Running an aggregate query in mongo_go_driver that includes javascript code: an easy guide

Question

Running an aggregate query in mongo_go_driver that includes javascript code: an easy guide

Currently, I am utilizing the mongo-go-driver () and attempting to achieve a similar action as below:

db.getCollection('mycollection').aggregate([
    { $lookup: {
        from: "anothercollection",
        localField: "_id",
        foreignField: "foreignID",
        as: "matched_docs"
    }},
    { $match: { "matched_docs": { $eq: [] } } },
    { $project: { "matched_docs": 0 } },
    { $match: {"dateTimeGMT":{$lt: (new Date(Date.now()-1000*60*60*24)).toISOString()}} }
])

I'm encountering difficulty in integrating the JavaScript commands using this approach.

pipeline := bson.NewArray(
    bson.VC.DocumentFromElements(
        bson.EC.SubDocumentFromElements( 
        //blah, blah, blah...
cursor, err := collection.Aggregate(ctx, pipeline)

(In general, I'm not fond of this technique. I desire the ability to develop queries in Robo 3T and easily transfer them into my code similar to how I perform with MySQL Workbench and PHP)

This method results in an empty *bson.Array within the pipeline

pipelineJSON := `[
    { $lookup: {
        from: "anothercollection",
        localField: "_id",
        foreignField: "interactionID",
        as: "matched_docs"
    }},
    { $match: { "matched_docs": { $eq: [] } } },
    { $project: { "matched_docs": 0 } },
    { $match: {"dateTimeGMT":{$lt: (new Date(Date.now()-1000*60*60*24)).toISOString()}} }
]`
pipeline, err = bson.ParseExtJSONArray(pipelineJSON)

I would greatly appreciate it if there was a way to transmit a MongoDB command as a string (like inputting it into Robo 3T) and receive a *mongo.Cursor in return. Is there a superior driver available (that is still actively supported by developers) that I should consider using instead? Or perhaps, do I need to develop my own?

Thank you!

javascript mongodb go aggregate

Answer 1

Answer №1

I'm struggling to insert the Javascript commands using this particular approach.

While I acknowledge that this may not be the preferred method for your specific scenario, here is how you can build the aggregation pipeline as bson.D using mongo-go-driver v1.0:

pipeline := mongo.Pipeline{
    {{"$lookup", bson.D{
        {"from", "tour"}, 
        {"localField", "_id"}, 
        {"foreignField", "foreignID"}, 
        {"as", "matched_docs"},
    }}},
    {{"$match", bson.D{
        {"matched_docs", bson.D{
            {"$eq", bson.A{}}},
        }, 
    }}},
    {{"$project", bson.D{
        {"matched_docs", 0}, 
    }}},        
    {{"$match", bson.D{
        {"dateTimeGMT", bson.D{
            {"$lt", time.Now().AddDate(0, 0, -1).UTC().Format(time.RFC3339)},
            }, 
        },
    }}},  
}

{ $project: { "matched_docs": 0 } },

You can combine the two $match operations into a single pipeline stage and then add $project at the end. For example:

db.collection.aggregate([
    { "$lookup":{
        "from":"anothercollection",
        "localField":"_id",
        "foreignField":"foreignID",
        "as":"matched_docs"}
    }, 
    { "$match": { "matched_docs": { "$eq": [] }, 
                  "datetimegmt": { "$lt": (new Date(Date.now()-1000*60*60*24)).toISOString() } 
                } 
    }, 
    { "$project": { "matched_docs": 0 } }
]);

{ $match: {"dateTimeGMT":{$lt: (new Date(Date.now()-1000*60*60*24)).toISOString()}} }

Based on the $match condition, it seems like dates are stored as strings instead of Date objects. It's recommended to store dates as proper Date objects for better index performance.

ParseExtJSONArray does function properly, but you cannot include JS or unquoted aggregation stages/expression operators as in MongoDB Shell.

The mongo shell offers convenient methods/types like ObjectID() to create MongoDB Extended JSON. The mongo shell serves more than just a JavaScript environment.

If you simply need to evaluate a JavaScript expression, consider using a JavaScript interpreter for Go (otto). Here's a rough example:

// Note the unquoted fields, as JSON is JavaScript native.
raw := `[
    { "$lookup": {
        from: "anothercollection",
        localField: "_id",
        foreignField: "foreignID",
        as: "matched_docs"
    }},
    { $match: { "matched_docs": { $eq: [] },
                "dateTimeGMT":{$lt: (new Date(Date.now()-1000*60*60*24)).toISOString() }, 
              }
    },
    { $project: { "matched_docs": 0 } },
]`
vm := otto.New()
// Evaluate JS expression
jsvalue, err := vm.Eval(raw)

// Export to Go interface{}
output, err := jsvalue.Export()

// Convert interface{} to bson.Document bytes
bsonbytes, err := bson.Marshal(output)

// Convert bson.Document bytes to bson.Document
pipeline, err := bson.UnmarshalDocument(bsonbytes)

Note that some objects like ObjectId() won't be recognized by a standard JavaScript interpreter.

I wish to create queries in Robo 3T and transfer them to my code similar to MySQL Workbench with PHP.

Although currently lacking support for Go, it's worth noting that MongoDB Compass has a feature for Exporting Queries to Different Languages. The current version (1.15) supports Java, Node, C#, and Python3. Hopefully, Go will be included in the future.

Answer 2

I'm struggling to insert the Javascript commands using this particular approach.

While I acknowledge that this may not be the preferred method for your specific scenario, here is how you can build the aggregation pipeline as bson.D using mongo-go-driver v1.0:

pipeline := mongo.Pipeline{
    {{"$lookup", bson.D{
        {"from", "tour"}, 
        {"localField", "_id"}, 
        {"foreignField", "foreignID"}, 
        {"as", "matched_docs"},
    }}},
    {{"$match", bson.D{
        {"matched_docs", bson.D{
            {"$eq", bson.A{}}},
        }, 
    }}},
    {{"$project", bson.D{
        {"matched_docs", 0}, 
    }}},        
    {{"$match", bson.D{
        {"dateTimeGMT", bson.D{
            {"$lt", time.Now().AddDate(0, 0, -1).UTC().Format(time.RFC3339)},
            }, 
        },
    }}},  
}

{ $project: { "matched_docs": 0 } },

You can combine the two $match operations into a single pipeline stage and then add $project at the end. For example:

db.collection.aggregate([
    { "$lookup":{
        "from":"anothercollection",
        "localField":"_id",
        "foreignField":"foreignID",
        "as":"matched_docs"}
    }, 
    { "$match": { "matched_docs": { "$eq": [] }, 
                  "datetimegmt": { "$lt": (new Date(Date.now()-1000*60*60*24)).toISOString() } 
                } 
    }, 
    { "$project": { "matched_docs": 0 } }
]);

{ $match: {"dateTimeGMT":{$lt: (new Date(Date.now()-1000*60*60*24)).toISOString()}} }

Based on the $match condition, it seems like dates are stored as strings instead of Date objects. It's recommended to store dates as proper Date objects for better index performance.

ParseExtJSONArray does function properly, but you cannot include JS or unquoted aggregation stages/expression operators as in MongoDB Shell.

The mongo shell offers convenient methods/types like ObjectID() to create MongoDB Extended JSON. The mongo shell serves more than just a JavaScript environment.

If you simply need to evaluate a JavaScript expression, consider using a JavaScript interpreter for Go (otto). Here's a rough example:

// Note the unquoted fields, as JSON is JavaScript native.
raw := `[
    { "$lookup": {
        from: "anothercollection",
        localField: "_id",
        foreignField: "foreignID",
        as: "matched_docs"
    }},
    { $match: { "matched_docs": { $eq: [] },
                "dateTimeGMT":{$lt: (new Date(Date.now()-1000*60*60*24)).toISOString() }, 
              }
    },
    { $project: { "matched_docs": 0 } },
]`
vm := otto.New()
// Evaluate JS expression
jsvalue, err := vm.Eval(raw)

// Export to Go interface{}
output, err := jsvalue.Export()

// Convert interface{} to bson.Document bytes
bsonbytes, err := bson.Marshal(output)

// Convert bson.Document bytes to bson.Document
pipeline, err := bson.UnmarshalDocument(bsonbytes)

Note that some objects like ObjectId() won't be recognized by a standard JavaScript interpreter.

I wish to create queries in Robo 3T and transfer them to my code similar to MySQL Workbench with PHP.

Although currently lacking support for Go, it's worth noting that MongoDB Compass has a feature for Exporting Queries to Different Languages. The current version (1.15) supports Java, Node, C#, and Python3. Hopefully, Go will be included in the future.

Answer 3

Answer №2

When using ParseExtJSONArray, it functions properly. However, unlike Mongo Shell, you are unable to incorporate JS or unquoted aggregation stages/expression operators. It is important to note that the ISO date for comparison is calculated in golang and all aggregation stages and expression operators must be enclosed in quotes.

pipelineJSON := fmt.Sprintf(`[
    { "$lookup": {
        "from": "another_collection",
        "localField": "_id",
        "foreignField": "interactionID",
        "as": "matched_docs"
    }},
    { "$match": { "matched_docs": { "$eq": [] } } },
    { "$project": { "matched_docs": 0 } },
    { "$match": {"dateTimeGMT":{"$lt": "%s"}} }
]`, time.Now().AddDate(0, 0, -1).UTC().Format(time.RFC3339))
pipeline, err = bson.ParseExtJSONArray(pipelineJSON)

The driver I inquired about provides the solution to this issue.

Answer 4

When using ParseExtJSONArray, it functions properly. However, unlike Mongo Shell, you are unable to incorporate JS or unquoted aggregation stages/expression operators. It is important to note that the ISO date for comparison is calculated in golang and all aggregation stages and expression operators must be enclosed in quotes.

pipelineJSON := fmt.Sprintf(`[
    { "$lookup": {
        "from": "another_collection",
        "localField": "_id",
        "foreignField": "interactionID",
        "as": "matched_docs"
    }},
    { "$match": { "matched_docs": { "$eq": [] } } },
    { "$project": { "matched_docs": 0 } },
    { "$match": {"dateTimeGMT":{"$lt": "%s"}} }
]`, time.Now().AddDate(0, 0, -1).UTC().Format(time.RFC3339))
pipeline, err = bson.ParseExtJSONArray(pipelineJSON)

The driver I inquired about provides the solution to this issue.

Running an aggregate query in mongo_go_driver that includes javascript code: an easy guide

Answer №1

Answer №2

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