yihua commented on code in PR #10957:
URL: https://github.com/apache/hudi/pull/10957#discussion_r1630825026
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hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/SparkFileFormatInternalRowReaderContext.scala:
##########
@@ -101,46 +121,150 @@ class
SparkFileFormatInternalRowReaderContext(readerMaps: mutable.Map[Long, Part
}
override def mergeBootstrapReaders(skeletonFileIterator:
ClosableIterator[InternalRow],
- dataFileIterator:
ClosableIterator[InternalRow]): ClosableIterator[InternalRow] = {
- doBootstrapMerge(skeletonFileIterator.asInstanceOf[ClosableIterator[Any]],
- dataFileIterator.asInstanceOf[ClosableIterator[Any]])
+ skeletonRequiredSchema: Schema,
+ dataFileIterator:
ClosableIterator[InternalRow],
+ dataRequiredSchema: Schema):
ClosableIterator[InternalRow] = {
+ doBootstrapMerge(skeletonFileIterator.asInstanceOf[ClosableIterator[Any]],
skeletonRequiredSchema,
+ dataFileIterator.asInstanceOf[ClosableIterator[Any]], dataRequiredSchema)
}
- protected def doBootstrapMerge(skeletonFileIterator: ClosableIterator[Any],
dataFileIterator: ClosableIterator[Any]): ClosableIterator[InternalRow] = {
- new ClosableIterator[Any] {
- val combinedRow = new JoinedRow()
-
- override def hasNext: Boolean = {
- //If the iterators are out of sync it is probably due to filter
pushdown
- checkState(dataFileIterator.hasNext == skeletonFileIterator.hasNext,
- "Bootstrap data-file iterator and skeleton-file iterator have to be
in-sync!")
- dataFileIterator.hasNext && skeletonFileIterator.hasNext
+ protected def doBootstrapMerge(skeletonFileIterator: ClosableIterator[Any],
+ skeletonRequiredSchema: Schema,
+ dataFileIterator: ClosableIterator[Any],
+ dataRequiredSchema: Schema):
ClosableIterator[InternalRow] = {
+ if (getUseRecordPosition) {
+ assert(AvroSchemaUtils.containsFieldInSchema(skeletonRequiredSchema,
ROW_INDEX_TEMPORARY_COLUMN_NAME))
+ assert(AvroSchemaUtils.containsFieldInSchema(dataRequiredSchema,
ROW_INDEX_TEMPORARY_COLUMN_NAME))
+ val javaSet = new java.util.HashSet[String]()
+ javaSet.add(ROW_INDEX_TEMPORARY_COLUMN_NAME)
+ val skeletonProjection = projectRecord(skeletonRequiredSchema,
+ AvroSchemaUtils.removeFieldsFromSchema(skeletonRequiredSchema,
javaSet))
+ //If we have log files, we will want to do position based merging with
those as well,
+ //so leave the row index column at the end
+ val dataProjection = if (getHasLogFiles) {
+ getIdentityProjection
+ } else {
+ projectRecord(dataRequiredSchema,
+ AvroSchemaUtils.removeFieldsFromSchema(dataRequiredSchema, javaSet))
}
- override def next(): Any = {
- (skeletonFileIterator.next(), dataFileIterator.next()) match {
- case (s: ColumnarBatch, d: ColumnarBatch) =>
- val numCols = s.numCols() + d.numCols()
- val vecs: Array[ColumnVector] = new Array[ColumnVector](numCols)
- for (i <- 0 until numCols) {
- if (i < s.numCols()) {
- vecs(i) = s.column(i)
+ //Always use internal row for positional merge because
+ //we need to iterate row by row when merging
+ new CachingIterator[InternalRow] {
+ val combinedRow = new JoinedRow()
+
+ //position column will always be at the end of the row
+ private def getPos(row: InternalRow): Long = {
+ row.getLong(row.numFields-1)
+ }
+
+ private def getNextSkeleton: (InternalRow, Long) = {
+ val nextSkeletonRow =
skeletonFileIterator.next().asInstanceOf[InternalRow]
+ (nextSkeletonRow, getPos(nextSkeletonRow))
+ }
+
+ private def getNextData: (InternalRow, Long) = {
+ val nextSkeletonRow =
skeletonFileIterator.next().asInstanceOf[InternalRow]
+ (nextSkeletonRow, getPos(nextSkeletonRow))
+ }
+
+ override def close(): Unit = {
+ skeletonFileIterator.close()
+ dataFileIterator.close()
+ }
+
+ override protected def doHasNext(): Boolean = {
+ if (!dataFileIterator.hasNext || !skeletonFileIterator.hasNext) {
+ false
+ } else {
+ var nextSkeleton = getNextSkeleton
+ var nextData = getNextData
+ while (nextSkeleton._2 != nextData._2) {
+ if (nextSkeleton._2 > nextData._2) {
+ if (!dataFileIterator.hasNext) {
+ return false
+ } else {
+ nextData = getNextData
+ }
} else {
- vecs(i) = d.column(i - s.numCols())
+ if (!skeletonFileIterator.hasNext) {
+ return false
+ } else {
+ nextSkeleton = getNextSkeleton
+ }
}
}
- assert(s.numRows() == d.numRows())
- sparkAdapter.makeColumnarBatch(vecs, s.numRows())
- case (_: ColumnarBatch, _: InternalRow) => throw new
IllegalStateException("InternalRow ColumnVector mismatch")
- case (_: InternalRow, _: ColumnarBatch) => throw new
IllegalStateException("InternalRow ColumnVector mismatch")
- case (s: InternalRow, d: InternalRow) => combinedRow(s, d)
+ nextRecord =
combinedRow(skeletonProjection.apply(nextSkeleton._1),
dataProjection.apply(nextData._1))
+ true
+ }
}
}
+ } else {
+ new ClosableIterator[Any] {
+ val combinedRow = new JoinedRow()
- override def close(): Unit = {
- skeletonFileIterator.close()
- dataFileIterator.close()
- }
- }.asInstanceOf[ClosableIterator[InternalRow]]
+ override def hasNext: Boolean = {
+ //If the iterators are out of sync it is probably due to filter
pushdown
+ checkState(dataFileIterator.hasNext == skeletonFileIterator.hasNext,
+ "Bootstrap data-file iterator and skeleton-file iterator have to
be in-sync!")
+ dataFileIterator.hasNext && skeletonFileIterator.hasNext
+ }
+
+ override def next(): Any = {
+ (skeletonFileIterator.next(), dataFileIterator.next()) match {
+ case (s: ColumnarBatch, d: ColumnarBatch) =>
+ //This will not be used until [HUDI-7693] is implemented
+ val numCols = s.numCols() + d.numCols()
+ val vecs: Array[ColumnVector] = new Array[ColumnVector](numCols)
+ for (i <- 0 until numCols) {
+ if (i < s.numCols()) {
+ vecs(i) = s.column(i)
+ } else {
+ vecs(i) = d.column(i - s.numCols())
+ }
+ }
+ assert(s.numRows() == d.numRows())
+ sparkAdapter.makeColumnarBatch(vecs, s.numRows())
+ case (_: ColumnarBatch, _: InternalRow) => throw new
IllegalStateException("InternalRow ColumnVector mismatch")
+ case (_: InternalRow, _: ColumnarBatch) => throw new
IllegalStateException("InternalRow ColumnVector mismatch")
+ case (s: InternalRow, d: InternalRow) => combinedRow(s, d)
+ }
+ }
+
+ override def close(): Unit = {
+ skeletonFileIterator.close()
+ dataFileIterator.close()
+ }
+ }.asInstanceOf[ClosableIterator[InternalRow]]
+ }
}
}
+
+object SparkFileFormatInternalRowReaderContext {
+ // From "ParquetFileFormat.scala": The names of the field for record
position.
+ private val ROW_INDEX = "row_index"
+ private val ROW_INDEX_TEMPORARY_COLUMN_NAME = s"_tmp_metadata_$ROW_INDEX"
+
+ // From "namedExpressions.scala": Used to construct to record position field
metadata.
+ private val FILE_SOURCE_GENERATED_METADATA_COL_ATTR_KEY =
"__file_source_generated_metadata_col"
+ private val FILE_SOURCE_METADATA_COL_ATTR_KEY = "__file_source_metadata_col"
+ private val METADATA_COL_ATTR_KEY = "__metadata_col"
+
+ def getRecordKeyRelatedFilters(filters: Seq[Filter], recordKeyColumn:
String): Seq[Filter] = {
+ filters.filter(f => f.references.exists(c =>
c.equalsIgnoreCase(recordKeyColumn)))
+ }
+
+ def isIndexTempColumn(field: StructField): Boolean = {
+ field.name.equals(ROW_INDEX_TEMPORARY_COLUMN_NAME)
+ }
+
+ def getAppliedRequiredSchema(requiredSchema: StructType): StructType = {
+ val metadata = new MetadataBuilder()
+ .putString(METADATA_COL_ATTR_KEY, ROW_INDEX_TEMPORARY_COLUMN_NAME)
+ .putBoolean(FILE_SOURCE_METADATA_COL_ATTR_KEY, value = true)
+ .putString(FILE_SOURCE_GENERATED_METADATA_COL_ATTR_KEY,
ROW_INDEX_TEMPORARY_COLUMN_NAME)
+ .build()
+ val rowIndexField = StructField(ROW_INDEX_TEMPORARY_COLUMN_NAME,
LongType, nullable = false, metadata)
Review Comment:
Where is the `TestFiltersInFileGroupReader` class?
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