inverted-index

问题 How do search engines such as Lucene, etc. perform AND queries where a term is common to many documents in the dataset? For example, in an inverted index of: term | document_id --------------------- program | 1, 2, 3, 5... python | 1, 4 code | 4 c++ | 4, 5 the term program is present in several documents meaning a query of program AND code would require performing an intersection upon a very large set of documents. Is there a way to perform AND queries without having to take the intersection

来源： https://stackoverflow.com/questions/31761218/forward-index-vs-inverted-index-why

问题 If we want to search a query like this "t1 t2 t3" (t1,t2 ,t3 must be queued) in an inverted index structure , which ways should we do ? 1-First we search the "t1" term and find all documents that contains "t1" , then do this work for "t2" and then "t3" . Then find documents that positions of "t1" , "t2" and "t3" are next to each other . 2-First we search the "t1" term and find all documents that contains "t1" , then in all documents that we found , we search the "t2" and next , in the result

问题 I want to create a big inverted index of around 10 6 terms. What method would you suggest? I'm thinking in fast binary key store DBs like Tokyo cabinet, voldemort, etc. Edit: I've tried MySQL in the past for storing a table of two integers to represent the inverted index, but even with the first column having a db index, queries were very slow. I think for those situations a SQL database has too much overhead, overhead of transactions, query parsing, etc. I'm searching for what technologies

问题 what i have in output is: word , file ----- ------ wordx Doc2, Doc1, Doc1, Doc1, Doc1, Doc1, Doc1, Doc1 what i want is: word , file ----- ------ wordx Doc2, Doc1 public static class LineIndexMapper extends MapReduceBase implements Mapper<LongWritable, Text, Text, Text> { private final static Text word = new Text(); private final static Text location = new Text(); public void map(LongWritable key, Text val, OutputCollector<Text, Text> output, Reporter reporter) throws IOException { FileSplit

问题 I'm building a small web search engine for searching about 1 million web pages and I want to know What is the best way to build the inverted index ? using the DBMS or What …? from many different views like storage cost, performance, speed of indexing and query? and I don't want to use any open source project for that I want to make my own one! 回答1: Perhaps you might want to elaborate why you do not wish to use F/OSS tools like Lucene or Sphinx. 回答2: Most of the current closed-source database

问题 How do search engines merge results from an inverted index? For example, if I searched for the inverted indexes of the words "dog" and "bat", there would be two huge lists of every document which contained one of the two words. I doubt that a search engine walks through these lists, one document at a time, and tries to find matches with the results of the lists. What is done algorithmically to make this merging process blazing fast? 回答1: Actually search engines do merge these document lists.

问题 Is there anyway in which I can create indexes in Solr to perform full-text search from HBase for Near Real Time. I didn't wanted to store the whole text in my solr indexes. Made "stored=false" Note: - Keeping in mind, I am working on large datasets and want to do Near Real Time search. WE are talking TB/PB of data. UPDATED Cloudera Distribution : 5.4.x is used with Cloudera Search components. Solr : 4.10.x HBase : 1.0.x Indexer Service : Lily HBase Indexer with cloudera morphlines Is there

问题 What can be the database for a search engine? I mean after creating inverted index for a site, where one could store it so that program can create indices for other sites and save them too. Later on indexer can query them also. Because indices can range in thousands of billions. Thanksyou 回答1: I would use Lucene. That's what it is made for. You even have your choice of many different languages. 来源： https://stackoverflow.com/questions/3581792/i-have-created-inverted-index-for-a-website-but

问题 I have thousand of pages in website which I parsed and stored it as Inverted Index viz document docid (PK,FK) url charactercount wordcount Charactercount and wordcount helps me determine long document from short which I may use later. word wordid (PK,FK) word doc_freq inverse_doc_freq For inverse_doc_freq calculation I use fictional high number (100000000) to prevent total document recalculation. loc wordid docid word_freq weight (wordid & docid combined unique) The weight is a score