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.

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

4. http://www.nngroup.com/articles/response-times-3-important-limits/

11. Kafka documentation

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
}

20. RocksDB
Bottled Water

23. Elasticsearch

24. https://github.com/zcox/data-replication-example