I am using the the following code for redis lock and release
var key = "test-x";
RedisValue token = (RedisValue) Guid.NewGuid().ToString();
if(db.LockTake(key, token, duration)) {
try {
// you have the lock do work
} finally {
db.LockRelease(key, token);
}
}
My problem:
In a unit test I am calling this method 2 times. The first time always work, but the second time I want to obtain the lock on this specific key, it does not work. From my understanding the db.LockRelease should release the lock, making it available for the second request. I did notice that db.LockRelease returns false.
Any idea what might be happening?
The lock key needs to be unique. You are probably using the same lock key as the cache key in you code. From https://stackoverflow.com/a/25138164:
the key (the unique name of the lock in the database)
Related
I am developing a web application with Vapor 4. It would be useful to persist client-made data on the server side for a few minutes at a time in between requests. I want to use sessions to do this. However, I am a bit confused on how the best way to automatically destroy this data after a set time. Should I make a job and have it check periodically? Or is there an easy way to set an expiry time on session creation?
I have used a bit of Middleware to achieve this for some months and it is very reliable.
It compares the timestamp now to the value from the immediate previous request. If the difference is greater than the allowed session timeout, it forces a logout.
I had to give a bit of thought to initialising the timestamp and "BAD" ensures a nil gets returned from trying to initialise a Double, which then gets the current timestamp to start the session 'timer'. I think this is safe as the user can't log in without having made at least one route call beforehand and I have other Middleware that checks to make sure the user is logged in. Try this:
struct SessionTimeoutMiddleware:Middleware
{
func respond(to request:Request, chainingTo next:Responder) -> EventLoopFuture<Response>
{
let lastRequestTimeStamp = Double(request.session.data["lastRequest"] ?? "BAD") ?? Date().timeIntervalSince1970
request.session.data["lastRequest"] = String(Date().timeIntervalSince1970)
if Date().timeIntervalSince1970 - lastRequestTimeStamp > 300.0 // seconds
{
request.auth.logout(User.self)
return request.eventLoop.makeSucceededFuture(request.redirect(to:"/somewhere/safe"))
}
return next.respond(to:request)
}
}
Then, register in configure.swift using:
let userAuthSessionsMW = User.authenticator()
let sessionTimeoutMW = SessionTimeoutMiddleware()
let timed = app.grouped(C.URI.Users).grouped(userAuthSessionsMW, sessionTimeoutMW)
try SecureRoutes(timed)
I'm trying to write a Groovy/Grails 3 function that looks up a database object, locks it, and then saves it (releasing the lock automatically).
If the function is called multiple times, it should wait until the lock is released, and then run the update. How can I accomplish this?
def updateUser(String name) {
User u = User.get(1)
// if locked, wait until released somehow?
u.lock()
u.name = name
u.save()
}
updateUser('bob')
updateUser('fred') // sees lock from previous call, waits until released, then updates
u.save(flush:true)
Flushing the Hibernate session should complete the transaction and release the lock on the database level.
Generally speaking, pessimistick locking only works in a transactional context.
So make sure to put the updateUser method in a service that is annotated with #Transactional.
Calling get() and then lock() results in 2 sql statements being executed (one for getting the object, another for locking it).
Using User.lock(), a single select ... for udpate query is issued instead.
#Transactional
class UserService {
def updateUser(String name) {
User u = User.lock(1) // blocks until lock is free
u.name = name
u.save()
}
}
I do the following:
def currentUser = springSecurityService.currentUser
currentUser.name = "test"
currentUser.save(flush: true)
// some other code
currentUser.gender = "male"
currentUser.save(flush: true) // Exception occurs
This is the exception I get:
ERROR events.PatchedDefaultFlushEventListener - Could not synchronize database state with session
org.hibernate.StaleObjectStateException: Row was updated or deleted by another transaction (or unsaved-value mapping was incorrect)
How can I prevent this error? What is the best solution for that?
I found different approaches:
here that you can use discard()
here that you can use merge()
Which one should I use?
You should use merge - it will update the object to match the current state in the database. If you use discard it will reset the object back to what the database has, discarding any changes. Everything else in the hibernate session you need to manage yourself.
More importantly code should be written in a service so that there is a database transaction, and you should use
save(flush:true)
once only at the end.
def currentUser = springSecurityService.currentUser
currentUser.name = "test"
// currentUser.save(flush: true) // removing this line because if a rollback occurs, then changes before this would be persisted.
// some other code
currentUser.gender = "male"
currentUser.merge() // This will merge persistent object with current state
currentUser.save(flush: true)
How to use Cache.getOrElse(java.lang.String key, java.util.concurrent.Callable block, int expiration)
Could someone give me a example？
My point is how to use “expiration",I know it means expire time.
By the way:
I want save some object to cache,and set a expire time.
when the expire time,I can reset the object to the cache.
Thanks.
Let's assume that, you want to set User object on cache, for that you set userId as key and user object as value. If need set expiration time, for sample i set it as 30secs.
cache.set(userId, userObject, 30);
At some point of time, if you want to get user object from cache, which you set earlier using userId as key, you might try the following way to get the user object from cache.
User user = cache.get(userId);
Above will return you the user object, if you access within 30secs, otherwise it will return NULL. This will be perfect for case like validating the session.
In some case, you frequently need to retrieve value from cache, for that following is the best approach.
User user = cache.getOrElse(userId, () -> User.get(userId), 30);
cache will check, whether it has given userId as key, if available then straight away return the user object and update the expiration time to 30secs further.
If given userId not available, then callable block gets invoked and set userId as key, user object fetched from db as value and expiration time as 30secs.
Expiration is the number of seconds that the Object would be hold in the Cache. If you pass 0 as expiration the Cache doesn't expire and you would have to control it by hand.
What getOrElse does is check the Cache, if the Object is not there then call the callable block that you are passing and adds the result to the cache for the number of seconds that you are passing as expiration time.
I based my comment in the Play Framework Cache Javadoc.
I use getOrElse in controllers when I have dynamic and static content to display. Cache the static and then render it together with the dynamic part:
try {
Html staticHtml = Cache.getOrElse("static-content", () -> staticView.render(), 60 * 60);
Html rendered = dynamicPage.render(arg1, arg2, staticHtml);
return ok(rendered);
} catch (Exception e) {
e.printStackTrace();
return internalServerError();
}
staticView.render() returns some html from a view. This view should not call any other pages which are dynamic or you stash something you do not really want to stash.
60*60 means I want to store it for one hour (60 seconds times 60 minutes... ok you can write 3600 if you want)
I should add that getOrElse gets the Object from the cache with the specified key (in this example the key is static-content) but if it cannot find it, then it calls the function which returns an object which is then stored for the specified amount of time in the cache with that key. Pretty neat.
Then you can call some other (dynamic) page and pass the html to it.
The dynamic stuff will stay dynamic :)
I have a bit of linq to entities code in a web app. It basically keeps a count of how many times an app was downloaded. I'm worried that this might happen:
Session 1 reads the download count (eg. 50)
Session 2 reads the download count (again, 50)
Session 1 increments it and writes it to the db (database stores 51)
Session 2 increments it and writes it to the db (database stores 51)
This is my code:
private void IncreaseHitCountDB()
{
JTF.JTFContainer jtfdb = new JTF.JTFContainer();
var app =
(from a in jtfdb.Apps
where a.Name.Equals(this.Title)
select a).FirstOrDefault();
if (app == null)
{
app = new JTF.App();
app.Name = this.Title;
app.DownloadCount = 1;
jtfdb.AddToApps(app);
}
else
{
app.DownloadCount = app.DownloadCount + 1;
}
jtfdb.SaveChanges();
}
Is it possible that this could happen? How could I prevent it?
Thank you,
Fidel
Entity Framework, by default, uses an optimistic concurrency model. Google says optimistic means "Hopeful and confident about the future", and that's exactly how Entity Framework acts. That is, when you call SaveChanges() it is "hopeful and confident" that no concurrency issue will occur, so it just tries to save your changes.
The other model Entity Framework can use should be called a pessimistic concurrency model ("expecting the worst possible outcome"). You can enable this mode on an entity-by-entity basis. In your case, you would enable it on the App entity. This is what I do:
Step 1. Enabling concurrency checking on an Entity
Right-click the .edmx file and choose Open With...
Choose XML (Text) Editor in the popup dialog, and click OK.
Locate the App entity in the ConceptualModels. I suggest toggling outlining and just expanding tags as necessary. You're looking for something like this:
<edmx:Edmx Version="2.0" xmlns:edmx="http://schemas.microsoft.com/ado/2008/10/edmx">
<!-- EF Runtime content -->
<edmx:Runtime>
<!-- SSDL content -->
...
<!-- CSDL content -->
<edmx:ConceptualModels>
<Schema Namespace="YourModel" Alias="Self" xmlns:annotation="http://schemas.microsoft.com/ado/2009/02/edm/annotation" xmlns="http://schemas.microsoft.com/ado/2008/09/edm">
<EntityType Name="App">
Under the EntityType you should see a bunch of <Property> tags. If one exists with Name="Status" modify it by adding ConcurrencyMode="Fixed". If the property doesn't exist, copy this one in:
<Property Name="Status" Type="Byte" Nullable="false" ConcurrencyMode="Fixed" />
Save the file and double click the .edmx file to go back to the designer view.
Step 2. Handling concurrency when calling SaveChanges()
SaveChanges() will throw one of two exceptions. The familiar UpdateException or an OptimisticConcurrencyException.
if you have made changes to an Entity which has ConcurrencyMode="Fixed" set, Entity Framework will first check the data store for any changes made to it. If there are changes, a OptimisticConcurrencyException will be thrown. If no changes have been made, it will continue normally.
When you catch the OptimisticConcurrencyException you need to call the Refresh() method of your ObjectContext and redo your calculation before trying again. The call to Refresh() updates the Entity(s) and RefreshMode.StoreWins means conflicts will be resolved using the data in the data store. The DownloadCount being changed concurrently is a conflict.
Here's what I'd make your code look like. Note that this is more useful when you have a lot of operations between getting your Entity and calling SaveChanges().
private void IncreaseHitCountDB()
{
JTF.JTFContainer jtfdb = new JTF.JTFContainer();
var app =
(from a in jtfdb.Apps
where a.Name.Equals(this.Title)
select a).FirstOrDefault();
if (app == null)
{
app = new JTF.App();
app.Name = this.Title;
app.DownloadCount = 1;
jtfdb.AddToApps(app);
}
else
{
app.DownloadCount = app.DownloadCount + 1;
}
try
{
try
{
jtfdb.SaveChanges();
}
catch (OptimisticConcurrencyException)
{
jtfdb.Refresh(RefreshMode.StoreWins, app);
app.DownloadCount = app.DownloadCount + 1;
jtfdb.SaveChanges();
}
}
catch (UpdateException uex)
{
// Something else went wrong...
}
}
You can prevent this from happenning if you only query the download count column right before you are about to increment it, the longer the time spent between reading and incrementing the longer the time another session has to read it (and later rewriting - wrongly - incremented number ) and thus messing up the count.
with a single SQL query :
UPDATE Data SET Counter = (Counter+1)
since its Linq To Entities,it means delayed execution,for another session to screw up the Count (increment the same base,losing 1 count there) it would have to try to increment the app.Download count i beleive between the two lines:
else
{
app.DownloadCount += 1; //First line
}
jtfdb.SaveChanges(); //Second line
}
thats means that the window for the change to occur, thus making the previous count old, is so small that for an application like this is virtually impossible.
Since Im no LINQ pro, i dont know whether LINQ actually gets app.DownLoadCount before adding one or just adds one through some SQL command, but in either case you shouldnt have to worry about that imho
You could easily test what would happen in this scenario - start a thread, sleep it, and then start another.
else
{
app.DownloadCount = app.DownloadCount + 1;
}
System.Threading.Thread.Sleep(10000);
jtfdb.SaveChanges();
But the simple answer is that no, Entity Framework does not perform any concurrency checking by default (MSDN - Saving Changes and Managing Concurrency).
That site will provide some background for you.
Your options are
to enable concurrency checking, which will mean that if two users download at the same time and the first updates after the second has read but before the second has updated, you'll get an exception.
create a stored procedure that will increment the value in the table directly, and call the stored procedure from code in a single operation - e.g. IncrementDownloadCounter. This will ensure that there is no 'read' and therefore no possibility of a 'dirty read'.