21 hours (usually 3 days including breaks)
- comfortable with Java programming language
- comfortable in Linux environment (navigating command line, editing files with vi / nano)
This course will introduce Cassandra – a popular NoSQL database. It will cover Cassandra principles, architecture and data model. Students will learn data modeling in CQL (Cassandra Query Language) in hands-on, interactive labs. This session also discusses Cassandra internals and some admin topics.
Audience : Developers
- 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
- 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 come up designs and models
- discuss various designs, analyze decisions
- Lab : implement one of the scenario
- 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
- Section 8: Administration
- Hardware selection
- Cassandra distributions
- Cassandra best practices (compaction, garbage collection,)
- troubleshooting tools and tips
- Lab : students install Cassandra, run benchmarks
- Section 9: Bonus Lab (time permitting)
- Implement a music service like Pandora / Spotify on Cassandra
Topics approached. Very complete.
Carlos Eloi Barros
The last exercise was very good.
I already using and have an application in production with Cassandra so mostly of the topics i already know but the data modeling and advanced topics are a lot interesting.
There was a lot of knowledge and material shared that will help me to do my current tasks.
I liked the amount of exercises. We could immediately apply the knowledge shared and ensure the information was on point.
I liked all technical explanation and theoretical introduction.
I enjoyed the very good explanations with in depth examples.
The practical exercises and examples of implementing examples of real models and contexts.
Bookings, Prices and Enquiries
|Number of Delegates||Private Remote|
|Number of Delegates||Public Classroom|
|Location||Date||Course Price [Remote/Classroom]|