I have a match expression in a mongodb aggregation. There are 3 fields that are included in the match but they don't all always contain data. I only want to include the fields in the match if the field isn't empty.
This is what the match looks like if all fields have data but for example, if the array used for studentGradeLevels is empty, then I don't want to include it or I want the query to still return data ignoring the empty parameter.
$match: {
"school._id": "7011",
"studentGradeLevels": { $in: ["09", "10", "11", "12"] },
"contentArea": {
$in: [
"English 1"
]
}
}
Is there a way to either dynamically build the match so that I only include the fields I want based on if they are empty or not or do something in the query so that parameters that are empty are ignored.
You can use $in when the array is not empty and $nin when the array is empty, this way the match field will not be taken into account ($nin : []):
function buildMatch(arr) {
var matcher = {};
if (arr.length == 0)
matcher["$nin"] = arr;
else
matcher["$in"] = arr;
return matcher;
}
var grades = ["09", "10", "11", "12"];
var areas = [ "English 2" ];
var gradeMatch = buildMatch(grades);
var areaMatch = buildMatch(areas);
db.students.aggregate([{
$match: {
"school._id": "7011",
"studentGradeLevels": gradeMatch,
"contentArea": areaMatch
}
}])
A variation: Check fields for existence and if so, change to a special value e.g. _ and add that to the $inlist:
db.foo.aggregate([
{$project: {"studentGradeLevels":{$ifNull: ["$studentGradeLevels","_"]},
"contentArea":{$ifNull: ["$contentArea","_"]}
}}
,{$match: {
"studentGradeLevels": { $in: ["_", "09", "10", "11", "12"] },
"contentArea": { $in: [ "_", "English 1" ] }
}}
]);
Related
I want to provide array in filter of .find method
I found this method which matches a string in an array of input , Is there a way we can do It other way round .
db.collection.find({"phoneNumber.type": { $in: ["ACD", "BFG"] } })
According to your comment where you are looking for something like: db.collection.find({ ['a','b','c'] : 'c' }) I think you can use this aggregate query:
First create an auxiliar field using $objectToArray to get keys as k field and value as v field.
Then $match using $in with keys. This $match return the documents where the key is in the array (in this case ["a", "b", "c"]) and value (v) is desired one. Also $elemMatch is used to ensure the object is the same.
And the last step is $project to remove the auxiliar field.
db.collection.aggregate([
{
"$addFields": {
"aux": {"$objectToArray": "$$ROOT"}
}
},
{
"$match": {
"aux": {
"$elemMatch": {
"k": {"$in": ["a","b","c"]},
"v": "c"
}
}
}
},
{
"$project": {
"aux": 0
}
}
])
Example here
You could dynamically build an array of criteria on the client side:
const fieldnames = [ "field1","field2","field3" ];
const value = "match";
const criteria = fieldNames.map(function(fname){
var ret = {};
ret[fname] = value;
return ret;
});
Then if you want documents where any of them match, use:
Model.find({$or: criteria})
If you only want documwents were all of them match, use:
Model.find({$and: criteria})
I am new to mongodb and now using aggregate.
I am in a problem that I have 2 column let this column1 and column2 I want to match either by column1 or column2 inside $match Is it possible. I am getting stuck please help.
db Structure:
{
"_id" : ObjectId("55794aa1be1f8fe822da139d"),
"transactionType" : "1",
"_store" : {
"storeLocation" : "Pitampura",
"storeName" : "Godown",
"_id" : "5576b5c5e414d90c03d1e330"
}
}
I am try to filter according to transactionType and storeName, I am sending these 2 params to api but when storeName sended as empty string then only filter according to transactionType else by both paramater. Not wanted to use if-elseif.
Well of course it can suit your query. You just handle as follows:
// Initial data
var request = { "storeName": "", "transactionType": "1" };
// Transform to array
var conditions = Object.keys(request).map(function(key) {
var obj = {},
newKey = "";
if ( key == "storeName" ) {
newKey = "_store." + key;
} else {
newKey = key;
}
obj[newKey] = request[key];
return obj;
});
db.collection.find({ "$or": conditions });
Where the whole structure after transformation breaks down to :
db.collection.find({
"$or": [
{ "_store.storeName": "" },
{ "transactionType": "1" }
]
})
Which of course matches the document on the condition that "transactionType" is met.
So that is what $or does, considers that at least one of the conditions in the query arguments matches data in the document.
The other thing here is that since the data presented in the request is not a "direct match" for the data in the document, manipulation is done on the "key name" to use the correct "dot notation" form for acessing that element.
These are just basic queries, so the same rules apply to aggregation $match, which is just a query element itself:
db.collection.aggregate([
// Possibly other pipeline before
// Your match phase, which probably should be first
{ "$match": {
"$or": [
{ "_store.storeName": "" },
{ "transactionType": "1" }
]
}},
// Other aggregagtion pipeline
])
Is there a way to conditionally $addToSet based on a specific key field in a subdocument on an array?
Here's an example of what I mean - given the collection produced by the following sample bootstrap;
cls
db.so.remove();
db.so.insert({
"Name": "fruitBowl",
"pfms" : [
{
"n" : "apples"
}
]
});
n defines a unique document key. I only want one entry with the same n value in the array at any one time. So I want to be able to update the pfms array using n so that I end up with just this;
{
"Name": "fruitBowl",
"pfms" : [
{
"n" : "apples",
"mState": 1111234
}
]
}
Here's where I am at the moment;
db.so.update({
"Name": "fruitBowl",
},{
// not allowed to do this of course
// "$pull": {
// "pfms": { n: "apples" },
// },
"$addToSet": {
"pfms": {
"$each": [
{
"n": "apples",
"mState": 1111234
}
]
}
}
}
)
Unfortunately, this adds another array element;
db.so.find().toArray();
[
{
"Name" : "fruitBowl",
"_id" : ObjectId("53ecfef5baca2b1079b0f97c"),
"pfms" : [
{
"n" : "apples"
},
{
"n" : "apples",
"mState" : 1111234
}
]
}
]
I need to effectively upsert the apples document matching on n as the unique identifier and just set mState whether or not an entry already exists. It's a shame I can't do a $pull and $addToSet in the same document (I tried).
What I really need here is dictionary semantics, but that's not an option right now, nor is breaking out the document - can anyone come up with another way?
FWIW - the existing format is a result of language/driver serialization, I didn't choose it exactly.
further
I've gotten a little further in the case where I know the array element already exists I can do this;
db.so.update({
"Name": "fruitBowl",
"pfms.n": "apples",
},{
$set: {
"pfms.$.mState": 1111234,
},
}
)
But of course that only works;
for a single array element
as long as I know it exists
The first limitation isn't a disaster, but if I can't effectively upsert or combine $addToSet with the previous $set (which of course I can't) then it the only workarounds I can think of for now mean two DB round-trips.
The $addToSet operator of course requires that the "whole" document being "added to the set" is in fact unique, so you cannot change "part" of the document or otherwise consider it to be a "partial match".
You stumbled on to your best approach using $pull to remove any element with the "key" field that would result in "duplicates", but of course you cannot modify the same path in different update operators like that.
So the closest thing you will get is issuing separate operations but also doing that with the "Bulk Operations API" which is introduced with MongoDB 2.6. This allows both to be sent to the server at the same time for the closest thing to a "contiguous" operations list you will get:
var bulk = db.so.initializeOrderedBulkOp();
bulk.find({ "Name": "fruitBowl", "pfms.n": "apples": }).updateOne({
"$pull": { "pfms": { "n": "apples" } }
});
bulk.find({ "Name": "fruitBowl" }).updateOne({
"$push": { "pfms": { "n": "apples", "state": 1111234 } }
})
bulk.execute();
That pretty much is your best approach if it is not possible or practical to move the elements to another collection and rely on "upserts" and $set in order to have the same functionality but on a collection rather than array.
I have faced the exact same scenario. I was inserting and removing likes from a post.
What I did is, using mongoose findOneAndUpdate function (which is similar to update or findAndModify function in mongodb).
The key concept is
Insert when the field is not present
Delete when the field is present
The insert is
findOneAndUpdate({ _id: theId, 'likes.userId': { $ne: theUserId }},
{ $push: { likes: { userId: theUserId, createdAt: new Date() }}},
{ 'new': true }, function(err, post) { // do the needful });
The delete is
findOneAndUpdate({ _id: theId, 'likes.userId': theUserId},
{ $pull: { likes: { userId: theUserId }}},
{ 'new': true }, function(err, post) { // do the needful });
This makes the whole operation atomic and there are no duplicates with respect to the userId field.
I hope this helpes. If you have any query, feel free to ask.
As far as I know MongoDB now (from v 4.2) allows to use aggregation pipelines for updates.
More or less elegant way to make it work (according to the question) looks like the following:
db.runCommand({
update: "your-collection-name",
updates: [
{
q: {},
u: {
$set: {
"pfms.$[elem]": {
"n":"apples",
"mState": NumberInt(1111234)
}
}
},
arrayFilters: [
{
"elem.n": {
$eq: "apples"
}
}
],
multi: true
}
]
})
In my scenario, The data need to be init when not existed, and update the field If existed, and the data will not be deleted. If the datas have these states, you might want to try the following method.
// Mongoose, but mostly same as mongodb
// Update the tag to user, If there existed one.
const user = await UserModel.findOneAndUpdate(
{
user: userId,
'tags.name': tag_name,
},
{
$set: {
'tags.$.description': tag_description,
},
}
)
.lean()
.exec();
// Add a default tag to user
if (user == null) {
await UserModel.findOneAndUpdate(
{
user: userId,
},
{
$push: {
tags: new Tag({
name: tag_name,
description: tag_description,
}),
},
}
);
}
This is the most clean and fast method in the scenario.
As a business analyst , I had the same problem and hopefully I have a solution to this after hours of investigation.
// The customer document:
{
"id" : "1212",
"customerCodes" : [
{
"code" : "I"
},
{
"code" : "YK"
}
]
}
// The problem : I want to insert dateField "01.01.2016" to customer documents where customerCodes subdocument has a document with code "YK" but does not have dateField. The final document must be as follows :
{
"id" : "1212",
"customerCodes" : [
{
"code" : "I"
},
{
"code" : "YK" ,
"dateField" : "01.01.2016"
}
]
}
// The solution : the solution code is in three steps :
// PART 1 - Find the customers with customerCodes "YK" but without dateField
// PART 2 - Find the index of the subdocument with "YK" in customerCodes list.
// PART 3 - Insert the value into the document
// Here is the code
// PART 1
var myCursor = db.customers.find({ customerCodes:{$elemMatch:{code:"YK", dateField:{ $exists:false} }}});
// PART 2
myCursor.forEach(function(customer){
if(customer.customerCodes != null )
{
var size = customer.customerCodes.length;
if( size > 0 )
{
var iFoundTheIndexOfSubDocument= -1;
var index = 0;
customer.customerCodes.forEach( function(clazz)
{
if( clazz.code == "YK" && clazz.changeDate == null )
{
iFoundTheIndexOfSubDocument = index;
}
index++;
})
// PART 3
// What happens here is : If i found the indice of the
// "YK" subdocument, I create "updates" document which
// corresponds to the new data to be inserted`
//
if( iFoundTheIndexOfSubDocument != -1 )
{
var toSet = "customerCodes."+ iFoundTheIndexOfSubDocument +".dateField";
var updates = {};
updates[toSet] = "01.01.2016";
db.customers.update({ "id" : customer.id } , { $set: updates });
// This statement is actually interpreted like this :
// db.customers.update({ "id" : "1212" } ,{ $set: customerCodes.0.dateField : "01.01.2016" });
}
}
}
});
Have a nice day !
How can I remove all fields that are null from all documents of a given collection?
I have a collection of documents such as:
{
'property1': 'value1',
'property2': 'value2',
...
}
but each document may have a null entry instead of a value entry.
I would like to save disk space by removing all null entries. The existence of the null entries does not contain any information in my case because I know the format of the JSON document a priori.
Starting Mongo 4.2, db.collection.update() can accept an aggregation pipeline, finally allowing the removal of a field based on its value:
// { _id: ObjectId("5d0e8...d2"), property1: "value1", property2: "value2" }
// { _id: ObjectId("5d0e8...d3"), property1: "value1", property2: null, property3: "value3" }
db.collection.update(
{},
[{ $replaceWith: {
$arrayToObject: {
$filter: {
input: { $objectToArray: "$$ROOT" },
as: "item",
cond: { $ne: ["$$item.v", null] }
}
}
}}],
{ multi: true }
)
// { _id: ObjectId("5d0e8...d2"), property1: "value1", property2: "value2" }
// { _id: ObjectId("5d0e8...d3"), property1: "value1", property3: "value3" }
In details:
The first part {} is the match query, filtering which documents to update (in our case all documents).
The second part [{ $replaceWith: { ... }] is the update aggregation pipeline (note the squared brackets signifying the use of an aggregation pipeline):
With $objectToArray, we first transform the document to an array of key/values such as [{ k: "property1", v: "value1" }, { k: "property2", v: null }, ...].
With $filter, we filter this array of key/values by removing items for which v is null.
We then transform back the filtered array of key/values to an object using $arrayToObject.
Finally, we replace the whole document by the modified one with $replaceWith.
Don't forget { multi: true }, otherwise only the first matching document will be updated.
// run in mongo shell
var coll = db.getCollection("collectionName");
var cursor = coll.find();
while (cursor.hasNext()) {
var doc = cursor.next();
var keys = {};
var hasNull = false;
for ( var x in doc) {
if (x != "_id" && doc[x] == null) {
keys[x] = 1;
hasNull = true;
}
}
if (hasNull) {
coll.update({_id: doc._id}, {$unset:keys});
}
}
This is an important question since mongodb cannot index null values (i.e. do not query for nulls or you will be waiting for a long time), so it is best to entirely avoid nulls and set default values using setOnInsert.
Here is a recursive solution to removing nulls:
/**
* RETRIEVES A LIST OF ALL THE KEYS IN A DOCUMENT, WHERE THE VALUE IS 'NULL' OR 'UNDEFINED'
*
* #param doc
* #param keyName
* #param nullKeys
*/
function getNullKeysRecursively(doc, keyName, nullKeys)
{
for (var item_property in doc)
{
// SKIP BASE-CLASS STUFF
if (!doc.hasOwnProperty(item_property))
continue;
// SKIP ID FIELD
if (item_property === "_id")
continue;
// FULL KEY NAME (FOR SUB-DOCUMENTS)
var fullKeyName;
if (keyName)
fullKeyName = keyName + "." + item_property;
else
fullKeyName = item_property;
// DEBUGGING
// print("fullKeyName: " + fullKeyName);
// NULL FIELDS - MODIFY THIS BLOCK TO ADD CONSTRAINTS
if (doc[item_property] === null || doc[item_property] === undefined)
nullKeys[fullKeyName] = 1;
// RECURSE OBJECTS / ARRAYS
else if (doc[item_property] instanceof Object || doc[item_property] instanceof Array)
getNullKeysRecursively(doc[item_property], fullKeyName, nullKeys);
}
}
/**
* REMOVES ALL PROPERTIES WITH A VALUE OF 'NULL' OR 'UNDEFINED'.
* TUNE THE 'LIMIT' VARIABLE TO YOUR MEMORY AVAILABILITY.
* ONLY CLEANS DOCUMENTS THAT REQUIRE CLEANING, FOR EFFICIENCY.
* USES bulkWrite FOR EFFICIENCY.
*
* #param collectionName
*/
function removeNulls(collectionName)
{
var coll = db.getCollection(collectionName);
var lastId = ObjectId("000000000000000000000000");
var LIMIT = 10000;
while (true)
{
// GET THE NEXT PAGE OF DOCUMENTS
var page = coll.find({ _id: { $gt: lastId } }).limit(LIMIT);
if (! page.hasNext())
break;
// BUILD BULK OPERATION
var arrBulkOps = [];
page.forEach(function(item_doc)
{
lastId = item_doc._id;
var nullKeys = {};
getNullKeysRecursively(item_doc, null, nullKeys);
// ONLY UPDATE MODIFIED DOCUMENTS
if (Object.keys(nullKeys).length > 0)
// UNSET INDIVIDUAL FIELDS, RATHER THAN REWRITE THE ENTIRE DOC
arrBulkOps.push(
{ updateOne: {
"filter": { _id: item_doc._id },
"update": { $unset: nullKeys }
} }
);
});
coll.bulkWrite(arrBulkOps, { ordered: false } );
}
}
// GO GO GO
removeNulls('my_collection');
document before:
{
"_id": ObjectId("5a53ed8f6f7c4d95579cb87c"),
"first_name": null,
"last_name": "smith",
"features": {
"first": {
"a": 1,
"b": 2,
"c": null
},
"second": null,
"third" : {},
"fourth" : []
},
"other": [
null,
123,
{
"a": 1,
"b": "hey",
"c": null
}
]
}
document after:
{
"_id" : ObjectId("5a53ed8f6f7c4d95579cb87c"),
"last_name" : "smith",
"features" : {
"first" : {
"a" : 1,
"b" : 2
}
},
"other" : [
null,
123,
{
"a" : 1,
"b" : "hey"
}
]
}
As you can see, it removes null, undefined, empty objects and empty arrays. If you need it to be more/less aggressive, it is a matter of modifying the block "NULL FIELDS - MODIFY THIS BLOCK TO ADD CONSTRAINTS".
edits welcome, especially #stennie
You can use the mongo updateMany functionality, but you must do this by specifying the parameter you are going to update, such as the year parameter:
db.collection.updateMany({year: null}, { $unset : { year : 1 }})
Like this question mentioned (mongodb query without field name):
Unfortunately, MongoDB does not support any method of querying all fields with a particular value.
So, you can either iterate the document (like Wizard's example) or do it in non-mongodb way.
If this is a JSON file, remove all the lines with null in sed might works:
sed '/null/d' ./mydata.json
Update for 2022:
If you delete keys with values Null, [], "", {} from the DB, that won't reduce it's size on disk.
You need to do that before you upload data into the collection.
Tested it myself. I had 6.000.000 documents in collection. Ran script of Xavier Guihot. Before script it was 7.8GB, after the script it became 7.9GB.
I confirm, that script do the job and remove keys, it's just that it doesn't reduce the size of the DB space allocation.
Then I deleted completely the collection, and imported .json dumps, that had already been formatted (removed all keys with values Null, [], "", {}). After collection size was 6.1GB That's minus 22% of the original size.
Here is python script I used to remove all empty keys from json dumps:
import fileinput
import json
for line in fileinput.input(inplace=1):
j = {k:v for k, v in json.loads(line).items() if v}
print(line.replace(line, json.dumps(j)))
Just run the script with file name as argument, for example: python3 main.py dump-00001
ps: take into account, that you need to wait ~200 seconds after changes to DB, because WiredTiger keep history backup of data for consistency after you make changes. That's mean, that only after 200 sec you will see real storage allocation of DB. 200 sec is default value for that action.
In the following example, "Algorithms in C++" is present twice.
The $unset modifier can remove a particular field but how to remove an entry from a field?
{
"_id" : ObjectId("4f6cd3c47156522f4f45b26f"),
"favorites" : {
"books" : [
"Algorithms in C++",
"The Art of Computer Programming",
"Graph Theory",
"Algorithms in C++"
]
},
"name" : "robert"
}
As of MongoDB 2.2 you can use the aggregation framework with an $unwind, $group and $project stage to achieve this:
db.users.aggregate([{$unwind: '$favorites.books'},
{$group: {_id: '$_id',
books: {$addToSet: '$favorites.books'},
name: {$first: '$name'}}},
{$project: {'favorites.books': '$books', name: '$name'}}
])
Note the need for the $project to rename the favorites field, since $group aggregate fields cannot be nested.
The easiest solution is to use setUnion (Mongo 2.6+):
db.users.aggregate([
{'$addFields': {'favorites.books': {'$setUnion': ['$favorites.books', []]}}}
])
Another (more lengthy) version that is based on the idea from #kynan's answer, but preserves all the other fields without explicitly specifying them (Mongo 3.4+):
> db.users.aggregate([
{'$unwind': {
'path': '$favorites.books',
// output the document even if its list of books is empty
'preserveNullAndEmptyArrays': true
}},
{'$group': {
'_id': '$_id',
'books': {'$addToSet': '$favorites.books'},
// arbitrary name that doesn't exist on any document
'_other_fields': {'$first': '$$ROOT'},
}},
{
// the field, in the resulting document, has the value from the last document merged for the field. (c) docs
// so the new deduped array value will be used
'$replaceRoot': {'newRoot': {'$mergeObjects': ['$_other_fields', "$$ROOT"]}}
},
// this stage wouldn't be necessary if the field wasn't nested
{'$addFields': {'favorites.books': '$books'}},
{'$project': {'_other_fields': 0, 'books': 0}}
])
{ "_id" : ObjectId("4f6cd3c47156522f4f45b26f"), "name" : "robert", "favorites" :
{ "books" : [ "The Art of Computer Programmning", "Graph Theory", "Algorithms in C++" ] } }
What you have to do is use map reduce to detect and count duplicate tags .. then use $set to replace the entire books based on { "_id" : ObjectId("4f6cd3c47156522f4f45b26f"),
This has been discussed sevel times here .. please seee
Removing duplicate records using MapReduce
Fast way to find duplicates on indexed column in mongodb
http://csanz.posterous.com/look-for-duplicates-using-mongodb-mapreduce
http://www.mongodb.org/display/DOCS/MapReduce
How to remove duplicate record in MongoDB by MapReduce?
function unique(arr) {
var hash = {}, result = [];
for (var i = 0, l = arr.length; i < l; ++i) {
if (!hash.hasOwnProperty(arr[i])) {
hash[arr[i]] = true;
result.push(arr[i]);
}
}
return result;
}
db.collection.find({}).forEach(function (doc) {
db.collection.update({ _id: doc._id }, { $set: { "favorites.books": unique(doc.favorites.books) } });
})
Starting in Mongo 4.4, the $function aggregation operator allows applying a custom javascript function to implement behaviour not supported by the MongoDB Query Language.
For instance, in order to remove duplicates from an array:
// {
// "favorites" : { "books" : [
// "Algorithms in C++",
// "The Art of Computer Programming",
// "Graph Theory",
// "Algorithms in C++"
// ]},
// "name" : "robert"
// }
db.collection.aggregate(
{ $set:
{ "favorites.books":
{ $function: {
body: function(books) { return books.filter((v, i, a) => a.indexOf(v) === i) },
args: ["$favorites.books"],
lang: "js"
}}
}
}
)
// {
// "favorites" : { "books" : [
// "Algorithms in C++",
// "The Art of Computer Programming",
// "Graph Theory"
// ]},
// "name" : "robert"
// }
This has the advantages of:
keeping the original order of the array (if that's not a requirement, then prefer #Dennis Golomazov's $setUnion answer)
being more efficient than a combination of expensive $unwind and $group stages.
$function takes 3 parameters:
body, which is the function to apply, whose parameter is the array to modify.
args, which contains the fields from the record that the body function takes as parameter. In our case "$favorites.books".
lang, which is the language in which the body function is written. Only js is currently available.