You are previewing Professional NoSQL.

Professional NoSQL

Cover of Professional NoSQL by Shashank Tiwari Published by Wrox
  1. Cover
  2. Contents
  3. Introduction
  4. Part I: Getting Started
    1. Chapter 1: NoSQL: What It Is and Why You Need it
      1. Definition and Introduction
      2. Sorted Ordered Column-Oriented Stores
      3. Key/Value Stores
      4. Document Databases
      5. Graph Databases
      6. Summary
    2. Chapter 2: Hello NoSQL: Getting Initial Hands-on Experience
      1. First Impressions — Examining Two Simple Examples
      2. Working with Language Bindings
      3. Summary
    3. Chapter 3: Interfacing and Interacting with NoSQL
      1. If No SQL, Then What?
      2. Language Bindings for NoSQL Data Stores
      3. Summary
  5. Part II: Learning the NoSQL Basics
    1. Chapter 4: Understanding the Storage Architecture
      1. Working with Column-Oriented Databases
      2. HBase Distributed Storage Architecture
      3. Document Store Internals
      4. Understanding Key/Value Stores in Memcached and Redis
      5. Eventually Consistent Non-relational Databases
      6. Summary
    2. Chapter 5: Performing CRUD Operations
      1. Creating Records
      2. Accessing Data
      3. Updating and Deleting Data
      4. Summary
    3. Chapter 6: Querying NoSQL Stores
      1. Similarities Between SQL and MongoDB Query Features
      2. Accessing Data from Column-Oriented Databases Like HBase
      3. Querying Redis Data Stores
      4. Summary
    4. Chapter 7: Modifying Data Stores and Managing Evolution
      1. Changing Document Databases
      2. Schema Evolution in Column-Oriented Databases
      3. HBase Data Import and Export
      4. Data Evolution in Key/Value Stores
      5. Summary
    5. Chapter 8: Indexing and Ordering Data Sets
      1. Essential Concepts Behind a Database Index
      2. Indexing and Ordering in MongoDB
      3. Creating and Using Indexes in MongoDB
      4. Indexing and Ordering in CouchDB
      5. Indexing in Apache Cassandra
      6. Summary
    6. Chapter 9: Managing Transactions and Data Integrity
      1. RDBMS AND ACID
      2. Distributed ACID Systems
      3. Upholding CAP
      4. Consistency Implementations in a Few NoSQL Products
      5. Summary
  6. Part III: Gaining Proficiency with NoSQL
    1. Chapter 10: Using NoSQL in the Cloud
      1. Google App Engine Data Store
      2. Amazon SimpleDB
      3. Summary
    2. Chapter 11: Scalable Parallel Processing with MapReduce
      1. Understanding MapReduce
      2. MapReduce with HBase
      3. MapReduce Possibilities and Apache Mahout
      4. Summary
    3. Chapter 12: Analyzing Big Data with Hive
      1. Hive Basics
      2. Back to Movie Ratings
      3. Good Old SQL
      4. JOIN(s) in Hive QL
      5. Summary
    4. Chapter 13: Surveying Database Internals
      1. MongoDB Internals
      2. Membase Architecture
      3. Hypertable Under the Hood
      4. Apache Cassandra
      5. Berkeley DB
      6. Summary
  7. Part IV: Mastering NoSQL
    1. Chapter 14: Choosing Among NoSQL Flavors
      1. Comparing NoSQL Products
      2. Benchmarking Performance
      3. Contextual Comparison
      4. Summary
    2. Chapter 15: Coexistence
      1. Using MySQL as a NoSQL Solution
      2. Mostly Immutable Data Stores
      3. Web Frameworks and NoSQL
      4. Migrating from RDBMS to NoSQL
      5. Summary
    3. Chapter 16: Performance Tuning
      1. Goals of Parallel Algorithms
      2. Influencing Equations
      3. Partitioning
      4. Scheduling in Heterogeneous Environments
      5. Additional MapReduce Tuning
      6. HBase Coprocessors
      7. Leveraging Bloom Filters
      8. Summary
    4. Chapter 17: Tools and Utilities
      1. RRDTool
      2. Nagios
      3. Scribe
      4. Flume
      5. Chukwa
      6. Pig
      7. Nodetool
      8. OpenTSDB
      9. Solandra
      10. Hummingbird and C5t
      11. GeoCouch
      12. Alchemy Database
      13. Webdis
      14. Summary
  8. Appendix: Installation and Setup Instructions
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Chapter 13

Surveying Database Internals

WHAT’S IN THIS CHAPTER?

  • Peeking under the hood of MongoDB, Membase, Hypertable, Apache Cassandra, and Berkeley DB
  • Exploring the internal architectural elements of a few select NoSQL products
  • Understanding the under-the-hood design choices

Learning a product or a tool involves at least three dimensions, namely:

  • Understanding its semantics and syntax
  • Learning by trying and using it
  • Understanding its internals and knowing what is happening under the hood

In the preceding chapters, you were exposed to a considerable amount of syntax, especially in the context of MongoDB, Redis, CouchDB, HBase, and Cassandra. Many of the examples illustrated the syntax and explained the concepts so trying them out would have given you a good hands-on head start to learning the NoSQL products. In some chapters, you had the opportunity to peek under the hood. In this chapter you dive deeper into in-depth discovery by exploring the architecture and the internals of a few select NoSQL products. As with the other chapters, the set of products I chose represents different types of NoSQL products. The products discussed in this chapter made it to the list for various reasons, some of which are as follows:

  • MongoDB — MongoDB has been featured in many chapters of this book. The book has already covered a few aspects of MongoDB internals and adding to that information base provides a comprehensive enough coverage of the product.
  • Membase — As far as key/value in-memory, ...

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