xREL.v3

.:PROUDLY PRESENTS:.
Cloud Academy Running Spark on Azure Databricks
Release Date.: 06-09-2019
Type.: Bookware
Disks.: 41x15mb
Link.: https://cloudacademy.com

Release Notes

Apache Spark is an open-source framework for doing big data
processing. It was developed as a replacement for Apache
Hadoop's MapReduce framework. Both Spark and MapReduce
process data on compute clusters, but one of Spark's big
advantages is that it does in-memory processing, which can
be orders of magnitude faster than the disk-based
processing that MapReduce uses. Not only does Spark handle
data analytics tasks, but it also handles machine learning.
In 2013, the creators of Spark started a company called
Databricks. The name of their product is also Databricks.
It's a cloud-based implementation of Spark with a user-
friendly interface for running code on clusters interactively.
Microsoft has partnered with Databricks to bring their
product to the Azure platform. The result is a service
called Azure Databricks. One of the biggest advantages of
using the Azure version of Databricks is that it's
integrated with other Azure services. For example, you can
train a machine learning model on a Databricks cluster and
then deploy it using Azure Machine Learning Services.
In this course, we will start by showing you how to set up
a Databricks workspace and a cluster. Next, we'll go
through the basics of how to use a notebook to run
interactive queries on a dataset. Then you'll see how to
run a Spark job on a schedule. After that, we'll show you
how to train a machine learning model. Finally, we'll go
through several ways to deploy a trained model as a
prediction service.
Learning Objectives

Create a Databricks workspace, cluster, and notebook
Run code in a Databricks notebook either interactively or
as a job
Train a machine learning model using Databricks
Deploy a Databricks-trained machine learning model as a
prediction service

Intended Audience

People who want to use Azure Databricks to run Apache Spark
for either analytics or machine learning workloads

Prerequisites

Prior experience with Azure and at least one programming language

Additional Resources
The GitHub repository for this course is at
https://github.com/cloudacademy/azure-databricks.

Greetings fly out to:

Kodemusen, KoseBamsen

STM is back.
For all the ppl we worked with
in the past. We salute you.

NFO by NiMiTech
Updated: 09/09/2002