I have a collection like this
{
"_id" : ObjectId("54368d9125c3dc7c1f43295f"),
"nome" : "John",
"eta" : 30,
"data" : ISODate("2014-10-09T10:30:00.000Z")
}
{
"_id" : ObjectId("54368d9c25c3dc7c1f432960"),
"nome" : "Paul",
"eta" : 31
}
And I do this Query
db.coll.find({eta:{$gt:30}})
My result is one Document (Paul)
db.coll.find({eta:{$gt:30}}).count() //1
If i do
db.coll.find({eta:{$gt:30}}).skip(1)
I haven't Result,and it's ok.
But If i do this
db.coll.find({eta:{$gt:30}}).skip(1).count()
my Result is 1
From the documentation for count():
By default, the count() method ignores the effects of the cursor.skip() and cursor.limit(). Set applySkipLimit to true to consider the effect of these methods.
So you can supply an optional parameter named applySkipLimit to count(), if you want the effect of skip() to be considered, like this:
db.coll.find({eta:{$gt:30}}).skip(1).count({applySkipLimit:1});
or simply
db.coll.find({eta:{$gt:30}}).skip(1).count(true);
Use size instead of count as it includes the effects of any skip and limit calls on the cursor:
db.coll.find({eta:{$gt:30}}).skip(1).size()
Related
for a collection as below
Document 1
{
"entity" : "university",
"parEnityHRCHY" : "Planet>continent>country>state>city",
"parEnityVal" : "earth>North America>Massachusetts>Boston",
"entityVal" : [
"MIT",
"Harvard",
"New England"
]
}
Document 2
{
"entity" : "university",
"parEnityHRCHY" : "Planet>continent>country>state",
"parEnityVal" : "earth>North America>Massachusetts",
"entityVal" : [
"A",
"B",
"C"
]
}
i want to fetch the best match "entityVal" for the input "entity","parEnityHRCHY","parEnityVal"
if the value is not available at the exact match it should look recursively till the root.
for eg. in above case if "university" value are not available at the city level it should look at the state level like
if matches exact below condition return result.
Input:
"parEnityHRCHY" : "Planet>continent>country>state>city",
"parEnityVal" : "earth>North America>Massachusetts>Boston",
else look at one level up
"parEnityHRCHY" : "Planet>continent>country>state",
"parEnityVal" : "earth>North America>Massachusetts",
and so on until the root element.
please suggest some approach, i am planning to use $text search , max number of documents in collection approx 1 Million, max HRCHY level 10.
You can try something like this:
db.doc.find({"parEnityHRCHY" : "Planet>continent>country>state",'parEnityVal':{$regex:"earth>North America>Massachusetts"}})
But I am not sure If you're looking for something like this.
Sample json object :
{ "_id" : ObjectId( "55887982498e2bef5a5f96db" ),
"a" : "x",
"q" : "null",
"p" : "",
"s" : "{\"f\":{\"b\":[\"I\"]},\"time\":\"fs\"}" }
need all documents where time = fs
My query :
{"s":{"time" : "fs"}}
above returns zero products but that is not true.
There are two problems here. First of all s is clearly a string so your query cannot work. You can use $regex as below but it won't be very efficient:
{s: {$regex: '"time"\:"fs"'}}
I would suggest converting s fields to proper documents. You can use JSON.parse to do it. Documents can be updated based on a current value using db.foo.find().snapshot().forEach. See this answer for details.
Second problem is your query is simply wrong. To match time field you should use dot notation:
{"s.time" : "fs"})
very interesting, mapreduce works fine in a single instance, but not on a sharded collection. as below, you may see that i got a collection and write a simple map-reduce
function,
mongos> db.tweets.findOne()
{
"_id" : ObjectId("5359771dbfe1a02a8cf1c906"),
"geometry" : {
"type" : "Point",
"coordinates" : [
131.71778292855996,
0.21856835860911106
]
},
"type" : "Feature",
"properties" : {
"isflu" : 1,
"cell_id" : 60079,
"user_id" : 35,
"time" : ISODate("2014-04-24T15:42:05.048Z")
}
}
mongos> db.tweets.find({"properties.user_id":35}).count()
44247
mongos> map_flow
function () { var key=this.properties.user_id; var value={ "cell_id":1}; emit(key,value); }
mongos> reduce2
function (key,values){ var ros={flows:[]}; values.forEach(function(v){ros.flows.push(v.cell_id);});return ros;}
mongos> db.tweets.mapReduce(map_flow,reduce2, { out:"flows2", sort:{"properties.user_id":1,"properties.time":1} })
but the results are not what i want
mongos> db.flows2.find({"_id":35})
{ "_id" : 35, "value" : { "flows" : [ null, null, null ] } }
I got lots of null and interesting all have three ones.
mongodb mapreduce seems not right on sharded collection?
The number one rule of MapReduce is:
thou shall emit the value of the same type as reduce function returneth
You broke this rule, so your MapReduce only works for small collection where reduce is only called once for each key (that's the second rule of MapReduce - reduce function may be called zero, once or many times).
Your map function emits exactly this value {cell_id:1} for each document.
How does your reduce function use this value? Well, you return a value which is a document with an array, into which you push the cell_id value. This is strange already, because that value was 1, so I'm not sure why you wouldn't just emit 1 (if you wanted to count).
But look what happens when multiple shards push a bunch of 1's into this flows array (whether it's what you intended, that's what your code is doing) and now reduce is called on several already reduced values:
reduce(key, [ {flows:[1,1,1,1]},{flows:[1,1,1,1,1,1,1,1,1]}, etc ] )
Your reduce function now tries to take each member of the values array (which is a document with a single field flows) and you push v.cell_id to your flows array. There is no cell_id field here, so of course you end up with null. And three nulls could be because you have three shards?
I would recommend that you articulate to yourself what exactly you are trying to aggregate in this code, and then rewrite your map and your reduce to comply with the rules that mapReduce in MongoDB expects your code to follow.
Gurus - I'm stuck in a situation that I can't figure out how I can query from the following collection "spouse", which has embedded document "surname" and check for equality with "surname" of this document:
{
"_id" : ObjectId("50bd2bb4fcfc6066b7ef090d"),
"name" : "Gwendolyn",
"surname" : "Davis",
"birthyear" : 1978,
"spouse" : {
"name" : "Dennis",
"surname" : "Evans",
"birthyear" : 1969
},
I need to query:
Output data for all spouses with the same surnames (if the surname of
one of the spouses is not specified, assume that it coincides with the
name of another)
I tried something like this:
db.task.find( {"surname" : { "spouse.surname" : 1 }} )
but it failed)
PLEASE PLEASE Guide me how I can achieve this any example/sample? based on this will be really helpful :-)
Thanks a lot!
You have three options.
Use $where modifier:
db.task.find({$where: 'this.spouse.surname === this.surname'})
Update all your documents and add special flag. After that you will be able to query documents by this flag. It's faster then $where, but requires altering your data.
Use MapReduce. It's quite complicated, but it allows you to do nearly anything.
I have a Mongo find query that works well to extract specific fields from a large document like...
db.profiles.find(
{ "profile.ModelID" : 'LZ241M4' },
{
_id : 0,
"profile.ModelID" : 1,
"profile.AVersion" : 2,
"profile.SVersion" : 3
}
);
...this produces the following output. Note how the SVersion comes before the AVersion in the document even though my projection asked for AVersion before SVersion.
{ "profile" : { "ModelID" : "LZ241M4", "SVersion" : "3.5", "AVersion" : "4.0.3" } }
{ "profile" : { "ModelID" : "LZ241M4", "SVersion" : "4.0", "AVersion" : "4.0.3" } }
...the problem is that I want the output to be...
{ "profile" : { "ModelID" : "LZ241M4", "AVersion" : "4.0.3", "SVersion" : "3.5" } }
{ "profile" : { "ModelID" : "LZ241M4", "AVersion" : "4.0.3", "SVersion" : "4.0" } }
What do I have to do get the Mongo JavaScript shell to present the results of my query in the field order that I specify?
I have achieved it by projecting the fields using aliases, instead of including and excluding by 0 and 1s.
Try this:
{
_id : 0,
"profile.ModelID" :"$profile.ModelID",
"profile.AVersion":"$profile.AVersion",
"profile.SVersion":"$profile.SVersion"
}
I get it now. You want to return results ordered by "fields" rather the value of a fields.
Simple answer is that you can't do this. Maybe its possible with the new aggregation framework. But this seems overkill just to order fields.
The second object in a find query is for including or excluding returned fields not for ordering them.
{
_id : 0, // 0 means exclude this field from results
"profile.ModelID" : 1, // 1 means include this field in the results
"profile.AVersion" :2, // 2 means nothing
"profile.SVersion" :3, // 3 means nothing
}
Last point, you shouldn't need to do this, who cares what order the fields come-back in.
You application should be able to make use of the fields it needs regardless of the order the fields are in.
Another solution I applied to achieve this is the following:
db.profiles
.find({ "profile.ModelID" : 'LZ241M4' })
.toArray()
.map(doc => ({
profile: {
ModelID: doc.profile.ModelID,
AVersion: doc.profile.AVersion,
SVersion: doc.profile.SVersion
}
}))
Since version 2.6 (that came out in 2014) MongoDB preserves the order of the document fields following the write operation (source).
P.S. If you are using Python you might find this interesting.