Let's talk about the cache!
summary
Covers JSR-107 terminology and concrete patterns: Cache Aside, Write-Behind, Read/Write Through with Java CacheLoader/CacheWriter examples and tradeoffs (synchronous write-through keeps cache consistent; asynchronous write-behind batches, conflates updates, and throttles DB load). Claims a CPU-cycle-to-latency analogy (if CPU = 1s, DRAM ≈ 6 minutes, SSD 2–6 days, HDD 1–12 months) to justify hot-set caching. Shows single-node local L1 + remote L2, mirrored/replicated/partition+replica clusters, Terracotta/Hazelcast pairing with Cassandra/Redis/MongoDB and compute-grid collocation for in-memory processing.
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chapters (16)
- 0:00Introduction to caching
- 1:40Why use a cache
- 4:52Cache basics and JSR 107
- 8:03Read-through cache pattern
- 10:31Write-through cache pattern
- 12:41Write-behind cache pattern
- 21:48Refresh-ahead cache pattern
- 24:15Cache scalability options
- 33:20Distributed cache vs in-memory data grid
- 35:51In-memory compute grid
- 38:41Event processing in caches
- 40:06In-memory databases vs caches
- 41:54Cache vs NoSQL consistency
- 43:44Cache as partner to NoSQL
- 46:11Open source in-memory grids
- 48:17Q&A and closing remarks
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