Hive 4 with Amazon S3: Building Scalable Data Lakes with Apache Hive 4 and Compatible Amazon S3 Storage by Alfonso Antolinez Garcia
English | November 11, 2024 | ISBN: N/A | ASIN: B0DMTLSWN9 | 70 pages | EPUB | 11 Mb
English | November 11, 2024 | ISBN: N/A | ASIN: B0DMTLSWN9 | 70 pages | EPUB | 11 Mb
Apache Hive is an enterprise-grade data warehousing solution designed for querying, managing, and analysing data stored in the Hadoop Distributed File System (HDFS).
Hive provides a Hive Query Language (HiveQL) that allows users to execute queries through the Hive CLI shell or other Hive client, while Beeline provides a JDBC client for connecting to Hive from various environments. HiveQL acts as a bridge between Hadoop and relational database management systems, enabling Hadoop to perform tasks using SQL-like commands.
This book serves as a comprehensive guide to building scalable data lakes using Apache Hive 4 with Amazon S3-compatible Object Storage. It provides clear, step-by-step instructions on setting up Hive 4 and configuring it to connect seamlessly with any S3-compatible storage provider, enabling users to create cost-effective, highly available data lakes for handling large datasets. The book begins with detailed guidance on installing Hive 4, followed by configuration techniques to integrate Hive with S3-compatible storage solutions. Readers are walked through creating external tables in Hive using data stored in S3 buckets, empowering them to leverage existing storage for efficient data processing. Finally, readers will learn how to query these external tables to derive insights, enabling robust data analysis capabilities for big data environments.