зеркало из https://github.com/mozilla/PyHive.git
117 строки
3.5 KiB
ReStructuredText
117 строки
3.5 KiB
ReStructuredText
======
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PyHive
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======
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PyHive is a collection of Python `DB-API <http://www.python.org/dev/peps/pep-0249/>`_ and
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`SQLAlchemy <http://www.sqlalchemy.org/>`_ interfaces for `Presto <http://prestodb.io/>`_ and
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`Hive <http://hive.apache.org/>`_.
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Usage
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=====
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DB-API
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------
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.. code-block:: python
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from pyhive import presto
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cursor = presto.connect('localhost').cursor()
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cursor.execute('SELECT * FROM my_awesome_data LIMIT 10')
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print cursor.fetchone()
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print cursor.fetchall()
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DB-API (asynchronous)
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---------------------
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.. code-block:: python
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from pyhive import hive
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from TCLIService.ttypes import TOperationState
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cursor = hive.connect('localhost').cursor()
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cursor.execute('SELECT * FROM my_awesome_data LIMIT 10', async=True)
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status = cursor.poll().operationState
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while status in (TOperationState.INITIALIZED_STATE, TOperationState.RUNNING_STATE):
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logs = cursor.fetch_logs()
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for message in logs:
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print message
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# If needed, an asynchronous query can be cancelled at any time with:
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# cursor.cancel()
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status = cursor.poll().operationState
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print cursor.fetchall()
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SQLAlchemy
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----------
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First install this package to register it with SQLAlchemy (see ``setup.py``).
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.. code-block:: python
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from sqlalchemy import *
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from sqlalchemy.engine import create_engine
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from sqlalchemy.schema import *
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engine = create_engine('presto://localhost:8080/hive/default')
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logs = Table('my_awesome_data', MetaData(bind=engine), autoload=True)
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print select([func.count('*')], from_obj=logs).scalar()
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Note: query generation functionality is not exhaustive or fully tested, but there should be no
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problem with raw SQL.
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Passing session configuration
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-----------------------------
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.. code-block:: python
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# DB-API
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hive.connect('localhost', configuration={'hive.exec.reducers.max': '123'})
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presto.connect('localhost', session_props={'query_max_run_time': '1234m'})
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# SQLAlchemy
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create_engine(
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'hive://user@host:10000/database',
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connect_args={'configuration': {'hive.exec.reducers.max': '123'}},
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)
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Requirements
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============
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Install using
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- ``pip install pyhive[hive]`` for the Hive interface and
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- ``pip install pyhive[presto]`` for the Presto interface.
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`PyHive` works with
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- Python 2.7 / Python 3
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- For Presto: Presto install
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- For Hive: `HiveServer2 <https://cwiki.apache.org/confluence/display/Hive/Setting+up+HiveServer2>`_ daemon
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There's also a `third party Conda package <https://binstar.org/blaze/pyhive>`_.
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Changelog
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=========
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See https://github.com/dropbox/PyHive/releases.
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Contributing
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============
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- Please fill out the Dropbox Contributor License Agreement at https://opensource.dropbox.com/cla/ and note this in your pull request.
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- Changes must come with tests, with the exception of trivial things like fixing comments. See .travis.yml for the test environment setup.
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Testing
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=======
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.. image:: https://travis-ci.org/dropbox/PyHive.svg
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:target: https://travis-ci.org/dropbox/PyHive
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.. image:: http://codecov.io/github/dropbox/PyHive/coverage.svg?branch=master
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:target: http://codecov.io/github/dropbox/PyHive?branch=master
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Run the following in an environment with Hive/Presto::
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./scripts/make_test_tables.sh
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virtualenv --no-site-packages env
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source env/bin/activate
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pip install -e .
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pip install -r dev_requirements.txt
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py.test
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WARNING: This drops/creates tables named ``one_row``, ``one_row_complex``, and ``many_rows``, plus a
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database called ``pyhive_test_database``.
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