From Data to Meaning (Cloud Developer Roadshow 2014)

Here we talk about the tools and methodologies that you can use to gain insight from your data using a specific example from the Personal Genome Project. This deck was delivered during the Google Cloud Platform Developer Roadshow events in 2014.

Transcript

1. From Data to Meaning
   A step by step guide
   Google Cloud Platform Developer Roadshow - 2014
   

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2. Hadoop Cluster Anyone?
   Images by Connie Zhou
   $ ./bdutil deploy
   

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3. Mapreduce
   A distributed computing paradigm that consists of:
   ● A map step, performed on subsets of the input data
   ● A reduce step, that combines the output together
   A Mapreduce can run on structured or unstructured data
   Hadoop
   An Open Source implementation of Mapreduce
   Some Definitions
   Apache™ Hadoop®
   

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4. Google Cloud Storage
   BigQuery and Datastore Connectors
   Hadoop
   BigQuery
   Connector
   Datastore
   Connector
   Cloud Storage
   Connector
   BigQuery
   Datastore
   

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5. Deployment, Configuration, and Toolkits
   bdutil - Thin wrapper around Cloud SDK command-line tools
   • Deploy Hadoop cluster on-demand
   • Installs and configures GCS connector
   • Extensible - add scripts to run during deployment
   Hadoop Master
   bdutil Hadoop Workers
   Compute
   Engine API
   

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6. Let’s talk briefly about Big Data...
   Courtesy of Nimbus Ninety – www.nimbusninety.com
   

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7. ● Personalised insights into your customer base
   ○ Loyalty Cards, In App Purchases, Point of Sale offers
   ● User retention activities
   ○ For Games, Mobile Apps, anything that has pattern based usage
   ● Predicting health problems
   ● Website optimization through analytics
   ● Enabling future breakthroughs in biology and medicine
   ● Autonomous Traffic Lights and Flying Cars
   Some examples
   

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8. https://developers.google.com/genomics/
   Source: iStockPhoto
   

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9. Your Your
   Business
   

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10. Personal Genome Project
    Where is your data?
    Genomic, Environmental, and Human Trait data
    

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11. Sometimes you just need to
    do something simple… but
    you need to do a lot of it!
    Source: iStockPhoto
    

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12. How Big is a Human Genome?
    Images by Connie Zhou
    $ gsutil ls gs://pgp-harvard-data-public/hu*/*/*/*/ASM/master*
    gs://pgp-harvard-data-public/hu011C57/GS000018120-DID/GS000015172-ASM/GS01669-
    DNA_B05/ASM/masterVarBeta-GS000015172-ASM.tsv.bz2
    gs://pgp-harvard-data-public/hu016B28/GS000018110-DID/GS000014561-ASM/GS01669-
    DNA_H03/ASM/masterVarBeta-GS000014561-ASM.tsv.bz2
    + 173 more…
    $ wc masterVarBeta-GS000015172-ASM.tsv
    17615429 306261586 2349556328 masterVarBeta-GS000015172-ASM.tsv
    One File Per
    Genome
    Participant Identifier
    Buried in Object Name
    

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13. What we have isn’t what we want
    Images by Connie Zhou
    $ head -n 30 masterVarBeta-GS000015172-ASM.tsv | cut -f -10
    #ASSEMBLY_ID GS000015172-ASM
    #CNV_DIPLOID_WINDOW_WIDTH 2000
    #CNV_NONDIPLOID_WINDOW_WIDTH 100000
    [...]
    >locus ploidy chromosome begin end zygosity varType reference allele1Seq
    allele2Seq
    1 2 chr1 0 10000 no-call no-ref = ? ?
    2 2 chr1 10000 10476 no-call complex = ? ?
    3 2 chr1 10476 10481 hom ref = = =
    4 2 chr1 10481 10518 no-call complex = ? ?
    [...]
    

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14. Wheelbarrow or Giant Truck?
    Images by Connie Zhou
    $ ./cgi-mapper.py ./hu011C57/masterVarBeta-GS000015172-ASM.tsv
    demo-m$ ./hadoop-install/bin/hadoop jar \
    ./hadoop-install/contrib/streaming/hadoop-streaming-1.2.1.jar \
    -input gs://pgp-harvard-data-public/hu0*/*/*/*/ASM/master* \
    -mapper cgi-mapper.py \
    -file cgi-mapper.py \
    --numReduceTasks 0 \
    -output gs://big-data-roadshow/output
    

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18. Goodbye Cluster!
    Images by Connie Zhou
    $ ./bdutil delete
    

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19. 434 GB, 3 billion rows
    bdutil deploy: ~3.5 minutes
    hadoop job: ~7 minutes
    bdutil delete: ~1.5 minutes
    Total time with manual entry: ~14 minutes
    n1-standard-16 instances: $1.16 / hour
    But what did it cost?
    

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20. Compute: $5.68
    But what did it cost?
    What about storage? 434 GB @ $0.026 GB / month
    $0.38 / day
    $11.28 / month
    What about networking?
    No Charge!
    

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21. But there’s more...
    

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22. Google BigQuery
    

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23. BigQuery: Big Data Analytics in the Cloud
    Unrivaled
    Performance and Scale
    ● Scan multiple TB’s in seconds
    ● Interactive query
    performance
    ● No limits on amount of data
    Ease of Use
    and Adoption
    ● No administration /
    provisioning
    ● Convenience of SQL
    ● Open interfaces
    (REST, WebUI, ODBC)
    ● First 1 TB of data processed
    per month is free
    Advanced “Big Data”
    Storage
    ● Familiar database structure
    ● Easy data management and
    ACL’s
    ● Fast, atomic imports
    

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28. http://www.nih.gov/news/health/may2014/ninds-09.htm
    

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29. http://www.ncbi.nlm.nih.gov/SNP/snp_ref.cgi?rs=rs9536314
    

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30. Subject chromosome reference allele1Seq allele2Seq Note
    huCCAFD0 chr13 = = = No Variant
    huE58004 chr13 T G T Variant in one Allele
    hu040C0A chr13 T G G Variant in both Alleles
    huF1DC30 chr13 = ? ? Not Sure
    Insight: What do we expect to see Guanine
    Thymine
    

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35. Where’s your Data? Is it in the right place? Is it in the right format?
    What questions do you
    want to ask?
    Extract, Transform,
    Load
    From Data to Meaning
    Data Meaning
    

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36. Coming Soon
    Cloud Pub/Sub Cloud Dataflow
    Apache Spark
    Images by Connie Zhou
    • bdutil support
    • Machine learning via
    MLlib
    • SQL via Shark
    • Managed Service
    • many-to-many, async
    messaging between
    apps
    • Limited Preview
    • Managed Service
    • Unified Batch and
    Streaming
    • Automatic Pipeline
    Optimization
    • Private Beta
    

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37. Hadoop on Google Cloud Platform - http://goo.gl/33PoKG
    (Covers the Hadoop Connectors and bdutil)
    Personal Genome Project - http://goo.gl/j1oTTF
    Cloud Developers console - https://console.developers.google.com
    Google BigQuery - https://developers.google.com/bigquery
    BigQuery Console - https://bigquery.cloud.google.com
    Resources
    

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38. End
    

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