During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book.

This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates.

Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

• Emphasis throughout on both performance and reliability
• Thorough coverage of storage engines, including in-depth tuning and optimizations for the InnoDB storage engine
• Effects of new features in MySQL 5.0 and 5.1, including stored procedures, partitioned databases, triggers, and views
• A detailed discussion on how to build very large, highly scalable systems with MySQL
• New options for backups and replication
• Optimization of advanced querying features, such as full-text searches
• Four new appendices

The book also includes chapters on benchmarking, profiling, backups, security, and tools and techniques to help you measure, monitor, and manage your MySQL installations.

Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop’s data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop’s database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems

If you have lots of data — whether it’s gigabytes or petabytes — Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. “Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk.” — Doug Cutting, Hadoop Founder, Yahoo!

Move quickly through SQL basics and learn several advanced features Use SQL data statements to generate, manipulate, and retrieve data Create database objects, such as tables, indexes, and constraints, using SQL schema statements Learn how data sets interact with queries, and understand the importance of subqueries Convert and manipulate data with SQL’s built-in functions, and use conditional logic in data statements

Knowledge of SQL is a must for interacting with data. With Learning SQL, you’ll quickly learn how to put the power and flexibility of this language to work.

Maybe you’ve written some simple SQL queries to interact with databases. But now you want more, you want to really dig into those databases and work with your data. Head First SQL will show you the fundamentals of SQL and how to really take advantage of it. We’ll take you on a journey through the language, from basic INSERT statements and SELECT queries to hardcore database manipulation with indices, joins, and transactions. We all know “Data is Power” – but we’ll show you how to have “Power over your Data”. Expect to have fun, expect to learn, and expect to be querying, normalizing, and joining your data like a pro by the time you’re finished reading!

Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Let’s face it, SQL is a deceptively simple language to learn, and many database developers never go far beyond the simple statement: SELECT FROM WHERE . But there is “so” much more you can do with the language. In the “SQL Cookbook,” experienced SQL developer Anthony Molinaro shares his favorite SQL techniques and features. You’ll learn about:

Window functions, arguably the most significant enhancement to SQL in the past decade. If you’re not using these, you’re missing out

Powerful, database-specific features such as SQL Server’s PIVOT and UNPIVOT operators, Oracle’s MODEL clause, and PostgreSQL’s very useful GENERATE_SERIES function

Pivoting rows into columns, reverse-pivoting columns into rows, using pivoting to facilitate inter-row calculations, and double-pivoting a result set

“Bucketization,” and why you should never use that term in Brooklyn.

How to create histograms, summarize data into buckets, perform aggregations over a moving range of values, generate running-totals and subtotals, and other advanced, data warehousing techniques

The technique of “walking a string,” which allows you to use SQL to parse through the characters, words, or delimited elements of a string

Written in O’Reilly’s popular Problem/Solution/Discussion style, the “SQL Cookbook” is sure to please. Anthony’s credo is: “When it comes down to it, we all go to work, weall have bills to pay, and we all want to go home at a reasonable time and enjoy what’s still available of our days.” The “SQL Cookbook” moves quickly from problem to solution, saving you time each step of the way.