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Posted to commits@spark.apache.org by gu...@apache.org on 2022/03/16 09:23:03 UTC
[spark] branch branch-3.3 updated: [SPARK-38563][PYTHON] Upgrade to Py4J 0.10.9.4
This is an automated email from the ASF dual-hosted git repository.
gurwls223 pushed a commit to branch branch-3.3
in repository https://gitbox.apache.org/repos/asf/spark.git
The following commit(s) were added to refs/heads/branch-3.3 by this push:
new 3bbf346 [SPARK-38563][PYTHON] Upgrade to Py4J 0.10.9.4
3bbf346 is described below
commit 3bbf346d9ca984faa0c3e67cd1387a13b2bd1e37
Author: Hyukjin Kwon <gu...@apache.org>
AuthorDate: Wed Mar 16 18:20:50 2022 +0900
[SPARK-38563][PYTHON] Upgrade to Py4J 0.10.9.4
### What changes were proposed in this pull request?
This PR upgrade Py4J 0.10.9.4, with relevant documentation changes.
### Why are the changes needed?
Py4J 0.10.9.3 has a resource leak issue when pinned thread mode is enabled - it's enabled by default in PySpark at https://github.com/apache/spark/commit/41af409b7bcfe1b3960274c0b3085bcc1f9d1c98.
We worked around this by enforcing users to use `InheritableThread` or `inhteritable_thread_target` as a workaround.
After upgrading, we don't need to enforce users anymore because it automatically cleans up, see also https://github.com/py4j/py4j/pull/471
### Does this PR introduce _any_ user-facing change?
Yes, users don't have to use `InheritableThread` or `inhteritable_thread_target` to avoid resource leaking problem anymore.
### How was this patch tested?
CI in this PR should test it out.
Closes #35871 from HyukjinKwon/SPARK-38563.
Authored-by: Hyukjin Kwon <gu...@apache.org>
Signed-off-by: Hyukjin Kwon <gu...@apache.org>
(cherry picked from commit 8193b405f02f867439dd2d2017bf7b3c814b5cc8)
Signed-off-by: Hyukjin Kwon <gu...@apache.org>
---
bin/pyspark | 2 +-
bin/pyspark2.cmd | 2 +-
core/pom.xml | 2 +-
.../org/apache/spark/api/python/PythonUtils.scala | 2 +-
dev/deps/spark-deps-hadoop-2-hive-2.3 | 2 +-
dev/deps/spark-deps-hadoop-3-hive-2.3 | 2 +-
docs/job-scheduling.md | 2 +-
python/docs/Makefile | 2 +-
python/docs/make2.bat | 2 +-
python/docs/source/getting_started/install.rst | 2 +-
python/lib/py4j-0.10.9.3-src.zip | Bin 42021 -> 0 bytes
python/lib/py4j-0.10.9.4-src.zip | Bin 0 -> 42404 bytes
python/pyspark/context.py | 6 ++--
python/pyspark/util.py | 35 +++------------------
python/setup.py | 2 +-
sbin/spark-config.sh | 2 +-
16 files changed, 20 insertions(+), 45 deletions(-)
diff --git a/bin/pyspark b/bin/pyspark
index 4840589..1e16c56 100755
--- a/bin/pyspark
+++ b/bin/pyspark
@@ -50,7 +50,7 @@ export PYSPARK_DRIVER_PYTHON_OPTS
# Add the PySpark classes to the Python path:
export PYTHONPATH="${SPARK_HOME}/python/:$PYTHONPATH"
-export PYTHONPATH="${SPARK_HOME}/python/lib/py4j-0.10.9.3-src.zip:$PYTHONPATH"
+export PYTHONPATH="${SPARK_HOME}/python/lib/py4j-0.10.9.4-src.zip:$PYTHONPATH"
# Load the PySpark shell.py script when ./pyspark is used interactively:
export OLD_PYTHONSTARTUP="$PYTHONSTARTUP"
diff --git a/bin/pyspark2.cmd b/bin/pyspark2.cmd
index a19627a..f20c320 100644
--- a/bin/pyspark2.cmd
+++ b/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-0.10.9.3-src.zip;%PYTHONPATH%
+set PYTHONPATH=%SPARK_HOME%\python\lib\py4j-0.10.9.4-src.zip;%PYTHONPATH%
set OLD_PYTHONSTARTUP=%PYTHONSTARTUP%
set PYTHONSTARTUP=%SPARK_HOME%\python\pyspark\shell.py
diff --git a/core/pom.xml b/core/pom.xml
index 9d3b170..953c76b 100644
--- a/core/pom.xml
+++ b/core/pom.xml
@@ -423,7 +423,7 @@
<dependency>
<groupId>net.sf.py4j</groupId>
<artifactId>py4j</artifactId>
- <version>0.10.9.3</version>
+ <version>0.10.9.4</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonUtils.scala b/core/src/main/scala/org/apache/spark/api/python/PythonUtils.scala
index 8daba86..a9c35369 100644
--- a/core/src/main/scala/org/apache/spark/api/python/PythonUtils.scala
+++ b/core/src/main/scala/org/apache/spark/api/python/PythonUtils.scala
@@ -27,7 +27,7 @@ import org.apache.spark.SparkContext
import org.apache.spark.api.java.{JavaRDD, JavaSparkContext}
private[spark] object PythonUtils {
- val PY4J_ZIP_NAME = "py4j-0.10.9.3-src.zip"
+ val PY4J_ZIP_NAME = "py4j-0.10.9.4-src.zip"
/** Get the PYTHONPATH for PySpark, either from SPARK_HOME, if it is set, or from our JAR */
def sparkPythonPath: String = {
diff --git a/dev/deps/spark-deps-hadoop-2-hive-2.3 b/dev/deps/spark-deps-hadoop-2-hive-2.3
index bcbf8b9..f2db663 100644
--- a/dev/deps/spark-deps-hadoop-2-hive-2.3
+++ b/dev/deps/spark-deps-hadoop-2-hive-2.3
@@ -233,7 +233,7 @@ parquet-hadoop/1.12.2//parquet-hadoop-1.12.2.jar
parquet-jackson/1.12.2//parquet-jackson-1.12.2.jar
pickle/1.2//pickle-1.2.jar
protobuf-java/2.5.0//protobuf-java-2.5.0.jar
-py4j/0.10.9.3//py4j-0.10.9.3.jar
+py4j/0.10.9.4//py4j-0.10.9.4.jar
remotetea-oncrpc/1.1.2//remotetea-oncrpc-1.1.2.jar
rocksdbjni/6.20.3//rocksdbjni-6.20.3.jar
scala-collection-compat_2.12/2.1.1//scala-collection-compat_2.12-2.1.1.jar
diff --git a/dev/deps/spark-deps-hadoop-3-hive-2.3 b/dev/deps/spark-deps-hadoop-3-hive-2.3
index 8ca7880..c56b4c9 100644
--- a/dev/deps/spark-deps-hadoop-3-hive-2.3
+++ b/dev/deps/spark-deps-hadoop-3-hive-2.3
@@ -221,7 +221,7 @@ parquet-hadoop/1.12.2//parquet-hadoop-1.12.2.jar
parquet-jackson/1.12.2//parquet-jackson-1.12.2.jar
pickle/1.2//pickle-1.2.jar
protobuf-java/2.5.0//protobuf-java-2.5.0.jar
-py4j/0.10.9.3//py4j-0.10.9.3.jar
+py4j/0.10.9.4//py4j-0.10.9.4.jar
remotetea-oncrpc/1.1.2//remotetea-oncrpc-1.1.2.jar
rocksdbjni/6.20.3//rocksdbjni-6.20.3.jar
scala-collection-compat_2.12/2.1.1//scala-collection-compat_2.12-2.1.1.jar
diff --git a/docs/job-scheduling.md b/docs/job-scheduling.md
index 4ed2aa9..f44ed82 100644
--- a/docs/job-scheduling.md
+++ b/docs/job-scheduling.md
@@ -304,5 +304,5 @@ via `sc.setJobGroup` in a separate PVM thread, which also disallows to cancel th
later.
`pyspark.InheritableThread` is recommended to use together for a PVM thread to inherit the inheritable attributes
- such as local properties in a JVM thread, and to avoid resource leak.
+ such as local properties in a JVM thread.
diff --git a/python/docs/Makefile b/python/docs/Makefile
index 9cb1a17..2628530 100644
--- a/python/docs/Makefile
+++ b/python/docs/Makefile
@@ -21,7 +21,7 @@ SPHINXBUILD ?= sphinx-build
SOURCEDIR ?= source
BUILDDIR ?= build
-export PYTHONPATH=$(realpath ..):$(realpath ../lib/py4j-0.10.9.3-src.zip)
+export PYTHONPATH=$(realpath ..):$(realpath ../lib/py4j-0.10.9.4-src.zip)
# Put it first so that "make" without argument is like "make help".
help:
diff --git a/python/docs/make2.bat b/python/docs/make2.bat
index 2e4e2b5..26ef220 100644
--- a/python/docs/make2.bat
+++ b/python/docs/make2.bat
@@ -25,7 +25,7 @@ if "%SPHINXBUILD%" == "" (
set SOURCEDIR=source
set BUILDDIR=build
-set PYTHONPATH=..;..\lib\py4j-0.10.9.3-src.zip
+set PYTHONPATH=..;..\lib\py4j-0.10.9.4-src.zip
if "%1" == "" goto help
diff --git a/python/docs/source/getting_started/install.rst b/python/docs/source/getting_started/install.rst
index 15a1240..3503be0 100644
--- a/python/docs/source/getting_started/install.rst
+++ b/python/docs/source/getting_started/install.rst
@@ -157,7 +157,7 @@ Package Minimum supported version Note
`pandas` 1.0.5 Optional for Spark SQL
`NumPy` 1.7 Required for MLlib DataFrame-based API
`pyarrow` 1.0.0 Optional for Spark SQL
-`Py4J` 0.10.9.3 Required
+`Py4J` 0.10.9.4 Required
`pandas` 1.0.5 Required for pandas API on Spark
`pyarrow` 1.0.0 Required for pandas API on Spark
`Numpy` 1.14 Required for pandas API on Spark
diff --git a/python/lib/py4j-0.10.9.3-src.zip b/python/lib/py4j-0.10.9.3-src.zip
deleted file mode 100644
index 428f3ac..0000000
Binary files a/python/lib/py4j-0.10.9.3-src.zip and /dev/null differ
diff --git a/python/lib/py4j-0.10.9.4-src.zip b/python/lib/py4j-0.10.9.4-src.zip
new file mode 100644
index 0000000..51b3404
Binary files /dev/null and b/python/lib/py4j-0.10.9.4-src.zip differ
diff --git a/python/pyspark/context.py b/python/pyspark/context.py
index e47f162..59b5fa7 100644
--- a/python/pyspark/context.py
+++ b/python/pyspark/context.py
@@ -1365,7 +1365,7 @@ class SparkContext:
to HDFS-1208, where HDFS may respond to Thread.interrupt() by marking nodes as dead.
If you run jobs in parallel, use :class:`pyspark.InheritableThread` for thread
- local inheritance, and preventing resource leak.
+ local inheritance.
Examples
--------
@@ -1405,7 +1405,7 @@ class SparkContext:
Notes
-----
If you run jobs in parallel, use :class:`pyspark.InheritableThread` for thread
- local inheritance, and preventing resource leak.
+ local inheritance.
"""
self._jsc.setLocalProperty(key, value)
@@ -1423,7 +1423,7 @@ class SparkContext:
Notes
-----
If you run jobs in parallel, use :class:`pyspark.InheritableThread` for thread
- local inheritance, and preventing resource leak.
+ local inheritance.
"""
self._jsc.setJobDescription(value)
diff --git a/python/pyspark/util.py b/python/pyspark/util.py
index 5abbbb9..b7b972a 100644
--- a/python/pyspark/util.py
+++ b/python/pyspark/util.py
@@ -331,13 +331,10 @@ def inheritable_thread_target(f: Callable) -> Callable:
@functools.wraps(f)
def wrapped(*args: Any, **kwargs: Any) -> Any:
- try:
- # Set local properties in child thread.
- assert SparkContext._active_spark_context is not None
- SparkContext._active_spark_context._jsc.sc().setLocalProperties(properties)
- return f(*args, **kwargs)
- finally:
- InheritableThread._clean_py4j_conn_for_current_thread()
+ # Set local properties in child thread.
+ assert SparkContext._active_spark_context is not None
+ SparkContext._active_spark_context._jsc.sc().setLocalProperties(properties)
+ return f(*args, **kwargs)
return wrapped
else:
@@ -377,10 +374,7 @@ class InheritableThread(threading.Thread):
assert hasattr(self, "_props")
assert SparkContext._active_spark_context is not None
SparkContext._active_spark_context._jsc.sc().setLocalProperties(self._props)
- try:
- return target(*a, **k)
- finally:
- InheritableThread._clean_py4j_conn_for_current_thread()
+ return target(*a, **k)
super(InheritableThread, self).__init__(
target=copy_local_properties, *args, **kwargs # type: ignore[misc]
@@ -401,25 +395,6 @@ class InheritableThread(threading.Thread):
self._props = SparkContext._active_spark_context._jsc.sc().getLocalProperties().clone()
return super(InheritableThread, self).start()
- @staticmethod
- def _clean_py4j_conn_for_current_thread() -> None:
- from pyspark import SparkContext
-
- jvm = SparkContext._jvm
- assert jvm is not None
- thread_connection = jvm._gateway_client.get_thread_connection()
- if thread_connection is not None:
- try:
- # Dequeue is shared across other threads but it's thread-safe.
- # If this function has to be invoked one more time in the same thead
- # Py4J will create a new connection automatically.
- jvm._gateway_client.deque.remove(thread_connection)
- except ValueError:
- # Should never reach this point
- return
- finally:
- thread_connection.close()
-
if __name__ == "__main__":
if "pypy" not in platform.python_implementation().lower() and sys.version_info[:2] >= (3, 7):
diff --git a/python/setup.py b/python/setup.py
index 673b146..ab9b64f 100755
--- a/python/setup.py
+++ b/python/setup.py
@@ -258,7 +258,7 @@ try:
license='http://www.apache.org/licenses/LICENSE-2.0',
# Don't forget to update python/docs/source/getting_started/install.rst
# if you're updating the versions or dependencies.
- install_requires=['py4j==0.10.9.3'],
+ install_requires=['py4j==0.10.9.4'],
extras_require={
'ml': ['numpy>=1.15'],
'mllib': ['numpy>=1.15'],
diff --git a/sbin/spark-config.sh b/sbin/spark-config.sh
index f27b6fe..341eb05 100755
--- a/sbin/spark-config.sh
+++ b/sbin/spark-config.sh
@@ -28,6 +28,6 @@ export SPARK_CONF_DIR="${SPARK_CONF_DIR:-"${SPARK_HOME}/conf"}"
# Add the PySpark classes to the PYTHONPATH:
if [ -z "${PYSPARK_PYTHONPATH_SET}" ]; then
export PYTHONPATH="${SPARK_HOME}/python:${PYTHONPATH}"
- export PYTHONPATH="${SPARK_HOME}/python/lib/py4j-0.10.9.3-src.zip:${PYTHONPATH}"
+ export PYTHONPATH="${SPARK_HOME}/python/lib/py4j-0.10.9.4-src.zip:${PYTHONPATH}"
export PYSPARK_PYTHONPATH_SET=1
fi
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