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Course Outline

  • Section 1: Introduction to Big Data / NoSQL
    • Overview of NoSQL databases
    • The CAP theorem
    • When NoSQL is the appropriate choice
    • Columnar storage mechanisms
    • The NoSQL ecosystem
  • Section 2: Cassandra Basics
    • Design and architecture
    • Cassandra nodes, clusters, and data centers
    • Keyspaces, tables, rows, and columns
    • Partitioning, replication, and tokens
    • Quorum and consistency levels
    • Labs: Interacting with Cassandra using CQLSH
  • Section 3: Data Modeling – Part 1
    • Introduction to CQL
    • CQL Datatypes
    • Creating keyspaces and tables
    • Selecting columns and data types
    • Choosing primary keys
    • Data layout for rows and columns
    • Time to live (TTL)
    • Querying with CQL
    • Updates via CQL
    • Collections (list, map, set)
    • Labs: Various data modeling exercises using CQL; experimentation with queries and supported data types
  • Section 4: Data Modeling – Part 2
    • Creating and utilizing 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 propose designs and models
    • Discussion of various designs and analysis of decisions
    • Lab: Implementation of one of the scenarios
  • Section 6: Cassandra Drivers
    • Introduction to the Java driver
    • CRUD (Create / Read / Update, Delete) operations using the Java client
    • Asynchronous queries
    • Labs: Using the Java API for Cassandra
  • Section 7: Cassandra Internals
    • Understanding Cassandra's underlying design
    • SSTables, memtables, and the commit log
    • Read path / write path
    • Caching mechanisms
    • Vnodes
  • Section 8: Administration
    • Hardware selection
    • Cassandra distributions
    • Cassandra best practices (compaction, garbage collection)
    • Troubleshooting tools and tips
    • Lab: Students install Cassandra and run benchmarks
  • Section 9: Bonus Lab (time permitting)
    • Implement a music service like Pandora / Spotify on Cassandra

Requirements

  • Familiarity with the Java programming language
  • Proficiency in the Linux environment (including command-line navigation and file editing with vi or nano)
 21 Hours

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