d3.queue is not giving an output - dc.js

This is the page I am trying to make it dynamic by enabling cross-filtering.
So the thing is they are having multiple API.
For the top first two: TOTAL CASES & DAILY CASES
They are using this API and the third one in the top is based on this API.
The bottom three AGE, GENDER, and NATIONALITY are from this API.
In all the API one thing is common that is a date but there are some API in which some data are missing for few dates like there is a gap( Not available for some of the dates).
So I thought of combining all the JSON API in terms of dates and then allow cross filter because I believe I can enable cross-filtering between them. Correct me If I am wrong.
Like If I click on gender female since it gives info about total cases where the patient was female so only confirmed cases from the Total cases will change not the recovered, deaths as data is not available. SO I guess I should combine the top 3 charts together and gender, age and nationality charts, together. Then Dc js would be able to handle nicely filtering between each segments (cases related to landmark, cases related to person info).
Line 123:
var log = console.log;
var q = queue()
.defer(d3.json, "https://api.covid19india.org/data.json")
.defer(d3.json, "https://api.rootnet.in/covid19-in/unofficial/covid19india.org/statewise/history");
q.await(function(error, data1, data2) {
log("==========>");
log("data1:", error,data1);
log("data2:", data2);
});
This is not working because I can't see console.log() output.
https://blockbuilder.org/ninjakx/8c48ab6481311aa0452046d66c4d8701
So my questions are:
1) Why d3.queue is not working?
2) Suggestion whether combining all the datas together and allowing a filltering is a good idea or not as there is limited data. Should I go for cross filtering between the same api charts. So in this case I will have 2 segments (cases related to landmark, cases related to person info)..
Using DC js I want to make it more interactive and display more info.

d3.queue is obsolete
The answer to your first question is cut-and-dried: you don't need d3.queue, and it was deprecated and removed in d3#5.
As of d3#5, D3's data loading APIs use ES6 Promises instead of asynchronous callbacks, so you can use Promise.all([...]) instead of d3.queue. Apparently no way to make the new API emit errors when called in the old way, so it just fails silently. :-/
The new way to write your code is
Promise.all([
d3.json("https://api.covid19india.org/data.json"),
d3.json("https://api.rootnet.in/covid19-in/unofficial/covid19india.org/statewise/history")
]).then(([data1,data2]) => {
log("==========>");
log("data1:", data1);
log("data2:", data2);
})
.catch(error => log('error', error))
I find this much easier to read and understand. A nice side effect is that if you neglect to do error handling (like most people), you'll automatically get a clear message in the log.
Working fork of your block.
Combining multiple data sets
Your second question is pretty open-ended, maybe it would be better to bring that to the dc.js users group?
In general, it's difficult to cross-filter more than one data set. You would have more than one chart group that redraws together, and you'd have to manually add handlers on some chart to initiate, clear filters, and redraw the other chart group.
I haven't seen too many dashboards that do this. You'd have to make it clear to users what is going on.

Related

How to keep derived state up to date with Apollo/GraphQL?

My situation is this: I have multiple components in my view that ultimately depend on the same data, but in some cases the view state is derived from the data. How do I make sure my whole view stays in sync when the underlying data changes? I'll illustrate with an example using everyone's favorite Star Wars API.
First, I show a list of all the films, with a query like this:
# ALL_FILMS
query {
allFilms {
id
title
releaseDate
}
}
Next, I want a separate component in the UI to highlight the most recent film. There's no query for that, so I'll implement it with a client-side resolver. The query would be:
# MOST_RECENT_FILM
query {
mostRecentFilm #client {
id
title
}
}
And the resolver:
function mostRecentFilmResolver(parent, variables, context) {
return context.client.query({ query: ALL_FILMS }).then(result => {
// Omitting the implementation here since it's not relevant
return deriveMostRecentFilm(result.data);
})
}
Now, where it gets interesting is when SWAPI gets around to adding The Last Jedi and The Rise of Skywalker to its film list. We can suppose I'm polling on the list so that it gets periodically refetched. That's great, now my list UI is up to date. But my "most recent film" UI isn't aware that anything has changed — it's still stuck in 2015 showing The Force Awakens, even though the user can clearly see there are newer films.
Maybe I'm spoiled; I come from the world of MobX where stuff like this Just Works™. But this doesn't feel like an uncommon problem. Is there a best practice in the realm of Apollo/GraphQL for keeping things in sync? Am I approaching this problem in entirely the wrong way?
A few ideas I've had:
My "most recent film" query could also poll periodically. But you don't want to poll too often; after all, Star Wars films only come out every other year or so. (Thanks, Disney!) And depending on how the polling intervals overlap there will still be a big window where things are out of sync.
Instead putting the deriveMostRecentFilm logic in a resolver, just put it in the component and share the ALL_FILMS query between components. That would work, but that's basically answering "How do I get this to work in Apollo?" with "Don't use Apollo."
Some complicated system of keeping track of the dependencies between queries and chaining refreshes based on that. (I'm not keen to invent this if I can avoid it!)
In Apollo observables are (in components) over queried values (cached data 'slots') but your mostRecentFilm is not an observable, is not based on cached values (they are cached) but on one time fired query result (updated on demand).
You're only missing an 'updating connection', f.e. like this:
# ALL_FILMS
query {
allFilms {
id
title
releaseDate
isMostRecentFilm #client
}
}
Use isMostRecentFilm local resolver to update mostRecentFilm value in cache.
Any query (useQuery) related to mostRecentFilm #client will be updated automatically. All without additional queries, polling etc. - Just Works? (not tested, it should work) ;)

Apply a sort to a dataset in a PowerApps component (PCF)

I’m trying to create a new dataset type Powerapps Component (PCF). For the moment I am using it to display a view of the records that are available in an entity in Microsoft Dynamics CRM.
I wish to make the view sort itself when I click on the grid column headers (in a similar way that the default CRM grid view does). I'm trying to figure out how to apply a sort to the dataset so that I can refresh it as indicated by the documentation for the dataset.refresh() function:
Refreshes the dataset based on filters, sorting, linking, new column.
New data will be pushed to control in another 'updateView' cycle.
The dataset object does have a “sorting” property, but changing its value and then refreshing the dataset doesn’t seem to have any effect. After the refresh, the sorting property reverts to the value it had before I changed it.
In short, the click handler for the grid header does something like the following bit of code. The refresh gets done and my updateView() function gets called as expected but the sorting was not applied.
dataset.sorting = [{name: 'createdon', sortDirection: 1}];
dataset.refresh();
Any help on getting the dataset sorting to work would be appreciated.
I've been experimenting with PowerApps Component Framework a little bit recently and I can confirm that the following code won't be working:
dataSet.sorting = [ { name: "columnName", sortDirection: 0 } ];
However, I managed to get this one working for me:
dataSet.sorting.pop(); // you may want to clean up the whole collection
dataSet.sorting.push({ name: "columnName", sortDirection: 0 });
I haven't really figured out the reason of this behavior. The sorting array may be implemented as some form of observable collection in the background.
I hope this will guide you to a functioning solution.
The documentation is pretty abysmal here, but here is my best guess from putting a few different pieces of information together.
TLDR: I think there is some kind of extra method that needs to be called on the .sorting property, but I can't find out what it is called. Maybe something like:
dataset.sorting.setSorting({name: 'createdon', sortDirection: 1});
I think you're going to have to try a bunch of likely method names and see what works.
Background and links:
The only reference I could find to dataset.sorting was from here:
In this preview for canvas apps, only a limited set of filtering and sortStatus methods are supported. Filter and sort can be applied to dataset on primary type columns except for the GUID. Filter and sorting can be applied in the same way as in model-driven apps.To retrieve the dataset with filtering and sorting information, call
the methods in context.parameters.[dataset_property_name].filtering
and context.parameters.[dataset_property_name].sorting, then invoke
the context.parameters.[dataset_property_name].refresh().
So it seems that the .filtering and .sorting properties are handled similarly, and that there are some methods attached to them, and only some are supported. That is about as vague as they could make it...
I did find an example of how .filtering is used:
_context.parameters.sampleDataset.filtering.setFilter({
conditions: conditionArray,
filterOperator: 1, // Or
});
There is a brief reference to .setFilter() in the docs, as well as FilterExpression
There is a SortStatus reference, but it doesn't have any corresponding methods explicitly called out. It is possible that this is not yet a supported feature in the public preview, or the documentation is lacking and the name and syntax of the method you need to call on .sorting is not yet documented.

What is the convention around derivative information?

I am working on a service that provides information about a few related entities, somewhat like a database. Suppose that there's calls to retrieve information about a school:
service MySchool {
rpc GetClassRoom (ClassRoomRequest) returns (ClassRoom);
rpc GetStudent (StudentRequest) returns (Student);
}
Now, suppose that I want to find out a class room's information, I'd receive a proto that looks like so:
message ClassRoom {
string id = 1;
string address = 2;
string teacher = 3;
}
Sometimes I also want to know all of the students of the classroom. I am struggling to think which is the better design pattern.
Option A) Add an extra rpc like so: rpc GetClassRoomStudents (ClassRoomRequest) returns (ClassRoomStudents), where ClassRoomStudents has a single field repeated Student students. This technique requires more than one call to get all the information that we want (and many if we wanted to know information for more than one classroom).
Option B) Add an extra repeated Student students field to the ClassRoom proto, and B') Fill it up only when necessary, or B") Fill it up whenever the server receives a GetClassRoom call. This may sometimes fetch extra information, or lead to ambiguity according to what fields are filled up.
I am not sure what's the best / most conventional way of dealing with this. How have some of you dealt with this?
There is no simple answer. It's a tradeoff between simplicity (option A) and performance (option B), and it depends on the situation which solution is best.
In general, I'd recommend to go with the simple solution first, unless your measurements demonstrate that it leads to performance issues. At that point, it's easy to add repeated Student students to ClassRoom and a field bool fetch_students [default=false] to ClassRoomRequest. Then clients are free to continue using the simple API, or choose to upgrade to the more performant API if they need to.
Note that this isn't specific to gRPC; the same issue is seen in REST APIs, and basically almost any request/response model.

How to structure Shopify data into a Firestore collection that can be queried efficiently

The Background
In an attempt to build some back-end services for my e-commerce (Shopify based) site I have set up a Firestore trigger that writes order details with every new order created which is updated by a web hook POST function provided by Shopify - (orders/Create webhook).
My current cloud function -
exports.saveOrderDetails = functions.https.onRequest((req, res) => {
var docRef = db.collection('orders').doc(req.body.name);
const details = req.body;
var setData = docRef.set(req.body).then( a =>{
res.status(200).send();
});
});
Which is able to capture the data from the webhook and store it in the order number's "name" document within my "orders" collection. This is how it looks in Firestore:
My question is - with the help of body-parser (already parsing out "name" which is represented as #9999 in my screenshot, to set my document name value) - how could I improve my cloud function to handle storing this webhook POST in a better data structure for Firestore and to query it later?
After reviewing the comments on this question, I moved this question over to Firebase-Talk and it appears the feature I am attempting here would be close to what is known as "collection group queries" and was informed I should adjust my data model approach since this feature is currently still on the road map - and perhaps look into the Firestore REST API as suggested by #jason-berryman
Besides the REST APi, #frank-van-puffelen made a great suggestion to look into working with Arrays, Lists, Sets for Firebase/Firestore
Another approach that could mitigate this in my scenario is to have my HTTP Firestore cloud trigger have multiple parsing arguments that create top more top level documents - however this could cause a point of scaling failure or an increase of cost factor due to putting more parsing processing logic in my cloud function and adding additional latency...
I will mark my question as answered for the time being to hopefully help others to understand how to work with documents in a single collection in Firestore and not attempt to query groups of collections before they get too far into modelling and need to restructure their app.

DOM-based data storage, best choices/performances?

This question is about load data embedded into DOM structure.
I am using jQuery2, but the question is valid for any other framework or single Javascript code.
There are two scenarios:
When the data is load once (with the page), no "refresh data" is need.
When data is refreshed by some event.
The average performance can be changed with either one or other
Suppose a typical case of scenario-2, where a page fragment must be reloaded, with new HTML and new data. So, the $('#myDiv').load('newHtmlFragment') will be used any way... And, for jQuery programmer, using AJAX, there are two ways to load an "DOM-based data":
by HTML: expressing all data into the "newHtmlFragment" HTML. Suppose many paragraphs, each like <p id="someId" data-X="someContent">...more content</p>. There are some "verbose overhead" for each data-X1="contentX1" data-X2="contentX2" ..., and is not elegant for webservice script if it is not an XHTML-oriented one (I am using PHP, my data is an array, and I preffer to use json_encode).
by jQuery evaluation: using the same $('#myDiv').load('newHtmlFragment') only for <p id="someId">...more content</p>, with no data-X. A second AJAX load an jQuery script like $('#someId').data(...) and evaluate it. So this is an overhead, for node-selection and data-inclusion, but with big item-data, each data can be enconded by JSON.
by pure JSON: similar to "by jQuery", but the second AJAX load an JSON object like var ALLDATA={'someId1':{...}, 'someId2':{...}, ...}. So this is an overhead for a static function that executes something like $('#myDiv p').each(function(){... foreach ... $(this).data('x',ALLDATA[id]['x']);}) retrive selection, but with big data, all data can be enconded by JSON.
The question: what the best choice? It depends on scenarios or another context parameter? There are signfificative performance tradeoffs?
PS: a complete answer needs to address the issue of performance... If no significative performance differences, the best choice relies on "best programming style" and software engineering considerations.
More context, if you need as reference to answer. My practical problem is at scenario-1, and I am using the second choice, "by jQuery script", executing:
$('#someId1').data({'bbox':[201733.2,7559711.5,202469.4,7560794.9],'2011-07':[3,6],'2011-08':[2,3],'2011-10':[4,4],'2012-01':[1,2],'2012-02':[12,12],'2012-03':[3,6],'2012-04':[6,12],'2012-05':[3,4],'2012-06':[2,4],'2012-07':[3,5],'2012-08':[10,11],'2012-09':[7,10],'2012-10':[1,2],'2012-12':[2,2],'2013-01':[6,10],'2013-02':[19,26],'2013-03':[2,4],'2013-04':[5,8],'2013-05':[4,5],'2013-06':[4,4]});
$('#someId2').data({'bbox':[197131.7,7564525.9,198932.0,7565798.1],'2011-07':[39,51],'2011-08':[2,3],'2011-09':[4,5],'2011-10':[13,14],'2011-11':[40,42],'2011-12':[21,25],'2012-01':[10,11],'2012-02':[26,31],'2012-03':[27,35],'2012-04':[8,10],'2012-05':[24,36],'2012-06':[4,7],'2012-07':[25,30],'2012-08':[9,11],'2012-09':[42,52],'2012-10':[4,7],'2012-11':[17,22],'2012-12':[7,8],'2013-01':[21,25],'2013-02':[5,8],'2013-03':[8,11],'2013-04':[28,40],'2013-05':[55,63],'2013-06':[1,1]});
$('#...').data(...); ... more 50 similar lines...
This question can be discussed from different aspects. Two that I can think of right now would be software engineering and end-user experience. A comprehensive solution covering first can also cover the later but as usually it's not possible to come up with such a solution (due to its cost) these two hardly overlap.
Software engineering point of view
In this POV it is strongly suggested that different parts of the system to be as isolated as possible. This means you better postpone the marriage of data and view as late as you can. It helps you to divide your developers into two separate groups; those who know server-side programming and have no idea how HTML (or any other interface layer technology) works and those who are solely experienced on HTML and Javascript. Just this division alone is a blessing for management and it helps greatly in big projects where teamwork is essential. It also helps the maintenance and expansion of the system, all the things software engineering aims at.
User experience point of view
As good as the previous solution sounds, it comes with (solvable) drawbacks. As you mentioned in your question, if we are to load view and data separately, it elevates the number of requests we have to send to server to retrieve them. It imposes two problems, first the overhead that comes with each request and second the delay user has to wait for each request to be responded. The second is more obvious so let's start with that. With all the advances to the Internet and bandwidths, yet our users' exceeding expectations enforce us to consider this delay. One way to reduce the number of requests would be your first choice: data within HTML fragments. Multiple number of requests also has an overhead problem as well. This can be explained by HTTP protocol's handshake (both on client-side and server-side) and by the fact that each request will lead to loading the session on server which in a large scale could be pretty considerable. So again your first option could be the answer to this problem.
Tie breaker
Having both sides of the story said, what then? The ultimate solution is a combination of both where data and view are married on client but they are downloaded at the same time. To be honest I don't know of such a library. But the principle is simple, you need a mechanism to package data and empty HTML fragments within the same response and combine them into what user will see on client. This solution is costy (to implement) but it is sort of the cost that once paid you can benefit from it for a life time.
It depends on how you are going to use the data that is stored. Consider this example:
Example
You have 300 items in a database (say server access logs of the last 300 days). Now you want to display 300 <div> tags, each tag representing one database-item.
Now there are 2 options to do this:
<div data-stat1="stat1" data-stat2="stat2" data-stat3="stat3">(...)</div>
<!-- again, this is repeated 300 times -->
<script>
// Example on how to show "stat1" value in all <div>s
function showStat1() {
for(var i=1; i<=300; i+= 1) {
var theID = '#id-' + i;
jQuery(theID).text(jQuery(theID).data('stat1'));
}
}
</script>
OR
<div id="id-1">(...)</div>
<!-- repeat this 300 times, for all DB items -->
<script>
data = { // JSON data which is displayed in the <div> tags
'1': ['stat1', 'stat2', 'stat3'],
// same for all 300 items
}
// Example on how to show "stat1" value in all <div>s
function showStat1() {
for(var i=1; i<=300; i+= 1) {
var theID = '#id-' + i;
jQuery(theID).text(data[i][0]);
}
}
</script>
Which scenario is better?
Case 1:
The data is directly coded into the DOM elements, which makes this one an easy to implement solution. You can see in my examples that the first code block takes a lot less code to generate and the code is less complex.
This solution is very powerful, when you want to store data that is directly related to an DOM element (as you do not have to create a logical connection between JSON and DOM): It is very simple to access data for the correct element.
However, your main concern is performance - this is NOT the way to go. Because every time you access data, you have to first select the correct DOM element and attribute via javascript, which takes considerable amount of time. So the simplicity costs you a lot of performance overhead when you want to read/write data in the element.
Case 2:
This scenario very cleanly separates the DISPLAY from the DATA storage. It has major advantages compared to the first case.
A) Data should not be mingled with the display elements - imagine you want to switch from <div> to <table> and suddenly you have to rewrite all javascript to correctly select the correct table cells
B) Data is directly accessible without traversing the DOM tree. Imagine you want to calculate an average sum of all values. In first case you need to loop all DOM elements and read value from them. In the second you simply loop a normal array
C) The data can be loaded or refreshed via ajax. You only transfer the JSON object but not all the HTML stuff that is required for displaying the data
D) Performance is way better, mostly because of the above mentioned points. Javascript is a lot better in handling simple arrays or (not too complex) JSON objects than it is in filtering data out of the DOM tree.
In general this solution is more than twice as fast as the first case. You will also discover - even though it is not obvious - that the second case is also easier to code and maintain! The code simply is easier to read and understand, as you clearly separate the data from the UI elements...
Performance comparison
You can compare the two solutions on this JSPerf scenario:
http://jsperf.com/performance-on-data-storage
Taking it further
For implementation of the second case I generally use this approach:
I generate the HTML code which will serve as the UI. It often happens that I have to generate HTML via javascript, but now I assume that the DOM tree will not change after the page is loaded
At the end of the HTML I include a tag with a JSON object for initial page display
Via jQuery onReady event I then parse the JSON object and update the UI elements as required (e.g. populating the table with data)
When data is loaded dynamically I simply transfer a new JSON object with the new data and use exact the same javascript function as in step 3 to display the new results.
Example of the HTML file:
<div>ID: <span class="the-id">-</span></div>
<div>Date: <span class="the-date">-</span></div>
<div>Total page hits: <span class="the-value">-</span></div>
<button type="button" class="refresh">Load new data</button>
<script src="my-function.js"></script>
<script>
function initial_data() {
return {"id":"1", "date":"2013-07-30", "hits":"1583"};
}
</script>
The "my-function.js" file:
jQuery(function initialize_ui() {
// Initialize the global variables we will use in the app
window.my_data = initial_data();
window.app = {};
app.the_id = jQuery('.the-id');
app.the_date = jQuery('.the-date');
app.the_value = jQuery('.the-value');
app.btn_refresh = jQuery('.refresh');
// Add event handler: When user clicks refresh button then load new data
app.btn_refresh.click(refresh_data);
// Display the initial data
render_data();
});
function render_data() {
app.the_id.text(my_data.id);
app.the_date.text(my_data.date);
app.the_value.text(my_data.hits);
}
function refresh_data() {
// For example fetch and display the values for date 2013-07-29
jQuery.post(url, {"date":"2013-07-29"}, function(text) {
my_data = jQuery.parseJSON(text);
render_data();
});
}
I did not test this code. Also there is crucial error handling and other optimization missing. But it helps to illustrate the concepts that I try to describe

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