Spark编译安装和运行
一、环境说明
Mac OSX Java 1.7.0_71 Spark
二、编译安装
tar -zxvf spark-.tgz cd spark- ./sbt/sbt assembly
ps:如果之前执行过编译,需要执行 ./sbt/sbt clean
清理后才能重新编译。
三、运行
adeMacBook-Pro:spark- apple$ ./bin/spark-shell log4j:WARN No appenders could be found for logger (org.apache.hadoop.metrics2.lib.MutableMetricsFactory). log4j:WARN Please initialize the log4j system properly. log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info. Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties // :: INFO SecurityManager: Changing view acls to: apple // :: INFO SecurityManager: Changing modify acls to: apple // :: INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(apple); users with modify permissions: Set(apple) // :: INFO HttpServer: Starting HTTP Server // :: INFO Server: jetty-.y.z-SNAPSHOT // :: INFO AbstractConnector: Started SocketConnector@ // :: INFO Utils: Successfully started service . Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ '_/ /___/ .__/\_,_/_/ /_/\_\ version /_/ Using Scala version (Java HotSpot(TM) -Bit Server VM, Java 1.7.0_71) Type in expressions to have them evaluated. Type :help for more information. // :: INFO SparkContext: Running Spark version // :: INFO SecurityManager: Changing view acls to: apple // :: INFO SecurityManager: Changing modify acls to: apple // :: INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(apple); users with modify permissions: Set(apple) // :: INFO Slf4jLogger: Slf4jLogger started // :: INFO Remoting: Starting remoting // :: INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriver@192.168.1.106:61567] // :: INFO Utils: Successfully started service . // :: INFO SparkEnv: Registering MapOutputTracker // :: INFO SparkEnv: Registering BlockManagerMaster // :: INFO DiskBlockManager: Created local directory at /-4d54-89f3-8d97bf15205f/blockmgr-b8410cda-aa29---d6155512cd53 // :: INFO MemoryStore: MemoryStore started with capacity 265.4 MB // :: INFO HttpFileServer: HTTP File server directory -4d54-89f3-8d97bf15205f/httpd-a1838f08-2ccd-42d2--6e91cb6fdfad // :: INFO HttpServer: Starting HTTP Server // :: INFO Server: jetty-.y.z-SNAPSHOT // :: INFO AbstractConnector: Started SocketConnector@ // :: INFO Utils: Successfully started service . // :: INFO SparkEnv: Registering OutputCommitCoordinator // :: INFO Server: jetty-.y.z-SNAPSHOT // :: INFO AbstractConnector: Started SelectChannelConnector@ // :: INFO Utils: Successfully started service . // :: INFO SparkUI: Started SparkUI at http://192.168.1.106:4040 // :: INFO Executor: Starting executor ID driver on host localhost // :: INFO Executor: Using REPL class URI: http://192.168.1.106:61566 // :: INFO Utils: Successfully started service . // :: INFO NettyBlockTransferService: Server created on // :: INFO BlockManagerMaster: Trying to register BlockManager // :: INFO BlockManagerMasterEndpoint: Registering block manager localhost: with ) // :: INFO BlockManagerMaster: Registered BlockManager // :: INFO SparkILoop: Created spark context.. Spark context available as sc. // :: INFO SparkILoop: Created sql context.. SQL context available as sqlContext. scala>
参考:
https://spark.apache.org/docs/latest/
三、使用spark交互模式
. 运行./spark-shell.sh . scala> val data = Array(, , , , ) //产生data data: Array[Int] = Array(, , , , ) . scala> val distData = sc.parallelize(data) //将data处理成RDD distData: spark.RDD[Int] = spark.ParallelCollection@7a0ec850 (显示出的类型为RDD) . scala> distData.reduce(_+_) //在RDD上进行运算,对data里面元素进行加和 // :: INFO spark.SparkContext: Starting job... . 最后运行得到 // :: INFO spark.SparkContext: Job finished in 0.076729174 s res2: Int =
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