oracle 单列索引 多列索引的性能测试
清除oralce 缓存：alter system flush buffer_cache;
环境：oracle 10g 、 400万条数据，频率5分钟一条
1.应用场景： 找出所有站点的最新一条数据。sql语句如下：
——————————————————————————————————————————————————
with aa as(
select t1.EQP_ID ,max(MEASURE_TIME) maxtm from PLU_WATER_DATA t1 where t1.MEASURE_TIME >= to_date('2014-01-28 00:00:00', 'yyyy-MM-dd hh24:mi:ss')
and t1.MEASURE_TIME < to_date('2014-01-28 02:00:00', 'yyyy-MM-dd hh24:mi:ss') group by t1.EQP_ID
)
, bb as
(
select T1.EQP_ID as STCD,
T1.MEASURE_TIME as TM,
T1.FLUX_VALUE as FLOW
from PLU_WATER_DATA T1
where t1.MEASURE_TIME >= to_date('2014-01-28 00:00:00', 'yyyy-MM-dd hh24:mi:ss')
and t1.MEASURE_TIME < to_date('2014-01-28 02:00:00', 'yyyy-MM-dd hh24:mi:ss')
)
select * from aa inner join bb on aa.EQP_ID = bb.stcd and aa.maxtm = bb.tm inner join vi_plustation cc on cc.stcd =aa.EQP_ID
——————————————————————————————————————————
执行结果：
a.创建tm+stcd多列索引、tm单列索引、stcd单列索引 （执行时间2秒）
b.创建tm+stcd多列索引、stcd单列索引 （执行时间20秒）
c.创建stcd单列索引 (执行时间N秒)
d.创建tm+stcd多列索引 (执行时间22秒)
e.创建tm+stcd+tn+tp+cod多列索引 (执行时间71秒)
f.创建tm单列索引 (执行时间2秒)
2.应用场景 ： 找出单个站点的一段时间内的数据。sql语句如下：
select T1.EQP_ID as STCD,
T1.MEASURE_TIME as TM,
T1.FLUX_VALUE as FLOW
from PLU_WATER_DATA T1
where t1.MEASURE_TIME >= to_date('2014-01-28 00:00:00', 'yyyy-MM-dd hh24:mi:ss')
and t1.MEASURE_TIME < to_date('2014-01-28 23:00:00', 'yyyy-MM-dd hh24:mi:ss') and eqp_id = '1244'
执行结果：
查询条件在 tm和stcd上
a. 创建tm单列索引 (执行时间17秒）
b. 创建tm单列索引、stcd单列索引 (执行时间 3秒）
c. 创建tm单列索引、stcd单列索引、tm+stcd多列索引 (执行时间 0.5秒）
d. 创建tm+stcd多列索引 (执行时间 0.7秒）
3.结论：查询条件中stcd或者tm是单独作为where条件，如果使用了stcd+tm的多列索引，效率降低。如果stcd和tm是作为联合where条件，建立stcd和tm的单列索引，效率明显低于使用stcd+tm的多列索引。
a.当一个sql语句有站点分组跟时间查询嵌套使用时，推荐将stcd和tm分开建立单列索引。列如：
select t1.EQP_ID ,max(MEASURE_TIME) maxtm from PLU_WATER_DATA t1 where t1.MEASURE_TIME >= to_date('2014-01-28 00:00:00', 'yyyy-MM-dd hh24:mi:ss') and t1.MEASURE_TIME < to_date('2014-01-28 02:00:00', 'yyyy-MM-dd hh24:mi:ss') group by t1.EQP_ID)
像这样的语句如果建立的是 stcd+tm的多列索引，那么读取速度是7m，而如果使用stcd和tm分开建立单列索引，速度在2m内。
b.当一个sql语句 指定“站点”和“时间”时，推荐建立stcd+tm多列索引。例如
select T1.EQP_ID as STCD,T1.MEASURE_TIME as TM,T1.FLUX_VALUE as FLOW from PLU_WATER_DATA T1
where t1.MEASURE_TIME >= to_date('2014-01-28 00:00:00', 'yyyy-MM-dd hh24:mi:ss')
and t1.MEASURE_TIME < to_date('2014-01-28 23:00:00', 'yyyy-MM-dd hh24:mi:ss') and eqp_id = '1244'
像这样的语句如果建立的是stcd和tm分开建立单列索引，速度在3m，但如果建立了stcd+tm的多列索引，速度在0.7m
c.当一个sql语句 制定“时间”查询时，推荐建立 tm单列索引。例如
select T1.EQP_ID as STCD,T1.MEASURE_TIME as TM,T1.FLUX_VALUE as FLOW from PLU_WATER_DATA T1
where t1.MEASURE_TIME >= to_date('2014-01-28 00:00:00', 'yyyy-MM-dd hh24:mi:ss')
and t1.MEASURE_TIME < to_date('2014-01-28 23:00:00', 'yyyy-MM-dd hh24:mi:ss')
像这样的语句如果建立的是stcd+tm的复合索引，速度在5m，如果建立在tm的单列索引上，速度在1.5m
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实例： 10分钟风速的表，数据表多，做了月的动态分区，针对14个站点2天内最新一条数据的查询，建了，时间+站点的索引，查询结果卡死。 加了 单独时间的索引。速度飞起来。看来最新一条数据的查询，主要是用到了时间的单独索引上。
select rownum RN,tmp2.* from (select * from (select * from (select PSW091201,fsw090101, bb.psw090101,bb.A3011300307, ObserveTimeS, ObserveTimeX, OBSERVETIME , A3001200402 , A3020402200, A3020402200X, A3020402202 , A3020400700, A3020400700X, A3020400702 , A3005000100 from( select t1.PSW091201,t1.fsw090101, psw090101,A3011300307 ,ObserveTime as ObserveTimeS,ObserveTime as ObserveTimeX, case t1.A3001200402 when '0' then to_char( ObserveTime ,'yyyy-mm-dd hh24:mi') when '3' then '<span style=''color:red''>?</span>' else '<span style=''color:red''>'||to_char( ObserveTime ,'yyyy-mm-dd hh24:mi') ||'</span>' end as OBSERVETIME , t1.A3001200402 , case A3020402202 when '0' then trim(trailing '.' from to_char( A3020402200 ,'fm999990.999999')) when '3' then '<span style=''color:red''>?</span>' else '<span style=''color:red''>'||trim(trailing '.' from to_char( A3020402200 ,'fm999990.999999')) ||'</span>' end as A3020402200 ,A3020402200 A3020402200X, A3020402202 , case A3020400702 when '0' then trim(trailing '.' from to_char( A3020400700 ,'fm999990.999999')) when '3' then '<span style=''color:red''>?</span>' else '<span style=''color:red''>'||trim(trailing '.' from to_char( A3020400700 ,'fm999990.999999')) ||'</span>' end as A3020400700,A3020400700 A3020400700X, A3020400702 , '<a href="javascript:void(0);" onclick="openFileYC(''ZJYCZ'','''||A3005000100||''','''||to_char(ObserveTime,'yyyy-mm-dd')||''','''||psw090101||''')" >' ||A3005000100||'</a>' as A3005000100 from TSW091201 t1 inner join ocean.TSW090101 t2 on t1.fsw090101 = t2.PSW090101 and t2.TYPE= '自建' and 1=1inner join （ select fsw090101 ,max(observetime) maxobservetime from TSW091201 where 1=1 and observetime >= to_date('2016-03-26 15:40','yyyy-MM-dd hh24:mi:ss') and observetime <= to_date('2016-03-28 15:40','yyyy-MM-dd hh24:mi:ss') and （A3020402202= 0 ） group by fsw090101 ）t3 on t1.fsw090101 = t3.fsw090101 and t1.observetime=t3.maxobservetime ) aa,
( select PSW090101,A3011300307 from ocean.tsw090101 where TYPE = '自建') bb
where aa.FSW090101(+) = bb.PSW090101) tb where 1=1 order by ObserveTimeS DESC) tmp where rownum<=20 ) tmp2
实例 ： 浮标次表层流 去年一年数据查询，总数据有2486125条 查最新20条数据，需要11s。有FSW080101, OBSERVETIME, A3010000300 唯一索引 OBSERVETIME索引，以及动态月分区
select rownum RN,tmp2.* from (select * from (select * from (select PSW080303, fsw080101 ,psw080101, SBMC ,ObserveTimeS,ObserveTimeX,OBSERVETIME ,A3001200402 , A3010000300 ,A3010800700, A3010800700X,A3010800702 , A3010800800 , A3010800800X,A3010800802 , A3000700200 , A3000700200X,A3000700202 , A3005000100 from( select t1.PSW080303, t1.fsw080101 ,psw080101, SBMC ,ObserveTime as ObserveTimeS, ObserveTime as ObserveTimeX, case t1.A3001200402 when '0' then to_char( ObserveTime ,'yyyy-mm-dd hh24:mi') when '3' then '<span style=''color:red''>?</span>' else '<span style=''color:red''>'||to_char( ObserveTime ,'yyyy-mm-dd hh24:mi') ||'</span>' end as OBSERVETIME , t1.A3001200402 , A3010000300 , case A3010800702 when '0' then trim(trailing '.' from to_char( A3010800700 ,'fm999990.999999')) when '3' then '<span style=''color:red''>?</span>' else '<span style=''color:red''>'||trim(trailing '.' from to_char( A3010800700 ,'fm999990.999999')) ||'</span>' end as A3010800700,A3010800700 A3010800700X, A3010800702 , case A3010800802 when '0' then trim(trailing '.' from to_char( A3010800800 ,'fm999990.999999')) when '3' then '<span style=''color:red''>?</span>' else '<span style=''color:red''>'||trim(trailing '.' from to_char( A3010800800 ,'fm999990.999999')) ||'</span>' end as A3010800800 ,A3010800800 A3010800800X, A3010800802 , case A3000700202 when '0' then trim(trailing '.' from to_char( A3000700200 ,'fm999990.999999')) when '3' then '<span style=''color:red''>?</span>' else '<span style=''color:red''>'||trim(trailing '.' from to_char( A3000700200 ,'fm999990.999999')) ||'</span>' end as A3000700200 ,A3000700200 A3000700200X, A3000700202 , '<a href="javascript:void(0);" onclick="openFile(''DFB'','''||A3005000100||''','''||to_char(ObserveTime,'yyyy-mm-dd')||''')" >' ||A3005000100||'</a>' as A3005000100 from TSW080303 t1 inner join ocean.tsw080101 t2 on t1.fsw080101 = t2.psw080101 and t2.TYPE = '大浮标' and 1=1)) tb where 1=1 and ObserveTimeS>=to_date('2015-01-01 00:00','yyyy-mm-dd hh24:mi:ss') and ObserveTimeS<=to_date('2015-12-31 23:59','yyyy-mm-dd hh24:mi:ss') order by ObserveTimeS desc) tmp where rownum<=20 ) tmp2
2天内的最新数据，如果站点有100个。那么做站点的左连接，查询出来是比较慢的 5s差不多 需要优化
最新的20条记录，数据有50万 即使做了datetime动态分区，再使用了order by datetime desc。也是超级慢 需要优化 其实是慢在 inner join上 已解决
查月数据，有时间排序，数据超过1万条，查最新20条 查询的时间3s
执行7秒
select * from TSW080303 t inner join ocean.tsw080101 t2 on t.fsw080101 =t2.psw080101
where ObserveTime>=to_date('2015-01-01 00:00','yyyy-mm-dd hh24:mi:ss')
and ObserveTime<=to_date('2015-12-31 23:59','yyyy-mm-dd hh24:mi:ss')
order by ObserveTime desc
执行0秒
select t.*,(select sbmc from ocean.TSW080101 tt where tt.psw080101 = t.fsw080101) from TSW080303 t
where ObserveTime>=to_date('2015-01-01 00:00','yyyy-mm-dd hh24:mi:ss')
and ObserveTime<=to_date('2015-12-31 23:59','yyyy-mm-dd hh24:mi:ss')
and t.fsw080101 in (select psw080101 from ocean.tsw080101)
order by ObserveTime desc
执行1秒以内 最终优化结果。
select * from
(select * from TSW080303 t where ObserveTime>=to_date('2015-01-01 00:00','yyyy-mm-dd hh24:mi:ss')
and ObserveTime<=to_date('2015-12-31 23:59','yyyy-mm-dd hh24:mi:ss') order by ObserveTime desc) t
inner join
ocean.tsw080101 t2 on t.fsw080101 =t2.psw080101
结论：
其实性能是耗在 inner join以后再排序 就很慢了。所以要先排序，然后再进行inner join 就不会慢了。！！！
调优前：3秒
select rownum RN,tmp2.* from (select * from (select * from (select PSW080303, fsw080101 ,
psw080101, SBMC ,ObserveTimeS,ObserveTimeX,OBSERVETIME
, A3000700200X,A3000700202 , A3005000100 from( select t1.PSW080303, t1.fsw080101 ,psw080101,
SBMC ,ObserveTime as ObserveTimeS, ObserveTime as ObserveTimeX,case t1.A3001200402 when
'0' then to_char( ObserveTime ,'yyyy-mm-dd hh24:mi') when '3' then '<span style=''color:red''>?</span>'
else '<span style=''color:red''>'||to_char( ObserveTime ,'yyyy-mm-dd hh24:mi') ||'</span>' end as OBSERVETIME
,A3000700200 A3000700200X, A3000700202 ,
'<a href="javascript:void(0);"
onclick="openFile(''DFB'','''||A3005000100||''','''||to_char(ObserveTime,'yyyy-mm-dd')||''')" >'
||A3005000100||'</a>'
as A3005000100 from TSW080303 t1
inner join ocean.tsw080101 t2 on t1.fsw080101 = t2.psw080101
and t2.TYPE = '大浮标' and 1=1)) tb where 1=1
and ObserveTimeS>=to_date('2015-11-01 00:00','yyyy-mm-dd hh24:mi:ss')
and ObserveTimeS<=to_date('2015-12-31 23:59','yyyy-mm-dd hh24:mi:ss')
order by ObserveTimeS desc) tmp where rownum<=20 ) tmp2
调优后：0秒
select rownum RN,tmp2.* from (select * from (select * from (select PSW080303, fsw080101 ,
psw080101, SBMC ,ObserveTimeS,ObserveTimeX,OBSERVETIME
, A3000700200X,A3000700202 , A3005000100 from( select t1.*,psw080101,
SBMC from (select t1.PSW080303, t1.fsw080101 ,ObserveTime as ObserveTimeS, ObserveTime as ObserveTimeX,case t1.A3001200402 when
'0' then to_char( ObserveTime ,'yyyy-mm-dd hh24:mi') when '3' then '<span style=''color:red''>?</span>'
else '<span style=''color:red''>'||to_char( ObserveTime ,'yyyy-mm-dd hh24:mi') ||'</span>' end as OBSERVETIME
,A3000700200 A3000700200X, A3000700202 ,
'<a href="javascript:void(0);"
onclick="openFile(''DFB'','''||A3005000100||''','''||to_char(ObserveTime,'yyyy-mm-dd')||''')" >'
||A3005000100||'</a>'
as A3005000100 from TSW080303 t1 where 1=1
and ObserveTime>=to_date('2015-11-01 00:00','yyyy-mm-dd hh24:mi:ss')
and ObserveTime<=to_date('2015-12-31 23:59','yyyy-mm-dd hh24:mi:ss') order by ObserveTimeS desc )t1
inner join ocean.tsw080101 t2 on t1.fsw080101 = t2.psw080101
and t2.TYPE = '大浮标' and 1=1)) tb
) tmp where rownum<=20 ) tmp2
left join 的问题
调优前 4秒
select rownum RN,tmp2.* from
(
select * from
(select * from (
select bb.STCD,
bb.STNM, TM, QW, TQ, FX, FXZ, FS,
FL, ZFFS,ZFFL,NJD,XDSD,HPMQY,JY,REMARK from
(
select t1.STCD, STNM,
TM, QW, TQ, FX, FXZ, FS, FL,
ZFFS,ZFFL,NJD,XDSD,HPMQY,JY,T1.REMARK from ocean.WT_WeatherData_m t1
inner join ocean.WT_WeatherStation t2 on t1.STCD = t2.STCD
and t2.Type = '台湾气象站' and 1=1inner join ( select STCD, max(TM)
maxTM from ocean.WT_WeatherData_m where 1=1 and TM >=
to_date('2016-03-22 15:02','yyyy-MM-dd hh24:mi:ss') and
TM <= to_date('2016-03-24 15:02','yyyy-MM-dd hh24:mi:ss') group by STCD) t3
on t1.STCD = t3.STCD and t1.TM = t3.maxTM
) aa,
(
select STCD,STNM from ocean.WT_WeatherStation
where TYPE = '台湾气象站'
) bb
where aa.STCD(+) = bb.STCD
) tb where 1=1 order by TM DESC
) tmp
where rownum<=20
) tmp2
问题出在 order by TM DESC这个语句上
