38c1def95a
* Kill tasks should honor the buffer period of unused segments. - The coordinator duty KillUnusedSegments determines an umbrella interval for each datasource to determine the kill interval. There can be multiple unused segments in an umbrella interval with different used_status_last_updated timestamps. For example, consider an unused segment that is 30 days old and one that is 1 hour old. Currently the kill task after the 30-day mark would kill both the unused segments and not retain the 1-hour old one. - However, when a kill task is instantiated with this umbrella interval, it’d kill all the unused segments regardless of the last updated timestamp. We need kill tasks and RetrieveUnusedSegmentsAction to honor the bufferPeriod to avoid killing unused segments in the kill interval prematurely. * Clarify default behavior in docs. * test comments * fix canDutyRun() * small updates. * checkstyle * forbidden api fix * doc fix, unused import, codeql scan error, and cleanup logs. * Address review comments * Rename maxUsedFlagLastUpdatedTime to maxUsedStatusLastUpdatedTime This is consistent with the column name `used_status_last_updated`. * Apply suggestions from code review Co-authored-by: Kashif Faraz <kashif.faraz@gmail.com> * Make period Duration type * Remove older variants of runKilLTask() in OverlordClient interface * Test can now run without waiting for canDutyRun(). * Remove previous variants of retrieveUnusedSegments from internal metadata storage coordinator interface. Removes the following interface methods in favor of a new method added: - retrieveUnusedSegmentsForInterval(String, Interval) - retrieveUnusedSegmentsForInterval(String, Interval, Integer) * Chain stream operations * cleanup * Pass in the lastUpdatedTime to markUnused test function and remove sleep. --------- Co-authored-by: Kashif Faraz <kashif.faraz@gmail.com>
| Workflow | Status |
|---|---|
| ⚙️ CodeQL Config |  |
| 🔍 CodeQL |  |
| 🕒 Cron Job ITS |  |
| 🏷️ Labeler |  |
| ♻️ Reusable Revised ITS |  |
| ♻️ Reusable Standard ITS |  |
| ♻️ Reusable Unit Tests |  |
| 🔄 Revised ITS |  |
| 🔧 Standard ITS |  |
| 🛠️ Static Checks |  |
| 🧪 Unit and Integration Tests Unified |  |
| 🔬 Unit Tests |  |
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 or extended Markdown (MDX). Then, open a pull request.
To build the site locally, you need Node 16.14 or higher and to install Docusaurus 2 with npm|yarn install in the website directory. Then you can run npm|yarn start to launch a local build of the docs.
If you're looking to update non-doc pages like Use Cases, those files are in the druid-website-src repo.
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