# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Snowflake Spark Connect API
  version: 1.0.0
extends: openapi/snowflake-spark-connect-api-openapi.yml
actions:
- target: $.info
  update:
    x-apievangelist-phrasing:
      method: generated
      generated: '2026-10-01'
      generator: build-phrasing.py
      label: Generated by API Evangelist
      operations: 10
- target: $.paths['/api/v2/spark-connect/execute-plan'].post
  update:
    x-apievangelist-phrasing:
      intent: Execute a Spark Connect query plan
      effect: write
      questions:
      - How do I run a Spark DataFrame plan against Snowflake through Spark Connect?
      - Does executing a Spark Connect plan always stream back at least one Arrow batch?
      instructions:
      - text: Execute this Spark Connect plan and stream the Arrow results back.
      - text: Run my Spark query plan on Snowflake as a reattachable execution.
      method: generated
      generated: '2026-10-01'
- target: $.paths['/api/v2/spark-connect/analyze-plan'].post
  update:
    x-apievangelist-phrasing:
      intent: Analyze a Spark query plan for metadata
      effect: read
      questions:
      - Can I get the schema of a Spark query without running it?
      - What metadata does Spark Connect return when analyzing a plan?
      instructions:
      - text: Analyze this Spark plan and return its output schema.
      - text: Explain the Spark query plan without executing it.
      method: generated
      generated: '2026-10-01'
- target: $.paths['/api/v2/spark-connect/config'].post
  update:
    x-apievangelist-phrasing:
      intent: Get or update Spark session configuration
      effect: write
      questions:
      - How do I read or change Spark configuration values for my Spark Connect session?
      - Can I set a Spark conf key on a session running against Snowflake?
      instructions:
      - text: Set the Spark session configuration value I specify.
      - text: Fetch the current Spark Connect session configuration.
      method: generated
      generated: '2026-10-01'
- target: $.paths['/api/v2/spark-connect/add-artifacts'].post
  update:
    x-apievangelist-phrasing:
      intent: Upload artifacts to a Spark session
      effect: write
      questions:
      - How do I add JARs or Python files to a Spark Connect session?
      - Can I upload my UDF dependencies to the Spark session?
      instructions:
      - text: Add these artifacts to my Spark Connect session.
      - text: Upload my Python dependency files into the Spark session.
      method: generated
      generated: '2026-10-01'
- target: $.paths['/api/v2/spark-connect/artifact-status'].post
  update:
    x-apievangelist-phrasing:
      intent: Check status of session artifacts
      effect: read
      questions:
      - Have the artifacts I uploaded to the Spark session already landed?
      - Can I check whether a named artifact exists in my Spark Connect session?
      instructions:
      - text: Check the status of the artifacts in my Spark session.
      - text: Tell me which of these artifact names already exist in the session.
      method: generated
      generated: '2026-10-01'
- target: $.paths['/api/v2/spark-connect/interrupt'].post
  update:
    x-apievangelist-phrasing:
      intent: Interrupt running Spark executions
      effect: destructive
      questions:
      - How do I stop a Spark Connect job that is still running?
      - Can I interrupt every execution in my Spark session at once?
      instructions:
      - text: Interrupt all running executions in my Spark session.
      - text: Cancel the Spark operation that is currently executing.
      method: generated
      generated: '2026-10-01'
- target: $.paths['/api/v2/spark-connect/reattach-execute'].post
  update:
    x-apievangelist-phrasing:
      intent: Reattach to a Spark execution
      effect: read
      questions:
      - My Spark result stream dropped before ResultComplete; how do I resume it?
      - Can I reattach to an execution that was started as reattachable?
      instructions:
      - text: Reattach to my reattachable Spark execution and continue streaming results.
      - text: Resume the interrupted result stream of the Spark plan I started earlier.
      method: generated
      generated: '2026-10-01'
- target: $.paths['/api/v2/spark-connect/release-execute'].post
  update:
    x-apievangelist-phrasing:
      intent: Release a reattachable Spark execution
      effect: write
      questions:
      - How do I free server resources held by a reattachable Spark execution?
      - Can I release only the already-consumed part of a reattachable execution's results?
      instructions:
      - text: Release the reattachable Spark execution I finished reading.
      - text: Release the consumed responses of my reattachable execution.
      method: generated
      generated: '2026-10-01'
- target: $.paths['/api/v2/spark-connect/pull-request'].post
  update:
    x-apievangelist-phrasing:
      intent: Pull the next Spark request for a sproc processor
      effect: read
      questions:
      - How does the stored procedure DataFrame processor fetch its next Spark request?
      - What endpoint does a sproc use to pull pending Spark work?
      instructions:
      - text: Pull the next Spark request for the stored procedure processor.
      - text: Get the next pending Spark request for my sproc DataFrame processor.
      method: generated
      generated: '2026-10-01'
- target: $.paths['/api/v2/spark-connect/push-response'].post
  update:
    x-apievangelist-phrasing:
      intent: Push a Spark response from a sproc processor
      effect: write
      questions:
      - How does a stored procedure send its Spark response back?
      - Where does the sproc DataFrame processor push completed Spark results?
      instructions:
      - text: Push this Spark response from the stored procedure processor.
      - text: Send the sproc's completed Spark result back to Snowflake.
      method: generated
      generated: '2026-10-01'