spark的源码使用了两种构建工具。maven和sbt。

很多人都推荐使用idea+sbt来导入spark的源码。我自己用idea+sbt试了一下。给sbt添加镜像源了，还是没有导入成功。也许是我对sbt不够了解吧。我感觉国内对sbt支持的不好，所以劝大家还是别用sbt了。

然后我又换成EclipseIDE + maven。给maven添加了镜像源，拉jar包确实没问题了。但是eclipse直接卡死了，而且各种报错。可以看出eclipse的插件对scala的确支持的不是很好。尤其是模块化的maven工程。

最后我选择了Idea+maven的方式。不得不说intellij的确做的好，启动速度快，界面还漂亮。一直以为intellij是收费的，所以不关注它。最近才知道竟然有一个社区版的。果断就选它了。再看看github上对Spark的介绍：“Spark is built using Apache Maven.”,咦？sbt哪儿去了？spark in github

重要提示：如果你跟我一样，选择以maven工程的方式导入。先别急着导入，配置好镜像源，然后进入到spark源码顶层目录。命令行下执行 mvn -DskipTests clean package。 这样拉jar包会快些。
注意虽然配置了镜像源，速度也很快。但是拉jar包的时候有的jar包会有问题。这是就要把本地仓库里有问题的jar删掉，再拉取一次。拉完了之后再导入到intellij里。 导入到intellij之后，
View>>Tool Windows>>Maven Projects>>点击小图标Generate Sources and Update Folders For All Projects.
如果你在pom.xml里新增加了依赖，Reimport一下就好了（相当于eclipse里的maven>>update project）。

maven的镜像源配置。不要用oschina了，别问我为什么。用aliyun的。

<mirrors>
    <mirror>
        <id>alimaven</id>
        <name>aliyun maven</name>
        <url>http://maven.aliyun.com/nexus/content/groups/public/</url>
        <mirrorOf>central</mirrorOf>
    </mirror>
    <mirror>
        <id>repo2</id>
        <mirrorOf>central</mirrorOf>
        <name>Human Readable Name for this Mirror.</name>
        <url>http://repo2.maven.org/maven2/</url>
    </mirror>

    <mirror>
        <id>ibiblio</id>
        <mirrorOf>central</mirrorOf>
        <name>Human Readable Name for this Mirror.</name>
        <url>http://mirrors.ibiblio.org/pub/mirrors/maven2/</url>
    </mirror>
    <mirror>
        <id>jboss-public-repository-group</id>
        <mirrorOf>central</mirrorOf>
        <name>JBoss Public Repository Group</name>
        <url>http://repository.jboss.org/nexus/content/groups/public</url>
    </mirror>
</mirrors>

intellij配置maven：
File>>Other Settings>>Default Settings>>Build, Execution, Deployment>>Maven>>Maven home Directory>>your maven home path

环境：
ubuntu16.04
maven3.3.9
Oracle JDK1.8
IntelliJ IDEA community 2017.1.4

导入完之后我想在intellij里直接运行spark-example里的JavaSparkPi。你会发现很多类找不到。原因是
spark-example这个模块里的很多jar包都是provided的。这个例子本意是你直接在spark的shell里运行的，shell脚步在bin目录下，所有依赖的jar包都在jars文件夹下，所以人家给个provided完全没问题。但是如果你直接在intellij里运行当然不行。 要把pom.xml里所有的provided替换成compile。还要加上其他jar包的依赖，如jetty。

要运行JavaSparkPi这样例子，需要加上这几个jar包：

<dependency>
    <groupId>com.google.guava</groupId>
    <artifactId>guava</artifactId>
    <version>14.0.1</version>
    <scope>compile</scope>
</dependency>
<dependency>
    <groupId>org.eclipse.jetty</groupId>
    <artifactId>jetty-server</artifactId>
    <version>9.3.11.v20160721</version>
    <scope>compile</scope>
</dependency>
<dependency>
    <groupId>org.eclipse.jetty</groupId>
    <artifactId>jetty-util</artifactId>
    <version>9.3.11.v20160721</version>
    <scope>compile</scope>
</dependency>
<dependency>
    <groupId>org.eclipse.jetty</groupId>
    <artifactId>jetty-servlet</artifactId>
    <version>9.3.11.v20160721</version>
    <scope>compile</scope>
</dependency>
<dependency>
    <groupId>org.eclipse.jetty</groupId>
    <artifactId>jetty-webapp</artifactId>
    <version>9.3.11.v20160721</version>
    <scope>compile</scope>
</dependency>
<dependency>
    <groupId>org.eclipse.jetty</groupId>
    <artifactId>jetty-security</artifactId>
    <version>9.3.11.v20160721</version>
    <scope>compile</scope>
</dependency>
<dependency>
    <groupId>org.eclipse.jetty</groupId>
    <artifactId>jetty-http</artifactId>
    <version>9.3.11.v20160721</version>
    <scope>compile</scope>
</dependency>

<dependency>
    <groupId>org.glassfish.jersey.core</groupId>
    <artifactId>jersey-client</artifactId>
    <scope>compile</scope>
</dependency>
<dependency>
    <groupId>org.glassfish.jersey.core</groupId>
    <artifactId>jersey-common</artifactId>
    <scope>compile</scope>
</dependency>
<dependency>
    <groupId>org.glassfish.jersey.core</groupId>
    <artifactId>jersey-server</artifactId>
    <scope>compile</scope>
</dependency>

然后运行的时候会报错
Exception in thread “main” org.apache.spark.SparkException: A master URL must be set in your configuration

你需要指定spark运行在本地模式：Run>>Edit Configurations>>VM Options>>写上-Dspark.master=local
然后再运行就OK了。最后控制台输出如下信息：

17/06/23 15:37:33 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
17/06/23 15:37:33 INFO DAGScheduler: ResultStage 0 (reduce at JavaSparkPi.java:54) finished in 0.430 s
17/06/23 15:37:33 INFO DAGScheduler: Job 0 finished: reduce at JavaSparkPi.java:54, took 0.455996 s
Pi is roughly 3.14166
17/06/23 15:37:33 INFO AbstractConnector: Stopped Spark@6c45ee6e{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
17/06/23 15:37:33 INFO SparkUI: Stopped Spark web UI at http://192.168.40.115:4040
17/06/23 15:37:33 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
17/06/23 15:37:33 INFO MemoryStore: MemoryStore cleared
17/06/23 15:37:33 INFO BlockManager: BlockManager stopped
17/06/23 15:37:33 INFO BlockManagerMaster: BlockManagerMaster stopped
17/06/23 15:37:33 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
17/06/23 15:37:33 INFO SparkContext: Successfully stopped SparkContext
17/06/23 15:37:33 INFO ShutdownHookManager: Shutdown hook called
17/06/23 15:37:33 INFO ShutdownHookManager: Deleting directory /tmp/spark-8fbff2d9-a87a-408e-bd4c-b5a4d4252762

Process finished with exit code 0