title: "SQL Editor / Notebook" date: 2019-03-13T18:28:09-07:00 draft: false
They provide SQL integration with any database via several connectors (native, JDBC, SQL Alchemy...).
Other modes like MapReduce, Java, Shell, Sqoop are also available. Here is a list of the existing connectors.
Connectors are pluggable and can new engines can be supported. Feel free to comment on the Hue list of github about it.
The SQL Editor page also describes the configuration steps.
Close to 100% of Hive and Impala grammar is supported which makes the autocomplete extremly powerful. Other languages defaults to a generic SQL grammar.
Hive, Impala, SparkSQL
SQL Alchemy supports comes with HUE-8740.
MySQL, Oracle, PostgreSQL, Phoenix, Presto, Kylin, Redshift, BigQuery, Drill
Use the query editor with any JDBC or Django-compatible database. View the JDBC connector.
MapReduce, Pig, Java, Shell, Sqoop, DistCp Oozie connector
Based on the Livy REST API
Dashboards are generic and support Solr and any SQL:
The API was influenced by Solr but is now generic:
Implementations:
When HS2, RDBMS, and JDBC Are Not Enough
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: Notebook Connectors. Each connector API subclasses the Base API and must implement the methods defined within; refer to the JdbcApi or RdbmsApi for representative examples.
A similar backend to Solr would need to be developed: HUE-7828