Skip to main content

Apache Lucene Search Engine’s Features


Apache Lucene is a high-performance, full featured text search engine library written entirely in Java. It is part of Apache Jakarta Project. Lucene was originally written by Doug Cutting in Java. While suitable for any application which requires full text indexing and searching capability, Lucene has been widely recognized for its utility in the implementation of Internet search engines and local, single-site searching. Lucene is Doug Cutting’s wife’s middle name !

Features

1. Scalable, High-Performance Indexing

  • Over 95GB/hour on modern hardware
  • Small RAM requirements — only 1MB heap
  • Incremental indexing as fast as batch indexing
  • Index size roughly 20-30% the size of text indexed


2. Powerful, Accurate and Efficient Search Algorithms

  • Ranked searching — best results returned first
  • Sorting by any field
  • Multiple-index searching with merged results
  • Allows simultaneous update and searching


3. Flexible Queries

  • Phrase queries –>  like “star wars” –> search for the full word star wars.
  • Wildcard queries  –> like star* or  sta?  –> search for a single character or multi character replacements for the search words
  • Fuzzy queries  –> like star~0.8  –> search for the similar words with some weightage
  • Proximity queries  –> like  ”star wars”~10 –> search for a “star” and “wars” within 10 words of each other in a document
  • Range queries  –>  like {star-stun}  –>  search for documents in between star and stun. Exclusive queries are denoted by curly brackets
  • Fielded searching   –>  fields like  title, author, contents
  • Date-range searching   –> like [2006-2007]  –>  search for documents with field value in between 2006 and 2007. Inclusive queries are denoted by square brackets
  • Boolean Operators  –>  like star AND wars . The OR operator is the default conjunction operator.
  • Boosting a Term –>  like star^4  wars –> make documents with term star more relevant
  • + Operator  –>  like +star wars –>  search for documents that must contain “star” and may contain “wars”
  • - Operator  –>  like star -wars –>  search for documents that contain “star” and not contains “wars”
  • Grouping –>  like (star AND wars) OR website –>  using parentheses to group clauses to form sub queries
  • Escape special character –>  The current list special characters are   + – && || ! ( ) { } [ ] ^ ” ~ * ? : \  . To escape these character use the \ before the character.


4. Cross-Platform Solution

  • Available as Open Source software under the Apache License which lets you use Lucene in both commercial and Open Source programs
  • 100%-pure Java
  • Implementations in other programming languages available that are index-compatible


At the core of Lucene's logical architecture is the idea of a document containing fields of text. This flexibility allows Lucene's API to be independent of the file format. Text from PDFs, HTML, Microsoft Word, and OpenDocument documents, as well as many others (except images), can all be indexed as long as their textual information can be extracted.
Index  --> sequence of documents ( Directory)
Document  -->  sequence of fields
Field  --> named sequence of terms
Term  --> a text string (e.g., a word)
Terms:
A search query is broken up into terms and operators. There are two types of terms: Single Terms and Phrases. A Single Term is a single word such as "test" or "hello". A Phrase is a group of words surrounded by double quotes such as "hello dolly". Multiple terms can be combined together with Boolean operators to form a more complex query.

Fields:
When performing a search you can either specify a field, or use the default field. You can search any field by typing the field name followed by a colon ":" and then the term you are looking for.

Comments

Popular posts from this blog

ATG Product Catalog schema ER diagram

Check out the O rder schema ER-Diagram @   http://tips4ufromsony.blogspot.in/2012/02/atg-order-schema-er-diagram.html Check out the User Profile  schema ER-Diagram @ http://tips4ufromsony.blogspot.in/2012/03/atg-user-profile-schema-er-diagram.html If you would like to know the relationship between different Product Catalog tables, please find below screen shots of  Product Catalog schema ER Diagrams.

ATG Search - search engine tuning settings

In this blog, I am going to list the best tuning settings for ATG Search engine. The AESoapConfig.xml, AESoapWaspConfig.xml  and AEConfig.xml are the xmls referred below and you can find it @  <ATG_DIR>\<Searchx.x>\SearchEngine\<operating_system>\bin\ folder. (1)  Make sure that the AESoapConfig.xml's rwTimeout is less than or equal to routing's readTimeoutMs. You could find the routing's readTimeoutMs @ atg\search\routing\SearchEngineService component.               rwTimeout is the  length of time in seconds to wait before a read or write operation times out on an active connection. The number can be decreased to improve performance. However, a value that is too low could cause slow connections to be prematurely closed. (2)  Adjust the number of engine threads to match the number of CPUs available to the engine. Note that the minimal value for maxThreads and maxSpar...

Intimation u/s 143(1) of the Income Tax act

Have you got your Income Tax filing e-receipt ? After a successful assessment of tax returns, income tax department issues Intimation u/s 143(1). Normally these intimations will be received through email to the Email address provided when filing income tax returns online. If “NET AMOUNT REFUNDABLE /NET AMOUNT DEMAND”  is less than Rs 100, you can treat this Intimation u/s 143(1) as completion of income tax returns assessment under Income Tax Act. It can be useful for the proof of Income/ Completion of income tax returns assessment. In case of demand , we need to pay the entire Demand within 30 days of receipt of this intimation.The payment can be made using the printed challan enclosed in the mail or you can go for online tax payment. The Tax Payment challan is enclosed if the Tax Payable exceeds Rs. 100. If you go for online tax payment, follow the instructions listed @   http://tips4ufromsony.blogspot.com/2011/03/online-income-tax-payment-using.html  a...

ATG Search architectural flow : Search and Index

I would like to explain the high level ATG Search implementation architecture ( for an online store) through the above diagram. In this diagram 1.x denotes the search functionality and 2.x denotes the indexing functionality. I have given JBoss as the application server. Physical Boxes and Application Servers in the diagram ( as recommended by ATG )  : Estore ( Commerce ) Box --> The box with the estore/site ear (with the site JSPs and Java codes). Search Engine Box --> The box with the search engine application running. Indexing Engine Box --> The box with the indexing engine application running. CA (Content Administration) Box --> The box with the ATG CA ear ( where we could take CA -BCC - Search Administration and configure the search projects) . Search Indexer Box --> The box with the ATG Search Index ear ( to fetch the index data from repository). Note that the engine performing indexing will need access ...

GC Log Analyzer from IBM

This blog is about the GC( garbage collection) log analyzer from IBM. If you have a GC log and you want to analyze the file,  this IBM tool will help you with some graphical analyzer and some recommendations. You can download it from the following URL : https://www.ibm.com/support/pages/ibm-pattern-modeling-and-analysis-tool-java-garbage-collector-pmat Please find below some screenshots and details that might help you. 1. Screenshot 1: 2. Screenshot 2 : 3. Screenshot 3 : 4. Screenshot 4: