Apache Cassandra

Apache Cassandra moves away from the master-slave model and instead uses a peer-to-peer model. This means there is no single master but all the nodes are potentially masters. This makes the writes and reads extremely scalable and even allows nodes to function in cases of partition tolerance.

This Apache Cassandra - Administrator training course provides expertise about the core concepts of Cassandra, highly scalable data models and Cassandra architecture for proper administration of Big Data applications. The Apache Cassandra - Developer training course provides skills about data model queries, indepth CQL, data modelling, complex queries and about whiteboard in NoSQL.

Objectives:

• In Apache Cassandra - Administrator workshop, delegates will learn to:
• Benchmark read and write operations
• Recognize different types of failure
• Fix a failed or partially failed cluster
• Identify potential performance bottlenecks
• Perform live schema updates
• Perform move operations
• Plan and perform cluster-wide operations
• Monitor compaction, repair, and hinted handoff
• In Apache Cassandra - Developer workshop, 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:

• The Write Path
• Log Structured Storage
• Memtables
• Flushing
• The Read Path
• SSTables
• Row Merging
• Cache (Key, Row)
• Compaction
• Distributed Deletes
• Memory Mapped Files
• Evolving Applications
• Introduction to CAP
• Partition Tolerance
• Data partitioners
• Replication strategies
• Snitches
• Hinted Handoff
• Availability
• How Cassandra handles failure of one or more nodes
• What to do in the face of failure
• Aspects of consistency
• Consistency
• Coordinators
• Read Repair
• Phi Accrual
• Hinted Handoff
• Anti-entropy Service
• Cassandra and the JVM
• Monitoring Cassandra
• How Cassandra works with the physical hardware
• CPU
• Disk
• Network
• Goals for Sizing
• The different storage strategies (disk configurations) including
• Specific concerns for cloud hosting
• Logical and Physical disk configuration
• Local disks vs. network mounted/shared drives
• Logging
• Cassandra
• System
• GC
• Backup and Recovery
• Backup
• Recovery