Using MemoryCacheHandle with RedisCacheBackplane but without RedisCacheHandle - caching

On the documentation it says
/// The cache manager must have at least one cache handle configured with <see cref="CacheHandleConfiguration.IsBackplaneSource"/> set to <c>true</c>.
/// Usually this is the redis cache handle, if configured. It should be the distributed and bottom most cache handle.
I know how to do it with RedisCacheHandle, since it's given as example on Cachemanager's website
var cache = CacheFactory.Build<int>("myCache", settings =>
{
settings
.WithSystemRuntimeCacheHandle("inProcessCache")
.And
.WithRedisConfiguration("redis", config =>
{
config.WithAllowAdmin()
.WithDatabase(0)
.WithEndpoint("localhost", 6379);
})
.WithMaxRetries(1000)
.WithRetryTimeout(100)
.WithRedisBackplane("redis")
.WithRedisCacheHandle("redis", true);
});
The problem is I don't want to use Redis as cache resource; I just want to make a distributed cache by the power of Redis Pub/Sub mechanism. According to my debugging through the code, by using Redis Backplane feature I'm able to send messages to and receive messages from Redis indeed. So why not use RedisCacheHandle and instead use SystemRuntimeCacheHandle?
So, my expectation was the successfull execution with the following cache configuration
var cache = CacheFactory.Build<int>("myCache", settings =>
{
settings
.WithSystemRuntimeCacheHandle("inProcessCache")
.And
.WithRedisConfiguration("redis", config =>
{
config.WithAllowAdmin()
.WithDatabase(0)
.WithEndpoint("localhost", 6379);
})
.WithMaxRetries(1000)
.WithRetryTimeout(100)
.WithRedisBackplane("redis")
.WithSystemRuntimeCacheHandle("inProcessCache", true);
});
But it's not working. Can you please show me a solution? What am I doing wrong? Or, eventhough it's written in the documentation as
...Usually this is the redis cache handle...
are there any way to use the cache synchronization feature without RedisCacheHandle?
https://github.com/MichaCo/CacheManager/issues/111

I guess you with "nor working" you mean that the other caches do not get synced, e.g. if I delete a key from cacheA, it doesn't get deleted from cacheB?
Yes this is currently an expected behavior.
The backplane is intended to work with out of process caches where you have only one state.
With 2 instances of the cache both using system runtime caching, you have two totally disconnected in proc caches.
Normally, if you have a Redis layer and you remove a key from cache instance A, the item would be removed from the Redis layer. The message gets send to other instances of the same cache and would remove the key from any other cache layer but redis (the one marked as backplane source).
This means, we expect that the backplane source is already in sync.
Now what if you have an in-process cache as backplane source. That doesn't work, because both instances will always be out of sync.
Lets look at this example:
var cacheConfig = ConfigurationBuilder.BuildConfiguration(settings =>
{
settings
.WithSystemRuntimeCacheHandle("inProcessCache")
.And
.WithRedisConfiguration("redis", config =>
{
config.WithAllowAdmin()
.WithDatabase(0)
.WithEndpoint("localhost", 6379);
})
.WithMaxRetries(1000)
.WithRetryTimeout(100)
.WithRedisBackplane("redis")
.WithSystemRuntimeCacheHandle("inProcessCache", true);
});
var cacheA = new BaseCacheManager<string>(cacheConfig);
var cacheB = new BaseCacheManager<string>(cacheConfig);
cacheB.Backplane.Removed += (obj, args) =>
{
Console.WriteLine(args.Key + " removed from B.");
};
cacheA.Add("key", "value");
var result = cacheB.Get("key");
Console.WriteLine("Result should be null:" + result);
cacheB.Add("key", "value");
result = cacheB.Get("key");
Console.WriteLine("Result should not be null:" + result);
// triggers backplane remove event
cacheA.Remove("key");
// lets give redis some time send messages
Thread.Sleep(100);
result = cacheB.Get("key");
Console.WriteLine("Result should be null again but isn't:" + result);
Console.ReadKey();
If you run this, you can see that the backplane event actually fires but because the only in-proc cache is the backplane source, the key does not get deleted.
That's why at the end, you still get the key returned back to you.
As I said, that is currently the expected behavior.
You could implement custom logic with listening to those events though.
(the events will change slightly in the next version, currently there are a few bugs and inconsistencies).
Also, don't expect that the backplane would transfer cache values over to other instances. That's not going to happen ever. CacheManager only sends key events, not the data because the data is handled by the out of process cache usually.
Meaning, if you have in-proc cache only with backplane, adding an item in cacheA, will NOT copy the item to cacheB! You might get a change event for the key on cacheB though.
I hope that makes sense ;)

Related

Is there a way to delay cache revalidation in service worker?

I am currently working on performance improvements for a React-based SPA. Most of the more basic stuff is already done so I started looking into more advanced stuff such as service workers.
The app makes quite a lot of requests on each page (most of the calls are not to REST endpoints but to an endpoint that basically makes different SQL queries to the database, hence the amount of calls). The data in the DB is not updated too often so we have a local cache for the responses, but it's obviously getting lost when a user refreshes a page. This is where I wanted to use the service worker - to keep the responses either in cache store or in IndexedDB (I went with the second option). And, of course, the cache-first approach does not fit here too well as there is still a chance that the data may become stale. So I tried to implement the stale-while-revalidate strategy: fetch the data once, then if the response for a given request is already in cache, return it, but make a real request and update the cache just in case.
I tried the approach from Jake Archibald's offline cookbook but it seems like the app is still waiting for real requests to resolve even when there is a cache entry to return from (I see those responses in Network tab).
Basically the sequence seems to be the following: request > cache entry found! > need to update the cache > only then show the data. Doing the update immediately is unnecessary in my case so I was wondering if there is any way to delay that? Or, alternatively, not to wait for the "real" response to be resolved?
Here's the code that I currently have (serializeRequest, cachePut and cacheMatch are helper functions that I have to communicate with IndexedDB):
self.addEventListener('fetch', (event) => {
// some checks to get out of the event handler if certain conditions don't match...
event.respondWith(
serializeRequest(request).then((serializedRequest) => {
return cacheMatch(serializedRequest, db.post_cache).then((response) => {
const fetchPromise = fetch(request).then((networkResponse) => {
cachePut(serializedRequest, response.clone(), db.post_cache);
return networkResponse;
});
return response || fetchPromise;
});
})
);
})
Thanks in advance!
EDIT: Can this be due to the fact that I put stuff into IndexedDB instead of cache? I am sort of forced to use IndexedDB instead of the cache because those "magic endpoints" are POST instead of GET (because of the fact they require the body) and POST cannot be inserted into the cache...

Biztalk Debatched Message Value Caching

I get a file with 4000 entries and debatch it, so i dont lose the whole message if one entry has corrupting data.
The Biztalkmap is accessing an SQL server, before i debatched the Message I simply cached the SLQ data in the Map, but now i have 4000 indipendent maps.
Without caching the process takes about 30 times longer.
Is there a way to cache the data from the SQL Server somewhere out of the Map without losing much Performance?
It is not a recommendable pattern to access a database in a Map.
Since what you describe sounds like you're retrieving static reference data, another option is to move the process to an Orchestration where the reference data is retrieved one time into a Message.
Then, you can use a dual input Map supplying the reference data and the business message.
In this patter, you can either debatch in the Orchestration or use a Sequential Convoy.
I would always avoid accessing SQL Server in a map - it gets very easy to inadvertently make many more calls than you intend (whether because of a mistake in the map design or because of unexpected volume or usage of the map on a particular port or set of ports). In fact, I would generally avoid making any kind of call in a map that has to access another system or service, but if you must, then caching can help.
You can cache using, for example, MemoryCache. The pattern I use with that generally involves a custom C# library where you first check the cache for your value, and if there's a miss you check SQL (either for the paritcular entry or the entire cache, e.g.:
object _syncRoot = new object();
...
public string CheckCache(string key)
{
string check = MemoryCache.Default.Get(key) as string;
if (check == null)
{
lock (_syncRoot)
{
// make sure someone else didn't get here before we acquired the lock, avoid duplicate work
check = MemoryCache.Default.Get(key) as string;
if (check != null) return check;
string sql = #"SELECT ...";
using (SqlConnection conn = new SqlConnection(connStr))
{
conn.Open();
using (SqlCommand cmd = conn.CreateCommand())
{
cmd.CommandText = sql;
cmd.Parameters.AddWithValue(...);
// ExecuteScalar or ExecuteReader as appropriate, read values out, store in cache
// use MemoryCache.Default.Add with sensible expiration to cache your data
}
}
}
}
else
{
return check;
}
}
A few things to keep in mind:
This will work on a per AppDomain basis, and pipelines and orchestrations run on separate app domains. If you are executing this map in both places, you'll end up with caches in both places. The complexity added in trying to share this accross AppDomains is probably not worth it, but if you really need that you should isolate your caching into something like a WCF NetTcp service.
This will use more memory - you shouldn't just throw everything and anything into a cache in BizTalk, and if you're going to cache stuff make sure you have lots of available memory on the machine and that BizTalk is configured to be able to use it.
The MemoryCache can store whatever you want - I'm using strings here, but it could be other primitive types or objects as well.

Caching Data in Web API

I have the need to cache a collection of objects that is mostly static (might have changes 1x per day) that is avaliable in my ASP.NET Web API OData service. This result set is used across calls (meaning not client call specific) so it needs to be cached at the application level.
I did a bunch of searching on 'caching in Web API' but all of the results were about 'output caching'. That is not what I'm looking for here. I want to cache a 'People' collection to be reused on subsequent calls (might have a sliding expiration).
My question is, since this is still just ASP.NET, do I use traditional Application caching techniques for persisting this collection in memory, or is there something else I need to do? This collection is not directly returned to the user, but rather used as the source behind the scenes for OData queries via API calls. There is no reason for me to go out to the database on every call to get the exact same information on every call. Expiring it hourly should suffice.
Any one know how to properly cache the data in this scenario?
The solution I ended up using involved MemoryCache in the System.Runtime.Caching namespace. Here is the code that ended up working for caching my collection:
//If the data exists in cache, pull it from there, otherwise make a call to database to get the data
ObjectCache cache = MemoryCache.Default;
var peopleData = cache.Get("PeopleData") as List<People>;
if (peopleData != null)
return peopleData ;
peopleData = GetAllPeople();
CacheItemPolicy policy = new CacheItemPolicy {AbsoluteExpiration = DateTimeOffset.Now.AddMinutes(30)};
cache.Add("PeopleData", peopleData, policy);
return peopleData;
Here is another way I found using Lazy<T> to take into account locking and concurrency. Total credit goes to this post: How to deal with costly building operations using MemoryCache?
private IEnumerable<TEntity> GetFromCache<TEntity>(string key, Func<IEnumerable<TEntity>> valueFactory) where TEntity : class
{
ObjectCache cache = MemoryCache.Default;
var newValue = new Lazy<IEnumerable<TEntity>>(valueFactory);
CacheItemPolicy policy = new CacheItemPolicy { AbsoluteExpiration = DateTimeOffset.Now.AddMinutes(30) };
//The line below returns existing item or adds the new value if it doesn't exist
var value = cache.AddOrGetExisting(key, newValue, policy) as Lazy<IEnumerable<TEntity>>;
return (value ?? newValue).Value; // Lazy<T> handles the locking itself
}
Yes, output caching is not what you are looking for. You can cache the data in memory with MemoryCache for example, http://msdn.microsoft.com/en-us/library/system.runtime.caching.memorycache.aspx . However, you will lose that data if the application pool gets recycled. Another option is to use a distributed cache like AppFabric Cache or MemCache to name a few.

Meteor Session Replacement?

In the latest Meteor release (version 0.5.8), Session has been removed from the server-side code.
Previously I've used Session to store client-specific variables for the server; what is the replacement for this functionality?
Example case: User One opens a browser, User Two opens a browser. One calls a method on the server setting some token, the other calls a method on the server doing the same. I then need to access this when the client requests something. How do I differentiate between the two?
You'll want to save your tokens to a collection in the database.
You could use a Session on the server if you wanted to simply by copying the session package into your application's packages directory and changing its package.js to also load on the server. But a Session is an in-memory data structure, and so won't work if you have multiple server instances; and you wouldn't be able to restart the server without losing your user's tokens.
If you store your tokens in the database they'll persist across server restarts, and will work with a future version of Meteor which is able to scale an application by adding more server instances when needed.
If you need to expire your tokens (so that your collection doesn't grow without bound), you could add a "lastUsed" Date field to your token collection, and periodically remove tokens that haven't been used for longer than your chosen expiration period.
You can use each one's session id which is unique to the tab too. Not too sure how to get the current session id but it should be there somewhere (you can see it in Meteor.default_server.sessions, so there is still a way:
Client js
Meteor.call("test", Meteor.default_connection._lastSessionId, function(err,result) {
console.log(result);
});
Server side Js
Session = {
set : function(key, value, sessionid) {
console.log(Meteor.default_server.sessions[sessionid]);
if(!Meteor.default_server.sessions[sessionid].session_hash) Meteor.default_server.sessions[sessionid].session_hash = {};
Meteor.default_server.sessions[sessionid].session_hash.key = value;
},
get : function(key, sessionid) {
if(Meteor.default_server.sessions[sessionid].session_hash)
return Meteor.default_server.sessions[sessionid].session_hash.key;
},
equals: function(key, value, sessionid) {
return (this.get(key, sessionid) == value)
},
listAllSessionids: function() {
return _.pluck(Meteor.default_server.sessions, "id");
}
};
Meteor.methods({
test:function(sessionid) {
if(!Session.get("initial_load", sessionid)) Session.set("initial_load", new Date().getTime(), sessionid);
return Session.get("initial_load", sessionid);
}
});
I hook into Meteor.default_connection._sessions to store the values so that theres some type of garbage collection involved when the session isn't valid anymore (i.e the user has closed his tabs) to prevent memory being wasted. In livedata_server.js these old sessions get destroyed after 1 minute of no activity on the DDP wire (like the heartbeat).
Because the server can see everyone's session you can use the sessionid to access another user's session data. and listAllSessionids to give out an array of all the sessionids currently active.
Automatically set session like this.userId in a Method without using a param in a call
It looks like there is functionality for this this but its not fully hooked up. The session id would be stored in this.sessionData but its likely still unfinished. Its there to be called in method but theres nowhere that its being set yet (in livedata_connection.js & livedata_server.js)

ExpressJS backend hanging with too much requests

I have an express app running with Sequelize.js as an ORM. My express app receives requests from my main Rails app, and because of the cross-domain policy, these requests are performed with getJSON.
On the client, the request is fired when the user hits a key.
Everything goes fine and express logs the queries being performed (and json being served) each time the user hits the key. Even trying to hit quickly it performs ok. But, whenever I leave the key pressed (or maybe several clients hitting the key very quickly), as it starts firing lots of requests, at some moment the server just hangs, all the requests from that point on are left pending (I see that in the Network tab of Chrome Dev Tools), and they slowly start to timeout. I have to reboot the server to make it respond again.
The server code for my request is:
models.Comment.findAllPublic(req.params.pId, req.params.sId, function(comments){
var json = comments.map(function(comment){
var com = {};
['user_id','user_avatar', 'user_slug', 'user_name', 'created_at', 'text', 'private', 'is_speaker_note'].forEach(function(key){
com[key]=comment[key];
});
return com;
});
res.json({comments: json});
});
And the findAllPublic method from the Comment model (this is a Sequelize model) is:
findAllPublicAndMyNotes: function(current_user, presentationId, slideId, cb){
db.query("SELECT * FROM `comments` WHERE commentable_type='Slide' AND commentable_id=(SELECT id from `slides` where `order_in_presentation`="+slideId+" AND `presentation_id`="+presentationId+") AND (`private` IS FALSE OR (`private` IS TRUE AND `user_id`="+current_user+" AND `is_speaker_note` IS FALSE))",self.Comment).on('success', cb).on('failure',function(err){console.log(err);});
}
How to avoid the server from getting stuck? Am I leaving some blocking code in the request that may slowly hang the server as new requests are made?
At first I thought it could be a problem because of the "forEach" when composing the json object from the Sequelize model, but I also tried leaving the callback for the mysql query empty, just responding empty json and it also got frozen.
Maybe it is a problem of the mysql connector? When the server gets stuck I can normally run the mysql console and perform queries on my database and it also responds, so I don't know if that's the problem.
I know I could just control the key event to prevent it from firing too many requests when the key gets pressed for a long time, but the problem seems to appear also when several clients hit the key repeatedly and concurrently.
Any thoughts? Thanks in advance for the help :D
Two things:
It seems like you have some path where res.render is not being called. It could be that the database you're connecting to is dropping the connection to your Express server after the absurd number of requests and the callback is never fired (and there's no database.on('close', function() { // Handle disconnect from DB, perhaps auto-restarting }) code to catch it.
Your client-side code should detect when an AJAX request on keypress is still pending while a new one is being started, and cancel the old one. I'm guessing getJSON is a jQuery method? Assuming it's jQuery's, then you need something like the following
.
var currKeyRequest = null;
function callOnKeyUp() {
var searchText = $('#myInputBox').value;
if(currKeyRequest) {
currKeyRequest.reject();
currKeyRequest = null;
}
currKeyRequest = $.getJSON('path/to/server', function(json) {
currKeyRequest = null;
// Use JSON code
});
}
This way, you reduce the load on the client, the latency of the autocomplete functionality (but why not use the jQuery UI autocomplete if that's what you're after?), and you can save the server from some of the load as well if the keypresses are faster than handshaking with the server (possible with a good touch-typist a few hours flight away).

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