Google Map-Reduce Framework
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A Google Map-Reduce Framework is a Map-Reduce Framework used by Google Inc..
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- Counter-Example(s):
- See: HDFS.
References
2014
- Michael Stonebraker. http://cacm.acm.org/magazines/2015/1/181612-a-valuable-lesson-and-whither-hadoop/fulltext
- QUOTE: The second recent announcement comes from Google, who announced MapReduce is yesterday's news and they have moved on, building their software offerings on top of better systems such as Dremmel, Big Table, and F1/Spanner (http://bit.ly/1pi7QVC). In fact, Google must be "laughing in their beer" about now. They invented MapReduce to support the Web crawl for their search engine in 2004. A few years ago they replaced MapReduce in this application with BigTable, because they wanted an interactive storage system and Map Reduce was batch-only. Hence, the driving application behind MapReduce moved to a better platform a while ago. Now Google is reporting they see little-to-no future need for MapReduce.
It is indeed ironic that Hadoop is picking up support in the general community about five years after Google moved on to better things. Hence, the rest of the world followed Google into Hadoop with a delay of most of a decade. Google has long since abandoned it. I wonder how long it will take the rest of the world to follow Google's direction and do likewise …
- QUOTE: The second recent announcement comes from Google, who announced MapReduce is yesterday's news and they have moved on, building their software offerings on top of better systems such as Dremmel, Big Table, and F1/Spanner (http://bit.ly/1pi7QVC). In fact, Google must be "laughing in their beer" about now. They invented MapReduce to support the Web crawl for their search engine in 2004. A few years ago they replaced MapReduce in this application with BigTable, because they wanted an interactive storage system and Map Reduce was batch-only. Hence, the driving application behind MapReduce moved to a better platform a while ago. Now Google is reporting they see little-to-no future need for MapReduce.
2006
- (Chu et al., 2006) ⇒ Cheng-Tao Chu, Sang Kyun Kim, Yi-An Lin, YuanYuan Yu, Gary Bradski, Andrew Y. Ng, and Kunle Olukotun. (2006). “Map-Reduce for Machine Learning on Multicore.” In: Proceedings of the 19th International Conference on Neural Information Processing Systems.
- QUOTE: ... We adapt Google's map-reduce [7] paradigm to demonstrate this parallel speed up technique on a variety of learning algorithms including locally weighted linear regression (LWLR), k-means, logistic regression (LR), naive Bayes (NB), SVM, ICA, PCA, gaussian discriminant analysis (GDA), EM, and backpropagation (NN). ...