What are the Key Features of Apache Solr Search?
Apache Solr is the search platform that powers the biggest websites across the globe today. This article takes a look into the powerful features of the standalone enterprise search server with tremendous search capabilities that has the Lucene Java Search library at its core.
Conceptualized and developed as an in-house project to add search capabilities to the CNET Networks website in 2004, Solr Search has indeed come a long way in the last decade. SearchBlox, 3RDi Search, Commvault, and Coveo are some examples of enterprise search platforms powered by Solr Search. It’s an open source platform written in Java but is usable from popular programming languages, including C#, PHP, Ruby and Python. Another interesting fact is its plugin architecture that supports advanced customization. It has an active community of developers who contribute new features to the platform. Here are some of its key features.
1] Faceted Navigation
Faceted navigation is a technique which involves the organization of data using a faceted classification system that classifies the elements of the information along multiple dimensions or facets. This approach to data classification facilitates the application of multiple filters on a collection of information.
2] Full Text Indexing & Search
When faced with unstructured data, Solr Search works in two steps. First, it examines each and every word in the document for potential keyword matches to create an index. Once the index is saved in the directory, the platform refers to this index when fetching results for a query instead of the text of the original document. This feature is extremely fast and effective when dealing with large amounts of data, as compared to the keyword based search engines.
3] Near Real Time Indexing
Solr is powered by Lucene – an open source full-text search library – with near real time indexing capabilities to make the documents available to the users for search almost immediately after indexing. Another advantage of this feature is that updates, if any, are incorporated in the results in near real time. An example is the ‘out of stock’ and discount offer updates on ecommerce platforms.
4] Scalable & Fault Tolerant Design
Solr makes it easy to scale up and down as it is built on the reliable Apache Zookeeper. In addition to that, it also offers replication, distribution, rebalancing and fault tolerance out of the box. The fault tolerance feature makes it extremely reliable as it implies the platform continues operation even if one or more of its components fail.
5] Extensive Plugin Architecture
In addition to scalability, Solr also offers high levels of customization. To begin with, it is an Apache-licensed open source platform that allows developers to change any code they want. Developers can load custom code to perform additional tasks within the platform, such as custom Request Handlers and custom Token filters. It also publishes various well-defined extension points to facilitate both index and query time plugins.
6] Geospatial Search
Solr supports location data for use in spatial and geospatial searches. Using the former feature, you can index points or other shapes and or set a rectangular box, a circle or any other shape as a filter for your query results. Talking about geospatial search, you can use it to find places, say a Mexican restaurant, within a specified distance of your current location.
Apache Solr, with its advanced search capabilities, is a highly preferred search platform for a range of websites and applications. Its powerful external configuration allows it to be configured to any and every application, making it an indispensable tool for enterprises to cope with Big Data.
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ABOUT THE AUTHOR
Elise Lowry is a technical writer and a web entrepreneur with many years of experience. She regularly blogs about rising IT companies, path breaking IT solutions, current IT trends and much more. Understanding how technology affects the world we live in, is her subject of interest.