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What is "worker" design pattern?
It could be that you are after a worker thread pattern, where you use a queue to schedule tasks that you want to be processed "offline" by a worker thread.
Some solutions will use a pool of worker threads instead of single thread to achieve performance gains by utilising paralelisation.
Something like MapReduce comes to mind. Where multiple tasks can be performed in parallel on worker nodes.
Edit: As #larsmans mentioned, this is known as the Master/Worker pattern.
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In a schedular ,which is running on all host at a time, right now I am using xdmp:lock-acquire to lock the collection, so that ,cts:uris will not pick the duplicate uris, but due to this scheduler is running in sequence .Is there any other alternative ,so that I avoid this lock, so that all run in parallel.
It's a bit unclear what you are trying to do, but it sounds like you have documents in the database that you are processing using a scheduled task, that runs on all hosts. Your existing query makes it possible for two tasks to attempt to process the same document.
The easiest would be to generate a list of forests on the host that the task is running on using xdmp:host-forests, and passing that list into cts:uris as $forest-ids
$forest-ids A sequence of IDs of forests to which the search will be
constrained. An empty sequence means to search all forests in the
database. The default is ().
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I have realized that most of the problems that I solve on a day to day basis are done via two programming techniques: iteration or recursion.
Are there other techniques out there? Any book recommendations or online references?
the programming techniques that you use to solve the problems can be divided into types of algorithms (not into the loop or technique they use in there program, like you mentioned). some of the methods are..
1. Divide and conquer
2. greedy
3. dynamic programming
you can refer this link to read more..
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What is the measurement of the application's reliability as a non-functional requirement?
You cannot measure reliability as it is linked to a bunch of different factors. Uptime can be one of them, for web apps. For other software, it can be something like the prevention of data loss under any circumstances.
You'll have to define it more exactly by breaking it down into your detailed expectations, then you can quantify values to measure against.
It is a core problem with nonfunctional requirements that you cannot measure them easily. You'll have to work around that as described above.
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In chubby the process of each log that write to db is one instance of the paxos process, and this instance may have many proposers, so it will have a master selected process.
why it has many proposers?
Having a single leader (aka a "Distinguished Proposer") is an optimization for Paxos. The whole point of Paxos is to decide a value when there are multiple proposers proposing different things.
The whole point of having multiple proposers is in case the "Distinguished Proposer" fails; something has to pick up that new role. Paxos, when it decides a value, implicitly decides between proposers.
As in your other question, I suggest looking at the other Paxos questions, perhaps read Paxos Made Simple.
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Is there anyway to monitor running Hive processes and ensure that they are indeed working in parallel?
I have setup an experimental Linux cluster (4 machines) and would like to understand the underlying processes.
top and ps don't give me too much info.
Hive query is divided into several MR called sql_text-stage 1, sql_text-stage-2 etc.
You can enter UI of your cluster's JobTracker web UI on
job_tracker_adress:50030
There you will see hive jobs and their progress.
For each job there will be list of tasks and for each task you can see on which nodes they are running, and their basic statistics