Ones of my preferred topics in programming are algorithms and distributed computing. You can have both with MapReduce. These are some of my links (thanks to @asehmi for his help; he sent me some of these links).
MapReduce is a software framework introduced by Google in 2004 to support distributed computing on large data sets on clusters of computers. Parts of the framework are patented in some countries.
MapReduce: Simplified Data Processing on Large Clusters
Parallel Processing Using the Map Reduce Programming Model
Graph Twiddling in a MapReduce World
Cloud9: a MapReduce library for Hadoop
An implementation of Map-Reduce in C#
Twister: iterative MapReduce
ySpace Qizmt – MySpace’s Open Source Mapreduce Framework
Cascading is a Data Processing API, Process Planner, and Process Scheduler used for defining and executing complex, scale-free, and fault tolerant data processing workflows on an Apache Hadoop cluster. All without having to ‘think’ in MapReduce.
Project Daytona – Microsoft Research
Iterative MapReduce on Windows Azure
InfoQ: Introduction to Oozie
Combine multiple Map/Reduce jobs into a logical unit of work
InfoQ: Ville Tuulos on Big Data and Map/Reduce in Erlang and Python with Disco
Spark Cluster Computing Framework
Preview of Storm: The Hadoop of Realtime Processing – BackType Technology
Hadoop in Azure – Distributed Development – Site Home – MSDN Blogs
MapReduce: A Soft Introduction
Mapreduce & Hadoop Algorithms in Academic Papers
MSDN Magazine: MapReduce in F# – Parsing Log Files with F#, MapReduce and Windows Azure
F#: With a few lines of code entered into the powershell and analyze gigabytes of cloud data! – Systems, architecture and engineering solutions!
Data-Intensive Text Processing with MapReduce
The Geomblog: Workshop on Parallelism, and a "breakthrough" in combinatorial geometry
Pragmatic Programming Techniques: Designing algorithms for Map Reduce
Mapreduce and Hadoop Algorithms in Bioinformatics Papers | Abhishek Tiwari
Pragmatic Programming Techniques: Map/Reduce to recommend people connection
High Scalability – Dremel: Interactive Analysis of Web-Scale Datasets – Data as a Programming Paradigm
Tutorial: MapReduce with Riak « myNoSQL
High Scalability – How Rackspace Now Uses MapReduce and Hadoop to Query Terabytes of Data
Pregel: Google’s other data-processing infrastructure | Scalable web architectures
Apache Mahout – Overview
The Apache Mahout™ machine learning library’s goal is to build scalable machine learning libraries.
InfoQ: Billy Newport Discusses Parallel Programming in Java
Sector/Sphere: High Performance Distributed Data Storage and Processing
MapReduce – The Fanfiction « Snail in a Turtleneck
Map / Reduce – A visual explanation
Graph algorithms (and MapReduce)
Using MapReduce Functionality To Process Data
More links about Hadoop and other systems are coming.