视图合并、hash join连接列数据分布不均匀引发的惨案
来源：互联网 发布：申根签证截止日期 知乎 编辑：程序博客网 时间：2024/05/01 03:30
表大小
SQL> select count(*) from agent.TB_AGENT_INFO; COUNT(*)---------- 1751SQL> select count(*) from TB_CHANNEL_INFO ; COUNT(*)---------- 1807SQL> select count(*) from TB_USER_CHANNEL; COUNT(*)---------- 7269SQL> select count(*) from OSS_USER_STATION; COUNT(*)---------- 2149SQL> select count(*) from tb_user_zgy ; COUNT(*)---------- 43SQL> select count(*) from act.tb_user_agent_relat; COUNT(*)---------- 29612SQL> select count(*) from agent.base_data_user_info ; COUNT(*)---------- 30005SQL> select count(*) from agent.base_data_invest_info; COUNT(*)---------- 3530163慢的sql
select a.city, a.agent_id, a.username, a.real_name, phone, zgy_name, login_count, user_count, count(distinct b.invest_id) user_invested, sum(b.order_amount / 100) invest_amount from (select a.city, a.agent_id, a.username, a.real_name, -- 业主姓名 a.phone, -- 业主手机号 d.real_name zgy_name, -- 所属专管员 count(distinct case when c.str_day <= '20160821' then c.login_name end) login_count, count(distinct case when c.str_day <= '20160821' then decode(c.status, 1, c.invest_id, null) end) user_count from (select agent_id, city, username, real_name, phone from agent.TB_AGENT_INFO where agent_id in (SELECT agent_id FROM (SELECT distinct * FROM TB_CHANNEL_INFO t START WITH t.CHANNEL_ID in (select CHANNEL_ID from TB_USER_CHANNEL where USER_ID = 596) CONNECT BY PRIOR t.CHANNEL_ID = t.PARENT_CHANNEL_ID) WHERE agent_id IS NOT NULL)) a left join oss_user_station e on a.agent_id = e.agent_id and e.user_type = 0 left join tb_user_zgy d on e.username = d.username left join act.tb_user_agent_relat c on a.agent_id = c.agent_id group by a.city, a.username, a.real_name, a.phone, d.real_name, a.agent_id) a left join (select invest_id, order_amount, agent_id, str_day from agent.base_data_invest_info where str_day >= '20150801' and str_day<='20160821') b on a.agent_id = b.agent_id group by a.city, a.agent_id, a.username, a.real_name, a.phone, a.zgy_name, a.login_count, a.user_count这个查询可以看成两部分，第一部分一堆小表关联的a和唯一的一个大表再做关联man----------------------------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |----------------------------------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 55M| 6616M| | 3934K (1)| 13:06:52 || 1 | HASH GROUP BY | | 55M| 6616M| | 3934K (1)| 13:06:52 || 2 | VIEW | VW_DAG_1 | 55M| 6616M| | 3934K (1)| 13:06:52 || 3 | HASH GROUP BY | | 55M| 6301M| 7681M| 3934K (1)| 13:06:52 || 4 | VIEW | VM_NWVW_0 | 55M| 6301M| | 2456K (1)| 08:11:15 || 5 | SORT GROUP BY | | 55M| 10G| 11G| 2456K (1)| 08:11:15 ||* 6 | HASH JOIN RIGHT OUTER | | 55M| 10G| | 21643 (2)| 00:04:20 || 7 | TABLE ACCESS FULL | TB_USER_AGENT_RELAT | 27937 | 1200K| | 102 (0)| 00:00:02 ||* 8 | HASH JOIN OUTER | | 3374K| 511M| | 21392 (1)| 00:04:17 ||* 9 | HASH JOIN SEMI | | 1712 | 188K| | 2007 (1)| 00:00:25 ||* 10 | HASH JOIN RIGHT OUTER | | 1712 | 173K| | 32 (0)| 00:00:01 || 11 | TABLE ACCESS FULL | TB_USER_ZGY | 43 | 903 | | 3 (0)| 00:00:01 ||* 12 | HASH JOIN RIGHT OUTER | | 1712 | 138K| | 29 (0)| 00:00:01 ||* 13 | TABLE ACCESS FULL | OSS_USER_STATION | 1075 | 25800 | | 6 (0)| 00:00:01 || 14 | TABLE ACCESS FULL | TB_AGENT_INFO | 1712 | 98K| | 23 (0)| 00:00:01 || 15 | VIEW | VW_NSO_1 | 16271 | 143K| | 1975 (1)| 00:00:24 ||* 16 | VIEW | | 16271 | 143K| | 1975 (1)| 00:00:24 || 17 | HASH UNIQUE | | 16271 | 8882K| 10M| 1975 (1)| 00:00:24 ||* 18 | CONNECT BY WITHOUT FILTERING (UNIQUE)| | | | | | ||* 19 | HASH JOIN RIGHT SEMI | | 530 | 146K| | 29 (0)| 00:00:01 ||* 20 | TABLE ACCESS FULL | TB_USER_CHANNEL | 600 | 7800 | | 7 (0)| 00:00:01 || 21 | TABLE ACCESS FULL | TB_CHANNEL_INFO | 1807 | 476K| | 22 (0)| 00:00:01 || 22 | TABLE ACCESS FULL | TB_CHANNEL_INFO | 1807 | 476K| | 22 (0)| 00:00:01 ||* 23 | TABLE ACCESS FULL | BASE_DATA_INVEST_INFO | 3374K| 148M| | 19375 (1)| 00:03:53 |----------------------------------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id):--------------------------------------------------- 6 - access("AGENT_ID"="C"."AGENT_ID"(+)) 8 - access("AGENT_ID"="AGENT_ID"(+)) 9 - access("AGENT_ID"="AGENT_ID") 10 - access("C"."USERNAME"="D"."USERNAME"(+)) 12 - access("AGENT_ID"="C"."AGENT_ID"(+)) 13 - filter("C"."USER_TYPE"(+)=0) 16 - filter("AGENT_ID" IS NOT NULL) 18 - access("T"."PARENT_CHANNEL_ID"=PRIOR "T"."CHANNEL_ID") 19 - access("T"."CHANNEL_ID"="CHANNEL_ID") 20 - filter("USER_ID"=596) 23 - filter("STR_DAY"(+)>='20150801' AND "STR_DAY"(+)<='20160821')尝试单独跑 a,很快
(select a.city, a.agent_id, a.username, a.real_name, -- 业主姓名 a.phone, -- 业主手机号 d.real_name zgy_name, -- 所属专管员 count(distinct case when c.str_day <= '20160821' then c.login_name end) login_count, count(distinct case when c.str_day <= '20160821' then decode(c.status, 1, c.invest_id, null) end) user_count from (select agent_id, city, username, real_name, phone from agent.TB_AGENT_INFO where agent_id in (SELECT agent_id FROM (SELECT distinct * FROM TB_CHANNEL_INFO t START WITH t.CHANNEL_ID in (select CHANNEL_ID from TB_USER_CHANNEL where USER_ID = 596) CONNECT BY PRIOR t.CHANNEL_ID = t.PARENT_CHANNEL_ID) WHERE agent_id IS NOT NULL)) a left join oss_user_station e on a.agent_id = e.agent_id and e.user_type = 0 left join tb_user_zgy d on e.username = d.username left join act.tb_user_agent_relat c on a.agent_id = c.agent_id group by a.city, a.username, a.real_name, a.phone, d.real_name, a.agent_id) a单独跑a很快，和b合在一起就很慢，那么怀疑是由于视图合并，导致了a内部的表提前去和b关联，引发了性能问题。
尝试禁止视图合并可以使用rownum>0,或no_merge hint
select a.city, a.agent_id, a.username, a.real_name, phone, zgy_name, login_count, user_count, count(distinct b.invest_id) user_invested, sum(b.order_amount / 100) invest_amount from (select * from (select a.city, a.agent_id, a.username, a.real_name, -- 业主姓名 a.phone, -- 业主手机号 d.real_name zgy_name, -- 所属专管员 count(distinct case when c.str_day <= '20160821' then c.login_name end) login_count, count(distinct case when c.str_day <= '20160821' then decode(c.status, 1, c.invest_id, null) end) user_count from (select agent_id, city, username, real_name, phone from agent.TB_AGENT_INFO where agent_id in (SELECT agent_id FROM (SELECT distinct * FROM TB_CHANNEL_INFO t START WITH t.CHANNEL_ID in (select CHANNEL_ID from TB_USER_CHANNEL where USER_ID = 596) CONNECT BY PRIOR t.CHANNEL_ID = t.PARENT_CHANNEL_ID) WHERE agent_id IS NOT NULL)) a left join oss_user_station e on a.agent_id = e.agent_id and e.user_type = 0 left join tb_user_zgy d on e.username = d.username left join act.tb_user_agent_relat c on a.agent_id = c.agent_id group by a.city, a.username, a.real_name, a.phone, d.real_name, a.agent_id) where rownum>0)a left join (select invest_id, order_amount, agent_id, str_day from agent.base_data_invest_info where str_day >= '20150801' and str_day<='20160821') b on a.agent_id = b.agent_id group by a.city, a.agent_id, a.username, a.real_name, a.phone, a.zgy_name, a.login_count, a.user_countkuai-----------------------------------------------------------------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |-----------------------------------------------------------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 823M| 96G| | 23M (1)| 78:59:52 || 1 | HASH GROUP BY | | 823M| 96G| | 23M (1)| 78:59:52 || 2 | VIEW | VW_DAG_0 | 823M| 96G| | 23M (1)| 78:59:52 || 3 | HASH GROUP BY | | 823M| 98G| 112G| 23M (1)| 78:59:52 ||* 4 | HASH JOIN OUTER | | 823M| 98G| 26M| 41358 (6)| 00:08:17 || 5 | VIEW | | 259K| 23M| | 11090 (1)| 00:02:14 || 6 | COUNT | | | | | | ||* 7 | FILTER | | | | | | || 8 | VIEW | | 259K| 23M| | 11090 (1)| 00:02:14 || 9 | SORT GROUP BY | | 259K| 38M| 41M| 11090 (1)| 00:02:14 ||* 10 | HASH JOIN | | 259K| 38M| | 2111 (1)| 00:00:26 ||* 11 | VIEW | | 16271 | 143K| | 1975 (1)| 00:00:24 || 12 | HASH UNIQUE | | 16271 | 8882K| 10M| 1975 (1)| 00:00:24 ||* 13 | CONNECT BY WITHOUT FILTERING (UNIQUE)| | | | | | ||* 14 | HASH JOIN RIGHT SEMI | | 530 | 146K| | 29 (0)| 00:00:01 ||* 15 | TABLE ACCESS FULL | TB_USER_CHANNEL | 600 | 7800 | | 7 (0)| 00:00:01 || 16 | TABLE ACCESS FULL | TB_CHANNEL_INFO | 1807 | 476K| | 22 (0)| 00:00:01 || 17 | TABLE ACCESS FULL | TB_CHANNEL_INFO | 1807 | 476K| | 22 (0)| 00:00:01 ||* 18 | HASH JOIN OUTER | | 27937 | 4037K| | 134 (0)| 00:00:02 ||* 19 | HASH JOIN RIGHT OUTER | | 1712 | 173K| | 32 (0)| 00:00:01 || 20 | TABLE ACCESS FULL | TB_USER_ZGY | 43 | 903 | | 3 (0)| 00:00:01 ||* 21 | HASH JOIN RIGHT OUTER | | 1712 | 138K| | 29 (0)| 00:00:01 ||* 22 | TABLE ACCESS FULL | OSS_USER_STATION | 1075 | 25800 | | 6 (0)| 00:00:01 || 23 | TABLE ACCESS FULL | TB_AGENT_INFO | 1712 | 98K| | 23 (0)| 00:00:01 || 24 | TABLE ACCESS FULL | TB_USER_AGENT_RELAT | 27937 | 1200K| | 102 (0)| 00:00:02 ||* 25 | TABLE ACCESS FULL | BASE_DATA_INVEST_INFO | 3374K| 109M| | 19375 (1)| 00:03:53 |-----------------------------------------------------------------------------------------------------------------------------------Predicate Information (identified by operation id):--------------------------------------------------- 4 - access("A"."AGENT_ID"="AGENT_ID"(+)) 7 - filter(ROWNUM>0) 10 - access("AGENT_ID"="AGENT_ID") 11 - filter("AGENT_ID" IS NOT NULL) 13 - access("T"."PARENT_CHANNEL_ID"=PRIOR "T"."CHANNEL_ID") 14 - access("T"."CHANNEL_ID"="CHANNEL_ID") 15 - filter("USER_ID"=596) 18 - access("AGENT_ID"="C"."AGENT_ID"(+)) 19 - access("C"."USERNAME"="D"."USERNAME"(+)) 21 - access("AGENT_ID"="C"."AGENT_ID"(+)) 22 - filter("C"."USER_TYPE"(+)=0) 25 - filter("STR_DAY"(+)>='20150801' AND "STR_DAY"(+)<='20160821')用no_merge hint禁止视图合并也可以
select a.city, a.agent_id, a.username, a.real_name, phone, zgy_name, login_count, user_count, count(distinct b.invest_id) user_invested, sum(b.order_amount / 100) invest_amount from (select /*+ no_merge */ a.city, a.agent_id, a.username, a.real_name, -- 业主姓名 a.phone, -- 业主手机号 d.real_name zgy_name, -- 所属专管员 count(distinct case when c.str_day <= '20160821' then c.login_name end) login_count, count(distinct case when c.str_day <= '20160821' then decode(c.status, 1, c.invest_id, null) end) user_count from (select /*+ qb_name(sb) */ agent_id, city, username, real_name, phone from agent.TB_AGENT_INFO where agent_id in (SELECT agent_id FROM (SELECT distinct * FROM TB_CHANNEL_INFO t START WITH t.CHANNEL_ID in (select CHANNEL_ID from TB_USER_CHANNEL where USER_ID = 596) CONNECT BY PRIOR t.CHANNEL_ID = t.PARENT_CHANNEL_ID) WHERE agent_id IS NOT NULL)) a left join oss_user_station e on a.agent_id = e.agent_id and e.user_type = 0 left join tb_user_zgy d on e.username = d.username left join (select * from act.tb_user_agent_relat c) c on a.agent_id = c.agent_id group by a.city, a.username, a.real_name, a.phone, d.real_name, a.agent_id) a left join (select invest_id, order_amount, agent_id, str_day from agent.base_data_invest_info where str_day >= '20150801' and str_day<='20160821') b on a.agent_id = b.agent_id group by a.city, a.agent_id, a.username, a.real_name, a.phone, a.zgy_name, a.login_count, a.user_count
至此sql从一个小时都跑不完，到最后两秒跑完，工作已经完成，但是单从慢的执行计划中并没有看出什么问题。有聚合函数group by走hash没有错，虽然有全表扫描带*但是要么过滤性太差，要么不是性能瓶颈。那为什么总共300多w就跑不完了呢
慢的执行计划做一个10046
Number of plan statistics captured: 1Rows (1st) Rows (avg) Rows (max) Row Source Operation---------- ---------- ---------- --------------------------------------------------- 0 0 0 HASH GROUP BY (cr=0 pr=0 pw=0 time=278 us cost=3934270 size=6937507584 card=55059584) 0 0 0 VIEW VW_DAG_1 (cr=0 pr=0 pw=0 time=111 us cost=3934270 size=6937507584 card=55059584) 0 0 0 HASH GROUP BY (cr=0 pr=0 pw=0 time=108 us cost=3934270 size=6607150080 card=55059584) 0 0 0 VIEW VM_NWVW_0 (cr=0 pr=0 pw=0 time=32 us cost=2456206 size=6607150080 card=55059584) 0 0 0 SORT GROUP BY (cr=0 pr=0 pw=0 time=31 us cost=2456206 size=11177095552 card=55059584) 148234852 148234852 148234852 HASH JOIN RIGHT OUTER (cr=34882 pr=0 pw=0 time=34098445 us cost=21643 size=11177095552 card=55059584) 29651 29651 29651 TABLE ACCESS FULL TB_USER_AGENT_RELAT (cr=332 pr=0 pw=0 time=8201 us cost=102 size=1229228 card=27937) 703556 703556 703556 HASH JOIN OUTER (cr=34550 pr=0 pw=0 time=1518631 us cost=21392 size=536480628 card=3374092) 612 612 612 HASH JOIN SEMI (cr=272 pr=0 pw=0 time=31359 us cost=2007 size=193456 card=1712) 1751 1751 1751 HASH JOIN RIGHT OUTER (cr=100 pr=0 pw=0 time=11404 us cost=32 size=178048 card=1712) 43 43 43 TABLE ACCESS FULL TB_USER_ZGY (cr=2 pr=0 pw=0 time=103 us cost=3 size=903 card=43) 1751 1751 1751 HASH JOIN RIGHT OUTER (cr=98 pr=0 pw=0 time=6664 us cost=29 size=142096 card=1712) 1312 1312 1312 TABLE ACCESS FULL OSS_USER_STATION (cr=15 pr=0 pw=0 time=420 us cost=6 size=25800 card=1075) 1751 1751 1751 TABLE ACCESS FULL TB_AGENT_INFO (cr=83 pr=0 pw=0 time=1804 us cost=23 size=101008 card=1712) 612 612 612 VIEW VW_NSO_1 (cr=172 pr=0 pw=0 time=19720 us cost=1975 size=146439 card=16271) 612 612 612 VIEW (cr=172 pr=0 pw=0 time=19351 us cost=1975 size=146439 card=16271) 613 613 613 HASH UNIQUE (cr=172 pr=0 pw=0 time=19224 us cost=1975 size=9095489 card=16271) 1215 1215 1215 CONNECT BY WITHOUT FILTERING (UNIQUE) (cr=172 pr=0 pw=0 time=16687 us) 603 603 603 HASH JOIN RIGHT SEMI (cr=97 pr=0 pw=0 time=4922 us cost=29 size=149990 card=530) 603 603 603 TABLE ACCESS FULL TB_USER_CHANNEL (cr=22 pr=0 pw=0 time=550 us cost=7 size=7800 card=600) 1807 1807 1807 TABLE ACCESS FULL TB_CHANNEL_INFO (cr=75 pr=0 pw=0 time=1615 us cost=22 size=487890 card=1807) 1807 1807 1807 TABLE ACCESS FULL TB_CHANNEL_INFO (cr=75 pr=0 pw=0 time=1133 us cost=22 size=487890 card=1807) 1631878 1631878 1631878 TABLE ACCESS FULL BASE_DATA_INVEST_INFO (cr=34278 pr=0 pw=0 time=950767 us cost=19375 size=155208232 card=3374092)id 6 1亿4千多万，一个多小时也没跑出来
并且temp撑爆了
第 43 行出现错误:
ORA-01652: 无法通过 128 (在表空间 TEMP 中) 扩展 temp 段
一亿四千多万，b表才300万，sql group by之前也不过一百多万的结果
根据 6 -
access(“AGENT_ID”=”C”.”AGENT_ID”(+)) 查看c和b表agent_id数据分布
select agent_id,count(*) from act.tb_user_agent_relat group by agent_id order by 2 desc 
最多的6827行，最少的1行
select agent_id,count(*) from agent.base_data_invest_info group by agent_id order by 2 desc
最多50w，最少1行
又一次进了hash join链接列数据分布不均匀的坑，hash join只适合数据分布均匀的列做链接条件
做个oradebug short_stack
SQL> select unique sid from v$mystat; SID---------- 1132SQL> select p.spid from v$process p ,v$session s where s.paddr=p.addr and s.sid=1132;SPID------------------------------------------------28539oradebug setospid 28539SQL> oradebug short_stackksedsts()+465<-ksdxfstk()+32<-ksdxcb()+1927<-sspuser()+112<-__sighandler()<-io_submit()+7<-skgfqio()+1275<-ksfd_skgfqio()+894<-ksfdgo()+423<-ksfdaio()+2290<-kcflbi()+906<-kcbldio()+3104<-kcblsltio()+530<-stsIssueWrite()+118<-stsGetBlock()+442<-sdbinb()+135<-sdbput()+1042<-smbwrt()+247<-smbput()+2503<-sorput()+93<-qesaEvaAndPutDistAggOpns()+590<-qergsRowP()+430<-qerhjWalkHashBucket()+397<-qerhjGenProbeHashTable()+1571<-qerhjGenProbeHashTable()+718<-kdstf11011010000km()+673<-kdsttgr()+153241<-qertbFetch()+2455<-rwsfcd()+103<-qerhjFetch()+1661<-rwsfcd()+103<-qerhjFetch()+1661<-qergsFetch()+757<-qervwFetch()+139<-qerghFetch()+315<-qervwFetch()+139<-qerghFetch()+315<-opifch2()+2766<-kpoal8()+2833<-opiodr()+917<-ttcpip()+2183<-opitsk()+1710<-opiino()+969<-opiodr()+917<-opidrv()+570<-sou2o()+103<-opimai_real()+133<-ssthrdmain()+265<-main()+201<-__libc_start_main()+244SQL> SQL> SQL> SQL> SQL> oradebug short_stackksedsts()+465<-ksdxfstk()+32<-ksdxcb()+1927<-sspuser()+112<-__sighandler()<-io_submit()+7<-skgfqio()+1275<-ksfd_skgfqio()+894<-ksfdgo()+423<-ksfdaio()+2290<-kcflbi()+906<-kcbldio()+3104<-kcblsltio()+530<-stsIssueWrite()+118<-stsGetBlock()+442<-sdbinb()+135<-sdbput()+1042<-smbwrt()+247<-smbput()+2503<-sorput()+93<-qesaEvaAndPutDistAggOpns()+590<-qergsRowP()+430<-qerhjWalkHashBucket()+397<-qerhjGenProbeHashTable()+1571<-qerhjWalkHashBucket()+397<-qerhjGenProbeHashTable()+1571<-kdstf11011010000km()+673<-kdsttgr()+153241<-qertbFetch()+2455<-rwsfcd()+103<-qerhjFetch()+1661<-rwsfcd()+103<-qerhjFetch()+1661<-qergsFetch()+757<-qervwFetch()+139<-qerghFetch()+315<-qervwFetch()+139<-qerghFetch()+315<-opifch2()+2766<-kpoal8()+2833<-opiodr()+917<-ttcpip()+2183<-opitsk()+1710<-opiino()+969<-opiodr()+917<-opidrv()+570<-sou2o()+103<-opimai_real()+133<-ssthrdmain()+265<-main()+201<-__libc_start_main()+244SQL> SQL> SQL> SQL> SQL> oradebug short_stackksedsts()+465<-ksdxfstk()+32<-ksdxcb()+1927<-sspuser()+112<-__sighandler()<-qergsRowP()+2161<-qerhjWalkHashBucket()+397<-qerhjGenProbeHashTable()+1571<-qerhjWalkHashBucket()+397<-qerhjGenProbeHashTable()+1571<-kdstf11011010000km()+673<-kdsttgr()+153241<-qertbFetch()+2455<-rwsfcd()+103<-qerhjFetch()+1661<-rwsfcd()+103<-qerhjFetch()+1661<-qergsFetch()+757<-qervwFetch()+139<-qerghFetch()+315<-qervwFetch()+139<-qerghFetch()+315<-opifch2()+2766<-kpoal8()+2833<-opiodr()+917<-ttcpip()+2183<-opitsk()+1710<-opiino()+969<-opiodr()+917<-opidrv()+570<-sou2o()+103<-opimai_real()+133<-ssthrdmain()+265<-main()+201<-__libc_start_main()+244SQL> oradebug short_stackksedsts()+465<-ksdxfstk()+32<-ksdxcb()+1927<-sspuser()+112<-__sighandler()<-lmebco()+63<-qesaSimpleCompare()+73<-smbput()+913<-sorput()+93<-qergsRowP()+1067<-qerhjWalkHashBucket()+397<-qerhjGenProbeHashTable()+1571<-qerhjGenProbeHashTable()+718<-kdstf11011010000km()+673<-kdsttgr()+153241<-qertbFetch()+2455<-rwsfcd()+103<-qerhjFetch()+1661<-rwsfcd()+103<-qerhjFetch()+1661<-qergsFetch()+757<-qervwFetch()+139<-qerghFetch()+315<-qervwFetch()+139<-qerghFetch()+315<-opifch2()+2766<-kpoal8()+2833<-opiodr()+917<-ttcpip()+2183<-opitsk()+1710<-opiino()+969<-opiodr()+917<-opidrv()+570<-sou2o()+103<-opimai_real()+133<-ssthrdmain()+265<-main()+201<-__libc_start_main()+244可以看到qerhjWalkHashBucketqerhjWalkHashBucket就表示在做hash join的过程中需要遍历hash bucket中的数据，当链接列数据分布不均，某些值特别多时，遍历其hash bucket的成本也就非常高，如果pga放不下了，就会放到temp进行磁盘io，这就是性能瓶颈的原因，这个例子把30g的temp表空间都撑爆了，可见hash bucket有多大！做个SQL MONITOR，也可以看出，瓶颈在id 6。如果做一个sql rpt也可以发现sql执行过程中的每妙逻辑读实际并不高，因为时间都花在了遍历hash bucket中 
1 0
- 视图合并、hash join连接列数据分布不均匀引发的惨案
- 数据分布不均匀走HASH JOIN导致的性能问题
- const引发的惨案
- 由proxool连接池所引发的惨案
- 一个电阻引发的惨案
- 谓词推入引发的惨案
- realloc函数引发的惨案
- 更换jdk引发的惨案
- HBase regions分布不均匀的解决
- DataFrame 数据合并，连接（merge,join,concat)
- DataFrame 数据合并，连接（merge,join,concat)
- 一个反射引发的异常惨案
- VS2010下注释引发的惨案
- SQL Server Collation引发的惨案
- 一条sleep语句引发的惨案
- 由sp单位引发的惨案
- javascript：一次alert引发的惨案
- 搞笑：一段内存引发的惨案
- Hibernate读书笔记-----SQL查询 addScalar()或addEntity()
- 【shell】从文件中读取参数传给驱动模块
- The special grammar for PHP
- Python学习笔记2
- 在154个元素组成有序表进行二分法查找，可能的比较次数为（）
- 视图合并、hash join连接列数据分布不均匀引发的惨案
- Java中使用ResponseCache类构建本地缓存
- Java中继承abstract class和interface以及继承abstract class和普通class的应用比较
- ecshop二次开发--节日关怀
- JSONArray JSONObjec
- linux内核编译 menuconfig详解
- Servlet详解
- oracle存储过程和oracle函数demo
- 【PAT甲级】【C】1002. A+B for Polynomials (25)
