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前言

Flink sink 流数据写入到es5和es7的简单示例。

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一、写入到Elasticsearch5

• pom maven依赖

        <dependency><groupId>org.apache.flink</groupId><artifactId>flink-connector-elasticsearch5_2.11</artifactId><version>${flink.version}</version></dependency>

• 代码如下（示例）：

public class Es5SinkDemo {public static void main(String[] args) throws Exception {StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();Row row=Row.of("张三","001",getTimestamp("2016-10-24 21:59:06"));Row row2=Row.of("张三","002",getTimestamp("2016-10-24 21:50:06"));Row row3=Row.of("张三","002",getTimestamp("2016-10-24 21:51:06"));Row row4=Row.of("李四","003",getTimestamp("2016-10-24 21:50:56"));Row row5=Row.of("李四","004",getTimestamp("2016-10-24 00:48:36"));Row row6=Row.of("王五","005",getTimestamp("2016-10-24 00:48:36"));DataStreamSource<Row> source =env.fromElements(row,row2,row3,row4,row5,row6);Map<String, String> config = new HashMap<>();
//        config.put("cluster.name", "my-cluster-name");
//        config.put("bulk.flush.max.actions", "1");List<InetSocketAddress> transportAddresses = new ArrayList<>();transportAddresses.add(new InetSocketAddress(InetAddress.getByName("10.68.8.60"), 9300));//Sink操作DataStreamSink<Row> rowDataStreamSink = source.addSink(new ElasticsearchSink<>(config, transportAddresses, new ElasticsearchSinkFunction<Row>() {public IndexRequest createIndexRequest(Row element) {Map<String, Object> json = new HashMap<>();json.put("name22", element.getField(0).toString());json.put("no22", element.getField(1));json.put("age", 34);json.put("create_time", element.getField(2));return Requests.indexRequest().index("cc").type("mtype").id(element.getField(1).toString()).source(json);}@Overridepublic void process(Row element, RuntimeContext ctx, RequestIndexer indexer) {//利用requestIndexer进行发送请求，写入数据indexer.add(createIndexRequest(element));}}));env.execute("es demo");}private static java.sql.Timestamp getTimestamp(String str) throws Exception {
//		String string = "2016-10-24 21:59:06";SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");java.util.Date date=sdf.parse(str);java.sql.Timestamp s = new java.sql.Timestamp(date.getTime());return s;}

二、写入到Elasticsearch7

• pom maven依赖

        <dependency><groupId>org.apache.flink</groupId><artifactId>flink-connector-elasticsearch7_2.11</artifactId><version>${flink.version}</version><scope>provided</scope></dependency>

• 代码如下（示例）：

import org.apache.flink.api.common.functions.RuntimeContext;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.elasticsearch.ElasticsearchSinkFunction;
import org.apache.flink.streaming.connectors.elasticsearch.RequestIndexer;
import org.apache.flink.streaming.connectors.elasticsearch7.ElasticsearchSink;
import org.apache.flink.types.Row;
import org.apache.http.HttpHost;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.client.Requests;import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
public class EsSinkDemo {public static void main(String[] args) throws Exception {StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();Row row=Row.of("张三","001",getTimestamp("2016-10-24 21:59:06"));Row row2=Row.of("张三","002",getTimestamp("2016-10-24 21:50:06"));Row row3=Row.of("张三","002",getTimestamp("2016-10-24 21:51:06"));Row row4=Row.of("李四","003",getTimestamp("2016-10-24 21:50:56"));Row row5=Row.of("李四","004",getTimestamp("2016-10-24 00:48:36"));Row row6=Row.of("王五","005",getTimestamp("2016-10-24 00:48:36"));DataStreamSource<Row> source =env.fromElements(row,row2,row3,row4,row5,row6);Map<String, String> config = new HashMap<>();
//        config.put("cluster.name", "my-cluster-name");
// This instructs the sink to emit after every element, otherwise they would be buffered
//        config.put("bulk.flush.max.actions", "1");List<HttpHost> hosts = new ArrayList<>();hosts.add(new HttpHost("10.68.8.69",9200,"http"));ElasticsearchSink.Builder<Row> esSinkBuilder = new ElasticsearchSink.Builder<Row>(hosts,new ElasticsearchSinkFunction<Row>() {public IndexRequest createIndexRequest(Row element) {Map<String, Object> json = new HashMap<>();json.put("name22", element.getField(0).toString());json.put("no22", element.getField(1));json.put("age", 34);
//                json.put("create_time", element.getField(2));return Requests.indexRequest().index("cc").id(element.getField(1).toString()).source(json);}@Overridepublic void process(Row element, RuntimeContext ctx, RequestIndexer indexer) {//利用requestIndexer进行发送请求，写入数据indexer.add(createIndexRequest(element));}});esSinkBuilder.setBulkFlushMaxActions(100);//Sink操作source.addSink(esSinkBuilder.build());env.execute("es demo");}private static java.sql.Timestamp getTimestamp(String str) throws Exception {
//		String string = "2016-10-24 21:59:06";SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");java.util.Date date=sdf.parse(str);java.sql.Timestamp s = new java.sql.Timestamp(date.getTime());return s;}
}

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总结

flink写入es5和es7 的区别是引入不同的flink-connector-elasticsearch,es7已没有type的概念故无需再设置type。