I have query results from MongoDB as an array of documents with nested subdocuments and arrays of subdocuments.
[
{
RecordID: 9000,
RecordType: 'Item',
Location: {
_id: 5d0699326e310a6fde926a08,
LocationName: 'Example Location A'
}
Items: [
{
Title: 'Example Title A',
Format: {
_id: 5d0699326e310a6fde926a01,
FormatName: 'Example Format A'
}
},
{
Title: 'Example Title B',
Format: {
_id: 5d0699326e310a6fde926a01,
FormatName: 'Example Format B'
}
}
],
},
{
RecordID: 9001,
RecordType: 'Item',
Location: {
_id: 5d0699326e310a6fde926a08,
LocationName: 'Example Location C'
},
Items: [
{
Title: 'Example Title C',
Format: {
_id: 5d0699326e310a6fde926a01,
FormatName: 'Example Format C'
}
}
],
}
]
Problem
I need to export the results to XLSX in column order. The XLSX library is working to export the top-level properties (such as RecordID and RecordType) only. I also need to export the nested objects and arrays of objects. Given a list of property names e.g. RecordID, RecordType, Location.LocationName, Items.Title, Items.Format.FormatName the properties must be exported to XLSX columns in the specified order.
Desired result
Here is the desired 'flattened' structure (or something similar) that
I think should be able to convert to XLSX columns.
[
{
'RecordID': 9000,
'RecordType': 'Item',
'Location.LocationName': 'Example Location A',
'Items.Title': 'Example Title A, Example Title B',
'Items.Format.FormatName': 'Example Format A, Example Format B',
},
{
'RecordID': 9001,
'RecordType': 'Item',
'Location.LocationName': 'Example Location C',
'Items.Title': 'Example Title C',
'Items.Format.FormatName': 'Example Format C',
}
]
I am using the XLSX library to convert the query results to XLSX which works for top-level properties only.
const worksheet: XLSX.WorkSheet = XLSX.utils.json_to_sheet(results.data);
const workbook: XLSX.WorkBook = { Sheets: { 'data': worksheet }, SheetNames: ['data'] };
const excelBuffer: any = XLSX.write(workbook, { bookType: 'xlsx', type: 'array' });
const data: Blob = new Blob([excelBuffer], { type: EXCEL_TYPE });
FileSaver.saveAs(data, new Date().getTime());
POSSIBLE OPTIONS
I am guessing I need to 'flatten' the structure either using aggregation in the query or by performing post-processing when the query is returned.
Option 1: Build the logic in the MongoDB query to flatten the results.
$replaceRoot might work since it is able to "promote an existing embedded document to the top level". Although I am not sure if this will solve the problem exactly, I do not want to modify the documents in place, I just need to flatten the results for exporting.
Here is the MongoDB query I am using to produce the results:
records.find({ '$and': [ { RecordID: { '$gt': 9000 } } ]},
{ skip: 0, limit: 10, projection: { RecordID: 1, RecordType: 1, 'Items.Title': 1, 'Items.Location': 1 }});
Option 2: Iterate and flatten the results on the Node server
This is likely not the most performant option, but might be the easiest if I can't find a way to do so within the MongoDB query.
UPDATE:
I may be able to use MongoDB aggregate $project to 'flatten' the results. For example, this aggregate query effectively 'flattens' the results by 'renaming' the properties. I just need to figure out how to implement the query conditions within the aggregate operation.
db.records.aggregate({
$project: {
RecordID: 1,
RecordType: 1,
Title: '$Items.Title',
Format: '$Items.Format'
}
})
UPDATE 2:
I have abandoned the $project solution because I would need to change the entire API to support aggregation. Also, I would need to find a solution for populate because aggregate does not support it, rather, it uses $lookup which is possible but time consuming because I would need to write the queries dynamically. I am going back to look into how to flatten the object by creating a function to iterate the array of objects recursively.
Below is a solution for transforming the Mongo data on the server via a function flattenObject which recursively flattens nested objects and returns a 'dot-type' key for nested paths.
Note that the snippet below contains a function that renders and editable table to preview, however, the important part you want (download the file), should be triggered when you run the snippet and click the 'Download' button.
const flattenObject = (obj, prefix = '') =>
Object.keys(obj).reduce((acc, k) => {
const pre = prefix.length ? prefix + '.' : '';
if (typeof obj[k] === 'object') Object.assign(acc, flattenObject(obj[k], pre + k));
else acc[pre + k] = obj[k];
return acc;
}, {});
var data = [{
RecordID: 9000,
RecordType: "Item",
Location: {
_id: "5d0699326e310a6fde926a08",
LocationName: "Example Location A"
},
Items: [{
Title: "Example Title A",
Format: {
_id: "5d0699326e310a6fde926a01",
FormatName: "Example Format A"
}
},
{
Title: "Example Title B",
Format: {
_id: "5d0699326e310a6fde926a01",
FormatName: "Example Format B"
}
}
]
},
{
RecordID: 9001,
RecordType: "Item",
Location: {
_id: "5d0699326e310a6fde926a08",
LocationName: "Example Location C"
},
Items: [{
Title: "Example Title C",
Format: {
_id: "5d0699326e310a6fde926a01",
FormatName: "Example Format C"
}
}]
}
];
const EXCEL_MIME_TYPE = `application/vnd.ms-excel`;
const flattened = data.map(e => flattenObject(e));
const ws_default_header = XLSX.utils.json_to_sheet(flattened);
const ws_custom_header = XLSX.utils.json_to_sheet(flattened, {
header: ['Items.Title', 'RecordID', 'RecordType', 'Location.LocationName', 'Items.Format.FormatName']
});
const def_workbook = XLSX.WorkBook = {
Sheets: {
'data': ws_default_header
},
SheetNames: ['data']
}
const custom_workbook = XLSX.WorkBook = {
Sheets: {
'data': ws_custom_header
},
SheetNames: ['data']
}
const def_excelBuffer = XLSX.write(def_workbook, {
bookType: 'xlsx',
type: 'array'
});
const custom_excelBuffer = XLSX.write(custom_workbook, {
bookType: 'xlsx',
type: 'array'
});
const def_blob = new Blob([def_excelBuffer], {
type: EXCEL_MIME_TYPE
});
const custom_blob = new Blob([custom_excelBuffer], {
type: EXCEL_MIME_TYPE
});
const def_button = document.getElementById('dl-def')
/* trigger browser to download file */
def_button.onclick = e => {
e.preventDefault()
saveAs(def_blob, `${new Date().getTime()}.xlsx`);
}
const custom_button = document.getElementById('dl-cus')
/* trigger browser to download file */
custom_button.onclick = e => {
e.preventDefault()
saveAs(custom_blob, `${new Date().getTime()}.xlsx`);
}
/*
render editable table to preview (for SO convenience)
*/
const html_string_default = XLSX.utils.sheet_to_html(ws_default_header, {
id: "data-table",
editable: true
});
const html_string_custom = XLSX.utils.sheet_to_html(ws_custom_header, {
id: "data-table",
editable: true
});
document.getElementById("container").innerHTML = html_string_default;
document.getElementById("container-2").innerHTML = html_string_custom;
<script src="https://cdnjs.cloudflare.com/ajax/libs/xlsx/0.14.3/xlsx.full.min.js"></script>
<head>
<title>Excel file generation from JSON</title>
<meta charset="utf-8" />
<style>
.xport,
.btn {
display: inline;
text-align: center;
}
a {
text-decoration: none
}
#data-table,
#data-table th,
#data-table td {
border: 1px solid black
}
</style>
</head>
<script>
function render(type, fn, dl) {
var elt = document.getElementById('data-table');
var wb = XLSX.utils.table_to_book(elt, {
sheet: "Sheet JS"
});
return dl ?
XLSX.write(wb, {
bookType: type,
bookSST: true,
type: 'array'
}) :
XLSX.writeFile(wb, fn || ('SheetJSTableExport.' + (type || 'xlsx')));
}
</script>
<div>Default Header</div>
<div id="container"></div>
<br/>
<div>Custom Header</div>
<div id="container-2"></div>
<br/>
<table id="xport"></table>
<button type="button" id="dl-def">Download Default Header Config</button>
<button type="button" id="dl-cus">Download Custom Header Config</button>
<script src="https://cdnjs.cloudflare.com/ajax/libs/FileSaver.js/1.3.8/FileSaver.min.js"></script>
I wrote a function to iterate all object in the results array and create new flattened objects recursively. The flattenObject function shown here is similar to the previous answer and I took additional inspiration from this related answer.
The '_id' properties are specifically excluded from being added to the flattened object, since ObjectIds are still being returned as bson types even though I have the lean() option set.
I still need to figure out how to sort the objects such that they are in the order given e.g. RecordID, RecordType, Items.Title. I believe that might be easiest to achieve by creating a separate function to iterate the flattened results, although not necessarily the most performant. Let me know if anyone has any suggestions on how to achieve the object sorting by a given order or has any improvements to the solution.
const apiCtrl = {};
/**
* Async array iterator
*/
apiCtrl.asyncForEach = async (array, callback) => {
for (let index = 0; index < array.length; index++) {
await callback(array[index], index, array)
}
}
// Check if a value is an object
const isObject = (val) => {
return typeof val == 'object' && val instanceof Object && !(val instanceof Array);
}
// Check if a value is a date object
const isDateObject = (val) => {
return Object.prototype.toString.call(val) === '[object Date]';
}
/**
* Iterate object properties recursively and flatten all values to top level properties
* #param {object} obj Object to flatten
* #param {string} prefix A string to hold the property name
* #param {string} res A temp object to store the current iteration
* Return a new object with all properties on the top level only
*
*/
const flattenObject = (obj, prefix = '', res = {}) =>
Object.entries(obj).reduce((acc, [key, val]) => {
const k = `${prefix}${key}`
// Skip _ids since they are returned as bson values
if (k.indexOf('_id') === -1) {
// Check if value is an object
if (isObject(val) && !isDateObject(val)) {
flattenObject(val, `${k}.`, acc)
// Check if value is an array
} else if (Array.isArray(val)) {
// Iterate each array value and call function recursively
val.map(element => {
flattenObject(element, `${k}.`, acc);
});
// If value is not an object or an array
} else if (val !== null & val !== 'undefined') {
// Check if property has a value already
if (res[k]) {
// Check for duplicate values
if (typeof res[k] === 'string' && res[k].indexOf(val) === -1) {
// Append value with a separator character at the beginning
res[k] += '; ' + val;
}
} else {
// Set value
res[k] = val;
}
}
}
return acc;
}, res);
/**
* Convert DB query results to an array of flattened objects
* Required to build a format that is exportable to csv, xlsx, etc.
* #param {array} results Results of DB query
* Return a new array of objects with all properties on the top level only
*/
apiCtrl.buildExportColumns = async (results) => {
const data = results.data;
let exportColumns = [];
if (data && data.length > 0) {
try {
// Iterate all records in results data array
await apiCtrl.asyncForEach(data, async (record) => {
// Convert the multi-level object to a flattened object
const flattenedObject = flattenObject(record);
// Push flattened object to array
exportColumns.push(flattenedObject);
});
} catch (e) {
console.error(e);
}
}
return exportColumns;
}
Related
I have an array of objects like with the same setup as the one below. I wanna insert this array of objects into postgres table that looks like this:[![Table setup][1]][1]
I have tried to make a function below but it returns error when inserting UNGDOMSKOLE because this is a string so it doesn't understand the space so it crashes on the second input value. How can I make it understand it is a string?
{
'#type': 'SensorSystem',
id: 'SN47230',
name: 'ÅKRA UNGDOMSSKOLE',
shortName: 'Åkra ',
country: 'Norge',
countryCode: 'NO',
geometry: {
'#type': 'Point',
coordinates: [ 5.1963, 59.2555 ],
nearest: false
},
masl: 18,
validFrom: '2013-10-29T00:00:00.000Z',
county: 'ROGALAND',
countyId: 11,
municipality: 'KARMØY',
municipalityId: 1149,
stationHolders: [ 'KARMØY KOMMUNE' ],
externalIds: [ '506131077' ],
wigosId: '0-578-0-47230'
}
Error code:
error: syntax error at or near "UNGDOMSSKOLE"
What I have tried so far:
let sqlinsert= data.data.map((source)=>{
if (source.geometry) {
if(!source.masl){
source.masl=0
}
let Point = `POINT(${source.geometry.coordinates[0]} ${source.geometry.coordinates[1]})`;
return `(${source.id}, ${source.name}, ${source.shortName},${source.country},${source.countryCode},${source.masl},${source.geometry.coordinates[0]},${source.geometry.coordinates[1]},${Point},${source.validFrom},${source.county},${source.countyId},${source.municipality},${source.municipalityId})`
}
})
const result = await db.query("INSERT INTO sources(source_id,name,shortName,country,countryCode,masl,long,lat,geog,valid_from,county,countyId,municipality,municipalityId) values"+sqlinsert[0])
A second problem I have with this is that inserting
POINT(59.2555 5.1963)
Gives a syntax error at 5.1963
[1]: https://i.stack.imgur.com/4RSkq.png
The main problem with your query as written is that you are adding raw, unescaped values into your VALUES records. You can use escapeLiteral on your db client to ensure that these values are properly escaped which will solve the syntax errors you are getting:
const data = [
{
"#type": "SensorSystem",
id: "SN47230",
name: "ÅKRA UNGDOMSSKOLE",
shortName: "Åkra ",
country: "Norge",
countryCode: "NO",
geometry: {
"#type": "Point",
coordinates: [5.1963, 59.2555],
nearest: false,
},
masl: 18,
validFrom: "2013-10-29T00:00:00.000Z",
county: "ROGALAND",
countyId: 11,
municipality: "KARMØY",
municipalityId: 1149,
stationHolders: ["KARMØY KOMMUNE"],
externalIds: ["506131077"],
wigosId: "0-578-0-47230",
},
].map((source) => {
const {
id,
name,
shortName,
country,
countryCode,
masl,
geometry: {
// the coordinates in your source data appear to be in y,x instead of
// x,y. Treating them as x,y results in the point being located
// in the Indian Ocean while y,x is somewhere in Norway.
coordinates: [lat, long],
},
validFrom,
county,
countyId,
municipality,
municipalityId,
} = source;
return [
id,
name,
shortName,
country,
countryCode,
masl || 0,
long,
lat,
`POINT( ${long} ${lat} )`,
validFrom,
county,
countyId,
municipality,
municipalityId,
];
});
const headers = [
"source_id",
"name",
"shortname",
"country",
"countrycode",
"masl",
"long",
"lat",
"geog",
"valid_from",
"county",
"countyid",
"municipality",
"municipalityid",
];
const sourceValStr = data
.map((sourceRecords, rowIndex) => {
return sourceRecords
.map((value, colIndex) => {
if (typeof value === "string") {
// safely escape string values
return dbClient.escapeLiteral(value);
}
if (
typeof value === "number" ||
typeof value === "boolean" ||
typeof value === "bigint"
) {
return value;
}
if (value === undefined || value === null) {
return "null";
}
throw new Error(
`non-simple value: ${JSON.stringify(value)} for ${
headers[colIndex]
} at row ${rowIndex}`
);
})
.join(",");
})
.map((value) => `(${value})`)
.join(",");
const sourceInsert = `INSERT INTO sources(${headers.join(
","
)}) VALUES ${sourceValStr};`;
await dbClient.query(sourceInsert);
A much more efficient and scalable way to insert the rows is to use the pg-copy-streams library in conjunction with a CSV library like csv-stringify which will bulk insert using a COPY FROM stream:
import { from as copyFrom } from "pg-copy-streams";
import { stringify } from "csv-stringify";
// ...
const copyStmt = `COPY sources(${headers.join(
","
)}) FROM STDIN (FORMAT CSV)`;
await new Promise<void>((resolve, reject) => {
const copyStream = dbClient.query(copyFrom(copyStmt));
const stringifiedStream = stringify(data, {
header: false,
encoding: "utf-8",
delimiter: ",",
quote: "\"",
});
stringifiedStream
.on("error", (err) => {
reject(err);
})
.on("end", () => resolve());
stringifiedStream.pipe(copyStream);
});
On my low-end laptop, this approach takes about 39 seconds to insert a million rows with no database optimizations.
I am building a product-filter in nodeJS. It works when i hard-code the following find()
const products = await Product.find({
price: {
$gte: price[0],
$lte: price[1],
}, category: categories, shipping: shipping})
The problem is of course that it only gives result if entered all the search options in the front-end.
However i also want the filter to work if i choose to NOT enter all the search options.
Thus i came up with the following code, to store all filters in an array, but it doesn't give any results.
The output of the array is =
{ price: { '$gte': 0, '$lte': 40820 } },
{
category: [
'60657e1d328b25043581e46f',
'601ef1ea8e06fc04cdaa5080',
'601eeaeb8e06fc04cdaa507f'
]
},
{ shipping: 'Yes' }
] <<<_--- content of searchArry????
This is my code, but it returns no results =
exports.searchFilters = async (req, res) => {
try {
const categories = req.body.categoryIds;
const price = req.body.price;
const shipping = req.body.shipping;
console.log(price, "<<<------- price data received in backend???");
console.log(categories, "<<--- categories data received in backend???");
console.log(shipping, "<<---- shipping data received in backend");
const searchArray = [];
if (req.body.price) {
const price = {
$gte: req.body.price[0],
$lte: req.body.price[1],
}
searchArray.push({ "price" : price });
}
if (req.body.categoryIds) {
searchArray.push({ "category" : categories });
}
if (req.body.shipping) {
searchArray.push({ "shipping" : shipping });
}
console.log(searchArray, "<<<_--- content of searchArry????");
const products = await Product.find({searchArray})
.populate("category", "_id name")
.populate("subs", "_id name")
.populate("postedBy", "_id name")
.exec();
res.json(products);
// console.log(products, "<<--producte?? ") console.log(products.length, "<<--- lengte") } catch(err) { console.log(err); }}
} catch(err) {
console.log(err);
}
}
Your hardcoded call looks like this:
Product.find({price, category, shipping}) // the arg is an object
And the second call (with searchArray) looks like:
Product.find({searchArray: [{price}, {category}, {shipping}]}) // the arg is an object containing an array of objects
Try merging the elements of searchArray into a single object:
Product.find(Object.assign({}, ...searchArray))
Note: Be aware that {variableName} is a shorthand for {variableName: variableName} or {"variableName": variableName}.
I have this array list of objects.
var list = [{
'ID':1,
'name' : 'Vikas Yadav',
'mobile':8095638475,
'sent':false
},
{
'ID':2,
'name' : 'Rajat Shukla',
'mobile':7486903546,
'sent':false
},
{
'ID':3,
'name' : 'Munna Bhaiya',
'mobile':9056284550,
'sent':false
},
{
'ID':4,
'name' : 'Guddu Pandit',
'mobile':7780543209,
'sent':false
},
{
'ID':5,
'name' : 'Srivani Iyer',
'mobile':8880976501,
'sent':false
}];
Now I want to push two more datas in specific element of this array via forLoop as:
var timeAndOTPArray = {
"time" : new Date(),
"OTP": req.params.ran
}
I am retrieving the list data via cookies into one of the route.
Below is the code I am trying to push the element according to the matching condition.
var lists = req.cookies.list;
Object.keys(lists).forEach(function(item) {
if(req.params.ID == lists[item].ID){ //look for match with name
(lists[item]).push(timeAndOTPArray);
newAddedList.push(lists[item]);
console.log(item, lists[item]);
}
});
Perhaps it's not the correct way. Please help!
Wish you a happy and a prosperous Diwali.
Cheers!
You can use findIndex and append to update the object into list like this:
//List only with ID, easier to read the code
var list = [{'ID':1,},{'ID':2,}]
//your object
var timeAndOTPArray = {
"time" : new Date(),
"OTP": "otp"
}
//Index where object with ID == 2 is
var index = list.findIndex(obj => obj.ID == 2);
//Append the 'timeAndOTPArray' properties into the object itself
list[index] = {"time": timeAndOTPArray.time, "OTP":timeAndOTPArray.OTP, ...list[index]}
console.log(list)
I guess this will help
var lists = req.cookies.list;
Object.keys(lists).forEach(function(item) {
if(req.params.ID == lists[item].ID){ //look for match with ID
Object.keys(timeAndOTPArray).forEach(key=>{
lists[item][key]=timeAndOTPArray[key];
})
}
});
Good evening) I can advice you the best option is update with map
const listItems = [
{
ID: 1,
name: 'Vikas Yadav',
mobile: 8095638475,
sent: false,
},
{
ID: 2,
name: 'Rajat Shukla',
mobile: 7486903546,
sent: false,
},
{
ID: 3,
name: 'Munna Bhaiya',
mobile: 9056284550,
sent: false,
},
{
ID: 4,
name: 'Guddu Pandit',
mobile: 7780543209,
sent: false,
},
{
ID: 5,
name: 'Srivani Iyer',
mobile: 8880976501,
sent: false,
},
];
const paramId = 4;
const result = listItems.map((item) => {
if (paramId === item.ID) {
return {
...item,
time: new Date(),
OTP: 'smth',
};
}
return item;
});
console.log('result', result);
for appending, you can do this,
lists[index] = Object.assign(lists[index], timeAndOTPArray);
If you are using es6,
lists[index] = {...lists[index], timeAndOTPArray};
Here lists is an array of objects.
so lists[item] is an object, so you cant push an object to an object.
In your code timeAndOTPArray is an object.
In your lists object, initialize an empty array called timeAndOTPArray
var index = lists.findIndex(function(item){ return item.ID == req.params.ID});
lists[index].timeAndOTPArray.push(timeAndOTPArray);
Background: Im developing an app that shows analytics for inventory management.
It gets an office EXCEL file uploaded, and as the file uploads the app convert it to an array of JSONs. Then, it comapers each json object with the objects in the DB, change its quantity according to the XLS file, and add a timestamp to the stamps array which contain the changes in qunatity.
For example:
{"_id":"5c3f531baf4fe3182cf4f1f2",
"sku":123456,
"product_name":"Example",
"product_cost":10,
"product_price":60,
"product_quantity":100,
"Warehouse":4,
"stamps":[]
}
after the XLS upload, lets say we sold 10 units, it should look like that:
{"_id":"5c3f531baf4fe3182cf4f1f2",
"sku":123456,
"product_name":"Example",
"product_cost":10,
"product_price":60,
"product_quantity":90,
"Warehouse":4,
"stamps":[{"1548147562": -10}]
}
Right now i cant find the right commands for mongoDB to do it, Im developing in Node.js and Angular, Would love to read some ideas.
for (let i = 0; i < products.length; i++) {
ProductsDatabase.findOneAndUpdate(
{"_id": products[i]['id']},
//CHANGE QUANTITY AND ADD A STAMP
...
}
You would need two operations here. The first will be to get an array of documents from the db that match the ones in the JSON array. From the list you compare the 'product_quantity' keys and if there is a change, create a new array of objects with the product id and change in quantity.
The second operation will be an update which uses this new array with the change in quantity for each matching product.
Armed with this new array of updated product properties, it would be ideal to use a bulk update for this as looping through the list and sending
each update request to the server can be computationally costly.
Consider using the bulkWrite method which is on the model. This accepts an array of write operations and executes each of them of which a typical update operation
for your use case would have the following structure
{ updateOne :
{
"filter" : <document>,
"update" : <document>,
"upsert" : <boolean>,
"collation": <document>,
"arrayFilters": [ <filterdocument1>, ... ]
}
}
So your operations would follow this pattern:
(async () => {
let bulkOperations = []
const ids = products.map(({ id }) => id)
const matchedProducts = await ProductDatabase.find({
'_id': { '$in': ids }
}).lean().exec()
for(let product in products) {
const [matchedProduct, ...rest] = matchedProducts.filter(p => p._id === product.id)
const { _id, product_quantity } = matchedProduct
const changeInQuantity = product.product_quantity - product_quantity
if (changeInQuantity !== 0) {
const stamps = { [(new Date()).getTime()] : changeInQuantity }
bulkOperations.push({
'updateOne': {
'filter': { _id },
'update': {
'$inc': { 'product_quantity': changeInQuantity },
'$push': { stamps }
}
}
})
}
}
const bulkResult = await ProductDatabase.bulkWrite(bulkOperations)
console.log(bulkResult)
})()
You can use mongoose's findOneAndUpdate to update the existing value of a document.
"use strict";
const ids = products.map(x => x._id);
let operations = products.map(xlProductData => {
return ProductsDatabase.find({
_id: {
$in: ids
}
}).then(products => {
return products.map(productData => {
return ProductsDatabase.findOneAndUpdate({
_id: xlProductData.id // or product._id
}, {
sku: xlProductData.sku,
product_name: xlProductData.product_name,
product_cost: xlProductData.product_cost,
product_price: xlProductData.product_price,
Warehouse: xlProductData.Warehouse,
product_quantity: productData.product_quantity - xlProductData.product_quantity,
$push: {
stamps: {
[new Date().getTime()]: -1 * xlProductData.product_quantity
}
},
updated_at: new Date()
}, {
upsert: false,
returnNewDocument: true
});
});
});
});
Promise.all(operations).then(() => {
console.log('All good');
}).catch(err => {
console.log('err ', err);
});
I'm attempting to use the mapReduce function of Mongodb via Mongoose, but the map function I'm passing in is never called. Here is the data currently contained in the "Post" model collection:
[ { data: 'Tag test data',
name: 'Tag Test',
_id: 5130dff2560105c235000002,
__v: 0,
comments: [],
tags: [ 'tag1', 'tag2', 'tag3' ] },
{ data: 'Testing tags. Again.',
name: 'Another test post',
_id: 5131213b611fe1f443000002,
__v: 0,
comments: [],
tags: [ 'tags', 'test', 'again' ] } ]
Here is the code:
var Schema = mongoose.Schema;
var PostSchema = new Schema ({
name : String
, data : String
, tags : [String]
});
mongoose.model('Post', PostSchema);
var o = {};
o.map = function() {
if (!this.tags) {
//console.log('No tags found for Post ' + this.name);
return;
}
for (index in this.tags) {
emit(this.tags[index], 1);
}
}
o.reduce = function(previous, current) {
var count = 0;
for (index in current) {
count += current[index];
}
return count;
}
o.out = { replace : 'tags'}
o.verbose = true;
var Post = mongoose.model('Post');
Post.mapReduce(o, function(error, model, stats) {
console.log('model: ' + model);
console.log('stats: ' + stats);
});
The "model" and "stats" objects are always undefined, and the log statements in the map function are never called. If I do something like this with the Post model outside of the mapReduce function, I get the data at the top of the post as expected:
Post.find().exec(function(err, posts) {
console.log(posts);
});
Any suggestions? I'm sure something is just slightly off...
You can't call console.log from within the map and reduce functions as it's not supported by Mongo's JavaScript engine.
To debug your map/reduce/finalize functions you can use the MongoDB print statement. The output will be added to your Mongo log file.