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Book Overview & Buying
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Table Of Contents
Practical Systems Programming in Go
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In this chapter, we explored the core ideas of time series data mining, focusing on how to uncover hidden patterns and relationships in data. We saw that finding these insights depends on choosing the right way to measure similarity, whether using simple distance checks or more flexible, elastic methods. But even the best math needs a solid program to run it. That is why we dove into the practical side of Go, examining how the Green Tea garbage collector manages memory and how to track goroutine metrics to keep performance high. We also learned how to use goroutine leak profiles to catch invisible bugs that can slow down your system. At the end of the day, building effective data mining tools requires balancing these two skills: understanding the data algorithms and mastering the Go runtime that powers them.
In the next chapter, we will shift our focus from the data inside the file to the metadata that describes it. We will build a high-performance indexing engine in Go that crawls...