This is an automated email from the ASF dual-hosted git repository.
dianfu pushed a commit to branch release-1.10
in repository https://gitbox.apache.org/repos/asf/flink.git
commit afe7c8e8346e7c8ecc844d8405619eed1ee588ad
Author: Dian Fu <dia...@apache.org>
AuthorDate: Fri Mar 13 14:32:57 2020 +0800
[FLINK-16538][python][docs] Restructure Python Table API documentation
(#11375)
Adds an item "Python Table API" under "Table API & SQL" and move the
documentation about Python Table API under it.
---
docs/dev/table/config.md | 4 -
docs/dev/table/functions/udfs.md | 151 ++--------------------
docs/dev/table/functions/udfs.zh.md | 151 ++--------------------
docs/dev/table/python/dependency_management.md | 94 ++++++++++++++
docs/dev/table/python/dependency_management.zh.md | 94 ++++++++++++++
docs/dev/table/python/index.md | 35 +++++
docs/dev/table/python/index.zh.md | 35 +++++
docs/dev/table/python/installation.md | 44 +++++++
docs/dev/table/python/installation.zh.md | 44 +++++++
docs/dev/table/python/python_config.md | 32 +++++
docs/dev/table/python/python_config.zh.md | 32 +++++
docs/dev/table/python/python_udfs.md | 125 ++++++++++++++++++
docs/dev/table/python/python_udfs.zh.md | 125 ++++++++++++++++++
docs/ops/python_shell.md | 7 +-
docs/ops/python_shell.zh.md | 7 +-
docs/tutorials/python_table_api.md | 16 +--
docs/tutorials/python_table_api.zh.md | 12 +-
17 files changed, 682 insertions(+), 326 deletions(-)
diff --git a/docs/dev/table/config.md b/docs/dev/table/config.md
index a9e9b71..dd312d6 100644
--- a/docs/dev/table/config.md
+++ b/docs/dev/table/config.md
@@ -104,7 +104,3 @@ The following options can be used to tune the performance
of the query execution
The following options can be used to adjust the behavior of the query
optimizer to get a better execution plan.
{% include generated/optimizer_config_configuration.html %}
-
-### Python Options
-
-{% include generated/python_configuration.html %}
diff --git a/docs/dev/table/functions/udfs.md b/docs/dev/table/functions/udfs.md
index 523cd61..37cfd04 100644
--- a/docs/dev/table/functions/udfs.md
+++ b/docs/dev/table/functions/udfs.md
@@ -134,37 +134,12 @@ object TimestampModifier extends ScalarFunction {
</div>
<div data-lang="python" markdown="1">
-<span class="label label-info">Note</span> Python 3.5+ and apache-beam==2.15.0
are required to run the Python scalar function.
+In order to define a Python scalar function, one can extend the base class
`ScalarFunction` in `pyflink.table.udf` and implement an evaluation method. The
behavior of a Python scalar function is determined by the evaluation method
which is named `eval`.
-<span class="label label-info">Note</span> By default PyFlink uses the command
“python” to run the python udf workers. Before starting cluster, run the
following command to confirm that it meets the requirements:
-
-{% highlight bash %}
-$ python --version
-# the version printed here must be 3.5+
-$ python -m pip install apache-beam==2.15.0
-{% endhighlight %}
-
-<span class="label label-info">Note</span> Currently, Python UDF is supported
in Blink planner both under streaming and batch mode while is only supported
under streaming mode in old planner.
-
-It supports to use both Java/Scala scalar functions and Python scalar
functions in Python Table API and SQL. In order to define a Python scalar
function, one can extend the base class `ScalarFunction` in `pyflink.table.udf`
and implement an evaluation method. The behavior of a Python scalar function is
determined by the evaluation method. An evaluation method must be named `eval`.
Evaluation method can also support variable arguments, such as `eval(*args)`.
-
-The following example shows how to define your own Java and Python hash code
functions, register them in the TableEnvironment, and call them in a query.
Note that you can configure your scalar function via a constructor before it is
registered:
+The following example shows how to define your own Python hash code function,
register it in the TableEnvironment, and call it in a query. Note that you can
configure your scalar function via a constructor before it is registered:
{% highlight python %}
-'''
-Java code:
-
-// The Java class must have a public no-argument constructor and can be
founded in current Java classloader.
-public class HashCode extends ScalarFunction {
- private int factor = 12;
-
- public int eval(String s) {
- return s.hashCode() * factor;
- }
-}
-'''
-
-class PyHashCode(ScalarFunction):
+class HashCode(ScalarFunction):
def __init__(self):
self.factor = 12
@@ -173,128 +148,18 @@ class PyHashCode(ScalarFunction):
table_env = BatchTableEnvironment.create(env)
-# register the Java function
-table_env.register_java_function("hashCode", "my.java.function.HashCode")
-
# register the Python function
-table_env.register_function("py_hash_code", udf(PyHashCode(),
DataTypes.BIGINT(), DataTypes.BIGINT()))
+table_env.register_function("hash_code", udf(HashCode(), DataTypes.BIGINT(),
DataTypes.BIGINT()))
# use the function in Python Table API
-my_table.select("string, bigint, string.hashCode(), hashCode(string),
bigint.py_hash_code(), py_hash_code(bigint)")
+my_table.select("string, bigint, string.hash_code(), hash_code(string)")
# use the function in SQL API
-table_env.sql_query("SELECT string, bigint, hashCode(string),
py_hash_code(bigint) FROM MyTable")
-{% endhighlight %}
-
-There are many ways to define a Python scalar function besides extending the
base class `ScalarFunction`. The following example shows the different ways to
define a Python scalar function which takes two columns of bigint as input
parameters and returns the sum of them as the result.
-
-{% highlight python %}
-# option 1: extending the base class `ScalarFunction`
-class Add(ScalarFunction):
- def eval(self, i, j):
- return i + j
-
-add = udf(Add(), [DataTypes.BIGINT(), DataTypes.BIGINT()], DataTypes.BIGINT())
-
-# option 2: Python function
-@udf(input_types=[DataTypes.BIGINT(), DataTypes.BIGINT()],
result_type=DataTypes.BIGINT())
-def add(i, j):
- return i + j
-
-# option 3: lambda function
-add = udf(lambda i, j: i + j, [DataTypes.BIGINT(), DataTypes.BIGINT()],
DataTypes.BIGINT())
-
-# option 4: callable function
-class CallableAdd(object):
- def __call__(self, i, j):
- return i + j
-
-add = udf(CallableAdd(), [DataTypes.BIGINT(), DataTypes.BIGINT()],
DataTypes.BIGINT())
-
-# option 5: partial function
-def partial_add(i, j, k):
- return i + j + k
-
-add = udf(functools.partial(partial_add, k=1), [DataTypes.BIGINT(),
DataTypes.BIGINT()],
- DataTypes.BIGINT())
-
-# register the Python function
-table_env.register_function("add", add)
-# use the function in Python Table API
-my_table.select("add(a, b)")
-{% endhighlight %}
-
-If the python scalar function depends on third-party dependencies, you can
specify the dependencies with the following table APIs or through <a href="{{
site.baseurl }}/ops/cli.html#usage">command line</a> directly when submitting
the job.
-
-<table class="table table-bordered">
- <thead>
- <tr>
- <th class="text-left" style="width: 20%">APIs</th>
- <th class="text-left">Description</th>
- </tr>
- </thead>
-
- <tbody>
- <tr>
- <td><strong>add_python_file(file_path)</strong></td>
- <td>
- <p>Adds python file dependencies which could be python files, python
packages or local directories. They will be added to the PYTHONPATH of the
python UDF worker.</p>
-{% highlight python %}
-table_env.add_python_file(file_path)
-{% endhighlight %}
- </td>
- </tr>
- <tr>
- <td><strong>set_python_requirements(requirements_file_path,
requirements_cache_dir=None)</strong></td>
- <td>
- <p>Specifies a requirements.txt file which defines the third-party
dependencies. These dependencies will be installed to a temporary directory and
added to the PYTHONPATH of the python UDF worker. For the dependencies which
could not be accessed in the cluster, a directory which contains the
installation packages of these dependencies could be specified using the
parameter "requirements_cached_dir". It will be uploaded to the cluster to
support offline installation.</p>
-{% highlight python %}
-# commands executed in shell
-echo numpy==1.16.5 > requirements.txt
-pip download -d cached_dir -r requirements.txt --no-binary :all:
-
-# python code
-table_env.set_python_requirements("requirements.txt", "cached_dir")
-{% endhighlight %}
- <p>Please make sure the installation packages matches the platform of
the cluster and the python version used. These packages will be installed using
pip, so also make sure the version of Pip (version >= 7.1.0) and the version of
SetupTools (version >= 37.0.0).</p>
- </td>
- </tr>
- <tr>
- <td><strong>add_python_archive(archive_path,
target_dir=None)</strong></td>
- <td>
- <p>Adds a python archive file dependency. The file will be extracted
to the working directory of python UDF worker. If the parameter "target_dir" is
specified, the archive file will be extracted to a directory named
"target_dir". Otherwise, the archive file will be extracted to a directory with
the same name of the archive file.</p>
-{% highlight python %}
-# command executed in shell
-# assert the relative path of python interpreter is py_env/bin/python
-zip -r py_env.zip py_env
-
-# python code
-table_env.add_python_archive("py_env.zip")
-# or
-table_env.add_python_archive("py_env.zip", "myenv")
-
-# the files contained in the archive file can be accessed in UDF
-def my_udf():
- with open("myenv/py_env/data/data.txt") as f:
- ...
-{% endhighlight %}
- <p>Please make sure the uploaded python environment matches the
platform that the cluster is running on. Currently only zip-format is
supported. i.e. zip, jar, whl, egg, etc.</p>
- </td>
- </tr>
- <tr>
- <td><strong>set_python_executable(python_exec)</strong></td>
- <td>
- <p>Sets the path of the python interpreter which is used to execute
the python udf workers, e.g., "/usr/local/bin/python3".</p>
-{% highlight python %}
-table_env.add_python_archive("py_env.zip")
-table_env.get_config().set_python_executable("py_env.zip/py_env/bin/python")
+table_env.sql_query("SELECT string, bigint, hash_code(bigint) FROM MyTable")
{% endhighlight %}
- <p>Please make sure that the specified environment matches the
platform that the cluster is running on.</p>
- </td>
- </tr>
- </tbody>
-</table>
+There are many ways to define a Python scalar function besides extending the
base class `ScalarFunction`.
+Please refer to the [Python Scalar Function]({{ site.baseurl
}}/dev/table/python/python_udfs.html#scalar-functions) documentation for more
details.
</div>
</div>
diff --git a/docs/dev/table/functions/udfs.zh.md
b/docs/dev/table/functions/udfs.zh.md
index c7cd78e..c35f56a 100644
--- a/docs/dev/table/functions/udfs.zh.md
+++ b/docs/dev/table/functions/udfs.zh.md
@@ -134,37 +134,12 @@ object TimestampModifier extends ScalarFunction {
</div>
<div data-lang="python" markdown="1">
-<span class="label label-info">Note</span> Python 3.5+ and apache-beam==2.15.0
are required to run the Python scalar function.
+In order to define a Python scalar function, one can extend the base class
`ScalarFunction` in `pyflink.table.udf` and implement an evaluation method. The
behavior of a Python scalar function is determined by the evaluation method
which is named `eval`.
-<span class="label label-info">Note</span> By default PyFlink uses the command
“python” to run the python udf workers. Before starting cluster, run the
following command to confirm that it meets the requirements:
-
-{% highlight bash %}
-$ python --version
-# the version printed here must be 3.5+
-$ python -m pip install apache-beam==2.15.0
-{% endhighlight %}
-
-<span class="label label-info">Note</span> Currently, Python UDF is supported
in Blink planner both under streaming and batch mode while is only supported
under streaming mode in old planner.
-
-It supports to use both Java/Scala scalar functions and Python scalar
functions in Python Table API and SQL. In order to define a Python scalar
function, one can extend the base class `ScalarFunction` in `pyflink.table.udf`
and implement an evaluation method. The behavior of a Python scalar function is
determined by the evaluation method. An evaluation method must be named `eval`.
Evaluation method can also support variable arguments, such as `eval(*args)`.
-
-The following example shows how to define your own Java and Python hash code
functions, register them in the TableEnvironment, and call them in a query.
Note that you can configure your scalar function via a constructor before it is
registered:
+The following example shows how to define your own Python hash code function,
register it in the TableEnvironment, and call it in a query. Note that you can
configure your scalar function via a constructor before it is registered:
{% highlight python %}
-'''
-Java code:
-
-// The Java class must have a public no-argument constructor and can be
founded in current Java classloader.
-public class HashCode extends ScalarFunction {
- private int factor = 12;
-
- public int eval(String s) {
- return s.hashCode() * factor;
- }
-}
-'''
-
-class PyHashCode(ScalarFunction):
+class HashCode(ScalarFunction):
def __init__(self):
self.factor = 12
@@ -173,128 +148,18 @@ class PyHashCode(ScalarFunction):
table_env = BatchTableEnvironment.create(env)
-# register the Java function
-table_env.register_java_function("hashCode", "my.java.function.HashCode")
-
# register the Python function
-table_env.register_function("py_hash_code", udf(PyHashCode(),
DataTypes.BIGINT(), DataTypes.BIGINT()))
+table_env.register_function("hash_code", udf(HashCode(), DataTypes.BIGINT(),
DataTypes.BIGINT()))
# use the function in Python Table API
-my_table.select("string, bigint, string.hashCode(), hashCode(string),
bigint.py_hash_code(), py_hash_code(bigint)")
+my_table.select("string, bigint, string.hash_code(), hash_code(string)")
# use the function in SQL API
-table_env.sql_query("SELECT string, bigint, hashCode(string),
py_hash_code(bigint) FROM MyTable")
-{% endhighlight %}
-
-There are many ways to define a Python scalar function besides extending the
base class `ScalarFunction`. The following example shows the different ways to
define a Python scalar function which takes two columns of bigint as input
parameters and returns the sum of them as the result.
-
-{% highlight python %}
-# option 1: extending the base class `ScalarFunction`
-class Add(ScalarFunction):
- def eval(self, i, j):
- return i + j
-
-add = udf(Add(), [DataTypes.BIGINT(), DataTypes.BIGINT()], DataTypes.BIGINT())
-
-# option 2: Python function
-@udf(input_types=[DataTypes.BIGINT(), DataTypes.BIGINT()],
result_type=DataTypes.BIGINT())
-def add(i, j):
- return i + j
-
-# option 3: lambda function
-add = udf(lambda i, j: i + j, [DataTypes.BIGINT(), DataTypes.BIGINT()],
DataTypes.BIGINT())
-
-# option 4: callable function
-class CallableAdd(object):
- def __call__(self, i, j):
- return i + j
-
-add = udf(CallableAdd(), [DataTypes.BIGINT(), DataTypes.BIGINT()],
DataTypes.BIGINT())
-
-# option 5: partial function
-def partial_add(i, j, k):
- return i + j + k
-
-add = udf(functools.partial(partial_add, k=1), [DataTypes.BIGINT(),
DataTypes.BIGINT()],
- DataTypes.BIGINT())
-
-# register the Python function
-table_env.register_function("add", add)
-# use the function in Python Table API
-my_table.select("add(a, b)")
-{% endhighlight %}
-
-If the python scalar function depends on third-party dependencies, you can
specify the dependencies with the following table APIs or through <a href="{{
site.baseurl }}/ops/cli.html#usage">command line</a> directly when submitting
the job.
-
-<table class="table table-bordered">
- <thead>
- <tr>
- <th class="text-left" style="width: 20%">APIs</th>
- <th class="text-left">Description</th>
- </tr>
- </thead>
-
- <tbody>
- <tr>
- <td><strong>add_python_file(file_path)</strong></td>
- <td>
- <p>Adds python file dependencies which could be python files, python
packages or local directories. They will be added to the PYTHONPATH of the
python UDF worker.</p>
-{% highlight python %}
-table_env.add_python_file(file_path)
-{% endhighlight %}
- </td>
- </tr>
- <tr>
- <td><strong>set_python_requirements(requirements_file_path,
requirements_cache_dir=None)</strong></td>
- <td>
- <p>Specifies a requirements.txt file which defines the third-party
dependencies. These dependencies will be installed to a temporary directory and
added to the PYTHONPATH of the python UDF worker. For the dependencies which
could not be accessed in the cluster, a directory which contains the
installation packages of these dependencies could be specified using the
parameter "requirements_cached_dir". It will be uploaded to the cluster to
support offline installation.</p>
-{% highlight python %}
-# commands executed in shell
-echo numpy==1.16.5 > requirements.txt
-pip download -d cached_dir -r requirements.txt --no-binary :all:
-
-# python code
-table_env.set_python_requirements("requirements.txt", "cached_dir")
-{% endhighlight %}
- <p>Please make sure the installation packages matches the platform of
the cluster and the python version used. These packages will be installed using
pip, so also make sure the version of Pip (version >= 7.1.0) and the version of
SetupTools (version >= 37.0.0).</p>
- </td>
- </tr>
- <tr>
- <td><strong>add_python_archive(archive_path,
target_dir=None)</strong></td>
- <td>
- <p>Adds a python archive file dependency. The file will be extracted
to the working directory of python UDF worker. If the parameter "target_dir" is
specified, the archive file will be extracted to a directory named
"target_dir". Otherwise, the archive file will be extracted to a directory with
the same name of the archive file.</p>
-{% highlight python %}
-# command executed in shell
-# assert the relative path of python interpreter is py_env/bin/python
-zip -r py_env.zip py_env
-
-# python code
-table_env.add_python_archive("py_env.zip")
-# or
-table_env.add_python_archive("py_env.zip", "myenv")
-
-# the files contained in the archive file can be accessed in UDF
-def my_udf():
- with open("myenv/py_env/data/data.txt") as f:
- ...
-{% endhighlight %}
- <p>Please make sure the uploaded python environment matches the
platform that the cluster is running on. Currently only zip-format is
supported. i.e. zip, jar, whl, egg, etc.</p>
- </td>
- </tr>
- <tr>
- <td><strong>set_python_executable(python_exec)</strong></td>
- <td>
- <p>Sets the path of the python interpreter which is used to execute
the python udf workers, e.g., "/usr/local/bin/python3".</p>
-{% highlight python %}
-table_env.add_python_archive("py_env.zip")
-table_env.get_config().set_python_executable("py_env.zip/py_env/bin/python")
+table_env.sql_query("SELECT string, bigint, hash_code(bigint) FROM MyTable")
{% endhighlight %}
- <p>Please make sure that the specified environment matches the
platform that the cluster is running on.</p>
- </td>
- </tr>
- </tbody>
-</table>
+There are many ways to define a Python scalar function besides extending the
base class `ScalarFunction`.
+Please refer to the [Python Scalar Function]({{ site.baseurl
}}/zh/dev/table/python/python_udfs.html#scalar-functions) documentation for
more details.
</div>
</div>
diff --git a/docs/dev/table/python/dependency_management.md
b/docs/dev/table/python/dependency_management.md
new file mode 100644
index 0000000..adb8cbe
--- /dev/null
+++ b/docs/dev/table/python/dependency_management.md
@@ -0,0 +1,94 @@
+---
+title: "Dependency Management"
+nav-parent_id: python_tableapi
+nav-pos: 100
+---
+<!--
+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.
+-->
+
+If third-party dependencies are used, you can specify the dependencies with
the following Python Table APIs or through <a href="{{ site.baseurl
}}/ops/cli.html#usage">command line arguments</a> directly when submitting the
job.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 20%">APIs</th>
+ <th class="text-left">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td><strong>add_python_file(file_path)</strong></td>
+ <td>
+ <p>Adds python file dependencies which could be python files, python
packages or local directories. They will be added to the PYTHONPATH of the
python UDF worker.</p>
+{% highlight python %}
+table_env.add_python_file(file_path)
+{% endhighlight %}
+ </td>
+ </tr>
+ <tr>
+ <td><strong>set_python_requirements(requirements_file_path,
requirements_cache_dir=None)</strong></td>
+ <td>
+ <p>Specifies a requirements.txt file which defines the third-party
dependencies. These dependencies will be installed to a temporary directory and
added to the PYTHONPATH of the python UDF worker. For the dependencies which
could not be accessed in the cluster, a directory which contains the
installation packages of these dependencies could be specified using the
parameter "requirements_cached_dir". It will be uploaded to the cluster to
support offline installation.</p>
+{% highlight python %}
+# commands executed in shell
+echo numpy==1.16.5 > requirements.txt
+pip download -d cached_dir -r requirements.txt --no-binary :all:
+
+# python code
+table_env.set_python_requirements("requirements.txt", "cached_dir")
+{% endhighlight %}
+ <p>Please make sure the installation packages matches the platform of
the cluster and the python version used. These packages will be installed using
pip, so also make sure the version of Pip (version >= 7.1.0) and the version of
SetupTools (version >= 37.0.0).</p>
+ </td>
+ </tr>
+ <tr>
+ <td><strong>add_python_archive(archive_path,
target_dir=None)</strong></td>
+ <td>
+ <p>Adds a python archive file dependency. The file will be extracted
to the working directory of python UDF worker. If the parameter "target_dir" is
specified, the archive file will be extracted to a directory named
"target_dir". Otherwise, the archive file will be extracted to a directory with
the same name of the archive file.</p>
+{% highlight python %}
+# command executed in shell
+# assert the relative path of python interpreter is py_env/bin/python
+zip -r py_env.zip py_env
+
+# python code
+table_env.add_python_archive("py_env.zip")
+# or
+table_env.add_python_archive("py_env.zip", "myenv")
+
+# the files contained in the archive file can be accessed in UDF
+def my_udf():
+ with open("myenv/py_env/data/data.txt") as f:
+ ...
+{% endhighlight %}
+ <p>Please make sure the uploaded python environment matches the
platform that the cluster is running on. Currently only zip-format is
supported. i.e. zip, jar, whl, egg, etc.</p>
+ </td>
+ </tr>
+ <tr>
+ <td><strong>set_python_executable(python_exec)</strong></td>
+ <td>
+ <p>Sets the path of the python interpreter which is used to execute
the python udf workers, e.g., "/usr/local/bin/python3".</p>
+{% highlight python %}
+table_env.add_python_archive("py_env.zip")
+table_env.get_config().set_python_executable("py_env.zip/py_env/bin/python")
+{% endhighlight %}
+ <p>Please make sure that the specified environment matches the
platform that the cluster is running on.</p>
+ </td>
+ </tr>
+ </tbody>
+</table>
diff --git a/docs/dev/table/python/dependency_management.zh.md
b/docs/dev/table/python/dependency_management.zh.md
new file mode 100644
index 0000000..5aaf771
--- /dev/null
+++ b/docs/dev/table/python/dependency_management.zh.md
@@ -0,0 +1,94 @@
+---
+title: "依赖管理"
+nav-parent_id: python_tableapi
+nav-pos: 100
+---
+<!--
+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.
+-->
+
+If third-party dependencies are used, you can specify the dependencies with
the following Python Table APIs or through <a href="{{ site.baseurl
}}/zh/ops/cli.html#usage">command line arguments</a> directly when submitting
the job.
+
+<table class="table table-bordered">
+ <thead>
+ <tr>
+ <th class="text-left" style="width: 20%">APIs</th>
+ <th class="text-left">Description</th>
+ </tr>
+ </thead>
+
+ <tbody>
+ <tr>
+ <td><strong>add_python_file(file_path)</strong></td>
+ <td>
+ <p>Adds python file dependencies which could be python files, python
packages or local directories. They will be added to the PYTHONPATH of the
python UDF worker.</p>
+{% highlight python %}
+table_env.add_python_file(file_path)
+{% endhighlight %}
+ </td>
+ </tr>
+ <tr>
+ <td><strong>set_python_requirements(requirements_file_path,
requirements_cache_dir=None)</strong></td>
+ <td>
+ <p>Specifies a requirements.txt file which defines the third-party
dependencies. These dependencies will be installed to a temporary directory and
added to the PYTHONPATH of the python UDF worker. For the dependencies which
could not be accessed in the cluster, a directory which contains the
installation packages of these dependencies could be specified using the
parameter "requirements_cached_dir". It will be uploaded to the cluster to
support offline installation.</p>
+{% highlight python %}
+# commands executed in shell
+echo numpy==1.16.5 > requirements.txt
+pip download -d cached_dir -r requirements.txt --no-binary :all:
+
+# python code
+table_env.set_python_requirements("requirements.txt", "cached_dir")
+{% endhighlight %}
+ <p>Please make sure the installation packages matches the platform of
the cluster and the python version used. These packages will be installed using
pip, so also make sure the version of Pip (version >= 7.1.0) and the version of
SetupTools (version >= 37.0.0).</p>
+ </td>
+ </tr>
+ <tr>
+ <td><strong>add_python_archive(archive_path,
target_dir=None)</strong></td>
+ <td>
+ <p>Adds a python archive file dependency. The file will be extracted
to the working directory of python UDF worker. If the parameter "target_dir" is
specified, the archive file will be extracted to a directory named
"target_dir". Otherwise, the archive file will be extracted to a directory with
the same name of the archive file.</p>
+{% highlight python %}
+# command executed in shell
+# assert the relative path of python interpreter is py_env/bin/python
+zip -r py_env.zip py_env
+
+# python code
+table_env.add_python_archive("py_env.zip")
+# or
+table_env.add_python_archive("py_env.zip", "myenv")
+
+# the files contained in the archive file can be accessed in UDF
+def my_udf():
+ with open("myenv/py_env/data/data.txt") as f:
+ ...
+{% endhighlight %}
+ <p>Please make sure the uploaded python environment matches the
platform that the cluster is running on. Currently only zip-format is
supported. i.e. zip, jar, whl, egg, etc.</p>
+ </td>
+ </tr>
+ <tr>
+ <td><strong>set_python_executable(python_exec)</strong></td>
+ <td>
+ <p>Sets the path of the python interpreter which is used to execute
the python udf workers, e.g., "/usr/local/bin/python3".</p>
+{% highlight python %}
+table_env.add_python_archive("py_env.zip")
+table_env.get_config().set_python_executable("py_env.zip/py_env/bin/python")
+{% endhighlight %}
+ <p>Please make sure that the specified environment matches the
platform that the cluster is running on.</p>
+ </td>
+ </tr>
+ </tbody>
+</table>
diff --git a/docs/dev/table/python/index.md b/docs/dev/table/python/index.md
new file mode 100644
index 0000000..4163374
--- /dev/null
+++ b/docs/dev/table/python/index.md
@@ -0,0 +1,35 @@
+---
+title: "Python Table API"
+nav-id: python_tableapi
+nav-parent_id: tableapi
+nav-pos: 100
+nav-show_overview: true
+---
+<!--
+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.
+-->
+
+Python Table API allows users to develop [Table API]({{ site.baseurl
}}/dev/table/tableApi.html) programs using the Python language.
+Apache Flink has provided Python Table API support since 1.9.0.
+
+## Where to go next?
+
+- [Installation]({{ site.baseurl }}/dev/table/python/installation.html):
Introduction of how to set up the Python Table API execution environment.
+- [User-defined Functions]({{ site.baseurl
}}/dev/table/python/python_udfs.html): Explanation of how to define Python
user-defined functions.
+- [Dependency Management]({{ site.baseurl
}}/dev/table/python/dependency_management.html): Specification of how to use
third-part dependencies in a Python Table API program.
+- [Configuration]({{ site.baseurl }}/dev/table/python/python_config.html):
Description of the config options available for Python Table API programs.
diff --git a/docs/dev/table/python/index.zh.md
b/docs/dev/table/python/index.zh.md
new file mode 100644
index 0000000..fa1323c
--- /dev/null
+++ b/docs/dev/table/python/index.zh.md
@@ -0,0 +1,35 @@
+---
+title: "Python Table API"
+nav-id: python_tableapi
+nav-parent_id: tableapi
+nav-pos: 100
+nav-show_overview: true
+---
+<!--
+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.
+-->
+
+Python Table API allows users to develop [Table API]({{ site.baseurl
}}/zh/dev/table/tableApi.html) programs using the Python language.
+Apache Flink has provided Python Table API support since 1.9.0.
+
+## Where to go next?
+
+- [环境安装]({{ site.baseurl }}/zh/dev/table/python/installation.html):
Introduction of how to set up the Python Table API execution environment.
+- [自定义函数]({{ site.baseurl }}/zh/dev/table/python/python_udfs.html):
Explanation of how to define Python user-defined functions.
+- [依赖管理]({{ site.baseurl }}/zh/dev/table/python/dependency_management.html):
Specification of how to use third-part dependencies in a Python Table API
program.
+- [配置]({{ site.baseurl }}/zh/dev/table/python/python_config.html): Description
of the config options available for Python Table API programs.
diff --git a/docs/dev/table/python/installation.md
b/docs/dev/table/python/installation.md
new file mode 100644
index 0000000..0dffb77
--- /dev/null
+++ b/docs/dev/table/python/installation.md
@@ -0,0 +1,44 @@
+---
+title: "Installation"
+nav-parent_id: python_tableapi
+nav-pos: 10
+---
+<!--
+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.
+-->
+
+* This will be replaced by the TOC
+{:toc}
+
+## Environment Requirements
+<span class="label label-info">Note</span> Python 3.5+ is required for
PyFlink. Please run the following command to make sure that it meets the
requirements:
+
+{% highlight bash %}
+$ python --version
+# the version printed here must be 3.5+
+{% endhighlight %}
+
+## Installation of PyFlink
+
+PyFlink has already been deployed to PyPi and can be installed as following:
+
+{% highlight bash %}
+$ python -m pip install apache-flink
+{% endhighlight %}
+
+You can also build PyFlink from source by following the [development guide]({{
site.baseurl }}/flinkDev/building.html#build-pyflink).
diff --git a/docs/dev/table/python/installation.zh.md
b/docs/dev/table/python/installation.zh.md
new file mode 100644
index 0000000..e07660a
--- /dev/null
+++ b/docs/dev/table/python/installation.zh.md
@@ -0,0 +1,44 @@
+---
+title: "环境安装"
+nav-parent_id: python_tableapi
+nav-pos: 10
+---
+<!--
+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.
+-->
+
+* This will be replaced by the TOC
+{:toc}
+
+## Environment Requirements
+<span class="label label-info">Note</span> Python 3.5+ is required for
PyFlink. Please run the following command to make sure that it meets the
requirements:
+
+{% highlight bash %}
+$ python --version
+# the version printed here must be 3.5+
+{% endhighlight %}
+
+## Installation of PyFlink
+
+PyFlink has already been deployed to PyPi and can be installed as following:
+
+{% highlight bash %}
+$ python -m pip install apache-flink
+{% endhighlight %}
+
+You can also build PyFlink from source by following the [development guide]({{
site.baseurl }}/zh/flinkDev/building.html#build-pyflink).
diff --git a/docs/dev/table/python/python_config.md
b/docs/dev/table/python/python_config.md
new file mode 100644
index 0000000..e25fbf5
--- /dev/null
+++ b/docs/dev/table/python/python_config.md
@@ -0,0 +1,32 @@
+---
+title: "Configuration"
+nav-parent_id: python_tableapi
+nav-pos: 120
+---
+<!--
+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.
+-->
+
+Depending on the requirements of a Python Table API program, it might be
necessary to adjust certain parameters for optimization.
+All the config options available for Java/Scala Table API program could also
be used in the Python Table API program.
+You could refer to the [Table API Configuration]({{ site.baseurl
}}/dev/table/config.html) for more details on all the available config options
for Java/Scala Table API programs.
+It has also provided examples on how to set the config options in a Table API
program.
+
+## Python Options
+
+{% include generated/python_configuration.html %}
diff --git a/docs/dev/table/python/python_config.zh.md
b/docs/dev/table/python/python_config.zh.md
new file mode 100644
index 0000000..fa4f59d
--- /dev/null
+++ b/docs/dev/table/python/python_config.zh.md
@@ -0,0 +1,32 @@
+---
+title: "配置"
+nav-parent_id: python_tableapi
+nav-pos: 120
+---
+<!--
+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.
+-->
+
+Depending on the requirements of a Python Table API program, it might be
necessary to adjust certain parameters for optimization.
+All the config options available for Java/Scala Table API program could also
be used in the Python Table API program.
+You could refer to the [Table API Configuration]({{ site.baseurl
}}/zh/dev/table/config.html) for more details on all the available config
options for Java/Scala Table API programs.
+It has also provided examples on how to set the config options in a Table API
program.
+
+## Python Options
+
+{% include generated/python_configuration.html %}
diff --git a/docs/dev/table/python/python_udfs.md
b/docs/dev/table/python/python_udfs.md
new file mode 100644
index 0000000..44a30ff
--- /dev/null
+++ b/docs/dev/table/python/python_udfs.md
@@ -0,0 +1,125 @@
+---
+title: "User-defined Functions"
+nav-parent_id: python_tableapi
+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.
+-->
+
+User-defined functions are important features, because they significantly
extend the expressiveness of Python Table API programs.
+
+* This will be replaced by the TOC
+{:toc}
+
+## Scalar Functions
+It supports to use Python scalar functions in Python Table API programs. In
order to define a Python scalar function,
+one can extend the base class `ScalarFunction` in `pyflink.table.udf` and
implement an evaluation method.
+The behavior of a Python scalar function is defined by the evaluation method
which is named `eval`.
+The evaluation method can support variable arguments, such as `eval(*args)`.
+
+The following example shows how to define your own Python hash code function,
register it in the TableEnvironment, and call it in a query.
+Note that you can configure your scalar function via a constructor before it
is registered:
+
+{% highlight python %}
+class HashCode(ScalarFunction):
+ def __init__(self):
+ self.factor = 12
+
+ def eval(self, s):
+ return hash(s) * self.factor
+
+table_env = BatchTableEnvironment.create(env)
+
+# register the Python function
+table_env.register_function("hash_code", udf(HashCode(), DataTypes.BIGINT(),
DataTypes.BIGINT()))
+
+# use the Python function in Python Table API
+my_table.select("string, bigint, bigint.hash_code(), hash_code(bigint)")
+
+# use the Python function in SQL API
+table_env.sql_query("SELECT string, bigint, hash_code(bigint) FROM MyTable")
+{% endhighlight %}
+
+It also supports to use Java/Scala scalar functions in Python Table API
programs.
+
+{% highlight python %}
+'''
+Java code:
+
+// The Java class must have a public no-argument constructor and can be
founded in current Java classloader.
+public class HashCode extends ScalarFunction {
+ private int factor = 12;
+
+ public int eval(String s) {
+ return s.hashCode() * factor;
+ }
+}
+'''
+
+table_env = BatchTableEnvironment.create(env)
+
+# register the Java function
+table_env.register_java_function("hash_code", "my.java.function.HashCode")
+
+# use the Java function in Python Table API
+my_table.select("string.hash_code(), hash_code(string)")
+
+# use the Java function in SQL API
+table_env.sql_query("SELECT string, bigint, hash_code(string) FROM MyTable")
+{% endhighlight %}
+
+There are many ways to define a Python scalar function besides extending the
base class `ScalarFunction`.
+The following examples show the different ways to define a Python scalar
function which takes two columns of
+bigint as the input parameters and returns the sum of them as the result.
+
+{% highlight python %}
+# option 1: extending the base class `ScalarFunction`
+class Add(ScalarFunction):
+ def eval(self, i, j):
+ return i + j
+
+add = udf(Add(), [DataTypes.BIGINT(), DataTypes.BIGINT()], DataTypes.BIGINT())
+
+# option 2: Python function
+@udf(input_types=[DataTypes.BIGINT(), DataTypes.BIGINT()],
result_type=DataTypes.BIGINT())
+def add(i, j):
+ return i + j
+
+# option 3: lambda function
+add = udf(lambda i, j: i + j, [DataTypes.BIGINT(), DataTypes.BIGINT()],
DataTypes.BIGINT())
+
+# option 4: callable function
+class CallableAdd(object):
+ def __call__(self, i, j):
+ return i + j
+
+add = udf(CallableAdd(), [DataTypes.BIGINT(), DataTypes.BIGINT()],
DataTypes.BIGINT())
+
+# option 5: partial function
+def partial_add(i, j, k):
+ return i + j + k
+
+add = udf(functools.partial(partial_add, k=1), [DataTypes.BIGINT(),
DataTypes.BIGINT()],
+ DataTypes.BIGINT())
+
+# register the Python function
+table_env.register_function("add", add)
+# use the function in Python Table API
+my_table.select("add(a, b)")
+{% endhighlight %}
diff --git a/docs/dev/table/python/python_udfs.zh.md
b/docs/dev/table/python/python_udfs.zh.md
new file mode 100644
index 0000000..7acba1f
--- /dev/null
+++ b/docs/dev/table/python/python_udfs.zh.md
@@ -0,0 +1,125 @@
+---
+title: "自定义函数"
+nav-parent_id: python_tableapi
+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.
+-->
+
+User-defined functions are important features, because they significantly
extend the expressiveness of Python Table API programs.
+
+* This will be replaced by the TOC
+{:toc}
+
+## Scalar Functions
+It supports to use Python scalar functions in Python Table API programs. In
order to define a Python scalar function,
+one can extend the base class `ScalarFunction` in `pyflink.table.udf` and
implement an evaluation method.
+The behavior of a Python scalar function is defined by the evaluation method
which is named `eval`.
+The evaluation method can support variable arguments, such as `eval(*args)`.
+
+The following example shows how to define your own Python hash code function,
register it in the TableEnvironment, and call it in a query.
+Note that you can configure your scalar function via a constructor before it
is registered:
+
+{% highlight python %}
+class HashCode(ScalarFunction):
+ def __init__(self):
+ self.factor = 12
+
+ def eval(self, s):
+ return hash(s) * self.factor
+
+table_env = BatchTableEnvironment.create(env)
+
+# register the Python function
+table_env.register_function("hash_code", udf(HashCode(), DataTypes.BIGINT(),
DataTypes.BIGINT()))
+
+# use the Python function in Python Table API
+my_table.select("string, bigint, bigint.hash_code(), hash_code(bigint)")
+
+# use the Python function in SQL API
+table_env.sql_query("SELECT string, bigint, hash_code(bigint) FROM MyTable")
+{% endhighlight %}
+
+It also supports to use Java/Scala scalar functions in Python Table API
programs.
+
+{% highlight python %}
+'''
+Java code:
+
+// The Java class must have a public no-argument constructor and can be
founded in current Java classloader.
+public class HashCode extends ScalarFunction {
+ private int factor = 12;
+
+ public int eval(String s) {
+ return s.hashCode() * factor;
+ }
+}
+'''
+
+table_env = BatchTableEnvironment.create(env)
+
+# register the Java function
+table_env.register_java_function("hash_code", "my.java.function.HashCode")
+
+# use the Java function in Python Table API
+my_table.select("string.hash_code(), hash_code(string)")
+
+# use the Java function in SQL API
+table_env.sql_query("SELECT string, bigint, hash_code(string) FROM MyTable")
+{% endhighlight %}
+
+There are many ways to define a Python scalar function besides extending the
base class `ScalarFunction`.
+The following examples show the different ways to define a Python scalar
function which takes two columns of
+bigint as the input parameters and returns the sum of them as the result.
+
+{% highlight python %}
+# option 1: extending the base class `ScalarFunction`
+class Add(ScalarFunction):
+ def eval(self, i, j):
+ return i + j
+
+add = udf(Add(), [DataTypes.BIGINT(), DataTypes.BIGINT()], DataTypes.BIGINT())
+
+# option 2: Python function
+@udf(input_types=[DataTypes.BIGINT(), DataTypes.BIGINT()],
result_type=DataTypes.BIGINT())
+def add(i, j):
+ return i + j
+
+# option 3: lambda function
+add = udf(lambda i, j: i + j, [DataTypes.BIGINT(), DataTypes.BIGINT()],
DataTypes.BIGINT())
+
+# option 4: callable function
+class CallableAdd(object):
+ def __call__(self, i, j):
+ return i + j
+
+add = udf(CallableAdd(), [DataTypes.BIGINT(), DataTypes.BIGINT()],
DataTypes.BIGINT())
+
+# option 5: partial function
+def partial_add(i, j, k):
+ return i + j + k
+
+add = udf(functools.partial(partial_add, k=1), [DataTypes.BIGINT(),
DataTypes.BIGINT()],
+ DataTypes.BIGINT())
+
+# register the Python function
+table_env.register_function("add", add)
+# use the function in Python Table API
+my_table.select("add(a, b)")
+{% endhighlight %}
diff --git a/docs/ops/python_shell.md b/docs/ops/python_shell.md
index f561a1c..259d3d2 100644
--- a/docs/ops/python_shell.md
+++ b/docs/ops/python_shell.md
@@ -27,12 +27,7 @@ It can be used in a local setup as well as in a cluster
setup.
See the [local setup page](../getting-started/tutorials/local_setup.html) for
more information about how to setup a local Flink.
You can also [build a local setup from source](../flinkDev/building.html).
-<span class="label label-info">Note</span> The Python Shell will run the
command “python”. Please run the following command to confirm that the command
“python” in current environment points to Python 3.5+:
-
-{% highlight bash %}
-$ python --version
-# the version printed here must be 3.5+
-{% endhighlight %}
+<span class="label label-info">Note</span> The Python Shell will run the
command “python”. <span class="label label-info">Note</span> The Python Shell
will run the command “python”. Please refer to the Python Table API
[installation guide]({{ site.baseurl }}/dev/table/python/installation.html) on
how to set up the Python execution environments.
To use the shell with an integrated Flink cluster, you can simply install
PyFlink with PyPi and execute the shell directly:
diff --git a/docs/ops/python_shell.zh.md b/docs/ops/python_shell.zh.md
index 0150e30..cae6a1d 100644
--- a/docs/ops/python_shell.zh.md
+++ b/docs/ops/python_shell.zh.md
@@ -27,12 +27,7 @@ Flink附带了一个集成的交互式Python Shell。
本地安装Flink，请看[本地安装](../getting-started/tutorials/local_setup.html)页面。
您也可以从源码安装Flink，请看[从源码构建 Flink](../flinkDev/building.html)页面。
-<span class="label label-info">注意</span> Python
Shell会调用“python”命令。请执行以下命令以确认当前环境下的指令“python”指向Python 3.5及以上版本：
-
-{% highlight bash %}
-$ python --version
-# the version printed here must be 3.5+
-{% endhighlight %}
+<span class="label label-info">注意</span> Python
Shell会调用“python”命令。关于Python执行环境的要求，请参考Python Table API[环境安装]({{ site.baseurl
}}/dev/dev/table/python/installation.html)。
你可以通过PyPi安装PyFlink，然后使用Python Shell:
diff --git a/docs/tutorials/python_table_api.md
b/docs/tutorials/python_table_api.md
index b7f0d1d..91fadb7 100644
--- a/docs/tutorials/python_table_api.md
+++ b/docs/tutorials/python_table_api.md
@@ -25,26 +25,14 @@ under the License.
This walkthrough will quickly get you started building a pure Python Flink
project.
-<span class="label label-info">Note</span> Python 3.5 or higher is required to
run PyFlink. Run the following command to confirm that the command “python” in
current environment points to Python 3.5+:
-
-{% highlight bash %}
-$ python --version
-# the version printed here must be 3.5+
-{% endhighlight %}
+Please refer to the Python Table API [installation guide]({{ site.baseurl
}}/dev/table/python/installation.html) 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.
-PyFlink is available via PyPi and can be easily installed using `pip`.
-
-{% highlight bash %}
-$ python -m pip install apache-flink
-{% endhighlight %}
-
-You can also build PyFlink from source by following the [development guide]({{
site.baseurl }}/flinkDev/building.html#build-pyflink).
+You can begin by creating a Python project and installing the PyFlink package
following the [installation guide]({{ site.baseurl
}}/dev/table/python/installation.html#installation-of-pyflink).
## Writing a Flink Python Table API Program
diff --git a/docs/tutorials/python_table_api.zh.md
b/docs/tutorials/python_table_api.zh.md
index 89be567..9a5d586 100644
--- a/docs/tutorials/python_table_api.zh.md
+++ b/docs/tutorials/python_table_api.zh.md
@@ -28,19 +28,11 @@ under the License.
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。
-<span class="label label-info">注意</span> PyFlink的运行需要Python 3.5及以上版本。
-
-执行以下命令以确认当前环境下的指令“python”指向Python 3.5及以上版本：
-
-{% highlight bash %}
-$ python --version
-# the version printed here must be 3.5+
-{% endhighlight %}
+关于Python执行环境的要求，请参考Python Table API[环境安装]({{ site.baseurl
}}/dev/dev/table/python/installation.html)。
## 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。之后执行命令`python -m pip install
apache-flink`从PyPI下载安装PyFlink包。
-如果您想从源码安装，请参考[构建PyFlink]({{ site.baseurl
}}/zh/flinkDev/building.html#build-pyflink)了解详细信息。
+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]({{ site.baseurl
}}/zh/dev/table/python/installation.html#installation-of-pyflink)了解详细信息。
## 编写一个Flink Python Table API程序
