Professional NoSQL -- Contents -- Introduction -- Part I: Getting Started -- Chapter 1: NoSQL: What It Is and Why You Need It -- Definition and Introduction -- Context and a Bit of History -- Big Data -- Scalability -- Definition and Introduction -- Sorted Ordered Column-Oriented Stores -- Key/Value Stores -- Document Databases -- Graph Databases -- Summary -- Chapter 2: Hello NoSQL: Getting Initial Hands-On Experience -- First Impressions - Examining Two Simple Examples -- A Simple Set of Persistent Preferences Data -- Storing Car Make and Model Data -- Working with Language Bindings -- MongoDB's Drivers -- A First Look at Thrift -- Summary -- Chapter 3: Interfacing and Interacting With NoSQL -- If No SQL, Then What? -- Storing and Accessing Data -- Storing Data In and Accessing Data from MongoDB -- Querying MongoDB -- Storing Data In and Accessing Data from Redis -- Querying Redis -- Storing Data In and Accessing Data from HBase -- Querying HBase -- Storing Data In and Accessing Data from Apache Cassandra -- Querying Apache Cassandra -- Language Bindings for NoSQL Data Stores -- Being Agnostic with Thrift -- Language Bindings for Java -- Language Bindings for Python -- Language Bindings for Ruby -- Language Bindings for PHP -- Summary -- Part II: Learning the NoSQL Basics -- Chapter 4: Understanding the Storage Architecture -- Working with Column-Oriented Databases -- Using Tables and Columns in Relational Databases -- Contrasting Column Databases with RDBMS -- Column Databases as Nested Maps of Key/Value Pairs -- Laying out the Webtable -- HBase Distributed Storage Architecture -- Document Store Internals -- Storing Data in Memory-Mapped Files -- Guidelines for Using Collections and Indexes in MongoDB -- MongoDB Reliability and Durability -- Horizontal Scaling -- Understanding Key/Value Stores in Memcached and Redis.

Under the Hood of Memcached -- Redis Internals -- Eventually Consistent Non-relational Databases -- Consistent Hashing -- Object Versioning -- Gossip-Based Membership and Hinted Handoff -- Summary -- Chapter 5: Performing CRUD Operations -- Creating Records -- Creating Records in a Document-Centric Database -- Using the Create Operation in Column-Oriented Databases -- Using the Create Operation in Key/Value Maps -- Accessing Data -- Accessing Documents from MongoDB -- Accessing Data from HBase -- Querying Redis -- Updating and Deleting Data -- Updating and Modifying Data in MongoDB, HBase, and Redis -- Limited Atomicity and Transactional Integrity -- Summary -- Chapter 6: Querying NoSQL Stores -- Similarities Between SQL and MongoDB Query Features -- Loading the MovieLens Data -- MapReduce in MongoDB -- Accessing Data from Column-Oriented Databases Like HBase -- The Historical Daily Market Data -- Querying Redis Data Stores -- Summary -- Chapter 7: Modifying Data Stores and Managing Evolution -- Changing Document Databases -- Schema-less Flexibility -- Exporting and Importing Data from and into MongoDB -- Schema Evolution in Column-Oriented Databases -- HBase Data Import and Export -- Data Evolution in Key/Value Stores -- Summary -- Chapter 8: Indexing and Ordering Data Sets -- Essential Concepts Behind a Database Index -- Indexing and Ordering in MongoDB -- Creating and Using Indexes in MongoDB -- Compound and Embedded Keys -- Creating Unique and Sparse Indexes -- Keyword-based Search and MultiKeys -- Indexing and Ordering in CouchDB -- The B-tree Index in CouchDB -- Indexing in Apache Cassandra -- Summary -- Chapter 9: Managing Transactions and Data Integrity -- RDBMS and ACID -- Isolation Levels and Isolation Strategies -- Distributed ACID Systems -- Consistency -- Availability -- Partition Tolerance -- Upholding CAP.

Compromising on Availability -- Compromising on Partition Tolerance -- Compromising on Consistency -- Consistency Implementations in a Few NoSQL Products -- Distributed Consistency in MongoDB -- Eventual Consistency in CouchDB -- Eventual Consistency in Apache Cassandra -- Consistency in Membase -- Summary -- Part III: Gaining Proficiency with NoSQL -- Chapter 10: Using NoSQL in the Cloud -- Google App Engine Data Store -- GAE Python SDK: Installation, Setup, and Getting Started -- Essentials of Data Modeling for GAE in Python -- Queries and Indexes -- Allowed Filters and Result Ordering -- Tersely Exploring the Java App Engine SDK -- Amazon SimpleDB -- Getting Started with SimpleDB -- Using the REST API -- Accessing SimpleDB Using Java -- Using SimpleDB with Ruby and Python -- Summary -- Chapter 11: Scalable Parallel Processing with MapReduce -- Understanding MapReduce -- Finding the Highest Stock Price for Each Stock -- Uploading Historical NYSE Market Data into CouchDB -- MapReduce with HBase -- MapReduce Possibilities and Apache Mahout -- Summary -- Chapter 12: Analyzing Big Data with Hive -- Hive Basics -- Back to Movie Ratings -- Good Old SQL -- JOIN(s) in Hive QL -- Explain Plan -- Partitioned Table -- Summary -- Chapter 13: Surveying Database Internals -- MongoDB Internals -- MongoDB Wire Protocol -- Inserting a Document -- Querying a Collection -- MongoDB Database Files -- Membase Architecture -- Hypertable Under the Hood -- Regular Expression Support -- Bloom Filter -- Apache Cassandra -- Peer-to-Peer Model -- Based on Gossip and Anti-entropy -- Fast Writes -- Hinted Handoff -- Berkeley DB -- Storage Configuration -- Summary -- Part IV: Mastering NoSQL -- Chapter 14: Choosing Among NoSQL Flavors -- Comparing NoSQL Products -- Scalability -- Transactional Integrity and Consistency -- Data Modeling -- Querying Support.

Access and Interface Availability -- Benchmarking Performance -- 50/50 Read and Update -- 95/5 Read and Update -- Scans -- Scalability Test -- Hypertable Tests -- Contextual Comparison -- Summary -- Chapter 15: Coexistence -- Using MySQL as a NoSQL Solution -- Mostly Immutable Data Stores -- Polyglot Persistence at Facebook -- Data Warehousing and Business Intelligence -- Web Frameworks and NoSQL -- Using Rails with NoSQL -- Using Django with NoSQL -- Using Spring Data -- Migrating from RDBMS to NoSQL -- Summary -- Chapter 16: Performance Tuning -- Goals of Parallel Algorithms -- The Implications of Reducing Latency -- How to Increase Throughput -- Linear Scalability -- Influencing Equations -- Amdahl's Law -- Little's Law -- Message Cost Model -- Partitioning -- Scheduling in Heterogeneous Environments -- Additional Map-Reduce Tuning -- Communication Overheads -- Compression -- File Block Size -- Parallel Copying -- HBase Coprocessors -- Leveraging Bloom Filters -- Summary -- Chapter 17: Tools and Utilities -- RRDTool -- Nagios -- Scribe -- Flume -- Chukwa -- Pig -- Interfacing with Pig -- Pig Latin Basics -- Nodetool -- OpenTSDB -- Solandra -- Hummingbird and C5t -- GeoCouch -- Alchemy Database -- Webdis -- Summary -- Appendix: Installation and Setup Instructions -- Installing and Setting Up Hadoop -- Installing Hadoop -- Configuring a Single-node Hadoop Setup -- Configuring a Pseudo-distributed Mode Setup -- Installing and Setting Up HBase -- Installing and Setting Up Hive -- Configuring Hive -- Overlaying Hadoop Configuration -- Installing and Setting Up Hypertable -- Making the Hypertable Distribution FHS-Compliant -- Configuring Hadoop with Hypertable -- Installing and Setting Up MongoDB -- Configuring MongoDB -- Installing and Configuring CouchDB -- Installing CouchDB from Source on Ubuntu 10.04 -- Installing and Setting Up Redis.

Installing and Setting Up Cassandra -- Configuring Cassandra -- Configuring log4j for Cassandra -- Installing Cassandra from Source -- Installing and Setting Up Membase Server and Memcached -- Installing and Setting Up Nagios -- Downloading and Building Nagios -- Configuring Nagios -- Compiling and Installing Nagios Plugins -- Installing and Setting Up RRDtool -- Installing Handler Socket for MySQL -- Index -- Advertisement.