Powering numerous internet websites across the globe with its superior navigation and search features, the Apache Solr has emerged as one of the biggest enablers in indexing in real time and extensive full-text searching. Being an open source search platform, the Apache Solr searches the stored data in the Hadoop’s HDFS. The Solr has made it possible for users to search any kind of data very quickly; this includes Hadoop’s sensor data, tabular data, geolocation and text. This search platform is optimized for the websites that receive huge traffic on regular basis.
The documents are inserted in the Apache Solr by Hadoop operators. The process is done by rapid indexing through JSON, Binary, CSV or XML over HTTP. Once this is done, the petabytes of data can be searched by the users through HTTP GET. The results can be accessed in CSV, JSON, Binary or XML.
How Apache Solr Works?
While written in Java, the Apache Solr works as a full-text search server in a servlet container like Jetty. At the center of search and full-text indexing, the Solr ropes in Apache Lucene Java search library. What makes it even easier to use along with various programming languages is its REST-like JSON and HTTP / XML APIs. Having a strong configuration externally, the Solr can be customized with almost all applications without Java coding. Moreover, extensive plugin architecture is available to cater the need of the advanced level of customization.
To set up of a group of Solr servers, Apache Solr utilizes a deployment methodology called SolrCloud, which is a combination of high availability and fault tolerance. Along with providing automated failover for queries in case of SolrCloud server failure, it also offers search capabilities and distributed indexing. However, for the purpose of cluster coordination and configuration, SolrCloud makes use of Apache ZooKeeper.
Apache Solr Features:-
1. Advanced Full-Text Search Capabilities
Collaborating with Apache Lucene, the Solr is inbuilt with excellent matching capabilities comprising joins, groupings, wildcards and phrases and various other data types.
2. Easy Monitoring
The server statistics in the form of metric data are exposed over JMX to give better and valuable insights of the Solr instances.
3. Optimised For High Traffic Volumes
The seamless working of Apache Solr has been well tested to cater extremely high volumes of traffic on the global platform.
4. Standards Based Open Interfaces
Solr makes use of the standards based open interfaces like HTTP, JSON, and XML to ease the process of application building.
5. Extremely Scalable & Fault Tolerant
Powered by the highly reliable Apache ZooKeeper, scaling up and down with Solr is no more a rewarding task. Apache Solr efficiently ropes in features like distribution, replication, fault tolerance and rebalancing.
6. Near Real Time Indexing
By banking on the Lucene’s near real-time indexing capabilities, Apache Solr allows viewing the updates and content whenever the user wants to.
7. Comprehensible HTML Administration Interfaces
Getting full control of the Solr instances is very easy as it comes integrated with a built-in and fully responsive administrative user interface in HTML format.
8. Easy Configuration, Flexible & Adaptable
Along with simplifying the configuration, the Solr is designed to match all the needs as it is linearly scalable, supports auto index replication, auto failover, and recovery.
9. Extensible Plugin Architecture
Through publishing many well-structured extension points, Solr makes it easy to plugin the query time and index plugins. Additionally, the Solr is an open source licensed by Apache and hence codes can be changed whenever required by the user.
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