How to optimize the response time for the following query:
SELECT
/*+parallel */
cc.customer_id AS customer_id,
cc.title1 AS title1,
cc.forename1 AS forename1,
cc.forename2 AS forename2,
cc.surname1 AS surname1,
cc.surname2 AS surname2,
cc.company_flag AS company_flag,
cc.COMPANY_NAME AS COMPANY_NAME,
ext_customer_code AS code,
cc.customer_type AS category,
ca.address1 AS address1,
ca.address2 AS address2,
ca.address3 AS address3,
ca.address4 AS address4,
ca.address5 AS address5,
ca.postcode AS postcode,
ca.postcode_prefix AS postcode_prefix,
ca.country_code AS country_code,
ca.town AS town,
ca.county AS county,
cc.client_id AS client_id,
cc.location_id AS location_id,
cc.data_source_id AS dataSource_id,
cc.SALUTATION AS salutation,
cc.ADDRESS_MATCHKEY AS addressMatchKey,
ccv.vehicle_id AS vehicle_id,
cc.customer_name AS customer_name,
cv.REG_NUM AS REG_NUM
FROM OEM.CDB_CUSTOMERS cc,
OEM.CDB_ADDRESSES ca,
OEM.CDB_CUSTOMER_VEHICLES ccv,
OEM.CDB_VEHICLES cv
WHERE cc.client_id = ca.client_id
AND cc.address_matchkey = ca.address_matchkey
AND cc.location_id = ca.location_id
AND cc.customer_id = ccv.customer_id
AND cc.client_id = ccv.client_id
AND cc.LOCATION_ID = ccv.LOCATION_ID
AND ccv.vehicle_id = cv.vehicle_id
AND ccv.client_id = cv.CLIENT_ID
AND ccv.LOCATION_ID = cv.LOCATION_ID
AND cv.LOCATION_ID = 1
AND ccv.rejection_flag = 'N'
AND ccv.owner_status IS NOT NULL
AND cc.client_id = 1776
AND ca.client_id = 1776
AND ca.country_code ='UK'
AND ca.area_id IN
( SELECT start_code postcode_id FROM MDB_FORMAT WHERE NAME = 'PC%1776'
)
AND cv.model_id IN
( SELECT m.start_code model_id FROM MDB_FORMAT m WHERE m.NAME = '10_RWMOD'
)
ORDER BY customer_name,
town,
postcode
Here’s execution plan:
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
| 0 | SELECT STATEMENT | | 1 | 317 | 320 (1)| 00:00:04 |
| 1 | SORT ORDER BY | | 1 | 317 | 320 (1)| 00:00:04 |
| 2 | NESTED LOOPS | | 1 | 317 | 319 (1)| 00:00:04 |
| 3 | NESTED LOOPS | | 1 | 299 | 319 (1)| 00:00:04 |
| 4 | NESTED LOOPS | | 1 | 273 | 319 (1)| 00:00:04 |
|* 5 | HASH JOIN | | 8 | 1992 | 314 (1)| 00:00:04 |
| 6 | TABLE ACCESS BY INDEX ROWID| CDB_ADDRESSES | 10 | 1060 | 1 (0)| 00:00:01 |
| 7 | NESTED LOOPS | | 501 | 62124 | 30 (0)| 00:00:01 |
|* 8 | INDEX RANGE SCAN | MDB_FORMAT_PK | 48 | 864 | 1 (0)| 00:00:01 |
|* 9 | INDEX RANGE SCAN | CDB_ADDRESSES_SMM_IDX1 | 10 | | 1 (0)| 00:00:01 |
| 10 | TABLE ACCESS BY INDEX ROWID| CDB_CUSTOMERS | 28544 | 3484K| 283 (0)| 00:00:04 |
|* 11 | INDEX RANGE SCAN | CDB_CUSTOMERS_UK1 | 28544 | | 38 (0)| 00:00:01 |
|* 12 | TABLE ACCESS BY INDEX ROWID | CDB_CUSTOMER_VEHICLES | 1 | 24 | 1 (0)| 00:00:01 |
|* 13 | INDEX RANGE SCAN | CDB_CUSTOMER_VEHICLES_PK | 1 | | 1 (0)| 00:00:01 |
| 14 | TABLE ACCESS BY INDEX ROWID | CDB_VEHICLES | 1 | 26 | 1 (0)| 00:00:01 |
|* 15 | INDEX RANGE SCAN | CDB_VEHICLES_PREF_IND | 1 | | 1 (0)| 00:00:01 |
|* 16 | INDEX RANGE SCAN | MDB_FORMAT_PK | 1 | 18 | 1 (0)| 00:00:01 |
Predicate Information (identified by operation id):
5 - access("CC"."CLIENT_ID"="CA"."CLIENT_ID" AND "CC"."ADDRESS_MATCHKEY"="CA"."ADDRESS_MATCHKEY"
AND "CC"."LOCATION_ID"="CA"."LOCATION_ID")
8 - access("NAME"='PC%1776')
9 - access("CA"."CLIENT_ID"=1776 AND "CA"."AREA_ID"=TO_NUMBER("START_CODE") AND
"CA"."COUNTRY_CODE"='UK' AND "CA"."LOCATION_ID"=1)
11 - access("CC"."CLIENT_ID"=1776 AND "CC"."LOCATION_ID"=1)
12 - filter("CCV"."OWNER_STATUS" IS NOT NULL AND "CCV"."REJECTION_FLAG"='N')
13 - access("CCV"."CLIENT_ID"=1776 AND "CC"."CUSTOMER_ID"="CCV"."CUSTOMER_ID" AND
"CCV"."LOCATION_ID"=1)
filter("CCV"."LOCATION_ID"=1)
15 - access("CCV"."VEHICLE_ID"="CV"."VEHICLE_ID" AND "CV"."CLIENT_ID"=1776 AND
"CV"."LOCATION_ID"=1)
16 - access("M"."NAME"='10_RWMOD')
filter("CV"."MODEL_ID"=TO_NUMBER("M"."START_CODE"))
41 rows selected
Step 1: Make sure the query is correct. I’m not sure what your data model is, but I noticed you say “SELECT start_code postcode_id” and “SELECT m.start_code model_id”. Do you mean to alias the same field for two purposes?
Step 2: Analyze the tables. Out-of-date statistics might cause the optimizer to chose a bad plan.
Step 3: Write your join conditions in the FROM clause (e.g., “table1 JOIN table2 ON (table1.id = table2.id)). This makes it obvious to you, the optimizer, and anyone reading your code what you’re trying to do. It’s easier to rearrange something that’s already organized.
Step 4: Repeat Step 1.
Step 5: We’ll talk about that when you’ve gotten there.