Hi all,
Re scalability of filter construction - the database is likely to hold stable primary keys not lucene doc ids
which are unstable in the face of updates.
This is the scalability issue I was concerned about. Assume the database call efficiently retrieves a sorted array of 50,000 stable primary keys. What is the best way to efficiently convert that list of primary keys to Lucene docIds.
I was looking at the Lucene in Action example code (which was not designed for this use case) where the Lucene docId is retrieved by iteratively calling termDocs.read. How expensive is this operation? Would 50,000 calls return in a few seconds or less?
for (String isbn : isbns) {
if (isbn != null) {
TermDocs termDocs =
reader.termDocs(new Term("isbn", isbn));
int count = termDocs.read(docs, freqs);
if (count == 1) {
bits.set(docs[0]);
}
That could involve a lot of disk seeks unless you cache a pk->docid lookup in ram.
That sounds interesting. How would the pk->docid lookup get populated?
Wouldn't a pk->docid cache be invalidated with each commit or merge?
Tom
-----Original Message-----
From: Mark Harwood
Sent: Friday, July 23, 2010 2:56 AM
To: java-user@lucene.apache.org
Subject: Re: on-the-fly "filters" from docID lists
Re scalability of filter construction - the database is likely to hold stable primary keys not lucene doc ids which are unstable in the face of updates. You therefore need a quick way of converting stable database keys read from the db into current lucene doc ids to create the filter. That could involve a lot of disk seeks unless you cache a pk->docid lookup in ram. You should use cachingwrapperfilter too to cache the computed user permissions from one search to the next.
This can get messy. If the access permissions are centred around roles/groups it is normally faster to tag docs with these group names and query them with the list of roles the user holds.
If individual user-doc-level perms are required you could also consider dynamically looking up perms for just the top n results being shown at the risk of needing to repeat the query with a larger n if insufficient matches pass the lookup.
Cheers
Mark
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