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Udemy - Apache Beam - A Hands-On Course To Build Big Data Pipelines

TORRENT SUMMARY

	Status:	All the torrents in this section have been verified by our verification system
Category:	eBooks
Infohash	1b5236d9cb43072fdafb9ee4f9403d4709325074
Size:	1.7 GB in 1 file
Release Date(s):	Torrent Release: 26-02-2020 by user
Swarm:	0 Seeds & 1 Peers
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DESCRIPTION

[ FreeCourseWeb.com ] Apache Beam | A Hands-On course to build Big data Pipelines

Download More Latest Courses Visit -->> https://FreeCourseWeb.com

h264, yuv420p, 1280x720 |ENGLISH, Audio: aac, 44100 Hz, stereo | 5h 04 mn | 1.8 GB

Created by: J Garg - Hadoop Real Time Learning

Build Big data pipelines with Apache Beam in any language and run it via Spark, Flink, GCP (Google Cloud Dataflow).

What you'll learn

Learn Apache Beam with its Real-Time implementation.

Build Real-Time business's Big data processing pipelines using Apache Beam.

Learn a portable programming model whose pipelines can be deployed on Spark, Flink, GCP (Google Cloud Dataflow) etc.

Understand the working of each and every component of Apache Beam with HANDS-ON Practicals.

Develop pipelines for Real world Big data case studies in various business domains.

Data-sets and Beam codes used in lectures are available in resources tab. This will save your typing efforts.

Course will be updated upon each new Beam version update.

Requirements

Basic knowledge of Distributed data processing architecture.

Basic knowledge of Python would be helpful.

Description

Apache Beam is a unified and portable programming model for both Batch and Streaming use cases.

Earlier we could run Spark, Flink & Cloud Dataflow Jobs only on their respective clusters. But now Apache Beam has come up with a portable programming model where we can build language agnostic Big data pipelines and run it using any Big data engine (Apache Spark, Flink or in Google Cloud Platform using its Cloud Dataflow and many more Big data engines).

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Filename		Size
	[ FreeCourseWeb.com ] Udemy - Apache Beam - A Hands-On course to build Big data Pipelines.zip	1.7 GB

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