Apache_lucene.ppt - STI Innsbruck

“Apache Lucene(TM) is a high-performance, full-featured text search engine library written entirely in Java. It is a technology suitable for nearly any application ...

1. Apache Lucene Ioan Toma based on slides from Aaron Bannert aaron@codemass.com © www.sti-innsbruck.at Copyright 2012 STI INNSBRUCK www.sti-innsbruck.at

2. What is Apache Lucene? “Apache Lucene(TM) is a high-performance, full-featured text search engine library written entirely in Java. It is a technology suitable for nearly any application that requires full-text search, especially cross- platform.” ­ from http://lucene.apache.org/ www.sti-innsbruck.at

3. Features • 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 • Powerful, Accurate and Efficient Search Algorithms – ranked searching -- best results returned first – many powerful query types: phrase queries, wildcard queries, proximity queries, range queries and more – fielded searching (e.g., title, author, contents) – date-range searching – sorting by any field – multiple-index searching with merged results – allows simultaneous update and searching www.sti-innsbruck.at

4. Features • 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 • CLucene - Lucene implementation in C++ • Lucene.Net - Lucene implementation in .NET • Zend Search - Lucene implementation in the Zend Framework for PHP 5 www.sti-innsbruck.at 4

5. Ranked Searching 1. Phrase Matching 2. Keyword Matching – Prefer more unique terms first – Scoring and ranking takes into account the uniqueness of each term when determining a document’s relevance score www.sti-innsbruck.at

6. Flexible Queries • Phrases “star wars” • Wildcards star* • Ranges {star­stun} [2006­2007] • Boolean Operators star AND wars www.sti-innsbruck.at

7. Field-specific Queries • Field-specific queries can be used to target specific fields in the Document Index. • For example title:”star wars” AND director:”George Lucas” www.sti-innsbruck.at

8. Sorting • Can sort any field in a Document – For example, by Price, Release Date, Amazon Sales Rank, etc… • By default, Lucene will sort results by their relevance score. Sorting by any other field in a Document is also supported. www.sti-innsbruck.at

9. LUCENE INTERNALS www.sti-innsbruck.at 9

10. Everything is a Document • A document can represent anything textual: – Word Document – DVD (the textual metadata only) – Website Member (name, ID, etc…) • A Lucene Document need not refer to an actual file on a disk, it could also resemble a row in a relational database. • Developers are responsible for turning their own data sets into Lucene Documents • A document is seen as a list of fields, where a field has a name an a value www.sti-innsbruck.at

11. Indexes • The unit of indexing in Lucene is a term. A term is often a word. • Indexes track term frequencies • Every term maps back to a Document • Lucene uses inverted index which allows Lucene to quickly locate every document currently associated with a given set up input search terms. www.sti-innsbruck.at

12. Basic Indexing 1. Parse different types of documents (HTML, PDF, Word, text files, etc.) 2. Extract tokens and related info (Lucene Analyser) 3. Add the Document to an Index Lucene provide a standard analyzer for English and latin based languages . www.sti-innsbruck.at

13. Basic Searching 1. Create a Query • (eg. by parsing user input) 2. Open an Index 3. Search the Index • Use the same Analyzer as before 4. Iterate through returned Documents • Extract out needed results • Extract out result scores (if needed) www.sti-innsbruck.at

14. Lucene as SOA 1. Design an HTTP query syntax – GET queries – XML for results 2. Wrap Tomcat around core code 3. Write a Client Library As it follows SOA principles, basic building blocks such as load balancers can be deployed to quickly scale up the capacity of the search subsystem. www.sti-innsbruck.at

15. Lucene as SOA Diagram Single-Machine Architecture Lucene-based Application includes three components 1. Lucene Custom Client Library 2. Search Service 3. Custom Core Search Library www.sti-innsbruck.at

16. LUCENE SCALABILITY www.sti-innsbruck.at 16

17. Scalability Limits • 3 main scalability factors: – Query Rate – Index Size – Update Rate www.sti-innsbruck.at

18. Query Rate Scalability • Lucene is already fast – Built-in caching • Easy solution for heavy workloads: (gives near-linear scaling) – Add more query servers behind a load balancer – Can grow as your traffic grows www.sti-innsbruck.at

19. Lucene as SOA Diagram High-Scale Multi-Machine Architecture www.sti-innsbruck.at

20. Index Size Scalability • Can easily handle millions of Documents • Lucene is very commonly deployed into systems with 10s of millions of Documents. • Main limits related to Index size that one is likely to run in to will be disk capacity and disk I/O limits. If you need bigger: • Built-in multi-machine capabilities – Can merge multiple remote indexes at query-time. www.sti-innsbruck.at

21. Update Rate • Lucene is threadsafe – Can update and query at the same time • I/O is limiting factor Strategies for achieving even higher update rates: – Vertical Split – for big workloads (Centralized Index Building) 1. Build indexes apart from query service 2. Push updated indexes on intervals – Horizontal Split – for huge workloads 1. Split data into columns 2. Merge columns for queries 3. Columns only receive their own data for updates www.sti-innsbruck.at