MongoDB: use $sum with multiple $cond - mongodb

I want calculate points based to the size of an array element.
I can use $sum with multiple $cond?
Something like this:
{
$project: {
points: {
$sum: [
{
$cond: [
{
$and: [{ $gt: [{ $arrayElemAt: ["$matches", 0] }, 0] }, { $gt: [{ $arrayElemAt: ["$matches", 1] }, 0] }, { $gt: [{ $arrayElemAt: ["$matches", 2] }, 0] }],
},
10,
0,
],
},
{
$cond: [
{
$and: [{ $gt: [{ $arrayElemAt: ["$matches", 3] }, 0] }, { $gt: [{ $arrayElemAt: ["$matches", 4] }, 0] }, { $gt: [{ $arrayElemAt: ["$matches", 5] }, 0] }],
},
10,
0,
],
},
],
},
},
},
This script always returns 20 even if not all conditions are true
Example of document:
{
"_id" : NumberInt(5),
"total_matches" : NumberInt(0),
"matches" : [
[
],
[
],
[
],
[
],
[
],
[
],
[
],
[
],
[
]
]
}
OUTPUT
{
"_id" : NumberInt(5),
"points" : 20.0,
"matches" : [
[
],
[
],
[
],
[
],
[
],
[
],
[
],
[
],
[
]
]
}

Ok, the problem is that I forgot $size in the query.
The right query is this:
{
$project: {
points: {
$sum: [
{
$cond: [
{
$and: [{ $gt: [{ $size:{ $arrayElemAt: ["$matches", 0] }}, 0] }, { $gt: [{ $arrayElemAt: ["$matches", 1] }, 0] }, { $gt: [{ $arrayElemAt: ["$matches", 2] }, 0] }],
},
10,
0,
],
},
{
$cond: [
{
$and: [{ $gt: [{ $size:{ $arrayElemAt: ["$matches", 3] }}, 0] }, { $gt: [{ $arrayElemAt: ["$matches", 4] }, 0] }, { $gt: [{ $arrayElemAt: ["$matches", 5] }, 0] }],
},
10,
0,
],
},
],
},
},
}

Related

MongoDB aggregation re-group deep nested array of objects

Good day all,
I need some help figuring out this aggregation issue. I have a document with nested arrays where I want to perform lookups on the nested array's values after which I want to restore the document to its original structure. see below:
[
{
"_id": "63c7fec2fe9afea23afdbcef",
"primary_language": "en",
"image_link": "avatar_image_linl",
"description": ["Some description text here"],
"source": "community",
"standard": "imperial",
"gender": "male",
"base_a": 47,
"base_w": 220,
"base_h": 71.65,
"status": "draft",
"date_created": "2023-01-18T14:14:26.201Z",
"product_plan": {
"p_len": 4,
"p_fre": 1,
"p_qua": 4,
"avg_len": 3583,
"total_wor": 16,
"total_exe": 128,
"plan": {
"field_we": 1,
"field_da": 1,
"field_ti": 1,
"field_rest_we": false,
"field_rest_da": false,
"product": {
"name": "W111",
"comment": {
"en": ""
},
"pro_diff": [
{
"itemID": 2,
"description": "Intermediate"
}
],
"pro_int": [
{
"itemID": 2,
"description": "Moderate"
}
],
"pro_dur": 3736,
"nbr_exe": 8,
"target_mus": [
{
"itemID": 1,
"description": "Adominorus"
},
{
"itemID": 16,
"description": "Tricerus"
},
{
"itemID": 5,
"description": "Chiwawak"
}
],
"target_are": [
{
"itemID": 1,
"description": "Adominorus"
},
{
"itemID": 4,
"description": "Chiwawak"
},
{
"itemID": 2,
"description": "Amanus"
}
],
"items": {
"itemid": 44,
"target_are": [
{
"itemID": 4,
"description": "Chiwawak"
}
],
"target_mus": [
{
"itemID": 5,
"description": "Chiwawak"
}
],
"nbr_ref": 4,
"int_rec": "06~10",
"type_rec": [
{
"itemID": 14,
"description": "Straight Set"
}
],
"tempo": "1-1-1-1",
"rest_time": 90,
"note": "",
"order": null,
"pro_dur": 520,
"_id": "63ca9b798d47745ae5589906",
"status": 0,
"pct_complete": 0,
"set": []
},
"isCustomName": false,
"status": 0,
"pct_complete": 0
},
"_id": "63ca95368d47745ae558985e"
},
"_id": "63c7fec2fe9afea23afdbcf0"
},
"title": "Short Title text here",
"itemID": "bodyfyme882212-1674051266.214",
"__v": 32
},
{
"_id": "63c7fec2fe9afea23afdbcef",
"primary_language": "en",
"image_link": "avatar_image_linl",
"description": ["Some description text here"],
"source": "community",
"standard": "imperial",
"gender": "male",
"base_a": 47,
"base_w": 220,
"base_h": 71.65,
"status": "draft",
"date_created": "2023-01-18T14:14:26.201Z",
"product_plan": {
"p_len": 4,
"p_fre": 1,
"p_qua": 4,
"avg_len": 3583,
"total_wor": 16,
"total_exe": 128,
"plan": {
"field_we": 1,
"field_da": 1,
"field_ti": 1,
"field_rest_we": false,
"field_rest_da": false,
"product": {
"name": "W111",
"comment": {
"en": ""
},
"pro_diff": [
{
"itemID": 2,
"description": "Intermediate"
}
],
"pro_int": [
{
"itemID": 2,
"description": "Moderate"
}
],
"pro_dur": 3736,
"nbr_exe": 8,
"target_mus": [
{
"itemID": 1,
"description": "Adominorus"
},
{
"itemID": 16,
"description": "Tricerus"
},
{
"itemID": 5,
"description": "Chiwawak"
}
],
"target_are": [
{
"itemID": 1,
"description": "Adominorus"
},
{
"itemID": 4,
"description": "Chiwawak"
},
{
"itemID": 2,
"description": "Amanus"
}
],
"items": {
"itemid": 339,
"target_are": [
{
"itemID": 4,
"description": "Chiwawak"
}
],
"target_mus": [
{
"itemID": 5,
"description": "Chiwawak"
}
],
"nbr_ref": 3,
"int_rec": "06~10",
"type_rec": [
{
"itemID": 14,
"description": "Straight Set"
}
],
"tempo": "1-1-1-1",
"rest_time": 90,
"note": "",
"order": null,
"pro_dur": 390,
"_id": "63ca9b798d47745ae5589907",
"status": 0,
"pct_complete": 0,
"set": []
},
"isCustomName": false,
"status": 0,
"pct_complete": 0
},
"_id": "63ca95368d47745ae558985e"
},
"_id": "63c7fec2fe9afea23afdbcf0"
},
"title": "Short Title text here",
"itemID": "bodyfyme882212-1674051266.214",
"__v": 32
},
{
"_id": "63c7fec2fe9afea23afdbcef",
"primary_language": "en",
"image_link": "avatar_image_linl",
"description": ["Some description text here"],
"source": "community",
"standard": "imperial",
"gender": "male",
"base_a": 47,
"base_w": 220,
"base_h": 71.65,
"status": "draft",
"date_created": "2023-01-18T14:14:26.201Z",
"product_plan": {
"p_len": 4,
"p_fre": 1,
"p_qua": 4,
"avg_len": 3583,
"total_wor": 16,
"total_exe": 128,
"plan": {
"field_we": 1,
"field_da": 2,
"field_ti": 1,
"field_rest_we": false,
"field_rest_da": false,
"product": {
"name": "W121",
"comment": {
"en": ""
},
"pro_diff": [
{
"itemID": 2,
"description": "Intermediate"
}
],
"pro_int": [
{
"itemID": 2,
"description": "Moderate"
}
],
"pro_dur": 2674,
"nbr_exe": 6,
"target_mus": [
{
"itemID": 9,
"description": "Lats"
},
{
"itemID": 10,
"description": "Lower Back"
},
{
"itemID": 11,
"description": "Middle Back"
}
],
"target_are": [
{
"itemID": 3,
"description": "Back"
}
],
"items": {
"itemid": 47,
"target_are": [
{
"itemID": 3,
"description": "Back"
}
],
"target_mus": [
{
"itemID": 10,
"description": "Lower Back"
}
],
"nbr_ref": 4,
"int_rec": "06~10",
"type_rec": [
{
"itemID": 14,
"description": "Straight Set"
}
],
"tempo": "1-1-1-1",
"rest_time": 90,
"note": "",
"order": null,
"pro_dur": 520,
"_id": "63caa1568d47745ae5589b25",
"status": 0,
"pct_complete": 0,
"set": []
},
"isCustomName": false,
"status": 0,
"pct_complete": 0
},
"_id": "63ca9b8e8d47745ae558994b"
},
"_id": "63c7fec2fe9afea23afdbcf0"
},
"title": "Short Title text here",
"itemID": "bodyfyme882212-1674051266.214",
"__v": 32
},
{
"_id": "63c7fec2fe9afea23afdbcef",
"primary_language": "en",
"image_link": "avatar_image_linl",
"description": ["Some description text here"],
"source": "community",
"standard": "imperial",
"gender": "male",
"base_a": 47,
"base_w": 220,
"base_h": 71.65,
"status": "draft",
"date_created": "2023-01-18T14:14:26.201Z",
"product_plan": {
"p_len": 4,
"p_fre": 1,
"p_qua": 4,
"avg_len": 3583,
"total_wor": 16,
"total_exe": 128,
"plan": {
"field_we": 1,
"field_da": 2,
"field_ti": 1,
"field_rest_we": false,
"field_rest_da": false,
"product": {
"name": "W121",
"comment": {
"en": ""
},
"pro_diff": [
{
"itemID": 2,
"description": "Intermediate"
}
],
"pro_int": [
{
"itemID": 2,
"description": "Moderate"
}
],
"pro_dur": 2674,
"nbr_exe": 6,
"target_mus": [
{
"itemID": 9,
"description": "Lats"
},
{
"itemID": 10,
"description": "Lower Back"
},
{
"itemID": 11,
"description": "Middle Back"
}
],
"target_are": [
{
"itemID": 3,
"description": "Back"
}
],
"items": {
"itemid": 495,
"target_are": [
{
"itemID": 3,
"description": "Back"
}
],
"target_mus": [
{
"itemID": 11,
"description": "Middle Back"
}
],
"nbr_ref": 3,
"int_rec": "10~12",
"type_rec": [
{
"itemID": 14,
"description": "Straight Set"
}
],
"tempo": "1-1-1-1",
"rest_time": 90,
"note": "",
"order": null,
"pro_dur": 414,
"_id": "63caa1568d47745ae5589b26",
"status": 0,
"pct_complete": 0,
"set": []
},
"isCustomName": false,
"status": 0,
"pct_complete": 0
},
"_id": "63ca9b8e8d47745ae558994b"
},
"_id": "63c7fec2fe9afea23afdbcf0"
},
"title": "Short Title text here",
"itemID": "bodyfyme882212-1674051266.214",
"__v": 32
},
{
......
}
]
Now i want to get the document back to this structure using aggregation.
{
"_id": "63c7fec2fe9afea23afdbcef",
"primary_language": "en",
"image_link": "avatar_image_linl",
"description": ["Some description text here"],
"source": "community",
"standard": "imperial",
"gender": "male",
"base_a": 47,
"base_w": 220,
"base_h": 71.65,
"status": "draft",
"date_created": "2023-01-18T14:14:26.201Z",
"product_plan": {
"p_len": 4,
"p_fre": 1,
"p_qua": 4,
"avg_len": 3583,
"total_wor": 16,
"total_exe": 128,
// Group plan here by product_plan._id
"plan": [
{
"field_we": 1,
"field_da": 1,
"field_ti": 1,
"field_rest_we": false,
"field_rest_da": false,
"product": {
"name": "W111",
"comment": {
"en": ""
},
"pro_diff": [
{
"itemID": 2,
"description": "Intermediate"
}
],
"pro_int": [
{
"itemID": 2,
"description": "Moderate"
}
],
"pro_dur": 3736,
"nbr_exe": 8,
"target_mus": [
{
"itemID": 1,
"description": "Adominorus"
},
{
"itemID": 16,
"description": "Tricerus"
},
{
"itemID": 5,
"description": "Chiwawak"
}
],
"target_are": [
{
"itemID": 1,
"description": "Adominorus"
},
{
"itemID": 4,
"description": "Chiwawak"
},
{
"itemID": 2,
"description": "Amanus"
}
],
// group items by plan._id
"items": [
{
"itemid": 44,
"target_are": [
{
"itemID": 4,
"description": "Chiwawak"
}
],
"target_mus": [
{
"itemID": 5,
"description": "Chiwawak"
}
],
"nbr_ref": 4,
"int_rec": "06~10",
"type_rec": [
{
"itemID": 14,
"description": "Straight Set"
}
],
"tempo": "1-1-1-1",
"rest_time": 90,
"note": "",
"order": null,
"pro_dur": 520,
"_id": "63ca9b798d47745ae5589906",
"status": 0,
"pct_complete": 0,
"set": []
},
{
"itemid": 339,
"target_are": [
{
"itemID": 4,
"description": "Chiwawak"
}
],
"target_mus": [
{
"itemID": 5,
"description": "Chiwawak"
}
],
"nbr_ref": 3,
"int_rec": "06~10",
"type_rec": [
{
"itemID": 14,
"description": "Straight Set"
}
],
"tempo": "1-1-1-1",
"rest_time": 90,
"note": "",
"order": null,
"pro_dur": 390,
"_id": "63ca9b798d47745ae5589907",
"status": 0,
"pct_complete": 0,
"set": []
},
],
"isCustomName": false,
"status": 0,
"pct_complete": 0
},
"_id": "63ca95368d47745ae558985e"
},
{
"field_we": 1,
"field_da": 2,
"field_ti": 1,
"field_rest_we": false,
"field_rest_da": false,
"product": {
"name": "W121",
"comment": {
"en": ""
},
"pro_diff": [
{
"itemID": 2,
"description": "Intermediate"
}
],
"pro_int": [
{
"itemID": 2,
"description": "Moderate"
}
],
"pro_dur": 2674,
"nbr_exe": 6,
"target_mus": [
{
"itemID": 9,
"description": "Lats"
},
{
"itemID": 10,
"description": "Lower Back"
},
{
"itemID": 11,
"description": "Middle Back"
}
],
"target_are": [
{
"itemID": 3,
"description": "Back"
}
],
// group items by plan._id
"items": [
{
"itemid": 47,
"target_are": [
{
"itemID": 3,
"description": "Back"
}
],
"target_mus": [
{
"itemID": 10,
"description": "Lower Back"
}
],
"nbr_ref": 4,
"int_rec": "06~10",
"type_rec": [
{
"itemID": 14,
"description": "Straight Set"
}
],
"tempo": "1-1-1-1",
"rest_time": 90,
"note": "",
"order": null,
"pro_dur": 520,
"_id": "63caa1568d47745ae5589b25",
"status": 0,
"pct_complete": 0,
"set": []
},
{
"itemid": 495,
"target_are": [
{
"itemID": 3,
"description": "Back"
}
],
"target_mus": [
{
"itemID": 11,
"description": "Middle Back"
}
],
"nbr_ref": 3,
"int_rec": "10~12",
"type_rec": [
{
"itemID": 14,
"description": "Straight Set"
}
],
"tempo": "1-1-1-1",
"rest_time": 90,
"note": "",
"order": null,
"pro_dur": 414,
"_id": "63caa1568d47745ae5589b26",
"status": 0,
"pct_complete": 0,
"set": []
}
],
"isCustomName": false,
"status": 0,
"pct_complete": 0
},
"_id": "63ca9b8e8d47745ae558994b"
}
],
"_id": "63c7fec2fe9afea23afdbcf0"
},
"title": "Short Title text here",
"itemID": "bodyfyme882212-1674051266.214",
"__v": 32
}
Any help would be greatly appreciated

Merge object fields aggregation

I'm using MongoDB 3.6 and I have the following data:
[
{
"valoresVencimentos": [
1468.12,
85.9,
14.1,
1899.99,
241.92,
869.99,
696.11
],
"classesVencimentos": [
"lim_up_1ano",
"lim_1ano",
"a_venc_180d",
"a_venc_180d",
"outros",
"a_venc_180d",
"a_venc_180d"
],
"classesModalidades": [
"financiamento",
"financiamento",
"curto prazo",
"cartao",
"cartao",
"cartao",
"cartao"
]
},
{
"valoresVencimentos": [
627.29,
241.92,
413.47,
229.74,
1687.58,
100
],
"classesVencimentos": [
"a_venc_180d",
"outros",
"a_venc_180d",
"a_venc_180d",
"lim_up_1ano",
"lim_1ano"
],
"classesModalidades": [
"cartao",
"cartao",
"cartao",
"cartao",
"financiamento",
"financiamento"
]
},
{
"valoresVencimentos": [
268.59,
27.6,
428.51,
173.85,
2301.45,
100,
241.11
],
"classesVencimentos": [
"a_venc_180d",
"outros",
"a_venc_180d",
"a_venc_180d",
"lim_up_1ano",
"lim_1ano",
"a_venc_180d"
],
"classesModalidades": [
"cartao",
"cartao",
"cartao",
"cartao",
"financiamento",
"financiamento",
"curto prazo"
]
}
]
And I need merge fields with same name of each object in the input array, to be:
{
"valoresVencimentos": [
1468.12,
85.9,
14.1,
1899.99,
241.92,
869.99,
696.11,
627.29,
241.92,
413.47,
229.74,
1687.58,
100,
268.59,
27.6,
428.51,
173.85,
2301.45,
100,
241.11
],
"classesVencimentos": [
"lim_up_1ano",
"lim_1ano",
"a_venc_180d",
"a_venc_180d",
"outros",
"a_venc_180d",
"a_venc_180d",
"a_venc_180d",
"outros",
"a_venc_180d",
"a_venc_180d",
"lim_up_1ano",
"lim_1ano",
"a_venc_180d",
"outros",
"a_venc_180d",
"a_venc_180d",
"lim_up_1ano",
"lim_1ano",
"a_venc_180d"
],
"classesModalidades": [
"financiamento",
"financiamento",
"curto prazo",
"cartao",
"cartao",
"cartao",
"cartao",
"cartao",
"cartao",
"cartao",
"cartao",
"financiamento",
"financiamento",
"cartao",
"cartao",
"cartao",
"cartao",
"financiamento",
"financiamento",
"curto prazo"
]
}
Currently my aggregation is:
db.collection.aggregate([
{
$match: { code: '11122233344' }
},
{
$project: {
_id: 0,
valoresVencimentos: '$response.operations.expirations.value',
classesVencimentos: '$response.operations.expirations.class',
classesModalidades: '$response.operations.expirations.modality'
}
},
{
$addFields: {
valoresVencimentos: {
$reduce: {
input: '$valoresVencimentos',
initialValue: [],
in: { $concatArrays: ['$$this', '$$value'] }
}
},
classesVencimentos: {
$reduce: {
input: '$classesVencimentos',
initialValue: [],
in: { $concatArrays: ['$$this', '$$value'] }
}
},
classesModalidades: {
$reduce: {
input: '$classesModalidades',
initialValue: [],
in: { $concatArrays: ['$$this', '$$value'] }
}
},
}
},
])
It's imporant to say that ordering should be the same of the input data, so I think that using $group maybe a problem, I already tried a lot of alternatives but my knowledge with the aggregation framework is kind limited, appreciate any help.
Try this:
db.myCollection.aggregate([
{
$facet: {
valoresVencimentos: [
{ $unwind: "$valoresVencimentos" },
{
$group: {
_id: null,
valoresVencimentos: { $push: "$valoresVencimentos" }
}
}
],
classesVencimentos: [
{ $unwind: "$classesVencimentos" },
{
$group: {
_id: null,
classesVencimentos: { $push: "$classesVencimentos" }
}
}
],
classesModalidades: [
{ $unwind: "$classesModalidades" },
{
$group: {
_id: null,
classesModalidades: { $push: "$classesModalidades" }
}
}
]
}
},
{ $unwind: "$valoresVencimentos" },
{ $unwind: "$classesVencimentos" },
{ $unwind: "$classesModalidades" },
{
$project: {
valoresVencimentos: "$valoresVencimentos.valoresVencimentos",
classesVencimentos: "$classesVencimentos.classesVencimentos",
classesModalidades: "$classesModalidades.classesModalidades"
}
}
]);
or you can combine last three $unwinds and $project into single $project:
...,
{
$project: {
valoresVencimentos: { $arrayElemAt: ["$valoresVencimentos.valoresVencimentos", 0] },
classesVencimentos: { $arrayElemAt: ["$classesVencimentos.classesVencimentos", 0] },
classesModalidades: { $arrayElemAt: ["$classesModalidades.classesModalidades", 0] }
}
}
...

Issues with geo indexes in mongodb

We have a collection of ~1M items that we query using the $nearSphere selector. It takes around between 3 seconds and 20 seconds to return 200 items.
From the explain plan of the request, we can see that is going through the same index 6 times.
Is it the expected behavior of mongodb query planner?
We would like to know if there is a way to force mongo to filter first by some field like endDate to reduce the set and then use $nearSphere?
On our monitoring system we can see some pagefault and assert but they might be related to the lack of IOPS of our hard drive.
Thank you for your help.
Here is the explan plan (I removed the rejected plans and troncates the BinData lines)
{
"queryPlanner": {
"plannerVersion": 1.0,
"namespace": "myCollection.Post",
"indexFilterSet": false,
"parsedQuery": {
"$and": [
{
"$or": [
{
"availableToUsers": {
"$eq": "M76zJCedq4"
}
},
{
"$nor": [
{
"availableToUsers": {
"$exists": true
}
}
]
}
]
},
{
"startDate": {
"$lt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"availableSubmitNumber": {
"$gt": 0.0
}
},
{
"endDate": {
"$gt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"name": {
"$in": ["Post1", "Post2"]
}
},
{
"$nor": [
{
"acceptedByUserId": {
"$eq": "M76zJCedq4"
}
}
]
},
{
"locationGeoPoint": {
"$nearSphere": [
174.9084055,
-36.9293289
]
}
}
]
},
"winningPlan": {
"stage": "FETCH",
"filter": {
"$and": [
{
"$or": [
{
"availableToUsers": {
"$eq": "M76zJCedq4"
}
},
{
"$nor": [
{
"availableToUsers": {
"$exists": true
}
}
]
}
]
},
{
"$nor": [
{
"acceptedByUserId": {
"$eq": "M76zJCedq4"
}
}
]
}
]
},
"inputStage": {
"stage": "GEO_NEAR_2D",
"keyPattern": {
"locationGeoPoint": "2d",
"endDate": 1.0,
"startDate": 1.0,
"availableSubmitNumber": 1.0,
"name": 1.0
},
"indexName": "locationGeoPoint_2d_endDate_1_startDate_1_availableSubmitNumber_1_name_1",
"indexVersion": 2.0,
"inputStages": [
{
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"filter": {
"$and": [
{
"endDate": {
"$gt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"startDate": {
"$lt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"availableSubmitNumber": {
"$gt": 0.0
}
},
{
"name": {
"$in": ["Post1", "Post2"]
}
}
]
},
"keyPattern": {
"locationGeoPoint": "2d",
"endDate": 1.0,
"startDate": 1.0,
"availableSubmitNumber": 1.0,
"name": 1.0
},
"indexName": "locationGeoPoint_2d_endDate_1_startDate_1_availableSubmitNumber_1_name_1",
"isMultiKey": false,
"isUnique": false,
"isSparse": false,
"isPartial": false,
"indexVersion": 2.0,
"direction": "forward",
"indexBounds": {
"locationGeoPoint": [
"[BinData(128, BEB167B000000000), BinData(128, BEB167BFFFFFFFFF)]"
],
"endDate": [
"[MinKey, MaxKey]"
],
"startDate": [
"[MinKey, MaxKey]"
],
"availableSubmitNumber": [
"[MinKey, MaxKey]"
],
"name": [
"[MinKey, MaxKey]"
]
}
}
},
{
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"filter": {
"$and": [
{
"endDate": {
"$gt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"startDate": {
"$lt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"availableSubmitNumber": {
"$gt": 0.0
}
},
{
"name": {
"$in": ["Post1", "Post2"]
}
}
]
},
"keyPattern": {
"locationGeoPoint": "2d",
"endDate": 1.0,
"startDate": 1.0,
"availableSubmitNumber": 1.0,
"name": 1.0
},
"indexName": "locationGeoPoint_2d_endDate_1_startDate_1_availableSubmitNumber_1_name_1",
"isMultiKey": false,
"isUnique": false,
"isSparse": false,
"isPartial": false,
"indexVersion": 2.0,
"direction": "forward",
"indexBounds": {
"locationGeoPoint": [
"[BinData(128, BEB1658000000000), BinData(128, BEB165BFFFFFFFFF)]",
"[BinData(128, BEB165C000000000), BinData(128, BEB165FFFFFFFFFF)]"
],
"endDate": [
"[MinKey, MaxKey]"
],
"startDate": [
"[MinKey, MaxKey]"
],
"availableSubmitNumber": [
"[MinKey, MaxKey]"
],
"name": [
"[MinKey, MaxKey]"
]
}
}
},
{
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"filter": {
"$and": [
{
"endDate": {
"$gt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"startDate": {
"$lt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"availableSubmitNumber": {
"$gt": 0.0
}
},
{
"name": {
"$in": ["Post1", "Post2"]
}
}
]
},
"keyPattern": {
"locationGeoPoint": "2d",
"endDate": 1.0,
"startDate": 1.0,
"availableSubmitNumber": 1.0,
"name": 1.0
},
"indexName": "locationGeoPoint_2d_endDate_1_startDate_1_availableSubmitNumber_1_name_1",
"isMultiKey": false,
"isUnique": false,
"isSparse": false,
"isPartial": false,
"indexVersion": 2.0,
"direction": "forward",
"indexBounds": {
"locationGeoPoint": [
"[BinData(128, BEB14BC000000000), BinData(128, BEB14BFFFFFFFFFF)]",
"[BinData(128, BEB14C0000000000), BinData(128, BEB14FFFFFFFFFFF)]",
"[BinData(128, BEB1580000000000), BinData(128, BEB15BFFFFFFFFFF)]",
"[BinData(128, BEB1600000000000), BinData(128, BEB163FFFFFFFFFF)]",
"[BinData(128, BEB1640000000000), BinData(128, BEB164FFFFFFFFFF)]",
"[BinData(128, BEB1650000000000), BinData(128, BEB1653FFFFFFFFF)]",
"[BinData(128, BEB1654000000000), BinData(128, BEB1657FFFFFFFFF)]",
"[BinData(128, BEB1680000000000), BinData(128, BEB16BFFFFFFFFFF)]"
],
"endDate": [
"[MinKey, MaxKey]"
],
"startDate": [
"[MinKey, MaxKey]"
],
"availableSubmitNumber": [
"[MinKey, MaxKey]"
],
"name": [
"[MinKey, MaxKey]"
]
}
}
},
{
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"filter": {
"$and": [
{
"endDate": {
"$gt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"startDate": {
"$lt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"availableSubmitNumber": {
"$gt": 0.0
}
},
{
"name": {
"$in": ["Post1", "Post2"]
}
}
]
},
"keyPattern": {
"locationGeoPoint": "2d",
"endDate": 1.0,
"startDate": 1.0,
"availableSubmitNumber": 1.0,
"name": 1.0
},
"indexName": "locationGeoPoint_2d_endDate_1_startDate_1_availableSubmitNumber_1_name_1",
"isMultiKey": false,
"isUnique": false,
"isSparse": false,
"isPartial": false,
"indexVersion": 2.0,
"direction": "forward",
"indexBounds": {
"locationGeoPoint": [
"[BinData(128, BE9BE00000000000), BinData(128, BE9BEFFFFFFFFFFF)]",
"[BinData(128, BE9BF80000000000), BinData(128, BE9BFBFFFFFFFFFF)]",
"[BinData(128, BEB1100000000000), BinData(128, BEB11FFFFFFFFFFF)]",
"[BinData(128, BEB1300000000000), BinData(128, BEB13FFFFFFFFFFF)]",
"[BinData(128, BEB1400000000000), BinData(128, BEB143FFFFFFFFFF)]"
],
"endDate": [
"[MinKey, MaxKey]"
],
"startDate": [
"[MinKey, MaxKey]"
],
"availableSubmitNumber": [
"[MinKey, MaxKey]"
],
"name": [
"[MinKey, MaxKey]"
]
}
}
},
{
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"filter": {
"$and": [
{
"endDate": {
"$gt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"startDate": {
"$lt": ISODate(
"2019-03-01T01:02:00.000+0000"
)
}
},
{
"availableSubmitNumber": {
"$gt": 0.0
}
},
{
"name": {
"$in": ["Post1", "Post2"]
}
}
]
},
"keyPattern": {
"locationGeoPoint": "2d",
"endDate": 1.0,
"startDate": 1.0,
"availableSubmitNumber": 1.0,
"name": 1.0
},
"indexName": "locationGeoPoint_2d_endDate_1_startDate_1_availableSubmitNumber_1_name_1",
"isMultiKey": false,
"isUnique": false,
"isSparse": false,
"isPartial": false,
"indexVersion": 2.0,
"direction": "forward",
"indexBounds": {
"locationGeoPoint": [
"[BinData(128, BE9B800000000000), BinData(128, BE9BBFFFFFFFFFFF)]",
"[BinData(128, BE9BC00000000000), BinData(128, BE9BCFFFFFFFFFFF)]"
],
"endDate": [
"[MinKey, MaxKey]"
],
"startDate": [
"[MinKey, MaxKey]"
],
"availableSubmitNumber": [
"[MinKey, MaxKey]"
],
"name": [
"[MinKey, MaxKey]"
]
}
}
}
]
}
}
},
"serverInfo": {
"port": 27017.0,
"version": "4.0.3",
"gitVersion": "7ea530946fa7880364d88c8d8b6026bbc9ffa48c"
},
"ok": 1.0,
"operationTime": Timestamp(1551940718,
4),
"$clusterTime": {
"clusterTime": Timestamp(1551940718,
4),
"signature": {
"hash": BinData(0,
"AAAAAAAAAAAAAAAAAAAAAAAAAAA="
),
"keyId": NumberLong(0)
}
}
}

List<Widgets> in rows and lines dynamically in Flutter

I have json:
{
"name": "Test",
"groupsCount": 5,
"groups": [
{
"name": "William Cooper",
"number": 1,
"linesCount": 2,
"lines": [
{
"name": "Brittany Ramirez",
"number": 1,
"placesCount": 15,
"places": [
{
"name": "Elizabeth Welch",
"number": 1
},
{
"name": "Bradley Pugh",
"number": 2
},
{
"name": "Noah Johnson",
"number": 3
},
{
"name": "Laura Cox",
"number": 4
},
{
"name": "Tiffany Hatfield",
"number": 5
},
{
"name": "Patricia Hayes",
"number": 6
},
{
"name": "Kevin Jenkins MD",
"number": 7
},
{
"name": "Brent Wilkins",
"number": 8
},
{
"name": "Mr. Bruce Hart",
"number": 9
},
{
"name": "Courtney Newman",
"number": 10
},
{
"name": "Dawn Campbell",
"number": 11
},
{
"name": "Ashley Scott",
"number": 12
},
{
"name": "Robert Becker",
"number": 13
},
{
"name": "Kevin Williams",
"number": 14
},
{
"name": "Elizabeth Davidson",
"number": 15
}
]
},
{
"name": "Carol Watson",
"number": 2,
"placesCount": 12,
"places": [
{
"name": "Kathleen Jones",
"number": 16
},
{
"name": "Robin Smith",
"number": 17
},
{
"name": "David Johnson",
"number": 18
},
{
"name": "Richard Boyd",
"number": 19
},
{
"name": "Mason Randolph",
"number": 20
},
{
"name": "James Bernard",
"number": 21
},
{
"name": "Timothy Miller",
"number": 22
},
{
"name": "Thomas Stone",
"number": 23
},
{
"name": "Steven Jones",
"number": 24
},
{
"name": "William Hernandez",
"number": 25
},
{
"name": "Joy Duarte",
"number": 26
},
{
"name": "Justin Anderson",
"number": 27
}
]
}
]
},
{
"name": "Sarah Jordan",
"number": 2,
"linesCount": 1,
"lines": [
{
"name": "Lacey Estrada",
"number": 3,
"placesCount": 15,
"places": [
{
"name": "Madison Smith",
"number": 28
},
{
"name": "Kathleen Wells",
"number": 29
},
{
"name": "Dale Gross",
"number": 30
},
{
"name": "Brandy Cabrera",
"number": 31
},
{
"name": "Ashley Torres",
"number": 32
},
{
"name": "Ralph Long",
"number": 33
},
{
"name": "Christopher Walker",
"number": 34
},
{
"name": "Kimberly Moore",
"number": 35
},
{
"name": "Andrea Ortiz",
"number": 36
},
{
"name": "Heidi Todd",
"number": 37
},
{
"name": "Austin Wang",
"number": 38
},
{
"name": "Bryan Adams",
"number": 39
},
{
"name": "Jeffrey Alvarado",
"number": 40
},
{
"name": "Richard Morrison",
"number": 41
},
{
"name": "Jennifer Hodge",
"number": 42
}
]
}
]
},
{
"name": "Tiffany Lynch",
"number": 3,
"linesCount": 1,
"lines": [
{
"name": "Kimberly Howe DVM",
"number": 4,
"placesCount": 15,
"places": [
{
"name": "Nancy King",
"number": 43
},
{
"name": "Angela Cabrera",
"number": 44
},
{
"name": "Elizabeth Mack",
"number": 45
},
{
"name": "Shelly Riggs",
"number": 46
},
{
"name": "Jeremy French",
"number": 47
},
{
"name": "Deborah Myers",
"number": 48
},
{
"name": "Robert Kramer",
"number": 49
},
{
"name": "Brian Cunningham MD",
"number": 50
},
{
"name": "Christopher Brown",
"number": 51
},
{
"name": "Kathryn James",
"number": 52
},
{
"name": "Cassandra Martinez",
"number": 53
},
{
"name": "Nathan Long",
"number": 54
},
{
"name": "Molly Wilson",
"number": 55
},
{
"name": "Matthew Reilly",
"number": 56
},
{
"name": "Erin Maddox",
"number": 57
}
]
}
]
},
{
"name": "Christopher Martin",
"number": 4,
"linesCount": 1,
"lines": [
{
"name": "Gina Brewer",
"number": 5,
"placesCount": 13,
"places": [
{
"name": "Dennis Owens",
"number": 58
},
{
"name": "Rebecca Caldwell",
"number": 59
},
{
"name": "James Mckinney",
"number": 60
},
{
"name": "Donna Lee",
"number": 61
},
{
"name": "Michelle Martinez",
"number": 62
},
{
"name": "Jennifer Davis",
"number": 63
},
{
"name": "Shawn Moore",
"number": 64
},
{
"name": "Jeremiah Reilly",
"number": 65
},
{
"name": "Bruce Mendoza",
"number": 66
},
{
"name": "Juan Weaver",
"number": 67
},
{
"name": "Brian Bates",
"number": 68
},
{
"name": "Caitlin Jenkins",
"number": 69
},
{
"name": "Rachel Thomas",
"number": 70
}
]
}
]
},
{
"name": "Michelle Thompson",
"number": 5,
"linesCount": 2,
"lines": [
{
"name": "Kathleen Hall",
"number": 6,
"placesCount": 12,
"places": [
{
"name": "Jennifer Vaughan",
"number": 71
},
{
"name": "Glenn Mayer",
"number": 72
},
{
"name": "Allison Coleman",
"number": 73
},
{
"name": "Brittany Harris",
"number": 74
},
{
"name": "John Mccullough",
"number": 75
},
{
"name": "James Curtis",
"number": 76
},
{
"name": "John Smith",
"number": 77
},
{
"name": "Alison Morales",
"number": 78
},
{
"name": "Matthew Jones",
"number": 79
},
{
"name": "Jessica Watson",
"number": 80
},
{
"name": "Yvonne Anderson",
"number": 81
},
{
"name": "David Price",
"number": 82
}
]
},
{
"name": "Sarah White",
"number": 7,
"placesCount": 10,
"places": [
{
"name": "Kathleen Owen",
"number": 83
},
{
"name": "Amy Strickland",
"number": 84
},
{
"name": "James Collier",
"number": 85
},
{
"name": "Keith Smith Jr.",
"number": 86
},
{
"name": "Christopher York",
"number": 87
},
{
"name": "Patricia Todd",
"number": 88
},
{
"name": "Matthew Harris",
"number": 89
},
{
"name": "Betty Mckee",
"number": 90
},
{
"name": "Kayla Hahn",
"number": 91
},
{
"name": "Craig Duncan",
"number": 92
}
]
}
]
}
]
}
and I want to build view using lines and places. So if group have 2 lines and each line has 15 places I want to build something like that:
...............
...............
This is my code:
import 'package:flutter/material.dart';
import 'package:parking/models/groups.dart';
import 'package:parking/models/parking_group.dart';
import 'package:parking/services/parking_service.dart';
class ParkingDetailsScreen extends StatefulWidget {
#override
createState() => ParkingDetailsState();
}
class ParkingDetailsState extends State<ParkingDetailsScreen> {
#override
Widget build(BuildContext context) {
return Scaffold(
appBar: AppBar(
title: Text("Parking Details"),
),
body: FutureBuilder<ParkingGroup>(
future: ParkingService.getParking(),
builder: (context, snapshot) {
if (snapshot.hasError) print(snapshot.error);
return snapshot.hasData
? _buildParking(snapshot.data)
: Center(child: CircularProgressIndicator());
},
)
);
}
}
final _parkings = <Groups>[];
Widget _buildParking(ParkingGroup parkingGroup) {
_parkings.clear();
_parkings.addAll(parkingGroup.groups);
return ListView.builder(
itemCount: _parkings.length,
itemBuilder: (context, index) {
return _buildRow(_parkings[index], context);
},
);
}
Widget _buildRow(Groups parkingGroup, BuildContext context) {
return Container(
padding: const EdgeInsets.all(16.0),
child: Row(
children: _buildRowList(parkingGroup),
),
);
}
List<Widget> _buildRowList(Groups parkingGroup) {
List<Widget> places = [];
for (var place in parkingGroup.lines) {
for (var placeLine in place.places) {
places.add(_buildPlace(placeLine));
}
}
return places;
}
Widget _buildPlace(place) {
return Container(
padding: const EdgeInsets.only(bottom: 8.0),
child:
SizedBox(
height: 5,
width: 5,
child: DecoratedBox(
decoration: BoxDecoration(
border: Border.all(color: Colors.blueAccent),
)),
),
);
}
//
//Widget _buildRow(Groups parkingGroup, BuildContext context) {
// return Container(
// padding: const EdgeInsets.all(16.0),
// child: Row(
// children: [
// Container(
// padding: const EdgeInsets.only(bottom: 8.0),
// child:
// SizedBox(
// height: 30,
// width: 30,
// child: DecoratedBox(
// decoration: BoxDecoration(
// border: Border.all(color: Colors.blueAccent),
// )),
// ),
// ),
// ],
// ),
// );
//}
but for this code I see all places in one line:
..............................
instead of
...............
...............
What I need to change in my code to get good result?
You need to change your _buildRow() and _buildRowList() methods:
Widget _buildRow(Groups parkingGroup, BuildContext context) {
return Container(
padding: const EdgeInsets.all(16.0),
child: Column( // As you expect multiple lines you need a column not a row
children: _buildRowList(parkingGroup),
),
);
}
List<Widget> _buildRowList(Groups parkingGroup) {
List<Widget> lines = []; // this will hold Rows according to available lines
for (var line in parkingGroup.lines) {
List<Widget> placesForLine = [] // this will hold the places for each line
for (var placeLine in line.places) {
placesForLine.add(_buildPlace(placeLine));
}
lines.add(Row(children: placesForLine));
}
return lines;
}

How to calculate YTD and MTD in mongodb?

How to calculate Month-To-Date(MTD) and Year-To-Date(YTD) in mongodb in a single query? sample data below, in this data requestedOn is a date field, I want to calculate MTD & YTD, on the assumption of financial year on "1st Jan of the year"(For example financial year for year 2016 is "01-Jan-2016" :
{
"_id": {
"$oid": "5808578b33fa6f161c9747f8"
},
"_class": "exceltest.TestBean",
"requestedOn": "2000-03-01",
"bookName": "Test6",
"revenue": 10.0,
"unitsSold": 1,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
},
{
"categoryCode": "Cooking/Beverages/Bartending"
},
{
"categoryCode": "Food Receipe/Taste"
}
]
}{
"_id": {
"$oid": "5808578b33fa6f161c9747f9"
},
"_class": "exceltest.TestBean",
"requestedOn": "2000-03-01",
"bookName": "Test1",
"revenue": 11.0,
"unitsSold": 2,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
},
{
"categoryCode": "Cooking/Beverages/Bartending"
},
{
"categoryCode": "Food Receipe/Taste"
}
]
}{
"_id": {
"$oid": "5808578b33fa6f161c9747fa"
},
"_class": "exceltest.TestBean",
"requestedOn": "2000-06-01",
"bookName": "Test2",
"revenue": 12.0,
"unitsSold": 3,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
},
{
"categoryCode": "Cooking/Beverages/Bartending"
},
{
"categoryCode": "Food Receipe/Taste"
}
]
}{
"_id": {
"$oid": "5808578b33fa6f161c9747fb"
},
"_class": "exceltest.TestBean",
"requestedOn": "2000-07-01",
"bookName": "Test3",
"revenue": 13.0,
"unitsSold": 4,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
},
{
"categoryCode": "Cooking/Beverages/Bartending"
},
{
"categoryCode": "Food Receipe/Taste"
}
]
}{
"_id": {
"$oid": "5808578b33fa6f161c9747fc"
},
"_class": "exceltest.TestBean",
"requestedOn": "2009-09-01",
"bookName": "Test4",
"revenue": 14.0,
"unitsSold": 5,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
},
{
"categoryCode": "Cooking/Beverages/Bartending"
},
{
"categoryCode": "Food Receipe/Taste"
}
]
}{
"_id": {
"$oid": "5808578b33fa6f161c9747fd"
},
"_class": "exceltest.TestBean",
"requestedOn": "2009-06-01",
"bookName": "Test5",
"revenue": 15.0,
"unitsSold": 6,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
},
{
"categoryCode": "Cooking/Beverages/Bartending"
},
{
"categoryCode": "Food Receipe/Taste"
}
]
}{
"_id": {
"$oid": "5808578b33fa6f161c9747fe"
},
"_class": "exceltest.TestBean",
"requestedOn": "2004-06-01",
"bookName": "Test10",
"revenue": 16.0,
"unitsSold": 7,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
},
{
"categoryCode": "Cooking/Beverages/Bartending"
},
{
"categoryCode": "Food Receipe/Taste"
}
]
}{
"_id": {
"$oid": "5808578b33fa6f161c9747ff"
},
"_class": "exceltest.TestBean",
"requestedOn": "2000-01-01",
"bookName": "Test11",
"revenue": 100.0,
"unitsSold": 100,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
},
{
"categoryCode": "Cooking/Beverages/Bartending"
},
{
"categoryCode": "Food Receipe/Taste"
}
]
}{
"_id": {
"$oid": "580857b833fa6f0c3499e462"
},
"_class": "exceltest.TestBean",
"requestedOn": "2000-02-01",
"bookName": "Test1",
"revenue": 20.0,
"unitsSold": 10,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
}
]
}{
"_id": {
"$oid": "580857b833fa6f0c3499e463"
},
"_class": "exceltest.TestBean",
"requestedOn": "2001-02-01",
"bookName": "Test2",
"revenue": 19.0,
"unitsSold": 9,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
}
]
}{
"_id": {
"$oid": "580857b833fa6f0c3499e464"
},
"_class": "exceltest.TestBean",
"requestedOn": "2001-02-01",
"bookName": "Test3",
"revenue": 18.0,
"unitsSold": 8,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
}
]
}{
"_id": {
"$oid": "580857b833fa6f0c3499e465"
},
"_class": "exceltest.TestBean",
"requestedOn": "2007-06-01",
"bookName": "Test4",
"revenue": 17.0,
"unitsSold": 7,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
}
]
}{
"_id": {
"$oid": "580857b833fa6f0c3499e466"
},
"_class": "exceltest.TestBean",
"requestedOn": "2005-06-01",
"bookName": "Test5",
"revenue": 16.0,
"unitsSold": 6,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
}
]
}{
"_id": {
"$oid": "580857b833fa6f0c3499e467"
},
"_class": "exceltest.TestBean",
"requestedOn": "2004-06-01",
"bookName": "Test1",
"revenue": 15.0,
"unitsSold": 5,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
}
]
}{
"_id": {
"$oid": "580857b833fa6f0c3499e468"
},
"_class": "exceltest.TestBean",
"requestedOn": "2002-06-01",
"bookName": "Test2",
"revenue": 14.0,
"unitsSold": 4,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
}
]
}{
"_id": {
"$oid": "580857b833fa6f0c3499e469"
},
"_class": "exceltest.TestBean",
"requestedOn": "2001-06-01",
"bookName": "Test3",
"revenue": 13.0,
"unitsSold": 3,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
}
]
}{
"_id": {
"$oid": "580857b833fa6f0c3499e46a"
},
"_class": "exceltest.TestBean",
"requestedOn": "2000-06-01",
"bookName": "Test4",
"revenue": 12.0,
"unitsSold": 2,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
}
]
}{
"_id": {
"$oid": "580857b833fa6f0c3499e46b"
},
"_class": "exceltest.TestBean",
"requestedOn": "2008-06-01",
"bookName": "Test5",
"revenue": 11.0,
"unitsSold": 1,
"bookCategory": [
{
"categoryCode": "Cooking/"
},
{
"categoryCode": "Cooking/Beverages"
},
{
"categoryCode": "Food Receipe/"
},
{
"categoryCode": "Food Receipe/Bartending"
}
]
}
Regards
Kris
It is a good practice to keep dates in MongoDB in its native dateformat ISODate().
You can use date formats like $year,$month,$day,$hour etc.
These can be used for grouping , in your case:
db.collectionName.aggregate([
{$group:{_id:{'Date':{$year:'$requestedOn'}},total:{$sum:'$FieldName'}}}
])
to convert string to ISODate , answers can be found at
- [http://stackoverflow.com/questions/15473772/how-to-convert-from-string-to-date-data-type?noredirect=1&lq=1][2]
- [http://stackoverflow.com/questions/15473772/how-to-convert-from-string-to-date-data-type?noredirect=1&lq=1][2]