War of the Hadoop SQL engines. And the winner is ...? - Sonra
War of the Hadoop SQL engines. And the winner is …? You may have wondered why we were quiet over the last couple of weeks? Well, we locked ourselves into the basement and did some research and a couple of projects and PoCs on Hadoop, Big Data, and distributed processing frameworks in general. We were also looking at Clickstream data and Web Analytics solutions. Over the next couple of weeks we wil
Scala and big data in ICM. Scoobie, Scalding, Spark, Stratosphere. Scalar 2014
This document discusses various big data frameworks including Spark, Scoobi, Hadoop, and GraphX. It provides an example of using Spark to interactively analyze log data stored on HDFS. Spark allows loading data into memory and running multiple queries efficiently. The document also discusses benefits of Spark such as its scalability, libraries for SQL, streaming, machine learning and more.Read les
Spark at Twitter - Seattle Spark Meetup, April 2014
Spark at Twitter - Seattle Spark Meetup, April 2014 The document discusses the results of a study on the impact of climate change on coffee production. Researchers found that suitable land for coffee production could decline by up to 50% by 2050 due to rising temperatures and changing rain patterns associated with climate change. Arabica coffee was found to be most at risk, as its growing regions
Engineering Blogs - Ooyala Community
Written by Anupama Shetty 4/13/17 Code coverage as defined by Wikipedia refers to a measure used to describe the degree to which the source code of a program is executed when a particular test suite runs. Thus, serving as a metric to track the percentage of code lines having a corresponding test to validate its functionality. While code coverage itself is not a self sufficient metric and may not a
Big Data Benchmark
Click Here for the previous version of the benchmark Introduction Several analytic frameworks have been announced in the last year. Among them are inexpensive data-warehousing solutions based on traditional Massively Parallel Processor (MPP) architectures (Redshift), systems which impose MPP-like execution engines on top of Hadoop (Impala, HAWQ), and systems which optimize MapReduce to improve per
Hive, Pig, Scalding, Scoobi, Scrunch and Spark
Comparison of Hadoop Frameworks I had to do simple processing of log files in a Hadoop cluster. Writing Hadoop MapReduce classes in Java is the assembly code of Big Data. There are several high level Hadoop frameworks that make Hadoop programming easier. Here is the list of Hadoop frameworks I tried: Pig Scalding Scoobi Hive Spark Scrunch Cascalog The task was to read log files join with other dat
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Real-time Recommendations using Spark Comcast Labs
Will Spark overtake Hadoop? Will Hadoop be replaced by Spark?
How do you compare Spark with Hadoop/Hive Stack? Anybody using it in production?
