Currently, I have an idea about building a centralized batch job management system (I temporarily call it batch service).
We own a microservice system, and the batch jobs are scattered across the services (including oracle's bacth jobs). So I intend to set up a bacth job management system.
But there is one problem that in microservices there are many databases, so I want the manipulation of data to be done by other services, and batch service only does the following things: setting, scheduling, checking status state, log, start, stop, retry.
My idea is to use message broker(kafka, rabbitmq, ...) to pass job request from batch service to other services. But I am not thinking of a solution to stop or save the log of jobs on the batch service.
Is this idea feasible and if so can you give me some advice on deployment technologies (We are deploying using spring boot at the moment).
Thanks for taking the time to read ^^.
Context
I'm in the process of drawing a solution to migrate a huge PL/SQL system to Java. The initial step is migrating some ETL jobs that:
Reads CSV, XML, (XLS, which is a new requirement) and Positional files from several ftp / sftp sources
Process the files according to rules stored in the database and write the results to a database table.
Currently this is done by several store procedures and Jobs.
My company is open to suggestions (if it can run in GlassFish 4 and share its logging and connection pool mechanisms, as well as the admin console, it is a plus).
I've done a little bit of research and the following options caught my eye:
Java EE 7 Batch Processing, sounds simple and particularly well fitted for GlassFish 4.
Spring Batch somewhat more mature and very similar to the Java EE 7 standard (which was probably based on it).
Apache Camel, sounds powerful and would spare us from a lot of fiddling with libraries such a Apache POI, but it also looks somewhat complex. Also I'm not sure if it is the best fit for the job (ETL over huge files).
Cook everything by myself. I could create a Application Client to run a Quartz / Spring Scheduler or even EJB Timers
While I'm still open to suggestions (recommendations would be nice), the best fit so far seems to be Java EE 7 Batch Processing.
One more thing, the infrastructure team have a solution to move files from every ftp source to a local directory, so FTP is really not an issue.
Problem
I've read several tutorials about Java EE Batch Processing and, in all of them, some kind of Servlet or EJB Timer is responsible for starting the Jobs:
JobOperator jobOperator = BatchRuntime.getJobOperator();
jobOperator.start("job", properties);
I could easily upload a web / ejb project and keep pooling for changes. But I was thinking about a push model:
Application client console application
Main class watches directories for new files
When there is a new file it would start a new job.
My doubts are:
Is this strategy possible/ advisable?
Will I need a JMS queue or some kind of producer / consumer strategy in the middle or should I just call jobOperator.start for every file and trust the batch processing layer to manage the application resources? In other words, if a thousand files are delivery to my folder at once and I call jobOperator.start a thousand times, will GlassFish 4 do some kind of smart enqueuing or should I create some kind of Gate so that no more than n jobs run simultaneously?
I've already implemented a project with Batch Processing in Wildfly (Jboss AS). I'm not familiar with configuration details on Glassfish (not using it anymore because the've dropped enterprise support), however I can give you some insights and guidelines according to my experience. Also, please note that Spring and the Batch spec. on EE 7 are quite similar, and your decision to use either technology must depend on "what else" you want to achieve with your application besides the batching. Do you want an easily maintained web interface? Do you want to depelop a REST api?, etc.
The ETL jobs you're describing fit pefeclty with the steps and chunks model in the EE 7 spec, so If you've already tried to develop some tests, you may have noticed that you still need to code the file readers and mappers for each file specification. Your reading sources are quite standard, and you will easily find a library to read/stream them and process their data.
The project I've implemented is quite simple. Customers uplodad files that need to be processed in order to feed a data warehouse. This service is on the "cloud". Files have a defined spec and must be in CSV format. Most processing results are dimentional "Upserts" and fact "erasing prior inserting". The user has a Web interface on which files and batch processing metadata must be shown (processing state, dates, rejected items, etc.). Because it is a cloud service, the files must not reside locally on each server (using S3).
So the first thing to design are the chunk steps. I didn't want to have an implementation for each file spec., So what I did is to design a "fit all cases" implemetation that process files according to the metadata contained in them and also the job configuration itself. This is the easy part. The second thing to think about is the processing and metadata administration. Here, I developed a REST api and a Web interface that uses it. After all this, Will it scale? Wilfly has thread configuration parameters for the Batch Processing, and you can increase or decrease the thread availability for the JobOperator. Jobs are not submitted if there are not enough threads available. So what happends to those requests? Well, they can reside on memory, a backed up stateful session can be developed, you can definitely implement MQ listener of queued processing requests. What I did was much simpler. The company doesn't have the resources to maintain a cluster, so whe did an elastic configuration that will expand accoding to cpu consumption and requests volume. So far, the application has processed 10 TB of data, from 15 customers, and at max request/processing peak, 3 elastic instances have fired up.
A file listener is an interesting idea. You can listen to a directory and drop a processing request to a queue or inmediately to the BatchRuntime. It will depend on how you want to scale it, your needed response time, the available resources, etc.
Feel free to ask me anything.
Regards.
EDIT: forgot to mention. I don't really recommend using the Application client unless you've already got something deployed on your organization. The recent security constraints and java SE updates mechanism has made a real hassle to maintain those kind of deployments. Think web.
I would approach it this way.
My hammers for this use case would be the Java Watch Service, a Servlet, a JMS queue, and the Batch service.
First, the Watch Service is the Java 7 go to place to handle the file system monitoring.
I would write a Watch Service implementation, and I would run it on a thread.
Where does the thread run you ask?
Officially, you should probably be using JCA for this. But, JCA is flat out a pain to work with, underutilized, thus under documented. There are solid examples, but it's simply not a common technology in the Java EE stack.
Another place is an asynchronous Session Bean invocation. There's nothing that suggests these can not be long lived invocations. You could stand up a #Singleton Session Bean, with #Startup, call the async method from a #PostConstruct method, and let it go. Then, in #PreDestroy signal the long running method to stop, so it can cleanly shut down. This should all be to spec, portable, and according to Hoyle.
The third place is to you a ServletContextListener, which is the pre-Java EE 6 go to place for tying code in to the life cycle of the application. Here, you would create the thread yourself in the contextInitialized method, and then tear it down in the contextDestroyed method.
Creating threads here is "less defined", but I've done it for years and never had a problem.
Now that you have your service running, the service (IMHO), will do two things.
1) It'll sense when a new file has arrived in the directory, and when it does, it will MOVE (mv, rename) the file to a parallel "processing" directory. The reason is that this tells you that a file has moved from incoming to processing, that the file is a work in progress. It's obvious from a directory listing, regardless of what the backend thinks it's doing. Remember, the system can go down mid way through a file.
2) Once moved, post the file name, and any other meta data on to a JMS queue and have an MDB do tool up the batch job.
Why add the JMS queue? It brings a couple of features to the party. First, it's great way to get stuff "from outside" the happy transactional context that EJB likes, to inside one. Second, it's transactional. You can, depending on your ETL use case, have the MDB directly process the job. And by doing so, you simply do not acknowledge the message from the queue until the processing is done (and the file is deleted or moved from the "processing" directory). In an ideal world, the message queue has messages matching the files in the processing directory. When the processing is done, the method returns, the message fetch "commits", and you're done. If the system crashes, this will restart from the beginning automatically (since the message is still on the queue and was never removed).
The MDB, by configuring it's instances, can gate the number of simultaneous jobs also. Configure 10 instances, only 10 files can be processed at the same time. But this can be a little too simple, too coarse. There's no priority for example (first come first serve). But it might work for you.
But either way, the MDB is a great gateway into system, since each one starts with it's own little bit of transactional context. Unlike the long running servlet thread or the long running async thread. The servlet thread has a questionable (if any) transactional status, the long running thread inherits it's state from the #Startup method, and retains it for it's life time. The MDB gets a new one each time. Much of this can be shenaniganed away calling methods with new transactions.
But I like the demarcation of the MDB. Even if it's entire task is to create the Batch entry for a file name, the MDB is a good gatekeeper.
And that's pretty much it.
The key parts are being a good citizen and tearing down your thread properly tied to the lifecycle of the application, understanding your transactional state at the various components, and understanding how all the moving parts fit together.
If you use the #Startup technique, make sure you invoke your async method via injecting another instance of your session bean. Otherwise the invocation will be a local call, and not asynchronous. You'll stare at it wondering why your server is hanging and not starting up. All of the EJB annotations only work when invoked through an injected or looked up proxy.
Have fun, share and enjoy.
Addenda to the question:
There's really no value to having an external process manage the watch service. One tied to the lifecycle of the server is easier to maintain. Two things come to mind. If the server is down, file will simply stack up in the file system until the server is started again, so you don't lose data. If you have an external service, then you either have it sending messages to a dead server, or you have to stage and manage the JMS server separate from the app server. In that case you now have 3 processes to manage: Watch service, JMS Server, and app server, rather than just the app server.
I agree with the other poster that should you decide to go with an external service anyway, a simple Java SE app posting simple messages to a JAX-RS REST service on the server, or even a trivial Servlet is much, MUCH more easy to maintain, stage and deploy than an app client. If you do it that way, you could write the watch service in something completely different.
But since the server (ostensibly) has direct access to the file system with the file, there's really no motivation to break this service outside of the container. Put the whole kit in to an EAR and have at it. Just flat easier management.
So, I have a web client and an EJB timer, deployed seperately.
The workflow is as follows:
1) User accesses client.
2) User requests an action to take place which is known to be long-running, so we write the request to run this process in a database table.
3) TimerOne is checking this table every few seconds to see if there are any waiting tasks, so it finds the user's request and runs the task.
My problem is that in some environments in which our application is run, we are taking advantage of server clustering. When we do this, both the client and the EJB timer are deployed to each server in the cluster.
It is okay for the client to be deployed to multiple servers, as it helps with workload; however, having the timer run on multiple servers is an issue. When the user requests for a long-running task to be run, both timers grab the task at the same time from the database and start running it. As the long-running jobs usually write to the database, this scenario leads to collisions, among other issues.
My goal is to be able to deploy my EJB timer to both servers, but for there to be some state maintained across the cluster which can be used by the timers to decide whether they should pick up the task or if one of the other instances has already picked it up.
I tried using the database for this and tried file storage, but these are either too slow, or I could not come up with a bullet-proof workflow for synchronization.
Does anyone know of a good way to handle this problem? Is it even possible?
The solution should be able to run on a clustered WebLogic domain, a non-clustered WebLogic domain, a clustered Glassfish domain, and a non-clustered Glassfish domain.
I am open to changing the way this is done, if there is another, more elegent solution.
Thanks for any ideas!
Yes this is possible with clustered timers or a Weblogic Singleton Service (and has been asked a number of times here already). See the following:
Clustered timers:
https://blogs.oracle.com/muraliveligeti/entry/ejb_timer_ejb
http://shaoxiongyang.blogspot.com/2010/10/how-to-use-ejb-3-timer-in-weblogic-10.html
http://java.sys-con.com/node/43944
Singleton Services:
https://blogs.oracle.com/jamesbayer/entry/a_simple_job_scheduler_example
http://developsimpler.blogspot.com/2012/03/weblogic-clusters-and-singleton-service.html
I am open to changing the way this is done, if there is another, more elegent solution.
I know that your question is about a EJB Timer, but take in mind the following:
In my opinion, you have a requirement that need the advantage of asynchronous processing.
In earlier Java EE versions, one of the alternatives to achieve this kind of requirement was to use JMS which allows you to send a message that is processed later for a business layer component. Other possibility was the one that you have described, that required the use of EJB Timer. I think both cases were a workaround that filled a gap in the EE specification.
Since Java EE 6, you can define asynchronous services which allows you make asynchronous calls, avoiding to use features were thought for other purposes.
The system contains an admin console and a cluster of working servers. Application state is stored in the database. From admin console user can add new jobs, monitor running jobs etc. Working servers fetch the job from db and process it.
Now, some configuration is stored in database, too. Configurations are also loaded on each working server and most of it is cached, as configuration is not changed frequently.
Admin is able to change configuration (from admin console). The change is stored in database. What would be the best way to push changes to working servers?
My ideas so far:
add triggers on configuration table on update/delete/insert and update the timestamp in some aux table. Each working server before accessing the cache checks this aux table for change.
CONS: Still accessing db.
send request from admin console to all working server that configuration is changed and that has to be read from db on next call.
CONS: introduces http communication between admin and servers - new layer that didn't exist so far - and its questionable how reliable that would be.
Any experience on this subject?
First approach seems more like a quick hack. Checking aux table timestamps almost defeats the purpose of a cache.
Second option seems to be the good one. This could be implemented as a simple task in their task queue to update their own configuration caches.
The main issue changing configuration of multiple services is their dependencies.
If parent service would start running with incompatible configuration to it's child services you might get a crash or undefined behaviour. To avoid this the synchronisation must be implemented.
One way is let parent service to update it's configuration and then issue configuration update commands to child services. After all child services are updated, parent would resume processing. Advantage of this approach would be that a simple management console could instruct only parent services about the configuration changes.
Other way is let management console handle dependent services. It would send a command to parent services to pause execution, update config and wait for resume command. In a mean time it would update all child services and instruct parents to resume. This way service dependencies would be more flexible and their configuration would be decoupled from their implementation. This would require a more advanced administration tool.
I currently have a tomcat container -- servlet running on it listening for requests. I need the result of an HTTP request to be a submission to a job queue which will then be processed asynchronously. I want each "job" to be persisted in a row in a DB for tracking and for recovery in case of failure. I've been doing a lot of reading. Here are my options (note I have to use open-source stuff for everything).
1) JMS -- use ActiveMQ (but who is the consumer of the job in this case another servlet?)
2) Have my request create a row in the DB. Have a seperate servlet inside my Tomcat container that always runs -- it Uses Quartz Scheduler or utilities provided in java.util.concurrent to continously process the rows as jobs (uses thread pooling).
I am leaning towards the latter because looking at the JMS documentation gives me a headache and while I know its a more robust solution I need to implement this relatively quickly. I'm not anticipating huge amounts of load in the early days of deploying this server in any case.
A lot of people say Spring might be good for either 1 or 2. However I've never used Spring and I wouldn't even know how to start using it to solve this problem. Any pointers on how to dive in without having to re-write my entire project would be useful.
Otherwise if you could weigh in on option 1 or 2 that would also be useful.
Clarification: The asynchronous process would be to screen scrape a third-party web site, and send a message notification to the original requester. The third-party web site is a bit flaky and slow and thats why it will be handled as an asynchronous process (several retry attempts built in). I will also be pulling files from that site and storing them in S3.
Your Quartz Job doesn't need to be a Servlet! You can persist incoming Jobs in the DB and have Quartz started when your main Servlet starts up. The Quartz Job can be a simple POJO and check the DB for any jobs periodically.
However, I would suggest to take a look at Spring. It's not hard to learn and easy to setup within Tomcat. You can find a lot of good information in the Spring reference documentation. It has Quartz integration, which is much easier than doing it manually.
A suitable solution which will not require you to do a lot of design and programming is to create the object you will need later in the servlet, and serialize it to a byte array. Then put that in a BLOB field in the database and be done with it.
Then your processing thread can just read the contents, deserialize it and work with the ressurrected object.
But, you may get better answers by describing what you need your system to actually DO :)