I'm planning to make use of Oracle AQ Asynchronous notification feature in an OLTP application.The number of messages it enqueues might go up to 1000 within a minute during peak hours. The dequeue callback procedure will process the message and inserts an entry into a table which is determined by the type of message.
My concern is that, does the large number of enqueue notifications it generates(the PL/SQL callback procedure that is being called in turn for every notification) cause database contention ?
Is it advisable to use Asynchronous notification for this purpose or Should I go with dequeue polling process where I can dequeue one message a time in a continous loop.
My database version is 10gR2
Your expert help is highly appreciated!!
For each message enqueued into the queue, ORACLE background process invokes the related callback procedure by creating a scheduler job.
As you are expecting 1000 messages with in a minute if you depend on the callback procedure it increases the load on ORACLE background processes and also creates those many onetime scheduler jobs, again if the no.of parallel scheduler jobs created is more than the "job_queue_processes" (ORACLE parameter) value configured in your database that delays the message processing, instead if you choose for polling to dequeue by using AQ listener, a single job can process all the messages enqueued in to the queue.
Related
What is the best practice or way to process the records from DB in scheduled.
Situation:
A Microservice based on Quarkus - responsible for sending a communication to customers.
DB Table Having Customers Records (100000 customers)
Microservice is running on multiple nodes (4 nodes)
Expectation:
There should be a scheduler that runs every 5 sec
Fetches the records from DB where employee status = pending
Should be Multithreaded architecture.
Send email to employee email.
Problem 1:
The same scheduler running on multiple nodes picks the same records and process How can we avoid this?
Problem 2:
Scheduler pics (100 records and processing it) and takes more than 5 seconds and scheduler run again pics few same records. How can we avoid that:
If you are planning to run your microservices on kubernetes I would sugest to use an external components as a scheduler and let this component distribute the work over your microservices using messages or HTTP invocations.
As responses to your questions here we go:
You can use some locking strategy or "reserve" each row including a field that indicates that your record is being processed and excluding all records containing this fields from your query. By this means when the scheduler fires it will read a set of rows not reserved and use a multithreading approach to process the records, by using a locking strategy (pesimits or optimist) you can prevent other records from marking the same row as reserved for them to be processed. After that the thread thas was able to commit the reserve process the records and updates the state or releases the "reserve" so other workers can work on the record if its needed.
You can always instruct your scheduler to do no execute if there is still an execution going.
#Scheduled(identity = "ProcessUpdateScheduler", every = "2s", concurrentExecution = Scheduled.ConcurrentExecution.SKIP)
You mainly have two approaches among other possible ones:
Pulling (Distribute mining or work distribution): Each instance of the microservice pick a random pending row and mark this row as "processing" commiting the transaction, if its able to commit then this instance holds the right to process this record continuing with its execution, if not it tries to retrieve a different row or just exists waiting for the next invocation. This approach scales horizontally because adding more workers will mean increasing your processing throughput.
Pushing (central distribution, distributed processing). You have two kinds of components: First the "Distributor" which is executed with the scheduler and is responsible for picking rows to be processed and marking then as "pending processing", this rows will be forward via a messaging system or HTTP call to the "Processor". The Processor component recieves as input a record and is responsible of processing this record completely or releasing the hold ("procesing pending") state.
Choouse the best suited for your scenario, if you go for the second option, you can have one or more distributors if its necessary, but in order to increment your processing throughput you only need to scale the "Processor" workers
Say you have a message queue that needs to be polled every x seconds. What are the usual ways to poll it and execute HTTP/Rest-based jobs? Do you simply create a cron service and call the worker script every x seconds?
Note: This is for a web application
I would write a windows service which constantly polls/waits for new messages.
Scheduling a program to run every x min has a number of problems
If your interval is too small the program will still be running with the next startup is triggered.
If your interval is too big the queue will fill up between runs.
Generally you expect a constant stream of messages, so there is no problem just keeping the program running 24/7
One common feature of the message queue systems I've worked with is that you don't poll but use a blocking read. If you have more than one waiting worker, the queue system will pick which one gets to process the message.
I have a function:
public async static Task Run([QueueTrigger("efs-api-call-last-datetime", Connection = "StorageConnectionString")]DateTime queueItem,
[Queue("efs-api-call-last-datetime", Connection = "StorageConnectionString")]CloudQueue inputQueue,
TraceWriter log)
{
Then I have long process for processing message from queue. Problem is the message will be readded to queue after 30 seconds, while I process this message. I don't need to add this message and process it twice.
I would like to have code like:
try
{
// long operation
}
catch(Exception ex)
{
// something wrong. Readd this message in 1 minute
await inputQueue.AddMessageAsync(new CloudQueueMessage(
JsonConvert.SerializeObject(queueItem)),
timeToLive: null,
initialVisibilityDelay: TimeSpan.FromMinutes(1),
options: null,
operationContext: null
);
}
and prevent to readd it automatically. Any way to do it?
There are couple of things here.
1) When there are multiple queue messages waiting, the queue trigger retrieves a batch of messages and invokes function instances concurrently to process them. By default, the batch size is 16. But this is configurable in Host.json. You can set the batch size to 1 if you want to minimize the parallel execution. Microsoft document explains this.
2) As it is long running process so it seems your messages are not complete and the function might timeout and message are visible again. You should try to break down your function into smaller functions. Then you can use durable function which will chain the work you have to do.
Yes, you can dequeue same message twice.
Reasons:
1.Worker A dequeues Message B and invisibility timeout expires. Message B becomes visible again and Worker C dequeues Message B, invalidating Worker A's pop receipt. Worker A finishes work, goes to delete Message B and error is thrown. This is most common.
2.The lock on the original message that triggers the first Azure Function to execute is likely expiring. This will cause the Queue to assume that processing the message failed, and it will then use that message to trigger the Function to execute again.
3.In certain conditions (very frequent queue polling) you can get the same message twice on a GetMessage. This is a type of race condition that while rare does occur. Worker A and B are polling very quickly and hit the queue simultaneously and both get same message. This used to be much more common (SDK 1.0 time frame) under high polling scenarios, but it has become much more rare now in later storage updates (can't recall seeing this recently).
1 and 3 only happen when you have more than 1 worker.
Workaround:
Install azure-webjobs-sdk 1.0.11015.0 version (visible in the 'Settings' page of the Functions portal). For more details, you could refer to fixing queue visibility renewals
Say I have a large set of calls to a procedure to run which have varying parameters but are independent so I want to make parallel/async calls. I use the service broker to fire these all off but the problem I have is I want to know neat ways of knowing how to wait for them all to complete (or error).
Is there a way to do this? I believe I could just loop with waits on the result table checking for completion on that but that isn't very "event triggered". Hoping for a nicer way to do this.
I have used the service broker with queue code and processing based off this other answer: Remus' service broker queuing example
Good day Shiv,
There are several ways (like always) that you can use in order to implement this requirement. One of these is using this logic:
(1) Create two queues: one will be the trigger to execute the main SP that you want execute in Asynchronous, and the other will be the trigger to execute whatever you want to execute after all the executions ended.
(2) When you create the message in the first queue you should also create a message in the second queue, which will only tell us which execution did not ended yet (first queue gives the information which execution started since once we START the execution we use the message and remove it from the queue).
(3) Inside the SP that you execute using the main first queue (this part executed in synchronous):
(3.1) execute the queries you need
(3.2) clear the equivalent message from the second queue (meaning that this message will removed only after the queries ended)
(3.3) check if there are messages in the second queue. If there are no messages then all the tasks ended and you can execute your final step
** Theoretically instead of using the second queue, you can store data in a table, but using second queue should probably give better performance then updating table each time an execution ended. Anyhow, you test the option of using a table as well.
I am looking for a distributed timer service. Multiple remote client services should be able to register for callbacks (via REST apis) after specified intervals. The length of an interval can be 1 minute. I can live with an error margin of around 1 minute. The number of such callbacks can go up to 100,000 for now but I would need to scale up later. I have been looking at schedulers like Quartz but I am not sure if they are a fit for the problem. With Quartz, I will probably have to save the callback requests in a DB and poll every minute for overdue requests on 100,000 rows. I am not sure that will scale. Are there any out of the box solutions around? Else, how do I go about building one?
Posting as answer since i cant comment
One more options to consider is a message queue. Where you publish a message with scheduled delay so that consumers can consume after that delay.
Amazon SQS Delay Queues
Delay queues let you postpone the delivery of new messages in a queue for the specified number of seconds. If you create a delay queue, any message that you send to that queue is invisible to consumers for the duration of the delay period. You can use the CreateQueue action to create a delay queue by setting the DelaySeconds attribute to any value between 0 and 900 (15 minutes). You can also change an existing queue into a delay queue using the SetQueueAttributes action to set the queue's DelaySeconds attribute.
Scheduling Messages with RabbitMQ
https://github.com/rabbitmq/rabbitmq-delayed-message-exchange/
A user can declare an exchange with the type x-delayed-message and then publish messages with the custom header x-delay expressing in milliseconds a delay time for the message. The message will be delivered to the respective queues after x-delay milliseconds.
Out of the box solution
RocketMQ meets your requirements since it supports the Scheduled messages:
Scheduled messages differ from normal messages in that they won’t be
delivered until a provided time later.
You can register your callbacks by sending such messages:
Message message = new Message("TestTopic", "");
message.setDelayTimeLevel(3);
producer.send(message);
And then, listen to this topic to deal with your callbacks:
consumer.subscribe("TestTopic", "*");
consumer.registerMessageListener(new MessageListenerConcurrently() {...})
It does well in almost every way except that the DelayTimeLevel options can only be defined before RocketMQ server start, which means that if your MQ server has configuration messageDelayLevel=1s 5s 10s, then you just can not register your callback with delayIntervalTime=3s.
DIY
Quartz+storage can build such callback service as you mentioned, while I don't recommend that you store callback data in relational DB since you hope it to achieve high TPS and constructing distributed service will be hard to get rid of lock and transaction which bring complexity to DB coding.
I do suggest storing callback data in Redis. Because it has better performance than relational DB and it's data structure ZSET suits this scene well.
I once developed a timed callback service based on Redis and Dubbo. it provides some more useful features. Maybe you can get some ideas from it https://github.com/joooohnli/delay-callback