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- Creating Instance
- Naming with Consecutive Numeric Suffixes or Designated Pattern String
- Viewing Instance
- Upgrading Instance
- Downgrading Instance Configuration
- Terminating/Returning Instances
- Change from Pay-as-You-Go to Monthly Subscription
- Upgrading Instance Version
- Adding Routing Policy
- Public Network Bandwidth Management
- Connecting to Prometheus
- AZ Migration
- Setting Maintenance Time
- Setting Message Size
- Topic Management
- Consumer Group
- Monitoring and Alarms
- Smart Ops
- Permission Management
- Tag Management
- Querying Message
- Event Center
- Migration to Cloud
- Data Compression
- Instance Management
- CKafka Connector
- Practical Tutorial
- Practical Tutorial of CKafka Client
- Connector Practical Tutorial
- Connecting Flink to CKafka
- Connecting Schema Registry to CKafka
- Connecting Spark Streaming to CKafka
- Connecting Flume to CKafka
- Connecting Kafka Connect to CKafka
- Connecting Storm to CKafka
- Connecting Logstash to CKafka
- Connecting Filebeat to CKafka
- Multi-AZ Deployment
- Log Access
- Replacing Supportive Route (Old)
- Practice Tutorial for Cluster Bandwidth in High CPU Utilization Scenarios
- Practice Tutorial for Cluster Capacity Planning
- Troubleshooting
- API Documentation
- History
- Introduction
- API Category
- Making API Requests
- DataHub APIs
- ACL APIs
- Topic APIs
- DescribeTopicProduceConnection
- BatchModifyGroupOffsets
- BatchModifyTopicAttributes
- CreateConsumer
- CreateDatahubTopic
- CreatePartition
- CreateTopic
- CreateTopicIpWhiteList
- DeleteTopic
- DeleteTopicIpWhiteList
- DescribeDatahubTopic
- DescribeTopic
- DescribeTopicAttributes
- DescribeTopicDetail
- DescribeTopicSubscribeGroup
- FetchMessageByOffset
- FetchMessageListByOffset
- ModifyDatahubTopic
- ModifyTopicAttributes
- DescribeTopicSyncReplica
- Instance APIs
- Route APIs
- Other APIs
- Data Types
- Error Codes
- SDK Documentation
- General References
- Conducting Production and Consumption Pressure Testing on CKafka
- Configuration Guide for Common Parameters in CKafka
- Connecting to Legacy Self-Built Kafka
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- CKafka Data Reliability Description
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- Service Level Agreement
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- Glossary
Failure to Delete Expired Messages Promptly
Last updated: 2024-01-09 14:57:56
Issue Description
Expired messages are not deleted promptly.
Possible Causes
The message deletion mechanism of Kafka may cause a problem where expired messages are not deleted promptly in certain business scenarios. You may feel confused if you are unfamiliar with this mechanism. For example, the message timestamps in partition 0 and partition 7 are obviously different, but the expired messages in partition 0 are not deleted promptly.
Kafka Message Deletion Mechanism
Kafka data is stored in three dimensions: topic, partition, and data segment. The message data deletion conditions are as follows:
Message data is deleted in the unit of data segment based on the retention period.
Currently, the maximum size of a data segment is set to 1 GB. After a data segment reaches 1 GB in size, a new segment will be generated, and so on.
Only after all messages in a data segment expire will the segment be deleted.
If a message in a data segment is still within the retention period, such as the last row of a segment file, then the file will not be deleted.
For some reasons, messages are written unevenly and concentrated in a certain partition (such as partition 7), while some other partitions (such as partition 0) have little data. In this case, the size of the data segment in partition 0 does not reach 1 GB, so no new segments are generated; however, there is data in the entire data segment within the retention period. Therefore, messages in partition 0 will not be deleted.
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