hood.ie couchdb findAll is it efficient and alternative way - database

I'm using hood.ie for a web app I'm making. I like the simplicity of it however there's something I'm not too sure about.
When retrieving data from the couchDB there is a method: findAll - which as an example looks like:
hoodie.store.findAll('todo')
.done(function(allTodos) {
//do something with allTodos
})
What I was wondering/don't really like is the fact that I'm getting all the items of type todo then filtering down once I have e.g. todo with todays date.
Instead of getting all of them, is it possible to just get ones I actually want.
I know there is a find method but that requires an id which i won't have.
Or do i simply not need to worry about this - is the call to get all data not that expensive (if i had 1000+ records I feel it may be).
Any guidance would be appreciated.
Thanks.

You don't need to worry about it.
Hoodie stores all data in your browser, from where it also retrieves the data, it does not send any requests to CouchDB in the background when you call hoodie.store.findAll('todo')
In future, this particular call will become more efficient as Hoodie will use indexing by object types, but unless you have thousands of objects per user, you shouldn't even see the the difference

Related

What's the preferred way to go about using backbone with non-crud resources?

New to backbone/marionette, but I believe that I understand how to use backbone when dealing with CRUD/REST; however, consider something like results from a search query. How should one model this? Of course the results likely relate to some model(s), but they are not meant to be tied to said model(s).
Part of me thinks that I should use a collection using a model that doesn't actually sync with a data store through the server, but instead just exists as a means of a modeling a search result object.
Another solution could be to have a collection with no models and just override parse.
I assume that the former is preferred, but again I have no experience with the framework. If there's an alternative/better solution than those listed above, please advise.
I prefer having one object which is responsible for both request and response parsing. It can parse the response to appropriate models and nothing more. I mean - if some of those parsed models are required somewhere in your page, there is something that keeps reference to this wrapper object and takes models from response it requires via wrapper methods.
Another option is to have Radio (https://github.com/marionettejs/backbone.radio) in this wrapper - you will not have to keep wrapper object in different places but call for data via Radio.

Seamless Integration with REST API

Many examples on the net show you how to use ng-repeat with in-memory data, but in my case I have long table with infinite scroll that gets data by sending requests to a REST API (scroll down - fetch some data, scroll down again - fetch some more data, etc.). It does work, but I'm wondering how can I integrate that with filters?
Right now I have to call a specific method of API service that makes a request based on text in "search" input box and then controller updates $scope.data.
Is it possible to build a custom filter that would do that? And then my view would be utterly decoupled from the service and I could declaratively tell it how to group and order and filter data, regardless if it's in-memory or comes from a remote server, server that can serve only limited records at a time.
Also later I'm gonna need grouping and ordering as well, I'm so tempted to download the entire dataset and lock parts of the app responsible for grouping, searching and ordering (until all data is on the client), but:
a) that dataset is huge (hundred thousands of records)
b) nobody wants to deal with cache invalidation headaches
c) doing so feels so damn wrong, you don't really expect me to 'keep' all that data in-memory, right?
Can you guys point me to maybe some open-source examples where I can steal some ideas from?
Basically I need to build a service and filters that let me to work with my "pageable" data that comes from api, like it's in memory-data.
Regardless of how you choose to solve it (there are many ways to infinite-scroll with angular, here is one: http://binarymuse.github.io/ngInfiniteScroll/), at its latest current beta version, ng-repeat works really bad with large amount of data - so do filters. The reason is obvious - pulling so much information for changes is a tuff job. Moreover, ng-repeat by default will re-draw your complete list every time something changes.
There are many solutions you can explore in this area, here are the ones I found productive:
http://kamilkp.github.io/angular-vs-repeat/#?tab=8
http://www.williambrownstreet.net/blog/2013/07/angularjs-my-solution-to-the-ng-repeat-performance-problem/
https://github.com/allaud/quick-ng-repeat
You should also consider the following, which really helps with large amounts of data.
https://github.com/Pasvaz/bindonce
Updated
I guess you can't really control your server output, because filtering and ordering large amount of data are better off done on the server side.
I was pointing out the links above since even if you write your own filters (and order-bys), which is quite simple to do - http://jsfiddle.net/gdefpfqL/ - (filter by some company name and then click the "Add More" button - to add more items). ordering by is virtually impossible if you can't control the data coming for the server - the only option is getting it all, ordering and then lazy load from the client's memory. So if each of your list items doesn't have many binding by it self (as in the example I've added) - the list item is a fairly simple one (for instance: you simply present the results as a plain text in a <li>{{item.name}}</li> then angular ng-repeat might work for you. In this case, filters will work as expected - say you filter by searched text:
<li ng-repeat="item in items | filter:searchedText"></li>
even for new items added after the user has searched a text, it will still works because the magic of binding.

GAE MapReduce Huge Query

Abstract: Is MapReduce a good idea when processing a collection of data from the database, instead of finding some answer to a somewhat complex (or just big) question?
I would like to sync a set of syndication sources (e.g. urls like http://xkcd.com/rss.xml ), which are stored in GAE's datastore as a collection/table. I see two options, one is straight forward. Make simple tasks which you put in a queue, where each task handle's 100 or 1000 or whatever natural number seems to fit in each task. The other option is MapReduce.
In the latter case, the Map does everything, and the Reduce does nothing. Moreover, the map has no result, it just alters the 'state' (of the datastore).
#Override public void map(Entity entity) {
String url = (String)entity.getProperty("url");
for(Post p : www.fetchPostsFromFeed(url)) {
p.save();
}
}
As you can see, one source can map to many posts, so my map might as well be called "Explode".
So no emits and nothing for reduce to do. The reason I like this map-approach, is that I tell google: Here, take my collection/table, split it however you see fit to different mappers, and then store the posts wherever you like. The datastore uses 'high replication'. So availability of the data is high and a best choice for what 'computational unit' does what entity doesn't really reduce network communication. The same goes for the save of the posts, as they need to go to all datastore units. What I do like is that mapreduce has some way of fault-recovery for map-computations that get stuck, and that it knows how many tasks to send to which node, instead of queueing some number of entities somewhere hoping it makes sense.
Maybe my way of thinking here is wrong, in which case, please correct me. Anyhow, is this approach 'wrong' for the lack of reduce and map being an 'explode'?
Nope, Map pretty does the same as as your manual enqueuing of tasks.

Self Tracking Entities Traffic Optimization

I'm working on a personal project using WPF with Entity Framework and Self Tracking Entities. I have a WCF web service which exposes some methods for the CRUD operations. Today I decided to do some tests and to see what actually travels over this service and even though I expected something like this, I got really disappointed. The problem is that for a simple update (or delete) operation for just one object - lets say Category I send to the server the whole object graph, including all of its parent categories, their items, child categories and their items, etc. I my case it was a 170 KB xml file on a really small database (2 main categories and about 20 total and about 60 items). I can't imagine what will happen if I have a really big database.
I tried to google for some articles concerning traffic optimization with STE, but with no success, so I decided to ask here if somebody has done something similar, knows some good practices, etc.
One of the possible ways I came out with is to get the data I need per object with more service calls:
return context.Categories.ToList();//only the categories
...
return context.Items.ToList();//only the items
Instead of:
return context.Categories.Include("Items").ToList();
This way the categories and the items will be separated and when making changes or deleting some objects the data sent over the wire will be less.
Has any of you faced a similar problem and how did you solve it or did you solve it?
We've encountered similiar challenges. First of all, as you already mentioned, is to keep the entities as small as possible (as dictated by the desired client functionality). And second, when sending entities back over the wire to be persisted: strip all navigation properties (nested objects) when they haven't changed. This sounds very simple but is not at all trivial. What we do is to recursively dig into the entities present in trackable collections of say the "topmost" entity (and their trackable collections, and theirs, and...) and remove them when their ChangeTracking state is "Unchanged". But be carefull with this, because in some cases you still need these entities because they have been removed or added to trackable collections of their parent entity (so then you shouldn't remove them).
This, what we call "StripEntity", is also mentioned (not with any code sample or whatsoever) in Julie Lerman's - Programming Entity Framework.
And although it might not be as efficient as a more purist kind of approach, the use of STE's saves a lot of code for queries against the database. We are not in need for optimal performance in a high traffic situation, so STE's suit our needs and takes away a lot of code to communicate with the database. You have to decide for your situation what the "best" solution is. Good luck!
You can find an Entity Framework project item at http://selftrackingentity.codeplex.com/. With version 0.9.8, I added a method called GetObjectGraphChanges() that returns an optimized entity object graph with only objects that have changes.
Also, there are two helper methods: EstimateObjectGraphSize() and EstimateObjectGraphChangeSize(). The first method returns the estimate size of the whole entity object along with its object graph; and the later returns the estimate size of the optimized entity object graph with only object that have changes. With these two helper methods, you can decide whether it makes sense to call GetObjectGraphChanges() or not.

How to model Data Transfer Objects for different front ends?

I've run into reoccuring problem for which I haven't found any good examples or patterns.
I have one core service that performs all heavy datasbase operations and that sends results to different front ends (html, silverlight/flash, web services etc).
One of the service operation is "GetDocuments", which provides a list of documents based on different filter criterias. If I only had one front-end, I would like to package the result in a list of Document DTOs (Data transfer objects) that just contains the data. However, different front-ends needs different amounts of "metadata". The simples client just needs the document headline and a link reference. Other clients wants a short text snippet of the document, another one also wants a thumbnail and a third wants the name of the author. Its basically all up to the implementation of the GUI what needs to be displayed.
Whats the best way to model this:
As a lot of different DTOs (Document, DocumentWithThumbnail, DocumentWithTextSnippet)
tends to become a lot of classes
As one DTO containing all the data, where the client choose what to display
Lots of unnecessary data sent
As one DTO where certain fields are populated based on what the client requested
Tends to become a very large class that needs to be extended over time
One DTO but with some kind of generic "Metadata" field containing requested metadata.
Or are there other options?
Since I want a high performance service, I need to think about both network load and caching strategies.
Does anyone have any good patterns or practices that might help me?
What I would do is give the front end the ability to request the presence of the wanted metadata ( say getDocument( WITH_THUMBNAILS | WITH_TEXT_SNIPPET ) )
Then this DTO is built with only this requested information.
Adding all the possible metadata is as you said, unacceptable.
I will surely stay with one class defining all the possible methods (getTitle(), getThumbnail()) and if possible it will return a placeholder when the thumbnail was not requested. Something like "Image not available".
If you want to model this like a pattern, take a look at the factory patterns.
Hope this helps you.
Is there any noticable cost to creating a DTO that has all the data any of your views could need and using it everywhere? I would do that, especially since it insulates you from a requirement change down the line to have one of the views incorporate data one of the other views uses
ex. Maybe your silverlight/flash view doesn't show the title itself b/c it's in the thumb now, but they decide they want to sort by it later.
To clarify, I do not necesarily think you need to pass down all of the data every time, but I think your DTO class should define all of them. Just don't fall into the pits of premature optimization or analysis paralysis. Do the simplest thing first, then justify added complexity. Throw it all in and profile it. If the perf is unacceptable, optimize and try again.

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