I am writing gatling tests and using JSONPath $..parentId.
I am getting the response:
[
"102044",
"102044",
"102044"
]
I want to check that every value is equal to 102044. The amount of values can change.
By now I'm checking only random one:
#Then("then is successful")
override def thenStep(): Seq[HttpCheck] = {
var checks = List[HttpCheck]()
checks ::= status.is(session => 200)
checks ::= jsonPath("$..totalElements").ofType[Int].gt(8)
checks ::= jsonPath("$..totalElements").ofType[Int].lt(15)
checks ::= jsonPath("$.data[*].parentId").findRandom.is("102044")
checks
}
I tried to save the amount of values and the do something with it, like this:
checks ::= jsonPath("$..totalElements").ofType[Int].saveAs("all")
checks ::= jsonPath("$.data[*].parentId").findAll.is(Seq.fill(s"$all")("102044"))
But this is not working.
Is there a simple solution?
This question is similar to: In Gatling, how to iterate json array in .check to validate all values
What you should be able to do, using JMESPath is:
totalElements
To find the totalElements property of your JSON.
And
length(data[?parentId != '102044'])
To find if there are elements where the parentId is not 102044.
So, your assertions end up being be:
checks ::= jmesPath("totalElements").ofInt().gt(8)
checks ::= jmesPath("totalElements").ofInt().lt(15)
checks ::= jmesPath("length(data[?parentId != '102044'])").ofInt().is(0)
All this is based on the assumption that your input looks something like what you provided in your previous question:
{
"pageable": {
"currentPage": 1,
"totalPages": 1,
"pageSize": 20,
"last": true,
"first": true
},
"sort": {
"orders": [],
"sorted": false,
"unsorted": true,
"empty": true
},
"totalElements": 6,
"data": [
{
"id": 1,
"roleName": "test1",
"userCount": 5,
"parentId": "102044"
},
{
"id": 2,
"roleName": "test2",
"userCount": 5,
"parentId": "102045"
}
]
}
Related
DB collection seatsObj:
{
"product_id": 46539040,
"freeSeating": false,
"tempTransId": "1ecae165f2d86315fea19963d0ded41a",
"seatLayout": {
"colAreas": {
"Count": 2,
"intMaxSeatId": 43,
"intMinSeatId": 2,
"objArea": [
{
"AreaDesc": "EXECUTIVE",
"AreaCode": "0000000003",
"AreaNum": "1",
"HasCurrentOrder": true,
"objRow": [
{
"GridRowId": 1,
"PhyRowId": "A",
"objSeat": [
{
"GridSeatNum": 1,
"SeatStatus": "1",
"seatNumber": 1,
"seatPrice": 400,
"ID": 111
},
{
"GridSeatNum": 2,
"SeatStatus": "0",
"seatNumber": 2,
"seatPrice": 450,
"ID": 112
},
I was able to find ways to locate and update specific fields using:
seatsObj.updateOne(
{"seatLayout.colAreas.objArea.0.objRow.0.objSeat.seatPrice": 470},
{$set: {"seatLayout.colAreas.objArea.0.objRow.0.objSeat.$.ID": 888}});
but i cannot find simple way to return a specific field value from objSeat array element based on search criteria (for example: get 400 as a result of querying seatPrice for the seat with ID = 111). Could anyone give me a direction? From my initial research I have to go into crazy nested $unwind -s and $objectToArray -s, etc... Isn't there a simpler way? Thank you!!
I'm trying to search any value that match with a "name" param, inside any object with any level in a MongoDB collection.
My BSON looks like this:
{
"name": "a",
"sub": {
"name": "b",
"sub": {
"name": "c",
"sub": [{
"name": "d"
},{
"name": "e",
"sub": {
"name": "f"
}
}]
}
}
}
I've created an index with db.collection.createIndex({"name": "text"}); and it seems to work, because it has created more than one.
{
"numIndexesBefore" : 1,
"numIndexesAfter" : 6,
"note" : "all indexes already exist",
"ok" : 1
}
But, when I use this db.collection.find({$text: {$search : "b"}}); to search, it does not work. It just searches at the first level.
I cannot do a search with precision, because the dimensions of the objects/arrays is dynamic and can grow or shrink at any time.
I appreciate your answers.
MongoDB cannot build an index on arbitrarily-nested objects. The index only occurs for the depth specified. In your case, the $text search will only check the top-level name field, but not the name field for any of the nested sub-documents. This is an inherent limitation for indexing.
To my knowledge, MongoDB has no support for handling these kinds of deeply-nested data structures. You really need to break your data out into separate documents in order to handle it correctly. For example, you could break it out into the following:
[
{
"_id": 0,
"name": "a",
"root_id": null,
"parent_id": null
},
{
"_id": 1,
"name": "b",
"root_id": 0,
"parent_id": 0
},
{
"_id": 2,
"name": "c",
"root_id": 0,
"parent_id": 1
},
{
"_id": 3,
"name": "d",
"root_id": 0,
"parent_id": 2
},
{
"_id": 4,
"name": "e",
"root_id": 0,
"parent_id": 2
},
{
"_id": 5,
"name": "f",
"root_id": 0,
"parent_id": 4
}
]
In the above structure, our original query db.collection.find({$text: {$search : "b"}}); will now return the following document:
{
"_id": 1,
"name": "b",
"root_id": 0,
"parent_id": 0
}
From here we can retrieve all related documents by retrieving the root_id value and finding all documents with an _id or root_id matching this value:
db.collection.find({
$or: [
{_id: 0},
{root_id: 0}
]
});
Finding all root-level documents is a simple matter of matching on root_id: null.
The drawback, of course, is that now you need to assemble these documents manually after retrieval by matching a document's parent_id with another document's _id because the hierarchical information has been abstracted away. Using a $graphLookup could help alleviate this somewhat by matching each subdocument with a list of ancestors, but you would still need to determine the nesting order manually.
Regardless of how you choose to structure your documents moving forward, this sort of restructure is going to be needed if you're going to query on arbitrarily-nested content. I would encourage you to consider different possibilities and determine which is most suited for your specific application needs.
As the title says, I need to retrieve the names of all the keys in my MongoDB collection, BUT I need them split up based on a key/value pair that each document has. Here's my clunky analogy: If you imagine the original collection is a zoo, I need a new collection that contains all the keys Zebras have, all the keys Lions have, and all the keys Giraffes have. The different animal types share many of the same keys, but those keys are meant to be specific to each type of animal (because the user needs to be able to (for example) search for Zebras taller than 3ft and giraffes shorter than 10ft).
Here's a bit of example code that I ran which worked well - it grabbed all the unique keys in my entire collection and threw them into their own collection:
db.runCommand({
"mapreduce" : "MyZoo",
"map" : function() {
for (var key in this) { emit(key, null); }
},
"reduce" : function(key, stuff) { return null; },
"out": "MyZoo" + "_keys"
})
I'd like a version of this command that would look through the MyZoo collection for animals with "type":"zebra", find all the unique keys, and place them in a new collection (MyZoo_keys) - then do the same thing for "type":"lion" & "type":"giraffe", giving each "type" its own array of keys.
Here's the collection I'm starting with:
{
"name": "Zebra1",
"height": "300",
"weight": "900",
"type": "zebra"
"zebraSpecific1": "somevalue"
},
{
"name": "Lion1",
"height": "325",
"weight": "1200",
"type": "lion",
},
{
"name": "Zebra2",
"height": "500",
"weight": "2100",
"type": "zebra",
"zebraSpecific2": "somevalue"
},
{
"name": "Giraffe",
"height": "4800",
"weight": "2400",
"type": "giraffe"
"giraffeSpecific1": "somevalue",
"giraffeSpecific2": "someothervalue"
}
And here's what I'd like the MyZoo_keys collection to look like:
{
"zebra": [
{
"name": null,
"height": null,
"weight": null,
"type": null,
"zebraSpecific1": null,
"zebraSpecific2": null
}
],
"lion": [
{
"name": null,
"height": null,
"weight": null,
"type": null
}
],
"giraffe": [
{
"name": null,
"height": null,
"weight": null,
"type": null,
"giraffeSpecific1": null,
"giraffeSpecific2": null
}
]
}
That's probably imperfect JSON, but you get the idea...
Thanks!
You can modify your code to dump the results in a more readable and organized format.
The map function:
Emit the type of animal as key, and an array of keys for
each animal(document). Leave out the _id field.
Code:
var map = function(){
var keys = [];
Object.keys(this).forEach(function(k){
if(k != "_id"){
keys.push(k);
}
})
emit(this.type,{"keys":keys});
}
The reduce function:
For each type of animal, consolidate and return the unique keys.
Use an Object(uniqueKeys) to check for duplicates, this increases the running
time even if it occupies some memory. The look up is O(1).
Code:
var reduce = function(key,values){
var uniqueKeys = {};
var result = [];
values.forEach(function(value){
value.keys.forEach(function(k){
if(!uniqueKeys[k]){
uniqueKeys[k] = 1;
result.push(k);
}
})
})
return {"keys":result};
}
Invoking Map-Reduce:
db.collection.mapReduce(map,reduce,{out:"t1"});
Aggregating the result:
db.t1.aggregate([
{$project:{"_id":0,"animal":"$_id","keys":"$value.keys"}}
])
Sample o/p:
{
"animal" : "lion",
"keys" : [
"name",
"height",
"weight",
"type"
]
}
{
"animal" : "zebra",
"keys" : [
"name",
"height",
"weight",
"type",
"zebraSpecific1",
"zebraSpecific2"
]
}
{
"animal" : "giraffe",
"keys" : [
"name",
"height",
"weight",
"type",
"giraffeSpecific1",
"giraffeSpecific2"
]
}
I am trying to update a nested document in MongoDB that looks similar to below (shortened to be concise).
{
"cols": "20",
"saveTime": "2014-06-15-10:44:09",
"rows": "20",
"gameID" : "66f2497c-7a2b-4210-a06b-80be0e6a8fd8",
"players": [
{
"id": "Inhuman",
"num": "1",
"color": "00ff00ff",
"name": "badComputer",
"type": "1"
},
<...>
],
"nodes": [
{
"g": "1",
"c": "0",
"r": "0",
"a": "0",
"o": ""
},
{
"g": "1",
"c": "0",
"r": "1",
"a": "0",
"o": ""
}
<...>
],
}
What I am trying to do is update one of the nodes. For example, I want to change the node:
{ "g": "1", "c": "0", "r": "0", "a": "0", "o": ""}
to
{ "g": "1", "c": "0", "r": "0", "a": "5", "o": ""}
I have tried using the dot (.) notation, with the $set command, ala:
db.game.update({"gameID" : "66f2497c-7a2b-4210-a06b-80be0e6a8fd8"}, { $set: {"nodes.r":"0", "nodes.c":"0", "nodes.a":"5"}}),
But that does not give me the expected behavior because I'm updating all nodes with the same r and c values. This is obviously not what I want, but I do not see how to update a specific piece of this document. Does anyone have any idea how to do this?
If you are looking to update a specific item in your "nodes" array that you do not know the position of but you know the "criteria" to match that item, then you need the $elemMatch operator along with the positional $ operator in the update side:
db.game.update(
{
"gameID" : "66f2497c-7a2b-4210-a06b-80be0e6a8fd8",
"nodes": { "$elemMatch": { "g": 1, "r": 0 } }
},
{ "$set": { "nodes.$.c":"0", "nodes.$.a":"5" } }
)
The positional $ operator contains the matched "index" position of the first element "matched" by your query conditions. If you do not use $elemMatch and use the "dot notation" form instead, then the match is only valid for the whole document containing values that would be true and does not reflect the "position" of the element that matches both of the field conditions.
Care must be taken that this is the "first" match, and typically expected as the only match. The reason being that the positional operator will only contain the "first" position where there were multiple matches. To update more than one array item matching the criteria in this way, then you need to issue the update several times until the document is no longer modified.
For a "known" position you can always directly use the "dot notation" form, including the position of the element that you wish to update:
db.game.update(
{
"gameID" : "66f2497c-7a2b-4210-a06b-80be0e6a8fd8",
},
{ "$set": { "nodes.0.c":"0", "nodes.0.a":"5" } }
)
So the index position is 0 for the first element, 1 for the second element and so on.
Noting that in both cases, you only need to pass to $set the fields you actually want to change. So unless you are unsure of a value being present ( which would not be the case if that was your query ) then you do not need to "set" fields to the value they already contain.
To update specific node - you would need to put that in the query part of your search.
As in
db.game.update({"gameID" : "66f2497c-7a2b-4210-a06b-80be0e6a8fd8","nodes.r":"0",
"nodes.c":"0", "nodes.a":"5" }, { $set: {"nodes.$.r":"0", "nodes.$.c":"0", "nodes.$.a":"5"}})
You see the $ sign takes the node object it found that matches the first part (query) of the call, and sends you there in the second part (projection) part of your call.
Also check out this question
Im tring to set 0 the items.qty of a document obtains by a id query.
db.warehouses.update(
// query
{
_id:ObjectId('5322f07e139cdd7e31178b78')
},
// update
{
$set:{"items.$.qty":0}
},
// options
{
"multi" : true, // update only one document
"upsert" : true // insert a new document, if no existing document match the query
}
);
Return:
Cannot apply the positional operator without a corresponding query field containing an array.
This is the document that i want to set all items.qty to 0
{
"_id": { "$oid" : "5322f07e139cdd7e31178b78" },
"items": [
{
"_id": { "$oid" : "531ed4cae604d3d30df8e2ca" },
"brand": "BJFE",
"color": "GDRNCCD",
"hand": 1,
"model": 0,
"price": 500,
"qty": 0,
"type": 0
},
{
"brand": "BJFE",
"color": "GDRNCCD",
"hand": 1,
"id": "23",
"model": 0,
"price": 500,
"qty": 4,
"type": 0
},
{
"brand": "BJFE",
"color": "GDRNCCD",
"hand": 1,
"id": "3344",
"model": 0,
"price": 500,
"qty": 6,
"type": 0
}
],
"name": "a"
}
EDIT
The detail missing from the question was that the required field to update was actually in a sub-document. This changes the answer considerably:
This is a constraint of what you can possibly do with updating array elements. And this is clearly explained in the documentation. Mostly in this paragraph:
The positional $ operator acts as a placeholder for the first element that matches the query document
So here is the thing. Trying to update all of the array elements in a single statement like this will not work. In order to do this you must to the following.
db.warehouses.find({ "items.qty": { "$gt": 0 } }).forEach(function(doc) {
doc.items.forEach(function(item) {
item.qty = 0;
});
db.warehouses.update({ "_id": doc._id }, doc );
})
Which is basically the way to update every array element.
The multi setting in .update() means across multiple "documents". It cannot be applied to multiple elements of an array. So presently the best option is to replace the whole thing. Or in this case we may just as well replace the whole document since we need to do that anyway.
For real bulk data, use db.eval(). But please read the documentation first:
db.eval(function() {
db.warehouses.find({ "items.qty": { "$gt": 0 } }).forEach(function(doc) {
doc.items.forEach(function(item) {
item.qty = 0;
});
db.warehouses.update({ "_id": doc._id }, doc );
});
})
Updating all the elements in an array across the whole collection is not simple.
Original
Pretty much exactly what the error says. In order to use a positional operator you need to match something first. As in:
db.warehouses.update(
// query
{
_id:ObjectId('5322f07e139cdd7e31178b78'),
"items.qty": { "$gt": 0 }
},
// update
{
$set:{"items.$.qty":0}
},
// options
{
"multi" : true,
"upsert" : true
}
);
So where the match condition fins the position of the items that are less than 0 then that index is passed to the positional operator.
P.S : When muti is true it means it updates every document. Leave it false if you only mean one. Which is the default.
You can use the $ positional operator only when you specify an array in the first argument (i.e., the query part used to identify the document you want to update).
The positional $ operator identifies an element in an array field to update without explicitly specifying the position of the element in the array.