Flink 简单入门示例

￡神魔★判官ぃ 2022-04-23 06:08 570阅读 0赞

## Flink 简单入门示例 ##

#### 1.Flink读取Socket流，实现Word Count示例 ####

import org.apache.flink.streaming.api.scala.{StreamExecutionEnvironment, _}
    import org.apache.flink.streaming.api.windowing.time.Time
    
    object SocketWindowWordCount {
    
      def main(args: Array[String]): Unit = {
    
        val env: StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment
    
        val res: DataStream[String] = env.socketTextStream("localhost", 9998, '\n')
    
        val wordCounts = res
          .flatMap { w => w.split(",") }
          .map(w => WordWithCount(w, 1))
          .keyBy("word")
          .timeWindow(Time.seconds(5), Time.seconds(1))
          .sum("count")
    
        wordCounts.print()
    
        env.execute("SocketWindowWordCount")
      }
    }

#### 2.Flink读取Text文件,实现Word Count示例 ####

import org.apache.flink.core.fs.FileSystem
    import org.apache.flink.streaming.api.scala.{StreamExecutionEnvironment, _}
    
    object TextWindowWordCount {
      def main(args: Array[String]): Unit = {
    
        val env = StreamExecutionEnvironment.getExecutionEnvironment
    
        // 设置并行度
        env.setParallelism(2)
    
        val values = env.readTextFile("/Users/zhangzhiqiang/Documents/test_project/flinkdemo/data")
    
        values.print()
    
        val res = values.flatMap(_.split(","))
          .filter(_.nonEmpty)
          .map((_, 1))
          .keyBy(0)
          .sum(1)
    
        res.writeAsCsv("/Users/zhangzhiqiang/Documents/test_project/flinkdemo/data2", FileSystem.WriteMode.NO_OVERWRITE)
    
        env.execute()
      }
    }

#### 3.Flink读取csv文件 ####

import org.apache.flink.api.scala.ExecutionEnvironment
    import org.apache.flink.streaming.api.scala._
    
    
    object ReadCsvFile {
    
      def main(args: Array[String]): Unit = {
        val env = ExecutionEnvironment.getExecutionEnvironment
        env.setParallelism(1)
        // 直接将数据，转成Student（相当于Schema）
        val values = env.readCsvFile[Student]("/Users/zhangzhiqiang/Documents/test_project/flinkdemo/data/1.csv")
        values.print()
      }
    }

Student类

case class Student(name: String, age: Int, sex: String, id: String)

#### 4.Flink读取csv文件，并使用Table sql转换 ####

import org.apache.flink.api.scala.ExecutionEnvironment
    import org.apache.flink.table.api.TableEnvironment
    import org.apache.flink.table.api.scala._
    import org.apache.flink.api.scala._
    
    object ReadTableCsvFile {
    
      def main(args: Array[String]): Unit = {
        val env = ExecutionEnvironment.getExecutionEnvironment
    
        val tableEnv = TableEnvironment.getTableEnvironment(env)
    
        val input = env.readCsvFile[Student]("/Users/zhangzhiqiang/Documents/test_project/flinkdemo/data/1.csv")
    
        input.print()
    
        tableEnv.registerDataSet("student", input)
    
        val result = tableEnv.sqlQuery("select * from student")
    
        result.printSchema()
    
        result.toDataSet[Student].print()
      }
    }

或者做些转换，如：

import org.apache.flink.api.scala.{ExecutionEnvironment, _}
    import org.apache.flink.table.api.TableEnvironment
    import org.apache.flink.table.api.scala._
    
    object ReadTableCsvFile2 {
    
      def main(args: Array[String]): Unit = {
        val env = ExecutionEnvironment.getExecutionEnvironment
    
        // 获取table env对象
        val tableEnv = TableEnvironment.getTableEnvironment(env)
    
        // 读取数据
        val input = env.readCsvFile[Student]("/Users/zhangzhiqiang/Documents/test_project/flinkdemo/data/1.csv")
    
        input.print()
    
        // 将DataSet转成Table对象
        val table = tableEnv.fromDataSet(input)
    
        // 注册 Table
        tableEnv.registerTable("student", table)
    
        // sql 查询语句
        val result = tableEnv.sqlQuery("select name,age,sex from student")
    
        result.printSchema()
    
        // 将数据转化输出
        result.toDataSet[People].print()
      }
    }

People类

case class People(name: String, age: Int, sex: String)

#### 5.Flink读取Kafka流，实现Word Count ####

import org.apache.flink.api.common.serialization.SimpleStringSchema
    import org.apache.flink.streaming.api.scala.{StreamExecutionEnvironment, _}
    import org.apache.flink.streaming.api.windowing.time.Time
    import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer010
    
    object KafkaWordCountStreaming {
    
      def main(args: Array[String]): Unit = {
    
        val env = StreamExecutionEnvironment.getExecutionEnvironment
    
        val properties = new Properties()
        properties.setProperty("bootstrap.servers", "localhost:9092")
        properties.setProperty("group.id", "test")
        val stream = env.addSource(new FlinkKafkaConsumer010[String]("test", new SimpleStringSchema(), properties))
    
        stream.print()
    
        val result = stream.flatMap(x => x.split(","))
          .map(x => (x, 1)).keyBy(0)
          .timeWindow(Time.seconds(10))
          .sum(1)
    
        result.print()
    
        env.execute("KafkaWordCountStreaming")
      }
    }

#### 6.Flink读取Kafka流，转换后输出 ####

import java.util.Properties
    
    import com.google.gson.Gson
    import org.apache.flink.api.common.serialization.SimpleStringSchema
    import org.apache.flink.streaming.api.scala.{StreamExecutionEnvironment, _}
    import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer010
    
    object KafkaJsonStreaming {
    
      def main(args: Array[String]): Unit = {
    
        val env = StreamExecutionEnvironment.getExecutionEnvironment
    
        val p = new Properties()
        p.setProperty("bootstrap.servers", "localhost:9092")
        p.setProperty("group.id", "test")
    
        val stream = env.addSource(new FlinkKafkaConsumer010[String]("test", new SimpleStringSchema(), p))
    
        stream.print()
    
        val result = stream.map { x =>
          val g = new Gson()
          val people = g.fromJson(x, classOf[People])
          people
        }
    
        result.print()
    
        env.execute("KafkaJsonStreaming")
      }
    }

#### 7.Flink读取Kafka流，并写入Kafka ####

import java.util.Properties
    
    import org.apache.flink.api.common.serialization.SimpleStringSchema
    import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
    import org.apache.flink.streaming.connectors.kafka.{FlinkKafkaConsumer010, FlinkKafkaProducer010}
    import org.apache.flink.streaming.api.scala._
    
    object KafkaToKafkaStreaming {
    
      def main(args: Array[String]): Unit = {
    
        val env = StreamExecutionEnvironment.getExecutionEnvironment
    
        val p = new Properties()
        p.setProperty("bootstrap.servers", "localhost:9092")
        p.setProperty("group.id", "test")
    
        val input = env.addSource(new FlinkKafkaConsumer010[String]("test", new SimpleStringSchema(), p))
    
        input.print()
    
        val p2 = new Properties()
        p2.setProperty("bootstrap.servers", "localhost:9092")
        p2.setProperty("zookeeper.connect", "localhost:2181")
        p2.setProperty("group.id", "test")
        input.addSink(new FlinkKafkaProducer010[String]("test", new SimpleStringSchema(), p2))
    
        env.execute("KafkaToKafkaStreaming")
      }
    }

[具体项目参见github][github]

[github]: https://github.com/zhang3550545/flinkdemo