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I have seen videos and read the documentation of Cloud firestore, from Google Firebase service, but I can't figure this out coming from realtime database.
I have this web app in mind in which I want to store my providers from different category of products. I want perform a search query through all my products to find what providers I have for such product, and eventually access that provider info.
I am planning to use this structure for this purpose:
Providers ( Collection )
Provider 1 ( Document )
Name
City
Categories
Provider 2
Name
City
Products ( Collection )
Product 1 ( Document )
Name
Description
Category
Provider ID
Product 2
Name
Description
Category
Provider ID
So my question is, is this approach the right way to access the provider info once I get the product I want?
I know this is possible in the realtime database, using the provider ID I could search for that provider in the providers section, but with Firestore I am not sure if its possible or if this is right approach.
What is the correct way to structure this kind of data in Firestore?
You need to know that there is no "perfect", "the best" or "the correct" solution for structuring a Cloud Firestore database. The best and correct solution is the solution that fits your needs and makes your job easier. Bear also in mind that there is also no single "correct data structure" in the world of NoSQL databases. All data is modeled to allow the use-cases that your app requires. This means that what works for one app, may be insufficient for another app. So there is not a correct solution for everyone. An effective structure for a NoSQL type database is entirely dependent on how you intend to query it.
The way you are structuring your data looks good to me. In general, there are two ways in which you can achieve the same thing. The first one would be to keep a reference of the provider in the product object (as you already do) or to copy the entire provider object within the product document. This last technique is called denormalization and is a quite common practice when it comes to Firebase. So we often duplicate data in NoSQL databases, to suit queries that may not be possible otherwise. For a better understanding, I recommend you see this video, Denormalization is normal with the Firebase Database. It's for Firebase Realtime Database but the same principles apply to Cloud Firestore.
Also, when you are duplicating data, there is one thing that needs to keep in mind. In the same way, you are adding data, you need to maintain it. In other words, if you want to update/delete a provider object, you need to do it in every place that it exists.
You might wonder now, which technique is best. In a very general sense, the best way in which you can store references or duplicate data in a NoSQL database is completely dependent on your project's requirements.
So you should ask yourself some questions about the data you want to duplicate or simply keep it as references:
Is the static or will it change over time?
If it does, do you need to update every duplicated instance of the data so they all stay in sync? This is what I have also mentioned earlier.
When it comes to Firestore, are you optimizing for performance or cost?
If your duplicated data needs to change and stay in sync in the same time, then you might have a hard time in the future keeping all those duplicates up to date. This will also might imply you spend a lot of money keeping all those documents fresh, as it will require a read and write for each document for each change. In this case, holding only references will be the winning variant.
In this kind of approach, you write very little duplicated data (pretty much just the Provider ID). So that means that your code for writing this data is going to be quite simple and quite fast. But when reading the data, you will need to load the data from both collections, which means an extra database call. This typically isn't a big performance issue for reasonable numbers of documents, but definitely does require more code and more API calls.
If you need your queries to be very fast, you may want to prefer to duplicate more data so that the client only has to read one document per item queried, rather than multiple documents. But you may also be able to depend on local client caches makes this cheaper, depending on the data the client has to read.
In this approach, you duplicate all data for a provider for each product document. This means that the code to write this data is more complex, and you're definitely storing more data, one more provider object for each product document. And you'll need to figure out if and how to keep up to date on each document. But on the other hand, reading a product document now gives you all information about the provider document in one read.
This is a common consideration in NoSQL databases: you'll often have to consider write performance and disk storage vs. reading performance and scalability.
For your choice of whether or not to duplicate some data, it is highly dependent on your data and its characteristics. You will have to think that through on a case-by-case basis.
So in the end, remember that both are valid approaches, and neither of them is pertinently better than the other. It all depends on what your use-cases are and how comfortable you are with this new technique of duplicating data. Data duplication is the key to faster reads, not just in Cloud Firestore or Firebase Realtime Database but in general. Any time you add the same data to a different location, you're duplicating data in favor of faster read performance. Unfortunately in return, you have a more complex update and higher storage/memory usage. But you need to note that extra calls in Firebase real-time database, are not expensive, in Firestore are. How much duplication data versus extra database calls is optimal for you, depends on your needs and your willingness to let go of the "Single Point of Definition mindset", which can be called very subjective.
After finishing a few Firebase projects, I find that my reading code gets drastically simpler if I duplicate data. But of course, the writing code gets more complex at the same time. It's a trade-off between these two and your needs that determines the optimal solution for your app. Furthermore, to be even more precise you can also measure what is happening in your app using the existing tools and decide accordingly. I know that is not a concrete recommendation but that's software development. Everything is about measuring things.
Remember also, that some database structures are easier to be protected with some security rules. So try to find a schema that can be easily secured using Cloud Firestore Security Rules.
Please also take a look at my answer from this post where I have explained more about collections, maps and arrays in Firestore.
I have a website that allows users to query for specific recipes using various search criteria. For example, you can say "Show me all recipes that I can make in under 30 minutes that will use chicken, garlic and pasta but not olive oil."
This query is sent to the web server over JSON, and deserialized into a SearchQuery object (which has various properties, arrays, etc).
The actual database query itself is fairly expensive, and there's a lot of default search templates that would be used quite frequently. For this reason, I'd like to start caching common queries. I've done a little investigation into various caching technologies and read plenty of other SO posts on the subject, but I'm still looking for advice on which way to go. Right now, I'm considering the following options:
Built in System.Web.Caching: This would provide a lot of control over how many items are in the cache, when they expire, and their priority. However, cached objects are keyed by a string, rather than a hashable object. Not only would I need to be able to convert a SearchQuery object into a string, but the hash would have to be perfect and not produce any collisions.
Develop my own InMemory cache: What I'd really like is a Dictionary<SearchQuery, Results> object that persists in memory across all sessions. Since search results can start to get fairly large, I'd want to be able to cap how many queries would be cached and provide a way for older queries to expire. Something like a FIFO queue would work well here. I'm worried about things like thread safety, and am wondering if writing my own cache is worth the effort here.
I've also looked into some other third party cache providers such as NCache and Velocity. These are both distributed cache providers and are probably completely overkill for what I need at the moment. Plus, it seems every cache system I've seen still requires objects to be keyed by a string. Ideally, I want something that holds a cache in process, allows me to key by an object's hash value, and allows me to control expiration times and priorities.
I'd appreciate any advice or references to free and preferably open source solutions that could help me out here. Thanks!
Based on what you are saying, I recommend you use System.Web.Caching and build that into your DataAccess layer shielding it from the rest of you system. When called you can make your real time query or pull from a cached object based on your business/application needs. I do this today, but with Memcached.
An in-memory cache should be pretty easy to implement. I can't think of any reason why you should have particular concerns about validating the uniqueness of a SearchQuery object versus any other - that is, while the key must be a string, you can just store the original object along with the results in the cache, and validate equality directly after you've got a hit on the hash. I would use System.Web.Caching for the benefits you've noted (expiration, etc.). If there happened to be a collision, then the 2nd one would just not get cached. But this would be extremely rare.
Also, the amount of memory needed to store search results should be trivial. You don't need to keep the data of every single field, of every single row, in complete detail. You just need to keep a fast way to access each result, e.g. an int primary key.
Finally, if there are possibly thousands of results for a search that could be cached, you don't even need to keep an ID for each one - just keep the first 100 or something (as well as the total number of hits). I suspect if you analyzed how people use search results, it's a rare person that goes beyond a few pages. If someone did, then you can just run the query again.
So basically you're just storing a primary key for the first X records of each common search, and then if you get a hit on your cache, all you have to do is run a very inexpensive lookup of a handful of indexed keys.
Give a quick look to the Enterprise library Caching Application Block. Assuming you want a web application wide cache, this might be the solution your looking for.
I'm assuming that generating a database query from a SearchQuery object is not expensive, and you want to cache the result (i.e. rowset) obtained from executing the query.
You could generate the query text from your SearchQuery object and use that text as the key for a lookup using System.Web.Caching.
From a quick reading the documentation for the Cache class it appears that the keys have to be unique - which they would be if you used they query text - not the hash of the key.
EDIT
If you are concerned about long cache keys then check the following links:
Cache key length in asp.net
Maximum length of cache keys in HttpRuntime.Cache object?
It seems that the Cache class stores the cached items in an internal dictionary, which uses the key's hash. Keys (query text) with the same hash would end-up in the same bucket in the dictionary, where its just a quick linear search to find the required one when do a cache lookup. So I think you'd be okay with long key strings.
The asp.net caching is pretty well thought out, and I don't think this is a case where you need something else.
I need to store a few attributes of an authenticated user (I am using Membership API) and I need to make a choice between using Profiles or adding a new table with UserId as the PK. It appears that using Profiles is quick and needs less work upfront. However, I see the following downsides:
The profile values are squished into a single ntext column. At some point in the future, I will have SQL scripts that may update user's attributes. Querying a ntext column and trying to update a value sounds a little buggy to me.
If I choose to add a new user specific property and would like to assign a default for all the existing users, would it be possible?
My first impression has been that using profiles may cause maintainance headaches in the long run. Thoughts?
There was an article on MSDN (now on ASP.NET http://www.asp.net/downloads/sandbox/table-profile-provider-samples) that discusses how to make a Profile Table Provider. The idea is to store the Profile data in a table versus a row, making it easier to query with just SQL.
More onto that point, SQL Server 2005/2008 provides support for getting data via services and CLR code. You could conceivably access the Profile data via the API instead of the underlying tables directly.
As to point #2, you can set defaults to properties, and while this will not update other profiles immediately, the profile would be updated when next it is accessed.
Seems to me you have answered your own question. If your point 1 is likely to happen, then a SQL table is the only sensible option.
Check out this question...
ASP.NET built in user profile vs. old stile user class/tables
The first hint that the built-in profiles are badly designed is their use of delimited data in a relational database. There are a few cases that delimited data in a RDBMS makes sense, but this is definitely not one of them.
Unless you have a specific reason to use ASP.Net Profiles, I'd suggest you go with the separate tables instead.
Can anybody detail some approach on how to save private data in social websites like facebook, etc. They cant save all the updates and friends list in clear text format because of privacy issues. So how do they actually save it?
Hashing all the data with user password so that only a valid session view it is one possibility. But I think there are some problem with this approach and there must be some better solution.
They can and probably do save it in plain text - it goes into a database on a server somewhere. There aren't really privacy issues there... and even if there were, Facebook has publicly admitted they don't care about privacy.
Most applications do not encrypt data like this in the database. The password will usally be stored in a salted hash, and the application artchitecture is responsible for limiting visibility based on appropriate rights/roles.
Most websites do in fact save updates and friends list in clear text format---that is, they save them in an SQL database. If you are a facebook developer you can access the database using FQL, the Facebook Query Language. Queries are restricted so that you can only look at the data of "friends" or of people running your application, or their friends, or what have you. (The key difference between SQL and FQL is that you must always include a WHERE X=id where the X is a keyed column.)
There are other approaches, however. You can store information in a Bloom filter or in some kind of hash. You might want to read Peter Wayner's book Translucent Databases---he goes into clever approaches for storing data so that you can detect if it is present or missing, but you can't do brute force searches.
For the sake of argument assume that I have a webform that allows a user to edit order details. User can perform the following functions:
Change shipping/payment details (all simple text/dropdowns)
Add/Remove/Edit products in the order - this is done with a grid
Add/Remove attachments
Products and attachments are stored in separate DB tables with foreign key to the order.
Entity Framework (4.0) is used as ORM.
I want to allow the users to make whatever changes they want to the order and only when they hit 'Save' do I want to commit the changes to the database. This is not a problem with textboxes/checkboxes etc. as I can just rely on ViewState to get the required information. However the grid is presenting a much larger problem for me as I can't figure out a nice and easy way to persist the changes the user made without committing the changes to the database. Storing the Order object tree in Session/ViewState is not really an option I'd like to go with as the objects could get very large.
So the question is - how can I go about preserving the changes the user made until ready to 'Save'.
Quick note - I have searched SO to try to find a solution, however all I found were suggestions to use Session and/or ViewState - both of which I would rather not use due to potential size of my object trees
If you have control over the schema of the database and the other applications that utilize order data, you could add a flag or status column to the orders table that differentiates between temporary and finalized orders. Then, you can simply store your intermediate changes to the database. There are other benefits as well; for example, a user that had a browser crash could return to the application and be able to resume the order process.
I think sticking to the database for storing data is the only reliable way to persist data, even temporary data. Using session state, control state, cookies, temporary files, etc., can introduce a lot of things that can go wrong, especially if your application resides in a web farm.
If using the Session is not your preferred solution, which is probably wise, the best possible solution would be to create your own temporary database tables (or as others have mentioned, add a temporary flag to your existing database tables) and persist the data there, storing a single identifier in the Session (or in a cookie) for later retrieval.
First, you may want to segregate your specific state management implementation into it's own class so that you don't have to replicate it throughout your systems.
Second, you may want to consider a hybrid approach - use session state (or cache) for a short time to avoid unnecessary trips to a DB or other external store. After some amount of inactivity, write the cached state out to disk or DB. The simplest way to do this, is to serialize your objects to text (using either serialization or a library like proto-buffers). This helps allow you to avoid creating redundant or duplicate data structure to capture the in-progress data relationally. If you don't need to query the content of this data - it's a reasonable approach.
As an aside, in the database world, the problem you describe is called a long running transaction. You essentially want to avoid making changes to the data until you reach a user-defined commit point. There are techniques you can use in the database layer, like hypothetical views and instead-of triggers to encapsulate the behavior that you aren't actually committing the change. The data is in the DB (in the real tables), but is only visible to the user operating on it. This is probably a more complicated implementation than you may be willing to undertake, and requires intrusive changes to your persistence layer and data model - but allows the application to be ignorant of the issue.
Have you considered storing the information in a JavaScript object and then sending that information to your server once the user hits save?
Use domain events to capture the users actions and then replay those actions over the snapshot of the order model ( effectively the current state of the order before the user started changing it).
Store each change as a series of events e.g. UserChangedShippingAddress, UserAlteredLineItem, UserDeletedLineItem, UserAddedLineItem.
These events can be saved after each postback and only need a link to the related order. Rebuilding the current state of the order is then as simple as replaying the events over the currently stored order objects.
When the user clicks save, you can replay the events and persist the updated order model to the database.
You are using the database - no session or viewstate is required therefore you can significantly reduce page-weight and server memory load at the expense of some page performance ( if you choose to rebuild the model on each postback ).
Maintenance is incredibly simple as due to the ease with which you can implement domain object, automated testing is easily used to ensure the system behaves as you expect it to (while also documenting your intentions for other developers).
Because you are leveraging the database, the solution scales well across multiple web servers.
Using this approach does not require any alterations to your existing domain model, therefore the impact on existing code is minimal. Biggest downside is getting your head around the concept of domain events and how they are used and abused =)
This is effectively the same approach as described by Freddy Rios, with a little more detail about how and some nice keyword for you to search with =)
http://jasondentler.com/blog/2009/11/simple-domain-events/ and http://www.udidahan.com/2009/06/14/domain-events-salvation/ are some good background reading about domain events. You may also want to read up on event sourcing as this is essentially what you would be doing ( snapshot object, record events, replay events, snapshot object again).
how about serializing your Domain object (contents of your grid/shopping cart) to JSON and storing it in a hidden variable ? Scottgu has a nice article on how to serialize objects to JSON. Scalable across a server farm and guess it would not add much payload to your page. May be you can write your own JSON serializer to do a "compact serialization" (you would not need product name,product ID, SKU id, etc, may be you can just "serialize" productID and quantity)
Have you considered using a User Profile? .Net comes with SqlProfileProvider right out of the box. This would allow you to, for each user, grab their profile and save the temporary data as a variable off in the profile. Unfortunately, I think this does require your "Order" to be serializable, but I believe all of the options except Session thus far would require the same.
The advantage of this is it would persist through crashes, sessions, server down time, etc and it's fairly easy to set up. Here's a site that runs through an example. Once you set it up, you may also find it useful for storing other user information such as preferences, favorites, watched items, etc.
You should be able to create a temp file and serialize the object to that, then save only the temp file name to the viewstate. Once they successfully save the record back to the database then you could remove the temp file.
Single server: serialize to the filesystem. This also allows you to let the user resume later.
Multiple server: serialize it but store the serialized value in the db.
This is something that's for that specific user, so when you persist it to the db you don't really need all the relational stuff for it.
Alternatively, if the set of data is v. large and the amount of changes is usually small, you can store the history of changes done by the user instead. With this you can also show the change history + support undo.
2 approaches - create a complex AJAX application that stores everything on the client and only submits the entire package of changes to the server. I did this once a few years ago with moderate success. The applicaiton is not something I would want to maintain though. You have a hard time syncing your client code with your server code and passing fields that are added/deleted/changed is nightmarish.
2nd approach is to store changes in the data base in a temp table or "pending" mode. Advantage is your code is more maintainable. Disadvantage is you have to have a way to clean up abandonded changes due to session timeout, power failures, other crashes. I would take this approach for any new development. You can have separate tables for "pending" and "committed" changes that opens up a whole new level of features you can add. What if? What changed? etc.
I would go for viewstate, regardless of what you've said before. If you only store the stuff you need, like { id: XX, numberOfProducts: 3 }, and ditch every item that is not selected by the user at this point; the viewstate size will hardly be an issue as long as you aren't storing the whole object tree.
When storing attachments, put them in a temporary storing location, and reference the filename in your viewstate. You can have a scheduled task that cleans the temp folder for every file that was last saved over 1 day ago or something.
This is basically the approach we use for storing information when users are adding floorplan information and attachments in our backend.
Are the end-users internal or external clients? If your clients are internal users, it may be worthwhile to look at an alternate set of technologies. Instead of webforms, consider using a platform like Silverlight and implementing a rich GUI there.
You could then store complex business objects within the applet, provide persistant "in progress" edit tracking across multiple sessions via offline storage and easily integrate with back-end services that providing saving / processing of the finalised order. All whilst maintaining access via the web (albeit closing out most *nix clients).
Alternatives include Adobe Flex or AJAX, depending on resources and needs.
How large do you consider large? If you are talking sessions-state (so it doesn't go back/fore to the actual user, like view-state) then state is often a pretty good option. Everything except the in-process state provider uses serialization, but you can influence how it is serialized. For example, I would tend to create a local model that represents just the state I care about (plus any id/rowversion information) for that operation (rather than the full domain entities, which may have extra overhead).
To reduce the serialization overhead further, I would consider using something like protobuf-net; this can be used as the implementation for ISerializable, allowing very light-weight serialized objects (generally much smaller than BinaryFormatter, XmlSerializer, etc), that are cheap to reconstruct at page requests.
When the page is finally saved, I would update my domain entities from the local model and submit the changes.
For info, to use a protobuf-net attributed object with the state serializers (typically BinaryFormatter), you can use:
// a simple, sessions-state friendly light-weight UI model object
[ProtoContract]
public class MyType {
[ProtoMember(1)]
public int Id {get;set;}
[ProtoMember(2)]
public string Name {get;set;}
[ProtoMember(3)]
public double Value {get;set;}
// etc
void ISerializable.GetObjectData(
SerializationInfo info,StreamingContext context)
{
Serializer.Serialize(info, this);
}
public MyType() {} // default constructor
protected MyType(SerializationInfo info, StreamingContext context)
{
Serializer.Merge(info, this);
}
}