object QualitySparkUtils
Set of utilities to reach in to private functions
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Type Members
- 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
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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def
add(left: Expression, right: Expression, dataType: DataType): Expression
Dbr 11.2 broke the contract for add and cast
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def
arguments(unresolvedFunction: UnresolvedFunction): Seq[Expression]
Arguments for everything above 2.4
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final
def
asInstanceOf[T0]: T0
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def
cast(child: Expression, dataType: DataType): Expression
Dbr 11.2 broke the contract for add and cast
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def
clone(): AnyRef
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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- def execute(logicalPlan: LogicalPlan, batch: Batch): LogicalPlan
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCalendarInterval(c: CalendarInterval, hashlongs: InterpretedHashLongsFunction, digest: Digest): Digest
Provides Spark 3 specific version of hashing CalendarInterval
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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- def isPrimitive(dataType: DataType): Boolean
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final
def
ne(arg0: AnyRef): Boolean
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def
newParser(): SparkSqlParser
Creates a new parser, introduced in 0.4 - 3.2.0 due to SparkSqlParser having no params
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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def
registerFunction(funcReg: FunctionRegistry)(name: String, builder: (Seq[Expression]) ⇒ Expression): Unit
Registers functions with spark, Introduced in 0.4 - 3.2.0 support due to extra source parameter - "built-in" is used as no other option is remotely close
- 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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final
def
synchronized[T0](arg0: ⇒ T0): T0
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- def toString(dataFrame: DataFrame, showParams: ShowParams = ShowParams()): String
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def
toString(): String
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def
tryResolveReferences(sparkSession: SparkSession)(expr: Expression, child: LogicalPlan): Expression
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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