what the principal things to look at when we have for the same query different performance results are?I have 2 different bases: the plan and data are the same but performance results are very differents.
View 10 RepliesI've got a query running a select count (*) over a table. The default plan takes in the order of 15 minutes to return, a hinted plan to use a different index takes 3 minutes to return.
Unfortunately I cant get at the index stats and a few other areas which I suspect may be key here.When running autotrace against the two queries I see fairly different values as one would expect.
Query
select count (*) from fulfilmentitem bfi where created >= sysdate-30 AND bfi.status = 'FA' AND bfi.fulfilmentmethod = 'D'
Slow run
PLAN_TABLE_OUTPUT
-----------------------------------------------------------------------------------------------
----------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)|
----------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 15 | 33119 (1)|
| 1 | SORT AGGREGATE | | 1 | 15 | |
|* 2 | TABLE ACCESS BY INDEX ROWID| FULFILMENTITEM | 12525 | 183K| 33119 (1)|
|* 3 | INDEX RANGE SCAN | IDX_FULFIL_METHODSTATUS | 250K| | 1786 (1)|
----------------------------------------------------------------------------------------------
[code]....
IDX_FULFIL_METHODSTATUS is across FULFILMENTMETHOD & STATUS in that order.
IDX_BFI_CREATED is on CREATED and is approx 70% of the size of the other index
The row counts estimated in the explain plan are out, the count(*) comes in at 32.8k rows.As you will have seen, the fast run shows a pretty significant consistent get increase compared to the slow run and a decent though not dramatic physical read drop.
My uncertainty is around if these changes in consistent get/phys read values would typically be enough to suggest the real time improvements I'm observing or if other (albeit perhaps temporary) factors are involved. It is a prod OLTP environment so the data will be rapidly changing and that may be a factor.
I know it can never be an exact science without intimately knowing the hardware/current loads etc but I also know that there's enough experience on these boards to have a loose handle on if the time shifts between queries are likely (or not) to be reflective of the stat changes or if those differences alone shouldn't (or typically wouldn't account) for it.
I'm thinking about instructing the query to ignore its original plan but am hesitant to do so without being a little more confident that it's not just a timing thing or something other than the change of index approach which may be causing the improvement. the autotrace stat changes observed I couldn't put my hand on heart say "yup - that change is good, ignore the default index all the time for this job".
How the length of column width effects index performance?
For example if i had IOT table emp_iot with columns:
(id number,
job varchar2(20),
time date,
plan number)
Table key consist of(id, job, time)
Column JOB has fixed list of distinct values ('ANALYST', 'NIGHT_WORKED', etc...).
What performance increase i could expect if in column "job" i would store not names but concrete numbers identifying job names.
For e.g. i would store "1" instead 'ANALYST' and "2" instead 'NIGHT_WORKED'.
I have a question about database fragmentation.I know that fragmentation can reduce performance in query times. The blocks are distributed in many extents and scans process takes a long time. Oracle engine have to locate the address of the next extent..
I want to know if there is any system view in which you can check if your table or index has high fragmentation. If it's needed I will have to re-create, move or rebulid the table or index, but before I want to know if the degree of fragmentation is high.
Any useful script or query to do this, any interesting oracle system view?
How many records could I have in a single table without performance degradation with Standard Edition without partitioning with cutting-edge server (8 or 12 cores, 72 GB RAM, FC 4 Gbit, etc...) and good storage?
300 Millions in only one table with 500K transactions / day is too much?
Simple database with simple schema.
How many records begin to be too many?
Testing our 9i to 11g upgrade, we've imported the entire DB into the new machine.We've found that certain procedures are really suffering performance problems. BUT, we've also found, that if we check out a production copy of the procedure from our source code control, and reinstall it, the performance issue goes away. Just alter the procedure and recompiling does NOT work.
The new machine where the 11g database exists is slightly different than the source, but it's not like we have this problem with every procedure. It's only a couple.
any possible reason that we'd have to re-install a procedure to correct a performance problem?
I need to check the package performance and need to improve the package performance.
1. how to check the package performance(each and every statement in the package)?
2. In the package using the delete statement to delete all records and observed that delete is taking long time to delete all the records in the table(Table records 7000000). This table is like staging table.Daily need to clean the data before inserting the data into it. what can I use instead of Delete.
Somewhere I read that we should not use hints in Oracle production environments, but we can use hints in the development environment and on achieving the desired execution plan we can adjust the 'statistics' to follow that plan without hints.
Q1. If it is true what statistics do we adjust for influencing the execution plan and how?
For example, I have the following simple query:
select e.empid, e.ename, d.dname
from emp e, dept d
where e.deptno=d.deptno;
emp.empid, emp.deptno and dep.deptno columns have indexes and the tables have the standard structure as found in the basic oracle examples.
If I look at the execution plan of the above query then I see that the driving table is empand the driven table is dept.Also the type of join that is taking place is 'Nested Loop'.
Questions: With respect to the above query,
Q 2. If I want to make dept the driving table and emp the driven table then how can I adjust the statistics to achieve that?
Q 3. If I want to use hash join instead of a nested loop join then then how can I adjust the statistics to achieve that?
I can put the ordered and the use_hash hint to effect this but again I have heard that altering statistics is a more robust way to control an execution plan as compared to hints.
I have an issue with export(expdp).
When i exporting an user using expdp utility, the load the on the server is going up-to 5. The size of the database is 180GB. Below is the command that i use for export.
expdp sys/xxxx directory=dbpdump dumpfile=expdp_trk_backup.dmp logfile=expdp_trk_backup.log exclude=statistics schemas=trk
Do i need any look into any memory parameters for this?
The following query gets input parameter from the Front End application, which User queries to get Reports.There are many drop down boxes like LOB, FAMILY, BRAND etc., The user may or may not select values from drop down boxes.
If the user select any one or more values ( against each drop down box) it has to fetch all matching values from DB. If the user does'nt select any values it has to fetch all the records, in this case application will send a value 'DEFAULT' (which is not a value in DB ) so that the DB will fetch all the records.
For getting this I wrote a query like below using DECODE, which colleague suggested that will hamper performance.From the below query all the variables V_ are defined in procedure which gets the values selected by user as a comma separated string here V_SELLOB and LOB_DESC is column in DB.
DECODE (V_SELLOB, 'DEFAULT', V_SELLOB, LOB_DESC) IN
OPEN v_refcursor FOR
SELECT /*+ FULL(a) PARALLEL(a, 5) */
*
FROM items a
WHERE a.sku_status = 'A'
[code]...
I am having only select_catalog_role in database. Can I take complete AWR report data from awr views without using DBMS_WORKLOAD_REPOSITORY package?
View 6 Replies View Relatedsometimes when I re-run a query a few times, the speed after the first run become much faster. this is a problem for me when I'm trying to optimize a query. is there some sort of cache? can it be disabled?
View 7 Replies View RelatedCREATE OR REPLACE procedure fast_proc (p_rows out number)
is
TYPE object_id_tab IS TABLE OF all_objects.object_name%TYPE INDEX BY BINARY_INTEGER
lt_object_id object_id_tab;
CURSOR c IS
[Code]....
Warning: Procedure created with compilation errors.
Errors for PROCEDURE FAST_PROC:
LINE/COL ERROR
-------- ---------------------------------------------------------
13/7 PL/SQL: SQL Statement ignored
13/22 PL/SQL: ORA-03001: unimplemented feature
I am not able to do INSERT but I am able to do UPDATE/DELETE? What is this inbuilt functionality?
We have few tables in our production database which are havoc in size and will increase in size in future too so as part of the corrective measures , we have jotted down the below 3 methods to manage the size of those tables :-
1> Partitioning the table and take the export of identified partitions and after that, truncate those partition.
2> Creating history tables and remove not so current data from the original table to history table.
I'm extracting/retrieving the data from the oracle database using Java application it's bit slow. However, when I retrieve from the SQL server it's faster than oracle.
View 6 Replies View RelatedWe have a data migration scripts written for oracle. Data is not huge but we are observing that the migration is faster in the development labs but is 5x slower in the production site.
The development Oracle setup is on Windows and Production setup on Solaris. I have attached the AWR generated for a period where migration was run for 3 hours and stopped due to slow performance.
Here is my initial analysis.
1) The first timed events is the DB CPU. Hence I feel the migration scripts can be modified to run in parallel so that they can finish faster. However here the question arises why it should run faster in development env if this is an issue.
2) I tried increasing the
a.large_pool_size set to 512M
b.sga_max_size set to 8G
c.sga_target set to 8G
from 0, 4G and 4G respectively.
I have attached the AWR and below are the etc/system contents for solaris settings.
* Begin MDD root info (do not edit)
rootdev:/pseudo/md@0:0,1,blk
* End MDD root info (do not edit)
set noexec_user_stack=1
set noexec_user_stack_log=1
* IBMdpo vpath_START (do not remove)
* default SCSI timeout is 60 seconds
* uncomment to change SCSI timeout * set sd:sd_io_time=0x1e
forceload: drv/vpathdd
* IBMdpo vpath_END (do not remove)
set noexec_user_stack=1
set semsys:seminfo_semmni=100
set semsys:seminfo_semmns=1024
set semsys:seminfo_semmsl=256
set semsys:seminfo_semvmx=32767
set shmsys:shminfo_shmmax=4294967295
set shmsys:shminfo_shmmin=1
set shmsys:shminfo_shmmni=100
set shmsys:shminfo_shmseg=10
P.S. The awr report is renamed to .txt from .html to be able to upload the file.
DB Used : Oracle 10g.
A table X : NUM, INST are column names
NUM ----- INST
1234 ----- 23,22,21,78
2235 ----- 20,7,2,1
1298 ----- 23,22,21,65,98
9087 ----- 20,7,2,1
-- Based upon requirement :
1) Split values from "INST" Column : suppose 23
2) Find all values from "NUM" column for above splitted value i.e 23 ,
Eg:
For Inst : 23 ,
It's corresponding "NUM" values are : 1234,1298
3) Save these values into
A table Y : INST, NUM are column names.
INST NUM
23 1234,1298
1) I have a thousand records in Table X , and for all of those records i need to split and save data into Table Y.Hence, I need to do this task with best possible performance.
2) After this whenever a new data comes in Table X, above 'split & save' operation should automatically be called and append corresponding data wherever possible..
are the most important performance keys we have to calculate or take in account to preserve or to increase the DB performance in terms of response times, and whatsoever according to performance ?
View 8 Replies View RelatedWe are on Oracle 10.2.0.4 on Solaris 10. There is a table in my production db that has 872944 number of rows. Most of its data is now unnecessary, we need to retain, based on a date column in the table just last one month's data and delete rest of the data. So after that the table will have just 3000 rows.
However as the table was huge earlier(872k rows prior to delete) , does the delete of data release its oracle blocks and does the size of the table reduce? If not, will it rebuild the table online (online redefinition) so that the query that does a full scan on this table goes faster?
I checked using an example table that just delete of data does not remove the oracle blocks - they remain in the user_tables for that table and cost of full table scan remains same. We have a query that does the full table scan so I am thinking that after this delete I should do an online table re-definition , is that the right decision?
I create a view on production server which takes almost 10 to 12 minutes when it shows data. this view contains 3 or 4 tables on which all primary and unique columns have indexes.which index will be better for fast retrieval of data .
View 5 Replies View RelatedI have a table which contains 8,21,177 amount of data totally.Now I am trying to delete around 4,84,000 of data from this table by using just one filter i.e. my query is something like below
DELETE /*+ parallel(resource,4) */ FROM resource where created_by = 'MIGN'
This is going to delete 4,84,000 rows of data . But my current issue is this is taking lots of time to delete the data . To be precise , its almost taking 25 hours to delete this data..The created_by column is indexed .
Execution Plan
----------------------------------------------------------
Plan hash value: 2389236532
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time
|
--------------------------------------------------------------------------------
| 0 | DELETE STATEMENT | | 499 | 20459 | 39 (0)| 00:00:
01 |
| 1 | DELETE | RESOURCE | | | |
[code]....
We are copying our transaction tables data into another database for our reporting applications (say every day midnight refresh will happen).
The Transaction Database has some 30tables. Existing system is following below points and it is taking 2hours to complete.
1) Truncate data from reporting database (or schema)
2) Direct path Insert into reporting database (or schema) as select * from transaction tables.
3) Rebuild index and Enable constraints.
Note: Each tables data will vary from 30lakhs to 50lakhs. Dump/import/export is not advised by the client.
I want to cut down the time i.e., below 2hours. Instead of above method. Can go for a field in each table specifying the time of each records update/insert operation and then pick the modified records only and copy into reporting db.
I am inserting data using a procedure for 2012 and 2013 year which is using partitioned tables includes crore of data in a partition taking lot of time or taking months. Is there any other way by which I can insert data fast from our query.
View 14 Replies View RelatedI have created a materialized view and also a normal View, which has 3 tables used in both the views, when inserted new records it reflects in a normal view but when i select the materialized view i cant see the updated data.
here is the materialized view i created;
CREATE MATERIALIZED VIEW pct_sales_materialized
BUILD IMMEDIATE REFRESH ON DEMAND
ENABLE QUERY REWRITE
AS
SELECT A.DEP_NAME,B.EMP_ID,C.EMP_NAME
FROM department_head A,department_child B,emp_detail C
WHERE A.DEP_ID = B.DEP_ID
AND B.EMP_ID = C.EMP_ID
We have a table with huge data which is skewed on a 'status' column. The 'status' column has 6 distinct values with 1 particular value occupying 80-85% records.
In the batch process we query the data on the status and process the retrieved records. My senior is insisting on partitioning which I see not much feasible considering cost implications just for a part of functionality
See there are 6 status 'A','B','C','D','E','F'
with 'A' occupying 80% records
'B' to 'F' occupies 2% till 14% records in the table(approx)
1) Create a conditional index on status (using case) to have records with all statuses except 'A' Then create If-ELSE structure
IF input parameter is 'A'
select /*+ FULL Parallel(t) */ * from t where status='A';
ELSE
Select /*+ INDEX (t conditional_index) */ * from t where status in ('B','C');
END IF;
I want to create conditional index here for 2 reasons
1] since it will have values for status except 'A' this nullify the chance that this index will be picked up when status='A' will be queried
Thus making the performance worst (status ='A' is for 80% records) - The IF-ELSE is additional protection
2] Less impact on the DMLS as the index will not be on status='A' which contribute to large chunk of records
2)Populate a dummy table which would contain rowid and status. Since the business closes at 21:00 and batch process starts at 21:30
Between these times periods refresh the dummy table every day using merge (to catch business transactions during the day)
Now during the batch process retrieve records from the main table using the rowids in the dummy table depending on the input status value
3)Create index on status
Make sure hard coded status values are used in the database procedures
Gather stats with the histograms
And leave it to the Optimizer to choose the best possible path
my sql query has three tables in from clause so it has two join conditions and one where condition.
account_no is number data type and v_account_no is varchar2() data type
The where clause is :
"where account_no=to_number(v_account_no)" with this condition in my sql query has the cost 392
we just modify the where clause as where v_account_no=to_char(account_no) with this condition in the sql query has the cost 11.
what is impact of this data type conversion and difference between these two "to_number() and to_char()" in performance wise to reduce the cost of query?
I am getting back into Oracle (from a long haul in MS only env.) and am now testing Oracle installs.I have been given a task of seeing the diff. between 12c and 10.2g...I set up 2 vms (excatly same configs) and used the same dmp file (on both env.) to restore data and settings for our jobs to run.We have some aggregated data, and cubes with DIM tables each being run on the vm machines. We run nightly jobs to rebuild our cubes.
I am supposed to see/analyze the value of 12c, and understand things might vary from company to company, but am perplexed at my result.12c is half the speed of 10.2g, both env. are the same out of the box with same dmp file and same hardware.
I am using the same dmp file, with the same jobs on each machine, with both vms having 10.2g or 12c installed out of the box as is.what default oracle settings might have changed from 10.2g to 12c that could make the exact same env. run twice as slow on the 12c?
Expectations were that out of the box with both machines running same jobs on same data (from dmp files) would have it that 10.2g would be slower than the 12c, except the 12c takes 2 times as long to run the jobs. I have reviewed every possibility as I know usually the problem is the person sitting in the chair and not the pc...but I confirmed all was identical from the one vm env. to the other, except the version of oracle out of the box.
What could be done to bring that default setting back to atleast equal time between the 2, that would give me a great starting point. Otherwise, I would have to toss this up to bloatware.
I read up a bit on the CBO, and know this might have changed in 12c.is there a way to bring it back to a backwards ealier config, so as to atleast match both env. execution plans?
In order to improve the performance of our live server, I am trying to do an exhaustive comparison with our test environment which is quite quick in spite of the fact that we port the data from Live every month.
There are no obviously slow queries appearing in the the top SQLs of AWR, we have optimised such things already. Right now it is about general uplift rather than SQL based tuning.
I picked up random SQLs and I noticed a marked differences in the execution time. Typically they are 3 to 4 times and there are cases much more than that.
1. I observed that, while the explain plan of the queries are same, trace of the queries give a different picture. I have observed that the recursive calls, consistent gets and sorts(memory) are quite high on Live.
2. I have no solid reasons to say this but my instincts tell me that the recursive calls is the major contributing factor. It is sometimes 2000+ for an SQL.
3. On googling more on that, it finally made me compare the data dictionary on the AWR report of test and Live.
The dc_objects caught my eyes. In that 4 hour AWR, there were about 10 million get requests and the pct miss was ~10. For similar load, the test server had 5 million gets with 0.08 PCT miss for 4 hours.
A website requires to display consolidated data from databases located in different geographical regions (India, London and New York). The application server for the website is hosted only in one location India. What are the techniques that can be used for faster retrieval of data from all 3 databases?
Note: There is no need of real time data retrieval from different regions; however the user should able to view the updated data at predefined intervals.
How To Increase Data Retrieval / Insertion Speed my data base has more than 0.5 million records Forms Some Time Respond Very Slow .
View 8 Replies View Related