Re: Google performance bottlenecks ;-) (Re: Lucene performance bottlenecks)
Hi Andrzej, This was a very interesting experiment -- thanks for sharing the results with us. The last range was the maximum in this case - Google wouldn't display any hit above 652 (which I find curious, too - because the total number of hits is, well, significantly higher - and Google claims to return up to the first 1000 results). I believe this may have something to do with the way Google compacts URLs. My guess is that initially a 1000 results is found and ranked. Then pruning is performed on that, leaving just a subset of results for the user to select from. If you try this, self-indulging, query (with filtering enabled): http://www.google.com/search?as_q=dawid+weissnum=10hl=enas_qdr=allas_occt=anyas_dt=isafe=activestart=900 You get: Results 781 - 782 of about 61,700 Now try disabling filtering: http://www.google.com/search?as_q=dawid+weissnum=10hl=enas_qdr=allas_occt=anyas_dt=isafe=imagesstart=900 Then you get: Results 781 - 782 of about 65,500 Hmmm... still the same number of available results, but the total estimate is higher. So far I used URL parameters found on the advanced search page. I tried to display the omitted search results, as Google suggested. Interestingly, this lead to: http://www.google.com/search?q=dawid+weisshl=enshb=tfilter=0start=900 Results 541 - 549 of about 65,400 And that's the maximum you can get. Sorry, my initial intuition proved wrong -- there is no clear logic behind the maximum limit of results you can see (unless you can find some logic in the fact that I can see _more_ results when I _exclude_ repeated ones from the total). Dawid
Re: Google performance bottlenecks ;-) (Re: Lucene performance bottlenecks)
Dawid Weiss wrote: Hi Andrzej, This was a very interesting experiment -- thanks for sharing the results with us. The last range was the maximum in this case - Google wouldn't display any hit above 652 (which I find curious, too - because the total number of hits is, well, significantly higher - and Google claims to return up to the first 1000 results). I believe this may have something to do with the way Google compacts URLs. My guess is that initially a 1000 results is found and ranked. Then pruning is performed on that, leaving just a subset of results for the user to select from. That was my guess, too ... Sorry, my initial intuition proved wrong -- there is no clear logic behind the maximum limit of results you can see (unless you can find some logic in the fact that I can see _more_ results when I _exclude_ repeated ones from the total). Well, trying not to sound too much like Spock... Fascinating :-), but the only logical conclusion is that at the user end we never deal with any hard results calculated directly from the hypothetical main index, we deal just with rough estimates from the estimated indexes. These change in time, and perhaps even with the group of servers that answered this particular query... My guess is that there could be different estimated indexes prepared for different values of the main boolean parameters, like filter=0... -- Best regards, Andrzej Bialecki ___. ___ ___ ___ _ _ __ [__ || __|__/|__||\/| Information Retrieval, Semantic Web ___|||__|| \| || | Embedded Unix, System Integration http://www.sigram.com Contact: info at sigram dot com
Google performance bottlenecks ;-) (Re: Lucene performance bottlenecks)
Hi, I made an experiment with Google, to see if they use a similar approach. I find the results to be most interesting. I selected a query which is guaranteed to give large result sets, but is more complicated than a single term query: http com. The total number of hits (approx) is 2,780,000,000. BTW, I find it curious that the last 3 or 6 digits always seem to be zeros ... there's some clever guesstimation involved here. The fact that Google Suggest is able to return results so quickly would support this suspicion. When I ran the query for the first time, the response time was 0.29 sec. All subsequent queries retrieving the first 10 results are in the order of 0.07 sec. This is for retrieving just the first page (first 10 results). Retrieving results 10-20 also takes 0.08 sec, which suggests that this result was cached somewhere. Starting from results 20+ the response time increases (linearly?), although it varies wildly between requests, sometimes returning quicker, sometimes taking the max time - which suggests that I'm hitting different servers each time. Also, if I wait ~30 sec to 1 minute, the response times are back to the values for the first-time run. start first repeated response 30 0.14 0.08-0.21 50 0.29 0.11-0.22 100 0.36 0.22-0.45 200 0.73 0.49-0.65 300 0.96 0.64-0.98 500 1.36 1.43-1.87 650 2.24 1.49-1.85 The last range was the maximum in this case - Google wouldn't display any hit above 652 (which I find curious, too - because the total number of hits is, well, significantly higher - and Google claims to return up to the first 1000 results). My impressions from this excercise are perhaps not so surprising: Google is highly optimized for retrieving the first couple of results, and the more results you want to retrieve the worse the performance. Finally, you won't be able to retrieve any results above a couple hundred, quite often less than the claimed 1000 results threshold. As for the exact techniques of this optimization, we'll never know for sure, but it seems like something similar is going on to what you outlined in your email. I think it would be great to try it out. Andrzej Doug Cutting wrote: Doug Cutting wrote: Implementing something like this for Lucene would not be too difficult. The index would need to be re-sorted by document boost: documents would be re-numbered so that highly-boosted documents had low document numbers. In particular, one could: 1. Create an array of int[maxDoc], with a[i] = i. 2. Sort the array with order(i,j) = boost(i) - boost(j); 3. Implement a FilterIndexReader that re-numbers using the sorted array. So, for example, the document numbers in the TermPositions will a[old.doc()]. Each term's positions will need to be read entirely into memory and sorted to perform this renumbering. The IndexOptimizer.java class in the searcher package was an old attempt to create something like what Suel calls fancy postings. It creates an index with the top 10% scoring postings. Since documents are not renumbered one can intermix postings from this with the full index. So for example, one can first try searching using this index for terms that occur more than, e.g., 10k times, and use the full index for rarer words. If that does not find 1000 hits then the full index must be searched. Such an approach can be combined with using a pre-sorted index. I think the first thing to implement would be to implement something like what Suel calls first-1000. Then we need to evaluate this and determine, for query log, how different the results are. Then a HitCollector can simply stop searching once a given number of hits are found. Doug -- Best regards, Andrzej Bialecki ___. ___ ___ ___ _ _ __ [__ || __|__/|__||\/| Information Retrieval, Semantic Web ___|||__|| \| || | Embedded Unix, System Integration http://www.sigram.com Contact: info at sigram dot com
Re: Google performance bottlenecks ;-) (Re: Lucene performance bottlenecks)
The total number of hits (approx) is 2,780,000,000. BTW, I find it curious that the last 3 or 6 digits always seem to be zeros ... there's some clever guesstimation involved here. The fact that Google Suggest is able to return results so quickly would support this suspicion. For more informations about fake Google counts, I suggest you to take a look to some tests performed by Jean Véronis, a French academic : http://aixtal.blogspot.com/2005/02/web-googles-missing-pages-mystery.html Jérôme -- http://motrech.free.fr/ http://www.frutch.org/
