Performance Tuning :: Access Direct Table Versus View
Dec 9, 2011
If you have 3 tables (yr09, yr10,yr11) one with 2009 data, 2010 and 2011 data respectively. And a view (vw_yr091011) with a "union all" on all three.
Question: Will the performance be same for the following two queries ?
Question: Will Oracle read all 3 tables in the view when we search for only one year ?
select count(*) from yr09
where year = 2009;
-- vs
select count(*) from vw_yr091011
where year = 2009;
The following link says yes, the performance remains the same.
Link: [URL]..........
when I tried on a volume of 14000 records. The count came out same but the view took 50 more sec. And the explain plan shows it accessed all three tables.
I have two design alternatives and need to understand how expensive (speed) is one of them against the other for a medium size table (100K-200K records):
create table xyz ( f1 number not null, f2 varchar2(20) not null, f3 number not null, f4 varchar2(50),
[code]....
the idea is to optimize the design by using a PK instead of the 3 keys and there is a debate that searching a unique index field(2nd scenario) is of the same speed than searching a PK field (1st scenario).
I have a huge table (about 60 gb) partition over range. The index on this table is global index created on 4 columns together. I have a query which is running very slowly. The explain plan is showing the use of this global index.Explain plan is not showing pstart and pend because the index is global.
Let's consider such table that all rows fit into single block:
SQL> create table test as select rownum id, '$'||rownum name from dual connect by level <= 530; Table created. SQL> create index i_test on test(id); Index created. SQL> SQL> begin
[code].....
why does approach with full scan take longer even if table occupies only one data block? PS. 11gR2
I am currently in the favorable situation in which I have excess amounts of memory available on the database server - a single node setup. The server only serves the single instance and no other processing. Database size is around 2.3tb and memory is 50gb. For the majority of processing, AIX is allocating a significant amount (anywhere from 30-40%) of the memory to the AIX file system cache (persistent pages).
I've been trying to find documentation about this, but have not had any luck yet. My guess is that it would be better to allow Oracle to cache this data - meaning increase the SGA target and max size to allow for a larger buffer cache. However, the nice thing about the AIX cache is if process memory is needed, the file system cache gives up pages. If the memory was allocated to the SGA, its pretty much locked in.
I have read several articles stating that a larger buffer cache is not always better, as a larger cache takes more management. But having both of the caches active seem to be a waste of memory, effectively storing the data twice - once in AIX persistent pages and a second time in Oracle database buffer cache.
base on performance it is better to retrieve data from view or mention the table names directly?
I have a select statement in from clause one of my table is view (which is having data collected from four tables) my question is whether performance of querry will be improved if i use directly all tables( four tables of a view) instead of a view
I have a view, below, which does few left outer joins to the same V_MARKET view to get data i need. When I run SQL by itself, ut runs pretty fast, 2-5 seconds. But when I do "select * from V_DEPT_DATA where busines_date = '01-APR-10'", it takes more than 10 minutes to run. I added all needed indexes and still have problems with it .
CREATE OR REPLACE VIEW V_DEPT_DATA AS SELECT v1.business_date , v1.division , v1.department , v1.account , en.trader , [code]........
I 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
I have an issue in materialized view which has got one of the null able column and query on this column taking approximately 2 mins where as other indexed columns takes less than 10 sec.
Here is the summary
SQL> Select Count (1), Count (VAT_NO) From Mv_customer;
If an index is created on VAT_NO will that improve the performance. What kind of index can be created considering very less number of records has got VAT_NO
I have a view on base tables holding historical data for previous 60 months(one table per month) with union all operators.create index on those base tables will improve performance or creating a primary key with disabled novalidate will improve for retrieving data?
The view has around 8 million data and used as a fact table with 4 dimension tables.A DTS package from MSSql side refreshes OLAP cube by retrieving data from these tables in oracle.
In search queries generally we select 10-25 columns (more can't be displayed on the screen) from 5-10 tables
Say in case of insurance related application, the search might be on policy number, policy holder's first name, policy holder's last name, region, policy type etc.
And not to many columns we are displaying on the screen, say, 4 tables have collectively 4 * 20 = 80 columns, then we are displaying say 12-15 columns with 2-3 columns have aggregates on it.
since the search criteria (e.g. first name, last name, policy number etc.) is not known till last moment it will be a generic dynamic query
Is it possible that instead we create a Materialized view with query with only joining conditions but no filter conditions and selecting only columns to be displayed on the screen and then we will refresh the materialized view (to take care of recent business transactions) and fire refined query with filter criteria on this materialized view
Select col1,col2,col3,col4,col5 From tab1,tab2,tab3,tab4 Where tab1.col1=tab2.col1 And tab2.col2=tab3.col2 And tab2.col2=tab4.col2;
Will it improve performance of the search functionality
I have a base table with ~20 mio. records with two FAST REFRESH Materialized Views based on that table using various aggregate functions in their view definition.
The problem is, when e.g. one record changes in the base table, I see two records in the MV log table MLOG$, but invoking the fast refresh mechanism by using using:
I have two tables with 113M records in DWH_BILL_DET & 103M in prd_rerate_chg_que and Im running following merge query, which is running for 13 hrs to update records, which is quiet longer time.
SQL> explain plan for MERGE /*+ parallel (rq, 16) */ INTO DWH_BILL_DET rq USING (SELECT rated_que_rowid, detail_rerate_flag_code, rerate_sel_key,
I am trying to update columns of Table A with the columns of Table B. Both these tables have 60,000 rows each. I tried this operation using following 2 queries:
Query 1
Update TableA A set (A.col1,A.col2,A.col3)=(select B.col1,B.col2,B.col3 from TableB where A.CODE=B.CODE)
Query 2 Update TableA A set (A.col1,A.col2,A.col3)=(select B.col1,B.col2,B.col3 from TableB where A.CODE=B.CODE) where exists A.code = (select B.code from TableB B where A.code=B.code)
When i execute these two above queries, it keeps executing indefinitely.
Oracle Server 11g on HP-UX Oracle Client on Windows
I am using swingbench tool to generate load on DB and using OLTP like benchmark i am comparing the performance of plain data and encrypted data.
I have created two different database. one for tde and other for plain. I have populated same number of rows in both databases. Then i start running the benchmark and i use SAR to collect disk I/O's, VSAR to CPU usage.
From the sar report it seems that,
Oracle plain has faster transactions, it uses minimum CPU. But when look in tot the Reads/Writes TDE has lower than the plain.
If TDE needs to encrypt the data to store in the disks it should occupy more space than the plain data. Then the I/O should be more in TDE..
Note: Bcz the DB parameters are same, number of rows in the tables are same. File system and its block size are same. I will run the swingbench seperately for both the databases.
I am attaching the excel sheet for sar results. Let me know if you need more information
With a very large database (VLDB) for a data warehouse (DW) using primarily a STAR based schema in an environment in which time (both human and CPU) is orders of magnitude more valuable than storage capacity, is there any signficant difference in query performance when tables have all fixed length (CHAR) columns compared to tables with variable length (VARCHAR2) columns?
I realize this is one of those "in general" questions so considering "a given VLDB DW environment" with all other things being equal, what, if any, is the time based performance difference between a database of tables with all fixed sized columns versus one of tables with variable length columns ?
select gam.SOL_ID,COUNT(gam.FORACID) from gam,smt where gam.ACID=smt.ACID and gam.ACID NOT IN(select ACID from imt) and gam.SCHM_TYPE in('SBA','CCA','CAA','ODA') and GAM.ACCT_CLS_FLG='N' and gam.SOL_ID IN(select SOL_ID from IMT) group by gam.SOL_ID /
attached is the explain plan.
in which index on IMT table is not used. And the query is doing a FTS on IMT table. What needs to be done to avoid FTS on IMT table.
I am using one script to delete the records from a table, its taking 1hr to delete.
declare cursor c1 is select ownerid,ownertype from nightly_metric_projects ; v1 c1%rowtype; open c1; loop fetch c1 into v1; exit when c1%notfound; DELETE FROM DGT_ITEMEFFORTDATA WHERE OWNERTYPE = c1.OWNERTYPE AND OWNERID = c1.OWNERID; end loop; close c1; commit;
nightly_metric_projects--1200 records DGT_ITEMEFFORTDATA--13200000
I have normal tables with hugh Data and would like to increase the performace by following means:
1) Add a new column in each table. Say this column Name is IS_LIVE. This new column have only two value 1 ( LIVE ) OR 0 ( NOT LIVE ). 2) Change the normal tables to Partitioned table. There would be only two partitioned in all the table. The partitioned key column would be IS_LIVE and both partitioend recrods would be in two different tablespace. 3) Added a POLICY function to these partitioned table to Always add a Query Predicate of '1' to all queuries.
I am interested to know that what kind of Indexes ( Global Or local ) would be suitable for these kind of Design.Is there any use of having Local index on IS_LIVE.Please note that Primary Key doesnot have this new column in it.
Objective : To find solution to archieve data from 2 big tables which is occupying maximum size in the data base. With current data (From Jan 2005 to Sept 2011) it has records as mentioned below:
We need to load data and run monthly batches from October 2011 to current month which will increase this space.
1. Issue is there will not be having so much space.
2. Maintenance of such table is diffcult now.Also there is huge impact on performance. Can we think of partitioning the table base on date aswe query 1st table based on certain date range?
3. Most of reports use this table and creating performances issues
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 have tried below steps for removing the table fregmentation but for some table i am not getting good result here.
1. It will collect the data which are having more than 100MB fragmentation.
select owner,table_name,blocks,num_rows,avg_row_len,round(((blocks*8/1024)),2)||'MB' "TOTAL_SIZE", round((num_rows*avg_row_len /1024/1024),2)||'Mb' "ACTUAL_SIZE", round(((blocks*8/1024)-(num_rows*avg_row_len/1024/1024)),2) ||'MB' "FRAGMENTED_SPACE" from dba_tables where owner in('a','b','c','d') and round(((blocks*8/1024)-(num_rows*avg_row_len/1024/1024)),2) > 100 order by 8 desc;
2. then move the object(table) to the same tablespace.
alter table abc move; alter table bcd move; alter table efg move;
3. also rebuild the dependent objects.
alter index abc_PK rebuild online;
4. Then analyze the table which are having more than 100MB of fragmentation.
From the below query i found that there are some stale stats for 3 tables.
================================= select table_name, stale_stats, last_analyzed from dba_tab_statistics where owner= 'SYSADM' and stale_stats='YES' order by last_analyzed desc
I collect stats for those above 3 tables with dbms_stats.gather_table_stats().But no luck.After collection of stats immediately I ran the above query.But still it is showing there are stale stats for 3 tables.
how can I change "STALE-STATS" status, so that optimizer can use the updated stats eficiently.
If a table(have a primary key) is empty(after truncate),the sql of dml(insert,update) is very quickly,but if the table have many rows about 10,000,000 rows, the dml is very slowly,why?
