Peter Schröder

Phoet, Señor Developer

Plötzliche Regenfälle können zum Betreten einer Buchhandlung zwingen.

- Loriot

In meiner Freizeit lese ich bevorzugt Fachbücher. Dabei sind die Themengebiete breit verstreut, neuerdings fokussiere ich mich jedoch hauptsächlich auf Objective-C/Cocoa und Ruby-Bücher.

Hier eine kleine zufällige Auswahl:

Beginning Mac Programming: Develop with Objective-C and Cocoa (Pragmatic Prog...
von Tim Isted
mit 419 Seiten
aufgelegt Pragmatic Bookshelf 2010-05-04 mit ISBN 9781934356517

Ruby Best Practices
von Gregory T Brown
mit 328 Seiten
aufgelegt O'Reilly and Associates 2009-07-02 mit ISBN 9780596523008

Ruby Best Practices Helps programmers learn how to design beautiful APIs and domain-specific languages, write code that's readable and expressive, work with functional programming ideas and techniques that can simplify code and make them more productive, and more. Full description

Crafting Rails Applications: Expert Practices for Everyday Rails Development ...
von Jose Valim
EUR 3,28 mit 184 Seiten
aufgelegt O'Reilly Vlg. Gmbh & Co. 2011-05-03 mit ISBN 9781934356739

Crafting Rails Applications Rails 3 is a huge step forward. This pioneering book is the first resource that deep dives into the new Rails 3 APIs and shows you how use them to write better web applications and make your day-to-day work with Rails more productive. Full description

Fast Data Processing with Spark
von Holden Karau
mit 120 Seiten
aufgelegt Packt Publishing 2013-10-23 mit ISBN

In Detail

Spark is a framework for writing fast, distributed programs. Spark solves similar problems as Hadoop MapReduce does but with a fast in-memory approach and a clean functional style API. With its ability to integrate with Hadoop and inbuilt tools for interactive query analysis (Shark), large-scale graph processing and analysis (Bagel), and real-time analysis (Spark Streaming), it can be interactively used to quickly process and query big data sets.

Fast Data Processing with Spark covers how to write distributed map reduce style programs with Spark. The book will guide you through every step required to write effective distributed programs from setting up your cluster and interactively exploring the API, to deploying your job to the cluster, and tuning it for your purposes.

Fast Data Processing with Spark covers everything from setting up your Spark cluster in a variety of situations (stand-alone, EC2, and so on), to how to use the interactive shell to write distributed code interactively. From there, we move on to cover how to write and deploy distributed jobs in Java, Scala, and Python.

We then examine how to use the interactive shell to quickly prototype distributed programs and explore the Spark API. We also look at how to use Hive with Spark to use a SQL-like query syntax with Shark, as well as manipulating resilient distributed datasets (RDDs).


This book will be a basic, step-by-step tutorial, which will help readers take advantage of all that Spark has to offer.

Who this book is for

Fast Data Processing with Spark is for software developers who want to learn how to write distributed programs with Spark. It will help developers who have had problems that were too much to be dealt with on a single computer. No previous experience with distributed programming is necessary. This book assumes knowledge of either Java, Scala, or Python.

Clojure: Grundlagen, Concurrent Programming, Java
von Stefan Kamphausen, Tim Oliver Kaiser
mit 344 Seiten
aufgelegt dpunkt 2010-09-20 mit ISBN 9783898646840