Flink实战（108）：connector（十七）hdfs 读写（二）写

1. 依赖HDFS

pom.xml 添加依赖

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>org.example</groupId>
    <artifactId>FlinkHdfs</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <flink.version>1.11.0</flink.version>
        <scala.binary.version>2.11</scala.binary.version>
        <log4j.version>2.12.1</log4j.version>
        <hive.version>3.1.2</hive.version>
        <hadoop.version>3.1.3</hadoop.version>
    </properties>
    <dependencies>
        <!-- 运行FLINK必须-->
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.56</version>
        </dependency>
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-scala_${scala.binary.version}</artifactId>
        <version>${flink.version}</version>
        <!--            <scope>provided</scope>-->
    </dependency>

    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-streaming-scala_${scala.binary.version}</artifactId>
        <version>${flink.version}</version>
        <!--            <scope>provided</scope>-->
    </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <!-- 读HDFS必须-->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-hadoop-compatibility_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>${hadoop.version}</version>
        </dependency>

        <!-- 写HDFS必须-->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka-0.11_2.11</artifactId>
            <version>${flink.version}</version>
            <exclusions>
                <exclusion>
                    <artifactId>slf4j-api</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
            </exclusions>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-filesystem_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>




    </dependencies>
</project>      

View Code

2. 配置 HDFS

将​

​hdfs-site.xml​

​和​

​core-site.xml​

​放入到​

​src/main/resources​

​目录下面

3.写入HDFS

输入参数：

{"deviceType":"0","userNums":0,"newusers":1,"dayActivenums":1,"timeinfoString":"","timeinfo":"2018090704","userId":"1","monthActivenums":1,"weekActivenums":1,"groupByField":"1==0==2018090704","times":1,"hourActivenums":1}

{"deviceType":"1","userNums":0,"newusers":0,"dayActivenums":0,"timeinfoString":"","timeinfo":"2018090705","userId":"2","monthActivenums":0,"weekActivenums":0,"groupByField":"2==1==2018090705","times":1,"hourActivenums":0}

1.主程序

package com.atguigu

import java.util.Properties

import org.apache.flink.api.common.serialization.SimpleStringEncoder
import org.apache.flink.core.fs.Path
import org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink
import org.apache.flink.streaming.api.scala._
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer011
import org.apache.flink.streaming.util.serialization.SimpleStringSchema

object WriteToHDFS {
  def main(args: Array[String]): Unit = {
    val bsEnv = StreamExecutionEnvironment.getExecutionEnvironment
    bsEnv.setParallelism(1)

     bsEnv.enableCheckpointing(5000L)//一定要开启checkpoint

    val properties = new Properties()
    properties.setProperty("bootstrap.servers", "hadoop102:9092,hadoop103:9092,hadoop104:9092")
    properties.setProperty("group.id", "caimoutest3");

    properties.setProperty("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer")
    properties.setProperty("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer")
    properties.setProperty("auto.offset.reset", "latest")

    val stream = bsEnv.addSource(new FlinkKafkaConsumer011(
      "datainfo4", new SimpleStringSchema(), properties
    ))

    val fileSink = StreamingFileSink
      .forRowFormat(new Path("hdfs://hadoop102:9820/dataanlay/liuliang/"),new SimpleStringEncoder[String]("UTF-8"))
      .withBucketAssigner(new LiuLiangUserDetailBucketAssigner()) // 自定义分区路径
      .withBucketCheckInterval(5*1000)
      .build()

    stream.addSink(fileSink)

    bsEnv.execute("LiuLiangHourUserDetailAnaly")






  }

}      

2 LiuLiangUserDetailBucketAssigner

package com.atguigu

import java.io.File

import com.alibaba.fastjson.JSON
import org.apache.flink.core.io.SimpleVersionedSerializer
import org.apache.flink.streaming.api.functions.sink.filesystem.BucketAssigner

class LiuLiangUserDetailBucketAssigner extends BucketAssigner[String,String] {
  override def getBucketId(in: String, context: BucketAssigner.Context): String = {
    System.out.println(in)
    val dateString = JSON.parseObject(in).getString("timeinfo")
    val result = dateString.substring(0, 8) + "/" + dateString.substring(8, 10)
    System.out.println(result)
    result






  }

  override def getSerializer: SimpleVersionedSerializer[String] = new LiuLiangStringSerializer

  def main(args: Array[String]): Unit = {
    val dateString = "2018090707"
    val result = dateString.substring(0, 8) + File.separator + dateString.substring(8, 10)
    System.out.println(result)

  }
}      

3 LiuLiangStringSerializer

package com.atguigu

import org.apache.flink.core.io.SimpleVersionedSerializer

class LiuLiangStringSerializer extends SimpleVersionedSerializer[String]{
  override def getVersion: Int = 0

  override def serialize(e: String): Array[Byte] = e.getBytes()

  override def deserialize(i: Int, bytes: Array[Byte]): String = {
    if (i != 77){
      throw new Exception("version mismatch")
    }else{
      new String(bytes)
    }
  }

}      

TIP

1. 请关闭HDFS 权限,不关闭需要把认证copy到resources目录下

<property>
        <name>dfs.permissions</name>
        <value>false</value>
    </property>