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Updated on 2025-03-03

Summary of transaction operations application of Redis in counters and personnel records

Solve transaction operations of counters and personnel records

Redis is a high-performance key-value storage system that supports a variety of data types, such as strings, lists, collections, hash tables, and ordered collections. Thanks to its single-threaded model and in-memory data storage, Redis performs exceptionally well when handling counters and simple transaction operations. Here is a guide on how to resolve transaction operations recorded by counters and people in Redis.

Counter operation

Redis providesINCR、DECR、INCRBYandDECRBYetc. commands that are used to atomically increment or decrement the integer values ​​stored in Redis. These commands are atomic, meaning they are not interrupted by other commands during execution, so they are ideal for use as counters.

  • INCR key: Increase the numeric value stored in the key by one. If the key does not exist, the value of the key will be initialized to 0 and then the INCR operation will be performed.
  • DECR key: Decrement the numeric value stored in the key by one. If the key does not exist, the value of the key will be initialized to 0 and then the DECR operation will be performed.
  • INCRBY key increment: Add the value stored in key to the specified increment.
  • DECRBY key decrement: Subtract the value stored in key from the specified decrement.

Transaction operations recorded by personnel

For transaction operations recorded by people, Redis provides two ways to ensure the atomicity and consistency of operations.

Transaction

A Redis transaction is a set of commands executed in sequence. During the transaction execution, the server does not interrupt the transaction to execute other commands. Redis transaction passesMULTI、EXEC、DISCARDandWATCHCommand to implement.

  • MULTI: Mark the beginning of a transaction.
  • EXEC: Execute commands in all transaction blocks.
  • DISCARD: Cancel the transaction and abandon all commands in the transaction block.
  • WATCH: Monitor one or more keys, if these keys are modified before the transaction is executed (i.e. they are changed by commands from other clients), the transaction will be interrupted.

Example: Add or update a person record using a transaction

# Start a transactionMULTI  
# Set or update personnel information (assuming that hash table storage)HSET person:1001 name "John Doe"  
HSET person:1001 age 30  
HSET person:1001 email "johndoe@"  
# Execute transactionsEXEC

In this example, we useHSETCommands to set or update personnel information, these commands are contained in a transaction, so they are either executed successfully or they are not executed (if the transaction is interrupted for some reason).

Multiplexing (Pipeline)

While Redis transactions provide atomicity guarantees, in some cases you may not need full atomicity, but rather want to reduce the number of network round trips to improve performance. At this time, you can use Redis's Pipeline function. Pipeline allows you to package multiple commands together and then send them to the Redis server at once to execute, and the server will package the results of all commands together and return.

Example: Add or update a person record using Pipeline

In programming (taking Python and redis-py libraries as examples):

import redis  
# Connect to the Redis serverr = (host='localhost', port=6379, db=0)  
# Create a pipelinepipe = ()  
# Add commands in the pipeline('person:1002', 'name', 'Jane Smith')  
('person:1002', 'age', 25)  
('person:1002', 'email', 'janesmith@')  
# Execute all commands in the pipeline()

In this example, we usepipeline()Method creates a pipeline and adds a series ofhsetCommand to set or update personnel information. Then, we useexecute()Method executes all commands in the pipeline at once.

Things to note

  • When using Redis transactions, make sure your Redis server version supports transaction functionality (supported by Redis 2.0 and above).
  • Since Redis is single-threaded, commands in transactions are executed in order without concurrency problems. However, if your operations depend on the state of an external system (such as a database), then you may need additional synchronization mechanisms to ensure consistency.
  • When using Pipeline, be careful not to put too many commands into a pipeline, as this may cause the server to handle timeouts or insufficient memory. Typically, you can adjust the number of commands in the pipeline based on network latency and command execution time.

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