You're reading from Azure Data Engineering Cookbook Get well versed in various data engineering techniques in Azure using this recipe-based guide

Product type Paperback

Published in Sep 2022

Publisher Packt

ISBN-13 9781803246789

Length 608 pages

Edition 2nd Edition

Languages

SQL

Tools

Azure

Concepts

Data Engineering

Authors (3):

Ahmad Osama

Nagaraj Venkatesan

Luca Zanna

View More author details

Table of Contents (16) Chapters

Preface

1. Chapter 1: Creating and Managing Data in Azure Data Lake

2. Chapter 2: Securing and Monitoring Data in Azure Data Lake FREE CHAPTER

3. Chapter 3: Building Data Ingestion Pipelines Using Azure Data Factory

4. Chapter 4: Azure Data Factory Integration Runtime

5. Chapter 5: Configuring and Securing Azure SQL Database

6. Chapter 6: Implementing High Availability and Monitoring in Azure SQL Database

7. Chapter 7: Processing Data Using Azure Databricks

8. Chapter 8: Processing Data Using Azure Synapse Analytics

9. Chapter 9: Transforming Data Using Azure Synapse Dataflows

10. Chapter 10: Building the Serving Layer in Azure Synapse SQL Pool

11. Chapter 11: Monitoring Synapse SQL and Spark Pools

12. Chapter 12: Optimizing and Maintaining Synapse SQL and Spark Pools

13. Chapter 13: Monitoring and Maintaining Azure Data Engineering Pipelines

14. Index

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Creating statistics and automating the update of statistics

Statistics play a key role in maintaining the optimal performance of the queries in a Synapse dedicated SQL pool. For each query submitted, the query optimizer prepares a query plan that comprises several operations (such as filtering, joining, sorting, and more). Statistics inform the optimizer how many rows are expected to be returned for each of those operations, and based on the statistics input, the optimizer prepares query plans. So, for the query plans to be effective and performance to be optimal, we need good statistics.

In this recipe, we will learn how to create statistics and update statistics.

Getting ready

Create a Synapse Analytics workspace as explained in the Provisioning an Azure Synapse Analytics workspace recipe of Chapter 8, Processing Data Using Azure Synapse Analytics.

Complete the Loading data into dedicated SQL pools using PolyBase using T-SQL recipe to create a dedicated SQL pool named...