Following text requires knowledge of basic terminology used by ReCodEx. Please, check [separate page](https://github.com/ReCodEx/GlobalWiki/wiki/Terminology).
Job is a set/list of tasks (it is generally a set, but order of tasks have some meaning). These tasks may have dependencies (arbitrary number), which needs to be observed. When recodex-worker processes job, it creates a task graph, where tasks are vertices and dependencies are edges (A -> B means that the task A is on the dependency list of task B) and creates its linear ordering. The graph must be acyclic (otherwise linear ordering will not exist) and the recodex-worker attempts to execute maximal number of tasks possible. Tasks without dependencies can be executed directly, other tasks are executed when all their dependencies have been successfully completed.
Tasks are executed sequentially -- by the linear ordering of the task graph. Parallel tasks (tasks, which are not directly dependent and thus their linear ordering may be arbitrary) are ordered first by their priority (higher number => higher priority) and second by their order in the configuration file. Priority is important for specifying evaluation flow. See sample picture for better understanding.
Each task has a unique ID (alphanum string like _CompileA_, _RunAA_, or _JudgeAB_ in the picture). These IDs are used to identify tasks (for dependency references, in the log, ...). Numbers in bottom right corner are priorities of each task. Higher number is greater priority. It means, that if task _RunAA_ is done, next must be _JudgeAA_ and not _RunAB_ (that will be also valid linear ordering, but _RunAB_ has lower priority).
- **Execute external process** (optionally inside Isolate). Linux default will be mandatory in Isolate, this option is here because of Windows.
- **Perform internal operation**. External processes are meant for compilation, testing, or execution of external judges. Internal operations comprise commands, which are typically related to file/directory maintenance and other evaluation management stuff. Few important examples:
Even though the internal operations may be handled by external executables (`mv`, `tar`, `pkzip`, `wget`, ...), it might be better to keep them inside the recodex-worker as it would simplify these operations and their portability among platforms. Furthermore, it is quite easy to implement them using common libraries (e.g., _zlib_, _curl_).
These tasks are typically executed in isolate (with given parameters) and the recodex-worker waits until they finish. The exit code determines, whether the task succeeded (0) or failed (anything else). A task may be marked as essential; in such case, failure will immediately cause termination of the whole job.
- **stdout** and **stderr** - can be individually redirected to a file or discarded. If this output options are specified, than it is possible to upload output files with results by copying them in result directory.
- **limits** - task have time and memory limits; if these limits are exceeded, the task also fails.
The task results (exit code, time, and memory consumption, etc.) are saved into result yaml file and eventually sent back to frontend application to address which was specified on input.
For each job execution unique directory structure is created. Job is not restricted to specified directories (tasks can do whatever is allowed on system), but it is advised to use them inside job. In recodex-worker configuration one can specify worker default directory, this is base of every file which is produced by recodex-worker.
Inside this directory temporary files for job execution are created:
- **${DEFAULT}/downloads/${WORKER_ID}/${JOB_ID}** - where the downloaded archive is saved
- **${DEFAULT}/submission/${WORKER_ID}/${JOB_ID}** - decompressed submission is stored here
- **${DEFAULT}/eval/${WORKER_ID}/${JOB_ID}** - this directory is accessible in job configuration using variables and all execution should happen here
- **${DEFAULT}/temp/${WORKER_ID}/${JOB_ID}** - directory where all sort of temporary files can be stored
- **${DEFAULT}/results/${WORKER_ID}/${JOB_ID}** - again accessible directory from job configuration which is used to store all files which will be upload on fileserver
Configuration of the job which is passed to worker is generated from two parts:
- **template** - Common template for similar kinds of tasks. Contains allmost all instructions - when fetch, move, rename files, run commands, judges, ..., task dependencies and priorities. This template can be shared by more problem assignments or every problem (probably in compiller class) can have different one.
This configuration example is written in YAML and serves only for demostration purposes. Therefore it is not working example which can be used in real traffic. Some items can be omitted and defaults will be used.
The job may have some input parameters (e.g., default config for Isolate, global parameters for the tested processes, ...). Similarly, the job has some structured results -- for each task (where applicable), it gathers exit code and consumed time and memory.
These parameters are stored in global, structured parameter space. I would suggest something that would map easily on JSON, for instance -- i.e., something that supports structures (named collections), arrays (ordered collections), and basic numeric and string values.
Input parameters have two sources, some defaults are present in the configuration of the worker, another set is provided in the configuration of the job. These sets are merged, job config has a priority.
Parameters are only read by the tasks (they can be used in task parameters). Some simple syntax needs to be used for evaluation of parameter expressions -- e.g., ("${params.tests[1].memoryLimit}"). _Parameters should be stored in worker's global namespace. Task configuration can make references to this structure. Validity should be checked before executing first task from the job. In this structure is only writable section "results" - here are written achieved memory and time limits of each task. Whole structure is send to WebApp with all logs._
_**TODO:** analysis required -- how complex expressions do we really need_
There is one general (mandatory) log, where the job progress is logged. Each row corresponds to one task and it holds only the task name, task exit code (or some other indication whether the task ended OK or not), and optionally things like consumed memory and time.
Other logs (stored in log dir) can be created. They do not have to be declared in advance, but they are specified at each task (if its output is going to a log) and created once some task produces an output that goes to the log.
