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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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Exclusive Private Team Training Course

Enhance your team's effectiveness and boost productivity with this course, delivered privately to your organization or to any preferred location, including options for hybrid or all-virtual delivery via AnyWare.

This training course could be customized, and combined with other courses, to meet the specific needs of your team's training.

Preferred method of contact:

Attendee Benefits

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 any time after class.

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