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 kylinpy

alternative, install by offline tarball package:

# download from https://pypi.org/project/kylinpy/#files
pip install kylinpy-<version>.tar.gz

Apache Kylin dialect for SQLAlchemy

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

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

kylin://<username>:<password>@<hostname>:<port>/<project>?<param1>=<value1>&<param2>=<value2>

DSN Fields	Default	Allow omitted
username	null	false
password	null	false
hostname	null	false
port	7070	true
project	null	false

DSN query string config is as follows

Fields	Default Value	Optional value	Description
is_ssl	0	0|1	Is the Kylin cluster enabled for https
prefix	/kylin/api	string	Kylin cluster API prefix
timeout	30	integer > 0	HTTP timeout with Kylin cluster
version	v1	v1|v2|v4	v1 == using Apache Kylin API v2 == using Kyligence Enterprise 3 API v4 == using Kyligence Enterprise 4 API
is_pushdown	0	0|1	If enabled, viewing a project table will use the hive source table
is_debug	0	0|1	Whether to enable debug mode

From SQLAlchemy access Apache Kylin

$ python
>>> import sqlalchemy as sa
>>> kylin_engine = sa.create_engine('kylin://ADMIN:KYLIN@sandbox/learn_kylin?timeout=60&is_debug=1')
>>> 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?timeout=60&is_debug=1')
 >>> 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.