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[SPARK-9759] [SQL] improve decimal.times() and cast(int, decimalType)
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This patch optimize two things:

1. passing MathContext to JavaBigDecimal.multiply/divide/reminder to do right rounding, because java.math.BigDecimal.apply(MathContext) is expensive

2. Cast integer/short/byte to decimal directly (without double)

This two optimizations could speed up the end-to-end time of a aggregation (SUM(short * decimal(5, 2)) 75% (from 19s -> 10.8s)

Author: Davies Liu <davies@databricks.com>

Closes apache#8052 from davies/optimize_decimal and squashes the following commits:

225efad [Davies Liu] improve decimal.times() and cast(int, decimalType)
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Davies Liu authored and rxin committed Aug 10, 2015
1 parent fe2fb7f commit c4fd2a2
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Showing 2 changed files with 22 additions and 32 deletions.
Original file line number Diff line number Diff line change
Expand Up @@ -155,7 +155,7 @@ case class Cast(child: Expression, dataType: DataType)
case ByteType =>
buildCast[Byte](_, _ != 0)
case DecimalType() =>
buildCast[Decimal](_, _ != Decimal.ZERO)
buildCast[Decimal](_, !_.isZero)
case DoubleType =>
buildCast[Double](_, _ != 0)
case FloatType =>
Expand Down Expand Up @@ -315,13 +315,13 @@ case class Cast(child: Expression, dataType: DataType)
case TimestampType =>
// Note that we lose precision here.
buildCast[Long](_, t => changePrecision(Decimal(timestampToDouble(t)), target))
case DecimalType() =>
case dt: DecimalType =>
b => changePrecision(b.asInstanceOf[Decimal].clone(), target)
case LongType =>
b => changePrecision(Decimal(b.asInstanceOf[Long]), target)
case x: NumericType => // All other numeric types can be represented precisely as Doubles
case t: IntegralType =>
b => changePrecision(Decimal(t.integral.asInstanceOf[Integral[Any]].toLong(b)), target)
case x: FractionalType =>
b => try {
changePrecision(Decimal(x.numeric.asInstanceOf[Numeric[Any]].toDouble(b)), target)
changePrecision(Decimal(x.fractional.asInstanceOf[Fractional[Any]].toDouble(b)), target)
} catch {
case _: NumberFormatException => null
}
Expand Down Expand Up @@ -534,10 +534,7 @@ case class Cast(child: Expression, dataType: DataType)
(c, evPrim, evNull) =>
s"""
try {
org.apache.spark.sql.types.Decimal tmpDecimal =
new org.apache.spark.sql.types.Decimal().set(
new scala.math.BigDecimal(
new java.math.BigDecimal($c.toString())));
Decimal tmpDecimal = Decimal.apply(new java.math.BigDecimal($c.toString()));
${changePrecision("tmpDecimal", target, evPrim, evNull)}
} catch (java.lang.NumberFormatException e) {
$evNull = true;
Expand All @@ -546,12 +543,7 @@ case class Cast(child: Expression, dataType: DataType)
case BooleanType =>
(c, evPrim, evNull) =>
s"""
org.apache.spark.sql.types.Decimal tmpDecimal = null;
if ($c) {
tmpDecimal = new org.apache.spark.sql.types.Decimal().set(1);
} else {
tmpDecimal = new org.apache.spark.sql.types.Decimal().set(0);
}
Decimal tmpDecimal = $c ? Decimal.apply(1) : Decimal.apply(0);
${changePrecision("tmpDecimal", target, evPrim, evNull)}
"""
case DateType =>
Expand All @@ -561,32 +553,28 @@ case class Cast(child: Expression, dataType: DataType)
// Note that we lose precision here.
(c, evPrim, evNull) =>
s"""
org.apache.spark.sql.types.Decimal tmpDecimal =
new org.apache.spark.sql.types.Decimal().set(
scala.math.BigDecimal.valueOf(${timestampToDoubleCode(c)}));
Decimal tmpDecimal = Decimal.apply(
scala.math.BigDecimal.valueOf(${timestampToDoubleCode(c)}));
${changePrecision("tmpDecimal", target, evPrim, evNull)}
"""
case DecimalType() =>
(c, evPrim, evNull) =>
s"""
org.apache.spark.sql.types.Decimal tmpDecimal = $c.clone();
Decimal tmpDecimal = $c.clone();
${changePrecision("tmpDecimal", target, evPrim, evNull)}
"""
case LongType =>
case x: IntegralType =>
(c, evPrim, evNull) =>
s"""
org.apache.spark.sql.types.Decimal tmpDecimal =
new org.apache.spark.sql.types.Decimal().set($c);
Decimal tmpDecimal = Decimal.apply((long) $c);
${changePrecision("tmpDecimal", target, evPrim, evNull)}
"""
case x: NumericType =>
case x: FractionalType =>
// All other numeric types can be represented precisely as Doubles
(c, evPrim, evNull) =>
s"""
try {
org.apache.spark.sql.types.Decimal tmpDecimal =
new org.apache.spark.sql.types.Decimal().set(
scala.math.BigDecimal.valueOf((double) $c));
Decimal tmpDecimal = Decimal.apply(scala.math.BigDecimal.valueOf((double) $c));
${changePrecision("tmpDecimal", target, evPrim, evNull)}
} catch (java.lang.NumberFormatException e) {
$evNull = true;
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -139,9 +139,9 @@ final class Decimal extends Ordered[Decimal] with Serializable {

def toBigDecimal: BigDecimal = {
if (decimalVal.ne(null)) {
decimalVal(MATH_CONTEXT)
decimalVal
} else {
BigDecimal(longVal, _scale)(MATH_CONTEXT)
BigDecimal(longVal, _scale)
}
}

Expand Down Expand Up @@ -280,13 +280,15 @@ final class Decimal extends Ordered[Decimal] with Serializable {
}

// HiveTypeCoercion will take care of the precision, scale of result
def * (that: Decimal): Decimal = Decimal(toBigDecimal * that.toBigDecimal)
def * (that: Decimal): Decimal =
Decimal(toJavaBigDecimal.multiply(that.toJavaBigDecimal, MATH_CONTEXT))

def / (that: Decimal): Decimal =
if (that.isZero) null else Decimal(toBigDecimal / that.toBigDecimal)
if (that.isZero) null else Decimal(toJavaBigDecimal.divide(that.toJavaBigDecimal, MATH_CONTEXT))

def % (that: Decimal): Decimal =
if (that.isZero) null else Decimal(toBigDecimal % that.toBigDecimal)
if (that.isZero) null
else Decimal(toJavaBigDecimal.remainder(that.toJavaBigDecimal, MATH_CONTEXT))

def remainder(that: Decimal): Decimal = this % that

Expand Down

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