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=========
Debugging
=========

This page describes how to debug in PyFlink.

Logging Infos
=============

Client Side Logging
-------------------

You can log contextual and debug information via ``print`` or standard Python logging modules in
PyFlink jobs in places outside Python UDFs. The logging messages will be printed in the log files
of the client during job submission.

.. code-block:: python

    from pyflink.table import EnvironmentSettings, TableEnvironment

    # create a TableEnvironment
    env_settings = EnvironmentSettings.in_streaming_mode()
    table_env = TableEnvironment.create(env_settings)

    table = table_env.from_elements([(1, 'Hi'), (2, 'Hello')])

    # use logging modules
    import logging
    logging.warning(table.get_schema())

    # use print function
    print(table.get_schema())

**Note:** The default logging level at client side is ``WARNING`` and so only messages with logging
level ``WARNING`` or above will appear in the log files of the client.

Server Side Logging
-------------------

You can log contextual and debug information via ``print`` or standard Python logging modules in Python UDFs.
The logging messages will be printed in the log files of the ``TaskManagers`` during job execution.

.. code-block:: python

    from pyflink.table import DataTypes
    from pyflink.table.udf import udf

    import logging

    @udf(result_type=DataTypes.BIGINT())
    def add(i, j):
        # use logging modules
        logging.info("debug")
        # use print function
        print('debug')
        return i + j

**Note:** The default logging level at server side is ``INFO`` and so only messages with logging level ``INFO`` or above
will appear in the log files of the ``TaskManagers``.

Accessing Logs
==============

If environment variable ``FLINK_HOME`` is set, logs will be written in the log directory under ``FLINK_HOME``.
Otherwise, logs will be placed in the directory of the PyFlink module. You can execute the following command to find
the log directory of the PyFlink module:

.. code-block:: bash

    $ python -c "import pyflink;import os;print(os.path.dirname(os.path.abspath(pyflink.__file__))+'/log')"

Debugging Python UDFs
=====================

Local Debug
-----------

You can debug your python functions directly in IDEs such as PyCharm.

Remote Debug
------------

You can make use of the `pydevd_pycharm <https://pypi.org/project/pydevd-pycharm/>`_ tool of PyCharm to debug Python UDFs.

1. Create a Python Remote Debug in PyCharm

   run -> Python Remote Debug -> + -> choose a port (e.g. 6789)

2. Install the ``pydevd-pycharm`` tool

   .. code-block:: bash

       $ pip install pydevd-pycharm

3. Add the following command in your Python UDF

   .. code-block:: python

       import pydevd_pycharm
       pydevd_pycharm.settrace('localhost', port=6789, stdoutToServer=True, stderrToServer=True)

4. Start the previously created Python Remote Debug Server

5. Run your Python Code

Profiling Python UDFs
=====================

You can enable the profile to analyze performance bottlenecks.

.. code-block:: python

    t_env.get_config().set("python.profile.enabled", "true")

Then you can see the profile result in the logs (see `Accessing Logs`_).