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Posted to reviews@spark.apache.org by "panbingkun (via GitHub)" <gi...@apache.org> on 2023/03/13 11:58:58 UTC
[GitHub] [spark] panbingkun opened a new pull request, #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
panbingkun opened a new pull request, #40397:
URL: https://github.com/apache/spark/pull/40397
### What changes were proposed in this pull request?
### Why are the changes needed?
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Add new UT.
Pass GA.
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[GitHub] [spark] cloud-fan commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1139897525
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##########
@@ -49,68 +48,137 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper, children)
+
override lazy val deterministic: Boolean = isUDFDeterministic && children.forall(_.deterministic)
override def nullable: Boolean = true
@transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ private val isUDFDeterministic = {
+ val udfType = evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
+ }
+
+ override def foldable: Boolean = isUDFDeterministic && children.forall(_.foldable)
+
+ override lazy val dataType: DataType = javaTypeToDataType(evaluator.method.getGenericReturnType)
+
+ // TODO: Finish input output types.
+ override def eval(input: InternalRow): Any = {
+ children.zipWithIndex.map {
+ case (child, idx) =>
+ evaluator.setArg(idx, child.eval(input))
Review Comment:
```suggestion
case (child, idx) => evaluator.setArg(idx, child.eval(input))
```
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[GitHub] [spark] cloud-fan commented on pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on PR #40397:
URL: https://github.com/apache/spark/pull/40397#issuecomment-1478896479
thanks, merging to master!
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[GitHub] [spark] cloud-fan closed pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan closed pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
URL: https://github.com/apache/spark/pull/40397
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[GitHub] [spark] panbingkun commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "panbingkun (via GitHub)" <gi...@apache.org>.
panbingkun commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1140123443
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##########
@@ -49,68 +48,137 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper, children)
+
override lazy val deterministic: Boolean = isUDFDeterministic && children.forall(_.deterministic)
override def nullable: Boolean = true
@transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ private val isUDFDeterministic = {
+ val udfType = evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
+ }
+
+ override def foldable: Boolean = isUDFDeterministic && children.forall(_.foldable)
+
+ override lazy val dataType: DataType = javaTypeToDataType(evaluator.method.getGenericReturnType)
+
+ // TODO: Finish input output types.
+ override def eval(input: InternalRow): Any = {
+ children.zipWithIndex.map {
+ case (child, idx) =>
+ evaluator.setArg(idx, child.eval(input))
+ }
+ evaluator.evaluate()
+ }
+
+ override def toString: String = {
+ s"$nodeName#${funcWrapper.functionClassName}(${children.mkString(",")})"
+ }
+
+ override def prettyName: String = name
+
+ override def sql: String = s"$name(${children.map(_.sql).mkString(", ")})"
+
+ override protected def withNewChildrenInternal(newChildren: IndexedSeq[Expression]): Expression =
+ copy(children = newChildren)
+
+ protected def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
+ val refEvaluator = ctx.addReferenceObj("evaluator", evaluator)
+ val evals = children.map(_.genCode(ctx))
+
+ val setValues = evals.zipWithIndex.map {
+ case (eval, i) =>
+ s"""
+ |if (${eval.isNull}) {
+ | $refEvaluator.setArg($i, null);
+ |} else {
+ | $refEvaluator.setArg($i, ${eval.value});
+ |}
+ |""".stripMargin
+ }
+
+ val resultType = CodeGenerator.boxedType(dataType)
+ val resultTerm = ctx.freshName("result")
+ ev.copy(code =
+ code"""
+ |${evals.map(_.code).mkString("\n")}
+ |${setValues.mkString("\n")}
+ |$resultType $resultTerm = null;
+ |boolean ${ev.isNull} = false;
+ |try {
+ | $resultTerm = ($resultType) $refEvaluator.evaluate();
+ | ${ev.isNull} = $resultTerm == null;
+ |} catch (Throwable e) {
+ | throw QueryExecutionErrors.failedExecuteUserDefinedFunctionError(
Review Comment:
Done
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[GitHub] [spark] panbingkun commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "panbingkun (via GitHub)" <gi...@apache.org>.
panbingkun commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1140125291
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFEvaluators.scala:
##########
@@ -0,0 +1,148 @@
+/*
+ * 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.hive
+
+import scala.collection.JavaConverters._
+
+import org.apache.hadoop.hive.ql.exec.{FunctionRegistry, UDF}
+import org.apache.hadoop.hive.ql.udf.{UDFType => HiveUDFType}
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDF
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDF._
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils.ConversionHelper
+import org.apache.hadoop.hive.serde2.objectinspector.{ObjectInspector, ObjectInspectorFactory}
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory.ObjectInspectorOptions
+
+import org.apache.spark.sql.catalyst.expressions.Expression
+import org.apache.spark.sql.errors.QueryExecutionErrors
+import org.apache.spark.sql.hive.HiveShim.HiveFunctionWrapper
+import org.apache.spark.sql.types.DataType
+
+abstract class HiveUDFEvaluatorBase[UDFType <: AnyRef](
+ funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
+ extends HiveInspectors with Serializable {
+
+ @transient
+ lazy val function = funcWrapper.createFunction[UDFType]()
+
+ @transient
+ val isUDFDeterministic = {
+ val udfType = function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
+ }
+
+ def returnType: DataType
Review Comment:
We have to add this method here because it will be used in exception handling.
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[GitHub] [spark] cloud-fan commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1139898978
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##########
@@ -49,68 +48,137 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper, children)
+
override lazy val deterministic: Boolean = isUDFDeterministic && children.forall(_.deterministic)
override def nullable: Boolean = true
@transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ private val isUDFDeterministic = {
+ val udfType = evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
+ }
+
+ override def foldable: Boolean = isUDFDeterministic && children.forall(_.foldable)
+
+ override lazy val dataType: DataType = javaTypeToDataType(evaluator.method.getGenericReturnType)
+
+ // TODO: Finish input output types.
+ override def eval(input: InternalRow): Any = {
+ children.zipWithIndex.map {
+ case (child, idx) =>
+ evaluator.setArg(idx, child.eval(input))
+ }
+ evaluator.evaluate()
+ }
+
+ override def toString: String = {
+ s"$nodeName#${funcWrapper.functionClassName}(${children.mkString(",")})"
+ }
+
+ override def prettyName: String = name
+
+ override def sql: String = s"$name(${children.map(_.sql).mkString(", ")})"
+
+ override protected def withNewChildrenInternal(newChildren: IndexedSeq[Expression]): Expression =
+ copy(children = newChildren)
+
+ protected def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
+ val refEvaluator = ctx.addReferenceObj("evaluator", evaluator)
+ val evals = children.map(_.genCode(ctx))
+
+ val setValues = evals.zipWithIndex.map {
+ case (eval, i) =>
+ s"""
+ |if (${eval.isNull}) {
+ | $refEvaluator.setArg($i, null);
+ |} else {
+ | $refEvaluator.setArg($i, ${eval.value});
+ |}
+ |""".stripMargin
+ }
+
+ val resultType = CodeGenerator.boxedType(dataType)
+ val resultTerm = ctx.freshName("result")
+ ev.copy(code =
+ code"""
+ |${evals.map(_.code).mkString("\n")}
+ |${setValues.mkString("\n")}
+ |$resultType $resultTerm = null;
+ |boolean ${ev.isNull} = false;
+ |try {
+ | $resultTerm = ($resultType) $refEvaluator.evaluate();
+ | ${ev.isNull} = $resultTerm == null;
+ |} catch (Throwable e) {
+ | throw QueryExecutionErrors.failedExecuteUserDefinedFunctionError(
Review Comment:
shall we move the try-catch to `evaluator.evaluate()`?
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[GitHub] [spark] panbingkun commented on pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "panbingkun (via GitHub)" <gi...@apache.org>.
panbingkun commented on PR #40397:
URL: https://github.com/apache/spark/pull/40397#issuecomment-1478870787
@cloud-fan Can we merge it to master? After it I will try to refactor HiveGenericUDTF & HiveUDAFFunction. Thanks!
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[GitHub] [spark] cloud-fan commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1139897200
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##########
@@ -49,68 +48,137 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper, children)
+
override lazy val deterministic: Boolean = isUDFDeterministic && children.forall(_.deterministic)
override def nullable: Boolean = true
@transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ private val isUDFDeterministic = {
+ val udfType = evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
Review Comment:
the code seems to be the same with generic UDF. maybe we can move it to `HiveUDFEvaluatorBase`
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[GitHub] [spark] panbingkun commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "panbingkun (via GitHub)" <gi...@apache.org>.
panbingkun commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1137141359
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##########
@@ -49,68 +48,140 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper, children)
+
+ @transient
+ private val isUDFDeterministic = {
+ val udfType = evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
+ }
+
override lazy val deterministic: Boolean = isUDFDeterministic && children.forall(_.deterministic)
override def nullable: Boolean = true
- @transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ override def foldable: Boolean = isUDFDeterministic && children.forall(_.foldable)
+
+ override lazy val dataType: DataType = javaTypeToDataType(evaluator.method.getGenericReturnType)
+
+ // TODO: Finish input output types.
+ override def eval(input: InternalRow): Any = {
+ children.zipWithIndex.map {
+ case (child, idx) =>
+ evaluator.setArg(idx, child.eval(input))
+ }
+ evaluator.evaluate()
+ }
+
+ override def toString: String = {
+ s"$nodeName#${funcWrapper.functionClassName}(${children.mkString(",")})"
+ }
+
+ override def prettyName: String = name
+
+ override def sql: String = s"$name(${children.map(_.sql).mkString(", ")})"
+
+ override protected def withNewChildrenInternal(newChildren: IndexedSeq[Expression]): Expression =
+ copy(children = newChildren)
+
+ protected def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
+ evaluator.doGenCode(ctx, ev, dataType)
+ }
+}
+
+abstract class HiveUDFEvaluatorBase[UDFType <: AnyRef](
+ funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
+ extends HiveInspectors with Serializable {
@transient
- private lazy val method =
- function.getResolver.getEvalMethod(children.map(_.dataType.toTypeInfo).asJava)
+ lazy val function = funcWrapper.createFunction[UDFType]()
+
+ def setArg(index: Int, arg: Any): Unit
+
+ def evaluate(): Any
+
+ final def doGenCode(ctx: CodegenContext, ev: ExprCode, dataType: DataType): ExprCode = {
Review Comment:
OK, Let's reserve some redundant logic first.
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[GitHub] [spark] panbingkun commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "panbingkun (via GitHub)" <gi...@apache.org>.
panbingkun commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1140123273
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##########
@@ -49,68 +48,137 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper, children)
+
override lazy val deterministic: Boolean = isUDFDeterministic && children.forall(_.deterministic)
override def nullable: Boolean = true
@transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ private val isUDFDeterministic = {
+ val udfType = evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
Review Comment:
OK
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##########
@@ -49,68 +48,137 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper, children)
+
override lazy val deterministic: Boolean = isUDFDeterministic && children.forall(_.deterministic)
override def nullable: Boolean = true
@transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ private val isUDFDeterministic = {
+ val udfType = evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
+ }
+
+ override def foldable: Boolean = isUDFDeterministic && children.forall(_.foldable)
+
+ override lazy val dataType: DataType = javaTypeToDataType(evaluator.method.getGenericReturnType)
+
+ // TODO: Finish input output types.
+ override def eval(input: InternalRow): Any = {
+ children.zipWithIndex.map {
+ case (child, idx) =>
+ evaluator.setArg(idx, child.eval(input))
+ }
+ evaluator.evaluate()
+ }
+
+ override def toString: String = {
+ s"$nodeName#${funcWrapper.functionClassName}(${children.mkString(",")})"
+ }
+
+ override def prettyName: String = name
+
+ override def sql: String = s"$name(${children.map(_.sql).mkString(", ")})"
+
+ override protected def withNewChildrenInternal(newChildren: IndexedSeq[Expression]): Expression =
+ copy(children = newChildren)
+
+ protected def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
+ val refEvaluator = ctx.addReferenceObj("evaluator", evaluator)
+ val evals = children.map(_.genCode(ctx))
+
+ val setValues = evals.zipWithIndex.map {
+ case (eval, i) =>
+ s"""
+ |if (${eval.isNull}) {
+ | $refEvaluator.setArg($i, null);
+ |} else {
+ | $refEvaluator.setArg($i, ${eval.value});
+ |}
+ |""".stripMargin
+ }
+
+ val resultType = CodeGenerator.boxedType(dataType)
+ val resultTerm = ctx.freshName("result")
+ ev.copy(code =
+ code"""
+ |${evals.map(_.code).mkString("\n")}
+ |${setValues.mkString("\n")}
+ |$resultType $resultTerm = null;
+ |boolean ${ev.isNull} = false;
+ |try {
+ | $resultTerm = ($resultType) $refEvaluator.evaluate();
+ | ${ev.isNull} = $resultTerm == null;
+ |} catch (Throwable e) {
+ | throw QueryExecutionErrors.failedExecuteUserDefinedFunctionError(
+ | "${funcWrapper.functionClassName}",
+ | "${children.map(_.dataType.catalogString).mkString(", ")}",
+ | "${dataType.catalogString}",
+ | e);
+ |}
+ |${CodeGenerator.javaType(dataType)} ${ev.value} = ${CodeGenerator.defaultValue(dataType)};
+ |if (!${ev.isNull}) {
+ | ${ev.value} = $resultTerm;
+ |}
+ |""".stripMargin
+ )
+ }
+}
+
+abstract class HiveUDFEvaluatorBase[UDFType <: AnyRef](
Review Comment:
Ok
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[GitHub] [spark] cloud-fan commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1140198056
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFEvaluators.scala:
##########
@@ -0,0 +1,148 @@
+/*
+ * 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.hive
+
+import scala.collection.JavaConverters._
+
+import org.apache.hadoop.hive.ql.exec.{FunctionRegistry, UDF}
+import org.apache.hadoop.hive.ql.udf.{UDFType => HiveUDFType}
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDF
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDF._
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils.ConversionHelper
+import org.apache.hadoop.hive.serde2.objectinspector.{ObjectInspector, ObjectInspectorFactory}
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory.ObjectInspectorOptions
+
+import org.apache.spark.sql.catalyst.expressions.Expression
+import org.apache.spark.sql.errors.QueryExecutionErrors
+import org.apache.spark.sql.hive.HiveShim.HiveFunctionWrapper
+import org.apache.spark.sql.types.DataType
+
+abstract class HiveUDFEvaluatorBase[UDFType <: AnyRef](
+ funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
+ extends HiveInspectors with Serializable {
+
+ @transient
+ lazy val function = funcWrapper.createFunction[UDFType]()
+
+ @transient
+ val isUDFDeterministic = {
Review Comment:
It should be `lazy val`, as it accesses a lazy val.
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[GitHub] [spark] panbingkun commented on pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "panbingkun (via GitHub)" <gi...@apache.org>.
panbingkun commented on PR #40397:
URL: https://github.com/apache/spark/pull/40397#issuecomment-1469911638
cc @cloud-fan
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[GitHub] [spark] cloud-fan commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1137003368
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##########
@@ -49,68 +48,140 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper, children)
+
+ @transient
+ private val isUDFDeterministic = {
+ val udfType = evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
+ }
+
override lazy val deterministic: Boolean = isUDFDeterministic && children.forall(_.deterministic)
override def nullable: Boolean = true
- @transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ override def foldable: Boolean = isUDFDeterministic && children.forall(_.foldable)
+
+ override lazy val dataType: DataType = javaTypeToDataType(evaluator.method.getGenericReturnType)
+
+ // TODO: Finish input output types.
+ override def eval(input: InternalRow): Any = {
+ children.zipWithIndex.map {
+ case (child, idx) =>
+ evaluator.setArg(idx, child.eval(input))
+ }
+ evaluator.evaluate()
+ }
+
+ override def toString: String = {
+ s"$nodeName#${funcWrapper.functionClassName}(${children.mkString(",")})"
+ }
+
+ override def prettyName: String = name
+
+ override def sql: String = s"$name(${children.map(_.sql).mkString(", ")})"
+
+ override protected def withNewChildrenInternal(newChildren: IndexedSeq[Expression]): Expression =
+ copy(children = newChildren)
+
+ protected def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
+ evaluator.doGenCode(ctx, ev, dataType)
+ }
+}
+
+abstract class HiveUDFEvaluatorBase[UDFType <: AnyRef](
+ funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
+ extends HiveInspectors with Serializable {
@transient
- private lazy val method =
- function.getResolver.getEvalMethod(children.map(_.dataType.toTypeInfo).asJava)
+ lazy val function = funcWrapper.createFunction[UDFType]()
+
+ def setArg(index: Int, arg: Any): Unit
+
+ def evaluate(): Any
+
+ final def doGenCode(ctx: CodegenContext, ev: ExprCode, dataType: DataType): ExprCode = {
Review Comment:
It's weird to implement codegen in the evaluator. If we really want to deduplicate the code, let's add `HiveUDFExpressionBase` later.
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[GitHub] [spark] cloud-fan commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1139896355
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##########
@@ -49,68 +48,137 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper, children)
+
override lazy val deterministic: Boolean = isUDFDeterministic && children.forall(_.deterministic)
override def nullable: Boolean = true
@transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ private val isUDFDeterministic = {
+ val udfType = evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
+ }
+
+ override def foldable: Boolean = isUDFDeterministic && children.forall(_.foldable)
+
+ override lazy val dataType: DataType = javaTypeToDataType(evaluator.method.getGenericReturnType)
+
+ // TODO: Finish input output types.
+ override def eval(input: InternalRow): Any = {
+ children.zipWithIndex.map {
+ case (child, idx) =>
+ evaluator.setArg(idx, child.eval(input))
+ }
+ evaluator.evaluate()
+ }
+
+ override def toString: String = {
+ s"$nodeName#${funcWrapper.functionClassName}(${children.mkString(",")})"
+ }
+
+ override def prettyName: String = name
+
+ override def sql: String = s"$name(${children.map(_.sql).mkString(", ")})"
+
+ override protected def withNewChildrenInternal(newChildren: IndexedSeq[Expression]): Expression =
+ copy(children = newChildren)
+
+ protected def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
+ val refEvaluator = ctx.addReferenceObj("evaluator", evaluator)
+ val evals = children.map(_.genCode(ctx))
+
+ val setValues = evals.zipWithIndex.map {
+ case (eval, i) =>
+ s"""
+ |if (${eval.isNull}) {
+ | $refEvaluator.setArg($i, null);
+ |} else {
+ | $refEvaluator.setArg($i, ${eval.value});
+ |}
+ |""".stripMargin
+ }
+
+ val resultType = CodeGenerator.boxedType(dataType)
+ val resultTerm = ctx.freshName("result")
+ ev.copy(code =
+ code"""
+ |${evals.map(_.code).mkString("\n")}
+ |${setValues.mkString("\n")}
+ |$resultType $resultTerm = null;
+ |boolean ${ev.isNull} = false;
+ |try {
+ | $resultTerm = ($resultType) $refEvaluator.evaluate();
+ | ${ev.isNull} = $resultTerm == null;
+ |} catch (Throwable e) {
+ | throw QueryExecutionErrors.failedExecuteUserDefinedFunctionError(
+ | "${funcWrapper.functionClassName}",
+ | "${children.map(_.dataType.catalogString).mkString(", ")}",
+ | "${dataType.catalogString}",
+ | e);
+ |}
+ |${CodeGenerator.javaType(dataType)} ${ev.value} = ${CodeGenerator.defaultValue(dataType)};
+ |if (!${ev.isNull}) {
+ | ${ev.value} = $resultTerm;
+ |}
+ |""".stripMargin
+ )
+ }
+}
+
+abstract class HiveUDFEvaluatorBase[UDFType <: AnyRef](
Review Comment:
can we move evaluators to a separated file?
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[GitHub] [spark] cloud-fan commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1139899830
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##########
@@ -49,68 +48,137 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper, children)
+
override lazy val deterministic: Boolean = isUDFDeterministic && children.forall(_.deterministic)
override def nullable: Boolean = true
@transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ private val isUDFDeterministic = {
+ val udfType = evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+ udfType != null && udfType.deterministic() && !udfType.stateful()
+ }
+
+ override def foldable: Boolean = isUDFDeterministic && children.forall(_.foldable)
+
+ override lazy val dataType: DataType = javaTypeToDataType(evaluator.method.getGenericReturnType)
+
+ // TODO: Finish input output types.
+ override def eval(input: InternalRow): Any = {
+ children.zipWithIndex.map {
+ case (child, idx) =>
+ evaluator.setArg(idx, child.eval(input))
+ }
+ evaluator.evaluate()
+ }
+
+ override def toString: String = {
+ s"$nodeName#${funcWrapper.functionClassName}(${children.mkString(",")})"
+ }
+
+ override def prettyName: String = name
+
+ override def sql: String = s"$name(${children.map(_.sql).mkString(", ")})"
+
+ override protected def withNewChildrenInternal(newChildren: IndexedSeq[Expression]): Expression =
+ copy(children = newChildren)
+
+ protected def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
+ val refEvaluator = ctx.addReferenceObj("evaluator", evaluator)
+ val evals = children.map(_.genCode(ctx))
+
+ val setValues = evals.zipWithIndex.map {
+ case (eval, i) =>
+ s"""
+ |if (${eval.isNull}) {
+ | $refEvaluator.setArg($i, null);
+ |} else {
+ | $refEvaluator.setArg($i, ${eval.value});
+ |}
+ |""".stripMargin
+ }
+
+ val resultType = CodeGenerator.boxedType(dataType)
+ val resultTerm = ctx.freshName("result")
+ ev.copy(code =
+ code"""
+ |${evals.map(_.code).mkString("\n")}
+ |${setValues.mkString("\n")}
+ |$resultType $resultTerm = null;
+ |boolean ${ev.isNull} = false;
+ |try {
+ | $resultTerm = ($resultType) $refEvaluator.evaluate();
+ | ${ev.isNull} = $resultTerm == null;
+ |} catch (Throwable e) {
+ | throw QueryExecutionErrors.failedExecuteUserDefinedFunctionError(
Review Comment:
BTW this seems like an unrelated change. The previous code does not rethrow the exception.
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[GitHub] [spark] panbingkun commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
Posted by "panbingkun (via GitHub)" <gi...@apache.org>.
panbingkun commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1140316433
##########
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFEvaluators.scala:
##########
@@ -0,0 +1,148 @@
+/*
+ * 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.hive
+
+import scala.collection.JavaConverters._
+
+import org.apache.hadoop.hive.ql.exec.{FunctionRegistry, UDF}
+import org.apache.hadoop.hive.ql.udf.{UDFType => HiveUDFType}
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDF
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDF._
+import org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils.ConversionHelper
+import org.apache.hadoop.hive.serde2.objectinspector.{ObjectInspector, ObjectInspectorFactory}
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory.ObjectInspectorOptions
+
+import org.apache.spark.sql.catalyst.expressions.Expression
+import org.apache.spark.sql.errors.QueryExecutionErrors
+import org.apache.spark.sql.hive.HiveShim.HiveFunctionWrapper
+import org.apache.spark.sql.types.DataType
+
+abstract class HiveUDFEvaluatorBase[UDFType <: AnyRef](
+ funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
+ extends HiveInspectors with Serializable {
+
+ @transient
+ lazy val function = funcWrapper.createFunction[UDFType]()
+
+ @transient
+ val isUDFDeterministic = {
Review Comment:
Done
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