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.
