От: | jazzer | Skype: enerjazzer | |
Дата: | 30.06.14 10:27 | ||
Оценка: | 10 (3) |
http://the-paper-trail.org/blog/the-elephant-was-a-trojan-horse-on-the-death-of-map-reduce-at-google/This morning, at their I/O Conference, Google revealed that they’re not using Map-Reduce to process data internally at all any more.
...
The truth is that Map-Reduce as a processing paradigm continues to be severely restrictive, and is no more than a subset of richer processing systems.
... ever since Dryad, in 2007 (at least), it was clear to me that Map-Reduce’s days were numbered.
http://www.datacenterknowledge.com/archives/2014/06/25/google-dumps-mapreduce-favor-new-hyper-scale-analytics-system/Google has abandoned MapReduce, the system for running data analytics jobs spread across many servers the company developed and later open sourced, in favor of a new cloud analytics system it has built called Cloud Dataflow.
...
“We don’t really use MapReduce anymore,” Hölzle said in his keynote presentation at the Google I/O conference in San Francisco Wednesday. The company stopped using the system “years ago.”
http://googlecloudplatform.blogspot.com/2014/06/sneak-peek-google-cloud-dataflow-a-cloud-native-data-processing-service.htmlYesterday, at Google I/O, you got a sneak peek of Google Cloud Dataflow, the latest step in our effort to make data and analytics accessible to everyone. You can use Cloud Dataflow:
for data integration and preparation (e.g. in preparation for interactive SQL in BigQuery)
to examine a real-time stream of events for significant patterns and activities
to implement advanced, multi-step processing pipelines to extract deep insight from datasets of any size
You will always get what you always got
If you always do what you always did