🐝
Mess around software system design
  • README
  • ArchitectureTradeOffAnalysis
    • Estimation
    • Middleware
    • Network
    • Server
    • Storage
  • Conversion cheat sheet
  • Scenarios
    • TinyURL
      • Estimation
      • Flowchart
      • Shortening mechanisms
      • Rest API
      • Performance
      • Storage
      • Follow-up
    • TaskScheduler
      • JDK delay queue
      • Timer based
      • RabbitMQ based
      • Kafka-based fixed delay time
      • Redis-based customized delay time
      • MySQL-based customized delay time
      • Timer TimingWheel
      • Industrial Scheduler
      • Workflow Engine
      • Airflow Arch
    • GoogleDrive
      • Estimation
      • Flowchart
      • Storage
      • Follow-up
    • Youtube
      • Estimation
      • Flowchart
      • Performance
      • Storage
      • Follow-up
      • Netflix
    • Uber
      • Estimation
      • Rest api
      • Flowchart
      • KNN algorithms
      • Geohash-based KNN mechanism
      • Redis implementation
      • Storage
    • Twitter
      • Estimation
      • Flowchart
      • Storage
      • Scalability
      • Follow-up
    • Instant messenger
      • Architecture overview
      • Presence
      • Unread count
      • Notifications
      • Read receipt
      • Large group chat
      • Storage-Offline 1:1 Chat
      • Storage-Offline group chat
      • Storage-Message roaming
      • NonFunc-Realtime
      • NonFunc-Reliability
      • NonFunc-Ordering
      • NonFunc-Security
      • Livecast-LinkedIn
    • Distributed Lock
      • Single machine
      • AP model based
      • CP model based
      • Chubby-TODO
    • Payment system
      • Resilience
      • Consistency
      • Flash sale
    • Key value store
      • Master-slave KV
      • Peer-to-peer KV
      • Distributed cache
  • Time series scenarios
    • Observability
      • TimeSeries data
      • Distributed traces
      • Logs
      • Metrics
      • NonFunc requirments
  • Search engine
    • Typeahead
    • Search engine
    • Distributed crawler
      • Estimation
      • Flowchart
      • Efficiency
      • Robustness
      • Performance
      • Storage
      • Standalone implementation
      • Python Scrapy framework
    • Stream search
  • Big data
    • GFS/HDFS
      • Data flow
      • High availability
      • Consistency
    • Map reduce
    • Big table/Hbase
    • Haystack
    • TopK
    • Stateful stream
    • Lambda architecture
    • storm架构
    • Beam架构
    • Comparing stream frameworks
    • Instagram-[TODO]
  • MicroSvcs
    • Service Registry
      • Flowchart
      • Data model
      • High availability
      • Comparison
      • Implementation
    • Service governance
      • Load balancing
      • Circuit breaker
      • Bulkhead
      • Downgrade
      • Timeout
      • API gateway
      • RateLimiter
        • Config
        • Algorithm comparison
        • Sliding window
        • Industrial impl
    • MicroSvcs_ConfigCenter-[TODO]
    • MicroSvcs_Security
      • Authentication
      • Authorization
      • Privacy
  • Cache
    • Typical topics
      • Expiration algorithm
      • Access patterns
      • Cache penetration
      • Big key
      • Hot key
      • Distributed lock
      • Data consistency
      • High availability
    • Cache_Redis
      • Data structure
      • ACID
      • Performance
      • Availability
      • Cluster
      • Applications
    • Cache_Memcached
  • Message queue
    • Overview
    • Kafka
      • Ordering
      • At least once
      • Message backlog
      • Consumer idempotency
      • High performance
      • Internal leader election
    • MySQL-based msg queue
    • Other msg queues
      • ActiveMQ-TODO
      • RabbitMQ-TODO
      • RocketMQ-TODO
      • Comparison between MQ
  • Traditional DB
    • Index data structure
    • Index categories
    • Lock
    • MVCC
    • Redo & Undo logs
    • Binlog
    • Schema design
    • DB optimization
    • Distributed transactions
    • High availability
    • Scalability
    • DB migration
    • Partition
    • Sharding
      • Sharding strategies
      • Sharding ID generator overview
        • Auto-increment key
        • UUID
        • Snowflake
        • Implement example
      • Cross-shard pagination queries
      • Non-shard key queries
      • Capacity planning
  • Non-Traditional DB
    • NoSQL overview
    • Rum guess
    • Data structure
    • MySQL based key value
    • KeyValueStore
    • ObjectStore
    • ElasticSearch
    • TableStore-[TODO]
    • Time series DB
    • DistributedAcidDatabase-[TODO]
  • Java basics
    • IO
    • Exception handling
  • Java concurrency
    • Overview
      • Synchronized
      • Reentrant lock
      • Concurrent collections
      • CAS
      • Others
    • Codes
      • ThreadLocal
      • ThreadPool
      • ThreadLifeCycle
      • SingletonPattern
      • Future
      • BlockingQueue
      • Counter
      • ConcurrentHashmap
      • DelayedQueue
  • Java JVM
    • Overview
    • Dynamic proxy
    • Class loading
    • Garbage collection
    • Visibility
  • Server
    • Nginx-[TODO]
  • Distributed system theories
    • Elementary school with CAP
    • Consistency
      • Eventual with Gossip
      • Strong with Raft
      • Tunable with Quorum
      • Fault tolerant with BFT-TODO
      • AutoMerge with CRDT
    • Time in distributed system
      • Logical time
      • Physical time
    • DDIA_Studying-[TODO]
  • Protocols
    • ApiDesign
      • REST
      • RPC
    • Websockets
    • Serialization
      • Thrift
      • Avro
    • HTTP
    • HTTPS
    • Netty-TODO
  • Statistical data structure
    • BloomFilter
    • HyperLoglog
    • CountMinSketch
  • DevOps
    • Container_Docker
    • Container_Kubernetes-[TODO]
  • Network components
    • CDN
    • DNS
    • Load balancer
    • Reverse proxy
    • 云中网络-TODO
  • Templates
    • interviewRecord
  • TODO
    • RecommendationSystem-[TODO]
    • SessionServer-[TODO]
    • Disk
    • Unix philosophy and Kafka
    • Bitcoin
    • Design pattern
      • StateMachine
      • Factory
    • Akka
    • GoogleDoc
      • CRDT
Powered by GitBook
On this page
  • Fixed time delay (Kafka based)
  • Flowchart
  • Rebalance
  • Consistency
  • Cons

Was this helpful?

  1. Scenarios
  2. TaskScheduler

Kafka-based fixed delay time

PreviousRabbitMQ basedNextRedis-based customized delay time

Last updated 1 year ago

Was this helpful?

Fixed time delay (Kafka based)

Flowchart

  • Delay topics are divided by different delay intervals.

  • Each delay topic corresponds to a dedicated consumer group.

Rebalance

Probem

  • Each time when dedicated consumer groups consume a message, the consumer group will sleep for certain period.

  • During the sleep, Kafka will judge that consumers are crashed. And a rebalance will be performed.

Solution

  1. Consumer group pulls a message (suppose offset = N after consumption), and check the remaining delay time t.

  2. Consumer group pauses the consumption and slept for delay time t.

    • During the pause, consumer group will still have poll request, but it won't actually poll data.

  3. After sleep, consumer group resumes from offset = N.

Consistency

Problem

  • Commit message first vs forward to business topic first?

Commit message first, then forward

  • If machine crashed in the middle, the message will not be delivered to business topic.

Forward message first, then commit

  • As long as message receiver could guarantee idempotency, then this will be the ideal solution.

Cons

  • Delay time must be fixed ahead of time. For example, in the flowchart above, delay time is set to 1, 3, or 10 mins.

  • There might be dramatically different load on different delay partitions. For example, maybe most of (80%) traffic lands on 3min delay period.

Fixed time delay (Kafka based)
Flowchart
Rebalance
Probem
Solution
Consistency
Problem
Commit message first, then forward
Forward message first, then commit
Cons
Delay Queue Components
Commit message first
Forward message first