Which is faster in performance

Hi all

I have a partition on the table according to the 5 data sources, i.e. the partition list. Table has about 100 KB of data.

gives better performance?

Select * from tab1 where source = 2;

or

Select * from tab1 partition (sr2);

Please suggest. As I need to use in queries using several of these tables.

Thank you
VJ

jvjmohan wrote:

I have a partition on the table according to the 5 data sources, i.e. the partition list. Table has about 100 KB of data.
gives better performance?
Select * from tab1 where source = 2;
or
Select * from tab1 partition (sr2);

Both are the same - a FTS of the contents of a single partition (assuming I read your comparison properly).

The problem with the 2nd approach is that uses a static reference to the partition. This cannot be a binding parameter. So let's say you have a 100 sheet music - there will be a 100 sliders in the shared pool for research as follows:
Select * from tab1 partition (sr1)
Select * from tab1 partition (sr2)
..
Select * from tab1 partition (sr100)

This is problematic. In PL/SQL (or), this means having to use dynamic SQL to create an SQL statement with the reference to the correct partition.

If the criteria of the partition is used, a single SQL cursor is necessary in the shared pool:
Select * from tab1 where source =: 1

And this slider can be used for all partitions of the table - as the value bound to the variable in the cursor, allows CBO to determine which partition to use (called partition size).

In General - by specifying a name of partition in the SQL query is incorrect. Lack of technique use perspective. And also bad from a data modeling perspective. Application code does give not record the database indexes to use for a selectSQL names. So why and then specify the name of a partition in a SQL Select ?

Inner layer of abstraction between database objects (indexes, partitions, constraints, etc.) and application SQL code, keep intact.

Tags: Database

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ETG vs. insert add in parallel (which is faster)?
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The oracle is 11.2.0.3 on a linux machine.

I would like to know what the most rapid between the ETG and insert add in parallel (not index).

----------------

case A: ETG

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as
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case B: table_a was established in nologgig mode without index.

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-----------------------

As far as I know, both use "direct path write."
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I would like to hear your experience which is faster in general and in THEORY.

Thanks in advance.
Best regards.
>
I would like to know what the most rapid between the ETG and insert add in parallel (not index).
. . .
in my test case, the two sql show similar performance.
>
How do you know? You don't post any case INSERT ADD then why don't test you what you posted and we seek clarification?

Which is faster or =
Hello

There are millions of records from a table and have to perform multiple filtering on the same column, which is faster

table.column_name = 10
or
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or
table.column_name = 30
or
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or+_

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Published by: jvjmohan on January 11, 2011 02:42
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There is so much difference in the two operators. in the case AND the requirements of thre must pass, only then you will get the output and there a lot of conditions

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BryanSw wrote:
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Which is faster?
I have a scénarion where I received a comment to replace the sliders of the Varray

Who is the fastest between the slider and VArray? and why?
What you have shown with this pseudo-code is a process loop nested within PL/SQL.

In SQL, this is called a nested loops join. A loop through the primary table (external) and for each row in this table, hit the secondary table (inside).

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select
  *
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where outer_table.columns meet condition 1  // apply condition 1
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select
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and outer_table.columns equals inner_table2.colums // join data

etc.
```

Lines AdvTable-multiple-gray on which the operation was performed.
I have advanced at table with multi lines check.
I need all values in col1 of selected lines in the advTableVo and insert it in a custom table joined with TestVO
Once the values of these lines are inserted in the TestVO, select box should grey out for these specific advanced table lines.

That's what I did.
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   if( pageContext.getParameter("InsertSelectedRows") != null);
    {           
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for (int j=0; j<listOfQuestionsToBeInserted.size(); j++)

{

System.out.println(" looking inside ArrayList " + listOfQuestionsToBeInserted.get(j)); ///this prints fine.

}





// Check If the value already exists in Question column in customdb (TestVO) 

// insert only unique values in TestVO

// once committed, How to grey out select checkbox for rows in advtableVO, which have been inserted?

 
```
Hello

The selected lines you have captured on the right!

Now, instead of multiple selection... Take a separate box and bind a transitional (Boolean) Attribute to his property off using SPEL.

You save records after that it again once, loop through the selected vo lines and set the Transient true attribute.

To ensure that the checkbox is disabled for the selected lines.

Thank you
Gerard

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http://I1093.Photobucket.com/albums/i438/junk000/CPU_zpsc43105d3.jpg

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http://cpuboss.com/CPUs/Intel-Core-i5-2467M-vs-Intel-Core-i3-530
http://www.CPU-world.com/compare/81/Intel_Core_i3_i3-530_vs_Intel_Core_i5_Mobile_i5-2467M.html

http://Ark.Intel.com/products/56858?wapkw=i5-2467m
http://Ark.Intel.com/products/46472/Intel-Core-i3-530-processor-4m-cache-2_93-GHz?wapkw=i3+530

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Commit performance on table with Fast Refresh MV

Hello world

Try to wrap your head around fast refresh performance and why I see (what I consider) high disk numbers / query associated with the update of the MV_LOG in a TKPROF.

The installation program.
(Oracle 10.2.0.4.0)

Database table:

SQL> desc action;
 Name                                      Null?    Type
 ----------------------------------------- -------- ----------------------------
 PK_ACTION_ID                              NOT NULL NUMBER(10)
 CATEGORY                                           VARCHAR2(20)
 INT_DESCRIPTION                                    VARCHAR2(4000)
 EXT_DESCRIPTION                                    VARCHAR2(4000)
 ACTION_TITLE                              NOT NULL VARCHAR2(400)
 CALL_DURATION                                      VARCHAR2(6)
 DATE_OPENED                               NOT NULL DATE
 CONTRACT                                           VARCHAR2(100)
 SOFTWARE_SUMMARY                                   VARCHAR2(2000)
 MACHINE_NAME                                       VARCHAR2(25)
 BILLING_STATUS                                     VARCHAR2(15)
 ACTION_NUMBER                                      NUMBER(3)
 THIRD_PARTY_NAME                                   VARCHAR2(25)
 MAILED_TO                                          VARCHAR2(400)
 FK_CONTACT_ID                                      NUMBER(10)
 FK_EMPLOYEE_ID                            NOT NULL NUMBER(10)
 FK_ISSUE_ID                               NOT NULL NUMBER(10)
 STATUS                                             VARCHAR2(80)
 PRIORITY                                           NUMBER(1)
 EMAILED_CUSTOMER                                   TIMESTAMP(6) WITH LOCAL TIME
                                                     ZONE


SQL> select count(*) from action;

  COUNT(*)
----------
   1388780

MV was created

create materialized view log on action with sequence, rowid
(pk_action_id, fk_issue_id, date_opened) 
including new values;

-- Create materialized view
create materialized view issue_open_mv
build immediate
refresh fast on commit
enable query rewrite as 
select  fk_issue_id issue_id,
     count(*) cnt,
     min(date_opened) issue_open,
     max(date_opened) last_action_date,
     min(pk_action_id) first_action_id,
     max(pk_action_id) last_action_id,
     count(pk_action_id) num_actions
from    action
group by fk_issue_id;

exec dbms_stats.gather_table_stats('tg','issue_open_mv')

SQL> select table_name, last_analyzed from dba_tables where table_name = 'ISSUE_OPEN_MV';

TABLE_NAME                     LAST_ANAL
------------------------------ ---------
ISSUE_OPEN_MV                  15-NOV-10

*note: table was created a couple of days ago *

SQL> exec dbms_mview.explain_mview('TG.ISSUE_OPEN_MV');

CAPABILITY_NAME                P REL_TEXT MSGTXT
------------------------------ - -------- ------------------------------------------------------------
PCT                            N
REFRESH_COMPLETE               Y
REFRESH_FAST                   Y
REWRITE                        Y
PCT_TABLE                      N ACTION   relation is not a partitioned table
REFRESH_FAST_AFTER_INSERT      Y
REFRESH_FAST_AFTER_ANY_DML     Y
REFRESH_FAST_PCT               N          PCT is not possible on any of the detail tables in the mater
REWRITE_FULL_TEXT_MATCH        Y
REWRITE_PARTIAL_TEXT_MATCH     Y
REWRITE_GENERAL                Y
REWRITE_PCT                    N          general rewrite is not possible or PCT is not possible on an
PCT_TABLE_REWRITE              N ACTION   relation is not a partitioned table

13 rows selected.

Fast refresh works fine. And the newspaper is kept small enough.

SQL> select count(*) from mlog$_action;

  COUNT(*)
----------
         0

When I update a row in the base table:

var in_action_id number;

exec :in_action_id := 398385;

UPDATE action
SET emailed_customer = SYSTIMESTAMP
WHERE pk_action_id = :in_action_id
AND DECODE(emailed_customer, NULL, 0, 1) = 0
/

commit;

What follows, I get via tkprof.

********************************************************************************

INSERT /*+ IDX(0) */ INTO "TG"."MLOG$_ACTION" (dmltype$$,old_new$$,snaptime$$,
  change_vector$$,sequence$$,m_row$$,"PK_ACTION_ID","DATE_OPENED",
  "FK_ISSUE_ID")
VALUES
 (:d,:o,to_date('4000-01-01:00:00:00','YYYY-MM-DD:HH24:MI:SS'),:c,
  sys.cdc_rsid_seq$.nextval,:m,:1,:2,:3)


call     count       cpu    elapsed       disk      query    current        rows
------- ------  -------- ---------- ---------- ---------- ----------  ----------
Parse        1      0.00       0.01          0          0          0           0
Execute      2      0.00       0.03          4          4          4           2
Fetch        0      0.00       0.00          0          0          0           0
------- ------  -------- ---------- ---------- ---------- ----------  ----------
total        3      0.00       0.04          4          4          4           2

Misses in library cache during parse: 1
Misses in library cache during execute: 1
Optimizer mode: CHOOSE
Parsing user id: SYS   (recursive depth: 1)

Rows     Row Source Operation
-------  ---------------------------------------------------
      2  SEQUENCE  CDC_RSID_SEQ$ (cr=0 pr=0 pw=0 time=28 us)


Elapsed times include waiting on following events:
  Event waited on                             Times   Max. Wait  Total Waited
  ----------------------------------------   Waited  ----------  ------------
  db file sequential read                         4        0.01          0.01
********************************************************************************

********************************************************************************

update "TG"."MLOG$_ACTION" set snaptime$$ = :1
where
 snaptime$$ > to_date('2100-01-01:00:00:00','YYYY-MM-DD:HH24:MI:SS')


call     count       cpu    elapsed       disk      query    current        rows
------- ------  -------- ---------- ---------- ---------- ----------  ----------
Parse        1      0.00       0.01          0          0          0           0
Execute      1      0.94       5.36      55996      56012          1           2
Fetch        0      0.00       0.00          0          0          0           0
------- ------  -------- ---------- ---------- ---------- ----------  ----------
total        2      0.94       5.38      55996      56012          1           2

Misses in library cache during parse: 1
Misses in library cache during execute: 1
Optimizer mode: CHOOSE
Parsing user id: SYS   (recursive depth: 1)

Rows     Row Source Operation
-------  ---------------------------------------------------
      0  UPDATE  MLOG$_ACTION (cr=56012 pr=55996 pw=0 time=5364554 us)
      2   TABLE ACCESS FULL MLOG$_ACTION (cr=56012 pr=55996 pw=0 time=46756 us)


Elapsed times include waiting on following events:
  Event waited on                             Times   Max. Wait  Total Waited
  ----------------------------------------   Waited  ----------  ------------
  db file scattered read                       3529        0.02          4.91
********************************************************************************

select dmltype$$, max(snaptime$$)
from
 "TG"."MLOG$_ACTION"  where snaptime$$ <= :1  group by dmltype$$


call     count       cpu    elapsed       disk      query    current        rows
------- ------  -------- ---------- ---------- ---------- ----------  ----------
Parse        1      0.00       0.00          0          0          0           0
Execute      1      0.00       0.00          0          0          0           0
Fetch        2      0.70       0.68      55996      56012          0           1
------- ------  -------- ---------- ---------- ---------- ----------  ----------
total        4      0.70       0.68      55996      56012          0           1

Misses in library cache during parse: 1
Misses in library cache during execute: 1
Optimizer mode: CHOOSE
Parsing user id: SYS   (recursive depth: 1)

Rows     Row Source Operation
-------  ---------------------------------------------------
      1  SORT GROUP BY (cr=56012 pr=55996 pw=0 time=685671 us)
      2   TABLE ACCESS FULL MLOG$_ACTION (cr=56012 pr=55996 pw=0 time=1851 us)


Elapsed times include waiting on following events:
  Event waited on                             Times   Max. Wait  Total Waited
  ----------------------------------------   Waited  ----------  ------------
  db file scattered read                       3529        0.00          0.38
********************************************************************************

delete from "TG"."MLOG$_ACTION"
where
 snaptime$$ <= :1


call     count       cpu    elapsed       disk      query    current        rows
------- ------  -------- ---------- ---------- ---------- ----------  ----------
Parse        1      0.00       0.00          0          0          0           0
Execute      1      0.71       0.70      55946      56012          3           2
Fetch        0      0.00       0.00          0          0          0           0
------- ------  -------- ---------- ---------- ---------- ----------  ----------
total        2      0.71       0.70      55946      56012          3           2

Misses in library cache during parse: 1
Misses in library cache during execute: 1
Optimizer mode: CHOOSE
Parsing user id: SYS   (recursive depth: 1)

Rows     Row Source Operation
-------  ---------------------------------------------------
      0  DELETE  MLOG$_ACTION (cr=56012 pr=55946 pw=0 time=702813 us)
      2   TABLE ACCESS FULL MLOG$_ACTION (cr=56012 pr=55946 pw=0 time=1814 us)


Elapsed times include waiting on following events:
  Event waited on                             Times   Max. Wait  Total Waited
  ----------------------------------------   Waited  ----------  ------------
  db file scattered read                       3530        0.00          0.39
  db file sequential read                        33        0.00          0.00
********************************************************************************

Could someone explain why the the SELECT/UPDATE/DELETE on MLOG$ _ACTION if 'expensive' when it should be only 2 rows (the old value and the new value) in this newspaper after an update? I could do to improve the performance of the update?

Let me know if you need more info... would be happy to provide.

My guess would be that you were once a very large transaction that inserted a large number of rows in this table. So the table segment is big enough now and the high watermark is average at the end of this segment, causing a full scan table to analyze a large number of empty blocks and retrieve the two lines.

You can issue a truncation on this table of $ MLOG: which would free up the empty blocks and brings back the high-watermark in the first block.

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THE IMPACT OF THE COMPUTER ON THE PERFORMANCE SPECIFICATION
http://www.gerryscomputertips.co.UK/performance1.htm

Performance of row_number, rank and dense_rank

Hello
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Hello

Tested with my own set of data and performance are as follows.

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