I have an ASP.Net MVC web app that includes a set of Forums. In order to maintain flexible security, I have chosen an access-control-list style of security.
However, this is getting to be a pretty heavy chunk of data to retrieve every time somebody views the forum index.
I am using the EnterpriseLibrary.Caching functionality to cache various non-LINQ items on the site. (The BBCode interpreter, the Skins, and etc.)
My question is this:
What is the safest and most elegant way to cache a LINQ result?
Essentially, I would like to keep a copy of the ACL for each forum in memory to prevent the database hit. That way, for each person that hits the site, at most I would have to fetch group membership information.
All-in-all I'm really looking for a way to cache large abouts of LINQ data effectively, not just these specific rows.
If you've already got a caching system for general objects, all you should need is this:
var whatever = linkQuery.ToList();
Related
I want to create a search box that will show result relating to the typed the text. I am using .NET MVC and I have been stuck on this for awhile. I want to use the AlphaVantage API search endpoint to create this.
It would like this. I just don't know what component to use or how to implement it.
As we don't know amount of your data and possible stack/budget in your project, autocompletion/autosuggestion could be implemented differently:
In memory (you break your word into all possible prefixes and map them to your entity through dictionary, could be optimized, like so - https://github.com/omerfarukz/autocomplete). Limit is around 10 million entries, a lot of memory consumption. Also support some storage mechanics, but I don't think it is more powerfull than fully fledged Lucene.
In Lucene index (Lucene.Net (4.8) AutoComplete / AutoSuggestion). Limited to 2 billions, very optimized usage of memory, stored on hard drive or anywhere else. Hard to work with, because provide low-level micro optimizations on indexes and overall pipeline of tokenization/indexing.
In Elasticsearch cluster (https://www.elastic.co/guide/en/elasticsearch/client/net-api/current/suggest-usage.html). Unlimited, uses Lucene indexes as sharding units. Same as lucene, but every cloud infrastructure provide it for pretty penny.
In SQL using full text index (SQL Server Full Text Catalog and Autocomplete). Limited by database providers such as SQLite/MSSQL/Oracle/etc, cheap, easy to use, usually consumes CPU as there is no tomorrow, but hey, it is relational, so you could join any data to results.
As to how to use it - basically you send request to desired framework instance and retrieve first N results, which then you serve in some REST GET response.
You'll have to make a POST request (HttpClient) to the API that will return your data. You'll also need to provide all required authorization information (whether headers or keys). That would need to be async or possibly a background worker so that it doesn't block your thread. The requests need to happen when there's a change in your search box.
You can probably find details on how to do the request here.
I have a situation at www.zipstory.com (beta) where I have n-permutations of feeds coming from the same database. For example, someone can get a feed for whatever city they are interested in and as many of these cities all together so its all sorted by most recent or most votes.
How should I cache things for each user without completely maxing out the available memory when there are thousands of users at the same time?
My only guess is don't. I could come up with a client-side caching strategy where I sort out the cities results but this way I could still cache in a one-size fits all strategy by city.
What approaches do you suggest? I'm in unfamiliar ground at this point and could use a good strategy. I noticed this website does not do that but Facebook does. They must be pulling from a pool of cached user-feeds and plucking them in client-side. Not sure, again I'm not smart enough to figure this out just yet.
In other words...
Each city has its own feed. Each user has an n-permutation of city feeds combined.
I would like to see possible solutions to this problem using c# and ASP.NET
Adding to this Febuary 28th, 2013. Here's what I did based on your comments so THANKS!...
For every user logging in, I cache their preferred city list
The top 10 post results are cached per city and stored in a Linq based object
When a user comes in and has x cities as feeds, I go through their city list loop then check if city postings are in cache, if not, I get from DB then populate the individual posting's html into cache along with other sorting elements.
I recombine the list of cities into one feed for the user and since i have some sorting elements on the linq object, i can resort them in the proper order and give back to the user
This does mean there is some CPU work everytime regardless as I have to combine city lists into a single city list but this avoids going to the database every time and everyone benefits in faster page response times. The main drawback is since I'm not doing a single query UNION on cities before, this requires a single query per city if each was not cached but each city is checked if cached or not individually so 10 queries per 10 cities would only happen if the site is a dead zone.
Judge the situation based on critical chain points.
If the memory is not a problem, consider having the whole feed cached and retrieving items from there. For this you can use distributed cache solutions. Some of them are even free. Start from the memcached, http://memcached.org/ . People refer to this approach as Load Ahead.
Sometimes memory is a problem if you want to use asp.net cache with expiration and priorities. In such a case, cache can be gone at any point when the memory becomes a problem. Thus, you load the data again on demand (called as Load Through) that affects bandwidth. In such a case, your code should be smarter to get along. If this is an option for you, then try to cache as little as possible. e.g. cache loaded items each and when the user requests a feed, check if all items are present in the cache. If not, you will have to fetch either all or missing ones again. I have done something similar in the past, but cannot provide the code. Key point is: cache entities and then cache feeds with references (IDs) to the entities. Thus, when a particular feed is requested, you check that all references are still valid in the cache. BTW, asp.net provides cache dependencies for such scenarios, so read about that too, - may be helpful.
In any case, have Decorator design pattern in mind when implementing data access layer, that would allow you to: 1 - postpone the caching concerns for the later development phases, and 2 - switch between the two approaches described above depending on how things go. I would start with simpler (and cheaper) built-in solution, and then would switch to the distributed cache solutions when really needed.
Only cache the minimal amount of different information per user that you need.
For example, if it fits in memory, cache the complete set of feeds and only store, per user, the id's of the feeds they are interested in.
When they request their feeds, just get those out of memory.
Have you considered cache-ing generic feeds, and tag them. And then per user, you just store reference to that tag/keyword.
Another possibility could be to store generic feed, and then filter on client. This will increase your bandwidth, but save cost on cache.
And if you are on HTML5, use Local Storage to hold user preference.
i have a similar requirement to stackoverflow to show a number of metrics on a page in my asp.net-mvc site that are very expensive to calculate. Stackoverflow has a lot of metrics on the page (like user accept rate, etc) which clearly is not being calculated on the fly on page request, given that it would be too slow.
What is a recommended practice for serving up calculated data really fast without the performance penalty (assuming we can accept that this data maybe a little out of date.
is this stored in some caching layer or stored in some other "results" database table so every day there is a job to calculate this data and store the results so they can be queries directly?
assuming that i am happy to deal with the delayed of having this data as a snapshot,what is the best solution for this type of problem.
Probably they may be relying on the Redis data store for such calculations and caching. This post from marcgravell may help.
yes, the answer is caching, how you do it is (can be) the complicated part, if you are using NHibernate adding caching is really easy, is part of your configuration and on the queries you just add .Cacheable and it manages it for you. Caching also depends on the type of environment, if you're using a single worker, web farm or web garden, you would have to build a caching layer to accomodate for your scenario
Although this is a somewhat-recent technique, one really great way to structure your system to make stuff like this possible is by using Command and Query Responsibility Segregation, more often referred to by CQRS.
I've been implementing MS Search Server 2010 and so far its really good. Im doing the search queries via their web service, but due to the inconsistent results, im thinking about caching the result instead.
The site is a small intranet (500 employees), so it shouldnt be any problems, but im curious what approach you would take if it was a bigger site.
I've googled abit, but havent really come over anything specific. So, a few questions:
What other approaches are there? And why are they better?
How much does it cost to store a dataview of 400-500 rows? What sizes are feasible?
Other points you should take into consideration.
Any input is welcome :)
You need to employ many techniques to pull this off successfully.
First, you need some sort of persistence layer. If you are using a plain old website, then the user's session would be the most logical layer to use. If you are using web services (meaning session-less) and just making calls through a client, well then you still need some sort of application layer (sort of a shared session) for your services. Why? This layer will be home to your database result cache.
Second, you need a way of caching your results in whatever container you are using (session or the application layer of web services). You can do this a couple of ways... If the query is something that any user can do, then a simple hash of the query will work, and you can share this stored result among other users. You probably still want some sort of GUID for the result, so that you can pass this around in your client application, but having a hash lookup from the queries to the results will be useful. If these queries are unique then you can just use the unique GUID for the query result and pass this along to the client application. This is so you can perform your caching functionality...
The caching mechanism can incorporate some sort of fixed length buffer or queue... so that old results will automatically get cleaned out/removed as new ones are added. Then, if a query comes in that is a cache miss, it will get executed normally and added to the cache.
Third, you are going to want some way to page your result object... the Iterator pattern works well here, though probably something simpler might work... like fetch X amount of results starting at point Y. However the Iterator pattern would be better as you could then remove your caching mechanism later and page directly from the database if you so desired.
Fourth, you need some sort of pre-fetch mechanism (as others suggested). You should launch a thread that will do the full search, and in your main thread just do a quick search with the top X number of items. Hopefully by the time the user tries paging, the second thread will be finished and your full result will now be in the cache. If the result isn't ready, you can just incorporate some simple loading screen logic.
This should get you some of the way... let me know if you want clarification/more details about any particular part.
I'll leave you with some more tips...
You don't want to be sending the entire result to the client app (if you are using Ajax or something like an IPhone app). Why? Well because that is a huge waste. The user likely isn't going to page through all of the results... now you just sent over 2MB of result fields for nothing.
Javascript is an awesome language but remember it is still a client side scripting language... you don't want to be slowing the user experience down too much by sending massive amounts of data for your Ajax client to handle. Just send the prefetched result your client and additional page results as the user pages.
Abstraction abstraction abstraction... you want to abstract away the cache, the querying, the paging, the prefetching... as much of it as you can. Why? Well lets say you want to switch databases or you want to page directly from the database instead of using a result object in cache... well if you do it right this is much easier to change later on. Also, if using web services, many many other applications can make use of this logic later on.
Now, I probably suggested an over-engineered solution for what you need :). But, if you can pull this off using all the right techniques, you will learn a ton and have a very good base in case you want to extend functionality or reuse this code.
Let me know if you have questions.
It sounds like the slow part of the search is the full-text searching, not the result retrieval. How about caching the resulting resource record IDs? Also, since it might be true that search queries are often duplicated, store a hash of the search query, the query, and the matching resources. Then you can retrieve the next page of results by ID. Works with AJAX too.
Since it's an intranet and you may control the searched resources, you could even pre-compute a new or updated resource's match to popular queries during idle time.
I have to admit that I am not terribly familiar with MS Search Server so this may not apply. I have often had situations where an application had to search through hundreds of millions of records for result sets that needed to be sorted, paginated and sub-searched in a SQL Server though. Generally what I do is take a two step approach. First I grab the first "x" results which need to be displayed and send them to the browser for a quick display. Second, on another thread, I finish the full query and move the results to a temp table where they can be stored and retrieved quicker. Any given query may have thousands or tens of thousands of results but in comparison to the hundreds of millions or even billions of total records, this smaller subset can be manipulated very easily from the temp table. It also puts less stress on the other tables as queries happen. If the user needs a second page of records, or needs to sort them, or just wants a subset of the original query, this is all pulled from the temp table.
Logic then needs to be put into place to check for outdated temp tables and remove them. This is simple enough and I let the SQL Server handle that functionality. Finally logic has to be put into place for when the original query changes (significant perimeter changes) so that a new data set can be pulled and placed into a new temp table for further querying. All of this is relatively simple.
Users are so used to split second return times from places like google and this model gives me enough flexibility to actually achieve that without needing the specialized software and hardware that they use.
Hope this helps a little.
Tim's answer is a great way to handle things if you have the ability to run the initial query in a second thread and the logic (paging / sorting / filtering) to be applied to the results requires action on the server ..... otherwise ....
If you can use AJAX, a 500 row result set could be called into the page and paged or sorted on the client. This can lead to some really interesting features .... check out the datagrid solutions from jQueryUI and Dojo for inspiration!
And for really intensive features like arbitrary regex filters and drag-and-drop column re-ordering you can totally free the server.
Loading the data to the browser all at once also lets you call in supporting data (page previews etc) as the user "requests" them ....
The main issue is limiting the data you return per result to what you'll actually use for your sorts and filters.
The possibilities are endless :)
Say I have some 10 "categories" that I need to reference in a web app. Currently I'm storing these categories in the DB and am retrieving them (category name and id) during pageload in my basepage, storing them in a hashtable and then using the hashtable to reference the categories. I realized that the DB call is being made during each pageload. I only need to pull these categories once as they never change during a given session. What's the best way to do this?
Do whatever I am doing, but store it as a Application variable?
Hard code the categories in the code, and do away with the database?
Store the categories in a session variable? And call the DB only if the session is empty?
Or something else?
I'm just curious to know what the best-practice is for doing such things.
If the categories are user dependent then I'd store them in the Session variable; otherwise I'd use the ASP.NET Caching functionality (or preferred distributed caching). This allows you to avoid hitting the database whilst being able to control how long the categories should be cached for.
Calling the database is not always as expensive as it seems, a typical website makes dozens of calls to the DB on each pageload. But if it becomes troublesome in terms of performance, consider using an ORM solution. The excellent open source NHibernate comes to mind, which is the "de facto" standard for mapping databases to classes and objects. Beyond the mapping, it automatically provides two levels of caching and connection pooling. Without too much trouble, your website outperforms any other's by a landslide.
The downside of using an ORM? To many people, it is considered a rather steep learning curve. If you want to read into this, make sure to pay a visit to the NHibernate Best Practices. A tough read at first, but definitely worthwhile.
If you combine NHibernate with FluentNHibernate, it becomes a breeze to use.