commit | db82adcdfde8c456cb78daf5394e032e1f8657f5 | [log] [tgz] |
---|---|---|
author | Gian Merlino <gianmerlino@gmail.com> | Fri Apr 26 16:01:17 2024 -0700 |
committer | GitHub <noreply@github.com> | Fri Apr 26 16:01:17 2024 -0700 |
tree | 966ea9d1f3e1d42ea22407394ceaca9f01feb136 | |
parent | 9cd1890855681d90464fb8b53c3c59e05d10f4a6 [diff] |
SCALAR_IN_ARRAY: Optimization and behavioral follow-ups. (#16311) * Four changes to scalar_in_array as follow-ups to #16306: 1) Align behavior for `null` scalars to the behavior of the native `in` and `inType` filters: return `true` if the array itself contains null, else return `null`. 2) Rename the class to more closely match the function name. 3) Add a specialization for constant arrays, where we build a `HashSet`. 4) Use `castForEqualityComparison` to properly handle cross-type comparisons. Additional tests verify comparisons between LONG and DOUBLE are now handled properly. * Fix spelling. * Adjustments from review.
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.
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 streaming and batch data using a point-and-click wizard to guide you through ingestion setup. Monitor one off tasks and ingestion supervisors.
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.
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.
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.
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-user
mailing list on Google Groups, and have more technical conversations in #troubleshooting
on Slack.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.
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.
Please follow the community guidelines for contributing.
For instructions on setting up IntelliJ dev/intellij-setup.md