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[Enhancement] [Vectorized] Refactor and optimize BinaryOperation (#9087)

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This commit is contained in:
Pxl
2022-05-07 10:55:15 +08:00
committed by GitHub
parent 2ccaa6338c
commit 98bfeaf560
15 changed files with 685 additions and 985 deletions
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39
be/src/vec/functions/math.cpp
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@ -15,10 +15,11 @@
// specific language governing permissions and limitations
// under the License.
#include "vec/core/types.h"
#include "vec/data_types/number_traits.h"
#include "vec/functions/function_const.h"
#include "vec/functions/function_binary_arithmetic.h"
#include "vec/functions/function_binary_arithmetic_to_null_type.h"
#include "vec/functions/function_binary_arithmetic.h"
#include "vec/functions/function_math_unary.h"
#include "vec/functions/function_math_unary_to_null_type.h"
#include "vec/functions/function_string.h"
@ -150,17 +151,39 @@ struct LogName {
template <typename A, typename B>
struct LogImpl {
using ResultType = Float64;
using Traits = NumberTraits::BinaryOperatorTraits<A, B>;
static const constexpr bool allow_decimal = false;
static constexpr double EPSILON = 1e-9;
template <typename Result = ResultType>
static void apply(const typename Traits::ArrayA& a, B b,
typename ColumnVector<Result>::Container& c,
typename Traits::ArrayNull& null_map) {
size_t size = c.size();
UInt8 is_null = b <= 0;
memset(null_map.data(), is_null, size);
if (!is_null) {
for (size_t i = 0; i < size; i++) {
if (a[i] <= 0 || std::fabs(a[i] - 1.0) < EPSILON) {
null_map[i] = 1;
} else {
c[i] = static_cast<Float64>(std::log(static_cast<Float64>(b)) /
std::log(static_cast<Float64>(a[i])));
}
}
}
}
template <typename Result>
static inline Result apply(A a, B b, NullMap& null_map, size_t index) {
constexpr double EPSILON = 1e-9;
null_map[index] = a <= 0 || b <= 0 || std::fabs(a - 1.0) < EPSILON;
static inline Result apply(A a, B b, UInt8& is_null) {
is_null = a <= 0 || b <= 0 || std::fabs(a - 1.0) < EPSILON;
return static_cast<Float64>(std::log(static_cast<Float64>(b)) /
std::log(static_cast<Float64>(a)));
}
};
using FunctionLog = FunctionBinaryArithmeticToNullType<LogImpl, LogName>;
using FunctionLog = FunctionBinaryArithmetic<LogImpl, LogName, true>;
struct CeilName {
static constexpr auto name = "ceil";
@ -357,7 +380,7 @@ struct PowImpl {
struct PowName {
static constexpr auto name = "pow";
};
using FunctionPow = FunctionBinaryArithmetic<PowImpl, PowName>;
using FunctionPow = FunctionBinaryArithmetic<PowImpl, PowName, false>;
template <typename A, typename B>
struct TruncateImpl {
@ -374,7 +397,7 @@ struct TruncateImpl {
struct TruncateName {
static constexpr auto name = "truncate";
};
using FunctionTruncate = FunctionBinaryArithmetic<TruncateImpl, TruncateName>;
using FunctionTruncate = FunctionBinaryArithmetic<TruncateImpl, TruncateName, false>;
/// round(double,int32)-->double
/// key_str:roundFloat64Int32
@ -395,7 +418,7 @@ struct RoundTwoImpl {
my_double_round(static_cast<Float64>(a), static_cast<Int32>(b), false, false));
}
};
using FunctionRoundTwo = FunctionBinaryArithmetic<RoundTwoImpl, RoundName>;
using FunctionRoundTwo = FunctionBinaryArithmetic<RoundTwoImpl, RoundName, false>;
// TODO: Now math may cause one thread compile time too long, because the function in math
// so mush. Split it to speed up compile time in the future