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  • Big Data
  • Cassandra advanced – modeling and analytics
Cursurile noastreBig DataCassandra advanced – modeling and analytics
  • Day 1: Cassandra Architecture and concepts Recap Q&A + exercises 5

    • Capitol1.1
      Indexing in Cassandra – recap through exercises
    • Capitol1.2
      Native secondary indexes and the possible combination with Allow Filtering
    • Capitol1.3
      SStable attached secondary indexes
    • Capitol1.4
      Materialized views
    • Capitol1.5
      Through hands on exercises we will compare performance of Secondary indexes vs Materialized views and Denormalized Tables.
  • Day 2: Important factors that impact queries performance, besides data modeling 9

    • Capitol2.1
      Deletes in Cassandra – theory + exercises
    • Capitol2.2
      Compaction in Cassandra: understand the way Size Tiered, Level Tiered and Time
    • Capitol2.3
      Cassandra Data Modeling process description:
    • Capitol2.4
      Conceptual data modeling, application workflow
    • Capitol2.5
      How to build a Chebotko diagram
    • Capitol2.6
      Logical modeling: principles, mapping rules, mapping patterns
    • Capitol2.7
      Physical modeling: partition size calculation
    • Capitol2.8
      KDM tool for data modeling
    • Capitol2.9
      Exercise to model data according to the data modeling process
  • Day 3: Analytics with Cassandra 5

    • Capitol3.1
      What you can and cannot do with Cassandra (functional limitations) and why is needed an analytical layer
    • Capitol3.2
      How to do analytics with Cassandra and Spark SQL
    • Capitol3.3
      Full analytics with Spark SQL, reading data from Cassandra
    • Capitol3.4
      Pre-aggregation in Cassandra, predicates push down from Spark to Cassandra, finalize analytics in Spark SQL
    • Capitol3.5
      Final exercise that will combine Spark and Cassandra functionalities
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    Prev What you can and cannot do with Cassandra (functional limitations) and why is needed an analytical layer
    Next Full analytics with Spark SQL, reading data from Cassandra

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