They provide integration with any SQL database or Job execution engine. Here is a list of the existing connectors.
Connectors are pluggable and new engines can be added. Feel free to contact the community.
If the built-in HiveServer2 (Hive, Impala, Spark SQL), RDBMS (MySQL, PostgreSQL, Oracle, SQLite), and JDBC interfaces don’t meet your needs, you can implement your own connector to the notebook app:
With the JDBC proxy, query editor with any JDBC compatible database. View the JDBC connector.
Note In the long term, SqlAlchemy is prefered as more “Python native”.
Based on the Livy REST API.
MapReduce, Pig, Java, Shell, Sqoop, DistCp Oozie connector.
The Job Browser is generic and can list any type of jobs, queries and provide bulk operations like kill, pause, delete… and access to logs and recommendations.
Here is its API.
The API currently supports:
Various storage systems can be interacted with. The
fsmanager.py is the main router to each API.
Note Ceph can be used via the S3 browser.
With just a few changes in the Python API, the HBase browser could be compatible with Apache Kudu or Google Big Table.
Dashboards are generic and support Apache Solr and SQL:
The API was influenced by Solr but is now generic:
A connector similar to Solr or SQL Alchemy binding would need to be developed HUE-7828.
The backends is pluggable by providing alternative client interfaces:
Currently only Apache Oozie is supported for your Datawarehouse, but the API is getting generic with HUE-3797 that is bringing Celery Beat integration.