Apache Cassandra for devs/analysts/business analysts/solution architects
Expert
Apache Cassandra for devs/analysts/business analysts/solution architects
Durată: 3 zile
Certificare: Diploma de participare
Cui îi este dedicat cursul?
This course is recommended for those who have basic concepts of Cassandra and aim to know more.
Cunoștințe și abilități inițiale
Cassandra concepts knowledge or completed Introduction to Cassandra training. It’s a must that participants know the Apache Cassandra basic architecture and fundamentals (data distribution & partitioning, replication and consistency, nodes communication, read & write path - cluster and node level ), CQL and SQL syntaxes.
Prezentarea cursului
The scope of this course is to provide a deeper understanding of Apache Cassandra data model, and to understand what other factors are important for getting a good query and system performance.
Ce subiecte abordează cursul
Day 1
- Cassandra Architecture and concepts Recap Q&A + exercises
- Indexing in Cassandra - recap through exercises
- - Native secondary indexes and the possible combination with Allow Filtering
- - SStable attached secondary indexes
- - Materialized views
- - 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.
- Deletes in Cassandra - theory + exercises
- Compaction in Cassandra: understand the way Size Tiered, Level Tiered and Time Window compaction strategy can be used, what settings can be done.
- Cassandra Data Modeling process description:
- Conceptual data modeling, application workflow
- How to build a Chebotko diagram
- Logical modeling: principles, mapping rules, mapping patterns
- Physical modeling: partition size calculation
- data modeling tools (e.g. KDM, ..)
- Exercise to model data according to the data modeling process.
Day 3
- Analytics with Cassandra
- What you can and cannot do with Cassandra (functional limitations) and why is needed an analytical layer
- How to do analytics with Cassandra and Spark SQL
- Full analytics with Spark SQL, reading data from Cassandra
- Pre-aggregation in Cassandra, predicates push down from Spark to Cassandra, finalize analytics in Spark SQL
- Final exercise that will combine Spark and Cassandra functionalities.
Ce abilități se dobândesc în urmă cursului
- Understand through exercises the rules behind Cassandra data modeling, how the performance differs depending on what we use for answering a query: remodeling of data, indexes, views or a combination of those;
- Understand what other factors are important, besides data modeling, for getting a good query and system performance;
- Understand the theory of modeling data for getting the best performance out of Cassandra, based on the design of the application workflow, Chebotko diagram, logical and physical modeling rules;
- Perform pre-aggregation of data in Cassandra and finalize data analytics in Spark SQL.
Course Requirements:
- We will need open Internet connection throughout the course. Please test prior to course that there is available an open Wi-Fi connection ( the port 22 for outbound connection to be open );
- Each participant need to have it’s own computer in order to run the exercises and need to make sure prior to the course that the computer settings allow access to Google docs and Github for getting access to presenters slides, documents and exercises;
- We will run Cassandra in public cloud thus please test prior to course that there is available an open Wi-Fi connection at the training location and as well:
- The port 22 for outbound connection is open;
- And an SSH client is installed ;
- Google Chrome is installed.