如何连接到flink elasticsearch版本6.2.2到flink 1.4.1

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：

首先，确保您已经安装了Flink和Elasticsearch，并且两者都已经正确配置和运行。
在Flink的项目中，您需要添加Elasticsearch的依赖项。可以在pom.xml文件中添加以下依赖项：

<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。

在Flink的代码中，您可以使用以下示例代码来连接到Elasticsearch：

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。