The Database Command

The merlin database command provides a straightforward way to interact with the data stored in Merlin's database. For more information on what type of data is stored in Merlin's database, see Understanding Merlin's Database Entities.

Usage:

merlin database [OPTIONS] SUBCOMMAND

This command can also be invoked with its db alias:

merlin db [OPTIONS] SUBCOMMAND

Common Options

The merlin database command supports the following option that applies to all subcommands:

• -l, --local: Use the local SQLite database (~/.merlin/merlin.db) instead of the configured results backend

Note

The only time Merlin will use the local SQLite database is if you execute a run in local mode.

Example:

merlin database -l info

Available Subcommands

The merlin database command supports the following subcommands:

Subcommand	Description	Documentation
info	Displays general information about the database	The Info Subcommand
get	Retrieves specific entries from the database and prints them to the console	Retrieving Data
delete	Removes entries from the database	Deleting Data
gc	Runs garbage collection to help keep the database up-to-date	Garbage Collection

Setting Up Test Data

For the examples throughout this documentation, we'll use the hello.yaml and hello_samples.yaml files from the Hello World Example.

To help distinguish between the workers in these examples, let's make some modifications to the specification files.

Modifying hello.yaml

Add the following merlin block to the hello.yaml file:

merlin:
    resources:
        workers:
            hello_worker:
                args: -l INFO --concurrency 1 --prefetch-multiplier 1
                steps: [all]

Modifying hello_samples.yaml

Update the merlin block of the hello_samples.yaml file:

merlin:
    samples:
        generate:
            cmd: python3 $(SPECROOT)/make_samples.py --filepath=$(MERLIN_INFO)/samples.csv --number=$(N_SAMPLES)
        file: $(MERLIN_INFO)/samples.csv
        column_labels: [WORLD]
    resources:
        workers:
            hello_samples_worker:
                args: -l INFO --concurrency 1 --prefetch-multiplier 1
                steps: [all]

Also add task queues to the steps in hello_samples.yaml:

study:
    - name: step_1
      description: say hello
      run:
          cmd: echo "$(GREET), $(WORLD)!"
          task_queue: step_1_queue

    - name: step_2
      description: print a success message
      run:
          cmd: print("Hurrah, we did it!")
          depends: [step_1_*]
          shell: /usr/bin/env python3
          task_queue: step_2_queue

Running the Test Studies

Now let's run these studies:

merlin run hello.yaml ; merlin run hello_samples.yaml

And execute them by submitting worker launch scripts (examples of these scripts can be found in the Distributed Runs section).