#
# 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 os
import sys
import signal
import platform
from subprocess import Popen, PIPE
from threading import Thread
from py4j.java_gateway import java_import, JavaGateway, GatewayClient
def launch_gateway():
SPARK_HOME = os.environ["SPARK_HOME"]
set_env_vars_for_yarn()
# 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-class.cmd" if on_windows else "./bin/spark-class"
command = [os.path.join(SPARK_HOME, script), "py4j.GatewayServer",
"--die-on-broken-pipe", "0"]
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, stdout=PIPE, stdin=PIPE, preexec_fn=preexec_func)
else:
# preexec_fn not supported on Windows
proc = Popen(command, stdout=PIPE, stdin=PIPE)
# Determine which ephemeral port the server started on:
port = int(proc.stdout.readline())
# Create a thread to echo output from the GatewayServer, which is required
# for Java log output to show up:
class EchoOutputThread(Thread):
def __init__(self, stream):
Thread.__init__(self)
self.daemon = True
self.stream = stream
def run(self):
while True:
line = self.stream.readline()
sys.stderr.write(line)
EchoOutputThread(proc.stdout).start()
# Connect to the gateway
gateway = JavaGateway(GatewayClient(port=port), auto_convert=False)
# 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.*")
java_import(gateway.jvm, "org.apache.spark.sql.SQLContext")
java_import(gateway.jvm, "org.apache.spark.sql.hive.HiveContext")
java_import(gateway.jvm, "org.apache.spark.sql.hive.LocalHiveContext")
java_import(gateway.jvm, "org.apache.spark.sql.hive.TestHiveContext")
java_import(gateway.jvm, "scala.Tuple2")
return gateway
def set_env_vars_for_yarn():
# Add the spark jar, which includes the pyspark files, to the python path
env_map = parse_env(os.environ.get("SPARK_YARN_USER_ENV", ""))
if "PYTHONPATH" in env_map:
env_map["PYTHONPATH"] += ":spark.jar"
else:
env_map["PYTHONPATH"] = "spark.jar"
os.environ["SPARK_YARN_USER_ENV"] = ",".join(k + '=' + v for (k, v) in env_map.items())
def parse_env(env_str):
# Turns a comma-separated of env settings into a dict that maps env vars to
# their values.
env = {}
for var_str in env_str.split(","):
parts = var_str.split("=")
if len(parts) == 2:
env[parts[0]] = parts[1]
elif len(var_str) > 0:
print "Invalid entry in SPARK_YARN_USER_ENV: " + var_str
sys.exit(1)
return env