# 情景介绍
目前要对flink进行多数据源适配工作，需要支持的有pclickhouse,elasticsearch
# 版本介绍
flink：1.13.1
elasticsearch:7.6.2
clickhouse:21.9.3.30
# 参考文献
# github
flink全量案例demo：https://github.com/zhisheng17/flink-learning
flink-connector连接器：https://github.com/DTStack/flinkx
flink-sink-clickhouse：https://github.com/ivi-ru/flink-clickhouse-sink
# csdn
注：以防原文连接丢失，此处综合两种方式的内容如下所示
flink-sink-clickhouse/elasticsearch
我亲测的github项目地址：https://github.com/ainusers/flink-adapter-datasource# jdbc模式 - flink写入clickhouse
1. clickhouse jdbc 依赖
<!-- 写入数据到clickhouse -->
<dependency>
<groupId>ru.yandex.clickhouse</groupId>
<artifactId>clickhouse-jdbc</artifactId>
<version>0.1.54</version>
</dependency>
2. User实体类
package com.lei.domain;
public class J_User {
public int id;
public String name;
public int age;
public J_User(int id, String name, int age) {
this.id = id;
this.name = name;
this.age = age;
}
public static J_User of(int id, String name, int age) {
return new J_User(id, name, age);
}
}
3. 工具类
package com.lei.util;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.SQLException;
public class ClickHouseUtil {
private static Connection connection;
public static Connection getConn(String host, int port, String database) throws SQLException, ClassNotFoundException {
Class.forName("ru.yandex.clickhouse.ClickHouseDriver");
String address = "jdbc:clickhouse://" + host + ":" + port + "/" + database;
connection = DriverManager.getConnection(address);
return connection;
}
public static Connection getConn(String host, int port) throws SQLException, ClassNotFoundException {
return getConn(host,port,"default");
}
public static Connection getConn() throws SQLException, ClassNotFoundException {
return getConn("node-01",8123);
}
public void close() throws SQLException {
connection.close();
}
}
4. 自定义clickhouse-connector
package com.lei.util;
import com.lei.domain.J_User;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.functions.sink.RichSinkFunction;
import java.sql.Connection;
import java.sql.PreparedStatement;
public class J_MyClickHouseUtil extends RichSinkFunction<J_User> {
Connection connection = null;
String sql;
public J_MyClickHouseUtil(String sql) {
this.sql = sql;
}
@Override
public void open(Configuration parameters) throws Exception {
super.open(parameters);
connection = ClickHouseUtil.getConn("node-01", 8123, "default");
}
@Override
public void close() throws Exception {
super.close();
if (connection != null) {
connection.close();
}
}
@Override
public void invoke(J_User user, Context context) throws Exception {
PreparedStatement preparedStatement = connection.prepareStatement(sql);
preparedStatement.setLong(1, user.id);
preparedStatement.setString(2, user.name);
preparedStatement.setLong(3, user.age);
preparedStatement.addBatch();
long startTime = System.currentTimeMillis();
int[] ints = preparedStatement.executeBatch();
connection.commit();
long endTime = System.currentTimeMillis();
System.out.println("批量插入完毕用时：" + (endTime - startTime) + " -- 插入数据 = " + ints.length);
}
}
5. 主程序测试类
package com.lei.sinktest;
import com.lei.domain.J_User;
import com.lei.util.J_MyClickHouseUtil;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
/*
进入clickhouse-client
use default;
drop table if exists user_table;
CREATE TABLE default.user_table(id UInt16, name String, age UInt16 ) ENGINE = TinyLog();
*/
public class J05_ClickHouseSinkTest {
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironment();
env.setParallelism(1);
// source
DataStream<String> inputStream = env.socketTextStream("localhost", 7777);
// Transform 操作
SingleOutputStreamOperator<J_User> dataStream = inputStream.map(new MapFunction<String, J_User>() {
@Override
public J_User map(String data) throws Exception {
String[] split = data.split(",");
return J_User.of(Integer.parseInt(split[0]),
split[1],
Integer.parseInt(split[2]));
}
});
// sink
String sql = "INSERT INTO default.user_table (id, name, age) VALUES (?,?,?)";
J_MyClickHouseUtil jdbcSink = new J_MyClickHouseUtil(sql);
dataStream.addSink(jdbcSink);
dataStream.print();
env.execute("clickhouse sink test");
}
}
6. 创建clickhouse表
-- 进入clickhouse-client
use default;
drop table if exists user_table;
CREATE TABLE default.user_table(id UInt16, name String, age UInt16 ) ENGINE = TinyLog();
# 中间件模式 - flink写入clickhouse
1. 添加clickhouse-maven依赖
<dependency>
<groupId>ru.ivi.opensource</groupId>
<artifactId>flink-clickhouse-sink</artifactId>
<version>1.2.0</version>
</dependency>
2. User实体类
package com.lei.domain;
public class J_User {
public int id;
public String name;
public int age;
public J_User(int id, String name, int age) {
this.id = id;
this.name = name;
this.age = age;
}
public static J_User of(int id, String name, int age) {
return new J_User(id, name, age);
}
// Java Bean 必须实现的方法，信息通过字符串进行拼接
public static String convertToCsv(J_User user) {
StringBuilder builder = new StringBuilder();
builder.append("(");
// add user.id
builder.append(user.id);
builder.append(", ");
// add user.name
builder.append("'");
builder.append(String.valueOf(user.name));
builder.append("', ");
// add user.age
builder.append(user.age);
builder.append(" )");
return builder.toString();
}
}
3. flink测试方法
package com.lei.sinktest;
import com.lei.domain.J_User;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import ru.ivi.opensource.flinkclickhousesink.ClickHouseSink;
import ru.ivi.opensource.flinkclickhousesink.model.ClickHouseClusterSettings;
import ru.ivi.opensource.flinkclickhousesink.model.ClickHouseSinkConst;
import java.util.HashMap;
import java.util.Map;
import java.util.Properties;
/*
进入clickhouse-client
use default;
drop table if exists user_table;
CREATE TABLE default.user_table(id UInt16, name String, age UInt16 ) ENGINE = TinyLog();
*/
public class J05_ClickHouseSinkTestByLib {
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironment();
Map<String, String> globalParameters = new HashMap<>();
// ClickHouse cluster properties
globalParameters.put(ClickHouseClusterSettings.CLICKHOUSE_HOSTS, "http://node-01:8123/");
//globalParameters.put(ClickHouseClusterSettings.CLICKHOUSE_USER, ...);
//globalParameters.put(ClickHouseClusterSettings.CLICKHOUSE_PASSWORD, ...);
// sink common
globalParameters.put(ClickHouseSinkConst.TIMEOUT_SEC, "1");
globalParameters.put(ClickHouseSinkConst.FAILED_RECORDS_PATH, "d:/");
globalParameters.put(ClickHouseSinkConst.NUM_WRITERS, "2");
globalParameters.put(ClickHouseSinkConst.NUM_RETRIES, "2");
globalParameters.put(ClickHouseSinkConst.QUEUE_MAX_CAPACITY, "2");
globalParameters.put(ClickHouseSinkConst.IGNORING_CLICKHOUSE_SENDING_EXCEPTION_ENABLED, "false");
// set global paramaters
ParameterTool parameters = ParameterTool.fromMap(globalParameters);
env.getConfig().setGlobalJobParameters(parameters);
env.setParallelism(1);
// source
DataStream<String> inputStream = env.socketTextStream("localhost", 7777);
// Transform 操作
SingleOutputStreamOperator<String> dataStream = inputStream.map(new MapFunction<String, String>() {
@Override
public String map(String data) throws Exception {
String[] split = data.split(",");
J_User user = J_User.of(Integer.parseInt(split[0]),
split[1],
Integer.parseInt(split[2]));
return J_User.convertToCsv(user);
}
});
// create props for sink
Properties props = new Properties();
props.put(ClickHouseSinkConst.TARGET_TABLE_NAME, "default.user_table");
props.put(ClickHouseSinkConst.MAX_BUFFER_SIZE, "10000");
ClickHouseSink sink = new ClickHouseSink(props);
dataStream.addSink(sink);
dataStream.print();
env.execute("clickhouse sink test");
}
}
4. 结果验证
