General Distributed Reduction For Data Parallel Computing

摘要

General-purpose distributed data-parallel computing using high-level computing languages is described. Data parallel portions of a sequential program written in a high-level language are automatically translated into a distributed execution plan. Map and reduction computations are automatically added to the plan. Patterns in the sequential program can be automatically identified to trigger map and reduction processing. Direct invocation of map and reduction processing is also provided. One or more portions of the reduce computation are pushed to the map stage and dynamic aggregation is inserted when possible. The system automatically identifies opportunities for partial reductions and aggregation, but also provides a set of extensions in a high-level computing language for the generation and optimization of the distributed execution plan. The extensions include annotations to declare functions suitable for these optimizations.