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[FLINK-36559][docs][elasticsearch] Add flink cdc elasticsearch pipeli…
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wangjunbo committed Oct 17, 2024
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---
title: "Elasticsearch"
weight: 4
type: docs
aliases:
- /connectors/pipeline-connectors/elasticsearch
---
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# Elasticsearch Pipeline Connector

Elasticsearch Pipeline 连接器可以用作 Pipeline 的 Data Sink, 将数据写入 Elasticsearch。 本文档介绍如何设置 Elasticsearch Pipeline 连接器。


How to create Pipeline
----------------

从 MySQL 读取数据同步到 Elasticsearch 的 Pipeline 可以定义如下：

```yaml
source:
type: mysql
name: MySQL Source
hostname: 127.0.0.1
port: 3306
username: admin
password: pass
tables: adb.\.*, bdb.user_table_[0-9]+, [app|web].order_\.*
server-id: 5401-5404

sink:
type: elasticsearch
name: Elasticsearch Sink
hosts: http://127.0.0.1:9092;http://127.0.0.1:9093

route:
- source-table: adb.\.*
sink-table: default_index
description: sync adb.\.* table to default_index

pipeline:
name: MySQL to Elasticsearch Pipeline
parallelism: 2
```
Pipeline Connector Options
----------------
<div class="highlight">
<table class="colwidths-auto docutils">
<thead>
<tr>
<th class="text-left" style="width: 25%">Option</th>
<th class="text-left" style="width: 8%">Required</th>
<th class="text-left" style="width: 7%">Default</th>
<th class="text-left" style="width: 10%">Type</th>
<th class="text-left" style="width: 50%">Description</th>
</tr>
</thead>
<tbody>
<tr>
<td>type</td>
<td>required</td>
<td style="word-wrap: break-word;">(none)</td>
<td>String</td>
<td>指定要使用的连接器, 这里需要设置成 <code>'elasticsearch'</code>.</td>
</tr>
<tr>
<td>name</td>
<td>optional</td>
<td style="word-wrap: break-word;">(none)</td>
<td>String</td>
<td>Sink 的名称。</td>
</tr>
<tr>
<td>hosts</td>
<td>required</td>
<td style="word-wrap: break-word;">(none)</td>
<td>String</td>
<td>要连接到的一台或多台 Elasticsearch 主机，例如: 'http://host_name:9092;http://host_name:9093'.</td>
</tr>
<tr>
<td>version</td>
<td>required</td>
<td style="word-wrap: break-word;">7</td>
<td>Integer</td>
<td>指定要使用的连接器，有效值为：
<ul>
<li>6: 连接到 Elasticsearch 6.x 的集群。</li>
<li>7: 连接到 Elasticsearch 7.x 的集群。</li>
<li>8: 连接到 Elasticsearch 8.x 的集群。</li>
</ul>
</td>
</tr>
<tr>
<td>username</td>
<td>optional</td>
<td style="word-wrap: break-word;">(none)</td>
<td>String</td>
<td>用于连接 Elasticsearch 实例认证的用户名。</td>
</tr>
<tr>
<td>password</td>
<td>optional</td>
<td style="word-wrap: break-word;">(none)</td>
<td>String</td>
<td>用于连接 Elasticsearch 实例认证的密码。</td>
</tr>
<tr>
<td>batch.size.max</td>
<td>optional</td>
<td style="word-wrap: break-word;">500</td>
<td>Integer</td>
<td>每个批量请求的最大缓冲操作数。 可以设置为'0'来禁用它。</td>
</tr>
<tr>
<td>inflight.requests.max</td>
<td>optional</td>
<td style="word-wrap: break-word;">5</td>
<td>Integer</td>
<td>连接器将尝试执行的最大并发请求数。</td>
</tr>
<tr>
<td>buffered.requests.max</td>
<td>optional</td>
<td style="word-wrap: break-word;">1000</td>
<td>Integer</td>
<td>每个批量请求的内存缓冲区中保留的最大请求数。</td>
</tr>
<tr>
<td>batch.size.max.bytes</td>
<td>optional</td>
<td style="word-wrap: break-word;">5242880</td>
<td>Long</td>
<td>每个批量请求的缓冲操作在内存中的最大值。</td>
</tr>
<tr>
<td>buffer.time.max.ms</td>
<td>optional</td>
<td style="word-wrap: break-word;">5000</td>
<td>Long</td>
<td>每个批量请求的缓冲 flush 操作的间隔。</td>
</tr>
<tr>
<td>record.size.max.bytes</td>
<td>optional</td>
<td style="word-wrap: break-word;">10485760</td>
<td>Long</td>
<td>单个记录的最大大小（以byte为单位）。</td>
</tr>
</tbody>
</table>
</div>
Usage Notes
--------
* The written index of Elasticsearch will be `namespace.schemaName.tableName` string of TableId，this can be changed using route function of pipeline.

* The feature for automatic Elasticsearch index creation is not yet supported.

Data Type Mapping
----------------
Elasticsearch stores document in a JSON string. So the data type mapping is between Flink CDC data type and JSON data type.
<div class="wy-table-responsive">
<table class="colwidths-auto docutils">
<thead>
<tr>
<th class="text-left">CDC type</th>
<th class="text-left">JSON type</th>
<th class="text-left" style="width:60%;">NOTE</th>
</tr>
</thead>
<tbody>
<tr>
<td>TINYINT</td>
<td>NUMBER</td>
<td></td>
</tr>
<tr>
<td>SMALLINT</td>
<td>NUMBER</td>
<td></td>
</tr>
<tr>
<td>INT</td>
<td>NUMBER</td>
<td></td>
</tr>
<tr>
<td>BIGINT</td>
<td>NUMBER</td>
<td></td>
</tr>
<tr>
<td>FLOAT</td>
<td>NUMBER</td>
<td></td>
</tr>
<tr>
<td>DOUBLE</td>
<td>NUMBER</td>
<td></td>
</tr>
<tr>
<td>DECIMAL(p, s)</td>
<td>STRING</td>
<td></td>
</tr>
<tr>
<td>BOOLEAN</td>
<td>BOOLEAN</td>
<td></td>
</tr>
<tr>
<td>DATE</td>
<td>STRING with format: date</td>
<td></td>
</tr>
<tr>
<td>TIMESTAMP</td>
<td>STRING with format: date-time</td>
<td></td>
</tr>
<tr>
<td>TIMESTAMP_LTZ</td>
<td>STRING with format: date-time (with UTC time zone)</td>
<td></td>
</tr>
<tr>
<td>CHAR(n)</td>
<td>STRING</td>
<td></td>
</tr>
<tr>
<td>VARCHAR(n)</td>
<td>STRING</td>
<td></td>
</tr>
<tr>
<td>ARRAY</td>
<td>ARRAY</td>
<td></td>
</tr>
<tr>
<td>MAP</td>
<td>STRING</td>
<td></td>
</tr>
<tr>
<td>ROW</td>
<td>STRING</td>
<td></td>
</tr>
</tbody>
</table>
</div>

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