I have the following form array in Vuelidate. But how can I base some validation based on another field's value on the same array index.
Below is my none working example, but I want the forename to be required IF something has been entered for the surname.
validations: {
fixturesArray: {
$each: {
fixtureName: {
//required
},
guestDetails: {
$each: {
forename: {
required: requiredIf(function() {
return $each.surname != ""
})
},
surname: {
},
dietaryRequirements: {
$each: {
name: {
}
}
}
}
}
}
}
},
let's assume your case is: Forename is required if surname is not null
validations: {
fixturesArray: {
$each: {
guestDetails: {
$each: {
forename: {
requiredIf: requiredIf((obj) => obj.surname != null)
},
surname: {
}
}
}
}
}
}
You can use requiredIf in $each like that, although this is not stated in the documentation. The obj parameter is the object being validated in this iteration. You can see more information here.
Hope it helps, cheers.
Related
I have a collection "Owners" and I want to return a list of "Owner" matching a filter (any filter), plus the count of "Pet" from the "Pets" collection for that owner, except I don't want the dead pets. (made up example)
I need the returned documents to look exactly like an "Owner" document with the addition of the "petCount" field because I'm using Java Pojos with the Mongo Java driver.
I'm using AWS DocumentDB that does not support $lookup with filters yet. If it did I would use this and I'd be done:
db.Owners.aggregate( [
{ $match: {_id: UUID("b13e733d-2686-4266-a686-d3dae6501887")} },
{ $lookup: { from: 'Pets', as: 'pets', 'let': { ownerId: '$_id' }, pipeline: [ { $match: { $expr: { $ne: ['$state', 'DEAD'] } } } ] } },
{ $addFields: { petCount: { $size: '$pets' } } },
{ $project: { pets: 0 } }
]).pretty()
But since it doesn't this is what I got so far:
db.Owners.aggregate( [
{ $match: {_id: { $in: [ UUID("cbb921f6-50f8-4b0c-833f-934998e5fbff") ] } } },
{ $lookup: { from: 'Pets', localField: '_id', foreignField: 'ownerId', as: 'pets' } },
{ $unwind: { path: '$pets', preserveNullAndEmptyArrays: true } },
{ $match: { 'pets.state': { $ne: 'DEAD' } } },
{ "$group": {
"_id": "$_id",
"doc": { "$first": "$$ROOT" },
"pets": { "$push": "$pets" }
}
},
{ $addFields: { "doc.petCount": { $size: '$pets' } } },
{ $replaceRoot: { "newRoot": "$doc" } },
{ $project: { pets: 0 } }
]).pretty()
This works perfectly, except if an Owner only has "DEAD" pets, then the owner doesn't get returned because all the "document copies" got filtered out by the $match. I'd need the parent document to be returned with petCount = 0 when ALL of them are "DEAD". I cannot figure out how to do this.
Any ideas?
These are the supported operations for DocDB 4.0 https://docs.amazonaws.cn/en_us/documentdb/latest/developerguide/mongo-apis.html
EDIT: update to use $filter as $reduce not supported by aws document DB
You can use $filter to keep only not DEAD pets in the lookup array, then count the size of the remaining array.
Here is the Mongo playground for your reference.
$reduce version
You can use $reduce in your aggregation pipeline to to a conditional sum for the state.
Here is Mongo playground for your reference.
As of January 2022, Amazon DocumentDB added support for $reduce, the solution posted above should work for you.
Reference.
There is an application with search input that gives an opportunity to search for contacts by their information stored in database.
For example, I can type 0972133122 Alan and my search engine must return all contacts whose firstname is Alan & whose numbers match 0972133122 string.
Of course, I can just type Alan 0972, for instance, and there must be returned all possible contacts matching this pattern. The query order may be different, so that I can type 0972 Alan Smith, and if there are 2 contacts with Alan names and whose phone numbers start with 0972, then additional Smith clarification should return the only 1 contact.
I suggest built in phone applications for Android make use of this search algorithm:
So that my goal is to achieve similar result, but I do know how to do this. Here my code:
GraphQL query
query contacts {
contacts(input: {
contactQuery: "Alan Smith"
}) {
name {
firstName
lastName
}
}
}
NodeJS query to MongoDB
const conditions = {};
const expr = contactQuery
.split(' ')
.map((contact) => new RegExp(`${contact}`, 'i'))
conditions.$or = [
{ 'firstName': { $in: expr } },
{ 'lastName': { $in: expr } },
{ 'university': { $in: expr } },
{ emails: { $elemMatch: { email: { $in: expr } } } },
{ phones: { $elemMatch: { phone: { $in: expr } } } },
{ socials: { $elemMatch: { id: { $in: expr } } } },
]
const contacts = await this.contacts
.find(conditions, undefined)
.exec()
This works partly, but I receive unwanted documents from MongoDB:
{
contacts: [
{
firstName: "Alan",
lastName: "Smith",
university: "KNTU",
...
},
{
firstName: "Alan",
lastName: "Alderson", // should not be returned
university: "ZNU",
...
},
...
]
}
But I need to get one contact that has strictly Alan firstname and Smith lastname. If it's impossible to do with MongoDB, -- please, provide me an example of SQL query. Any suggestions & solutions will be accepted!
Please, let me know if my question still is not clear.
Firstly, you need to separate out the numbers and words from the search text and then you can create a possible combination of it for an example:
FirstName: Alan, LastName: Smith
FirstName: Smith, LastName: Alan
Using regex you can do this easily and then you can use logical operators of mongodb to create your query like this
Approach 1
db.collection.find({
$or: [
{
$and: [
{
firstName: {
$regex: "Alan",
$options: "i"
}
},
{
lastName: {
$regex: "Smith",
$options: "i"
}
}
]
},
{
$and: [
{
firstName: {
$regex: "Smith",
$options: "i"
}
},
{
lastName: {
$regex: "Alan",
$options: "i"
}
}
]
}
]
})
Here is the link to the playground for you to look at it in action Mongo Playground
Approach 2
Another way is where you concat all the searchable keys into one field and then use regex to filter it out like this
db.collection.aggregate([
{
$addFields: {
text: {
$concat: [
"$firstName",
" ",
"$lastName",
" ",
"$university",
" ",
"$phones"
]
}
}
},
{
$match: {
text: {
$regex: "(?=.*?(0972))(?=.*?(Alan))(?=.*?(Smith))",
$options: "i"
}
}
},
{
$project: {
text: 0
}
}
])
Code to build the query:
let text = "0972 Alan Smith";
let parts = text.split(" ");
let query = parts.map(part => "(?=.*?("+part+"))").join("");
console.log(query);
But you need to check the performance implication of this approach or you can create a view and then query to view to make your query more cleaner
Here is the link to the playground for you to look at it in action Mongo Playground
What is the optimize Query for this situation
So the Situation is a User is following many XY user and these XY have got events, So what will the best and optimize query to get all the events from his followers XY in sorted form (sort by Date). I have got create Date in my schema
This is my User Schema
var userSchema = new Schema({
followers:[{
type: Schema.Types.ObjectId,
ref: 'XY'
}]
});
var User = mongoose.model('User',userSchema);
module.exports = User;
Here is My XY schema
var XY= new Schema({
events:[{
type: Schema.Types.ObjectId,
ref: 'Event'
}],
});
var XY= mongoose.model('XY',XY);
module.exports = XY;
Try this.
User.aggregate([
{ $match: { _id: mongoose.Types.ObjectId(<userId here>) } },
{ $unwind: { path: "$followers" } },
{ $lookup: { from: 'XY', localField: 'followers', foreignField: '_id', as: 'followers' } },
{ $unwind: { path: "$followers" } },
{ $unwind: { path: "$followers.events" } },
{ $lookup: { from: 'Event', localField: 'followers.events', foreignField: '_id', as: 'followers.events' } },
{ $unwind: { path: "$followers.events" } },
{ $sort: { "followers.events.createdDate": **-1** } }, // -1 -> desc, 1 -> asc
{
"$project":
{
"_id": "$followers.events._id",
"createdDate": "$followers.events.createdDate",
// populate other event details here accordingly
}
}
], function (err, events, next) {
});
$lookup lets you populate a sub-document from a different schema.
After populating, the resultant documents will be an array, so $unwind is used before working on them.
note that $unwind is also used before doing a $lookup here as the field we are trying to populate is itself an array.
I have this query that provides me the join I want to:
db.summoners.aggregate([
{ "$match": { "nick":"Luispfj" } },
{ "$unwind": "$matches" },
{
"$lookup": {
"from":"matches",
"localField":"matches.gameId",
"foreignField":"gameId",
"as":"fullMatches"
}
},
{ "$unwind": "$fullMatches" },
{
"$group": {
"_id": null,
"matches": { "$push":"$fullMatches" }
}
}
])
But when I run the unwind function the null entries are gone. How do I retrieve them (with their respective "gameId"s, if possible?
Also, is there a way to retrieve only the matches array, instead of it being a subproperty of the "null-id-object" it creates?
$unwind takes an optional field preserveNullAndEmptyArrays which by default is false. If you set it to true, unwind will output the documents that are null. Read more about $unwind
{
"$unwind": {
path: "$fullMatches",
preserveNullAndEmptyArrays: true
}
},
I've been having troubles with Elastic Search (ES) dynamic mappings. Seems like I'm in a catch-22. https://www.elastic.co/guide/en/elasticsearch/guide/current/custom-dynamic-mapping.html
The main goal is to store everything as a string that comes into ES.
What I've tried:
In ES you can't create a dynamic mapping until the index has been
created. Okay, makes sense.
I can't create an empty index, so if
the first item sent into the index is not a string, I can't
re-assign it... I won't know what type of object with be the first
item in the index, it could be any type, due to how the the app accepts a variety of objects/events.
So if I can't create the mapping ahead of time, and I can't insert an empty index to create the mapping, and I can't change the mapping after the fact, how do I deal with the first item if its NOT a string???
Here's what I'm currently doing (using the Javascript Client).
createESIndex = function (esClient){
esClient.index({
index: 'timeline-2015-11-21',
type: 'event',
body: event
},function (error, response) {
if (error) {
logger.log(logger.SEVERITY.ERROR, 'acceptEvent elasticsearch create failed with: '+ error + " req:" + JSON.stringify(event));
console.log(logger.SEVERITY.ERROR, 'acceptEvent elasticsearch create failed with: '+ error + " req:" + JSON.stringify(event));
res.status(500).send('Error saving document');
} else {
res.status(200).send('Accepted');
}
});
}
esClientLookup.getClient( function(esClient) {
esClient.indices.putTemplate({
name: "timeline-mapping-template",
body:{
"template": "timeline-*",
"mappings": {
"event": {
"dynamic_templates": [
{ "timestamp-only": {
"match": "#timestamp",
"match_mapping_type": "date",
"mapping": {
"type": "date",
}
}},
{ "all-others": {
"match": "*",
"match_mapping_type": "string",
"mapping": {
"type": "string",
}
}
}
]
}
}
}
}).then(function(res){
console.log("put template response: " + JSON.stringify(res));
createESIndex(esClient);
}, function(error){
console.log(error);
res.status(500).send('Error saving document');
});
});
Index templates to the rescue !! That's exactly what you need, the idea is to create a template of your index and as soon as you wish to store a document in that index, ES will create it for you with the mapping you gave (even dynamic ones)
curl -XPUT localhost:9200/_template/my_template -d '{
"template": "index_name_*",
"settings": {
"number_of_shards": 1
},
"mappings": {
"type_name": {
"dynamic_templates": [
{
"strings": {
"match": "*",
"match_mapping_type": "*",
"mapping": {
"type": "string"
}
}
}
],
"properties": {}
}
}
}'
Then when you index anything in an index whose name matches index_name_*, the index will be created with the dynamic mapping above.
For instance:
curl -XPUT localhost:9200/index_name_1/type_name/1 -d '{
"one": 1,
"two": "two",
"three": true
}'
That will create a new index called index_name_1 with a mapping type for type_name where all properties are string. You can verify that with
curl -XGET localhost:9200/index_name_1/_mapping/type_name
Response:
{
"index_name_1" : {
"mappings" : {
"type_name" : {
"dynamic_templates" : [ {
"strings" : {
"mapping" : {
"type" : "string"
},
"match" : "*",
"match_mapping_type" : "*"
}
} ],
"properties" : {
"one" : {
"type" : "string"
},
"three" : {
"type" : "string"
},
"two" : {
"type" : "string"
}
}
}
}
}
}
Note that if you're willing to do this via the Javascript API, you can use the indices.putTemplate call.
export const user = {
email: {
type: 'text',
},
};
export const activity = {
date: {
type: 'text',
},
};
export const common = {
name: {
type: 'text',
},
};
import { Client } from '#elastic/elasticsearch';
import { user } from './user';
import { activity } from './activity';
import { common } from './common';
export class UserDataFactory {
private schema = {
...user,
...activity,
...common,
relation_type: {
type: 'join',
eager_global_ordinals: true,
relations: {
parent: ['activity'],
},
},
};
constructor(private client: Client) {
Object.setPrototypeOf(this, UserDataFactory.prototype);
}
async create() {
const settings = {
settings: {
analysis: {
normalizer: {
useLowercase: {
filter: ['lowercase'],
},
},
},
},
mappings: {
properties: this.schema,
},
};
const { body } = await this.client.indices.exists({
index: ElasticIndex.UserDataFactory,
});
await Promise.all([
await (async (client) => {
await new Promise(async function (resolve, reject) {
if (!body) {
await client.indices.create({
index: ElasticIndex.UserDataFactory,
});
}
resolve({ body });
});
})(this.client),
]);
await this.client.indices.close({ index: ElasticIndex.UserDataFactory });
await this.client.indices.putSettings({
index: ElasticIndex.UserDataFactory,
body: settings,
});
await this.client.indices.open({
index: ElasticIndex.UserDataFactory,
});
await this.client.indices.putMapping({
index: ElasticIndex.UserDataFactory,
body: {
dynamic: 'strict',
properties: {
...this.schema,
},
},
});
}
}
wrapper.ts
class ElasticWrapper {
private _client: Client = new Client({
node: process.env.elasticsearch_node,
auth: {
username: 'elastic',
password: process.env.elasticsearch_password || 'changeme',
},
ssl: {
ca: process.env.elasticsearch_certificate,
rejectUnauthorized: false,
},
});
get client() {
return this._client;
}
}
export const elasticWrapper = new ElasticWrapper();
index.ts
new UserDataFactory(elasticWrapper.client).create();