Packages

object DecimalPrecision extends Rule[LogicalPlan] with TypeCoercionRule

Calculates and propagates precision for fixed-precision decimals. Hive has a number of rules for this based on the SQL standard and MS SQL: https://cwiki.apache.org/confluence/download/attachments/27362075/Hive_Decimal_Precision_Scale_Support.pdf https://msdn.microsoft.com/en-us/library/ms190476.aspx

In particular, if we have expressions e1 and e2 with precision/scale p1/s2 and p2/s2 respectively, then the following operations have the following precision / scale:

Operation Result Precision Result Scale ------------------------------------------------------------------------ e1 + e2 max(s1, s2) + max(p1-s1, p2-s2) + 1 max(s1, s2) e1 - e2 max(s1, s2) + max(p1-s1, p2-s2) + 1 max(s1, s2) e1 * e2 p1 + p2 + 1 s1 + s2 e1 / e2 p1 - s1 + s2 + max(6, s1 + p2 + 1) max(6, s1 + p2 + 1) e1 % e2 min(p1-s1, p2-s2) + max(s1, s2) max(s1, s2) e1 union e2 max(s1, s2) + max(p1-s1, p2-s2) max(s1, s2)

When spark.sql.decimalOperations.allowPrecisionLoss is set to true, if the precision / scale needed are out of the range of available values, the scale is reduced up to 6, in order to prevent the truncation of the integer part of the decimals.

To implement the rules for fixed-precision types, we introduce casts to turn them to unlimited precision, do the math on unlimited-precision numbers, then introduce casts back to the required fixed precision. This allows us to do all rounding and overflow handling in the cast-to-fixed-precision operator.

In addition, when mixing non-decimal types with decimals, we use the following rules: - BYTE gets turned into DECIMAL(3, 0) - SHORT gets turned into DECIMAL(5, 0) - INT gets turned into DECIMAL(10, 0) - LONG gets turned into DECIMAL(20, 0) - FLOAT and DOUBLE cause fixed-length decimals to turn into DOUBLE - Literals INT and LONG get turned into DECIMAL with the precision strictly needed by the value

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TypeCoercionRule, Rule[LogicalPlan], Logging, AnyRef, Any
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  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  4. def apply(plan: LogicalPlan): LogicalPlan

    Applies any changes to AttributeReference data types that are made by the transform method to instances higher in the query tree.

    Applies any changes to AttributeReference data types that are made by the transform method to instances higher in the query tree.

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    TypeCoercionRuleRule
  5. final def asInstanceOf[T0]: T0
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  7. def coerceTypes(plan: LogicalPlan): LogicalPlan
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  8. final def eq(arg0: AnyRef): Boolean
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  9. def equals(arg0: Any): Boolean
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  13. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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  14. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
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  15. final def isInstanceOf[T0]: Boolean
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  16. def isTraceEnabled(): Boolean
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  17. def log: Logger
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  18. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
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  19. def logDebug(msg: ⇒ String): Unit
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  20. def logError(msg: ⇒ String, throwable: Throwable): Unit
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  21. def logError(msg: ⇒ String): Unit
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  22. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
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  23. def logInfo(msg: ⇒ String): Unit
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  24. def logName: String
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  25. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
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  26. def logTrace(msg: ⇒ String): Unit
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  27. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
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  28. def logWarning(msg: ⇒ String): Unit
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  29. final def ne(arg0: AnyRef): Boolean
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  30. final def notify(): Unit
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  31. final def notifyAll(): Unit
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  32. val ruleName: String

    Name for this rule, automatically inferred based on class name.

    Name for this rule, automatically inferred based on class name.

    Definition Classes
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  33. final def synchronized[T0](arg0: ⇒ T0): T0
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  34. def toString(): String
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  35. final def wait(): Unit
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  36. final def wait(arg0: Long, arg1: Int): Unit
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  37. final def wait(arg0: Long): Unit
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  38. def widerDecimalType(p1: Int, s1: Int, p2: Int, s2: Int): DecimalType
  39. def widerDecimalType(d1: DecimalType, d2: DecimalType): DecimalType

Inherited from TypeCoercionRule

Inherited from Rule[LogicalPlan]

Inherited from Logging

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