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Posted to commits@rocketmq.apache.org by ji...@apache.org on 2023/01/18 02:28:37 UTC
[rocketmq-site] branch new-official-website updated: [ISSUE #378]Translation for "数据集成-概念" Section in the v4.x & 5.0 Document (CN -> EN) (#438)
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jinrongtong pushed a commit to branch new-official-website
in repository https://gitbox.apache.org/repos/asf/rocketmq-site.git
The following commit(s) were added to refs/heads/new-official-website by this push:
new 43bb1d9e4 [ISSUE #378]Translation for "数据集成-概念" Section in the v4.x & 5.0 Document (CN -> EN) (#438)
43bb1d9e4 is described below
commit 43bb1d9e4af9c0d9d8c937a30e7dc59620eca5fb
Author: mxsm <lj...@gmail.com>
AuthorDate: Wed Jan 18 10:28:29 2023 +0800
[ISSUE #378]Translation for "数据集成-概念" Section in the v4.x & 5.0 Document (CN -> EN) (#438)
* [ISSUE #378]Translation for "数据集成-概念" Section in the v4.x & 5.0 Document (CN -> EN)
* polish document
---
.../26RocketMQ Connect Concept.md" | 22 ++++++++++------------
.../26RocketMQ Connect Concept.md" | 22 ++++++++++------------
2 files changed, 20 insertions(+), 24 deletions(-)
diff --git "a/i18n/en/docusaurus-plugin-content-docs/current/08-\346\225\260\346\215\256\351\233\206\346\210\220/26RocketMQ Connect Concept.md" "b/i18n/en/docusaurus-plugin-content-docs/current/08-\346\225\260\346\215\256\351\233\206\346\210\220/26RocketMQ Connect Concept.md"
index 501455350..eb4ca6d2d 100644
--- "a/i18n/en/docusaurus-plugin-content-docs/current/08-\346\225\260\346\215\256\351\233\206\346\210\220/26RocketMQ Connect Concept.md"
+++ "b/i18n/en/docusaurus-plugin-content-docs/current/08-\346\225\260\346\215\256\351\233\206\346\210\220/26RocketMQ Connect Concept.md"
@@ -1,28 +1,26 @@
-# 概念
+# RocketMQ Connect Concept
## Connector
-连接器，定义数据从哪复制到哪，是从源数据系统读取数据写入RocketMQ，这种是SourceConnector
-，或从RocketMQ读数据写入到目标系统,这种是SinkConnector。Connector决定需要创建任务的数量，从Worker接收配置传递给任务。
+The connector defines where the data is copied from and where it is copied to. It reads data from the source system and writes it to RocketMQ, which is the SourceConnector, or reads data from RocketMQ and writes it to the target system, which is the SinkConnector. The Connector decides the number of tasks to be created, and receives configuration from the Worker and passes it to the task.
## Task
-是Connector任务分片的最小分配单位，是实际将源数据源数据复制数据到RocketMQ（SourceTask），或者将数据从RocketMQ读取数据写入到目标系统（SinkTask）真正的执行者，Task是无状态的可以动态的启停任务，多个Task是可以并行执行的，Connector复制数据的并行度主要体现在Task数量上。
+Task is the minimum allocation unit of Connector task sharding, which is responsible for actually copying the source data to RocketMQ (SourceTask), or reading data from RocketMQ and writing it to the target system (SinkTask). Tasks are stateless, and can be started and stopped dynamically. Multiple tasks can be executed in parallel, and the parallelism of data copying by the Connector is mainly reflected in the number of tasks.
-
+
-通过Connect的Api也可以看到Connector和Task各自的职责，Connector实现时就已经确定数据复制的流向，Connector接收数据源相关的配置，taskClass获取需要创建的任务类型，通过taskConfigs指定最大任务数量，并且为task分配好配置。task拿到配置以后从数据源取数据写入到目标存储。
+Through Connect's API, you can also see the responsibilities of Connector and Task, Connector has determined the data copy flow when it is implemented, Connector receives data source related configuration, taskClass obtains the type of task to be created, and taskConfigs specifies the maximum number of tasks, and allocates configuration for tasks. After task gets the configuration, it reads data from the data source and writes it to the target storage.
-通过下面的两张图可以清楚的看到，Connecotr和Task处理基本流程。
+From the following two diagrams, it is clear to see the basic flow of processing for Connector and Task.
-
+
## Worker
-worker 进程是Connector和Task运行环境，它提供RESTFul能力，接受HTTP请求，将获取到的配置传递给Connector和Task。
-除此之外它还负责启动Connector和Task，保存Connector配置信息，保存Task同步数据的位点信息，负载均衡能力，Connect集群高可用，扩缩容，故障处理主要依赖Worker的负载均衡能力实现的。
+The worker process is the running environment for Connector and Task, it provides RESTful capabilities, accepts HTTP requests, and passes the obtained configuration to Connector and Task. In addition, it is responsible for starting Connector and Task, saving Connector configuration information, saving the position information of Task's synchronized data, and load balancing capability. High availability, scaling and fault handling of Connect clusters mainly rely on the load balancing capa [...]
-
+
-从上面面这张图，看到Worker通过提供的REST Api接收http请求，将接收到的配置信息传递给配置管理服务，配置管理服务将配置保存到本地并同步给其它worker节点，同时触发负载均衡。
+From the above diagram, it can be seen that the Worker receives http requests through the provided REST API, and passes the received configuration information to the configuration management service. The configuration management service saves the configuration locally and synchronizes it with other worker nodes, while also triggering load balancing.
diff --git "a/i18n/en/docusaurus-plugin-content-docs/version-5.0/08-\346\225\260\346\215\256\351\233\206\346\210\220/26RocketMQ Connect Concept.md" "b/i18n/en/docusaurus-plugin-content-docs/version-5.0/08-\346\225\260\346\215\256\351\233\206\346\210\220/26RocketMQ Connect Concept.md"
index 501455350..eb4ca6d2d 100644
--- "a/i18n/en/docusaurus-plugin-content-docs/version-5.0/08-\346\225\260\346\215\256\351\233\206\346\210\220/26RocketMQ Connect Concept.md"
+++ "b/i18n/en/docusaurus-plugin-content-docs/version-5.0/08-\346\225\260\346\215\256\351\233\206\346\210\220/26RocketMQ Connect Concept.md"
@@ -1,28 +1,26 @@
-# 概念
+# RocketMQ Connect Concept
## Connector
-连接器，定义数据从哪复制到哪，是从源数据系统读取数据写入RocketMQ，这种是SourceConnector
-，或从RocketMQ读数据写入到目标系统,这种是SinkConnector。Connector决定需要创建任务的数量，从Worker接收配置传递给任务。
+The connector defines where the data is copied from and where it is copied to. It reads data from the source system and writes it to RocketMQ, which is the SourceConnector, or reads data from RocketMQ and writes it to the target system, which is the SinkConnector. The Connector decides the number of tasks to be created, and receives configuration from the Worker and passes it to the task.
## Task
-是Connector任务分片的最小分配单位，是实际将源数据源数据复制数据到RocketMQ（SourceTask），或者将数据从RocketMQ读取数据写入到目标系统（SinkTask）真正的执行者，Task是无状态的可以动态的启停任务，多个Task是可以并行执行的，Connector复制数据的并行度主要体现在Task数量上。
+Task is the minimum allocation unit of Connector task sharding, which is responsible for actually copying the source data to RocketMQ (SourceTask), or reading data from RocketMQ and writing it to the target system (SinkTask). Tasks are stateless, and can be started and stopped dynamically. Multiple tasks can be executed in parallel, and the parallelism of data copying by the Connector is mainly reflected in the number of tasks.
-
+
-通过Connect的Api也可以看到Connector和Task各自的职责，Connector实现时就已经确定数据复制的流向，Connector接收数据源相关的配置，taskClass获取需要创建的任务类型，通过taskConfigs指定最大任务数量，并且为task分配好配置。task拿到配置以后从数据源取数据写入到目标存储。
+Through Connect's API, you can also see the responsibilities of Connector and Task, Connector has determined the data copy flow when it is implemented, Connector receives data source related configuration, taskClass obtains the type of task to be created, and taskConfigs specifies the maximum number of tasks, and allocates configuration for tasks. After task gets the configuration, it reads data from the data source and writes it to the target storage.
-通过下面的两张图可以清楚的看到，Connecotr和Task处理基本流程。
+From the following two diagrams, it is clear to see the basic flow of processing for Connector and Task.
-
+
## Worker
-worker 进程是Connector和Task运行环境，它提供RESTFul能力，接受HTTP请求，将获取到的配置传递给Connector和Task。
-除此之外它还负责启动Connector和Task，保存Connector配置信息，保存Task同步数据的位点信息，负载均衡能力，Connect集群高可用，扩缩容，故障处理主要依赖Worker的负载均衡能力实现的。
+The worker process is the running environment for Connector and Task, it provides RESTful capabilities, accepts HTTP requests, and passes the obtained configuration to Connector and Task. In addition, it is responsible for starting Connector and Task, saving Connector configuration information, saving the position information of Task's synchronized data, and load balancing capability. High availability, scaling and fault handling of Connect clusters mainly rely on the load balancing capa [...]
-
+
-从上面面这张图，看到Worker通过提供的REST Api接收http请求，将接收到的配置信息传递给配置管理服务，配置管理服务将配置保存到本地并同步给其它worker节点，同时触发负载均衡。
+From the above diagram, it can be seen that the Worker receives http requests through the provided REST API, and passes the received configuration information to the configuration management service. The configuration management service saves the configuration locally and synchronizes it with other worker nodes, while also triggering load balancing.