Join Miriah Peterson and Bryan Boreham in a discussion on optimizing Go programs for performance. They cover profiling, design philosophy, resource requirements, mechanical sympathy, memory optimization, and the nuances of writing efficient Go code. Also, explore the drawbacks of using 'I rate' function in Prometheus query language and Apple's Pickle language release.
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Quick takeaways
Importance of profiling and optimizing code for Go programs.
Consideration of language choice for data engineering tasks based on performance and efficiency.
Deep dives
Optimizing Go performance: Tips from the experts
In this podcast episode, the hosts discuss the foundations of Go performance and provide guidance for optimizing Go programs. Key points include the importance of profiling, understanding Go's design principles, and focusing on efficient code. They also touch upon the impact of memory allocation, using pointers judiciously, and preallocating slices and maps. The hosts emphasize the need for benchmarking and continually iterating to improve performance. They advise on doing less work by optimizing regular expression and template usage, as well as avoiding unnecessary memory allocation. Finally, they advocate for writing elegant code while considering the results of profiling and benchmarking.
The pros and cons of using Python in data engineering
In this episode, a panelist expresses the controversial opinion that Python is not suitable for data engineering due to its slowness and bloated nature. They argue that Python is better suited for data analysis and scientific purposes. They suggest using other languages that offer better performance and do not wrap other languages for data engineering tasks. While acknowledging Python's prevalence in the field, they posit that languages like Go or Rust may be better choices for efficient and performant data engineering applications.
In the first of a multi-part series, Ian & Johnny are joined by Miriah Peterson & Bryan Boreham to peel back the first layer of the things that matter when it comes to the performance of your Go programs.
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