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Course Outline

  • Section 1: Introduction to Big Data / NoSQL
    • NoSQL overview
    • CAP theorem
    • When is NoSQL appropriate
    • Columnar storage
    • NoSQL ecosystem
  • Section 2 : Cassandra Basics
    • Design and architecture
    • Cassandra nodes, clusters, datacenters
    • Keyspaces, tables, rows and columns
    • Partitioning, replication, tokens
    • Quorum and consistency levels
    • Labs : interacting with Cassandra using CQLSH
  • Section 3: Data Modeling – part 1
    • Introduction to CQL
    • CQL Datatypes
    • Creating keyspaces & tables
    • Choosing columns and types
    • Choosing primary keys
    • Data layout for rows and columns
    • Time to live (TTL)
    • Querying with CQL
    • CQL updates
    • Collections (list / map / set)
    • Labs : various data modeling exercises using CQL; experimenting with queries and supported data types
  • Section 4: Data Modeling – part 2
    • Creating and using secondary indexes
    • Composite keys (partition keys and clustering keys)
    • Time series data
    • Best practices for time series data
    • Counters
    • Lightweight transactions (LWT)
    • Labs : creating and using indexes; modeling time series data
  • Section 5 : Data Modeling Labs  : Group design session
    • Multiple use cases from various domains are presented
    • Students work in groups to develop designs and models
    • Discuss various designs, analyze decisions
    • Lab : implement one of the scenarios
  • Section 6: Cassandra drivers
    • Introduction to Java driver
    • CRUD (Create / Read / Update, Delete) operations using Java client
    • Asynchronous queries
    • Labs : using Java API for Cassandra
  • Section 7 : Cassandra Internals
    • Understand Cassandra design under the hood
    • SSTables, memtables, commit log
    • Read path / write path
    • Caching
    • VNodes
  • Section 8: Administration
    • Hardware selection
    • Cassandra distributions
    • Installing Cassandra
    • Running benchmarks
    • Tools for monitoring performance and node activities
      • DataStax OpsCenter
    • Diagnosing Cassandra performance issues
    • Investigating a node crash
    • Understanding data repair, deletion and replication
    • Other troubleshooting tools and tips
    • Cassandra best practices (compaction, garbage collection,)
  • Section 9:  Bonus Lab (time permitting)
    • Implement a music service like Pandora / Spotify on Cassandra

Requirements

  • Proficiency in the Java programming language
  • Comfort with the Linux environment (navigating the command line, editing files using vi/nano)

Lab environment:

A functioning Cassandra environment will be provided for students. Participants will need an SSH client and a web browser to access the cluster.

Zero Install : There is no need to install Cassandra on students’ machines!

 21 Hours

Custom Corporate Training

Training solutions designed exclusively for businesses.

  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

Price per private group, online live training, starting from 3900 € + VAT*

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