This slide is showing how you can divide a request for a page into multiple database queries, such as a query for the ads, a query for search requests, a query for recommendations, etc.
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AnnabelleBlue
*This is good for parallelism because each database query can be done in parallel. This will decrease the time for a response since the database queries are not reliant upon each other. This method can greatly decrease latency.
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Avesh
Here's a quick summary of the linked article:
Latency on websites matters far more than most think. Marissa Mayer (back when she was at Google) reported that users unanimously want 30 results per page, but 10 results /page did way better in A/B testing. This was because the 10 results page takes .4 seconds to generate, whereas the 30 results page takes .9.
This finding is corroborated with data from AOL, Shopzilla, and additional Google data.
Interestingly, the bulk of the web page latency on popular sites like Facebook and Ebay was actually front-end time rather than server latency.
I suspect that this is because these sites have already implemented the methods described in this slide, and not because these methods are not important.
This slide is showing how you can divide a request for a page into multiple database queries, such as a query for the ads, a query for search requests, a query for recommendations, etc.
This comment was marked helpful 0 times.
*This is good for parallelism because each database query can be done in parallel. This will decrease the time for a response since the database queries are not reliant upon each other. This method can greatly decrease latency.
This comment was marked helpful 0 times.
Here's a quick summary of the linked article:
Latency on websites matters far more than most think. Marissa Mayer (back when she was at Google) reported that users unanimously want 30 results per page, but 10 results /page did way better in A/B testing. This was because the 10 results page takes .4 seconds to generate, whereas the 30 results page takes .9.
This finding is corroborated with data from AOL, Shopzilla, and additional Google data.
Interestingly, the bulk of the web page latency on popular sites like Facebook and Ebay was actually front-end time rather than server latency.
I suspect that this is because these sites have already implemented the methods described in this slide, and not because these methods are not important.
Here is a clickable link to the article: http://perspectives.mvdirona.com/2009/10/31/TheCostOfLatency.aspx
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