>
withSQLConf(SQLConf.USE_V1_SOURCE_READER_LIST.key -> useV1SourceReaderList) {
withTempDir { dir =>
val path = dir.toString
spark.range(1000).write.mode("append").orc(path)
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@dongjoon-hyun dongjoon-hyun Apr 9, 2019

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ditto.

val df = spark.read.orc(path).cache()
assert(df.count() == 1000)
spark.range(10).write.mode("append").orc(path)
assert(df.count() == 1010)
assert(spark.read.orc(path).count() == 1010)
}
}
}
}

test("Return correct results when data columns overlap with partition columns") {
Seq("parquet", "orc", "json").foreach { format =>
withTempPath { path =>
Expand Down
24 changes: 0 additions & 24 deletions ...src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
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Expand Up @@ -70,30 +70,6 @@ class ParquetQuerySuite extends QueryTest with ParquetTest with SharedSQLContext
TableIdentifier("tmp"), ignoreIfNotExists = true, purge = false)
}

test("SPARK-15678: not use cache on overwrite") {
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@gengliangwang gengliangwang Apr 8, 2019

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Delete the original test case for following reasons:

  1. The cache invalidation is for all file sources
  2. The two test cases in ParquetQuerySuite is covered by the new test cases of this PR.
  3. The Parquet data source is not migrated to V2 yet.

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@dongjoon-hyun dongjoon-hyun Apr 8, 2019

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+1

withTempDir { dir =>
val path = dir.toString
spark.range(1000).write.mode("overwrite").parquet(path)
val df = spark.read.parquet(path).cache()
assert(df.count() == 1000)
spark.range(10).write.mode("overwrite").parquet(path)
assert(df.count() == 10)
assert(spark.read.parquet(path).count() == 10)
}
}

test("SPARK-15678: not use cache on append") {
withTempDir { dir =>
val path = dir.toString
spark.range(1000).write.mode("append").parquet(path)
val df = spark.read.parquet(path).cache()
assert(df.count() == 1000)
spark.range(10).write.mode("append").parquet(path)
assert(df.count() == 1010)
assert(spark.read.parquet(path).count() == 1010)
}
}

test("self-join") {
// 4 rows, cells of column 1 of row 2 and row 4 are null
val data = (1 to 4).map { i =>
Expand Down