6.2 Distributed locking

  • Redis in Action – Home
  • Foreword
  • Preface
  • Part 1: Getting Started
  • Part 2: Core concepts
  • 1.3.1 Voting on articles
  • 1.3.2 Posting and fetching articles
  • 1.3.3 Grouping articles
  • 4.2.1 Configuring Redis for replication
  • 4.2.2 Redis replication startup process
  • 4.2.3 Master/slave chains
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  • 5.1 Logging to Redis
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  • 5.3.1 Loading the location tables
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  • 5.4.2 One Redis server per application component
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  • 8.1.1 User information
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  • 9.1.1 The ziplist representation
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  • Chapter 10: Scaling Redis
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  • 10.1 Scaling reads
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  • 11.1.1 Loading Lua scripts into Redis
  • 11.1.2 Creating a new status message
  • 11.2 Rewriting locks and semaphores with Lua
  • 11.3 Doing away with WATCH/MULTI/EXEC
  • 11.4 Sharding LISTs with Lua
  • 11.5 Summary
  • 11.2.1 Why locks in Lua?
  • 11.2.2 Rewriting our lock
  • 11.2.3 Counting semaphores in Lua
  • 11.4.1 Structuring a sharded LIST
  • 11.4.2 Pushing items onto the sharded LIST
  • 11.4.4 Performing blocking pops from the sharded LIST
  • A.1 Installation on Debian or Ubuntu Linux
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  • B.1 Forums for help
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  • Buy the paperback
  • Redis in Action – Home
  • Foreword
  • Preface
  • Part 1: Getting Started
  • Part 2: Core concepts
  • 1.3.1 Voting on articles
  • 1.3.2 Posting and fetching articles
  • 1.3.3 Grouping articles
  • 4.2.1 Configuring Redis for replication
  • 4.2.2 Redis replication startup process
  • 4.2.3 Master/slave chains
  • 4.2.4 Verifying disk writes
  • 5.1 Logging to Redis
  • 5.2 Counters and statistics
  • 5.3 IP-to-city and -country lookup
  • 5.4 Service discovery and configuration
  • 5.1.1 Recent logs
  • 5.1.2 Common logs
  • 5.2.2 Storing statistics in Redis
  • 5.3.1 Loading the location tables
  • 5.3.2 Looking up cities
  • 5.4.1 Using Redis to store configuration information
  • 5.4.2 One Redis server per application component
  • 5.4.3 Automatic Redis connection management
  • 8.1.1 User information
  • 8.1.2 Status messages
  • 9.1.1 The ziplist representation
  • 9.1.2 The intset encoding for SETs
  • Chapter 10: Scaling Redis
  • Chapter 11: Scripting Redis with Lua
  • 10.1 Scaling reads
  • 10.2 Scaling writes and memory capacity
  • 10.3 Scaling complex queries
  • 10.2.2 Creating a server-sharded connection decorator
  • 10.3.1 Scaling search query volume
  • 10.3.2 Scaling search index size
  • 10.3.3 Scaling a social network
  • 11.1.1 Loading Lua scripts into Redis
  • 11.1.2 Creating a new status message
  • 11.2 Rewriting locks and semaphores with Lua
  • 11.3 Doing away with WATCH/MULTI/EXEC
  • 11.4 Sharding LISTs with Lua
  • 11.5 Summary
  • 11.2.1 Why locks in Lua?
  • 11.2.2 Rewriting our lock
  • 11.2.3 Counting semaphores in Lua
  • 11.4.1 Structuring a sharded LIST
  • 11.4.2 Pushing items onto the sharded LIST
  • 11.4.4 Performing blocking pops from the sharded LIST
  • A.1 Installation on Debian or Ubuntu Linux
  • A.2 Installing on OS X
  • B.1 Forums for help
  • B.4 Data visualization and recording
  • Buy the paperback

    6.2 Distributed locking

    Generally, when you “lock” data, you first acquire the lock, giving you exclusive access to the data. You then perform your operations. Finally, you release the lock to others. This sequence of acquire, operate, release is pretty well known in the context of shared-memory data structures being accessed by threads. In the context of Redis, we’ve been using WATCH as a replacement for a lock, and we call it optimistic locking, because rather than actually preventing others from modifying the data, we’re notified if someone else changes the data before we do it ourselves.

    With distributed locking, we have the same sort of acquire, operate, release operations, but instead of having a lock that’s only known by threads within the same process, or processes on the same machine, we use a lock that different Redis clients on different machines can acquire and release. When and whether to use locks or WATCH will depend on a given application; some applications don’t need locks to operate correctly, some only require locks for parts, and some require locks at every step.

    One reason why we spend so much time building locks with Redis instead of using operating system–level locks, language-level locks, and so forth, is a matter of scope. Clients want to have exclusive access to data stored on Redis, so clients need to have access to a lock defined in a scope that all clients can see—Redis. Redis does have a basic sort of lock already available as part of the command set (SETNX), which we use, but it’s not full-featured and doesn’t offer advanced functionality that users would expect of a distributed lock.

    Throughout this section, we’ll talk about how an overloaded WATCHed key can cause performance issues, and build a lock piece by piece until we can replace WATCH for some situations.