Book Image

SQL Server 2017 Integration Services Cookbook

By : Christian Cote, Dejan Sarka, David Peter Hansen, Matija Lah, Samuel Lester, Christo Olivier
Book Image

SQL Server 2017 Integration Services Cookbook

By: Christian Cote, Dejan Sarka, David Peter Hansen, Matija Lah, Samuel Lester, Christo Olivier

Overview of this book

SQL Server Integration Services is a tool that facilitates data extraction, consolidation, and loading options (ETL), SQL Server coding enhancements, data warehousing, and customizations. With the help of the recipes in this book, you’ll gain complete hands-on experience of SSIS 2017 as well as the 2016 new features, design and development improvements including SCD, Tuning, and Customizations. At the start, you’ll learn to install and set up SSIS as well other SQL Server resources to make optimal use of this Business Intelligence tools. We’ll begin by taking you through the new features in SSIS 2016/2017 and implementing the necessary features to get a modern scalable ETL solution that fits the modern data warehouse. Through the course of chapters, you will learn how to design and build SSIS data warehouses packages using SQL Server Data Tools. Additionally, you’ll learn to develop SSIS packages designed to maintain a data warehouse using the Data Flow and other control flow tasks. You’ll also be demonstrated many recipes on cleansing data and how to get the end result after applying different transformations. Some real-world scenarios that you might face are also covered and how to handle various issues that you might face when designing your packages. At the end of this book, you’ll get to know all the key concepts to perform data integration and transformation. You’ll have explored on-premises Big Data integration processes to create a classic data warehouse, and will know how to extend the toolbox with custom tasks and transforms.
Table of Contents (18 chapters)
Title Page
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Installing JRE for PolyBase


Java Runtime Engine (JRE) is required for PolyBase installations. SQL Server PolyBase is the technology that allows data integration from other sources other than SQL Server tables. PolyBase is used to access data stored in Hadoop File System (HFS) or Windows Azure Storage Blob (WASB).

As you will see later in this book, SSIS can now interact with these types of storage natively but having PolyBase handy can save us valuable time in our ETL.

Getting ready

For this recipe you will need to have access to the internet and have administrative rights on your PC to install JRE.

How to do it...

  1. To download JRE, follow this link: http://www.oracle.com/technetwork/java/javase/downloads/index.html . You will see the screen shown in the following screenshot:

This directs you to the Java SE Download at Oracle.

  1. Click the download link in the JRE section as shown in the following screenshot:

  1. You must accept the license agreement to be able to select a file to download. Select Accept License Agreement as indicated in the following screenshot:

  1. Since SQL Server 2016 only exists in a 64-bit version, download the 64-bit JRE. The version of Java SE runtime environment might be different from the one show in the screenshot, which is the one available at the time this book was written:.

  1. Once downloaded, launch the installer. Click on Run as shown in Edge browser. Otherwise, go to your Downloads folder and double-click on the file you just downloaded (jre-8U102-windows-x64.exe in our case); you will see the following window:

  1. The Oracle JRE installation starts. Click on Install. The following screen appears. It indicates the progress of the JRE installation.

  1. Once the installation is completed, click on Close to quit the installer:

You are now ready to proceed to install SQL Server 2016. We'll do that in the next section.

How it works...

Microsoft integrated PolyBase in SQL Server 2016 to connect almost natively to the Hadoop and NoSQL platforms. Here are the technologies it allows us to connect to:

  • HDFS (Hortonworks and Cloudera)
  • Azure Blob Storage

Since Hadoop is using Java technology, JRE is used to interact with its functionalities.