IBM announced a major commitment to Apache®Spark™, potentially the most important new open source project in a decade that is being defined by data. At the core of this commitment, IBM plans to embed Spark into its industry-leading Analytics and Commerce platforms, and to offer Spark as a service on IBM Cloud. IBM will also put more than 3,500 IBM researchers and developers to work on Spark-related projects at more than a dozen labs worldwide; donate its breakthrough IBM SystemML machine learning technology to the Spark open source ecosystem; and educate more than one million data scientists and data engineers on Spark.
As data and analytics are embedded into the fabric of business and society –from popular apps to the Internet of Things (IoT) –Spark brings essential advances to large-scale data processing.
1. it dramatically improves the performance of data dependent apps.
2. it radically simplifies the process of developing intelligent apps, which are fueled by data.
What is Spark?
Apache® Spark™ is an open-source cluster computing framework with in-memory processing to speed analytic applications up to 100 times faster compared to technologies on the market today. Developed in the AMPLab at UC Berkeley, Spark can help reduce data interaction complexity, increase processing speed and enhance mission-critical applications with deep intelligence.
It simplifies the process of developing "smart" distributed applications. By managing in-memory computing resources, it provides primitives that can boost performance by 100-times for applications like machine learning. Spark keeps all often-used data in-memory, rather than on mass storage devices, allowing it to be quickly and repeatedly accessed, which is why it is appropriate for smart apps such as machine learning. The Apache Software Foundation claims Spark is its most active project, with over 465 contributors in 2014 alone.
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As data and analytics are embedded into the fabric of business and society –from popular apps to the Internet of Things (IoT) –Spark brings essential advances to large-scale data processing.
1. it dramatically improves the performance of data dependent apps.
2. it radically simplifies the process of developing intelligent apps, which are fueled by data.
What is Spark?
Apache® Spark™ is an open-source cluster computing framework with in-memory processing to speed analytic applications up to 100 times faster compared to technologies on the market today. Developed in the AMPLab at UC Berkeley, Spark can help reduce data interaction complexity, increase processing speed and enhance mission-critical applications with deep intelligence.
It simplifies the process of developing "smart" distributed applications. By managing in-memory computing resources, it provides primitives that can boost performance by 100-times for applications like machine learning. Spark keeps all often-used data in-memory, rather than on mass storage devices, allowing it to be quickly and repeatedly accessed, which is why it is appropriate for smart apps such as machine learning. The Apache Software Foundation claims Spark is its most active project, with over 465 contributors in 2014 alone.
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