Data compression in Modern Application

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In this lecture, Sergei Koren, System architect at LivePerson production team presents data & image compression and its effective usage in modern web and data flows.

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Data compression in Modern Application

  1. 1. Compression by Sergei Koren.
  2. 2. Compression as we used to know
  3. 3. Compression indeed
  4. 4. Compression classification We will focus on lossless codecs
  5. 5. There is always trade off
  6. 6. There is always trade-off.. ● … ● Is there? It is all about the need and implementation
  7. 7. What is difference?
  8. 8. Hadoop M/R Data transfer stage
  9. 9. Terasoft results hadoop jar /usr/lib/hadoop-0.20-mapreduce/hadoop- examples.jar terasort - Dmapred.compress.map.output=true - Dmapred.reduce.slowstart.completed.maps=0.95 - Dmapred.reduce.tasks=100 - Dmapred.map.output.compression.codec=org.apach e.hadoop.io.compress.GzipCodec teragen-input terasort-output
  10. 10. Compression for web Demo: using compression to optimize web delivery
  11. 11. Compression for web
  12. 12. References From Salesforce From Cisco
  13. 13. Wrap up ● Compression usage is must in modern systems ● Get to know your data and flows ● Choose codecs carefully. You may no penalty at all to use them!

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