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* Add join-related DataSource types, and analysis functionality. Builds on #9111 and implements the datasource analysis mentioned in #8728. Still can't handle join datasources, but we're a step closer. Join-related DataSource types: 1) Add "join", "lookup", and "inline" datasources. 2) Add "getChildren" and "withChildren" methods to DataSource, which will be used in the future for query rewriting (e.g. inlining of subqueries). DataSource analysis functionality: 1) Add DataSourceAnalysis class, which breaks down datasources into three components: outer queries, a base datasource (left-most of the highest level left-leaning join tree), and other joined-in leaf datasources (the right-hand branches of the left-leaning join tree). 2) Add "isConcrete", "isGlobal", and "isCacheable" methods to DataSource in order to support analysis. Other notes: 1) Renamed DataSource#getNames to DataSource#getTableNames, which I think is clearer. Also, made it a Set, so implementations don't need to worry about duplicates. 2) The addition of "isCacheable" should work around #8713, since UnionDataSource now returns false for cacheability. * Remove javadoc comment. * Updates reflecting code review. * Add comments. * Add more comments. |
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README.md
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Apache Druid
Druid is a high performance real-time analytics database. Druid's main value add is to reduce time to insight and action.
Druid is designed for workflows where fast queries and ingest really matter. Druid excels at powering UIs, running operational (ad-hoc) queries, or handling high concurrency. Consider Druid as an open source alternative to data warehouses for a variety of use cases.
Getting started
You can get started with Druid with our quickstart.
Druid provides a rich set of APIs (via HTTP and JDBC) for loading, managing, and querying your data. You can also interact with Druid via the built-in console (shown below).
Load data
Load streaming and batch data using a point-and-click wizard to guide you through ingestion setup. Monitor one off tasks and ingestion supervisors.
Manage the cluster
Manage your cluster with ease. Get a view of your datasources, segments, ingestion tasks, and services from one convenient location. All powered by SQL systems tables, allowing you to see the underlying query for each view.
Issue queries
Use the built-in query workbench to prototype DruidSQL and native queries or connect one of the many tools that help you make the most out of Druid.
Documentation
You can find the documentation for the latest Druid release on the project website.
If you would like to contribute documentation, please do so under
/docs in this repository and submit a pull request.
Community
Community support is available on the druid-user mailing list, which is hosted at Google Groups.
Development discussions occur on dev@druid.apache.org, which you can subscribe to by emailing dev-subscribe@druid.apache.org.
Chat with Druid committers and users in real-time on the #druid channel in the Apache Slack team. Please use this invitation link to join the ASF Slack, and once joined, go into the #druid channel.
Building from source
Please note that JDK 8 is required to build Druid.
For instructions on building Druid from source, see docs/development/build.md
Contributing
Please follow the community guidelines for contributing.
For instructions on setting up IntelliJ dev/intellij-setup.md