Here is how the documents in db look like.
/* 1 */
{
"_id" : 1,
"feat" : {
"processName": [
{
"value" : {
"value": "Process1"
}
}
],
"processUsage": [
{
"value" : {
"value": 23.21
}
}
]
}
}
/* 2 */
{
"_id" : 2,
"feat" : {
"processName": [
{
"value" : {
"value": "Process2"
}
}
],
"memoryUsage": [
{
"value" : {
"value": 2.411502e+05
}
}
]
}
}
/* 3 */
{
"_id" : 3,
"feat" : {
"processName": [
{
"value" : {
"value": "Process1"
}
}
],
"processUsage": [
{
"value" : {
"value": 67.42
}
}
]
}
}
/* 4 */
{
"_id" : 4,
"feat" : {
"processName": [
{
"value" : {
"value": "Process3"
}
}
],
"processUsage": [
{
"value" : {
"value": 39.97
}
}
]
}
}
/* 5 */
{
"_id" : 5,
"feat" : {
"processName": [
{
"value" : {
"value": "Process2"
}
}
],
"processUsage": [
{
"value" : {
"value": 21.05
}
}
]
}
}
Each process has entries with processUsage and memoryUsage. What I am interest in is the average processUsage. So, I'd like to ignore the entries with memoryUsage.
I tried $match + $group in an aggregate with $avg, but for each process I just got back as average 0.00000000.
Then I tried my luck with mapReduce using javascript, unfortunately it did not work out either.
Could someone just show me how to do that? By the way, I am using Robomongo 0.8.5
Edit:
The query looks like this:
db.database.aggregate([
{ $match : {"$feat.processUsage.value.value": {$gt : -1}
},
{
$group: {_id: "$feats.processName.value.value", average: {$avg:
"$feats.processUsage.value.value"}
}
])
You can use the following aggregate query:
db.test.aggregate(
[
{
$unwind : "$feat.processUsage"
},
{
$group: {
_id: "$feat.processName.value.value",
average: {$avg:"$feat.processUsage.value.value"}
}
}
]
)
Unwinding in the initial phase will let you filter documents that has processUsage key in document.
Result:
{ "_id" : [ "Process2" ], "average" : 21.05 }
{ "_id" : [ "Process3" ], "average" : 39.97 }
{ "_id" : [ "Process1" ], "average" : 45.315 }
Related
Customer appointments with top level locationId sample data set:
[
{
"locationId": 9999,
"customerAppointments": [
{
"customerId": "1",
"appointments": [
{
"appointmentId": "cbbce566-da59-42c2-8845-53976ba63d56",
"locationName": "Sullivan St"
},
{
"appointmentId": "5f09e2af-ddae-47aa-9f7c-fd1001a9c5e6",
"locationName": "Oak St"
}
]
},
{
"customerId": "2",
"appointments": [
{
"appointmentId": "964a3c1c-ccec-4082-99e2-65795352ba79",
"locationName": "Kellet St"
}
]
},
{
"customerId": "3",
"appointments": []
}
]
},
{
...
},
{
...
}
]
I need to pull out appointment by locationId and customerId and only get the appointment for that customerId e.g
Sample response:
[
{
"appointmentId": "964a3c1c-ccec-4082-99e2-65795352ba79",
"locationName": "Kellet St"
}
]
Tried below query, but it just returns all records for all customers ids (which is kind of expected):
db.getCollection("appointments").find(
{
"locationId" : NumberInt(9999),
"customerAppointments" : {
"$elemMatch" : {
"customerId" : "2"
}
}
}
);
But how can I get just the appointment record for a specific customerId?
When asking this question I was unaware of the older version of MongoDB driver (< v5) so we cannot use the $getField operator.
However, this query seems to work well:
db.getCollection("appointments").aggregate([
{
$match: {
"locationId": NumberInt(9999)
}
},
{
$unwind: "$customerAppointments"
},
{
$match: {
"customerAppointments.customerId": "2"
}
},
{
$project: {
appointments: "$customerAppointments.appointments"
}
}
]);
Yields:
{
"_id" : ObjectId("63eebe95c7a0da54804c1db2"),
"appointments" : [
{
"appointmentId" : "964a3c1c-ccec-4082-99e2-65795352ba79",
"locationName" : "Kellet St"
}
]
}
I need to update the MongoDB field with the array of objects where JSON object to be updated with as an array
if I have something like this in MongoDB
"designSectionContents" : [
{
"_id" : "5bae17ecbd7595540145ec98",
"type" : "subSection",
"columns" : [
{
"0" : {
"itemId" : "5b7465980783d9a37058f160",
"type" : "field"
}
},
{
"0" : {
"itemId" : "5b7465630783d9a37058f15c",
"type" : "field"
}
},
{
"0" : {
"itemId" : "5b7465810783d9a37058f15e",
"type" : "field"
}
}
],
"subSectionContentLayout" : {
"labelPlacement" : "Top",
"columns" : 3
}
}
]
I want to change the above snippet to below in MongoDB
"designSectionContents" : [
{
"_id" : ObjectId("5bae17ecbd7595540145ec98"),
"type" : "subSection",
"columns" : [
[
{
"itemId" : "5b7465980783d9a37058f160",
"type" : "field"
}
],
[
{
"itemId" : "5b7465630783d9a37058f15c",
"type" : "field"
}
],
[
{
"itemId" : "5b7465810783d9a37058f15e",
"type" : "field"
}
]
]
}
]
curly braces opening and closing tag has to be changed to array
This should work:
db.collection.aggregate([
{
"$project": {
"designSectionContents": {
"$map": {
"input": "$designSectionContents",
"as": "designSectionContent",
"in": {
"_id": "$$designSectionContent._id",
"type": "$$designSectionContent.type",
"columns": {
"$map": {
"input": "$$designSectionContent.columns",
"as": "inp",
"in": [
"$$inp.0"
]
}
}
}
}
}
}
}
]);
Here's the working link.
I wanted to provide explicit mapping to the fields in my document, So I defined a mapping for my index demo and It looks like this below:
PUT /demo
{
"mappings": {
"properties": {
"X" : {
"X" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"Sub_X" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
}
}
}
After running the query , I am getting error as :
{
"error" : {
"root_cause" : [
{
"type" : "mapper_parsing_exception",
"reason" : "No type specified for field [X]"
}
],
"type" : "mapper_parsing_exception",
"reason" : "Failed to parse mapping [_doc]: No type specified for field [X]",
"caused_by" : {
"type" : "mapper_parsing_exception",
"reason" : "No type specified for field [X]"
}
},
"status" : 400
}
The field X in json document looks like :
"X" : {
"X" : [
"a"
],
"Sub_X" : [
[
"b"
]
]
},
Please help me out with this elastic search mapper_parse_exception error.
What you have is called nested data type
You have X which in turn contains X and Sub_X.
Mapping:
{
"properties": {
"X": {
"type": "nested"
}
}
}
Data:
{
"X": {
"X": [
"a"
],
"Sub_X": [
[
"b"
]
]
}
}
Query:
{
"query": {
"nested": {
"path": "X",
"query": {
"bool": {
"must": [
{ "match": { "X.X": "a" }},
{ "match": { "X.Sub_X": "b" }}
]
}
}
}
}
}
It outputs the document.
below is my query:
while executing below query getting mongoerror : Expression $in takes exactly 2 arguments. 1 were passed in.
i am using $in Comparison operator
{
"$expr": {
"$not": {
"$eq":{
"$and": [
{
"PrName": {
"$in": [
"pname"
]
}
},
{
"AccountId": {
"$in": [
"34562",
"88765",
"87654",
"12345"
]
}
}
]
}
}
}
}
When you use $expr, the operator expressions syntax changes a little:
{ $in: [ <expression>, <array expression> ] }
{
"$expr": {
"$not": {
"$and": [
{
"$in": [
"$PrName",
[
"pname"
]
]
},
{
"$in": [
"$AccountId",
[
"34562",
"88765",
"87654",
"12345"
]
]
}
]
}
}
}
I am trying to add a "not" filter inside "and" filter
Sample input:
{
"query":{
"filtered":{
"query":{
"query_string":{
"query":"error",
"fields":[
"request"
]
}
},
"filter":{
and:[
{
"terms":{
"hashtag":[
"br2"
]
},
"not":{
"terms":{
"hashtag":[
"br1"
]
}
}
}
]
}
}
}
},
}
But above is giving error, i also tried various combination but in vain.
Above is just an example in short i require a query in which both "and", "not" filter are present.
you forgot the "filters" array.
Write it like this :
{
"from" : 0,
"size" : 25,
"query" : {
"filtered" : {
"query" : {
"match_all" : {}
},
"filter" : {
"and" : {
"filters" : [{
"term" : {
"field1" : "val1"
}
}, {
"not" : {
"filter" : {
"term" : {
"field2" : "val2",
}
}
}
}
]
}
}
}
}
}