SQL query, function or SP for converting varbinary to image(.jpg format).
Dear Sir/Mam
I want SQL query, function or SP which converts binary data to image (.jpg format).
I m able to convert image (.jpg format) to varbinary. But not able to convert vice versa.
thanks in advance.
Binary data is binary data - "image" is only an intrepretation of binary data. Therefore your question makes little sense in the context of sql server since it does not have any facilities to utilize images. Since you provide no context, I'm
guessing that you are trying to retrieve an image stored in the database in a varbinary column and have your application use it as an image. If so, you should post your question to a forum that is specific to your development environment.
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SQL Query - store the result for optimization?
Good day experts,
I am looking for advice on a report. I did a lot of analytic functions to get core data that I need to make my report and its takes around 50 min for SQL to complete. Now with this data I need to create 3 different reports and I cant use the same SQL since there is a lot of agregation (example would be group by product in one case and by client in 2nd). For each of those different group bys I need a different report.
So how to create 3 reports from 1 SQL query without running the query 3 times?
First thing that comes to mind is to store the result set into a dummy table and then query the table since the core data I get is around 300 rows and then do different group bys.
Best regards,
IgorSo how to create 3 reports from 1 SQL query without running the query 3 times?
You already know the obvious answer - store the data 'somewhere'.
The appropriate 'somewhere' depends on your actual business requirements and you did not provide ALL of them.
MV - if the query is always the same you could use an MV and do a complete refresh when you want new data. The data is permanent and can be queried by other sessions but the query that accesses the data will be frozen into the MV definition.
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First thing that comes to mind is to store the result set into a dummy table and then query the table since the core data I get is around 300 rows and then do different group bys.
That is commonly referred to as a 'REPORT-READY table'. Those are useful when the data needs to be permanent and available to multiple sessions/users. Typically there is a batch process (e.g. package procedure) that periodically refreshes/updates the data during an outage window. Or the table can have a column (e.g. AS_OF) that lets it contain multiple sets of data and the update process leaves existing data alone and creates a new set of data.
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Hi ,
I have problems writing a difficult sql query, please help me
I have a table t in which there are 50000 records
the table has columns like
create table t
(MATCH_ID NUMBER(4) NOT NULL,
TEAM_ID NUMBER(4),
PLAYER_ID NUMBER(4),
RUNS NUMBER(3))
here match_id, player_id and team_id are jointly primary key
SQL> SELECT * FORM T WHERE MATCH_ID < 10
MATCH_ID TEAM_ID PL_ID RUNS
1 2 1228 8
1 2 1203 82
1 2 1316 24
1 1 1150 27
1 1 1278 13
1 1 1243 60
2 1 1278 37
2 1 1291 0
2 1 1243 53
2 2 1228 25
2 2 1285 103
2 2 1316 60
3 2 1228 8
3 2 1285 25
3 2 858 43
3 1 1278 52
3 1 1394 6
3 1 1243 31
4 1 1278 61
4 1 1394 6
4 1 1243 3
4 2 1228 41
4 2 1285 40
4 2 858 5
6 2 1228 20
6 2 1285 100
6 2 1408 0
7 2 1228 15
7 2 1285 34
7 2 1408 44
8 2 1228 0
8 2 1420 31
8 2 1340 66
9 2 1420 19
9 2 1385 28
9 2 1340 0
.....so on upto 50000 records..
the problem is that I want to extract how many times each player_id in each
match exists in the table, prior to that match_id (or current_match_id)
along with that in another column, I also want the sum of 'RUNS' for each
player_id prior to that match_id (or current_match_id)
my disired output is:
MATCH_ID TEAM_ID player_ID RUNS NO_OF_OCCURENCES SUM(RUNS)
BEFORE_THIS_MATCH BEFORE_THIS_MATCH
FOR_THIS_PLAYER_ID FOR_THIS_PLAYER_ID
1 2 1228 8 0 0
1 2 1203 82 0 0
1 2 1316 24 0 0
1 1 1150 27 0 0
1 1 1278 13 0 0
1 1 1243 60 0 0
2 1 1278 37 1 13
2 1 1291 0 0 0
2 1 1243 53 1 60
2 2 1228 25 1 8
2 2 1285 103 0 0
2 2 1316 60 1 24
3 2 1228 8 2 33
3 2 1285 25 1 103
3 2 858 43 0 0
3 1 1278 52 2 50
3 1 1394 6 0 0
3 1 1243 31 2 113
4 1 1278 61 3 102
4 1 1394 6 1 6
4 1 1243 3 3 144
4 2 1228 41 3 41
4 2 1285 40 2 128
4 2 858 5 1 43
6 2 1228 20 4 82
6 2 1285 100 3 168
6 2 1408 0 0 0
7 2 1228 15 5 102
7 2 1285 34 4 268
7 2 1408 44 1 0
8 2 1228 0 6 117
8 2 1420 31 0 0
8 2 1340 66 0 0
9 2 1420 19 1 31
9 2 1385 28 0 0
9 2 1340 0 1 66
as you can see from the above data (5TH COLUMN), i have mentioned the
existance of each player_id in each match prior to the current_match_id
since match_id = 1 is the 1st match in the table so no player_id comes in the
table before match number 1.
In match number 2 , player_id = 1278 was also present in match_id = 1 so
thats why Number_OF_OCCURENCES = 1 for player_id = 1278 in match_id = 2
and so on..
same is the case with 'RUNS' column but here RUNS are the SUM of each
player_id's 'RUNS' before the current match
Note: if some player_id does not exist in the table before the current
match_ID then the query should return zero for that player_id ( as in 4th and
5th columns of no_of_occurances and sum(runs) respectively)
for example: in above data
MATCH_ID TEAM_ID PLayer_ID RUNS NO_OF_OCCURENCES SUM(RUNS)
BEFORE_THIS_MATCH BEFORE_THIS_MATCH
FOR_THIS_PLAYER_ID FOR_THIS_PLAYER_ID
9 2 1385 28 0 0
I hope this will clear my problem
i would be extremely grateful if someone helps me out??
here is sample ddl of the above data
create table t
(MATCH_ID NUMBER(4) NOT NULL,
TEAM_ID NUMBER(4),
PLAYER_ID NUMBER(4),
RUNS NUMBER(3))
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (1, 2, 1228, 8);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (1, 2, 1203, 82);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (1, 2, 1316, 24);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (1, 1, 1150, 27);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (1, 1, 1278, 13);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (1, 1, 1243, 60);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (2, 1, 1278, 37);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (2, 1, 1291, 0);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (2, 1, 1243, 53);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (2, 2, 1228, 25);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (2, 2, 1285, 103);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (2, 2, 1316, 60);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (3, 2, 1228, 8);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (3, 2, 1285, 25);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (3, 2, 858, 43);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (3, 1, 1278, 52);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (3, 1, 1394, 6);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (3, 1, 1243, 31);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (4, 1, 1278, 61);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (4, 1, 1394, 6);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (4, 1, 1243, 3);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (4, 2, 1228, 41);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (4, 2, 1285, 40);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (4, 2, 858, 5);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (6, 2, 1228, 20);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (6, 2, 1285, 100);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (6, 2, 1408, 0);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (7, 2, 1228, 15);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (7, 2, 1285, 34);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (7, 2, 1408, 44);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (8, 2, 1228, 0);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (8, 2, 1420, 31);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (8, 2, 1340, 66);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (9, 2, 1420, 19);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (9, 2, 1385, 28);
insert into t (MATCH_ID, TEAM_ID, PLAYER_ID, RUNS) values (9, 2, 1340, 0);regards
ramis.Ramis,
SQL> select * from tt;
MATCH_ID TEAM_ID PLAYER_ID RUNS
1 2 1228 8
1 2 1203 82
1 2 1316 24
1 1 1150 27
1 1 1278 13
1 1 1243 60
2 1 1278 37
2 1 1291 0
2 1 1243 53
2 2 1228 25
2 2 1285 103
2 2 1316 60
3 2 1228 8
3 2 1285 25
3 2 858 43
3 1 1278 52
3 1 1394 6
3 1 1243 31
4 1 1278 61
4 1 1394 6
4 1 1243 3
4 2 1228 41
4 2 1285 40
4 2 858 5
6 2 1228 20
6 2 1285 100
6 2 1408 0
7 2 1228 15
7 2 1285 34
7 2 1408 44
8 2 1228 0
8 2 1420 31
8 2 1340 66
9 2 1420 19
9 2 1385 28
9 2 1340 0
36 rows selected.
SQL> select tt.match_id,
tt.team_id,
tt.player_id,
tt.runs,
nvl(a.sum_player,0) OCC,
nvl(b.sum_runs,0) SUM_RUNS
from
tt,
(select a.match_id,a.team_id,a.player_id,a.runs,count(*) sum_player
from tt a,
(select match_id,player_id
from tt
group by match_id,player_id) b
where a.match_id>b.match_id
and a.player_id=b.player_id
group by a.match_id,a.team_id,a.player_id,a.runs
) a,
(select a.match_id,a.team_id,a.player_id,a.runs,sum(b.runs) sum_runs
from tt a,
(select match_id,player_id,runs
from tt) b
where a.match_id>b.match_id
and a.player_id=b.player_id
group by a.match_id,a.team_id,a.player_id,a.runs
) b
where tt.match_id=a.match_id(+)
and tt.team_id=a.team_id(+)
and tt.player_id=a.player_id(+)
and tt.match_id=b.match_id(+)
and tt.team_id=b.team_id(+)
and tt.player_id=b.player_id(+)
MATCH_ID TEAM_ID PLAYER_ID RUNS OCC SUM_RUNS
1 1 1150 27 0 0
1 1 1243 60 0 0
1 1 1278 13 0 0
1 2 1203 82 0 0
1 2 1228 8 0 0
1 2 1316 24 0 0
2 1 1243 53 1 60
2 1 1278 37 1 13
2 1 1291 0 0 0
2 2 1228 25 1 8
2 2 1285 103 0 0
2 2 1316 60 1 24
3 1 1243 31 2 113
3 1 1278 52 2 50
3 1 1394 6 0 0
3 2 858 43 0 0
3 2 1228 8 2 33
3 2 1285 25 1 103
4 1 1243 3 3 144
4 1 1278 61 3 102
4 1 1394 6 1 6
4 2 858 5 1 43
4 2 1228 41 3 41
4 2 1285 40 2 128
6 2 1228 20 4 82
6 2 1285 100 3 168
6 2 1408 0 0 0
7 2 1228 15 5 102
7 2 1285 34 4 268
7 2 1408 44 1 0
8 2 1228 0 6 117
8 2 1340 66 0 0
8 2 1420 31 0 0
9 2 1340 0 1 66
9 2 1385 28 0 0
9 2 1420 19 1 31
36 rows selected.
SQL> Is this do you want ?
Nicolas. -
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I am running concurrent program,that is taking time to execute ,i want to know which sql query causing performance
Thanaks,
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My Learning: Diagnosing Oracle Applications Concurrent Programmes - 11i/R12
How to run a Trace for a Concurrent Program? (Doc ID 415640.1)
FAQ: Common Tracing Techniques in Oracle E-Business Applications 11i and R12 (Doc ID 296559.1)
How To Get Level 12 Trace And FND Debug File For Concurrent Programs (Doc ID 726039.1)
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Regards
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Regards,
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EXPORTING
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Sql query to betwen clause for date
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COURSESTUDENT.Year,
MARKS.ExamMark,
MARKS.EntryNo
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//g=255
//b=255
rgb = ColorConversionOps.convert32_16(rgb);
ColorConversionOps.printRGB_16((short)rgb);
//a=15
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rgb = ColorConversionOps.convert16_32((short)rgb);
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Tuning SQL query with similar subqueries for select columns
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1> SELECT
2> A.COL1,
3> SUM(CASE WHEN A.flag=100 AND NVL(B.flag,0)=0 AND
4> EXISTS (
5> SELECT 'ROW_EXISTS'
6> FROM A A0
7> WHERE A0.COL2=100 AND NVL(A0.flag,0)=0 AND 0.DIRN<>A.DIRN)
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18>END) SUM_COLUMN2
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20>WHERE A.COL=B.KEY_COL
21>GROUP BY A.COL1
My problem is that I need to index scan the tables A aliased as A0 in the two exist queries. Lines: 5-7 and 13-15.
The major performance degradation i see with the query is that it has to scan A0 twice to compute SUM_COLUMN1 and SUM_COLUMN2.
Is there any way by which i can use the same subquery to scan the table just once to compute the columns.
The table A has more than a 100million records. So i need to improve performance of this query though it is a small issue.
Please feel free to ask me more if i'm not clear with the example.
Thanks in advance,
RajAlso you could use analytic functions:
SQL> select deptno, sum(case when e.mgr is not null and
2 exists (select 1 from emp e1 where e1.empno <> e.empno
3 and e1.deptno = 10 and e1.sal >= 1500)
4 then 1 else 0 end) sum1,
5 sum(case when e.mgr is not null and e.sal >= 1200 and
6 exists (select 1 from emp e1 where e1.empno <> e.empno and e1.deptno = 10)
7 then 1 else 0 end) sum2
8 from emp e
9 group by deptno
10 /
DEPTNO SUM1 SUM2
10 2 2
20 5 3
30 6 5
SQL> select deptno, sum(case when mgr is not null and
2 (d12 != empno or empno !=d11) then 1 else 0 end) sum1,
3 sum(case when mgr is not null and (d21 != empno or empno !=d22)
4 and sal >= 1200 then 1 else 0 end) sum2
5 from (
6 select deptno, empno, mgr, sal,
7 min(case when deptno = 10 and sal >= 1500
8 then empno else -1 end) over(order by null) d11,
9 max(case when deptno = 10 and sal >= 1500
10 then empno else -1 end) over(order by null) d12,
11 min(case when deptno = 10 then empno else -1 end) over(order by null) d21,
12 max(case when deptno = 10 then empno else -1 end) over(order by null) d22
13 from emp e
14 )
15 group by deptno
16 /
DEPTNO SUM1 SUM2
10 2 2
20 5 3
30 6 5In your case it could be something like
SELECT COL1,
SUM( CASE WHEN a_flag = 100 and nvl(b_flag,0)=0 and
(DIRN != MIN_A OR DIRN != MAX_A) THEN 1 ELSE 0 END) SUM_COLUMN1,
SUM( CASE WHEN a_flag = 100 and
(DIRN != MIN_B OR DIRN != MAX_B) THEN 1 ELSE 0 END) SUM_COLUMN2
FROM (
SELECT A.COL1, A.FLAG A_FLAG, B.FLAG B_FLAG, A.DIRN,
MIN(CASE WHEN A.COL2=100 and NVL(A.flag,0) = 0 THEN A.DIRN ELSE null END) OVER(order by null) MIN_A,
MAX(CASE WHEN A.COL2=100 and NVL(A.flag,0) = 0 THEN A.DIRN ELSE null END) OVER(order by null) MAX_A,
MIN(CASE WHEN A.COL2=100 THEN A.DIRN ELSE null END) OVER(order by null) MIN_B,
MAX(CASE WHEN A.COL2=100 THEN A.DIRN ELSE null END) OVER(order by null) MAX_B
FROM A,B
WHERE A.COL=B.KEY_COL
GROUP BY COL1
Rgds.
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