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.

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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Transcript

  • 1. Compression by Sergei Koren.
  • 2. Compression as we used to know
  • 3. Compression indeed
  • 4. Compression classification We will focus on lossless codecs
  • 5. There is always trade off
  • 6. There is always trade-off.. ● … ● Is there? It is all about the need and implementation
  • 7. What is difference?
  • 8. Hadoop M/R Data transfer stage
  • 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. Compression for web Demo: using compression to optimize web delivery
  • 11. Compression for web
  • 12. References From Salesforce From Cisco
  • 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!