Big Data Trendz

From Cloudera Blog, thanks to    Justin Kestelyn   for valuable post in cloudera blog. The super-active Apache Spark community is exerting a strong gravitational pull within the Apache Hadoop ecosystem. I recently had that opportunity to ask Cloudera’s Apache Spark committers (Sean Owen, Imran Rashid [PMC], Sandy Ryza, and Marcelo Vanzin) for their perspectives about how the Spark community has worked and is working together, and the work to be done via the  One Platform initiative  to make the Spark stack enterprise-ready. Recently, Apache Spark has become the most currently active project in the Apache Hadoop ecosystem (measured by number of contributors/commits over time), if not the entire ASF. Why do you think that is? Owen: Partly because of scope: Apache Spark has been many sub-projects under an umbrella from the start, some large and complex in their own right, and has tacked on several more in just the last six months. Culture is anothe...

this post is from cloudera blog, thanks to IIya Ganelin Our thanks to Ilya Ganelin, Senior Data Engineer at Capital One Labs, for the guest post below about his hard-earned lessons from using Spark. I started using Apache Spark in late 2014, learning it at the same time as I learned Scala, so I had to wrap my head around the various complexities of a new language as well as a new computational framework. This process was a great in-depth introduction to the world of Big Data (I previously worked as an electrical engineer for Boeing), and I very quickly found myself deep in the guts of Spark. The hands-on experience paid off; I now feel extremely comfortable with Spark as my go-to tool for a wide variety of data analytics tasks, but my journey here was no cakewalk. Capital One’s original use case for Spark was to surface product recommendations for a set of 25 million users and 10 million products, one of the largest datasets available for this type of modeling. Moreover, we had ...

Source from Cloudera Also,  Reintroducing Cloudera Enterprise, now with Apache Spark - See more at: cloudera spark Cloudera is announcing the general availability of support for Spark, bringing interactive machine learning and stream processing to enterprise data hubs. Cloudera is pleased to announce the immediate availability of its first release of  Apache Spark  for Cloudera Enterprise (comprising CDH and Cloudera Manager). Spark was created and contributed to the Apache Software Foundation by UC Berkeley, and it has quickly gained adoption for machine learning, interactive analytics, and streaming analytics over large datasets. It features a general programming model for writing applications by composing arbitrary operators, such as mappers, reducers, joins, group-bys, and filters. Spark keeps track of the data that each of the operators produces, enabling applications to reliably store this data in memory, which makes it ideal for low-latency computation...