Thoughts on hashing optimizations

Your hasing function looks like the hashCode algorhythm. That correct?

Hypothetically

Would you be willing to have any dependencies? Would you be willing to have different dependencies for the npm/node.js version?

• murmurhash3 (pure javascript) is about 140% as fast as hashCode.
• cityhash (c++ node.js module) is about 280% as fast as hashCode

[kofrasa]

Hi Ben,

I think your request sounds reasonable. Different use cases may need different hashing guarantees.

I will take a look at the PR soon.

Regards, Francis

On Mon, Nov 30, 2020 at 6:25 PM Benjamin DANIEL [e-mail] wrote:

Here a fork to avoid hash collision, but loosing performances : https://github.com/BenjD90/mingo

Here an exemple of processing error that it avoid :

import mingo from ‘mingo’ const collection = [ { “codes”: [“KNE_OC42-midas”] }, { “codes”: [“KNE_OCS3-midas”] }]; const criteria = { “codes”: { “$in”: [“KNE_OCS3-midas”] }}; console.log(---- START ----); let query = new mingo.Query(criteria)const cursor = query.find(collection) // print all match, should match only the 2ndwhile (cursor.hasNext()) { console.log(cursor.next())} console.log(---- END ----) /* Output :---- START ----{ codes: [ ‘KNE_OC42-midas’ ] }{ codes: [ ‘KNE_OCS3-midas’ ] }---- END ----*/

I’ll try do make de PR soon, to allow user to give it’s own hash function, and tell it in the documentation.

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[kofrasa]

After some tweaks and a few more runs, it turns out the XOR version of the djb2 algorithm provides better performance per collision. [UPDATE] hashCode still performs better