apache cassandra - developer

Database Administrators, Data Analytics professionals, Data architects, Managers

In Apache Cassandra - Developer training course, Delegates will learn to:

  • Architect and engineer Cassandra databases for competitive advantage
  • 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
  • Implement commonly used Cassandra design patterns

COURSE AGENDA

  • Drawing comparisons with the relational model
  • Organizing data with keyspaces, tables and columns
  • Creating collections and counters
  • Defining Cassandra Query Language, CQL
  • Enumerating CQL data types
  • Manipulating data from the cqlsh interface
  • Defining column family data stores
  • Surveying Cassandra
  • Dissecting the basic Cassandra architecture
  • Justifying non-relational data stores
  • Listing the categories of NoSQL Data Stores
  • Designing tables around access patterns
  • Clustering with compound primary keys
  • Improving data distribution with composite partition Keys
  • Identifying consistency levels
  • Selecting appropriate read and write consistency levels
  • Distinguishing consistency repair features
  • Relating replication factor and consistency
  • Trading consistency for availability
  • Trading consistency for availability
  • Grouping elements in sets
  • Ordering elements in lists
  • Expressing relationships with maps
  • Nesting collections
  • Mapping data to tuples and user defined types
  • Investigating the frozen keyword
  • Applying the Valueless Columns Pattern
  • Strategic implementation of clustering columns
  • Expiring temporal data with time-to-live
  • Reviewing how tombstones achieve distributed deletes
  • Executing DELETEs and UPDATEs in the future
  • Modeling time series data
  • Enhancing queries with materialized views
  • Materialized views maintained in the application
  • Driving analytics from materialized views
  • Creating triggers by implementing ITrigger
  • Attaching triggers to tables
  • Supporting materialized views with triggers
  • Connecting to a Cassandra cluster
  • Running CQL through the Java Driver
  • Batching prepared statements
  • Paginating large queries
  • Defining the Java Persistence Architecture, JPA
  • Configuring Kundera to work with Cassandra
  • Generating schemas automatically
  • Managing JPA transactions in Kundera
  • Loading data into Hadoop MapReduce with the Cassandra InputFormat
  • Utilizing the Cassandra Loader to create Pig relations
  • Converting a Cassandra table to a Hive table with the Casssandra serializer/deserializer (SerDe)