bill/AQuery
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

bug fixes, restructure, user module parsing

Browse Source
This commit is contained in:
bill
2022-08-26 08:35:09 +08:00
parent 1732835692
commit 42c334af84
25 changed files with 173 additions and 51 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tests/funcs.a
+35
View File
@@ -0,0 +1,35 @@
FUNCTION covariance (x , y ) {
xmean := avg (x) ;
ymean := avg (y) ;
avg (( x - xmean ) * (y - ymean ))
}
FUNCTION sd ( x) {
sqrt ( covariance (x , x) )
}
AGGREGATION FUNCTION covariances(x, y, w){
static xmeans := 0, ymeans := 0, cnt := 0;
if (cnt < w) { xmeans += x; }
else {
xmeans += (x - x.vec[cnt - w]) / w;
ymeans += (y - y.vec[cnt - w]) / w;
}
avg (( x.vec(x.len-w, x.len) - xmean ) * (y.vec(y.len - w, y.len) - ymean ))
}
FUNCTION pairCorr (x , y ) {
covariance (x , y ) / ( sd (x) * sd (y ))
}
CREATE TABLE test1(a INT, b INT, c INT, d INT)
LOAD DATA INFILE "test.csv"
INTO TABLE test1
FIELDS TERMINATED BY ","
SELECT pairCorr(c, b) * d, sum(a), b
FROM test1
group by c,b,d
order by b ASC
tests/joins.a
+34
View File
@@ -0,0 +1,34 @@
FUNCTION covariance (x , y ) {
xmean := avg (x) ;
ymean := avg (y) ;
avg (( x - xmean ) * (y - ymean ))
}
FUNCTION sd ( x) {
sqrt ( covariance (x , x) )
}
FUNCTION pairCorr (x , y ) {
covariance (x , y ) / ( sd (x) * sd (y ))
}
-- FUNCTION covariances (w, x , y ) {
-- xmean := avgs (w, x) ;
-- ymean := avgs (y) ;
-- avg (( x - xmean ) * (y - ymean ))
-- }
CREATE TABLE tt(a INT, b INT, c INT, d INT)
LOAD DATA INFILE "test.csv"
INTO TABLE tt
FIELDS TERMINATED BY ","
CREATE TABLE sale(Mont INT, sales INT)
LOAD DATA INFILE "moving_avg.csv"
INTO TABLE sale
FIELDS TERMINATED BY ","
select sd(a) + sales from tt, sale where tt.a = sale.Mont
tests/modules.a
+5
View File
@@ -0,0 +1,5 @@
LOAD MODULE FROM "test.so"
FUNCTIONS (
div(a:int, b:int) -> double,
mulvec(a:int, b:vecfloat) -> vecfloat
);
tests/moving_avg.a
+14
View File
@@ -0,0 +1,14 @@
CREATE TABLE sale(Mont INT, sales INT)
LOAD DATA INFILE "moving_avg.csv"
INTO TABLE sale
FIELDS TERMINATED BY ","
SELECT Mont,avgs(3,sales)
FROM sale
ASSUMING ASC Mont
INTO OUTFILE "moving_avg_output.csv"
FIELDS TERMINATED BY ";"
select Mont, mins(2,sales) from sale assuming desc Mont group by Mont
into outfile "flatten.csv"
tests/q.sql
+112
View File
@@ -0,0 +1,112 @@
FUNCTION
execStrategy ( alloc , mavgday , mavgmonth , px ) {
buySignal := mavgday > mavgmonth ;
f := a + b ;
alloc * prd (
CASE maxs ( buySignal )
WHEN TRUE THEN
CASE buySignal
WHEN TRUE THEN 1 / px
ELSE px
END
ELSE 1
END )
}
FUNCTION covariance (x , y ) {
xmean := avg (x) ;
ymean := avg (y) ;
avg (( x - xmean ) * (y - ymean ))
}
FUNCTION sd ( x) {
sqrt ( covariance (x , x) )
}
FUNCTION pairCorr (x , y ) {
covariance (x , y ) / ( sd (x) * sd (y ))
}
<k>
`
p:5
q:2
phi:(p+1)?1.
theta:q?1.
"p q phi theta"
p
q
phi
theta
l:()
e:()
`
L1:10?20
Le1:10?2.
L2:3?20
Le2:3?2.
"L1 Le1 L2 Le2"
L1
Le1
L2
Le2
`
"Add L1, then predict"
l:l,L1
e:e,Le1
predict:(phi(0)) + (sum ({[x](phi(x+1)) * (l(((#l)-1)-x))}[!p])) - (sum ({[x](theta(x)) * (e(((#e)-1)-x))}[!q]))
predict
`
"Add L2, then predict"
l:l,L2
e:e,Le2
predict:(phi(0)) + (sum ({[x](phi(x+1)) * (l(((#l)-1)-x))}[!p])) - (sum ({[x](theta(x)) * (e(((#e)-1)-x))}[!q]))
predict
</k>
WITH
Target (Id , TradeDate , ClosePrice ) AS
( SELECT
Id , TradeDate , ClosePrice
FROM price
WHERE Id IN stock10 AND
TradeDate >= startYear10 AND
TradeDate <= startYear10 + 365 * 10),
weekly (Id , bucket , name , low , high , mean ) AS
( SELECT
Id ,
timeBucket ,
" weekly " ,
min ( ClosePrice ) ,
max ( ClosePrice ) ,
avg ( ClosePrice )
FROM Target
GROUP BY Id , getWeek ( TradeDate ) as
timeBucket ),
monthly ( Id , bucket , name , low , high , mean ) AS
( SELECT
Id ,
timeBucket ,
" monthly " ,
min ( ClosePrice ) ,
max ( ClosePrice ) ,
avg ( ClosePrice )
FROM Target
GROUP BY Id , getMonth ( TradeDate ) as
timeBucket ),
yearly (Id , bucket , name , low , high , mean ) AS
( SELECT
Id ,
timeBucket ,
" yearly " ,
min ( ClosePrice ) ,
max ( ClosePrice ) ,
avg ( ClosePrice )
FROM Target
GROUP BY Id , getYear ( TradeDate ) as
timeBucket )
SELECT
Id , bucket , name , low , high , mean
FROM
CONCATENATE ( weekly , monthly , yearly )
ASSUMING ASC Id , ASC name , ASC bucket
tests/q1.sql
+10
View File
@@ -0,0 +1,10 @@
CREATE TABLE testq1(a INT, b INT, c INT, d INT)
LOAD DATA INFILE "test.csv"
INTO TABLE testq1
FIELDS TERMINATED BY ","
SELECT sum(c), b, d
FROM testq1
group by a,b,d
order by d DESC, b ASC
tests/stock.a
+32
View File
@@ -0,0 +1,32 @@
CREATE TABLE stocks(timestamp INT, price INT)
INSERT INTO stocks VALUES(1,15)
INSERT INTO stocks VALUES(2,19)
INSERT INTO stocks VALUES(3,16)
INSERT INTO stocks VALUES(4,17)
INSERT INTO stocks VALUES(5,15)
INSERT INTO stocks VALUES(6,13)
INSERT INTO stocks VALUES(7,5)
INSERT INTO stocks VALUES(8,8)
INSERT INTO stocks VALUES(9,7)
INSERT INTO stocks VALUES(10,13)
INSERT INTO stocks VALUES(11,11)
INSERT INTO stocks VALUES(12,14)
INSERT INTO stocks VALUES(13,10)
INSERT INTO stocks VALUES(14,5)
INSERT INTO stocks VALUES(15,2)
INSERT INTO stocks VALUES(16,5)
/*<k> "q1" </k>*/
-- SELECT max(price-min(timestamp)) FROM stocks
/*<k> "q2" </k>*/
-- SELECT max(price-mins(price)) FROM stocks
/*<k> "q3"</k>*/
SELECT price, timestamp FROM stocks where price - timestamp > 1 and not (price*timestamp<100)
/*<k> "q4"</k>*/
-- SELECT max(price-mins(price))
-- FROM stocks
-- ASSUMING DESC timestamp
tests/strings.a
+7
View File
@@ -0,0 +1,7 @@
CREATE TABLE types_test(names varchar(10), val real, id int)
LOAD DATA INFILE "datatypes.csv"
INTO TABLE types_test
FIELDS TERMINATED BY ","
select names, val * 10000 + id from types_test
tests/udf2.a
+14
View File
@@ -0,0 +1,14 @@
AGGREGATION FUNCTION covariances(x, y, w){
static xmeans := 0., ymeans := 0., cnt := 0;
if (cnt < w)
{
xmeans += x;
ymeans += y;
cnt+=1;
}
else {
xmeans += (x - x.vec[cnt - w]) / w;
ymeans += (y - y.vec[cnt - w]) / w;
}
avg (( x.vec(x.len-w, x.len) - xmeans ) * (y.vec(y.len - w, y.len) - ymeans ))
}
tests/udf3.a
+39
View File
@@ -0,0 +1,39 @@
AGGREGATION FUNCTION covariances2(x, y, w){
xmeans := 0.;
ymeans := 0.;
l := _builtin_len;
if (l > 0)
{
xmeans := x[0];
ymeans := y[0];
_builtin_ret[0] := 0.;
}
if (w > l)
w := l;
for (i := 1, j:= 0; i < w; i := i+1) {
xmeans += x[i];
ymeans += y[i];
_builtin_ret[i] := avg (( x(0, i) - xmeans/i ) * (y(0, i) - ymeans/i ));
}
xmeans /= w;
ymeans /= w;
for (i := w; i < l; i += 1)
{
xmeans += (x[i] - x[i - w]) / w;
ymeans += (y[i] - y[i - w]) / w;
_builtin_ret[i] := avg (( x(i-w, i) - xmeans ) * (y(i - w, i) - ymeans ));
}
Null
}
CREATE TABLE test(a INT, b INT, c INT, d INT)
LOAD DATA INFILE "test2.csv"
INTO TABLE test
FIELDS TERMINATED BY ","
select covariances2(a, b, 4), a+b from test group by c;
tests/udf4.a
+32
View File
@@ -0,0 +1,32 @@
AGGREGATION FUNCTION covariances2(x, y, w){
xmeans := 0.;
ymeans := 0.;
l := _builtin_len;
if (w > l)
w := l;
elif (w > l + 2)
{
l := 3;
w := 4;
}
elif(w < 99){
l := 8;
}
elif(w<999)
w := 6;
else
l := l / 2;
for (i := 0, j:= 0; i < w; i := i+1) {
xmeans += x[i];
ymeans += y[i];
_builtin_ret[i] := avg (( x(l-w, l) - xmeans ) * (y(l - w, l) - ymeans ));
}
for (i := 0; i < l; i += 1)
{
xmeans += (x[i] - x[i - w]) / w;
ymeans += (y[i] - y[i - w]) / w;
_builtin_ret[i] := avg (( x(l-w, l) - xmeans ) * (y(l - w, l) - ymeans ));
}
Null
}