Data streams: algorithms and applications

@article{Muthukrishnan2003DataSA,
  title={Data streams: algorithms and applications},
  author={S. Muthukrishnan},
  journal={Foundations and Trends in Theoretical Computer Science},
  year={2003},
  volume={1}
}
In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse… CONTINUE READING

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