[GitHub] [spark] panbingkun commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
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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[GitHub] [spark] panbingkun commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
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] panbingkun commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
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
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} = $resultTerm;
+ |}
+ |""".stripMargin
+)
+ }
+}
+
+abstract class HiveUDFEvaluatorBase[UDFType <: AnyRef](
Review Comment:
Ok
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[GitHub] [spark] panbingkun commented on a diff in pull request #40397: [SPARK-42052][SQL] Codegen Support for HiveSimpleUDF
panbingkun commented on code in PR #40397:
URL: https://github.com/apache/spark/pull/40397#discussion_r1137141359
##
sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala:
##
@@ -49,68 +48,140 @@ private[hive] case class HiveSimpleUDF(
name: String, funcWrapper: HiveFunctionWrapper, children: Seq[Expression])
extends Expression
with HiveInspectors
- with CodegenFallback
- with Logging
with UserDefinedExpression {
+ @transient
+ private lazy val evaluator = new HiveSimpleUDFEvaluator(funcWrapper,
children)
+
+ @transient
+ private val isUDFDeterministic = {
+val udfType =
evaluator.function.getClass.getAnnotation(classOf[HiveUDFType])
+udfType != null && udfType.deterministic() && !udfType.stateful()
+ }
+
override lazy val deterministic: Boolean = isUDFDeterministic &&
children.forall(_.deterministic)
override def nullable: Boolean = true
- @transient
- lazy val function = funcWrapper.createFunction[UDF]()
+ override def foldable: Boolean = isUDFDeterministic &&
children.forall(_.foldable)
+
+ override lazy val dataType: DataType =
javaTypeToDataType(evaluator.method.getGenericReturnType)
+
+ // TODO: Finish input output types.
+ override def eval(input: InternalRow): Any = {
+children.zipWithIndex.map {
+ case (child, idx) =>
+evaluator.setArg(idx, child.eval(input))
+}
+evaluator.evaluate()
+ }
+
+ override def toString: String = {
+s"$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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