Consider this example:
f = {'a': 'b'}
col.insert(f)
print f
, where col is a mongodb collection.
The above code will print something among the lines of:
{'a': 'b', '_id': ObjectId('5278bc183e8b1310247e047b')}
I know why mongo needs to add the _id field when inserting the document into the collection, but I don't understand why it has to modify the dictionary I pass as an argument. I would like my dictionary f to remain unmodified.
I know I can just del f['_id'] after the insert, but is there any argument I can pass to insert that will make it not modify my dict?
Simply set the manipulate argument to False, e.g.:
col.insert(f, manipulate=False)
See http://api.mongodb.org/python/current/api/pymongo/collection.html#pymongo.collection.Collection.insert
If I understand the documentation on the insert method correctly, manipulate parameter is what you're looking for:
If manipulate is True, the document(s) are manipulated using any SONManipulator instances that have been added to this Database. In this case an "_id" will be added if the document(s) does not already contain one and the "id" (or list of "_id" values for more than one document) will be returned. If manipulate is False and the document(s) does not include an "_id" one will be added by the server. The server does not return the "_id" it created so None is returned.
in my program , ten process to write mongodb by update(key, doc, upsert=true)
the "key" is mongodb index, but is not unique.
query = {'hotelid':hotelid,"arrivedate":arrivedate,"leavedate":leavedate}
where = "data.%s" % sourceid
data_value_where = {where:value}
self.collection.update(query,{'$set':data_value_where},True)
the "query" id the not unique index
I found sometimes the update not update exists data, but create a new data.
I write a log for update method return, the return is " {u'ok': 1.0, u'err': None, u'upserted': ObjectId('5245378b4b184fbbbea3f790'), u'singleShard': u'rs1/192.168.0.21:10000,192.168.1.191:10000,192.168.1.192:10000,192.168.1.41:10000,192.168.1.113:10000', u'connectionId': 1894107, u'n': 1, u'updatedExisting': False, u'lastOp': 5928205554643107852L}"
I modify the update method to update(query, {'$set':data_value_where},upsert=True, safe=True), but three is no change for this question.
You can call it "threadsafe", as the update itself is not done in Python, it's in the mongodb, which is built to cater many requests at once.
So in summary: You can safely do that.
You would not end up with duplicate documents due to the operator you are using. You are actually using an atomic operator to update.
Atomic (not to be confused with SQL atomic operations of all or nothing here) operations are done in sequence so each process will never pick up a stale document or be allowed to write two ids to the same array since the document each $set operation picks up will have the result of the last $set.
The fact that you did get duplicate documents most likely means you have an error in your code.
After upgrading MongoEngine from 0.7.9 to 0.8.3, any attempts to save any existing documents in any collection results in a NotUniqueError (user collection shown in example):
Tried to save duplicate unique keys (E11000 duplicate key error index: foo.user.$_id_ dup key: { : ObjectId('xxxxxx') })
I get the same error if I create a new document and save it more than once:
a = Foo()
a.save()
a.save() # results in duplicate error
Mongo by default creates an index on _id which cannot be removed, and I have no other indexes which use _id. Most issues similar to this that I've seen have been on duplicate indexes that aren't _id and can be removed, but this is really odd. I am doing nothing weird with the _id field, just letting Mongo generate it on its own.
Any ideas on what might be causing this to happen?
Thanks!
There was a custom save function which hadn't been migrated to using the new save() arguments, so one of them was caused force_insert to evaluate to true.
So dumb...
I am using Pymongo to access Mongo db. I want to search for all people nearby a specified location with name contains a string. For example, I want to search all people nearby [105.0133, 21.3434] and name contains 'Mark'. So I write the query like this:
db.users.find({ "location.coords": { "$nearSphere": [105.0133, 21.3434], "$maxDistance": 10/EARTH_RADIUS }, "name": "/Mark/" })
(I have an index "location.coords" in my "users" collection)
The query works fine in Mongodb console, but while execute by Pymongo, the dictionary being re-sort like this:
{ "name": "/Mark/", "location.coords": { "$nearSphere": [105.0133, 21.3434], "$maxDistance": 10/EARTH_RADIUS } }
(The "name" key is before "location.coords", that is not what I expected - also Mongodb expected)
That causes Mongodb cannot understand the query and returns no results. Can anyone help me to figure out how to force the Pymongo does not re-sort my dictionary.
Thanks and regards
The dictionary type is inherently orderless. From the python documentation:
It is best to think of a dictionary as an unordered set of key: value
pairs, with the requirement that the keys are unique (within one
dictionary).
If you want to index your dictionary in a specific order, you'll have to store your order somehow. One easy way to do this is to keep your keys in a list, like:
mongo_keys = ["location.coords", "name"]
for k in mongo_keys:
do_something(mongo_result[k])
You also might want to investigate:
class collections.OrderedDict([items])
Return an instance of a dict
subclass, supporting the usual dict methods. An OrderedDict is a dict
that remembers the order that keys were first inserted. If a new entry
overwrites an existing entry, the original insertion position is left
unchanged. Deleting an entry and reinserting it will move it to the
end.
Unfortunately if you need more help than that, you'll need to provide more details of your situation.
The issue isn't the ordering, it's "/Mark/". The notation with forward slashes is a convenience provided by the javascript shell, and don't constitute a part of the regular expression pattern itself (unless you meant for them to be literal slashes, in which case I've misunderstood your question).
To use a regular expression ("contains") filter in PyMongo, you need to pass a Python regular expression object. Try this:
{ "name": re.compile("Mark"), "location.coords": { "$nearSphere": [105.0133, 21.3434], "$maxDistance": 10/EARTH_RADIUS } }
Every day, I receive a stock of documents (an update). What I want to do is insert each item that does not already exist.
I also want to keep track of the first time I inserted them, and the last time I saw them in an update.
I don't want to have duplicate documents.
I don't want to remove a document which has previously been saved, but is not in my update.
95% (estimated) of the records are unmodified from day to day.
I am using the Python driver (pymongo).
What I currently do is (pseudo-code):
for each document in update:
existing_document = collection.find_one(document)
if not existing_document:
document['insertion_date'] = now
else:
document = existing_document
document['last_update_date'] = now
my_collection.save(document)
My problem is that it is very slow (40 mins for less than 100 000 records, and I have millions of them in the update).
I am pretty sure there is something builtin for doing this, but the document for update() is mmmhhh.... a bit terse.... (http://www.mongodb.org/display/DOCS/Updating )
Can someone advise how to do it faster?
Sounds like you want to do an upsert. MongoDB has built-in support for this. Pass an extra parameter to your update() call: {upsert:true}. For example:
key = {'key':'value'}
data = {'key2':'value2', 'key3':'value3'};
coll.update(key, data, upsert=True); #In python upsert must be passed as a keyword argument
This replaces your if-find-else-update block entirely. It will insert if the key doesn't exist and will update if it does.
Before:
{"key":"value", "key2":"Ohai."}
After:
{"key":"value", "key2":"value2", "key3":"value3"}
You can also specify what data you want to write:
data = {"$set":{"key2":"value2"}}
Now your selected document will update the value of key2 only and leave everything else untouched.
As of MongoDB 2.4, you can use $setOnInsert (http://docs.mongodb.org/manual/reference/operator/setOnInsert/)
Set insertion_date using $setOnInsert and last_update_date using $set in your upsert command.
To turn your pseudocode into a working example:
now = datetime.utcnow()
for document in update:
collection.update_one(
filter={
'_id': document['_id'],
},
update={
'$setOnInsert': {
'insertion_date': now,
},
'$set': {
'last_update_date': now,
},
},
upsert=True,
)
You could always make a unique index, which causes MongoDB to reject a conflicting save. Consider the following done using the mongodb shell:
> db.getCollection("test").insert ({a:1, b:2, c:3})
> db.getCollection("test").find()
{ "_id" : ObjectId("50c8e35adde18a44f284e7ac"), "a" : 1, "b" : 2, "c" : 3 }
> db.getCollection("test").ensureIndex ({"a" : 1}, {unique: true})
> db.getCollection("test").insert({a:2, b:12, c:13}) # This works
> db.getCollection("test").insert({a:1, b:12, c:13}) # This fails
E11000 duplicate key error index: foo.test.$a_1 dup key: { : 1.0 }
You may use Upsert with $setOnInsert operator.
db.Table.update({noExist: true}, {"$setOnInsert": {xxxYourDocumentxxx}}, {upsert: true})
Summary
You have an existing collection of records.
You have a set records that contain updates to the existing records.
Some of the updates don't really update anything, they duplicate what you have already.
All updates contain the same fields that are there already, just possibly different values.
You want to track when a record was last changed, where a value actually changed.
Note, I'm presuming PyMongo, change to suit your language of choice.
Instructions:
Create the collection with an index with unique=true so you don't get duplicate records.
Iterate over your input records, creating batches of them of 15,000 records or so. For each record in the batch, create a dict consisting of the data you want to insert, presuming each one is going to be a new record. Add the 'created' and 'updated' timestamps to these. Issue this as a batch insert command with the 'ContinueOnError' flag=true, so the insert of everything else happens even if there's a duplicate key in there (which it sounds like there will be). THIS WILL HAPPEN VERY FAST. Bulk inserts rock, I've gotten 15k/second performance levels. Further notes on ContinueOnError, see http://docs.mongodb.org/manual/core/write-operations/
Record inserts happen VERY fast, so you'll be done with those inserts in no time. Now, it's time to update the relevant records. Do this with a batch retrieval, much faster than one at a time.
Iterate over all your input records again, creating batches of 15K or so. Extract out the keys (best if there's one key, but can't be helped if there isn't). Retrieve this bunch of records from Mongo with a db.collectionNameBlah.find({ field : { $in : [ 1, 2,3 ...}) query. For each of these records, determine if there's an update, and if so, issue the update, including updating the 'updated' timestamp.
Unfortunately, we should note, MongoDB 2.4 and below do NOT include a bulk update operation. They're working on that.
Key Optimization Points:
The inserts will vastly speed up your operations in bulk.
Retrieving records en masse will speed things up, too.
Individual updates are the only possible route now, but 10Gen is working on it. Presumably, this will be in 2.6, though I'm not sure if it will be finished by then, there's a lot of stuff to do (I've been following their Jira system).
I don't think mongodb supports this type of selective upserting. I have the same problem as LeMiz, and using update(criteria, newObj, upsert, multi) doesn't work right when dealing with both a 'created' and 'updated' timestamp. Given the following upsert statement:
update( { "name": "abc" },
{ $set: { "created": "2010-07-14 11:11:11",
"updated": "2010-07-14 11:11:11" }},
true, true )
Scenario #1 - document with 'name' of 'abc' does not exist:
New document is created with 'name' = 'abc', 'created' = 2010-07-14 11:11:11, and 'updated' = 2010-07-14 11:11:11.
Scenario #2 - document with 'name' of 'abc' already exists with the following:
'name' = 'abc', 'created' = 2010-07-12 09:09:09, and 'updated' = 2010-07-13 10:10:10.
After the upsert, the document would now be the same as the result in scenario #1. There's no way to specify in an upsert which fields be set if inserting, and which fields be left alone if updating.
My solution was to create a unique index on the critera fields, perform an insert, and immediately afterward perform an update just on the 'updated' field.
1. Use Update.
Drawing from Van Nguyen's answer above, use update instead of save. This gives you access to the upsert option.
NOTE: This method overrides the entire document when found (From the docs)
var conditions = { name: 'borne' } , update = { $inc: { visits: 1 }} , options = { multi: true };
Model.update(conditions, update, options, callback);
function callback (err, numAffected) { // numAffected is the number of updated documents })
1.a. Use $set
If you want to update a selection of the document, but not the whole thing, you can use the $set method with update. (again, From the docs)...
So, if you want to set...
var query = { name: 'borne' }; Model.update(query, ***{ name: 'jason borne' }***, options, callback)
Send it as...
Model.update(query, ***{ $set: { name: 'jason borne' }}***, options, callback)
This helps prevent accidentally overwriting all of your document(s) with { name: 'jason borne' }.
In general, using update is better in MongoDB as it will just create the document if it doesn't exist yet, though I'm not sure how to work that with your python adapter.
Second, if you only need to know whether or not that document exists, count() which returns only a number will be a better option than find_one which supposedly transfer the whole document from your MongoDB causing unnecessary traffic.
Method For Pymongo
The Official MongoDB Driver for Python
5% of the times you may want to update and overwrite, while other times you like to insert a new row, this is done with updateOne and upsert
95% (estimated) of the records are unmodified from day to day.
The following solution is taken from this core mongoDB function:
db.collection.updateOne(filter, update, options)
Updates a single document within the collection based on the filter.
This is done with this Pymongo's function update_one(filter, new_values, upsert=True)
Code Example:
# importing pymongo's MongoClient
from pymongo import MongoClient
conn = MongoClient('localhost', 27017)
db = conn.databaseName
# Filter by appliances called laptops
filter = { 'user_id': '4142480', 'question_id': '2801008' }
# Update number of laptops to
new_values = { "$set": { 'votes': 1400 } }
# Using update_one() method for single update with upsert.
db.collectionName.update_one(filter, new_values, upsert=True)
What upsert=True Do?
Creates a new document if no documents match the filter.
Updates a single document that matches the filter.
I do propose the using of await now.