[SPARK-13848][SPARK-5185] Update to Py4J 0.9.2 in order to fix classloading issue

This patch upgrades Py4J from 0.9.1 to 0.9.2 in order to include a patch which modifies Py4J to use the current thread's ContextClassLoader when performing reflection / class loading. This is necessary in order to fix [SPARK-5185](https://issues.apache.org/jira/browse/SPARK-5185), a longstanding issue affecting the use of `--jars` and `--packages` in PySpark.

In order to demonstrate that the fix works, I removed the workarounds which were added as part of [SPARK-6027](https://issues.apache.org/jira/browse/SPARK-6027) / #4779 and other patches.

Py4J diff: https://github.com/bartdag/py4j/compare/0.9.1...0.9.2

/cc zsxwing tdas davies brkyvz

Author: Josh Rosen <joshrosen@databricks.com>

Closes #11687 from JoshRosen/py4j-0.9.2.

LICENSE

@@ -263,7 +263,7 @@ The text of each license is also included at licenses/LICENSE-[project].txt.
      (New BSD license) Protocol Buffer Java API (org.spark-project.protobuf:protobuf-java:2.4.1-shaded - http://code.google.com/p/protobuf)
      (The BSD License) Fortran to Java ARPACK (net.sourceforge.f2j:arpack_combined_all:0.1 - http://f2j.sourceforge.net)
      (The BSD License) xmlenc Library (xmlenc:xmlenc:0.52 - http://xmlenc.sourceforge.net)
-     (The New BSD License) Py4J (net.sf.py4j:py4j:0.9.1 - http://py4j.sourceforge.net/)
+     (The New BSD License) Py4J (net.sf.py4j:py4j:0.9.2 - http://py4j.sourceforge.net/)
      (Two-clause BSD-style license) JUnit-Interface (com.novocode:junit-interface:0.10 - http://github.com/szeiger/junit-interface/)
      (BSD licence) sbt and sbt-launch-lib.bash
      (BSD 3 Clause) d3.min.js (https://github.com/mbostock/d3/blob/master/LICENSE)

bin/pyspark

@@ -67,7 +67,7 @@ export PYSPARK_PYTHON
 
 # Add the PySpark classes to the Python path:
 export PYTHONPATH="${SPARK_HOME}/python/:$PYTHONPATH"
-export PYTHONPATH="${SPARK_HOME}/python/lib/py4j-0.9.1-src.zip:$PYTHONPATH"
+export PYTHONPATH="${SPARK_HOME}/python/lib/py4j-0.9.2-src.zip:$PYTHONPATH"
 
 # Load the PySpark shell.py script when ./pyspark is used interactively:
 export OLD_PYTHONSTARTUP="$PYTHONSTARTUP"

bin/pyspark2.cmd

@@ -30,7 +30,7 @@ if "x%PYSPARK_DRIVER_PYTHON%"=="x" (
 )
 
 set PYTHONPATH=%SPARK_HOME%\python;%PYTHONPATH%
-set PYTHONPATH=%SPARK_HOME%\python\lib\py4j-0.9.1-src.zip;%PYTHONPATH%
+set PYTHONPATH=%SPARK_HOME%\python\lib\py4j-0.9.2-src.zip;%PYTHONPATH%
 
 set OLD_PYTHONSTARTUP=%PYTHONSTARTUP%
 set PYTHONSTARTUP=%SPARK_HOME%\python\pyspark\shell.py

core/pom.xml

@@ -314,7 +314,7 @@
     <dependency>
       <groupId>net.sf.py4j</groupId>
       <artifactId>py4j</artifactId>
-      <version>0.9.1</version>
+      <version>0.9.2</version>
     </dependency>
     <dependency>
       <groupId>org.apache.spark</groupId>

core/src/main/scala/org/apache/spark/api/python/PythonUtils.scala

@@ -32,7 +32,7 @@ private[spark] object PythonUtils {
     val pythonPath = new ArrayBuffer[String]
     for (sparkHome <- sys.env.get("SPARK_HOME")) {
       pythonPath += Seq(sparkHome, "python", "lib", "pyspark.zip").mkString(File.separator)
-      pythonPath += Seq(sparkHome, "python", "lib", "py4j-0.9.1-src.zip").mkString(File.separator)
+      pythonPath += Seq(sparkHome, "python", "lib", "py4j-0.9.2-src.zip").mkString(File.separator)
     }
     pythonPath ++= SparkContext.jarOfObject(this)
     pythonPath.mkString(File.pathSeparator)

dev/deps/spark-deps-hadoop-2.2

@@ -153,7 +153,7 @@ pmml-agent-1.2.7.jar
 pmml-model-1.2.7.jar
 pmml-schema-1.2.7.jar
 protobuf-java-2.5.0.jar
-py4j-0.9.1.jar
+py4j-0.9.2.jar
 pyrolite-4.9.jar
 reflectasm-1.07-shaded.jar
 scala-compiler-2.11.7.jar

dev/deps/spark-deps-hadoop-2.3

@@ -144,7 +144,7 @@ pmml-agent-1.2.7.jar
 pmml-model-1.2.7.jar
 pmml-schema-1.2.7.jar
 protobuf-java-2.5.0.jar
-py4j-0.9.1.jar
+py4j-0.9.2.jar
 pyrolite-4.9.jar
 reflectasm-1.07-shaded.jar
 scala-compiler-2.11.7.jar

dev/deps/spark-deps-hadoop-2.4

@@ -145,7 +145,7 @@ pmml-agent-1.2.7.jar
 pmml-model-1.2.7.jar
 pmml-schema-1.2.7.jar
 protobuf-java-2.5.0.jar
-py4j-0.9.1.jar
+py4j-0.9.2.jar
 pyrolite-4.9.jar
 reflectasm-1.07-shaded.jar
 scala-compiler-2.11.7.jar

dev/deps/spark-deps-hadoop-2.6

@@ -151,7 +151,7 @@ pmml-agent-1.2.7.jar
 pmml-model-1.2.7.jar
 pmml-schema-1.2.7.jar
 protobuf-java-2.5.0.jar
-py4j-0.9.1.jar
+py4j-0.9.2.jar
 pyrolite-4.9.jar
 reflectasm-1.07-shaded.jar
 scala-compiler-2.11.7.jar

dev/deps/spark-deps-hadoop-2.7

@@ -152,7 +152,7 @@ pmml-agent-1.2.7.jar
 pmml-model-1.2.7.jar
 pmml-schema-1.2.7.jar
 protobuf-java-2.5.0.jar
-py4j-0.9.1.jar
+py4j-0.9.2.jar
 pyrolite-4.9.jar
 reflectasm-1.07-shaded.jar
 scala-compiler-2.11.7.jar

external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaUtils.scala

@@ -615,7 +615,7 @@ object KafkaUtils {
 /**
  * This is a helper class that wraps the KafkaUtils.createStream() into more
  * Python-friendly class and function so that it can be easily
- * instantiated and called from Python's KafkaUtils (see SPARK-6027).
+ * instantiated and called from Python's KafkaUtils.
  *
  * The zero-arg constructor helps instantiate this class from the Class object
  * classOf[KafkaUtilsPythonHelper].newInstance(), and the createStream()

python/docs/Makefile

@@ -7,7 +7,7 @@ SPHINXBUILD   = sphinx-build
 PAPER         =
 BUILDDIR      = _build
 
-export PYTHONPATH=$(realpath ..):$(realpath ../lib/py4j-0.9.1-src.zip)
+export PYTHONPATH=$(realpath ..):$(realpath ../lib/py4j-0.9.2-src.zip)
 
 # User-friendly check for sphinx-build
 ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1)

python/pyspark/streaming/flume.py

@@ -111,12 +111,9 @@ class FlumeUtils(object):
     @staticmethod
     def _get_helper(sc):
         try:
-            helperClass = sc._jvm.java.lang.Thread.currentThread().getContextClassLoader() \
+            return sc._jvm.org.apache.spark.streaming.flume.FlumeUtilsPythonHelper()
-                .loadClass("org.apache.spark.streaming.flume.FlumeUtilsPythonHelper")
+        except TypeError as e:
-            return helperClass.newInstance()
+            if str(e) == "'JavaPackage' object is not callable":
-        except Py4JJavaError as e:
-            # TODO: use --jar once it also work on driver
-            if 'ClassNotFoundException' in str(e.java_exception):
                 FlumeUtils._printErrorMsg(sc)
             raise
 

python/pyspark/streaming/kafka.py

@@ -192,13 +192,9 @@ class KafkaUtils(object):
     @staticmethod
     def _get_helper(sc):
         try:
-            # Use KafkaUtilsPythonHelper to access Scala's KafkaUtils (see SPARK-6027)
+            return sc._jvm.org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper()
-            helperClass = sc._jvm.java.lang.Thread.currentThread().getContextClassLoader() \
+        except TypeError as e:
-                .loadClass("org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper")
+            if str(e) == "'JavaPackage' object is not callable":
-            return helperClass.newInstance()
-        except Py4JJavaError as e:
-            # TODO: use --jar once it also work on driver
-            if 'ClassNotFoundException' in str(e.java_exception):
                 KafkaUtils._printErrorMsg(sc)
             raise
 

python/pyspark/streaming/kinesis.py

@@ -74,16 +74,14 @@ class KinesisUtils(object):
 
         try:
             # Use KinesisUtilsPythonHelper to access Scala's KinesisUtils
-            helperClass = ssc._jvm.java.lang.Thread.currentThread().getContextClassLoader()\
+            helper = ssc._jvm.org.apache.spark.streaming.kinesis.KinesisUtilsPythonHelper()
-                .loadClass("org.apache.spark.streaming.kinesis.KinesisUtilsPythonHelper")
+        except TypeError as e:
-            helper = helperClass.newInstance()
+            if str(e) == "'JavaPackage' object is not callable":
-            jstream = helper.createStream(ssc._jssc, kinesisAppName, streamName, endpointUrl,
-                                          regionName, initialPositionInStream, jduration, jlevel,
-                                          awsAccessKeyId, awsSecretKey)
-        except Py4JJavaError as e:
-            if 'ClassNotFoundException' in str(e.java_exception):
                 KinesisUtils._printErrorMsg(ssc.sparkContext)
             raise
+        jstream = helper.createStream(ssc._jssc, kinesisAppName, streamName, endpointUrl,
+                                      regionName, initialPositionInStream, jduration, jlevel,
+                                      awsAccessKeyId, awsSecretKey)
         stream = DStream(jstream, ssc, NoOpSerializer())
         return stream.map(lambda v: decoder(v))
 

python/pyspark/streaming/mqtt.py

@@ -38,18 +38,15 @@ class MQTTUtils(object):
         :param storageLevel:  RDD storage level.
         :return: A DStream object
         """
-        jlevel = ssc._sc._getJavaStorageLevel(storageLevel)
-
         try:
-            helperClass = ssc._jvm.java.lang.Thread.currentThread().getContextClassLoader() \
+            helper = ssc._jvm.org.apache.spark.streaming.mqtt.MQTTUtilsPythonHelper()
-                .loadClass("org.apache.spark.streaming.mqtt.MQTTUtilsPythonHelper")
+        except TypeError as e:
-            helper = helperClass.newInstance()
+            if str(e) == "'JavaPackage' object is not callable":
-            jstream = helper.createStream(ssc._jssc, brokerUrl, topic, jlevel)
-        except Py4JJavaError as e:
-            if 'ClassNotFoundException' in str(e.java_exception):
                 MQTTUtils._printErrorMsg(ssc.sparkContext)
             raise
 
+        jlevel = ssc._sc._getJavaStorageLevel(storageLevel)
+        jstream = helper.createStream(ssc._jssc, brokerUrl, topic, jlevel)
         return DStream(jstream, ssc, UTF8Deserializer())
 
     @staticmethod

python/pyspark/streaming/tests.py

@@ -1006,10 +1006,7 @@ class KafkaStreamTests(PySparkStreamingTestCase):
 
     def setUp(self):
         super(KafkaStreamTests, self).setUp()
-
+        self._kafkaTestUtils = self.ssc._jvm.org.apache.spark.streaming.kafka.KafkaTestUtils()
-        kafkaTestUtilsClz = self.ssc._jvm.java.lang.Thread.currentThread().getContextClassLoader()\
-            .loadClass("org.apache.spark.streaming.kafka.KafkaTestUtils")
-        self._kafkaTestUtils = kafkaTestUtilsClz.newInstance()
         self._kafkaTestUtils.setup()
 
     def tearDown(self):
@@ -1271,10 +1268,7 @@ class FlumeStreamTests(PySparkStreamingTestCase):
 
     def setUp(self):
         super(FlumeStreamTests, self).setUp()
-
+        self._utils = self.ssc._jvm.org.apache.spark.streaming.flume.FlumeTestUtils()
-        utilsClz = self.ssc._jvm.java.lang.Thread.currentThread().getContextClassLoader() \
-            .loadClass("org.apache.spark.streaming.flume.FlumeTestUtils")
-        self._utils = utilsClz.newInstance()
 
     def tearDown(self):
         if self._utils is not None:
@@ -1339,10 +1333,7 @@ class FlumePollingStreamTests(PySparkStreamingTestCase):
     maxAttempts = 5
 
     def setUp(self):
-        utilsClz = \
+        self._utils = self.sc._jvm.org.apache.spark.streaming.flume.PollingFlumeTestUtils()
-            self.sc._jvm.java.lang.Thread.currentThread().getContextClassLoader() \
-                .loadClass("org.apache.spark.streaming.flume.PollingFlumeTestUtils")
-        self._utils = utilsClz.newInstance()
 
     def tearDown(self):
         if self._utils is not None:
@@ -1419,10 +1410,7 @@ class MQTTStreamTests(PySparkStreamingTestCase):
 
     def setUp(self):
         super(MQTTStreamTests, self).setUp()
-
+        self._MQTTTestUtils = self.ssc._jvm.org.apache.spark.streaming.mqtt.MQTTTestUtils()
-        MQTTTestUtilsClz = self.ssc._jvm.java.lang.Thread.currentThread().getContextClassLoader() \
-            .loadClass("org.apache.spark.streaming.mqtt.MQTTTestUtils")
-        self._MQTTTestUtils = MQTTTestUtilsClz.newInstance()
         self._MQTTTestUtils.setup()
 
     def tearDown(self):
@@ -1498,10 +1486,7 @@ class KinesisStreamTests(PySparkStreamingTestCase):
 
         import random
         kinesisAppName = ("KinesisStreamTests-%d" % abs(random.randint(0, 10000000)))
-        kinesisTestUtilsClz = \
+        kinesisTestUtils = self.ssc._jvm.org.apache.spark.streaming.kinesis.KinesisTestUtils()
-            self.sc._jvm.java.lang.Thread.currentThread().getContextClassLoader() \
-                .loadClass("org.apache.spark.streaming.kinesis.KinesisTestUtils")
-        kinesisTestUtils = kinesisTestUtilsClz.newInstance()
         try:
             kinesisTestUtils.createStream()
             aWSCredentials = kinesisTestUtils.getAWSCredentials()

sbin/spark-config.sh

@@ -27,4 +27,4 @@ fi
 export SPARK_CONF_DIR="${SPARK_CONF_DIR:-"${SPARK_HOME}/conf"}"
 # Add the PySpark classes to the PYTHONPATH:
 export PYTHONPATH="${SPARK_HOME}/python:${PYTHONPATH}"
-export PYTHONPATH="${SPARK_HOME}/python/lib/py4j-0.9.1-src.zip:${PYTHONPATH}"
+export PYTHONPATH="${SPARK_HOME}/python/lib/py4j-0.9.2-src.zip:${PYTHONPATH}"

yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala

@@ -1087,9 +1087,9 @@ private[spark] class Client(
         val pyArchivesFile = new File(pyLibPath, "pyspark.zip")
         require(pyArchivesFile.exists(),
           "pyspark.zip not found; cannot run pyspark application in YARN mode.")
-        val py4jFile = new File(pyLibPath, "py4j-0.9.1-src.zip")
+        val py4jFile = new File(pyLibPath, "py4j-0.9.2-src.zip")
         require(py4jFile.exists(),
-          "py4j-0.9.1-src.zip not found; cannot run pyspark application in YARN mode.")
+          "py4j-0.9.2-src.zip not found; cannot run pyspark application in YARN mode.")
         Seq(pyArchivesFile.getAbsolutePath(), py4jFile.getAbsolutePath())
       }
   }

yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala

@@ -154,7 +154,7 @@ class YarnClusterSuite extends BaseYarnClusterSuite {
     // needed locations.
     val sparkHome = sys.props("spark.test.home")
     val pythonPath = Seq(
-        s"$sparkHome/python/lib/py4j-0.9.1-src.zip",
+        s"$sparkHome/python/lib/py4j-0.9.2-src.zip",
         s"$sparkHome/python")
     val extraEnv = Map(
       "PYSPARK_ARCHIVES_PATH" -> pythonPath.map("local:" + _).mkString(File.pathSeparator),