209b9361ac
## What changes were proposed in this pull request? This change uses Arrow to optimize the creation of a Spark DataFrame from a Pandas DataFrame. The input df is sliced according to the default parallelism. The optimization is enabled with the existing conf "spark.sql.execution.arrow.enabled" and is disabled by default. ## How was this patch tested? Added new unit test to create DataFrame with and without the optimization enabled, then compare results. Author: Bryan Cutler <cutlerb@gmail.com> Author: Takuya UESHIN <ueshin@databricks.com> Closes #19459 from BryanCutler/arrow-createDataFrame-from_pandas-SPARK-20791.
129 lines
5.8 KiB
Python
129 lines
5.8 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 pyspark.find_spark_home import _find_spark_home
|
|
from pyspark.serializers import read_int
|
|
|
|
|
|
def launch_gateway(conf=None):
|
|
"""
|
|
launch jvm gateway
|
|
:param conf: spark configuration passed to spark-submit
|
|
:return:
|
|
"""
|
|
if "PYSPARK_GATEWAY_PORT" in os.environ:
|
|
gateway_port = int(os.environ["PYSPARK_GATEWAY_PORT"])
|
|
else:
|
|
SPARK_HOME = _find_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"
|
|
command = [os.path.join(SPARK_HOME, script)]
|
|
if conf:
|
|
for k, v in conf.getAll():
|
|
command += ['--conf', '%s=%s' % (k, v)]
|
|
submit_args = os.environ.get("PYSPARK_SUBMIT_ARGS", "pyspark-shell")
|
|
if os.environ.get("SPARK_TESTING"):
|
|
submit_args = ' '.join([
|
|
"--conf spark.ui.enabled=false",
|
|
submit_args
|
|
])
|
|
command = command + 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.ml.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.api.python.*")
|
|
java_import(gateway.jvm, "org.apache.spark.sql.hive.*")
|
|
java_import(gateway.jvm, "scala.Tuple2")
|
|
|
|
return gateway
|