Book Image

Learn Azure Synapse Data Explorer

By : Pericles (Peri) Rocha
Book Image

Learn Azure Synapse Data Explorer

By: Pericles (Peri) Rocha

Overview of this book

Large volumes of data are generated daily from applications, websites, IoT devices, and other free-text, semi-structured data sources. Azure Synapse Data Explorer helps you collect, store, and analyze such data, and work with other analytical engines, such as Apache Spark, to develop advanced data science projects and maximize the value you extract from data. This book offers a comprehensive view of Azure Synapse Data Explorer, exploring not only the core scenarios of Data Explorer but also how it integrates within Azure Synapse. From data ingestion to data visualization and advanced analytics, you’ll learn to take an end-to-end approach to maximize the value of unstructured data and drive powerful insights using data science capabilities. With real-world usage scenarios, you’ll discover how to identify key projects where Azure Synapse Data Explorer can help you achieve your business goals. Throughout the chapters, you'll also find out how to manage big data as part of a software as a service (SaaS) platform, as well as tune, secure, and serve data to end users. By the end of this book, you’ll have mastered the big data life cycle and you'll be able to implement advanced analytical scenarios from raw telemetry and log data.
Table of Contents (19 chapters)
1
Part 1 Introduction to Azure Synapse Data Explorer
6
Part 2 Working with Data
12
Part 3 Managing Azure Synapse Data Explorer

Monitoring Data Explorer pools

The Monitor hub offers resources to help monitor the status of Data Explorer pools, the execution of query requests, pipeline runs, and more. As we did with the Manage hub, let’s look at the sections of the Monitor hub in detail:

  • Analytics pools: This section lists your SQL pools, Apache Spark pools, and Data Explorer pools. Here, you can easily glance at details of your Data Explorer pools, such as their current status, size, instance count, the count of virtual CPUs they utilize, and the allocated cache and RAM sizes. By selecting a specific Data Explorer pool here, you can see up to a 30-day view of query results over time, as illustrated in Figure 3.17.
Figure 3.17 – A historical view of queries processed by Data Explorer

Figure 3.17 – A historical view of queries processed by Data Explorer

Besides recent queries, on this page, you can also see instance count over time and ingestion results over time, in the same fashion as recent queries. Analyzing resource consumption...