Possible duplicate
What I'm specifically looking for are analogs for the LEFT, SUBSTRING and REPLACE functions from SQL in mongo.
After researching this for some time, I can't find any direct analogs for those functions nor am I seasoned enough with mongodb that I can see another way of performing an equivalent operation.
An example of a similar query that I'm looking for is as follows:
REPLACE(case when LEFT(title,1) = '"' then SUBSTRING(title, 2, LEN(title)) else title end,char(9),'')
Which is to be used as part of a $project.
Cheers.
String operations you need:
{ $concat: [ <expression1>, <expression2>, ... ] }
{ $substr: [ <string>, <start>, <length> ] }
Examples:
{ "_id" : 1, "item" : "ABC1", quarter: "13Q1", "description" : "product 1" }
{ "_id" : 2, "item" : "ABC2", quarter: "13Q4", "description" : "product 2" }
{ "_id" : 3, "item" : "XYZ1", quarter: "14Q2", "description" : null }
Concat:
db.inventory.aggregate(
[
{ $project: { itemDescription: { $concat: [ "$item", " - ", "$description" ] } } }
]
)
Substr:
db.inventory.aggregate(
[
{
$project:
{
item: 1,
yearSubstring: { $substr: [ "$quarter", 0, 2 ] },
quarterSubtring: { $substr: [ "$quarter", 2, -1 ] }
}
}
]
)
Look at the string operations here. I think you should combine $cond-operator with the string ones.
Related
I have a Mongo collection that contains data on saved searches in a Vue/Laravel app, and it contains records like the following:
{
"_id" : ObjectId("6202f3357a02e8740039f343"),
"q" : null,
"name" : "FCA last 3 years",
"frequency" : "Daily",
"scope" : "FederalContractAwardModel",
"filters" : {
"condition" : "AND",
"rules" : [
{
"id" : "awardDate",
"operator" : "between_relative_backward",
"value" : [
"now-3.5y/d",
"now/d"
]
},
{
"id" : "subtypes.extentCompeted",
"operator" : "in",
"value" : [
"Full and Open Competition"
]
}
]
},
The problem is the value in the item in the rules array that has the decimal.
"value" : [
"now-3.5y/d",
"now/d"
]
in particular the decimal. Because of a UI error, the user was allowed to enter a decimal value, and so this needs to be fixed to remove the decimal like so.
"value" : [
"now-3y/d",
"now/d"
]
My problem is writing a Mongo query to identify these records (I'm a Mongo noob). What I need is to identify records in this collection that have an item in the filters.rules array with an item in the 'value` array that contains a decimal.
Piece of cake, right?
Here's as far as I've gotten.
myCollection.find({"filters.rules": })
but I'm not sure where to go from here.
UPDATE: After running the regex provided by #R2D2, I found that it also brings up records with a valid date string , e.g.
"rules" : [
{
"id" : "dueDate",
"operator" : "between",
"value" : [
"2018-09-10T19:04:00.000Z",
null
]
},
so what I need to do is filter out cases where the period has a double 0 on either side (i.e. 00.00). If I read the regex correctly, this part
[^\.]
is excluding characters, so I would want something like
[^00\.00]
but running this query
db.collection.find( {
"filters.rules.value": { $regex: /\.[^00\.00]*/ }
} )
still returns the same records, even though it works as expected in a regex tester. What am I missing?
To find all documents containing at least one value string with (.) , try:
db.collection.find( {
"filters.rules.value": { $regex: /\.[^\.]*/ }
} )
Or you can filter only the fields that need fix via aggregation as follow:
[direct: mongos]> db.tes.aggregate([ {$unwind:"$filters.rules"}, {$unwind:"$filters.rules.value"}, {$match:{ "filters.rules.value": {$regex: /\.[^\.]*/ } }} ,{$project:{_id:1,oldValue:"$filters.rules.value"}} ])
[
{ _id: ObjectId("6202f3357a02e8740039f343"), oldValue: 'now-3.5y/d' }
]
[direct: mongos]>
Later to update those values:
db.collection.update({
"filters.rules.value": "now-3.5y/d"
},
{
$set: {
"filters.rules.$[x].value.$": "now-3,5y/d-CORRECTED"
}
},
{
arrayFilters: [
{
"x.value": "now-3.5y/d"
}
]
})
playground
I have MongoDB document with structure like this:
{
"_id" : ObjectId("56ebce0d1e3c51fe6a5053f3"),
"timestamp" : 1458294285,
"values" : [
{
"offset" : 132,
"packets" : [
{
"type" : "type1",
"data" : "some_data1"
},
{
"type" : "type2",
"data" : "some_data2"
}
]
}
}
I use it for storage time series data.
I want to create the query which insert a packet in packets array.
I use MongoDB c++ legacy driver 1.1.0.
When I will execute twice code below with equal timestamp and offset:
mongo::BSONObj query = BSON("timestamp" << timestamp);
mongo::BSONObj mainObj =
BSON ("$push" << BSON("values" << BSON("offset" << timestampOffset <<
"packets" << BSON_ARRAY(obj))));
connection.update(collectionName, query, mainObj, true);
I have result like this:
{
"_id" : ObjectId("56f90c1a3b20b7c1f61dccf7"),
"timestamp" : 1459080000,
"values" : [
{
"offset" : 68457,
"packets" : [
{
"type" : "type1",
"data" : "some_data1"
}
]
},
{
"offset" : 68457,
"packets" : [
{
"type" : "type2",
"data" : "some_data2"
}
]
}
]
}
Can somebody help me create right query for insert data into the document with specific structure?
I am trying to write a search script in MongoDB but can't figure out how to do it....The thing I wan't to do is as follows....
Lets I have a string array XD = {"the","new","world"}
Now i want to search string array XD in MongoDB document (using regex) and get the result document. For example..
{ _id: 1, _content: "there was a boy" }
{ _id: 2, _content: "there was a boy in a new world" }
{ _id: 3, _content: "a boy" }
{ _id: 4, _content: "there was a boy in world" }
now I want to get result in accordance to _content contains the string in string array XD
{ _id: 2, _content: "there was a boy in a new world", _times: 3 }
{ _id: 4, _content: "there was a boy in world", times: 2 }
{ _id: 1, _content: "there was a boy", times: 1 }
as first document (_id : 2 ) contains all three { "the" in there, "new" as new, "world" as world } so it got 3
second document (_id: 4) only two { "world" as world } so it got 2
Here is what you can do.
Create a Regex to be matched with _content
XD = ["the","new","world"];
regex = new RegExp(XD.join("|"), "g");
Store a JS function on the server, which matches the _content with XD and returns the counts matched
db.system.js.save(
{
_id: "findMatchCount",
value : function(str, regexStr) {
XD = ["the","new","world"];
var matches = str.match(regexStr);
return (matches !== null) ? matches.length : 0;
}
}
)
Use the function with mapReduce
db.test.mapReduce(
function(regex) {
emit(this._id, findMatchCount(this._content, regex));
},
function(key,values) {
return values;
},
{ "out": { "inline": 0 } }
);
This will produce the output as below:
{
"results" : [
{
"_id" : 1,
"value" : 1
},
{
"_id" : 2,
"value" : 1
},
{
"_id" : 3,
"value" : 1
},
{
"_id" : 4,
"value" : 1
}
],
"timeMillis" : 1,
"counts" : {
"input" : 4,
"emit" : 4,
"reduce" : 0,
"output" : 4
},
"ok" : 1
}
I am not sure how efficient this solution is but it works.
Hope this helps.
I want to create a small MongoDB Search Query where I want to sort the result set based exact match followed by no. of matches.
For eg. if I have following labels
Physics
11th-Physics
JEE-IIT-Physics
Physics-Physics
Then, if I search for "Physics" it should sort as
Physics
Physics-Physics
11th-Physics
JEE-IIT-Physics
Looking for the sort of "scoring" you are talking about here is an excercise in "imperfect solutions". In this case, the "best fit" here starts with "text search", and "imperfect" is the term to consider first when working with the text search capabilties of MongoDB.
MongoDB is "not" a dedicated "text search" product, nor is it ( like most databases ) trying to be one. Full capabilites of "text search" is reserved for dedicated products that do that as there area of expertise. So maybe not the best fit, but "text search" is given as an option for those who can live with the limitations and don't want to implement another engine. Or Yet! At least.
With that said, let's look at what you can do with the data sample as given. First set up some data in a collection:
db.junk.insert([
{ "data": "Physics" },
{ "data": "11th-Physics" },
{ "data": "JEE-IIT-Physics" },
{ "data": "Physics-Physics" },
{ "data": "Something Unrelated" }
])
Then of course to "enable" the text search capabilties, then you need to index at least one of the fields in the document with the "text" index type:
db.junk.createIndex({ "data": "text" })
Now that is "ready to go", let's have a look at a first basic query:
db.junk.find(
{ "$text": { "$search": "\"Physics\"" } },
{ "score": { "$meta": "textScore" } }
).sort({ "score": { "$meta": "textScore" } })
That is going to give results like this:
{
"_id" : ObjectId("55af83b964876554be823f33"),
"data" : "Physics-Physics",
"score" : 1.5
}
{
"_id" : ObjectId("55af83b964876554be823f30"),
"data" : "Physics",
"score" : 1
}
{
"_id" : ObjectId("55af83b964876554be823f31"),
"data" : "11th-Physics",
"score" : 0.75
}
{
"_id" : ObjectId("55af83b964876554be823f32"),
"data" : "JEE-IIT-Physics",
"score" : 0.6666666666666666
}
So that is "close" to your desired result, but of course there is no "exact match" component. In addition, the logic here used by the text search capabilities with the $text operator means that "Physics-Physics" is the preferred match here.
This is because then engine does not recognize "non words" such as the "hyphen" in between. To it, the word "Physics" appears several times in the indexed content for the document, therefore it has a higher score.
Now the rest of your logic here depends on the application of "exact match" and what you mean by that. If you are looking for "Physics" in the string and "not" surrounded by "hyphens" or other characters then the following does not suit. But you can just match a field "value" that is "exactly" just "Physics":
db.junk.aggregate([
{ "$match": {
"$text": { "$search": "Physics" }
}},
{ "$project": {
"data": 1,
"score": {
"$add": [
{ "$meta": "textScore" },
{ "$cond": [
{ "$eq": [ "$data", "Physics" ] },
10,
0
]}
]
}
}},
{ "$sort": { "score": -1 } }
])
And that will give you a result that both looks at the "textScore" produced by the engine and then applies some math with a logical test. In this case where the "data" is exactly equal to "Physics" then we "weight" the score by an additional factor using $add:
{
"_id": ObjectId("55af83b964876554be823f30"),
"data" : "Physics",
"score" : 11
}
{
"_id" : ObjectId("55af83b964876554be823f33"),
"data" : "Physics-Physics",
"score" : 1.5
}
{
"_id" : ObjectId("55af83b964876554be823f31"),
"data" : "11th-Physics",
"score" : 0.75
}
{
"_id" : ObjectId("55af83b964876554be823f32"),
"data" : "JEE-IIT-Physics",
"score" : 0.6666666666666666
}
That is what the aggregation framework can do for you, by allowing manipulation of the returned data with additional conditions. The end result is passed to the $sort stage ( notice it is reversed in descending order ) to allow that new value to be to sorting key.
But the aggregation framework can really only deal with "exact matches" like this on strings. There is no facility at present to deal with regular expression matches or index positions in strings that return a meaningful value for projection. Not even a logical match. And the $regex operation is only used to "filter" in queries, so not of use here.
So if you were looking for something in a "phrase" thats was a bit more invovled than a "string equals" exact match, then the other option is using mapReduce.
This is another "imperfect" approach as the limitations of the mapReduce command mean that the "textScore" from such a query by the engine is "completely gone". While the actual documents will be selected correctly, the inherrent "ranking data" is not available to the engine. This is a by-product of how MongoDB "projects" the "score" into the document in the first place, and "projection" is not a feature available to mapReduce.
But you can "play with" the strings using JavaScript, as in my "imperfect" sample:
db.junk.mapReduce(
function() {
var _id = this._id,
score = 0;
delete this._id;
score += this.data.indexOf(search);
score += this.data.lastIndexOf(search);
emit({ "score": score, "id": _id }, this);
},
function() {},
{
"out": { "inline": 1 },
"query": { "$text": { "$search": "Physics" } },
"scope": { "search": "Physics" }
}
)
Which gives results like this:
{
"_id" : {
"score" : 0,
"id" : ObjectId("55af83b964876554be823f30")
},
"value" : {
"data" : "Physics"
}
},
{
"_id" : {
"score" : 8,
"id" : ObjectId("55af83b964876554be823f33")
},
"value" : {
"data" : "Physics-Physics"
}
},
{
"_id" : {
"score" : 10,
"id" : ObjectId("55af83b964876554be823f31")
},
"value" : {
"data" : "11th-Physics"
}
},
{
"_id" : {
"score" : 16,
"id" : ObjectId("55af83b964876554be823f32")
},
"value" : {
"data" : "JEE-IIT-Physics"
}
}
My own "silly little algorithm" here is basically taking both the "first" and "last" index position of the matched string here and adding them together to produce a score. It's likely not what you really want, but the point is that if you can code your logic in JavaScript, then you can throw it at the engine to produce the desired "ranking".
The only real "trick" here to remember is that the "score" must be the "preceeding" part of the grouping "key" here, and that if including the orginal document _id value then that composite key part must be renamed, otherwise the _id will take precedence of order.
This is just part of mapReduce where as an "optimization" all output "key" values are sorted in "ascending order" before being processed by the reducer. Which of course does nothing here since we are not "aggregating", but just using the JavaScript runner and document reshaping of mapReduce in general.
So the overall note is, those are the available options. None of them perfect, but you might be able to live with them or even just "accept" the default engine result.
If you want more then look at external "dedicated" text search products, which would be better suited.
Side Note: The $text searches here are preferred over $regex because they can use an index. A "non-anchored" regular expression ( without the caret ^ ) cannot use an index optimally with MongoDB. Therefore the $text searches are generally going to be a better base for finding "words" within a phrase.
One more way is using the $indexOfCp aggregation operator to get the index of matched string and then apply sort on the indexed field
Data insertion
db.junk.insert([
{ "data": "Physics" },
{ "data": "11th-Physics" },
{ "data": "JEE-IIT-Physics" },
{ "data": "Physics-Physics" },
{ "data": "Something Unrelated" }
])
Query
const data = "Physics";
db.junk.aggregate([
{ "$match": { "data": { "$regex": data, "$options": "i" }}},
{ "$addFields": { "score": { "$indexOfCP": [{ "$toLower": "$data" }, { "$toLower": data }]}}},
{ "$sort": { "score": 1 }}
])
Here you can test the output
[
{
"_id": ObjectId("5a934e000102030405000000"),
"data": "Physics",
"score": 0
},
{
"_id": ObjectId("5a934e000102030405000003"),
"data": "Physics-Physics",
"score": 0
},
{
"_id": ObjectId("5a934e000102030405000001"),
"data": "11th-Physics",
"score": 5
},
{
"_id": ObjectId("5a934e000102030405000002"),
"data": "JEE-IIT-Physics",
"score": 8
}
]
My documents in elasticsearch are of the form
{
...
dimensions : list[string]
...
}
I'd like to find all dimensions over all the documents that match a regex. I feel like an aggregation would probably do the trick, but I'm having trouble formulating it.
For example, suppose I have three documents as below:
{
...
dimensions : ["alternative", "alto", "hello"]
...
}
{
...
dimensions : ["hello", "altar"]
...
}
{
...
dimensions : ["nore", "sore"]
...
}
I'd like to get the result ["alternative", "alto", "altar"] when I'm querying for the regex "alt.*"
You can achieve that with a simple terms aggregation parametrized with an include property which you can use to specify either a regexp (e.g. alt.* in your case) or an array of values to be included in the buckets. Note that there is also the exclude counterpart, if needed:
{
"size": 0,
"aggs": {
"dims": {
"terms": {
"field": "dimensions",
"include": "alt.*"
}
}
}
}
Results:
{
...
"aggregations" : {
"dims" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [ {
"key" : "altar",
"doc_count" : 1
}, {
"key" : "alternative",
"doc_count" : 1
}, {
"key" : "alto",
"doc_count" : 1
} ]
}
}
}