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[KYUUBI #6315] Spark 3.5: MaxScanStrategy supports DSv2 #5852

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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@ import org.apache.spark.sql.catalyst.planning.ScanOperation
import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
import org.apache.spark.sql.execution.SparkPlan
import org.apache.spark.sql.execution.datasources.{CatalogFileIndex, HadoopFsRelation, InMemoryFileIndex, LogicalRelation}
import org.apache.spark.sql.execution.datasources.v2.DataSourceV2ScanRelation
import org.apache.spark.sql.types.StructType

import org.apache.kyuubi.sql.KyuubiSQLConf
Expand Down Expand Up @@ -232,6 +233,40 @@ case class MaxScanStrategy(session: SparkSession)
logicalRelation.catalogTable)
}
}
case ScanOperation(
_,
_,
_,
relation @ DataSourceV2ScanRelation(_, _, _, _, _)) =>
val table = relation.relation.table
if (table.partitioning().nonEmpty) {
val partitionColumnNames = table.partitioning().map(_.describe())
val stats = relation.computeStats()
lazy val scanFileSize = stats.sizeInBytes
if (maxFileSizeOpt.exists(_ < scanFileSize)) {
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throw new MaxFileSizeExceedException(
s"""
|SQL job scan file size in bytes: $scanFileSize
|exceed restrict of table scan maxFileSize ${maxFileSizeOpt.get}
|You should optimize your SQL logical according partition structure
|or shorten query scope such as p_date, detail as below:
|Table: ${table.name()}
|Partition Structure: ${partitionColumnNames.mkString(",")}
|""".stripMargin)
}
} else {
val stats = relation.computeStats()
lazy val scanFileSize = stats.sizeInBytes
if (maxFileSizeOpt.exists(_ < scanFileSize)) {
throw new MaxFileSizeExceedException(
s"""
|SQL job scan file size in bytes: $scanFileSize
|exceed restrict of table scan maxFileSize ${maxFileSizeOpt.get}
|detail as below:
|Table: ${table.name()}
|""".stripMargin)
}
}
case _ =>
}
}
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,64 @@
/*
* 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.spark.sql

import java.util.OptionalLong

import org.apache.spark.sql.connector.{RangeInputPartition, SimpleBatchTable, SimpleScanBuilder, SimpleWritableDataSource}
import org.apache.spark.sql.connector.catalog.Table
import org.apache.spark.sql.connector.expressions.{Expressions, FieldReference, Transform}
import org.apache.spark.sql.connector.read.{InputPartition, ScanBuilder, Statistics, SupportsReportPartitioning, SupportsReportStatistics}
import org.apache.spark.sql.connector.read.partitioning.{KeyGroupedPartitioning, Partitioning}
import org.apache.spark.sql.util.CaseInsensitiveStringMap

class ReportStatisticsAndPartitionAwareDataSource extends SimpleWritableDataSource {
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Do we need to add a new data source? Is it better to use iceberg datasource directly? @pan3793 WDYT?

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Prefer to use a dummy DS like Spark does.


class MyScanBuilder(
val partitionKeys: Seq[String]) extends SimpleScanBuilder
with SupportsReportStatistics with SupportsReportPartitioning {

override def estimateStatistics(): Statistics = {
new Statistics {
override def sizeInBytes(): OptionalLong = OptionalLong.of(80)

override def numRows(): OptionalLong = OptionalLong.of(10)

}
}

override def planInputPartitions(): Array[InputPartition] = {
Array(RangeInputPartition(0, 5), RangeInputPartition(5, 10))
}

override def outputPartitioning(): Partitioning = {
new KeyGroupedPartitioning(partitionKeys.map(FieldReference(_)).toArray, 10)
}
}

override def getTable(options: CaseInsensitiveStringMap): Table = {
new SimpleBatchTable {
override def newScanBuilder(options: CaseInsensitiveStringMap): ScanBuilder = {
new MyScanBuilder(Seq("i"))
}

override def partitioning(): Array[Transform] = {
Array(Expressions.identity("i"))
}
}
}
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,53 @@
/*
* 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.spark.sql

import java.util.OptionalLong

import org.apache.spark.sql.connector._
import org.apache.spark.sql.connector.catalog.Table
import org.apache.spark.sql.connector.read._
import org.apache.spark.sql.util.CaseInsensitiveStringMap

class ReportStatisticsDataSource extends SimpleWritableDataSource {

class MyScanBuilder extends SimpleScanBuilder
with SupportsReportStatistics {

override def estimateStatistics(): Statistics = {
new Statistics {
override def sizeInBytes(): OptionalLong = OptionalLong.of(80)

override def numRows(): OptionalLong = OptionalLong.of(10)
}
}

override def planInputPartitions(): Array[InputPartition] = {
Array(RangeInputPartition(0, 5), RangeInputPartition(5, 10))
}

}

override def getTable(options: CaseInsensitiveStringMap): Table = {
new SimpleBatchTable {
override def newScanBuilder(options: CaseInsensitiveStringMap): ScanBuilder = {
new MyScanBuilder
}
}
}
}
Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@ import scala.collection.JavaConverters._

import org.apache.commons.io.FileUtils
import org.apache.spark.sql.catalyst.plans.logical.{GlobalLimit, LogicalPlan}
import org.apache.spark.sql.execution.datasources.v2.DataSourceV2ScanRelation

import org.apache.kyuubi.sql.{KyuubiSQLConf, KyuubiSQLExtensionException}
import org.apache.kyuubi.sql.watchdog.{MaxFileSizeExceedException, MaxPartitionExceedException}
Expand Down Expand Up @@ -607,4 +608,36 @@ trait WatchDogSuiteBase extends KyuubiSparkSQLExtensionTest {
assert(e.getMessage == "Script transformation is not allowed")
}
}

test("watchdog with scan maxFileSize -- data source v2") {
val df = spark.read.format(classOf[ReportStatisticsAndPartitionAwareDataSource].getName).load()
df.createOrReplaceTempView("test")
val logical = df.queryExecution.optimizedPlan.collect {
case d: DataSourceV2ScanRelation => d
}.head
val tableSize = logical.computeStats().sizeInBytes.toLong
withSQLConf(KyuubiSQLConf.WATCHDOG_MAX_FILE_SIZE.key -> tableSize.toString) {
sql("SELECT * FROM test").queryExecution.sparkPlan
}
withSQLConf(KyuubiSQLConf.WATCHDOG_MAX_FILE_SIZE.key -> (tableSize / 2).toString) {
intercept[MaxFileSizeExceedException](
sql("SELECT * FROM test").queryExecution.sparkPlan)
}

val nonPartDf = spark.read.format(classOf[ReportStatisticsDataSource].getName).load()
nonPartDf.createOrReplaceTempView("test_non_part")
val nonPartLogical = nonPartDf.queryExecution.optimizedPlan.collect {
case d: DataSourceV2ScanRelation => d
}.head
val nonPartTableSize = nonPartLogical.computeStats().sizeInBytes.toLong

withSQLConf(KyuubiSQLConf.WATCHDOG_MAX_FILE_SIZE.key -> nonPartTableSize.toString) {
sql("SELECT * FROM test_non_part").queryExecution.sparkPlan
}

withSQLConf(KyuubiSQLConf.WATCHDOG_MAX_FILE_SIZE.key -> (nonPartTableSize / 2).toString) {
intercept[MaxFileSizeExceedException](
sql("SELECT * FROM test_non_part").queryExecution.sparkPlan)
}
}
}
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