529b983ad0
* GroupBy: Reduce allocations by reusing entry and key holders. Two main changes: 1) Reuse Entry objects returned by various implementations of Grouper.iterator. 2) Reuse key objects contained within those Entry objects. This is allowed by the contract, which states that entries must be processed and immediately discarded. However, not all call sites respected this, so this patch also updates those call sites. One particularly sneaky way that the old code retained entries too long is due to Guava's MergingIterator and CombiningIterator. Internally, these both advance to the next value prior to returning the current value. So, this patch addresses that in two ways: 1) For merging, we have our own implementation MergeIterator already, although it had the same problem. So, this patch updates our implementation to return the current item prior to advancing to the next item. It also adds a forbidden-api entry to ensure that this safer implementation is used instead of Guava's. 2) For combining, we address the problem in a different way: by copying the key when creating the new, combined entry. * Attempt to fix test. * Remove unused import. |
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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. 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 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 Apache Druid Slack channel. Please use this invitation link to join and invite others.
Building from source
Please note that JDK 8 or JDK 11 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