nsivabalan commented on code in PR #9373:
URL: https://github.com/apache/hudi/pull/9373#discussion_r1285082443
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/HoodieBaseRelation.scala:
##########
@@ -343,7 +343,7 @@ abstract class HoodieBaseRelation(val sqlContext:
SQLContext,
*/
override final def needConversion: Boolean = false
- override def inputFiles: Array[String] =
fileIndex.allFiles.map(_.getPath.toUri.toString).toArray
+ override def inputFiles: Array[String] =
fileIndex.allBaseFiles.map(_.getPath.toUri.toString).toArray
Review Comment:
Are we sure on this change? also, can we add java docs as to whats the
expected file list here and how it is used.
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestRecordLevelIndexWithSQL.scala:
##########
@@ -45,12 +52,71 @@ class TestRecordLevelIndexWithSQL extends
RecordLevelIndexTestBase {
validate = false)
createTempTable(hudiOpts)
- val reckey =
mergedDfList.last.limit(1).collect()(0).getAs("_row_key").toString
- spark.sql("select * from " + sqlTempTable + " where '" + reckey + "' =
_row_key").show(false)
+ testInQuery(hudiOpts)
+ testEqualToQuery(hudiOpts)
+ }
+
+ def testEqualToQuery(hudiOpts: Map[String, String]): Unit = {
+ val reckey = mergedDfList.last.limit(1).collect().map(row =>
row.getAs("_row_key").toString)
+ val dataFilter = EqualTo(attribute("_row_key"), Literal(reckey(0)))
+ assertEquals(1, spark.sql("select * from " + sqlTempTable + " where " +
dataFilter.sql).count())
+ verifyPruningFileCount(hudiOpts, dataFilter, 1)
+ }
+
+ def testInQuery(hudiOpts: Map[String, String]): Unit = {
+ var reckey = mergedDfList.last.limit(1).collect().map(row =>
row.getAs("_row_key").toString)
+ var dataFilter = In(attribute("_row_key"), reckey.map(l =>
literal(l)).toList)
+ assertEquals(1, spark.sql("select * from " + sqlTempTable + " where " +
dataFilter.sql).count())
+ var numFiles = if (isTableMOR()) 2 else 1
+ verifyPruningFileCount(hudiOpts, dataFilter, numFiles)
+
+ reckey = mergedDfList.last.limit(2).collect().map(row =>
row.getAs("_row_key").toString)
+ dataFilter = In(attribute("_row_key"), reckey.map(l => literal(l)).toList)
+ assertEquals(2, spark.sql("select * from " + sqlTempTable + " where " +
dataFilter.sql).count())
+ numFiles = if (isTableMOR()) 2 else 2
+ verifyPruningFileCount(hudiOpts, dataFilter, numFiles)
+ }
+
+ private def attribute(partition: String): AttributeReference = {
+ AttributeReference(partition, StringType, true)()
+ }
+
+ private def literal(value: String): Literal = {
+ Literal.create(value)
+ }
+
+ private def verifyPruningFileCount(opts: Map[String, String], dataFilter:
Expression, numFiles: Int): Unit = {
+ metaClient = HoodieTableMetaClient.reload(metaClient)
+ val fileIndex = HoodieFileIndex(spark, metaClient, None, opts + ("path" ->
basePath))
+ fileIndex.setIncludeLogFiles(isTableMOR())
+ val filteredPartitionDirectories = fileIndex.listFiles(Seq(),
Seq(dataFilter))
+ val filteredFilesCount = filteredPartitionDirectories.flatMap(s =>
s.files).size
+ assertTrue(filteredFilesCount < getLatestDataFilesCount(opts))
+ assertEquals(filteredFilesCount, numFiles)
+ }
+
+ private def isTableMOR(): Boolean = {
+ metaClient.getTableType == HoodieTableType.MERGE_ON_READ
+ }
+
+ private def getLatestDataFilesCount(opts: Map[String, String],
includeLogFiles: Boolean = true) = {
+ var totalLatestDataFiles = 0L
+
getTableFileSystenView(opts).getAllLatestFileSlicesBeforeOrOn(metaClient.getActiveTimeline.lastInstant().get().getTimestamp)
+ .values()
+ .forEach(JFunction.toJavaConsumer[java.util.stream.Stream[FileSlice]]
+ (slices => slices.forEach(JFunction.toJavaConsumer[FileSlice](
+ slice => totalLatestDataFiles += (if (includeLogFiles)
slice.getLogFiles.count() else 0)
+ + (if (slice.getBaseFile.isPresent) 1 else 0)))))
+ totalLatestDataFiles
+ }
+
+ private def getTableFileSystenView(opts: Map[String, String]):
HoodieMetadataFileSystemView = {
+ new HoodieMetadataFileSystemView(metaClient, metaClient.getActiveTimeline,
metadataWriter(getWriteConfig(opts)).getTableMetadata)
}
private def createTempTable(hudiOpts: Map[String, String]): Unit = {
val readDf = spark.read.format("hudi").options(hudiOpts).load(basePath)
+ readDf.printSchema()
Review Comment:
whats the necessity for this ?
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/RecordLevelIndexSupport.scala:
##########
@@ -123,28 +123,47 @@ class RecordLevelIndexSupport(spark: SparkSession,
* @param queryFilters The queries that need to be filtered.
* @return Tuple of List of filtered queries and list of record key literals
that need to be matched
*/
- private def filterQueryFiltersWithRecordKey(queryFilters: Seq[Expression]):
(List[Expression], List[String]) = {
+ private def filterQueriesWithRecordKey(queryFilters: Seq[Expression]):
(List[Expression], List[String]) = {
var recordKeyQueries: List[Expression] = List.empty
var recordKeys: List[String] = List.empty
for (query <- queryFilters) {
- query match {
- case equalToQuery: EqualTo =>
- val (attribute, literal) =
getAttributeLiteralTuple(equalToQuery.left, equalToQuery.right).orNull
- if (attribute != null && attribute.name != null &&
attributeMatchesRecordKey(attribute.name)) {
- recordKeys = recordKeys :+ literal.value.toString
- recordKeyQueries = recordKeyQueries :+ equalToQuery
- }
- case _ =>
- }
+ filterQueryWithRecordKey(query).foreach({
+ case (exp: Expression, recKeys: List[String]) =>
+ recordKeys = recordKeys ++ recKeys
+ recordKeyQueries = recordKeyQueries :+ exp
+ })
}
+
Tuple2.apply(recordKeyQueries, recordKeys)
}
- /**
+ private def filterQueryWithRecordKey(queryFilter: Expression):
Option[(Expression, List[String])] = {
Review Comment:
can we add java docs on what are the supported filtering as of now.
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestRecordLevelIndexWithSQL.scala:
##########
@@ -45,12 +52,71 @@ class TestRecordLevelIndexWithSQL extends
RecordLevelIndexTestBase {
validate = false)
createTempTable(hudiOpts)
- val reckey =
mergedDfList.last.limit(1).collect()(0).getAs("_row_key").toString
- spark.sql("select * from " + sqlTempTable + " where '" + reckey + "' =
_row_key").show(false)
+ testInQuery(hudiOpts)
+ testEqualToQuery(hudiOpts)
+ }
+
+ def testEqualToQuery(hudiOpts: Map[String, String]): Unit = {
+ val reckey = mergedDfList.last.limit(1).collect().map(row =>
row.getAs("_row_key").toString)
+ val dataFilter = EqualTo(attribute("_row_key"), Literal(reckey(0)))
+ assertEquals(1, spark.sql("select * from " + sqlTempTable + " where " +
dataFilter.sql).count())
+ verifyPruningFileCount(hudiOpts, dataFilter, 1)
+ }
+
+ def testInQuery(hudiOpts: Map[String, String]): Unit = {
+ var reckey = mergedDfList.last.limit(1).collect().map(row =>
row.getAs("_row_key").toString)
+ var dataFilter = In(attribute("_row_key"), reckey.map(l =>
literal(l)).toList)
+ assertEquals(1, spark.sql("select * from " + sqlTempTable + " where " +
dataFilter.sql).count())
+ var numFiles = if (isTableMOR()) 2 else 1
+ verifyPruningFileCount(hudiOpts, dataFilter, numFiles)
+
+ reckey = mergedDfList.last.limit(2).collect().map(row =>
row.getAs("_row_key").toString)
+ dataFilter = In(attribute("_row_key"), reckey.map(l => literal(l)).toList)
+ assertEquals(2, spark.sql("select * from " + sqlTempTable + " where " +
dataFilter.sql).count())
+ numFiles = if (isTableMOR()) 2 else 2
+ verifyPruningFileCount(hudiOpts, dataFilter, numFiles)
+ }
+
+ private def attribute(partition: String): AttributeReference = {
+ AttributeReference(partition, StringType, true)()
+ }
+
+ private def literal(value: String): Literal = {
+ Literal.create(value)
+ }
+
+ private def verifyPruningFileCount(opts: Map[String, String], dataFilter:
Expression, numFiles: Int): Unit = {
+ metaClient = HoodieTableMetaClient.reload(metaClient)
+ val fileIndex = HoodieFileIndex(spark, metaClient, None, opts + ("path" ->
basePath))
+ fileIndex.setIncludeLogFiles(isTableMOR())
+ val filteredPartitionDirectories = fileIndex.listFiles(Seq(),
Seq(dataFilter))
Review Comment:
also, lets check for a case where the record key does not exists only w/
equal to or IN clause
for eg _row_key = 'xyz' should not even scan any files and return right away
if RLI did not return any matching entries.
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