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VideoStreamingJob

Params

name

A human readable description of the object.

service

An instance of VideoStreaming.

resolution

description to be done

video_duration

video streaming job video duration from hypothesis in minute.

refresh_rate

video streaming job frames per second from hypothesis in 1 / second.

data_stored

data stored by request video streaming job from hypothesis in megabyte.

Calculated attributes

request_duration

ExplainableQuantity in minute, representing the video streaming job request duration.

Example value: 20 minute

Depends directly on:

through the following calculations:

You can also visit the link to Video streaming job request duration’s full calculation graph.

dynamic_bitrate

ExplainableQuantity in megabyte / second, representing the video streaming job dynamic bitrate.

Example value: 0.78 megabyte / second

Depends directly on:

through the following calculations:

You can also visit the link to Video streaming job dynamic bitrate’s full calculation graph.

data_transferred

ExplainableQuantity in gigabyte, representing the video streaming job data transferred.

Example value: 0.93 gigabyte

Depends directly on:

through the following calculations:

You can also visit the link to Video streaming job data transferred’s full calculation graph.

compute_needed

ExplainableQuantity in cpu_core, representing the video streaming job cpu needed.

Example value: 0.0 cpu_core

Depends directly on:

through the following calculations:

You can also visit the link to Video streaming job CPU needed’s full calculation graph.

ram_needed

ExplainableQuantity in megabyte, representing the video streaming job ram needed.

Example value: 50 megabyte

Depends directly on:

through the following calculations:

You can also visit the link to Video streaming job RAM needed’s full calculation graph.

hourly_occurrences_per_usage_pattern

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

Example value: {
id-2dd2c8-usage-pattern: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in dimensionless:
first 10 vals [9, 8, 6, 1, 5, 8, 7, 2, 7, 3],
last 10 vals [3, 6, 6, 3, 1, 6, 3, 2, 9, 1],
}

Depends directly on:

through the following calculations:

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

hourly_avg_occurrences_per_usage_pattern

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

Example value: {
id-2dd2c8-usage-pattern: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in dimensionless:
first 10 vals [3.0, 2.67, 2.0, 0.33, 1.67, 2.67, 2.33, 0.67, 2.33, 1.0],
last 10 vals [1.0, 2.0, 2.0, 1.0, 0.33, 2.0, 1.0, 0.67, 3.0, 0.33],
}

Depends directly on:

through the following calculations:

You can also visit the link to Average hourly Video streaming 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 video streaming job in usage pattern as values, in gigabyte.

Example value: {
id-2dd2c8-usage-pattern: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in GB:
first 10 vals [8.4, 7.46, 5.6, 0.93, 4.67, 7.46, 6.53, 1.87, 6.53, 2.8],
last 10 vals [2.8, 5.6, 5.6, 2.8, 0.93, 5.6, 2.8, 1.87, 8.4, 0.93],
}

Depends directly on:

through the following calculations:

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

hourly_data_stored_per_usage_pattern

Dictionary with UsagePattern as keys and hourly data stored for video streaming job in usage pattern as values, in megabyte.

Example value: {
id-2dd2c8-usage-pattern: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in MB:
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 data stored for Video streaming job in usage pattern’s full calculation graph.

hourly_occurrences_across_usage_patterns

hourly video streaming job occurrences across usage patterns in dimensionless.

Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in dimensionless:
first 10 vals [9, 8, 6, 1, 5, 8, 7, 2, 7, 3],
last 10 vals [3, 6, 6, 3, 1, 6, 3, 2, 9, 1]

Depends directly on:

through the following calculations:

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

hourly_avg_occurrences_across_usage_patterns

hourly video streaming job average occurrences across usage patterns in dimensionless.

Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in dimensionless:
first 10 vals [3.0, 2.67, 2.0, 0.33, 1.67, 2.67, 2.33, 0.67, 2.33, 1.0],
last 10 vals [1.0, 2.0, 2.0, 1.0, 0.33, 2.0, 1.0, 0.67, 3.0, 0.33]

Depends directly on:

through the following calculations:

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

hourly_data_transferred_across_usage_patterns

hourly video streaming job data transferred across usage patterns in gigabyte.

Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in GB:
first 10 vals [8.4, 7.46, 5.6, 0.93, 4.67, 7.46, 6.53, 1.87, 6.53, 2.8],
last 10 vals [2.8, 5.6, 5.6, 2.8, 0.93, 5.6, 2.8, 1.87, 8.4, 0.93]

Depends directly on:

through the following calculations:

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

hourly_data_stored_across_usage_patterns

hourly video streaming job data stored across usage patterns in megabyte.

Example value: 26299 values from 2024-12-31 23:00:00 to 2028-01-01 17:00:00 in MB:
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 Video streaming job data stored across usage patterns’s full calculation graph.