<!channel> 🎂 Happy 3rd Anniversary, StarRocks Community! We’ve come a long way in 3 years, thanks to YOU – our users, contributors, and supporters. Your contributions, feedback, and engagement have been the heart and soul of StarRocks’ growth. Thank you for joining us on this amazing ride! Let’s continue to break new ground and celebrate many more milestones together. 🎉

🔔 Just a friendly reminder that today’s session, *“*Query Engine Must-Haves for the Best Apache Superset Experience” is happening at 10 AM PT | 1 PM ET. <!channel> https://celerdata.wistia.com/live/events/zhxc0m4nxu Agenda: • Fast and flexible ad-hoc queries: Run complex SQL queries on the fly without extensive pre-computation for interactive data analysis. • On-demand query acceleration: Enable your underlying engine to add pre-computations on demand without manual SQL rewriting. • Support for open formats: Integrate with open formats to simplify your data pipeline while improving data governance. Get your questions answered and see these critical features in action with a demo that showcases these capabilities using Preset (powered by Apache Superset), CelerData (powered by StarRocks), and Apache Iceberg.

Release - v3.5.1 New release published by yingtingdong Release Date: July 1, 2025 ### New Features • [Experimental] Starting from v3.5.1, StarRocks introduces a high-performance data transfer channel based on the Apache Arrow Flight SQL protocol, comprehensively optimizing the data import channel and significantly improving transfer efficiency. This solution establishes a fully columnar data transfer pipeline from the StarRocks columnar execution engine to the client, eliminating the frequent row-column conversions and serialization overhead typically seen in traditional JDBC and ODBC interfaces, and achieving true zero-copy, low-latency, and high-throughput data transfer capabilities. #57956 • Java Scalar UDFs (user-defined functions) now support ARRAY and MAP types as input parameters. #55356 • Cross-node data cache sharing: Enables nodes to share cached external table data of data lakes across compute nodes via the network. If a local cache miss occurs, the system first attempts to fetch data from the caches of other nodes within the same cluster. Only if all caches miss will it re-fetch data from remote storage. This feature effectively reduces performance jitter caused by cache invalidation during elastic scaling and ensures stable query performance. A new FE configuration parameter

enable_trace_historical_node

controls this behavior (Default:

false

). #57083 • Storage Volume adds native support for Google Cloud Storage (GCS): You can now use GCS as a backend storage volume and manage and access GCS resources through the native SDK. #58815 ### Improvements • Optimized error messages when creating Hive external tables fails. #60076 • Optimized

count(1)

query performance using the

file_record_count

in Iceberg metadata. #60022 • Refined the Compaction scheduling logic to avoid delayed scheduling when all subtasks succeed. #59998 • Added

JAVA_OPTS="--add-opens=java.base/java.util=ALL-UNNAMED"

to BE and CN after upgrading to JDK 17. #59947 • Supports modifying the

kafka_broker_list

property via the ALTER ROUTINE LOAD command when Kafka Broker endpoints change. #59787 • Supports reducing build dependencies of the Docker base image through parameters. #59772 • Supports accessing Azure using Managed Identity authentication. #59657 • Improved error messages when querying external data via

Files()

function with duplicate path column names. #59597 • Optimized LIMIT pushdown logic. #59265 ### Bug Fixes Fixed the following issues: • Partition pruning issue when queries include Max and Min aggregations and empty partitions. #60162 • Incorrect query results when rewriting queries with materialized views due to missing NULL partitions. #60087 • Refresh errors on Iceberg external tables when using partition expressions based on

str2date

. #60089 • Incorrect partition range when creating temporary partitions using the START END syntax. #60014 • Incorrect display of Routine Load metrics on non-leader FE nodes. #59985 • BE/CN crashes when executing queries containing

COUNT(*)

window functions. #60003 • Stream Load failures when the target table name contains Chinese characters. #59722 • Overall loading failures to triple-replica tables when loading to a secondary replica fails. #59762 • Missing parameters in SHOW CREATE VIEW output. #59714 ### Behavior Changes • Some FE metrics include the

is_leader

label. #59883 StarRocks/starrocks

Hi Beryl, I haven't been able to attend the live event, is there any recording available?

Release - 3.3.16 New release published by wangsimo0 ## 3.3.16 Release Date: July 4, 2025 ### Improvements • Optimized error logs when creating Hive tables with duplicate names. #60076 • Added the FE parameter

slow_lock_print_stack

to prevent process stalls in large clusters when printing thread stacks. #59967 • Reduced unnecessary locks during tablet scheduling. #59744 ### Bug Fixes Fixed the following issues: • SplitOR fails to prune scan columns. #60223 • Incorrect query plan for null-aware left anti joins. #60119 • Incorrect query results when rewriting queries with materialized views due to missing NULL partitions. #60087 • Partition pruning errors when tables contain empty partitions. #60162 • Refresh errors on Iceberg external tables when using partition expressions based on

str2date

. #60089 • Unexpected behavior caused by materialized view schema changes. #60079 • Issues related to low-cardinality global dictionaries in UNION operators. #60075 • Incorrect partition ranges for temporary partitions created using the START END syntax. #60014 • Lock issues with SUBMIT TASK. #60026 • Partial updates fail on Primary Key tables under certain conditions. #60052 • Crashes caused by BE failing to create directories due to a lack of permissions to access storage paths. #60028 • Cache failures due to cache key duplication in concurrent scenarios. #60053 • Hive table metadata background refresh failure in Unified Catalog. #55215 • Query failures caused by incorrect return types of CASE WHEN. #59972 • Query failures when Delta Lake tables UNION themselves. #60030 • Partition creation failure when writing to multiple tables within the same transaction. #59954 • Queries could return empty results instead of errors when tablet versions were updated during execution. #53060 • Queries against modified columns in a table return null after upgrading to v3.4. #59941 • Authentication information is printed in logs. #59907 • Metadata refresh failures for external tables in Hive Catalog. #54596 • CACHE SELECT failures for tables after schema changes. #59812 • Broker Load could not recover after FE Leader shifts. #59732 • Stream Load failures when the target table name contains Chinese characters. #59722 • Incorrect query results in external tables due to search key hash collisions (affecting Iceberg/Delta/Paimon). #59781 StarRocks/starrocks

Hi <!channel>, Just flagging this in case it’s helpful—we’ve compiled best practices around key topics like partitioning, clustering, bucketing, and primary key tables in StarRocks. These were put together by our engineering team to address things that come up often. danceml 📄 Check them out if you haven’t already: https://docs.starrocks.io/docs/category/best-practices/

Release - 3.4.5 New release published by jaogoy Release Date: July 10, 2025 ### Improvements • Enhanced observability of loading job execution: Unified the runtime information of loading tasks into the

information_schema.loads

view. Users can view the execution details of all INSERT, Broker Load, Stream Load, and Routine Load subtasks in this view. Additional fields have been added to help users better understand the status of loading tasks and the association with parent jobs (PIPES, Routine Load Jobs). • Support modifying

kafka_broker_list

via the

ALTER ROUTINE LOAD

statement. ### Bug Fixes The following issues have been fixed: • Under high-frequency loading scenarios, Compaction could be delayed. #59998 • Querying Iceberg external tables via Unified Catalog would throw an error:

not support getting unified metadata table factory

. #59412 • When using

DESC FILES()

to view CSV files in remote storage, incorrect results were returned because the system mistakenly inferred

xinf

as the FLOAT type. #59574 •

INSERT INTO

could cause BE to crash when encountering empty partitions. #59553 • When StarRocks reads Equality Delete files in Iceberg, it could still access deleted data if the data had already been removed from the Iceberg table. #59709 • Query failures caused by renaming columns. #59178 ### Behavior Changes • The default value of the BE configuration item

skip_pk_preload

has been changed from

false

to

true

. As a result, the system will skip preloading Primary Key Indexes for Primary Key tables to reduce the likelihood of

Reached Timeout

errors. This change may increase query latency for operations that require loading Primary Key Indexes. StarRocks/starrocks

Hey <!channel>! I'm Ron, the new Developer Advocate at CelerData. I'm thrilled to be part of the team and to support and grow the StarRocks community. Next Thursday, I’ll be speaking at the Apache Iceberg Community Meetup, hosted at Snowflake’s Atlanta office. I’ll be sharing how you can meet your SLAs and low latency goals using materialized views. If you're in the area, it’s a great chance to connect with others in the Iceberg community and with CelerData (that’s me!). Come join us for an evening of learning, insights, and great conversation. Register here on Luma! ->>>> https://lu.ma/vdbjh2fc?tk=fZUnv1 Hope to see you there! And in the meantime, if you have any questions or just want to connect, feel free to reach out 😄 https://www.linkedin.com/in/ron-kapoor-swe/

Release - 3.5.2 New release published by yingtingdong Release Date: July 18, 2025 ### Improvements • Collected NDV (number of distinct values) statistics for ARRAY columns to improve query plan accuracy. #60623 • Disabled replica balancing for Colocate tables and tablet scheduling in Shared-data clusters to reduce unnecessary log output. #60737 • Optimized Catalog access workflow: FE now delays accessing external data sources asynchronously at startup to prevent hanging due to external service unavailability. #60614 • Added session variable

enable_predicate_expr_reuse

to control predicate pushdown. #60603 • Supports a retry mechanism when fetching Kafka partition information fails. #60513 • Removed the restriction requiring exact mapping of partition columns between materialized views and base tables. #60565 • Supports building Runtime In-Filters to enhance aggregation performance by filtering data during aggregation. #59288 ### Bug Fixes Fixed the following issues: • COUNT DISTINCT queries crash due to low-cardinality optimization for multiple columns. #60664 • Incorrect matching of global UDFs when multiple functions share the same name. #60550 • Null pointer exception (NPE) issue during Stream Load import. #60755 • Null pointer exception (NPE) issue when starting FE during a recovery from a cluster snapshot. #60604 • BE crash caused by column mode mismatch when processing short-circuit queries with out-of-order values. #60466 • Session variables set via PROPERTIES in SUBMIT TASK statements did not take effect. #60584 • Incorrect results for

SELECT min/max

queries under specific conditions. #60601 • Incorrect bucket pruning when the left side of a predicate is a function, leading to incorrect query results. #60467 • Crash for queries against a non-existent

query_id

via Arrow Flight SQL. #60497 ### Behavior Changes • The default value of

lake_compaction_allow_partial_success

is set to

true

. Compaction operations can now be marked as successful even if partially completed, preventing blockage of subsequent compaction tasks. #60643 StarRocks/starrocks

Hi <!channel> ! 👋 The StarRocks Global Summit 2025 site is live - https://summit.starrocks.io/2025 danceml Grab your free pass and join us online on September 10 for a full day of engineer-to-engineer sessions led by StarRocks PMCs and key members of the user community. Spare a few hours, skip the guesswork, and learn from teams who’ve solved some of the toughest data challenges using StarRocks. We’re sharing hard-won lessons, real use cases, and tips you can take straight into production—or your next proof of concept! 🔗 Save your spot now: https://summit.starrocks.io/2025 🎤 Got something to share? There’s still time to *submit a talk*—CFP is open a bit longer!

Friendly reminder: Today’s session, "Introducing StarRocks 3.5," is happening at 10 AM PT | 1 PM ET! Save your seat here*:* https://celerdata.wistia.com/live/events/vwke0ga4l8 Here’s a sneak peek at what we’ll cover: • Cluster management & security: Snapshot & restore for better disaster recovery, LDAP/JWT/OAuth2 authentication, and more • Table & ingestion: Spilling for stable massive batch ingestion, partition merge, TTL • Open format/Lakehouse integration: Low-cardinality optimization with dictionary encoding • Materialized views: TTL support to boost performance and save storage And we’ll open the floor for all your StarRocks questions at the end!

Release - 3.3.17 New release published by wangsimo0 ## v3.3.17 Release Date: July 30, 2025 ### Bug Fixes The following issues have been fixed: • Upgraded HttpClient5 to 5.4.3. #61298 • Incorrect

cpu_core_used_permille

limit in resource groups. #61177 • Conflict between ALTER jobs and partition creation tasks. #61167 • NPE caused by missing

globalStateMgr

in

ConnectContext

. #60880 • Partition creation failed when partition names matched case-insensitively but had different values. #60909 • Lock competition caused by synchronous access to partition statistics. #61041 • ANALYZE tasks stuck in

pending

state after FE restart. #61113 • Issue with JIT (Just-In-Time) compilation in BE. #61060 • Leader address issue in Starmgr. #61016 • CVE vulnerabilities in Broker. #60908 • Actual number of JDBC connections exceeded

jdbc_connection_pool_size

limit. #61004 • CVE-2022-41404 vulnerability. #59689 • CVEs related to Parquet and HttpClient5. #58750 • Partition not removed from

_partition_map

when physical partition ID was empty. #60842 • Missing version check in shared-data clusters. #59422 • Transaction log missing when publishing logs in batches in shared-data clusters. #60949 • Concurrent publishing of the same transaction when Batch Publish is enabled in shared-data clusters. #57574 • Statistics overwrite issue caused by lack of semi-synchronous mode. #60897 • Inaccurate

maxInstantTime

used for filtering Hudi files when retrieving latest merged file slices. #60927 • TaskRun state incompatible with earlier versions. #60438 • CVE-2025-52999 vulnerability. #60795 • Vulnerability caused by

log4j-1.2.17-cloudera6

in Broker. #59579 • BE crash when loading OOM partitions. #60778 • Base Compaction tasks blocking other compaction tasks. #60711 • Inefficient handling of error string truncation. #60878 • Materialized view rewrite failed in multi-FE environments. #60841 • INSERT OVERWRITE failed on manually created partitions. #60750 • Issue caused by using random distribution in aggregate keys. #60702 • Crash caused by low cardinality rewrite in

multi_distinct_count

. #60664 • Issue with Pivot resolving fields. #60748 • Upgraded

hudi-common

to 1.0.2. #59501 • BE crash when CLONE and DROP TABLE run concurrently. #61359 StarRocks/starrocks

Hi <!channel>, We recently hosted a webinar diving into the new features in StarRocks 3.5 with @Sida Shen—and had a great discussion with tons of thoughtful questions from the community! If you missed it (or just want to revisit the highlights), Sida also wrote two blog posts so you can catch up anytime: 📝 Blog: Introducing StarRocks 3.5 https://www.starrocks.io/blog/introducing-starrocks-3-5 💬 Q&A Recap: Security, Iceberg, and more https://www.starrocks.io/blog/35-webinar-qa-recap-starrocks-security-iceberg-support-and-more 🎬 Watch the full recording:

Release - 3.4.6 New release published by jaogoy Release Date: August 7, 2025 ### Improvements • When exporting data to Parquet files using

INSERT INTO FILES

, you can now specify the Parquet version via the </StarRocks/starrocks/blob/sql-reference/sql-functions/table-functions/files.md#parquetversion|`parquet.version`> property to improve compatibility with other tools when reading the exported files. #60843 ### Bug Fixes The following issues have been fixed: • Loading jobs failed due to overly coarse lock granularity in

TableMetricsManager

. #58911 • Case sensitivity issue in column names when loading Parquet data via

FILES()

. #61059 • Cache did not take effect after upgrading a shared-data cluster from v3.3 to v3.4 or later. #60973 • A division-by-zero error occurred when the partition ID was null, causing a BE crash. #60842 • Broker Load jobs failed during BE scaling. #60224 ### Behavior Changes • The

keyword

column in the

information_schema.keywords

view has been renamed to

word

to align with the MySQL definition. #60863 StarRocks/starrocks

Release - 3.5.3 New release published by yingtingdong Release Date: August 11, 2025 ### Feature Enhancements • Lake Compaction adds Segment write time statistics. #60891 • Avoid bRPC communication in local PassThrough exchange scenarios. #60538 • Disable inline mode for Data Cache writes to avoid performance degradation. #60530 • Iceberg metadata scan supports shared file I/O. #61012 • Support termination of all PENDING ANALYZE tasks. #61118 • Force reuse when there are too many CTE nodes to avoid excessive optimization time. #60983 • Added

BALANCE

type to cluster balance results. #61081 • Optimized materialized view rewrite for external tables. #61037 • Default value of system variable

enable_materialized_view_agg_pushdown_rewrite

is changed to

true

, enabling aggregation pushdown for materialized view queries by default. #60976 • Optimized partition statistics lock competition. #61041 ### Bug Fixes The following issues have been fixed: • Inconsistent Chunk column size after column pruning. #61271 • Synchronous execution of partition statistics loading may cause deadlocks. #61300 • Crash when

array_map

processes constant array columns. #61309 • Setting an auto-increment column to NULL results in the system mistakenly rejecting valid data within the same Chunk. #61255 • The actual number of JDBC connections may exceed the

jdbc_connection_pool_size

limit. #61038 • FQDN mode did not use IP addresses as cache map keys. #61203 • Array column cloning error during array comparison. #61036 • Deploying serialized thread pool blockage led to query performance degradation. #61150 • OK hbResponse not synchronized after heartbeat retry counter reset. #61249 • Incorrect result for the

hour_from_unixtime

function. #61206 • Conflicts between ALTER TABLE jobs and partition creation. #60890 • Cache does not take effect after upgrading from v3.3 to v3.4 or later. #60973 • Vector index metric

hit_count

is not set. #61102 • Stream Load transactions fail to find the coordinator node. #60154 • BE crashes when loading OOM partitions. #60778 • INSERT OVERWRITE failed on manually created partitions. #60750 • Partition creation failed when partition names matched case-insensitively but had different values. #60909 • The system does not support PostgreSQL UUID type. #61021 • Case sensitivity issue with column names when loading Parquet data via

FILES()

. #61059 StarRocks/starrocks

<!channel> Friendly reminder: Today’s session, _"_Why Customer-Facing Analytics Breaks—and How to Build It Right_,"_ is happening at 10 AM PT | 1 PM ET! Save your seat here: https://celerdata.wistia.com/live/events/uqt1a3umn1 Join us as we explore real-world strategies for delivering analytics directly to your customers—whether through dashboards, APIs, or AI agents. We’ll break down the common pitfalls of BI and OLAP systems and share examples of companies that overcame bottlenecks by rebuilding their architectures with StarRocks and Apache Iceberg. (No stress if you’re busy—register to get the recording afterward!)

Good news for our Japanese community 🇯🇵 — StarRocks docs are available in Japanese 👉🏻 https://docs.starrocks.io/ja/docs/introduction/StarRocks_intro/ 日本語ドキュメントをご覧いただき、気づいたことや直したほうがいい点があればぜひ教えてください 🙌

Hey <!channel>! Ron here. You might have seen me at a meetup or chatted with me on Slack, but I’m excited to officially introduce myself as CelerData’s new Developer Advocate! I joined the team almost two months ago and have been ramping up behind the scenes. To that end, I recently wrote a blog introducing myself to the community and wanted to share it here on Slack! https://medium.com/starrocks-engineering/hello-from-your-new-dev-advocate-9e27cec4ffe3 👋 I can’t wait to connect with you all, share what I’m working on, and hear your ideas!

Release - 3.5.4 New release published by yingtingdong Release Date: August 22, 2025 ### Improvements • Added logs to clarify the reason that tablets cannot be repaired. #61959 • Optimized DROP PARTITION information in logs. #61787 • Assigned a large but configurable row count to tables with unknown stats for statistical estimation. #61332 • Added balance statistic according to label location. #61905 • Added colocate group balance statistics to improve cluster monitoring. #61736 • Skipped the Publish waiting phase when the number of healthy replicas exceeds the default replica count. #61820 • Included the tablet information collection time in the tablet report. #61643 • Supports writing Starlet files with tags. #61605 • Supports viewing cluster balance statistics via SHOW PROC. #61578 • Bumped librdkafka to 2.11.0 to support Kafka 4.0 and removed deprecated configurations. #61698 • Added

prepared_timeout

configuration to Stream Load Transaction Interface. #61539 • Upgraded StarOS to v3.5‑rc3. #61685 ### Bug Fixes The following issues have been fixed: • Incorrect Dict version of random distribution tables. #61933 • Incorrect query context in context conditions. #61929 • Publish failures caused by synchronous Publish for shadow tablets during ALTER operations. #61887 • CVE‑2025‑55163 issue. #62041 • Memory leak in real-time data ingestion from Apache Kafka. #61698 • Incorrect count of rebuild files in the lake persistent index. #61859 • Statistics collection on generated expression columns causes cross-database query errors. #61829 • Query Cache misaligns in shared-nothing clusters, causing inconsistent results. #61783 • High memory usage in CatalogRecycleBin due to retaining deleted partition information.#61582 • SQL Server JDBC connections fail when the timeout exceeds 65,535 milliseconds. #61719 • Security Integration fails to encrypt passwords, exposing sensitive information. #60666 •

MIN()

and

MAX()

functions on Iceberg partition columns return NULL unexpectedly. #61858 • Other predicates of Join containing non‑push‑down subfields were incorrectly rewritten. #61868 • QueryContext cancellation can lead to a use‑after‑free situation. #61897 • CBO’s table pruning overlooks other predicates. #61881 • Partial Updates in

COLUMN_UPSERT_MODE

may overwrite auto-increment columns with zero. #61341 • JDBC TIME type conversion uses an incorrect timezone offset that leads to wrong time values. #61783 •

max_filter_ratio

was not being serialized in Routine Load jobs. #61755 • Precision loss in the

now(precision)

function in Stream Load. #61721 • Cancelling a query may result in a “query id not found” error. #61667 • LDAP authentication may miss PartialResultException, causing incomplete query results. #60667 • Paimon Timestamp timezone conversion issue when the query condition contains DATETIME. #60473 StarRocks/starrocks

Release - 3.3.18 New release published by wangsimo0 ## 3.3.18 Release Date: August 28, 2025 ### Bug Fixes The following issues have been fixed: • BE crashes when

LakePersistentIndex

initialization failed due to cleanup of

_memtable

. #62279 • A concurrency issue caused by missing locks when retrieving the maximum Tablet version in the replication transaction manager. #62238 • A hang issue in the phased scheduler, which waited indefinitely during synchronous Profile collection (after the fix, the system correctly terminates Profile collection when scheduling errors occur). #62140 • Exception handling issues in low-cardinality optimization under the

ALLOW_THROW_EXCEPTION

mode (after the fix, exceptions in expression evaluation are properly caught and returned). #62098 • FThe system failed to compute nested CTE statistics outside of the memo during table pruning when

enable_rbo_table_prune

was set to

false

. #62070 • CVE-2025-55163 issue. #62041 • An issue where

split_morsel_queue

nested inside

partition_morsel_queue

failed to correctly receive the Tablet Schema. #62034 • Incorrect handling of

NULL

arrays during Parquet writes, which could cause data inconsistency or crashes (after the fix, the system ensures the

split

function can correctly handle

NULL

input strings). #61999 • Failure when creating materialized views using

CASE WHEN

expressions due to incompatible return types of VARCHAR (after the fix, the system ensures consistency before and after refresh). #61996 • A concurrency safety issue caused by long operations holding shard-level locks while calculating compression scores. #61899 • An incomplete table pruning issue in CBO caused by pruning logic not considering all relevant predicates. #61881 StarRocks/starrocks

Shout-out to @Anton Borisov and the data team at Fresha for this fantastic deep dive 👏 https://medium.com/fresha-data-engineering/how-we-accidentally-became-one-of-uks-first-starrocks-production-pioneers-7db249f10010 — check it out before you dive in. Fresha—the world’s leading marketplace for beauty, wellness, and self-care, trusted by millions of consumers and businesses worldwide—hit a wall by mid-2024 when Postgres (OLTP) was overloaded by analytics and Snowflake turned out to be too slow and too costly for near real-time needs. See how adopting StarRocks as the middle layer brought together OLTP protection, open-format federation, and real-time performance—making customer dashboards render in ~200ms. Anton is joining the lineup at our #C090XCAJWQ2 Don’t miss his session! See who else is speaking at the Summit. <!channel>

danceml We’d love for you to join our StarRocks Global Summit Swag Giveaway! StarRocks Summit 2025 is happening free and online on September 10, and we’re celebrating with some premium StarRocks swag packs. Here’s how you can get in on it: • Already registered? Enter the email you used to register [in this form] and you’re in! • Not registered yet? Sign up for Summit HERE, then drop the email you used [in this form] to join the drawing. We’ll pick 2 winners after Summit and ship the swag straight to you!

Release - 3.4.7 New release published by jaogoy Release Date: September 1, 2025 ### Bug Fixes The following issues have been fixed: •

max_filter_ratio

is not persisted for Routine Load jobs. #61755 • In Stream Load, the

now(precision)

function lost the precision parameter. #61721 • In Audit Log, the Scan Rows result for

INSERT INTO SELECT

statements was inaccurate. #61381 • After upgrading the cluster to v3.4.5, the

fslib read iops

metric increased compared to before the upgrade. #61724 • Queries against SQLServer using JDBC Catalog often got stuck. #61719 StarRocks/starrocks

LAST CALL! starrocks*Make a 10-second StarRocks video, get $100*starrocks We’re inviting YOU to share 🎥 A quick 10–30 seconds on why you use, love, or contribute to StarRocks (phone video is perfect!). If your clip makes it into the Summit reel, you get a $100 Amazon gift card. Details are HERE. It takes 5 minutes 😎

Release - 3.5.5 New release published by yingtingdong Release date: September 5, 2025 ### Improvements • Added a new system variable

enable_drop_table_check_mv_dependency

(default:

false

). When set to

true

, if the object to be dropped is referenced by a downstream materialized view, the system prevents the execution of

DROP TABLE

/

DROP VIEW

/

DROP MATERIALIZED VIEW

. The error message lists the dependent materialized views and suggests checking the

sys.object_dependencies

view for details. #61584 • Logs now include the Linux distribution and CPU architecture of the build, to facilitate issue reproduction and troubleshooting. Log format:

... build <hash> distro <id> arch <arch>

. #62017 • Persisted per-Tablet index and incremental column group file sizes are now cached, replacing on-demand directory scans. This accelerates Tablet status reporting in BE and reduces latency under high I/O scenarios. #61901 • Downgraded several high-frequency INFO logs in FE and BE to VLOG, and aggregated task submission logs, significantly reducing redundant storage-related logs and log volume under heavy load. #62121 • Improved query performance for External Catalog metadata through

information_schema

by pushing table filters before calling

getTable

, avoiding per-table RPCs. #62404 ### Bug Fixes The following issues have been fixed: • NullPointerException when fetching partition-level column statistics during the Plan stage due to missing data. #61935 • Fixed Parquet write issues with non-empty NULL arrays, and corrected

SPLIT(NULL, …)

behavior to consistently return NULL, preventing data corruption and runtime errors. #61999 • Failure when creating materialized views using

CASE WHEN

expressions due to incompatible VARCHAR type returns (fixed by ensuring consistency before and after refresh, and introducing a new FE configuration

transform_type_prefer_string_for_varchar

to prefer STRING and avoid length mismatch). #61996 • Statistics for nested CTEs could not be computed outside of memo when

enable_rbo_table_prune

was

false

. #62070 • In Audit Logs, inaccurate Scan Rows results for INSERT INTO SELECT statements. #61381 • ExceptionInInitializerError/NullPointerException during initialization caused FE startup failure when Query Queue v2 was enabled. #62161 • BE crash when

LakePersistentIndex

initialization failed and

_memtable

cleanup was triggered. #62279 • Permission issues during materialized view refresh due to creator roles not being activated (fixed by adding FE configuration

mv_use_creator_based_authorization

. When set to

false

, materialized views are refreshed as root, for compatibility with LDAP-authenticated clusters). #62396 • Materialized view refresh failures caused by case-sensitive List partition table names (fixed by enforcing case-insensitive uniqueness checks on partition names, aligning with OLAP table semantics). #62389 StarRocks/starrocks

Release - 4.0.0-RC New release published by wangsimo0 ## 4.0.0-RC Release date: September 9, 2025 ### Data Lake Analytics • Unified Page Cache and Data Cache for BE metadata, and adopted an adaptive strategy for scaling. #61640 • Optimized metadata file parsing for Iceberg statistics to avoid repetitive parsing. #59955 • Optimized COUNT/MIN/MAX queries against Iceberg metadata by efficiently skipping over data file scans, significantly improving aggregation query performance on large partitioned tables and reducing resource consumption. #60385 • Supports compaction for Iceberg tables via procedure

rewrite_data_files

. • Supports Iceberg tables with hidden partitions, including creating, writing, and reading the tables. #58914 • Supports the TIME data type in the Paimon catalog. #58292 ### Security and Authentication • In scenarios where JWT authentication and the Iceberg REST Catalog are used, StarRocks supports the passthrough of user login information to Iceberg via the REST Session Catalog for subsequent data access authentication. #59611 #58850 • Supports vended credentials for the Iceberg catalog. ### Storage Optimization and Cluster Management • Introduced the File Bundling optimization for the cloud-native table in shared-data clusters to automatically bundle the data files generated by loading, Compaction, or Publish operations, thereby reducing the API cost caused by high-frequency access to the external storage system. #58316 • Supports Kafka 4.0 for Routine Load. • Supports full-text inverted indexes on Primary Key tables in shared-nothing clusters. • Supports enabling case-insensitive processing on names of catalogs, databases, tables, views, and materialized views. #61136 • Supports blacklisting Compute Nodes in shared-data clusters. #60830 • Supports global connection ID. #57256 ### Query and Performance Improvement • Supports DECIMAL256 data type, expanding the upper limit of precision from 38 to 76 bits. Its 256-bit storage provides better adaptability to high-precision financial and scientific computing scenarios, effectively mitigating DECIMAL128's precision overflow problem in very large aggregations and high-order operations. #59645 • Optimized the performance of the JOIN and AGG operators. #61691 • [Preview] Introduced SQL Plan Manager to allow users to bind a query plan to a query, thereby preventing the query plan from changing due to system state changes (mainly data updates and statistics updates), thus stabilizing query performance. #56310 • Introduced Partition-wise Spillable Aggregate/Distinct operators to replace the original Spill implementation based on sorted aggregation, significantly improving aggregation performance and reducing read/write overhead in complex and high-cardinality GROUP BY scenarios. #60216 • Flat JSON V2: • Supports configuring Flat JSON on the table level. #57379 • Enhance JSON columnar storage by retaining the V1 mechanism while adding page- and segment-level indexes (ZoneMaps, Bloom filters), predicate pushdown with late materialization, dictionary encoding, and integration of a low-cardinality global dictionary to significantly boost execution efficiency. #60953 • Supports an adaptive ZoneMap index creation strategy for the STRING data type. #61960 ### Functions and SQL Syntax • Added the following functions: •

bitmap_hash64

#56913 •

bool_or

#57414 •

strpos

#57278 •

to_datetime

and

to_datetime_ntz

#60637 •

regexp_count

#57182 •

tokenize

#58965 •

format_bytes

#61535 • Provides the following syntactic extensions: • Supports IF NOT EXISTS keywords in CREATE ANALYZE FULL TABLE. #59789 • Supports EXCLUDE clauses in SELECT. #57411 • Supports FILTER clauses in aggregate functions, improving readability and execution efficiency of conditional aggregations. #58937 StarRocks/starrocks

Quick heads-up — StarRocks Summit 2025 is tomorrow (Sept 10)! yay See the full agenda + grab your free pass if you haven’t already: [link] <!channel> We’ve shared a lot already, so I’ll keep this short: it’s one day, free, and virtual. 25+ engineer-to-engineer sessions. Real lessons. Real solutions. Real production wins. You’ll hear directly from engineers at Intuit, Coinbase, Pinterest, Demandbase, TRM Labs, Celonis, Eightfold, Fresha, and more — sharing what actually worked (and what broke) in their stacks. Expect deep dives into real-time customer-facing analytics, StarRocks + Iceberg powering lakehouse architectures, and hands-on lessons from engineers working with AI and agents. Excited to learn together with you all tomorrow! cat dance

Summit goes live in 1 hour — 9 AM PT / 12 PM ET / 6 PM CEST / 9:30 PM IST danceml Grab a coffee ☕ and join the ride with us! <!channel> 👉 See the full agenda + grab your free pass if you haven’t already: [link]

Hi folks, we hosted our very first StarRocks Global Summit. It was a successful event, with engineers from well-known companies such as Intuit, Celonis, Fanatics, and Pinterest sharing their use cases with StarRocks. The content was excellent, and the feedback from the audience was very positive. Many thanks to the colleagues who helped organize the summit, the speakers, and the audience from around the world. We also recorded a community voice session from our open-source users. You’re welcome to like and share it! 🎉 https://www.linkedin.com/posts/starrocks-oss_starrockssummit2025-dataanalytics-dataen[…]m=member_desktop&amp;rcm=ACoAAAEXiCEBMiHpzHjFkEm-Y43MqOWlMShBEAo