Apache Cassandra

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What you'll learn on the course

Apache

Course programme

Course Preview
  • Apache Cassandra
    • Lesson 0 - Course Overview
      • 0.1 Course Overview
      • 0.2 Course Objectives
      • 0.3 Course Overview
      • 0.4 Target Audience
      • 0.5 Course Prerequisites
      • 0.6 Value to the Professionals
      • 0.7 Lessons Covered
      • 0.8 Conclusion
    • Lesson 1 - Apache Cassandra L1 Overview Big Data and NoSQL Database
      • 1.1 Overview of Big Data and NoSQL Database
      • 1.2 Course Map
      • 1.3 Objectives
      • 1.4 The 3 Vs of Big Data
      • 1.5 Volume
      • 1.6 Data Sizes-Terms
      • 1.7 Velocity
      • 1.8 Variety
      • 1.9 Data Evolution
      • 1.10 Features of Big Data
      • 1.11 Big Data-Use Cases
      • 1.12 Big Data Analytics
      • 1.13 Traditional Technology vs. Big Data Technology
      • 1.14 Apache Hadoop
      • 1.15 HDFS
      • 1.16 MapReduce
      • 1.17 NoSQL Databases
      • 1.18 Brewer’s CAP Principle
      • 1.19 Approaches to NoSQL Databases-Types
      • 1.20 Quiz
      • 1.21 Summary
      • 1.22 Conclusion
    • Lesson 2 - Introduction to Cassandra
      • 2.1 Introduction to Cassandra
      • 2.2 Course Map
      • 2.3 Objectives
      • 2.4 Introducing Cassandra
      • 2.5 Behind the Name
      • 2.6 History of Cassandra
      • 2.7 Main Features of Cassandra
      • 2.8 When is Cassandra Used
      • 2.9 Simple Cassandra Program
      • 2.10 Cassandra Command Line Interface
      • 2.11 Advantages of Cassandra
      • 2.12 Limitations of Cassandra
      • 2.13 VMware
      • 2.14 Simplilearn Virtual Machine
      • 2.15 PuTTY
      • 2.16 WinSCP
      • 2.17 Demo-Install and Setup VM
      • 2.18 Demo-Install and Setup VM
      • 2.19 Quiz
      • 2.20 Summary
      • 2.21 Conclusion
    • Lesson 3 - Cassandra Architecture
      • 3.1 Cassandra Architecture
      • 3.2 Course Map
      • 3.3 Objectives
      • 3.4 Architecture Requirements of Cassandra
      • 3.5 Cassandra Architecture
      • 3.6 Cassandra Architecture (contd.)
      • 3.7 Effects of the Architecture
      • 3.8 Cassandra Write Process
      • 3.9 Rack
      • 3.10 Cassandra Read Process
      • 3.11 Example of Cassandra Read Process
      • 3.12 Data Partitions
      • 3.13 Replication in Cassandra
      • 3.14 Network Topology
      • 3.15 Snitches
      • 3.16 Gossip Protocol
      • 3.17 Seed Nodes
      • 3.18 Configuration
      • 3.19 Virtual Nodes
      • 3.20 Token Generator
      • 3.21 Example of Token Generator
      • 3.22 Failure Scenarios Node Failure
      • 3.23 Failure Scenarios Disk Failure
      • 3.24 Failure Scenarios Rack Failure
      • 3.25 Failure Scenarios Data Center Failure
      • 3.26 Quiz
      • 3.27 Summary
      • 3.28 Conclusion
    • Lesson 4 - Cassandra Installation and Configuration
      • 4.1 Cassandra Installation and Configuration
      • 4.2 Course Map
      • 4.3 Objectives
      • 4.4 Cassandra Versions
      • 4.5 Steps to Install and Configure Cassandra on Ubuntu System
      • 4.6 Step 1-Operating System Selection
      • 4.7 Step 2-Machine Selection
      • 4.8 Step 3-Preparing for Installation
      • 4.9 Step 4-Setup Repository
      • 4.10 Step 5-Install Cassandra
      • 4.11 Step 6-Check the Installation
      • 4.12 Step 7-Configuring Cassandra
      • 4.13 Step 8-Configuration for a Single-Node Cluster
      • 4.14 Step 9-Configuration for a Multi-Node and Multi-Datacenter Clusters
      • 4.15 Step 10-Setup Property File
      • 4.16 Step 11-Configuration for a Production Cluster
      • 4.17 Step 12-Setup Gossiping Property File
      • 4.18 Step 13-Starting Cassandra Services
      • 4.19 Step 14-Connecting to Cassandra
      • 4.20 Installing on CentOS
      • 4.21 Demo-Installing and Configuring Cassandra on Ubuntu
      • 4.22 Demo-Installing and Configuring Cassandra on Ubuntu
      • 4.23 Quiz
      • 4.24 Summary
      • 4.25 Conclusion
    • Lesson 5 - Cassandra Data Model
      • 5.1 Cassandra Data Model
      • 5.2 Course Map
      • 5.3 Objectives
      • 5.4 Cassandra Data Model
      • 5.5 Cassandra Data Model Components
      • 5.6 Keyspaces
      • 5.7 Tables
      • 5.8 Columns
      • 5.9 UUID and TimeUUID
      • 5.10 Counter
      • 5.11 Compound Keys
      • 5.12 Indexes
      • 5.13 Collection Columns
      • 5.14 Collection Columns Set
      • 5.15 DDL and DML Statements
      • 5.16 DDL Statements
      • 5.17 DML Statements INSERT
      • 5.18 DML Statements UPDATE
      • 5.19 DML Statements COPY
      • 5.20 DML Statements SELECT
      • 5.21 SELECT Statements Restrictions
      • 5.22 Valid and Invalid SELECT Statements Example
      • 5.23 DML Statements DELETE
      • 5.24 Demo 1-Data Definition and Data Manipulation Statements
      • 5.25 Demo 1-Data Definition and Data Manipulation Statements
      • 5.26 Demo 2-Create a Table with Composite Key
      • 5.27 Demo 2-Create a Table with Composite Key
      • 5.28 Demo 3-Collection Columns in Cassandra
      • 5.29 Demo 3-Collection Columns in Cassandra
      • 5.30 Quiz
      • 5.31 Summary
      • 5.32 Conclusion
    • Lesson 6 - Cassandra Interfaces
      • 6.1 Lesson 6-Cassandra Interfaces
      • 6.2 Course Map
      • 6.3 Objectives
      • 6.4 Cassandra Interfaces
      • 6.5 Cassandra Command Line Interface
      • 6.6 Cqlsh Options
      • 6.7 Cqlsh Commands
      • 6.8 Cqlsh Shell Commands
      • 6.9 Cqlsh Help
      • 6.10 Java Interfaces
      • 6.11 Using the Java Interface
      • 6.12 Querying Cassandra using Java
      • 6.13 Java Example
      • 6.14 Java Example (contd.)
      • 6.15 Full Program
      • 6.16 Compiling the Java Program
      • 6.17 Compiling the Java Program (contd.)
      • 6.18 Running the Java Program
      • 6.19 Java Interface observations
      • 6.20 ODBC Interface
      • 6.21 Quiz
      • 6.22 Summary
      • 6.23 Conclusion
    • Lesson 7 - Cassandra Advanced Architecture
      • 7.1 Cassandra Advanced Architecture and Cluster Management
      • 7.2 Course Map
      • 7.3 Objectives
      • 7.4 Partitioning
      • 7.5 Murmur3Partitioner
      • 7.6 RandomPartitioner
      • 7.7 ByteOrderedPartitioner
      • 7.8 Replication of Data
      • 7.9 Replication Strategy
      • 7.10 SimpleStrategy
      • 7.11 NetworkTopologyStrategy
      • 7.12 NetworkTopologyStrategy (contd.)
      • 7.13 Replication Example
      • 7.14 Tunable Consistency
      • 7.15 Read Consistency
      • 7.16 Write Consistency
      • 7.17 Read or Write Failure
      • 7.18 Hinted Handoff
      • 7.19 Time to Live
      • 7.20 Tombstones
      • 7.21 Monitoring the Cluster
      • 7.22 Nodetool Options
      • 7.23 Install and Configure OpsCenter
      • 7.24 Monitoring with OpsCenter
      • 7.25 Monitoring with OpsCenter (contd.)
      • 7.26 Administer using OpsCenter
      • 7.27 Quiz
      • 7.28 Summary
      • 7.29 Conclusion
    • Lesson 8 - Apache Ecosystem around Cassandra
      • 8.1 Apache Ecosystem around Cassandra
      • 8.2 Course Map
      • 8.3 Objectives
      • 8.4 Stream
      • 8.5 Apache Storm
      • 8.6 Storm Architecture
      • 8.7 Storm Architecture (contd.)
      • 8.8 Storm Data Model
      • 8.9 Storm Topology
      • 8.10 Storm Topology - Example
      • 8.11 Apache Kafka
      • 8.12 Kafka Data Model
      • 8.13 Kafka Data Model (contd.)
      • 8.14 Kafka Architecture
      • 8.15 Kafka Architecture (contd.)
      • 8.16 Kafka-Queue System
      • 8.17 Kafka-Publish-Subscribe System
      • 8.18 Real-Time Data Analysis Platform
      • 8.19 Real-Time Data Analysis Platform (contd.)
      • 8.20 Apache Spark
      • 8.21 Apache Spark Architecture
      • 8.22 Resilient Distributed Datasets
      • 8.23 Operations in Spark
      • 8.24 Spark and Scala
      • 8.25 Spark - Example
      • 8.26 Quiz
      • 8.27 Summary
      • 8.28 Thank you

Achievements for this centre

2016

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