python如何解析复杂sql,实现数据库和表的提取的实例剖析

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

selectb.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) costfrom hive.bdc_dwd.dw_mk_order t1left 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_idleft 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_idwhere 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_amountfrom hive.bdc_dwd.dw_fn_deal_asyn_order awhere 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) costfrom hive.bdc_dwd.dw_mk_order t1where 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 = 12group 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’)aleft 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’ endorder by count(a.order_id) desclimit 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:

# coding=utf-8from __future__ import absolute_importfrom __future__ import divisionfrom __future__ import print_functionfrom __future__ import unicode_literalsimport sqlparsefrom sqlparse.sql import Identifier, IdentifierListfrom sqlparse.tokens import Keyword, NameRESULT_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(’ tn;’) 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 overbreak 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 = posbreak 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_resclass 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].valuec = identifier.tokens[4].valueif i == ’ ’: return full_treefull_tree = ’{}.{}.{}’.format(a, b, c)return full_tree return None, Noneif __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:

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_priceEND) 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 = 11AND t4.product2_type = 1AND 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’ )aLEFT JOIN mysql7.dataview_trade.ddc_product_info b ON a.product_id = b.product_idAND 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’ ENDORDER BY count(a.order_id) DESCLIMIT 10

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