NoSQL Architecture Comparison Training – Big Data

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Chapter 1. Defining Big Data

Transforming Data into Business Information
Quality of Data
Gartner’s Definition of Big Data
More Definitions of Big Data
Processing Big Data
Challenges Posed by Big Data
The Cloud and Big Data
The Business Value of Big Data
Big Data: Hype or Reality?
Big Data Quiz
Big Data Quiz Answers
Summary

Chapter 2. NoSQL and Big Data Systems Overview

Limitations of Relational Databases
Limitations of Relational Databases (Con’t)
What are NoSQL (Not Only SQL) Databases?
The Past and Present of the NoSQL World
NoSQL Database Properties
NoSQL Benefits
NoSQL Database Storage Types
The CAP Theorem
Mechanisms to Guarantee a Single CAP Property
NoSQL Systems CAP Triangle
Limitations of NoSQL Databases
Big Data Sharding
Sharding Example
Amazon S3
Amazon Storage SLAs
Amazon Glacier
Amazon S3 Security
Data Lifecycle Management with Amazon S3
Amazon S3 Cost Monitoring
OpenStack
Object Store (Swift)
Components of Swift
Google BigTable
BigTable-based Applications
BigTable Design
Google Cloud Storage
Summary

Chapter 3. Adopting NoSQL

Hype Cycle and Technology Adoption Model
Barriers to Adoption
Dismantling Barriers to Adoption
Use Cases for NoSQL Database Systems
Example Applications
Industry trends
Enterprise Hadoop Solutions Offerings
Enterprise Big Data / NoSQL Offerings
IBM InfoSphere Platform
Oracle Big Data Appliance
NoSQL Technology Adoption Action Plan
Summary

Chapter 4. MapReduce Overview

MapReduce Defined
Google’s MapReduce
MapReduce Explained
MapReduce Word Count Job
MapReduce Shared-Nothing Architecture
Similarity with SQL Aggregation Operations
Example of Map & Reduce Operations using JavaScript
Problems Suitable for Solving with MapReduce
Typical MapReduce Jobs
Fault-tolerance of MapReduce
Distributed Computing Economics
MapReduce Systems
Summary

Chapter 5. Introduction to MongoDB

MongoDB
MongoDB Features (Cont’d)
MongoDB’s Logo
Positioning of MongoDB
Sharding in MongoDB
Data Replication
A Sample Sharded Cluster Diagram
MongoDB Security
Authentication
Data and Network Encryption
MongoDB Limitations
MongoDB Operational Intelligence
MongoDB Use Cases
MongoDB Data Model
The _id Primary Key Filed Considerations
Terminology
MongoDB Data Model
Data Modeling in RDBMS
Data Modeling in MongoDB
MongoDB Data Modeling
A Sample JSON Document Matching the Schema
Data Lifecycle Management
Data Lifecycle Management: TTL
Data Lifecycle Management: Capped Collections
MongoDB Query Language (QL)
The
find
and
findOne
Methods
The
find
and
findOne
Methods
A MongoDB QL Example
Data Inserts
Creating an Index
MongoDB vs Apache CouchDB
Summary

Chapter 6. Hadoop Overview

Apache Hadoop
Apache Hadoop Logo
Typical Hadoop Applications
Hadoop Clusters
Hadoop Design Principles
Hadoop’s Core Components
Hadoop Simple Definition
High-Level Hadoop Architecture
Hadoop-based Systems for Data Analysis
Hadoop Caveats
Summary

Chapter 7. Hadoop Distributed File System Overview

Hadoop Distributed File System
Data Blocks
Data Block Replication Example
HDFS NameNode Directory Diagram
Accessing HDFS
Examples of HDFS Commands
Client Interactions with HDFS for the Read Operation
Read Operation Sequence Diagram
Client Interactions with HDFS for the Write Operation
Communication inside HDFS
Summary

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Chapter 8. MapReduce with Hadoop

Hadoop’s MapReduce
MapReduce v1 (“Classic MapReduce”)
JobTracker and TaskTracker
YARN (MapReduce v2)
MapReduce Programming Options
Java MapReduce API
The Structure of a Java MapReduce Program
The Mapper Class
The Reducer Class
The Driver Class
Compiling Classes
Running the MapReduce Job
The Structure of a Single MapReduce Program
Combiner Pass (Optional)
Hadoop’s Streaming MapReduce
Python Word Count Mapper Program Example
Python Word Count Reducer Program Example
Setting up Java Classpath for Streaming Support
Streaming Use Cases
The Streaming API vs Java MapReduce API
Amazon Elastic MapReduce
Summary

Chapter 9. Apache Pig Scripting Platform

What is Pig?
Pig Latin
Apache Pig Logo
Pig Execution Modes
Local Execution Mode
MapReduce Execution Mode
Running Pig
Running Pig in Batch Mode
What is Grunt?
Pig Latin Statements
Pig Programs
Pig Latin Script Example
SQL Equivalent
Differences between Pig and SQL
Statement Processing in Pig
Comments in Pig
Supported Simple Data Types
Supported Complex Data Types
Arrays
Defining Relation’s Schema
The bytearray Generic Type
Using Field Delimiters
Referencing Fields in Relations
Summary

Chapter 10. Apache Pig HDFS Interface

The HDFS Interface
FSShell Commands (Short List)
Grunt’s Old File System Commands
Summary

Chapter 11. Apache Pig Relational and Eval Operators

Pig Relational Operators
Example of Using the JOIN Operator
Example of Using the Order By Operator
Caveats of Using Relational Operators
Pig Eval Functions
Caveats of Using Eval Functions (Operators)
Example of Using Single-column Eval Operations
Example of Using Eval Operators For Global Operations
Summary

Chapter 12. Hive

What is Hive?
Apache Hive Logo
Hive’s Value Proposition
Who uses Hive?
Hive’s Main Systems
Hive Features
Hive Architecture
HiveQL
Where are the Hive Tables Located?
Hive Command-line Interface (CLI)
Summary

Chapter 13. Hive Command-line Interface

Hive Command-line Interface (CLI)
The Hive Interactive Shell
Running Host OS Commands from the Hive Shell
Interfacing with HDFS from the Hive Shell
The Hive in Unattended Mode
The Hive CLI Integration with the OS Shell
Executing HiveQL Scripts
Comments in Hive Scripts
Variables and Properties in Hive CLI
Setting Properties in CLI
Example of Setting Properties in CLI
Hive Namespaces
Using the SET Command
Setting Properties in the Shell
Setting Properties for the New Shell Session
Summary

Chapter 14. Hive Data Definition Language

Hive Data Definition Language
Creating Databases in Hive
Using Databases
Creating Tables in Hive
Supported Data Type Categories
Common Primitive Types
Example of the CREATE TABLE Statement
The STRUCT Type
Table Partitioning
Table Partitioning
Table Partitioning on Multiple Columns
Viewing Table Partitions
Row Format
Data Serializers / Deserializers
File Format Storage
More on File Formats
The EXTERNAL DDL Parameter
Example of Using EXTERNAL
Creating an Empty Table
Dropping a Table
Table / Partition(s) Truncation
Alter Table/Partition/Column
Views
Create View Statement
Why Use Views?
Restricting Amount of Viewable Data
Examples of Restricting Amount of Viewable Data
Creating and Dropping Indexes
Describing Data
Summary

Chapter 15. Apache HBase

What is HBase?
HBase Design
HBase Features
The Write-Ahead Log (WAL) and MemStore
HBase vs RDBS
HBase vs Apache Cassandra
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
Table Horizontal Partitioning with Regions
HBase Compaction
Loading Data in HBase
HBase Shell
HBase Shell Command Groups
Creating and Populating a Table in HBase Shell
Getting a Cell’s Value
Counting Rows in an HBase Table
Summary