Skip to main content
Version: Latest-4.1

Query queues

This topic describes how to manage query queues in StarRocks.

From v2.5, StarRocks supports query queues. With query queues enabled, StarRocks automatically queues the incoming queries when the concurrency threshold or resource limit is reached, thereby avoiding the overload deteriorating. Pending queries wait in a queue until there is enough compute resources available to begin execution.

The Query Queue feature has two versions:

  • Query Queue v1: Triggers queuing based on query concurrency, BE memory usage, and BE CPU usage. The original query queue configurations and behaviors in this topic belong to v1. From v3.1.4 onwards, v1 supports setting query queues on the resource group level.
  • Query Queue v2: Supported from v3.3 onwards. v2 estimates the BE resources consumed by each query, represents BE resources as logical slots, and queues and schedules queries based on the number of slots each query needs.

Query Queue v1​

Query Queue v1 supports setting thresholds on CPU usage, memory usage, and query concurrency to trigger query queues.

Roadmap:

VersionGlobal query queueResource group-level query queueCollective concurrency managementDynamic concurrency adjustment
v2.5βœ…βŒβŒβŒ
v3.1.4βœ…βœ…βœ…βœ…

Enable Query Queue v1​

Query queues are disabled by default. You can enable global or resource group-level query queues for INSERT loading, SELECT queries, and statistics queries by setting corresponding global session variables.

Enable global query queues​

  • Enable query queues for loading tasks:
SET GLOBAL enable_query_queue_load = true;
  • Enable query queues for SELECT queries:
SET GLOBAL enable_query_queue_select = true;
  • Enable query queues for statistics queries:
SET GLOBAL enable_query_queue_statistic = true;

Enable resource group-level query queues​

From v3.1.4 onwards, StarRocks supports setting query queues on the resource group level.

To enable the resource group-level query queues, you also need to set enable_group_level_query_queue in addition to the global session variables mentioned above.

SET GLOBAL enable_group_level_query_queue = true;

Specify resource thresholds​

Specify resource thresholds for global query queues​

You can set the thresholds that trigger query queues via the following global session variables:

VariableDefaultDescription
query_queue_concurrency_limit0The upper limit of concurrent queries on a BE. It takes effect only after being set greater than 0. Setting it to 0 indicates no limit is imposed.
query_queue_mem_used_pct_limit0The upper limit of memory usage percentage on a BE. It takes effect only after being set greater than 0. Setting it to 0 indicates no limit is imposed. Range: [0, 1]
query_queue_cpu_used_permille_limit0The upper limit of CPU usage permille (CPU usage * 1000) on a BE. It takes effect only after being set greater than 0. Setting it to 0 indicates no limit is imposed. Range: [0, 1000]
note
  • After Query Queue v2 is enabled, query_queue_cpu_used_permille_limit is no longer supported for queue triggering, and query_queue_mem_used_pct_limit still applies. See Memory admission.
  • By default, BE reports resource usage to FE at one-second intervals. You can change this interval by setting the BE configuration item report_resource_usage_interval_ms.

Specify resource thresholds for resource group-level query queues​

From v3.1.4 onwards, you can set individual concurrency limits (concurrency_limit) and CPU core limits (max_cpu_cores) when creating a resource group. When a query is initiated, if any of the resource consumptions exceed the resource threshold at either the global or resource group level, the query will be placed in queue until all resource consumptions are within the threshold.

VariableDefaultDescription
concurrency_limit0The concurrency limit for the resource group on a single BE node. It takes effect only when it is set to greater than 0.
max_cpu_cores0The CPU core limit for this resource group on a single BE node. It takes effect only when it is set to greater than 0. Range: [0, avg_be_cpu_cores], where avg_be_cpu_cores represents the average number of CPU cores across all BE nodes.

You can use SHOW USAGE RESOURCE GROUPS to view the resource usage information for each resource group on each BE node, as described in View Resource Group Usage Information.

Manage query concurrency​

When the number of running queries (num_running_queries) exceeds the global or resource group's concurrency_limit, incoming queries are placed in the queue. The way to obtain num_running_queries differs between versions < v3.1.4 and >= v3.1.4.

  • In versions < v3.1.4, num_running_queries is reported by BEs at the interval specified in report_resource_usage_interval_ms. Therefore, there might be some delay in the identification of changes in num_running_queries. For example, if the num_running_queries reported by BEs at the moment does not exceed the global or resource group's concurrency_limit, but incoming queries arrive and exceed the concurrency_limit before the next report, these incoming queries will be executed without waiting in the queue.

  • In versions >= v3.1.4, all running queries are collectively managed by the Leader FE. Each Follower FE notifies the Leader FE when initiating or finishing a query, allowing the StarRocks to handle scenarios where there is a sudden increase in queries exceeding the concurrency_limit.

Configure Query Queue v1​

You can set the capacity of a query queue and the maximum timeout of queries in queues via the following global session variables:

VariableDefaultDescription
query_queue_max_queued_queries1024The upper limit of queries in a queue. When this threshold is reached, incoming queries are rejected. It takes effect only after being set greater than 0.
query_queue_pending_timeout_second300The maximum timeout of a pending query in a queue. When this threshold is reached, the corresponding query is rejected. Unit: second.

Configure dynamic adjustment of query concurrency​

Starting from version v3.1.4, for queries managed by the query queue and run by the Pipeline Engine, StarRocks can dynamically adjust the query concurrency pipeline_dop for incoming queries based on the current number of running queries num_running_queries, the number of fragments num_fragments, and the query concurrency pipeline_dop. This allows you to dynamically control query concurrency while minimizing scheduling overhead, ensuring optimal BE resource utilization. For more information about fragments and query concurrency pipeline_dop, see Query Management - Adjusting Query Concurrency.

For each query under a query queue, StarRocks maintains a concept of drivers, which represent the concurrent fragments of a query on a single BE. Its logical value num_drivers, which represents the total concurrency of all fragments of that query on a single BE, is equal to num_fragments * pipeline_dop. When a new query arrives, StarRocks adjusts the query concurrency pipeline_dop based on the following rules:

  • The more the number of running drivers num_drivers exceeds the low water limit of concurrent drivers query_queue_driver_low_water, the lower the query concurrency pipeline_dop is adjusted to.
  • StarRocks restrains the number of running drivers num_drivers below the high water limit of concurrent drivers for queries query_queue_driver_high_water.

You can configure the dynamic adjustment of query concurrency pipeline_dop using the following global session variables:

VariableDefaultDescription
query_queue_driver_high_water-1The high water limit of concurrent drivers for a query. It takes effect only when it is set to a non-negative value. When set to 0, it is equivalent to avg_be_cpu_cores * 16, where avg_be_cpu_cores represents the average number of CPU cores across all BE nodes. When set to a value greater than 0, that value is used directly.
query_queue_driver_low_water-1The lower limit of concurrent drivers for queries. It takes effect only when it is set to a non-negative value. When set to 0, it is equivalent to avg_be_cpu_cores * 8. When set to a value greater than 0, that value is used directly.

Query Queue v2​

From v3.3 onwards, StarRocks supports Query Queue v2. In Query Queue v2, query queues are no longer triggered based on fixed thresholds for query concurrency, BE memory usage, or BE CPU usage. Instead, it estimates the BE resources required by each query and queues and schedules queries based on logical slots. If there are not enough available slots, the query waits in the queue until enough slots are released.

Configure Query Queue v2​

Query Queue v2 is enabled and tuned through FE configuration items. Changes to enable_query_queue_v2 require restarting FE nodes to take effect.

Configuration itemDefaultDescription
enable_query_queue_v2false (v3.3 to v4.0)
true (from v4.1 onwards)
Whether to enable Query Queue v2. When this item is set to true, StarRocks uses the v2 slot-based query scheduling mechanism.
query_queue_v2_concurrency_level4The logical concurrency level used by Query Queue v2 to calculate the total number of cluster slots. A larger value allows the system to admit more queries. This is a relative tuning parameter.
query_queue_slots_estimator_strategyPBEThe slot estimation strategy used for queue-based queries. Valid values: PBE (parallelism-based, the default), MBE (memory-cost-based), and CBE (CPU-cost-based). PBE estimates a query's slots from scan parallelism, capped by the worker count: for OLAP tables it uses the number of scan ranges left after pruning, so only very small queries fall below the worker count; a connector/external scan is treated as a full-parallelism scan (the worker count) rather than a single-slot query. MBE estimates slots from the query's memory cost divided by query_queue_v2_mem_bytes_per_slot. CBE estimates slots from the plan CPU cost divided by query_queue_v2_cpu_costs_per_slot. MBE and CBE per-query slots are additionally capped by number_of_workers * max(1, pipeline_dop / 2). The legacy values MAX and MIN are still accepted for forward compatibility and are treated as the default estimator; any other value is rejected by configuration validation.
query_queue_v2_schedule_strategySWRRThe scheduling policy used by Query Queue V2 to order pending queries. Supported values (case-insensitive) are SWRR (Smooth Weighted Round Robin) β€” the default, suitable for mixed/hybrid workloads that need fair weighted sharing β€” and SJF (Short Job First + Aging) β€” prioritizes short jobs while using aging to avoid starvation. The value is parsed with case-insensitive enum lookup; an unrecognized value is logged as an error and the default policy is used. This configuration only affects behavior when Query Queue V2 is enabled and interacts with V2 sizing settings such as query_queue_v2_concurrency_level.
query_queue_v2_mem_bytes_per_slot0Per-slot memory target used by the memory-cost-based estimator (MBE). When query_queue_slots_estimator_strategy is MBE, the total slots are derived from the warehouse memory budget, and a query's slots are estimated from its total memory cost divided by this value, capped by number_of_workers * max(1, pipeline_dop / 2). If it is non-positive, Query Queue V2 uses the average worker memory per core.
query_queue_v2_cpu_costs_per_slot1000000000Per-slot CPU cost threshold used by the CPU-cost-based estimator (CBE) to estimate how many slots a query needs from its plan CPU cost. The scheduler computes slots as ceil(plan_cpu_costs / query_queue_v2_cpu_costs_per_slot) and clamps the result to the range [1, min(totalSlots, number_of_workers * max(1, pipeline_dop / 2))]. A non-positive value is normalized to 1. Increasing this value reduces slots allocated per query (favoring fewer, larger-slot queries); decreasing it increases slots per query.
query_queue_mem_used_pct_limit0A global session variable. The memory usage limit of a node, as a fraction of the memory limit of the node. While the process memory usage of any alive node reaches this value, new queries wait in the queue. Range: [0, 1]. 0 means no memory gating. See Memory admission.
query_queue_concurrency_limit0The upper limit of concurrent queries on a BE. It takes effect only after being set greater than 0. Setting it to 0 indicates no limit is imposed.
note

query_queue_cpu_used_permille_limit applies only to Query Queue v1. For how Query Queue v2 applies query_queue_mem_used_pct_limit, see Memory admission.

Resource slots​

Query Queue v2 represents BE resources as logical slots:

  • Total cluster slots: StarRocks sets a logical total number of slots for the entire cluster. This total is positively correlated with the number of BEs and BE CPU cores, and is also affected by query_queue_v2_concurrency_level.
  • Slots required by a query: StarRocks estimates the number of slots required by each query. The estimation is based on factors such as statistics, query complexity, the number of fragments, estimated input and output data volumes of complex operators, and DOP.

Queuing logic​

When the number of slots required by a query exceeds the current number of remaining slots, the query waits in the queue. Query Queue v2 preferentially satisfies queries that require fewer slots, allowing small queries to obtain resources first and avoiding head-of-line blocking where a large query at the head of the queue blocks later small queries.

The entire queuing logic is completed on FE, including setting the total number of cluster slots, estimating the number of slots required by a query, and deciding which query's slot requirement to satisfy first. Slot scheduling does not depend on the actual resource usage of BEs. The only input taken from actual usage is the optional memory usage limit query_queue_mem_used_pct_limit, which makes new queries wait while a node uses too much memory. See Memory admission.

Choose an estimation strategy​

PBE​

Parallel-based estimation (PBE) strategy is best for:

  • Normal reporting queries
  • Mixed point lookups and large queries
  • Users who do not want to understand cost model details
  • DBAs who want stable, simple, and explainable queueing behavior first

Expected behaviors with PBE include:

  • Point lookups or queries that scan little data after pruning use fewer slots
  • Queries that scan larger ranges use more slots
  • Small queries are more likely to get execution resources during peak hours

The following example sets PBE as the strategy:

ADMIN SET FRONTEND CONFIG ("query_queue_slots_estimator_strategy" = "PBE");

MBE​

Memory cost-based estimation (MBE) strategy is suitable for dealing with memory pressure, such as large joins, large aggregations, or high-cardinality aggregations.

The following example sets MBE as the strategy, and allocates 2 GB of memory to each slot:

ADMIN SET FRONTEND CONFIG ("query_queue_slots_estimator_strategy" = "MBE");
ADMIN SET FRONTEND CONFIG ("query_queue_v2_mem_bytes_per_slot" = "2147483648");

MBE divides the query’s total memory cost by this value to get query slots, and divides the warehouse memory budget by this value to get total slots.

Tune the MBE strategy in the following directions:

Symptom: Memory still gets saturated easily

  • Adjustment: Decrease query_queue_v2_concurrency_level
  • Effect: Directly lowers the MBE total memory budget

Symptom: Queue is too long but BE memory still has room

  • Adjustment: Increase query_queue_v2_concurrency_level
  • Effect: Directly raises the MBE total memory budget

Symptom: max_slots is very small and integer rounding is visible

  • Adjustment: Decrease query_queue_v2_mem_bytes_per_slot
  • Effect: Uses a finer memory slot granularity and reduces coarse rounding error

CBE​

CPU cost-based estimation (CBE) strategy is suitable for dealing with memory pressure, such as compute-heavy SQL, complex expressions, or heavy CPU work after scanning.

The following example sets CBE as the strategy, and set the CPU cost threshold to 1000000000 for each slot:

ADMIN SET FRONTEND CONFIG ("query_queue_slots_estimator_strategy" = "CBE");
ADMIN SET FRONTEND CONFIG ("query_queue_v2_cpu_costs_per_slot" = "1000000000");

Symptom: CPU is often saturated

  • Adjustment: Decrease query_queue_v2_cpu_costs_per_slot
  • Effect: The same CPU cost for more slots, making concurrency more conservative

Symptom: Queries queue noticeably but CPU still has room

  • Adjustment: Increase query_queue_v2_cpu_costs_per_slot
  • Effect: The same CPU cost for fewer slots, making concurrency looser

Tune concurrency capacity​

If you only want to increase or decrease overall concurrency, do not switch between PBE, MBE, and CBE first. Tune total slot capacity first:

ADMIN SET FRONTEND CONFIG ("query_queue_v2_concurrency_level" = "<value>");

Recommended process:

  1. Start with default value 4.
  2. Observe remain_slots, max_slots, query_pending_length, CPU, memory, and query latency.
  3. If there is resource headroom but queries queue noticeably, gradually increase query_queue_v2_concurrency_level.
  4. If resources are often saturated or queries interfere with each other heavily, gradually decrease query_queue_v2_concurrency_level.
  5. Make small changes each time, such as 10% to 25%, and observe one business peak period before making another change.

Tuning Priority: Use query_queue_v2_concurrency_level to tune overall capacity first. Consider switching to MBE or PBE only after that. Do not change multiple parameters at the same time at the beginning, because it becomes hard to tell which parameter caused the effect.

Fallback Concurrency Cap​

query_queue_concurrency_limit is a fallback concurrency cap and applies to PBE, MBE, and CBE. Query Queue V2 first estimates the slots required by a query with the current estimator and checks whether total slots are available. After that, it checks whether the current number of running queries has reached query_queue_concurrency_limit.

The default value 0 means unlimited. Set it only when you need an absolute cap on the number of concurrently running queries:

ALTER WAREHOUSE default_warehouse SET ("query_queue_concurrency_limit" = "8");

Use query_queue_v2_concurrency_level to tune resource capacity first. Use query_queue_concurrency_limit only when you need to explicitly limit the number of queries run at the same time.

Memory admission​

Slots do not measure the memory that queries use. Memory admission controls memory with two settings:

  • query_queue_mem_used_pct_limit: the memory usage limit of a node. While the process memory usage of any alive node reaches this fraction of the node's memory limit, new queries wait in the queue. It is the same global session variable that Query Queue v1 uses.
  • query_mem_limit: the existing session variable that sets the memory limit of a query on each BE node.

query_queue_mem_used_pct_limit defaults to 0, which means that no query waits because of memory. Set it with SET GLOBAL.

Memory usage limit​

query_queue_mem_used_pct_limit is a fraction in [0, 1], such as 0.8 for 80%. It is compared with the memory usage of each node: the process memory that the node uses, divided by the memory limit of the node. The process memory includes not only queries but also loads, compaction, metadata, and the in-memory data cache. A query fails when either its query pool or the BE process runs out of memory, so comparing the process memory keeps a buffer against both limits, and new queries wait before a node runs out of memory.

The memory usage limit works as follows:

  • Each BE and CN node reports its memory usage every second, as set by the BE configuration item report_resource_usage_interval_ms. Only the leader FE receives these reports, and the leader FE makes the admission decisions.
  • While the memory usage of any alive node is at or above the limit, new queries wait in the queue. Running queries are not affected. Once every node is below the limit, the queued queries are admitted again. The decision is binary: there is no gradual throttling between the two states.
  • The memory usage limit is checked together with the slot pool and query_queue_concurrency_limit. A query is admitted only when all three allow it.
  • When no query that was admitted by the queue is running, one query is still admitted even if a node is over the limit. The memory may be held by loads, caches, or queries that bypass the queue, and keeping queued queries waiting cannot release it.
  • A node whose latest report is older than the global variable query_queue_fresh_resource_usage_interval_ms (5000 milliseconds by default) does not take part in the decision, so that a node that stops reporting cannot keep new queries waiting. A node that is not alive does not take part either.
  • The memory usage limit does not read or depend on resource groups.

Memory admission is part of the admission decision of Query Queue v2, so it applies only to queries that go through the query queue. The nodes are all BE and CN nodes of the cluster in a shared-nothing cluster, and all CN nodes of the cluster in a shared-data cluster.

Choose a limit​

A large part of the process memory is usually the in-memory data cache, which holds the decompressed pages that queries read from segment files. Its size is limited by the BE configuration item datacache_mem_size (20% of the process memory limit by default), and it grows as queries read data. BE gives this memory back when the process memory is high: above the BE configuration item memory_high_level (75 percent of the process memory limit by default), BE evicts the cache gradually, and above memory_urgent_level (85 by default), BE shrinks the cache immediately.

We recommend a limit between 0.75 and 0.85:

  • Within this range, when queries need more memory, the cache gives memory back as the process memory usage rises above 75%, and new queries wait only until the cache has shrunk.
  • Below 0.75, BE does not release the cache, so a node with a large cache can keep new queries waiting. The cluster then admits one query at a time, when nothing is running.
  • A lower limit leaves more room for the queries that are already running to grow. On a node that holds little besides queries, the room left before the query pool limit (90% of the process memory limit by default, as set by the BE configuration item query_max_memory_limit_percent) is 0.9 minus the limit.

Per-query memory limit on each node​

The session variable query_mem_limit sets the memory limit of a query on each BE node, in bytes. The default value 0 means no limit. To set it for the current session, run SET query_mem_limit = <bytes>;. To set it for all future sessions, run SET GLOBAL query_mem_limit = <bytes>;. For more information, see query_mem_limit.

On each node, BE applies the smallest of query_mem_limit, the resource group property big_query_mem_limit, and the limits of the parent memory trackers. When a query exceeds query_mem_limit, the error message contains Mem usage has exceed the limit of single query, You can change the limit by set session variable query_mem_limit.

Configure memory admission​

The following example sets the memory usage limit:

SET GLOBAL query_queue_mem_used_pct_limit = 0.8;

The following example limits each query to 8 GB of memory on each BE node in all future sessions:

SET GLOBAL query_mem_limit = 8589934592;

Whenever you set query_queue_mem_used_pct_limit, also set query_mem_limit. See Limitations for the reason.

Monitor memory admission​

To see the memory usage that is compared with the limit, run SHOW BACKENDS in a shared-nothing cluster or SHOW COMPUTE NODES in a shared-data cluster. The MemUsedPct column is the memory usage of each node, as a percentage of its memory limit. Only the leader FE receives the memory usage that the nodes report, so run the statement on the leader FE.

Limitations​

  • Admission reserves no memory. A newly admitted query adds to the usage only after it allocates memory and the next report arrives, so the queries admitted in one batch can together overshoot the limit. The slot pool and query_queue_concurrency_limit bound how many queries a batch admits, but only query_mem_limit bounds how much memory each of them can use on a node. This is why the FE log records a warning, once for each limit value, when the memory usage limit is set but the global default of query_mem_limit is 0.
  • One node at or above the limit makes all new queries wait, even if the other nodes have free memory, because queries usually run on all nodes.

Monitor query queues​

You can view information related to query queues using the following methods.

SHOW PROC​

You can check the number of running queries, and memory and CPU usages in BE nodes using SHOW PROC:

mysql> SHOW PROC '/backends'\G
*************************** 1. row ***************************
...
NumRunningQueries: 0
MemUsedPct: 0.79 %
CpuUsedPct: 0.0 %

SHOW PROCESSLIST​

You can check if a query is in a queue (when IsPending is true) using SHOW PROCESSLIST:

mysql> SHOW PROCESSLIST;
+------+------+---------------------+-------+---------+---------------------+------+-------+-------------------+-----------+
| Id | User | Host | Db | Command | ConnectionStartTime | Time | State | Info | IsPending |
+------+------+---------------------+-------+---------+---------------------+------+-------+-------------------+-----------+
| 2 | root | xxx.xx.xxx.xx:xxxxx | | Query | 2022-11-24 18:08:29 | 0 | OK | SHOW PROCESSLIST | false |
+------+------+---------------------+-------+---------+---------------------+------+-------+-------------------+-----------+

FE audit log​

You can check the FE audit log file fe.audit.log. The field PendingTimeMs indicates the time a query spent waiting in a queue, and its unit is milliseconds.

Monitoring metrics​

You can obtain metrics of query queues in StarRocks using the Monitor and Alert feature. The following FE metrics are derived from the statistical data of each FE node.

MetricUnitTypeDescription
starrocks_fe_query_queue_pendingCountInstantaneousThe current number of queries in the queue.
starrocks_fe_query_queue_totalCountInstantaneousThe total number of queries historically queued (including those currently running).
starrocks_fe_query_queue_timeoutCountInstantaneousThe total number of queries that have timed out while in the queue.
starrocks_fe_resource_group_query_queue_totalCountInstantaneousThe total number of queries historically queued in this resource group (including those currently running). The name label indicates the name of the resource group. This metric is supported from v3.1.4 onwards.
starrocks_fe_resource_group_query_queue_pendingCountInstantaneousThe number of queries currently in the queue for this resource group. The name label indicates the name of the resource group. This metric is supported from v3.1.4 onwards.
starrocks_fe_resource_group_query_queue_timeoutCountInstantaneousThe number of queries that have timed out while in the queue for this resource group. The name label indicates the name of the resource group. This metric is supported from v3.1.4 onwards.

SHOW RUNNING QUERIES​

From v3.1.4 onwards, StarRocks supports the SQL statement SHOW RUNNING QUERIES, which is used to display queue information for each query. The meanings of each field are as follows:

  • QueryId: The ID of the query.
  • ResourceGroupId: The ID of the resource group that the query hit. When there is no hit on a user-defined resource group, it will be displayed as "-".
  • StartTime: The start time of the query.
  • PendingTimeout: The time when the PENDING query will time out in the queue.
  • QueryTimeout: The time when the query times out.
  • State: The queue state of the query, where "PENDING" indicates it is in the queue, and "RUNNING" indicates it is currently executing.
  • Slots: The logical resource quantity requested by the query. In Query Queue v1, this value is usually 1. In Query Queue v2, this value is the estimated number of slots for the query.
  • Frontend: The FE node that initiated the query.
  • FeStartTime: The start time of the FE node that initiated the query.

Example:

MySQL [(none)]> SHOW RUNNING QUERIES;
+--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
| QueryId | ResourceGroupId | StartTime | PendingTimeout | QueryTimeout | State | Slots | Frontend | FeStartTime |
+--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
| a46f68c6-3b49-11ee-8b43-00163e10863a | - | 2023-08-15 16:56:37 | 2023-08-15 17:01:37 | 2023-08-15 17:01:37 | RUNNING | 1 | 127.00.00.01_9010_1692069711535 | 2023-08-15 16:37:03 |
| a6935989-3b49-11ee-935a-00163e13bca3 | 12003 | 2023-08-15 16:56:40 | 2023-08-15 17:01:40 | 2023-08-15 17:01:40 | RUNNING | 1 | 127.00.00.02_9010_1692069658426 | 2023-08-15 16:37:03 |
| a7b5e137-3b49-11ee-8b43-00163e10863a | 12003 | 2023-08-15 16:56:42 | 2023-08-15 17:01:42 | 2023-08-15 17:01:42 | PENDING | 1 | 127.00.00.03_9010_1692069711535 | 2023-08-15 16:37:03 |
+--------------------------------------+-----------------+---------------------+---------------------+---------------------+-----------+-------+---------------------------------+---------------------+
Rocky the happy otterStarRocks Assistant

AI generated answers are based on docs and other sources. Please test answers in non-production environments.