Actually no. Let's say you have 10 machines and hence 10 search
servers. You would run through 10 iterations of fetch-index-deploy, one
to each machine. Lets say you have 3 million pages per machine so this
whole system could support a 30 million page index.
Once you deploy to 10 you would want to start over as you don't have any
more space (machines, etc.). So you would reset the crawldb (this is a
special job that simply makes sure that all pages are available for
fetching and are not filtered by next crawl date). Then you would run
the next generate with topN which would grab the next top 3 million urls
to be fetched again. This fetch-index-deploy cycle would then replace
(not overwrite) the deployment on search server 1, then 2,3,... as you
do more cycles. This way the best urls would continually rise to the top.
One point is there is no concept of depth, only of top urls to fetch.
With each cycle we update a single master crawldb so the top urls will
continually change. But we are not fetching levels as in the whole web
crawl tutorial. While going through the cycle we don't reset the
crawldb and therefore any pages we have fetched during the run of
machines wouldn't get fetched again until we reset the crawldb after all
machines have been deployed and we start the whole cycle over again.
And yes you may have some duplicates in your indexes but this is taken
care of in the search itself (there is a dedupField option in
NutchBean). Of the duplicates the one with the best score (most
relevant) should be returned.
This whole process is continuous and would just keep running until you
tell it to stop. The search would never be fully down as only a single
search server would be down at once and only for a few seconds while the
database files are replaced. And you would continually get the best
urls in your index for the space you have. I imagine that this is very
similar to how the google dance works.
Dennis Kubes
charlie w wrote:
On 8/1/07, Dennis Kubes <[EMAIL PROTECTED]> wrote:
I am currently writing a python script to automate this whole process
from inject to pushing out to search servers. It should be done in a
day or two and I will post it on the wiki.
I'm very much looking forward to this. Reading the code always helps make
it concrete to me.
You can do a dedeup of results on the search itself. So yes there are
duplicates in the different index segments, but you will always be
returning the "best" pages to the user.
I get it; so dedup based on the timestamp of each version of the document
with a particular URL that was a hit.
It also seems that I must be missing something regarding new pages. If,
as
in step 9, you are replacing the index on a search server, wouldn't you
possibly create the effect of removing documents from the index? Say
you
have the same 2 search servers, but do 10 iterations of fetching as a
"depth" of crawl. Wouldn't you be replacing the documents in search
server
1 several times over the course of those 10 iterations?
No because you are updating a single master crawldb and on the next
iteration it wouldn't grab the same pages, it would grab the next best n
pages.
I had the impression you were overwriting the index on the search servers
with the segment and index from the new iteration of fetching. Meaning in
my 2 search server example, iteration 3 of fetching would overwrite
the index built by iteration 1 of fetching (they'd both wind up on search
server 1). But instead, you're actually merging the results of iteration 3
into the search server's existing index from iteration 1, rather than
replacing the entire index?
- C
