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Automating Distributed Partial Aggregation
| Content Provider | Microsoft Research |
|---|---|
| Author | Liu, Chang Zhang, Jiaxing Zhou, Hucheng McDirmid, Sean Guo, Zhenyu Moscibroda, Thomas |
| Copyright Year | 2014 |
| Abstract | Partial aggregation is of great importance in many distributed data-parallel systems. Most notably, it is commonly applied by MapReduce programs to optimize I/O by successively aggregating partially reduced results into a final result, as opposed to aggregating all input records at once. In spite of its importance, programmers currently enable partial aggregation by tediously encoding their reduce functionality into separate reduce and combine functions. This is error prone and often leads to missed optimization opportunities. |
| Language | English |
| Publisher | ACM Association for Computing Machinery ACM |
| Publisher Date | 2014-11-01 |
| Access Restriction | Open |
| Rights Holder | Microsoft Corporation |
| Subject Keyword | Computer systems networking |
| Content Type | Text |
| Resource Type | Proceeding |
