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Peat

Peat is a command-line app to run another command-line app of your choice repeatedly with different parameters.

Peat can easily play the role of a sub-contractor in a WDL workflow to reduce scatter overhead: if you have 10,000 jobs, but don't want to run 10,000 machines, you can use WDL to run 200 machines and use Peat to then run 50 jobs on each machine. Peat makes it especially easy to make sure that each of the 10,000 jobs is actually run and only run once.

Table of Contents

Usage

USAGE:
    peat [FLAGS] [peat file]

FLAGS:
    -d, --dry-run       Parse and evaluate expressions, but do not actually run jobs.
    -r, --parse-only    Parse only. Do not evaluate expressions and do not run jobs.
    -h, --help          Prints help information
    -V, --version       Prints version information

ARGS:
    <peat file>

Get Peat

You can use one of our Docker images or build Peat yourself.

To get the Peat source code, clone the Peat repo:

git clone https://github.com/broadinstitute/peat.git
cd peat

To use Version 1.0.0:

git checkout v1.0.0

Peat is written in Rust. To compile, install the Rust toolchain, go to the peat directory and compile using:

cargo build --release

The peat binary will be in target/release/peat.

Hello, World!

To print "Hello, world!" to the console, without repetition, we can use the file example/hello.peat in the Peat repo:

Peat 1.0
===
echo "Hello, World!"

Each Peat file has divider - the first line that contains just ===. Everything before that is the head, which starts with the version line Peat 1.0, followed optionally by declarations, one per line (more later). Everything after the divider is the body, which is a template for an sh script. Here, the script just contains the line with the echo . So, Peat will write that line to a script and then use sh to execute it, printing the desired "Hello, world".

We run this with Peat:

peat example/hello.peat

This produces the following output:

Peat file uses version 1.0
Declarations: [none]
Now evaluating
Bindings: [empty]
Hello, World!
Process completed successfully.
Done!

Yay, we printed, "Hello, World".

Instead of using a file, Peat can also read from standard input, so we can, for example, run Peat by providing the code via a heredoc in sh:

peat << EOF
Peat 1.0
===
echo "Hello, World!"
EOF

The body can contain more than one line, by the way:

peat << EOF
Peat 1.0
===
echo "Hello, World!"
echo "How are you?"
echo "Hope all is wonderful!"
EOF

To do something more interesting, we need to declare variables.

Variables

Next, we look at examples/declarations.peat:

Peat 1.0
X=1
Y=2
Z=X
===
echo "Hello, declarations! X is <:X:>, Y is <:Y:> and Z is <:Z:>"

This declares three variables X, Y, and Z in the head using assignment (=).

In the body, there are placeholders marked with <: and :>, which will be filled by the values of variables, e.g. <:X:> will be filled by the value of X (i.e. 1) and so on.

Declared variables can be used in subsequent declarations, such as X has been used in the declaration of Z.

We run this with

peat examples/declarations.peat

and get:

Peat file uses version 1.0
Declarations: X = 1, Y = 2, Z = X
Now evaluating
Bindings: X = 1, Y = 2, Z = 1
Hello, declarations! X is 1, Y is 2 and Z is 1
Process completed successfully.
Done!

So far, Peat has only executed one script per invocation. Next, we will let Peat iterate.

Ranges and iterations

Next, let us look at examples/range.peat:

Peat 1.0
X = 1
Y <- 0 .. 3
===
echo "Hello, range! X is <:X:> and Y is <:Y:>"

Note how Y is followed not by an assignment operator (=), but by an iteration operator (<-).

The 0 .. 3 is a range from the lower bound (inclusive) until the upper bound (exclusive), so the range contains the numbers 0, 1 and 2. Y will be iterated over this range.

This time, peat prints:

Peat file uses version 1.0
Declarations: X = 1, Y <- 0 .. 3
Now evaluating
Bindings: X = 1, Y = 0
Hello, range! X is 1 and Y is 0
Process completed successfully.
Bindings: X = 1, Y = 1
Hello, range! X is 1 and Y is 1
Process completed successfully.
Bindings: X = 1, Y = 2
Hello, range! X is 1 and Y is 2
Process completed successfully.
Done!

We can see that the script is executed three times, with X always 1 and Y iterating over 0, 1 and 2.

We can also nest iterations, such as in nested.peat:

Peat 1.0
X <- 0 .. 5
Y <- 0 .. X
Z <- 0 .. Y
===
echo "Hello, nested! <:Z:> < <:Y:> < <:X:> < 5"

Here, we have three iterations. The latter ones will be nested inside the earlier ones, so we get:

Peat file uses version 1.0
Declarations: X <- 0 .. 5, Y <- 0 .. X, Z <- 0 .. Y
Now evaluating
Bindings: X = 2, Y = 1, Z = 0
Hello, nested! 0 < 1 < 2 < 5
Process completed successfully.
Bindings: X = 3, Y = 1, Z = 0
Hello, nested! 0 < 1 < 3 < 5
Process completed successfully.
Bindings: X = 3, Y = 2, Z = 0
Hello, nested! 0 < 2 < 3 < 5
Process completed successfully.
Bindings: X = 3, Y = 2, Z = 1
Hello, nested! 1 < 2 < 3 < 5
Process completed successfully.
Bindings: X = 4, Y = 1, Z = 0
Hello, nested! 0 < 1 < 4 < 5
Process completed successfully.
Bindings: X = 4, Y = 2, Z = 0
Hello, nested! 0 < 2 < 4 < 5
Process completed successfully.
Bindings: X = 4, Y = 2, Z = 1
Hello, nested! 1 < 2 < 4 < 5
Process completed successfully.
Bindings: X = 4, Y = 3, Z = 0
Hello, nested! 0 < 3 < 4 < 5
Process completed successfully.
Bindings: X = 4, Y = 3, Z = 1
Hello, nested! 1 < 3 < 4 < 5
Process completed successfully.
Bindings: X = 4, Y = 3, Z = 2
Hello, nested! 2 < 3 < 4 < 5
Process completed successfully.
Done!

One may wonder why in the output, X does not start at 0? Actually, X does start at 0, but for X=0, the range for Y is empty. Likewise, for X=1, Y can only be Y=0, and then the range for Z is empty. To get a non-empty range for Z, X needs to be at least 2.

We could easily tell Peat to iterate over 10,000 jobs in one call.

If that is too much for one call, we will see how to distribute the jobs into groups in the next sections.

Why distribute jobs into groups?

Peat can help distribute jobs.

Let's say we have 10,000 jobs and running them on a single machine would take too long.

We could use the scatter feature in WDL to distribute them over 10,000 machines, but that would be a large overhead, because we have to start up 10,000 machines, pull the Docker image 10,000 times, and copy the input files from storage to local disk 10,000 times.

The only reasonable solution might be to divide the jobs into groups. For example, we could use scatter in WDL to fan out into 200 branches, which means 200 machines, and then run 50 jobs on each machine.

In principle, this is easy. We could write a shell script with a loop. In practice, it is awkward and easy to get wrong, especially if we decide at some later point to change the number of jobs, or the number of machines.

Peat has been designed to make this as easy as possible and blend well with WDL. The next section explains, how.

Grouping ranges and picking a group

The next example divides a range into groups and then picks a group. It is examples/pick1.peat:

Peat 1.0
I <- 0 .. 10 / 0 .. 3 $ 1
===
echo "This is job <:I:> of 10 jobs, part of group 1 of 3 groups."

This gives the following output:

Peat file uses version 1.0
Declarations: I <- 0 .. 10 / 0 .. 3 $ 1
Now evaluating
Bindings: I = 4
This is job 4 of 10 jobs, part of group 1 of 3 groups.
Process completed successfully.
Bindings: I = 5
This is job 5 of 10 jobs, part of group 1 of 3 groups.
Process completed successfully.
Bindings: I = 6
This is job 6 of 10 jobs, part of group 1 of 3 groups.
Process completed successfully.
Done!

The interesting part is the iteration of I.

The expression 0 .. 10 / 0 .. 3 $ 1 divides the range of jobs into three sub-ranges with indices 0, 1 and 2, and then pick the sub-range with index 1 for I to iterate over, resulting in iteration over 4, 5 and 6.

Let us break this down into details.

The range 0 .. 10 consists ot the numbers { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 }.

The range 0 .. 3 consists of the numbers { 0, 1, 2 }.

The range division 0 .. 10 / 0 .. 3 takes the first range and divides it into sub-ranges, with one sub-range for each member of the second range. The result is { 0: { 0, 1, 2, 3 }, 1: { 4, 5, 6 }, 2: { 7, 8, 9 } }.

Then we apply the pick operator $ which picks the subrange of the given index, here 1, so the result is the numbers 4, 5 and 6, or written as range, 4 .. 7.

To get the same results, but be more flexible and more self-commenting, we replace constants by variables in examples/pick2.peat. By using variables, we also make it more easy to embed into a larger context, such as WDL:

Peat 1.0
N_JOBS = 10
N_GROUPS = 3
I_GROUP = 1
I <- 0 .. N_JOBS / 0 .. N_GROUPS $ I_GROUP
===
echo "This is job <:I:> of <:N_JOBS:> jobs, part of group <:I_GROUP:> of <:N_GROUPS:> groups."

Finally, if we wanted to iterate over all groups, we could do so, as in examples/pickall.peat:

Peat 1.0
N_JOBS = 10
N_GROUPS = 3
I_GROUP <- 0 .. N_GROUPS
I <- 0 .. N_JOBS / 0 .. N_GROUPS $ I_GROUP
===
echo "This is job <:I:> of <:N_JOBS:> jobs, part of group <:I_GROUP:> of <:N_GROUPS:> groups."

This will iterate over all groups, and therefore over all jobs:

Peat file uses version 1.0
Declarations: N_JOBS = 10, N_GROUPS = 3, I_GROUP <- 0 .. N_GROUPS, I <- 0 .. N_JOBS / 0 .. N_GROUPS $ I_GROUP
Now evaluating
Bindings: N_JOBS = 10, N_GROUPS = 3, I_GROUP = 0, I = 0
This is job 0 of 10 jobs, part of group 0 of 3 groups.
Process completed successfully.
Bindings: N_JOBS = 10, N_GROUPS = 3, I_GROUP = 0, I = 1
This is job 1 of 10 jobs, part of group 0 of 3 groups.
Process completed successfully.
Bindings: N_JOBS = 10, N_GROUPS = 3, I_GROUP = 0, I = 2
This is job 2 of 10 jobs, part of group 0 of 3 groups.
Process completed successfully.
Bindings: N_JOBS = 10, N_GROUPS = 3, I_GROUP = 0, I = 3
This is job 3 of 10 jobs, part of group 0 of 3 groups.
Process completed successfully.
Bindings: N_JOBS = 10, N_GROUPS = 3, I_GROUP = 1, I = 4
This is job 4 of 10 jobs, part of group 1 of 3 groups.
Process completed successfully.
Bindings: N_JOBS = 10, N_GROUPS = 3, I_GROUP = 1, I = 5
This is job 5 of 10 jobs, part of group 1 of 3 groups.
Process completed successfully.
Bindings: N_JOBS = 10, N_GROUPS = 3, I_GROUP = 1, I = 6
This is job 6 of 10 jobs, part of group 1 of 3 groups.
Process completed successfully.
Bindings: N_JOBS = 10, N_GROUPS = 3, I_GROUP = 2, I = 7
This is job 7 of 10 jobs, part of group 2 of 3 groups.
Process completed successfully.
Bindings: N_JOBS = 10, N_GROUPS = 3, I_GROUP = 2, I = 8
This is job 8 of 10 jobs, part of group 2 of 3 groups.
Process completed successfully.
Bindings: N_JOBS = 10, N_GROUPS = 3, I_GROUP = 2, I = 9
This is job 9 of 10 jobs, part of group 2 of 3 groups.
Process completed successfully.
Done!

Docker images

Peat 1.0.0 is available as Docker image for Alpine and Ubuntu:

  • Alpine 3.13: gcr.io/nitrogenase-docker/peat:1.0.0-alpine
  • Ubuntu 21.04: gcr.io/nitrogenase-docker/peat:1.0.0-ubuntu

Other images may be available upon request, or create take inspiration from the Dockerfiles in Peat repo to make your own.

WDL scatter without Peat

We have a simple example of scatter in WDL without Peat in the Peat repo . For simplicity, the jobs to be scattered each just write a line to a file, and then there is a final task to concat all files into a single file. Here is the scatter clause:

scatter(i_job in range(n_jobs)) {
    String worker_out_file_name = worker_out_file_name_base + "." + i_job + ".txt"
    call worker {
        input:
            i_job = i_job,
            out_file_name = worker_out_file_name
    }
}

Pretty straight-forward: range(n_jobs) goes from 0 to n_jobs, so i_job iterates over these values.

From inside the scatter block, worker.out_file refers to the output file of the current worker and is of type File. From outside the scatter block, on the other hand, worker.outfile is an Array[File] and refers to all worker output files, so the final task takes an array of files as input.

The task workerhas the following command section:

echo "Hello, world, this is job ~{i_job}!" > ~{out_file_name}

This is all very straight-forward, until n_jobs becomes large and incurs an unacceptable overhead. Then, Peat to the rescue.

This workflow is also available on Terra .

WDL scatter with Peat

Finally, we have a version of the workflow above with Peat .

Now, we specify both the number of jobs (n_jobs) and the number of groups (n_groups).

The scatter clause now goes over groups instead of jobs:

scatter(i_group in range(n_groups)) {
    call worker {
        input:
            n_jobs = n_jobs,
            n_groups = n_groups,
            i_group = i_group,
            out_file_prefix = worker_out_file_prefix,
            out_file_suffix = worker_out_file_suffix,
    }
}

The command section of the task now is an invocation of Peat with a heredoc to run the payload job multiple times:

peat << EOF
Peat 1.0
N_JOBS = ~{n_jobs}
N_GROUPS = ~{n_groups}
I_GROUP = ~{i_group}
I <- 0 .. N_JOBS / 0 .. N_GROUPS $ I_GROUP
===
echo "Hello, world, this is job <:I:> from group <:I_GROUP:>!" \
       > ~{out_file_prefix}<:I:>~{out_file_suffix}
EOF

Another change is that instead of a single output file worker.out_file, we now have multiple output files per call, worker.out_files. As seen from within the scatter branch, worker.out_files is an array of files (Array[File]). From outside the scatter branch, worker.out_files is actually an array of arrays of files (Array[Array[File]]). To get back a simple array of files (Array[File]), we use flatten(worker.out_files) outside the scatter block.

The final task that concats all files into one remains the same.

This workflow is also available on Terra .

Peat Demo Terra Workspace

We also have a workspace on Terra to Demo Peat, containing the workflows above.

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Light-weight scatterer to blend well with WDL to reduce overhead

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