Posted by BlairMABEL25 April - 12 - 2016 ADD COMMENTS

Advanced Analytics with Spark: Patterns for Learning from Data at Scale

Advanced Analytics with Spark: Patterns for Learning from Data at Scale

In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example.You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—classification, collaborative filtering, and anomaly detection among others—to fields su

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Data-Intensive Text Processing with MapReduce (Synthesis Lectures on Human Language Technologies)

Data-Intensive Text Processing with MapReduce (Synthesis Lectures on Human Language Technologies)

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Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale

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Apache Hadoop YARN: Moving Beyond MapReduce and Batch Processing with Apache

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Instant Mapreduce Patterns - Hadoop Essentials How-to by Srinath Perera (English
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Posted by gildenshelton565 February - 23 - 2016 ADD COMMENTS

Hadoop co-creator: Spark is great — but people want more
Ten years after its creation, the Hadoop ecosystem is sprawling and ever transforming. InfoWorld's Andy Oliver went as far as to say, "The biggest thing you need to know about Hadoop is that it isn't Hadoop anymore" — at least, not Hadoop as we once …
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For Data Scientists, Big Data is not so Big
Not surprisingly, because these data can be easily analyzable within that environment, most data scientists do not need skills in Big and Distributed Data (e.g., Hadoop and MapReduce). The size of data sets that data scientists analyze have remained …
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Posted by admin February - 9 - 2016 ADD COMMENTS

Splice Machine bags m to fund RDBMS on Hadoop and Spark
Splice Machine has secured $ 9m in C-round funding to carry on splicing Hadoop and relational database management system (RDBMS) technologies together. Total funding is now $ 31m and the extra cash will pay for accelerated product, sales and …
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Hortonworks takes Beabloo's raw data to Hadoop and back for massive analytics
Intelligence from the data is displayed through dashboards with heat maps, detailed zone analysis and personalised KPIs. Hortonworks is one of the major players in the Hadoop space and has created a fully open source Apache Hadoop data platform.
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Posted by BlairMABEL25 February - 6 - 2016 ADD COMMENTS

Hadoop Survey Shows Spark Coming of Age in 2016
Apache Spark, which has been shaking up the Apache Hadoop ecosystem for a couple years now, will come of age this year, moving from a talking point into enterprise deployment, according to a new Hadoop survey from Syncsort Inc. Interest in Spark …
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Picking the Right SQL-on-Hadoop Tool for the Job
SQL is, arguably, the biggest workload many organizations run on their Hadoop clusters. And there's good reason why: The combination of a familiar interface (SQL) along with a modern computing architecture (Hadoop) enables people to manipulate and …
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3 Ways Hadoop Can Minimize Security Risks
According to Ted Dunning, chief application architect at MapR Technologies, it's possible to get in front of attacks by analyzing all network event data with tools such as Apache Spark running on a real-time Hadoop platform, and to do so economically.
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Posted by gildenshelton565 June - 5 - 2015 ADD COMMENTS

Most popular Data Analytics eBay auctions:

Data Driven: How Performance Analytics D Elivers Extraordinary Sales Results

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Posted by admin April - 10 - 2015 ADD COMMENTS

Big Data Analytics Beyond Hadoop: Real-Time Applications with Storm, Spark, and More Hadoop Alternatives (FT Press Analytics)

Big Data Analytics Beyond Hadoop: Real-Time Applications with Storm, Spark, and More Hadoop Alternatives (FT Press Analytics)

Master alternative Big Data technologies that can do what Hadoop can’t: real-time analytics and iterative machine learning.   When most technical professionals think of Big Data analytics today, they think of Hadoop. But there are many cutting-edge applications that Hadoop isn’t well suited for, especially real-time analytics and contexts requiring the use of iterative machine learning algorithms. Fortunately, several powerful new technologies have been developed specifically for use cases s

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Posted by BlairMABEL25 March - 30 - 2015 ADD COMMENTS

Cloudera Doesn't Spark Hadoop Wars, Really?
Don't tell Oracle's head honcho Larry Ellison that some of his former employees have taken a page from his book, but darn if geeks at Cloudera aren't saying inflammatory things about the competition. In this case, the competition is Pivotal Software …
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The three open source projects that transformed Hadoop
Initially, Hadoop implementation required skilled teams of engineers and data scientists, making Hadoop too costly and cumbersome for many organizations. Now, thanks to a number of open source projects, big data analytics with Hadoop has become much …
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Airbnb Boosts Presto SQL Query Engine For Hadoop
Airbnb, the data-driven travel giant, announced Thursday that it's donating an internally developed tool called Airpal to open source, a move that could give Facebook-developed Presto an edge in SQL-on-Hadoop querying. Airpal is a Web-based …
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What you need to know about Hadoop right now
In fact, HBase is even more vital and Cassandra is on fire in the marketplace, although many now consider it to be its own thing outside of Hadoop. (If you think your brain is running out of room, at least you can forget that HAWQ or Greenplum ever …
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Posted by gildenshelton565 December - 17 - 2014 ADD COMMENTS

Storm or Spark: Choose your real-time weapon
Storm, a distributed computation framework for event stream processing, began life as a project of BackType, a marketing intelligence company bought by Twitter in 2011. Twitter soon open-sourced the project and put it on GitHub, but Storm ultimately …
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The Internet Of Things' Best-Kept Secret
“Today, part of the product is hardware and part of it is software and part of the software is in the product and part of it is in the cloud and the cloud has a whole new computing architecture. You need a data center … From what Heppelmann calls a …
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Posted by jaymepobre748 November - 21 - 2014 ADD COMMENTS

McLean, VA (PRWEB) November 12, 2014

MetiStream, a leader in implementing highly scalable real-time analytic and streaming solutions using innovative open source technologies, announced today that it has become a Spark Certified Systems Integrator and Certified Spark Trainer by Databricks, the company founded by the team that created and continues to drive Apache Spark, the most active open source project in the Big Data ecosystem.

MetiStream realized early on the potential of what Apache Spark could do to simplify Big Data implementations and has aligned its capabilities around Spark through its Spark 30-day Quick Start and Resilient Stream framework which leverages the Spark platform. Spark — with its integrated platform to support both batch and real-time processing — was a natural fit for MetiStream’s services offerings and technology frameworks. Investing in Spark allows MetiStream to ultimately share new innovative capabilities, speed deployment and lower cost of Big Data implementations to its end customers.

Beyond these certifications, MetiStream has also invested heavily in increasing community awareness of Spark through the Washington DC Area Apache Spark Interactive Meetup which they founded in May of this year and now has over 500 active members. Last week, MetiStream convened the first Spark Bake-off in DC to recognize some of the best Spark experts in the area.

“We are committed to continuing to grow and cultivate the capabilities and innovation around Spark locally, nationally, and within the Open Source community,” MetiStream’s CEO, Chiny Driscoll stated. “Databricks has been a great partner to team with and we are excited to work with them to expand the Spark community and most importantly help customers realize all the value that Spark has to offer”.

“The continued growth in adoption and deployment in production of Apache Spark by enterprises requires consulting services with certified expertise,” said John Tripier, Alliances and Ecosystem Lead at Databricks. “The ‘Certified on Spark’ Program ensures that certified systems integrators have the right level of expertise and experience to deliver Spark solutions. We are excited to collaborate with MetiStream and to see Enterprises benefit from their expertise in fast starting Spark projects and developing large scale streaming solutions.”

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About MetiStream

MetiStream offers solutions and expertise in implementing highly scalable real-time analytic and streaming solutions using innovative open source technologies. Located in the Washington DC area, the company is a woman and minority owned Big Data technology solutions provider. MetiStream’s mission is to help customers shorten the Time-to-Value issues seen in legacy and batch environments. A differentiator for MetiStream is their focus on implementing Big Data solutions using Open Source based technologies. For more information, visit http://www.metistream.com.

About Databricks

Databricks was founded by the creators of Apache Spark, who have been working for the past six years on cutting-edge systems to analyze and process Big Data. They believe that Big Data is a tremendous opportunity that is still largely untapped, and are actively working to revolutionize what enterprises can do with it. Databricks is venture-backed by Andreessen Horowitz. For more information, visit http://www.databricks.com.







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Posted by BlairMABEL25 September - 10 - 2014 ADD COMMENTS

Reza Zadeh, ICME Stanford As computer clusters scale up, data flow models such as MapReduce have emerged as a way to run fault-tolerant computations on commo…
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