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How do you find the location of someone visiting your site? And, how do you do it fast? If you've ever been curious about how analytics services can place your site visitors on a map, or about how to analyze and improve a slow running query, then this talk is for you! In this session, you'll learn about IP address networking, fundamental database operations, and query performance tuning. We'll develop a geolocation system from the ground up, and make sure it's running lightning fast along the way.
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In the session titled "Geolocation EXPLAINed," Kevin Lesht discusses how to determine the location of visitors to a website quickly and efficiently. This presentation stems from his experiences at Home Chef, where he encountered challenges in conditionally displaying meal offerings based on customers' geographical locations. The goal was to provide site visitors with relevant meal options depending on which facility their orders were being shipped from, all while ensuring quick response times. Key Points Discussed: - **Problem Overview**: Lesht outlines the major challenge of identifying logged-out visitors' locations without having access to their delivery address, which they can only obtain from logged-in customers. - **Initial Solutions Explored**: Several approaches were considered, including using third-party APIs and leveraging Cloudflare's geolocation services. However, these options were dismissed due to performance limitations. - **Finding a Viable Solution**: The talk introduces MaxMind, a service that provides geolocation data linked to IP addresses. Lesht explains how they set up their own geolocation system from scratch using this data. - **Understanding IP Addressing**: He delves into networking concepts, including CIDR notation, to explain how to manage and interpret IP address ranges effectively. - **Performance Tuning**: A portion of the session focuses on database optimizations. Lesht utilizes PostgreSQL's query analysis tools to investigate the slow performance of geolocation requests, identifying three key operations: sequential scans, nested loop joins, and index scans. - **Optimization Techniques**: Lesht partly demonstrates how to enhance query performance by using indexing strategies to significantly reduce response times. He showcases that an initial geolocation request that took approximately 200 milliseconds could be optimized down to around 1.67 milliseconds by correctly implementing an index scan. - **Final Results**: The improvements made not only expedited the geolocation requests dramatically but also showcased his team's capability to enhance the system's efficiency. In conclusion, the presentation not only provides technical insights into geolocation implementation via IP address management but also illustrates how database optimizations, especially indexing, can lead to substantial performance improvements. Lesht emphasizes the importance of these techniques in enhancing user experience and meeting business needs in real-time data processing.
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