I have a mongo collection where each document has a 'loc' array as follows:
> db.trucks.findOne()
{
"_id" : ObjectId("52afe2a9e8de3f311ec675ee"),
"objectid" : "427856",
"fooditems" : "Cupcakes",
"facilitytype" : "Truck",
"loc" : [
37.7901490737255,
-122.398658184604
],
"priorpermit" : "0",
"location" : {
"latitude" : "37.7901490874965",
"needs_recoding" : false,
"longitude" : "-122.398658184594"
},
"lot" : "055",
"cnn" : "101000",
"status" : "REQUESTED",
"schedule" : "http://bsm.sfdpw.org/PermitsTracker/reports/report.aspx?title=schedule&report=rptSchedule¶ms=permit=13MFF-0068&ExportPDF=1&Filename=13MFF-0068_schedule.pdf",
"locationdescription" : "01ST ST: STEVENSON ST to JESSIE ST (21 - 56)",
"latitude" : "37.7901490737255",
"blocklot" : "3708055",
"address" : "50 01ST ST",
"received" : "Mar 14 2013 3:34PM",
"applicant" : "Cupkates Bakery, LLC",
"longitude" : "-122.398658184604",
"expirationdate" : "2013-03-15T00:00:00",
"permit" : "13MFF-0068",
"y" : "2115738.283",
"x" : "6013063.33",
"block" : "3708"
}
When I try to index on 'loc', it doesn't get added:
> db.trucks.ensureIndex( { loc : "2d" } )
> db.trucks.getIndexes()
[
{
"v" : 1,
"key" : {
"_id" : 1
},
"ns" : "food.trucks",
"name" : "_id_"
}
]
What am I doing wrong?
Shouldn't be db.trucks.ensureIndex( { loc : "2d" } )? You are creating indexes on some other collection.
Related
I need to execute the following query:
db.S12_RU.find({"venue.raw":a,"title":/b|c|d|e/}).sort({"year":-1}).skip(X).limit(Y);
where X and Y are numbers.
The number of documents in my collection is:
208915369
Currently, this sort of query takes about 6 minutes to execute.
I have the following indexes:
[
{
"v" : 2,
"key" : {
"_id" : 1
},
"name" : "_id_"
},
{
"v" : 2,
"key" : {
"venue.raw" : 1
},
"name" : "venue.raw_1"
},
{
"v" : 2,
"key" : {
"venue.raw" : 1,
"title" : 1,
"year" : -1
},
"name" : "venue.raw_1_title_1_year_-1"
}
]
A standard document looks like this:
{ "_id" : ObjectId("5fc25fc091e3146fb10484af"), "id" : "1967181478", "title" : "Quality of Life of Swedish Women with Fibromyalgia Syndrome, Rheumatoid Arthritis or Systemic Lupus Erythematosus", "authors" : [ { "name" : "Carol S. Burckhardt", "id" : "2052326732" }, { "name" : "Birgitha Archenholtz", "id" : "2800742121" }, { "name" : "Kaisa Mannerkorpi", "id" : "240289002" }, { "name" : "Anders Bjelle", "id" : "2419758571" } ], "venue" : { "raw" : "Journal of Musculoskeletal Pain", "id" : "49327845" }, "year" : 1993, "n_citation" : 31, "page_start" : "199", "page_end" : "207", "doc_type" : "Journal", "publisher" : "Taylor & Francis", "volume" : "1", "issue" : "", "doi" : "10.1300/J094v01n03_20" }
Is there any way to make this query execute in a few seconds?
in my collection i have this document:
{
"_id" : ObjectId("5eecb84a9e41ff609fd6389a"),
"uid" : NumberLong(619942065802969109),
"banmute" : 0,
"expire" : ISODate("2023-03-15T13:06:18.694Z"),
"fid" : "3cac4490b6ca491e838d4e5317e5b87e",
"id" : null,
"nick" : "Flawe",
"nicks_ld" : "",
"old_nicks" : "",
"reason" : ""
}
Indexes is:
/* 1 */
[
{
"v" : 2,
"key" : {
"_id" : 1
},
"name" : "_id_",
"ns" : "fsl.index_profile"
},
{
"v" : 2,
"unique" : true,
"key" : {
"uid" : 1
},
"name" : "uid_1",
"ns" : "fsl.index_profile",
"background" : true
}
]
On direct request i have null answer:
db.getCollection('index_profile').findOne({uid: 619942065802969109})
result: ->
null
But if i request $gte i found it:
db.getCollection('index_profile').find({uid: {$gte: 619942065802969109}}).limit(1)
result: ->
/* 1 */
{
"_id" : ObjectId("5eecb84a9e41ff609fd6389a"),
"uid" : NumberLong(619942065802969109),
"banmute" : 0,
"expire" : ISODate("2023-03-15T13:06:18.694Z"),
"fid" : "3cac4490b6ca491e838d4e5317e5b87e",
"id" : null,
"nick" : "Flawe",
"nicks_ld" : "",
"old_nicks" : "",
"reason" : ""
}
I tried deleting the cache, rebooting the server, deleting indexes, assigned different new indexes
I am in despair, help solve this problem
have you tried:
db.getCollection('index_profile').findOne({uid: NumberLong(619942065802969109)})
I am pretty new to mongodb. I have 3 levels of documents.
Parent > Child > Child, all having _id field.
{
"_id" : "n2qw5sojs4bajrj",
"Title" : "Mr",
"Instance" : "HQ",
"FirstName" : "ppp",
"LastName" : "uuuu",
"Position" : "BF",
"EmailAddress" : "xxx#ppp.com",
"Requests" : [
{
"_id" : "121",
"Date" : "12/02/2018",
"Status" : "New",
"ApprovedBy" : {
"_id" : "sdfsdf",
"Name" : "MAN"
},
"PPE" : [
{
"_id" : "121",
"Code" : "PPE",
"Status" : "New",
"Title" : "Trousers",
"Type" : "STD",
"Size" : "10111116",
"Qty" : 1,
"LostDamage" : {
"Reason" : "asdaD",
"Location" : "Station",
"Damage" : "Damged"
}
},
{
"_id" : "122",
"Code" : "PPEOPP",
"Status" : "New",
"Title" : "TrousASDASDASDers",
"Type" : "STD",
"Size" : "10111116",
"Qty" : 1,
"LostDamage" : {
"Reason" : "asdaD",
"Location" : "Station",
"Damage" : "Damged"
}
}
]
}
]
}
I would like find out how to delete the last PPE Element (Parent > Request > PPE) by the _id column.
So I would to delete the following child:
{
"_id" : "121",
"Code" : "PPE",
"Status" : "New",
"Title" : "Trousers",
"Type" : "STD",
"Size" : "10111116",
"Qty" : 1,
"LostDamage" : {
"Reason" : "asdaD",
"Location" : "Station",
"Damage" : "Damged"
}
}
Any tips / help would be great.
Thanks
Paul
You can use MongoDb $pop to remove your last element from array. Like this go to https://docs.mongodb.com/manual/reference/operator/update/pop/
db.collection.update({id:1}, { $pop:{ 'request.PPE':1}});
i've passed a mysql database to mongoDB for a project. My db is about a pharmacy. I have a collection of factures, where which has the list of medicines sold. I'm trying to find the medicine which was sold the most.
{
"_id" : ObjectId("5c3c71f2760c4f47c701fe13"),
"cliente" : {
"tlmv" : "910987654",
"nome" : "Josefina Vivida da Paz",
"nif" : "122133144",
"pontos" : NumberLong(0),
"id" : NumberLong(2),
"pass" : "1eab06cab995dfeb32b6b7c709b8a6c62cabacfe",
"email" : "josefina#hotmail.pt"
},
"data_f" : ISODate("2018-06-03T00:00:01Z"),
"data_s" : ISODate("2018-06-02T23:55:59Z"),
"desconto" : 0,
"funcionario" : {
"tlmv" : "934567123",
"nome" : "Pedro Jorge Rito Lima",
"ordenado" : 800.32,
"iban" : "PT 50 2751 3262 76598707612",
"pass" : "3cfa1c281281ffe4f5db2ccfbe7a17f8a9479808",
"niss" : "14385639201",
"id" : NumberLong(2),
"cedula" : "54321"
},
"id" : NumberLong(15),
"id_c" : NumberLong(2),
"id_func" : NumberLong(2),
"medicamentos" : [
{
"categoria" : "Analg�sico",
"receita" : "N",
"des" : "Ben-U-Ron 500",
"qt" : 20,
"formato" : "granulado",
"qt_v" : NumberLong(1),
"pos" : "A12",
"lab" : "Laborat�rio do Rio Ave",
"preco_l" : 2.51,
"un" : "un",
"preco" : 2.51,
"preco_v" : 2.51,
"id" : NumberLong(1),
"stock" : NumberLong(21)
},
{
"categoria" : "Estatina",
"receita" : "S",
"des" : "Sinvastatina",
"qt" : 30,
"formato" : "comprimido",
"qt_v" : NumberLong(1),
"pos" : "K23",
"lab" : "Mylan",
"preco_l" : 16.45,
"un" : "un",
"preco" : 16.45,
"preco_v" : 16.45,
"id" : NumberLong(6),
"stock" : NumberLong(25)
}
],
"pontos_r" : NumberLong(10),
"pontos_u" : NumberLong(0),
"total" : 18.96
}
So my objective is to count every medicine -"medicamento"- sorted by different descriptions-"des". Similiar to Count on mysql. Any ideas how? The code above is abount 1 facture.
You need $unwind to get a medicine per document and then $group with $sum to get count per medicine, try:
db.collection.aggregate([
{
$unwind: "$medicamentos"
},
{
$group: {
_id: "$medicamentos.des",
count: { $sum: 1 }
}
}
])
the collection nodesWays has the following indexes:
> db.nodesWays.getIndexes()
[
{
"v" : 1,
"key" : {
"_id" : 1
},
"name" : "_id_",
"ns" : "h595.nodesWays"
},
{
"v" : 1,
"key" : {
"amenity" : 1,
"geo" : "2dsphere"
},
"name" : "amenity_1_geo_2dsphere",
"ns" : "h595.nodesWays",
"2dsphereIndexVersion" : 2
},
{
"v" : 1,
"key" : {
"geo" : "2dsphere"
},
"name" : "geo_2dsphere",
"ns" : "h595.nodesWays",
"2dsphereIndexVersion" : 2
}
]
Now the following two queries should return the same result, but they don't.
I want the nearest 10 restaurants to the specified point.
The first query is working how it should be, the second is not working like intended.
The only difference between these two queries is that the first one uses the geo_2dsphere-Index
and the second query the amenity_1_geo_2dsphere-Index.
> db.nodesWays.find(
{
geo:{
$nearSphere:{
$geometry:{
type: "Point", coordinates: [9.7399777,52.3715156]
}
}
}, "amenity":"restaurant",
name: {$exists: true}
}, {id:1, name:1}).hint( "geo_2dsphere" ).limit(10)
{ "_id" : ObjectId("53884860e552e471be2b7192"), "id" : "321256694", "name" : "Masa" }
{ "_id" : ObjectId("53884860e552e471be2b7495"), "id" : "323101271", "name" : "Bavarium" }
{ "_id" : ObjectId("53884862e552e471be2ba605"), "id" : "442496282", "name" : "Naxos" }
{ "_id" : ObjectId("53884860e552e471be2b7488"), "id" : "323101189", "name" : "Block House" }
{ "_id" : ObjectId("53884878e552e471be2d1a41"), "id" : "2453236451", "name" : "Maestro" }
{ "_id" : ObjectId("53884870e552e471be2c8aab"), "id" : "1992166428", "name" : "Weinstube Leonardo Ristorante" }
{ "_id" : ObjectId("53884869e552e471be2c168b"), "id" : "1440320284", "name" : "Altdeutsche küche" }
{ "_id" : ObjectId("53884861e552e471be2b88f7"), "id" : "353119010", "name" : "Mövenpick" }
{ "_id" : ObjectId("5388485de552e471be2b2c86"), "id" : "265546900", "name" : "Miles" }
{ "_id" : ObjectId("53884863e552e471be2bb5d3"), "id" : "532304135", "name" : "Globetrotter" }
> db.nodesWays.find(
{
geo:{
$nearSphere:{
$geometry:{
type: "Point", coordinates: [9.7399777,52.3715156]
}
}
}, "amenity":"restaurant",
name: {$exists: true}
}, {id:1, name:1}).hint( "amenity_1_geo_2dsphere" ).limit(10)
{ "_id" : ObjectId("53884875e552e471be2cf4a8"), "id" : "2110027373", "name" : "Schloßhof Salder" }
{ "_id" : ObjectId("5388485be552e471be2aff19"), "id" : "129985174", "name" : "Balkan Paradies" }
{ "_id" : ObjectId("5388485be552e471be2afeb4"), "id" : "129951134", "name" : "Asia Dragon" }
{ "_id" : ObjectId("53884863e552e471be2ba811"), "id" : "450130115", "name" : "Kings Palast" }
{ "_id" : ObjectId("53884863e552e471be2ba823"), "id" : "450130135", "name" : "Restaurant Montenegro" }
{ "_id" : ObjectId("53884877e552e471be2d053a"), "id" : "2298722569", "name" : "Pizzaria Da-Lucia" }
{ "_id" : ObjectId("53884869e552e471be2c152e"), "id" : "1420101752", "name" : "Napoli" }
{ "_id" : ObjectId("5388485be552e471be2b0028"), "id" : "136710095", "name" : "Europa" }
{ "_id" : ObjectId("53884862e552e471be2ba5bc"), "id" : "442136241", "name" : "Syrtaki" }
{ "_id" : ObjectId("53884863e552e471be2ba763"), "id" : "447972565", "name" : "Pamukkale" }
My goal with the second index is to:
select all restaurants
then use the nearSphere-Operator to sort them in regards to the distance from the specified point
Auf Wiedersehen
I think you should try to put the geolocation first in the index.