在windowns下安装Anaconda3运行spark

1. 准备工做

1.1须要的软件：
Anaconda3-5.0.0-Windows-x86_64
hadoop-2.7.4
jdk1.8+
spark-2.2.0-bin-hadoop2.7

1.2下载软件
Anaconda 官网下载地址：https://www.continuum.io/downloads
目前最新版本是 python 3.6，默认下载也是 Python 3.6，百度网盘下载地址：http://pan.baidu.com/s/1jIePjPc 密码是：robu 固然，也能够在官网下载最新版本的 Anaconda3，而后根据本身须要设置成 python 3.6

Hadoop 官网下载地址：http://hadoop.apache.org/releases.html

Spark 官网下载地址：http://spark.apache.org/downloads.html

jdk 下载官网地址：http://www.oracle.com/technetwork/java/javase/downloads/index.html

2.安装并在windowns下配置环境变量

Anaconda 安装较为简单，基本都是下一步，为了不没必要要的麻烦，最后默认安装路径，具体安装过程为：
双击安装文件，启动安装程序

点击I Agree 进行下一步操做

点击Next 进行下一步

若是系统只有一个用户选择默认的第一个便可，若是有多个用户并且都要用到 Anaconda ，则选择第二个选项。

为了不以后没必要要的麻烦，建议默认路径安装便可，须要占用空间大约 1.8 G左右。

安装须要一段时间，等待安装完成便可。

到这里就安装完成了，能够将“Learn more about Aanaconda Cloud”Learn more about Aanaconda Support”前的对号去掉，而后点击“Finish”便可。

jdk1.8+也解压到默认的路径下;hadoop-2.7.4和spark-2.2.0-bin-hadoop2.7能够装在任意磁盘下

在windowns下配置环境变量(hadoop/spark/Java)

Java环境变量:

hadoop环境变量:

spark环境变量:

配置path:

上述操做以后,剩下的就是一直点”肯定”,这样环境变量就配置好了

4.启动 spark

在启动以前须要在hadoop-2.7.4的bin目录下,安装winutils.exe文件,不然就会报错,错误以下

E:\>spark-shell Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel). 17/06/05 21:34:43 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.<clinit>(Shell.java:387) at org.apache.hadoop.hive.conf.HiveConf$ConfVars.findHadoopBinary(HiveConf.java:2327) at org.apache.hadoop.hive.conf.HiveConf$ConfVars.<clinit>(HiveConf.java:365) at org.apache.hadoop.hive.conf.HiveConf.<clinit>(HiveConf.java:105) at java.lang.Class.forName0(Native Method) at java.lang.Class.forName(Class.java:348) at org.apache.spark.util.Utils$.classForName(Utils.scala:229) at org.apache.spark.sql.SparkSession$.hiveClassesArePresent(SparkSession.scala:991) at org.apache.spark.repl.Main$.createSparkSession(Main.scala:92) at $line3.$read$$iw$$iw.<init>(<console>:15) at $line3.$read$$iw.<init>(<console>:42) at $line3.$read.<init>(<console>:44) at $line3.$read$.<init>(<console>:48) at $line3.$read$.<clinit>(<console>) at $line3.$eval$.$print$lzycompute(<console>:7) at $line3.$eval$.$print(<console>:6) at $line3.$eval.$print(<console>) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:497) at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:786) at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1047) at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:638) at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:637) at scala.reflect.internal.util.ScalaClassLoader$class.asContext(ScalaClassLoader.scala:31) at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:19) at scala.tools.nsc.interpreter.IMain$WrappedRequest.loadAndRunReq(IMain.scala:637) at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:569) at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:565) at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:807) at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:681) at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:395) at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply$mcV$sp(SparkILoop.scala:38) at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:37) at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:37) at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:214) at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:37) at org.apache.spark.repl.SparkILoop.loadFiles(SparkILoop.scala:105) at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:920) at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909) at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909) at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97) at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:909) at org.apache.spark.repl.Main$.doMain(Main.scala:69) at org.apache.spark.repl.Main$.main(Main.scala:52) at org.apache.spark.repl.Main.main(Main.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:497) at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:743) at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187) at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

或者不用装hadoop,直接安装一个winustil.exe 可是必须配置环境变量.接下来在”开始”菜单键找到”jupyter notebook”,双击运行

启动以后会看到以下图所示:

在浏览器上会出现以下图所示:

以后在页面的右上角找到”New”建立”Python3”,如图所示:

以后在输入以下代码,启动spark

import os
import sys

spark_home = os.environ.get('SPARK_HOME', None)
if not spark_home:
    raise ValueError('SPARK_HOME environment variable is not set')
sys.path.insert(0, os.path.join(spark_home, 'python'))
sys.path.insert(0, os.path.join(spark_home, 'python/lib/py4j-0.10.4-src.zip'))
comm=os.path.join(spark_home, 'python/lib/py4j-0.10.4-src.zip')
print ('start spark....',comm)
exec(open(os.path.join(spark_home, 'python/pyspark/shell.py')).read())

如图所示:

至此,spark启动成功

5.启动时出现的错误及解决办法

1.错误以下:

java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveSessionState':
  at org.apache.spark.sql.SparkSession$.org$apache$spark$sql$SparkSession$$reflect(SparkSession.scala:981)
  at org.apache.spark.sql.SparkSession.sessionState$lzycompute(SparkSession.scala:110)
  at org.apache.spark.sql.SparkSession.sessionState(SparkSession.scala:109)
  at org.apache.spark.sql.SparkSession$Builder$$anonfun$getOrCreate$5.apply(SparkSession.scala:878)
  at org.apache.spark.sql.SparkSession$Builder$$anonfun$getOrCreate$5.apply(SparkSession.scala:878)
  at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:99)
  at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:99)
  at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:230)
  at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
  at scala.collection.mutable.HashMap.foreach(HashMap.scala:99)
  at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:878)
  at org.apache.spark.repl.Main$.createSparkSession(Main.scala:96)
  ... 47 elided
Caused by: java.lang.reflect.InvocationTargetException: java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveExternalCatalog':
  at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
  at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
  at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
  at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
  at org.apache.spark.sql.SparkSession$.org$apache$spark$sql$SparkSession$$reflect(SparkSession.scala:978)
  ... 58 more
Caused by: java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveExternalCatalog':
  at org.apache.spark.sql.internal.SharedState$.org$apache$spark$sql$internal$SharedState$$reflect(SharedState.scala:169)
  at org.apache.spark.sql.internal.SharedState.<init>(SharedState.scala:86)
  at org.apache.spark.sql.SparkSession$$anonfun$sharedState$1.apply(SparkSession.scala:101)
  at org.apache.spark.sql.SparkSession$$anonfun$sharedState$1.apply(SparkSession.scala:101)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.sql.SparkSession.sharedState$lzycompute(SparkSession.scala:101)
  at org.apache.spark.sql.SparkSession.sharedState(SparkSession.scala:100)
  at org.apache.spark.sql.internal.SessionState.<init>(SessionState.scala:157)
  at org.apache.spark.sql.hive.HiveSessionState.<init>(HiveSessionState.scala:32)
  ... 63 more
Caused by: java.lang.reflect.InvocationTargetException: java.lang.reflect.InvocationTargetException: java.lang.RuntimeException: java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: ---------
  at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
  at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
  at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
  at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
  at org.apache.spark.sql.internal.SharedState$.org$apache$spark$sql$internal$SharedState$$reflect(SharedState.scala:166)
  ... 71 more
Caused by: java.lang.reflect.InvocationTargetException: java.lang.RuntimeException: java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: ---------
  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:422)
  at org.apache.spark.sql.hive.client.IsolatedClientLoader.createClient(IsolatedClientLoader.scala:264)
  at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:358)
  at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:262)
  at org.apache.spark.sql.hive.HiveExternalCatalog.<init>(HiveExternalCatalog.scala:66)
  ... 76 more
Caused by: java.lang.RuntimeException: java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: ---------
  at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:522)
  at org.apache.spark.sql.hive.client.HiveClientImpl.<init>(HiveClientImpl.scala:188)
  ... 84 more
Caused by: java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: ---------
  at org.apache.hadoop.hive.ql.session.SessionState.createRootHDFSDir(SessionState.java:612)
  at org.apache.hadoop.hive.ql.session.SessionState.createSessionDirs(SessionState.java:554)
  at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:508)
  ... 85 more

错误消息中提示零时目录 /tmp/hive 没有写的权限：

The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: ---------

因此咱们须要更新E:/tmp/hive的权限(我在E盘下运行的spark-shell命令，若是在其余盘运行，就改为对应的盘符+/tmp/hive)。运行以下命令：

E:\>C:\winutils\bin\winutils.exe chmod 777 E:\tmp\hive

再次运行spark-shell，spark启动成功。此时能够经过 http://localhost:4040 来访问Spark UI

解决错误的参考博客:https://yq.aliyun.com/articles/96424?t=t1
http://www.cnblogs.com/czm1032851561/p/5751722.html