python 安装pyspark_PySpark笔记(一)：Spark简介与安装

Apache Spark 是专为大规模数据处理而设计的快速通用的计算引擎。Spark是UC Berkeley AMP lab (加州大学伯克利分校的AMP实验室)所开源的类Hadoop MapReduce的通用并行框架，Spark拥有Hadoop MapReduce所具有的优点；但不同MapReduce的是Job中间输出结果可以保存在内存中，从而不再需要读写HDFS，因此Spark能更好适用于数据挖掘与机器学习等需要迭代的MapReduce的算法。

Spark提供了一个更快、更通用的数据处理平台。和Hadoop相比，Spark可以让你的程序在内存中运行时速度提升100倍，或者在磁盘上运行时速度提升10倍。去年，在100 TB Daytona GraySort比赛中，Spark战胜了Hadoop，它只使用了十分之一的机器，但运行速度提升了3倍。Spark也已经成为针对 PB 级别数据排序的最快的开源引擎。

Spark支持Scala、Java、Python、R等接口，本文均使用Python环境进行学习。

下载

如下图所示，选择最新版本的Spark，Pre-built版本下载之后可以直接运行，不需要我们再次编译。在不使用集群环境时，我们可以不安装Hadoop环境直接进行运行。选择完成后就可以点击选项4中的链接进行下载。

Spark下载

安装

1.下载的Spark直接解压就完成了安装，Windows 用户如果把Spark 安装到带有空格的路径下，可能会遇到一些问题。所以需要把Spark 安装到不带空格的路径下，比如C:\spark 这样的目录中。

2.Spark由于是使用Scala语言编写，因此需要安装对应版本的JDK包才能正常使用。JDK同样安装到不带空格的路径下。

3.Spark启动时需要根据HADOOP_HOME找到winutils.exe，因此需要下载对应版本的环境。

1.下载winutils的windows版本

由于我们的包是2.7版本，因此下载2.7版本的环境。

2.配置环境变量

增加用户变量HADOOP_HOME，指向文件解压的目录，然后在系统变量path里增加%HADOOP_HOME%\bin 即可。

4.将spark-python文件夹下的pyspark文件夹拷贝到python对应的文件夹中。或者执行以下命令安装：

pip install PySpark

Linux环境的配置类似即可。

测试

在conf 目录下复制log4j.properties.template为log4j.properties ，这个文件用来管理日志设置。接下来找到下面这一行：

log4j.rootCategory=INFO, console

然后通过下面的设定降低日志级别，只显示警告及更严重的信息：

log4j.rootCategory=WARN, console

在spark-bin文件夹下执行pyspark命令就可以进入pyspark-shell环境。也可以为Spark设置环境变量，同以上Hadoop环境的操作。

spark

在shell中执行下列代码测试，计算文件行数：

lines = sc.textFile("E:\Documents\Desktop\s.txt")

lines.count()

count

测试独立应用连接spark，将下列代码保存在demo.py，执行spark-submit demo.py，命令。

# coding:utf-8

from pyspark import SparkConf, SparkContext

if __name__ == '__main__':

# 连接集群local，本应用名称为Demo

conf = SparkConf().setMaster('local').setAppName('Demo')

sc = SparkContext(conf=conf)

# 统计文件中包含mape的行数，并打印第一行

lines = sc.textFile("E:\Documents\Desktop\s.txt")

plines = lines.filter(lambda lines: 'mape' in lines)

print(plines.count())

print(plines.first())

sc.stop

在Spark2.0中只要创建一个SparkSession就够了，SparkConf、SparkContext和SQLContext都已经被封装在SparkSession当中,因此代码也可以写成如下：

from pyspark.sql import SparkSession

# 连接集群local，本应用名称为Demo

sc = SparkSession.builder.master("local").appName(Demo").config("spark.some.config.option", "some-value").getOrCreate()

向spark提交的运行结果如图所示：

submit.jpg

异常处理

在windows下进行安装调试Spark时出现了多种异常状况，就我遇到的异常状况进行一下总结。

Hadoop winutils不存在异常

最开始没有配置winutils环境导致的异常，异常关键提示为：

Failed to locate the winutils binary in the hadoop binary path

F:\spark-2.2.0\bin>pyspark

Python 3.5.2 |Anaconda 4.2.0 (64-bit)| (default, Jul 5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)] on win32

Type "help", "copyright", "credits" or "license" for more information.

17/10/25 16:13:59 ERROR Shell: Failed to locate the winutils binary in the hadoop binary path

java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.

at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:379)

at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:394)

at org.apache.hadoop.util.Shell.(Shell.java:387)

at org.apache.hadoop.hive.conf.HiveConf$ConfVars.findHadoopBinary(HiveConf.java:2327)

at org.apache.hadoop.hive.conf.HiveConf$ConfVars.(HiveConf.java:365)

at org.apache.hadoop.hive.conf.HiveConf.(HiveConf.java:105)

at java.lang.Class.forName0(Native Method)

at java.lang.Class.forName(Class.java:348)

at py4j.reflection.CurrentThreadClassLoadingStrategy.classForName(CurrentThreadClassLoadingStrategy.java:40)

at py4j.reflection.ReflectionUtil.classForName(ReflectionUtil.java:51)

at py4j.reflection.TypeUtil.forName(TypeUtil.java:243)

at py4j.commands.ReflectionCommand.getUnknownMember(ReflectionCommand.java:175)

at py4j.commands.ReflectionCommand.execute(ReflectionCommand.java:87)

at py4j.GatewayConnection.run(GatewayConnection.java:214)

at java.lang.Thread.run(Thread.java:748)

17/10/25 16:14:01 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

Hadoop winutils版本异常

最开始下载的winutils版本是Hadoop 2.0版本，不符合Spark编译的2.7版本，因此出现了代码异常，更换版本后正常。关键异常提示为：

Caused by: org.apache.spark.sql.AnalysisException: java.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.createDirectoryWithMode0(Ljava/lang/String;I)V;

pyspark.sql.utils.IllegalArgumentException: "Error while instantiating 'org.apache.spark.sql.hive.HiveSessionStateBuilder':"

F:\spark-2.2.0\bin>pyspark

Python 3.5.2 |Anaconda 4.2.0 (64-bit)| (default, Jul 5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)] on win32

Type "help", "copyright", "credits" or "license" for more information.

Traceback (most recent call last):

File "F:\spark-2.2.0\python\pyspark\sql\utils.py", line 63, in deco

return f(*a, **kw)

File "F:\spark-2.2.0\python\lib\py4j-0.10.4-src.zip\py4j\protocol.py", line 319, in get_return_value

py4j.protocol.Py4JJavaError: An error occurred while calling o23.sessionState.

: java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveSessionStateBuilder':

at org.apache.spark.sql.SparkSession$.org$apache$spark$sql$SparkSession$$instantiateSessionState(SparkSession.scala:1053)

at org.apache.spark.sql.SparkSession$$anonfun$sessionState$2.apply(SparkSession.scala:130)

at scala.Option.getOrElse(Option.scala:121)

at org.apache.spark.sql.SparkSession.sessionState$lzycompute(SparkSession.scala:129)

at org.apache.spark.sql.SparkSession.sessionState(SparkSession.scala:126)

at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)

at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)

at java.lang.reflect.Method.invoke(Method.java:498)

at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)

at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)

at py4j.Gateway.invoke(Gateway.java:280)

at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)

at py4j.commands.CallCommand.execute(CallCommand.java:79)

at py4j.GatewayConnection.run(GatewayConnection.java:214)

at java.lang.Thread.run(Thread.java:748)

Caused by: org.apache.spark.sql.AnalysisException: java.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.createDirectoryWithMode0(Ljava/lang/String;I)V;

at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:106)

at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:193)

at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:105)

at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:93)

at org.apache.spark.sql.hive.HiveSessionStateBuilder.externalCatalog(HiveSessionStateBuilder.scala:39)

at org.apache.spark.sql.hive.HiveSessionStateBuilder.catalog$lzycompute(HiveSessionStateBuilder.scala:54)

at org.apache.spark.sql.hive.HiveSessionStateBuilder.catalog(HiveSessionStateBuilder.scala:52)

at org.apache.spark.sql.hive.HiveSessionStateBuilder.catalog(HiveSessionStateBuilder.scala:35)

at org.apache.spark.sql.internal.BaseSessionStateBuilder.build(BaseSessionStateBuilder.scala:289)

at org.apache.spark.sql.SparkSession$.org$apache$spark$sql$SparkSession$$instantiateSessionState(SparkSession.scala:1050)

... 16 more

Caused by: java.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.createDirectoryWithMode0(Ljava/lang/String;I)V

at org.apache.hadoop.io.nativeio.NativeIO$Windows.createDirectoryWithMode0(Native Method)

at org.apache.hadoop.io.nativeio.NativeIO$Windows.createDirectoryWithMode(NativeIO.java:524)

at org.apache.hadoop.fs.RawLocalFileSystem.mkOneDirWithMode(RawLocalFileSystem.java:478)

at org.apache.hadoop.fs.RawLocalFileSystem.mkdirsWithOptionalPermission(RawLocalFileSystem.java:532)

at org.apache.hadoop.fs.RawLocalFileSystem.mkdirs(RawLocalFileSystem.java:509)

at org.apache.hadoop.fs.FilterFileSystem.mkdirs(FilterFileSystem.java:305)

at org.apache.hadoop.hive.ql.exec.Utilities.createDirsWithPermission(Utilities.java:3679)

at org.apache.hadoop.hive.ql.session.SessionState.createRootHDFSDir(SessionState.java:597)

at org.apache.hadoop.hive.ql.session.SessionState.createSessionDirs(SessionState.java:554)

at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:508)

at org.apache.spark.sql.hive.client.HiveClientImpl.(HiveClientImpl.scala:191)

at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)

at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)

at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)

at java.lang.reflect.Constructor.newInstance(Constructor.java:423)

at org.apache.spark.sql.hive.client.IsolatedClientLoader.createClient(IsolatedClientLoader.scala:264)

at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:362)

at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:266)

at org.apache.spark.sql.hive.HiveExternalCatalog.client$lzycompute(HiveExternalCatalog.scala:66)

at org.apache.spark.sql.hive.HiveExternalCatalog.client(HiveExternalCatalog.scala:65)

at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply$mcZ$sp(HiveExternalCatalog.scala:194)

at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$databaseExists$1.apply(HiveExternalCatalog.scala:194)

at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)

... 25 more

During handling of the above exception, another exception occurred:

Traceback (most recent call last):

File "F:\spark-2.2.0\bin\..\python\pyspark\shell.py", line 45, in

spark = SparkSession.builder\

File "F:\spark-2.2.0\python\pyspark\sql\session.py", line 179, in getOrCreate

session._jsparkSession.sessionState().conf().setConfString(key, value)

File "F:\spark-2.2.0\python\lib\py4j-0.10.4-src.zip\py4j\java_gateway.py", line 1133, in __call__

File "F:\spark-2.2.0\python\pyspark\sql\utils.py", line 79, in deco

raise IllegalArgumentException(s.split(': ', 1)[1], stackTrace)

pyspark.sql.utils.IllegalArgumentException: "Error while instantiating 'org.apache.spark.sql.hive.HiveSessionStateBuilder':"

访问权限权限异常

由于windows与Linux权限的区别，在windows启动Spark时需要在tmp文件夹由于权限问题，无法写入导致的异常。使用管理员权限启动cmd，并且提前使在对应盘根目录下创建tmp文件夹，问题解决。关键异常提示：

Caused by: java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: ---------

F:\spark-2.2.0\bin>pyspark

Python 3.5.2 |Anaconda 4.2.0 (64-bit)| (default, Jul 5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)] on win32

Type "help", "copyright", "credits" or "license" for more information.

Traceback (most recent call last):

File "F:\spark-2.2.0\python\pyspark\sql\utils.py", line 63, in deco

return f(*a, **kw)

File "F:\spark-2.2.0\python\lib\py4j-0.10.4-src.zip\py4j\protocol.py", line 319, in get_return_value

py4j.protocol.Py4JJavaError: An error occurred while calling o23.sessionState.

: java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveSessionStateBuilder':

at org.apache.spark.sql.SparkSession$.org$apache$spark$sql$SparkSession$$instantiateSessionState(SparkSession.scala:1053)

at org.apache.spark.sql.SparkSession$$anonfun$sessionState$2.apply(SparkSession.scala:130)

at scala.Option.getOrElse(Option.scala:121)

at org.apache.spark.sql.SparkSession.sessionState$lzycompute(SparkSession.scala:129)

at org.apache.spark.sql.SparkSession.sessionState(SparkSession.scala:126)

at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)

at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)

at java.lang.reflect.Method.invoke(Method.java:498)

at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)

at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)

at py4j.Gateway.invoke(Gateway.java:280)

at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)

at py4j.commands.CallCommand.execute(CallCommand.java:79)

at py4j.GatewayConnection.run(GatewayConnection.java:214)

at java.lang.Thread.run(Thread.java:748)

Caused by: org.apache.spark.sql.AnalysisException: java.lang.RuntimeException: java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: ---------;