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Day 1: Cassandra Architecture and concepts Recap Q&A + exercises 5
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Indexing in Cassandra – recap through exercisesCapitol1.1
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Native secondary indexes and the possible combination with Allow FilteringCapitol1.2
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SStable attached secondary indexesCapitol1.3
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Materialized viewsCapitol1.4
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Through hands on exercises we will compare performance of Secondary indexes vs Materialized views and Denormalized Tables.Capitol1.5
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Day 2: Important factors that impact queries performance, besides data modeling 9
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Deletes in Cassandra – theory + exercisesCapitol2.1
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Compaction in Cassandra: understand the way Size Tiered, Level Tiered and TimeCapitol2.2
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Cassandra Data Modeling process description:Capitol2.3
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Conceptual data modeling, application workflowCapitol2.4
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How to build a Chebotko diagramCapitol2.5
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Logical modeling: principles, mapping rules, mapping patternsCapitol2.6
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Physical modeling: partition size calculationCapitol2.7
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KDM tool for data modelingCapitol2.8
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Exercise to model data according to the data modeling processCapitol2.9
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Day 3: Analytics with Cassandra 5
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What you can and cannot do with Cassandra (functional limitations) and why is needed an analytical layerCapitol3.1
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How to do analytics with Cassandra and Spark SQLCapitol3.2
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Full analytics with Spark SQL, reading data from CassandraCapitol3.3
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Pre-aggregation in Cassandra, predicates push down from Spark to Cassandra, finalize analytics in Spark SQLCapitol3.4
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Final exercise that will combine Spark and Cassandra functionalitiesCapitol3.5
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