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Understanding Lucene Using the basic indexing API Working with the search API Considering alternative products One of the key factors behind Lucene's popularity and success is its simplicity. The careful exposure of its indexing and searching API is a sign of the well-designed software.
Connecting your users with the content they need when they need it isn't just optional anymore. With the rise of Google and similarly sophisticated search engines, users expect high-quality search results that help them find what they're looking for quickly and easily. Your manager has equally high expectations for your online shopping site -- a scalable, highly available, easy-to-maintain search solution that doesn't cost a fortune to install. As for you, you just want to advance your career, keep your employer and customers happy, and hold on to your sanity. You can meet all these needs with Apache Solr, an open source, Lucene Java-based search server that is easy to incorporate into your Web applications.
This article introduces you to the indexing mechanism of Lucene, a popular full-text IR library written in the Java language. First, I'll demonstrate how to index your documents with Lucene, then I'll discuss how to improve the indexing performance. Finally, I'll analyze Lucene's index file structure.
As you know from many of my entries I’m a big fan of couchdb , and if you’re interested you should really be following janl , jchris and lethain as they push this technology forward. As you might also guess from my earlier post I’m working to build and install it on Dreamhost , another thing I support enthusiastically. Unfortunately, being on the outer fringe of technology meant I wasn’t able to get them to install it for me, but that’s completely understandable. Given that the current package release has no Auth support (I believe the repository builds do but that would have required more software installs) if I were supporting a multi-user production environment it might make me a little nervous too.