| commit | f8301a314fdaa3e66eb357e632798f32e69b3c32 | [log] [tgz] |
|---|---|---|
| author | Clint Wylie <cwylie@apache.org> | Tue Aug 27 00:34:41 2024 -0700 |
| committer | GitHub <noreply@github.com> | Tue Aug 27 00:34:41 2024 -0700 |
| tree | 5c076668d9e628759b1b4eabaca81b4d2504b732 | |
| parent | ed3dbd62424ef49fa69316e50c907e6891fbd3e8 [diff] |
generic block compressed complex columns (#16863) changes: * Adds new `CompressedComplexColumn`, `CompressedComplexColumnSerializer`, `CompressedComplexColumnSupplier` based on `CompressedVariableSizedBlobColumn` used by JSON columns * Adds `IndexSpec.complexMetricCompression` which can be used to specify compression for the generic compressed complex column. Defaults to uncompressed because compressed columns are not backwards compatible. * Adds new definition of `ComplexMetricSerde.getSerializer` which accepts an `IndexSpec` argument when creating a serializer. The old signature has been marked `@Deprecated` and has a default implementation that returns `null`, but it will be used by the default implementation of the new version if it is implemented to return a non-null value. The default implementation of the new method will use a `CompressedComplexColumnSerializer` if `IndexSpec.complexMetricCompression` is not null/none/uncompressed, or will use `LargeColumnSupportedComplexColumnSerializer` otherwise. * Removed all duplicate generic implementations of `ComplexMetricSerde.getSerializer` and `ComplexMetricSerde.deserializeColumn` into default implementations `ComplexMetricSerde` instead of being copied all over the place. The default implementation of `deserializeColumn` will check if the first byte indicates that the new compression was used, otherwise will use the `GenericIndexed` based supplier. * Complex columns with custom serializers/deserializers are unaffected and may continue doing whatever it is they do, either with specialized compression or whatever else, this new stuff is just to provide generic implementations built around `ObjectStrategy`. * add ObjectStrategy.readRetainsBufferReference so CompressedComplexColumn only copies on read if required * add copyValueOnRead flag down to CompressedBlockReader to avoid buffer duplicate if the value needs copied anyway
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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.
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