idea搭建flink环境

<properties>
<maven.compiler.source>1.8maven.compiler.source>
<maven.compiler.target>1.8maven.compiler.target>
<encoding>UTF-8encoding>
<scala.version>2.11.12scala.version>
<scala.binary.version>2.11scala.binary.version>
<flink.version>1.6.1flink.version>
properties>
<dependencies>
<dependency>
<groupId>org.apache.flinkgroupId>
<artifactId>flink-scala_${scala.binary.version}artifactId>
<version>${flink.version}version>
<scope>providedscope>
dependency>
<dependency>
<groupId>org.apache.flinkgroupId>
<artifactId>flink-streaming-scala_${scala.binary.version}artifactId>
<version>${flink.version}version>
<scope>providedscope>
dependency>
dependencies>

package it.bigdata.flink.study
import org.apache.flink.streaming.api.scala.{DataStream, StreamExecutionEnvironment}
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.streaming.api.scala._
//流处理 word count
object SteamWordCount {
def main(args: Array[String]): Unit = {
//创建流处理的执行环境
val env: StreamExecutiOnEnvironment= StreamExecutionEnvironment.getExecutionEnvironment
env.setParallelism(8)
//接受一个socket文本流
val inputDataStream: DataStream[String] = env.socketTextStream("10.18.35.155", 777)
// 进行转换处理统计
inputDataStream
.flatMap(_.split(" "))
.filter(_.nonEmpty)
.map((_,1))
.keyBy(0)
.sum(1)
.print()
env.execute("word count")
}
}