![]() Non-key based partitioning strategies raise prohibitively high memory overhead for the stateful operations with a large number of keys and high data parallelism, while the key-based schemes introduce load imbalance for highly skewed data. Existing data partitioning schemes for DSPS suffer from the scalability problem and system in-efficiency. Load balancing among the processing elements (PEs) of distributed stream processing system (DSPS) is a key issue in the presence of data skewness.
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