In the installation tutorial, we ran a simple script that performed echo "howdy, your job launched successfully!" >> howdy.txt". Looking inside fw_test.yaml, you might have noticed that command defined within a ‘FireTask’ labeled ‘SubprocessTask’. A FireTask is a predefined job template; the SubprocessTask is a FireTask that runs an arbitrary shell script. In this section, we’ll demonstrate how to use and define FireTasks.
Note
In this tutorial, we will run examples on the central server for simplicity. One could just as easily run them on a FireWorker using the instructions from the installation tutorial.
You can run multiple tasks within the same FireWork. For example, the first step of your FireWork might write an input file that the second step processes. Let’s create a FireWork where the first step prints howdy.txt, and the second step counts the number of words in that file.
Navigate to the tasks tutorial directory:
cd <INSTALL_DIR>/fw_tutorials/firetask
Look inside the file fw_multi.yaml. You should see two FireTasks; the second one runs the wc -w command to count the number of characters in howdy.txt and exports the result to words.txt.
Run this multi-step FireWork on the central server:
launchpad_run.py initialize <TODAY'S DATE>
launchpad_run.py upsert_fw fw_multi.yaml
rocket_run.py
Tip
You can run all three of these commands on a single line by separating them with a semicolon. This will allow you to reset the database, insert a FW, and run it within a single command.
You should see two files written out to the system, howdy.txt and words.txt, confirming that you successfully ran a two-step job!
While running arbitrary shell scripts is nice, it’s not particularly well-organized. The command (echo), its arguments ("howdy, your job launched successfully!"), and its output (howdy.txt) are all intermingled within the same line. If we separated these components, it would be easier to do a data-parallel task where the same commands are run for multiple arguments. Let’s explore a better way to define our multi-step job:
Navigate to the tasks tutorial directory and remove any output from the previous step:
cd <INSTALL_DIR>/fw_tutorials/firetask
rm *.txt fw.json
Look inside the file fw_better_multi.yaml. You should see two FireTasks as before. However, this time, the text we are printing is separated into its own echo_text parameter. We just need to change the value of this parameter in order to perform the same commands (echo and wc) on different input data. Note also that the names of the input and output files are also clearly separated from the commands themselves within the FireWork specification.
Run the FireWork on the central server to confirm that this new formulation also works as intended:
launchpad_run.py initialize <TODAY'S DATE>
launchpad_run.py upsert_fw fw_better_multi.yaml
rocket_run.py
Because the SubprocessTask can run arbitrary shell scripts, it can in theory run any type of job and is an ‘all-encompassing’ FireTask. However, it is better to define your own custom FireTasks (job templates) for the codes you run. A custom FireTask can clarify the usage of your code and guard against unintended behavior by restricting the commands that can be executed. For example, let’s create a custom FireTask that adds one or more numbers using Python’s sum() function:
Navigate to the tasks tutorial directory and remove any output from the previous step:
cd <INSTALL_DIR>/fw_tutorials/firetask
rm *.txt fw.json
Look inside the file fw_adder.yaml for a new FireWork definition. This FireWork references a new FireTask, Addition Task, which is defined inside the file addition_task.py in the same directory.
Note
The main method in addition_task.py is not necessary to define a FireTask. However, it demonstrates how we created the fw_adder.yaml file.
Run the FireWork on the central server to confirm that the Addition Task works:
launchpad_run.py initialize <TODAY'S DATE>
launchpad_run.py upsert_fw fw_adder.yaml
rocket_run.py
With custom FireTasks, you can now go beyond running shell commands and execute arbitrary Python code templates. Furthermore, these templates can operate on dynamic input from the spec of the FireWork. For example, the Addition Task used the input_array from the spec to decide what numbers to add.
While one could construct an entire workflow by chaining together FireTasks within a single FireWork, this is often not ideal. For example, we might want to switch between different FireWorkers for different parts of the workflow depending on the computing requirements for each step. Or, we might have a restriction on walltime that necessitates breaking up the workflow into more atomic steps. Finally, we might want to employ complex branching logic or error-correction that would be cumbersome to employ within a single FireWork. The next step in the tutorial is to explore connecting together FireWorks into a true workflow.