场景1

使用场景：本案例适合满足以下条件的场景

关联条件使用OR连接
关联条件中使用同一列做数据筛选

原始语句

SELECT

t2.PARTNER_CHANNEL_CODE AS CHANNEL_ID

,t1.COUNTRY_CODE

,t1.BRAND

,t2.CHANNEL_ID AS CHANNEL_ID2

FROM

t1

LEFT JOIN

t2

ON

( t2.CHANNEL_ID = t1.CHANNEL_ID AND t1.TYPE = 'DR' )

OR ( t2.PARTNER_CHANNEL_CODE = t1.CHANNEL_ID AND t1.TYPE = 'ALL' )

GROUP BY

t2.PARTNER_CHANNEL_CODE

,t1.COUNTRY_CODE

,t1.BRAND

,t2.CHANNEL_ID

性能分析

通过查询计划分析发现，t1表和t2表关联走了NEST LOOP，查询整体耗时45S，NEST LOOP耗时占用整个查询执行耗时的96%。因此考虑能否通过SQL改写或HINT规避NEST LOOP。观察发现t1表和t2表包含两个关联关联条件，两个关联条件之间使用OR连接，属于非等值关联，因此不能走HASH JOIN。进一步分析SQL发现两个关联条件中都使用t1.TYPE进行过滤筛选：

(t2.CHANNEL_ID = t1.CHANNEL_ID AND t1.TYPE='DR')

OR (t2.PARTNER_CHANNEL_CODE = t1.CHANNEL_ID AND t1.TYPE='ALL' )

该关联条件包含以下三种关联组合：

t1表中t1.TYPE=’DR’的行，只能使用第一个关联条件与t2表关联；
t1表中t1.TYPE=’ALL’的行，只能使用第二个关联条件与t2表关联；
t1表中t1.TYPE NOT IN (‘ALL’,’DR’)的行，不与t2表关联，直接补空。

t1表中的一行数据只能选择这三个关联条件中的一个与t2表关联，因此该关联条件可以改写为不同关联条件的UNION ALL（UNION会去重，不等价）。

优化改写

改写后SQL如下所示：

SELECT

CHANNEL_ID

,COUNTRY_CODE

,BRAND

,CHANNEL_ID

FROM

(

SELECT

t2.PARTNER_CHANNEL_CODE AS CHANNEL_ID

,t1.COUNTRY_CODE

,t1.BRAND

,t2.CHANNEL_ID AS CHANNEL_ID2

FROM

t1

LEFT JOIN

t2

ON

t2.CHANNEL_ID = t1.CHANNEL_ID

WHERE

t1.TYPE = 'DR'

UNION ALL

SELECT

t2.PARTNER_CHANNEL_CODE AS CHANNEL_ID

,t1.COUNTRY_CODE

,t1.BRAND

,t2.CHANNEL_ID AS CHANNEL_ID2

FROM

t1

t2

ON t2.PARTNER_CHANNEL_CODE = t1.CHANNEL_ID

WHERE t1.TYPE='ALL'

UNION ALL

SELECT

t2.PARTNER_CHANNEL_CODE AS CHANNEL_ID

,t1.COUNTRY_CODE

,t1.BRAND

,t2.CHANNEL_ID AS CHANNEL_ID2

FROM t1

LEFT JOIN

t2

ON FALSE

WHERE t1.TYPE NOT IN ('ALL','DR')

)

GROUP BY CHANNEL_ID,COUNTRY_CODE,BRAND,CHANNEL_ID

改写后SQL变为三个子查询的UNION ALL，执行时间缩减至1s以内，性能优化45倍。

场景二

使用场景：本案例适合满足以下条件的场景

大表A不等值关联小表B
B的等值关联字段为主键

【原始语句】

SELECT

T.CREATE_INVOICE_USER,

T.PERIOD_ID,

T.AP_INVOICE_ID,

T.AP_INVOICE_NUM,

T.AP_BATCH_NAME,

EMP1.EMPLOYEE_NO,

EMP1.EMPLOYEE_NAME

FROM DWACTDI.DWR_AP_GLOBAL_INVOICE_DETAIL_F_I T

LEFT JOIN DWRDIM_DW1.DWR_DIM_EMPLOYEE_D EMP1 ON (EMP1.SCD_ACTIVE_IND = 1 AND(T.CREATE_INVOICE_USER = EMP1.EMPLOYEE_NO OR SUBSTR(T.CREATE_INVOICE_USER, 2) = EMP1.EMPLOYEE_NO))

【性能分析】

原始语句执行超时(超过1h)，执行计划如下。可以看到执行语句存在大表NestLoop操作

分析发现表dwrdim_dw1.dwr_dim_employee_d是维度表，且关联列employee_no是主键

【优化改写】

SELECT

T.CREATE_INVOICE_USER,

T.PERIOD_ID,

T.AP_INVOICE_ID,

T.AP_INVOICE_NUM,

T.AP_BATCH_NAME,

nvl(EMP1_0.EMPLOYEE_NO, EMP1_1.EMPLOYEE_NO) AS EMPLOYEE_NO,

nvl(EMP1_0.EMPLOYEE_NAME, EMP1_1.EMPLOYEE_NAME) AS ERP_ACCOUNTANT_ENAME

FROM DWACTDI.DWR_AP_GLOBAL_INVOICE_DETAIL_F_I T

LEFT JOIN DWRDIM_DW1.DWR_DIM_EMPLOYEE_D EMP1_0 ON (EMP1_0.SCD_ACTIVE_IND = 1 AND(T.CREATE_INVOICE_USER = EMP1_0.EMPLOYEE_NO))

LEFT JOIN DWRDIM_DW1.DWR_DIM_EMPLOYEE_D EMP1_1 ON (EMP1_1.SCD_ACTIVE_IND = 1 AND(SUBSTR(T.CREATE_INVOICE_USER, 2) = EMP1_1.EMPLOYEE_NO))

改写后执行信息如下

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2个数仓中不等值关联优化案例

场景1