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When milliseconds matter: Maximizing query performance in CrateDB

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When milliseconds matter: Maximizing query performance in CrateDB
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When ms matter: Maximizing query performance in CrateDB
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60
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CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Release Date2023
LanguageEnglish

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Abstract
Distributed databases provide easy scaling, high performance, and availability crucial to handle large amounts of data. However, achieving optimal execution plans in these systems is often a challenge and requires special considerations. In this talk, we will explore the key concepts and best practices for optimizing query performance in the CrateDB database. CrateDB is a highly scalable and distributed SQL database that offers a unique blend of SQL and NoSQL capabilities. Although the focus of the talk is going to be on CrateDB, most of the techniques we are going to discuss apply to many distributed databases. As a first step, we will go through query planning to better understand potential bottlenecks. Then, we will discuss the practical implications of indexing, sharding, and partitioning strategies, and provide practical advice on how to further optimize CrateDB queries for optimal performance. All these topics will be covered by real-world examples and practical solutions to some of the most common issues. At the end of the talk, you will be equipped with practical tips and techniques for detecting performance issues and optimizing your queries. Key learnings: - Intro to CrateDB and query plans - How different sharding, partitioning, and indexing strategies affect query performance - Real-life examples and tips for debugging slow queries