QUERYING MONGODB: RETREIVE SHOPS BY NAME AND BY LOCATION WITH ONE SINGLE QUERY
Hi folks!
I'm building a "search shops" application using MEAN Stack.
I store shops documents in MongoDB "location" collection like this:
{
_id: .....
name: ...//shop name
location : //...GEOJson
}
UI provides to the users one single input for shops searching. Basically, I would perform one single query to retrieve in the same results array:
All shops near the user (eventually limit to x)
All shops named "like" the input value
On logical side, I think this is a "$or like" query
Based on this answer
Using full text search with geospatial index on Mongodb
probably assign two special indexes (2dsphere and full text) to the collection is not the right manner to achieve this, anyway I think this is a different case just because I really don't want to apply sequential filter to results, "simply" want to retreive data with 2 distinct criteria.
If I should set indexes on my collection, of course the approach is to perform two distinct queries with two distinct mehtods ($near for locations and $text for name), and then merge the results with some server side logic to remove duplicate documents and sort them in some useful way for user experience, but I'm still wondering if exists a method to achieve this result with one single query.
So, the question is: is it possible or this kind of approach is out of MongoDB purpose?
Hope this is clear and hope that someone can teach something today!
Thanks
Related
I am working on a database of Polish verbs and I'd like to find out how to display my results such that each verb conjugation appears in the following order: 1ps (1st person singular), 2ps, 3ps, 1ppl (1st person plural, etc.), 2ppl, 3ppl. It displays fine when I insert documents:
verb "żyć/przeżyć" conjugation as array and nested document
But when I go to perform queries it jumbles all the array elements up, in the first case (I want to see them in order of array indices), and sorts the nested document elements into alphabetical order (whereas I want to see them in the order in which they were inserted).
verb "żyć/przeżyć" conjugation array/document query
This should be an easy one to solve, I hope this comes across as a reasonable beginner's question. I have searched for answers but couldn't find much info on this topic. Any and all help is greatly appreciated!
Cheers,
LC.
Your screenshots highlight two different views in MongoDB Compass.
The Schema view is based on a sampling of multiple documents and the order of the fields displayed cannot be specified. The schema analysis (as at Compass 1.7) lists fields in case-insensitive alphabetical order with the _id field at the top. Since this is an aggregate schema view based on multiple documents, the ordering of fields is not expected to reflect individual document order.
If you want to work with individual documents and field ordering you need to use the Documents view, as per your second screenshot. In addition to displaying the actual documents, this view allows you to include sort and skip options for queries:
I have data across three collections and need to produce a data set which aggregates data from these collections, and filters by a date range.
The collections are:
db.games
{
_id : ObjectId,
startTime : MongoDateTime
}
db.entries
{
player_id : ObjectId, // refers to db.players['_id']
game_id : ObjectId // refers to db.games['_id']
}
db.players
{
_id : ObjectId,
screen_name,
email
}
I want to return a collection which is number of entries by player for games within a specified range. Where the output should look like:
output
{
player_id,
screen_name,
email,
sum_entries
}
I think I need to start by creating a collection of games within the date range, combined with all the entries and then aggregate over count of entries, and finally output collection with the player data, it's seems a lot of steps and I'm not sure how to go about this.
The reason why you have these problems is because you try to use MongoDB like a relational database, not like a document-oriented database. Normalizing your data over many collections is often counter-productive, because MongoDB can not perform any JOIN-operations. MongoDB works much better when you have nested documents which embed other objects in arrays instead of referencing them. A better way to organize that data in MongoDB would be to either have each game have an array of players which took part in it or to have an array in each player with the games they took part in. It's also not necessarily a mistake to have some redundant additional data in these arrays, like the names and not just the ID's.
But now you have the problem, so let's see how we can deal with it.
As I said, MongoDB doesn't do JOINs. There is no way to access data from more than one collection at a time.
One thing you can do is solving the problem programmatically. Create a program which fetches all players, then all entries for each player, and then the games referenced by the entries where startTimematches.
Another thing you could try is MapReduce. MapReduce can be used to append results to another collection. You could try to use one MapReduce job for each of the relevant collections into one and then query the resulting collection.
I am trying to fetch the documents from a collection based on the existence of a reference to these documents in another collection.
Let's say I have two collections Users and Courses and the models look like this:
User: {_id, name}
Course: {_id, name, user_id}
Note: this just a hypothetical example and not actual use case. So let's assume that duplicates are fine in the name field of Course. Let's thin Course as CourseRegistrations.
Here, I am maintaining a reference to User in the Course with the user_id holding the _Id of User. And note that its stored as a string.
Now I want to retrieve all users who are registered to a particular set of courses.
I know that it can be done with two queries. That is first run a query and get the users_id field from the Course collection for the set of courses. Then query the User collection by using $in and the user ids retrieved in the previous query. But this may not be good if the number of documents are in tens of thousands or more.
Is there a better way to do this in just one query?
What you are saying is a typical sql join. But thats not possible in mongodb. As you suggested already you can do that in 2 different queries.
There is one more way to handle it. Its not exactly a solution, but the valid workaround in NonSql databases. That is to store most frequently accessed fields inside the same collection.
You can store the some of the user collection fields, inside the course collection as embedded field.
Course : {
_id : 'xx',
name: 'yy'
user:{
fname : 'r',
lname :'v',
pic: 's'
}
}
This is a good approach if the subset of fields you intend to retrieve from user collection is less. You might be wondering the redundant user data stored in course collection, but that's exactly what makes mongodb powerful. Its a one time insert but your queries will be lot faster.
For example, we have two collections
users {userId, firstName, lastName}
votes {userId, voteDate}
I need a report of the name of all users which have more than 20 votes a day.
How can I write query to get data from MongoDB?
The easiest way to do this is to cache the number of votes for each user in the user documents. Then you can get the answer with a single query.
If you don't want to do that, the map-reduce the results into a results collection, and query that collection. You can then run incremental map-reduces that only calculate new votes to keep your results up to date: http://www.mongodb.org/display/DOCS/MapReduce#MapReduce-IncrementalMapreduce
You shouldn't really be trying to do joins with Mongo. If you are you've designed your schema in a relational manner.
In this instance I would store the vote as an embedded document on the user.
In some scenarios using embedded documents isn't feasible, and in that situation I would do two database queries and join the results at the client rather than using MapReduce.
I can't provide a fuller answer now, but you should be able to achieve this using MapReduce. The Map step would return the userIds of the users who have more than 20 votes, the reduce step would return the firstName and lastName, I think...have a look here.
I have 2 collections on 2 separate DBs. Both store an array field. I plan to query both at once so that:
All collection 1 documents that have elements [A,B] in their array
field and their _ids are present in collection 2's array field with a
specific document _id.
As an example:
docs (collection 1, DB 1):
[{"_id":ObjectId("doc1"), "array1":["A","B"]}, {"_id":ObjectId("doc2"), "array1":["A","C"]}]
user_docs (collection 2, DB 2):
[{"_id":ObjectId("usr1"), "array2": [ObjectId("doc1"),ObjectId("foo")]}, {"_id":ObjectId("usr2"), "array2": [ObjectId("bar"),ObjectId("baz")]}]
I need a query that given A,B and usr1, returns the 'doc1' object (because it has A,B in it's array1 field and usr1 has it in it's array2 field).
I obviously can fetch all docs having A,B in one query and all usr1's docs in another query and find the common elements at application level, but is there any better way of doing it using MongoDB?
Thanks for your help.
Ok im not sure i understand exactly what your trying to do from your description. But i dont understand why you would query data across db's this just seems very heavy handed to me why cant you store both the data sets in the same db. You can always separate later if required? Im not sure this will solve your vague problem but it would be a good place to start.
best of Luck.
You will have to query MongoDB twice, since you have no possibility of a join. You will have to do it on application level. If you can denormalize, do it. Cash the needed data in a embedded doc, so that you can do one query only.
I think #Eamonn is right, that you shouldn't have to do a query across DBs.