Streaming SQL Multi-Turn Dialogue and Query Refinement Dataset

#Multi-Turn Dialogue Generation #Streaming SQL Generation #Requirement Clarification #Iterative SQL Refinement #Streaming Data Analytics #Data Engineering Assistants #Natural Language to SQL #Conversational Query Building

5600
0.4GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-03

AI Analysis & Value Prop

This dataset contains multi-turn text conversations in which users describe streaming analytics needs, add constraints, and iteratively refine SQL queries. It covers streaming concepts such as windowing, time semantics, and aggregation, with records that can include the full transcript, requirement and clarification summaries, the final query, SQL dialect, and revision history. It supports training models to interpret requirements through dialogue, generate streaming SQL, and revise queries based on feedback.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
sql_dialect	string	The streaming SQL dialect or engine identified or assumed for the final query, when available.
final_sql_query	string	The final streaming SQL query produced or revised during the conversation, including relevant windowing and time semantics.
clarification_summary	string	A summary of ambiguities identified and clarified during the conversation, including the resulting decisions.
query_revision_summary	string	A summary of how the SQL query changed across iterations and which user-provided constraints motivated those changes.
streaming_sql_features	string	A concise list of streaming concepts used or requested, such as event time, watermarks, windows, joins, state, and aggregations.
conversation_transcript	string	The complete original conversation, preserving turn order and the user's requests, constraints, clarifications, and assistant responses.
conversation_turn_count	integer	The number of conversational turns represented in the original transcript.
user_requirements_summary	string	A concise summary of the analytics goal, requested outputs, and explicit user constraints derived from the conversation.

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 contain?: It contains multi-turn conversations about writing and revising streaming SQL, including user requirements, added constraints, clarification exchanges, and final queries. Records can also provide the SQL dialect, streaming features, and a summary of query revisions.

Which streaming SQL concepts are covered?: The dataset focuses on streaming analytics concepts such as windowing, time semantics, and aggregation. Records may also cover event time, watermarks, joins, and state, depending on the example.

Which training tasks is it suitable for?: It can support dialogue SFT for understanding evolving analytics requirements, resolving ambiguity through conversation, generating streaming SQL, and refining queries in response to user constraints.

How can I obtain the dataset, and what are the licensing terms?: Refer to the product page and applicable license for access methods, available formats, and permitted uses. Before use, check the terms for commercial use, redistribution, and derivative datasets.

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Cite this Work

@dataset{Mobiusi2026,
  title={Streaming SQL Multi-Turn Dialogue and Query Refinement Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/d6318509bdb0965e9cf9fba37f35497c},
  urldate={2026-10-22},
  keywords={streaming SQL dataset,multi-turn dialogue data,SQL generation training,streaming analytics,dialogue SFT,natural language to SQL,SQL query refinement,window aggregation,time semantics,data engineering assistant},
  version={1.0}
}

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