ektravel commented on code in PR #15173: URL: https://github.com/apache/druid/pull/15173#discussion_r1373325541
########## docs/do-not-merge.md: ########## @@ -0,0 +1,827 @@ +<!--Intentionally, there's no Apache license so that the GHA fails it. This file is not meant to be merged. +--> + +Apache Druid 28.0.0 contains over $NUMBER_FEATURES new features, bug fixes, performance enhancements, documentation improvements, and additional test coverage from $NUMBER_OF_CONTRIBUTORS contributors. + +See the [complete set of changes](https://github.com/apache/druid/issues?q=is%3Aclosed+milestone%3A28.0+sort%3Aupdated-desc+) for additional details, including bug fixes. + +Review the [upgrade notes](#upgrade-notes) and [incompatible changes](#incompatible-changes) before you upgrade to Druid 28.0.0. + +# Highlights + +<!-- HIGHLIGHTS H2. FOR EACH MAJOR FEATURE FOR THE RELEASE --> + +## Window functions (experimental) + +You can use [window functions](https://druid.apache.org/docs/latest/querying/sql-window-functions) in Apache Druid to produce values based upon the relationship of one row within a window of rows to the other rows within the same window. A window is a group of related rows within a result set. For example, rows with the same value for a specific dimension. + +Enable window functions in your query with the `enableWindowing: true` context parameter. + +[#15184](https://github.com/apache/druid/pull/15184) + +## Concurrent append and replace (experimental) + +Druid 28.0.0 adds experimental support for concurrent append and replace. +This feature allows you to safely replace the existing data in an interval of a datasource while new data is being appended to that interval. One of the most common applications of this is appending new data to an interval while compaction of that interval is already in progress. +For more information, see [Concurrent append and replace](https://druid.apache.org/docs/latest/data-management/automatic-compaction#concurrent-append-and-replace). + +Segment locking will be deprecated and removed in favor of concurrent append and replace that is much simpler in design. With concurrent append and replace, Druid doesn't lock compaction jobs out because of active realtime ingestion. + +### Task locks for append and replace batch ingestion jobs + +Append batch ingestion jobs can now share locks. This allows you to run multiple append batch ingestion jobs against the same time internal. Replace batch ingestion jobs still require an exclusive lock. This means you can run multiple append batch ingestion jobs and one replace batch ingestion job for a given interval. + +[#14407](https://github.com/apache/druid/pull/14407) + +### Streaming ingestion with concurrent replace + +Streaming jobs reading from Kafka and Kinesis with `APPEND` locks can now ingest concurrently with compaction running with `REPLACE` locks. The segment granularity of the streaming job must be equal to or finer than that of the concurrent replace job. + +[#15039](https://github.com/apache/druid/pull/15039) + +## Query from deep storage + +[Query from deep storage](https://druid.apache.org/docs/latest/querying/query-deep-storage/) is no longer an experimental feature. When you query from deep storage, more data is available for queries without having to scale your Historical processes to accommodate more data. To benefit from the space saving that query from deep storage offers, configure your load rules to unload data from your Historical processes. + +### Support for multiple result formats + +Query from deep storage now supports multiple result formats. +Previously, the `/druid/v2/sql/statements/` endpoint only supported results in the `object` format. Now, results can be written in any format specified in the `resultFormat` parameter. +For more information on result parameters supported by the Druid SQL API, see [Responses](https://druid.apache.org/docs/latest/api-reference/sql-api#responses). + +[#14571](https://github.com/apache/druid/pull/14571) + +### Broadened access for queries for deep storage Review Comment: Updated -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
