Event-Time Watermark and Late-Data State Simulation Dataset

#State Prediction #Watermark Progression Prediction #Window Completion Estimation #Late-Event Handling Prediction #Aggregation State Prediction #Stream Processing Engine Testing #Event-Time Semantics Analysis #Window Aggregation Evaluation #Late-Data Policy Validation

7200
0.5GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-02

AI Analysis & Value Prop

This dataset provides simulated stream-processing runs with out-of-order events, event-time distributions, watermark strategies, window configurations, and late-data handling rules. It records watermark progression, window completion, pending late events, and aggregation states to show how state changes under different time-semantics configurations. Use it to support state prediction, temporal-semantics modeling, strategy comparison, and testing of stream-processing engines.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
simulation_input	object	Raw inputs containing the event stream and the watermark, window, late-data, and simulation-run configurations.
aggregation_state	array	Records intermediate streaming aggregation states and updates by window and grouping key.
simulation_summary	object	Summarizes event processing, watermark behavior, and final window results for the complete simulation run.
pending_late_events	array	Records late events that remain unresolved at the current simulation step and their degree of lateness.
watermark_progression	array	Records observed watermarks, progression increments, and states at each simulation processing step.
window_completion_state	array	Records the completion ratio, event count, and finalization status for each event-time window.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset simulate?: It covers out-of-order events, event-time distributions, watermark strategies, window configurations, and late-data rules. The run sequences record watermark progression, window completion, pending late events, and aggregation states.

How is the data structured?: The dataset includes raw simulation inputs, step-by-step watermark sequences, window completion states, pending late events, aggregation state sequences, and a simulation summary. This structure supports analysis by run step and window state.

Which training or evaluation tasks can it support?: It can support state prediction tasks for watermark progression, window completion, late-event handling, and aggregation states, as well as temporal-semantics modeling and strategy comparison for stream-processing engines.

How can I access the data, and what are the licensing terms?: Check the dataset product page for available access methods, file specifications, and license terms. Before commercial use or redistribution, verify the applicable license scope and restrictions.

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Cite this Work

@dataset{Mobiusi2026,
  title={Event-Time Watermark and Late-Data State Simulation Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/51956ecdc37f37f74fdc446b3b6175e0?dataset_task_cate_id=11},
  urldate={2026-10-27},
  keywords={event-time dataset,watermark simulation,stream processing data,late-data handling,window state prediction,stream aggregation simulation,time-semantics modeling,stream engine testing},
  version={1.0}
}

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