Apache Spark 2.0 con Scala - Manos con datos grandes!

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Apache Spark 2.0 con Scala – Manos con datos grandes!. ¡Sumérgete en más de 20 ejemplos prácticos de análisis de grandes conjuntos de datos con Apache Spark, en tu escritorio o en Hadoop!

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No te pierdas este fabuloso curso online llamado Apache Spark 2.0 con Scala – Manos con datos grandes!. Es 100% online y comenzarás justo en el momento de matricularte. Tú serás el que marques tu propio ritmo de aprendizaje.

Breve descripción del curso llamado Apache Spark 2.0 con Scala – Manos con datos grandes!

¡Sumérgete en más de 20 ejemplos prácticos de análisis de grandes conjuntos de datos con Apache Spark, en tu escritorio o en Hadoop!

El profesor de este fabuloso curso 100% online es Frank Kane, un auténtico experto en la materia, y con el que aprenderás todo lo necesario para ser más competitivo. El curso se ofrece en Inglés con subtítulos.

Descripción completa del curso llamado Apache Spark 2.0 con Scala – Manos con datos grandes!

Course Description New! Updated for Spark 2.0.0. “Big data” analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark. Employers including Amazon, EBay, NASA JPL, and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You’ll learn those same techniques, using your own Windows system right at home. It’s easier than you might think, and you’ll be learning from an ex-engineer and senior manager from Amazon and IMDb. Spark works best when using the Scala programming language, and this course includes a crash-course in Scala to get you up to speed quickly. For those more familiar with Python however, a Python version of this class is also available: “Taming Big Data with Apache Spark and Python – Hands On”. Learn and master the art of framing data analysis problems as Spark problems through over 20 hands-on examples, and then scale them up to run on cloud computing services in this course. Learn the concepts of Spark’s Resilient Distributed DatastoresGet a crash course in the Scala programming languageDevelop and run Spark jobs quickly using ScalaTranslate complex analysis problems into iterative or multi-stage Spark scriptsScale up to larger data sets using Amazon’s Elastic MapReduce serviceUnderstand how Hadoop YARN distributes Spark across computing clustersPractice using other Spark technologies, like Spark SQL, DataFrames, DataSets, Spark Streaming, and GraphX By the end of this course, you’ll be running code that analyzes gigabytes worth of information – in the cloud – in a matter of minutes. We’ll have some fun along the way. You’ll get warmed up with some simple examples of using Spark to analyze movie ratings data and text in a book. Once you’ve got the basics under your belt, we’ll move to some more complex and interesting tasks. We’ll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We’ll analyze a social graph of superheroes, and learn who the most “popular” superhero is – and develop a system to find “degrees of separation” between superheroes. Are all Marvel superheroes within a few degrees of being connected to SpiderMan? You’ll find the answer. This course is very hands-on; you’ll spend most of your time following along with the instructor as we write, analyze, and run real code together – both on your own system, and in the cloud using Amazon’s Elastic MapReduce service. 7.5 hours of video content is included, with over 20 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX. Enjoy the course!