Running Spark on Azure Databricks Cloud Academy

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Running Spark on Azure Databricks | Cloud Academy
English | Size: 575.35 MB
Genre: eLearning

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

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