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https://github.com/dropbox/PyHive

Python interface to Hive and Presto. 🐝
https://github.com/dropbox/PyHive

dbapi hive hiveserver2 presto python sqlalchemy

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Python interface to Hive and Presto. 🐝

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README 

        
========================================================

PyHive project has been donated to  Apache Kyuubi

========================================================



You can follow it's development and report any issues you are experiencing here: https://github.com/apache/kyuubi/tree/master/python/pyhive 



Legacy notes / instructions

===========================



PyHive

**********



PyHive is a collection of Python `DB-API `_ and

`SQLAlchemy `_ interfaces for `Presto `_ ,

`Hive `_ and `Trino `_.



Usage

**********



DB-API

------

.. code-block:: python



    from pyhive import presto  # or import hive or import trino

    cursor = presto.connect('localhost').cursor()  # or use hive.connect or use trino.connect

    cursor.execute('SELECT * FROM my_awesome_data LIMIT 10')

    print cursor.fetchone()

    print cursor.fetchall()



DB-API (asynchronous)

---------------------

.. code-block:: python



    from pyhive import hive

    from TCLIService.ttypes import TOperationState

    cursor = hive.connect('localhost').cursor()

    cursor.execute('SELECT * FROM my_awesome_data LIMIT 10', async=True)



    status = cursor.poll().operationState

    while status in (TOperationState.INITIALIZED_STATE, TOperationState.RUNNING_STATE):

        logs = cursor.fetch_logs()

        for message in logs:

            print message



        # If needed, an asynchronous query can be cancelled at any time with:

        # cursor.cancel()



        status = cursor.poll().operationState



    print cursor.fetchall()



In Python 3.7 `async` became a keyword; you can use `async_` instead:



.. code-block:: python



    cursor.execute('SELECT * FROM my_awesome_data LIMIT 10', async_=True)



SQLAlchemy

----------

First install this package to register it with SQLAlchemy, see ``entry_points`` in ``setup.py``.



.. code-block:: python



    from sqlalchemy import *

    from sqlalchemy.engine import create_engine

    from sqlalchemy.schema import *

    # Presto

    engine = create_engine('presto://localhost:8080/hive/default')

    # Trino

    engine = create_engine('trino+pyhive://localhost:8080/hive/default')

    # Hive

    engine = create_engine('hive://localhost:10000/default')



    # SQLAlchemy < 2.0

    logs = Table('my_awesome_data', MetaData(bind=engine), autoload=True)

    print select([func.count('*')], from_obj=logs).scalar()



    # Hive + HTTPS + LDAP or basic Auth

    engine = create_engine('hive+https://username:password@localhost:10000/')

    logs = Table('my_awesome_data', MetaData(bind=engine), autoload=True)

    print select([func.count('*')], from_obj=logs).scalar()



    # SQLAlchemy >= 2.0

    metadata_obj = MetaData()

    books = Table("books", metadata_obj, Column("id", Integer), Column("title", String), Column("primary_author", String))

    metadata_obj.create_all(engine)

    inspector = inspect(engine)

    inspector.get_columns('books')



    with engine.connect() as con:

        data = [{ "id": 1, "title": "The Hobbit", "primary_author": "Tolkien" }, 

                { "id": 2, "title": "The Silmarillion", "primary_author": "Tolkien" }]

        con.execute(books.insert(), data[0])

        result = con.execute(text("select * from books"))

        print(result.fetchall())



Note: query generation functionality is not exhaustive or fully tested, but there should be no

problem with raw SQL.



Passing session configuration

-----------------------------



.. code-block:: python



    # DB-API

    hive.connect('localhost', configuration={'hive.exec.reducers.max': '123'})

    presto.connect('localhost', session_props={'query_max_run_time': '1234m'})

    trino.connect('localhost',  session_props={'query_max_run_time': '1234m'})

    # SQLAlchemy

    create_engine(

        'presto://user@host:443/hive',

        connect_args={'protocol': 'https',

                      'session_props': {'query_max_run_time': '1234m'}}

    )

    create_engine(

        'trino+pyhive://user@host:443/hive',

        connect_args={'protocol': 'https',

                      'session_props': {'query_max_run_time': '1234m'}}

    )

    create_engine(

        'hive://user@host:10000/database',

        connect_args={'configuration': {'hive.exec.reducers.max': '123'}},

    )

    # SQLAlchemy with LDAP

    create_engine(

        'hive://user:password@host:10000/database',

        connect_args={'auth': 'LDAP'},

    )



Requirements

************



Install using



- ``pip install 'pyhive[hive]'`` or ``pip install 'pyhive[hive_pure_sasl]'`` for the Hive interface

- ``pip install 'pyhive[presto]'`` for the Presto interface

- ``pip install 'pyhive[trino]'`` for the Trino interface



Note: ``'pyhive[hive]'`` extras uses `sasl `_ that doesn't support Python 3.11, See `github issue `_.

Hence PyHive also supports `pure-sasl `_ via additional extras ``'pyhive[hive_pure_sasl]'`` which support Python 3.11.



PyHive works with



- Python 2.7 / Python 3

- For Presto: `Presto installation `_

- For Trino: `Trino installation `_

- For Hive: `HiveServer2 `_ daemon



Changelog

*********

See https://github.com/dropbox/PyHive/releases.



Contributing

************

- Please fill out the Dropbox Contributor License Agreement at https://opensource.dropbox.com/cla/ and note this in your pull request.

- Changes must come with tests, with the exception of trivial things like fixing comments. See .travis.yml for the test environment setup.

- Notes on project scope:



  - This project is intended to be a minimal Hive/Presto client that does that one thing and nothing else.

    Features that can be implemented on top of PyHive, such integration with your favorite data analysis library, are likely out of scope.

  - We prefer having a small number of generic features over a large number of specialized, inflexible features.

    For example, the Presto code takes an arbitrary ``requests_session`` argument for customizing HTTP calls, as opposed to having a separate parameter/branch for each ``requests`` option.



Tips for test environment setup

****************************************

You can setup test environment by following ``.travis.yaml`` in this repository. It uses `Cloudera's CDH 5 `_ which requires username and password for download.

It may not be feasible for everyone to get those credentials. Hence below are alternative instructions to setup test environment.



You can clone `this repository `_ which has Docker Compose setup for Presto and Hive.

You can add below lines to its docker-compose.yaml to start Trino in same environment::

 

    trino:

        image: trinodb/trino:351    

        ports:     

            - "18080:18080"    

        volumes:    

            - ./trino:/etc/trino



Note: ``./trino`` for docker volume defined above is `trino config from PyHive repository `_



Then run::

    docker-compose up -d



Testing

*******

.. image:: https://travis-ci.org/dropbox/PyHive.svg

    :target: https://travis-ci.org/dropbox/PyHive

.. image:: http://codecov.io/github/dropbox/PyHive/coverage.svg?branch=master

    :target: http://codecov.io/github/dropbox/PyHive?branch=master



Run the following in an environment with Hive/Presto::



    ./scripts/make_test_tables.sh

    virtualenv --no-site-packages env

    source env/bin/activate

    pip install -e .

    pip install -r dev_requirements.txt

    py.test



WARNING: This drops/creates tables named ``one_row``, ``one_row_complex``, and ``many_rows``, plus a

database called ``pyhive_test_database``.



Updating TCLIService

********************



The TCLIService module is autogenerated using a ``TCLIService.thrift`` file. To update it, the

``generate.py`` file can be used: ``python generate.py ``. When left blank, the

version for Hive 2.3 will be downloaded.