| Description |
1 online resource (1 streaming video file (3 hr., 30 min., 14 sec.)) |
| Performer |
Presenter, Nimish Narang. |
| Note |
Title from resource description page (Safari, viewed March 15, 2019). |
| Summary |
"Processing big data in real time is challenging due to scalability, information consistency, and fault-tolerance. Big Data Processing with Apache Spark teaches you how to use Spark to make your overall analytical workflow faster and more efficient. You'll explore all core concepts and tools within the Spark ecosystem, such as Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming. You'll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs), SQL, Datasets, and Dataframes APIs. After grasping these fundamentals, you'll move on to using Spark Streaming APIs to consume data in real time from TCP sockets, and integrate Amazon Web Services (AWS) for stream consumption. By the end of this course, you'll not only have understood how to use machine learning extensions and structured streams but you'll also be able to apply Spark in your own upcoming big data projects."--Resource description page |
| Subject |
Spark (Electronic resource : Apache Software Foundation)
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Spark (Electronic resource : Apache Software Foundation) |
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Big data.
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Python (Computer program language)
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Application program interfaces (Computer software)
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Cloud computing.
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Electronic data processing.
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Données volumineuses. |
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Python (Langage de programmation) |
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Interfaces de programmation d'applications. |
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Infonuagique. |
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APIs (interfaces) |
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Application program interfaces (Computer software) |
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Big data. |
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Cloud computing. |
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Electronic data processing. |
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Python (Computer program language) |
| Genre |
Electronic videos. |
| Note |
Sub-title on title screen: Efficiently tackle large datasets and perform big data analysis with Spark and Python |
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