The document discusses improving performance at Twitter through caching and message queue optimizations. It describes four caching policies implemented including a vector, row, fragment, and page cache that achieved hit rates from 40-99%. A message queue was rewritten in Scala for better scalability and the memcached client was optimized which benefited both caching and the queue. Various profiling and debugging tools helped identify performance bottlenecks and measure improvements.
20. Simplest MQ ever:
Gives up constraints for scalability
No strict ordering of jobs
No shared state among servers
Just like memcached
Uses memcached protocol
21. First version was written in
Ruby
Ruby is “optimization-
resistant”
Mainly due to the GC
22. If the consumers could not
keep pace, the MQ would fill
up and crash
Ported it to Scala for this
reason