Performance compared to Mongoose

[zacharynevin]

I made a minor addition to my initial pull request (small error where leftKeys.split('.') should have been leftKeys[0].split('.')) and it works perfectly on my system in doing nested joins.

My question is: do you know the performance of this compared to the ad-hoc joins performed in Mongoose? I never cared much for ORMs or ODMs, but I was just curious.

[khous]

I don't know offhand what the performance difference is. Also sorry about
the delay in accepting the merge request.
On Jun 23, 2014 8:46 PM, "zacharynevin" notifications@github.com wrote:

I made a minor addition to my initial pull request (small error where
leftKeys.split('.') should have been leftKeys[0].split('.')) and it works
perfectly on my system in doing nested joins.

My question is: do you know the performance of this compared to the ad-hoc
joins performed in Mongoose? I never cared much for ORMs or ODMs, but I
was just curious.

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#8.

[zacharynevin]

I notice as well that there is no way to select the columns wanted from the joining collection. I can create a new pull request for this.

[khous]

Yeah that's a good idea. A lot of web frameworks support field filtering.
On Jun 23, 2014 8:55 PM, "zacharynevin" notifications@github.com wrote:

I notice as well that there is no way to select the columns wanted from
the joining collection. I can create a new pull request for this.

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#8 (comment)
.

[zacharynevin]

Yeah it would be especially useful if you are joining on a user's table, which is probably the most common use case for this.

[zacharynevin]

At first glance it looks like I just need to add a projection operator to the getSubqueries function. Does this sound correct?

[khous]

Not sure. I'm on my phone right now, but yes a projection will work. As
long as the join fields are returned as well.
On Jun 23, 2014 9:00 PM, "zacharynevin" notifications@github.com wrote:

At first glance it looks like I just need to add a projection operator to
the getSubQueries function. Does this sound correct?

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#8 (comment)
.