IBM BigData

@RomeoKienzler

Preface

Most of the Technologies mentioned in this presentation are available in the IBM Cloud Free Tier at no cost, please have a look http://ibm.biz/joinIBMCloud

State of the Art

  • SQL (42%)
  • R (33%)
  • Python (26%)
  • Excel (25%)
  • Java, Ruby, C++ (17%)
  • SPSS, SAS (9%)

Limits

  • Main Memory
  • CPU <> Main Memory Bandwidth
  • CPU
  • Storage <> Main Memory Bandwidth (either Single node or SAN)

Hadoop

Hadoop

Why is Hadoop so fast?

Time to read 1 TB from Disk

  • 1 disk - 3.4h
  • 10 disks - 20m
  • 100 disks - 2m
  • 1000 disks - 12s

 

Time to read 1 TB from Main Memory

  • 1 node - 100s
  • 10 nodes - 10s
  • 100 nodes - 1s
  • 1000 nodes - 100ms

Data Parallelism

Why use so much data?

The Unreasonable Effectiveness of Data¹: "sometimes it's not who has the best algorithm that wins; it's who has the most data."

 ¹http://www.csee.wvu.edu/~gidoretto/courses/2011-fall-cp/reading/TheUnreasonable%20EffectivenessofData_IEEE_IS2009.pdf

How to store so much data?

"Imagine a Filesystem with unlimited capacity, scalability and fault tolerance"

BigR

BigR

Spark

Spark

Life Science

Hadoop - Genomics

Crossbow

  • 1st tool on Hadoop 
  • based on Bowtie + soapSNP

ADAM

  • genomics analysis platform 
  • runs on top of Spark

Hadoop - BAM

  • on top of the Picard SAM JDK

Hadoop - Genomics

...some more examples...

  • Contrail
  • PeakRanger
  • Quake
  • BlastReduce
  • CloudBLAST
  • MrsRF

Downstream Analytics

...downstream analytics...

Downstream Analytics

Image/Video Processing

On Hadoop

Fiji/ImageJ

  • 3D Image Processing library
  • runs also on Hadoop / Spark

OpenCV

  • Video Processing library
  • runs also on Hadoop / Spark or IBM InfoSphere Streams

IBM BigData

By Romeo Kienzler

IBM BigData

A short overview on IBM BigData

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