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Split View: 캐시 데이터베이스란 무언인가?(Redis)

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캐시 데이터베이스란 무언인가?(Redis)

10분 테코톡 저문, 라온의 Cache & Redis 영상을 보고 정리하였습니다.

캐시 사용이유.

  • 시간적 지역성: 이전에 접근했던 데이터에 또 다시 접근할 확률이 높음
  • 공간적 지역성: 인접된 곳의 데이터를 계속 접근할 확률이 높음

캐시 전략 패턴

읽기 전략

Look Aside Pattern 캐시에 데이터가 없을 때, DB에서 데이터를 가져오는 전략. 장점: 캐시에 문제가 생기는 경우 DB로 요청을 위임 단점: 캐시 DB데이터 정합성 유지 어려움. 첫 조회시 DB과부하 발생

Read Through Pattern 항상 Cache로 부터 데이터를 읽는 전략. 장점: 캐시, DB간의 데이터 정합성 보장 단점: 캐시가 죽으면 어플리케이션에 문제 발생

쓰기 전략

Write Around 쓰기우회. 캐시에 직접쓰지 않고 DB에 쓴다. 만약 읽기전략과 혼합해서 사용할 때는 캐시 miss가 발생할 경우 캐시 스토어에 쓰기도 한다. 장정: 성능이 좋음. 불필요한 데이터를 캐시에 올리지 않고 바로 쓰기 때문에 리소스를 아낄 수 있다. 단점: 캐시 DB간의 연결점이 없기 때문에 정합성 유지가 어려움

Write Back 캐시에 쓰기작업을 먼저 쓰고, 나중에 DB에 반영한다. 한꺼번에 많은양의 쓰기작업을 scheduling을 한다. 장점: 쓰기횟수 비용을 줄일 수 있음 단점: 캐시의 데이터 유실 가능성

Write Trough 모든 데이터 쓰기를 Cache를 거쳐서 진행한다. 장점: 데이터 정합성이 보장됨. 단점: 필수적으로 두번의 쓰기가 항상 진행되기 때문에 성능이 고려되어야 함.

캐시사용시 주의 사항

  1. 자주 사용되면서 변경되지 않는 데이터
  2. 유실되어도 크게 문제가 없는 데이터
  3. 데이터베이스와 함께 사용할 때 데이터 정합성 문제 고려되어야

Redis (Remote Dictionary)

Key-value구조. Hashmap과 비슷함. memory기반의 key-value store. 캐시 구현방법 Memcached, Redis, Local memory기반의 임시 작업 큐, 실시간 채팅, 메시지 브로커로도 활용됨.

특징

  • Get/Set의 경우 10만 TPS 가능.
  • 다양한 자료구조 제공(Collection)
  • Key: string
  • Value: Hash, List Set, Sorted Set
  • Single Thread
  • 한번에 하나의 명령만을 처리
  • Race condition이 (거의) 발생하지 않음
  • Persistence: 메모리에 저장된 데이터를 디스크에 영속화할 수 있다.
    • RDB(Redis Database Backup): 압축하여 저장하기 때문에 크기가 작음. 스냅샷 남김
    • AOF(Append Only File): insert, update, delete가 일어날 때마다 Log파일에 기록. 크기가 크고 복원 소요시간 김.

Redis 우아하게 사용하기

  1. 데이터 타입에 따른 적절한 자료구조 사용 sorted set의 정렬기능 활용하면, SQL의 ORDERBY(정렬), DISTINCT(중복제거) 를 한번에 해결 가능하다.

  2. O(N) 명령어 주의 KEYS/FLUSHALL , FLUSHDB, DELETE Collections , Get All Collections 같은 O(N)명령어를 실행하면, single thread인 Redis가 다른 명령어를 처리하지 못할 수 있다.

  3. 메모리 관리 메모리 단편화 (내부단편화, 외부 단편화) 발생. 사용가능한 공간이 충분함에도 새로운 메모리 공간 할당이 불가함. -> RSS(Resident Set Size) 모니터링 필요

  4. 목적성 캐시용인지 저장소용인지 명확히 구분하여 Persistent 기능을 끌 수 있으면 끄자.

References

What Is a Cache Database? (Redis)

This article is a summary based on the video 10-minute Techie Talk: Cache & Redis by Jeomun and Raon.

Why Use Cache

  • Temporal locality: There is a high probability of accessing data that was previously accessed
  • Spatial locality: There is a high probability of continuously accessing data in adjacent locations

Cache Strategy Patterns

Read Strategies

Look Aside Pattern A strategy that fetches data from the DB when the data is not in the cache. Advantage: If there is a problem with the cache, requests are delegated to the DB Disadvantage: Difficult to maintain data consistency between cache and DB. DB overload occurs on first query

Read Through Pattern A strategy that always reads data from the cache. Advantage: Guarantees data consistency between cache and DB Disadvantage: If the cache goes down, it causes application problems

Write Strategies

Write Around Write bypass. Data is written directly to the DB, not to the cache. If used in combination with a read strategy, it also writes to the cache store when a cache miss occurs. Advantage: Good performance. Resources are saved by not putting unnecessary data in the cache and writing directly. Disadvantage: Difficult to maintain consistency because there is no connection between cache and DB

Write Back Write operations are first written to the cache, then reflected in the DB later. A large number of write operations are scheduled at once. Advantage: Can reduce write frequency costs Disadvantage: Possibility of data loss in the cache

Write Through All data writes go through the Cache. Advantage: Data consistency is guaranteed. Disadvantage: Performance must be considered since two writes are always required.

Precautions When Using Cache

  1. Data that is frequently used but rarely changes
  2. Data where loss is not a critical issue
  3. Data consistency issues must be considered when used with a database

Redis (Remote Dictionary)

Key-value structure. Similar to a HashMap. Memory-based key-value store. Cache implementation methods include Memcached, Redis, and local memory-based approaches. Also used for temporary work queues, real-time chat, and message brokers.

Characteristics

  • Can handle 100,000 TPS for Get/Set operations.
  • Provides various data structures (Collections)
  • Key: string
  • Value: Hash, List, Set, Sorted Set
  • Single Thread
  • Processes only one command at a time
  • Race conditions (almost) never occur
  • Persistence: Data stored in memory can be persisted to disk.
    • RDB (Redis Database Backup): Small in size because it is compressed and stored. Takes snapshots.
    • AOF (Append Only File): Records to a log file every time an insert, update, or delete occurs. Large in size and takes longer to restore.

Using Redis Gracefully

  1. Use appropriate data structures based on data types By leveraging the sorting feature of sorted sets, you can accomplish SQL ORDER BY (sorting) and DISTINCT (deduplication) at once.

  2. Be cautious with O(N) commands Executing O(N) commands like KEYS/FLUSHALL, FLUSHDB, DELETE Collections, or Get All Collections may prevent single-threaded Redis from processing other commands.

  3. Memory management Memory fragmentation (internal fragmentation, external fragmentation) occurs. New memory space allocation may be impossible even when there is sufficient available space. Therefore, RSS (Resident Set Size) monitoring is necessary.

  4. Purpose clarity Clearly distinguish whether it is for caching or for storage, and turn off the Persistence feature if possible.

References

Quiz

Q1: What is the main topic covered in "What Is a Cache Database? (Redis)"? What Is a Cache Database? (Redis)

Q2: Why Use Cache? Temporal locality: There is a high probability of accessing data that was previously accessed Spatial locality: There is a high probability of continuously accessing data in adjacent locations

Q3: Explain the core concept of Cache Strategy Patterns. Read Strategies Look Aside Pattern A strategy that fetches data from the DB when the data is not in the cache. Advantage: If there is a problem with the cache, requests are delegated to the DB Disadvantage: Difficult to maintain data consistency between cache and DB.

Q4: What are the key aspects of Precautions When Using Cache? Data that is frequently used but rarely changes Data where loss is not a critical issue Data consistency issues must be considered when used with a database

Q5: How does Redis (Remote Dictionary) work? Key-value structure. Similar to a HashMap. Memory-based key-value store. Cache implementation methods include Memcached, Redis, and local memory-based approaches. Also used for temporary work queues, real-time chat, and message brokers.