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CODEMENTOR . IO {}

  1. Analyzed Page
  2. Matching Content Categories
  3. CMS
  4. Monthly Traffic Estimate
  5. How Does Codementor.io Make Money
  6. Keywords
  7. Topics
  8. Questions
  9. Schema
  10. External Links
  11. Libraries
  12. Hosting Providers
  13. CDN Services

We are analyzing https://www.codementor.io/@evalparse/an-empirical-study-of-group-by-strategies-in-julia-dagnosell.

Title:
An empirical study of group-by strategies in Julia | Codementor
Description:
Julia can be faster than data.table in some group-by operations! This post details a number of strategies employed to try and optimize Julia group-by performance.
Website Age:
12 years and 2 months (reg. 2013-04-09).

Matching Content Categories {๐Ÿ“š}

  • Technology & Computing
  • Education
  • Science

Content Management System {๐Ÿ“}

What CMS is codementor.io built with?

Custom-built

No common CMS systems were detected on Codementor.io, but we identified it was custom coded using Next.js (JavaScript).

Traffic Estimate {๐Ÿ“ˆ}

What is the average monthly size of codementor.io audience?

๐ŸŒŸ Strong Traffic: 100k - 200k visitors per month


Based on our best estimate, this website will receive around 100,019 visitors per month in the current month.
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How Does Codementor.io Make Money? {๐Ÿ’ธ}

We can't tell how the site generates income.

Not every website is profit-driven; some are created to spread information or serve as an online presence. Websites can be made for many reasons. This could be one of them. Codementor.io could have a money-making trick up its sleeve, but it's undetectable for now.

Keywords {๐Ÿ”}

data, julia, datatable, array, groupby, radixsort, algorithm, faster, years, time, code, sumby, performance, algorithms, seconds, sort, method, ago, string, source, function, vector, end, group, show, gpl, type, found, inbounds, performant, sorted, hash, machine, columns, timings, groups, case, dict, elements, sum, res, julias, closed, radixgroup, types, multithreaded, work, number, implemented, benchmark,

Topics {โœ’๏ธ}

reverse-engineering closed-source software mit/bsd-licensed code based multi-threaded radixsort method multi-column group-bys chris' comment pointed tables pre-indexed group machine learning developer multi-threaded code multi-threaded version team lead level radixsort-based methods data manipulation platform closed source software mutually-exclusive subarrays real life settings laptop/desktop computers enable simd instructions high-level understanding high-level explanation data related projects data jointly accessible initial investigation r' /xiaodaigh/fbdbbfd32062e33a20b1895af24e1542 focus arbitrary zipped types novice julia coder wholeheartedly recommend julia requires prior knowledge newly created array array achieving parallelism effectively โ€œclosed sourceโ€ efficient data structure point worth mentioning require prior knowledge large input size biggest performance gap statsbase import statsbase richer data ecosystem machine learning generic groupby function sorting implies grouping radix sort method actively store metadata counting sort works lightning fast performance default sorting algorithm passing cache=true pooledarrays import pooledarrays categoricalarray/pooledarray columns data scientist achieve peak performance

Questions {โ“}

  • But its code is GPL, right?
  • Enjoy this post?
  • Is inlining the iterator via the @iter macro still required to get the full efficiency out?
  • So your conclusion is that itโ€™s faster to first sort the data using radix sort, and only compute the group sums in a second step, rather than accumulating the sums on the fly?
  • Table eventually for performance?

Schema {๐Ÿ—บ๏ธ}

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Libraries {๐Ÿ“š}

  • FontAwesome
  • Moment.js
  • Normalize.css
  • Popper.js
  • Three.js

Emails and Hosting {โœ‰๏ธ}

Mail Servers:

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Name Servers:

  • ns1.dnsimple.com
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CDN Services {๐Ÿ“ฆ}

  • Cloudflare
  • Codementor
  • Filestackcontent

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