USE APACHE LUCENE FOR INDEXING FULL

In a classic index, for every document, we collect the full list of words or terms the document contains. But instead of creating a classic index, Lucene makes use of Inverted Indices. The obvious question which should come to your mind is, how is Lucene so fast in running full-text search queries? The answer to this, of course, is with the help of indices it creates. This is because the information we need might exist in a single file out of billions of files kept on the web. Running the full-text search on this kind of volume of data is a difficult task. The velocity at which data is being stored in an application today is huge. Even if it did, it will take an unacceptable amount of time to run the search this big.Ī full-text search engine is capable of running a search query on millions of files at once. But what about the Web or a Music application or a code repository or a combination of all of these? The database cannot store this data in its columns. Databases like MySQL support full-text search. One might think that a simple relational database can also support searching. This search can be across multiple web-pages which exist on the Web or a Music application or a code repository or a combination of all of these. Search is one of the most common operations we perform multiple times a day. Before we start with an application which demonstrates the working of Apache Lucene, we will understand how Lucene works and many of its components. Lucene is one of the most powerful engine on which Elasticsearch is built up on. With Apache Lucene, we can use the APIs it exposes in many programming languages and builds the features we need. In this lesson, we will understand the workings behind one of the most powerful full-text search engine, Apache Lucene.

Use apache lucene for indexing