klion26 commented on a change in pull request #9188: [FLINK-12940][docs-zh]
Translate Apache Cassandra Connector page into…
URL: https://github.com/apache/flink/pull/9188#discussion_r305619109
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File path: docs/dev/connectors/cassandra.zh.md
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@@ -43,77 +43,68 @@ To use this connector, add the following dependency to
your project:
</dependency>
{% endhighlight %}
-Note that the streaming connectors are currently __NOT__ part of the binary
distribution. See how to link with them for cluster execution [here]({{
site.baseurl}}/dev/projectsetup/dependencies.html).
+请注意，流连接器当前不是 Flink
二进制发布包的一部分。了解如何链接它们以进行集群执行[此处]({{site.baseurl}}/zh/dev/projectsetup/dependencies.html)。
-## Installing Apache Cassandra
-There are multiple ways to bring up a Cassandra instance on local machine:
-1. Follow the instructions from [Cassandra Getting Started
page](http://cassandra.apache.org/doc/latest/getting_started/index.html).
-2. Launch a container running Cassandra from [Official Docker
Repository](https://hub.docker.com/_/cassandra/)
+## 安装 Apache Cassandra
+有多种方法可以在本地计算机上启动Cassandra实例：
+
+1.
按照[Cassandra入门页面](http://cassandra.apache.org/doc/latest/getting_started/index.html)中的说明进行操作。
+2. 从[Official Docker Repository](https://hub.docker.com/_/cassandra/)启动运行
Cassandra 的容器
## Cassandra Sinks
-### Configurations
+### 配置
-Flink's Cassandra sink are created by using the static
CassandraSink.addSink(DataStream<IN> input) method.
-This method returns a CassandraSinkBuilder, which offers methods to further
configure the sink, and finally `build()` the sink instance.
+Flink的 Cassandra 接收器是使用静态 `CassandraSink.addSink(DataStream<IN> input)`
方法创建的。这个方法返回一个 `CassandraSinkBuilder`，它提供了进一步配置接收器的方法，最后通过 `build（）` 创建接收器实例。
-The following configuration methods can be used:
+可以使用以下配置方法：
1. _setQuery(String query)_
- * Sets the upsert query that is executed for every record the sink
receives.
- * The query is internally treated as CQL statement.
- * __DO__ set the upsert query for processing __Tuple__ data type.
- * __DO NOT__ set the query for processing __POJO__ data types.
+ * 设置为接收器接收的每个记录执行的 upsert 查询。
+ * 查询在内部被视为 CQL 语句。
+ * __DO__ 设置 upsert 查询以处理 __Tuple__ 数据类型。
+ * __DO NOT__ 设置查询以处理 __POJO__ 数据类型。
2. _setClusterBuilder()_
- * Sets the cluster builder that is used to configure the connection to
cassandra with more sophisticated settings such as consistency level, retry
policy and etc.
+ * 将用于配置创建更复杂的 cassandra cluster builder，例如一致性级别，重试策略等。
3. _setHost(String host[, int port])_
- * Simple version of setClusterBuilder() with host/port information to
connect to Cassandra instances
+ * 简单版本的 setClusterBuilder()，包含连接到 Cassandra 实例的主机/端口信息
4. _setMapperOptions(MapperOptions options)_
- * Sets the mapper options that are used to configure the DataStax
ObjectMapper.
- * Only applies when processing __POJO__ data types.
+ * 设置用于配置 DataStax ObjectMapper 的映射器选项。
+ * 仅在处理 __POJO__ 数据类型时适用。
5. _setMaxConcurrentRequests(int maxConcurrentRequests, Duration timeout)_
- * Sets the maximum allowed number of concurrent requests with a timeout
for acquiring permits to execute.
- * Only applies when __enableWriteAheadLog()__ is not configured.
+ * 设置允许执行许可的超时的最大并发请求数。
+ * 仅在未配置 __enableWriteAheadLog()__ 时适用。
6. _enableWriteAheadLog([CheckpointCommitter committer])_
- * An __optional__ setting
- * Allows exactly-once processing for non-deterministic algorithms.
+ * __optional__ 设置
+ * 允许对非确定性算法进行精确一次处理。
7. _setFailureHandler([CassandraFailureHandler failureHandler])_
- * An __optional__ setting
- * Sets the custom failure handler.
+ * __optional__ 设置。
+ * 设置自定义失败处理程序。
8. _build()_
- * Finalizes the configuration and constructs the CassandraSink instance.
+ * 完成配置并构造 CassandraSink 实例。
-### Write-ahead Log
+### 预写日志
-A checkpoint committer stores additional information about completed
checkpoints
-in some resource. This information is used to prevent a full replay of the last
-completed checkpoint in case of a failure.
-You can use a `CassandraCommitter` to store these in a separate table in
cassandra.
-Note that this table will NOT be cleaned up by Flink.
+一个 checkpoint 提交者存储有关已完成 checkpoint 的附加信息在某些资源中。此信息用于防止在发生故障时从最后一次完整保存的
checkpoint 中重播恢复数据 。
+您可以使用 `CassandraCommitter` 将它们存储在 cassandra 的单独表中。请注意，Flink 不会清理此表。
-Flink can provide exactly-once guarantees if the query is idempotent (meaning
it can be applied multiple
-times without changing the result) and checkpointing is enabled. In case of a
failure the failed
-checkpoint will be replayed completely.
+如果查询是幂等的，Flink 启用了 checkpoint 情况下可以提供精确一次保证（意味着它可以应用多个时间而不更改结果）。如果失败则会从已完整保存的
checkpoint 中重播恢复数据。
-Furthermore, for non-deterministic programs the write-ahead log has to be
enabled. For such a program
-the replayed checkpoint may be completely different than the previous attempt,
which may leave the
-database in an inconsistent state since part of the first attempt may already
be written.
-The write-ahead log guarantees that the replayed checkpoint is identical to
the first attempt.
-Note that that enabling this feature will have an adverse impact on latency.
+此外，对于非确定性程序，必须启用预写日志。对于这样的计划重播的 checkpoint
可能与之前的尝试完全不同，后者可能会离开数据库处于不一致状态，因为可能已经编写了第一次尝试的部分内容。预写日志保证重放的 checkpoint
与第一次尝试相同。请注意，启用此功能会对延迟产生负面影响。
-<p style="border-radius: 5px; padding: 5px" class="bg-danger"><b>Note</b>: The
write-ahead log functionality is currently experimental. In many cases it is
sufficient to use the connector without enabling it. Please report problems to
the development mailing list.</p>
+<p style="border-radius: 5px; padding: 5px"
class="bg-danger"><b>注意</b>：预写日志功能目前是实验性的。在许多情况下，使用连接器而不启用它就足够了。请将问题报告给开发邮件列表。</p>
Review comment:
`在许多情况下，使用连接器而不启用它就足够了` -> `在许多情况下，并不需要启用它`？
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