kylinpy 2.3.0

Apache Kylin Python Client Library

Apache Kylin Python Client Library

Apache Kylin Python Client Library is a python-based Apache Kylin client.

Any application that uses SQLAlchemy can now query Apache Kylin with this Apache Kylin dialect installed.

Installation

The easiest way to install Apache Kylin Python Client Library is to use pip:

pip install --upgrade kylinpy

Alternatiely, you may install this library from local project path, You are welcomed to also commit to this library:

git clone https://github.com/Kyligence/kylinpy.git
pip install -e kylinpy

Apache Kylin dialect for SQLAlchemy

Any application that uses SQLAlchemy can now query Apache Kylin with this Apache Kylin dialect installed. It is part of the Apache Kylin Python Client Library, so if you already installed this library in the previous step, you are ready to use.

You may use below template to build DSN to connect Apache Kylin:

kylin://<username>:<password>@<hostname>:<port>/<project>

DSN Field	Default Value
username
password
hostname
port	7070
project

SQLAlchemy create_engine takes an argument connect_args which is an additional dictionary that will be passed to connect().

key	Default Value
is_ssl	False
prefix	kylin/api
timeout(unit: seconds)	30
unverified	True
version	v1
is_pushdown	False

From SQLAlchemy access Apache Kylin

$ python
>>> import sqlalchemy as sa
>>> kylin_engine = sa.create_engine('kylin://ADMIN:KYLIN@sandbox/learn_kylin', connect_args={'is_ssl': True, 'timeout': 60})
>>> results = kylin_engine.execute('SELECT count(*) FROM KYLIN_SALES')
>>> [e for e in results]
[(4953,)]
>>> kylin_engine.table_names()
[u'KYLIN_ACCOUNT',
 u'KYLIN_CAL_DT',
 u'KYLIN_CATEGORY_GROUPINGS',
 u'KYLIN_COUNTRY',
 u'KYLIN_SALES',
 u'KYLIN_STREAMING_TABLE']

From Pandas access Apache Kylin

$ python
 >>> import sqlalchemy as sa
 >>> import pandas as pd
 >>> kylin_engine = sa.create_engine('kylin://ADMIN:KYLIN@sandbox/learn_kylin', connect_args={'is_ssl': True, 'timeout': 60})
 >>> sql = 'select * from kylin_sales limit 10'
 >>> pd.read_sql(sql, kylin_engine)

From Superset access Apache Kylin

Now you can configure the DSN in your application to establish the connection with Apache Kylin.

For example, you may install Apache Kylin Python Client Library in your Superset environment and configure connection to Apache Kylin in Superset

then you may be able to query Apache Kylin one table at a time from Superset

you may also be able to query detail data

Alternatively, you may also be able to query multiple tables from Apache Kylin by using SQL Lab in Superset.