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backends-velox/src/main/scala/org/apache/gluten/execution/ProjectColumnarExec.scala
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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.execution | ||
|
|
||
| import org.apache.gluten.GlutenConfig | ||
| import org.apache.gluten.columnarbatch.ColumnarBatches | ||
| import org.apache.gluten.extension.{GlutenPlan, ValidationResult} | ||
| import org.apache.gluten.memory.arrow.alloc.ArrowBufferAllocators | ||
| import org.apache.gluten.sql.shims.SparkShimLoader | ||
| import org.apache.gluten.utils.iterator.Iterators | ||
| import org.apache.gluten.vectorized.ArrowWritableColumnVector | ||
| import org.apache.spark.rdd.RDD | ||
| import org.apache.spark.sql.catalyst.InternalRow | ||
| import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference, MutableProjection, NamedExpression, SortOrder, UnsafeProjection, UnsafeRow} | ||
| import org.apache.spark.sql.execution.metric.SQLMetrics | ||
| import org.apache.spark.sql.execution.{ExplainUtils, OrderPreservingNodeShim, PartitioningPreservingNodeShim, SparkPlan, UnaryExecNode} | ||
| import org.apache.spark.sql.execution.vectorized.{MutableColumnarRow, WritableColumnVector} | ||
| import org.apache.spark.sql.types.{BinaryType, BooleanType, ByteType, DataType, DateType, DecimalType, DoubleType, FloatType, IntegerType, LongType, NullType, ShortType, StringType, TimestampType, YearMonthIntervalType} | ||
| import org.apache.spark.sql.utils.SparkSchemaUtil | ||
| import org.apache.spark.sql.vectorized.{ColumnVector, ColumnarBatch} | ||
|
|
||
| case class ProjectColumnarExec(projectList: Seq[NamedExpression], child: SparkPlan) | ||
| extends UnaryExecNode | ||
| with PartitioningPreservingNodeShim | ||
| with OrderPreservingNodeShim | ||
| with GlutenPlan { | ||
|
|
||
| @transient override lazy val metrics = Map( | ||
| "time" -> SQLMetrics.createTimingMetric(sparkContext, "time of project"), | ||
| "column_to_row_time" -> SQLMetrics.createTimingMetric( | ||
| sparkContext, | ||
| "time of velox to Arrow ColumnarBatch"), | ||
| "row_to_column_time" -> SQLMetrics.createTimingMetric( | ||
| sparkContext, | ||
| "time of Arrow ColumnarBatch to velox") | ||
| ) | ||
|
|
||
| private val (mutableProjectList, projectIndexInChild, projectIndexes) = removeAttributeReferenceFromProjectList() | ||
|
|
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| private val mutableProjectOutput = mutableProjectList.map(_.toAttribute) | ||
|
|
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| override protected def orderingExpressions: Seq[SortOrder] = child.outputOrdering | ||
|
|
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| override protected def outputExpressions: Seq[NamedExpression] = projectList | ||
|
|
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| override protected def doExecute(): RDD[InternalRow] = throw new UnsupportedOperationException() | ||
|
|
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| override protected def withNewChildInternal(newChild: SparkPlan): SparkPlan = | ||
| copy(child = newChild) | ||
|
|
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| override def output: Seq[Attribute] = projectList.map(_.toAttribute) | ||
|
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| override def supportsColumnar: Boolean = true | ||
|
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|
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|
|
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| // Only the mutable data type is valid | ||
| private def validateDataType(dataType: DataType): Boolean = { | ||
| dataType match { | ||
| case _: BooleanType => true | ||
| case _: ByteType => true | ||
| case _: ShortType => true | ||
| case _: IntegerType => true | ||
| case _: LongType => true | ||
| case _: FloatType => true | ||
| case _: DoubleType => true | ||
| case _: TimestampType => true | ||
| case _: DateType => true | ||
| case _: DecimalType => true | ||
| case _ => false | ||
| } | ||
| } | ||
|
|
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| // Return the expression in projectList to MutableProjection | ||
| // Return the index in child output | ||
| // Return the index in this operator output | ||
| private def removeAttributeReferenceFromProjectList(): (Seq[NamedExpression], Seq[Int], Seq[Int]) = { | ||
| val childOutput = child.output | ||
| val (attrs, notAttrs) = projectList.zipWithIndex.partition(e => e._1.isInstanceOf[AttributeReference]) | ||
| (notAttrs.map(_._1), attrs.map( a => childOutput.indexWhere(a._1.exprId == _.exprId)), attrs.map(_._2)) | ||
| } | ||
|
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| // override def doExecuteColumnar(): RDD[ColumnarBatch] = { | ||
| // val timeMetric = longMetric("time") | ||
| // val c2rTime = longMetric("column_to_row_time") | ||
| // val r2cTime = longMetric("row_to_column_time") | ||
| // child.executeColumnar().mapPartitions { | ||
| // batches => | ||
| // val res: Iterator[Iterator[ColumnarBatch]] = new Iterator[Iterator[ColumnarBatch]] { | ||
| // override def hasNext: Boolean = batches.hasNext | ||
| // | ||
| // override def next(): Iterator[ColumnarBatch] = { | ||
| // val batch = batches.next() | ||
| // if (batch.numRows == 0) { | ||
| // Iterator.empty | ||
| // } else { | ||
| // val start = System.currentTimeMillis() | ||
| // val proj = MutableProjection.create(mutableProjectList, child.output) | ||
| // val numRows = batch.numRows() | ||
| // val c2rStart = System.currentTimeMillis() | ||
| // val arrowBatch = | ||
| // ColumnarBatches.ensureLoadedWithoutRefcount(ArrowBufferAllocators.contextInstance(), batch) | ||
| // c2rTime += System.currentTimeMillis() - c2rStart | ||
| // val selectedBatch = ColumnarBatches.select(batch, projectIndexInChild.toArray) | ||
| // | ||
| // val schema = | ||
| // SparkShimLoader.getSparkShims.structFromAttributes(mutableProjectOutput) | ||
| // val vectors: Array[WritableColumnVector] = ArrowWritableColumnVector | ||
| // .allocateColumns(numRows, schema) | ||
| // .map { | ||
| // vector => | ||
| // vector.setValueCount(numRows) | ||
| // vector.asInstanceOf[WritableColumnVector] | ||
| // } | ||
| // val targetRow = new MutableColumnarRow(vectors) | ||
| // for (i <- 0 until numRows) { | ||
| // targetRow.rowId = i | ||
| // proj.target(targetRow).apply(arrowBatch.getRow(i)) | ||
| // } | ||
| // val r2cStart = System.currentTimeMillis() | ||
| // val targetBatch = | ||
| // new ColumnarBatch(vectors.map(_.asInstanceOf[ColumnVector]), numRows) | ||
| // val veloxBatch = ColumnarBatches | ||
| // .ensureOffloaded(ArrowBufferAllocators.contextInstance(), targetBatch) | ||
| // r2cTime += System.currentTimeMillis() - r2cStart | ||
| // val composeBatch = if (selectedBatch.numCols() == 0) { | ||
| // ColumnarBatches.retain(veloxBatch) | ||
| // veloxBatch | ||
| // } else { | ||
| // val composeBatch = ColumnarBatches.composeWithReorder(selectedBatch, projectIndexes.toArray, veloxBatch) | ||
| // veloxBatch.close() | ||
| // composeBatch | ||
| // } | ||
| // timeMetric += System.currentTimeMillis() - start | ||
| // arrowBatch.close() | ||
| // targetBatch.close() | ||
| // selectedBatch.close() | ||
| // Iterator.single(composeBatch) | ||
| // } | ||
| // } | ||
| // } | ||
| // Iterators | ||
| // .wrap(res.flatten) | ||
| // .protectInvocationFlow() // Spark may call `hasNext()` again after a false output which | ||
| // // is not allowed by Gluten iterators. E.g. GroupedIterator#fetchNextGroupIterator | ||
| // .recyclePayload(_.close()) | ||
| // .create() | ||
| // } | ||
| // } | ||
|
|
||
| override def doExecuteColumnar(): RDD[ColumnarBatch] = { | ||
| val timeMetric = longMetric("time") | ||
| val c2rTime = longMetric("column_to_row_time") | ||
| val r2cTime = longMetric("row_to_column_time") | ||
| val childOutput = child.output | ||
| child.executeColumnar().mapPartitions { | ||
| batches => | ||
| val res: Iterator[Iterator[ColumnarBatch]] = new Iterator[Iterator[ColumnarBatch]] { | ||
| override def hasNext: Boolean = batches.hasNext | ||
|
|
||
| override def next(): Iterator[ColumnarBatch] = { | ||
| val batch = batches.next() | ||
| if (batch.numRows == 0) { | ||
| Iterator.empty | ||
| } else { | ||
| val start = System.currentTimeMillis() | ||
| val proj = UnsafeProjection.create(mutableProjectList, childOutput) | ||
| val c2rStart = System.currentTimeMillis() | ||
| val rows = VeloxColumnarToRowExec.toRowIterator(Iterator.single(batch), childOutput).map(proj) | ||
| c2rTime += System.currentTimeMillis() - c2rStart | ||
| val selectedBatch = ColumnarBatches.select(batch, projectIndexInChild.toArray) | ||
| val schema = | ||
| SparkShimLoader.getSparkShims.structFromAttributes(mutableProjectOutput) | ||
| val iter = RowToVeloxColumnarExec.toColumnarBatchIterator( | ||
| rows, | ||
| schema, | ||
| batch.numRows()).map { | ||
| b => if (selectedBatch.numCols() == 0) { | ||
| ColumnarBatches.retain(b) | ||
| selectedBatch.close() | ||
| b | ||
| } else { | ||
| print("project batch" + ColumnarBatches.toString(b, 0, 20)) | ||
| val composeBatch = ColumnarBatches.composeWithReorder(selectedBatch, projectIndexes.toArray, b) | ||
| b.close() | ||
| selectedBatch.close() | ||
| composeBatch | ||
| } | ||
| } | ||
| timeMetric += System.currentTimeMillis() - start | ||
| iter | ||
| } | ||
| } | ||
| } | ||
| Iterators | ||
| .wrap(res.flatten) | ||
| .protectInvocationFlow() // Spark may call `hasNext()` again after a false output which | ||
| // is not allowed by Gluten iterators. E.g. GroupedIterator#fetchNextGroupIterator | ||
| .recyclePayload(_.close()) | ||
| .create() | ||
| } | ||
| } | ||
|
|
||
| override def verboseStringWithOperatorId(): String = { | ||
| s""" | ||
| |$formattedNodeName | ||
| |${ExplainUtils.generateFieldString("Output", output)} | ||
| |${ExplainUtils.generateFieldString("Input", child.output)} | ||
| |${ExplainUtils.generateFieldString("MutableProject", mutableProjectList)} | ||
| |""".stripMargin | ||
| } | ||
|
|
||
| override protected def doValidateInternal(): ValidationResult = { | ||
| if (!GlutenConfig.getConf.enableProjectColumnarExec) { | ||
| return ValidationResult.failed("Config disable this feature") | ||
| } | ||
| if (mutableProjectOutput.exists(f => !validateDataType(f.dataType))) { | ||
| return ValidationResult.failed("Output type is not mutable") | ||
| } | ||
| if (mutableProjectOutput.size == projectList.size) { | ||
| return ValidationResult.failed("All the project list is needed") | ||
| } | ||
| ValidationResult.succeeded | ||
| } | ||
| } |
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