Incorporating partitioning and parallel plans into the SCOPE optimizer

  title={Incorporating partitioning and parallel plans into the SCOPE optimizer},
  author={Jingren Zhou and Per-{\AA}ke Larson and Ronnie Chaiken},
  journal={2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)},
Massive data analysis on large clusters presents new opportunities and challenges for query optimization. Data partitioning is crucial to performance in this environment. However, data repartitioning is a very expensive operation so minimizing the number of such operations can yield very significant performance improvements. A query optimizer for this environment must therefore be able to reason about data partitioning including its interaction with sorting and grouping. SCOPE is a SQL-like… CONTINUE READING
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