An example of the MongoDB Aggregation pipelines and commands used for some general filters. View

ExampleGeneralMongoDBAggregations.js

// -----------------------------------------------------------------
//   Applying aggregation pipeline #1 Customer - HAVE
// -----------------------------------------------------------------
db.command({
    "aggregate": "app.customer",
    "pipeline": [{
        "$match": {
            "$and": [{
                // -- Ensure the customers we are selecting are active and have a Firebase token so we can send them a push notification
                "status": "active",
                "firebaseToken": {"$exists": true, "$ne": null} // We likely wouldn't add the firebaseToken check if sending coupons
            }, {
                // -- Checking for the Age ranges 0-20, 31-40, 41-50, 51-60
                "$or": [{
                    "$and": [{
                        "dateOfBirth": {
                            "$lte": 1589068800,
                            "$gte": 957916800
                        }
                    }]
                }, {
                    "$and": [{
                        "dateOfBirth": {
                            "$lte": 610761600,
                            "$gte": 326764800
                        }
                    }]
                }, {
                    "$and": [{
                        "dateOfBirth": {
                            "$lte": 295142400,
                            "$gte": 11145600
                        }
                    }]
                }, {
                    "$and": [{
                        "dateOfBirth": {
                            "$lte": -20390400,
                            "$gte": -304387200
                        }
                    }]
                }
                ]
            }, {
                // Check for the state
                "state": {"$in": ['SA', 'Vic', 'QLD', 'NSW', 'WA', 'Tas']}
            }]
        }
    }, {
        // Only get the Customer's _id field
        "$project": {"_id": 1}
    }, {
        "$merge": {
            "into": "customerGroup-5eb78328af2f5c079a1e9352",
            "on": "_id",
            "whenMatched": "keepExisting",
            "whenNotMatched": "insert" // This is the first aggregation run, so we just insert all entries, don't need to merge
        }
    }],
})

// -----------------------------------------------------------------
//   Applying aggregation pipeline #2 Transaction - HAVE
// -----------------------------------------------------------------
db.command({
    "aggregate": "app.customerTransaction",
    "pipeline": [
        {
            "$match":
                {
                    // We thankfully can $and all the HAVE $match'es together
                    "$and": [
                        {
                            // -- Search for customers who in the last 60 days have shopped at the listed stores
                            "$and": [
                                {
                                    "transactionDate": {"$gte": 1583884800}
                                }, {
                                    "storeId": {"$in": ["MongoDB\\BSON\\ObjectId(5e6111bcaf2f5c1d9f7f88f2)", "MongoDB\\BSON\\ObjectId(5e6111bcaf2f5c1d9f7f88f3)", "MongoDB\\BSON\\ObjectId(5e6111bcaf2f5c1d9f7f88f4)", "MongoDB\\BSON\\ObjectId(5e6111bcaf2f5c1d9f7f88f5)", "MongoDB\\BSON\\ObjectId(5e6111bcaf2f5c1d9f7f88f6)", "MongoDB\\BSON\\ObjectId(5e6111bcaf2f5c1d9f7f88f7)", "MongoDB\\BSON\\ObjectId(5e6111bcaf2f5c1d9f7f88fb)"]}
                                }
                            ]
                        }, {
                            // -- For the Exclude of "Haven't Purchased With Product Categories X Within Y Days" filter
                            // we convert it to an include (select) of those who HAVE purchased the various Product Categories in the last 100 days
                            // as we are then removing those who haven't made such a purchase
                            "$and": [
                                {
                                    "transactionDate": {"$gte": 1580428800}
                                },
                                {
                                    "productCategories": {
                                        "$in": ["MongoDB\\BSON\\ObjectId(5e79a458af2f5c1f95415062)", "MongoDB\\BSON\\ObjectId(5e79a458af2f5c1f95415084)", "MongoDB\\BSON\\ObjectId(5e79a458af2f5c1f95415087)", "MongoDB\\BSON\\ObjectId(5e79a458af2f5c1f9541508b)", "MongoDB\\BSON\\ObjectId(5e79a458af2f5c1f9541508f)", "MongoDB\\BSON\\ObjectId(5e79a458af2f5c1f9541508d)"]
                                    }
                                }]
                        }]
                }
        },
        {
            // Select just the customerId field
            "$group": {"_id": "$customerId"}
        }, {
            // Add a selected: true to the customers we match on
            "$addFields": {"selected": true}
        }, {
            "$merge": {
                "into": "customerGroup-5eb78328af2f5c079a1e9352",
                "on": "_id",
                "whenMatched": "merge", // Merge the results, setting selected:true to these
                "whenNotMatched": "discard" // We aren't adding any new customers, we are filtering down the existing set
            }
        }],
});

// Delete all entries we didn't just mark as selected
db['customerGroup-5eb78328af2f5c079a1e9352'].bulkWrite([{
    "type": "delete",
    "condition": {"selected": {"$exists": false}},
    "options": {"multi": true}
}])

// Remove the selected field, ready for the next pipelines
db['customerGroup-5eb78328af2f5c079a1e9352'].bulkWrite([{
    "type": "update",
    "condition": {"selected": {"$exists": true}},
    "document": {"$unset": {"selected": ""}},
    "options": {"multi": true, "upsert": false}
}])

// End of pipeline 2

// -----------------------------------------------------------------
//   Applying aggregation pipeline #3 Customer - Have Not
// -----------------------------------------------------------------
db.command({
    "aggregate": "app.customer",
    "pipeline": [{
        "$match": {
            "$or": [{
                // Excluding the males by
                // selecting the males and then removing them
                "gender": {"$in": ["male"]}
            }]
        }
    }, {
        // Just want the customer._id field
        "$project": {"_id": 1}
    }, {
        // Add an excluded:true field to the ones we match
        "$addFields": {"excluded": true}
    }, {
        "$merge": {
            "into": "customerGroup-5eb78328af2f5c079a1e9352",
            "on": "_id",
            "whenMatched": "merge", // Here's where we say we are merging the excluded field
            "whenNotMatched": "discard"
        }
    }],
});

// Delete the excluded customers
db['customerGroup-5eb78328af2f5c079a1e9352'].bulkWrite([{
    "type": "delete",
    "condition": {"excluded": true},
    "options": {"multi": true}
}]);

// End of pipeline 3

// -----------------------------------------------------------------
//   Applying aggregation pipeline #4 Transaction - Have Not
// -----------------------------------------------------------------
db.command({
    "aggregate": "app.customerTransaction",
    "pipeline": [{
        "$match": {
            // $or the HAVE NOT's together
            "$or": [{
                "$and": [{
                    // The Include filter of "Haven't Purchased With Product Categories X Within Y Days, productCategories: SEAFOOD - SPECIAL, days: 2"
                    // gets converted into an exclude of those who have purchased.
                    // So we select and exclude anyone who's purchased from the Special Seafood category of food in the last 2 days
                    "transactionDate": {"$gte": 1588896000}
                }, {
                    "productCategories": {"$in": ["MongoDB\\BSON\\ObjectId(5e79a458af2f5c1f95415067)"]}
                }]
            }, {
                // The Exclude filter of "Have Purchased Products X Within Y Days, products: 180 PROT BAR VEGAN CHOC MINT 40G, days: 90"
                // Gets converted into us selecting and excluding those who've purchased the Vegan protein bar in the last 90 days.
                "$and": [{
                    "transactionDate": {"$gte": 1581292800}
                }, {
                    "products": {"$in": ["MongoDB\\BSON\\ObjectId(5e916292af2f5c0896207e37)"]}
                }]
            }]
        }
    }, {
        "$group": {
            "_id": "$customerId"
        }
    }, {
        "$addFields": {"excluded": true}
    }, {
        "$merge": {
            "into": "customerGroup-5eb78328af2f5c079a1e9352",
            "on": "_id",
            "whenMatched": "merge",
            "whenNotMatched": "discard"
        }
    }],
});

// Remove the excluded customers
db['customerGroup-5eb78328af2f5c079a1e9352'].bulkWrite([{"type":"delete","condition":{"excluded":true},"options":{"multi":true}}]);

// End of pipeline 4

// -----------------------------
// We are using "customerGroup-<customerGroupId>" for the merged collection results name. So each customerGroup has it's own merged collection with results.
// The collection customerGroup-5eb78328af2f5c079a1e9352 should now have a set of _id's which are the customerId's which match all the filters.
// We can now load up the actual customer models in batches based on those _id's and process them, sending push notifications, coupons, surveys, etc..
// We save a customerGroup.lastRan unixtime field so we know if the merged results are stale and need re-creating.

// Note: Whilst this is nearly valid MongoDB commands, it's been modified and is based on the PHP output of run commands
// You'll want to change "MongoDB\\BSON\\ObjectId(5e79a458af2f5c1f95415062)" to something like ObjectId("5e79a458af2f5c1f95415062")