Effective Scala
Effective Scala Marius Eriksen, Twitter Inc. marius@twitter.com (@marius) Table of Contents Introduction Formatting: Whitespace, Naming, Imports, Braces, Pattern matching, Comments Types and Generics: Return type annotations, Variance, Type aliases, Implicits Collections: Hierarchy, Use, Style, Performance, Java Collections Concurrency: Futures, Collections Control structures: Recursion, Returns,
Improving Running Components at Twitter
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 profilin
Building on Open Source
Kestral photo by mugley When we plan new engineering projects at Twitter, we measure our requirements against the capabilities of open source offerings, and prefer to use open source whenever it makes sense. By this approach, much of Twitter is now built on open source software. In some cases, our requirements—in particular, the scalability requirements of our service—lead us to develop projects f
Scarling » Kestrel
Ever since we deployed scarling in production, its name has progressed from being a stale joke to an annoyance. It started out as a test of porting starling to scala, but as features have been added and it’s been hardened by the real world, it has needed its own identity. I wanted to stay with the bird theme, because I think it’s cute, so after spending several days mulling over possible new names
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