Solr date range search- Easy for faceting data
Faceted search refers to the forceful clustering of items or various search results into groups that allow people into the search results by any type of value in any kind of field. Every facet exhibited also reveals the number of hits inside the search that match a particular group. The users are then facilitated to "drill down" by using particular constraints to the search outcomes. Moreover, faceted search is known as faceted navigation, faceted browsing, guided navigation and at times parametric search.
Faceted search offers an efficient method to permit the users to filter search results constantly and searching down till the preferred items are located. The advantages of faceted search include:
• Advanced feedback
The users are able to see at a glance, a gist of the search results and how these search results break down by various criteria.
• No dead ends
The users get to know how many search results go with, prior to their clicking. The values with zero counts are usually eliminated to mitigate the visual noise and remove the chance of a user selecting by chance, a constraint that will direct to no results.
• No selection hierarchy is forced
The users are usually free to insert or eliminate constraints in any order.
It is comparatively very simple to access faceting information from Solr date range search, because there exist a few prerequisites. The Solr provides the following kinds of faceting, all of them could be requested with no previous configuration:
• Field faceting
This enables to get back the counts for all the terms or for only the top terms in any type of field. But the field ought to be indexed.
• Query faceting
These permits to send back the number of documents in the present search results that also go with the given query.
• Date faceting
This allows sending back the number of documents that come under some Solr date range search.
The faceting instructions are included in any usual Solr query request, and the faceting counts return to similar query response.
Apart from indexing the data, several of the sophisticated full text search systems, including Solr, facilitates you to store and get back the information in its original fashion. The reason is that it enables to match a search result list with the original data. The chosen documents or records are often retrieved from their actual location, but you can also store up the complete document or record in the search system and see it from inside the system.
Faceted search offers an efficient method to permit the users to filter search results constantly and searching down till the preferred items are located. The advantages of faceted search include:
• Advanced feedback
The users are able to see at a glance, a gist of the search results and how these search results break down by various criteria.
• No dead ends
The users get to know how many search results go with, prior to their clicking. The values with zero counts are usually eliminated to mitigate the visual noise and remove the chance of a user selecting by chance, a constraint that will direct to no results.
• No selection hierarchy is forced
The users are usually free to insert or eliminate constraints in any order.
It is comparatively very simple to access faceting information from Solr date range search, because there exist a few prerequisites. The Solr provides the following kinds of faceting, all of them could be requested with no previous configuration:
• Field faceting
This enables to get back the counts for all the terms or for only the top terms in any type of field. But the field ought to be indexed.
• Query faceting
These permits to send back the number of documents in the present search results that also go with the given query.
• Date faceting
This allows sending back the number of documents that come under some Solr date range search.
The faceting instructions are included in any usual Solr query request, and the faceting counts return to similar query response.
Apart from indexing the data, several of the sophisticated full text search systems, including Solr, facilitates you to store and get back the information in its original fashion. The reason is that it enables to match a search result list with the original data. The chosen documents or records are often retrieved from their actual location, but you can also store up the complete document or record in the search system and see it from inside the system.
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