Book Image

SQL Server 2016 Developer's Guide

By : Miloš Radivojević, Dejan Sarka, William Durkin
Book Image

SQL Server 2016 Developer's Guide

By: Miloš Radivojević, Dejan Sarka, William Durkin

Overview of this book

Microsoft SQL Server 2016 is considered the biggest leap in the data platform history of the Microsoft, in the ongoing era of Big Data and data science. This book introduces you to the new features of SQL Server 2016 that will open a completely new set of possibilities for you as a developer. It prepares you for the more advanced topics by starting with a quick introduction to SQL Server 2016's new features and a recapitulation of the possibilities you may have already explored with previous versions of SQL Server. The next part introduces you to small delights in the Transact-SQL language and then switches to a completely new technology inside SQL Server - JSON support. We also take a look at the Stretch database, security enhancements, and temporal tables. The last chapters concentrate on implementing advanced topics, including Query Store, column store indexes, and In-Memory OLTP. You will finally be introduced to R and learn how to use the R language with Transact-SQL for data exploration and analysis. By the end of this book, you will have the required information to design efficient, high-performance database applications without any hassle.
Table of Contents (21 chapters)
SQL Server 2016 Developer's Guide
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
12
In-Memory OLTP Improvements in SQL Server 2016

Manipulating data


Before you can extract some information from your data, you need to understand how the data is stored. First, you need to understand data structures in R.

Scalars and vectors are the most basic data structures. In R terminology, you analyze a dataset. A dataset consists of rows with cases or observations to analyze and columns representing the variables or attributes of the cases. This definition of a dataset looks like a SQL Server table. However, R does not work with tables in the relational sense. For example, in a relational, the order of rows and columns is not defined. In order to get a value, you need the column name and the key of the row. However, in R, you can use the position of a cell for most of the data structures. You have already seen this position reference for vectors.

In this section, you will learn about the data structures in R and the basic manipulation of datasets, including:

  • Arrays and matrices

  • Factors

  • Data frames

  • Lists

  • Creating new variables

  • Recoding variables...