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Original file line number Diff line number Diff line change
@@ -0,0 +1,207 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.gluten.delta

import org.apache.gluten.sql.shims.SparkShimLoader

import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.delta.GlutenDeltaParquetFileFormat
import org.apache.spark.sql.delta.actions.DeletionVectorDescriptor
import org.apache.spark.sql.delta.deletionvectors.{RoaringBitmapArrayFormat, StoredBitmap}
import org.apache.spark.sql.delta.storage.dv.HadoopFileSystemDVStore
import org.apache.spark.sql.execution.datasources.PartitionedFile

import org.apache.hadoop.fs.Path

import java.util.{ArrayList => JArrayList}

import scala.collection.JavaConverters._
import scala.util.control.NonFatal

object DeltaDeletionVectorScanInfo {
object RowIndexFilterType extends Enumeration {
type RowIndexFilterType = Value
val KEEP_ALL, IF_CONTAINED, IF_NOT_CONTAINED = Value
}

import RowIndexFilterType._

final case class DeletionVectorInfo(
hasDeletionVector: Boolean,
rowIndexFilterType: RowIndexFilterType,
cardinality: Long,
serializedDeletionVector: Array[Byte])
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nit: can we reorder to place hasDeletionVector as the first field?

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Thanks @zhztheplayer! Will reorder hasDeletionVector first in both Delta 3.3 and Delta 4.0.


final case class PartitionFileScanInfo(
normalizedOtherMetadataColumns: Map[String, Object],
deletionVectorInfo: DeletionVectorInfo)

private val RowIndexFilterIdEncoded =
GlutenDeltaParquetFileFormat.FILE_ROW_INDEX_FILTER_ID_ENCODED
private val RowIndexFilterTypeKey =
GlutenDeltaParquetFileFormat.FILE_ROW_INDEX_FILTER_TYPE

def extract(
spark: SparkSession,
partitionColumnCount: Int,
file: PartitionedFile): PartitionFileScanInfo = {
val metadata = otherMetadataColumns(file)
val normalizedMetadata = metadata -- Seq(RowIndexFilterIdEncoded, RowIndexFilterTypeKey)
val dvInfo = extractDeletionVectorInfo(spark, partitionColumnCount, file, metadata)
PartitionFileScanInfo(normalizedMetadata, dvInfo)
}

def extractAll(
spark: SparkSession,
partitionColumnCount: Int,
files: Seq[PartitionedFile]): Seq[PartitionFileScanInfo] = {
files.map(extract(spark, partitionColumnCount, _))
}

def extractAllFromJava(
spark: SparkSession,
partitionColumnCount: Int,
files: java.util.List[PartitionedFile]): java.util.List[PartitionFileScanInfo] = {
new JArrayList(extractAll(spark, partitionColumnCount, files.asScala.toSeq).asJava)
}

private def extractDeletionVectorInfo(
spark: SparkSession,
partitionColumnCount: Int,
file: PartitionedFile,
metadata: Map[String, Object]): DeletionVectorInfo = {
val descriptorValue = metadata.get(RowIndexFilterIdEncoded)
val filterTypeValue = metadata.get(RowIndexFilterTypeKey)

(descriptorValue, filterTypeValue) match {
case (None, None) =>
DeletionVectorInfo(false, KEEP_ALL, 0L, Array.emptyByteArray)
case (Some(encodedDescriptor), Some(filterType)) =>
val descriptor = parseDescriptor(encodedDescriptor.toString)
val serializedPayload = serializePayload(spark, partitionColumnCount, file, descriptor)
DeletionVectorInfo(
true,
parseRowIndexFilterType(filterType.toString),
descriptor.cardinality,
serializedPayload)
case _ =>
throw new IllegalStateException(
s"Both $RowIndexFilterIdEncoded and $RowIndexFilterTypeKey must either be present or absent")
}
}

private def otherMetadataColumns(file: PartitionedFile): Map[String, Object] = {
val otherMetadata =
SparkShimLoader.getSparkShims.getOtherConstantMetadataColumnValues(file)
if (otherMetadata == null) {
Map.empty
} else {
otherMetadata.asScala.toMap
}
}

private def parseDescriptor(encodedDescriptor: String): DeletionVectorDescriptor = {
try {
DeletionVectorDescriptor.deserializeFromBase64(encodedDescriptor)
} catch {
case NonFatal(e) =>
throw new IllegalArgumentException("Unable to parse Delta deletion vector descriptor", e)
}
}

private def parseRowIndexFilterType(filterType: String): RowIndexFilterType = {
filterType match {
case "IF_CONTAINED" => IF_CONTAINED
case "IF_NOT_CONTAINED" => IF_NOT_CONTAINED
case "KEEP_ALL" => KEEP_ALL
case unexpected =>
throw new IllegalStateException(s"Unexpected row index filter type: $unexpected")
}
}

private def serializePayload(
spark: SparkSession,
partitionColumnCount: Int,
file: PartitionedFile,
descriptor: DeletionVectorDescriptor): Array[Byte] = {
val tablePath = resolveTablePath(spark, partitionColumnCount, file)
if (tablePath == null) {
throw new IllegalStateException(
"Unable to resolve Delta table path while materializing deletion vector payload")
}
val dvStore = new HadoopFileSystemDVStore(spark.sessionState.newHadoopConf())
StoredBitmap
.create(descriptor, tablePath)
.load(dvStore)
.serializeAsByteArray(RoaringBitmapArrayFormat.Portable)
}

private def resolveTablePath(
spark: SparkSession,
partitionColumnCount: Int,
file: PartitionedFile): Path = {
val fileParent = new Path(unescapePathName(file.filePath.toString)).getParent
var tablePath = fileParent
for (_ <- 0 until partitionColumnCount) {
tablePath = tablePath.getParent
}
if (tablePath != null && isDeltaTablePath(spark, tablePath)) {
return tablePath
}

var candidate = fileParent
while (candidate != null && !isDeltaTablePath(spark, candidate)) {
candidate = candidate.getParent
}
if (candidate != null) candidate else tablePath
}

private def isDeltaTablePath(spark: SparkSession, tablePath: Path): Boolean = {
val deltaLogPath = new Path(tablePath, "_delta_log")
try {
deltaLogPath.getFileSystem(spark.sessionState.newHadoopConf()).exists(deltaLogPath)
} catch {
case NonFatal(_) => false
}
}

private def unescapePathName(path: String): String = {
if (path == null || path.indexOf('%') < 0) {
path
} else {
val builder = new StringBuilder(path.length)
var index = 0
while (index < path.length) {
if (path.charAt(index) == '%' && index + 2 < path.length) {
val high = Character.digit(path.charAt(index + 1), 16)
val low = Character.digit(path.charAt(index + 2), 16)
if (high >= 0 && low >= 0) {
builder.append(((high << 4) | low).toChar)
index += 3
} else {
builder.append(path.charAt(index))
index += 1
}
} else {
builder.append(path.charAt(index))
index += 1
}
}
builder.toString()
}
}
}
Original file line number Diff line number Diff line change
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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.gluten.delta

import org.apache.gluten.delta.DeltaDeletionVectorScanInfo.RowIndexFilterType

import org.apache.spark.SparkConf
import org.apache.spark.paths.SparkPath
import org.apache.spark.sql.QueryTest
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.delta.{DeltaLog, GlutenDeltaParquetFileFormat}
import org.apache.spark.sql.delta.catalog.DeltaCatalog
import org.apache.spark.sql.delta.test.DeltaSQLTestUtils
import org.apache.spark.sql.execution.datasources.PartitionedFile
import org.apache.spark.sql.internal.{SQLConf, StaticSQLConf}
import org.apache.spark.sql.test.SharedSparkSession
import org.apache.spark.tags.ExtendedSQLTest

import io.delta.sql.DeltaSparkSessionExtension
import org.apache.hadoop.fs.Path

@ExtendedSQLTest
class DeltaDeletionVectorScanInfoSuite
extends QueryTest
with SharedSparkSession
with DeltaSQLTestUtils {

import testImplicits._

override protected def sparkConf: SparkConf = {
super.sparkConf
.set(StaticSQLConf.SPARK_SESSION_EXTENSIONS.key, classOf[DeltaSparkSessionExtension].getName)
.set(SQLConf.V2_SESSION_CATALOG_IMPLEMENTATION.key, classOf[DeltaCatalog].getName)
.set("spark.databricks.delta.snapshotPartitions", "2")
}

test("extracts essential Delta DV scan info from split metadata") {
withTempDir {
tempDir =>
val path = tempDir.getCanonicalPath
Seq((1, "a"), (2, "b"), (3, "c"), (4, "d"))
.toDF("id", "value")
.coalesce(1)
.write
.format("delta")
.save(path)

spark.sql(
s"ALTER TABLE delta.`$path` SET TBLPROPERTIES ('delta.enableDeletionVectors' = true)")
spark.sql(s"DELETE FROM delta.`$path` WHERE id IN (3, 4)")

val dataFile = DeltaLog
.forTable(spark, new Path(path))
.update()
.allFiles
.collect()
.find(_.deletionVector != null)
.get
val partitionedFile = partitionedFileWithMetadata(
path,
dataFile.path,
dataFile.size,
Map(
GlutenDeltaParquetFileFormat.FILE_ROW_INDEX_FILTER_ID_ENCODED ->
dataFile.deletionVector.serializeToBase64(),
GlutenDeltaParquetFileFormat.FILE_ROW_INDEX_FILTER_TYPE -> "IF_CONTAINED",
"kept_key" -> "kept_value"
)
)

val scanInfo = DeltaDeletionVectorScanInfo.extract(spark, 0, partitionedFile)
val dvInfo = scanInfo.deletionVectorInfo

assert(dvInfo.hasDeletionVector)
assert(dvInfo.rowIndexFilterType == RowIndexFilterType.IF_CONTAINED)
assert(dvInfo.cardinality == dataFile.deletionVector.cardinality)
assert(dvInfo.serializedDeletionVector.nonEmpty)
assert(scanInfo.normalizedOtherMetadataColumns == Map("kept_key" -> "kept_value"))
}
}

test("returns keep-all scan info when Delta DV metadata is absent") {
withTempDir {
tempDir =>
val path = tempDir.getCanonicalPath
Seq((1, "a")).toDF("id", "value").coalesce(1).write.format("delta").save(path)

val dataFile = DeltaLog.forTable(spark, new Path(path)).update().allFiles.collect().head
val partitionedFile = partitionedFileWithMetadata(
path,
dataFile.path,
dataFile.size,
Map("kept_key" -> "kept_value"))

val scanInfo = DeltaDeletionVectorScanInfo.extract(spark, 0, partitionedFile)
val dvInfo = scanInfo.deletionVectorInfo

assert(!dvInfo.hasDeletionVector)
assert(dvInfo.rowIndexFilterType == RowIndexFilterType.KEEP_ALL)
assert(dvInfo.cardinality == 0L)
assert(dvInfo.serializedDeletionVector.isEmpty)
assert(scanInfo.normalizedOtherMetadataColumns == Map("kept_key" -> "kept_value"))
}
}

test("rejects partial Delta DV split metadata") {
withTempDir {
tempDir =>
val path = tempDir.getCanonicalPath
Seq((1, "a")).toDF("id", "value").coalesce(1).write.format("delta").save(path)

val dataFile = DeltaLog.forTable(spark, new Path(path)).update().allFiles.collect().head
val partitionedFile = partitionedFileWithMetadata(
path,
dataFile.path,
dataFile.size,
Map(GlutenDeltaParquetFileFormat.FILE_ROW_INDEX_FILTER_TYPE -> "IF_CONTAINED"))

val error = intercept[IllegalStateException] {
DeltaDeletionVectorScanInfo.extract(spark, 0, partitionedFile)
}
assert(error.getMessage.contains("must either be present or absent"))
}
}

private def partitionedFileWithMetadata(
tablePath: String,
relativeFilePath: String,
fileSize: Long,
metadata: Map[String, Object]): PartitionedFile = {
PartitionedFile(
partitionValues = InternalRow.empty,
filePath = SparkPath.fromPath(new Path(tablePath, relativeFilePath)),
start = 0L,
length = fileSize,
fileSize = fileSize,
otherConstantMetadataColumnValues = metadata
)
}
}
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