Running a Simple R Script on Bacalhau

You can use official Docker containers for each language, like R or Python. In this example, we will use the official R container and run it on Bacalhau.

In this tutorial example, we will run a "hello world" R script on Bacalhau.

Prerequisites​

To get started, you need to install the Bacalhau client, see more information here

1. Running an R Script Locally​

To install R follow these instructions A Installing R and RStudio | Hands-On Programming with R. After R and RStudio are installed, create and run a script called hello.R:

# hello.R
print("hello world")

Run the script:

Rscript hello.R

Next, upload the script to your public storage (in our case, IPFS). We've already uploaded the script to IPFS and the CID is: QmVHSWhAL7fNkRiHfoEJGeMYjaYZUsKHvix7L54SptR8ie. You can look at this by browsing to one of the HTTP IPFS proxies like ipfs.io or w3s.link.

2. Running a Job on Bacalhau​

Now it's time to run the script on Bacalhau:

export JOB_ID=$(bacalhau docker run \
    --wait \
    --id-only \
    -i ipfs://QmQRVx3gXVLaRXywgwo8GCTQ63fHqWV88FiwEqCidmUGhk:/hello.R \
    r-base \
    -- Rscript hello.R)

Structure of the command​

1. bacalhau docker run: call to Bacalhau

2. i ipfs://QmQRVx3gXVLaRXywgwo8GCTQ63fHqWV88FiwEqCidmUGhk:/hello.R: Mounting the uploaded dataset at /inputs in the execution. It takes two arguments, the first is the IPFS CID (QmQRVx3gXVLaRXywgwo8GCTQ63fHqWV88FiwEqCidmUGhk) and the second is file path within IPFS (/hello.R)

3. r-base: docker official image we are using

4. Rscript hello.R: execute the R script

When a job is submitted, Bacalhau prints out the related job_id. We store that in an environment variable so that we can reuse it later on:

Declarative job description​

The same job can be presented in the declarative format. In this case, the description will look like this:

name: Running a Simple R Script
type: batch
count: 1
tasks:
  - name: My main task
    Engine:
      type: docker
      params:
        Image: r-base:latest
        Entrypoint:
          - /bin/bash
        Parameters:
          - -c        
          - Rscript /hello.R
    InputSources:
      - Target: "/"
        Source:
          Type: urlDownload
          Params:
            URL: https://raw.githubusercontent.com/bacalhau-project/examples/main/scripts/hello.R
            Path: /hello.R

The job description should be saved in .yaml format, e.g. rhello.yaml, and then run with the command:

bacalhau job run rhello.yaml

3. Checking the State of your Jobs​

Job status: You can check the status of the job using bacalhau list.

bacalhau list --id-filter ${JOB_ID}

When it says Published or Completed, that means the job is done, and we can get the results.

Job information: You can find out more information about your job by using bacalhau describe.

bacalhau describe  ${JOB_ID}

Job download: You can download your job results directly by using bacalhau get. Alternatively, you can choose to create a directory to store your results. In the command below, we created a directory (results) and downloaded our job output to be stored in that directory.

rm -rf results && mkdir results
bacalhau get ${JOB_ID} --output-dir results

4. Viewing your Job Output​

To view the file, run the following command:

cat results/stdout

Futureproofing your R Scripts​

You can generate the job request using bacalhau describe with the --spec flag. This will allow you to re-run that job in the future:

bacalhau describe ${JOB_ID} --spec > job.yaml

cat job.yaml

Support​

If you have questions or need support or guidance, please reach out to the Bacalhau team via Slack (#general channel).