Determine the performance goals: Before you start, you need a clear understanding of what you want to achieve. In broad terms, when you want to improve a program’s efficiency, this generic checklist applies to most situations:ġ. To do so yourself, you can adopt any of a number of performance methodologies, some more suited than others, depending on the class of issues and analysis you want to make. Whatever application we’re trying to speed up, we use deterministic, concise, and methodical ways to monitor and analyze performance. These techniques involve collecting and analyzing data about the application’s behavior and its resource usage to identify bottlenecks, optimize resource utilization, and improve overall performance. Performance analysis and workload characterization are important techniques for understanding applications’ performance characteristics. Performance analysis and the geographic use case The takeaway: We can reach four times the throughput on GEOSEARCH queries, and that enhancement has already been released as part of Redis 7. In this post, we share those optimization techniques, such as reducing wasteful computation and simplifying algorithms, as well as the results of our analysis. The goals were to identify bottlenecks, optimize resource utilization, and improve overall performance. To maximize the Redis GEO commands’ execution performance, we delved into performance analysis and workload characterization techniques. To accomplish that, it’s important to optimize the queries and algorithms you use to interact with GEO data. And as with any database that is part of your critical business logic, you want the best possible performance – particularly when the systems accessing the data are moving around physically (that delivery truck) and thus need real-time responses. Ultimately, those longitudes and latitudes are just data for your applications to access and update. Then Redis can perform math and coordinate-based operations on that data, such as determining the distance between two points (How far away is the delivery car with my lunch order?) or finding all registered points within a given radius of another point (Where is the closest pet store to my current location?). Redis can store an object’s geographic coordinates, such as store locations or delivery trucks on the move. Redis’s GEO commands (formally geospatial indices) are a powerful tool for working with geographic data. Altogether, we improved Redis performance by up to four times the previous speed! Intel and Redis have made significant performance enhancements! Here we share the optimization techniques we used to evaluate and maximize Redis GEO command performance, such as reducing wasteful computation and simplifying algorithms.Īll the work has paid off.
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