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

Using server-side export to pull data

A very common pattern used in databases is to perform a query that writes its results to another table. In KQL, this pattern is called Ingest from Query. There are four KQL control commands that support Ingest from Query in Data Explorer pools:

  • .set: This command can be used only if the destination table, that is, the table that will receive the data from a query result, doesn’t yet exist. If it does exist, the command fails.
  • .append: Produces the opposite of the .set command. If the destination table doesn’t yet exist, the command fails. If the table already exists, it appends the query results to the destination table.
  • .set-or-append: This command combines the .set and .append commands. If the destination table exists, data is appended to the table. If it doesn’t, the table is created and data is ingested.
  • .set-or-replace: Similar to .set-or-append except that if the destination table already exists, the...