要连接Flink Elasticsearch版本6.2.2到Flink 1.4.1,您可以按照以下步骤进行操作:
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-elasticsearch6_2.11</artifactId>
<version>${flink.version}</version>
</dependency>
请注意,${flink.version}
应该替换为您正在使用的Flink版本。
import org.apache.flink.api.common.functions.RuntimeContext;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.elasticsearch.ElasticsearchSink;
import org.apache.flink.streaming.connectors.elasticsearch6.ElasticsearchSink.Builder;
import org.apache.flink.streaming.connectors.elasticsearch6.ElasticsearchSinkFunction;
import org.apache.flink.streaming.connectors.elasticsearch6.RequestIndexer;
import org.apache.http.HttpHost;
import org.elasticsearch.client.Requests;
import org.elasticsearch.common.xcontent.XContentType;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
public class FlinkElasticsearchExample {
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// 设置Flink的并行度
env.setParallelism(1);
// 创建一个DataStream,假设数据源为Kafka
DataStream<String> dataStream = env.addSource(/* Kafka source */);
// 创建Elasticsearch连接配置
List<HttpHost> httpHosts = new ArrayList<>();
httpHosts.add(new HttpHost("localhost", 9200, "http"));
// 创建ElasticsearchSinkFunction,用于将数据写入Elasticsearch
ElasticsearchSinkFunction<String> elasticsearchSinkFunction = new ElasticsearchSinkFunction<String>() {
public void process(String element, RuntimeContext ctx, RequestIndexer indexer) {
Map<String, String> json = new HashMap<>();
json.put("data", element);
indexer.add(Requests.indexRequest()
.index("your-index")
.type("your-type")
.source(json, XContentType.JSON));
}
};
// 创建ElasticsearchSink
ElasticsearchSink.Builder<String> esSinkBuilder = new ElasticsearchSink.Builder<>(httpHosts, elasticsearchSinkFunction);
// 设置刷新前缓冲的最大记录数
esSinkBuilder.setBulkFlushMaxActions(1);
// 将ElasticsearchSink添加到DataStream
dataStream.addSink(esSinkBuilder.build());
// 执行Flink任务
env.execute("Flink Elasticsearch Example");
}
}
请注意,上述示例代码中的localhost
、9200
、your-index
和your-type
应根据您的Elasticsearch配置进行相应更改。
这样,您就成功地将Flink版本6.2.2连接到Flink 1.4.1,并将数据写入Elasticsearch中了。