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体验新版 GitCode,发现更多精彩内容 >>
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c888cbf0
编写于
11月 14, 2022
作者:
H
Haojun Liao
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
refactor: do some internal refactor.
上级
7b53b814
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
305 addition
and
51 deletion
+305
-51
include/libs/function/function.h
include/libs/function/function.h
+1
-1
source/libs/executor/src/executorimpl.c
source/libs/executor/src/executorimpl.c
+8
-8
source/libs/function/src/builtinsimpl.c
source/libs/function/src/builtinsimpl.c
+15
-15
source/libs/function/src/detail/tavgfunction.c
source/libs/function/src/detail/tavgfunction.c
+278
-24
source/libs/function/src/detail/tminmax.c
source/libs/function/src/detail/tminmax.c
+3
-3
未找到文件。
include/libs/function/function.h
浏览文件 @
c888cbf0
...
...
@@ -115,7 +115,7 @@ typedef struct SInputColumnInfoData {
int32_t
startRowIndex
;
// handle started row index
int32_t
numOfRows
;
// the number of rows needs to be handled
int32_t
numOfInputCols
;
// PTS is not included
bool
colData
Agg
IsSet
;
// if agg is set or not
bool
colData
SMA
IsSet
;
// if agg is set or not
SColumnInfoData
*
pPTS
;
// primary timestamp column
SColumnInfoData
**
pData
;
SColumnDataAgg
**
pColumnDataAgg
;
...
...
source/libs/executor/src/executorimpl.c
浏览文件 @
c888cbf0
...
...
@@ -349,13 +349,13 @@ typedef struct {
}
SFunctionCtxStatus
;
static
void
functionCtxSave
(
SqlFunctionCtx
*
pCtx
,
SFunctionCtxStatus
*
pStatus
)
{
pStatus
->
hasAgg
=
pCtx
->
input
.
colData
Agg
IsSet
;
pStatus
->
hasAgg
=
pCtx
->
input
.
colData
SMA
IsSet
;
pStatus
->
numOfRows
=
pCtx
->
input
.
numOfRows
;
pStatus
->
startOffset
=
pCtx
->
input
.
startRowIndex
;
}
static
void
functionCtxRestore
(
SqlFunctionCtx
*
pCtx
,
SFunctionCtxStatus
*
pStatus
)
{
pCtx
->
input
.
colData
Agg
IsSet
=
pStatus
->
hasAgg
;
pCtx
->
input
.
colData
SMA
IsSet
=
pStatus
->
hasAgg
;
pCtx
->
input
.
numOfRows
=
pStatus
->
numOfRows
;
pCtx
->
input
.
startRowIndex
=
pStatus
->
startOffset
;
}
...
...
@@ -372,8 +372,8 @@ void doApplyFunctions(SExecTaskInfo* taskInfo, SqlFunctionCtx* pCtx, SColumnInfo
// not a whole block involved in query processing, statistics data can not be used
// NOTE: the original value of isSet have been changed here
if
(
pCtx
[
k
].
input
.
colData
Agg
IsSet
&&
forwardStep
<
numOfTotal
)
{
pCtx
[
k
].
input
.
colData
Agg
IsSet
=
false
;
if
(
pCtx
[
k
].
input
.
colData
SMA
IsSet
&&
forwardStep
<
numOfTotal
)
{
pCtx
[
k
].
input
.
colData
SMA
IsSet
=
false
;
}
if
(
fmIsWindowPseudoColumnFunc
(
pCtx
[
k
].
functionId
))
{
...
...
@@ -486,7 +486,7 @@ static int32_t doSetInputDataBlock(SExprSupp* pExprSup, SSDataBlock* pBlock, int
SInputColumnInfoData
*
pInput
=
&
pCtx
[
i
].
input
;
pInput
->
uid
=
pBlock
->
info
.
uid
;
pInput
->
colData
Agg
IsSet
=
false
;
pInput
->
colData
SMA
IsSet
=
false
;
SExprInfo
*
pOneExpr
=
&
pExprSup
->
pExprInfo
[
i
];
for
(
int32_t
j
=
0
;
j
<
pOneExpr
->
base
.
numOfParams
;
++
j
)
{
...
...
@@ -798,7 +798,7 @@ void setBlockSMAInfo(SqlFunctionCtx* pCtx, SExprInfo* pExprInfo, SSDataBlock* pB
pInput
->
totalRows
=
numOfRows
;
if
(
pBlock
->
pBlockAgg
!=
NULL
)
{
pInput
->
colData
Agg
IsSet
=
true
;
pInput
->
colData
SMA
IsSet
=
true
;
for
(
int32_t
j
=
0
;
j
<
pExprInfo
->
base
.
numOfParams
;
++
j
)
{
SFunctParam
*
pFuncParam
=
&
pExprInfo
->
base
.
pParam
[
j
];
...
...
@@ -807,7 +807,7 @@ void setBlockSMAInfo(SqlFunctionCtx* pCtx, SExprInfo* pExprInfo, SSDataBlock* pB
int32_t
slotId
=
pFuncParam
->
pCol
->
slotId
;
pInput
->
pColumnDataAgg
[
j
]
=
pBlock
->
pBlockAgg
[
slotId
];
if
(
pInput
->
pColumnDataAgg
[
j
]
==
NULL
)
{
pInput
->
colData
Agg
IsSet
=
false
;
pInput
->
colData
SMA
IsSet
=
false
;
}
// Here we set the column info data since the data type for each column data is required, but
...
...
@@ -818,7 +818,7 @@ void setBlockSMAInfo(SqlFunctionCtx* pCtx, SExprInfo* pExprInfo, SSDataBlock* pB
}
}
}
else
{
pInput
->
colData
Agg
IsSet
=
false
;
pInput
->
colData
SMA
IsSet
=
false
;
}
}
...
...
source/libs/function/src/builtinsimpl.c
浏览文件 @
c888cbf0
...
...
@@ -498,13 +498,13 @@ static int32_t getNumOfElems(SqlFunctionCtx* pCtx) {
int32_t
numOfElem
=
0
;
/*
* 1. column data missing (schema modified) causes pInputCol->hasNull == true. pInput->colData
Agg
IsSet == true;
* 2. for general non-primary key columns, pInputCol->hasNull may be true or false, pInput->colData
Agg
IsSet == true;
* 3. for primary key column, pInputCol->hasNull always be false, pInput->colData
Agg
IsSet == false;
* 1. column data missing (schema modified) causes pInputCol->hasNull == true. pInput->colData
SMA
IsSet == true;
* 2. for general non-primary key columns, pInputCol->hasNull may be true or false, pInput->colData
SMA
IsSet == true;
* 3. for primary key column, pInputCol->hasNull always be false, pInput->colData
SMA
IsSet == false;
*/
SInputColumnInfoData
*
pInput
=
&
pCtx
->
input
;
SColumnInfoData
*
pInputCol
=
pInput
->
pData
[
0
];
if
(
pInput
->
colData
Agg
IsSet
&&
pInput
->
totalRows
==
pInput
->
numOfRows
)
{
if
(
pInput
->
colData
SMA
IsSet
&&
pInput
->
totalRows
==
pInput
->
numOfRows
)
{
numOfElem
=
pInput
->
numOfRows
-
pInput
->
pColumnDataAgg
[
0
]
->
numOfNull
;
ASSERT
(
numOfElem
>=
0
);
}
else
{
...
...
@@ -593,7 +593,7 @@ int32_t sumFunction(SqlFunctionCtx* pCtx) {
goto
_sum_over
;
}
if
(
pInput
->
colData
Agg
IsSet
)
{
if
(
pInput
->
colData
SMA
IsSet
)
{
numOfElem
=
pInput
->
numOfRows
-
pAgg
->
numOfNull
;
ASSERT
(
numOfElem
>=
0
);
...
...
@@ -658,7 +658,7 @@ int32_t sumInvertFunction(SqlFunctionCtx* pCtx) {
SSumRes
*
pSumRes
=
GET_ROWCELL_INTERBUF
(
GET_RES_INFO
(
pCtx
));
if
(
pInput
->
colData
Agg
IsSet
)
{
if
(
pInput
->
colData
SMA
IsSet
)
{
numOfElem
=
pInput
->
numOfRows
-
pAgg
->
numOfNull
;
ASSERT
(
numOfElem
>=
0
);
...
...
@@ -770,7 +770,7 @@ bool getSumFuncEnv(SFunctionNode* UNUSED_PARAM(pFunc), SFuncExecEnv* pEnv) {
// goto _avg_over;
// }
//
// if (pInput->colData
Agg
IsSet) {
// if (pInput->colData
SMA
IsSet) {
// numOfElem = numOfRows - pAgg->numOfNull;
// ASSERT(numOfElem >= 0);
//
...
...
@@ -1161,7 +1161,7 @@ bool getMinmaxFuncEnv(SFunctionNode* UNUSED_PARAM(pFunc), SFuncExecEnv* pEnv) {
// }
//
// // data in current data block are qualified to the query
// if (pInput->colData
Agg
IsSet) {
// if (pInput->colData
SMA
IsSet) {
// numOfElems = pInput->numOfRows - pAgg->numOfNull;
// ASSERT(pInput->numOfRows == pInput->totalRows && numOfElems >= 0);
// if (numOfElems == 0) {
...
...
@@ -2471,7 +2471,7 @@ int32_t percentileFunction(SqlFunctionCtx* pCtx) {
// the first stage, only acquire the min/max value
if
(
pInfo
->
stage
==
0
)
{
if
(
pCtx
->
input
.
colData
Agg
IsSet
)
{
if
(
pCtx
->
input
.
colData
SMA
IsSet
)
{
double
tmin
=
0
.
0
,
tmax
=
0
.
0
;
if
(
IS_SIGNED_NUMERIC_TYPE
(
type
))
{
tmin
=
(
double
)
GET_INT64_VAL
(
&
pAgg
->
min
);
...
...
@@ -2933,14 +2933,14 @@ int32_t firstFunction(SqlFunctionCtx* pCtx) {
pInfo
->
bytes
=
pInputCol
->
info
.
bytes
;
// All null data column, return directly.
if
(
pInput
->
colData
Agg
IsSet
&&
(
pInput
->
pColumnDataAgg
[
0
]
->
numOfNull
==
pInput
->
totalRows
))
{
if
(
pInput
->
colData
SMA
IsSet
&&
(
pInput
->
pColumnDataAgg
[
0
]
->
numOfNull
==
pInput
->
totalRows
))
{
ASSERT
(
pInputCol
->
hasNull
==
true
);
// save selectivity value for column consisted of all null values
firstlastSaveTupleData
(
pCtx
->
pSrcBlock
,
pInput
->
startRowIndex
,
pCtx
,
pInfo
);
return
0
;
}
SColumnDataAgg
*
pColAgg
=
(
pInput
->
colData
Agg
IsSet
)
?
pInput
->
pColumnDataAgg
[
0
]
:
NULL
;
SColumnDataAgg
*
pColAgg
=
(
pInput
->
colData
SMA
IsSet
)
?
pInput
->
pColumnDataAgg
[
0
]
:
NULL
;
TSKEY
startKey
=
getRowPTs
(
pInput
->
pPTS
,
0
);
TSKEY
endKey
=
getRowPTs
(
pInput
->
pPTS
,
pInput
->
totalRows
-
1
);
...
...
@@ -3037,14 +3037,14 @@ int32_t lastFunction(SqlFunctionCtx* pCtx) {
pInfo
->
bytes
=
bytes
;
// All null data column, return directly.
if
(
pInput
->
colData
Agg
IsSet
&&
(
pInput
->
pColumnDataAgg
[
0
]
->
numOfNull
==
pInput
->
totalRows
))
{
if
(
pInput
->
colData
SMA
IsSet
&&
(
pInput
->
pColumnDataAgg
[
0
]
->
numOfNull
==
pInput
->
totalRows
))
{
ASSERT
(
pInputCol
->
hasNull
==
true
);
// save selectivity value for column consisted of all null values
firstlastSaveTupleData
(
pCtx
->
pSrcBlock
,
pInput
->
startRowIndex
,
pCtx
,
pInfo
);
return
0
;
}
SColumnDataAgg
*
pColAgg
=
(
pInput
->
colData
Agg
IsSet
)
?
pInput
->
pColumnDataAgg
[
0
]
:
NULL
;
SColumnDataAgg
*
pColAgg
=
(
pInput
->
colData
SMA
IsSet
)
?
pInput
->
pColumnDataAgg
[
0
]
:
NULL
;
TSKEY
startKey
=
getRowPTs
(
pInput
->
pPTS
,
0
);
TSKEY
endKey
=
getRowPTs
(
pInput
->
pPTS
,
pInput
->
totalRows
-
1
);
...
...
@@ -3988,7 +3988,7 @@ int32_t spreadFunction(SqlFunctionCtx* pCtx) {
SSpreadInfo
*
pInfo
=
GET_ROWCELL_INTERBUF
(
GET_RES_INFO
(
pCtx
));
if
(
pInput
->
colData
Agg
IsSet
)
{
if
(
pInput
->
colData
SMA
IsSet
)
{
numOfElems
=
pInput
->
numOfRows
-
pAgg
->
numOfNull
;
if
(
numOfElems
==
0
)
{
goto
_spread_over
;
...
...
@@ -4163,7 +4163,7 @@ int32_t elapsedFunction(SqlFunctionCtx* pCtx) {
goto
_elapsed_over
;
}
if
(
pInput
->
colData
Agg
IsSet
)
{
if
(
pInput
->
colData
SMA
IsSet
)
{
if
(
pInfo
->
min
==
TSKEY_MAX
)
{
pInfo
->
min
=
GET_INT64_VAL
(
&
pAgg
->
min
);
pInfo
->
max
=
GET_INT64_VAL
(
&
pAgg
->
max
);
...
...
source/libs/function/src/detail/tavgfunction.c
浏览文件 @
c888cbf0
...
...
@@ -48,15 +48,14 @@ typedef struct SAvgRes {
int16_t
type
;
// store the original input type, used in merge function
}
SAvgRes
;
static
void
floatVectorSumAVX
(
const
SInputColumnInfoData
*
pInput
,
const
float
*
plist
,
SAvgRes
*
pRes
)
{
static
void
floatVectorSumAVX
(
const
float
*
plist
,
int32_t
numOfRows
,
SAvgRes
*
pRes
)
{
#if __AVX__
// find the start position that are aligned to 32bytes address in memory
int32_t
startIndex
=
0
;
//((uint64_t)plist) & ((1<<8u)-1);
int32_t
bitWidth
=
8
;
int32_t
remainder
=
numOfRows
%
bitWidth
;
int32_t
rounds
=
numOfRows
/
bitWidth
;
int32_t
remain
=
(
pInput
->
numOfRows
-
startIndex
)
%
bitWidth
;
int32_t
rounds
=
(
pInput
->
numOfRows
-
startIndex
)
/
bitWidth
;
const
float
*
p
=
&
plist
[
startIndex
];
const
float
*
p
=
plist
;
__m256
val
;
__m256
sum
=
_mm256_setzero_ps
();
...
...
@@ -71,18 +70,126 @@ static void floatVectorSumAVX(const SInputColumnInfoData* pInput, const float* p
const
float
*
q
=
(
const
float
*
)
&
sum
;
pRes
->
sum
.
dsum
+=
q
[
0
]
+
q
[
1
]
+
q
[
2
]
+
q
[
3
]
+
q
[
4
]
+
q
[
5
]
+
q
[
6
]
+
q
[
7
];
// calculate the front and the reminder items in array list
for
(
int32_t
j
=
0
;
j
<
startIndex
;
++
j
)
{
pRes
->
sum
.
dsum
+=
plist
[
j
];
int32_t
startIndex
=
rounds
*
bitWidth
;
for
(
int32_t
j
=
0
;
j
<
remainder
;
++
j
)
{
pRes
->
sum
.
dsum
+=
plist
[
j
+
startIndex
];
}
#endif
}
static
void
doubleVectorSumAVX
(
const
double
*
plist
,
int32_t
numOfRows
,
SAvgRes
*
pRes
)
{
#if __AVX__
// find the start position that are aligned to 32bytes address in memory
int32_t
bitWidth
=
4
;
int32_t
remainder
=
numOfRows
%
bitWidth
;
int32_t
rounds
=
numOfRows
/
bitWidth
;
const
double
*
p
=
plist
;
__m256d
val
;
__m256d
sum
=
_mm256_setzero_pd
();
startIndex
+=
rounds
*
bitWidth
;
for
(
int32_t
j
=
0
;
j
<
remain
;
++
j
)
{
for
(
int32_t
i
=
0
;
i
<
rounds
;
++
i
)
{
val
=
_mm256_loadu_pd
(
p
);
sum
=
_mm256_add_pd
(
sum
,
val
);
p
+=
bitWidth
;
}
// let sum up the final results
const
double
*
q
=
(
const
double
*
)
&
sum
;
pRes
->
sum
.
dsum
+=
q
[
0
]
+
q
[
1
]
+
q
[
2
]
+
q
[
3
];
int32_t
startIndex
=
rounds
*
bitWidth
;
for
(
int32_t
j
=
0
;
j
<
remainder
;
++
j
)
{
pRes
->
sum
.
dsum
+=
plist
[
j
+
startIndex
];
}
#endif
}
static
void
i8VectorSumAVX2
(
const
int8_t
*
plist
,
int32_t
numOfRows
,
SAvgRes
*
pRes
)
{
#if __AVX2__
// find the start position that are aligned to 32bytes address in memory
int32_t
bitWidth
=
16
;
int32_t
remainder
=
numOfRows
%
bitWidth
;
int32_t
rounds
=
numOfRows
/
bitWidth
;
const
int8_t
*
p
=
plist
;
__m256i
sum
=
_mm256_setzero_si256
();
for
(
int32_t
i
=
0
;
i
<
rounds
;
++
i
)
{
__m256i
val
=
_mm256_lddqu_si256
((
__m256i
*
)
p
);
// __m256i extVal = _mm256_cvtepi8_epi64(val);
sum
=
_mm256_add_epi8
(
sum
,
val
);
p
+=
bitWidth
;
}
// let sum up the final results
const
int8_t
*
q
=
(
const
int8_t
*
)
&
sum
;
pRes
->
sum
.
isum
+=
q
[
0
]
+
q
[
1
]
+
q
[
2
]
+
q
[
3
];
int32_t
startIndex
=
rounds
*
bitWidth
;
for
(
int32_t
j
=
0
;
j
<
remainder
;
++
j
)
{
pRes
->
sum
.
isum
+=
plist
[
j
+
startIndex
];
}
#endif
}
static
void
i32VectorSumAVX2
(
const
int32_t
*
plist
,
int32_t
numOfRows
,
SAvgRes
*
pRes
)
{
#if __AVX2__
// find the start position that are aligned to 32bytes address in memory
int32_t
bitWidth
=
8
;
int32_t
remainder
=
numOfRows
%
bitWidth
;
int32_t
rounds
=
numOfRows
/
bitWidth
;
const
int32_t
*
p
=
plist
;
__m256i
sum
=
_mm256_setzero_si256
();
for
(
int32_t
i
=
0
;
i
<
rounds
;
++
i
)
{
__m256i
val
=
_mm256_lddqu_si256
((
__m256i
*
)
p
);
sum
=
_mm256_add_epi32
(
sum
,
val
);
p
+=
bitWidth
;
}
// let sum up the final results
const
int64_t
*
q
=
(
const
int64_t
*
)
&
sum
;
pRes
->
sum
.
isum
+=
q
[
0
]
+
q
[
1
]
+
q
[
2
]
+
q
[
3
];
int32_t
startIndex
=
rounds
*
bitWidth
;
for
(
int32_t
j
=
0
;
j
<
remainder
;
++
j
)
{
pRes
->
sum
.
isum
+=
plist
[
j
+
startIndex
];
}
#endif
}
static
void
i64VectorSumAVX2
(
const
int64_t
*
plist
,
int32_t
numOfRows
,
SAvgRes
*
pRes
)
{
#if __AVX2__
// find the start position that are aligned to 32bytes address in memory
int32_t
bitWidth
=
4
;
int32_t
remainder
=
numOfRows
%
bitWidth
;
int32_t
rounds
=
numOfRows
/
bitWidth
;
const
int64_t
*
p
=
plist
;
__m256i
sum
=
_mm256_setzero_si256
();
for
(
int32_t
i
=
0
;
i
<
rounds
;
++
i
)
{
__m256i
val
=
_mm256_lddqu_si256
((
__m256i
*
)
p
);
sum
=
_mm256_add_epi64
(
sum
,
val
);
p
+=
bitWidth
;
}
// let sum up the final results
const
int64_t
*
q
=
(
const
int64_t
*
)
&
sum
;
pRes
->
sum
.
isum
+=
q
[
0
]
+
q
[
1
]
+
q
[
2
]
+
q
[
3
];
int32_t
startIndex
=
rounds
*
bitWidth
;
for
(
int32_t
j
=
0
;
j
<
remainder
;
++
j
)
{
pRes
->
sum
.
isum
+=
plist
[
j
+
startIndex
];
}
#endif
}
static
int32_t
handleFloatCols
(
const
SColumnInfoData
*
pCol
,
const
SInputColumnInfoData
*
pInput
,
SAvgRes
*
pRes
)
{
int32_t
numOfElems
=
0
;
float
*
plist
=
(
float
*
)
pCol
->
pData
;
...
...
@@ -105,7 +212,7 @@ static int32_t handleFloatCols(const SColumnInfoData* pCol, const SInputColumnIn
// 3. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
tsAVXEnable
&&
tsSIMDEnable
)
{
floatVectorSumAVX
(
p
Input
,
plist
,
pRes
);
floatVectorSumAVX
(
p
list
,
pInput
->
numOfRows
,
pRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pRes
->
sum
.
dsum
+=
plist
[
i
];
...
...
@@ -133,8 +240,25 @@ bool avgFunctionSetup(SqlFunctionCtx* pCtx, SResultRowEntryInfo* pResultInfo) {
return
true
;
}
static
int32_t
calculateAvgBySMAInfo
(
SAvgRes
*
pRes
,
int32_t
numOfRows
,
int32_t
type
,
const
SColumnDataAgg
*
pAgg
)
{
int32_t
numOfElem
=
numOfRows
-
pAgg
->
numOfNull
;
ASSERT
(
numOfElem
>=
0
);
pRes
->
count
+=
numOfElem
;
if
(
IS_SIGNED_NUMERIC_TYPE
(
type
))
{
pRes
->
sum
.
isum
+=
pAgg
->
sum
;
}
else
if
(
IS_UNSIGNED_NUMERIC_TYPE
(
type
))
{
pRes
->
sum
.
usum
+=
pAgg
->
sum
;
}
else
if
(
IS_FLOAT_TYPE
(
type
))
{
pRes
->
sum
.
dsum
+=
GET_DOUBLE_VAL
((
const
char
*
)
&
(
pAgg
->
sum
));
}
return
numOfElem
;
}
int32_t
avgFunction
(
SqlFunctionCtx
*
pCtx
)
{
int32_t
numOfElem
=
0
;
int32_t
numOfElem
=
0
;
const
int32_t
THRESHOLD_SIZE
=
8
;
SInputColumnInfoData
*
pInput
=
&
pCtx
->
input
;
SColumnDataAgg
*
pAgg
=
pInput
->
pColumnDataAgg
[
0
];
...
...
@@ -154,19 +278,149 @@ int32_t avgFunction(SqlFunctionCtx* pCtx) {
goto
_avg_over
;
}
if
(
pInput
->
colDataAggIsSet
)
{
numOfElem
=
numOfRows
-
pAgg
->
numOfNull
;
ASSERT
(
numOfElem
>=
0
);
pAvgRes
->
count
+=
numOfElem
;
if
(
IS_SIGNED_NUMERIC_TYPE
(
type
))
{
pAvgRes
->
sum
.
isum
+=
pAgg
->
sum
;
}
else
if
(
IS_UNSIGNED_NUMERIC_TYPE
(
type
))
{
pAvgRes
->
sum
.
usum
+=
pAgg
->
sum
;
}
else
if
(
IS_FLOAT_TYPE
(
type
))
{
pAvgRes
->
sum
.
dsum
+=
GET_DOUBLE_VAL
((
const
char
*
)
&
(
pAgg
->
sum
));
if
(
pInput
->
colDataSMAIsSet
)
{
// try to use SMA if available
numOfElem
=
calculateAvgBySMAInfo
(
pAvgRes
,
numOfRows
,
type
,
pAgg
);
}
else
if
(
!
pCol
->
hasNull
)
{
// try to employ the simd instructions to speed up the loop
numOfElem
=
pInput
->
numOfRows
;
pAvgRes
->
count
+=
pInput
->
numOfRows
;
bool
simdAvaiable
=
tsAVXEnable
&&
tsSIMDEnable
&&
(
numOfRows
>
THRESHOLD_SIZE
);
switch
(
type
)
{
case
TSDB_DATA_TYPE_TINYINT
:
{
const
int8_t
*
plist
=
(
const
int8_t
*
)
pCol
->
pData
;
// 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
simdAvaiable
)
{
i8VectorSumAVX2
(
plist
,
numOfRows
,
pAvgRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pAvgRes
->
sum
.
isum
+=
plist
[
i
];
}
}
break
;
}
case
TSDB_DATA_TYPE_SMALLINT
:
{
const
double
*
plist
=
(
const
double
*
)
pCol
->
pData
;
// 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
simdAvaiable
)
{
doubleVectorSumAVX
(
plist
,
numOfRows
,
pAvgRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pAvgRes
->
sum
.
isum
+=
plist
[
i
];
}
}
break
;
}
case
TSDB_DATA_TYPE_INT
:
{
const
int32_t
*
plist
=
(
const
int32_t
*
)
pCol
->
pData
;
// 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
simdAvaiable
)
{
i32VectorSumAVX2
(
plist
,
numOfRows
,
pAvgRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pAvgRes
->
sum
.
isum
+=
plist
[
i
];
}
}
break
;
}
case
TSDB_DATA_TYPE_BIGINT
:
{
const
int64_t
*
plist
=
(
const
int64_t
*
)
pCol
->
pData
;
// 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
simdAvaiable
)
{
i64VectorSumAVX2
(
plist
,
numOfRows
,
pAvgRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pAvgRes
->
sum
.
isum
+=
plist
[
i
];
}
}
break
;
}
case
TSDB_DATA_TYPE_FLOAT
:
{
const
float
*
plist
=
(
const
float
*
)
pCol
->
pData
;
// 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
simdAvaiable
)
{
floatVectorSumAVX
(
plist
,
numOfRows
,
pAvgRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pAvgRes
->
sum
.
dsum
+=
plist
[
i
];
}
}
break
;
}
case
TSDB_DATA_TYPE_DOUBLE
:
{
const
double
*
plist
=
(
const
double
*
)
pCol
->
pData
;
// 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
simdAvaiable
)
{
doubleVectorSumAVX
(
plist
,
numOfRows
,
pAvgRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pAvgRes
->
sum
.
dsum
+=
plist
[
i
];
}
}
break
;
}
case
TSDB_DATA_TYPE_UTINYINT
:
{
const
double
*
plist
=
(
const
double
*
)
pCol
->
pData
;
// 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
simdAvaiable
)
{
doubleVectorSumAVX
(
plist
,
numOfRows
,
pAvgRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pAvgRes
->
sum
.
usum
+=
plist
[
i
];
}
}
break
;
}
case
TSDB_DATA_TYPE_USMALLINT
:
{
const
double
*
plist
=
(
const
double
*
)
pCol
->
pData
;
// 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
simdAvaiable
)
{
doubleVectorSumAVX
(
plist
,
numOfRows
,
pAvgRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pAvgRes
->
sum
.
usum
+=
plist
[
i
];
}
}
break
;
}
case
TSDB_DATA_TYPE_UINT
:
{
const
double
*
plist
=
(
const
double
*
)
pCol
->
pData
;
// 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
simdAvaiable
)
{
doubleVectorSumAVX
(
plist
,
numOfRows
,
pAvgRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pAvgRes
->
sum
.
usum
+=
plist
[
i
];
}
}
break
;
}
case
TSDB_DATA_TYPE_UBIGINT
:
{
const
double
*
plist
=
(
const
double
*
)
pCol
->
pData
;
// 1. If the CPU supports AVX, let's employ AVX instructions to speedup this loop
if
(
simdAvaiable
)
{
doubleVectorSumAVX
(
plist
,
numOfRows
,
pAvgRes
);
}
else
{
for
(
int32_t
i
=
pInput
->
startRowIndex
;
i
<
pInput
->
numOfRows
+
pInput
->
startRowIndex
;
++
i
)
{
pAvgRes
->
sum
.
usum
+=
plist
[
i
];
}
}
break
;
}
default:
ASSERT
(
0
);
}
}
else
{
// computing based on the true data block
}
else
{
switch
(
type
)
{
case
TSDB_DATA_TYPE_TINYINT
:
{
int8_t
*
plist
=
(
int8_t
*
)
pCol
->
pData
;
...
...
source/libs/function/src/detail/tminmax.c
浏览文件 @
c888cbf0
...
...
@@ -36,7 +36,7 @@ static int32_t i32VectorCmpAVX2(const int32_t* pData, int32_t numOfRows, bool is
if
(
!
isMinFunc
)
{
// max function
for
(
int32_t
i
=
0
;
i
<
rounds
;
++
i
)
{
next
=
_mm256_l
oad
u_si256
((
__m256i
*
)
p
);
next
=
_mm256_l
ddq
u_si256
((
__m256i
*
)
p
);
initialVal
=
_mm256_max_epi32
(
initialVal
,
next
);
p
+=
bitWidth
;
}
...
...
@@ -61,7 +61,7 @@ static int32_t i32VectorCmpAVX2(const int32_t* pData, int32_t numOfRows, bool is
}
}
else
{
// min function
for
(
int32_t
i
=
0
;
i
<
rounds
;
++
i
)
{
next
=
_mm256_l
oad
u_si256
((
__m256i
*
)
p
);
next
=
_mm256_l
ddq
u_si256
((
__m256i
*
)
p
);
initialVal
=
_mm256_min_epi32
(
initialVal
,
next
);
p
+=
bitWidth
;
}
...
...
@@ -369,7 +369,7 @@ int32_t doMinMaxHelper(SqlFunctionCtx* pCtx, int32_t isMinFunc) {
}
// data in current data block are qualified to the query
if
(
pInput
->
colData
Agg
IsSet
)
{
if
(
pInput
->
colData
SMA
IsSet
)
{
numOfElems
=
pInput
->
numOfRows
-
pAgg
->
numOfNull
;
ASSERT
(
pInput
->
numOfRows
==
pInput
->
totalRows
&&
numOfElems
>=
0
);
if
(
numOfElems
==
0
)
{
...
...
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