Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
/*
* 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.execution
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.expressions.codegen._
import org.apache.spark.sql.catalyst.expressions.codegen.Block._
import org.apache.spark.sql.catalyst.plans.physical.Partitioning
import org.apache.spark.sql.execution.metric.SQLMetrics
import org.apache.spark.sql.types._
/**
* For lazy computing, be sure the generator.terminate() called in the very last
* TODO reusing the CompletionIterator?
*/
private[execution] sealed case class LazyIterator(func: () => TraversableOnce[InternalRow])
extends Iterator[InternalRow] {
lazy val results: Iterator[InternalRow] = func().toIterator
override def hasNext: Boolean = results.hasNext
override def next(): InternalRow = results.next()
}
/**
* Applies a [[Generator]] to a stream of input rows, combining the
* output of each into a new stream of rows. This operation is similar to a `flatMap` in functional
* programming with one important additional feature, which allows the input rows to be joined with
* their output.
*
* This operator supports whole stage code generation for generators that do not implement
* terminate().
*
* @param generator the generator expression
* @param requiredChildOutput required attributes from child's output
* @param outer when true, each input row will be output at least once, even if the output of the
* given `generator` is empty.
* @param generatorOutput the qualified output attributes of the generator of this node, which
* constructed in analysis phase, and we can not change it, as the
* parent node bound with it already.
*/
case class GenerateExec(
generator: Generator,
requiredChildOutput: Seq[Attribute],
outer: Boolean,
generatorOutput: Seq[Attribute],
child: SparkPlan)
extends UnaryExecNode with CodegenSupport {
override def output: Seq[Attribute] = requiredChildOutput ++ generatorOutput
override lazy val metrics = Map(
"numOutputRows" -> SQLMetrics.createMetric(sparkContext, "number of output rows"))
override def producedAttributes: AttributeSet = AttributeSet(generatorOutput)
override def outputPartitioning: Partitioning = child.outputPartitioning
lazy val boundGenerator: Generator = BindReferences.bindReference(generator, child.output)
protected override def doExecute(): RDD[InternalRow] = {
// boundGenerator.terminate() should be triggered after all of the rows in the partition
val numOutputRows = longMetric("numOutputRows")
child.execute().mapPartitionsWithIndexInternal { (index, iter) =>
val generatorNullRow = new GenericInternalRow(generator.elementSchema.length)
val rows = if (requiredChildOutput.nonEmpty) {
val pruneChildForResult: InternalRow => InternalRow =
if (child.outputSet == AttributeSet(requiredChildOutput)) {
identity
} else {
UnsafeProjection.create(requiredChildOutput, child.output)
}
val joinedRow = new JoinedRow
iter.flatMap { row =>
// we should always set the left (required child output)
joinedRow.withLeft(pruneChildForResult(row))
val outputRows = boundGenerator.eval(row)
if (outer && outputRows.isEmpty) {
joinedRow.withRight(generatorNullRow) :: Nil
} else {
outputRows.toIterator.map(joinedRow.withRight)
}
} ++ LazyIterator(() => boundGenerator.terminate()).map { row =>
// we leave the left side as the last element of its child output
// keep it the same as Hive does
joinedRow.withRight(row)
}
} else {
iter.flatMap { row =>
val outputRows = boundGenerator.eval(row)
if (outer && outputRows.isEmpty) {
Seq(generatorNullRow)
} else {
outputRows
}
} ++ LazyIterator(() => boundGenerator.terminate())
}
// Convert the rows to unsafe rows.
val proj = UnsafeProjection.create(output, output)
proj.initialize(index)
rows.map { r =>
numOutputRows += 1
proj(r)
}
}
}
override def supportCodegen: Boolean = generator.supportCodegen
override def inputRDDs(): Seq[RDD[InternalRow]] = {
child.asInstanceOf[CodegenSupport].inputRDDs()
}
protected override def doProduce(ctx: CodegenContext): String = {
child.asInstanceOf[CodegenSupport].produce(ctx, this)
}
override def needCopyResult: Boolean = true
override def doConsume(ctx: CodegenContext, input: Seq[ExprCode], row: ExprCode): String = {
val requiredAttrSet = AttributeSet(requiredChildOutput)
val requiredInput = child.output.zip(input).filter {
case (attr, _) => requiredAttrSet.contains(attr)
}.map(_._2)
boundGenerator match {
case e: CollectionGenerator => codeGenCollection(ctx, e, requiredInput)
case g => codeGenTraversableOnce(ctx, g, requiredInput)
}
}
/**
* Generate code for [[CollectionGenerator]] expressions.
*/
private def codeGenCollection(
ctx: CodegenContext,
e: CollectionGenerator,
input: Seq[ExprCode]): String = {
// Generate code for the generator.
val data = e.genCode(ctx)
// Generate looping variables.
val index = ctx.freshName("index")
// Add a check if the generate outer flag is true.
val checks = optionalCode(outer, s"($index == -1)")
// Add position
val position = if (e.position) {
if (outer) {
Seq(ExprCode(
JavaCode.isNullExpression(s"$index == -1"),
JavaCode.variable(index, IntegerType)))
} else {
Seq(ExprCode(FalseLiteral, JavaCode.variable(index, IntegerType)))
}
} else {
Seq.empty
}
// Generate code for either ArrayData or MapData
val (initMapData, updateRowData, values) = e.collectionType match {
case ArrayType(st: StructType, nullable) if e.inline =>
val row = codeGenAccessor(ctx, data.value, "col", index, st, nullable, checks)
val fieldChecks = checks ++ optionalCode(nullable, row.isNull)
val columns = st.fields.toSeq.zipWithIndex.map { case (f, i) =>
codeGenAccessor(
ctx,
row.value,
s"st_col${i}",
i.toString,
f.dataType,
f.nullable,
fieldChecks)
}
("", row.code, columns)
case ArrayType(dataType, nullable) =>
("", "", Seq(codeGenAccessor(ctx, data.value, "col", index, dataType, nullable, checks)))
case MapType(keyType, valueType, valueContainsNull) =>
// Materialize the key and the value arrays before we enter the loop.
val keyArray = ctx.freshName("keyArray")
val valueArray = ctx.freshName("valueArray")
val initArrayData =
s"""
|ArrayData $keyArray = ${data.isNull} ? null : ${data.value}.keyArray();
|ArrayData $valueArray = ${data.isNull} ? null : ${data.value}.valueArray();
""".stripMargin
val values = Seq(
codeGenAccessor(ctx, keyArray, "key", index, keyType, nullable = false, checks),
codeGenAccessor(ctx, valueArray, "value", index, valueType, valueContainsNull, checks))
(initArrayData, "", values)
}
// In case of outer=true we need to make sure the loop is executed at-least once when the
// array/map contains no input. We do this by setting the looping index to -1 if there is no
// input, evaluation of the array is prevented by a check in the accessor code.
val numElements = ctx.freshName("numElements")
val init = if (outer) {
s"$numElements == 0 ? -1 : 0"
} else {
"0"
}
val numOutput = metricTerm(ctx, "numOutputRows")
s"""
|${data.code}
|$initMapData
|int $numElements = ${data.isNull} ? 0 : ${data.value}.numElements();
|for (int $index = $init; $index < $numElements; $index++) {
| $numOutput.add(1);
| $updateRowData
| ${consume(ctx, input ++ position ++ values)}
|}
""".stripMargin
}
/**
* Generate code for a regular [[TraversableOnce]] returning [[Generator]].
*/
private def codeGenTraversableOnce(
ctx: CodegenContext,
e: Expression,
requiredInput: Seq[ExprCode]): String = {
// Generate the code for the generator
val data = e.genCode(ctx)
// Generate looping variables.
val iterator = ctx.freshName("iterator")
val hasNext = ctx.freshName("hasNext")
val current = ctx.freshName("row")
// Add a check if the generate outer flag is true.
val checks = optionalCode(outer, s"!$hasNext")
val values = e.dataType match {
case ArrayType(st: StructType, nullable) =>
st.fields.toSeq.zipWithIndex.map { case (f, i) =>
codeGenAccessor(ctx, current, s"st_col${i}", s"$i", f.dataType, f.nullable, checks)
}
}
// In case of outer=true we need to make sure the loop is executed at-least-once when the
// iterator contains no input. We do this by adding an 'outer' variable which guarantees
// execution of the first iteration even if there is no input. Evaluation of the iterator is
// prevented by checks in the next() and accessor code.
val numOutput = metricTerm(ctx, "numOutputRows")
if (outer) {
val outerVal = ctx.freshName("outer")
s"""
|${data.code}
|scala.collection.Iterator $iterator = ${data.value}.toIterator();
|boolean $outerVal = true;
|while ($iterator.hasNext() || $outerVal) {
| $numOutput.add(1);
| boolean $hasNext = $iterator.hasNext();
| InternalRow $current = (InternalRow)($hasNext? $iterator.next() : null);
| $outerVal = false;
| ${consume(ctx, requiredInput ++ values)}
|}
""".stripMargin
} else {
s"""
|${data.code}
|scala.collection.Iterator $iterator = ${data.value}.toIterator();
|while ($iterator.hasNext()) {
| $numOutput.add(1);
| InternalRow $current = (InternalRow)($iterator.next());
| ${consume(ctx, requiredInput ++ values)}
|}
""".stripMargin
}
}
/**
* Generate accessor code for ArrayData and InternalRows.
*/
private def codeGenAccessor(
ctx: CodegenContext,
source: String,
name: String,
index: String,
dt: DataType,
nullable: Boolean,
initialChecks: Seq[String]): ExprCode = {
val value = ctx.freshName(name)
val javaType = CodeGenerator.javaType(dt)
val getter = CodeGenerator.getValue(source, dt, index)
val checks = initialChecks ++ optionalCode(nullable, s"$source.isNullAt($index)")
if (checks.nonEmpty) {
val isNull = ctx.freshName("isNull")
val code =
code"""
|boolean $isNull = ${checks.mkString(" || ")};
|$javaType $value = $isNull ? ${CodeGenerator.defaultValue(dt)} : $getter;
""".stripMargin
ExprCode(code, JavaCode.isNullVariable(isNull), JavaCode.variable(value, dt))
} else {
ExprCode(code"$javaType $value = $getter;", FalseLiteral, JavaCode.variable(value, dt))
}
}
private def optionalCode(condition: Boolean, code: => String): Seq[String] = {
if (condition) Seq(code)
else Seq.empty
}
override protected def withNewChildInternal(newChild: SparkPlan): GenerateExec =
copy(child = newChild)
}
