MapReduce has proven to be a valuable tool at Google. As of early 2007, we have more than 6,000 distinct programs written using the MapReduce programming model, and run more than 35,000 MapReduce jobs per day, processing about 8 petabytes of input data per day (a sustained rate of about 100 gigabytes per second). Although we originally developed the MapReduce programming model as part of our efforts to rewrite the indexing system for our web search product, it has shown itself to be useful across a very broad range of problems, including machine learning, statistical machine translation, log analysis, information retrieval experimentation, and general large-scale data processing and computation tasks.