Lucid Imagination helped a large not-for-profit research institute streamline and standardize their Solr search implementation with:
On-site benchmark and analysis of Solr search framework and custom code modules
Best practices recommendations on scalable architecture and overall efficiencies
Guidance and assistance on setting up a replicated search environment
A large not-for-profit research institutes online collection offers one-stop searching of 2 million records, including nearly a quarter of a million media files (images, media files, online journals, and other resources) distributed across dozens of archives, databases, museums, and libraries. Both institutional and public researchers use the online search service.
The research institute had developed a broad set of customized search capabilities using Solr, enabling users to search across a very diverse set of information. Recently, the IT staff noticed that while most of the searches were very fast, some were very slow. Over time, the complicated taxonomy they had built.
The research institute engaged the following services from Lucid Imagination:
Search Health Check
ExpertLink consulting services
Lucid Imagination consultants did an in-depth analysis, reviewing Solr caches, identifying better ways to set up configuration files, and removing inefficient unused code. The consultants reviewed the institutes custom code modules to identify opportunities for efficiency gains, specifically those functions that can now be handled by native Solr, with a view to configuring for best practices.
Lucid also provided training to internal ITstaff. to bring them up to speed on the latest Solr capabilities, and establish better self-reliance for ongoing search application development and refinement. The training also included a focus on knowledge transfer, so that changes made during consulting on analysis and reconfiguration were well understood by the team at-large, and they could be take ownership of them and maintain them effectively going forward.
Lucid was also able to advise the institute on hierarchical facetingusing taxonomic information to create more detailed search results that are presented in a tree structure. Lucid also introduced the institute to search opportunities with geo-searching. While this capability is not yet in core Solr, Lucid was able to advise them on related projects and how best to make use of them.
All custom code developed by the institute’s IT staff was thoroughly reviewed and unused modules were removed to improve efficiency and performance. A comprehensive recommendation was made for a framework to improve scalability. Because there had been no backup of the search index, Lucid provided the institute with strategy for how to set up a redundant environment with a replication server, and helped coach the implementationfor example, providing recommendations on update intervals to balance performance needs and hardware requirements.
To know more about Open Source Search and Enterprise search check out Lucid Imagination website