Summary: I collect the doc ids of all hits for a given search by using a custom Collector (it populates a BitSet with the ids). The searching and getting doc ids are quite fast according to my needs but when it comes to actually fetching the documents from disk, things get very slow. Is there a way to optimize Lucene for faster document collection?
Details: I'm working on a processed corpus of Wikipedia and I keep each sentence as a separate document. When I search for "computer", I get all sentences containing the term computer. Currently, searching the corpus and getting all document ids work in sub-second but fetching the first 1000 documents takes around 20 seconds. Fetching all documents takes proportionally more time (i.e. another 20 sec for each 1000 batch).
Subsequent searches and document fetching takes much more little time (though I don't know who's doing the caching, OS or Lucene?) but I'll be searching for many diverse terms and I don't want to rely on caching, the performance on the very first search is crucial for me.
I'm looking for suggestions/tricks that will improve the document-fetching performance (if it's possible at all). Thanks in advance!
Addendum:
I use Lucene 3.0.0 but I use Jython to drive Lucene classes. Which means, I call the get_doc method of the following Jython class for every doc id I retrieved during the search:
class DocumentFetcher():
def __init__(self, index_name):
self._directory = FSDirectory.open(java.io.File(index_name))
self._index_reader = IndexReader.open(self._directory, True)
def get_doc(self, doc_id):
return self._index_reader.document(doc_id)
I have 50M documents in my index.