MERGE INTO ////////1 GFO
USING
(SELECT *
FROM
(SELECT facto/////rid,
p-Id,
PRE/////EDATE,
RU//MODE,
cre///date,
ROW_NUMBER() OVER (PARTITION BY facto/////id ORDER BY cre///te DESC) col
FROM ///////////2
) x
WHERE x.col = 1) UFD
ON (GFO.FACTO-/////RID=UFD.FACTO////RID)
WHEN MATCHED THEN UPDATE
SET
GFO.PRE////DATE=UFD.PRE//////DATE
WHERE UFD.CRE/////DATE IS NOT NULL
AND UFD.RU//MODE= 'S'
AND GFO.P////ID=:2
hi every1, my above merge statement is taking too long , it has to run 40 times on table 1 using table2 each having 4millions plus records, for 40 different p--id, please suggest more efficient way as currently its taking 40+ minutes.
its updating only one colummn using a column from table2.t
i am unable to execute the query, its returning
Error: cannot fetch last explain plan from PLAN_TABLE
EXPLAIN PLAN IMAGE
HERE IS THE SCREENSHOT OF EXPLAIN PLAN
cost
The shown plan seems to by OK, the observed problem stems from the LOOP over P_ID that do not scale.
I assume you performs something like this (strongly simplified) - assuming the P_ID to be processed are in table TAB_PID
begin
for cur in (select p_id from tab_pid) loop
merge INTO tab1 USING tab2 ON (tab1.r_id = tab2.r_id)
WHEN MATCHED THEN
UPDATE SET tab1.col1=tab2.col1 WHERE p_id = cur.p_id;
end loop;
end;
/
HASH JOIN on large tables (in NO PARALLEL mode) with elapsed time 60 seconds is not a catastrophic result. But looping 40 times makes your 40 minutes.
So I'd sugesst to try to integrate the loop in the MERGE statement, without knowing details something like this (mayby you'll need also ajdust the MERGE JOIN condition).
merge INTO tab1 USING tab2 ON (tab1.r_id = tab2.r_id)
WHEN MATCHED THEN
UPDATE SET tab1.col1=tab2.col1
WHERE p_id in (select p_id from tab_pid);
Related
I have below kind of script to execute which is taking approx 2 hours to update only 23% of records from the table. table has approx 170K records with 150 columns.
DECLARE
V_EMP_SAL NUMBER;
BEGIN
For EmpIDs in (SELECT EmpID From Employees Where Emp_Address is null and Emp_phone is null and Emp_active='Y')
LOOP
SELECT SUM(EMP_SAL) into V_EMP_SAL FROM Employees
where Emp_ID=EmpIDs.EmpID and Emp_Active='Y';
UPDATE Employees
Set EMP_SAL_HIKE = SAL- V_EMP_SAL
WHERE EMP_ID=EmpIDs.EmpID;
COMMIT;
END LOOP;
EXCEPTION
WHEN OTHERS THEN
DBMS_OUTPUT.PUT_LINE('ERROR OCCURED');
END;
Despite of writing this query in single update like below which is also taking similar time.
UPDATE Employees E1
Set E1.EMP_SAL_HIKE = E1.SAL- (SELECT SUM(EMP_SAL) FROM Employees
where Emp_ID=E1.EmpID and Emp_Active='Y')
WHERE E1.Emp_Address is null
AND E1.Emp_phone is null
AND E1.Emp_active='Y';
my question is
Why is it taking this much of time.
how to know which part is taking more time.
how to optimize this so that this gets executed very fast.
Thanks in advance.
Row-by-row (in a loop) is slow-by-slow.
Your best option is to skip PL/SQL and loop completely and switch to a single update (or merge) statement, e.g.
merge into employees a
using (select emp_id,
sum(emp_sal) v_emp_sal
from employees
where emp_address is null
and emp_phone is null
and emp_active = 'Y'
group by emp_id
) x
on (e.emp_id = x.emp_id)
when matched then update set
a.emp_sal_hike = a.sal - x.v_emp_sal;
I'm trying to update a table based on another one's information:
Source_Table (Table 1) columns:
TABLE_ROW_ID (Based on trigger-sequence when insert)
REP_ID
SOFT_ASSIGNMENT
Description (Table 2) columns:
REP_ID
NEW_SOFT_ASSIGNMENT
This is my loop statement:
SELECT count(table_row_id) INTO V_ROWS_APPROVED FROM Source_Table;
FOR i IN 1..V_ROWS_APPROVED LOOP
SELECT REQUESTED_SOFT_MAPPING INTO V_SOFT FROM Source_Table WHERE ROW_ID = i;
SELECT REP_ID INTO V_REP_ID FROM Source_Table WHERE ROW_ID = i;
UPDATE Description_Table D
SET D.NEW_SOFT_ASSIGNMENT = V_SOFT
WHERE D.REP_ID = V_REP_ID;
END LOOP;
END;
The ending result of this loop is a beautiful ''504 Gateway Time-out''.
I know the issue is on the Update query but there's no other way (I can think about) of doing it.
Can someone give me a hand please?
Thanks
Unless your row_id values are contiguous - i.e. count(row_id) == max(row_id) - then this will get a no-data-found. Sequences aren't gapless, so this seems fairly likely. We have no way of telling if that is happening and somehow that is leaving your connection hanging until it times out, or if it's just taking a long time because you're doing a lot of individual queries and updates over a large data set. (And you may be squashing any errors that do occur, though you haven't shown that.)
You don't need to query and update in a loop though, or even use PL/SQL; you can apply all the values in the source table to the description table with a single update or merge:
merge into description_table d
using source_table s
on (s.rep_id = d.rep_id)
when matched then
update set d.new_soft_assignment = s.requested_soft_mapping;
db<>fiddle with some dummy data, including a non-contiguous row_id to show that erroring.
I am recieving information from a csv file from one department to compare with the same inforation in a different department to check for discrepencies (About 3/4 of a million rows of data with 44 columns in each row). After I have the data in a table, I have a program that will take the data and send reports based on a HQ. I feel like the way I am going about this is not the most efficient. I am using oracle for this comparison.
Here is what I have:
I have a vb.net program that parses the data and inserts it into an extract table
I run a procedure to do a full outer join on the two tables into a new table with the fields in one department prefixed with '_c'
I run another procedure to compare the old/new data and update 2 different tables with detail and summary information. Here is code from inside the procedure:
DECLARE
CURSOR Cur_Comp IS SELECT * FROM T.AEC_CIS_COMP;
BEGIN
FOR compRow in Cur_Comp LOOP
--If service pipe exists in CIS but not in FM and the service pipe has status of retired in CIS, ignore the variance
If(compRow.pipe_num = '' AND cis_status_c = 'R')
continue
END IF
--If there is not a summary record for this HQ in the table for this run, create one
INSERT INTO t.AEC_CIS_SUM (HQ, RUN_DATE)
SELECT compRow.HQ, to_date(sysdate, 'DD/MM/YYYY') from dual WHERE NOT EXISTS
(SELECT null FROM t.AEC_CIS_SUM WHERE HQ = compRow.HQ AND RUN_DATE = to_date(sysdate, 'DD/MM/YYYY'))
-- Check fields and update the tables accordingly
If (compRow.cis_loop <> compRow.cis_loop_c) Then
--Insert information into the details table
INSERT INTO T.AEC_CIS_DET( Fac_id, Pipe_Num, Hq, Address, AutoUpdatedFl,
DateTime, Changed_Field, CIS_Value, FM_Value)
VALUES(compRow.Fac_ID, compRow.Pipe_Num, compRow.Hq, compRow.Street_Num || ' ' || compRow.Street_Name,
'Y', sysdate, 'Cis_Loop', compRow.cis_loop, compRow.cis_loop_c);
-- Update information into the summary table
UPDATE AEC_CIS_SUM
SET cis_loop = cis_loop + 1
WHERE Hq = compRow.Hq
AND Run_Date = to_date(sysdate, 'DD/MM/YYYY')
End If;
END LOOP;
END;
Any suggestions of an easier way of doing this rather than an if statement for all 44 columns of the table? (This is run once a week if it matters)
Update: Just to clarify, there are 88 columns of data (44 of duplicates to compare with one suffixed with _c). One table lists each field in a row that is different so one row can mean 30+ records written in that table. The other table keeps tally of the number of discrepencies for each week.
First of all I believe that your task can be implemented (and should be actually) with staight SQL. No fancy cursors, no loops, just selects, inserts and updates. I would start with unpivotting your source data (it is not clear if you have primary key to join two sets, I guess you do):
Col0_PK Col1 Col2 Col3 Col4
----------------------------------------
Row1_val A B C D
Row2_val E F G H
Above is your source data. Using UNPIVOT clause we convert it to:
Col0_PK Col_Name Col_Value
------------------------------
Row1_val Col1 A
Row1_val Col2 B
Row1_val Col3 C
Row1_val Col4 D
Row2_val Col1 E
Row2_val Col2 F
Row2_val Col3 G
Row2_val Col4 H
I think you get the idea. Say we have table1 with one set of data and the same structured table2 with the second set of data. It is good idea to use index-organized tables.
Next step is comparing rows to each other and storing difference details. Something like:
insert into diff_details(some_service_info_columns_here)
select some_service_info_columns_here_along_with_data_difference
from table1 t1 inner join table2 t2
on t1.Col0_PK = t2.Col0_PK
and t1.Col_name = t2.Col_name
and nvl(t1.Col_value, 'Dummy1') <> nvl(t2.Col_value, 'Dummy2');
And on the last step we update difference summary table:
insert into diff_summary(summary_columns_here)
select diff_row_id, count(*) as diff_count
from diff_details
group by diff_row_id;
It's just rough draft to show my approach, I'm sure there is much more details should be taken into account. To summarize I suggest two things:
UNPIVOT data
Use SQL statements instead of cursors
You have several issues in your code:
If(compRow.pipe_num = '' AND cis_status_c = 'R')
continue
END IF
"cis_status_c" is not declared. Is it a variable or a column in AEC_CIS_COMP?
In case it is a column, just put the condition into the cursor, i.e. SELECT * FROM T.AEC_CIS_COMP WHERE not (compRow.pipe_num = '' AND cis_status_c = 'R')
to_date(sysdate, 'DD/MM/YYYY')
That's nonsense, you convert a date into a date, simply use TRUNC(SYSDATE)
Anyway, I think you can use three single statements instead of a cursor:
INSERT INTO t.AEC_CIS_SUM (HQ, RUN_DATE)
SELECT comp.HQ, trunc(sysdate)
from AEC_CIS_COMP comp
WHERE NOT EXISTS
(SELECT null FROM t.AEC_CIS_SUM WHERE HQ = comp.HQ AND RUN_DATE = trunc(sysdate));
INSERT INTO T.AEC_CIS_DET( Fac_id, Pipe_Num, Hq, Address, AutoUpdatedFl, DateTime, Changed_Field, CIS_Value, FM_Value)
select comp.Fac_ID, comp.Pipe_Num, comp.Hq, comp.Street_Num || ' ' || comp.Street_Name, 'Y', sysdate, 'Cis_Loop', comp.cis_loop, comp.cis_loop_c
from T.AEC_CIS_COMP comp
where comp.cis_loop <> comp.cis_loop_c;
UPDATE AEC_CIS_SUM
SET cis_loop = cis_loop + 1
WHERE Hq IN (Select Hq from T.AEC_CIS_COMP)
AND trunc(Run_Date) = trunc(sysdate);
They are not tested but they should give you a hint how to do it.
I have 2 delete statements that are taking a long time to complete. There are several indexes on the columns in where clause.
What is a duplicate?
If 2 or more records have same values in columns id,cid,type,trefid,ordrefid,amount and paydt then there are duplicates.
The DELETEs delete about 1 million record.
Can they be re-written in any way to make it quicker.
DELETE FROM TABLE1 A WHERE loaddt < (
SELECT max(loaddt) FROM TABLE1 B
WHERE
a.id=b.id and
a.cid=b.cid and
NVL(a.type,'-99999') = NVL(b.type,'-99999') and
NVL(a.trefid,'-99999')=NVL(b.trefid,'-99999') and
NVL(a.ordrefid,'-99999')= NVL(b.ordrefid,'-99999') and
NVL(a.amount,'-99999')=NVL(b.amount,'-99999') and
NVL(a.paydt,TO_DATE('9999-12-31','YYYY-MM-DD'))=NVL(b.paydt,TO_DATE('9999-12-31','YYYY-MM-DD'))
);
COMMIT;
DELETE FROM TABLE1 a where rowid > (
Select min(rowid) from TABLE1 b
WHERE
a.id=b.id and
a.cid=b.cid and
NVL(a.type,'-99999') = NVL(b.type,'-99999') and
NVL(a.trefid,'-99999')=NVL(b.trefid,'-99999') and
NVL(a.ordrefid,'-99999')= NVL(b.ordrefid,'-99999') and
NVL(a.amount,'-99999')=NVL(b.amount,'-99999') and
NVL(a.paydt,TO_DATE('9999-12-31','YYYY-MM-DD'))=NVL(b.paydt,TO_DATE('9999-12-31','YYYY-MM-DD'))
);
commit;
Explain Plan:
DELETE TABLE1
HASH JOIN 1296491
Access Predicates
AND
A.ID=ITEM_1
A.CID=ITEM_2
ITEM_3=NVL(TYPE,'-99999')
ITEM_4=NVL(TREFID,'-99999')
ITEM_5=NVL(ORDREFID,'-99999')
ITEM_6=NVL(AMOUNT,(-99999))
ITEM_7=NVL(PAYDT,TO_DATE(' 9999-12-31 00:00:00', 'syyyy-mm-dd hh24:mi:ss'))
Filter Predicates
LOADDT<MAX(LOADDT)
TABLE ACCESS TABLE1 FULL 267904
VIEW VW_SQ_1 690385
SORT GROUP BY 690385
TABLE ACCESS TABLE1 FULL 267904
How large is the table? If count of deleted rows is up to 12% then you may think about index.
Could you somehow partition your table - like week by week and then scan only actual week?
Maybe this could be more effecient. When you're using aggregate function, then oracle must walk through all relevant rows (in your case fullscan), but when you use exists it stops when the first occurence is found. (and of course the query would be much faster, when there was one function-based(because of NVL) index on all columns in where clause)
DELETE FROM TABLE1 A
WHERE exists (
SELECT 1
FROM TABLE1 B
WHERE
A.loaddt != b.loaddt
a.id=b.id and
a.cid=b.cid and
NVL(a.type,'-99999') = NVL(b.type,'-99999') and
NVL(a.trefid,'-99999')=NVL(b.trefid,'-99999') and
NVL(a.ordrefid,'-99999')= NVL(b.ordrefid,'-99999') and
NVL(a.amount,'-99999')=NVL(b.amount,'-99999') and
NVL(a.paydt,TO_DATE('9999-12-31','YYYY-MM-DD'))=NVL(b.paydt,TO_DATE('9999-12-31','YYYY-MM-DD'))
);
Although some may disagree, I am a proponent of running large, long running deletes procedurally. In my view it is much easier to control and track progress (and your DBA will like you better ;-) Also, not sure why you need to join table1 to itself to identify duplicates (and I'd be curious if you ever run into snapshot too old issues with your current approach). You also shouldn't need multiple delete statements, all duplicates should be handled in one process. Finally, you should check WHY you're constantly re-introducing duplicates each week, and perhaps change the load process (maybe doing a merge/upsert rather than all inserts).
That said, you might try something like:
-- first create mat view to find all duplicates
create materialized view my_dups_mv
tablespace my_tablespace
build immediate
refresh complete on demand
as
select id,cid,type,trefid,ordrefid,amount,paydt, count(1) as cnt
from table1
group by id,cid,type,trefid,ordrefid,amount,paydt
having count(1) > 1;
-- dedup data (or put into procedure and schedule along with mat view refresh above)
declare
-- make sure my_dups_mv is refreshed first
cursor dup_cur is
select * from my_dups_mv;
type duprec_t is record(row_id rowid);
duprec duprec_t;
type duptab_t is table of duprec_t index by pls_integer;
duptab duptab_t;
l_ctr pls_integer := 0;
l_dupcnt pls_integer := 0;
begin
for rec in dup_cur
loop
l_ctr := l_ctr + 1;
-- assuming needed indexes exist
select rowid
bulk collect into duptab
from table1
where id = rec.id
and cid = rec.cid
and type = rec.type
and trefid = rec.trefid
and ordrefid = rec.ordrefid
and amount = rec.amount
and paydt = rec.paydt
-- order by whatever makes sense to make the "keeper" float to top
order by loaddt desc
;
for i in 2 .. duptab.count
loop
l_dupcnt := l_dupcnt + 1;
delete from table1 where rowid = duptab(i).row_id;
end loop;
if (mod(l_ctr, 10000) = 0) then
-- log to log table here (calling autonomous procedure you'll need to implement)
insert_logtable('Table1 deletes', 'Commit reached, deleted ' || l_dupcnt || ' rows');
commit;
end if;
end loop;
commit;
end;
Check your log table for progress status.
1. Parallel
alter session enable parallel dml;
DELETE /*+ PARALLEL */ FROM TABLE1 A WHERE loaddt < (
...
Assuming you have Enterprise Edition, a sane server configuration, and you are on 11g. If you're not on 11g, the parallel syntax is slightly different.
2. Reduce memory requirements
The plan shows a hash join, which is probably a good thing. But without any useful filters, Oracle has to hash the entire table. (Tbone's query, that only use a GROUP BY, looks nicer and may run faster. But it will also probably run into the same problem trying to sort or hash the entire table.)
If the hash can't fit in memory it must be written to disk, which can be very slow. Since you run this query every week, only one of the tables needs to look at all the rows. Depending on exactly when it runs, you can add something like this to the end of the query: ) where b.loaddt >= sysdate - 14. This may significantly reduce the amount of writing to temporary tablespace. And it may also reduce read IO if you use some partitioning strategy like jakub.petr suggested.
3. Active Report
If you want to know exactly what your query is doing, run the Active Report:
select dbms_sqltune.report_sql_monitor(sql_id => 'YOUR_SQL_ID_HERE', type => 'active')
from dual;
(Save the output to an .html file and open it with a browser.)
I've a table in an Oracle (10g XE) database, and I'm going to clean it up and only keep the three recent records of each account. Here is what I'm doing right now:
CREATE TABLE ACCOUNT_TRANSACTION_TMP NOLOGGING AS SELECT * FROM ACCOUNT_TRANSACTION WHERE 1=2;
DECLARE
CURSOR mbsacc_cur (account_id_var account_transaction.account_id%TYPE) IS
SELECT * FROM account_transaction WHERE account_id = account_id_var ORDER BY transaction_time DESC;
account_transaction_rec account_transaction%ROWTYPE;
BEGIN
FOR i IN (SELECT DISTINCT(account_id) FROM account_transaction) LOOP
OPEN mbsacc_cur(i.account_id);
LOOP
FETCH mbsacc_cur INTO account_transaction_rec;
EXIT WHEN mbsacc_cur%NOTFOUND OR mbsacc_cur%ROWCOUNT > 3;
INSERT /*+ append */ INTO account_transaction_tmp VALUES account_transaction_rec;
END LOOP;
CLOSE mbsacc_cur;
END LOOP;
END;
/
And then I'll drop the old table, rename this new one to old one and add constraints.
But the problem is the above code runs forever (~3-4 hours) for about 1 million record which approximately half of them should be removed.
Is there any way to improve the performance of this?
Instead of creating an empty table and populating in an RBAR fashion create a table with the rows you want....
CREATE TABLE ACCOUNT_TRANSACTION_TMP NOLOGGING AS
SELECT account_id, col1, col2, col3, transaction_time from
( select at.*
, row_number()
over (partition by at.account_id
order by at.transaction_time desc) as to_keep
FROM ACCOUNT_TRANSACTION at)
where to_keep <= 3
/
Then skip straight to the renaming part of your plan.
You can do that with analytics (although I am not at all well versed in it myself). Take a look at this question, which seems to address a situation similar to yours:
http://asktom.oracle.com/pls/asktom/f?p=100:11:0::::P11_QUESTION_ID:1212501913138