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

Performing robust exports with server-side data push

Server-side exports with the push model are the most scalable and flexible way to export data from Data Explorer pools. They allow you to export data to a cloud storage container (such as ADLS Gen2 or Amazon S3), to a SQL table, or to a Data Explorer external table. The mechanism that allows the push method is exposed through the .export commands that perform a query on a Data Explorer pool table and writes the query results to the destination store.

Data exports with server-side data push have the following advantages:

  • Support for async exports: You can run your export task and continue doing your work while the task runs in the background. The .show operations command can be used to track the progress of all data export tasks. The .show operation details command retrieves completion results specific to a task in particular.
  • Allows scalable writes: When writing to cloud storage, you can specify multiple connection...