The Presto community has mushroomed since its origins at Facebook in 2012. But ramping up this distributed SQL query engine can be challenging even for the most experienced engineers. This practical book shows you how to begin Presto operations at your organization to derive insights on datasets wherever they reside. Authors Angelica Lo Duca, Vivek Bharathan, and George Wang explain what Presto is, where it came from, and how it differs from other data warehousing solutions. You'll discover why Facebook, Uber, Twitter, and cloud providers, including AWS, Google Cloud, and Alibaba, use Presto and how you can quickly deploy Presto in production. You'll learn about: Presto security and administration Syntax and connectors Clusters and tuning Troubleshooting: logs, error messages, and more Extending Presto for real-time business insight Extending PrestoDB

Gain the key knowledge and skills required to manage data science projects using Comet Key Features Discover techniques to build, monitor, and optimize your data science projects Move from prototyping to production using Comet and DevOps tools Get to grips with the Comet experimentation platform Book DescriptionThis book provides concepts and practical use cases which can be used to quickly build, monitor, and optimize data science projects. Using Comet, you will learn how to manage almost every step of the data science process from data collection through to creating, deploying, and monitoring a machine learning model. The book starts by explaining the features of Comet, along with exploratory data analysis and model evaluation in Comet. You'll see how Comet gives you the freedom to choose from a selection of programming languages, depending on which is best suited to your needs. Next, you will focus on workspaces, projects, experiments, and models. You will also learn how to build a narrative from your data, using the features provided by Comet. Later, you will review the basic concepts behind DevOps and how to extend the GitLab DevOps platform with Comet, further enhancing your ability to deploy your data science projects. Finally, you will cover various use cases of Comet in machine learning, NLP, deep learning, and time series analysis, gaining hands-on experience with some of the most interesting and valuable data science techniques available. By the end of this book, you will be able to confidently build data science pipelines according to bespoke specifications and manage them through Comet. What you will learn Prepare for your project with the right data Understand the purposes of different machine learning algorithms Get up and running with Comet to manage and monitor your pipelines Understand how Comet works and how to get the most out of it See how you can use Comet for machine learning Discover how to integrate Comet with GitLab Work with Comet for NLP, deep learning, and time series analysis Who this book is forThis book is for anyone who has programming experience, and wants to learn how to manage and optimize a complete data science lifecycle using Comet and other DevOps platforms. Although an understanding of basic data science concepts and programming concepts is needed, no prior knowledge of Comet and DevOps is required.