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Editorial Team
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Asked: 2026-06-15T02:19:05+00:00

I am experimenting with Dojo’s dgrid (which is great!). I am using Nodejs/Mongoose on

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I am experimenting with Dojo’s dgrid (which is great!). I am using Nodejs/Mongoose on the server side.
I want to write a “log browser”: I have a big mongodb table containing lots of log entries; using dgrid, I want to be able to 1) Filter by certain parameters 2) Paginate using dgrid’s native pagination.

Hence the problem: dojo’s JsonRest stores will send a request like this:

Accept:application/javascript, application/json
Accept-Charset:ISO-8859-1,utf-8;q=0.7,*;q=0.3
...
Host:localhost:3000
Range:items=0-24

Hence the problem: it will give a range (that’s all it can do, really) and will display things on the client side according to what it receives from the server.
It’s unrealistic to expect a cliend side JsonRest object to make requests other than “ranges”. However, I am aware that skip/limit doesn’t go very well with Mongoose:

What is the best way to do ajax pagination with MongoDb and Nodejs?

My idea was to render the dgrid, allowing the users to pick filters, and let them happily paginate through their logs. However, the fact that skip/limit are out of question, I am in a bit of a pickle…

Any pearls of wisdom, other than ditch dgrid altogether and implementing pagination on my own without using Dojo stores?

Merc.

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1 Answer

  1. Editorial Team

    Front-end

    The filtering isn’t as feature-full in dgrid as it is in the dojo EnhancedGrid filter plugin so you will probably need to implement that part yourself.

    The good news is you get the paging simply by mixing-in “dgrid/OnDemandGrid” when you create your grid.

    Back-end

    The docs seem to indicate that your best bet for performance is to do some tricks with indices and query based on those to get your ranges.

    You are probably already referencing these, but here they are;
    http://mongoosejs.com/docs/api.html#query_Query-skip
    http://docs.mongodb.org/manual/reference/method/cursor.skip/

    Since log data is usually sequential and rarely modified, you could probably just use a monotonically increasing index for each row of log data and query using those to get the right offset into and count of the rows.

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