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O’Reilly – Analyzing Big Data with Spark and Amazon EMR

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O’Reilly – Analyzing Big Data with Spark and Amazon EMR
English | Size: 453.51 MB
Category: Tutorial


You’re a software developer somewhat familiar with Apache Spark and how it’s used to analyze Big Data. You’ve been tasked with a Big Data analysis job and you want to rent space on a cluster to do it. But where to begin?

This is a hands-on course where Amazon Web Services pro Frank Kane shows you how to rent Amazon’s Elastic MapReduce service (EMR) at minimal cost and use it to run Spark scripts on top of a real Hadoop cluster. Kane’s approach is fun: You’ll learn a Big Data analysis process by actually deploying Spark on EMR to build a working movie recommendation engine using real movie ratings data.
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Real World Vagrant – Build an Apache Spark Development Env

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Real World Vagrant – Build an Apache Spark Development Env
English | Size: 825.74 MB
Category:CBTs


This course enables you to package a complete Spark Development environment into your own custom 2.3GB vagrant box.
Once built you no longer need to manipulate your Windows machine in order to get a fully fledged Spark environment to work. With the final solution, you can boot up a complete Apache Spark environment in under 3 minutes!!
Install any version of Spark you prefer. We have codified for 1.6.2 or 2.0.1. but it’s pretty easy to extend this for a new version. [Read more…]

Pluralsight – Applying the Lambda Architecture with Spark, Kafka, and Cassandra

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Pluralsight – Applying the Lambda Architecture with Spark, Kafka, and Cassandra
English | Size:843.90 MB
Category:Languages


This course aims to get beyond all the hype in the big data world and focus on what really works for building robust, highly-scalable batch and real-time systems. In this course, Applying the Lambda Architecture with Spark, Kafka, and Cassandra, you’ll string together different technologies that fit well and have been designed by some of the companies with the most demanding data requirements (such as Facebook, Twitter, and LinkedIn) to companies that are leading the way in the design of data processing frameworks, like Apache Spark, which plays an integral role throughout this course
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Udemy – Big Data Analytics with Apache Spark and Python [47 MP4]

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Udemy – Big Data Analytics with Apache Spark and Python [47 MP4]
English | Size: 1.90 GB (2,035,367,476 bytes )
Category: Tutorial


Learn to use Apache Spark to store and analyze data in real time.

“Apache Spark is the hottest Big Data technology today. Its adoption is growing fast and so is the demand for professionals trained in it”.

Apache Spark is the most active Apache project, and it is pushing back Map Reduce. It is fast, general purpose and supports multiple programming languages, data sources and management systems. More and more organizations are adapting Apache Spark to build big data solutions through batch, interactive and stream processing paradigms. The demand for trained professionals in Spark is going through the roof. Being a new technology, there aren’t enough training sources to provide easy guidance on building end-to-end solutions. [Read more…]

[Pluralsight.com] Apache Spark Fundamentals

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[Pluralsight.com] Apache Spark Fundamentals

English | Size: 596.61 MB (625,590,062 Bytes)
Category: CBTs


Our ever-connected world is creating data faster than Moore’s law can keep up, making it so that we have to be smarter in our decisions on how to analyze it. Previously, we had Hadoop’s MapReduce framework for batch processing, but modern big data processing demands have outgrown this framework. That’s where Apache Spark steps in, boasting speeds 10-100x faster than Hadoop and setting the world record in large scale sorting. Spark’s general abstraction means it can expand beyond simple batch processing, making it capable of such things as blazing-fast, iterative algorithms and exactly once streaming semantics. In this course, you’ll learn Spark from the ground up, starting with its history before creating a Wikipedia analysis application as one of the means for learning a wide scope of its core API. That core knowledge will make it easier to look into Spark’s other libraries, such as the streaming and SQL APIs. Finally, you’ll learn how to avoid a few commonly encountered rough edges of Spark. You will leave this course with a tool belt capable of creating your own performance-maximized Spark application. [Read more…]