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[SPARK-9992][SPARK-9994][SPARK-9998][SQL]Implement the local TopK, sample and intersect operators #8573
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[SPARK-9992][SPARK-9994][SPARK-9998][SQL]Implement the local TopK, sample and intersect operators #8573
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d252265
Implement the local sample operator
zsxwing d1acc2a
Implement the local TopK operator
zsxwing 4ccca2a
Implement the local intersect operator
zsxwing 4090902
Merge branch 'master' into more-local-operators
zsxwing a3270b0
Address Andrew's comments
zsxwing File filter
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63 changes: 63 additions & 0 deletions
63
sql/core/src/main/scala/org/apache/spark/sql/execution/local/IntersectNode.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. | ||
*/ | ||
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package org.apache.spark.sql.execution.local | ||
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import scala.collection.mutable | ||
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import org.apache.spark.sql.SQLConf | ||
import org.apache.spark.sql.catalyst.InternalRow | ||
import org.apache.spark.sql.catalyst.expressions.Attribute | ||
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case class IntersectNode(conf: SQLConf, left: LocalNode, right: LocalNode) | ||
extends BinaryLocalNode(conf) { | ||
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override def output: Seq[Attribute] = left.output | ||
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private[this] var leftRows: mutable.HashSet[InternalRow] = _ | ||
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private[this] var currentRow: InternalRow = _ | ||
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override def open(): Unit = { | ||
left.open() | ||
leftRows = mutable.HashSet[InternalRow]() | ||
while (left.next()) { | ||
leftRows += left.fetch().copy() | ||
} | ||
left.close() | ||
right.open() | ||
} | ||
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override def next(): Boolean = { | ||
currentRow = null | ||
while (currentRow == null && right.next()) { | ||
currentRow = right.fetch() | ||
if (!leftRows.contains(currentRow)) { | ||
currentRow = null | ||
} | ||
} | ||
currentRow != null | ||
} | ||
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override def fetch(): InternalRow = currentRow | ||
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override def close(): Unit = { | ||
left.close() | ||
right.close() | ||
} | ||
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} |
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82 changes: 82 additions & 0 deletions
82
sql/core/src/main/scala/org/apache/spark/sql/execution/local/SampleNode.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. | ||
*/ | ||
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package org.apache.spark.sql.execution.local | ||
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import java.util.Random | ||
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import org.apache.spark.sql.SQLConf | ||
import org.apache.spark.sql.catalyst.InternalRow | ||
import org.apache.spark.sql.catalyst.expressions.Attribute | ||
import org.apache.spark.util.random.{BernoulliCellSampler, PoissonSampler} | ||
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/** | ||
* Sample the dataset. | ||
* | ||
* @param conf the SQLConf | ||
* @param lowerBound Lower-bound of the sampling probability (usually 0.0) | ||
* @param upperBound Upper-bound of the sampling probability. The expected fraction sampled | ||
* will be ub - lb. | ||
* @param withReplacement Whether to sample with replacement. | ||
* @param seed the random seed | ||
* @param child the LocalNode | ||
*/ | ||
case class SampleNode( | ||
conf: SQLConf, | ||
lowerBound: Double, | ||
upperBound: Double, | ||
withReplacement: Boolean, | ||
seed: Long, | ||
child: LocalNode) extends UnaryLocalNode(conf) { | ||
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override def output: Seq[Attribute] = child.output | ||
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private[this] var iterator: Iterator[InternalRow] = _ | ||
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private[this] var currentRow: InternalRow = _ | ||
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override def open(): Unit = { | ||
child.open() | ||
val (sampler, _seed) = if (withReplacement) { | ||
val random = new Random(seed) | ||
// Disable gap sampling since the gap sampling method buffers two rows internally, | ||
// requiring us to copy the row, which is more expensive than the random number generator. | ||
(new PoissonSampler[InternalRow](upperBound - lowerBound, useGapSamplingIfPossible = false), | ||
// Use the seed for partition 0 like PartitionwiseSampledRDD to generate the same result | ||
// of DataFrame | ||
random.nextLong()) | ||
} else { | ||
(new BernoulliCellSampler[InternalRow](lowerBound, upperBound), seed) | ||
} | ||
sampler.setSeed(_seed) | ||
iterator = sampler.sample(child.asIterator) | ||
} | ||
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override def next(): Boolean = { | ||
if (iterator.hasNext) { | ||
currentRow = iterator.next() | ||
true | ||
} else { | ||
false | ||
} | ||
} | ||
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override def fetch(): InternalRow = currentRow | ||
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override def close(): Unit = child.close() | ||
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} |
73 changes: 73 additions & 0 deletions
73
sql/core/src/main/scala/org/apache/spark/sql/execution/local/TakeOrderedAndProjectNode.scala
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@@ -0,0 +1,73 @@ | ||
/* | ||
* 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. | ||
*/ | ||
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package org.apache.spark.sql.execution.local | ||
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import org.apache.spark.sql.SQLConf | ||
import org.apache.spark.sql.catalyst.InternalRow | ||
import org.apache.spark.sql.catalyst.expressions._ | ||
import org.apache.spark.util.BoundedPriorityQueue | ||
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case class TakeOrderedAndProjectNode( | ||
conf: SQLConf, | ||
limit: Int, | ||
sortOrder: Seq[SortOrder], | ||
projectList: Option[Seq[NamedExpression]], | ||
child: LocalNode) extends UnaryLocalNode(conf) { | ||
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private[this] var projection: Option[Projection] = _ | ||
private[this] var ord: InterpretedOrdering = _ | ||
private[this] var iterator: Iterator[InternalRow] = _ | ||
private[this] var currentRow: InternalRow = _ | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. can you
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override def output: Seq[Attribute] = { | ||
val projectOutput = projectList.map(_.map(_.toAttribute)) | ||
projectOutput.getOrElse(child.output) | ||
} | ||
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override def open(): Unit = { | ||
child.open() | ||
projection = projectList.map(new InterpretedProjection(_, child.output)) | ||
ord = new InterpretedOrdering(sortOrder, child.output) | ||
// Priority keeps the largest elements, so let's reverse the ordering. | ||
val queue = new BoundedPriorityQueue[InternalRow](limit)(ord.reverse) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. need to copy the comment here too:
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while (child.next()) { | ||
queue += child.fetch() | ||
} | ||
// Close it eagerly since we don't need it. | ||
child.close() | ||
iterator = queue.iterator | ||
} | ||
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override def next(): Boolean = { | ||
if (iterator.hasNext) { | ||
val _currentRow = iterator.next() | ||
currentRow = projection match { | ||
case Some(p) => p(_currentRow) | ||
case None => _currentRow | ||
} | ||
true | ||
} else { | ||
false | ||
} | ||
} | ||
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override def fetch(): InternalRow = currentRow | ||
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override def close(): Unit = child.close() | ||
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} |
35 changes: 35 additions & 0 deletions
35
sql/core/src/test/scala/org/apache/spark/sql/execution/local/IntersectNodeSuite.scala
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@@ -0,0 +1,35 @@ | ||
/* | ||
* 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. | ||
*/ | ||
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package org.apache.spark.sql.execution.local | ||
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class IntersectNodeSuite extends LocalNodeTest { | ||
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import testImplicits._ | ||
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test("basic") { | ||
val input1 = (1 to 10).map(i => (i, i.toString)).toDF("key", "value") | ||
val input2 = (1 to 10).filter(_ % 2 == 0).map(i => (i, i.toString)).toDF("key", "value") | ||
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checkAnswer2( | ||
input1, | ||
input2, | ||
(node1, node2) => IntersectNode(conf, node1, node2), | ||
input1.intersect(input2).collect() | ||
) | ||
} | ||
} |
40 changes: 40 additions & 0 deletions
40
sql/core/src/test/scala/org/apache/spark/sql/execution/local/SampleNodeSuite.scala
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@@ -0,0 +1,40 @@ | ||
/* | ||
* 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. | ||
*/ | ||
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package org.apache.spark.sql.execution.local | ||
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class SampleNodeSuite extends LocalNodeTest { | ||
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import testImplicits._ | ||
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private def testSample(withReplacement: Boolean): Unit = { | ||
test(s"withReplacement: $withReplacement") { | ||
val seed = 0L | ||
val input = sqlContext.sparkContext. | ||
parallelize((1 to 10).map(i => (i, i.toString)), 1). // Should be only 1 partition | ||
toDF("key", "value") | ||
checkAnswer( | ||
input, | ||
node => SampleNode(conf, 0.0, 0.3, withReplacement, seed, node), | ||
input.sample(withReplacement, 0.3, seed).collect() | ||
) | ||
} | ||
} | ||
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testSample(withReplacement = true) | ||
testSample(withReplacement = false) | ||
} |
54 changes: 54 additions & 0 deletions
54
.../src/test/scala/org/apache/spark/sql/execution/local/TakeOrderedAndProjectNodeSuite.scala
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@@ -0,0 +1,54 @@ | ||
/* | ||
* 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. | ||
*/ | ||
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package org.apache.spark.sql.execution.local | ||
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import org.apache.spark.sql.Column | ||
import org.apache.spark.sql.catalyst.expressions.{Ascending, Expression, SortOrder} | ||
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class TakeOrderedAndProjectNodeSuite extends LocalNodeTest { | ||
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import testImplicits._ | ||
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private def columnToSortOrder(sortExprs: Column*): Seq[SortOrder] = { | ||
val sortOrder: Seq[SortOrder] = sortExprs.map { col => | ||
col.expr match { | ||
case expr: SortOrder => | ||
expr | ||
case expr: Expression => | ||
SortOrder(expr, Ascending) | ||
} | ||
} | ||
sortOrder | ||
} | ||
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private def testTakeOrderedAndProjectNode(desc: Boolean): Unit = { | ||
val testCaseName = if (desc) "desc" else "asc" | ||
test(testCaseName) { | ||
val input = (1 to 10).map(i => (i, i.toString)).toDF("key", "value") | ||
val sortColumn = if (desc) input.col("key").desc else input.col("key") | ||
checkAnswer( | ||
input, | ||
node => TakeOrderedAndProjectNode(conf, 5, columnToSortOrder(sortColumn), None, node), | ||
input.sort(sortColumn).limit(5).collect() | ||
) | ||
} | ||
} | ||
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testTakeOrderedAndProjectNode(desc = false) | ||
testTakeOrderedAndProjectNode(desc = true) | ||
} |
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hm, why not just use the provided seed? It will allow us to test this more deterministically. We can just have the seed in the constructor default to
Utils.random.nextLong
just like howPartitionwiseSampledRDD
does it.There was a problem hiding this comment.
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PartitionwiseSampledRDD doesn't use the provided seed directly, it calls
random.nextLong
to createseed
for each partition. Here I want to makeSampleNode
generate the same result like the first partition ofPartitionwiseSampledRDD
, so I don't use the provided seed directly.There was a problem hiding this comment.
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I see, it uses the seed to generate a random seed