Spark



With Spark Page Turn words and images into beautiful, magazine-style web stories that will impress readers on any device.

  1. Www.sparkletts.com
  2. Sparkletts
  3. Sparknotes.com
  4. Sparkle In Pink

Www.sparkletts.com

Sparklight
  1. To help protect, Spark comes equipped with 10 standard airbags, † and a a high-strength steel safety cage. And with available advanced active safety features such as Automatic Emergency Braking, Forward Collision Alert and Lane Departure Warning, you can take the wheel with even more confidence.
  2. Exciting and responsive, Spark lets you handle turns and tight parking spots when you’re driving around town looking for adventure. It offers what you need to stay connected and has a spectrum of bold color choices to perfectly suit your style. A car as fun as it is functional? Now we’re getting somewhere.
  3. Spark was created to address the limitations to MapReduce, by doing processing in-memory, reducing the number of steps in a job, and by reusing data across multiple parallel operations. With Spark, only one-step is needed where data is read into memory, operations performed, and the results written back—resulting in a much faster execution.

Sparkletts

Apache Spark started in 2009 as a research project at UC Berkley’s AMPLab, a collaboration involving students, researchers, and faculty, focused on data-intensive application domains. The goal of Spark was to create a new framework, optimized for fast iterative processing like machine learning, and interactive data analysis, while retaining the scalability, and fault tolerance of Hadoop MapReduce. The first paper entitled, “Spark: Cluster Computing with Working Sets” was published in June 2010, and Spark was open sourced under a BSD license. In June, 2013, Spark entered incubation status at the Apache Software Foundation (ASF), and established as an Apache Top-Level Project in February, 2014. Spark can run standalone, on Apache Mesos, or most frequently on Apache Hadoop.

Sparknotes.com

Sparkling

Sparkle In Pink

Today, Spark has become one of the most active projects in the Hadoop ecosystem, with many organizations adopting Spark alongside Hadoop to process big data. In 2017, Spark had 365,000 meetup members, which represents a 5x growth over two years. It has received contribution by more than 1,000 developers from over 200 organizations since 2009.