Updated April 7, 2023
What is Apache Solr?
Apache Lucene is an open-source, Java-based Full-Text search library that makes it easier to incorporate search functionality in any application. Lucene was originally developed by Doug Cutting who is also a co-founder of Apache Hadoop, which is used widely for Storing and Processing large volumes of data. Apache Solr is an open-source, enterprise search platform based on Apache Lucene which is used to create search-based functionality on the application and various search applications. It’s basically a layer on top of Java-based Lucene with added functionality and in 2010 Solr and Lucene were merged.
Apache Solr is widely used alongside Hadoop as it deals with large sets of data and Solr enables the search aspect of it. As Solr can also store data it is a NoSQL, Non-Relational Storage, and processing technology.
Need for Apache Solr
Here are some of the need for apache solr which are explained below:
- The ability is to search the most basic requirement of a modern-day Application. For long, enterprises had an inherent problem relating to search their databases and applications.
- They created highly structured SQL based data that followed the natural path for search results through sequencing. This was complex, time-consuming and mostly came up with irrelevant results. The end-user had only one thing in mind and that is relevant results. With Solr based search applications, results are relevant and lazing fast.
- Solr processes structured, semi-structured and unstructured data from various sources and provide search results in Real-time. It is also used for its analytical capabilities as explained earlier as it’s not just a search platform but can-do tasks like Social Media analytics.
- Apache Solr is also a customizable search system that allows us to have full control over what needs to be crawled on the website and what database can be accessed and if any pre or post-processing needs to be done with the results.
- Also, like MySQL, Solr is a server-based application that can be hosted on Linux based servers. Solr works with HTTP Extensible Markup Language (XML). It offers JSON APIs and libraries for Programming languages like C#, PHP, Python, and Ruby.
- To put simply Solr is a stale, reliable, Fault-tolerant search platform with a rich set of features unlike any other platform and therefore used and trusted by major MNCs and especially Technology companies like Yahoo, Facebook, Google, and others.
How Apache Solr Works?
Solr follows a three-step process of Indexing, Querying, and Ranking.
1. Indexing
There are various methods through which Solr indexes documents and other rich text-based data. One of the advantages of Solr is that it allows users to directly upload their documents in PDF, CSV, XML formats and the system can read and index data from these sources automatically. Further, it can also upload texts and documents from Email and Attachments.
Solr uses an inverted index to store data where it uses Keyword centric rather than Page centric data structure; a simpler way to understand the concept is how words are indexed at the end of any book where the word on the page is mentioned along with its meaning. Hence, it can achieve a faster response time and gives relevant search results in no time.
2. Querying
A Query can be anything like searching for text, Images, or geolocation. When a query is sent, Solr processes it with a query handler which returns the document from the Solr Index.
3. Ranking the Results
As the system is matching the Query with the data from the indexed files based on keywords; it ranks the results based on relevance. This process creates a hierarchy of results based on relevance.
Applications of Apache Solr
As discussed, Solr is a very scalable, quick, and relevant solution that has become critical to enterprise success. Besides strong search features, it also provides a roust gamut of Analytical features. Apart from Technology and Social Media companies, it’s used in almost all other sectors like Finance, Retail, Manufacturing, Legal and Governmental. It’s used by almost all Fortune 500 Companies.
There are several use cases for Solr like:
- Enterprise can use Solr to search and analyze documents and Email attachments to gain meaningful insights.
- It can be used in Healthcare by researchers to march countless DNA patterns and also doctors to find anomalies and cure a Patient or prescribe drugs analyzing patterns.
- Hiring Managers in Human Resources can scan and analyze various CVs to find certain keywords from the countless number of documents.
- In Finance also the possibilities are endless where Bankers, Analysts can track and predict certain customers by analyzing past behavior towards savings or spending and design financial products or create complex models using macro-economic concepts.
- By tracking data from various technologies like Geo Tagging and Motion sensors it can track and give meaningful insights as to where to plan the next Theatre or the next Town Hall. The opportunities are endless.
Advantages and Disadvantages of Apache Solr
Some of the Advantages of Solr are explained below:
- Apart from simple Text-based searches Solr provides advanced, real-time searching capabilities such as GeoSpatial, Fielded Searches, Boolean queries, Fuzzy Queries, etc.
- It also provides comprehensive Administrative interfaces by a built-in user interface that enables managing adding, deleting, updating or searching documents.
- Its optimized for high traffic which is extremely for tech companies like Twitter, Facebook, etc. Which generates astronomical amounts of data every microsecond.
- Solr also has a smart search facility that auto-corrects a misspelled search and still projects relevant results for its user creating a great user experience.
- Search in Solr can be also highly configurable where the result can be subcategorized as requested by the user.
Although it is the most trusted and widely used Search platform for enterprises across the world, it still possesses certain disadvantages as:
- Solr being an Open source platform requires dedication and a general learning curve where certain developers can be used to a particular Commercial Search platform and transforming to an Open-source platform could require a lot of learning and workaround.
- Since Solr requires at least 8 GB of RAM, a number of old systems could not run it optimally and thereby companies could refuse to transition to Solr due to underfunding or System inadequacies.
Conclusion
Apache Solr is the backbone of any Enterprise which needs to incorporate the Search platform into its application. It has uses in almost all major industries and therefore the possibilities are endless and although it’s touted as a search platform it can perform analytical tasks with great complexity and with a user interface that’s second to none. Therefore, learning Solr along with other technologies like Hadoop and Big data Analytics is imperative for anyone looking for an interesting career in Data Science or ‘Search’ in any major Tech Companies.
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