4b1ffbc452
* Various changes and fixes to UNNEST. Native changes: 1) UnnestDataSource: Replace "column" and "outputName" with "virtualColumn". This enables pushing expressions into the datasource. This in turn allows us to do the next thing... 2) UnnestStorageAdapter: Logically apply query-level filters and virtual columns after the unnest operation. (Physically, filters are pulled up, when possible.) This is beneficial because it allows filters and virtual columns to reference the unnested column, and because it is consistent with how the join datasource works. 3) Various documentation updates, including declaring "unnest" as an experimental feature for now. SQL changes: 1) Rename DruidUnnestRel (& Rule) to DruidUnnestRel (& Rule). The rel is simplified: it only handles the UNNEST part of a correlated join. Constant UNNESTs are handled with regular inline rels. 2) Rework DruidCorrelateUnnestRule to focus on pulling Projects from the left side up above the Correlate. New test testUnnestTwice verifies that this works even when two UNNESTs are stacked on the same table. 3) Include ProjectCorrelateTransposeRule from Calcite to encourage pushing mappings down below the left-hand side of the Correlate. 4) Add a new CorrelateFilterLTransposeRule and CorrelateFilterRTransposeRule to handle pulling Filters up above the Correlate. New tests testUnnestWithFiltersOutside and testUnnestTwiceWithFilters verify this behavior. 5) Require a context feature flag for SQL UNNEST, since it's undocumented. As part of this, also cleaned up how we handle feature flags in SQL. They're now hooked into EngineFeatures, which is useful because not all engines support all features. |
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README.md
Website | Twitter | Download | Get Started | Documentation | Community | Build | Contribute | License
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. The design documentation explains the key concepts.
Getting started
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 web 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
See the latest documentation for the documentation for the current official release. If you need information on a previous release, you can browse previous releases documentation.
Make documentation and tutorials updates in /docs using MarkDown and contribute them using a pull request.
Community
Visit the official project community page to read about getting involved in contributing to Apache Druid, and how we help one another use and operate Druid.
- Druid users can find help in the
druid-usermailing list on Google Groups, and have more technical conversations in#troubleshootingon Slack. - Druid development discussions take place in the
druid-devmailing list (dev@druid.apache.org). Subscribe by emailing dev-subscribe@druid.apache.org. For live conversations, join the#devchannel on Slack.
Check out the official community page for details of how to join the community Slack channels.
Find articles written by community members and a calendar of upcoming events on the project site - contribute your own events and articles by submitting a PR in the apache/druid-website-src repository.
Building from source
Please note that JDK 8 or JDK 11 is required to build Druid.
See the latest build guide for instructions on building Apache Druid from source.
Contributing
Please follow the community guidelines for contributing.
For instructions on setting up IntelliJ dev/intellij-setup.md