17.2. MapReduceTask Distributed Execution

Procedure 17.1. Mapping Phase

1. The input keys are grouped according to their owner nodes.
2. On each node the Mapper function processes all key/value pairs local to that node.
3. The results of the mapping process are collected using a Collector.
4. If a Reducer is specified, it is applied to all intermediate values collected for each outgoing key (KOut, VOut).

Procedure 17.2. Outgoing Key and Outgoing Value Migration Phase

1. Intermediate keys exposed by the Mapper are grouped by the intermediate outgoing key (KOut values. This grouping preserves the keys, as the mapping phase, when applied to other nodes in the cluster, may generate identical intermediate keys.
2. Once the Reduce phase has been invoked, (as described in Step 4 of the Mapping Phase above), an underlying hashing mechanism, a temporary distributed cache, and a DeltaAware cache insertion mechanism are used to:
   • hash the intermediate key KOut using its owner node.
   • migrate the hashed KOut key and its corresponding VOut value to the same owner node.
3. The list of KOut keys are returned to the master node. VOut values are not returned as they are not required by the master node.

Procedure 17.3. Reduce Phase

1. KOut keys are grouped according to owner node.
2. The reduce operation applies to each node and its input (grouped KOut keys) as follows:
   • The reduce operation locates the temporary distributed cache created during the migration phase on the target node.
   • For each KOut key, a list of VOut values is taken from the temporary cache.
   • The KOut and VOut values are wrapped in an Iterator and the reduce operation is applied to the result.
3. The reduce operation generates a map where each key is KOut and each value is VOut.
   Each node has its own map.
4. The maps from each node in the cluster are combined into a single map (M).
5. The MapReduce task returns map (M) to the node that initiated the MapReduce task.