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April 09, 2017
Technology
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Fast In-memory Analytics for Retail Data with Columnar Databases

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ernestoarbitrio

April 09, 2017
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Transcript

  1. Fast In-memory Analytics for Retail Data with Columnar Databases Ernesto

    Arbitrio - Valerio Maggio
 arbitrio | [email protected] Florence April 6, 2017

  2. Retail Data • Overview of data we have • granularity

    • refresh/update rate • Quantity and storage required (space) • services developed around these data

  3. “Materialized Views” • Description of what they are (non-technical) •

    Some examples of Analytics we do on this data

  4. The Problem! ~1 TByte Data We need OLAP Performance:
 75M

    rows -> 5hours

  5. The Solution! Use a Column-oriented Database
 (i.e. Just swap Rows

    with Columns) Chuck Norris Test 
 Passed!
  6. None

  7. Query

  8. None

  9. Thank you get in touch @__pamaron__ @leriomaggio