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Status

Current state: Under Discussion

Discussion thread: here

JIRA: here

Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).

Motivation

This KIP builds upon KIP-932, which introduced the concept of Queues/Cooperative Consumption in Kafka. KIP-932 implementation introduced Share Group, Share Partitions and Delayed Share Fetch purgatory to enable this cooperative consumption behavior. The proposed metrics in this KIP will enhance the debugging and monitoring capabilities for cooperative consumption. By providing a more granular view of the underlying mechanisms, these metrics will aid in identifying and resolving potential issues and optimizing performance.

Public Interfaces

RationaleMetric NameTypeGroupTagsDescriptionJMX Bean
Similar to existing fetch metric TotalFetchRequestsPerSec  for Fetch, which record all topic cumulative and individual topic stats.TotalShareFetchRequestsPerSecMeterShareGroupMetricstopic:{topic}The fetch request rate per second.

kafka.server:type=ShareGroupMetrics,name=TotalShareFetchRequestsPerSec

kafka.server:type=ShareGroupMetrics,name=TotalShareFetchRequestsPerSec,topic={topic}

Similar to existing fetch metric FailedFetchRequestsPerSec  for Fetch, which record all topic cumulative and individual topic stats.FailedShareFetchRequestsPerSecMeterShareGroupMetricstopic:{topic}The share fetch request rate for requests that failed.

kafka.server:type=ShareGroupMetrics,name=FailedShareFetchRequestsPerSec

kafka.server:type=ShareGroupMetrics,name=FailedShareFetchRequestsPerSec,topic={topic}

Similar to above defined share fetch metrics, this metirc tracks the number of share release requests stats.TotalShareReleaseRequestsPerSecMeterShareGroupMetricstopic:{topic}The share release request rate per second.

kafka.server:type=ShareGroupMetrics,name=TotalShareReleaseRequestsPerSec

kafka.server:type=ShareGroupMetrics,name=TotalShareReleaseRequestsPerSec,topic={topic}

Similar to above defined failed fetch metrics, this metirc tracks the number of failed share release requests stats.FailedShareReleaseRequestsPerSecMeterShareGroupMetricstopic:{topic}The share release request rate for requests that failed

kafka.server:type=ShareGroupMetrics,name=FailedShareReleaseRequestsPerSec

kafka.server:type=ShareGroupMetrics,name=FailedShareReleaseRequestsPerSec,topic={topic}

Similar to above defined failed fetch metrics, this metirc tracks the number of failed share acknowledgement requests stats.FailedShareAcknowledgementRequestsPerSecMeterShareGroupMetricstopic:{topic}The share acknowledgement request rate for requests that failed

kafka.server:type=ShareGroupMetrics,name=FailedShareAcknowledgementRequestsPerSec

kafka.server:type=ShareGroupMetrics,name=FailedShareAcknowledgementRequestsPerSec,topic={topic}

In shared consumption, topic-partitions are locked before fetching data to ensure exclusive access for each share fetch request. Multiple consumers can request the same partitions, but only a subset can acquire locks.

This metric represents the ratio of successfully fetched topic-partitions to the total requested in a share fetch. A low ratio indicates that many requests are unable to fetch from a significant portion of the requested partitions.

Potential Causes for Low Ratios:

  • High Share Consumer Count: A large number of share consumers can lead to increased competition for partitions.
  • Strict Locks Limit: A low group.share.partition.max.record.locks value can exclude partition a share consumer can acquire, if reached.
  • Fewer Topic Partitions: Fewer partitions can intensify competition, especially with a high share consumer count.
  • Suboptimal Partition Assignments: Inefficient assignments can hinder efficient consumption.

This metric, in conjunction with other metrics and configuration parameters, can help optimize shared consumption by adjusting consumer counts, partition limits, and partition assignments.

RequestTopicPartitionsFetchRatioMeterShareGroupMetrics

The ratio of topic-partitions acquired to the total number of topic-partitions in share fetch request.

kafka.server:type=ShareGroupMetrics,name=RequestTopicPartitionsFetchRatio
Specifies the number of share fetch requests where no topic-partition can be acquired for fetch.RequestTopicPartitionsFetchEmptyCountGaugeShareGroupMetrics

The number of share fetch requests completed without any acquired topic-partition.

kafka.server:type=ShareGroupMetrics,name=RequestTopicPartitionsFetchEmptyCount
Tracks the number of client timeouts acknowledging share fetches. Timeout is set by group.share.record.lock.duration.ms.AcquisitionLockTimeoutCountGaugeSharePartitionMetricsshare-partition : {group-topic-partition}

The number of times acquisition lock timed out for share partition.

kafka.server:type=SharePartitionMetrics,name=AcquisitionLockTimeoutCount,share-partition={group-topic-partition}
Defines the maximum number of in-flight messages per share partition, as set by group.share.partition.max.record.locks. A share partition cannot be acquired for fetching messages if this limit is reached.InFlightMessageCountGaugeSharePartitionMetricsshare-partition : {group-topic-partition}

The number of in-flight messages for the share partition.

kafka.server:type=SharePartitionMetrics,name=InFlightMessageCount,share-partition={group-topic-partition}
Specifies the number of batches currently being processed by a share partition. This metric provides insights into memory consumption and performance bottlenecks, aiding in optimization efforts.InFlightBatchCountGaugeSharePartitionMetricsshare-partition : {group-topic-partition}

The number of in-flight batches for the share partition.

kafka.server:type=SharePartitionMetrics,name=InFlightBatchCount,share-partition={group-topic-partition}
Specifies the number of messages in a single in-flight batch.InFlightBatchMessageCountGaugeSharePartitionMetricsshare-partition : {group-topic-partition}

The number of messages in the in-flight batch.

kafka.server:type=SharePartitionMetrics,name=InFlightBatchMessageCount,share-partition={group-topic-partition}
Similar to IncrementalFetchSessionEvictionsPerSec ShareSessionEvictionsPerSecMeterShareSessionCache

The share session eviction rate per second.

kafka.server:type=ShareSessionCache,name=ShareSessionEvictionsPerSec
Similar to NumIncrementalFetchPartitionsCached SharePartitionsCountGaugeShareSessionCache

The number of cached share partitions.

kafka.server:type=ShareSessionCache,name=SharePartitionsCount
Similar to NumIncrementalFetchSessions ShareSessionsCountGaugeShareSessionCache

The number of cached share sessions.

kafka.server:type=ShareSessionCache,name=ShareSessionsCount
Similar to ExpiresPerSec  for other existing delayed operations i.e. DelayedFetch , etc.ExpiresPerSecMeterDelayedShareFetchMetrics

The expired delayed share fetch operation rate per second.

kafka.server:type=DelayedShareFetchMetrics,name=ExpiresPerSec
Add ShareFetch  to existing MessageConversionsPerSec metric.

MessageConversionsPerSec

(ShareFetch added to existing metric for Produce and Fetch)

MeterBrokerTopicMetricstopic : {topic}

The message format conversion rate, for Produce, Fetch or ShareFetch requests, per topic. Omitting ‘topic={…}’ will yield the all-topic rate.

kafka.server:type=BrokerTopicMetrics,name={Produce|Fetch|ShareFetch}MessageConversionsPerSec,topic=([-.\w]+)
Add ShareFetch  to existing purgatory metrics.PurgatorySize (ShareFetch)GaugeDelayedOperationPurgatorydelayedOperation : ShareFetch

The number of requests waiting in the share fetch purgatory. This is high if share consumers use a large value for fetch.wait.max.ms

kafka.server:type=DelayedOperationPurgatory,delayedOperation=ShareFetch,name=PurgatorySize
Add ShareFetch  to existing purgatory metrics.NumDelayedOperations (ShareFetch)GaugeDelayedOperationPurgatorydelayedOperation : ShareFetch

The number of delayed operations for share fetch purgatory.

kafka.server:type=DelayedOperationPurgatory,delayedOperation=ShareFetch,name=NumDelayedOperations

Move share-group-metrics  defined in KIP-932 to Yammer based metrics.

Proposed Changes

We are proposing to add the above metrics. This will give a more insightful set of metrics for those using the Cooperative Consumption.

Compatibility, Deprecation, and Migration Plan

These are new metrics and as such shouldn't have compatibility concerns.

Test Plan

Unit and integration tests.

Rejected Alternatives

  • The Meter metrics can be either Yammer or Kafka Metrics. To ensure uniformity in metric naming conventions and to align with existing Fetch and ShareFetch metrics (such as PurgatorySize), we suggest using Yammer metrics for all metrics introduced in this KIP, rather than Kafka Metrics.
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