case class GpuOverrides() extends Rule[SparkPlan] with Logging with Product with Serializable
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def
apply(sparkPlan: SparkPlan): SparkPlan
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def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
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def
isDeltaLakeMetadataQuery(plan: SparkPlan, detectDeltaCheckpoint: Boolean): Boolean
Determine whether query is running against Delta Lake _delta_log JSON files or if Delta is doing stats collection that ends up hardcoding the use of AQE, even though the AQE setting is disabled.
Determine whether query is running against Delta Lake _delta_log JSON files or if Delta is doing stats collection that ends up hardcoding the use of AQE, even though the AQE setting is disabled. To protect against the latter, we check for a ScalaUDF using a tahoe.Snapshot function and if we ever see an AdaptiveSparkPlan on a Spark version we don't expect, fallback to the CPU for those plans. Note that the Delta Lake delta log checkpoint parquet files are just inefficient to have to copy the data to GPU and then back off after it does the scan on Delta Table Checkpoint, so have the entire plan fallback to CPU at that point.
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isTraceEnabled(): Boolean
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log: Logger
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ruleId: RuleId
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ruleName: String
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