Apache Cassandra Online Training
Apache Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure. Cassandra offers robust support for clusters spanning multiple datacenters, with asynchronous masterless replication allowing low latency operations for all clients. Cassandra achieves the highest throughput for the maximum number of nodes in all experiments. Cassandra's data model is a partitioned row store with tunable consistency. Cassandra introduces CQL (Cassandra Query Language). Linear scalability and proven fault-tolerance on COMMODITY hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra's support for replicating across multiple datacenters.
Unit 1: Getting Started with Cassandra Topics -Quick Review of RDBMS: Transactions, ACIDity, Schema, Two Phase Commit, Sharding and Share Nothing Architecture, Feature Based, Key Based, Lookup Table Based, NoSQL Databases, Brewers CAP Theorem, Cassandra Definition and Features, Distributed and Decentralised, Elastic Scalability, High Availability and Fault Tolerance, Tuneable Consistency, Strict Consistency, Casual Consistency, Weak (Eventual Consistency). Unit 2: Understanding Cassandra Data Model Topics -Installing Cassandra, Running the Command-Line Client Interface, Basic CLI Commands, Help, Connecting to a Server, Describing the Environment, Creating and Keyspace and Column Family, Writing and Reading Data, The Relational Data Model, Simple Introduction, Cluster, Keyspaces, Column Families, Column Family Options, Columns, Wide Rows, Skinny Rows, Column Sorting, Super Columns, Composite Keys, Design Differences between RDBMS and CASSANDRA, Query Language.
Unit 3: Understanding Cassandra Architecture Topics -System Keyspace, Peer-To-Peer, Gossip and Failure Detection, AntiEntropy and Read Repair, Memtables, SSTables, and Commit Logs, Hinted Handoff, Compaction, Bloom Filters, Tombstones, Staged Event-Driven Architecture (SEDA), Read, Mutation, Gossip, Response, Anti-Entropy, Load Balance, Migration, Streaming, Managers and Services, Cassandra Daemon, Storage Service, Messaging Service, Hinted Handoff Manager. Unit 4: Creating Sample Application Topics -Database Design, Sample Application RDBMS Design, Sample Application Cassandra Design, Application Code, Creating Database, Loading Schema, Data Structures, Setting Connections, Population of database, Application Features. Unit 5: Configuring, Reading and Writing Data in Cassandra Topics -Keyspaces, Replicas, Replica Placement Strategy, Replication Factor, Partitioner, Snitches, Creating Clusters, Dynamic Ring Participation, Security, Miscellaneous Settings, Additional Tools, Query differences between RDBMS and Cassandra, Basic Write Properties.
Unit 6: Integrating Cassandra with Hadoop Topics -Hadoop, MapReduce, Cassandra Hadoop Source Package, Outputting Data to Cassandra, PIG, HIVE, Use Cases. Unit 7: CQL Topics -Data Definition language(DDL) Statements, Data Manipulation Language (DML), Create and modify Users, User permission, Capture CQL output to a file, Import and export data, CQL scripts from within CQL, CQL Scripts from the command prompt. Unit 8: Clients and Live Project Topics -Basic Client API, Thrift, Thrift Support for Java, Exceptions, Thrift Summary, Cassandra Web Console, Hector (Java), Features, Hector API, Live Project.
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