Replicating application data into materialized views
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The document discusses replicating application data into materialized views or publishing data changes to Kafka. It notes issues with caching like staleness and network latency. It provides code examples of caching user data and checking for cache misses or stale data. Resources mentioned include the NNGroup on response times, Kafka documentation, I ♥ Logs book, RocksDB and Bottled Water.
Replicating application data into materialized views
- 1. Replicating Application Data Into Materialized Views -or- Why You Should Publish Data Changes to Kafka Zach Cox @zcox Jack Henry & Associates Iowa Code Camp Dec 2015
- 12. I ♥ Logs book
- 16. def getUser(id: String): User = readUserFromCache(id) match { case Some(user) => user case None => val user = readUserFromDatabase(id) writeUserToCache(user) user }
- 17. def getUser(id: String): User = readUserFromCache(id) match { case Some(user) => user case None => //cache miss! val user = readUserFromDatabase(id) writeUserToCache(user) user }
- 18. def getUser(id: String): User = readUserFromCache(id) match { case Some(user) => user //stale? case None => //cache miss! val user = readUserFromDatabase(id) writeUserToCache(user) user }
- 19. def getUser(id: String): User = readUserFromCache(id) match { //network latency case Some(user) => user //stale? case None => //cache miss! val user = readUserFromDatabase(id) writeUserToCache(user) user }
- 23. Elasticsearch