Quick Start

This Quick Start guide shows how to run your first Bacalhau job with minimal setup. Bacalhau's design as a single self-contained binary makes it incredibly easy to set up your own distributed compute network in minutes.

Prerequisites

• Docker installed on any machine that runs a compute node

• Bacalhau CLI installed (see below)

1. Installation

1. Install Bacalhau using the one-liner below (Linux/macOS) or see the installation guide for Windows and Docker options.

curl -sL https://get.bacalhau.org/install.sh | bash

1. Once installed, verify with:

bacalhau version

2. Start a Hybrid Node

Open a terminal and run:

bacalhau serve --orchestrator --compute

• This command launches both an orchestrator and a compute node in one process

• Keep it running; you'll see logs indicating it's ready

3. Submit a Data Analysis Job

Bacalhau supports two primary methods of job submission: Imperative (CLI) and Declarative (YAML). We'll demonstrate a word count job on the classic novel Moby Dick.

Imperative (CLI)

bacalhau docker run \
  --input https://www.gutenberg.org/files/2701/2701-0.txt:/data/moby-dick.txt \
  --output outputs:/outputs \
  --publisher local \
  ghcr.io/bacalhau-project/word-count:latest -- --output-file /outputs/moby-dick-counts.txt /data/moby-dick.txt

Declarative (YAML)

Create a word-count.yaml file:

Type: batch
Count: 1
Tasks:
  - Name: main
    Engine:
      Type: docker
      Params:
        Image: ghcr.io/bacalhau-project/word-count:latest
        Parameters:
        - --output-file
        - /outputs/moby-dick-counts.txt
        - /data/moby-dick.txt
    Publisher:
      Type: local
    InputSources:
      - Alias: input_custom
        Target: /data/moby-dick.txt
        Source:
          Type: urlDownload
          Params:
            URL: https://www.gutenberg.org/files/2701/2701-0.txt
    ResultPaths:
    - Name: outputs
      Path: /outputs

Then run the job using:

bacalhau job run word-count.yaml

• The job downloads a sample dataset and processes it locally

• Bacalhau will display job progress until completion

• You'll receive a Job ID once the job is submitted

4. Inspect the Job

bacalhau job describe <jobID>

• Replace <jobID> with the actual ID printed in step 2

• You can run bacalhau job logs <job-id> to just get the execution logs

5. Retrieve Results

Download and view your job results:

# Download the results
bacalhau job get <jobID>

# View the analysis output
head job-*/outputs/moby-dick-counts.txt

Note: You should see a word frequency analysis of the Moby Dick text file!

🎉 Success!

You've just:

1. Started a local Bacalhau network

2. Submitted a job using both imperative and declarative methods

3. Tracked job progress with detailed descriptions

4. Retrieved and viewed job results