96b3498a40
* init multiValue column group by * Changing sorting to Lexicographic as default * Adding initial tests * 1.Fixing test cases adding 2.Optimized inmem structs * Linking SQL layer to native layer * Adding multiDimension support to group by column strategy * 1. Removing array coercion in Calcite layer 2. Removing ResultRowDeserializer * 1. Supporting all primitive array types 2. Removing dimension spec as part of columnSelector * 1. Supporting all primitive array types 2. Removing dimension spec as part of columnSelector * 1. Checkstyle things 2. Removing flag * Minor naming things * CheckStyle Things * Fixing test case * Fixing hashing * 1. Adding the MV function 2. Added few test cases * 1. Adding MV function test cases * Adding Selector strategy function test cases * Fixing ClientQuerySegmentWalkerTest * Adding GroupByQueryRunnerTest test cases * Fixing test cases * Adding few more test cases * Fixing Exception asset statement and intellij inspection * Adding null compatibility tests * Review comments * Fixing few failing tests * Fixing few failing tests * Do no convert to topN Q incase of group by on array * Fixing checkstyle * Fixing differences between jdk's class cast exception message * 1. Fixing ordering if the grouping key is an array * Fixing DefaultLimitSpec * Fixing CalciteArraysQueryTest * Dummy commit for LGTM * changes: * only coerce multi-value string null values when `ExpressionPlan.Trait.NEEDS_APPLIED` is set * correct return type inference for ARRAY_APPEND,ARRAY_PREPEND,ARRAY_SLICE,ARRAY_CONCAT * fix bug with ExprEval.ofType when actual type of object from binding doesn't match its claimed type * Review comments * Fixing test cases * Fixing spot bugs * Fixing strict compile Co-authored-by: Clint Wylie <cwylie@apache.org>
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 #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