表关联优化方法分享

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在数据库中，表与表之间的关联，通过JOIN连接。可以理解为“横向关联”，如果是多个大表，“横向关联”，效率比较慢；

“纵向关联”：UNION每个表，再GROUPBY去重，得到“关联”的效果。“纵向关联”效率比“横向关联”强很多。

举例：T1，T2，T3，T4，T5，每个表有5000万条数据。

“横向关联”： JOIN关联，实际是5000万*5000万*5000万*5000万*5000万，实际是在笛卡尔集基础上，再过滤条件。【Hadoop：超过几个小时】

“纵向关联”：5000万+5000万+5000万+5000万+5000万。【Hadoop：30分内】

“纵向关联”示例代码：

INSERT OVERWRITE TABLET_DM_SCORE

SELECT

'20160606',

CUST_NO,

ID_NUMBER,

NAME,

MAX(SCORE1) AS SCORE1,

MAX(SCORE2) AS SCORE2,

MAX(SCORE3) AS SCORE3,

MAX(SCORE4) AS SCORE4,

MAX(SCORE5) AS SCORE5,

0 AS SCORE6,

0 AS SCORE7,

(MAX(SCORE1) + MAX(SCORE2) + MAX(SCORE3) + MAX(SCORE4) + MAX(SCORE5)) ASSCORE_ALL,

MAX(ASSET_MAVG_SUM) AS ASSET_MAVG_SUM

FROM

(SELECTCUST_NO, CERT_ID AS ID_NUMBER, CUST_NAME AS NAME,

-90000 AS SCORE1, -90000 AS SCORE2, -90000 AS SCORE3, -90000 AS SCORE4, -90000AS SCORE5, NVL(ASSET_MAVG_SUM,0) AS ASSET_MAVG_SUM

FROM T_GET_WAIVER_ALL_CUST_BPH_INFO T0

UNION ALL

SELECTCUST_NO, ID_NUMBER, NAME, SCORE AS SCORE1, -90000 AS SCORE2, -90000 AS SCORE3,-90000 AS SCORE4, -90000 AS SCORE5, -90000 AS ASSET_MAVG_SUM

FROM T_DM_ABILITY_SCORET1

UNION ALL

SELECTCUST_NO, ID_NUMBER, NAME, -90000 AS SCORE1, SCORE AS SCORE2, -90000 AS SCORE3,-90000 AS SCORE4, -90000 AS SCORE5, -90000 AS ASSET_MAVG_SUM

FROM T_DM_ACTIVETY_SCORET2

UNION ALL

SELECTCUST_NO, ID_NUMBER, NAME, -90000 AS SCORE1, -90000 AS SCORE2, SCORE AS SCORE3,-90000 AS SCORE4, -90000 AS SCORE5, -90000 AS ASSET_MAVG_SUM

FROM T_DM_BEHAVIOR_SCORET3

UNION ALL

SELECTCUST_NO, ID_NUMBER, NAME, -90000 AS SCORE1, -90000 AS SCORE2, -90000 AS SCORE3,SCORE AS SCORE4, -90000 AS SCORE5, -90000 AS ASSET_MAVG_SUM

FROM T_DM_CREDIT_SCORET4

UNION ALL

SELECTCUST_NO, ID_NUMBER, NAME, -90000 AS SCORE1, -90000 AS SCORE2, -90000 AS SCORE3,-90000 AS SCORE4, SCORE AS SCORE5, -90000 AS ASSET_MAVG_SUM

FROM T_DM_IDENTITY_SCORET5

)TA

GROUPBY CUST_NO, ID_NUMBER, NAME;

“纵向关联”理解：第2步骤为UNION合并表，第3步GROUP BY去重，达到“关联”的目的。

注：不适用一对多的关系表关联

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