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perf: fuse Comet cache vector reads into Spark codegen #5859
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ec92ee5
perf: reduce Spark cache row conversion overhead
peterxcli 17dcdc6
chore: remove cache row reader benchmark results
peterxcli 8dc61ad
perf: feed cached Arrow columns into Spark codegen
peterxcli 091eb00
docs: illustrate Comet cache columnar rewrite
peterxcli eafdba5
fix: honor Comet disable switches for fused cache reads
peterxcli 49b7ec0
fix: align cache fusion with Spark codegen settings
peterxcli 03981e5
Merge branch 'main' into codex/cache-spark-consumer-benchmark
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95 changes: 95 additions & 0 deletions
95
spark/src/main/scala/org/apache/comet/rules/CometCacheColumnarRule.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,95 @@ | ||
| /* | ||
| * 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.comet.rules | ||
|
|
||
| import org.apache.spark.sql.catalyst.expressions.LeafExpression | ||
| import org.apache.spark.sql.catalyst.expressions.codegen.CodegenFallback | ||
| import org.apache.spark.sql.catalyst.rules.Rule | ||
| import org.apache.spark.sql.comet.execution.arrow.ArrowCachedBatchSerializer | ||
| import org.apache.spark.sql.execution.{CodegenSupport, ColumnarToRowExec, ColumnarToRowTransition, SparkPlan, WholeStageCodegenExec} | ||
| import org.apache.spark.sql.execution.adaptive.QueryStageExec | ||
| import org.apache.spark.sql.execution.columnar.InMemoryTableScanExec | ||
| import org.apache.spark.sql.internal.SQLConf | ||
|
|
||
| import org.apache.comet.CometConf.COMET_EXEC_IN_MEMORY_CACHE_ENABLED | ||
| import org.apache.comet.CometSparkSessionExtensions.isCometLoaded | ||
|
|
||
| /** | ||
| * Lets Spark's generated consumers read cached Arrow vectors without an intermediate UnsafeRow. | ||
| * | ||
| * Data flows upward. Spark's InputAdapter/whole-stage wrappers and an optional AQE cache stage | ||
| * are omitted: | ||
| * {{{ | ||
| * Before After | ||
| * +------------------------+ +------------------------+ | ||
| * | Spark codegen consumer | | Spark codegen consumer | | ||
| * +------------------------+ +------------------------+ | ||
| * ^ ^ | ||
| * | UnsafeRow | column values | ||
| * +------------------------+ +------------------------+ | ||
| * | InMemoryTableScanExec | | ColumnarToRowExec | | ||
| * | row iterator | | fused with consumer | | ||
| * +------------------------+ +------------------------+ | ||
| * ^ | ||
| * | ColumnarBatch | ||
| * +------------------------+ | ||
| * | InMemoryTableScanExec | | ||
| * | Arrow vectors | | ||
| * +------------------------+ | ||
| * }}} | ||
| */ | ||
| object CometCacheColumnarRule extends Rule[SparkPlan] { | ||
| override def apply(plan: SparkPlan): SparkPlan = { | ||
| if (!isCometLoaded(conf) || !COMET_EXEC_IN_MEMORY_CACHE_ENABLED.get(conf)) return plan | ||
| if (!conf.wholeStageEnabled) return plan | ||
| if (conf.getConf(SQLConf.CODEGEN_FACTORY_MODE).toString == "NO_CODEGEN") return plan | ||
|
|
||
| plan.transformUp { | ||
| case parent: CodegenSupport | ||
| if parent.supportCodegen && !parent.supportsColumnar && | ||
| !parent.isInstanceOf[ColumnarToRowTransition] && | ||
| !WholeStageCodegenExec.isTooManyFields(conf, parent.schema) && | ||
| !parent.children.exists(p => WholeStageCodegenExec.isTooManyFields(conf, p.schema)) && | ||
| !parent.expressions.exists(_.exists { | ||
| case _: LeafExpression => false | ||
| case _: CodegenFallback => true | ||
| case _ => false | ||
| }) => | ||
| // Match the consuming edge rather than every scan: an existing columnar consumer (or a | ||
| // cache stage being materialized by AQE) must keep receiving batches. Spark inserts an | ||
| // InputAdapter around the scan later, while this transition fuses with the row consumer. | ||
| parent.withNewChildren(parent.children.map { | ||
| case child if isColumnarCometCache(child) => ColumnarToRowExec(child) | ||
| case child => child | ||
| }) | ||
| } | ||
| } | ||
|
|
||
| private def isColumnarCometCache(plan: SparkPlan): Boolean = { | ||
| plan.supportsColumnar && (plan match { | ||
| case scan: InMemoryTableScanExec => | ||
| // The serializer delegates unsupported schemas to Spark, whose cache keeps its own reader. | ||
| scan.relation.cacheBuilder.serializer.isInstanceOf[ArrowCachedBatchSerializer] && | ||
| ArrowCachedBatchSerializer.supportsSchema(scan.relation.output) | ||
| case stage: QueryStageExec => isColumnarCometCache(stage.plan) | ||
| case _ => false | ||
| }) | ||
| } | ||
| } | ||
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131 changes: 131 additions & 0 deletions
131
spark/src/main/scala/org/apache/spark/sql/comet/execution/arrow/CachedBatchRowIterator.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,131 @@ | ||
| /* | ||
| * 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.comet.execution.arrow | ||
|
|
||
| import org.apache.spark.sql.catalyst.InternalRow | ||
| import org.apache.spark.sql.catalyst.expressions.{Attribute, BoundReference, CodeGeneratorWithInterpretedFallback, InterpretedUnsafeProjection} | ||
| import org.apache.spark.sql.catalyst.expressions.codegen._ | ||
| import org.apache.spark.sql.catalyst.expressions.codegen.Block._ | ||
| import org.apache.spark.sql.vectorized.{ColumnarBatch, ColumnVector} | ||
|
|
||
| /** | ||
| * Reads vectors directly into Spark's reusable UnsafeRow buffer. The input iterator owns the | ||
| * batches and releases them on advancement or task completion. As with Spark's cache reader, | ||
| * callers must copy rows they retain across next(), but the returned row owns its variable-width | ||
| * values and remains valid when hasNext() releases the batch that supplied them. | ||
| */ | ||
| private[arrow] class CachedBatchRowIterator(attributes: Seq[Attribute]) | ||
| extends CodeGeneratorWithInterpretedFallback[Iterator[ColumnarBatch], Iterator[InternalRow]] { | ||
|
|
||
| private def fields: Seq[BoundReference] = attributes.zipWithIndex.map { case (attr, i) => | ||
| BoundReference(i, attr.dataType, attr.nullable) | ||
| } | ||
|
|
||
| override protected def createCodeGeneratedObject( | ||
| batches: Iterator[ColumnarBatch]): Iterator[InternalRow] = { | ||
| val ctx = new CodegenContext | ||
| val columns = attributes.indices.map { i => | ||
| ctx.addMutableState(classOf[ColumnVector].getName, s"column$i") | ||
| } | ||
| ctx.currentVars = attributes.zip(columns).map { case (attr, column) => | ||
| val value = JavaCode.variable(ctx.freshName("value"), attr.dataType) | ||
| val getter = CodeGenerator.getValueFromVector(column, attr.dataType, "rowId") | ||
| val javaType = CodeGenerator.javaType(attr.dataType) | ||
| if (attr.nullable) { | ||
| val isNull = JavaCode.isNullVariable(ctx.freshName("isNull")) | ||
| ExprCode( | ||
| code""" | ||
| boolean $isNull = $column.isNullAt(rowId); | ||
| $javaType $value = $isNull ? ${CodeGenerator.defaultValue(attr.dataType)} : ($getter); | ||
| """, | ||
| isNull, | ||
| value) | ||
| } else { | ||
| ExprCode(code"$javaType $value = $getter;", FalseLiteral, value) | ||
| } | ||
| } | ||
| val projection = GenerateUnsafeProjection.createCode(ctx, fields) | ||
| val batchesRef = ctx.addReferenceObj("batches", batches, "scala.collection.Iterator") | ||
| val bindColumns = columns.zipWithIndex | ||
| .map { case (column, i) => | ||
| s"$column = batch.column($i);" | ||
| } | ||
| .mkString("\n") | ||
| val code = s""" | ||
| public Object generate(Object[] references) { | ||
| return new SpecificCachedBatchRowIterator(references); | ||
| } | ||
|
|
||
| class SpecificCachedBatchRowIterator extends scala.collection.AbstractIterator { | ||
| private final Object[] references; | ||
| private final scala.collection.Iterator batches; | ||
| private int rowId = 0; | ||
| private int numRows = 0; | ||
| ${ctx.declareMutableStates()} | ||
|
|
||
| public SpecificCachedBatchRowIterator(Object[] references) { | ||
| this.references = references; | ||
| this.batches = $batchesRef; | ||
| ${ctx.initMutableStates()} | ||
| } | ||
|
|
||
| public boolean hasNext() { | ||
| while (rowId >= numRows && batches.hasNext()) { | ||
| ${classOf[ColumnarBatch].getName} batch = | ||
| (${classOf[ColumnarBatch].getName}) batches.next(); | ||
| numRows = batch.numRows(); | ||
| rowId = 0; | ||
| $bindColumns | ||
| } | ||
| return rowId < numRows; | ||
| } | ||
|
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| public InternalRow next() { | ||
| if (!hasNext()) throw new java.util.NoSuchElementException(); | ||
| ${projection.code} | ||
| rowId++; | ||
| return ${projection.value}; | ||
| } | ||
|
|
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| ${ctx.declareAddedFunctions()} | ||
| } | ||
| """ | ||
| val (compiled, _) = | ||
| CodeGenerator.compile(new CodeAndComment(code, ctx.getPlaceHolderToComments())) | ||
| compiled.generate(ctx.references.toArray).asInstanceOf[Iterator[InternalRow]] | ||
| } | ||
|
|
||
| override protected def createInterpretedObject( | ||
| batches: Iterator[ColumnarBatch]): Iterator[InternalRow] = { | ||
| val toUnsafe = InterpretedUnsafeProjection.createProjection(fields) | ||
| batches.flatMap { batch => | ||
| new Iterator[InternalRow] { | ||
| private var rowId = 0 | ||
| override def hasNext: Boolean = rowId < batch.numRows() | ||
| override def next(): InternalRow = { | ||
| if (!hasNext) throw new NoSuchElementException | ||
| val row = toUnsafe(batch.getRow(rowId)) | ||
| rowId += 1 | ||
| row | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } |
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