[SPARK-31312][SQL] Cache Class instance for the UDF instance in HiveFunctionWrapper #28079
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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.hive | ||
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| import org.apache.spark.sql.{QueryTest, Row} | ||
| import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Expression} | ||
| import org.apache.spark.sql.hive.HiveShim.HiveFunctionWrapper | ||
| import org.apache.spark.sql.hive.test.TestHiveSingleton | ||
| import org.apache.spark.sql.test.SQLTestUtils | ||
| import org.apache.spark.sql.types.{IntegerType, StringType} | ||
| import org.apache.spark.util.Utils | ||
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| class HiveUDFDynamicLoadSuite extends QueryTest with SQLTestUtils with TestHiveSingleton { | ||
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| case class UDFTestInformation( | ||
| identifier: String, | ||
| funcName: String, | ||
| className: String, | ||
| fnVerifyQuery: () => Unit, | ||
| fnCreateHiveUDFExpression: () => Expression) | ||
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| private val udfTestInfos: Seq[UDFTestInformation] = Array( | ||
| // UDF | ||
| // UDFExampleAdd2 is slightly modified version of UDFExampleAdd in hive/contrib, | ||
| // which adds two integers or doubles. | ||
| UDFTestInformation( | ||
| "UDF", | ||
| "udf_add2", | ||
| "org.apache.hadoop.hive.contrib.udf.example.UDFExampleAdd2", | ||
| () => { | ||
| checkAnswer(sql("SELECT udf_add2(1, 2)"), Row(3) :: Nil) | ||
| }, | ||
| () => { | ||
| HiveSimpleUDF( | ||
| "default.udf_add2", | ||
| HiveFunctionWrapper("org.apache.hadoop.hive.contrib.udf.example.UDFExampleAdd2"), | ||
| Array( | ||
| AttributeReference("a", IntegerType, nullable = false)(), | ||
| AttributeReference("b", IntegerType, nullable = false)())) | ||
| }), | ||
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| // GenericUDF | ||
| // GenericUDFTrim2 is cloned version of GenericUDFTrim in hive/contrib. | ||
| UDFTestInformation( | ||
| "GENERIC_UDF", | ||
| "generic_udf_trim2", | ||
| "org.apache.hadoop.hive.contrib.udf.example.GenericUDFTrim2", | ||
| () => { | ||
| checkAnswer(sql("SELECT generic_udf_trim2(' hello ')"), Row("hello") :: Nil) | ||
| }, | ||
| () => { | ||
| HiveGenericUDF( | ||
| "default.generic_udf_trim2", | ||
| HiveFunctionWrapper("org.apache.hadoop.hive.contrib.udf.example.GenericUDFTrim2"), | ||
| Array(AttributeReference("a", StringType, nullable = false)()) | ||
| ) | ||
| } | ||
| ), | ||
|
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||
| // AbstractGenericUDAFResolver | ||
| // GenericUDAFSum2 is cloned version of GenericUDAFSum in hive/exec. | ||
| UDFTestInformation( | ||
| "GENERIC_UDAF", | ||
| "generic_udaf_sum2", | ||
| "org.apache.hadoop.hive.ql.udf.generic.GenericUDAFSum2", | ||
| () => { | ||
| import spark.implicits._ | ||
| val df = Seq((0: Integer) -> 0, (1: Integer) -> 1, (2: Integer) -> 2, (3: Integer) -> 3) | ||
| .toDF("key", "value").createOrReplaceTempView("t") | ||
| checkAnswer(sql("SELECT generic_udaf_sum2(value) FROM t GROUP BY key % 2"), | ||
| Row(2) :: Row(4) :: Nil) | ||
| }, | ||
| () => { | ||
| HiveUDAFFunction( | ||
| "default.generic_udaf_sum2", | ||
| HiveFunctionWrapper("org.apache.hadoop.hive.ql.udf.generic.GenericUDAFSum2"), | ||
| Array(AttributeReference("a", IntegerType, nullable = false)()) | ||
| ) | ||
| } | ||
| ), | ||
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| // UDAF | ||
| // UDAFExampleMax2 is cloned version of UDAFExampleMax in hive/contrib. | ||
| UDFTestInformation( | ||
| "UDAF", | ||
| "udaf_max2", | ||
| "org.apache.hadoop.hive.contrib.udaf.example.UDAFExampleMax2", | ||
| () => { | ||
| import spark.implicits._ | ||
| val df = Seq((0: Integer) -> 0, (1: Integer) -> 1, (2: Integer) -> 2, (3: Integer) -> 3) | ||
| .toDF("key", "value").createOrReplaceTempView("t") | ||
| checkAnswer(sql("SELECT udaf_max2(value) FROM t GROUP BY key % 2"), | ||
| Row(2) :: Row(3) :: Nil) | ||
| }, | ||
| () => { | ||
| HiveUDAFFunction( | ||
| "default.udaf_max2", | ||
| HiveFunctionWrapper("org.apache.hadoop.hive.contrib.udaf.example.UDAFExampleMax2"), | ||
| Array(AttributeReference("a", IntegerType, nullable = false)()), | ||
| isUDAFBridgeRequired = true | ||
| ) | ||
| } | ||
| ), | ||
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||
| // GenericUDTF | ||
| // GenericUDTFCount3 is slightly modified version of GenericUDTFCount2 in hive/contrib, | ||
| // which emits the count for three times. | ||
| UDFTestInformation( | ||
| "GENERIC_UDTF", | ||
| "udtf_count3", | ||
| "org.apache.hadoop.hive.contrib.udtf.example.GenericUDTFCount3", | ||
| () => { | ||
| checkAnswer( | ||
| sql("SELECT udtf_count3(a) FROM (SELECT 1 AS a FROM src LIMIT 3) t"), | ||
| Row(3) :: Row(3) :: Row(3) :: Nil) | ||
| }, | ||
| () => { | ||
| HiveGenericUDTF( | ||
| "default.udtf_count3", | ||
| HiveFunctionWrapper("org.apache.hadoop.hive.contrib.udtf.example.GenericUDTFCount3"), | ||
| Array.empty[Expression] | ||
| ) | ||
| } | ||
| ) | ||
| ) | ||
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| udfTestInfos.foreach { udfInfo => | ||
| // The test jars are built from below commit: | ||
| // https://github.com/HeartSaVioR/hive/commit/12f3f036b6efd0299cd1d457c0c0a65e0fd7e5f2 | ||
| // which contain new UDF classes to be dynamically loaded and tested via Spark. | ||
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| // This jar file should not be placed to the classpath. | ||
| val jarPath = "src/test/noclasspath/hive-test-udfs.jar" | ||
| val jarUrl = s"file://${System.getProperty("user.dir")}/$jarPath" | ||
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| test("Spark should be able to run Hive UDF using jar regardless of " + | ||
| s"current thread context classloader (${udfInfo.identifier}") { | ||
| Utils.withContextClassLoader(Utils.getSparkClassLoader) { | ||
| withUserDefinedFunction(udfInfo.funcName -> false) { | ||
| val sparkClassLoader = Thread.currentThread().getContextClassLoader | ||
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| sql(s"CREATE FUNCTION ${udfInfo.funcName} AS '${udfInfo.className}' USING JAR '$jarUrl'") | ||
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| assert(Thread.currentThread().getContextClassLoader eq sparkClassLoader) | ||
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| // JAR will be loaded at first usage, and it will change the current thread's | ||
| // context classloader to jar classloader in sharedState. | ||
| // See SessionState.addJar for details. | ||
| udfInfo.fnVerifyQuery() | ||
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| assert(Thread.currentThread().getContextClassLoader ne sparkClassLoader) | ||
| assert(Thread.currentThread().getContextClassLoader eq | ||
| spark.sqlContext.sharedState.jarClassLoader) | ||
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| val udfExpr = udfInfo.fnCreateHiveUDFExpression() | ||
| // force initializing - this is what we do in HiveSessionCatalog | ||
| udfExpr.dataType | ||
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| // Roll back to the original classloader and run query again. Without this line, the test | ||
| // would pass, as thread's context classloader is changed to jar classloader. But thread | ||
| // context classloader can be changed from others as well which would fail the query; one | ||
| // example is spark-shell, which thread context classloader rolls back automatically. This | ||
| // mimics the behavior of spark-shell. | ||
| Thread.currentThread().setContextClassLoader(sparkClassLoader) | ||
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| udfInfo.fnVerifyQuery() | ||
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| val newExpr = udfExpr.makeCopy(udfExpr.productIterator.map(_.asInstanceOf[AnyRef]) | ||
| .toArray) | ||
| newExpr.dataType | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } |
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If we add
clazz = nullbelow this line, the new UT (SPARK-31312) fails with UDF type (only one of 5 fails, because other cases this cases instance instead).