1、找到CDH的版本
[root@web02 spark1.3]# hadoop version
Hadoop 2.0.0-cdh4.7.0
Subversion file:///var/lib/jenkins/workspace/CDH4.7.0-Packaging-Hadoop/build/cdh4/hadoop/2.0.0-cdh4.7.0/source/hadoop-common-project/hadoop-common -r c2ecdeb17590d43320f2151f64e48603aa4849f7
Compiled by jenkins on Wed May 28 09:41:14 PDT 2014
From source with checksum f60207d0daa9f943f253cc8932d598c8
This command was run using /app/home/hadoop/src/hadoop-2.0.0-cdh4.7.0/share/hadoop/common/hadoop-common-2.0.0-cdh4.7.0.jar
对应版本号:
2.0.0-cdh4.7.0
编译参考地址:http://spark.apache.org/docs/latest/building-spark.html
指定编译的profile,可以选择的有yarn, hive, hive-thriftserver
mvn -Dhadoop.version=1.2.1 -DskipTests clean package
/app/hadoop/shengli/apache-maven-3.0.5/bin/mvn -Dhadoop.version=2.0.0-cdh4.7.0 -Pyarn-alpha -Phive -Phive-thriftserver -DskipTests clean package
Test Case测试:
mvn -Dhadoop.version=… -DwildcardSuites=org.apache.spark.repl.ReplSuite test
对对应版本号进行编译:
build/sbt -Pyarn -Phadoop-2.3 assembly
SPARK_YARN_USER_ENV
用户可以在这个参数中设置Spark on YARN的环境变量,可以省略。
例如:SPARK_YARN_USER_ENV=”JAVA_HOME=/jdk64,FOO=bar”
SPARK_JAR
设置Spark jar在HDFS的位置。
例如:export SPARK_JAR=hdfs:///some/path.
在每台Hadoop NodeManager节点上设置变量
将Spark发布包放到hdfs上,而不是每次提交都提交spark jar包,使用命令 SPARK_JAR=hdfs://xxx/xx/spark-assembly-1.3.1-hadoop2.5.0.jar
例如:
SPARK_JAR=hdfs://xxxxxx/xxxxxxx/spark-assembly-1.3.1-hadoop2.5.0.jar ./bin/spark-submit --class org.apache.spark.examples.SparkPI --master yarn-cluster --num-executors 3 --driver-memory 1g --executor-memory 3g --executor-cores 2 lib/spark-examples*.jar 10
Build Spark1.3.1 with CDH HADOOP
原文:http://blog.csdn.net/oopsoom/article/details/45152161