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. : ________| / | _______ ____\_____ | _.______
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19
PROUDLY PRESENTING:
Conceptualizing.the.Processing.Model.for.Azure.Databricks.Service
INFORMATION:
Date............: 2020-07-22
Rars............: 18 Rar Files
Course Length...: 2 hrs 51 mins
Website.........: https://tinyurl.com/yywm6nsx
Release Notes...:
Modern data pipelines often include streaming data, that needs to be processed
in real-time. While Apache Spark is very popular for big data processing and
can help us build reliable streaming pipelines, managing the Spark environment
is no cakewalk. In this course, Conceptualizing the Processing Model for Azure
Databricks Service, you will learn how to use Spark Structured Streaming on
Databricks platform, which is running on Microsoft Azure, and leverage its
features to build an end-to-end streaming pipeline quickly and reliably. And
all this while learning about collaboration options and optimizations that it
brings, but without worrying about the infrastructure management. First, you
will learn about the processing model of Spark Structured Streaming, about the
Databricks platform and features, and how it is runs on Microsoft Azure. Next,
you will see how to setup the environment, like workspace, clusters, and security;
configure streaming sources and sinks, and see how Structured Streaming fault
tolerance works. Followed by this, you will learn how to build each phase of
streaming pipeline, by extracting the data from source, transforming it, and
loading it in a sink. And then make it production ready, and run it using
Databricks jobs. You will also see, how to customize the cluster using
Initialization scripts and Docker containers, to suit your business requirements.
Finally, you will explore other aspects. You will see what are the different
workloads available, and how pricing works. We will also talk about best practices,
in terms of development, performance, stability and cost. And lastly, you will see
how Spark Structured Streaming on Azure Databricks compares to other managed
services, like Flink on AWS, Azure Stream Analytics, Beam on Google Cloud etc.
By the end of this course, you will have the skills and knowledge of Azure
Databricks platform needed to build an end-to-end streaming pipeline, using
Spark Structured streaming.
Install Notes...:
Unrar, Learn and Enjoy!
GREETINGS:
- KNOWN - HONOR - SKIDROW - DARKSiDERS - DAUDiO - JAVSiDERS - dbOOk - z0ne -