Fix data post API call to fix inconsistencies, like typos? - arrays

Question

Ok, so this is going to be a complicated question, I hope I'm clear. Full admission, I just finished a Bootcamp yesterday so I'm not aware of a lot of technologies out there, and I think I may need additional technologies to accomplish what I'm looking for...
Right now, I have an application that uses bandsintown API call to populate a database. What I've noticed is that bandsintown isn't consistent with their data returns in each object, which makes operations after retrieving the objects difficult/seemingly impossible. An example would be that different artists performing at the same venue returns different latitude, longitude, venue name, etc. Examples:
Here is Primus playing at Bonnaroo:
{
"offers": [],
"venue": {
"country": "United States",
"city": "Manchester",
"latitude": "35.4839582",
"name": "Bonnaroo Music and Arts Festival 2020",
"location": "",
"region": "TN",
"longitude": "-86.08963169999998"
},
"datetime": "2020-09-25T12:00:00",
"on_sale_datetime": "",
"description": "",
"lineup": [
"Primus"
],
"bandsintown_plus": false,
"id": "1020701795",
"title": "",
"artist_id": "1263",
"url": "https://www.bandsintown.com/e/1020701795?app_id=451f31b2808001d069daed45c32a9dac&came_from=267&utm_medium=api&utm_source=public_api&utm_campaign=event"
}
compared to The Weeknd playing at Bonnaroo:
{
"id": "18604416",
"url": "https://www.bandsintown.com/e/18604416?app_id=451f31b2808001d069daed45c32a9dac&came_from=267&utm_medium=api&utm_source=public_api&utm_campaign=event",
"datetime": "2017-05-17T19:00:00",
"title": "",
"description": "",
"venue": {
"location": "",
"name": "Bonnaroo",
"latitude": "35.476247",
"longitude": "-86.081026",
"city": "Manchester",
"country": "United States",
"region": "TN"
},
"lineup": [
"The Weeknd"
],
"offers": [],
"artist_id": "1371750",
"on_sale_datetime": "",
"bandsintown_plus": false
}
My issue is now I wish to aggregate and $group in MongoDB because both events were at Bonnaroo, but the Object{venue.name} is not the same... Even the latitude & longitude is different so I can't use those either. I'm wondering if there is a way to alter the data of the objects automatically without having to go into the DB and edit individual objects. Both these events include the word Bonnaroo, so could I have something find and match text and then slice out the text that isn't similar? If so, can I then use the matched venue name field as a reference to change the latitude & longitude values too?
I hope I was clear, feel free to ask any clarifying questions if I wasn't. This site has helped me so many times and I appreciate all the hard work the community puts in to help each other! Thanks ahead of time!
~~~EDIT~~~
Thanks for the first reply #morad takhtameshloo.
So I was able to build something before I saw your reply that splits the data into an array, which is along the same lines as what you offered. The only thing that won't work is the $arrayToElem with the index cause there are some venues that:
Have multiple-word names (e.g. The Stone Pony)
Have words before the actual venue name (saw it in one result that was like
"Verizon Live Presents at The Stony Pony")
Using this Bonnaroo example, I have the new field returning every word as a value in the array:
"venueName": ["Bonnaroo", "Music", "and","Arts","Festival","2020"]
My next step is going to be to compare the [venueName] of the 'Primus' object and the 'The Weeknd' object, find what values in the array are the same, and return them back to the value of "venueName".
Hope this makes more sense, I appreciate your input!

Answer 1

actual the trick depends to your data, you should provide more data if the ones you've provided does not depict the whole problem
in other words how deep you want to dive in.
for the dumbest answer, at least for the data you've provided
db.prod4.aggregate([
{
$addFields: {
venueName: {
$arrayElemAt: [{ $split: ['$venue.name', ' '] }, 0],
},
},
},
])
but that not the case of course, something that comes to mind is that venue's geolocations for the same venue should not be far away from each other, for instance, the data you've provided two locations are in 1.16 KM of each other.
so another dummy solution that works would be writing a simple script that selects a random element from the array of all data, and finds data that their lat/lng is for example in 2km of that point, and removes those elements from array and selects another random element from the array and do the same
if you provide more data it would be much more easier, because the easiest solution is to find many patterns and plan only for them