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社区首页 >专栏 >python如何解析复杂sql,实现数据库和表的提取的实例剖析

python如何解析复杂sql,实现数据库和表的提取的实例剖析

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砸漏
发布2020-11-02 10:26:38
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发布2020-11-02 10:26:38
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文章被收录于专栏:恩蓝脚本

需求:

公司的数据分析师,提交一个sql, 一般都三四百行。由于数据安全的需要,不能开放所有的数据库和数据表给数据分析师查询,所以需要解析sql中的数据库和表,与权限管理系统中记录的数据库和表权限信息比对,实现非法查询的拦截。

解决办法:

在解决这个问题前,现在github找了一下轮子,发现python下面除了sql parse没什么好的解析数据库和表的轮轮。到是在java里面找到presto-parser解析的比较准。于是自己结合sql parse源码写了个类,供大家参考,测试了一下,检测还是准的。

测试sql

代码语言:javascript
复制
select
b.product_name "产品",
count(a.order_id) "订单量",
b.selling_price_max "销售价",
b.gross_profit_rate_max/100 "毛利率",
case when b.business_type =1 then '自营消化' when b.business_type =2 then '服务商消化' end "消化模式"
from(select 'CRM签单' label,date(d.update_ymd) close_ymd,c.product_name,c.product_id,
a.order_id,cast(a.recipient_amount as double) amt,d.cost
from mysql4.dataview_fenxiao.fx_order a
left join mysql4.dataview_fenxiao.fx_order_task b on a.order_id = b.order_id
left join mysql7.dataview_trade.ddc_product_info c on cast(c.product_id as varchar) = a.product_ids and c.snapshot_version = 'SELLING'
inner join (select t1.par_order_id,max(t1.update_ymd) update_ymd,
sum(case when t4.product2_type = 1 and t5.shop_id is not null then t5.price else t1.order_hosted_price end) cost
from hive.bdc_dwd.dw_mk_order t1
left join hive.bdc_dwd.dw_mk_order_status t2 on t1.order_id = t2.order_id and t2.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
left join mysql7.dataview_trade.mk_order_merchant t3 on t1.order_id = t3.order_id
left join mysql7.dataview_trade.ddc_product_info t4 on t4.product_id = t3.MERCHANT_ID and t4.snapshot_version = 'SELLING'
left join mysql4.dataview_scrm.sc_tprc_product_info t5 on t5.product_id = t4.product_id and t5.shop_id = t1.seller_id
where t1.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
and t2.valid_state in (100,200) ------有效订单
and t1.order_mode = 10  --------产品消耗订单
and t2.complete_state = 1 -----订单已经完成
group by t1.par_order_id
) d on d.par_order_id = b.task_order_id
where c.product_type = 0 and date(from_unixtime(a.last_recipient_time))   date('2016-01-01') and a.payee_type <  1 -----------已收款
UNION ALL
select '企业管家消耗' label,date(c.update_ymd) close_ymd,b.product_name,b.product_id,
a.task_id,(case when a.yb_price = 0 and b.product2_type = 1 then b.selling_price_min else a.yb_price end) amt,
(case when a.yb_price = 0 and b.product2_type = 2 then 0 when b.product2_type = 1 and e.shop_id is not null then e.price else c.order_hosted_price end) cost
from mysql8.dataview_tprc.tprc_task a
left join mysql7.dataview_trade.ddc_product_info b on a.product_id = b.product_id and b.snapshot_version = 'SELLING'
inner join hive.bdc_dwd.dw_mk_order c on a.order_id = c.order_id and c.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
left join hive.bdc_dwd.dw_mk_order_status d on d.order_id = c.order_id and d.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
left join mysql4.dataview_scrm.sc_tprc_product_info e on e.product_id = b.product_id and e.shop_id = c.seller_id
where d.valid_state in (100,200) and d.complete_state = 1 and c.order_mode = 10
union ALL
select '交易管理系统' label,date(t6.close_ymd) close_ymd,t4.product_name,t4.product_id,
t1.order_id,(t1.order_hosted_price-t1.order_refund_price) amt,
(case when t1.order_mode <  11 then t7.user_amount when t1.order_mode = 11 and t4.product2_type = 1 and t5.shop_id is not null then t5.price else t8.cost end) cost
from hive.bdc_dwd.dw_mk_order t1
left join hive.bdc_dwd.dw_mk_order_business t2 on t1.order_id = t2.order_id and t2.acct_day=substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
left join mysql7.dataview_trade.mk_order_merchant t3 on t1.order_id = t3.order_id
left join mysql7.dataview_trade.ddc_product_info t4 on t4.product_id = t3.MERCHANT_ID and t4.snapshot_version = 'SELLING'
left join mysql4.dataview_scrm.sc_tprc_product_info t5 on t5.product_id = t4.product_id and t5.shop_id = t1.seller_id
left join hive.bdc_dwd.dw_fact_task_ss_daily t6 on t6.task_id = t2.task_id and t6.acct_time=date_format(date_add('day',-1,current_date),'%Y-%m-%d')
left join (select a.task_id,sum(a.user_amount) user_amount
from hive.bdc_dwd.dw_fn_deal_asyn_order a
where a.is_new=1 and a.service='Trade_Payment' and a.state=1 and a.acct_day=substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
group by a.task_id)t7 on t7.task_id = t2.task_id     
left join (select t1.par_order_id,sum(t1.order_hosted_price - t1.order_refund_price) cost
from hive.bdc_dwd.dw_mk_order t1
where t1.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2) and t1.order_type = 1 and t1.order_stype = 4 and t1.order_mode = 12
group by t1.par_order_id) t8 on t1.order_id = t8.par_order_id
where t1.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
and t1.order_type = 1 and t1.order_stype in (4,5) and t1.order_mode <  12 and t4.product_id is not null and t1.order_hosted_price   0 and t6.is_deal = 1 and t6.close_ymd  = '2018-12-31'
)a
left join mysql7.dataview_trade.ddc_product_info b on a.product_id = b.product_id and b.snapshot_version = 'SELLING'
where b.product2_type = 1 -------标品
and close_ymd between DATE_ADD('day',-7,CURRENT_DATE) and DATE_ADD('day',-1,CURRENT_DATE)
GROUP BY b.product_name,
b.selling_price_max,
b.gross_profit_rate_max/100,
b.actrul_supply_num,
case when b.business_type =1 then '自营消化' when b.business_type =2 then '服务商消化' end
order by count(a.order_id) desc
limit 10

可以看到该sql比较杂,也没有格式化,不太好提取数据库和表。所以第一步需要对sql进行格式化

直接上代码:

代码语言:javascript
复制
# coding=utf-8
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import sqlparse
from sqlparse.sql import Identifier, IdentifierList
from sqlparse.tokens import Keyword, Name
RESULT_OPERATIONS = {'UNION', 'INTERSECT', 'EXCEPT', 'SELECT'}
ON_KEYWORD = 'ON'
PRECEDES_TABLE_NAME = {'FROM', 'JOIN', 'DESC', 'DESCRIBE', 'WITH'}
class BaseExtractor(object):
def __init__(self, sql_statement):
self.sql = sqlparse.format(sql_statement, reindent=True, keyword_case='upper')
self._table_names = set()
self._alias_names = set()
self._limit = None
self._parsed = sqlparse.parse(self.stripped())
for statement in self._parsed:
self.__extract_from_token(statement)
self._limit = self._extract_limit_from_query(statement)
self._table_names = self._table_names - self._alias_names
@property
def tables(self):
return self._table_names
@property
def limit(self):
return self._limit
def is_select(self):
return self._parsed[0].get_type() == 'SELECT'
def is_explain(self):
return self.stripped().upper().startswith('EXPLAIN')
def is_readonly(self):
return self.is_select() or self.is_explain()
def stripped(self):
return self.sql.strip(' \t\n;')
def get_statements(self):
statements = []
for statement in self._parsed:
if statement:
sql = str(statement).strip(' \n;\t')
if sql:
statements.append(sql)
return statements
@staticmethod
def __precedes_table_name(token_value):
for keyword in PRECEDES_TABLE_NAME:
if keyword in token_value:
return True
return False
@staticmethod
def get_full_name(identifier):
if len(identifier.tokens)   1 and identifier.tokens[1].value == '.':
return '{}.{}'.format(identifier.tokens[0].value,
identifier.tokens[2].value)
return identifier.get_real_name()
@staticmethod
def __is_result_operation(keyword):
for operation in RESULT_OPERATIONS:
if operation in keyword.upper():
return True
return False
@staticmethod
def __is_identifier(token):
return isinstance(token, (IdentifierList, Identifier))
def __process_identifier(self, identifier):
if '(' not in '{}'.format(identifier):
self._table_names.add(self.get_full_name(identifier))
return
# store aliases
if hasattr(identifier, 'get_alias'):
self._alias_names.add(identifier.get_alias())
if hasattr(identifier, 'tokens'):
# some aliases are not parsed properly
if identifier.tokens[0].ttype == Name:
self._alias_names.add(identifier.tokens[0].value)
self.__extract_from_token(identifier)
def as_create_table(self, table_name, overwrite=False):
exec_sql = ''
sql = self.stripped()
if overwrite:
exec_sql = 'DROP TABLE IF EXISTS {};\n'.format(table_name)
exec_sql += 'CREATE TABLE {} AS \n{}'.format(table_name, sql)
return exec_sql
def __extract_from_token(self, token):
if not hasattr(token, 'tokens'):
return
table_name_preceding_token = False
for item in token.tokens:
if item.is_group and not self.__is_identifier(item):
self.__extract_from_token(item)
if item.ttype in Keyword:
if self.__precedes_table_name(item.value.upper()):
table_name_preceding_token = True
continue
if not table_name_preceding_token:
continue
if item.ttype in Keyword or item.value == ',':
if (self.__is_result_operation(item.value) or
item.value.upper() == ON_KEYWORD):
table_name_preceding_token = False
continue
# FROM clause is over
break
if isinstance(item, Identifier):
self.__process_identifier(item)
if isinstance(item, IdentifierList):
for token in item.tokens:
if self.__is_identifier(token):
self.__process_identifier(token)
def _get_limit_from_token(self, token):
if token.ttype == sqlparse.tokens.Literal.Number.Integer:
return int(token.value)
elif token.is_group:
return int(token.get_token_at_offset(1).value)
def _extract_limit_from_query(self, statement):
limit_token = None
for pos, item in enumerate(statement.tokens):
if item.ttype in Keyword and item.value.lower() == 'limit':
limit_token = statement.tokens[pos + 2]
return self._get_limit_from_token(limit_token)
def get_query_with_new_limit(self, new_limit):
if not self._limit:
return self.sql + ' LIMIT ' + str(new_limit)
limit_pos = None
tokens = self._parsed[0].tokens
# Add all items to before_str until there is a limit
for pos, item in enumerate(tokens):
if item.ttype in Keyword and item.value.lower() == 'limit':
limit_pos = pos
break
limit = tokens[limit_pos + 2]
if limit.ttype == sqlparse.tokens.Literal.Number.Integer:
tokens[limit_pos + 2].value = new_limit
elif limit.is_group:
tokens[limit_pos + 2].value = (
'{}, {}'.format(next(limit.get_identifiers()), new_limit)
)
str_res = ''
for i in tokens:
str_res += str(i.value)
return str_res
class SqlExtractor(BaseExtractor):
"""提取sql语句"""
@staticmethod
def get_full_name(identifier, including_dbs=False):
if len(identifier.tokens)   1 and identifier.tokens[1].value == '.':
a = identifier.tokens[0].value
b = identifier.tokens[2].value
db_table = (a, b)
full_tree = '{}.{}'.format(a, b)
if len(identifier.tokens) == 3:
return full_tree
else:
i = identifier.tokens[3].value
c = identifier.tokens[4].value
if i == ' ':
return full_tree
full_tree = '{}.{}.{}'.format(a, b, c)
return full_tree
return None, None
if __name__ == '__main__':
sql = """select
b.product_name "产品",
count(a.order_id) "订单量",
b.selling_price_max "销售价",
b.gross_profit_rate_max/100 "毛利率",
case when b.business_type =1 then '自营消化' when b.business_type =2 then '服务商消化' end "消化模式"
from(select 'CRM签单' label,date(d.update_ymd) close_ymd,c.product_name,c.product_id,
a.order_id,cast(a.recipient_amount as double) amt,d.cost
from mysql4.dataview_fenxiao.fx_order a
left join mysql4.dataview_fenxiao.fx_order_task b on a.order_id = b.order_id
left join mysql7.dataview_trade.ddc_product_info c on cast(c.product_id as varchar) = a.product_ids and c.snapshot_version = 'SELLING'
inner join (select t1.par_order_id,max(t1.update_ymd) update_ymd,
sum(case when t4.product2_type = 1 and t5.shop_id is not null then t5.price else t1.order_hosted_price end) cost
from hive.bdc_dwd.dw_mk_order t1
left join hive.bdc_dwd.dw_mk_order_status t2 on t1.order_id = t2.order_id and t2.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
left join mysql7.dataview_trade.mk_order_merchant t3 on t1.order_id = t3.order_id
left join mysql7.dataview_trade.ddc_product_info t4 on t4.product_id = t3.MERCHANT_ID and t4.snapshot_version = 'SELLING'
left join mysql4.dataview_scrm.sc_tprc_product_info t5 on t5.product_id = t4.product_id and t5.shop_id = t1.seller_id
where t1.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
and t2.valid_state in (100,200) ------有效订单
and t1.order_mode = 10  --------产品消耗订单
and t2.complete_state = 1 -----订单已经完成
group by t1.par_order_id
) d on d.par_order_id = b.task_order_id
where c.product_type = 0 and date(from_unixtime(a.last_recipient_time))   date('2016-01-01') and a.payee_type <  1 -----------已收款
UNION ALL
select '企业管家消耗' label,date(c.update_ymd) close_ymd,b.product_name,b.product_id,
a.task_id,(case when a.yb_price = 0 and b.product2_type = 1 then b.selling_price_min else a.yb_price end) amt,
(case when a.yb_price = 0 and b.product2_type = 2 then 0 when b.product2_type = 1 and e.shop_id is not null then e.price else c.order_hosted_price end) cost
from mysql8.dataview_tprc.tprc_task a
left join mysql7.dataview_trade.ddc_product_info b on a.product_id = b.product_id and b.snapshot_version = 'SELLING'
inner join hive.bdc_dwd.dw_mk_order c on a.order_id = c.order_id and c.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
left join hive.bdc_dwd.dw_mk_order_status d on d.order_id = c.order_id and d.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
left join mysql4.dataview_scrm.sc_tprc_product_info e on e.product_id = b.product_id and e.shop_id = c.seller_id
where d.valid_state in (100,200) and d.complete_state = 1 and c.order_mode = 10
union ALL
select '交易管理系统' label,date(t6.close_ymd) close_ymd,t4.product_name,t4.product_id,
t1.order_id,(t1.order_hosted_price-t1.order_refund_price) amt,
(case when t1.order_mode <  11 then t7.user_amount when t1.order_mode = 11 and t4.product2_type = 1 and t5.shop_id is not null then t5.price else t8.cost end) cost
from hive.bdc_dwd.dw_mk_order t1
left join hive.bdc_dwd.dw_mk_order_business t2 on t1.order_id = t2.order_id and t2.acct_day=substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
left join mysql7.dataview_trade.mk_order_merchant t3 on t1.order_id = t3.order_id
left join mysql7.dataview_trade.ddc_product_info t4 on t4.product_id = t3.MERCHANT_ID and t4.snapshot_version = 'SELLING'
left join mysql4.dataview_scrm.sc_tprc_product_info t5 on t5.product_id = t4.product_id and t5.shop_id = t1.seller_id
left join hive.bdc_dwd.dw_fact_task_ss_daily t6 on t6.task_id = t2.task_id and t6.acct_time=date_format(date_add('day',-1,current_date),'%Y-%m-%d')
left join (select a.task_id,sum(a.user_amount) user_amount
from hive.bdc_dwd.dw_fn_deal_asyn_order a
where a.is_new=1 and a.service='Trade_Payment' and a.state=1 and a.acct_day=substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
group by a.task_id)t7 on t7.task_id = t2.task_id     
left join (select t1.par_order_id,sum(t1.order_hosted_price - t1.order_refund_price) cost
from hive.bdc_dwd.dw_mk_order t1
where t1.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2) and t1.order_type = 1 and t1.order_stype = 4 and t1.order_mode = 12
group by t1.par_order_id) t8 on t1.order_id = t8.par_order_id
where t1.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) as varchar),9,2)
and t1.order_type = 1 and t1.order_stype in (4,5) and t1.order_mode <  12 and t4.product_id is not null and t1.order_hosted_price   0 and t6.is_deal = 1 and t6.close_ymd  = '2018-12-31'
)a
left join mysql7.dataview_trade.ddc_product_info b on a.product_id = b.product_id and b.snapshot_version = 'SELLING'
where b.product2_type = 1 -------标品
and close_ymd between DATE_ADD('day',-7,CURRENT_DATE) and DATE_ADD('day',-1,CURRENT_DATE)
GROUP BY b.product_name,
b.selling_price_max,
b.gross_profit_rate_max/100,
b.actrul_supply_num,
case when b.business_type =1 then '自营消化' when b.business_type =2 then '服务商消化' end
order by count(a.order_id) desc
limit 10"""
sql_extractor = SqlExtractor(sql)
print(sql_extractor.sql)
print(sql_extractor.tables)

输出结果:

{‘mysql8.dataview_tprc.tprc_task’, ‘hive.bdc_dwd.dw_mk_order’, ‘mysql4.dataview_fenxiao.fx_order_task’, ‘mysql4.dataview_fenxiao.fx_order’, ‘hive.bdc_dwd.dw_mk_order_business’, ‘mysql7.dataview_trade.mk_order_merchant’, ‘mysql4.dataview_scrm.sc_tprc_product_info’, ‘hive.bdc_dwd.dw_fn_deal_asyn_order’, ‘hive.bdc_dwd.dw_fact_task_ss_daily’, ‘mysql7.dataview_trade.ddc_product_info’, ‘hive.bdc_dwd.dw_mk_order_status’}

格式化结果:

代码语言:javascript
复制
SELECT b.product_name "产品",
count(a.order_id) "订单量",
b.selling_price_max "销售价",
b.gross_profit_rate_max/100 "毛利率",
CASE
WHEN b.business_type =1 THEN '自营消化'
WHEN b.business_type =2 THEN '服务商消化'
END "消化模式" from
(SELECT 'CRM签单' label,date(d.update_ymd) close_ymd,c.product_name,c.product_id, a.order_id,cast(a.recipient_amount AS DOUBLE) amt,d.cost
FROM mysql4.dataview_fenxiao.fx_order a
LEFT JOIN mysql4.dataview_fenxiao.fx_order_task b ON a.order_id = b.order_id
LEFT JOIN mysql7.dataview_trade.ddc_product_info c ON cast(c.product_id AS varchar) = a.product_ids
AND c.snapshot_version = 'SELLING'
INNER JOIN
(SELECT t1.par_order_id,max(t1.update_ymd) update_ymd, sum(CASE
WHEN t4.product2_type = 1
AND t5.shop_id IS NOT NULL THEN t5.price
ELSE t1.order_hosted_price
END) cost
FROM hive.bdc_dwd.dw_mk_order t1
LEFT JOIN hive.bdc_dwd.dw_mk_order_status t2 ON t1.order_id = t2.order_id
AND t2.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) AS varchar),9,2)
LEFT JOIN mysql7.dataview_trade.mk_order_merchant t3 ON t1.order_id = t3.order_id
LEFT JOIN mysql7.dataview_trade.ddc_product_info t4 ON t4.product_id = t3.MERCHANT_ID
AND t4.snapshot_version = 'SELLING'
LEFT JOIN mysql4.dataview_scrm.sc_tprc_product_info t5 ON t5.product_id = t4.product_id
AND t5.shop_id = t1.seller_id
WHERE t1.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) AS varchar),9,2)
AND t2.valid_state IN (100,200)------有效订单
AND t1.order_mode = 10 --------产品消耗订单
AND t2.complete_state = 1 -----订单已经完成
GROUP BY t1.par_order_id ) d ON d.par_order_id = b.task_order_id
WHERE c.product_type = 0
AND date(from_unixtime(a.last_recipient_time))   date('2016-01-01')
AND a.payee_type <  1 -----------已收款
UNION ALL SELECT '企业管家消耗' label,date(c.update_ymd) close_ymd,b.product_name,b.product_id, a.task_id,(CASE
WHEN a.yb_price = 0
AND b.product2_type = 1 THEN b.selling_price_min
ELSE a.yb_price
END) amt, (CASE
WHEN a.yb_price = 0
AND b.product2_type = 2 THEN 0
WHEN b.product2_type = 1
AND e.shop_id IS NOT NULL THEN e.price
ELSE c.order_hosted_price
END) cost
FROM mysql8.dataview_tprc.tprc_task a
LEFT JOIN mysql7.dataview_trade.ddc_product_info b ON a.product_id = b.product_id
AND b.snapshot_version = 'SELLING'
INNER JOIN hive.bdc_dwd.dw_mk_order c ON a.order_id = c.order_id
AND c.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) AS varchar),9,2)
LEFT JOIN hive.bdc_dwd.dw_mk_order_status d ON d.order_id = c.order_id
AND d.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) AS varchar),9,2)
LEFT JOIN mysql4.dataview_scrm.sc_tprc_product_info e ON e.product_id = b.product_id
AND e.shop_id = c.seller_id
WHERE d.valid_state IN (100,200)
AND d.complete_state = 1
AND c.order_mode = 10
UNION ALL SELECT '交易管理系统' label,date(t6.close_ymd) close_ymd,t4.product_name,t4.product_id, t1.order_id,(t1.order_hosted_price-t1.order_refund_price) amt, (CASE
WHEN t1.order_mode <  11 THEN t7.user_amount
WHEN t1.order_mode = 11
AND t4.product2_type = 1
AND t5.shop_id IS NOT NULL THEN t5.price
ELSE t8.cost
END) cost
FROM hive.bdc_dwd.dw_mk_order t1
LEFT JOIN hive.bdc_dwd.dw_mk_order_business t2 ON t1.order_id = t2.order_id
AND t2.acct_day=substring(cast(DATE_ADD('day',-1,CURRENT_DATE) AS varchar),9,2)
LEFT JOIN mysql7.dataview_trade.mk_order_merchant t3 ON t1.order_id = t3.order_id
LEFT JOIN mysql7.dataview_trade.ddc_product_info t4 ON t4.product_id = t3.MERCHANT_ID
AND t4.snapshot_version = 'SELLING'
LEFT JOIN mysql4.dataview_scrm.sc_tprc_product_info t5 ON t5.product_id = t4.product_id
AND t5.shop_id = t1.seller_id
LEFT JOIN hive.bdc_dwd.dw_fact_task_ss_daily t6 ON t6.task_id = t2.task_id
AND t6.acct_time=date_format(date_add('day',-1,CURRENT_DATE),'%Y-%m-%d')
LEFT JOIN
(SELECT a.task_id,sum(a.user_amount) user_amount
FROM hive.bdc_dwd.dw_fn_deal_asyn_order a
WHERE a.is_new=1
AND a.service='Trade_Payment'
AND a.state=1
AND a.acct_day=substring(cast(DATE_ADD('day',-1,CURRENT_DATE) AS varchar),9,2)
GROUP BY a.task_id)t7 ON t7.task_id = t2.task_id
LEFT JOIN
(SELECT t1.par_order_id,sum(t1.order_hosted_price - t1.order_refund_price) cost
FROM hive.bdc_dwd.dw_mk_order t1
WHERE t1.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) AS varchar),9,2)
AND t1.order_type = 1
AND t1.order_stype = 4
AND t1.order_mode = 12
GROUP BY t1.par_order_id) t8 ON t1.order_id = t8.par_order_id
WHERE t1.acct_day = substring(cast(DATE_ADD('day',-1,CURRENT_DATE) AS varchar),9,2)
AND t1.order_type = 1
AND t1.order_stype IN (4,5)
AND t1.order_mode <  12
AND t4.product_id IS NOT NULL
AND t1.order_hosted_price   0
AND t6.is_deal = 1
AND t6.close_ymd  = '2018-12-31' )a
LEFT JOIN mysql7.dataview_trade.ddc_product_info b ON a.product_id = b.product_id
AND b.snapshot_version = 'SELLING'
WHERE b.product2_type = 1 -------标品
AND close_ymd BETWEEN DATE_ADD('day',-7,CURRENT_DATE) AND DATE_ADD('day',-1,CURRENT_DATE)
GROUP BY b.product_name,
b.selling_price_max,
b.gross_profit_rate_max/100,
b.actrul_supply_num,
CASE
WHEN b.business_type =1 THEN '自营消化'
WHEN b.business_type =2 THEN '服务商消化'
END
ORDER BY count(a.order_id) DESC
LIMIT 10

以上这篇python如何解析复杂sql,实现数据库和表的提取的实例剖析就是小编分享给大家的全部内容了,希望能给大家一个参考。

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