Best way of partitioning the huge size table in oracle 11gr2
hi,
OS: linux
DB: oracle 11gR2
table size is about 2T and single table space with multiple dbf files in ASM,
table partition with dbms.redefinition is running past 2 days (range partition).. its running but not that fast..
note: exchange partition is too slow.. hence not used..
what is the best way of doing the huge size table partition. please suggest, thanks.
>
what is the best way of doing the huge size table partition
>
A few questions
1. Is that an OLTP or OLAP table?
2. Is all of the data still needed online or is some of it archivable?
3. What type of partitiioning are you doing? RANGE? LIST? COMPOSITE?
4. Why do you you say 'exchange partition is too slow' - did you do a test?
For example if data will be partitioned by create date then one stragety is to initially put all existing data into the root partition of a range partitioned table. Then you can start using new partitions for new incoming data and take your time to partition the current data.
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Hi,
Please suggest me the best way to fetch the record from the table designed below. It is Oracle 10gR2 on Linux
Whenever a client visit the office a record will be created for him. The company policy is to maintain 10 years of data on the transaction table but the table holds record count of 3 Million records per year.
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Client_Visit
ID Number(12,0) --sequence generated number
EFF_DTE DATE --effective date of the customer (sometimes the client becomes invalid and he will be valid again)
Create_TS Timestamp(6)
Client_ID Number(9,0)
Cascade Flg vahrchar2(1)
On most of the reports the records are fetched by Max(eff_dte) and Max(create_ts) and cascade flag ='Y'.
I have following queries but the both of them are not cost effective and takes 8 minutes to display the records.
Code 1:
SELECT au_subtyp1.au_id_k,
au_subtyp1.pgm_struct_id_k
FROM au_subtyp au_subtyp1
WHERE au_subtyp1.create_ts =
(SELECT MAX (au_subtyp2.create_ts)
FROM au_subtyp au_subtyp2
WHERE au_subtyp2.au_id_k =
au_subtyp1.au_id_k
AND au_subtyp2.create_ts <
TO_DATE ('2013-01-01',
'YYYY-MM-DD'
AND au_subtyp2.eff_dte =
(SELECT MAX
(au_subtyp3.eff_dte
FROM au_subtyp au_subtyp3
WHERE au_subtyp3.au_id_k =
au_subtyp2.au_id_k
AND au_subtyp3.create_ts <
TO_DATE
('2013-01-01',
'YYYY-MM-DD'
AND au_subtyp3.eff_dte < =
TO_DATE
('2012-12-31',
'YYYY-MM-DD'
AND au_subtyp1.exists_flg = 'Y'
Explain Plan
Plan hash value: 2534321861
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
| 0 | SELECT STATEMENT | | 1 | 91 | | 33265 (2)| 00:06:40 |
|* 1 | FILTER | | | | | | |
| 2 | HASH GROUP BY | | 1 | 91 | | 33265 (2)| 00:06:40 |
|* 3 | HASH JOIN | | 1404K| 121M| 19M| 33178 (1)| 00:06:39 |
|* 4 | HASH JOIN | | 307K| 16M| 8712K| 23708 (1)| 00:04:45 |
| 5 | VIEW | VW_SQ_1 | 307K| 5104K| | 13493 (1)| 00:02:42 |
| 6 | HASH GROUP BY | | 307K| 13M| 191M| 13493 (1)| 00:02:42 |
|* 7 | INDEX FULL SCAN | AUSU_PK | 2809K| 125M| | 13493 (1)| 00:02:42 |
|* 8 | INDEX FAST FULL SCAN| AUSU_PK | 2809K| 104M| | 2977 (2)| 00:00:36 |
|* 9 | TABLE ACCESS FULL | AU_SUBTYP | 1404K| 46M| | 5336 (2)| 00:01:05 |
Predicate Information (identified by operation id):
1 - filter("AU_SUBTYP1"."CREATE_TS"=MAX("AU_SUBTYP2"."CREATE_TS"))
3 - access("AU_SUBTYP2"."AU_ID_K"="AU_SUBTYP1"."AU_ID_K")
4 - access("AU_SUBTYP2"."EFF_DTE"="VW_COL_1" AND "AU_ID_K"="AU_SUBTYP2"."AU_ID_K")
7 - access("AU_SUBTYP3"."EFF_DTE"<=TO_DATE(' 2012-12-31 00:00:00', 'syyyy-mm-dd
hh24:mi:ss') AND "AU_SUBTYP3"."CREATE_TS"<TIMESTAMP' 2013-01-01 00:00:00')
filter("AU_SUBTYP3"."CREATE_TS"<TIMESTAMP' 2013-01-01 00:00:00' AND
"AU_SUBTYP3"."EFF_DTE"<=TO_DATE(' 2012-12-31 00:00:00', 'syyyy-mm-dd hh24:mi:ss'))
8 - filter("AU_SUBTYP2"."CREATE_TS"<TIMESTAMP' 2013-01-01 00:00:00')
9 - filter("AU_SUBTYP1"."EXISTS_FLG"='Y')Code 2:
I already raised a thread a week back and Dom suggested the following query, it is cost effective but the performance is same and used the same amount of Temp tablespace
select au_id_k,pgm_struct_id_k from (
SELECT au_id_k
, pgm_struct_id_k
, ROW_NUMBER() OVER (PARTITION BY au_id_k ORDER BY eff_dte DESC, create_ts DESC) rn,
create_ts, eff_dte,exists_flg
FROM au_subtyp
WHERE create_ts < TO_DATE('2013-01-01','YYYY-MM-DD')
AND eff_dte <= TO_DATE('2012-12-31','YYYY-MM-DD')
) d where rn =1 and exists_flg = 'Y'
--Explain Plan
Plan hash value: 4039566059
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
| 0 | SELECT STATEMENT | | 2809K| 168M| | 40034 (1)| 00:08:01 |
|* 1 | VIEW | | 2809K| 168M| | 40034 (1)| 00:08:01 |
|* 2 | WINDOW SORT PUSHED RANK| | 2809K| 133M| 365M| 40034 (1)| 00:08:01 |
|* 3 | TABLE ACCESS FULL | AU_SUBTYP | 2809K| 133M| | 5345 (2)| 00:01:05 |
Predicate Information (identified by operation id):
1 - filter("RN"=1 AND "EXISTS_FLG"='Y')
2 - filter(ROW_NUMBER() OVER ( PARTITION BY "AU_ID_K" ORDER BY
INTERNAL_FUNCTION("EFF_DTE") DESC ,INTERNAL_FUNCTION("CREATE_TS") DESC )<=1)
3 - filter("CREATE_TS"<TIMESTAMP' 2013-01-01 00:00:00' AND "EFF_DTE"<=TO_DATE('
2012-12-31 00:00:00', 'syyyy-mm-dd hh24:mi:ss'))Thanks,
VijayHi Justin,
Thanks for your reply. I am running this on our Test environment as I don't want to run this on Production environment now. The test environment holds 2809605 records (2 Million).
The query output count is 281699 (2 Hundred Thousand) records and the selectivity is 0.099. The Distinct values of create_ts, eff_dte, and exists_flg is 2808905 records. I am sure the index scan is not going to help out much as you said.
The core problem is both queries are using lot of Temp tablespace. When we use this query to join the tables, the other table has the same design as below so the temp tablespace grows bigger.
Both the production and test environment are 3 Node RAC.
First Query...
CPU used by this session 4740
CPU used when call started 4740
Cached Commit SCN referenced 21393
DB time 4745
OS Involuntary context switches 467
OS Page reclaims 64253
OS System time used 26
OS User time used 4562
OS Voluntary context switches 16
SQL*Net roundtrips to/from client 9
bytes received via SQL*Net from client 2487
bytes sent via SQL*Net to client 15830
calls to get snapshot scn: kcmgss 37
consistent gets 52162
consistent gets - examination 2
consistent gets from cache 52162
enqueue releases 19
enqueue requests 19
enqueue waits 1
execute count 2
ges messages sent 1
global enqueue gets sync 19
global enqueue releases 19
index fast full scans (full) 1
index scans kdiixs1 1
no work - consistent read gets 52125
opened cursors cumulative 2
parse count (hard) 1
parse count (total) 2
parse time cpu 1
parse time elapsed 1
physical write IO requests 69
physical write bytes 17522688
physical write total IO requests 69
physical write total bytes 17522688
physical write total multi block requests 69
physical writes 2139
physical writes direct 2139
physical writes direct temporary tablespace 2139
physical writes non checkpoint 2139
recursive calls 19
recursive cpu usage 1
session cursor cache hits 1
session logical reads 52162
sorts (memory) 2
sorts (rows) 760
table scan blocks gotten 23856
table scan rows gotten 2809607
table scans (short tables) 1
user I/O wait time 1
user calls 11
workarea executions - onepass 1
workarea executions - optimal 9
Second Query
CPU used by this session 1197
CPU used when call started 1197
Cached Commit SCN referenced 21393
DB time 1201
OS Involuntary context switches 8684
OS Page reclaims 21769
OS System time used 14
OS User time used 1183
OS Voluntary context switches 50
SQL*Net roundtrips to/from client 9
bytes received via SQL*Net from client 767
bytes sent via SQL*Net to client 15745
calls to get snapshot scn: kcmgss 17
consistent gets 23871
consistent gets from cache 23871
db block gets 16
db block gets from cache 16
enqueue releases 25
enqueue requests 25
enqueue waits 1
execute count 2
free buffer requested 1
ges messages sent 1
global enqueue get time 1
global enqueue gets sync 25
global enqueue releases 25
no work - consistent read gets 23856
opened cursors cumulative 2
parse count (hard) 1
parse count (total) 2
parse time elapsed 1
physical read IO requests 27
physical read bytes 6635520
physical read total IO requests 27
physical read total bytes 6635520
physical read total multi block requests 27
physical reads 810
physical reads direct 810
physical reads direct temporary tablespace 810
physical write IO requests 117
physical write bytes 24584192
physical write total IO requests 117
physical write total bytes 24584192
physical write total multi block requests 117
physical writes 3001
physical writes direct 3001
physical writes direct temporary tablespace 3001
physical writes non checkpoint 3001
recursive calls 25
session cursor cache hits 1
session logical reads 23887
sorts (disk) 1
sorts (memory) 2
sorts (rows) 2810365
table scan blocks gotten 23856
table scan rows gotten 2809607
table scans (short tables) 1
user I/O wait time 2
user calls 11
workarea executions - onepass 1
workarea executions - optimal 5Thanks,
Vijay
Edited by: Vijayaraghavan Krishnan on Nov 28, 2012 11:17 AM
Edited by: Vijayaraghavan Krishnan on Nov 28, 2012 11:19 AM -
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Most of the DW examples I've seen use a dimDateTime table in the database. That table has multiple columns related to the specific time... For example, here are the columns that are in the, SQL Server sample database, "AdventureWorkdDW"... "DimTime" table
COLUMN_NAME COLUMN_INFO
TimeKey (int, not null)
FullDateAlternateKey (datetime, null)
DayNumberOfWeek (tinyint, null)
EnglishDayNameOfWeek (nvarchar(10), null)
SpanishDayNameOfWeek (nvarchar(10), null)
FrenchDayNameOfWeek (nvarchar(10), null)
DayNumberOfMonth (tinyint, null)
DayNumberOfYear (smallint, null)
WeekNumberOfYear (tinyint, null)
EnglishMonthName (nvarchar(10), null)
SpanishMonthName (nvarchar(10), null)
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CalendarYear (char(4), null)
CalendarSemester (tinyint, null)
FiscalQuarter tinyint, null)
FiscalYear (char(4), null)
FiscalSemester (tinyint, null)
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