Book Image

SQL for Data Analytics - Third Edition

By : Jun Shan, Matt Goldwasser, Upom Malik, Benjamin Johnston
Book Image

SQL for Data Analytics - Third Edition

By: Jun Shan, Matt Goldwasser, Upom Malik, Benjamin Johnston

Overview of this book

Every day, businesses operate around the clock, and a huge amount of data is generated at a rapid pace. This book helps you analyze this data and identify key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level. SQL for Data Analytics, Third Edition is a great way to get started with data analysis, showing how to effectively sort and process information from raw data, even without any prior experience. You will begin by learning how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you will learn how to write SQL queries to aggregate, calculate, and combine SQL data from sources outside of your current dataset. You will also discover how to work with advanced data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you will be able to understand your business at a deeper level. Finally, the book lets you in on the secret to getting information faster and more effectively by using advanced techniques like profiling and automation. By the end of this book, you will be proficient in the efficient application of SQL techniques in everyday business scenarios and looking at data with the critical eye of analytics professional.
Table of Contents (11 chapters)
9. Using SQL to Uncover the Truth: A Case Study

Killing Queries

Sometimes, you have a lot of data or perhaps insufficient hardware resources, and a query just runs for a very long time. In such a situation, you may need to stop the query—perhaps so you can implement an alternative query to get the information you need, but without the delayed response. In this section, you are going to investigate how you can stop hanging or, at least, extremely long-running queries using a secondary PostgreSQL interpreter. The following are some of the commands that you will use to kill queries:

  • pg_sleep is a command that allows you to tell the SQL interpreter to essentially do nothing for a specified period as defined by the input to the function in seconds.
  • The pg_cancel_backend command causes the interpreter to end the query specified by the process ID (PID). The process will be terminated cleanly, allowing for appropriate resource cleanup. Clean termination should also be the first preference as it reduces the possibility...