This is an automated email from the ASF dual-hosted git repository.
dianfu pushed a commit to branch release-1.11
in repository https://gitbox.apache.org/repos/asf/flink.git
The following commit(s) were added to refs/heads/release-1.11 by this push:
new b6d53fb [FLINK-18912][python][docs] Add Python api tutorial under
Python GettingStart (#13192)
b6d53fb is described below
commit b6d53fb1717023faafb79948a305b8dc1e3de2c4
Author: Hequn Cheng <hequn....@alibaba-inc.com>
AuthorDate: Thu Aug 20 09:52:33 2020 +0800
[FLINK-18912][python][docs] Add Python api tutorial under Python
GettingStart (#13192)
---
docs/dev/python/getting-started/tutorial/index.md | 24 ++++
.../python/getting-started/tutorial/index.zh.md | 24 ++++
.../tutorial/table_api_tutorial.md} | 9 +-
.../tutorial/table_api_tutorial.zh.md} | 9 +-
docs/try-flink/python_table_api.md | 156 +-------------------
docs/try-flink/python_table_api.zh.md | 158 +--------------------
6 files changed, 60 insertions(+), 320 deletions(-)
diff --git a/docs/dev/python/getting-started/tutorial/index.md
b/docs/dev/python/getting-started/tutorial/index.md
new file mode 100644
index 0000000..b862506
--- /dev/null
+++ b/docs/dev/python/getting-started/tutorial/index.md
@@ -0,0 +1,24 @@
+---
+title: "Tutorial"
+nav-id: python_tutorial
+nav-parent_id: python_start
+nav-pos: 20
+---
+<!--
+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.
+-->
diff --git a/docs/dev/python/getting-started/tutorial/index.zh.md
b/docs/dev/python/getting-started/tutorial/index.zh.md
new file mode 100644
index 0000000..e81b7a2
--- /dev/null
+++ b/docs/dev/python/getting-started/tutorial/index.zh.md
@@ -0,0 +1,24 @@
+---
+title: "教程"
+nav-id: python_tutorial
+nav-parent_id: python_start
+nav-pos: 20
+---
+<!--
+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.
+-->
diff --git a/docs/try-flink/python_table_api.md
b/docs/dev/python/getting-started/tutorial/table_api_tutorial.md
similarity index 97%
copy from docs/try-flink/python_table_api.md
copy to docs/dev/python/getting-started/tutorial/table_api_tutorial.md
index 9c8bd9c..401020c 100644
--- a/docs/try-flink/python_table_api.md
+++ b/docs/dev/python/getting-started/tutorial/table_api_tutorial.md
@@ -1,8 +1,7 @@
---
-title: "Python API Tutorial"
-nav-title: Python API
-nav-parent_id: try-flink
-nav-pos: 4
+title: "Table API Tutorial"
+nav-parent_id: python_tutorial
+nav-pos: 20
---
<!--
Licensed to the Apache Software Foundation (ASF) under one
@@ -180,4 +179,4 @@ pyflink 1
This should get you started with writing your own Flink Python Table API
programs.
To learn more about the Python Table API, you can refer
-[Flink Python Table API Docs]({{ site.pythondocs_baseurl }}/api/python) for
more details.
+[Flink Python API Docs]({{ site.pythondocs_baseurl }}/api/python) for more
details.
diff --git a/docs/try-flink/python_table_api.zh.md
b/docs/dev/python/getting-started/tutorial/table_api_tutorial.zh.md
similarity index 97%
copy from docs/try-flink/python_table_api.zh.md
copy to docs/dev/python/getting-started/tutorial/table_api_tutorial.zh.md
index 3fbea18..f94ab72 100644
--- a/docs/try-flink/python_table_api.zh.md
+++ b/docs/dev/python/getting-started/tutorial/table_api_tutorial.zh.md
@@ -1,8 +1,7 @@
---
-title: "Python API 教程"
-nav-title: Python API
-nav-parent_id: try-flink
-nav-pos: 4
+title: "Table API 教程"
+nav-parent_id: python_tutorial
+nav-pos: 20
---
<!--
Licensed to the Apache Software Foundation (ASF) under one
@@ -183,4 +182,4 @@ pyflink 1
{% endhighlight %}
上述教程介绍了如何编写并运行一个Flink Python Table API程序，如果想了解Flink Python Table API
-的更多信息，可以参考[Flink Python Table API文档]({{ site.pythondocs_baseurl }}/api/python)。
+的更多信息，可以参考[Flink Python API文档]({{ site.pythondocs_baseurl }}/api/python)。
diff --git a/docs/try-flink/python_table_api.md
b/docs/try-flink/python_table_api.md
index 9c8bd9c..2583c9f 100644
--- a/docs/try-flink/python_table_api.md
+++ b/docs/try-flink/python_table_api.md
@@ -23,161 +23,9 @@ specific language governing permissions and limitations
under the License.
-->
-This walkthrough will quickly get you started building a pure Python Flink
project.
-
-Please refer to the Python Table API [installation guide]({% link
dev/python/getting-started/installation.md %}) on how to set up the Python
execution environments.
-
* This will be replaced by the TOC
{:toc}
-## Setting up a Python Project
-
-You can begin by creating a Python project and installing the PyFlink package
following the [installation guide]({% link
dev/python/getting-started/installation.md %}#installation-of-pyflink).
-
-## Writing a Flink Python Table API Program
-
-Table API applications begin by declaring a table environment; either a
`BatchTableEvironment` for batch applications or `StreamTableEnvironment` for
streaming applications.
-This serves as the main entry point for interacting with the Flink runtime.
-It can be used for setting execution parameters such as restart strategy,
default parallelism, etc.
-The table config allows setting Table API specific configurations.
-
-{% highlight python %}
-exec_env = ExecutionEnvironment.get_execution_environment()
-exec_env.set_parallelism(1)
-t_config = TableConfig()
-t_env = BatchTableEnvironment.create(exec_env, t_config)
-{% endhighlight %}
-
-The the table environment created, you can declare source and sink tables.
-
-{% highlight python %}
-t_env.connect(FileSystem().path('/tmp/input')) \
- .with_format(OldCsv()
- .field('word', DataTypes.STRING())) \
- .with_schema(Schema()
- .field('word', DataTypes.STRING())) \
- .create_temporary_table('mySource')
-
-t_env.connect(FileSystem().path('/tmp/output')) \
- .with_format(OldCsv()
- .field_delimiter('\t')
- .field('word', DataTypes.STRING())
- .field('count', DataTypes.BIGINT())) \
- .with_schema(Schema()
- .field('word', DataTypes.STRING())
- .field('count', DataTypes.BIGINT())) \
- .create_temporary_table('mySink')
-{% endhighlight %}
-You can also use the TableEnvironment.sql_update() method to register a
source/sink table defined in DDL:
-{% highlight python %}
-my_source_ddl = """
- create table mySource (
- word VARCHAR
- ) with (
- 'connector.type' = 'filesystem',
- 'format.type' = 'csv',
- 'connector.path' = '/tmp/input'
- )
-"""
-
-my_sink_ddl = """
- create table mySink (
- word VARCHAR,
- `count` BIGINT
- ) with (
- 'connector.type' = 'filesystem',
- 'format.type' = 'csv',
- 'connector.path' = '/tmp/output'
- )
-"""
-
-t_env.sql_update(my_source_ddl)
-t_env.sql_update(my_sink_ddl)
-{% endhighlight %}
-This registers a table named `mySource` and a table named `mySink` in the
execution environment.
-The table `mySource` has only one column, word, and it consumes strings read
from file `/tmp/input`.
-The table `mySink` has two columns, word and count, and writes data to the
file `/tmp/output`, with `\t` as the field delimiter.
-
-You can now create a job which reads input from table `mySource`, preforms
some transformations, and writes the results to table `mySink`.
-
-{% highlight python %}
-t_env.from_path('mySource') \
- .group_by('word') \
- .select('word, count(1)') \
- .insert_into('mySink')
-{% endhighlight %}
-
-Finally you must execute the actual Flink Python Table API job.
-All operations, such as creating sources, transformations and sinks are lazy.
-Only when `t_env.execute(job_name)` is called will the job be run.
-
-{% highlight python %}
-t_env.execute("tutorial_job")
-{% endhighlight %}
-
-The complete code so far:
-
-{% highlight python %}
-from pyflink.dataset import ExecutionEnvironment
-from pyflink.table import TableConfig, DataTypes, BatchTableEnvironment
-from pyflink.table.descriptors import Schema, OldCsv, FileSystem
-
-exec_env = ExecutionEnvironment.get_execution_environment()
-exec_env.set_parallelism(1)
-t_config = TableConfig()
-t_env = BatchTableEnvironment.create(exec_env, t_config)
-
-t_env.connect(FileSystem().path('/tmp/input')) \
- .with_format(OldCsv()
- .field('word', DataTypes.STRING())) \
- .with_schema(Schema()
- .field('word', DataTypes.STRING())) \
- .create_temporary_table('mySource')
-
-t_env.connect(FileSystem().path('/tmp/output')) \
- .with_format(OldCsv()
- .field_delimiter('\t')
- .field('word', DataTypes.STRING())
- .field('count', DataTypes.BIGINT())) \
- .with_schema(Schema()
- .field('word', DataTypes.STRING())
- .field('count', DataTypes.BIGINT())) \
- .create_temporary_table('mySink')
-
-t_env.from_path('mySource') \
- .group_by('word') \
- .select('word, count(1)') \
- .insert_into('mySink')
-
-t_env.execute("tutorial_job")
-{% endhighlight %}
-
-## Executing a Flink Python Table API Program
-Firstly, you need to prepare input data in the "/tmp/input" file. You can
choose the following command line to prepare the input data:
-
-{% highlight bash %}
-$ echo -e "flink\npyflink\nflink" > /tmp/input
-{% endhighlight %}
-
-Next, you can run this example on the command line (Note: if the result file
"/tmp/output" has already existed, you need to remove the file before running
the example):
-
-{% highlight bash %}
-$ python WordCount.py
-{% endhighlight %}
-
-The command builds and runs the Python Table API program in a local mini
cluster.
-You can also submit the Python Table API program to a remote cluster, you can
refer
-[Job Submission Examples]({{ site.baseurl
}}/ops/cli.html#job-submission-examples)
-for more details.
-
-Finally, you can see the execution result on the command line:
-
-{% highlight bash %}
-$ cat /tmp/output
-flink 2
-pyflink 1
-{% endhighlight %}
+## Python Table API tutorial
-This should get you started with writing your own Flink Python Table API
programs.
-To learn more about the Python Table API, you can refer
-[Flink Python Table API Docs]({{ site.pythondocs_baseurl }}/api/python) for
more details.
+You can refer to the [Python Table API Tutorial]({% link
dev/python/getting-started/tutorial/table_api_tutorial.md %}) Docs for more
details.
diff --git a/docs/try-flink/python_table_api.zh.md
b/docs/try-flink/python_table_api.zh.md
index 3fbea18..8952f5f 100644
--- a/docs/try-flink/python_table_api.zh.md
+++ b/docs/try-flink/python_table_api.zh.md
@@ -26,161 +26,7 @@ under the License.
* This will be replaced by the TOC
{:toc}
-在该教程中，我们会从零开始，介绍如何创建一个Flink Python项目及运行Python Table API程序。
-关于Python执行环境的要求，请参考Python Table API[环境安装]({% link
dev/python/getting-started/installation.zh.md %})。
+## Python Table API 教程
-## 创建一个Python Table API项目
-
-首先，使用您最熟悉的IDE创建一个Python项目，然后安装PyFlink包，请参考[PyFlink安装指南]({% link
dev/python/getting-started/installation.zh.md %}#pyflink-安装)了解详细信息。
-
-## 编写一个Flink Python Table API程序
-
-编写Flink Python Table API程序的第一步是创建`BatchTableEnvironment`
-(或者`StreamTableEnvironment`，如果你要创建一个流式作业)。这是Python Table API作业的入口类。
-
-{% highlight python %}
-exec_env = ExecutionEnvironment.get_execution_environment()
-exec_env.set_parallelism(1)
-t_config = TableConfig()
-t_env = BatchTableEnvironment.create(exec_env, t_config)
-{% endhighlight %}
-
-`ExecutionEnvironment` (或者`StreamExecutionEnvironment`，如果你要创建一个流式作业)
-可以用来设置执行参数，比如重启策略，缺省并发值等。
-
-`TableConfig`可以用来设置缺省的catalog名字，自动生成代码时方法大小的阈值等.
-
-接下来，我们将介绍如何创建源表和结果表。
-
-{% highlight python %}
-t_env.connect(FileSystem().path('/tmp/input')) \
- .with_format(OldCsv()
- .field('word', DataTypes.STRING())) \
- .with_schema(Schema()
- .field('word', DataTypes.STRING())) \
- .create_temporary_table('mySource')
-
-t_env.connect(FileSystem().path('/tmp/output')) \
- .with_format(OldCsv()
- .field_delimiter('\t')
- .field('word', DataTypes.STRING())
- .field('count', DataTypes.BIGINT())) \
- .with_schema(Schema()
- .field('word', DataTypes.STRING())
- .field('count', DataTypes.BIGINT())) \
- .create_temporary_table('mySink')
-{% endhighlight %}
-
-You can also use the TableEnvironment.sql_update() method to register a
source/sink table defined in DDL:
-{% highlight python %}
-my_source_ddl = """
- create table mySource (
- word VARCHAR
- ) with (
- 'connector.type' = 'filesystem',
- 'format.type' = 'csv',
- 'connector.path' = '/tmp/input'
- )
-"""
-
-my_sink_ddl = """
- create table mySink (
- word VARCHAR,
- `count` BIGINT
- ) with (
- 'connector.type' = 'filesystem',
- 'format.type' = 'csv',
- 'connector.path' = '/tmp/output'
- )
-"""
-
-t_env.sql_update(my_source_ddl)
-t_env.sql_update(my_sink_ddl)
-{% endhighlight %}
-
-上面的程序展示了如何创建及在`ExecutionEnvironment`中注册表名分别为`mySource`和`mySink`的表。
-其中，源表`mySource`有一列: word，该表代表了从输入文件`/tmp/input`中读取的单词；
-结果表`mySink`有两列: word和count，该表会将计算结果输出到文件`/tmp/output`中，字段之间使用`\t`作为分隔符。
-
-接下来，我们介绍如何创建一个作业：该作业读取表`mySource`中的数据，进行一些变换，然后将结果写入表`mySink`。
-
-{% highlight python %}
-t_env.scan('mySource') \
- .group_by('word') \
- .select('word, count(1)') \
- .insert_into('mySink')
-{% endhighlight %}
-
-最后，需要做的就是启动Flink Python Table API作业。上面所有的操作，比如创建源表
-进行变换以及写入结果表的操作都只是构建作业逻辑图，只有当`t_env.execute(job_name)`被调用的时候，
-作业才会被真正提交到集群或者本地进行执行。
-
-{% highlight python %}
-t_env.execute("python_job")
-{% endhighlight %}
-
-该教程的完整代码如下:
-
-{% highlight python %}
-from pyflink.dataset import ExecutionEnvironment
-from pyflink.table import TableConfig, DataTypes, BatchTableEnvironment
-from pyflink.table.descriptors import Schema, OldCsv, FileSystem
-
-exec_env = ExecutionEnvironment.get_execution_environment()
-exec_env.set_parallelism(1)
-t_config = TableConfig()
-t_env = BatchTableEnvironment.create(exec_env, t_config)
-
-t_env.connect(FileSystem().path('/tmp/input')) \
- .with_format(OldCsv()
- .field('word', DataTypes.STRING())) \
- .with_schema(Schema()
- .field('word', DataTypes.STRING())) \
- .create_temporary_table('mySource')
-
-t_env.connect(FileSystem().path('/tmp/output')) \
- .with_format(OldCsv()
- .field_delimiter('\t')
- .field('word', DataTypes.STRING())
- .field('count', DataTypes.BIGINT())) \
- .with_schema(Schema()
- .field('word', DataTypes.STRING())
- .field('count', DataTypes.BIGINT())) \
- .create_temporary_table('mySink')
-
-t_env.from_path('mySource') \
- .group_by('word') \
- .select('word, count(1)') \
- .insert_into('mySink')
-
-t_env.execute("python_job")
-{% endhighlight %}
-
-## 执行一个Flink Python Table API程序
-
-首先，你需要在文件 “/tmp/input” 中准备好输入数据。你可以选择通过如下命令准备输入数据：
-
-{% highlight bash %}
-$ echo -e "flink\npyflink\nflink" > /tmp/input
-{% endhighlight %}
-
-接下来，可以在命令行中运行作业（假设作业名为WordCount.py）（注意：如果输出结果文件“/tmp/output”已经存在，你需要先删除文件，否则程序将无法正确运行起来）：
-
-{% highlight bash %}
-$ python WordCount.py
-{% endhighlight %}
-
-上述命令会构建Python Table API程序，并在本地mini cluster中运行。如果想将作业提交到远端集群执行，
-可以参考[作业提交示例]({{ site.baseurl }}/zh/ops/cli.html#job-submission-examples)。
-
-最后，你可以通过如下命令查看你的运行结果：
-
-{% highlight bash %}
-$ cat /tmp/output
-flink 2
-pyflink 1
-{% endhighlight %}
-
-上述教程介绍了如何编写并运行一个Flink Python Table API程序，如果想了解Flink Python Table API
-的更多信息，可以参考[Flink Python Table API文档]({{ site.pythondocs_baseurl }}/api/python)。
+详细信息请参考 [Python Table API 教程]({% link
dev/python/getting-started/tutorial/table_api_tutorial.zh.md %})文档
