1. 准备工作
1.1需要的软件：
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 当然，也可以在官网下载最新版本的 Anaconda3，然后根据自己需要设置成 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，为了避免不必要的麻烦，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 进行下一步操作
点击Next 进行下一步
如果系统只有一个用户选择默认的第一个即可，如果有多个用户而且都要用到 Anaconda ，则选择第二个选项。
为了避免之后不必要的麻烦，建议默认路径安装即可，需要占用空间大约 1.8 G左右。
安装需要一段时间，等待安装完成即可。
到这里就安装完成了，可以将“Learn more about Aanaconda Cloud”Learn more about Aanaconda Support”前的对号去掉，然后点击“Finish”即可。
jdk1.8+也解压到默认的路径下;hadoop-2.7.4和spark-2.2.0-bin-hadoop2.7可以装在任意磁盘下
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:
上述操作之后,剩下的就是一直点”确定”,这样环境变量就配置好了
4.启动 spark
在启动之前需要在hadoop-2.7.4的bin目录下,安装winutils.exe文件,否则就会报错,错误如下
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$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)或者不用装hadoop,直接安装一个winustil.exe 但是必须配置环境变量.接下来在”开始”菜单键找到”jupyter notebook”,双击运行
启动之后会看到如下图所示:
在浏览器上会出现如下图所示:
之后在页面的右上角找到”New”创建”Python3”,如图所示:
之后在输入如下代码,启动spark
import os
import sys
spark_home = os.environ.get('SPARK_HOME', None)
if not spark_home:
raise ValueError('SPARK_HOME environment variable is not set')
sys.path.insert(0, os.path.join(spark_home, 'python'))
sys.path.insert(0, os.path.join(spark_home, 'python/lib/py4j-0.10.4-src.zip'))
comm=os.path.join(spark_home, 'python/lib/py4j-0.10.4-src.zip')
print ('start spark....',comm)
exec(open(os.path.join(spark_home, 'python/pyspark/shell.py')).read())如图所示:
至此,spark启动成功
5.启动时出现的错误及解决办法
1.错误如下:
java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveSessionState':
at org.apache.spark.sql.SparkSession$.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: ---------所以我们需要更新E:/tmp/hive的权限(我在E盘下运行的spark-shell命令，如果在其他盘运行，就改成对应的盘符+/tmp/hive)。运行如下命令：
E:\>C:\winutils\bin\winutils.exe chmod 777 E:\tmp\hive再次运行spark-shell，spark启动成功。此时可以通过 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