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HomeDatabaseMysql TutorialSQL Optimization: A very simple article to improve SQL performance!

In order to improve the query efficiency in SQL queries, we often take some measures to optimize the query statements. Some of the methods summarized below can be referred to if necessary. In the optimization experience of a certain operator, I once encountered a relatively interesting SQL, the details are as follows:

1 The execution of the initial SQL is as follows

SQL> SELECT
  2    NVL(T.RELA_OFFER_SPEC_ID, SUBOS.SUB_OFFER_SPEC_ID) "offerSpecId"
  3    FROM OFFER_SPEC_RELA T
  4    LEFT JOIN OFFER_SPEC_GRP_RELA SUBOS
  5    ON T.RELA_GRP_ID     = SUBOS.OFFER_SPEC_GRP_ID
  6    AND subos.start_dt  <= SYSDATE
  7    AND subos.end_dt    >= SYSDATE
  8    WHERE T.RELA_TYPE_CD = 2
  9    AND t.start_dt      <= SYSDATE
 10    AND t.end_dt        >= SYSDATE
 11    AND (T.OFFER_SPEC_ID = 109910000618
 12    OR EXISTS
 13      (SELECT A.OFFER_SPEC_GRP_ID
 14      FROM OFFER_SPEC_GRP_RELA A
 15      WHERE A.SUB_OFFER_SPEC_ID = 109910000618
 16      AND T.OFFER_SPEC_GRP_ID   = A.OFFER_SPEC_GRP_ID
 17      ))
 18    AND rownum<500;

no rows selected
 
Execution Plan
----------------------------------------------------------
Plan hash value: 1350156609

SQL Optimization: A very simple article to improve SQL performance!

Predicate Information (identified by operation id):
---------------------------------------------------
   1 - filter(ROWNUM<500)
   2 - filter("T"."OFFER_SPEC_ID"=109910000618 OR  EXISTS (SELECT 0 FROM
              "SPEC"."OFFER_SPEC_GRP_RELA" "A" WHERE "A"."OFFER_SPEC_GRP_ID"=:B1 AND
              "A"."SUB_OFFER_SPEC_ID"=109910000618))
   3 - access("T"."RELA_GRP_ID"="SUBOS"."OFFER_SPEC_GRP_ID"(+))
   4 - filter("T"."RELA_TYPE_CD"=2 AND "T"."END_DT">=SYSDATE@! AND
              "T"."START_DT"<=SYSDATE@!)
   5 - filter("SUBOS"."END_DT"(+)>=SYSDATE@! AND "SUBOS"."START_DT"(+)<=SYSDATE@!)
   6 - access("A"."SUB_OFFER_SPEC_ID"=109910000618 AND "A"."OFFER_SPEC_GRP_ID"=:B1)
 
Statistics
----------------------------------------------------------
          0  recursive calls
          0  db block gets
      12444  consistent gets
          0  physical reads
          0  redo size
        339  bytes sent via SQL*Net to client
        509  bytes received via SQL*Net from client
          1  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
          0  rows processed
 
                  PLAN                     GET     DISK    WRITE              ROWS      ROWS USER_IO(MS)  ELA(MS)  CPU(MS) CLUSTER(MS)    PLSQL
END_TI I    HASH VALUE EXEC           PRE EXEC PRE EXEC PER EXEC ROW_P    PRE EXEC PRE FETCH    PER EXEC PRE EXEC PRE EXEC    PER EXEC PER EXEC

SQL Optimization: A very simple article to improve SQL performance!

2 First analysis
There should be the following points worth noting at this time
1) The sql is executed every day Thousands of times, the average execution returns less than 10 rows of data, but the average logical read reaches 1.2W, which may cause performance problems.
2) Two full table scans appear in the execution plan path with IDs 4 and 5. Seeing this, we can think that there may be no suitable indexes, resulting in a full table scan and low execution efficiency.
3) FILTER appears in the execution plan path with ID 2, and 3, and 6 are its sub-paths. If FILTER has two or more sub-paths, its execution principle will be similar to a nested loop. , if the subpath with the smallest ID number returns a large number of rows, it may cause the subpath with the smaller ID number to be executed multiple times, resulting in low performance. This situation generally occurs when "OR EXISTS" exists and can be avoided according to the situation.

Related links:

PHP-FPM achieves performance optimization, php-fpm performance optimization

[SQL]MySQL performance Optimization_MySQL

MySQL Optimization Video Tutorial

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