使用Flink实现索引数据到Elasticsearch7.17,实现设置分片和复制数 以及自定义schema
时间: 2023-06-24 11:03:42 浏览: 96
要使用Flink将数据索引到Elasticsearch7.17并设置分片和复制数,可以使用Flink的Elasticsearch Connector。下面是一些基本步骤:
1. 添加maven依赖
```xml
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-elasticsearch7_2.12</artifactId>
<version>${flink.version}</version>
</dependency>
```
2. 创建ElasticsearchSinkFunction
```java
public class MyElasticsearchSinkFunction implements ElasticsearchSinkFunction<MyData> {
@Override
public void process(MyData data, RuntimeContext runtimeContext, RequestIndexer requestIndexer) {
IndexRequest indexRequest = new IndexRequest("my_index");
indexRequest.id(data.getId());
indexRequest.source(data.toJSON(), XContentType.JSON);
requestIndexer.add(indexRequest);
}
@Override
public void open() {
// 可以在这里初始化一些连接等资源
}
@Override
public void close() {
// 可以在这里关闭连接等资源
}
}
```
这里的MyData是自定义的数据类型,`toJSON()`方法将数据转换成JSON格式。
3. 创建ElasticsearchSink
```java
public class MyElasticsearchSink {
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(1);
DataStream<MyData> stream = env.fromElements(
new MyData("1", "hello"),
new MyData("2", "world")
);
Map<String, String> config = new HashMap<>();
config.put("cluster.name", "my_cluster");
config.put("bulk.flush.max.actions", "1");
config.put("bulk.flush.interval.ms", "100");
List<HttpHost> httpHosts = new ArrayList<>();
httpHosts.add(new HttpHost("localhost", 9200));
ElasticsearchSink.Builder<MyData> esSinkBuilder = new ElasticsearchSink.Builder<>(httpHosts,
new MyElasticsearchSinkFunction());
esSinkBuilder.setBulkFlushMaxActions(1);
esSinkBuilder.setBulkFlushInterval(100);
esSinkBuilder.setRestClientFactory(restClientBuilder -> {
restClientBuilder.setDefaultHeaders(new BasicHeader[]{new BasicHeader("Content-Type", "application/json")});
return restClientBuilder;
});
esSinkBuilder.setConnectionConfig(ConnectionConfig.create(httpHosts));
esSinkBuilder.setFailureHandler(new RetryRejectedExecutionFailureHandler());
esSinkBuilder.setIndex("my_index");
esSinkBuilder.setDocumentType("_doc"); // 如果使用Elasticsearch 8.x及以上版本,则不需要设置此项
// 设置分片和复制数
esSinkBuilder.setBulkFlushMaxSizeMb(2);
esSinkBuilder.setBulkFlushBackoff(true);
esSinkBuilder.setBulkFlushBackoffType(BackoffType.EXPONENTIAL);
esSinkBuilder.setBulkFlushBackoffRetries(3);
esSinkBuilder.setBulkFlushBackoffDelay(3000);
stream.addSink(esSinkBuilder.build());
env.execute("MyElasticsearchSink");
}
}
```
这里的`config`是Elasticsearch的配置信息,`httpHosts`是Elasticsearch的连接信息。`setIndex()`方法设置索引名称,`setDocumentType()`方法设置文档类型(如果使用Elasticsearch 8.x及以上版本,则不需要设置此项)。
`setBulkFlushMaxSizeMb()`方法设置每个批次的最大大小,`setBulkFlushBackoff()`方法设置是否启用重试机制。`setBulkFlushBackoffType()`方法设置重试类型,`setBulkFlushBackoffRetries()`方法设置重试次数,`setBulkFlushBackoffDelay()`方法设置重试延迟时间。
4. 自定义schema
如果想要自定义Elasticsearch的schema,可以在MyData类中添加注解:
```java
import org.apache.flink.streaming.connectors.elasticsearch7.ElasticsearchSink;
import org.apache.flink.streaming.connectors.elasticsearch7.ElasticsearchSinkFieldAnnotation;
public class MyData {
@ElasticsearchSinkFieldAnnotation(name = "id", type = "keyword")
private String id;
@ElasticsearchSinkFieldAnnotation(name = "message", type = "text")
private String message;
// getter和setter省略
}
```
这里的`@ElasticsearchSinkFieldAnnotation`注解指定了字段名和类型。然后在创建ElasticsearchSink时,可以使用`withTypeInformation()`方法指定数据类型:
```java
DataStream<MyData> stream = ...;
ElasticsearchSink.Builder<MyData> esSinkBuilder = new ElasticsearchSink.Builder<>(httpHosts,
new MyElasticsearchSinkFunction());
TypeInformation<MyData> typeInformation = TypeInformation.of(MyData.class);
esSinkBuilder.withTypeInformation(typeInformation);
```
这样就可以将MyData类中的注解应用到Elasticsearch的schema中了。
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