imply-cheddar f684df4c22
Use an HllSketchHolder object to enable optimized merge (#13737)
* Use an HllSketchHolder object to enable optimized merge

HllSketchAggregatorFactory.combine had been implemented using a
pure pair-wise, "make a union -> add 2 things to union -> get sketch"
algorithm.  This algorithm does 2 things that was CPU

1) The Union object always builds an HLL_8 sketch regardless of the
  target type.  This means that when the target type is not HLL_8, we
  spent CPU cycles converting to HLL_8 and back over and over again
2) By throwing away the Union object and converting back to the
  HllSketch only to build another Union object, we do lots and lots
  of copy+conversions of the HllSketch

This change introduces an HllSketchHolder object which can hold onto
a Union object and delay conversion back into an HllSketch until
it is actually needed.  This follows the same pattern as the
SketchHolder object for theta sketches.
2023-02-07 13:57:48 -08:00
2023-02-03 20:11:17 -08:00
2023-01-11 21:15:30 +05:30
2019-12-20 16:45:38 -08:00
2019-08-28 08:49:30 -07:00

Build Status Language grade: Java Coverage Status Docker Helm


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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

data loader Kafka

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

management

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

query view combo

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-user mailing list on Google Groups, and have more technical conversations in #troubleshooting on Slack.
  • Druid development discussions take place in the druid-dev mailing list (dev@druid.apache.org). Subscribe by emailing dev-subscribe@druid.apache.org. For live conversations, join the #dev channel 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

License

Apache License, Version 2.0

Description
Apache Druid: a high performance real-time analytics database.
Readme Apache-2.0 716 MiB
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