Real-time MapReduce: Why MapReduce is making a comeback
What if we could adapt MapReduce to real-time data processing? Spoiler: it’s awesome and we’re building a next-gen data platform based on it! In the 2020’s, MapReduce isn’t a processing model that will turn many heads. It’s been around for well over a decade, and is easy to write off as an idea that might’ve been groundbreaking in its time, but is dated today. MapReduce was a big deal for a reason
MapReduce with Deltas
Status In proceedings of PDPTA 2011 Authors Ralf Lämmel and David Saile Abstract The MapReduce programming model is extended conservatively to deal with deltas for input data such that recurrent MapReduce computations can be more efficient for the case of input data that changes only slightly over time. That is, the extended model enables more frequent re-execution of MapReduce computations and th
Monoidify! Monoids as a Design Principle for Efficient MapReduce Algorithms
It is well known that since the sort/shuffle stage in MapReduce is costly, local aggregation is one important principle to designing efficient algorithms. This short paper represents an attempt to more clearly articulate this design principle in terms of monoids, which generalizes the use of combiners and the in-mapper combining pattern.
WWW2002 - Eleventh International World Wide Web Conference
IW3C2 is partnering with Geek Cruises and hereby announces our FIRST "mid-year" meeting! *************************************************** "WWW2002 Midyear: A Tech Update" WESTERN CARIBBEAN, November 9-16 2002 *************************************************** Learn about critical web technologies from leading experts on a relaxing cruise in the Western Caribbean! http://www.geekcruises.com/hom
Mr.LDA: Scalable Topic Modeling Using Variational Inference in MapReduce
Scalable Topic Modeling Using Variational Inference in MapReduce View the Project on GitHub lintool/Mr.LDA Introduction Mr.LDA is an open-source package for flexible, scalable, multilingual topic modeling using variational inference in MapReduce. Latent Dirichlet Allocation (LDA) and related topic modeling technique are useful for exploring document collections. Because of the increasing prevalenc
Tenzing A SQL Implementation On The MapReduce Framework
Proceedings of VLDB, VLDB Endowment (2011), pp. 1318-1327 Tenzing is a query engine built on top of MapReduce for ad hoc analysis of Google data. Tenzing supports a mostly complete SQL implementation (with several extensions) combined with several key characteristics such as heterogeneity, high performance, scalability, reliability, metadata awareness, low latency, support for columnar storage and
BigQuery についてのホワイトペーパーを公開しました
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The Elephant was a Trojan Horse: On the Death of Map-Reduce at Google - Paper Trail
Note: this is a personal blog post, and doesn’t reflect the views of my employers at Cloudera Map-Reduce is on its way out. But we shouldn’t measure its importance in the number of bytes it crunches, but the fundamental shift in data processing architectures it helped popularise. This morning, at their I/O Conference, Google revealed that they’re not using Map-Reduce to process data internally at
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https://cs.uwaterloo.ca/~jimmylin/publications/Lin_IEEE2017a.pdf
http://theory.stanford.edu/~sergei/papers/soda10-mrc.pdf
Dimension Independent Matrix Square using MapReduce
https://cloud.github.com/downloads/SWIMProjectUCB/SWIM/MapReduceWorkloadMASCOTSCameraReady.pdf
GitHub - SWIMProjectUCB/SWIM: Statistical Workload Injector for MapReduce - Project at UC Berkeley AMP Lab
http://web.stanford.edu/~ashishg/papers/mapreducecomplexity.pdf
https://people.eecs.berkeley.edu/~kubitron/courses/cs262a-F13/projects/reports/project16_report.pdf
Scalding: Reaching Efficient MapReduce
Scale-out Beyond MapReduce
mrcube_talk_icde11
https://arnab.org/files/mrcube.pdf
http://arxiv.org/pdf/1304.1467.pdf