Druid Operator has a new release 1.2.1 change log : https://github.com/datainfrahq/druid-operator/releases/tag/v1.2.1 Slack Conversation

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Mainly looking for the multiple Ingestion to a single data source feature .

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The Apache Druid team is proud to announce the release of Apache Druid 28.0.0 Druid is a high performance analytics data store for event-driven data. Apache Druid 28.0.0 contains over 420 new features, bug fixes, performance enhancements, documentation improvements, and additional test coverage from 57 contributors. Major new features and improvements include: • Three valued logic, strict booleans and flipping the null handling mode (useDefaultValueForNull) for more consistent behaviour with SQL’s standard. Flags can restore the old behaviour if required. • Ingest from multiple Kafka topics to a single datasource • Query from deep storage is no longer experimental, and support for multiple result formats have been added • MSQ’s parity with SQL - MSQ can query real time tasks, UNION ALL and UNNEST are now supported with MSQ • Concurrent append and replace (experimental) • Window functions (experimental) • Ability to ingest array types in SQL based ingestion & numeric array support for MSQ. Source and binary distributions can be downloaded from: https://druid.apache.org/downloads/ Release notes are at: https://github.com/apache/druid/releases/tag/druid-28.0.0. A big thank you to all the contributors in this milestone release!

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Vote for Druid 28.0.1 patch release is up: https://lists.apache.org/thread/q2c2n6l3pzs1rkxot326cboxrzbxpw5v. Release notes: https://github.com/apache/druid/issues/15535

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Hi Druid 28 helm chart will be released when ?

The Apache Druid team is proud to announce the release of Apache Druid 29.0.0 Druid is a high performance analytics data store for event-driven data. Apache Druid 29.0.0 contains over 350 new features, bug fixes, performance enhancements, documentation improvements, and additional test coverage from 67 contributors. Major new features and improvements include: - Experimental support for MSQ EXPORT statements - Experimental support for the SQL PIVOT and UNPIVOT operators - Window functions (experimental) now support ranges where both endpoints are unbounded or are the current row - Improved concurrent and replace (experimental) to automatically determine the task lock type - First and last aggregators for the double, float, and long types in native and MSQ ingestion spec and MSQ queries - Support for logging audit events and improved coverage of audited REST API endpoints - Three new extensions - DDSketch, Spectator Histogram, and Delta Lake Source and binary distributions can be downloaded from: https://druid.apache.org/downloads/ Release notes are at: https://github.com/apache/druid/releases/tag/druid-29.0.0. A big thank you to all the contributors in this milestone release!

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Hi All The Apache Druid team is proud to announce the release of Apache Druid 29.0.1 . Druid is a high performance analytics data store for event-driven data. Apache Druid 29.0.1 is a patch release on top of druid 29.0.0, that contains the following patches: Bug fixes • Added type verification for INSERT and REPLACE to validate that strings and string arrays aren't mixed #15920 • Concurrent replace now allows pending Peon segments to be upgraded using the Supervisor #15995 • Changed the

targetDataSource

attribute to return a string containing the name of the datasource. This reverts the breaking change introduced in Druid 29.0.0 for INSERT and REPLACE MSQ queries #16004 #16031 • Decreased the size of the distribution Docker image #15968 • Fixed an issue with SQL-based ingestion where string inputs, such as from CSV, TSV, or string-value fields in JSON, are ingested as null values when they are typed as LONG or BIGINT #15999 • Fixed an issue where a web console-generated Kafka supervisor spec has

flattenSpec

in the wrong location #15946 • Fixed an issue with filters on expression virtual column indexes incorrectly considering values null in some cases for expressions which translate null values into not null values #15959 • Fixed an issue where the data loader crashes if the incoming data can't be parsed #15983 • Improved DOUBLE type detection in the web console #15998 • Web console-generated queries now only set the context parameter

arrayIngestMode

to

array

when you explicitly opt in to use arrays #15927 • The web console now displays the results of an MSQ query that writes to an external destination through the

EXTERN

function #15969 Incompatible changes Changes to

targetDataSource

in EXPLAIN queries Druid 29.0.1 includes a breaking change that restores the behavior for

targetDataSource

to its 28.0.0 and earlier state, different from Druid 29.0.0 and only 29.0.0. In 29.0.0,

targetDataSource

returns a JSON object that includes the datasource name. In all other versions,

targetDataSource

returns a string containing the name of the datasource. If you're upgrading from any version other than 29.0.0, there is no change in behavior. If you are upgrading from 29.0.0, this is an incompatible change. #16004 Dependency updates • Updated PostgreSQL JDBC Driver version to 42.7.2 #15931 Source and binary distributions can be downloaded from: https://druid.apache.org/downloads.html All the release notes are present at: https://github.com/apache/druid/releases/tag/druid-29.0.1 A big thank you to all the contributors in this milestone release

What is the release strategy? Noticed that with a patch release e.g.

28.0.1

the base version

28.0.0

is entirely removed the download link. Don't see that pattern with releases prior to

28.0.0

Hi everyone when I am passing azure gen2 storage link ingestion in imply I am able to ingest data .same link if I pass to druid open source version I need to replace azurestorage with azure .I am getting no data returned from sampler

Druid 30.0.0 release branch is cut: https://github.com/apache/druid/tree/30.0.0

aused by: java.lang.IllegalArgumentException: newLimit > capacity: (9456258 > 4194304) at java.base/java.nio.Buffer.createLimitException(Buffer.java:395) ~[?:?] at java.base/java.nio.Buffer.limit(Buffer.java:369) ~[?:?] at java.base/java.nio.ByteBuffer.limit(ByteBuffer.java:1529) ~[?:?] at java.base/java.nio.MappedByteBuffer.limit(MappedByteBuffer.java:330) ~[?:?] at java.base/java.nio.MappedByteBuffer.limit(MappedByteBuffer.java:73) ~[?:?] at org.apache.druid.segment.data.GenericIndexed.createGenericIndexedVersionOne(GenericIndexed.java:686) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.data.GenericIndexed.read(GenericIndexed.java:192) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.column.StringEncodingStrategies.getStringDictionarySupplier(StringEncodingStrategies.java:103) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.nested.ScalarStringColumnAndIndexSupplier.read(ScalarStringColumnAndIndexSupplier.java:69) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.serde.NestedCommonFormatColumnPartSerde$StringColumnDeserializer.read(NestedCommonFormatColumnPartSerde.java:195) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.column.ColumnDescriptor.read(ColumnDescriptor.java:111) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.IndexIO$V9IndexLoader.deserializeColumn(IndexIO.java:794) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.IndexIO$V9IndexLoader.registerColumnHolder(IndexIO.java:771) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.IndexIO$V9IndexLoader.registerColumnHolders(IndexIO.java:726) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.IndexIO$V9IndexLoader.load(IndexIO.java:650) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.IndexIO.loadIndex(IndexIO.java:205) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.loading.MMappedQueryableSegmentizerFactory.factorize(MMappedQueryableSegmentizerFactory.java:49) ~[druid-processing-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.segment.loading.SegmentLocalCacheLoader.getSegment(SegmentLocalCacheLoader.java:71) ~[druid-server-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.server.SegmentManager.getSegmentReference(SegmentManager.java:325) ~[druid-server-2024.03.1-iap.jar:2024.03.1-iap] at org.apache.druid.server.SegmentManager.loadSegment(SegmentManager.java:268) ~[druid-server-2024.03.1-iap.jar:2024.03.1-iap] at io.imply.druid.query.lookup.SegmentManagerWithCallbacks.loadSegment(SegmentManagerWithCallbacks.java:56) ~[?:?]

does anyone know how to resolve this problem??

Hi, Druid recommends using JAVA 17 in the latest versions. MariaDB recommends using MariaDB Connector/J 3.3 with JAVA 17. However, Druid does not work with MariaDB Connector/J 3.3. Is there a plan to support MariaDB Connector/J 3.3 in Druid?

Any plans to release v30?

The Apache Druid team is proud to announce the release of Apache Druid 30.0.0. Druid is a high performance analytics data store for event-driven data. Apache Druid 30.0.0 contains over 407 new features, performance enhancements, bug fixes, and major documentation improvements from 50 contributors. Major new features and improvements include: - Improvements to concurrent append and replace. - Support for grouping on complex columns and nested arrays. - Performance improvements for GroupBy queries. - Performance improvements for AND filters. - Storing centralized datasource schema on coordinator, to improve startup time for Brokers. (Alpha) - MSQ support for window functions. - GCS support for MSQ Export. - A new RabbitMQ extension that lets you manage the creation and lifetime of rabbit indexing tasks. Source and binary distributions can be downloaded from: https://druid.apache.org/downloads.html Release notes are at: https://github.com/apache/druid/releases/tag/druid-30.0.0 A big thank you to all the contributors in this milestone release!

🚀 Introducing MIDAS: The Intelligent Autoscaler for Druid’s MiddleManager! 🚀 Hey Druid community! 🌟 Ever felt the pain of wrestling with scaling Druid’s MiddleManager service on Kubernetes? I did too—until I built MIDAS (Middle Manager Intelligent Dynamic Autoscaler)💡 You may have tried using HPA(Horizontal Pod Scaling) to autoscale your MiddleManagers, you might have faced issues like scaling down even when tasks are running, or spinning up more MiddleManagers than necessary. 😅 But with MIDAS, you can autoscale your MiddleManagers without any ingestion failures, ensuring that only the resources required to fulfill ingestion requests are used.🕺🏻 Using MIDAS we have cut our Druid infrastructure costs by 30%🤘🏻. Now, we can scale Druid’s MiddleManagers without worrying about unexpected ingestion failures, and we’re paying only for the resources we actually use🥳 Curious about how MIDAS can turn your chaotic infrastructure into a well-oiled machine? Check out my latest article on Druid Autoscaling: Medium 🔗 The best part? MIDAS is open-sourced! 🎉 Feel free to explore, contribute, or just marvel at how it can revolutionize your Druid deployments. Let’s make Druid even more powerful together! 💪. Repository 🔗 Looking forward to your thoughts and feedback! Feel free to connect with me on LinkedIn 🔗 Cheers, Rahul

The Apache Druid team is proud to announce the release of Apache Druid 30.0.1. Druid is a high performance analytics data store for event-driven data. Apache Druid 30.0.1 contains security, doc and task monitor fixes. Source and binary distributions can be downloaded from: https://druid.apache.org/downloads.html Release notes are at: https://github.com/apache/druid/releases/tag/druid-30.0.1

Druid 31 is around the corner. We are working on building an RC as we speak. I, and many other Druid developers, are very excited about this release as we will announce experimental support for two major features. We will also discuss these new features in the upcoming Druid summit (https://druidsummit.org/). If you are curious, want to attend the summit, and need help getting a pass for Druid Summit, let me know 🙂 Look forward to meeting many people on this channel in person at the event.

Hi Team.. we are using apache druid version druid-0.22.1 and we are planning to upgrade EKS version 1.27 and 1.29 , does this EKS version support this 0.22.1? or do we need to upgrade druid to latest one?

The Apache Druid team is proud to announce the release of Apache Druid 31.0.0. Druid is a high performance analytics data store for event-driven data. Apache Druid 31.0.0 contains over 589 new features, performance enhancements, bug fixes, and major documentation improvements from 64 contributors. Major new features and improvements include: - Window Functions are now GA in both the native and MSQ query engines - Concurrent append and replace is now GA - Several improvements to Delta Lake and Iceberg connectors - Low latency high complexity queries using Dart (experimental) - Web-console improvements to the Explore view and MSQ stages view - Updated documentation Source and binary distributions can be downloaded from: https://druid.apache.org/downloads.html Release notes are at: https://github.com/apache/druid/releases/tag/druid-31.0.0 A big thank you to all the contributors in this milestone release!

Druid 32 has been released! https://github.com/apache/druid/releases/tag/druid-32.0.0

Druid 31.0.2 and Druid 32.0.1 have been released! https://github.com/apache/druid/releases/tag/druid-31.0.2 https://github.com/apache/druid/releases/tag/druid-32.0.1

Hi, why the 2 parallel version releases including 1 major?