@Rocky - an application connecting from a dedicated service account to starrocks 3.5.20 that runs in shared-data mode is getting periodic error "error connecting: Timeout expired. The timeout period elapsed prior to obtaining a connection from the pool." What can be done to resolve this issue?

@Rocky can I update table partition from month to day ? new partitions loading will go to day and older will be in month only

@Rocky mysql vs starrocks varchar size differnece? starrocks in bytes but mysql in char size.

@Rocky StarRocks 3.5.20, deployed in shared-date mode through kubernetes operator has a problem spinning up with just one replica in shared_data mode producing the following logs: 2026-08-10 164002.308-04:00 INFO (...) [CatalogUtil.loadFileIO():376] Loading custom FileIO implementation: <FILE_IO_IMPLEMENTATION> 2026-08-10 164002.441-04:00 INFO (...) [ConnectorTableMetadataProcessor.registerCachingIcebergCatalog():81] register to caching iceberg catalog on <CATALOG_NAME> in the ConnectorTableMetadataProcessor 2026-08-10 164002.441-04:00 INFO (...) [ConnectorTableMetadataProcessor.registerCachingIcebergCatalog():81] register to caching iceberg catalog on <CATALOG_NAME> in the ConnectorTableMetadataProcessor 2026-08-10 164003.715-04:00 INFO (...) [StarMgrServer.loadImage():247] star mgr image does not exist in <PATH> 2026-08-10 164003.716-04:00 INFO (...) [StateChangeExecutor.runOneCycle():85] begin to transfer FE type from INIT to UNKNOWN 2026-08-10 164003.718-04:00 INFO (...) [StateChangeExecutor.runOneCycle():179] finished to transfer FE type from INIT to UNKNOWN 2026-08-10 164003.773-04:00 WARN (...) [NativeCodeLoader.<clinit>():60] Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 2026-08-10 164003.876-04:00 INFO (...) [HiveMetaStoreClient.openInternal():462] Trying to connect to metastore with URI <METASTORE_URI> 2026-08-10 164003.922-04:00 INFO (...) [HiveMetaStoreClient.openInternal():543] Opened a connection to metastore, current connections: 1 2026-08-10 164003.983-04:00 INFO (...) [HiveMetaStoreClient.openInternal():604] Connected to metastore. 2026-08-10 164004.197-04:00 INFO (...) [HiveMetaStoreClient.openInternal():462] Trying to connect to metastore with URI <METASTORE_URI> 2026-08-10 164004.200-04:00 INFO (...) [HiveMetaStoreClient.openInternal():543] Opened a connection to metastore, current connections: 2 2026-08-10 164004.203-04:00 INFO (...) [HiveMetaStoreClient.openInternal():604] Connected to metastore. 2026-08-10 164004.283-04:00 INFO (...) [BaseMetastoreTableOperations.refreshFromMetadataLocation():190] Refreshing table metadata from new version: s3a://<BUCKET>/<PATH>/metadata/<METADATA_FILE>.metadata.json 2026-08-10 164004.283-04:00 INFO (...) [BaseMetastoreTableOperations.refreshFromMetadataLocation():190] Refreshing table metadata from new version: s3a://<BUCKET>/<PATH>/metadata/<METADATA_FILE>.metadata.json 2026-08-10 164004.295-04:00 INFO (...) [CatalogUtil.loadFileIO():376] Loading custom FileIO implementation: <FILE_IO_IMPLEMENTATION> 2026-08-10 164004.296-04:00 INFO (...) [CatalogUtil.loadFileIO():376] Loading custom FileIO implementation: <FILE_IO_IMPLEMENTATION> 2026-08-10 164005.716-04:00 INFO (...) [GlobalStateMgr.waitForReady():1228] wait globalStateMgr to be ready. FE type: INIT. is ready: false 2026-08-10 164006.852-04:00 INFO (...) [CatalogUtil.loadMetricsReporter():500] Loading custom MetricsReporter implementation: <METRICS_REPORTER_IMPLEMENTATION> 2026-08-10 164006.852-04:00 INFO (...) [CatalogUtil.loadMetricsReporter():500] Loading custom MetricsReporter implementation: <METRICS_REPORTER_IMPLEMENTATION> 2026-08-10 164006.853-04:00 INFO (...) [BaseMetastoreCatalog.loadTable():69] Table loaded by catalog: <CATALOG>.<SCHEMA>.<TABLE> 2026-08-10 164006.853-04:00 INFO (...) [BaseMetastoreCatalog.loadTable():69] Table loaded by catalog: <CATALOG>.<SCHEMA>.<TABLE> 2026-08-10 164007.081-04:00 INFO (...) [InternalData.registerSupportedFormats():70] Unable to register Parquet for metadata files: Cannot find method: register 2026-08-10 164007.633-04:00 INFO (...) [BaseMetastoreTableOperations.refreshFromMetadataLocation():190] Refreshing table metadata from new version: s3a://<BUCKET>/<PATH>/metadata/<METADATA_FILE>.metadata.json 2026-08-10 164007.634-04:00 INFO (...) [BaseMetastoreTableOperations.refreshFromMetadataLocation():190] Refreshing table metadata from new version: s3a://<BUCKET>/<PATH>/metadata/<METADATA_FILE>.metadata.json 2026-08-10 164007.687-04:00 INFO (...) [BaseMetastoreCatalog.loadTable():69] Table loaded by catalog: <CATALOG>.<SCHEMA>.<TABLE> 2026-08-10 164007.699-04:00 INFO (...) [BaseMetastoreCatalog.loadTable():69] Table loaded by catalog: <CATALOG>.<SCHEMA>.<TABLE> 2026-08-10 164007.718-04:00 INFO (...) [GlobalStateMgr.waitForReady():1228] wait globalStateMgr to be ready. FE type: INIT. is ready: false 2026-08-10 164007.807-04:00 INFO (...) [ConnectorTblMetaInfoMgr.addConnectorTableInfo():70] <CATALOG>.<SCHEMA>.<TABLE>:<OBJECT_ID> add persistent connector table info : ConnectorTableInfo {relatedMaterializedViews=[MvId{dbId=<DB_ID>, id=<MV_ID>}]} 2026-08-10 164007.814-04:00 INFO (...) [MaterializedView.setActive():689] set <MATERIALIZED_VIEW_NAME> to active 2026-08-10 164007.822-04:00 INFO (...) [BaseMetastoreTableOperations.refreshFromMetadataLocation():190] Refreshing table metadata from new version: s3a://<BUCKET>/<PATH>/metadata/<METADATA_FILE>.metadata.json 2026-08-10 164007.903-04:00 INFO (...) [BaseMetastoreCatalog.loadTable():69] Table loaded by catalog: <CATALOG>.<SCHEMA>.<TABLE> 2026-08-10 164008.022-04:00 INFO (...) [BaseMetastoreTableOperations.refreshFromMetadataLocation():190] Refreshing table metadata from new version: s3a://<BUCKET>/<PATH>/metadata/<METADATA_FILE>.metadata.json 2026-08-10 164008.032-04:00 INFO (...) [CachingMvPlanContextBuilder.lambda$submitAsyncTask$5():551] async task <TASK_NAME> finished successfully, cost: 6705ms 2026-08-10 164008.075-04:00 INFO (...) [BaseMetastoreCatalog.loadTable():69] Table loaded by catalog: <CATALOG>.<SCHEMA>.<TABLE> 2026-08-10 164008.098-04:00 INFO (...) [BaseMetastoreTableOperations.refreshFromMetadataLocation():190] Refreshing table metadata from new version: s3a://<BUCKET>/<PATH>/metadata/<METADATA_FILE>.metadata.json 2026-08-10 164008.139-04:00 INFO (...) [BaseMetastoreCatalog.loadTable():69] Table loaded by catalog: <CATALOG>.<SCHEMA>.<TABLE> 2026-08-10 164008.205-04:00 INFO (...) [ConnectorTblMetaInfoMgr.addConnectorTableInfo():70] <CATALOG>.<SCHEMA>.<TABLE>:<OBJECT_ID> add persistent connector table info : ConnectorTableInfo {relatedMaterializedViews=[MvId{dbId=<DB_ID>, id=<MV_ID>}]} 2026-08-10 164008.205-04:00 INFO (...) [MaterializedView.setActive():689] set <MATERIALIZED_VIEW_NAME> to active 2026-08-10 164008.213-04:00 INFO (...) [BaseMetastoreTableOperations.refreshFromMetadataLocation():190] Refreshing table metadata from new version: s3a://<BUCKET>/<PATH>/metadata/<METADATA_FILE>.metadata.json 2026-08-10 164008.306-04:00 INFO (...) [BaseMetastoreCatalog.loadTable():69] Table loaded by catalog: <CATALOG>.<SCHEMA>.<TABLE> 2026-08-10 164008.356-04:00 INFO (...) [ConnectorTblMetaInfoMgr.addConnectorTableInfo():70] <CATALOG>.<SCHEMA>.<TABLE>:<OBJECT_ID> add persistent connector table info : ConnectorTableInfo {relatedMaterializedViews=[MvId{dbId=<DB_ID>, id=<MV_ID>}]} 2026-08-10 164008.357-04:00 INFO (...) [ConnectorTblMetaInfoMgr.addConnectorTableInfo():70] <CATALOG>.<SCHEMA>.<TABLE>:<OBJECT_ID> add persistent connector table info : ConnectorTableInfo {relatedMaterializedViews=[MvId{dbId=<DB_ID>, id=<MV_ID>}]} 2026-08-10 164008.357-04:00 INFO (...) [ConnectorTblMetaInfoMgr.addConnectorTableInfo():70] <CATALOG>.<SCHEMA>.<TABLE>:<OBJECT_ID> add persistent connector table info : ConnectorTableInfo {relatedMaterializedViews=[MvId{dbId=<DB_ID>, id=<MV_ID>}]} 2026-08-10 164008.358-04:00 INFO (...) [MaterializedView.checkIsActiveOnLoadBlocking():1431] baseMv: <MATERIALIZED_VIEW_NAME> is reloading, wait it to be reloaded first 2026-08-10 164008.426-04:00 INFO (...) [CachingMvPlanContextBuilder.lambda$submitAsyncTask$5():551] async task <TASK_NAME> finished successfully, cost: 7098ms 2026-08-10 164008.428-04:00 INFO (...) [MaterializedView.checkIsActiveOnLoadBlocking():1431] baseMv: <MATERIALIZED_VIEW_NAME> is reloading, wait it to be reloaded first I have tried ignore_materialized_view_error = true in fe.conf, but to no avail

Hi @Rocky just wondering if anyone is using Starrocks with Sigma Computing, or any other BI layer that uses the MySQL connector in the absence of a dedicated starrocks connector?

@Rocky where to check brpc_idle_timeout_sec this?

@Rocky when adding a new BE node, how can I know once the tablet distribution is stabilized and finished?

This message was deleted.

@Rocky Error occurred during SQL query execution SQL Error [1064] [42000]: Getting syntax error at line 3, column 36. Detail message: Unexpected input 'CURRENT_DATE', the most similar input is {a legal identifier}. CREATE TABLE

bi_top_24h_pct_tbl

(

symbol

*varchar*(20) NOT NULL COMMENT "Trading pair, e.g. BICOUSDT",

sys_run_date

date NULL DEFAULT (*CURRENT_DATE*()) COMMENT "",

fetched_at

datetime NULL DEFAULT CURRENT_TIMESTAMP COMMENT "Row ingestion time",

open_time

datetime NULL COMMENT "Stats window open time",

close_time

datetime NULL COMMENT "Stats window close time",

open_price

*decimal*(24, 8) NULL COMMENT "",

high_price

*decimal*(24, 8) NULL COMMENT "",

low_price

*decimal*(24, 8) NULL COMMENT "",

last_price

*decimal*(24, 8) NULL COMMENT "",

last_qty

*decimal*(24, 8) NULL COMMENT "",

price_change

*decimal*(24, 8) NULL COMMENT "",

price_change_percent

*decimal*(10, 4) NULL COMMENT "",

weighted_avg_price

*decimal*(24, 8) NULL COMMENT "",

volume

*decimal*(30, 8) NULL COMMENT "Base asset volume",

quote_volume

*decimal*(30, 8) NULL COMMENT "Quote asset volume",

count

*bigint*(20) NULL COMMENT "Number of trades",

first_id

*bigint*(20) NULL COMMENT "",

last_id

*bigint*(20) NULL COMMENT "" ) ENGINE=OLAP PRIMARY *KEY*(

symbol

,

sys_run_date

) PARTITION BY date_trunc('day',

sys_run_date

) DISTRIBUTED BY HASH(

symbol

) BUCKETS 1 PROPERTIES ( "compression" = "LZ4", "fast_schema_evolution" = "true", "partition_live_number" = "5", "replicated_storage" = "true", "replication_num" = "2" );

@Rocky During one of my loads, it failed because of disk out of space. HOw can I clear the dormant data without waiting for GC

@Rocky StarRocks 3.5.20 shared_data mode. External iceberg catalog is mapped as iceberg_catalog_hms. I have an iceberg table that is partitioned with create statement. I want to create an ASYNC partitioned materialized view in StarRocks that is doing SELECT * from this table. How do I do it? The table create statement is as follows: CREATE TABLE

table_a

(

id_1

varchar(1073741824) DEFAULT NULL,

id_2

varchar(1073741824) DEFAULT NULL,

attribute_1

varchar(1073741824) DEFAULT NULL,

status_value

varchar(1073741824) DEFAULT NULL,

status_reason

varchar(1073741824) DEFAULT NULL,

payload_data

varchar(1073741824) DEFAULT NULL,

timestamp_epoch

bigint(20) DEFAULT NULL,

timestamp_utc

datetime DEFAULT NULL,

customer_id

int(11) DEFAULT NULL,

location_id

int(11) DEFAULT NULL ) PARTITION BY (day(timestamp_utc)) PROPERTIES ( "write.format.default" = "PARQUET", "location" = "s3a://<storage-path>/<container>/table_a", "write.parquet.compression-codec" = "zstd" ); I want to create an ASYNC partitioned materialized view in StarRocks that is doing SELECT * from this table. How do I do it?

@Rocky I am planning to use AWS NLB with FE to high availability and scalability. Can you tell me the port and address that AWS NLB should use for FE health checks? Even though

/api/health

shows

http 200/Status OK

when there are no active BEs and

total_backend_num=0

(meaning no queries can be processed), I don't think this is sufficient.

@Rocky What is the maximum cluster size? I'd like to know the number of FEs and BEs. The reasoning is that I'm unsure whether it's better to scale up each node to increase the number of CPU cores and memory modules, or to add nodes to the cluster, in order to ensure scalability. If scaling out is the case, I believe the advantage is the ability to add capacity in finer increments, such as 4vcpu or 8vcpu.

Does staarrocks support iceberg v3?

@Rocky Does StarRocks supports array unnest inside async MVs with partition-mapped incremental refresh without silently falling back to a full table scan? My use case is as a DSP, each record of bid request can have multiple inventory package ids associated with it. THey are stored as an array. Now, I want to count impression opportunities per inventory package IDs. This means unnesting the array and performing group by per unnested inventory package ID. Obviously this is not feasible in realtime since it causes row explosion. i have ~5.5 billion rows per 24 hours. What solutions do I have? I am thinking of async MVs creating hourly rollups

@Rocky Hi, I’m testing a large StarRocks Broker Load from Parquet files in S3. The load starts fast but progressively slows down. CPU remains underutilized, disk I/O is relatively low during most of the load, and then spikes near the end. The profile shows significant writer backpressure (

OutputFullTime

/

WaitWriteTime

). Increasing

pipeline_dop

improved initial throughput, but increasing

flush_thread_num_per_store

did not help and may have made it slightly worse. Could this be caused by MemTable/segment-writer backpressure, page-cache writeback, or storage sync latency? What metrics or configuration would you recommend checking to improve sustained load throughput and keep disk utilization more consistent?

@Rocky I see even starrocks 4.1.4 is available in docker hub but we still don't see release for 4.1.3 on GitHub and website are going to skip 4.1.3?

@Rocky do we have arrow flight metrics on starrocks?

@Rocky can I specify the limit on number of scan partitions per table wise?

@Rocky when powerbi gets data from starrocks via arrow flight service the data is buffered off heap on fe pod? or it is consumed from cn nodes?

@Rocky Starrocks 3.5.20 shared-data mode running on k8s through kubernetes operator. When attempting to run SHOW MATERIALIZED VIEWS I am getting:

Getting analyzing error. Detail message: RepoExecutorexecute sql failed: WITH MaxStartRunID AS (    SELECT        task_name,        cast(history_content_json->'startTaskRunId' as string) start_run_id    FROM _statistics_.task_run_history     WHERE (task_name, create_time) IN (            SELECT task_name, MAX(create_time)            FROM _statistics_.task_run_history            WHERE TRUE AND  get_json_string(history_content_json, 'dbName') = 'default_cluster:test_db' AND  task_name IN ('mv-10171','mv-10214','mv-10256','mv-10301')            GROUP BY task_name    ) ) SELECT t.history_content_json FROM _statistics_.task_run_history t JOIN MaxStartRunID msr   ON t.task_name = msr.task_name   AND cast(t.history_content_json->'startTaskRunId' as string) = msr.start_run_id ORDER BY t.create_time DESC.

@Rocky can I know what all tables cached in specific compute nodes?

@Rocky I'm using 4.0.8 shared data cluster, I have a table with datacache.enable=true, I'm trying to alter table by setting property to false. It is not allowing. Is there a way to not cached the data of the table going forward?

Hi @Rocky , I have starrocks cluster deployed on no shared arch version 3.3.2 , the issue i am facing is after restoring the backup when i run my streaming job i get and publish timeout error

Does StarRocks support MERGE INTO on Iceberg external catalog tables? If not, what's the recommended way to upsert?

@Rocky How often should data backups be performed?

@Rocky hello

@Rocky I am unable to get data in _statistics.query_history table. I have set global enable_query_history_

@Rocky WHat's idea size for ingesting parquet to StarRocks in iceberg table? I'm using is4gen.4xlarge EC2 as CN

@Rocky How can I install and load AuditLoader and how it is different from

enable_query_history

global variable. So basically my usecase is query monitoring like what all queries ran, errors, error reasons, etc. Also profiling for big queries