Comments on: asynctools – A Tale of Two Queries http://squeeville.com/2009/07/24/asynctools/ Jason Collins. No redaction. Mon, 11 Jan 2010 15:11:29 +0000 http://wordpress.com/ hourly 1 By: Roman Nurik http://squeeville.com/2009/07/24/asynctools/#comment-121 Roman Nurik Thu, 03 Sep 2009 04:22:00 +0000 http://squeeville.com/?p=88#comment-121 Wow, this is great. I can't wait to try it out in http://code.google.com/p/geomodel . This seems like it can drastically improve performance of IN queries, which I rely on heavily. Wow, this is great. I can’t wait to try it out in http://code.google.com/p/geomodel . This seems like it can drastically improve performance of IN queries, which I rely on heavily.

]]> By: Google: App Engine on Parallel Bars Goes for Gold : Beyond Search http://squeeville.com/2009/07/24/asynctools/#comment-119 Google: App Engine on Parallel Bars Goes for Gold : Beyond Search Wed, 19 Aug 2009 11:05:58 +0000 http://squeeville.com/?p=88#comment-119 [...] Short honk: If you are not familiar with Google’s enterprise initiatives, you will want to bone up. The Google has made what I think is an important announcement about the Google App Engine. Google said on August 17, 2009: Written by a group of engineers at VendAsta, asynctools is a rather nifty toolkit that allows you to execute datastore queries in parallel in the Python runtime. The interface is slightly more involved than using standard queries, but the ability to execute multiple queries in parallel can substantially reduce the render time for a page where you need to execute multiple independent queries. Jason Collins has written a detailed article about how and why they wrote asynctools, which can be found here. [...] [...] Short honk: If you are not familiar with Google’s enterprise initiatives, you will want to bone up. The Google has made what I think is an important announcement about the Google App Engine. Google said on August 17, 2009: Written by a group of engineers at VendAsta, asynctools is a rather nifty toolkit that allows you to execute datastore queries in parallel in the Python runtime. The interface is slightly more involved than using standard queries, but the ability to execute multiple queries in parallel can substantially reduce the render time for a page where you need to execute multiple independent queries. Jason Collins has written a detailed article about how and why they wrote asynctools, which can be found here. [...]

]]> By: VendAsta wows the Google App Engine world with asynctools. « The VendAsta Blog http://squeeville.com/2009/07/24/asynctools/#comment-118 VendAsta wows the Google App Engine world with asynctools. « The VendAsta Blog Tue, 18 Aug 2009 23:18:37 +0000 http://squeeville.com/?p=88#comment-118 [...] The VendAsta Blog Just another WordPress.com weblog « VendAsta Technologies – Top 25 Up and Comers in Canada VendAsta wows the Google App Engine world with asynctools. August 18, 2009 I’m going to write this for dummies like me. More technically-adept readers should just go read this post by Jason Collins. [...] [...] The VendAsta Blog Just another WordPress.com weblog « VendAsta Technologies – Top 25 Up and Comers in Canada VendAsta wows the Google App Engine world with asynctools. August 18, 2009 I’m going to write this for dummies like me. More technically-adept readers should just go read this post by Jason Collins. [...]

]]> By: Ben Nevile http://squeeville.com/2009/07/24/asynctools/#comment-117 Ben Nevile Tue, 18 Aug 2009 16:48:38 +0000 http://squeeville.com/?p=88#comment-117 Thanks for making this public!! Really looking forward to trying it out today. Thanks for making this public!! Really looking forward to trying it out today.

]]> By: Anthony Mills http://squeeville.com/2009/07/24/asynctools/#comment-116 Anthony Mills Tue, 18 Aug 2009 15:00:42 +0000 http://squeeville.com/?p=88#comment-116 Keep in mind the api_cpu_ms posted is a very simple calculation for Google: Retrieve given id/key name: 12 ms * results Query: 17.5 ms + 13.5 ms * results Inserts/Updates/Deletes: ~3000 ms + ~350 ms * entities In other words, do requests in parallel, sure, but be careful to issue inserts/updates/deletes in batches. Keep in mind the api_cpu_ms posted is a very simple calculation for Google:

Retrieve given id/key name: 12 ms * results
Query: 17.5 ms + 13.5 ms * results
Inserts/Updates/Deletes: ~3000 ms + ~350 ms * entities

In other words, do requests in parallel, sure, but be careful to issue inserts/updates/deletes in batches.

]]> By: Tim http://squeeville.com/2009/07/24/asynctools/#comment-114 Tim Tue, 18 Aug 2009 06:34:56 +0000 http://squeeville.com/?p=88#comment-114 This is awesome ! Really smart approach to one of the issues we face too often. Thumbs up for making it opensource. Thanks ! This is awesome ! Really smart approach to one of the issues we face too often. Thumbs up for making it opensource. Thanks !

]]> By: Jason Collins http://squeeville.com/2009/07/24/asynctools/#comment-113 Jason Collins Wed, 12 Aug 2009 14:58:46 +0000 http://squeeville.com/?p=88#comment-113 Thanks Ryan! It's already been a really important tool in the toolkit, though admittedly, if you get lazy, you're tempted to use it in places where an alternate Entity Model would yield a better result. It's sort of like a big cannon that you should aim and shoot carefully and sparingly. Thanks Ryan! It’s already been a really important tool in the toolkit, though admittedly, if you get lazy, you’re tempted to use it in places where an alternate Entity Model would yield a better result. It’s sort of like a big cannon that you should aim and shoot carefully and sparingly.

]]> By: Ryan http://squeeville.com/2009/07/24/asynctools/#comment-112 Ryan Wed, 12 Aug 2009 01:06:09 +0000 http://squeeville.com/?p=88#comment-112 awesome work! we're all really excited to see this open sourced and available for everyone to use. congratulations on the launch! awesome work! we’re all really excited to see this open sourced and available for everyone to use. congratulations on the launch!

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