Can anyone point me in the direction of some documentation (or provide the information here) about the following tables, created by JBoss 5.1.0 when it starts up?
I know what they are for at a high level, and know why they are there, but I could do with some lower-level documentation about each table's purpose.
The tables are:
hilosequences
timers
jbm_counter
jbm_dual
jbm_id_cache
jbm_msg
jbm_msg_ref
jbm_postoffice
jbm_role
jbm_tx
jbm_user
I know that the first two are associated with uuid-key-generator and the EJB Timer Service respectively, while the rest are associated with JBoss Messaging. What I want to know is something along the lines of "jmg_msg stores each message when it is created...", that kind of thing.
Thanks
Rich
ps: I originally asked this question at ServerFault but didn't get a response
hilosequences is used by the uuid-key-generator.sar which provides the jboss:service=KeyGeneratorFactory,type=HiLo service, which basically allows you to have UUID keys consistently across all aplications of an instance
timers is used by ejb2-timer-service.xml, a legacy timer service
and the jbm* tables are used by JBoss Messaging (JMS) to store messages, queues, etc, which is why it's strongly recommended to change the DB from the default (Hypersonic) to a production ready one
Related
After reading into the Dapr docs, I'm left with a few questions regarding the behavior of input bindings. From what I understand, it's not possible to tell Dapr that a specific input binding should only trigger a specific endpoint of one particular app in a declarative sense. Rather, you create an input binding and define its endpoint (e.g. 'checkout'), and then dapr will test all apps for that endpoint. Correct?
If so then, tbh, I don't understand this design decision. For example, if the input binding is coming from a queue (e.g. SQS), then each item should only be processed once. But then, if multiple apps are automatically configured to process items from the queue simply because they have the same endpoint, how would you guarantee that the correct one does the job? Does this behavior change if the apps are in the same vs. differing namespaces?
In this use-case, this set-up is a big bummer since it means you cannot develop your apps independently (or else you risk running into naming collisions).
Hopefully I've missed a few details, so please correct me if I'm wrong. Thank you!
Context
Greetings,
One day I randomly found RethinkDB and I was really fascinated by the whole real-time changes thing. In order to learn how to use this tool I quickly spinned up a container running RethinkDB and i started making a small project. I wanted to make something very simple therefore i thought about creating a service in which speakers can create room and the audience can ask questions. Other users can upvote questions in order to let the speaker know which one are the best. Obviously this project has a lot of realtime needs that i believe are best satisfied by using RethinkDB.
Design
I wanted to use a vary specific set of tools for this. The backend would be made in Laravel Lumen, the frontend in Vue.JS and the database of course would be RethinkDB.
The problem
RethinkDB as it seems is not designed to be exposed to the end user directly despite the fact that no security concern exists.
Assuming that the user only needs to see the questions and the upvoted in real time, no write permissions are needed and if a user changed the room ID nothing bad will happen since the rooms are all publicly accessible.
Therefore something is needed in order to await data updates and push it through a socket to the client (socket.io for example or pusher).
Given the fact that the backend is written in PHP i cannot tell Lumen to stay awake and wait for data updates. From what i have seen from the online tutorials a secondary system should be used that should listen for changes and then push them. (lets say a node.js service for example)
This is understandable however i strongly believe that this way of transferring the data to the user is inefficient and it defeats the purpose of RethinkDB.
If I have to send the action from the client's computer (user asks a question), save it to the database, have a script that listens for changes, then push the changes to socket.io and finally have the client (vue.js) act when a new event arrives, what is the point of having a real-time database in the first place?
I could avoid all this headache simply by having the Lumen app push the event directly to socket.io and user any other database system instead.
I really cant understand the point of all this. I am not experienced with no-sql databases by any means but i really want to experiment with them.
Thank you.
This is understandable however i strongly believe that this way of transferring the data to the user is inefficient and it defeats the purpose of RethinkDB.
RethinkDB has no built in mechanism to transfer data to end-users. It has no access control (in the conventional sense) as well. The common way, like you said, is to spin up one / multiple node instance(s) running socket.io. On each instance you can listen on your RethinkDB change streams and use socket.io's broadcast functionality. This would be a common way, but as RethinkDB's streams are pretty optimized, you could also open a change stream for every incoming socket.io connection.
I'd like to develop a bunch of SaaS-Applications in Java and I'm not sure wat is the best way to go.
Each Application will have a WAR containing the Webservice and will have at least one Worker-WAR, which is a Thread waiting for new Tasks in the DB to come up and then working off this task. This worker contains the intelligence of the application and uses a lot of cpu. The Webservice gives Users the possibility to add new tasks and other stuff ...
Resource Limitations
The infrastructure must ensure the following:
The Webservice must always get a certain amount of cpu time to be able to respond to the user. So the hungry Worker must not get all cpu time for its working.
Each Tenant has its own worker and they must not interfere with each other as it must be not possible to block the whole system (and all tenants) with a single task.
Resource Sharing
It would be nice to be able to share the resources but always ensure that in extreme situations every worker and webservice gets the required minimum.
Versioning
As new Versions of a application are released each tenant must have the possibility to initiate a update on its own when he adapted to the API-Changes. Furthermore a tenant must be able to keep more than one application-endpoint (lets call them channels) to have a production channel and a beta-channel. In the Beta-Channel the tenant can test againts new versions and when he feels comfortable with the new version he can update his production channel.
User-Management
All applications of a tenant must share a user-Database and have the same way to authenticate.
Environment
I want to use Java EE 7. I would enjoy using Wildfly.
Question
What is the best infrastructure to approach these aims? I want to host this on my own servers.
What I already found
I understand that you cannot limit CPU-usage in a jvm. So the Workers must have their own jvms.
I looked at PaaS-Providers like OpenShift Origin, but it seems that they encourage you to run a application-server per tenant, per application which sounds to me as a resource-eater.
Is there no way to have one Wildfly running and limit the amount cpu-usage per tenant and app?
Thank You
Lukas
our devices (microscopes with cameras) produce images and additional information to each image.
Now a middleware supplies wants to connect these devices to lab automation system. They have to acquire the data and we have to provide it. An astonishing thing for me was their interface suggestion - a very cryptical token separated format (ASTM E1394-97). Unfortunatelly, they even can't accomodate images in their protocol, and are aiming to get file-paths.
I thought it is not the up-to date approach. While lookink for alternatives, I saw CoachDB.
So, my idea was, our devices would import data including images in CoachDB and they could get the data. It seems even, that using mustache, we could produce the format they want (ascii-text) and placing URLs as image references instead of path's.
My question is, did someone applied CoachDB for such a use case already? It seems to be a little-bit misuse of CoachDB, as the main intention is interface not data storage. Another point disturbing me is, that the inventor of CoachDB went to other project Coachbase. Could it mean lack of support for CoachDB in the future?
Thank you very much for any insights and suggestions!
It's ok use-case and actually we're using CouchDB in such way - as proxing middleware between medical laboratory analyzers and LIS. Some of them publish images or pdf data on shared folders and we'd just loading them into related document as attachments.
More over you'd like to know, CouchDB is able to serve external processes (aka os_daemons) and take care about their lifespan: restarting if someone had terminated and starting right after you update config options through HTTP interface. This helps to setup ASTM client and server processes since this protocol is different from HTTP (which is native for CouchDB) which communicates with devices and creates documents as regular CouchDB clients. In same way you may setup daemons to monitor shared folders for specific files. And all this is just CouchDB with few "low bounded" plugins.
I've recently discovered the lift framework and have read that it's stateful.
Therefore, if I had a high-traffic site running on Lift - say something that was running a chat application that required users to be logged in - and I wanted to upgrade my app, would doing so kick everyone out of chat and make them have to log in again?
None of the previous answers are correct. Many of the artefacts held within the LiftSession are non-serilizable, so cant be stuffed into a database. You have two options for doing rollig upgrades of stateful applications:
1) Session bleeding. Basically you ween one of the deployments sessions away until their sessions have ended or X duration passes and then you remove the app from production whilst automatically rerouting traffic to another instance of Lift. Google around for rolling upgrades using HAProxy as this should help you from the cluster perspective.
2) If your state is fairly trivial (mostly primitive-style types: ints, strings etc) then you could think about using ContainerVar/MigratableSession and clustering the state using terracotta or similar. This comes with a range of limits though because it then uses the HTTPSession rather than LiftSession.
You might want to checkout chapter 15 of Lift in Action which details that latter solution in a fair amount of detail.
If you keep your state in memory and redeploy the web application, that state will be lost. You could save it to a database or a file before redeploying though and read it back from there.