Flink读取Kafka数据Sink到MySQL和HBase数据库

Flink将流数据Sink到数据库，一般需要自己自定义Sink的实现。下面示例，演示Sink到MySQL和HBase示例。

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.api.scala._
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer010

object KafkaToSinkStreaming {

 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))

 // 自定义MysqlSink类，将数据Sink到mysql
 val sink = new MysqlSink("jdbc:mysql://localhost:3306/test", "root", "root")
 input.addSink(sink)

 // 自定义HBaseSink类，将数据Sink到HBase
 val hBaseSink = new HBaseSink("student", "info")
 input.addSink(hBaseSink)

 env.execute("KafkaToSinkStreaming")
 }
}

自定义MysqlSink类

import java.sql.{Connection, DriverManager}

import com.google.gson.Gson
import org.apache.flink.configuration.Configuration
import org.apache.flink.streaming.api.functions.sink.{RichSinkFunction, SinkFunction}

class MysqlSink(url: String, user: String, pwd: String) extends RichSinkFunction[String] {

 var conn: Connection = _

 override def open(parameters: Configuration): Unit = {
 super.open(parameters)
 Class.forName("com.mysql.jdbc.Driver")
 conn = DriverManager.getConnection(url, user, pwd)
 conn.setAutoCommit(false)
 }

 override def invoke(value: String, context: SinkFunction.Context[_]): Unit = {
 val g = new Gson()
 val s = g.fromJson(value, classOf[Student])
 println(value)
 val p = conn.prepareStatement("replace into student(name,age,sex,sid) values(?,?,?,?)")
 p.setString(1, s.name)
 p.setString(2, s.age.toString)
 p.setString(3, s.sex)
 p.setString(4, s.sid)
 p.execute()
 conn.commit()
 }

 override def close(): Unit = {
 super.close()
 conn.close()
 }

}

自定义HBaseSink类

import com.google.gson.Gson
import org.apache.flink.configuration.Configuration
import org.apache.flink.streaming.api.functions.sink.{RichSinkFunction, SinkFunction}
import org.apache.hadoop.hbase.{HBaseConfiguration, HConstants, TableName}
import org.apache.hadoop.hbase.client._
import org.apache.hadoop.hbase.util.Bytes

class HBaseSink(tableName: String, family: String) extends RichSinkFunction[String] {


 var conn: Connection = _

 override def open(parameters: Configuration): Unit = {
 super.open(parameters)
 val conf = HBaseConfiguration.create()
 conf.set(HConstants.ZOOKEEPER_QUORUM, "localhost")
 conn = ConnectionFactory.createConnection(conf)
 }

 override def invoke(value: String, context: SinkFunction.Context[_]): Unit = {
 val g = new Gson()
 val student = g.fromJson(value, classOf[Student])
 println(value)
 println(student)

 val t: Table = conn.getTable(TableName.valueOf(tableName))

 val put: Put = new Put(Bytes.toBytes(student.sid))
 put.addColumn(Bytes.toBytes(family), Bytes.toBytes("name"), Bytes.toBytes(student.name))
 put.addColumn(Bytes.toBytes(family), Bytes.toBytes("age"), Bytes.toBytes(student.age))
 put.addColumn(Bytes.toBytes(family), Bytes.toBytes("sex"), Bytes.toBytes(student.sex))
 t.put(put)
 t.close()
 }

 override def close(): Unit = {
 super.close()
 conn.close()
 }
}

Student类

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

执行KafkaToSinkStreaming程序后，在kafka product端输入。

{"name":"zhangsan","age":"18","sex":"male","sid":"1001"}
{"name":"lisi","age":"20","sex":"male","sid":"1002"}
{"name":"laowang","age":"20","sex":"male","sid":"1003"}
{"name":"caocao","age":"28","sex":"male","sid":"1004"}

mysql的数据库结果：

HBase数据库结果：

项目源码：https://github.com/zhang3550545/flinkdemo

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