The default is therefore a null_combiner which does nothing. The combiner is optional, and can actually degrade performance on a single machine implementation due to the additional file sorting that is required. The default implementation iterates a given directory and feeds each Map Task with a Filename and std::ifstream to the open file as a key/value pair.Ĭombiner A Combiner is an optimization technique, originally designed to reduce network traffic by applying a local reduction of intermediate key/value pairs in the Map phase before being passed to the Reduce phase. Policyĭatasource This policy implements a data provider for Map Tasks. Default implementations are provided to enable the library user to run MapReduce simply by implementing the core Map and Reduce tasks, but can be replaced to provide specific features.

The library is designed to be extensible and configurable through a Policy-based mechanism. Void operator()( typename map_task::intermediate_key_type const &key, It it, It ite) Reduce_task(job::reduce_task_runner &runner) The MapTask class must define four data types the key/value types for the inputs to the Map Tasks and the intermediate types. In addition, there are three optional template parameters that can be used to modify the default implementation behavior Datasource that implements a mechanism to feed data to the Map Tasks - on request of the MapReduce library, Combiner that can be used to partially consolidate results of the Map Task before they are passed to the Reduce Tasks, and IntermediateStore that handles storage, merging and sorting of intermediate results between the Map and Reduce phases. The developer is required to write two classes MapTask implements a mapping function to process key/value pairs generate a set of intermediate key/value pairs and ReduceTask that implements a reduce function to merges all intermediate values associated with the same intermediate key.

Typename IntermediateStore=intermediates::local_disk >

C&c general zero hour mods