創(chuàng)建包含10個列（c01 - c10）的表my_table，用如下語句創(chuàng)建2個索引，并向表中插入6w條記錄。這6w條記錄的c01列，全部都是2017年04月21日的數(shù)據(jù)。

CREATE INDEX my_table_index1ON my_tableUSING btree(c05, c01, c02) TABLESPACE smart_history_index;CREATE INDEX my_table_index2ON my_tableUSING btree(c01, c02, c03, c04, c05) TABLESPACE smart_history_index;

使用以下SQL1語句查詢，查詢時間為2分鐘。
SQL1：

select * from my_table t1 where (select count(*) from my_table t2 where ((t1.c01 = t2.c01 ) or (t1.c01 is null and t2.c01 is null)) and ((t1.c02 = t2.c02 ) or (t1.c02 is null and t2.c02 is null)) and ((t1.c03 = t2.c03 ) or (t1.c03 is null and t2.c03 is null)) and ((t1.c04 = t2.c04 ) or (t1.c04 is null and t2.c04 is null)) and ((t1.c05 = t2.c05 ) or (t1.c05 is null and t2.c05 is null)) and ((t1.c06 = t2.c06 ) or (t1.c06 is null and t2.c06 is null)) and ((t1.c07 = t2.c07 ) or (t1.c07 is null and t2.c07 is null)) and ((t1.c08 = t2.c08 ) or (t1.c08 is null and t2.c08 is null)) and ((t1.c09 = t2.c09 ) or (t1.c09 is null and t2.c09 is null)) and ((t1.c10 = t2.c10 ) or (t1.c10 is null and t2.c10 is null)) )>1;

使用以下SQL2語句查詢，查詢時間為2.8秒。
SQL2：

select * from my_table t1 where (select count(*) from my_table t2 where ((t1.c01 = t2.c01 ) or (t1.c01 is null and t2.c01 is null)) and ((t1.c02 = t2.c02 ) or (t1.c02 is null and t2.c02 is null)) and ((t1.c03 = t2.c03 ) or (t1.c03 is null and t2.c03 is null)) and ((t1.c04 = t2.c04 ) or (t1.c04 is null and t2.c04 is null)) and ((t1.c05 = t2.c05 ) or (t1.c05 is null and t2.c05 is null)) and ((t1.c06 = t2.c06 ) or (t1.c06 is null and t2.c06 is null)) and ((t1.c07 = t2.c07 ) or (t1.c07 is null and t2.c07 is null)) and ((t1.c08 = t2.c08 ) or (t1.c08 is null and t2.c08 is null)) and ((t1.c09 = t2.c09 ) or (t1.c09 is null and t2.c09 is null)) and ((t1.c10 = t2.c10 ) or (t1.c10 is null and t2.c10 is null)) and (c01 >= '2017-04-20 00:00:00' and c01 < '2017-04-21 00:00:00') )>1 and (c01 >= '2017-04-20 00:00:00' and c01 < '2017-04-21 00:00:00');

雖然SQL2最后對于c01列的where條件并為實(shí)質(zhì)上減少過濾出的數(shù)據(jù)量。但是能夠顯著的提高查詢效率（60倍），進(jìn)一步使用以下SQL3語句監(jiān)視索引使用情況發(fā)現(xiàn)，SQL2只調(diào)用了my_table_index2，而SQL1既調(diào)用了my_table_index1也調(diào)用了my_table_index2。
SQL3：

select relname, indexrelname, idx_scan, idx_tup_read, idx_tup_fetch from pg_stat_user_indexes where relname = 'my_table' order by idx_scan asc, idx_tup_read asc, idx_tup_fetch asc;

顯然my_table_index2肯定比my_table_index1的辨識度更高。之所以SQL優(yōu)化解析器會做出這樣的選擇，猜測可能是因?yàn)閙y_table_index2中列c01處于第一個的位置，而SQL2最后的c01查詢條件剛好暗示強(qiáng)化了解釋器去選擇my_table_index2。
在此基礎(chǔ)上我進(jìn)行了進(jìn)一步的實(shí)驗(yàn)：如果drop掉my_table_index1只保留my_table_index2，則無論是SQL1還是SQL2都能達(dá)到大約2.8秒的查詢速度；如果drop掉my_table_index2只保留my_table_index1，則無論是SQL1還是SQL2都需要2分鐘才能完成查詢；當(dāng)然my_table_index1也并不是一無是處，如果將兩個索引全部drop掉，那么做一次查詢（全表掃描）大約需要10分鐘。

最后說兩點(diǎn)啟示：
1.索引不能隨便建，如果建的不好，不僅影響插入效率，也會影響查詢效率。
2.SQL語句優(yōu)化之路，任重而道遠(yuǎn)。

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