Meteor JS Search Tool

Question

Im pretty new when it comes to db and search, so please bear with me. I am trying to implement a search function in a Meteor application. Ive checked the atmosphere and rated these 4 options.

• Matodem easy search
• Search source
• Elastic Atmosphere search package (heard it dated)
• Flexible large atmospheric dataset

My needs are for a simple search that can handle large datasets that nesting data might have. For example, a task may contain comments or links, etc. (Full text and a more regular request would be good)

I read that for a convenient search, even using some form of elastic or Mongolian application, it seems that this application is for only one Mongo collection? For example, what if I wanted to find Dinosaurs = new Meteor.Collection('dinosaurs'); and Mammals = new Meteor.Collection('mammals'); ?

Please rate any of the pros and cons of the four options above? 1 seems relatively easy to implement, but I'm not sure what that means using an elastic motor here . If I were to use elastic material, how do I do this in Meteor? And will it be different from the Elasticsearch HTTP API implementation?

Similarly for Source, it also supports Elastic. Honestly, I have no idea about the differences.

Answer 1

This github project demonstrates how to use Meteor with ElasticSearch (not Mongo) for search applications.

https://github.com/hharnisc/meteor-elasticsearch-demo/tree/master/elasticsearch-demo/packages/elastic-collection

it basically associates a field with a session variable that starts a search by elastic. The results are stored in the Mongo collection, which is transmitted to the client using Meteor mechanics. They are much smaller than a dataset and therefore are quickly updated.

As for assembly searches, this is a typical problem with defining a database schema. If you need to make connections, mongodb is not the best solution. and a relational database, like any SQL database, will be better suited. However, you should study the “denormalization” of your data to see if you can create a structure that will work well for your use case.

This article explains what this means:

http://blog.mongodb.org/post/87892923503/6-rules-of-thumb-for-mongodb-schema-design-part-2

Good luck.