DMLWithDeletionVectorsHelper¶

createTargetDfForScanningForMatches¶

createTargetDfForScanningForMatches(
  spark: SparkSession,
  target: LogicalPlan,
  fileIndex: TahoeFileIndex): DataFrame

createTargetDfForScanningForMatches creates a DataFrame with replaceFileIndex logical operator (based on the given target and TahoeFileIndex)

createTargetDfForScanningForMatches is used when:

• DeleteCommand is requested to performDelete (with deletion vectors enabled)
• UpdateCommand is requested to performUpdate (with deletion vectors enabled)

Replacing FileIndex¶

replaceFileIndex(
  target: LogicalPlan,
  fileIndex: TahoeFileIndex): LogicalPlan

replaceFileIndex replaces a FileIndex in all the delta tables in the given target logical plan (with some other changes).

replaceFileIndex transforms (recognizes) the following logical operators in given target logical plan:

1. LogicalRelations with HadoopFsRelations (Spark SQL) with DeltaParquetFileFormat
2. Projects

replaceFileIndex adds the following metadata columns to the output schema (of the logical operators):

1. Delta-specific __delta_internal_row_index
2. FileFormat-specific _metadata (Spark SQL)

In addition, for LogicalRelations, replaceFileIndex changes the HadoopFsRelation to use the following:

• The given TahoeFileIndex as the FileIndex (Spark SQL)
• The DeltaParquetFileFormat with splitting and pushdowns disabled

findTouchedFiles¶

findTouchedFiles(
  sparkSession: SparkSession,
  txn: OptimisticTransaction,
  hasDVsEnabled: Boolean,
  deltaLog: DeltaLog,
  targetDf: DataFrame,
  fileIndex: TahoeFileIndex,
  condition: Expression,
  opName: String): Seq[TouchedFileWithDV]

findTouchedFiles...FIXME

findTouchedFiles is used when:

• DeleteCommand is requested to performDelete
• UpdateCommand is requested to performUpdate

findFilesWithMatchingRows¶

findFilesWithMatchingRows(
  txn: OptimisticTransaction,
  nameToAddFileMap: Map[String, AddFile],
  matchedFileRowIndexSets: Seq[DeletionVectorResult]): Seq[TouchedFileWithDV]

findFilesWithMatchingRows...FIXME

processUnmodifiedData¶

processUnmodifiedData(
  spark: SparkSession,
  touchedFiles: Seq[TouchedFileWithDV],
  snapshot: Snapshot): (Seq[FileAction], Map[String, Long])

processUnmodifiedData calculates the following metrics (using the given touchedFiles):

• The total number of modified rows
• The number of isFullyReplaced data files

processUnmodifiedData splits (partitions) the given TouchedFileWithDVs into fully removed ones and the others (based on isFullyReplaced flag).

processUnmodifiedData...FIXME

In the end, processUnmodifiedData returns a collection of the RemoveFile and AddFile actions along with the following metrics:

• numModifiedRows
• numRemovedFiles
• numDeletionVectorsAdded
• numDeletionVectorsRemoved
• numDeletionVectorsUpdated

processUnmodifiedData is used when:

• DeleteCommand is requested to performDelete (with shouldWritePersistentDeletionVectors enabled and supported)