Book Image

Distributed Data Systems with Azure Databricks

By : Alan Bernardo Palacio
Book Image

Distributed Data Systems with Azure Databricks

By: Alan Bernardo Palacio

Overview of this book

Microsoft Azure Databricks helps you to harness the power of distributed computing and apply it to create robust data pipelines, along with training and deploying machine learning and deep learning models. Databricks' advanced features enable developers to process, transform, and explore data. Distributed Data Systems with Azure Databricks will help you to put your knowledge of Databricks to work to create big data pipelines. The book provides a hands-on approach to implementing Azure Databricks and its associated methodologies that will make you productive in no time. Complete with detailed explanations of essential concepts, practical examples, and self-assessment questions, you’ll begin with a quick introduction to Databricks core functionalities, before performing distributed model training and inference using TensorFlow and Spark MLlib. As you advance, you’ll explore MLflow Model Serving on Azure Databricks and implement distributed training pipelines using HorovodRunner in Databricks. Finally, you’ll discover how to transform, use, and obtain insights from massive amounts of data to train predictive models and create entire fully working data pipelines. By the end of this MS Azure book, you’ll have gained a solid understanding of how to work with Databricks to create and manage an entire big data pipeline.
Table of Contents (17 chapters)
1
Section 1: Introducing Databricks
4
Section 2: Data Pipelines with Databricks
9
Section 3: Machine and Deep Learning with Databricks

Using ADLS Gen2

To persist data in Azure Databricks, we need a data lake. We will use ADLS Gen2, so our first step is to set up an account. This will allow us to store permanent data and use it to run ETL pipelines, get analytics, or use it to build machine learning (ML) models.

Setting up a basic ADLS Gen2 data lake

To set up an ADLS Gen2 subscription, we first need to create a new resource in our Azure portal. To do this, follow these next steps:

  1. Search for Storage accounts and select Create a new Storage account.
  2. Attach it to a resource group, set up a name, set the Account kind field to StorageV2 (general-purpose v2) and, finally, set Replication to Locally-redundant storage (LRS), as illustrated in the following screenshot:

    Figure 3.1 – Creating an ADLS Gen2 subscription

  3. Before finalizing, in the Advanced tab, set the Hierarchical namespace option to Enabled so that we can use ADLS Gen2 from our notebooks. The following screenshot illustrates this...