Let's say we query the server with this request, we only want to get the following user's Email, My current implementation requests the whole User object from the MongoDB, which I can imagine is extremely inefficient.
GQL
{
user(id:"34567345637456") {
email
}
}
How would you go about creating a MongoDB filter that would only return those Specified Fields? E.g,
JS object
{
"email": 1
}
My current server is running Node.js, Fastify and Mercurius
which I can imagine is extremely inefficient.
Doing this task is an advanced feature with many pitfalls. I would suggest starting building a simple extraction that read all the fields. This solution works and does not return any additional field to the client.
The pitfalls are:
nested queries
complex object composition
aliasing
multiple queries into one request
Here an example that does what you are looking for.
It manages aliasing and multiple queries.
const Fastify = require('fastify')
const mercurius = require('mercurius')
const app = Fastify({ logger: true })
const schema = `
type Query {
select: Foo
}
type Foo {
a: String
b: String
}
`
const resolvers = {
Query: {
select: async (parent, args, context, info) => {
const currentQueryName = info.path.key
// search the input query AST node
const selection = info.operation.selectionSet.selections.find(
(selection) => {
return (
selection.name.value === currentQueryName ||
selection.alias.value === currentQueryName
)
}
)
// grab the fields requested by the user
const project = selection.selectionSet.selections.map((selection) => {
return selection.name.value
})
// do the query using the projection
const result = {}
project.forEach((fieldName) => {
result[fieldName] = fieldName
})
return result
},
},
}
app.register(mercurius, {
schema,
resolvers,
graphiql: true,
})
app.listen(3000)
Call it using:
query {
one: select {
a
}
two: select {
a
aliasMe:b
}
}
Returns
{
"data": {
"one": {
"a": "a"
},
"two": {
"a": "a",
"aliasMe": "b"
}
}
}
Expanding from #Manuel Spigolon original answer, where he stated that one of the pitfalls of his implementation is that it doesn't work on nested queries and 'multiple queries into one request' which this implementation seeks to fix.
function formFilter(context:any) {
let filter:any = {};
let getValues = (selection:any, parentObj?:string[]) => {
//selection = labelSelection(selection);
selection.map((selection:any) => {
// Check if the parentObj is defined
if(parentObj)
// Merge the two objects
_.merge(filter, [...parentObj, null].reduceRight((obj, next) => {
if(next === null) return ({[selection.name?.value]: 1});
return ({[next]: obj});
}, {}));
// Check for a nested selection set
if(selection.selectionSet?.selections !== undefined){
// If the selection has a selection set, then we need to recurse
if(!parentObj) getValues(selection.selectionSet?.selections, [selection.name.value]);
// If the selection is nested
else getValues(selection.selectionSet?.selections, [...parentObj, selection.name.value]);
}
});
}
// Start the recursive function
getValues(context.operation.selectionSet.selections);
return filter;
}
Input
{
role(id: "61f1ccc79623d445bd2f677f") {
name
users {
user_name
_id
permissions {
roles
}
}
permissions
}
}
Output (JSON.stringify)
{
"role":{
"name":1,
"users":{
"user_name":1,
"_id":1,
"permissions":{
"roles":1
}
},
"permissions":1
}
}
I am trying to do what should be a rather simple operation in my mongoDB/Node environment. Every document in the collection I'm targeting has a field "openBalance", which is a number value. All I want to do is find the totalOpenBalance by adding all of those together.
So far, in reviewing the MongoDB documentation, both $add and $sum seem to be used to perform an operation on the individual documents within the collection, rather than on the collection itself.
This leads me to wonder, is there a different way I should approach this? I've tried numerous constructions, but none work. Here is my function in full:
exports.getClientData = async function (req, res, next) {
let MongoClient = await require('../config/database')();
let db = MongoClient.connection.db;
let search, skip, pagesize, page, ioOnly = false, client;
let docs = [];
let records = 0;
if (_.isUndefined(req.params)) {
skip = parseInt(req.skip) || 0;
search = JSON.parse(req.search);
pagesize = parseInt(req.pagesize) || 0;
page = parseInt(req.page) || 0;
client = req.client || '';
ioOnly = true;
}
else {
skip = parseInt(req.query.skip) || 0;
search = req.body;
pagesize = parseInt(req.query.pagesize) || 0;
page = parseInt(req.query.page) || 0;
client = req.query.client || '';
}
search = {};
if (skip === 0) {
skip = page * pagesize;
}
if (client) {
let arrClient = [];
arrClient = client.split(",");
if (arrClient) {
// convert each ID to a mongo ID
let mongoArrClient = arrClient.map(client => new mongo.ObjectID(client));
if (mongoArrClient) {
search['client._id'] = { $in: mongoArrClient };
}
}
}
console.log(search);
let counter = 0;
let count = await db.collection('view_client_data').find(search).count();
let totalClients = await db.collection('view_client_data').find(search).count({ $sum: "client._id" });
console.log('totalClients', totalClients);
let totalOpenBalance = await db.collection('view_client_data').find(search).count({ $sum: { "$add" : "openBalance" } });
console.log('totalOpenBalance', totalOpenBalance);
db.collection('view_client_data').find(search).skip(skip).limit(pagesize).forEach(function (doc) {
counter ++; {
console.log(doc);
docs.push(doc);
}
}, function (err) {
if (err) {
if (!ioOnly) {
return next(err);
} else {
return res(err);
}
}
if (ioOnly) {
res({ sessionId: sessID, count: count, data: docs, totalClients: totalClients, totalOpenBalance: totalOpenBalance });
}
else {
res.send({ count: count, data: docs, totalClients: totalClients, totalOpenBalance: totalOpenBalance });
}
});
}
As you can see in the above code, I am getting the total number of clients with this code:
let totalClients = await db.collection('view_client_data').find(search).count({ $sum: "client._id" });
console.log('totalClients', totalClients);
That works perfectly, adding up the instances of a client and giving me the total.
Again, to be crystal clear, where I'm running into a problem is in summing up the numerical value for all of the openBalance values. Each document has a field, openBalance. All I want to do is add those up and output them in a variable titled totalOpenBalance and pass that along in the response I send, just like I do for totalClients. I have tried numerous options, including this:
let totalOpenBalance = await db.collection('view_client_data').find(search).count({ $sum: { "$add" : "openBalance" } });
console.log('totalOpenBalance', totalOpenBalance);
and this:
let totalOpenBalance = await db.collection('view_client_data').find(search).aggregate({ $sum: { "$add" : "openBalance" } });
console.log('totalOpenBalance', totalOpenBalance);
... but as I say, none work. Sometimes I get a circular reference error, sometimes an aggregate is not a function error, other times different errors. I've been wracking my brain trying to figure this out -- and I assume it shouldn't be that complicated once I understand the required syntax. How can I get my totalOpenBalance here?
By the way, the documents I'm targeting look something like this:
{
"_id": "3hu40890sf131d361f1ad908",
"client": {
"_id": "4ft9d366121j04563be0b01d6",
"name": {
"first": "John",
"last": "Smith"
}
},
"openBalance": 128,
"lastPurchaseDate": "2018-01-19T00:00:00.000Z"
},
$sum is an accumulator operator that must appear within a $group or $project aggregate pipeline stage. To also incorporate your search filter, you can include a $match stage in your pipeline.
let result = await db.collection('view_client_data').aggregate([
{$match: search},
{$group: {_id: null, totalOpenBalance: {$sum: '$openBalance'}}}
]).next();
console.log(result.totalOpenBalance);
I think $group is what you're looking for.
So for example to calculate all the openBalance fields
db.view_client_data.aggregate(
[
{
$group: {
_id : null
totalOpenBalance: { $sum: "$openBalance" },
}
}
]
)
this should give you an object back like {totalOpenBalance: 900}
Here is the mongodb documentation for some more examples
https://docs.mongodb.com/manual/reference/operator/aggregation/group/#pipe._S_group
I'd like to get the names of all the keys in a MongoDB collection.
For example, from this:
db.things.insert( { type : ['dog', 'cat'] } );
db.things.insert( { egg : ['cat'] } );
db.things.insert( { type : [] } );
db.things.insert( { hello : [] } );
I'd like to get the unique keys:
type, egg, hello
You could do this with MapReduce:
mr = db.runCommand({
"mapreduce" : "my_collection",
"map" : function() {
for (var key in this) { emit(key, null); }
},
"reduce" : function(key, stuff) { return null; },
"out": "my_collection" + "_keys"
})
Then run distinct on the resulting collection so as to find all the keys:
db[mr.result].distinct("_id")
["foo", "bar", "baz", "_id", ...]
With Kristina's answer as inspiration, I created an open source tool called Variety which does exactly this: https://github.com/variety/variety
You can use aggregation with the new $objectToArray aggregation operator in version 3.4.4 to convert all top key-value pairs into document arrays, followed by $unwind and $group with $addToSet to get distinct keys across the entire collection. (Use $$ROOT for referencing the top level document.)
db.things.aggregate([
{"$project":{"arrayofkeyvalue":{"$objectToArray":"$$ROOT"}}},
{"$unwind":"$arrayofkeyvalue"},
{"$group":{"_id":null,"allkeys":{"$addToSet":"$arrayofkeyvalue.k"}}}
])
You can use the following query for getting keys in a single document.
db.things.aggregate([
{"$match":{_id: "<<ID>>"}}, /* Replace with the document's ID */
{"$project":{"arrayofkeyvalue":{"$objectToArray":"$$ROOT"}}},
{"$project":{"keys":"$arrayofkeyvalue.k"}}
])
A cleaned up and reusable solution using pymongo:
from pymongo import MongoClient
from bson import Code
def get_keys(db, collection):
client = MongoClient()
db = client[db]
map = Code("function() { for (var key in this) { emit(key, null); } }")
reduce = Code("function(key, stuff) { return null; }")
result = db[collection].map_reduce(map, reduce, "myresults")
return result.distinct('_id')
Usage:
get_keys('dbname', 'collection')
>> ['key1', 'key2', ... ]
If your target collection is not too large, you can try this under mongo shell client:
var allKeys = {};
db.YOURCOLLECTION.find().forEach(function(doc){Object.keys(doc).forEach(function(key){allKeys[key]=1})});
allKeys;
If you are using mongodb 3.4.4 and above then you can use below aggregation using $objectToArray and $group aggregation
db.collection.aggregate([
{ "$project": {
"data": { "$objectToArray": "$$ROOT" }
}},
{ "$project": { "data": "$data.k" }},
{ "$unwind": "$data" },
{ "$group": {
"_id": null,
"keys": { "$addToSet": "$data" }
}}
])
Here is the working example
Try this:
doc=db.thinks.findOne();
for (key in doc) print(key);
Using python. Returns the set of all top-level keys in the collection:
#Using pymongo and connection named 'db'
reduce(
lambda all_keys, rec_keys: all_keys | set(rec_keys),
map(lambda d: d.keys(), db.things.find()),
set()
)
Here is the sample worked in Python:
This sample returns the results inline.
from pymongo import MongoClient
from bson.code import Code
mapper = Code("""
function() {
for (var key in this) { emit(key, null); }
}
""")
reducer = Code("""
function(key, stuff) { return null; }
""")
distinctThingFields = db.things.map_reduce(mapper, reducer
, out = {'inline' : 1}
, full_response = True)
## do something with distinctThingFields['results']
I am surprise, no one here has ans by using simple javascript and Set logic to automatically filter the duplicates values, simple example on mongo shellas below:
var allKeys = new Set()
db.collectionName.find().forEach( function (o) {for (key in o ) allKeys.add(key)})
for(let key of allKeys) print(key)
This will print all possible unique keys in the collection name: collectionName.
I think the best way do this as mentioned here is in mongod 3.4.4+ but without using the $unwind operator and using only two stages in the pipeline. Instead we can use the $mergeObjects and $objectToArray operators.
In the $group stage, we use the $mergeObjects operator to return a single document where key/value are from all documents in the collection.
Then comes the $project where we use $map and $objectToArray to return the keys.
let allTopLevelKeys = [
{
"$group": {
"_id": null,
"array": {
"$mergeObjects": "$$ROOT"
}
}
},
{
"$project": {
"keys": {
"$map": {
"input": { "$objectToArray": "$array" },
"in": "$$this.k"
}
}
}
}
];
Now if we have a nested documents and want to get the keys as well, this is doable. For simplicity, let consider a document with simple embedded document that look like this:
{field1: {field2: "abc"}, field3: "def"}
{field1: {field3: "abc"}, field4: "def"}
The following pipeline yield all keys (field1, field2, field3, field4).
let allFistSecondLevelKeys = [
{
"$group": {
"_id": null,
"array": {
"$mergeObjects": "$$ROOT"
}
}
},
{
"$project": {
"keys": {
"$setUnion": [
{
"$map": {
"input": {
"$reduce": {
"input": {
"$map": {
"input": {
"$objectToArray": "$array"
},
"in": {
"$cond": [
{
"$eq": [
{
"$type": "$$this.v"
},
"object"
]
},
{
"$objectToArray": "$$this.v"
},
[
"$$this"
]
]
}
}
},
"initialValue": [
],
"in": {
"$concatArrays": [
"$$this",
"$$value"
]
}
}
},
"in": "$$this.k"
}
}
]
}
}
}
]
With a little effort, we can get the key for all subdocument in an array field where the elements are object as well.
This works fine for me:
var arrayOfFieldNames = [];
var items = db.NAMECOLLECTION.find();
while(items.hasNext()) {
var item = items.next();
for(var index in item) {
arrayOfFieldNames[index] = index;
}
}
for (var index in arrayOfFieldNames) {
print(index);
}
Maybe slightly off-topic, but you can recursively pretty-print all keys/fields of an object:
function _printFields(item, level) {
if ((typeof item) != "object") {
return
}
for (var index in item) {
print(" ".repeat(level * 4) + index)
if ((typeof item[index]) == "object") {
_printFields(item[index], level + 1)
}
}
}
function printFields(item) {
_printFields(item, 0)
}
Useful when all objects in a collection has the same structure.
To get a list of all the keys minus _id, consider running the following aggregate pipeline:
var keys = db.collection.aggregate([
{ "$project": {
"hashmaps": { "$objectToArray": "$$ROOT" }
} },
{ "$group": {
"_id": null,
"fields": { "$addToSet": "$hashmaps.k" }
} },
{ "$project": {
"keys": {
"$setDifference": [
{
"$reduce": {
"input": "$fields",
"initialValue": [],
"in": { "$setUnion" : ["$$value", "$$this"] }
}
},
["_id"]
]
}
}
}
]).toArray()[0]["keys"];
I know I am late to the party, but if you want a quick solution in python finding all keys (even the nested ones) you could do with a recursive function:
def get_keys(dl, keys=None):
keys = keys or []
if isinstance(dl, dict):
keys += dl.keys()
list(map(lambda x: get_keys(x, keys), dl.values()))
elif isinstance(dl, list):
list(map(lambda x: get_keys(x, keys), dl))
return list(set(keys))
and use it like:
dl = db.things.find_one({})
get_keys(dl)
if your documents do not have identical keys you can do:
dl = db.things.find({})
list(set(list(map(get_keys, dl))[0]))
but this solution can for sure be optimized.
Generally this solution is basically solving finding keys in nested dicts, so this is not mongodb specific.
Based on #Wolkenarchitekt answer: https://stackoverflow.com/a/48117846/8808983, I write a script that can find patterns in all keys in the db and I think it can help others reading this thread:
"""
Python 3
This script get list of patterns and print the collections that contains fields with this patterns.
"""
import argparse
import pymongo
from bson import Code
# initialize mongo connection:
def get_db():
client = pymongo.MongoClient("172.17.0.2")
db = client["Data"]
return db
def get_commandline_options():
description = "To run use: python db_fields_pattern_finder.py -p <list_of_patterns>"
parser = argparse.ArgumentParser(description=description)
parser.add_argument('-p', '--patterns', nargs="+", help='List of patterns to look for in the db.', required=True)
return parser.parse_args()
def report_matching_fields(relevant_fields_by_collection):
print("Matches:")
for collection_name in relevant_fields_by_collection:
if relevant_fields_by_collection[collection_name]:
print(f"{collection_name}: {relevant_fields_by_collection[collection_name]}")
# pprint(relevant_fields_by_collection)
def get_collections_names(db):
"""
:param pymongo.database.Database db:
:return list: collections names
"""
return db.list_collection_names()
def get_keys(db, collection):
"""
See: https://stackoverflow.com/a/48117846/8808983
:param db:
:param collection:
:return:
"""
map = Code("function() { for (var key in this) { emit(key, null); } }")
reduce = Code("function(key, stuff) { return null; }")
result = db[collection].map_reduce(map, reduce, "myresults")
return result.distinct('_id')
def get_fields(db, collection_names):
fields_by_collections = {}
for collection_name in collection_names:
fields_by_collections[collection_name] = get_keys(db, collection_name)
return fields_by_collections
def get_matches_fields(fields_by_collections, patterns):
relevant_fields_by_collection = {}
for collection_name in fields_by_collections:
relevant_fields = [field for field in fields_by_collections[collection_name] if
[pattern for pattern in patterns if
pattern in field]]
relevant_fields_by_collection[collection_name] = relevant_fields
return relevant_fields_by_collection
def main(patterns):
"""
:param list patterns: List of strings to look for in the db.
"""
db = get_db()
collection_names = get_collections_names(db)
fields_by_collections = get_fields(db, collection_names)
relevant_fields_by_collection = get_matches_fields(fields_by_collections, patterns)
report_matching_fields(relevant_fields_by_collection)
if __name__ == '__main__':
args = get_commandline_options()
main(args.patterns)
As per the mongoldb documentation, a combination of distinct
Finds the distinct values for a specified field across a single collection or view and returns the results in an array.
and indexes collection operations are what would return all possible values for a given key, or index:
Returns an array that holds a list of documents that identify and describe the existing indexes on the collection
So in a given method one could do use a method like the following one, in order to query a collection for all it's registered indexes, and return, say an object with the indexes for keys (this example uses async/await for NodeJS, but obviously you could use any other asynchronous approach):
async function GetFor(collection, index) {
let currentIndexes;
let indexNames = [];
let final = {};
let vals = [];
try {
currentIndexes = await collection.indexes();
await ParseIndexes();
//Check if a specific index was queried, otherwise, iterate for all existing indexes
if (index && typeof index === "string") return await ParseFor(index, indexNames);
await ParseDoc(indexNames);
await Promise.all(vals);
return final;
} catch (e) {
throw e;
}
function ParseIndexes() {
return new Promise(function (result) {
let err;
for (let ind in currentIndexes) {
let index = currentIndexes[ind];
if (!index) {
err = "No Key For Index "+index; break;
}
let Name = Object.keys(index.key);
if (Name.length === 0) {
err = "No Name For Index"; break;
}
indexNames.push(Name[0]);
}
return result(err ? Promise.reject(err) : Promise.resolve());
})
}
async function ParseFor(index, inDoc) {
if (inDoc.indexOf(index) === -1) throw "No Such Index In Collection";
try {
await DistinctFor(index);
return final;
} catch (e) {
throw e
}
}
function ParseDoc(doc) {
return new Promise(function (result) {
let err;
for (let index in doc) {
let key = doc[index];
if (!key) {
err = "No Key For Index "+index; break;
}
vals.push(new Promise(function (pushed) {
DistinctFor(key)
.then(pushed)
.catch(function (err) {
return pushed(Promise.resolve());
})
}))
}
return result(err ? Promise.reject(err) : Promise.resolve());
})
}
async function DistinctFor(key) {
if (!key) throw "Key Is Undefined";
try {
final[key] = await collection.distinct(key);
} catch (e) {
final[key] = 'failed';
throw e;
}
}
}
So querying a collection with the basic _id index, would return the following (test collection only has one document at the time of the test):
Mongo.MongoClient.connect(url, function (err, client) {
assert.equal(null, err);
let collection = client.db('my db').collection('the targeted collection');
GetFor(collection, '_id')
.then(function () {
//returns
// { _id: [ 5ae901e77e322342de1fb701 ] }
})
.catch(function (err) {
//manage your error..
})
});
Mind you, this uses methods native to the NodeJS Driver. As some other answers have suggested, there are other approaches, such as the aggregate framework. I personally find this approach more flexible, as you can easily create and fine-tune how to return the results. Obviously, this only addresses top-level attributes, not nested ones.
Also, to guarantee that all documents are represented should there be secondary indexes (other than the main _id one), those indexes should be set as required.
We can achieve this by Using mongo js file. Add below code in your getCollectionName.js file and run js file in the console of Linux as given below :
mongo --host 192.168.1.135 getCollectionName.js
db_set = connect("192.168.1.135:27017/database_set_name"); // for Local testing
// db_set.auth("username_of_db", "password_of_db"); // if required
db_set.getMongo().setSlaveOk();
var collectionArray = db_set.getCollectionNames();
collectionArray.forEach(function(collectionName){
if ( collectionName == 'system.indexes' || collectionName == 'system.profile' || collectionName == 'system.users' ) {
return;
}
print("\nCollection Name = "+collectionName);
print("All Fields :\n");
var arrayOfFieldNames = [];
var items = db_set[collectionName].find();
// var items = db_set[collectionName].find().sort({'_id':-1}).limit(100); // if you want fast & scan only last 100 records of each collection
while(items.hasNext()) {
var item = items.next();
for(var index in item) {
arrayOfFieldNames[index] = index;
}
}
for (var index in arrayOfFieldNames) {
print(index);
}
});
quit();
Thanks #ackuser
Following the thread from #James Cropcho's answer, I landed on the following which I found to be super easy to use. It is a binary tool, which is exactly what I was looking for:
mongoeye.
Using this tool it took about 2 minutes to get my schema exported from command line.
I know this question is 10 years old but there is no C# solution and this took me hours to figure out. I'm using the .NET driver and System.Linq to return a list of the keys.
var map = new BsonJavaScript("function() { for (var key in this) { emit(key, null); } }");
var reduce = new BsonJavaScript("function(key, stuff) { return null; }");
var options = new MapReduceOptions<BsonDocument, BsonDocument>();
var result = await collection.MapReduceAsync(map, reduce, options);
var list = result.ToEnumerable().Select(item => item["_id"].ToString());
This one lines extracts all keys from a collection into a comma separated sorted string:
db.<collection>.find().map((x) => Object.keys(x)).reduce((a, e) => {for (el of e) { if(!a.includes(el)) { a.push(el) } }; return a}, []).sort((a, b) => a.toLowerCase() > b.toLowerCase()).join(", ")
The result of this query typically looks like this:
_class, _id, address, city, companyName, country, emailId, firstName, isAssigned, isLoggedIn, lastLoggedIn, lastName, location, mobile, printName, roleName, route, state, status, token
I extended Carlos LM's solution a bit so it's more detailed.
Example of a schema:
var schema = {
_id: 123,
id: 12,
t: 'title',
p: 4.5,
ls: [{
l: 'lemma',
p: {
pp: 8.9
}
},
{
l: 'lemma2',
p: {
pp: 8.3
}
}
]
};
Type into the console:
var schemafy = function(schema, i, limit) {
var i = (typeof i !== 'undefined') ? i : 1;
var limit = (typeof limit !== 'undefined') ? limit : false;
var type = '';
var array = false;
for (key in schema) {
type = typeof schema[key];
array = (schema[key] instanceof Array) ? true : false;
if (type === 'object') {
print(Array(i).join(' ') + key+' <'+((array) ? 'array' : type)+'>:');
schemafy(schema[key], i+1, array);
} else {
print(Array(i).join(' ') + key+' <'+type+'>');
}
if (limit) {
break;
}
}
}
Run:
schemafy(db.collection.findOne());
Output
_id <number>
id <number>
t <string>
p <number>
ls <object>:
0 <object>:
l <string>
p <object>:
pp <number>
I was trying to write in nodejs and finally came up with this:
db.collection('collectionName').mapReduce(
function() {
for (var key in this) {
emit(key, null);
}
},
function(key, stuff) {
return null;
}, {
"out": "allFieldNames"
},
function(err, results) {
var fields = db.collection('allFieldNames').distinct('_id');
fields
.then(function(data) {
var finalData = {
"status": "success",
"fields": data
};
res.send(finalData);
delteCollection(db, 'allFieldNames');
})
.catch(function(err) {
res.send(err);
delteCollection(db, 'allFieldNames');
});
});
After reading the newly created collection "allFieldNames", delete it.
db.collection("allFieldNames").remove({}, function (err,result) {
db.close();
return;
});
I have 1 simpler work around...
What you can do is while inserting data/document into your main collection "things" you must insert the attributes in 1 separate collection lets say "things_attributes".
so every time you insert in "things", you do get from "things_attributes" compare values of that document with your new document keys if any new key present append it in that document and again re-insert it.
So things_attributes will have only 1 document of unique keys which you can easily get when ever you require by using findOne()
I receive a POST argument that looks like this:
sort:
[
{ field: 'name', dir: 'asc', compare: '' },
{ field: 'org', dir: 'asc', compare: '' }
]
}
and I need to create a MongoDB query based on that, so it should look like:
db.collection("my_collection").find( ... ).sort({'name': 'asc', 'org': 'asc'}).toArray(...);
Anyways, keep in mind that more fields could be passed. Also, it could happen that none of those fields is passed, meaning that the query won't have .sort().
My question: How can I create dynamically a query with Node's MongoDB driver? Is there a query builder or something similar?
I've found that most cases are unique regarding passed data, so building query objects varies from project to project.
So first ideas was to create middleware for express (in my case), that would parse query arguments into objects that are valid for query.
mongo-native can use as chained options to cursor, as well as in object:
Chained:
items.find({ type: 'location' }).sort({ title: 1 }).limit(42).toArray(function(err, data) {
// ...
});
Non-chained:
items.find({ type: 'location' }, { sort: { title: 1 }, limit: 42 }).toArray(function(err, data) {
// ...
});
As you can see Non-Chained can accept everything as object, while chained returns cursor after every method and can be reused. So generally you have two options:
For Chained:
var cursor = items.find({ type: 'location' });
if (sort) {
cursor.sort(sort);
}
cursor.toArray(function(err, data) {
// ...
});
For Non-Chained:
var options = { };
if (sort) {
options.sort = sort;
}
items.find({ type: 'location' }, options).toArray(function(err, data) {
// ...
});
It is important to remember that any data from query have to be validated and parsed properly. As well if you are developing API (for example), and will decide to change the way sorting arguments are passed or will want to add new way, then making middleware (in express.js) for parsing this data - is the way to go.
Example for pagination:
function pagination(options) {
return function(req, res, next) {
var limit = options.limit ? options.limit : 0;
var skip = 0;
if (req.query.limit) {
var tmp = parseInt(req.query.limit);
if (tmp != NaN) {
limit = tmp;
}
}
if (req.query.skip) {
var tmp = parseInt(req.query.skip);
if (tmp != NaN && tmp > 0) {
skip = tmp;
}
}
if (options.max) {
limit = Math.min(limit, options.max);
}
if (options.min) {
limit = Math.max(limit, options.min);
}
req.pagination = {
limit: limit,
skip: skip
};
next();
}
}
Usage:
app.get('/items', pagination({
limit: 8, // by default will return up to 8 items
min: 1, // minimum 1
max: 64 // maximum 64
}), function(req, res, next) {
var options = {
limit: req.pagination.limit,
skip: req.pagination.limit
};
items.find({ }, options).toArray(function(err, data) {
if (!err) {
res.json(data);
} else {
next(err);
}
});
});
And url examples:
http://example.com/items
http://example.com/items?skip=64
http://example.com/items?skip=256&limit=32
So it is the way to develop well flexible framework, which does not creates any rules of how things have to be coded as well as solving your challenge.