1.优化分布分析元素去重数,列表去重数,集合去重数没有数据的问题
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@ -1015,9 +1015,9 @@ async def scatter_model(
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if df.empty:
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if df.empty:
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return schemas.Msg(code=-9, msg='无数据', data=None)
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return schemas.Msg(code=-9, msg='无数据', data=None)
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if 'list' in str(type(df['values'][0])):
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if 'list' in str(type(df['values'][0])):
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f=lambda x:x[0]
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# f=lambda x:x[0]
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df['values']=df['values'].map(f)
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# df['values']=df['values'].map(f)
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df = df.explode("values").reset_index(drop=True)
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#df['values']=df['values'].astype(str)
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#df['values']=df['values'].astype(str)
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df.fillna(0, inplace=True)
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df.fillna(0, inplace=True)
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#转换数据类型为int
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#转换数据类型为int
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@ -1190,8 +1190,9 @@ async def scatter_model(
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if df.empty:
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if df.empty:
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return schemas.Msg(code=-9, msg='无数据', data=None)
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return schemas.Msg(code=-9, msg='无数据', data=None)
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if 'list' in str(type(df['values'][0])):
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if 'list' in str(type(df['values'][0])):
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f = lambda x: x[0]
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# f = lambda x: x[0]
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df['values'] = df['values'].map(f)
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# df['values'] = df['values'].map(f)
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df = df.explode("values").reset_index(drop=True)
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df.fillna(0, inplace=True)
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df.fillna(0, inplace=True)
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# 转换数据类型为int
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# 转换数据类型为int
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df['values'] = df['values'].astype(int)
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df['values'] = df['values'].astype(int)
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@ -295,6 +295,16 @@ class Settings(BaseSettings):
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'id': 'not in',
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'id': 'not in',
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'title': '不是'
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'title': '不是'
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},
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},
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],
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'array': [
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{
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'id': 'is not null',
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'title': '有值'
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},
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{
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'id': 'is null',
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'title': '无值'
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}
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]
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]
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}
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}
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ARITHMETIC = {
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ARITHMETIC = {
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@ -302,6 +312,7 @@ class Settings(BaseSettings):
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'-': lambda x, y: x - y,
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'-': lambda x, y: x - y,
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'*': lambda x, y: x * y,
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'*': lambda x, y: x * y,
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'/': lambda x, y: x / y,
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'/': lambda x, y: x / y,
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#'%': lambda x, y:(x)-int(x/y)*(y) 取模用
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}
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}
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PROPHET_TIME_GRAIN_MAP = {
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PROPHET_TIME_GRAIN_MAP = {
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@ -389,7 +400,7 @@ class Settings(BaseSettings):
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class Debug(Settings):
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class Debug(Settings):
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MDB_HOST: str = '10.0.0.7'
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MDB_HOST: str = '10.0.0.9'
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MDB_PORT: int = 27017
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MDB_PORT: int = 27017
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MDB_USER: str = 'root'
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MDB_USER: str = 'root'
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MDB_PASSWORD: str = 'iamciniao'
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MDB_PASSWORD: str = 'iamciniao'
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@ -611,7 +611,7 @@ ORDER BY level
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event = self.events[0]
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event = self.events[0]
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event_name = event['eventName']
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event_name = event['eventName']
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analysis = event['analysis']
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analysis = event['analysis']
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if analysis == 'list_distinct':
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if analysis in ['list_distinct',"set_distinct","ele_distinct"]:
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analysis = 'max'
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analysis = 'max'
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e_account_id_col = getattr(self.event_tbl.c, '#account_id').label('uid')
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e_account_id_col = getattr(self.event_tbl.c, '#account_id').label('uid')
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u_account_id_col = getattr(self.user_tbl.c, '#account_id')
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u_account_id_col = getattr(self.user_tbl.c, '#account_id')
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