Re: Query rewriting - caching rewritten quries

Hi again, I see I missed very important thing in your response. I thought I cannot reuse rewritten queries in different types of IndexReader but you wrote I cannot use rewritten queries even in another instance of IndexReader: "not even if it's a reopened reader against the same index". I thought

Re: Query rewriting - caching rewritten quries

Hi, Thank you for your response Chris. I see good news that I can pre-build rewritten queries for a given IndexReader and then use it in the same IndexReader. Can you tell me how I can achieve this? I see each Query has rewrite method which takes IndexReader as an argument. The only thing is just

Re: bigram problem

Dear Parnab, Thanks a lot for your guidance. I prefer to follow the second method, as I have already indexed the bigrams using ShingleFilterWrapper. But, I have no any idea about how to use NGramTokenizer here. So, could you please write one or two lines of the code which shows how to use NGramTok

Re: Query rewriting - caching rewritten quries

: In the system which I develop I have to store many query objects in memory. : The system also receives documents. For each document MemoryIndex is : instantiated. I execute all stored queries on this MemoryIndex. I realized : that searching over MemoryIndex takes much time for query rewriting. I'

Query rewriting - caching rewritten quries

Hi, In the system which I develop I have to store many query objects in memory. The system also receives documents. For each document MemoryIndex is instantiated. I execute all stored queries on this MemoryIndex. I realized that searching over MemoryIndex takes much time for query rewriting. I'm w

Re: Incremental Field Updates

Using BinaryDocValues is not recommended for all scenarios. It is a "catchall" alternative to the other DocValues types. I would not use it unless it makes sense for your application, even if it means that you need to re-index a document in order to update a single field. DocValues are not good fo

Re: bigram problem

TF is straight forward, you can simply count the no of occurrences in the doc by simple string matching. For IDF you need to know total no of docs in the collection and the no. of docs having the bigram. reader.maxDoc() will give you the total no of docs in the collection. To calculate the number o

bigram problem

Hi, Could please explain me how to determine the tf-idf score for bigrams. My program is able to index and search bigrams correctly, but it does not calculate the tf-idf for bigrams. If someone can, please help me to resolve this. Regards, Manjula.