#jobs #tasks #cluster #automate #experiments

bin+lib expjobserver

This is a job server and client for running many experiments across many test platforms. In some sense, it is like a simple cluster manager.

4 releases (breaking)

new 0.7.0 Sep 14, 2020
0.6.0 Aug 18, 2020
0.4.0 Jul 2, 2020
0.3.0 Jun 26, 2020

#74 in Science

28 downloads per month

MIT/Apache

165KB
3.5K SLoC

expjobserver

This is a job server and client for running many experiments across many test machines. In some sense, it is like a simple cluster manager.

The high-level idea is that you have a server (the expjobserver) that runs on your machine (some machine that is always on, like a desktop), perhaps in a screen session or something. You have a bunch of experiments that you want to run from some driver application or script. You also have a bunch of machines, possibly of different types, where you want to run jobs. expjobserver schedules those jobs to run on those machines and copies the results back to the host machine (the one running the server). One interracts with the server using the stateless CLI client.

Additionally, expjobserver supports the following:

  • An awesome CLI client, with the ability to generate shell completion scripts.
  • Machine classes: similar machines are added to the same class, and jobs are scheduled to run on any machine in the class.
  • Machine setup: the expjobserver can run a sequence of setup machines and automatically add machines to its class when finished.
  • Job matrices: Run jobs with different combinations of parameters.
  • Automatically copies results back to the host, as long as the experiment driver outputs a line to stdout with format RESULTS: <OUTPUT FILENAME>.
  • Good server logging.
  • Tries to be a bit resilient to failures, crashes, and mismatching server/client version by using protobufs to save server history and communicate with client"

Prerequisites

  • rust 1.37+

Installing

cargo install expjobserver

This will install both the client (j) and server (expjobserver).

Building

These commands both build client and server:

# Debug
cargo build

# Release
cargo build --release

In practice, it doesn't matter, as I've disable optimizations and added debuginfo for the release build too. The reason is that performance doesn't matter that much here (and the server isn't performance-optimized anyway), whereas debuggability is very helpful.

Usage

Running the server

expjobserver \
  /path/to/experiment/driver \
  /path/to/logs/ \
  /path/to/log4rs/config.yaml

The first time you run it, you will need to pass the --allow_snap_fail flag, which allows overwriting server history. The default is to fail and exit if loading history fails. It is intended to give a little bit of safety so that if you restart in a weird configuration it won't wipe out your server's history, which can be annoying.

You may want to run the server in a screen or tmux session. That way, you can detach and leave it running in the background. You can always check the logs by either attaching again or looking at /path/to/logs from the command, where the server will dump debug logs.

The server uses the log4rs library for logging. It is highly configurable. example.log.yml is a reasonable config that I use. To use it, point the server to it using the second argument in the command.

Running the client

j --help

There are a lot of subcommands. They are well-documented by the CLI usage message.

Examples

This is mostly intended as a quick tour of what you can do (for the client side). It's not comprehensive. Read the usage message (--help) for more info on all the things you can do. There are a lot of nifty features!

Adding machines to the pool

First, let's list the machines in the pool.

$ j machine ls


Currently, there are none. Let's add some. If we have machine already set up, we can use j machine add, but we can also have a machine run a setup script and be automatically added to the pool afterwards.

$ j machine setup --class foo -m my.machine.foo.com:22 -- "setup-the-thing {MACHINE} --flag --blah" "another-setup-command"
Server response: Jiresp(
    JobIdResp {
        jid: 0,
    },
)

Here {MACHINE} is replaced automatically by my.machine.foo.com:22. You can also use other variables (see the j var commands). This can help in a few ways:

  • {MACHINE} allows you to use the same command for multiple machines (you can pass -m multiple times).
  • You can use other variables to minimize the number of secrets that end up in your bash history (e.g. if you need a github token or something).

At this point, the machine my.machine.foo.com:22 will start running the listed commands in the given order. Assuming that they all succeed, the machine will be added to the foo class in the pool and will be ready to run any jobs that request a foo-class machine.

Listing and Enqueuing Jobs

The jid: 0 in the server response above is the job ID of the setup task. We can see the currently running tasks, including setup tasks.

$ j job ls
 Job   Status  Class  Command                                  Machine                Output
   0  Running  foo    setup-the-thing {MACHINE} --flag --blah  my.machine.foo.com:22

Currently, the only thing running so far is the setup task we started above.

We can queue up some other jobs for foo-class machines to run on it when ready:

$ j job add foo "bar --the --foo baz" /path/to/results/dir -x 3
Server response: Jiresp(
    JobIdResp {
        jid: 1,
    },
)
Server response: Jiresp(
    JobIdResp {
        jid: 2,
    },
)
Server response: Jiresp(
    JobIdResp {
        jid: 3,
    },
)

Here we enqueue 3 identical tasks to run on the first available foo machine. The jobs run in the enqueued order.

$ j job ls
 Job   Status  Class  Command                                  Machine                Output
   0     Done  foo    setup-the-thing {MACHINE} --flag --blah  my.machine.foo.com:22
   1  Running  foo    bar --the --foo baz                      my.machine.foo.com:22
   2  Waiting  foo    bar --the --foo baz
   3  Waiting  foo    bar --the --foo baz

We can look at the job's stdout (using tail):

j job log -t 1

where 1 is the job ID from the table above for the running task. You can also look at the log of completed tasks or get the path of the log file:

$ j job log -l 0                # look at the log of 0 with `less`
...

$ j job log 0                   # path to the log file
/some/path/0-setup-the-thing_my.machine.foo.com:22_--flag_--blah

Job Matrices

Sometimes you want to run a bunch of similar commands with slight variations (e.g. to see the effect of varying a parameter).

You can do this with j job matrix:

j job matrix add foo "my-experiment-cmd --param0 {I} --param1 {J} --param2 {K}" \
    /path/to/copy/results/ I=1,2,3,4 J=linear,quadratic,exotic K=banana,rockingchair,airplane

This command will enqueue 4x3x3 = 36 jobs, which you can see with j job ls or j job matrix stat.

Moreover, you can dump a CSV of the matrix and any results paths using j job matrix csv.

More

Take a look at the --help message for the various commands and subcommand to learn about even more goodies.

Dependencies

~5–7MB
~104K SLoC