sunjincheng121 commented on a change in pull request #8675: [FLINK-12716][python] Add an interactive shell for Python Table API URL: https://github.com/apache/flink/pull/8675#discussion_r293262036
########## File path: docs/ops/python_shell.zh.md ########## @@ -0,0 +1,179 @@ +--- +title: "Python REPL" +nav-parent_id: ops +nav-pos: 7 +--- +<!-- +Licensed to the Apache Software Foundation (ASF) under one +or more contributor license agreements. See the NOTICE file +distributed with this work for additional information +regarding copyright ownership. The ASF licenses this file +to you under the Apache License, Version 2.0 (the +"License"); you may not use this file except in compliance +with the License. You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, +software distributed under the License is distributed on an +"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +KIND, either express or implied. See the License for the +specific language governing permissions and limitations +under the License. +--> + +Flink附带了一个集成的交互式Python Shell。 +它既能够用在本地启动的local模式，也能够用在集群启动的cluster模式下。 + +为了使用Flink的Python Shell，你只需要在Flink的binary目录下执行: + +{% highlight bash %} +bin/pyflink-shell.sh local +{% endhighlight %} + +关于如何在一个Cluster集群上运行Python shell，可以参考下面的启动那一节的内容 + +## 使用 + +当前Python shell支持Table API的功能。 +在启动之后，Table Environment的相关内容将会被自动加载。 +可以通过变量"bt_env"来使用BatchTableEnvironment，通过变量"st_env"来使用StreamTableEnvironment。 + +### Table API + +下面的内容是关于如何通过Table API来实现一个wordcount的作业: +<div class="codetabs" markdown="1"> +<div data-lang="stream" markdown="1"> +{% highlight python %} +>>> import tempfile +>>> import os +>>> sink_path = tempfile.gettempdir() + '/streaming.csv' +>>> if os.path.isfile(sink_path): +>>> os.remove(sink_path) +>>> t = st_env.from_elements([(1, 'hi', 'hello'), (2, 'hi', 'hello')], ['a', 'b', 'c']) +>>> st_env.connect(FileSystem().path(sink_path))\ +>>> .with_format(OldCsv() +>>> .field_delimiter(',') +>>> .field("a", DataTypes.BIGINT()) +>>> .field("b", DataTypes.STRING()) +>>> .field("c", DataTypes.STRING()))\ +>>> .with_schema(Schema() +>>> .field("a", DataTypes.BIGINT()) +>>> .field("b", DataTypes.STRING()) +>>> .field("c", DataTypes.STRING()))\ +>>> .register_table_sink("stream_sink") +>>> t.select("a + 1, b, c")\ +>>> .insert_into("stream_sink") +>>> st_env.execute() +{% endhighlight %} +</div> +<div data-lang="batch" markdown="1"> +{% highlight python %} +>>> import tempfile +>>> import os +>>> sink_path = tempfile.gettempdir() + '/batch.csv' +>>> if os.path.isfile(sink_path): +>>> os.remove(sink_path) +>>> t = bt_env.from_elements([(1, 'hi', 'hello'), (2, 'hi', 'hello')], ['a', 'b', 'c']) +>>> bt_env.connect(FileSystem().path(sink_path))\ +>>> .with_format(OldCsv() +>>> .field_delimiter(',') +>>> .field("a", DataTypes.BIGINT()) +>>> .field("b", DataTypes.STRING()) +>>> .field("c", DataTypes.STRING()))\ +>>> .with_schema(Schema() +>>> .field("a", DataTypes.BIGINT()) +>>> .field("b", DataTypes.STRING()) +>>> .field("c", DataTypes.STRING()))\ +>>> .register_table_sink("batch_sink") +>>> t.select("a + 1, b, c")\ +>>> .insert_into("batch_sink") +>>> bt_env.execute() +{% endhighlight %} +</div> +</div> + +## 启动 + +为了概览Python Shell提供的可选参数，可以使用: + +{% highlight bash %} +bin/pyflink-shell.sh --help +{% endhighlight %} + +### Local + +可以指定Python Shell运行在local本地，只需要执行: + +{% highlight bash %} +bin/pyflink-shell.sh local +{% endhighlight %} + + +### Remote + +可以指定Python Shell运行在一个指定的JobManager上，通过关键字`remote`和对应的JobManager +的地址和端口号来进行指定: + +{% highlight bash %} +bin/pyflink-shell.sh remote <hostname> <portnumber> +{% endhighlight %} + +### Yarn Python Shell cluster + +可以指定Python Shell运行在YARN集群之上。YARN的container的数量可以通过参数`-n <arg>`进行 +指定。Python shell在Yarn上部署一个新的Flink集群，并进行连接。除了指定container数量，你也 +可以指定JobManager的内存，YARN应用的名字等参数。 +例如，运行Python Shell部署一个包含两个TaskManager的Yarn集群: + +{% highlight bash %} + bin/pyflink-shell.sh yarn -n 2 +{% endhighlight %} + +关于所有可选的参数，可以查看本页面底部的完整说明。 + + +### Yarn Session + +如果你已经通过Flink Yarn Session部署了一个Flink集群，能够通过以下的命令连接到这个集群: + +{% highlight bash %} + bin/pyflink-shell.sh yarn +{% endhighlight %} + + +## 完整的参考 + +{% highlight bash %} +Flink Python Shell +使用: pyflink-shell.sh [local|remote|yarn] [options] <args>... + +命令: local [选项] +启动一个部署在local本地的Flink Python shell Review comment: `local本地` -> `local`? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
