| commit | 4d2a92f46a121fc8b3f5a02f1480156ccc62bb4a | [log] [tgz] |
|---|---|---|
| author | Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com> | Sat Oct 10 06:12:30 2020 +0530 |
| committer | GitHub <noreply@github.com> | Fri Oct 09 17:42:30 2020 -0700 |
| tree | add4b44a151f2a54233c4a2e6cf54b98a58e90d1 | |
| parent | 4c78b514c962d8d93b6b9686c4125061a3d20712 [diff] |
Add caching support to join queries (#10366) * Proposed changes for making joins cacheable * Add unit tests * Fix tests * simplify logic * Pull empty byte array logic out of CachingQueryRunner * remove useless null check * Minor refactor * Fix tests * Fix segment caching on Broker * Move join cache key computation in Broker Move join cache key computation in Broker from ResultLevelCachingQueryRunner to CachingClusteredClient * Fix compilation * Review comments * Add more tests * Fix inspection errors * Pushed condition analysis to JoinableFactory * review comments * Disable join caching for broker and add prefix key to BroadcastSegmentIndexedTable * Remove commented lines * Fix populateCache * Disable caching for selective datasources Refactored the code so that we can decide at the data source level, whether to enable cache for broker or data nodes
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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.
You can get started with Druid with our local or Docker 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 streaming and batch data using a point-and-click wizard to guide you through ingestion setup. Monitor one off tasks and ingestion supervisors.
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.
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.
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 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.
Please note that JDK 8 is required to build Druid.
For instructions on building Druid from source, see docs/development/build.md
Please follow the community guidelines for contributing.
For instructions on setting up IntelliJ dev/intellij-setup.md