object QualitySparkUtils
Set of utilities to reach in to private functions
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- case class Batch(name: String, strategy: Strategy, rules: Rule[LogicalPlan]*) extends Product with Serializable
- case class FakePlan(expr: Expression, child: LogicalPlan) extends LogicalPlan with UnaryNode with Product with Serializable
- case class Strategy(maxIterations: Int, errorOnExceed: Boolean = false, maxIterationsSetting: String = null) extends Product with Serializable
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def
drop_field(update: Column, fieldNames: String*): Column
Drops a field from a structure
Drops a field from a structure
- fieldNames
may be nested
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eq(arg0: AnyRef): Boolean
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- def execute(logicalPlan: LogicalPlan, batch: Batch): LogicalPlan
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finalize(): Unit
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- def resolution(analyzer: Analyzer, sparkSession: SparkSession, plan: LogicalPlan): Batch
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def
resolveExpression(dataFrame: DataFrame, expr: Expression): Expression
Resolves expressions against a dataframe, this allows them to be swapped out after name checking - spark cannot then simply optimise the tree so certain things like constant folding etc.
Resolves expressions against a dataframe, this allows them to be swapped out after name checking - spark cannot then simply optimise the tree so certain things like constant folding etc. won't show up.
- dataFrame
resolve's must be against a given dataframe to keep names matching
- expr
the expression to resolve
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def
resolveWithOverride(orig: Option[DataFrame]): Option[DataFrame]
Where resolveWith is not possible (e.g.
Where resolveWith is not possible (e.g. 10.x DBRs) it is disabled here. This is, in the 10.x DBR case, due to the class files for UnaryNode (FakePlan) being radically different and causing an IncompatibleClassChangeError: Implementing class
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def
toString(): String
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def
transformFields(exp: Expression): Expression
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def
tryResolveReferences(sparkSession: SparkSession)(expr: Expression, child: LogicalPlan): Expression
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def
update_field(update: Column, transformations: (String, Column)*): Column
Adds fields, in order, for each field path it's paired transformation is applied to the update column
Adds fields, in order, for each field path it's paired transformation is applied to the update column
- returns
a new copy of update with the changes applied
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wait(arg0: Long): Unit
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