spark-instrumented-optimizer/python/pyspark/java_gateway.py
Josh Rosen 520ec0ff9d [SPARK-8850] [SQL] Enable Unsafe mode by default
This pull request enables Unsafe mode by default in Spark SQL. In order to do this, we had to fix a number of small issues:

**List of fixed blockers**:

- [x] Make some default buffer sizes configurable so that HiveCompatibilitySuite can run properly (#7741).
- [x] Memory leak on grouped aggregation of empty input (fixed by #7560 to fix this)
- [x] Update planner to also check whether codegen is enabled before planning unsafe operators.
- [x] Investigate failing HiveThriftBinaryServerSuite test.  This turns out to be caused by a ClassCastException that occurs when Exchange tries to apply an interpreted RowOrdering to an UnsafeRow when range partitioning an RDD.  This could be fixed by #7408, but a shorter-term fix is to just skip the Unsafe exchange path when RangePartitioner is used.
- [x] Memory leak exceptions masking exceptions that actually caused tasks to fail (will be fixed by #7603).
- [x]  ~~https://issues.apache.org/jira/browse/SPARK-9162, to implement code generation for ScalaUDF.  This is necessary for `UDFSuite` to pass.  For now, I've just ignored this test in order to try to find other problems while we wait for a fix.~~ This is no longer necessary as of #7682.
- [x] Memory leaks from Limit after UnsafeExternalSort cause the memory leak detector to fail tests. This is a huge problem in the HiveCompatibilitySuite (fixed by f4ac642a4e5b2a7931c5e04e086bb10e263b1db6).
- [x] Tests in `AggregationQuerySuite` are failing due to NaN-handling issues in UnsafeRow, which were fixed in #7736.
- [x] `org.apache.spark.sql.ColumnExpressionSuite.rand` needs to be updated so that the planner check also matches `TungstenProject`.
- [x] After having lowered the buffer sizes to 4MB so that most of HiveCompatibilitySuite runs:
  - [x] Wrong answer in `join_1to1` (fixed by #7680)
  - [x] Wrong answer in `join_nulls` (fixed by #7680)
  - [x] Managed memory OOM / leak in `lateral_view`
  - [x] Seems to hang indefinitely in `partcols1`.  This might be a deadlock in script transformation or a bug in error-handling code? The hang was fixed by #7710.
  - [x] Error while freeing memory in `partcols1`: will be fixed by #7734.
- [x] After fixing the `partcols1` hang, it appears that a number of later tests have issues as well.
- [x] Fix thread-safety bug in codegen fallback expression evaluation (#7759).

Author: Josh Rosen <joshrosen@databricks.com>

Closes #7564 from JoshRosen/unsafe-by-default and squashes the following commits:

83c0c56 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-by-default
f4cc859 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-by-default
963f567 [Josh Rosen] Reduce buffer size for R tests
d6986de [Josh Rosen] Lower page size in PySpark tests
013b9da [Josh Rosen] Also match TungstenProject in checkNumProjects
5d0b2d3 [Josh Rosen] Add task completion callback to avoid leak in limit after sort
ea250da [Josh Rosen] Disable unsafe Exchange path when RangePartitioning is used
715517b [Josh Rosen] Enable Unsafe by default
2015-07-30 10:45:32 -07:00

127 lines
5.7 KiB
Python

#
# 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.
#
import atexit
import os
import sys
import select
import signal
import shlex
import socket
import platform
from subprocess import Popen, PIPE
if sys.version >= '3':
xrange = range
from py4j.java_gateway import java_import, JavaGateway, GatewayClient
from py4j.java_collections import ListConverter
from pyspark.serializers import read_int
# patching ListConverter, or it will convert bytearray into Java ArrayList
def can_convert_list(self, obj):
return isinstance(obj, (list, tuple, xrange))
ListConverter.can_convert = can_convert_list
def launch_gateway():
if "PYSPARK_GATEWAY_PORT" in os.environ:
gateway_port = int(os.environ["PYSPARK_GATEWAY_PORT"])
else:
SPARK_HOME = os.environ["SPARK_HOME"]
# Launch the Py4j gateway using Spark's run command so that we pick up the
# proper classpath and settings from spark-env.sh
on_windows = platform.system() == "Windows"
script = "./bin/spark-submit.cmd" if on_windows else "./bin/spark-submit"
submit_args = os.environ.get("PYSPARK_SUBMIT_ARGS", "pyspark-shell")
if os.environ.get("SPARK_TESTING"):
submit_args = ' '.join([
"--conf spark.ui.enabled=false",
"--conf spark.buffer.pageSize=4mb",
submit_args
])
command = [os.path.join(SPARK_HOME, script)] + shlex.split(submit_args)
# Start a socket that will be used by PythonGatewayServer to communicate its port to us
callback_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
callback_socket.bind(('127.0.0.1', 0))
callback_socket.listen(1)
callback_host, callback_port = callback_socket.getsockname()
env = dict(os.environ)
env['_PYSPARK_DRIVER_CALLBACK_HOST'] = callback_host
env['_PYSPARK_DRIVER_CALLBACK_PORT'] = str(callback_port)
# Launch the Java gateway.
# We open a pipe to stdin so that the Java gateway can die when the pipe is broken
if not on_windows:
# Don't send ctrl-c / SIGINT to the Java gateway:
def preexec_func():
signal.signal(signal.SIGINT, signal.SIG_IGN)
proc = Popen(command, stdin=PIPE, preexec_fn=preexec_func, env=env)
else:
# preexec_fn not supported on Windows
proc = Popen(command, stdin=PIPE, env=env)
gateway_port = None
# We use select() here in order to avoid blocking indefinitely if the subprocess dies
# before connecting
while gateway_port is None and proc.poll() is None:
timeout = 1 # (seconds)
readable, _, _ = select.select([callback_socket], [], [], timeout)
if callback_socket in readable:
gateway_connection = callback_socket.accept()[0]
# Determine which ephemeral port the server started on:
gateway_port = read_int(gateway_connection.makefile(mode="rb"))
gateway_connection.close()
callback_socket.close()
if gateway_port is None:
raise Exception("Java gateway process exited before sending the driver its port number")
# In Windows, ensure the Java child processes do not linger after Python has exited.
# In UNIX-based systems, the child process can kill itself on broken pipe (i.e. when
# the parent process' stdin sends an EOF). In Windows, however, this is not possible
# because java.lang.Process reads directly from the parent process' stdin, contending
# with any opportunity to read an EOF from the parent. Note that this is only best
# effort and will not take effect if the python process is violently terminated.
if on_windows:
# In Windows, the child process here is "spark-submit.cmd", not the JVM itself
# (because the UNIX "exec" command is not available). This means we cannot simply
# call proc.kill(), which kills only the "spark-submit.cmd" process but not the
# JVMs. Instead, we use "taskkill" with the tree-kill option "/t" to terminate all
# child processes in the tree (http://technet.microsoft.com/en-us/library/bb491009.aspx)
def killChild():
Popen(["cmd", "/c", "taskkill", "/f", "/t", "/pid", str(proc.pid)])
atexit.register(killChild)
# Connect to the gateway
gateway = JavaGateway(GatewayClient(port=gateway_port), auto_convert=True)
# Import the classes used by PySpark
java_import(gateway.jvm, "org.apache.spark.SparkConf")
java_import(gateway.jvm, "org.apache.spark.api.java.*")
java_import(gateway.jvm, "org.apache.spark.api.python.*")
java_import(gateway.jvm, "org.apache.spark.mllib.api.python.*")
# TODO(davies): move into sql
java_import(gateway.jvm, "org.apache.spark.sql.*")
java_import(gateway.jvm, "org.apache.spark.sql.hive.*")
java_import(gateway.jvm, "scala.Tuple2")
return gateway