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Original file line number Diff line number Diff line change
Expand Up @@ -33,6 +33,8 @@ class AttributeMap[A](baseMap: Map[ExprId, (Attribute, A)])

override def get(k: Attribute): Option[A] = baseMap.get(k.exprId).map(_._2)

override def contains(k: Attribute): Boolean = get(k).isDefined

override def + [B1 >: A](kv: (Attribute, B1)): Map[Attribute, B1] = baseMap.values.toMap + kv

override def iterator: Iterator[(Attribute, A)] = baseMap.valuesIterator
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Expand Up @@ -22,6 +22,7 @@ import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.expressions.aggregate.AggregateExpression
import org.apache.spark.sql.catalyst.plans._
import org.apache.spark.sql.catalyst.plans.logical.statsEstimation.ProjectEstimation
import org.apache.spark.sql.types._
import org.apache.spark.util.Utils

Expand Down Expand Up @@ -53,6 +54,9 @@ case class Project(projectList: Seq[NamedExpression], child: LogicalPlan) extend

override def validConstraints: Set[Expression] =
child.constraints.union(getAliasedConstraints(projectList))

override lazy val statistics: Statistics =
ProjectEstimation.estimate(this).getOrElse(super.statistics)
}

/**
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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.
*/

package org.apache.spark.sql.catalyst.plans.logical.statsEstimation

import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeMap}
import org.apache.spark.sql.catalyst.plans.logical.{ColumnStat, LogicalPlan}
import org.apache.spark.sql.types.StringType


object EstimationUtils {

/** Check if each plan has rowCount in its statistics. */
def rowCountsExist(plans: LogicalPlan*): Boolean =
plans.forall(_.statistics.rowCount.isDefined)

/** Get column stats for output attributes. */
def getOutputMap(inputMap: AttributeMap[ColumnStat], output: Seq[Attribute])
: AttributeMap[ColumnStat] = {
AttributeMap(output.flatMap(a => inputMap.get(a).map(a -> _)))
}

def getRowSize(attributes: Seq[Attribute], attrStats: AttributeMap[ColumnStat]): Long = {
// We assign a generic overhead for a Row object, the actual overhead is different for different
// Row format.
8 + attributes.map { attr =>
if (attrStats.contains(attr)) {
attr.dataType match {
case StringType =>
// UTF8String: base + offset + numBytes
attrStats(attr).avgLen + 8 + 4
case _ =>
attrStats(attr).avgLen
}
} else {
attr.dataType.defaultSize
}
}.sum
}
}
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@@ -0,0 +1,44 @@
/*
* 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.catalyst.plans.logical.statsEstimation

import org.apache.spark.sql.catalyst.expressions.{Alias, Attribute, AttributeMap}
import org.apache.spark.sql.catalyst.plans.logical.{Project, Statistics}

object ProjectEstimation {
import EstimationUtils._

def estimate(project: Project): Option[Statistics] = {
if (rowCountsExist(project.child)) {
val childStats = project.child.statistics
val inputAttrStats = childStats.attributeStats
// Match alias with its child's column stat
val aliasStats = project.expressions.collect {
case alias @ Alias(attr: Attribute, _) if inputAttrStats.contains(attr) =>
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my question from before was really whether we need to match on other things as well (that are not just Alias - e.g. can an attribute be other NamedExpression?)

cc @cloud-fan

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In the long run, we should define a statistics interface in Expression, so that we can propagate the column stats more naturally, for more cases(not only Alias, but also Add, Mod, etc.). But currently catalyst doesn't propagate attributes correctly, e.g. https://issues.apache.org/jira/browse/SPARK-17995 (Union, Except, etc. has the same problem), we may need to hack a lot of places to propagate column stats correctly.

According to @wzhfy 's benchmark, it turns out we can speed up most of the cases if we take care of Alias, so I'm ok with the current approach.

alias.toAttribute -> inputAttrStats(attr)
}
val outputAttrStats =
getOutputMap(AttributeMap(inputAttrStats.toSeq ++ aliasStats), project.output)
Some(childStats.copy(
sizeInBytes = childStats.rowCount.get * getRowSize(project.output, outputAttrStats),
attributeStats = outputAttrStats))
} else {
None
}
}
}
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@@ -0,0 +1,51 @@
/*
* 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.catalyst.statsEstimation

import org.apache.spark.sql.catalyst.expressions.{Alias, AttributeMap, AttributeReference}
import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.plans.logical.statsEstimation.EstimationUtils._
import org.apache.spark.sql.types.IntegerType


class ProjectEstimationSuite extends StatsEstimationTestBase {

test("estimate project with alias") {
val ar1 = AttributeReference("key1", IntegerType)()
val ar2 = AttributeReference("key2", IntegerType)()
val colStat1 = ColumnStat(2, Some(1), Some(2), 0, 4, 4)
val colStat2 = ColumnStat(1, Some(10), Some(10), 0, 4, 4)

val child = StatsTestPlan(
outputList = Seq(ar1, ar2),
stats = Statistics(
sizeInBytes = 2 * (4 + 4),
rowCount = Some(2),
attributeStats = AttributeMap(Seq(ar1 -> colStat1, ar2 -> colStat2))))

val project = Project(Seq(ar1, Alias(ar2, "abc")()), child)
val expectedColStats = Seq("key1" -> colStat1, "abc" -> colStat2)
val expectedAttrStats = toAttributeMap(expectedColStats, project)
// The number of rows won't change for project.
val expectedStats = Statistics(
sizeInBytes = 2 * getRowSize(project.output, expectedAttrStats),
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the way this test is written getRowSize is completely untested. We can almost change getRowSize to always return 0 and all the tests would pass. Can you have test cases covering it?

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I tested getRowSize for int type. But yes, we should have a separate test for this method.

rowCount = Some(2),
attributeStats = expectedAttrStats)
assert(project.statistics == expectedStats)
}
}
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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.spark.sql.catalyst.statsEstimation

import org.apache.spark.SparkFunSuite
import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeMap}
import org.apache.spark.sql.catalyst.plans.logical.{ColumnStat, LeafNode, LogicalPlan, Statistics}


class StatsEstimationTestBase extends SparkFunSuite {

/** Convert (column name, column stat) pairs to an AttributeMap based on plan output. */
def toAttributeMap(colStats: Seq[(String, ColumnStat)], plan: LogicalPlan)
: AttributeMap[ColumnStat] = {
val nameToAttr: Map[String, Attribute] = plan.output.map(a => (a.name, a)).toMap
AttributeMap(colStats.map(kv => nameToAttr(kv._1) -> kv._2))
}
}

/**
* This class is used for unit-testing. It's a logical plan whose output and stats are passed in.
*/
protected case class StatsTestPlan(outputList: Seq[Attribute], stats: Statistics) extends LeafNode {
override def output: Seq[Attribute] = outputList
override lazy val statistics = stats
}