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869 high scalability-2010-07-30-Hot Scalability Links for July 30, 2010


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Introduction: Jeremy Zawodny, while performing data alchemy in the dungeons of Craigslist, stored 1,250,000,000 Key/Value Pairs in Redis on a 32GB Machine . Data sorting world record: 1 terabyte, 1 minute . The system has  52 computer nodes, each node is a commodity server with two quad-core processors, 24 gigabytes (GB) memory and sixteen 500 GB disks . It's not just hardware though, they also built a software that utilized all their CPU and RAM. Tweets of Gold: wm : I am really getting the sense that none of you yokels waxing profound about scalability actually has anything factual to say joestump : I think you can do things to *mitigate* pain points up front. You don't need to over-engineer, but it's not hard to look forward. danielcrenna : I love it when I check in debug code accidentally and it turns into a three day hunt for a major scalability problem joestump : Your post also makes me think of another phrase I say often: Scaling == Specialization. Bigger scale =


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2 Data sorting world record: 1 terabyte, 1 minute . [sent-2, score-0.083]

3 The system has  52 computer nodes, each node is a commodity server with two quad-core processors, 24 gigabytes (GB) memory and sixteen 500 GB disks . [sent-3, score-0.113]

4 It's not just hardware though, they also built a software that utilized all their CPU and RAM. [sent-4, score-0.083]

5 Tweets of Gold: wm : I am really getting the sense that none of you yokels waxing profound about scalability actually has anything factual to say joestump : I think you can do things to *mitigate* pain points up front. [sent-5, score-0.332]

6 danielcrenna : I love it when I check in debug code accidentally and it turns into a three day hunt for a major scalability problem joestump : Your post also makes me think of another phrase I say often: Scaling == Specialization. [sent-7, score-0.289]

7 Quora: What are the scaling issues to keep in mind while developing a social network feed? [sent-9, score-0.133]

8 Very good discussion of scaling advice: denormalize; cache; SSD; optimize writes; avoid stupid things. [sent-10, score-0.212]

9 Each and every problem has an appropriate set of applicable technologies, and it’s up to the engineer to justify their use. [sent-12, score-0.161]

10 In a system of no significant scale, basically anything works. [sent-15, score-0.101]

11 In a system of significant scale, there is no magic bullet. [sent-18, score-0.101]

12 I think with great tools like memcached it is easy to get carried away and use it as the mallet for every performance problem, but in many cases it should not be your first choice . [sent-20, score-0.079]

13 Caching should be seen more as a burden that many applications just can’t live without. [sent-21, score-0.149]

14 You don’t want that burden until you have exhausted all other easily reachable optimizations . [sent-22, score-0.346]

15 NVIDIA announced that it had partnered with PEER 1 to provide the industry’s first large-scale hosted GPU cloud . [sent-24, score-0.094]

16 The basic insight behind Levenshtein automata is that it's possible to construct a  Finite state automaton  that recognizes exactly the set of strings within a given Levenshtein distance of a target word. [sent-27, score-0.5]

17 A sweet 127 slide  whirlwind tour of the theory and application of graphs . [sent-29, score-0.108]

18 On an AWS Cluster Compute Instance I was able to insert a million small documents in about 3 minutes. [sent-31, score-0.113]

19 A smart grid network will be highly dependent on “people’s willingness to connect in this way,” and “this is not going to be something that can be forced on anyone no matter how hard we try. [sent-37, score-0.275]


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