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_r293641314
########## File path: docs/ops/python_shell.md ########## @@ -0,0 +1,185 @@ +--- +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 comes with an integrated interactive Python Shell. +It can be used in a local setup as well as in a cluster setup. + +To use the shell with an integrated Flink cluster just execute: + +{% highlight bash %} +bin/pyflink-shell.sh local +{% endhighlight %} + +in the root directory of your binary Flink directory. To run the Shell on a +cluster, please see the Setup section below. + +## Usage + +The shell only supports Table API currently. +The Table Environments are automatically prebound after startup. +Use "bt_env" and "st_env" to access BatchTableEnvironment and StreamTableEnvironment respectively. + +### Table API + +The example below is a simple program using Table API: +<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> + +## Setup + +To get an overview of what options the Python Shell provides, please use + +{% highlight bash %} +bin/pyflink-shell.sh --help +{% endhighlight %} + +### Local + +To use the shell with an integrated Flink cluster just execute: + +{% highlight bash %} +bin/pyflink-shell.sh local +{% endhighlight %} + + +### Remote + +To use it with a running cluster, please start the Python shell with the keyword `remote` +and supply the host and port of the JobManager with: + +{% highlight bash %} +bin/pyflink-shell.sh remote <hostname> <portnumber> +{% endhighlight %} + +### Yarn Python Shell cluster + +The shell can deploy a Flink cluster to YARN, which is used exclusively by the +shell. The number of YARN containers can be controlled by the parameter `-n <arg>`. +The shell deploys a new Flink cluster on YARN and connects the +cluster. You can also specify options for YARN cluster such as memory for +JobManager, name of YARN application, etc. + +For example, to start a Yarn cluster for the Python Shell with two TaskManagers +use the following: + +{% highlight bash %} + bin/pyflink-shell.sh yarn -n 2 +{% endhighlight %} + +For all other options, see the full reference at the bottom. + + +### Yarn Session + +If you have previously deployed a Flink cluster using the Flink Yarn Session, +the Python shell can connect with it using the following command: + +{% highlight bash %} + bin/pyflink-shell.sh yarn +{% endhighlight %} + + +## Full Reference Review comment: The doc of the `full reference` should some as the command line output`:  ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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