8e5048e643
* Avoid mapping hydrants in create segments phase for native ingestion * Drop queriable indices after a given sink is fully merged * Do not drop memory mappings for realtime ingestion * Style fixes * Renamed to match use case better * Rollback memoization code and use the real time flag instead * Null ptr fix in FireHydrant toString plus adjustments to memory pressure tracking calculations * Style * Log some count stats * Make sure sinks size is obtained at the right time * BatchAppenderator unit test * Fix comment typos * Renamed methods to make them more readable * Move persisted metadata from FireHydrant class to AppenderatorImpl. Removed superfluous differences and fix comment typo. Removed custom comparator * Missing dependency * Make persisted hydrant metadata map concurrent and better reflect the fact that keys are Java references. Maintain persisted metadata when dropping/closing segments. * Replaced concurrent variables with normal ones * Added batchMemoryMappedIndex "fallback" flag with default "false". Set this to "true" make code fallback to previous code path. * Style fix. * Added note to new setting in doc, using Iterables.size (and removing a dependency), and fixing a typo in a comment. * Forgot to commit this edited documentation message |
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README.md
Website | Documentation | Developer Mailing List | User Mailing List | Slack | Twitter | Download
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 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 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