I have an 'applications' collection in the following form:
{
"_id" : "<id>",
"versions" : {
"2_2_1" : 5,
"2_2_2" : 38,
"2_2_3" : 76
}
}
I want to increment the version number based on the version of application that sends a request. How can I write the $inc operator for my update query?
I can't seem to get my query working because the incremented version number can always vary from request to request. I can't get the positional $ operator working correctly for my query.
You use "dot notation" in order to access the specifc value under "version", but also you are going to have to "build" the object key by whatever language you are using.
As a JavaScript example:
var request = "2_2_1";
var update = { "$inc": { } };
update["$inc"]["versions." + request] = 1;
This yields:
{ "$inc": { "versions.2_2_1": 1 } }
So you just perform the update:
db.collection.update({ "_id": id },update);
If that "request" version sub-key exists then it is "incremented" from it's previous value. If it is a "new" key then the initial value will be 1.
Related
I have a collection called dealers as follows.
{
"_id" : ObjectId("5b9ba196cd5f5af83bb0dc71"),
"name" : "SOME COMPANY",
"outletID" : "GS0061920",
"companyID" : "GC0050397"
}
I have about 5000 documents in this collection where outletID and companyID properties are empty.
I would like to update both of these properties for all documents in this collection with incremental values.
I'm not sure how I should go about this.
Note: MongoDB 3.4 is in use.
Assuming you are running on mongodb shell. You can use the following:
> var counter = 1;
> db.collection.find().forEach(
function(elem) {
db.myColl.update(
{ "outletID" : null, "companyID" : null},
{$set:{ outletID: counter , companyID: counter }
});
counter++;
});
The mongo shell is an interactive JavaScript interface. I have used JS for the task. counter is a simple variable which is used to update values. $set is used to update the fields.
The $set operator replaces the value of a field with the specified value. You can find more data in its official documentation.
I created a sample data and tested my function. Hope it works fine.
I have lots of documents inside a collection.
The structure of each of the documents inside the collection is as it follows:
{
"_id" : ObjectId(....),
"valor" : {
"AB" : {
"X" : 0.0,
"Y" : 142.6,
},
"FJ" : {
"X" : 0.2,
"Y" : 3.33
....
The collection has currently about 200 documents and I have noticed that one of the keys inside valor has the wrong name. In this case we will say "FJ" shall be "JOF" in all the docs of the collection.
Im pretty sure it is possible to change the key in all the docs using the update function of pymongo. The problem I am facing is that when I visit the online doc available https://docs.mongodb.com/v3.0/reference/method/db.collection.update/ only explains how to change the values(which I would like to remain how they currently are and change only the keys).
This is what I have tried:
def multi_update(spec_key,key_updte):
rdo=col.update((valor.spec_key),{"$set":(valor.key_updte)},multi=True)
return rdo
print(multi_update('FJ','JOF'))
But outputs name 'valor' is not defined . I thought I shall use valor.specific_key to access to the corresponding json
how can I update a key only along the docs of the collection?
You have two problems. First, valor is not an identifier in your Python code, it's a field name of a MongoDB document. You need to quote it in single or double quotes in Python in order to make it a string and use it in a PyMongo update expression.
Your second problem is, MongoDB's update command doesn't allow you set one field to the value of another, nor to rename a field. However, you can reshape all the documents in your collection using the aggregate command with a $project stage and store the results in a second collection using a $out stage.
Here's a complete example to play with:
db = MongoClient().test
collection = db.collection
collection.delete_many({})
collection.insert_one({
"valor" : {
"AB" : {
"X" : 0.0,
"Y" : 142.6,
},
"FJ" : {
"X" : 0.2,
"Y" : 3.33}}})
collection.aggregate([{
"$project": {
"valor": {
"AB": "$valor.AB",
"FOJ": "$valor.FJ"
}
}
}, {
"$out": "collection2"
}])
This is the dangerous part. First, check that "collection2" has all the documents you want, in the desired shape. Then:
collection.drop()
db.collection2.rename("collection")
import pprint
pprint.pprint(collection.find_one())
I've got the following doc in my db:
{
"_id": ObjectId("ABCDEFG12345"),
"options" : {
"foo": "bar",
"another": "something"
},
"date" : {
"created": 1234567890,
"updated": 0
}
}
And I want to update options.foo and date.updated at the same time using dot notation, like so:
var mongojs = require('mongojs');
var optionName = 'foo';
var optionValue = 'baz';
var updates = {};
updates['options.' + optionName] = optionValue;
updates['date.updated'] = new Date().getTime();
db.myCollection.findAndModify({
query : {
_id : ObjectId('ABCDEFG12345')
},
update : {
$set : updates
},
upsert : false,
new : true
}, function(error, doc, result) {
console.log(doc.options);
console.log(doc.date);
});
And this results in:
{
foo : 'baz',
another : 'something'
}
{
updated : 1234567890
}
Specifically, my pre-existing date.created field is getting clobbered even though I'm using dot notation.
Why is this only partially working? The options sub-document retains its pre-existing data (options.another), why doesn't the date sub-document retain its pre-existing data?
The behavior described typically happens when the object passed in the $set operator is of the form { "data" : { "updated" : 1234567890 } } rather than { "data.updated" : 1234567890 }, but I'm not familiar with dots in JavaScript enough to tell if that could be the cause on JS's side.
Also, it wouldn't explain why it happens with data and not options.
If you could print the object stored in the variable updates and that is sent to MongoDB in the update field, that would allow to tell on which side the issue is (JS or MongoDB).
i pass your code to a test environment and use the same library you are using. The mongojs library, for query by native ObjectId is like this mongojs.ObjectId("####") Can look the official documentation.
for the callback function in the findAndModify function, the docs parameter is an array so i navigate like an array
Note: [to concatenate the string i use template literals] (https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Template_literals)
All work fine...
I am attempting to build a query to run from Mongo client that will allow access to the following element of a hash within a hash within a hash.
Here is the structure of the data:
"_id" : ObjectId("BSONID"),
"e1" : "value",
"e2" : "value",
"e3" : "value"),
"updated_at" : ISODate("2015-08-31T21:04:37.669Z"),
"created_at" : ISODate("2015-01-05T07:20:17.833Z"),
"e4" : 62,
"e5" : {
"sube1" : {
"26444745" : {
"subsube1" : "value",
"subsube2" : "value",
"subsube3" : "value I am looking for",
"subsube4" : "value",
"subsube5" : "value"
},
"40937803" : {
"subsube1" : "value",
"subsube2" : "value",
"subsube3" : "value I am looking for",
"subsube4" : "value",
"subsube5" : "value"
},
"YCPGF5SRTJV2TVVF" : {
"subsube1" : "value",
"subsube2" : "value",
"subsube3" : "value I am looking for",
"subsube4" : "value",
"subsube5" : "value"
}
}
}
So I have tried dotted notation based on a suggestion for "diving" into an wildcard named hash using db.my_collection.find({"e5.sube1.subsube4": "value I am looking for"}) which keeps coming back with an empty result set. I have also tried the find using a match instead of an exact value using /value I am lo/ and still an empty result set. I know there is at least 1 document which has the "value I am looking for".
Any ideas - note I am restricted to using the Mongo shell client.
Thanks.
So since this is not capable of being made into a javascript/mongo shell array I will go to plan B which is write some code be it Perl or Ruby and pull the result set into an array of hashes and walk each document/sub-document.
Thanks Mario for the help.
You have two issues:
You're missing one level.
You are checking subsube4 instead of subsube3
Depending on what subdocument of sube1 you want to check, you should do
db.my_collection.find({"e5.sube1.26444745.subsube4": "value I am looking for"})
or
db.my_collection.find({"e5.sube1.40937803.subsube4": "value I am looking for"})
or
db.my_collection.find({"e5.sube1.YCPGF5SRTJV2TVVF.subsube4": "value I am looking for"})
You could use the $or operator if you want to look in any one of the three.
If you don't know the keys of your documents, that's an issue with your schema design: you should use arrays instead of objects. Similar case: How to query a dynamic key - mongodb schema design
EDIT
Since you explain that you have a special request to know the count of "value I am looking for" only one time, we can run a map reduce. You can run those commands in the shell.
Define map function
var iurMapFunction = function() {
for (var key in this.e5.sube1) {
if (this.e5.sube1[key].subsube3 == "value I am looking for") {
var value = {
count: 1,
subkey: key
}
emit(key, value);
}
}
};
Define reduce function
var iurReduceFunction = function(keys, countObjVals) {
reducedVal = {
count: 0
};
for (var idx = 0; idx < countObjVals.length; idx++) {
reducedVal.count += countObjVals[idx].count;
}
return reducedVal;
};
Run mapreduce command
db.my_collection.mapReduce(iurMapFunction,
iurReduceFunction, {
out: {
replace: "map_reduce_result"
},
}
);
Find your counts
db.map_reduce_result.find()
This should give you, for each dynamic key in your object, the number of times it had an embedded field subsube3 with value value I am looking for.
I'm trying to use MongoDB to analyse Apache log files. I've created a receipts collection from the Apache access logs. Here's an abridged summary of what my models look like:
db.receipts.findOne()
{
"_id" : ObjectId("4e57908c7a044a30dc03a888"),
"path" : "/videos/1/show_invisibles.m4v",
"issued_at" : ISODate("2011-04-08T00:00:00Z"),
"status" : "200"
}
I've written a MapReduce function that groups all data by the issued_at date field. It summarizes the total number of requests, and provides a breakdown of the number of requests for each unique path. Here's an example of what the output looks like:
db.daily_hits_by_path.findOne()
{
"_id" : ISODate("2011-04-08T00:00:00Z"),
"value" : {
"count" : 6,
"paths" : {
"/videos/1/show_invisibles.m4v" : {
"count" : 2
},
"/videos/1/show_invisibles.ogv" : {
"count" : 3
},
"/videos/6/buffers_listed_and_hidden.ogv" : {
"count" : 1
}
}
}
}
How can I make the output look like this instead:
{
"_id" : ISODate("2011-04-08T00:00:00Z"),
"count" : 6,
"paths" : {
"/videos/1/show_invisibles.m4v" : {
"count" : 2
},
"/videos/1/show_invisibles.ogv" : {
"count" : 3
},
"/videos/6/buffers_listed_and_hidden.ogv" : {
"count" : 1
}
}
}
It's not currently possible, but I would suggest voting for this case: https://jira.mongodb.org/browse/SERVER-2517.
Taking the best from previous answers and comments:
db.items.find().hint({_id: 1}).forEach(function(item) {
db.items.update({_id: item._id}, item.value);
});
From http://docs.mongodb.org/manual/core/update/#replace-existing-document-with-new-document
"If the update argument contains only field and value pairs, the update() method replaces the existing document with the document in the update argument, except for the _id field."
So you need neither to $unset value, nor to list each field.
From https://docs.mongodb.com/manual/core/read-isolation-consistency-recency/#cursor-snapshot
"MongoDB cursors can return the same document more than once in some situations. ... use a unique index on this field or these fields so that the query will return each document no more than once. Query with hint() to explicitly force the query to use that index."
AFAIK, by design Mongo's map reduce will spit results out in "value tuples" and I haven't seen anything that will configure that "output format". Maybe the finalize() method can be used.
You could try running a post-process that will reshape the data using
results.find({}).forEach( function(result) {
results.update({_id: result._id}, {count: result.value.count, paths: result.value.paths})
});
Yep, that looks ugly. I know.
You can do Dan's code with a collection reference:
function clean(collection) {
collection.find().forEach( function(result) {
var value = result.value;
delete value._id;
collection.update({_id: result._id}, value);
collection.update({_id: result.id}, {$unset: {value: 1}} ) } )};
A similar approach to that of #ljonas but no need to hardcode document fields:
db.results.find().forEach( function(result) {
var value = result.value;
delete value._id;
db.results.update({_id: result._id}, value);
db.results.update({_id: result.id}, {$unset: {value: 1}} )
} );
All the proposed solutions are far from optimal. The fastest you can do so far is something like:
var flattenMRCollection=function(dbName,collectionName) {
var collection=db.getSiblingDB(dbName)[collectionName];
var i=0;
var bulk=collection.initializeUnorderedBulkOp();
collection.find({ value: { $exists: true } }).addOption(16).forEach(function(result) {
print((++i));
//collection.update({_id: result._id},result.value);
bulk.find({_id: result._id}).replaceOne(result.value);
if(i%1000==0)
{
print("Executing bulk...");
bulk.execute();
bulk=collection.initializeUnorderedBulkOp();
}
});
bulk.execute();
};
Then call it:
flattenMRCollection("MyDB","MyMRCollection")
This is WAY faster than doing sequential updates.
While experimenting with Vincent's answer, I found a couple of problems. Basically, if you perform updates within a foreach loop, this will move the document to the end of the collection and the cursor will reach that document again (example). This can be circumvented if $snapshot is used. Hence, I am providing a Java example below.
final List<WriteModel<Document>> bulkUpdate = new ArrayList<>();
// You should enable $snapshot if performing updates within foreach
collection.find(new Document().append("$query", new Document()).append("$snapshot", true)).forEach(new Block<Document>() {
#Override
public void apply(final Document document) {
// Note that I used incrementing long values for '_id'. Change to String if
// you used string '_id's
long docId = document.getLong("_id");
Document subDoc = (Document)document.get("value");
WriteModel<Document> m = new ReplaceOneModel<>(new Document().append("_id", docId), subDoc);
bulkUpdate.add(m);
// If you used non-incrementing '_id's, then you need to use a final object with a counter.
if(docId % 1000 == 0 && !bulkUpdate.isEmpty()) {
collection.bulkWrite(bulkUpdate);
bulkUpdate.removeAll(bulkUpdate);
}
}
});
// Fixing bug related to Vincent's answer.
if(!bulkUpdate.isEmpty()) {
collection.bulkWrite(bulkUpdate);
bulkUpdate.removeAll(bulkUpdate);
}
Note : This snippet takes an average of 7.4 seconds to execute on my machine with 100k records and 14 attributes (IMDB dataset). Without batching, it takes an average of 25.2 seconds.