Sketching Algorithms: Making Sense of Big Data in a Single Stroke

Sketching Algorithms: Making Sense of Big Data in a Single Stroke

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apache datasketches java, c++, python

27 of 29

27 of 29

apache datasketches java, c++, python

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Sketching Algorithms: Making Sense of Big Data in a Single Stroke

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  1. 1 intro
  2. 2 preamble
  3. 3 hello
  4. 4 quix
  5. 5 quix streams
  6. 6 quix cloud
  7. 7 what is a sketch?
  8. 8 approximate answers
  9. 9 sketch characteristics
  10. 10 sketch components
  11. 11 why exact == slow
  12. 12 distributed processing
  13. 13 unique word count
  14. 14 massively parallel processing mpp
  15. 15 shuffling is slow
  16. 16 latency numbers every programmer should know
  17. 17 why sketches == fast
  18. 18 sketch design
  19. 19 sublinear data structure growth
  20. 20 mergability
  21. 21 non-additive challenges are everywhere
  22. 22 unique counts are non-additive
  23. 23 non-additive challenges solved
  24. 24 types of sketches
  25. 25 count min sketch
  26. 26 open source sketches
  27. 27 apache datasketches java, c++, python
  28. 28 datasketch extensions
  29. 29 thank you

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