high_scalability high_scalability-2010 high_scalability-2010-771 knowledge-graph by maker-knowledge-mining

771 high scalability-2010-02-04-Hot Scalability Links for February 4, 2010


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Introduction: Lots of cool stuff happening this week... Voldemort gets rebalancing. It's one thing to shard data to scale, it's a completely different level of functionality to manage those shards intelligently. Voldemort has stepped up by adding advanced rebalancing functionality: Dynamic addition of new nodes to the cluster; Deletion of nodes from cluster; Load balancing of data inside a cluster. Microsoft Finally Opens Azure for Business. Out of the blue Microsoft opens up their platform as a service service. Good to have more competition and we'll keep an eye out for experience reports. New details on LinkedIn architecture by Greg Linden. LinkedIn appears to only use caching minimally, preferring to spend their efforts and machine resources on making sure they can recompute computations quickly than on hiding poor performance behind caching layers . The end of SQL and relational databases?   by David Intersimone . For new projects, I believe, we have genuine non-relational a


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1 It's one thing to shard data to scale, it's a completely different level of functionality to manage those shards intelligently. [sent-5, score-0.105]

2 Voldemort has stepped up by adding advanced rebalancing functionality: Dynamic addition of new nodes to the cluster; Deletion of nodes from cluster; Load balancing of data inside a cluster. [sent-6, score-0.317]

3 Out of the blue Microsoft opens up their platform as a service service. [sent-8, score-0.278]

4 Good to have more competition and we'll keep an eye out for experience reports. [sent-9, score-0.081]

5 LinkedIn appears to only use caching minimally, preferring to spend their efforts and machine resources on making sure they can recompute computations quickly than on hiding poor performance behind caching layers . [sent-11, score-0.515]

6 For new projects, I believe, we have genuine non-relational alternatives on the table (pun intended) . [sent-14, score-0.189]

7 When you make millions of widgets saving pennies per widget quickly adds up to real money. [sent-16, score-0.436]

8 Facebook released HipHop, a PHP compiler, aimed at shaving off cycle of CPU and bytes of memory in production of their social widgets. [sent-17, score-0.388]

9 What Second Life can teach your datacenter about scaling Web apps By Ian Wilkes . [sent-18, score-0.091]

10 This article will lay out some pragmatic advice for getting past this point in the real world of limited foresight and budgets . [sent-20, score-0.229]

11 A nice explanation of why DNS sucks for failover and Google's proposal to fix it (and get location information). [sent-23, score-0.191]

12 Learn all about the esoterica of write-ahead-logging and how HBase uses it to survive server crashes. [sent-25, score-0.083]

13 Plurk released instant notifications which allows hundred thousands of active users , who have post posted over 1 billion unique messages, to converse with only sub-second delays. [sent-27, score-0.396]

14 Not only is this impressive, but as impressive is that they use Node. [sent-28, score-0.152]

15 If you are a worried about how to scale the future, this sounds pretty good to me. [sent-33, score-0.098]

16 But yesterday's organizations — from carmakers, to investment banks, to the healthcare system, to the energy industry, to the Senate itself — are broken. [sent-36, score-0.328]

17 Today's biggest human challenge isn't leading broken organizations slightly better. [sent-37, score-0.213]

18 It isn't about leadership: it's about "buildership", or what I often refer to as Constructivism. [sent-39, score-0.095]


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Introduction: Hibernate and iBATIS and other similar tools have documentation with recommendations for avoiding the "N+1 select" problem. The problem being that if you wanted to retrieve a set of widgets from a table, one query would be used to to retrieve all the ids of the matching widgets (select widget_id from widget where ...) and then for each id, another select is used to retrieve the details of that widget (select * from widget where widget_id = ?). If you have 100 widgets, it requires 101 queries to get the details of them all. I can see why this is bad, but what if you're doing entity caching? i.e. If you run the first query to get your list of ids, and then for each widget you retrive it from the cache. Surely in that case, N+1(+caching) is good? Assuming of course that there is a high probability of all of the matching entities being in the cache. I may be asking a daft question here - one whose answer is obviously implied by the large scalable mechanisms for storing data th

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