Trino the definitive guide : SQL at any scale, on any storage, in any environment

Perform fast interactive analytics against different data sources using the Trino high-performance distributed SQL query engine. In the second edition of this practical guide, you'll learn how to conduct analytics on data where it lives, whether it's a data lake using Hive, a modern lakeho...

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Bibliographic Details
Main Author: Fuller, Matt
Other Authors: Moser, Manfred, Traverso, Martin
Format: eBook
Language:English
Published: Sebastopol, California O'Reilly Media, Inc. 2022
Edition:2nd edition
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
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505 0 |a Java Virtual Machine -- Python -- Installation -- Configuration -- Adding a Data Source -- Running Trino -- Conclusion -- Chapter 3. Using Trino -- Trino Command-Line Interface -- Getting Started -- Pagination -- History and Completion -- Additional Diagnostics -- Executing Queries -- Output Formats -- Ignoring Errors -- Trino JDBC Driver -- Downloading and Registering the Driver -- Establishing a Connection to Trino -- Trino and ODBC -- Client Libraries -- Trino Web UI -- SQL with Trino -- Concepts -- First Examples -- Conclusion -- Part II. Diving Deeper into Trino 
505 0 |a Cover -- Copyright -- Table of Contents -- Foreword -- Preface -- Conventions Used in This Book -- Code Examples, Permissions, and Attribution -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Part I. Getting Started with Trino -- Chapter 1. Introducing Trino -- The Problems with Big Data -- Trino to the Rescue -- Designed for Performance and Scale -- SQL-on-Anything -- Separation of Data Storage and Query Compute Resources -- Trino Use Cases -- One SQL Analytics Access Point -- Access Point to Data Warehouse and Source Systems -- Provide SQL-Based Access to Anything 
505 0 |a Chapter 4. Trino Architecture -- Coordinator and Workers in a Cluster -- Coordinator -- Discovery Service -- Workers -- Connector-Based Architecture -- Catalogs, Schemas, and Tables -- Query Execution Model -- Query Planning -- Parsing and Analysis -- Initial Query Planning -- Optimization Rules -- Predicate Pushdown -- Cross Join Elimination -- TopN -- Partial Aggregations -- Implementation Rules -- Lateral Join Decorrelation -- Semi-Join (IN) Decorrelation -- Cost-Based Optimizer -- The Cost Concept -- Cost of the Join -- Table Statistics -- Filter Statistics 
505 0 |a Federated Queries -- Semantic Layer for a Virtual Data Warehouse -- Data Lake Query Engine -- SQL Conversions and ETL -- Better Insights Due to Faster Response Times -- Big Data, Machine Learning, and Artificial Intelligence -- Other Use Cases -- Trino Resources -- Website -- Documentation -- Community Chat -- Source Code, License, and Version -- Contributing -- Book Repository -- Iris Data Set -- Flight Data Set -- A Brief History of Trino -- Conclusion -- Chapter 2. Installing and Configuring Trino -- Trying Trino with the Docker Container -- Installing from the Archive File 
505 0 |a Table Statistics for Partitioned Tables -- Join Enumeration -- Broadcast Versus Distributed Joins -- Working with Table Statistics -- Trino ANALYZE -- Gathering Statistics When Writing to Disk -- Hive ANALYZE -- Displaying Table Statistics -- Conclusion -- Chapter 5. Production-Ready Deployment -- Configuration Details -- Server Configuration -- Logging -- Node Configuration -- JVM Configuration -- Launcher -- Cluster Installation -- RPM Installation -- Installation Directory Structure -- Configuration -- Uninstall Trino -- Installation in the Cloud -- Helm Chart for Kubernetes Deployment 
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520 |a Perform fast interactive analytics against different data sources using the Trino high-performance distributed SQL query engine. In the second edition of this practical guide, you'll learn how to conduct analytics on data where it lives, whether it's a data lake using Hive, a modern lakehouse with Iceberg or Delta Lake, a different system like Cassandra, Kafka, or SingleStore, or a relational database like PostgreSQL or Oracle. Analysts, software engineers, and production engineers learn how to manage, use, and even develop with Trino and make it a critical part of their data platform. Authors Matt Fuller, Manfred Moser, and Martin Traverso show you how a single Trino query can combine data from multiple sources to allow for analytics across your entire organization. Explore Trino's use cases, and learn about tools that help you connect to Trino for querying and processing huge amounts of data Learn Trino's internal workings, including how to connect to and query data sources with support for SQL statements, operators, functions, and more Deploy and secure Trino at scale, monitor workloads, tune queries, and connect more applications Learn how other organizations apply Trino successfully