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Job

Params

name

A human readable description of the object.

server

An instance of Server.

data_transferred

sum of all data uploads and downloads for request manually defined job from e-footprint hypothesis in kilobyte.

data_stored

data stored by request manually defined job from e-footprint hypothesis in kilobyte.

request_duration

request duration of manually defined job from e-footprint hypothesis in second.

compute_needed

cpu cores needed on server server to process manually defined job from e-footprint hypothesis in cpu_core.

ram_needed

ram needed on server server to process manually defined job from e-footprint hypothesis in megabyte.

Calculated attributes

hourly_occurrences_per_usage_pattern

Dictionary with UsagePattern as keys and hourly manually defined job occurrences in usage pattern as values, in dimensionless.

Example value: {
id-46655e-usage-pattern: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in dimensionless:
first 10 vals [5.0, 9.0, 1.0, 4.0, 4.0, 8.0, 4.0, 6.0, 5.0, 5.0],
last 10 vals [8.0, 6.0, 9.0, 3.0, 9.0, 1.0, 5.0, 1.0, 9.0, 1.0],
}

Depends directly on:

through the following calculations:

You can also visit the link to Hourly Manually defined job occurrences in usage pattern’s full calculation graph.

hourly_avg_occurrences_per_usage_pattern

Dictionary with UsagePattern as keys and average hourly manually defined job occurrences in usage pattern as values, in dimensionless.

Example value: {
id-46655e-usage-pattern: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in dimensionless:
first 10 vals [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
last 10 vals [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
}

Depends directly on:

through the following calculations:

You can also visit the link to Average hourly Manually defined job occurrences in usage pattern’s full calculation graph.

hourly_data_transferred_per_usage_pattern

Dictionary with UsagePattern as keys and hourly data transferred for manually defined job in usage pattern as values, in kilobyte.

Example value: {
id-46655e-usage-pattern: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in kB:
first 10 vals [750.0, 1350.0, 150.0, 600.0, 600.0, 1200.0, 600.0, 900.0, 750.0, 750.0],
last 10 vals [1200.0, 900.0, 1350.0, 450.0, 1350.0, 150.0, 750.0, 150.0, 1350.0, 150.0],
}

Depends directly on:

through the following calculations:

You can also visit the link to Hourly data transferred for Manually defined job in usage pattern’s full calculation graph.

hourly_data_stored_per_usage_pattern

Dictionary with UsagePattern as keys and hourly data stored for manually defined job in usage pattern as values, in kilobyte.

Example value: {
id-46655e-usage-pattern: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in kB:
first 10 vals [500.0, 900.0, 100.0, 400.0, 400.0, 800.0, 400.0, 600.0, 500.0, 500.0],
last 10 vals [800.0, 600.0, 900.0, 300.0, 900.0, 100.0, 500.0, 100.0, 900.0, 100.0],
}

Depends directly on:

through the following calculations:

You can also visit the link to Hourly data stored for Manually defined job in usage pattern’s full calculation graph.

hourly_occurrences_across_usage_patterns

hourly manually defined job occurrences across usage patterns in dimensionless.

Example value: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in dimensionless:
first 10 vals [5.0, 9.0, 1.0, 4.0, 4.0, 8.0, 4.0, 6.0, 5.0, 5.0],
last 10 vals [8.0, 6.0, 9.0, 3.0, 9.0, 1.0, 5.0, 1.0, 9.0, 1.0]

Depends directly on:

through the following calculations:

You can also visit the link to Hourly Manually defined job occurrences across usage patterns’s full calculation graph.

hourly_avg_occurrences_across_usage_patterns

hourly manually defined job average occurrences across usage patterns in dimensionless.

Example value: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in dimensionless:
first 10 vals [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
last 10 vals [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]

Depends directly on:

through the following calculations:

You can also visit the link to Hourly Manually defined job average occurrences across usage patterns’s full calculation graph.

hourly_data_transferred_across_usage_patterns

hourly manually defined job data transferred across usage patterns in kilobyte.

Example value: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in kB:
first 10 vals [750.0, 1350.0, 150.0, 600.0, 600.0, 1200.0, 600.0, 900.0, 750.0, 750.0],
last 10 vals [1200.0, 900.0, 1350.0, 450.0, 1350.0, 150.0, 750.0, 150.0, 1350.0, 150.0]

Depends directly on:

through the following calculations:

You can also visit the link to Hourly Manually defined job data transferred across usage patterns’s full calculation graph.

hourly_data_stored_across_usage_patterns

hourly manually defined job data stored across usage patterns in kilobyte.

Example value: 26298 values from 2024-12-31 23:00:00+00:00 to 2028-01-01 17:00:00+00:00 in kB:
first 10 vals [500.0, 900.0, 100.0, 400.0, 400.0, 800.0, 400.0, 600.0, 500.0, 500.0],
last 10 vals [800.0, 600.0, 900.0, 300.0, 900.0, 100.0, 500.0, 100.0, 900.0, 100.0]

Depends directly on:

through the following calculations:

You can also visit the link to Hourly Manually defined job data stored across usage patterns’s full calculation graph.