4 ms·

Buying RAM as a substitute for algorithms is for people who don't work for Google (disclaimer: I work for Google).

by cletus 16y ago

mmaunder 16y ago
Didn't you guys just pass 20,000 employees?
- staunch 16y ago
  Little known fact: Google's secret algorithm is not PigeonRank[1] but PeopleRank. Those 20,000 people are constantly counting <a> tags across the web. 1. http://www.google.com/technology/pigeonrank.html http://www.google.com/technology/pigeonrank.html
younata 16y ago
Wait, so instead of spending a semester learning about algorithms and stuff, I can go throw money at the problem? Why am I in school?
- jbrennan 16y ago
  Technically you are throwing money at the problem (or someone is, for you).
  - Keyframe 16y ago
    So, does buying hardware have better ROI than college?
    - wlievens 16y ago
      Sometimes yes, sometimes no, but you need a trained brain to spot the difference.
      - rbanffy 16y ago
        It goes like this: - turn the screw: US$ 5 - knowing which screw to turn: US$ 5000
- wladimir 16y ago
  Indeed. Why are we doing anything if just throwing money will solve all our problems. Let's just sit back, relax, and throw money at stuff... Algorithms are a poor substitute for us poor engineers that don't have money to throw :)
- iwwr 16y ago
  The difference between O(n) and O(n^2) is huge, but once optimizations get you fractions of constants, it may be worth looking at more memory.
fierarul 16y ago
Few people work for Google or tackle problems that size. Buying more RAM is most of the time a quick and economical solution.
deleted 16y ago
[deleted]
demallien 16y ago
Or people that develop for smartphones. Or people that develop on embedded systems/consumer electronics. Or people that work with raw bitmaps (eg games writers). You need to get out more if you think (as your comment would seem to suggest) that only Google has efficiency problems...
csomar 16y ago
If you have only one server, then you are going to add $xx; instead of spending $xxxx fixing it. Google has to add $xx * the number of its' servers vs. $xxxx fixing it by one or two developers.
alexgartrell 16y ago
You may not have intended it, but your comment reads as "Google has awesome hard problems that only badasses can work on" "Also, I work there". Not ever mention of one's workplace warrants a disclaimer. :) But you do bring up an interesting point, how does Google handle the heterogeneous server problem? One assumes that not all nodes are created equal (if only because it would be cost prohibitive to upgrade all at once), so do you just use dynamic task scheduling and hope for the best or is there something cooler going on there?
dan_manges 16y ago
I think that's more of a disclosure than a disclaimer.

Buying RAM as a substitute for algorithms is for people who don't work for Google (disclaimer: I work for Google).

by cletus 16y ago

Buying RAM as a substitute for algorithms is for people who don't work for Google (disclaimer: I work for Google).

mmaunder 16y ago

Didn't you guys just pass 20,000 employees?

staunch 16y ago
Little known fact: Google's secret algorithm is not PigeonRank[1] but PeopleRank. Those 20,000 people are constantly counting <a> tags across the web. 1. http://www.google.com/technology/pigeonrank.html http://www.google.com/technology/pigeonrank.html

younata 16y ago

Wait, so instead of spending a semester learning about algorithms and stuff, I can go throw money at the problem? Why am I in school?

jbrennan 16y ago
Technically you are throwing money at the problem (or someone is, for you).
- Keyframe 16y ago
  So, does buying hardware have better ROI than college?
  - wlievens 16y ago
    Sometimes yes, sometimes no, but you need a trained brain to spot the difference.
    - rbanffy 16y ago
      It goes like this: - turn the screw: US$ 5 - knowing which screw to turn: US$ 5000
wladimir 16y ago
Indeed. Why are we doing anything if just throwing money will solve all our problems. Let's just sit back, relax, and throw money at stuff... Algorithms are a poor substitute for us poor engineers that don't have money to throw :)
iwwr 16y ago
The difference between O(n) and O(n^2) is huge, but once optimizations get you fractions of constants, it may be worth looking at more memory.

fierarul 16y ago

Few people work for Google or tackle problems that size. Buying more RAM is most of the time a quick and economical solution.

deleted 16y ago

[deleted]

demallien 16y ago

Or people that develop for smartphones. Or people that develop on embedded systems/consumer electronics. Or people that work with raw bitmaps (eg games writers). You need to get out more if you think (as your comment would seem to suggest) that only Google has efficiency problems...

csomar 16y ago

If you have only one server, then you are going to add $xx; instead of spending $xxxx fixing it. Google has to add $xx * the number of its' servers vs. $xxxx fixing it by one or two developers.

alexgartrell 16y ago

You may not have intended it, but your comment reads as "Google has awesome hard problems that only badasses can work on" "Also, I work there". Not ever mention of one's workplace warrants a disclaimer. :) But you do bring up an interesting point, how does Google handle the heterogeneous server problem? One assumes that not all nodes are created equal (if only because it would be cost prohibitive to upgrade all at once), so do you just use dynamic task scheduling and hope for the best or is there something cooler going on there?

dan_manges 16y ago

I think that's more of a disclosure than a disclaimer.