We have had a very good experience with the combined performance of filtering on Lucene index first before querying database, with its proven trackrecord we have incorporated it into all our existing as well as new software solutions. Idea is to search Lucene first, get a subset of only matching records and use that subset to query the database. This is very useful as Lucene can search millions of documents faster than searching millions of records in database. These Id or fields can subsequently be used for querying the database. The returned documents can be read for required data and displayed to userĪlternatively, retrieve the Id or specific field(ex: employee code) from the returned documents. With lucene, developers need to programmatically query the lucene index first which does fast retrieval of documents matching the search criteria. Normally, developers would code an application search or query functionality as database query and return records. Lucene first time indexing is an expensive process, so care should be taken to perform the first time indexing at off-peak hours. Lucene can also index and search document files like Word, PDF, HTML, Text files. For example, we can combine the details of Department and Employee table into one object and index them as documents in lucene index with one document per employee. These documents can have a unique Id as key. This is done programmatically by a one-time query of database, creating mapped objects for the records and serializing those objects as Lucene documents. Software solution programmers can introduce a lucene layer which indexes all the related data from database as documents in lucene index. Since lucene index creation is time consuming process, the indexes can be created in one machine and distributed to the onsite and offshore development teams, teams can then just place the index files in a configured location in filesystem and use it. Index and search algorithms make Lucene faster than any known databases. With inverted index, Lucene indexes all possible combination of the values in documents, when search is done, it first matches the value combinations with some fast algorithms and returns documents (objects) which have fields with those values. A search is done from top to bottom i.e it searches for objects having fields with matching values and returns those objects. Normally, datasources structure the data as an object or record, which in turn have fields and values. Lucene is very fast at searching for data because of its inverted index technique. It can even support the “Did you mean?” functionality like in google search which gives suggestions for any incorrect/unrecognized words. Query execution slows down as records and indexes grow.Īpache Lucene is a high-performance text search engine suitable for nearly any application that requires full-text search. at database level in an attempt to improve query performance. This is true even if we introduce clusters, indexes, materialized views, etc. Software solutions with large database will experience load performance issues due to several reasons, most probably due to combining data structures (ex: table joins) and retrieval (ex: query). Application Search functionality can mean a search box in user interface or some internal data query. Most software solutions on different platforms will certainly have search functionality that needs to query data from datasources and serve to the consuming application.
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