Interpreting the Data: Parallel Analysis with Sawzall (Draft)


Posted by Thomas Sutton on February 26, 2006

Interpreting the Data: Parallel Analysis with Sawzall (Draft)

While MapReduce and GFS allow Google to use their massive computer clusters effectively, the use of C++ can make programming for such a systems more difficult than it needs to be. Cue Sawzall, a new language that Google use to write distributed, parallel data-processing programs for use on their clusters. While the language isn’t particularly attractive (I’ve never liked C-style syntax’s), the approach is very interesting and the implementation issues they describe are enlightening.

LtU | CiteULike

This post was published on February 26, 2006 and last modified on January 26, 2024. It is tagged with: papers, programming languages.