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Building Apache Cassandra Databases

COURSE TYPE

Intermediate

Course Number

1260

Duration

3 Days

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The large volume and variety of data that today's businesses process require the need for a highly available, low latency database. Apache Cassandra provides this solution by permitting high-speed reads and writes across a replicated, distributed system. This Apache Cassandra training course provides data modelling experience to take advantage of the linearly scalable peer-to-peer design of Cassandra.

You Will Learn How To

  • Architect Cassandra databases and implement commonly used design patterns
  • Model data in Cassandra based on query patterns
  • Access Cassandra databases using CQL and Java
  • Create a balance between read/write speed and data consistency
  • Integrate Cassandra with Hadoop, Pig, and Hive

Important Course Information

Recommended Experience:

  • Knowledge of databases and SQL
  • Java programming

Course Outline

  • Introduction to Apache Cassandra

NoSQL Overview

  • Justifying non-relational data stores
  • Listing the categories of NoSQL Data Stores

Exploring Cassandra

  • Defining column family data stores
  • Surveying Cassandra
  • Dissecting the basic Cassandra architecture

Querying Cassandra

  • Defining Cassandra Query Language, CQL
  • Enumerating CQL data types
  • Manipulating data from the cqlsh interface
  • Representing Data in the Cassandra Data Model

Leveraging Cassandra structures and types

  • Drawing comparisons with the relational model
  • Organising data with keyspaces, tables and columns
  • Creating collections and counters

Modelling data based on queries

  • Designing tables around access patterns
  • Clustering with compound primary keys
  • Improving data distribution with composite partition Keys
  • Configuring Data Consistency

Detailing tunable consistency

  • Identifying consistency levels
  • Selecting appropriate read and write consistency levels
  • Distinguishing consistency repair features

Balancing consistency and performance

  • Relating replication factor and consistency
  • Trading consistency for availability
  • Achieving linearisable consistency with Compare-And-Set
  • Leveraging Cassandra Idioms and Programming Patterns

Working with Cassandra collection types

  • Grouping elements in sets
  • Ordering elements in lists
  • Expressing relationships with maps
  • Nesting collections

Storing data for easy retrieval

  • Mapping data to tuples and user defined types
  • Investigating the frozen keyword
  • Applying the Valueless Columns Pattern
  • Strategic implementation of clustering columns

Controlling data life span

  • Expiring temporal data with time-to-live
  • Reviewing how tombstones achieve distributed deletes
  • Executing DELETEs and UPDATEs in the future

Constructing materialised views and time series

  • Modelling time series data
  • Enhancing queries with materialised views
  • Materialised views maintained in the application
  • Driving analytics from materialised views

Managing triggers

  • Creating triggers by implementing ITrigger
  • Attaching triggers to tables
  • Supporting materialised views with triggers
  • Accessing Cassandra Programmatically

Querying Cassandra data with the Datastax Java Driver

  • Connecting to a Cassandra cluster
  • Running CQL through the Java Driver
  • Batching prepared statements
  • Paginating large queries

Persisting Java Objects with Kundera

  • Defining the Java Persistence Architecture, JPA
  • Configuring Kundera to work with Cassandra
  • Generating schemas automatically
  • Managing JPA transactions in Kundera
  • Integrating Cassandra with Analytical Frameworks

Leveraging built-in Cassandra connectors

  • Loading data into Hadoop MapReduce with the Cassandra InputFormat
  • Utilising the Cassandra Loader to create Pig relations
  • Converting a Cassandra table to a Hive table with the Casssandra serialiser/deserialiser (SerDe)
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Convenient Ways to Attend This Instructor-Led Course

Hassle-Free Enrolment: No advance payment required to reserve your seat.
Tuition Fee due 30 days after you attend your course.

In the Classroom

Live, Online

Private Team Training

In the Classroom — OR — Live, Online

Tuition Fee — Standard: £1695  

AFTERNOON START: Attend these live courses online via Anyware

14 - 16 Mar (3 Days)
1:00 PM - 8:30 PM GMT
Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

How would you like to attend?

Live, Online
In-Class

5 - 7 Sep (3 Days)
2:00 PM - 9:30 PM BST
Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

How would you like to attend?

Live, Online
In-Class

Guaranteed to Run

Private Team Training

Enroling at least 3 people in this course? Consider bringing this (or any course that can be custom designed) to your preferred location as a private team training.

For details, call 0800 282 353 or Click here »

Tuition Fee

Standard

In Classroom or
Online

Standard

£1695

Private Team Training

Contact Us »

Course Tuition Fee Includes:

After-Course Instructor Coaching
When you return to work, you are entitled to schedule a free coaching session with your instructor for help and guidance as you apply your new skills.

After-Course Computing Sandbox
You'll be given remote access to a preconfigured virtual machine for you to redo your hands-on exercises, develop/test new code, and experiment with the same software used in your course.

Free Course Exam
You can take your Learning Tree course exam on the last day of your course or online at any time after class and receive a Certificate of Achievement with the designation "Awarded with Distinction."

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Training Hours

Standard class hours:
9:00 a.m. - 4:30 p.m.

Last day class hours:
9:00 a.m. - 3:30 p.m.

Free Course Exam – Last Day:
3:30 p.m. - 4:30 p.m.

Each class day:
Informal discussion with instructor about your projects or areas of special interest:
4:30 p.m. - 5:30 p.m.

AFTERNOON START class hours:
2:00 p.m. - 9:30 p.m.


Last day class hours:
2:00 p.m. - 8:30 p.m.


Free Course Exam – Last Day:
8:30 p.m. - 9:30 p.m.


Each class day:
Informal discussion with instructor about your projects or areas of special interest
9:30 p.m. - 10:30 p.m.

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