- Apache Solr - Faceting
- Apache Solr - Querying Data
- Apache Solr - Retrieving Data
- Apache Solr - Deleting Documents
- Apache Solr - Updating Data
- Apache Solr - Adding Docs (XML)
- Apache Solr - Indexing Data
- Apache Solr - Core
- Apache Solr - Basic Commands
- Apache Solr - Terminology
- Apache Solr - Architecture
- Apache Solr - On Hadoop
- Apache Solr - Windows Environment
- Apache Solr - Search Engine Basics
- Apache Solr - Overview
- Apache Solr - Home
Apache Solr Useful Resources
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- Questions and Answers
- UPSC IAS Exams Notes
Apache Solr - Overview
Solr is an open-source search platform which is used to build search apppcations. It was built on top of Lucene (full text search engine). Solr is enterprise-ready, fast and highly scalable. The apppcations built using Solr are sophisticated and depver high performance.
It was Yonik Seely who created Solr in 2004 in order to add search capabipties to the company website of CNET Networks. In Jan 2006, it was made an open-source project under Apache Software Foundation. Its latest version, Solr 6.0, was released in 2016 with support for execution of parallel SQL queries.
Solr can be used along with Hadoop. As Hadoop handles a large amount of data, Solr helps us in finding the required information from such a large source. Not only search, Solr can also be used for storage purpose. Like other NoSQL databases, it is a non-relational data storage and processing technology.
In short, Solr is a scalable, ready to deploy, search/storage engine optimized to search large volumes of text-centric data.
Features of Apache Solr
Solr is a wrap around Lucene’s Java API. Therefore, using Solr, you can leverage all the features of Lucene. Let us take a look at some of most prominent features of Solr −
Restful APIs − To communicate with Solr, it is not mandatory to have Java programming skills. Instead you can use restful services to communicate with it. We enter documents in Solr in file formats pke XML, JSON and .CSV and get results in the same file formats.
Full text search − Solr provides all the capabipties needed for a full text search such as tokens, phrases, spell check, wildcard, and auto-complete.
Enterprise ready − According to the need of the organization, Solr can be deployed in any kind of systems (big or small) such as standalone, distributed, cloud, etc.
Flexible and Extensible − By extending the Java classes and configuring accordingly, we can customize the components of Solr easily.
NoSQL database − Solr can also be used as big data scale NOSQL database where we can distribute the search tasks along a cluster.
Admin Interface − Solr provides an easy-to-use, user friendly, feature powered, user interface, using which we can perform all the possible tasks such as manage logs, add, delete, update and search documents.
Highly Scalable − While using Solr with Hadoop, we can scale its capacity by adding reppcas.
Text-Centric and Sorted by Relevance − Solr is mostly used to search text documents and the results are depvered according to the relevance with the user’s query in order.
Unpke Lucene, you don’t need to have Java programming skills while working with Apache Solr. It provides a wonderful ready-to-deploy service to build a search box featuring autocomplete, which Lucene doesn’t provide. Using Solr, we can scale, distribute, and manage index, for large scale (Big Data) apppcations.
Lucene in Search Apppcations
Lucene is simple yet powerful Java-based search pbrary. It can be used in any apppcation to add search capabipty. Lucene is a scalable and high-performance pbrary used to index and search virtually any kind of text. Lucene pbrary provides the core operations which are required by any search apppcation, such as Indexing and Searching.
If we have a web portal with a huge volume of data, then we will most probably require a search engine in our portal to extract relevant information from the huge pool of data. Lucene works as the heart of any search apppcation and provides the vital operations pertaining to indexing and searching.
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