Calling Values From A Database into Javascript - joomla3.0

I have a Joomla 3 site and need to add a calculator from Codeweavers.net. I am using DJ Classifieds and the site is up and running. The calculator is designed to to provide HP or PCP finance. The Javacript fields are below. The info to populate the fields is already in the database.
<script type='text/javascript'>
function loadPlugin() {
codeweavers.main({
pluginContentDivId: 'pluginContent',
vehicle: {
type: 'Car',
identifier: '',
identifierType: 'CAPSHORTCODE',
isNew: false,
cashPrice: '',
mileage: '',
imageUrl: '',
linkBackUrl: '',
registration: {number: ''},
}
});
}
loadPlugin();
</script>
The database fields are below:
identifier (field in database is id 27, name capcode )
cashPrice (Price from the item table, name price)
mileage (field in database is id 4, name mileage)
imageUrl (This would be the first image from the vehicle details page)
linkBackUrl (This would be the url for the detail page)
registration (field in database is id 11, name registration)
I am looking for guidance or maybe someone to provide me with a quote to carry out the work? Codeweavers themselves do not provide support for integration.
Thanks
Dave

It can be done with custom codes.
I think it needs spend 3-5 hrs.
I think it will be around 50$

Is that $50 for 3 hours work or the hourly rate?

Related

How to model this NoSQL data structure in Firestore (Review my first approach)

I am a fairly new web developer and would need your help with a project I am currently working on. I have worked in the past on a very simple realtime database example and have little to none experience in firestore or NoSql in general.
I want to create a system which allows end-users to get an email once a week that contains a list of special offers from bars the end-user has subscribed to. The offers change each day of the week. Bar owners can fill out a form in a vue.js web application every week with their weekly special offers.
Every Monday morning a cron job has to look up which end user has subscribed to which bars and then aggregate the data and send it via email.
The question is how would you structure the data so that I can easily compose the email and send it via a cloud function?
My approach would be to have three main collections: RestaurantOwner, EndUser, SpecialOfferings
Please see the graphic for an example process:
BarOwner and EndUser are pretty straight forward. However, the difficult part is how to structure the SpecialOffers in order to be queried the right way.
My idea would be to structure it based on the calendar week and link it to the uid from the barOwner:
specialOffers: {
2019_CW27: {
barUID001: {
mon: {
title: 'Banana Daiquir',
price: 4.99,
},
tue: {
title: 'After Five',
price: 2.99,
},
wed: {
title: 'Cool Colada',
price: 6.99
},
thu: {
title: 'Crantini',
price: 5.99
},
fri: {
title: 'French Martini',
price: 4.99
}
},
barUID002: {
mon: {
title: 'Gin & Tonic',
price: 8.99,
},
tue: {
title: 'Cratini',
price: 4.99,
},
wed: {
title: 'French Martini',
price: 4.99
},
thu: {
title: 'After Five',
price: 3.99
},
fri: {
title: 'Cool Colada',
price: 6.99
}
}
},
2019_CW28: {
barUID01: {~~~},
barUID02: {~~~}
}
}
The disadvantage of this approach is that it creates a deeply nested object when you imagine that there are 52 calendar weeks, f.e 100 signed up bars à 5 special offers per week and I am not sure if I am able to query it the way I need to.
Is this approach reasonable or what would you do differently?
Thank you so much for your help! I highly appreciate it.
I'm assuming the following scenarios:
1) The bar owners make modifications to their offers very often.
2) The bar owners should be the only ones allowed to modify each bar's offers.
If you have these two scenarios, I would recommend a sub-collections approach here.
When to use sub-collections:
1) When there are lot of fields in a document. Cloud Firestore has 20,000 field limit. (If the number of Bars can exceed more than 20,000 fields)
2) When updating the parent collection is a common operation. Firestore only lets you update the document at rate of 1 write/second. (If the SpecialOffers information of each bar is modified very often. If two bar owners modify their offers, only 1 write is successful and the second write operation waits until the first is completed. This can delay the updation offers particularly at the end of a week when almost all the bars update the offers.)
3) When you want to limit the access to particular fields of a document. (If you want to restrict the access to a Bar's Offers to the barOwner alone. You can restrict the access to each document in the Bars sub-collection according to its owner using Firestore Security Rules)
So I would recommend a sub-collection Bars under the main collection SpecialOffers. This way the design becomes scalable and you can add restaurants and super-markets as other similar sub-collections in the future without heavily altering your design.
Another advantage is that sub-collections are basically collections and they don't have a limit for number of documents it can hold. So even if the number of bars registered is above 20,000 which is the limit of number of fields for a fire-store document, your sub-collection wont be having a problem but your document will run out of fields to save the offers for a new bar.
Ultimately the choice depends on your use cases.
Hope this helps.

Mongodb schema best storage of Achievement system [closed]

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Im going to create a achievement system in Mongodb. But im not sure how i would format/store it in the database.
As of the users should have a progress (on each achievement they would have some progress value stored), im really confused what would be the best way to perform this, and without having an performence issue.
what should i do?, cause i dont know, what i had in mind, was maybe something like:
Should i store each achievement in an unique row in a Achievement collection, and an user array within that row, containing object with userid and achievement progress?
Would i then get an performance issue when its 1000+ achievements, that is beeing checked fairy often?
or should i do something else?
example schema for the option above:
{
name:{
type:String,
default:'Achievement name'
},
users:[
{
userid:{
type:String,
default:' users id here'
},
progress:{
type:Number,
default:0
}
}
]
}
Even though the question is specifically about the database design, I will give a solution for the tracking/awarding logic as well to establish more accurate context for the db design.
I would store the achievements progress separately from the already awarded achievements for cleaner tracking and discovery.
The whole logic is event based and has multiple layers of event handling. This gives you TONS of flexibility on how you track your data and also gives you a pretty good mechanism to track history. Basically, you can look at it as a form of logging.
Of course, your system design and contracts are highly dependent on the information you're gonna be tracking and its complexity. A simple progress field may not suffice for each case(you might want to track something more complex, not a simple number between X and Y). There is also the case of tracking data which updates quite frequently(as distance travelled in games, for example). You didn't give any context on the topic of your achievement system so we're gonna stick with a generic solution. It's just a couple of things that you should take a note about as it will affect the design.
Okay, so, let's start from the top and track the entire flow for a tracked piece of data and its eventual achievement progress. Let's say we're tracking consecutive days of user login and we're gonna award him with an achievement when he reaches [10].
Note that everything below is just a pseudo-code.
So, let's say today is [8th of July, 2017]. For now, our User entity looks like this:
User: {
id: 7;
trackingData: {
lastLogin: 7 of July, 2017 (should be full DateTime object, but using this for brevity),
consecutiveDays: 9
},
achievementProgress: [
{
achievementID: 10,
progress: 9
}
],
achievements: []
}
And our achievements collection contains the following entity:
Achievement: {
id: 10,
name: '10 Consecutive Days',
rewardValue: 10
}
The user tries to login(or visit the site). The application handler takes note of that and after handling the login logic fires an event of type ACTION:
ACTION_EVENT = {
type: ACTION,
name: USER_LOGIN,
payload: {
userID: 7,
date: 8 of July, 2017 (should be full DateTime object, but using this for brevity)
}
}
We have an ActionHandler which listens for events of type ACTION:
ActionHandler.handleEvent(actionEvent) {
subscribersMap = Map<eventName, handlers>;
subscribersMap[actionEvent.name].forEach(subscriber => subscriber.execute(actionEvent.payload));
}
subscribersMap gives us a collection of handlers that should respond to each specific action(this should resolve to USER_LOGIN for us). In our case we can have 1 or 2 that concern themselves with updating the user tracking information of lastLogin and consecutiveDays tracking properties in the user entity. The handlers in our case will update the tracking information and fire new events further down the line.
Once again, for brevity, we're gonna incorporate both into one:
updateLoginHandler: function(payload) {
user = db.getUser(payload.userID);
let eventType;
let eventValue;
if (date - user.trackingData.lastLogin > 1 day) {
user.trackingData = 1;
eventType = 'PROGRESS_RESET';
eventValue = 1;
}
else {
const newValue = user.trackingData.consecutiveDays + 1;
user.trackingData.consecutiveDays = newValue;
eventType = 'PROGRESS_INCREASE';
eventValue = newValue;
}
user.trackingData.lastLogin = payload.date;
/* DISPATCH NEW EVENT OF TYPE ACHIEVEMENT_PROGRESS */
AchievementProgressHandler.dispatch({
type: ACHIEVEMENT_PROGRESS
name: eventType,
payload: {
userID: payload.userID,
achievmentID: 10,
value: eventValue
}
});
}
Here, PROGRESS_RESET have the same contract as the PROGRESS_INCREASE but have a different semantic meaning and I would keep them separate for history/tracking purposes. If you wish, you can combine them into a single PROGRESS_UPDATE event.
Basically, we update the tracked fields that are dependent on the lastLogin date and fire a new ACHIEVEMENT_PROGRESS event which should be handled by a separate handler with the same pattern(AchievementProgressHandler). In our case:
ACHIEVEMENT_PROGRESS_EVENT = {
type: ACHIEVEMENT_PROGRESS,
name: PROGRESS_INCREASE
payload: {
userID: 7,
achievementID: 10,
value: 10
}
}
Then, in AchievementProgressHandler we follow the same pattern:
AchievementProgressHandler: function(event) {
achievementCheckers = Map<achievementID, achievementChecker>;
/* update user.achievementProgress code */
switch(event.name): {
case 'PROGRESS_INCREASE':
achievementCheckers[event.payload.achievementID].execute(event.payload);
break;
case 'PROGRESS_RESET':
...
}
}
achievementCheckers contains a checker function for each specific achievement that decides if the achievement has reached its desired value(a progress of 100%) and should be awarded. This enables us to handle all kinds of complex cases. If you only track a single X out of Y scenario, you can share the function between all achievements.
The handler basically does this:
achievementChecker: function(payload) {
achievementAwardHandler;
achievement = db.getAchievement(payload.achievementID);
if (payload.value >= achievement.rewardValue) {
achievementAwardHandler.dispatch({
type: ACHIEVEMENT_AWARD,
name: ACHIEVEMENT_AWARD,
payload: {
userID: payload.userID,
achievementID: achievementID,
awardedAt: [current date]
}
});
/* Here you can clear the entry from user.achievementProgress as you no longer need it. You can also move this inside the achievementAwardHandler. */
}
}
We once again dispatch an event and use an event handler - achievementAwardHandler. You can skip the event creation step and award the achievement to the user directly but we keep it consistent with the whole history logging flow.
An added benefit here is that you can use the handler to defer the achievement awarding to a specific later time thus effectively batching awarding for multiple users, which serve a couple of purposes including performance enhancement.
Basically, this pseudo code handles the flow from [a user action] to [achievement rewarding] with all intermediate steps included. It's not set in stone, you can modify it as you like but all in all, it gives you a clean separation of concerns, cleaner entities, it's performant, let's you add complex checks and handlers which are easy to reason about while in the same time provide a great history log of the user overall progress.
Regarding the DB schema entities, I would suggest the following:
User: {
id: any;
trackingData: {},
achievementProgress: {} || [],
achievements: []
}
Where:
trackingData is an object that contains everything you're willing
to track about the user. The beauty is that properties here are
independent from achievement data. You can track whatever and eventually use it for achievement purposes.
achievementProgress: a map of <key: achievementID, value: data> or
an array containing the current progress for each achievement.
achievements: an array of awarded achievements.
and Achievement:
Achievement: {
id: any,
name: any,
rewardValue: any (or any other field/fields. You have complete freedom to introduce any kind of tracking with the approach above),
users?: [
{
userID: any,
awardedAt: date
}
]
}
users is a collection of users who have been rewarded the given achievement. This is optional and is here only if you have the use for it and query for this data frequently.
What you might be looking for is a Badge style implementation. Just like Stack Overflow rewards it's users with badges for specific achievements.
Method 1: You can have flags in the user profile for each badge. Since you're doing it in NoSQL database, you just have to set a flag for each badge.
const badgeSchema = new mongoose.Schema({
badgeName: {
type: String,
required: true,
},
badgeDescription: {
type: String,
required: true,
}
});
const userSchema = new mongoose.Schema({
userName: {
type: String,
required: true,
},
badges: {
type: [Object],
required: true,
}
});
If your application architecture is event based, you can trigger awarding badges to users. And that operation is just inserting Badge object with progress in User badges array.
{
badgeId: ObjectId("602797c8242d59d42715ba2c"),
progress: 10
}
Update operation will be to find and update the badges array with progress percentage number
And while displaying user achievements on user interface, you can just loop over badges array to show the badges this user has achieved and their progress with it.
Method 2: Have a separate mongo collection for Badge and User Mapping. Whenever a user achieves a badge you insert a record in that collection. It will be one to one mapping of user _id and badge _id and progress value. But as the table will grow huge you will need to do indexing to efficiently query user and badge mapping.
You will have to do analysis on best approach according to your specific use case.
MongoDB is flexible enough to allow teams develop applications quickly, and involve their model with litter friction as the application needs it. In cases where you need a robust model from day one, theirs is a flexible methodology that can guide you through the process of modeling your data.
The methodology is composed of:
Workload: This stage is about gathering as much information as possible to understand your data. This will allow you formulate assumptions about, you data size the operations that will be performance against it (reads and writes), quantify operations and qualify operations.
You can get this by:
Scenarios
Prototype
Production Logs & Stats (if you are migrating).
Relationships: Identify the relationship between the different entities in your data, quantify those relationships and apply embedding or linking. In general you should prefer embedding by default, but remember that arrays should not grow without bound (6 Rules of Thumb for MongoDB Schema Design: Part 3).
Patterns: Apply schema design patterns. Take a look at Building with Patterns: A Summary, it presents a matrix that highlights the pattern that could be useful for a given use case.
Finally, the goal of this methodology is help you create a model, that can scale and perform well under stress.
If you design the achievement schema like this:
{
name: {
type: String,
default: "Achievement name",
},
userid: {
type: String,
default: " users id here",
},
progress: {
type: Number,
default: 0,
},
}
}
When an achievement is gained you just add another entry
for getting achievements Map-Reduce is a good candidate for running map reduce on the database. you can run them on a less regular basis, using them for offline computation of the data that you want.
based on documentation you can do like the following photo

Efficient way to store frequently requested key-value data with relations?

Let's say I'm building Twitter.
One of the tasks is to track, which tweets are read by particular user and store this data on server. When user requests somebody's feed, server should return:
[
{
id: 1,
tweet: "Hey there!",
isRead: false
},
{
id: 2,
tweet: "Here's my cat, look",
isRead: true
},
{
id: 2,
tweet: "Blue or yellow? Thats the question",
isRead: true
},
...
]
Which is the most efficient way to store data for which tweets are read by which user, and retrieving this data when returning somebody's feed for particular user?
Any ideas about data storing architecture are highly appreciated. My current stack is PostgreSQL for storing users and "tweets". Redis, MongoDB and neo4j are also used in the project, so available.
The first guess was to use Redis, like:
user_id: tweet_id
-----------------
user_id: tweet_id
-----------------
....
But I think, there may be better variants, more suitable for persistent data storage.
Thank you in advance.
Have a look at this Twitter-clone that Redis' author, antirez (a.k.a Salvatore Sanfilippo), had made: http://redis.io/topics/twitter-clone

When to use a nested array versus using a separate collection

I need to use mongoose with dbref but I don't know which design is better for me.
First design:
var user = mongoose.Schema({
name: 'string'
});
var eventSchema = mongoose.Schema({
title: 'string',
propietary_id: 'String',
comments : [{
text: 'string',
user: { type : mongoose.Schema.Types.ObjectId, ref : 'users' },
createdAt: {type: Date, default: Date.now }
}]
});
Second design:
var user = mongoose.Schema({
name: 'string'
});
var eventSchema = mongoose.Schema({
title: 'string',
propietary_id: 'String'
});
var commentSchema = mongoose.Schema({
text: 'string',
event_id : { type : mongoose.Schema.Types.ObjectId, ref : 'events' },
user_id : { type : mongoose.Schema.Types.ObjectId, ref : 'users' },
createdAt: {type: Date, default: Date.now }
});
How it works? On my website there is an event list and if you want to see comments you have to click every event, then angularjs gets all comments (text, user name and user photo) of the selected events.
There are pros and cons with both solutions and the best one for you depends on your usage. Remember that you can produce exactly the same API independent of your design it only comes down to how quickly and easily you can maintain the backend. First some thoughts on both designs:
First design:
First a comment, I wouldn't save comments as a nested document but as an array instead. Otherwise you are limited to one comment per event. Use this schema instead:
comments: [
{
text: { type: String },
user: { type: mongoose.Schema.Types.ObjectId, ref : 'users' },
createdAt: { type: Date, default: Date.now },
}
]
Pros:
No need for multiple collections
You will have the comments returned with the event in the get request which will mean less requests to your backend
No need to map comments to events
Cons:
You will have the comments returned to you with the event, even if you don't want them displayed
If there are a lot of comments to an event, the request response will be pretty large
If you want to remove or edit comments in your array it will be trickier (not impossible though)
Second design:
Pros:
You will have the events and comments separated which means leaner objects
You can much easier extract one comment for edit or delete
You can more easily get events without comments and then request comments at another point
Cons:
You will need to always map comments to events which will mean more code
Two collections will mean two requests usually
Maintenance of another collection
Verdict:
All the pros and cons are judged by how much extra code you need to write. Of course you can always have comments returned with your events in the second design as well but then you will have the extract the comments first and returned them with the event object which will mean extra code to maintain.
I think the second design would work better for you. I'm judging this by your comment that you will only need comments if the user click on an event. I would then be requesting the events first and do another request for comments as soon as the user click on the event, however, having the comments always be returned with the events should make the ui more snappy as the comments will already have been loaded.
It all depends in the end what is more important for you to do with the data. Please let me know if you have any questions on any of the points.

Data Modeling Best Practices in Firebase/AngularFire

I'm developing an application in Firebase for the first time and was curious how I should model the data between two objects, a user and a post. I come from more of a relational db background and was curious not only how this would be done in nonrelational DBs but specifically how to set up a relationship between two objects in Firebase.
For example, my application has many Users, and each user creates many Posts.
User {
firstName: String,
lastname: String,
userName: String
}
Post {
title: String,
content: String,
date: Date,
writtenBy: [User object?]
}
How should I structure these two objects in Firebase so that a Post belongs to a User, but all Posts can be queried for regardless of User, and both User and Post objects can be edited without disrupting the other object's data and/or relationship?
And how should I create new "relational" objects via firebase:
sync.$set({userA: {
firstname: "Billy",
lastName: "Bob",
userName: "BillyBob",
Posts: {
// .....
}
}
});
Thanks!
Firebase is built with performance in mind. This is the reason you have to design data structures differently, normalization is your enemy in most cases. Every object in Firebase can be accessed by URL, and you should always keep this in mind.
There are still many ways of designing the data structures, it depends on what queries do you want to execute. If one of the queries is to be able to display all messages (I believe a number of latest messages would be the most common use case), but at the same time you want to be able to show messages per user than one of the possible data structures could look like this:
User {
userId(assigned by Firebase automatically) {
firstName: String,
lastname: String,
userName: String
}
}
Post {
User {
userId(matching userId in the User object) {
postId(assigned by Firebase for every new post automatically) {
title: String,
content: String,
date: Date,
writtenBy: String, userName or userId (this is not really needed, but may keep it for easier data access)
}
}
}
}
Then you can change any user data without triggering data change events in Posts, like in your example, (which would be extremely heavy if you have large number of messages).
You can get all messages independently of user:
var postListRef = new Firebase(URL);
var lastPostQuery = postListRef.child("Post").limit(500);
You can also use startAt() and endAt() quesries https://www.firebase.com/docs/web/api/query/limit.html
As a drawback - you have to unpack every message in the for loop if you need to show only messages, but I would expect you would show user info as well, so it should be ok.
If you want to listen for just one user messages, it's very simple and fast:
var postListRef = new Firebase(URL);
var lastPostQuery = postListRef.child("Post/User").child(userId);
And Angular/AngularFire has great support for this kind of data structures.
I am also new to Firebase, I would recommend the following structure.
Users: {
userID: {
firstName: String,
lastname: String,
userName: String,
posts: {
postID1:true,
postID2:true
}
Posts: {
postID1:{
title: String,
content: String,
date: Date,
writtenBy: userID
}
}
It allows you to get the latest posts without having to through any users. Plus you can get all the post made by any user.

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