Planet MySQL Planet MySQL: Meta Deutsch Español Français Italiano 日本語 Русский Português 中文
Showing entries 1 to 10 of 19 9 Older Entries

Displaying posts with tag: MapReduce (reset)

Data Analytics at NBCUniversal. Interview with Matthew Eric Bassett.
+0 Vote Up -0Vote Down
“The most valuable thing I’ve learned in this role is that judicious use of a little bit of knowledge can go a long way. I’ve seen colleagues and other companies get caught up in the “Big Data” craze by spend hundreds of thousands of pounds sterling on a Hadoop cluster that sees a few megabytes [...]
On Big Data, Analytics and Hadoop. Interview with Daniel Abadi.
+0 Vote Up -0Vote Down
“Some people even think that “Hadoop” and “Big Data” are synonymous (though this is an over-characterization). Unfortunately, Hadoop was designed based on a paper by Google in 2004 which was focused on use cases involving unstructured data (e.g. extracting words and phrases from Webpages in order to create Google’s Web index). Since it was not [...]
Typical “Big” Data Architecture
+1 Vote Up -0Vote Down
Here is the typical “Big” data architecture, that covers most components involved in the data pipeline. More or less, we have the same architecture in production in number of places[...]
MySQL and Hadoop
Employee_Team +2 Vote Up -0Vote Down

Introduction

"Improving MySQL performance using Hadoop" was the talk which I and Manish Kumar gave at Java One & Oracle Develop 2012, India. Based on the response and interest of the audience, we decided to summarize the talk in a blog post. The slides of this talk can be found here. They also include a screen-cast of a live Hadoop system pulling data from MySQL and working on the popular 'word count' problem.



MySQL and Hadoop have been popularly considered as 'Friends with benefits' and our talk was aimed at showing how!



  [Read more...]
A super-set of MySQL for Big Data. Interview with John Busch, Schooner.
+0 Vote Up -0Vote Down
“Legacy MySQL does not scale well on a single node, which forces granular sharding and explicit application code changes to make them sharding-aware and results in low utilization of severs”– Dr. John Busch, Schooner Information Technology A super-set of MySQL suitable for Big Data? On this subject, I have interviewed Dr. John Busch, Founder, Chairman, [...]
451 CAOS Links 2011.08.23
+0 Vote Up -0Vote Down

Engine Yard acquires Orchestra. Red Hat considers NoSQL move. And more.

# Engine Yard announced a definitive agreement to acquire Orchestra, bringing PHP expertise to the Engine Yard platform.

# Red Hat’s CEO indicated the company is interested in a NoSQL or Hadoop acquisition.

# Gluster announced Apache Hadoop compatibility in the next GlusterFS release.

# Microsoft signed an agreement with China Standard Software Co (CS2C) to support CS2C

  [Read more...]
451 CAOS Links 2011.07.01
+0 Vote Up -0Vote Down

A herd of Hadoop announcements. Rockmelt raises $30m. And more.

A herd of Hadoop announcements
# Yahoo! and Benchmark Capital confirmed the formation of Hortonworks, an independent company focused on the development and support of Apache Hadoop.

# Cloudera announced the availability of Cloudera Enterprise 3.5 and the launch of Cloudera SCM Express, based on the new Service and Configuration Manager in Cloudera Enterprise 3.5.

# MapR


  [Read more...]
451 CAOS Links 2010.10.08
+0 Vote Up -0Vote Down

Patents! Patents! Patents! Canonical’s perfect 10. And more.

Follow 451 CAOS Links live @caostheory on Twitter and Identi.ca, and daily at Paper.li/caostheory
“Tracking the open source news wires, so you don’t have to.”

# Google responded to Oracle’s claims that its Android OS infringes copyrights and patents related to Java.

# Matt Asay evaluated the various patent claims against Android and its related devices.

# Microsoft licensed smartphone patents from ACCESS Co and a subsidiary of Acacia Research.

# Glyn Moody assessed what Microsoft’s


  [Read more...]
The SMAQ stack for big data
+0 Vote Up -0Vote Down

SMAQ report sections

→ MapReduce

→ Storage

→ Query

→ Conclusion

"Big data" is data that becomes large enough that it cannot be processed using conventional methods. Creators of web search engines were among the first to confront this problem. Today, social networks, mobile phones, sensors and science contribute to petabytes of data created daily.

To meet the challenge of processing such large data sets, Google created MapReduce. Google's work and Yahoo's creation of the Hadoop MapReduce implementation has spawned an ecosystem of big data processing tools.

As MapReduce has grown in  [Read more...]

MapReduce – DBInputFormat – Serialization on readers
+1 Vote Up -0Vote Down
Last week I was working on EC2 MySQL server where one of the slave is taking lot of time to catch-up; and only job that is running on that server[...]
Showing entries 1 to 10 of 19 9 Older Entries

Planet MySQL © 1995, 2014, Oracle Corporation and/or its affiliates   Legal Policies | Your Privacy Rights | Terms of Use

Content reproduced on this site is the property of the respective copyright holders. It is not reviewed in advance by Oracle and does not necessarily represent the opinion of Oracle or any other party.