Dina Belova f015d3b55d [docs][5] Re-design docs to cover all user-groups

First pack of changes in upcoming chain to redesign Rally docs.
All information related to Rally plugins separated and refactored.
Modified files fit 80 symbols margin where possible.

[TODO] continue with other parts of the docs:
       - Contribute to Rally
       - Request New Features
       - Project Info
[TODO] add 80 symbols margin check similar to what
       Performance Documentation has

Change-Id: I5d19a2bbbcdd9be463793bce50de62c5608b6157

2016-12-02 10:57:20 -08:00

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Scenario runner as a plugin

Let's create a scenario runner plugin that runs a given benchmark scenario a random number of times (chosen at random from a given range).

Creation

Inherit a class for your plugin from the base ScenarioRunner class and implement its API (the _run_scenario() method):

import random

from rally.task import runner
from rally import consts


@runner.configure(name="random_times")
class RandomTimesScenarioRunner(runner.ScenarioRunner):
    """Sample scenario runner plugin.

    Run scenario random number of times, which is chosen between min_times and
    max_times.
    """

    CONFIG_SCHEMA = {
        "type": "object",
        "$schema": consts.JSON_SCHEMA,
        "properties": {
            "type": {
                "type": "string"
            },
            "min_times": {
                "type": "integer",
                "minimum": 1
            },
            "max_times": {
                "type": "integer",
                "minimum": 1
            }
        },
        "additionalProperties": True
    }

    def _run_scenario(self, cls, method_name, context, args):
        # runners settings are stored in self.config
        min_times = self.config.get('min_times', 1)
        max_times = self.config.get('max_times', 1)

        for i in range(random.randrange(min_times, max_times)):
            run_args = (i, cls, method_name,
                        runner._get_scenario_context(context), args)
            result = runner._run_scenario_once(run_args)
            # use self.send_result for result of each iteration
            self._send_result(result)

Usage

You can refer to your scenario runner in the benchmark task configuration files in the same way as any other runners. Don't forget to put your runner-specific parameters in the configuration as well ("min_times" and "max_times" in our example):

{
    "Dummy.dummy": [
        {
            "runner": {
                "type": "random_times",
                "min_times": 10,
                "max_times": 20,
            },
            "context": {
                "users": {
                    "tenants": 1,
                    "users_per_tenant": 1
                }
            }
        }
    ]
}

Different plugin samples are available here.

3.2 KiB Raw Blame History

Scenario runner as a plugin

Creation

Usage

3.2 KiB

Raw Blame History