I'm a little newer to using MongoDB and NoSQL for my stack. ULTIMATELY, I'm switching to NoSQL for the fact of JSON parsed data already. I can accomplish what I want in MySQL - but I'm also attempting to teach myself something new.
Currently, I have no problem getting connected and setting up my Schemas for NodeJS. I have a document within MongoDB that returns what my customers pay on fuel according to National Averages - our customers give us ranges for us to be able to find what specific dollar amount they are paying.
My MongoDB Document looks as the following :
main_database
|- customerFSC (name of document)
|--
{
"_id":{"$oid":"5e5ecc04e8da861114079ab2"},
"custID":"01",
"custName":"Customer ABC",
"avgLow":["1.19","1.24","1.29","1.34","1.39","1.44","1.49","1.54","1.59","1.64","1.69","1.74","1.79","1.84","1.89","1.94","1.99"],
"avgHigh":["1.239","1.289","1.339","1.389","1.439","1.489","1.539","1.589","1.639","1.689","1.739","1.789","1.839","1.889","1.939","1.989","2.039"],
"custFscPM":["0.01","0.02","0.03","0.04","0.05","0.06","0.07","0.08","0.09","0.10","0.11","0.12","0.13","0.14","0.15","0.16","0.17"]
}
If fuel average for the week is at 1.215 - it would be ranged between the avgLow of 1.19 and the avgHigh of 1.239 but return the actual pay of 0.01 in custFscPM
My MongoDB Mongoose Node code is as follows
const mongoose = require('mongoose');
const Schema = mongoose.Schema;
const fscCustSchema = new Schema({
custID: String,
custName: String,
avgLow: Array,
avgHigh: Array,
custFscPM: Array
},
{ collection: 'customerFSC' }
);
module.exports = mongoose.model('customerFSC', fscCustSchema);
fscCustModel.find( { $and: [
{ $gte: [ { avgLow: USAFscAVG } ] },
{ $lte: [ { avgHigh: USAFscAVG } ] }
]},function(err2,resp2) {
if (err2) console.log("Error Thrown Looking up Fuel:" + err2);
console.log(resp);
});
You can use aggregation which is way to powerful way of querying MongoDB than using .find(), Try below query :
db.collection.aggregate([
{
$project: {
custFscPM: {
$arrayElemAt: [
"$custFscPM",
{
$indexOfArray: [
"$avgLow",
{
$arrayElemAt: [
{
$filter: {
input: "$avgLow",
cond: {
$gte: [
{
$toDouble: "$$this"
},
1.94 // Your input
]
}
}
},
0
]
}
]
}
]
}
}
}
])
Looking at your data, in this query we're finding the element in avgLow array which is greater than or equal to passed in value & getting it's index & find the element from custFscPM at the same index would resolve your requirement.
Note : As your values in avgLow are strings we need to convert those to double in order to do comparison.
Test : MongoDB-Playground
Related
I have a collection of workorders where it have time_started and time_completed values. I want to have auto-calculated field called duration that automatically calculated time_completed - time_started. What is the best way?
Essentially what I want is, when App post requests with a completed time, my duration is auto calculated.
Example data
router.post('/completed', function (req, res) {
const time_completed = req.body.time_completed
const workorder_id = req.body.workorder_id
db.collection(workorder).updateOne(
{ _id: ObjectId(workorder_id) },
{
$set: {
time_completed: time_completed,
}
},
function (err, result) {
if (err) throw err
res.send('Updated')
}
)
});
Query
pipeline update requires >= MongoDB 4.2
add the time_completed
add the duration also
*replace the 6 with the javascript variable that holds the time_completed Date
*duration will be in milliseconds
Test code here
db.collection.update(
{"_id": 1},
[
{
"$set": {
"time_completed": 6,
"duration": {
"$subtract": [
6,
"$time_started"
]
}
}
}
])
Edit
You have strings on your database, i thought it was dates, best thing to do is to convert all those string-dates to Date with $dataFromString like the code bellow, and use the first query.
To get the string if you needed from Date you can do $stringFromDate when you need it.
Query
same like above but it converts string dates to Date to do the substraction (keeps the dates in strings inside the database)
Test code here
db.collection.update({
"_id": 1
},
[
{
"$set": {
"time_completed": "2021-11-21T00:00:00.000Z",
"duration": {
"$subtract": [
ISODate("2021-11-21T00:00:00Z"),
{
"$dateFromString": {
"dateString": "$time_started"
}
}
]
}
}
}
])
In a nodejs app with mongodb storage, I have the following query from user:
const rawQuery = [
'{"field":"ingredient","type":"AND","value":"green and blue"}',
'{"field":"ingredient","type":"AND","value":"black"}',
'{"field":"ingredient","type":"OR","value":"pink"}',
'{"field":"ingredient","type":"OR","value":"orange"}',
'{"field":"place","type":"AND","value":"london"}',
'{"field":"school","type":"NOT","value":"fifth"}',
'{"field":"food","type":"OR","value":"burger"}',
'{"field":"food","type":"OR","value":"pizza"}',
'{"field":"ownerFirstName","type":"AND","value":"Jimmy"}'
];
I have a collection called restaurant, and a collection called owners.
Would this query aim to handle such a search scenario?
const query = {
$and: : [
{ ingredient: 'green and blue' },
{ ingredient: 'black' },
{ $or : [
{ ingredient: 'pink' },
{ ingredient: 'orange' },
]
},
{ place: 'london' },,
{ school: { $ne: 'fifth' } },
{ $or : [
{ food: 'burger' },
{ food: 'pizza' },
]
}
]
};
How can I transform the rawQuery into this mongo query? (Given that it has to be dynamic, because I have many fields, and in this example I just included a couple of them.)
This example query aims to get the restaurants that match the description/place/school/food queries in the restaurant and also to match the owner's first name from another collection. Each restaurant document will have a ownerUuid field that points to the owner in the other collection.
What is the best solution to do a search in the mongodb for such a query in production env?
How can this be achieved with Elasticsearch?
In MongoDB, is it possible to update the value of a field using the value from another field? The equivalent SQL would be something like:
UPDATE Person SET Name = FirstName + ' ' + LastName
And the MongoDB pseudo-code would be:
db.person.update( {}, { $set : { name : firstName + ' ' + lastName } );
The best way to do this is in version 4.2+ which allows using the aggregation pipeline in the update document and the updateOne, updateMany, or update(deprecated in most if not all languages drivers) collection methods.
MongoDB 4.2+
Version 4.2 also introduced the $set pipeline stage operator, which is an alias for $addFields. I will use $set here as it maps with what we are trying to achieve.
db.collection.<update method>(
{},
[
{"$set": {"name": { "$concat": ["$firstName", " ", "$lastName"]}}}
]
)
Note that square brackets in the second argument to the method specify an aggregation pipeline instead of a plain update document because using a simple document will not work correctly.
MongoDB 3.4+
In 3.4+, you can use $addFields and the $out aggregation pipeline operators.
db.collection.aggregate(
[
{ "$addFields": {
"name": { "$concat": [ "$firstName", " ", "$lastName" ] }
}},
{ "$out": <output collection name> }
]
)
Note that this does not update your collection but instead replaces the existing collection or creates a new one. Also, for update operations that require "typecasting", you will need client-side processing, and depending on the operation, you may need to use the find() method instead of the .aggreate() method.
MongoDB 3.2 and 3.0
The way we do this is by $projecting our documents and using the $concat string aggregation operator to return the concatenated string.
You then iterate the cursor and use the $set update operator to add the new field to your documents using bulk operations for maximum efficiency.
Aggregation query:
var cursor = db.collection.aggregate([
{ "$project": {
"name": { "$concat": [ "$firstName", " ", "$lastName" ] }
}}
])
MongoDB 3.2 or newer
You need to use the bulkWrite method.
var requests = [];
cursor.forEach(document => {
requests.push( {
'updateOne': {
'filter': { '_id': document._id },
'update': { '$set': { 'name': document.name } }
}
});
if (requests.length === 500) {
//Execute per 500 operations and re-init
db.collection.bulkWrite(requests);
requests = [];
}
});
if(requests.length > 0) {
db.collection.bulkWrite(requests);
}
MongoDB 2.6 and 3.0
From this version, you need to use the now deprecated Bulk API and its associated methods.
var bulk = db.collection.initializeUnorderedBulkOp();
var count = 0;
cursor.snapshot().forEach(function(document) {
bulk.find({ '_id': document._id }).updateOne( {
'$set': { 'name': document.name }
});
count++;
if(count%500 === 0) {
// Excecute per 500 operations and re-init
bulk.execute();
bulk = db.collection.initializeUnorderedBulkOp();
}
})
// clean up queues
if(count > 0) {
bulk.execute();
}
MongoDB 2.4
cursor["result"].forEach(function(document) {
db.collection.update(
{ "_id": document._id },
{ "$set": { "name": document.name } }
);
})
You should iterate through. For your specific case:
db.person.find().snapshot().forEach(
function (elem) {
db.person.update(
{
_id: elem._id
},
{
$set: {
name: elem.firstname + ' ' + elem.lastname
}
}
);
}
);
Apparently there is a way to do this efficiently since MongoDB 3.4, see styvane's answer.
Obsolete answer below
You cannot refer to the document itself in an update (yet). You'll need to iterate through the documents and update each document using a function. See this answer for an example, or this one for server-side eval().
For a database with high activity, you may run into issues where your updates affect actively changing records and for this reason I recommend using snapshot()
db.person.find().snapshot().forEach( function (hombre) {
hombre.name = hombre.firstName + ' ' + hombre.lastName;
db.person.save(hombre);
});
http://docs.mongodb.org/manual/reference/method/cursor.snapshot/
Starting Mongo 4.2, db.collection.update() can accept an aggregation pipeline, finally allowing the update/creation of a field based on another field:
// { firstName: "Hello", lastName: "World" }
db.collection.updateMany(
{},
[{ $set: { name: { $concat: [ "$firstName", " ", "$lastName" ] } } }]
)
// { "firstName" : "Hello", "lastName" : "World", "name" : "Hello World" }
The first part {} is the match query, filtering which documents to update (in our case all documents).
The second part [{ $set: { name: { ... } }] is the update aggregation pipeline (note the squared brackets signifying the use of an aggregation pipeline). $set is a new aggregation operator and an alias of $addFields.
Regarding this answer, the snapshot function is deprecated in version 3.6, according to this update. So, on version 3.6 and above, it is possible to perform the operation this way:
db.person.find().forEach(
function (elem) {
db.person.update(
{
_id: elem._id
},
{
$set: {
name: elem.firstname + ' ' + elem.lastname
}
}
);
}
);
I tried the above solution but I found it unsuitable for large amounts of data. I then discovered the stream feature:
MongoClient.connect("...", function(err, db){
var c = db.collection('yourCollection');
var s = c.find({/* your query */}).stream();
s.on('data', function(doc){
c.update({_id: doc._id}, {$set: {name : doc.firstName + ' ' + doc.lastName}}, function(err, result) { /* result == true? */} }
});
s.on('end', function(){
// stream can end before all your updates do if you have a lot
})
})
update() method takes aggregation pipeline as parameter like
db.collection_name.update(
{
// Query
},
[
// Aggregation pipeline
{ "$set": { "id": "$_id" } }
],
{
// Options
"multi": true // false when a single doc has to be updated
}
)
The field can be set or unset with existing values using the aggregation pipeline.
Note: use $ with field name to specify the field which has to be read.
Here's what we came up with for copying one field to another for ~150_000 records. It took about 6 minutes, but is still significantly less resource intensive than it would have been to instantiate and iterate over the same number of ruby objects.
js_query = %({
$or : [
{
'settings.mobile_notifications' : { $exists : false },
'settings.mobile_admin_notifications' : { $exists : false }
}
]
})
js_for_each = %(function(user) {
if (!user.settings.hasOwnProperty('mobile_notifications')) {
user.settings.mobile_notifications = user.settings.email_notifications;
}
if (!user.settings.hasOwnProperty('mobile_admin_notifications')) {
user.settings.mobile_admin_notifications = user.settings.email_admin_notifications;
}
db.users.save(user);
})
js = "db.users.find(#{js_query}).forEach(#{js_for_each});"
Mongoid::Sessions.default.command('$eval' => js)
With MongoDB version 4.2+, updates are more flexible as it allows the use of aggregation pipeline in its update, updateOne and updateMany. You can now transform your documents using the aggregation operators then update without the need to explicity state the $set command (instead we use $replaceRoot: {newRoot: "$$ROOT"})
Here we use the aggregate query to extract the timestamp from MongoDB's ObjectID "_id" field and update the documents (I am not an expert in SQL but I think SQL does not provide any auto generated ObjectID that has timestamp to it, you would have to automatically create that date)
var collection = "person"
agg_query = [
{
"$addFields" : {
"_last_updated" : {
"$toDate" : "$_id"
}
}
},
{
$replaceRoot: {
newRoot: "$$ROOT"
}
}
]
db.getCollection(collection).updateMany({}, agg_query, {upsert: true})
(I would have posted this as a comment, but couldn't)
For anyone who lands here trying to update one field using another in the document with the c# driver...
I could not figure out how to use any of the UpdateXXX methods and their associated overloads since they take an UpdateDefinition as an argument.
// we want to set Prop1 to Prop2
class Foo { public string Prop1 { get; set; } public string Prop2 { get; set;} }
void Test()
{
var update = new UpdateDefinitionBuilder<Foo>();
update.Set(x => x.Prop1, <new value; no way to get a hold of the object that I can find>)
}
As a workaround, I found that you can use the RunCommand method on an IMongoDatabase (https://docs.mongodb.com/manual/reference/command/update/#dbcmd.update).
var command = new BsonDocument
{
{ "update", "CollectionToUpdate" },
{ "updates", new BsonArray
{
new BsonDocument
{
// Any filter; here the check is if Prop1 does not exist
{ "q", new BsonDocument{ ["Prop1"] = new BsonDocument("$exists", false) }},
// set it to the value of Prop2
{ "u", new BsonArray { new BsonDocument { ["$set"] = new BsonDocument("Prop1", "$Prop2") }}},
{ "multi", true }
}
}
}
};
database.RunCommand<BsonDocument>(command);
MongoDB 4.2+ Golang
result, err := collection.UpdateMany(ctx, bson.M{},
mongo.Pipeline{
bson.D{{"$set",
bson.M{"name": bson.M{"$concat": []string{"$lastName", " ", "$firstName"}}}
}},
)
In MongoDB, is it possible to update the value of a field using the value from another field? The equivalent SQL would be something like:
UPDATE Person SET Name = FirstName + ' ' + LastName
And the MongoDB pseudo-code would be:
db.person.update( {}, { $set : { name : firstName + ' ' + lastName } );
The best way to do this is in version 4.2+ which allows using the aggregation pipeline in the update document and the updateOne, updateMany, or update(deprecated in most if not all languages drivers) collection methods.
MongoDB 4.2+
Version 4.2 also introduced the $set pipeline stage operator, which is an alias for $addFields. I will use $set here as it maps with what we are trying to achieve.
db.collection.<update method>(
{},
[
{"$set": {"name": { "$concat": ["$firstName", " ", "$lastName"]}}}
]
)
Note that square brackets in the second argument to the method specify an aggregation pipeline instead of a plain update document because using a simple document will not work correctly.
MongoDB 3.4+
In 3.4+, you can use $addFields and the $out aggregation pipeline operators.
db.collection.aggregate(
[
{ "$addFields": {
"name": { "$concat": [ "$firstName", " ", "$lastName" ] }
}},
{ "$out": <output collection name> }
]
)
Note that this does not update your collection but instead replaces the existing collection or creates a new one. Also, for update operations that require "typecasting", you will need client-side processing, and depending on the operation, you may need to use the find() method instead of the .aggreate() method.
MongoDB 3.2 and 3.0
The way we do this is by $projecting our documents and using the $concat string aggregation operator to return the concatenated string.
You then iterate the cursor and use the $set update operator to add the new field to your documents using bulk operations for maximum efficiency.
Aggregation query:
var cursor = db.collection.aggregate([
{ "$project": {
"name": { "$concat": [ "$firstName", " ", "$lastName" ] }
}}
])
MongoDB 3.2 or newer
You need to use the bulkWrite method.
var requests = [];
cursor.forEach(document => {
requests.push( {
'updateOne': {
'filter': { '_id': document._id },
'update': { '$set': { 'name': document.name } }
}
});
if (requests.length === 500) {
//Execute per 500 operations and re-init
db.collection.bulkWrite(requests);
requests = [];
}
});
if(requests.length > 0) {
db.collection.bulkWrite(requests);
}
MongoDB 2.6 and 3.0
From this version, you need to use the now deprecated Bulk API and its associated methods.
var bulk = db.collection.initializeUnorderedBulkOp();
var count = 0;
cursor.snapshot().forEach(function(document) {
bulk.find({ '_id': document._id }).updateOne( {
'$set': { 'name': document.name }
});
count++;
if(count%500 === 0) {
// Excecute per 500 operations and re-init
bulk.execute();
bulk = db.collection.initializeUnorderedBulkOp();
}
})
// clean up queues
if(count > 0) {
bulk.execute();
}
MongoDB 2.4
cursor["result"].forEach(function(document) {
db.collection.update(
{ "_id": document._id },
{ "$set": { "name": document.name } }
);
})
You should iterate through. For your specific case:
db.person.find().snapshot().forEach(
function (elem) {
db.person.update(
{
_id: elem._id
},
{
$set: {
name: elem.firstname + ' ' + elem.lastname
}
}
);
}
);
Apparently there is a way to do this efficiently since MongoDB 3.4, see styvane's answer.
Obsolete answer below
You cannot refer to the document itself in an update (yet). You'll need to iterate through the documents and update each document using a function. See this answer for an example, or this one for server-side eval().
For a database with high activity, you may run into issues where your updates affect actively changing records and for this reason I recommend using snapshot()
db.person.find().snapshot().forEach( function (hombre) {
hombre.name = hombre.firstName + ' ' + hombre.lastName;
db.person.save(hombre);
});
http://docs.mongodb.org/manual/reference/method/cursor.snapshot/
Starting Mongo 4.2, db.collection.update() can accept an aggregation pipeline, finally allowing the update/creation of a field based on another field:
// { firstName: "Hello", lastName: "World" }
db.collection.updateMany(
{},
[{ $set: { name: { $concat: [ "$firstName", " ", "$lastName" ] } } }]
)
// { "firstName" : "Hello", "lastName" : "World", "name" : "Hello World" }
The first part {} is the match query, filtering which documents to update (in our case all documents).
The second part [{ $set: { name: { ... } }] is the update aggregation pipeline (note the squared brackets signifying the use of an aggregation pipeline). $set is a new aggregation operator and an alias of $addFields.
Regarding this answer, the snapshot function is deprecated in version 3.6, according to this update. So, on version 3.6 and above, it is possible to perform the operation this way:
db.person.find().forEach(
function (elem) {
db.person.update(
{
_id: elem._id
},
{
$set: {
name: elem.firstname + ' ' + elem.lastname
}
}
);
}
);
I tried the above solution but I found it unsuitable for large amounts of data. I then discovered the stream feature:
MongoClient.connect("...", function(err, db){
var c = db.collection('yourCollection');
var s = c.find({/* your query */}).stream();
s.on('data', function(doc){
c.update({_id: doc._id}, {$set: {name : doc.firstName + ' ' + doc.lastName}}, function(err, result) { /* result == true? */} }
});
s.on('end', function(){
// stream can end before all your updates do if you have a lot
})
})
update() method takes aggregation pipeline as parameter like
db.collection_name.update(
{
// Query
},
[
// Aggregation pipeline
{ "$set": { "id": "$_id" } }
],
{
// Options
"multi": true // false when a single doc has to be updated
}
)
The field can be set or unset with existing values using the aggregation pipeline.
Note: use $ with field name to specify the field which has to be read.
Here's what we came up with for copying one field to another for ~150_000 records. It took about 6 minutes, but is still significantly less resource intensive than it would have been to instantiate and iterate over the same number of ruby objects.
js_query = %({
$or : [
{
'settings.mobile_notifications' : { $exists : false },
'settings.mobile_admin_notifications' : { $exists : false }
}
]
})
js_for_each = %(function(user) {
if (!user.settings.hasOwnProperty('mobile_notifications')) {
user.settings.mobile_notifications = user.settings.email_notifications;
}
if (!user.settings.hasOwnProperty('mobile_admin_notifications')) {
user.settings.mobile_admin_notifications = user.settings.email_admin_notifications;
}
db.users.save(user);
})
js = "db.users.find(#{js_query}).forEach(#{js_for_each});"
Mongoid::Sessions.default.command('$eval' => js)
With MongoDB version 4.2+, updates are more flexible as it allows the use of aggregation pipeline in its update, updateOne and updateMany. You can now transform your documents using the aggregation operators then update without the need to explicity state the $set command (instead we use $replaceRoot: {newRoot: "$$ROOT"})
Here we use the aggregate query to extract the timestamp from MongoDB's ObjectID "_id" field and update the documents (I am not an expert in SQL but I think SQL does not provide any auto generated ObjectID that has timestamp to it, you would have to automatically create that date)
var collection = "person"
agg_query = [
{
"$addFields" : {
"_last_updated" : {
"$toDate" : "$_id"
}
}
},
{
$replaceRoot: {
newRoot: "$$ROOT"
}
}
]
db.getCollection(collection).updateMany({}, agg_query, {upsert: true})
(I would have posted this as a comment, but couldn't)
For anyone who lands here trying to update one field using another in the document with the c# driver...
I could not figure out how to use any of the UpdateXXX methods and their associated overloads since they take an UpdateDefinition as an argument.
// we want to set Prop1 to Prop2
class Foo { public string Prop1 { get; set; } public string Prop2 { get; set;} }
void Test()
{
var update = new UpdateDefinitionBuilder<Foo>();
update.Set(x => x.Prop1, <new value; no way to get a hold of the object that I can find>)
}
As a workaround, I found that you can use the RunCommand method on an IMongoDatabase (https://docs.mongodb.com/manual/reference/command/update/#dbcmd.update).
var command = new BsonDocument
{
{ "update", "CollectionToUpdate" },
{ "updates", new BsonArray
{
new BsonDocument
{
// Any filter; here the check is if Prop1 does not exist
{ "q", new BsonDocument{ ["Prop1"] = new BsonDocument("$exists", false) }},
// set it to the value of Prop2
{ "u", new BsonArray { new BsonDocument { ["$set"] = new BsonDocument("Prop1", "$Prop2") }}},
{ "multi", true }
}
}
}
};
database.RunCommand<BsonDocument>(command);
MongoDB 4.2+ Golang
result, err := collection.UpdateMany(ctx, bson.M{},
mongo.Pipeline{
bson.D{{"$set",
bson.M{"name": bson.M{"$concat": []string{"$lastName", " ", "$firstName"}}}
}},
)
I have the following mongodb query in node.js which gives me a list of unique zip codes with a count of how many times the zip code appears in the database.
collection.aggregate( [
{
$group: {
_id: "$Location.Zip",
count: { $sum: 1 }
}
},
{ $sort: { _id: 1 } },
{ $match: { count: { $gt: 1 } } }
], function ( lookupErr, lookupData ) {
if (lookupErr) {
res.send(lookupErr);
return;
}
res.send(lookupData.sort());
});
});
How can this query be modified to return one specific zip code? I've tried the condition clause but have not been able to get it to work.
Aggregations that require filtered results can be done with the $match operator. Without tweaking what you already have, I would suggest just sticking in a $match for the zip code you want returned at the top of the aggregation list.
collection.aggregate( [
{
$match: {
zip: 47421
}
},
{
$group: {
...
This example will result in every aggregation operation after the $match working on only the data set that is returned by the $match of the zip key to the value 47421.
in the $match pipeline operator add
{ $match: { count: { $gt: 1 },
_id : "10002" //replace 10002 with the zip code you want
}}
As a side note, you should put the $match operator first and in general as high in the aggregation chain as you can.