VideoStreamingJob
Params
name
A human readable description of the object.
service
An instance of VideoStreaming.
resolution
Video streaming job resolution.
For example, 1080p (1920 x 1080).
video_duration
Video streaming job video duration in minute.
refresh_rate
Video streaming job frames per second in 1 / second.
data_stored
Data stored by request video streaming job in megabyte.
Backwards links
Calculated attributes
request_duration
ExplainableQuantity in minute, representing the Video streaming job request duration.
Example value: 20 min
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: 0.778 MB/s
Depends directly on:
- Video streaming job resolution from e-footprint hypothesis
- Video streaming service bits per pixel from e-footprint hypothesis
- Video streaming job frames per second from e-footprint hypothesis
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: 933 MB
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: 0.00311 cpu_core
Depends directly on:
- Video streaming service CPU cost per static stream from e-footprint hypothesis
- Video streaming job dynamic bitrate
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_ram, representing the Video streaming job ram needed.
Example value: 50 MB_ram
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 usagepattern usage pattern as values, in occurrence.
Example value: {
UsagePattern usage pattern (7703de): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [6, 6, 1, 1, 7, 7, 1, 7, 9, 1],
last 10 vals [7, 1, 3, 1, 7, 5, 6, 3, 3, 4],
}
Depends directly on:
through the following calculations:
You can also visit the link to Hourly Video streaming job occurrences in UsagePattern 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 concurrent.
Example value: {
UsagePattern usage pattern (7703de): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [2, 2, 0.333, 0.333, 2.33, 2.33, 0.333, 2.33, 3, 0.333],
last 10 vals [2.33, 0.333, 1, 0.333, 2.33, 1.67, 2, 1, 1, 1.33],
}
Depends directly on:
- Hourly Video streaming job occurrences in UsagePattern usage pattern
- Video streaming job request duration
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 megabyte.
Example value: {
UsagePattern usage pattern (7703de): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in GB:
first 10 vals [5.6, 5.6, 0.933, 0.933, 6.53, 6.53, 0.933, 6.53, 8.4, 0.933],
last 10 vals [6.53, 0.933, 2.8, 0.933, 6.53, 4.67, 5.6, 2.8, 2.8, 3.73],
}
Depends directly on:
- Average hourly Video streaming job occurrences in usage pattern
- Video streaming job data transferred
- Video streaming job request duration
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: {
UsagePattern usage pattern (7703de): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in B:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
last 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
}
Depends directly on:
- Average hourly Video streaming job occurrences in usage pattern
- Data stored by request Video streaming job from e-footprint hypothesis
- Video streaming job request duration
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_avg_occurrences_across_usage_patterns
Hourly video streaming job average occurrences across usage patterns in concurrent.
Example value: 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [2, 2, 0.333, 0.333, 2.33, 2.33, 0.333, 2.33, 3, 0.333],
last 10 vals [2.33, 0.333, 1, 0.333, 2.33, 1.67, 2, 1, 1, 1.33]
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 megabyte.
Example value: 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in GB:
first 10 vals [5.6, 5.6, 0.933, 0.933, 6.53, 6.53, 0.933, 6.53, 8.4, 0.933],
last 10 vals [6.53, 0.933, 2.8, 0.933, 6.53, 4.67, 5.6, 2.8, 2.8, 3.73]
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: 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in B:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
last 10 vals [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.
fabrication_impact_repartition_weights
Dictionary with UsageJourneyStep as keys and 20 min streaming weight in video streaming job impact repartition as values, in concurrent.
Example value: {
UsageJourneyStep 20 min streaming (624221): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [2, 2, 0.333, 0.333, 2.33, 2.33, 0.333, 2.33, 3, 0.333],
last 10 vals [2.33, 0.333, 1, 0.333, 2.33, 1.67, 2, 1, 1, 1.33],
}
Depends directly on:
through the following calculations:
You can also visit the link to 20 min streaming weight in Video streaming job impact repartition’s full calculation graph.
fabrication_impact_repartition_weight_sum
Sum of video streaming job fabrication impact repartition weights in concurrent.
Example value: 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [2, 2, 0.333, 0.333, 2.33, 2.33, 0.333, 2.33, 3, 0.333],
last 10 vals [2.33, 0.333, 1, 0.333, 2.33, 1.67, 2, 1, 1, 1.33]
Depends directly on:
through the following calculations:
You can also visit the link to Sum of Video streaming job fabrication impact repartition weights’s full calculation graph.
fabrication_impact_repartition
Dictionary with UsageJourneyStep as keys and Video streaming job fabrication impact attribution to 20 min streaming as values, in concurrent.
Example value: {
UsageJourneyStep 20 min streaming (624221): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
}
Depends directly on:
- 20 min streaming weight in Video streaming job impact repartition
- Sum of Video streaming job fabrication impact repartition weights
through the following calculations:
You can also visit the link to Video streaming job fabrication impact attribution to 20 min streaming’s full calculation graph.
usage_impact_repartition_weights
Dictionary with UsageJourneyStep as keys and 20 min streaming weight in video streaming job impact repartition as values, in concurrent * gram / kilowatt_hour.
Example value: {
UsageJourneyStep 20 min streaming (624221): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in ·g/kWh:
first 10 vals [170, 170, 28.3, 28.3, 198, 198, 28.3, 198, 255, 28.3],
last 10 vals [198, 28.3, 85, 28.3, 198, 142, 170, 85, 85, 113],
}
Depends directly on:
through the following calculations:
You can also visit the link to 20 min streaming weight in Video streaming job impact repartition’s full calculation graph.
usage_impact_repartition_weight_sum
Sum of video streaming job usage impact repartition weights in concurrent * gram / kilowatt_hour.
Example value: 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in ·g/kWh:
first 10 vals [170, 170, 28.3, 28.3, 198, 198, 28.3, 198, 255, 28.3],
last 10 vals [198, 28.3, 85, 28.3, 198, 142, 170, 85, 85, 113]
Depends directly on:
through the following calculations:
You can also visit the link to Sum of Video streaming job usage impact repartition weights’s full calculation graph.
usage_impact_repartition
Dictionary with UsageJourneyStep as keys and Video streaming job usage impact attribution to 20 min streaming as values, in concurrent.
Example value: {
UsageJourneyStep 20 min streaming (624221): 26298 values from 2025-01-01 00:00:00+00:00 to 2028-01-01 18:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
}
Depends directly on:
- 20 min streaming weight in Video streaming job impact repartition
- Sum of Video streaming job usage impact repartition weights
through the following calculations:
You can also visit the link to Video streaming job usage impact attribution to 20 min streaming’s full calculation graph.