(4)FlinkSQL将socket数据写入到mysql方式一
本章节主要演示从socket接收数据,通过滚动窗口每30秒运算一次窗口数据,然后将结果写入Mysql数据库
(1)准备一个实体对象,消息对象
package com.pojo; import java.io.Serializable; /** * Created by lj on 2022-07-05. */ public class WaterSensor implements Serializable { private String id; private long ts; private int vc; public WaterSensor(){ } public WaterSensor(String id,long ts,int vc){ this.id = id; this.ts = ts; this.vc = vc; } public int getVc() { return vc; } public void setVc(int vc) { this.vc = vc; } public String getId() { return id; } public void setId(String id) { this.id = id; } public long getTs() { return ts; } public void setTs(long ts) { this.ts = ts; } }
(2)编写socket代码,模拟数据发送
package com.producers; import java.io.BufferedWriter; import java.io.IOException; import java.io.OutputStreamWriter; import java.net.ServerSocket; import java.net.Socket; import java.util.Random; /** * Created by lj on 2022-07-05. */ public class Socket_Producer { public static void main(String[] args) throws IOException { try { ServerSocket ss = new ServerSocket(9999); System.out.println("启动 server ...."); Socket s = ss.accept(); BufferedWriter bw = new BufferedWriter(new OutputStreamWriter(s.getOutputStream())); String response = "java,1,2"; //每 2s 发送一次消息 int i = 0; Random r=new Random(); String[] lang = {"flink","spark","hadoop","hive","hbase","impala","presto","superset","nbi"}; while(true){ Thread.sleep(2000); response= lang[r.nextInt(lang.length)] + "," + i + "," + i+"\n"; System.out.println(response); try{ bw.write(response); bw.flush(); i++; }catch (Exception ex){ System.out.println(ex.getMessage()); } } } catch (IOException | InterruptedException e) { e.printStackTrace(); } } }
(3)从socket端接收数据,并设置30秒触发执行一次窗口运算
package com.examples; import com.pojo.WaterSensor; import com.sinks.RetractStream_Mysql; import org.apache.flink.api.common.functions.MapFunction; import org.apache.flink.streaming.api.datastream.DataStreamSource; import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator; import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; import org.apache.flink.table.api.Table; import org.apache.flink.table.api.bridge.java.StreamTableEnvironment; import org.apache.flink.types.Row; import static org.apache.flink.table.api.Expressions.$; /** * Created by lj on 2022-07-06. */ public class Flink_Group_Window_Tumble_Sink_Mysql { public static void main(String[] args) throws Exception { StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); env.setParallelism(1); StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env); DataStreamSource<String> streamSource = env.socketTextStream("127.0.0.1", 9999,"\n"); SingleOutputStreamOperator<WaterSensor> waterDS = streamSource.map(new MapFunction<String, WaterSensor>() { @Override public WaterSensor map(String s) throws Exception { String[] split = s.split(","); return new WaterSensor(split[0], Long.parseLong(split[1]), Integer.parseInt(split[2])); } }); // 将流转化为表 Table table = tableEnv.fromDataStream(waterDS, $("id"), $("ts"), $("vc"), $("pt").proctime()); tableEnv.createTemporaryView("EventTable", table); Table result = tableEnv.sqlQuery( "SELECT " + "id, " + //window_start, window_end, "COUNT(ts) ,SUM(ts)" + "FROM TABLE( " + "TUMBLE( TABLE EventTable , " + "DESCRIPTOR(pt), " + "INTERVAL '30' SECOND)) " + "GROUP BY id , window_start, window_end" ); tableEnv.toRetractStream(result, Row.class).addSink(new RetractStream_Mysql()); env.execute(); } }
(4)定义一个写入到mysql的sink
package com.sinks; import java.sql.Connection; import java.sql.DriverManager; import java.sql.PreparedStatement; import org.apache.flink.api.java.tuple.Tuple2; import org.apache.flink.configuration.Configuration; import org.apache.flink.streaming.api.functions.sink.RichSinkFunction; import org.apache.flink.types.Row; /** * Created by lj on 2022-07-06. */ public class RetractStream_Mysql extends RichSinkFunction<Tuple2<Boolean, Row>> { private static final long serialVersionUID = -4443175430371919407L; PreparedStatement ps; private Connection connection; /** * open() 方法中建立连接,这样不用每次 invoke 的时候都要建立连接和释放连接 * * @param parameters * @throws Exception */ @Override public void open(Configuration parameters) throws Exception { super.open(parameters); connection = getConnection(); } @Override public void close() throws Exception { super.close(); //关闭连接和释放资源 if (connection != null) { connection.close(); } if (ps != null) { ps.close(); } } /** * 每条数据的插入都要调用一次 invoke() 方法 * * @param context * @throws Exception */ @Override public void invoke(Tuple2<Boolean, Row> userPvEntity, Context context) throws Exception { String sql = "INSERT INTO flinkcomponent(componentname,componentcount,componentsum) VALUES(?,?,?);"; ps = this.connection.prepareStatement(sql); ps.setString(1,userPvEntity.f1.getField(0).toString()); ps.setInt(2, Integer.parseInt(userPvEntity.f1.getField(1).toString())); ps.setInt(3, Integer.parseInt(userPvEntity.f1.getField(2).toString())); ps.executeUpdate(); } private static Connection getConnection() { Connection con = null; try { Class.forName("com.mysql.jdbc.Driver"); con = DriverManager.getConnection("jdbc:mysql://localhost:3306/testdb?useUnicode=true&characterEncoding=UTF-8&useSSL=false","root","root"); } catch (Exception e) { System.out.println("-----------mysql get connection has exception , msg = "+ e.getMessage()); } return con; } }
(5)效果演示,每30秒往数据库写一次数据
package com.sinks;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.functions.sink.RichSinkFunction;
import org.apache.flink.types.Row;
/**
* Created by lj on 2022-07-06.
*/
public class RetractStream_Mysql extends RichSinkFunction<Tuple2<Boolean, Row>> {
private static final long serialVersionUID = -4443175430371919407L;
PreparedStatement ps;
private Connection connection;
/**
* open() 方法中建立连接,这样不用每次 invoke 的时候都要建立连接和释放连接
*
* @param parameters
* @throws Exception
*/
@Override
public void open(Configuration parameters) throws Exception {
super.open(parameters);
connection = getConnection();
}
@Override
public void close() throws Exception {
super.close();
//关闭连接和释放资源
if (connection != null) {
connection.close();
}
if (ps != null) {
ps.close();
}
}
/**
* 每条数据的插入都要调用一次 invoke() 方法
*
* @param context
* @throws Exception
*/
@Override
public void invoke(Tuple2<Boolean, Row> userPvEntity, Context context) throws Exception {
String sql = "INSERT INTO flinkcomponent(componentname,componentcount,componentsum) VALUES(?,?,?);";
ps = this.connection.prepareStatement(sql);
ps.setString(1,userPvEntity.f1.getField(0).toString());
ps.setInt(2, Integer.parseInt(userPvEntity.f1.getField(1).toString()));
ps.setInt(3, Integer.parseInt(userPvEntity.f1.getField(2).toString()));
ps.executeUpdate();
}
private static Connection getConnection() {
Connection con = null;
try {
Class.forName("com.mysql.jdbc.Driver");
con = DriverManager.getConnection("jdbc:mysql://localhost:3306/testdb?useUnicode=true&characterEncoding=UTF-8&useSSL=false","root","root");
} catch (Exception e) {
System.out.println("-----------mysql get connection has exception , msg = "+ e.getMessage());
}
return con;
}
}