PluralSight.Implement.Full.text.Search.in.Couchbase-BOOKWARE-KNiSO

Section

Appz

Group

KNiSO

Size

373,23 MB

Files

29

Date

2020-07-08

NFO

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                              PROUDLY PRESENTING:
                    
                   Implement.Full.text.Search.in.Couchbase



				 INFORMATION:

  Date............: 2020-07-08
  Rars............: 27 Rar Files
  Course Length...: 2 hrs 48 mins
  Website.........: https://app.pluralsight.com/library/courses/implement-full-text-search-couchbase

			      Release Notes...:
                                                                              
  When using Couchbase to store documents containing text data, you would like the 
  ability to search within those documents with natural language capabilities. This 
  is precisely what the Couchbase Full Text Service has to offer. In this course, 
  Implement Full-text Search in Couchbase, you will delve into how full-text indexes 
  work in Couchbase and how these indexes can be created, used and configured. First, 
  you will begin by exploring how full-text searches in general rank documents for each 
  query which is sent to them. This includes concepts such as term frequency and inverse 
  document frequency. Next, you will get hands-on and build full-text indexes in a 
  Couchbase cluster and submit a variety of queries to them. Then, you will move on to 
  how full-text searches are likely to be performed from an application - by submitting 
  search requests using N1QL queries and the Couchbase REST API. Finally, you will 
  explore the use of analyzers and filters to only include specific words and terms 
  within a full-text index. When you are finished with this course, you will be 
  well-versed in the options available to build, use, and configure full-text indexes 
  in Couchbase. This will give you the skills needed to speed up text-based searches 
  against the data in your Couchbase cluster, and deliver better search results to 
  your end users.

			      Install Notes...: 
			 Unrar, Learn and Enjoy!                                                                            
                                                     
                         
			      GREETINGS:

 - KNOWN - HONOR - SKIDROW - DARKSiDERS - DAUDiO - JAVSiDERS - dbOOk - z0ne -
        

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