java - 异常 : Java gateway process exited before sending the driver its port number while creating a Spark Session in Python

Question

因此，我尝试使用以下方法在 Python 2.7 中创建一个 Spark session :

#Initialize SparkSession and SparkContext
from pyspark.sql import SparkSession  
from pyspark import SparkContext

#Create a Spark Session
SpSession = SparkSession \
    .builder \
    .master("local[2]") \
    .appName("V2 Maestros") \
    .config("spark.executor.memory", "1g") \
    .config("spark.cores.max","2") \
    .config("spark.sql.warehouse.dir", "file:///c:/temp/spark-warehouse")\
    .getOrCreate()

#Get the Spark Context from Spark Session    
SpContext = SpSession.sparkContext

我收到以下指向 python\lib\pyspark.zip\pyspark\java_gateway.pypath`

的错误

Exception: Java gateway process exited before sending the driver its port number

试图查看包含以下内容的 java_gateway.py 文件:

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",
                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.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.hive.*")
    java_import(gateway.jvm, "scala.Tuple2")

    return gateway

我是 Spark 和 Pyspark 的新手，因此无法在此处调试问题。我还尝试查看其他一些建议: Spark + Python - Java gateway process exited before sending the driver its port number?和 Pyspark: Exception: Java gateway process exited before sending the driver its port number

但目前无法解决这个问题。请帮忙!

这是 spark 环境的样子:

# This script loads spark-env.sh if it exists, and ensures it is only loaded once.
# spark-env.sh is loaded from SPARK_CONF_DIR if set, or within the current directory's
# conf/ subdirectory.

# Figure out where Spark is installed
if [ -z "${SPARK_HOME}" ]; then
  export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
fi

if [ -z "$SPARK_ENV_LOADED" ]; then
  export SPARK_ENV_LOADED=1

  # Returns the parent of the directory this script lives in.
  parent_dir="${SPARK_HOME}"

  user_conf_dir="${SPARK_CONF_DIR:-"$parent_dir"/conf}"

  if [ -f "${user_conf_dir}/spark-env.sh" ]; then
    # Promote all variable declarations to environment (exported) variables
    set -a
    . "${user_conf_dir}/spark-env.sh"
    set +a
  fi
fi

# Setting SPARK_SCALA_VERSION if not already set.

if [ -z "$SPARK_SCALA_VERSION" ]; then

  ASSEMBLY_DIR2="${SPARK_HOME}/assembly/target/scala-2.11"
  ASSEMBLY_DIR1="${SPARK_HOME}/assembly/target/scala-2.10"

  if [[ -d "$ASSEMBLY_DIR2" && -d "$ASSEMBLY_DIR1" ]]; then
    echo -e "Presence of build for both scala versions(SCALA 2.10 and SCALA 2.11) detected." 1>&2
    echo -e 'Either clean one of them or, export SPARK_SCALA_VERSION=2.11 in spark-env.sh.' 1>&2
    exit 1
  fi

  if [ -d "$ASSEMBLY_DIR2" ]; then
    export SPARK_SCALA_VERSION="2.11"
  else
    export SPARK_SCALA_VERSION="2.10"
  fi
fi

以下是我的 Spark 环境是如何在 Python 中设置的:

import os
import sys

# NOTE: Please change the folder paths to your current setup.
#Windows
if sys.platform.startswith('win'):
    #Where you downloaded the resource bundle
    os.chdir("E:/Udemy - Spark/SparkPythonDoBigDataAnalytics-Resources")
    #Where you installed spark.    
    os.environ['SPARK_HOME'] = 'E:/Udemy - Spark/Apache Spark/spark-2.0.0-bin-hadoop2.7'
#other platforms - linux/mac
else:
    os.chdir("/Users/kponnambalam/Dropbox/V2Maestros/Modules/Apache Spark/Python")
    os.environ['SPARK_HOME'] = '/users/kponnambalam/products/spark-2.0.0-bin-hadoop2.7'

os.curdir

# Create a variable for our root path
SPARK_HOME = os.environ['SPARK_HOME']
# Create a variable for our root path
SPARK_HOME = os.environ['SPARK_HOME']

#Add the following paths to the system path. Please check your installation
#to make sure that these zip files actually exist. The names might change
#as versions change.
sys.path.insert(0,os.path.join(SPARK_HOME,"python"))
sys.path.insert(0,os.path.join(SPARK_HOME,"python","lib"))
sys.path.insert(0,os.path.join(SPARK_HOME,"python","lib","pyspark.zip"))
sys.path.insert(0,os.path.join(SPARK_HOME,"python","lib","py4j-0.10.1-src.zip"))

#Initialize SparkSession and SparkContext
from pyspark.sql import SparkSession  
from pyspark import SparkContext

Answer 1

阅读许多帖子后，我终于让 Spark 在我的 Windows 笔记本电脑上运行。我使用 Anaconda Python，但我相信这也适用于标准发行版。

因此，您需要确保可以独立运行 Spark。我的假设是您安装了有效的 python 路径和 Java。对于 Java，我在路径中定义了“C:\ProgramData\Oracle\Java\javapath”，它重定向到我的 Java8 bin 文件夹。

1. 从 https://spark.apache.org/downloads.html 下载预构建的 Hadoop 版本的 Spark并提取它，例如到 C:\spark-2.2.0-bin-hadoop2.7
2. 创建环境变量 SPARK_HOME，稍后 pyspark 将需要它来获取本地 Spark 安装。

3. 转到 %SPARK_HOME%\bin 并尝试运行 pyspark，它是 Python Spark shell。如果你的环境和我的一样，你会看到关于无法找到 winutils 和 hadoop 的异常。第二个异常(exception)是关于缺少 Hive:

   pyspark.sql.utils.IllegalArgumentException:u“实例化‘org.apache.spark.sql.hive.HiveSessionStateBuilder’时出错:”

4. 然后我找到并简单地关注了https://jaceklaskowski.gitbooks.io/mastering-apache-spark/spark-tips-and-tricks-running-spark-windows.html具体来说:

5. 下载winutils，放到c:\hadoop\bin。创建 HADOOP_HOME env 并将 %HADOOP_HOME%\bin 添加到 PATH。
6. 为 Hive 创建目录，例如c:\tmp\hive 并在管理员模式下在 cmd 中运行 winutils.exe chmod -R 777 C:\tmp\hive。
7. 然后转到 %SPARK_HOME%\bin 并确保当您运行 pyspark 时，您会看到一个漂亮的 ASCII Spark Logo :请注意，需要已经定义 sc spark 上下文变量。
8. 好吧，我的主要目的是让 pyspark 在我的 IDE 中自动完成，这就是 SPARK_HOME(第 2 步)发挥作用的时候。如果一切设置正确，您应该会看到以下几行:

希望对您有所帮助，您可以享受在本地运行 Spark 代码的乐趣。