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[SPARK-19851][SQL] Add support for EVERY and ANY (SOME) aggregates #22809

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Original file line number Diff line number Diff line change
Expand Up @@ -300,6 +300,9 @@ object FunctionRegistry {
expression[CollectList]("collect_list"),
expression[CollectSet]("collect_set"),
expression[CountMinSketchAgg]("count_min_sketch"),
expression[EveryAgg]("every"),
expression[AnyAgg]("any"),
expression[SomeAgg]("some"),

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nit: unneeded newline

// string functions
expression[Ascii]("ascii"),
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Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@ import java.util.Locale

import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.analysis.{TypeCheckResult, TypeCoercion}
import org.apache.spark.sql.catalyst.expressions.aggregate.DeclarativeAggregate
import org.apache.spark.sql.catalyst.expressions.codegen._
import org.apache.spark.sql.catalyst.expressions.codegen.Block._
import org.apache.spark.sql.catalyst.trees.TreeNode
Expand Down Expand Up @@ -282,6 +283,31 @@ trait RuntimeReplaceable extends UnaryExpression with Unevaluable {
override lazy val canonicalized: Expression = child.canonicalized
}

/**
* An aggregate expression that gets rewritten (currently by the optimizer) into a
* different aggregate expression for evaluation. This is mainly used to provide compatibility
* with other databases. For example, we use this to support every, any/some aggregates by rewriting
* them with Min and Max respectively.
*/
trait UnevaluableAggregate extends DeclarativeAggregate {

override def nullable: Boolean = true
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why do we set them always as nullable?

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@mgaido91 most of the aggregates are nullable, no ? Did you have an suggestion here ?

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shouldn't this be nullable only if the incoming expression is?

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@dilipbiswal dilipbiswal Oct 26, 2018

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@mgaido91 I think for aggregates, its different ? Please see Max, Min, they all define it to be nullable. I think they work on group of rows and can return null on empty input.

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Ah, right, I was missing that case, sorry, thanks.


override lazy val aggBufferAttributes =
throw new UnsupportedOperationException(s"Cannot evaluate aggBufferAttributes: $this")

override lazy val initialValues: Seq[Expression] =
throw new UnsupportedOperationException(s"Cannot evaluate initialValues: $this")

override lazy val updateExpressions: Seq[Expression] =
throw new UnsupportedOperationException(s"Cannot evaluate updateExpressions: $this")

override lazy val mergeExpressions: Seq[Expression] =
throw new UnsupportedOperationException(s"Cannot evaluate mergeExpressions: $this")

override lazy val evaluateExpression: Expression =
throw new UnsupportedOperationException(s"Cannot evaluate evaluateExpression: $this")
}

/**
* Expressions that don't have SQL representation should extend this trait. Examples are
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Original file line number Diff line number Diff line change
@@ -0,0 +1,62 @@
/*
* 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.expressions.aggregate

import org.apache.spark.sql.catalyst.analysis.TypeCheckResult
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.types._

abstract class UnevaluableBooleanAggBase(arg: Expression)
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why don't we reuse RuntimeReplaceable?

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@mgaido91 RuntimeReplaceble works for scalar expressions but not for aggregate expressions.

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why it doesn't work? Sorry if the question is dumb, but I can't see the problem in using it here, probably I am missing something.

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@dilipbiswal dilipbiswal Oct 26, 2018

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@mgaido91 Actually i tried a few different ideas. They are in the comment of original PR link. I had prepared two branches with two approaches .. [comment] (#22047 (comment)). Could you please take a look ?

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ok, I see you mentioned that there were issues using RuntimeReplaceble. Can we have a similar approach to that though? I mean introducing a new method here which returns the replaced value, so that in ReplaceExpressions we can simply match on UnevaluableAggregate and include the logic of replacement in the single items?

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@mgaido91 I tried it here. I had trouble getting it to work for window expressions. Thats why @cloud-fan suggested to try the current approach in this comment

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@dilipbiswal dilipbiswal Oct 26, 2018

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@mgaido91 I re-read your comments again and here is what i think you are implying :

  1. In UnevaluableAggregate, define a method say replacedExpression
  2. The sub-class overrides it and return an actual rewritten expression
  3. In optimized, match UnevaluableAggregate and call replacedExpression

Did i understand it correctly ? If so, actually, i wouldn't prefer that way. The reason is, the replacedExpression is hidden from analyzer and so it may not be safe. The way ReplaceExpression framework is nicely designed, the analyzer resolves the rewritten expression normally (as its the child expression). Thats the reason, i have opted for specific/targeted rewrites.

If Wenchen and you think otherwise, then i can change.

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yes, but in the analyzer you analyze the children of the current expression right? So we would just have something like def replacedExpression = Min(arg), which means doing exactly the same which is done now, the only difference is where the conversion logic is put. Adn IMHO having all the conversion logic for all the expression in ReplaceExpressions is harder to maintain than having all the logic related to the expression contained in it.

Anyway, since you have a different opinion, let's see what @cloud-fan thinks on this. Thanks.

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We can leave a TODO saying that we should create a framework to replace aggregate functions, but I think the current patch is good enough for these 3 functions, and I'm not aware of more functions like them that we need to deal with.

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@cloud-fan @mgaido91 Thank you. I have added a TODO for now.

extends UnevaluableAggregate with ImplicitCastInputTypes {

override def children: Seq[Expression] = arg :: Nil

override def dataType: DataType = BooleanType

override def inputTypes: Seq[AbstractDataType] = Seq(BooleanType)

override def checkInputDataTypes(): TypeCheckResult = {
arg.dataType match {
case dt if dt != BooleanType =>
TypeCheckResult.TypeCheckFailure(s"Input to function '$prettyName' should have been " +
s"${BooleanType.simpleString}, but it's [${arg.dataType.catalogString}].")
case _ => TypeCheckResult.TypeCheckSuccess
}
}
}

@ExpressionDescription(
usage = "_FUNC_(expr) - Returns true if all values of `expr` are true.",
since = "3.0.0")
case class EveryAgg(arg: Expression) extends UnevaluableBooleanAggBase(arg) {
override def nodeName: String = "Every"
}

@ExpressionDescription(
usage = "_FUNC_(expr) - Returns true if at least one value of `expr` is true.",
since = "3.0.0")
case class AnyAgg(arg: Expression) extends UnevaluableBooleanAggBase(arg) {
override def nodeName: String = "Any"
}

@ExpressionDescription(
usage = "_FUNC_(expr) - Returns true if at least one value of `expr` is true.",
since = "3.0.0")
case class SomeAgg(arg: Expression) extends UnevaluableBooleanAggBase(arg) {
override def nodeName: String = "Some"
}
Original file line number Diff line number Diff line change
Expand Up @@ -21,20 +21,29 @@ import scala.collection.mutable

import org.apache.spark.sql.catalyst.catalog.SessionCatalog
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.expressions.aggregate._
import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.rules._
import org.apache.spark.sql.catalyst.util.DateTimeUtils
import org.apache.spark.sql.types._


/**
* Finds all [[RuntimeReplaceable]] expressions and replace them with the expressions that can
* be evaluated. This is mainly used to provide compatibility with other databases.
* For example, we use this to support "nvl" by replacing it with "coalesce".
* Finds all the expressions that are unevaluable and replace/rewrite them with semantically
* equivalent expressions that can be evaluated. Currently we replace two kinds of expressions:
* 1) [[RuntimeReplaceable]] expressions
* 2) [[UnevaluableAggregate]] expressions such as Every, Some, Any
* This is mainly used to provide compatibility with other databases.
* Few examples are:
* we use this to support "nvl" by replacing it with "coalesce".
* we use this to replace Every and Any with Min and Max respectively.
*/
object ReplaceExpressions extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = plan transformAllExpressions {
case e: RuntimeReplaceable => e.child
case SomeAgg(arg) => Max(arg)
case AnyAgg(arg) => Max(arg)
case EveryAgg(arg) => Min(arg)
}
}

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Original file line number Diff line number Diff line change
Expand Up @@ -144,6 +144,9 @@ class ExpressionTypeCheckingSuite extends SparkFunSuite {
assertSuccess(Sum('stringField))
assertSuccess(Average('stringField))
assertSuccess(Min('arrayField))
assertSuccess(new EveryAgg('booleanField))
assertSuccess(new AnyAgg('booleanField))
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shall we add also SomeAgg?

assertSuccess(new SomeAgg('booleanField))

assertError(Min('mapField), "min does not support ordering on type")
assertError(Max('mapField), "max does not support ordering on type")
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66 changes: 66 additions & 0 deletions sql/core/src/test/resources/sql-tests/inputs/group-by.sql
Original file line number Diff line number Diff line change
Expand Up @@ -80,3 +80,69 @@ SELECT 1 FROM range(10) HAVING true;
SELECT 1 FROM range(10) HAVING MAX(id) > 0;

SELECT id FROM range(10) HAVING id > 0;

-- Test data
CREATE OR REPLACE TEMPORARY VIEW test_agg AS SELECT * FROM VALUES
(1, true), (1, false),
(2, true),
(3, false), (3, null),
(4, null), (4, null),
(5, null), (5, true), (5, false) AS test_agg(k, v);

-- empty table
SELECT every(v), some(v), any(v) FROM test_agg WHERE 1 = 0;

-- all null values
SELECT every(v), some(v), any(v) FROM test_agg WHERE k = 4;

-- aggregates are null Filtering
SELECT every(v), some(v), any(v) FROM test_agg WHERE k = 5;

-- group by
SELECT k, every(v), some(v), any(v) FROM test_agg GROUP BY k;

-- having
SELECT k, every(v) FROM test_agg GROUP BY k HAVING every(v) = false;
SELECT k, every(v) FROM test_agg GROUP BY k HAVING every(v) IS NULL;

-- basic subquery path to make sure rewrite happens in both parent and child plans.
SELECT k,
Every(v) AS every
FROM test_agg
WHERE k = 2
AND v IN (SELECT Any(v)
FROM test_agg
WHERE k = 1)
GROUP BY k;

-- basic subquery path to make sure rewrite happens in both parent and child plans.
SELECT k,
Every(v) AS every
FROM test_agg
WHERE k = 2
AND v IN (SELECT Every(v)
FROM test_agg
WHERE k = 1)
GROUP BY k;

-- input type checking Int
SELECT every(1);

-- input type checking Short
SELECT some(1S);

-- input type checking Long
SELECT any(1L);

-- input type checking String
SELECT every("true");

-- every/some/any aggregates are supported as windows expression.
SELECT k, v, every(v) OVER (PARTITION BY k ORDER BY v) FROM test_agg;
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@dilipbiswal dilipbiswal Oct 24, 2018

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@cloud-fan here are a few window tests. (fyi)

SELECT k, v, some(v) OVER (PARTITION BY k ORDER BY v) FROM test_agg;
SELECT k, v, any(v) OVER (PARTITION BY k ORDER BY v) FROM test_agg;

-- simple explain of queries having every/some/any agregates. Optimized
-- plan should show the rewritten aggregate expression.
EXPLAIN EXTENDED SELECT k, every(v), some(v), any(v) FROM test_agg GROUP BY k;

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