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new 2a6aa8e [SPARK-31312][SQL] Cache Class instance for the UDF instance
in HiveFunctionWrapper
2a6aa8e is described below
commit 2a6aa8e87bec39f6bfec67e151ef8566b75caecd
Author: Jungtaek Lim (HeartSaVioR) <kabhwan.opensou...@gmail.com>
AuthorDate: Tue Mar 31 16:17:26 2020 +0000
[SPARK-31312][SQL] Cache Class instance for the UDF instance in
HiveFunctionWrapper
### What changes were proposed in this pull request?
This patch proposes to cache Class instance for the UDF instance in
HiveFunctionWrapper to fix the case where Hive simple UDF is somehow
transformed (expression is copied) and evaluated later with another classloader
(for the case current thread context classloader is somehow changed). In this
case, Spark throws CNFE as of now.
It's only occurred for Hive simple UDF, as HiveFunctionWrapper caches the
UDF instance whereas it doesn't do for `UDF` type. The comment says Spark has
to create instance every time for UDF, so we cannot simply do the same. This
patch caches Class instance instead, and switch current thread context
classloader to which loads the Class instance.
This patch extends the test boundary as well. We only tested with
GenericUDTF for SPARK-26560, and this patch actually requires only UDF. But to
avoid regression for other types as well, this patch adds all available types
(UDF, GenericUDF, AbstractGenericUDAFResolver, UDAF, GenericUDTF) into the
boundary of tests.
Credit to cloud-fan as he discovered the problem and proposed the solution.
### Why are the changes needed?
Above section describes why it's a bug and how it's fixed.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
New UTs added.
Closes #28079 from HeartSaVioR/SPARK-31312.
Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensou...@gmail.com>
Signed-off-by: Wenchen Fan <wenc...@databricks.com>
---
.../scala/org/apache/spark/sql/hive/HiveShim.scala | 18 +-
.../src/test/noclasspath/TestUDTF-spark-26560.jar | Bin 7462 -> 0 bytes
sql/hive/src/test/noclasspath/hive-test-udfs.jar | Bin 0 -> 35660 bytes
.../spark/sql/hive/HiveUDFDynamicLoadSuite.scala | 190 +++++++++++++++++++++
.../spark/sql/hive/execution/SQLQuerySuite.scala | 47 -----
5 files changed, 203 insertions(+), 52 deletions(-)
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveShim.scala
b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveShim.scala
index 3beef6b..04a6a8f 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveShim.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveShim.scala
@@ -118,9 +118,12 @@ private[hive] object HiveShim {
*
* @param functionClassName UDF class name
* @param instance optional UDF instance which contains additional
information (for macro)
+ * @param clazz optional class instance to create UDF instance
*/
- private[hive] case class HiveFunctionWrapper(var functionClassName: String,
- private var instance: AnyRef = null) extends java.io.Externalizable {
+ private[hive] case class HiveFunctionWrapper(
+ var functionClassName: String,
+ private var instance: AnyRef = null,
+ private var clazz: Class[_ <: AnyRef] = null) extends
java.io.Externalizable {
// for Serialization
def this() = this(null)
@@ -232,8 +235,10 @@ private[hive] object HiveShim {
in.readFully(functionInBytes)
// deserialize the function object via Hive Utilities
+ clazz = Utils.getContextOrSparkClassLoader.loadClass(functionClassName)
+ .asInstanceOf[Class[_ <: AnyRef]]
instance = deserializePlan[AnyRef](new
java.io.ByteArrayInputStream(functionInBytes),
- Utils.getContextOrSparkClassLoader.loadClass(functionClassName))
+ clazz)
}
}
@@ -241,8 +246,11 @@ private[hive] object HiveShim {
if (instance != null) {
instance.asInstanceOf[UDFType]
} else {
- val func = Utils.getContextOrSparkClassLoader
-
.loadClass(functionClassName).getConstructor().newInstance().asInstanceOf[UDFType]
+ if (clazz == null) {
+ clazz =
Utils.getContextOrSparkClassLoader.loadClass(functionClassName)
+ .asInstanceOf[Class[_ <: AnyRef]]
+ }
+ val func = clazz.getConstructor().newInstance().asInstanceOf[UDFType]
if (!func.isInstanceOf[UDF]) {
// We cache the function if it's no the Simple UDF,
// as we always have to create new instance for Simple UDF
diff --git a/sql/hive/src/test/noclasspath/TestUDTF-spark-26560.jar
b/sql/hive/src/test/noclasspath/TestUDTF-spark-26560.jar
deleted file mode 100644
index b73b17d..0000000
Binary files a/sql/hive/src/test/noclasspath/TestUDTF-spark-26560.jar and
/dev/null differ
diff --git a/sql/hive/src/test/noclasspath/hive-test-udfs.jar
b/sql/hive/src/test/noclasspath/hive-test-udfs.jar
new file mode 100644
index 0000000..a5bfa45
Binary files /dev/null and b/sql/hive/src/test/noclasspath/hive-test-udfs.jar
differ
diff --git
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveUDFDynamicLoadSuite.scala
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveUDFDynamicLoadSuite.scala
new file mode 100644
index 0000000..ee8e6f4
--- /dev/null
+++
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveUDFDynamicLoadSuite.scala
@@ -0,0 +1,190 @@
+/*
+ * 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 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
+
+class HiveUDFDynamicLoadSuite extends QueryTest with SQLTestUtils with
TestHiveSingleton {
+
+ case class UDFTestInformation(
+ identifier: String,
+ funcName: String,
+ className: String,
+ fnVerifyQuery: () => Unit,
+ fnCreateHiveUDFExpression: () => Expression)
+
+ 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)()))
+ }),
+
+ // 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)())
+ )
+ }
+ ),
+
+ // 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)())
+ )
+ }
+ ),
+
+ // 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
+ )
+ }
+ ),
+
+ // 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]
+ )
+ }
+ )
+ )
+
+ 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.
+
+ // 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"
+
+ 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
+
+ sql(s"CREATE FUNCTION ${udfInfo.funcName} AS '${udfInfo.className}'
USING JAR '$jarUrl'")
+
+ assert(Thread.currentThread().getContextClassLoader eq
sparkClassLoader)
+
+ // 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()
+
+ assert(Thread.currentThread().getContextClassLoader ne
sparkClassLoader)
+ assert(Thread.currentThread().getContextClassLoader eq
+ spark.sqlContext.sharedState.jarClassLoader)
+
+ val udfExpr = udfInfo.fnCreateHiveUDFExpression()
+ // force initializing - this is what we do in HiveSessionCatalog
+ udfExpr.dataType
+
+ // 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)
+
+ udfInfo.fnVerifyQuery()
+
+ val newExpr =
udfExpr.makeCopy(udfExpr.productIterator.map(_.asInstanceOf[AnyRef])
+ .toArray)
+ newExpr.dataType
+ }
+ }
+ }
+ }
+}
diff --git
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
index 539b464..65c1db5 100644
---
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
+++
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
@@ -2492,51 +2492,4 @@ class SQLQuerySuite extends QueryTest with SQLTestUtils
with TestHiveSingleton {
}
}
}
-
- test("SPARK-26560 Spark should be able to run Hive UDF using jar regardless
of " +
- "current thread context classloader") {
- // force to use Spark classloader as other test (even in other test
suites) may change the
- // current thread's context classloader to jar classloader
- Utils.withContextClassLoader(Utils.getSparkClassLoader) {
- withUserDefinedFunction("udtf_count3" -> false) {
- val sparkClassLoader = Thread.currentThread().getContextClassLoader
-
- // This jar file should not be placed to the classpath;
GenericUDTFCount3 is slightly
- // modified version of GenericUDTFCount2 in hive/contrib, which emits
the count for
- // three times.
- val jarPath = "src/test/noclasspath/TestUDTF-spark-26560.jar"
- val jarURL = s"file://${System.getProperty("user.dir")}/$jarPath"
-
- sql(
- s"""
- |CREATE FUNCTION udtf_count3
- |AS
'org.apache.hadoop.hive.contrib.udtf.example.GenericUDTFCount3'
- |USING JAR '$jarURL'
- """.stripMargin)
-
- assert(Thread.currentThread().getContextClassLoader eq
sparkClassLoader)
-
- // 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.
- checkAnswer(
- sql("SELECT udtf_count3(a) FROM (SELECT 1 AS a FROM src LIMIT 3) t"),
- Row(3) :: Row(3) :: Row(3) :: Nil)
-
- assert(Thread.currentThread().getContextClassLoader ne
sparkClassLoader)
- assert(Thread.currentThread().getContextClassLoader eq
- spark.sqlContext.sharedState.jarClassLoader)
-
- // 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)
- checkAnswer(
- sql("SELECT udtf_count3(a) FROM (SELECT 1 AS a FROM src LIMIT 3) t"),
- Row(3) :: Row(3) :: Row(3) :: Nil)
- }
- }
- }
}
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