Apache Kafka（七）- Kafka ElasticSearch Comsumer

Kafka ElasticSearch Consumer

对于Kafka Consumer，我们会写一个例子用于消费Kafka 数据传输到ElasticSearch。

1. 构造ElasticSearch 基本代码

我们使用如下代码构造一个 Elastic Search Client，并向 ES写入一个index：

import org.apache.http.HttpHost;
import org.apache.http.impl.nio.client.HttpAsyncClientBuilder;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.common.xcontent.XContentType;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.io.IOException;

public class ElasticSearchConsumer {


    public static void main(String[] args) throws IOException {
        Logger logger = LoggerFactory.getLogger(ElasticSearchConsumer.class.getName());
        RestHighLevelClient client = createClient();


        String jsonString = "{"foo": "bar"}";

        // create an index

        IndexRequest indexRequest = new IndexRequest (
                "kafkademo"
        ).source(jsonString, XContentType.JSON);

        IndexResponse indexResponse = client.index(indexRequest, RequestOptions.DEFAULT);
        String id = indexResponse.getId();

        logger.info(id);

        // close the client
        client.close();
    }

    public static RestHighLevelClient createClient(){
        String hostname = "xxxxx";

        RestClientBuilder builder = RestClient.builder(
                new HttpHost(hostname, 443, "https"))
                .setHttpClientConfigCallback(new RestClientBuilder.HttpClientConfigCallback() {
                    @Override
                    public HttpAsyncClientBuilder customizeHttpClient(HttpAsyncClientBuilder httpAsyncClientBuilder) {
                        return httpAsyncClientBuilder;
                    }
                });

        RestHighLevelClient client = new RestHighLevelClient(builder);

        return client;
    }
}

在 ES 端查看index 以及条目信息：

> curl https://xxx/_cat/indices?v

health status index uuid pri rep docs.count docs.deleted store.size pri.store.size

green open .kibana_1 tQuukokDTbWg9OyQI8Bh4A 1 1 0 0 566b 283b

green open .kibana_2 025DtfBLR3CUexrUkX9x9Q 1 1 0 0 566b 283b

green open kafkademo elXjncvwQPam7dqMd5gedg 5 1 1 0 9.3kb 4.6kb

green open .kibana ZvzR21YqSOi-8nbjffSuTA 5 1 1 0 10.4kb 5.2kb

> curl https://xxx/kafkademo/

{"kafkademo":{"aliases":{},"mappings":{"properties":{"foo":{"type":"text","fields":{"keyword":{"type":"keyword","ignore_above":256}}}}},"settings":{"index":{"creation_date":"1566985949656","number_of_shards":"5","number_of_replicas":"1","uuid":"elXjncvwQPam7dqMd5gedg","version":{"created":"7010199"},"provided_name":"kafkademo"}}}}

2. 向Kafka 生产消息

为了模拟输入到 Kafka 的消息，我们使用一个开源的json-data-generator，github地址如下：

https://github.com/everwatchsolutions/json-data-generator

使用此工具可以很方便地向 Kafka 生产随机的 json数据。

下载此工具后，配置好Kafka broker list地址，启动向Kafka 生产消息：

> java -jar json-data-generator-1.4.0.jar jackieChanSimConfig.json

3. 将消息发往ElasticSearch

在原有Kafka Consumer 的基础上，我们增加以下代码：

// poll for new data
while(true){
    ConsumerRecords<String, String> records =
            consumer.poll(Duration.ofMinutes(100));

    for(ConsumerRecord record : records) {
        // where we insert data into ElasticSearch
        IndexRequest indexRequest = new IndexRequest(
                "kafkademo"
        ).source(record.value(), XContentType.JSON);

        IndexResponse indexResponse = client.index(indexRequest, RequestOptions.DEFAULT);
        String id = indexResponse.getId();

        logger.info(id);

        try {
            Thread.sleep(1000); // introduce a small delay
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
    }
    }

可以看到消息被正常发往ElasticSearch，其中随机字符串为插入ES后的 _id：