作者：MattFuller
页数：288
出版社：东南大学出版社
出版日期：2021
ISBN：9787564195885
电子书格式：pdf/epub/txt
内容简介
高性能分布式SQL查询引擎Presto可用于对不同的数据源执行快速的交互式分析。这本实用指南将带你学习如何对Hive、Cassandra、关系数据库或专有数据存储中的数据进行分析。分析师、软件工程师、生产工程师可以从中学习Presto的管理、使用甚至开发。很初由Facebook开发的开源软件Presto如今已被Netflix、Airbnb、LinkedIn、Twitter、Uber和许多其他公司使用。Matt Fuller、Manfred Moser、Martin Traverso向你展示了单个Presto查询如何组合来自多个源头的数据，从而对整个组织进行分析。
作者简介
Matt Fuller是Presto公司Starburst的联合创始人。Matt Fuller是Presto公司Starburst的联合创始人。
目录
Foreword.
Preface.
Part I. Getting Started with Presto
1. Introducing Presto..
The Problems with Big Data
Presto to the Rescue
Designed for Performance and Scale
SQL-on-Anything
Separation of Data Storage and Query Compute Resources
Presto Use Cases
One SQL Analytics Access Point
Access Point to Data Warehouse and Source Systems
Provide SQL-Based Access to Anything
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 Artifi Intelligence
Other Use Cases
Presto Resources
Website
Documentation
Community Chat
Source Code, License, and Version
Contributing
Book Repository
Iris Data Set
Flight Data Set
A Brief History of Presto
Conclusion
2. Installing and Configuring Presto.
Trying Presto with the Docker Container
Installing from Archive File
Java Virtual Machine
Python
Installation
Configuration
Adding a Data Source
Running Presto
Conclusion
3. Using Presto
Presto Command-Line Interface
Getting Started
Pagination
History
Additional Diagnostics
Executing Queries
Output Formats
Ignoring Errors
Presto JDBC Driver
Downloading and Registering the Driver
Establishing a Connection to Presto
Presto and ODBC
Client Libraries
Presto Web UI
SQL with Presto
Concepts
First Examples
Conclusion
Part II. Diving Deeper into presto
Part III. Presto in Real-World Uses
Index
Preface.
Part I. Getting Started with Presto
1. Introducing Presto..
The Problems with Big Data
Presto to the Rescue
Designed for Performance and Scale
SQL-on-Anything
Separation of Data Storage and Query Compute Resources
Presto Use Cases
One SQL Analytics Access Point
Access Point to Data Warehouse and Source Systems
Provide SQL-Based Access to Anything
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 Artifi Intelligence
Other Use Cases
Presto Resources
Website
Documentation
Community Chat
Source Code, License, and Version
Contributing
Book Repository
Iris Data Set
Flight Data Set
A Brief History of Presto
Conclusion
2. Installing and Configuring Presto.
Trying Presto with the Docker Container
Installing from Archive File
Java Virtual Machine
Python
Installation
Configuration
Adding a Data Source
Running Presto
Conclusion
3. Using Presto
Presto Command-Line Interface
Getting Started
Pagination
History
Additional Diagnostics
Executing Queries
Output Formats
Ignoring Errors
Presto JDBC Driver
Downloading and Registering the Driver
Establishing a Connection to Presto
Presto and ODBC
Client Libraries
Presto Web UI
SQL with Presto
Concepts
First Examples
Conclusion
Part II. Diving Deeper into presto
Part III. Presto in Real-World Uses
Index
