Introduction To Big Data And NoSQL

IT Business Management Training

Introduction To Big Data And NoSQL

Available since November 2, 2019
...
Category

IT Business Management Training

Duration

1 day

Course description

COURSE AGENDA:
Defining Big Data
Big Data Stores Overview
NoSQL
Big Data BI & Analytics
Real World Case Studies
Adopting NoSQL

Target audience

General audience including business and technology team leadership

Course requirements

Basic programming skills, some knowledge of SQL

Course Plan

Section 01

Chapter 1

  • Introduction to NoSQL Systems
  • Gartner's Definition of Big Data
  • The V3Properties
  • Limitations of Relational Databases
  • Limitations of Relational Databases (Cont'd)
  • What are NoSQL (Not Only SQL) Databases?
  • What are NoSQL Databases?
  • The Past and Present of the NoSQL World
  • NoSQL Database Properties
  • NoSQL BenefitsUse Cases for NoSQL Database Systems
  • NoSQL Database Storage Types
  • The CAP Theorem
  • Mechanisms to Guarantee a Single CAP Property
  • NoSQL Systems CAP Triangle
  • Limitations of NoSQL Databases
  • Mix-and-Match Approach
  • Big Data Sharding
  • Sharding Example
  • Google BigTable
  • BigTable-based Applications
  • BigTable Design
  • Barriers to Adoption
  • Dismantling Barriers to Adoption
  • Industry trends
  • NoSQL Technology Adoption Action Plan
  • Quiz
  • Quiz Answers
  • Summary
Section 02

Chapter 2

  • Introduction to Hadoop
  • The Client u2013 Server Processing Pattern
  • Apache Hadoop
  • Apache Hadoop Logo
  • Typical Hadoop Applications
  • Hadoop Clusters
  • Hadoop Distributions
  • Hadoop's Main Components
  • Hadoop Distributed File System (HDFS)
  • HDFS Considerations
  • Data Blocks
  • HDFS Name
  • Node Directory Diagram
  • HDFS Balancing
  • Accessing HDFS
  • Examples of HDFS Commands
  • Other Supported File Systems
  • YARN
  • Hadoop-based Systems for Data Analysis
  • MapReduce
  • Similarity with SQL Aggregation Operations
  • MapReduce Word Count Example
  • Distributed Computing Economics
  • Discussion: Divide and Conquer
  • Apache PigPig Latin
  • Running PigPig Latin Script Example
  • What is Hive?
  • Hive's Value Proposition
  • Who uses Hive?
  • What Hive Does Not Have
  • HiveQL
  • Working with Hive Tables
  • Summary
Section 03

Chapter 3

  • Apache HBase
  • What is HBase?
  • HBase Design
  • HBase Master (HMaster)
  • Sparse Data Sets
  • Regions and Region Servers
  • HBase Features
  • HBase High Availability
  • The Write-Ahead Log (WAL) and MemStoreHBase vs RDBSHBase vs RDBS (Cont'd)
  • Interfacing with HBase
  • HBase Thrift and REST Gateway
  • HBase Table Design
  • Column Families
  • A Cell's Value Versioning
  • Timestamps
  • Accessing Cells
  • HBase Table Design Digest
  • The Conceptual View of an HBase Table
  • HBase Compaction
  • Loading Data in HBase
  • Column Families Notes
  • Cardinality of Column Families
  • Hotspotting
  • Rowkey Design Notes
  • Security
  • HBase Shell
  • HBase Shell Command Groups
  • Creating and Populating a Table Using HBase Shell
  • Getting a Cell's Value
  • Counting Rows in an HBase Table
  • HBase Java Client
  • HBase Scanners
  • The Scan Class
  • The Key
  • Value Class
  • The Result Class
  • Getting Versions of Cell Values Example
  • The Cell Interface
  • HBase Java Client Example
  • Scanning the Table Rows
  • Dropping a Table
  • The Bytes Utility Class
  • Table Schema Main Rules to Follow
  • Good Use Cases for HBase
  • Not Good Use Cases for HBase
  • Business Continuity Caveats
  • Summary
Section 04

Chapter 4

  • Apache Cassandra
  • What is Apache Cassandra?
  • Main Features
  • Peer-to-Peer (No Master)
  • Wide Column Store NoSQL Databases
  • Cassandra Model vs Relational Model
  • Column Families
  • Columns
  • Simplified Data Model
  • Data Model
  • The Cap Placement
  • CQLCQL Simple Examples
  • The Update Statement
  • Update Caveats
  • Update Statement with TTL and TIMESTAMP Examples
  • Collections
  • Example of Using a Set Collection
  • Using the List Collection
  • Data Replication
  • Visualizing Data Replication
  • The Write Path
  • Sequential Data Storage Engine
  • Java Client Code Example
  • Data Distribution
  • Native Aggregate Functions
  • Creating UDFs
  • HBase vs Apache Cassandra
  • Cassandra vs Mongo DBSecurity
  • WAN-Wide High Availability
  • Summary
Section 05

Lab Exercises

  • Lab 1. Learning the Lab Environment
  • Lab 2. The Hadoop Distributed File System
  • Lab 3. Using HBase Shell
  • Lab 4. Comparing NoSQL Systems

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Total Price: Request Quotation
Skill level: Beginner
Language: English
Certificate: No
Max students: 10
Total Duration: 1 day

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