如何使用Python读取Hive数据库?
实际业务读取hive数据库的代码
import logging import pandas as pd from impala.dbapi import connect import sqlalchemy from sqlalchemy.orm import sessionmaker import os import time import os import datetime from dateutil.relativedelta import relativedelta from typing import Dict, List import logging import threading import pandas as pd import pickle class HiveHelper(object): def __init__( self, host='10.2.32.22', port=21051, database='ur_ai_dw', auth_mechanism='LDAP', user='urbi', password='Ur#730xd', logger:logging.Logger=None ): self.host = host self.port = port self.database = database self.auth_mechanism = auth_mechanism self.user = user self.password = password self.logger = logger self.impala_conn = None self.conn = None self.cursor = None self.engine = None self.session = None def create_table_code(self, file_name): '''创建表类代码''' os.system(f'sqlacodegen {self.connection_str} > {file_name}') return self.conn def get_conn(self): '''创建连接或获取连接''' if self.conn is None: engine = self.get_engine() self.conn = engine.connect() return self.conn def get_impala_conn(self): '''创建连接或获取连接''' if self.impala_conn is None: self.impala_conn = connect( host=self.host, port=self.port, database=self.database, auth_mechanism=self.auth_mechanism, user=self.user, password=self.password ) return self.impala_conn def get_engine(self): '''创建连接或获取连接''' if self.engine is None: self.engine = sqlalchemy.create_engine('impala://', creator=self.get_impala_conn) return self.engine def get_cursor(self): '''创建连接或获取连接''' if self.cursor is None: self.cursor = self.conn.cursor() return self.cursor def get_session(self) -> sessionmaker: '''创建连接或获取连接''' if self.session is None: engine = self.get_engine() Session = sessionmaker(bind=engine) self.session = Session() return self.session def close_conn(self): '''关闭连接''' if self.conn is not None: self.conn.close() self.conn = None self.dispose_engine() self.close_impala_conn() def close_impala_conn(self): '''关闭impala连接''' if self.impala_conn is not None: self.impala_conn.close() self.impala_conn = None def close_session(self): '''关闭连接''' if self.session is not None: self.session.close() self.session = None self.dispose_engine() def dispose_engine(self): '''释放engine''' if self.engine is not None: # self.engine.dispose(close=False) self.engine.dispose() self.engine = None def close_cursor(self): '''关闭cursor''' if self.cursor is not None: self.cursor.close() self.cursor = None def get_data(self, sql, auto_close=True) -> pd.DataFrame: '''查询数据''' conn = self.get_conn() data = None try: # 异常重试3次 for i in range(3): try: data = pd.read_sql(sql, conn) break except Exception as ex: if i == 2: raise ex # 往外抛出异常 time.sleep(60) # 一分钟后重试 except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: if auto_close: self.close_conn() return data pass class VarsHelper(): def __init__(self, save_dir, auto_save=True): self.save_dir = save_dir self.auto_save = auto_save self.values = {} if not os.path.exists(os.path.dirname(self.save_dir)): os.makedirs(os.path.dirname(self.save_dir)) if os.path.exists(self.save_dir): with open(self.save_dir, 'rb') as f: self.values = pickle.load(f) f.close() def set_value(self, key, value): self.values[key] = value if self.auto_save: self.save_file() def get_value(self, key): return self.values[key] def has_key(self, key): return key in self.values.keys() def save_file(self): with open(self.save_dir, 'wb') as f: pickle.dump(self.values, f) f.close() pass class GlobalShareArgs(): args = { "debug": False } def get_args(): return GlobalShareArgs.args def set_args(args): GlobalShareArgs.args = args def set_args_value(key, value): GlobalShareArgs.args[key] = value def get_args_value(key, default_value=None): return GlobalShareArgs.args.get(key, default_value) def contain_key(key): return key in GlobalShareArgs.args.keys() def update(args): GlobalShareArgs.args.update(args) pass class ShareArgs(): args = { "labels_dir":"./hjx/shop_group/month_w_amt/data/labels", # 标签目录 "labels_output_dir":"./hjx/shop_group/month_w_amt/data/labels_output", # 聚类导出标签目录 "common_datas_dir":"./hjx/data", # 共用数据目录。ur_bi_dw的公共 "only_predict": False, # 只识别,不训练 "delete_model": True, # 先删除模型,仅在训练时使用 "export_excel": False, # 导出excel "classes": 12, # 聚类数 "batch_size": 16, "hidden_size": 32, "max_nrof_epochs": 100, "learning_rate": 0.0005, "loss_type": "categorical_crossentropy", "avg_model_num": 10, "steps_per_epoch": 4.0, # 4.0 "lr_callback_patience": 4, "lr_callback_cooldown": 1, "early_stopping_callback_patience": 6, "get_data": True, } def get_args(): return ShareArgs.args def set_args(args): ShareArgs.args = args def set_args_value(key, value): ShareArgs.args[key] = value def get_args_value(key, default_value=None): return ShareArgs.args.get(key, default_value) def contain_key(key): return key in ShareArgs.args.keys() def update(args): ShareArgs.args.update(args) pass class UrBiGetDatasBase(): # 线程锁列表,同保存路径共用锁 lock_dict:Dict[str, threading.Lock] = {} # 时间列表,用于判断是否超时 time_dict:Dict[str, datetime.datetime] = {} # 用于记录是否需要更新超时时间 get_data_timeout_dict:Dict[str, bool] = {} def __init__( self, host='10.2.32.22', port=21051, database='ur_ai_dw', auth_mechanism='LDAP', user='urbi', password='Ur#730xd', save_dir=None, logger:logging.Logger=None, ): self.save_dir = save_dir self.logger = logger self.db_helper = HiveHelper( host=host, port=port, database=database, auth_mechanism=auth_mechanism, user=user, password=password, logger=logger ) # 创建子目录 if self.save_dir is not None and not os.path.exists(self.save_dir): os.makedirs(self.save_dir) self.vars_helper = None if GlobalShareArgs.get_args_value('debug'): self.vars_helper = VarsHelper('./hjx/data/vars/UrBiGetDatas') def close(self): '''关闭连接''' self.db_helper.close_conn() def get_last_time(self, key_name) -> bool: '''获取是否超时''' # 转静态路径,确保唯一性 key_name = os.path.abspath(key_name) if self.vars_helper is not None and self.vars_helper.has_key('UrBiGetDatasBase.time_list'): UrBiGetDatasBase.time_dict = self.vars_helper.get_value('UrBiGetDatasBase.time_list') timeout = 12 # 12小时 if GlobalShareArgs.get_args_value('debug'): timeout = 24 # 24小时 get_data_timeout = False if key_name not in UrBiGetDatasBase.time_dict.keys() or (datetime.datetime.today() - UrBiGetDatasBase.time_dict[key_name]).total_seconds()>(timeout*60*60): self.logger.info('超时%d小时,重新查数据:%s', timeout, key_name) # UrBiGetDatasBase.time_list[key_name] = datetime.datetime.today() get_data_timeout = True else: self.logger.info('未超时%d小时,跳过查数据:%s', timeout, key_name) # if self.vars_helper is not None : # self.vars_helper.set_value('UrBiGetDatasBase.time_list', UrBiGetDatasBase.time_list) UrBiGetDatasBase.get_data_timeout_dict[key_name] = get_data_timeout return get_data_timeout def save_last_time(self, key_name): '''更新状态超时''' # 转静态路径,确保唯一性 key_name = os.path.abspath(key_name) if UrBiGetDatasBase.get_data_timeout_dict[key_name]: UrBiGetDatasBase.time_dict[key_name] = datetime.datetime.today() if self.vars_helper is not None : UrBiGetDatasBase.time_dict[key_name] = datetime.datetime.today() self.vars_helper.set_value('UrBiGetDatasBase.time_list', UrBiGetDatasBase.time_dict) def get_lock(self, key_name) -> threading.Lock: '''获取锁''' # 转静态路径,确保唯一性 key_name = os.path.abspath(key_name) if key_name not in UrBiGetDatasBase.lock_dict.keys(): UrBiGetDatasBase.lock_dict[key_name] = threading.Lock() return UrBiGetDatasBase.lock_dict[key_name] def get_data_of_date( self, save_dir, sql, sort_columns:List[str], del_index_list=[-1], # 删除最后下标 start_date = datetime.datetime(2017, 1, 1), # 开始时间 offset = relativedelta(months=3), # 时间间隔 date_format_fun = lambda d: '%04d%02d01' % (d.year, d.month), # 查询语句中替代时间参数的格式化 filename_format_fun = lambda d: '%04d%02d.csv' % (d.year, d.month), # 查询语句中替代时间参数的格式化 stop_date = '20700101', # 超过时间则停止 data_format_fun = None, # 格式化数据 ): '''分时间增量读取数据''' # 创建文件夹 if not os.path.exists(save_dir): os.makedirs(save_dir) else: #删除最后一个文件 file_list = os.listdir(save_dir) if len(file_list)>0: file_list.sort() for del_index in del_index_list: os.remove(os.path.join(save_dir,file_list[del_index])) print('删除最后一个文件:', file_list[del_index]) select_index = -1 # start_date = datetime.datetime(2017, 1, 1) while True: end_date = start_date + offset start_date_str = date_format_fun(start_date) end_date_str = date_format_fun(end_date) self.logger.info('date: %s-%s', start_date_str, end_date_str) file_path = os.path.join(save_dir, filename_format_fun(start_date)) # self.logger.info('file_path: %s', file_path) if not os.path.exists(file_path): data:pd.DataFrame = self.db_helper.get_data(sql % (start_date_str, end_date_str)) if data is None: break self.logger.info('data: %d', len(data)) # self.logger.info('data: %d', data.columns) if len(data)>0: select_index+=1 if data_format_fun is not None: data = data_format_fun(data) # 排序 data = data.sort_values(sort_columns) data.to_csv(file_path) elif select_index!=-1: break elif stop_date < start_date_str: raise Exception("读取数据异常,时间超出最大值!") start_date = end_date pass class UrBiGetDatas(UrBiGetDatasBase): def __init__( self, host='10.2.32.22', port=21051, database='ur_ai_dw', auth_mechanism='LDAP', user='urbi', password='Ur#730xd', save_dir='./hjx/data/ur_bi_dw_data', logger:logging.Logger=None ): self.save_dir = save_dir self.logger = logger super().__init__( host=host, port=port, database=database, auth_mechanism=auth_mechanism, user=user, password=password, save_dir=save_dir, logger=logger ) def get_dim_date(self): '''日期数据''' file_path = os.path.join(self.save_dir,'ur_bi_dw.dim_date.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return sql = 'SELECT * FROM ur_bi_dw.dim_date' data:pd.DataFrame = self.db_helper.get_data(sql) columns = list(data.columns) columns = {c:'dim_date.'+c for c in columns} data = data.rename(columns=columns) data = data.sort_values(['dim_date.date_key']) data.to_csv(file_path) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_dim_shop(self): '''店铺数据''' file_path = os.path.join(self.save_dir,'ur_bi_dw.dim_shop.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return sql = 'SELECT * FROM ur_bi_dw.dim_shop' data:pd.DataFrame = self.db_helper.get_data(sql) columns = list(data.columns) columns = {c:'dim_shop.'+c for c in columns} data = data.rename(columns=columns) data = data.sort_values(['dim_shop.shop_no']) data.to_csv(file_path) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_dim_vip(self): '''会员数据''' sub_dir = os.path.join(self.save_dir,'vip_no') now_lock = self.get_lock(sub_dir) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(sub_dir): return sql = '''SELECT dv.*, dd.date_key, dd.date_name2 FROM ur_bi_dw.dim_vip as dv INNER JOIN ur_bi_dw.dim_date as dd ON dv.card_create_date=dd.date_name2 where dd.date_key >= %s and dd.date_key < %s''' # data:pd.DataFrame = self.db_helper.get_data(sql) sort_columns = ['dv.vip_no'] # TODO: self.get_data_of_date( save_dir=sub_dir, sql=sql, sort_columns=sort_columns, start_date=datetime.datetime(2017, 1, 1), # 开始时间 offset=relativedelta(years=1) ) # 更新超时时间 self.save_last_time(sub_dir) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_weather(self): '''天气数据''' sub_dir = os.path.join(self.save_dir,'weather') now_lock = self.get_lock(sub_dir) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(sub_dir): return sql = """ select weather.* from ur_bi_ods.ods_base_weather_data_1200 as weather where weather.date_key>=%s and weather.date_key<%s """ sort_columns = ['weather.date_key','weather.areaid'] def data_format_fun(data): columns = list(data.columns) columns = {c:'weather.'+c for c in columns} data = data.rename(columns=columns) return data self.get_data_of_date( save_dir=sub_dir, sql=sql, sort_columns=sort_columns, del_index_list=[-2, -1], # 删除最后下标 data_format_fun=data_format_fun, ) # 更新超时时间 self.save_last_time(sub_dir) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_weather_city(self): '''天气城市数据''' file_path = os.path.join(self.save_dir,'ur_bi_dw.weather_city.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return sql = 'SELECT * FROM ur_bi_dw.dim_weather_city as weather_city' data:pd.DataFrame = self.db_helper.get_data(sql) columns = list(data.columns) columns = {c:'weather_city.'+c for c in columns} data = data.rename(columns=columns) data.to_csv(file_path) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_dim_goods(self): '''货品数据''' file_path = os.path.join(self.save_dir,'ur_bi_dw.dim_goods.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return sql = 'SELECT * FROM ur_bi_dw.dim_goods' data:pd.DataFrame = self.db_helper.get_data(sql) columns = list(data.columns) columns = {c:'dim_goods.'+c for c in columns} data = data.rename(columns=columns) data.to_csv(file_path) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_dim_goods_market_shop_date(self): '''店铺商品生命周期数据''' file_path = os.path.join(self.save_dir,'ur_bi_dw.dim_goods_market_shop_date.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return # sql = 'SELECT * FROM ur_bi_dw.dim_goods_market_shop_date as goods_shop_date' sql = ''' select shop_no, sku_no, shop_market_date, lifecycle_end_date, lifecycle_days FROM ur_bi_dw.dim_goods_market_shop_date where lifecycle_end_date is not null ''' data:pd.DataFrame = self.db_helper.get_data(sql) columns = list(data.columns) columns = {c:c.replace('lifecycle_end_date.','') for c in columns} data = data.rename(columns=columns) data = data.sort_values(['shop_market_date']) data.to_csv(file_path, index=False) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_dim_goods_market_date(self): '''全国商品生命周期数据''' file_path = os.path.join(self.save_dir,'ur_bi_dw.dim_goods_market_date.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return sql = ''' select * FROM ur_bi_dw.dim_goods_market_date ''' data:pd.DataFrame = self.db_helper.get_data(sql) columns = list(data.columns) columns = {c:'dim_goods_market_date.'+c for c in columns} data = data.rename(columns=columns) data = data.sort_values(['dim_goods_market_date.sku_no']) data.to_csv(file_path, index=False) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_dim_goods_color_dev_sizes(self): '''商品开发码数数据''' file_path = os.path.join(self.save_dir,'dim_goods_color_dev_sizes.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return # sql = 'SELECT * FROM ur_bi_dw.dim_goods_market_shop_date as goods_shop_date' sql = 'SELECT * FROM ur_bi_dm.dim_goods_color_dev_sizes' data:pd.DataFrame = self.db_helper.get_data(sql) columns = list(data.columns) columns = {c:c.replace('dim_goods_color_dev_sizes.','') for c in columns} data = data.rename(columns=columns) data.to_csv(file_path, index=False) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_dwd_daily_sales_size(self): '''实际销售金额''' sub_dir = os.path.join(self.save_dir,'dwd_daily_sales_size_all') now_lock = self.get_lock(sub_dir) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(sub_dir): return sql = """ select shop_no,sku_no,date_key,`size`, sum(tag_price) as `tag_price`, sum(sales_qty) as `sales_qty`, sum(sales_tag_amt) as `sales_tag_amt`, sum(sales_amt) as `sales_amt`, count(0) as `sales_count` from ur_bi_dw.dwd_daily_sales_size as sales where sales.date_key>=%s and sales.date_key<%s and sales.currency_code='CNY' group by shop_no,sku_no,date_key,`size` """ sort_columns = ['date_key','shop_no','sku_no'] self.get_data_of_date( save_dir=sub_dir, sql=sql, sort_columns=sort_columns, start_date=datetime.datetime(2017, 1, 1), # 开始时间 ) # 更新超时时间 self.save_last_time(sub_dir) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_dwd_daily_delivery_size(self): '''实际配货金额''' sub_dir = os.path.join(self.save_dir,'dwd_daily_delivery_size_all') now_lock = self.get_lock(sub_dir) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(sub_dir): return sql = """ select shop_no,sku_no,date_key,`size`, sum(delivery.shop_distr_received_qty) as `shop_distr_received_qty`, sum(delivery.shop_distr_received_amt) as `shop_distr_received_amt`, sum(delivery.online_distr_received_qty) as `online_distr_received_qty`, sum(delivery.online_distr_received_amt) as `online_distr_received_amt`, sum(delivery.pr_received_qty) as `pr_received_qty`, count(0) as `delivery_count` from ur_bi_dw.dwd_daily_delivery_size as delivery where delivery.date_key>=%s and delivery.date_key<%s and delivery.currency_code='CNY' group by shop_no,sku_no,date_key,`size` """ sort_columns = ['date_key','shop_no','sku_no'] self.get_data_of_date( save_dir=sub_dir, sql=sql, sort_columns=sort_columns, start_date=datetime.datetime(2017, 1, 1), # 开始时间 ) # 更新超时时间 self.save_last_time(sub_dir) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_v_last_nation_sales_status(self): '''商品畅滞销数据''' file_path = os.path.join(self.save_dir,'v_last_nation_sales_status.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return sql = 'SELECT * FROM ur_bi_dw.v_last_nation_sales_status' data:pd.DataFrame = self.db_helper.get_data(sql) columns = list(data.columns) columns = {c:c.replace('v_last_nation_sales_status.','') for c in columns} data = data.rename(columns=columns) data.to_csv(file_path, index=False) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_dwd_daily_finacial_goods(self): '''商品成本价数据''' file_path = os.path.join(self.save_dir,'dwd_daily_finacial_goods.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return sql = """ select t1.sku_no,t1.`size`,t1.cost_tax_incl from ur_bi_dw.dwd_daily_finacial_goods as t1 inner join ( select sku_no,`size`,max(date_key) as date_key from ur_bi_dw.dwd_daily_finacial_goods where currency_code='CNY' and country_code='CN' group by sku_no,`size` ) as t2 on t2.sku_no=t1.sku_no and t2.`size`=t1.`size` and t2.date_key=t1.date_key where t1.currency_code='CNY' and t1.country_code='CN' """ data:pd.DataFrame = self.db_helper.get_data(sql) columns = list(data.columns) columns = {c:c.replace('t1.','') for c in columns} data = data.rename(columns=columns) data.to_csv(file_path, index=False) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_dim_size_group(self): '''尺码映射数据''' file_path = os.path.join(self.save_dir,'dim_size_group.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return sql = """select * from ur_bi_dw.dim_size_group""" data:pd.DataFrame = self.db_helper.get_data(sql) columns = list(data.columns) columns = {c:c.replace('dim_size_group.','') for c in columns} data = data.rename(columns=columns) data.to_csv(file_path, index=False) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 pass def get_common_datas( host='10.2.32.22', port=21051, database='ur_ai_dw', auth_mechanism='LDAP', user='urbi', password='Ur#730xd', logger:logging.Logger=None): # 共用文件 common_datas_dir = ShareArgs.get_args_value('common_datas_dir') common_ur_bi_dir = os.path.join(common_datas_dir, 'ur_bi_data') ur_bi_get_datas = UrBiGetDatas( host=host, port=port, database=database, auth_mechanism=auth_mechanism, user=user, password=password, save_dir=common_ur_bi_dir, logger=logger ) try: logger.info('正在查询日期数据...') ur_bi_get_datas.get_dim_date() logger.info('查询日期数据完成!') logger.info('正在查询店铺数据...') ur_bi_get_datas.get_dim_shop() logger.info('查询店铺数据完成!') logger.info('正在查询天气数据...') ur_bi_get_datas.get_weather() logger.info('查询天气数据完成!') logger.info('正在查询天气城市数据...') ur_bi_get_datas.get_weather_city() logger.info('查询天气城市数据完成!') logger.info('正在查询货品数据...') ur_bi_get_datas.get_dim_goods() logger.info('查询货品数据完成!') logger.info('正在查询实际销量数据...') ur_bi_get_datas.get_dwd_daily_sales_size() logger.info('查询实际销量数据完成!') except Exception as ex: logger.exception(ex) raise ex # 往外抛出异常 finally: ur_bi_get_datas.close() pass class CustomUrBiGetDatas(UrBiGetDatasBase): def __init__( self, host='10.2.32.22', port=21051, database='ur_ai_dw', auth_mechanism='LDAP', user='urbi', password='Ur#730xd', save_dir='./hjx/data/ur_bi_data', logger:logging.Logger=None ): self.save_dir = save_dir self.logger = logger super().__init__( host=host, port=port, database=database, auth_mechanism=auth_mechanism, user=user, password=password, save_dir=save_dir, logger=logger ) def get_sales_goal_amt(self): '''销售目标金额''' file_path = os.path.join(self.save_dir,'month_of_year_sales_goal_amt.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return sql = ''' select sales_goal.shop_no, if(sales_goal.serial='Y','W',sales_goal.serial) as `sales_goal.serial`, dates.month_of_year, sum(sales_goal.sales_goal_amt) as sales_goal_amt from ur_bi_dw.dwd_sales_goal_west as sales_goal inner join ur_bi_dw.dim_date as dates on sales_goal.date_key = dates.date_key group by sales_goal.shop_no, if(sales_goal.serial='Y','W',sales_goal.serial), dates.month_of_year ''' data:pd.DataFrame = self.db_helper.get_data(sql) data = data.rename(columns={ 'shop_no':'sales_goal.shop_no', 'serial':'sales_goal.serial', 'month_of_year':'dates.month_of_year', }) # 排序 data = data.sort_values(['sales_goal.shop_no','sales_goal.serial','dates.month_of_year']) data.to_csv(file_path) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 def get_shop_serial_area(self): '''店-系列面积''' file_path = os.path.join(self.save_dir,'shop_serial_area.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 if not self.get_last_time(file_path): return sql = ''' select shop_serial_area.shop_no, if(shop_serial_area.serial='Y','W',shop_serial_area.serial) as `shop_serial_area.serial`, shop_serial_area.month_of_year, sum(shop_serial_area.area) as `shop_serial_area.area` from ur_bi_dw.dwd_shop_serial_area as shop_serial_area where shop_serial_area.area is not null group by shop_serial_area.shop_no,if(shop_serial_area.serial='Y','W',shop_serial_area.serial),shop_serial_area.month_of_year ''' data:pd.DataFrame = self.db_helper.get_data(sql) data = data.rename(columns={ 'shop_no':'shop_serial_area.shop_no', 'serial':'shop_serial_area.serial', 'month_of_year':'shop_serial_area.month_of_year', 'area':'shop_serial_area.area', }) # 排序 data = data.sort_values(['shop_serial_area.shop_no','shop_serial_area.serial','shop_serial_area.month_of_year']) data.to_csv(file_path) # 更新超时时间 self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 pass def get_datas( host='10.2.32.22', port=21051, database='ur_ai_dw', auth_mechanism='LDAP', user='urbi', password='Ur#730xd', save_dir='./data/sales_forecast/ur_bi_dw_data', logger:logging.Logger=None): ur_bi_get_datas = CustomUrBiGetDatas( host=host, port=port, database=database, auth_mechanism=auth_mechanism, user=user, password=password, save_dir=save_dir, logger=logger ) try: # 店,系列,品类,年月,销售目标金额 logger.info('正在查询年月销售目标金额数据...') ur_bi_get_datas.get_sales_goal_amt() logger.info('查询年月销售目标金额数据完成!') except Exception as ex: logger.exception(ex) raise ex # 往外抛出异常 finally: ur_bi_get_datas.close() pass def getdata_ur_bi_dw( host='10.2.32.22', port=21051, database='ur_ai_dw', auth_mechanism='LDAP', user='urbi', password='Ur#730xd', save_dir='./data/sales_forecast/ur_bi_dw_data', logger=None ): get_common_datas( host=host, port=port, database=database, auth_mechanism=auth_mechanism, user=user, password=password, logger=logger ) get_datas( host=host, port=port, database=database, auth_mechanism=auth_mechanism, user=user, password=password, save_dir=save_dir, logger=logger ) pass # 代码入口 # getdata_ur_bi_dw( # host=ur_bi_dw_host, # port=ur_bi_dw_port, # database=ur_bi_dw_database, # auth_mechanism=ur_bi_dw_auth_mechanism, # user=ur_bi_dw_user, # password=ur_bi_dw_password, # save_dir=ur_bi_dw_save_dir, # logger=logger # )
代码说明和领悟
每个类的具体作用说明,代码需要根据下面的文字说明进行“食用”:
(第一层)HiveHelper完成了连接数据库、关闭数据库连接、生成事务、执行、引擎、连接等功能
VarsHelper提供了一个简单的持久化功能,可以将对象以文件的形式存放在磁盘上。并提供设置值、获取值、判断值是否存在的方法
GlobalShareArgs提供了一个字典,并且提供了获取字典、设置字典、设置字典键值对、设置字典键的值、判断键是否在字典中、更新字典等方法
ShareArgs跟GlobalShareArgs类似,只是一开始字典的初始化的键值对比较多
(第二层)UrBiGetDataBase类,提供了线程锁字典、时间字典、超时判断字典,都是类变量;使用了HiveHelper类,但注意,不是继承。在具体的sql读数时,提供了线程固定和时间判断
(第三层)UrBiGetDatas类,获取hive数据库那边的日期数据、店铺数据、会员数据、天气数据、天气城市数据、商品数据、店铺生命周期数据、全国商品生命周期数据、商品开发码数数据、实际销售金额、实际配货金额、商品畅滞销数据、商品成本价数据、尺码映射数据等。
(第四层)get_common_data函数,使用URBiGetData类读取日期、店铺、天气、天气城市、货品、实际销量数据,并缓存到文件夹./yongjian/data/ur_bi_data下面
CustomUrBiGetData类,继承了UrBiGetDatasBase类,读取销售目标金额、点系列面积数据。
(这个也是第四层)get_datas函数,通过CustomUrBiGetData类,读取年月销售目标金额。
总的函数:(这个是总的调用入口函数)get_data_ur_bi_dw函数,调用了get_common_data和get_datas函数进行读取数据,然后将数据保存到某个文件夹目录下面。
举一反三,如果你不是hive数据库,你可以将第一层这个底层更换成mysql。主页有解释如果进行更换。第二层不需要改变,第三层就是你想要进行读取的数据表,不同的数据库你想要读取的数据表也不同,所以sql需要你在这里写,套用里面的方法即可,基本上就是修改sql就好了。
这种方法的好处在于,数据不会重复读取,并且读取的数据都可以得到高效的使用。
后续附上修改成mysql的一个例子代码
import logging import pandas as pd from impala.dbapi import connect import sqlalchemy from sqlalchemy.orm import sessionmaker import os import time import os import datetime from dateutil.relativedelta import relativedelta from typing import Dict, List import logging import threading import pandas as pd import pickle class MySqlHelper(object): def __init__( self, host='192.168.15.144', port=3306, database='test_ims', user='spkjz_writer', password='7cmoP3QDtueVJQj2q4Az', logger:logging.Logger=None ): self.host = host self.port = port self.database = database self.user = user self.password = password self.logger = logger self.connection_str = 'mysql+pymysql://%s:%s@%s:%d/%s' %( self.user, self.password, self.host, self.port, self.database ) self.conn = None self.cursor = None self.engine = None self.session = None def create_table_code(self, file_name): '''创建表类代码''' os.system(f'sqlacodegen {self.connection_str} > {file_name}') return self.conn def get_conn(self): '''创建连接或获取连接''' if self.conn is None: engine = self.get_engine() self.conn = engine.connect() return self.conn def get_engine(self): '''创建连接或获取连接''' if self.engine is None: self.engine = sqlalchemy.create_engine(self.connection_str) return self.engine def get_cursor(self): '''创建连接或获取连接''' if self.cursor is None: self.cursor = self.conn.cursor() return self.cursor def get_session(self) -> sessionmaker: '''创建连接或获取连接''' if self.session is None: engine = self.get_engine() Session = sessionmaker(bind=engine) self.session = Session() return self.session def close_conn(self): '''关闭连接''' if self.conn is not None: self.conn.close() self.conn = None self.dispose_engine() def close_session(self): '''关闭连接''' if self.session is not None: self.session.close() self.session = None self.dispose_engine() def dispose_engine(self): '''释放engine''' if self.engine is not None: # self.engine.dispose(close=False) self.engine.dispose() self.engine = None def close_cursor(self): '''关闭cursor''' if self.cursor is not None: self.cursor.close() self.cursor = None def get_data(self, sql, auto_close=True) -> pd.DataFrame: '''查询数据''' conn = self.get_conn() data = None try: # 异常重试3次 for i in range(3): try: data = pd.read_sql(sql, conn) break except Exception as ex: if i == 2: raise ex # 往外抛出异常 time.sleep(60) # 一分钟后重试 except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: if auto_close: self.close_conn() return data pass class VarsHelper(): def __init__(self, save_dir, auto_save=True): self.save_dir = save_dir self.auto_save = auto_save self.values = {} if not os.path.exists(os.path.dirname(self.save_dir)): os.makedirs(os.path.dirname(self.save_dir)) if os.path.exists(self.save_dir): with open(self.save_dir, 'rb') as f: self.values = pickle.load(f) f.close() def set_value(self, key, value): self.values[key] = value if self.auto_save: self.save_file() def get_value(self, key): return self.values[key] def has_key(self, key): return key in self.values.keys() def save_file(self): with open(self.save_dir, 'wb') as f: pickle.dump(self.values, f) f.close() pass class GlobalShareArgs(): args = { "debug": False } def get_args(): return GlobalShareArgs.args def set_args(args): GlobalShareArgs.args = args def set_args_value(key, value): GlobalShareArgs.args[key] = value def get_args_value(key, default_value=None): return GlobalShareArgs.args.get(key, default_value) def contain_key(key): return key in GlobalShareArgs.args.keys() def update(args): GlobalShareArgs.args.update(args) pass class ShareArgs(): args = { "labels_dir":"./hjx/shop_group/month_w_amt/data/labels", # 标签目录 "labels_output_dir":"./hjx/shop_group/month_w_amt/data/labels_output", # 聚类导出标签目录 "common_datas_dir":"./hjx/data", # 共用数据目录。ur_bi_dw的公共 "only_predict": False, # 只识别,不训练 "delete_model": True, # 先删除模型,仅在训练时使用 "export_excel": False, # 导出excel "classes": 12, # 聚类数 "batch_size": 16, "hidden_size": 32, "max_nrof_epochs": 100, "learning_rate": 0.0005, "loss_type": "categorical_crossentropy", "avg_model_num": 10, "steps_per_epoch": 4.0, # 4.0 "lr_callback_patience": 4, "lr_callback_cooldown": 1, "early_stopping_callback_patience": 6, "get_data": True, } def get_args(): return ShareArgs.args def set_args(args): ShareArgs.args = args def set_args_value(key, value): ShareArgs.args[key] = value def get_args_value(key, default_value=None): return ShareArgs.args.get(key, default_value) def contain_key(key): return key in ShareArgs.args.keys() def update(args): ShareArgs.args.update(args) pass class IMSGetDatasBase(): # 线程锁列表,同保存路径共用锁 lock_dict:Dict[str, threading.Lock] = {} # 时间列表,用于判断是否超时 time_dict:Dict[str, datetime.datetime] = {} # 用于记录是否需要更新超时时间 get_data_timeout_dict:Dict[str, bool] = {} def __init__( self, host='192.168.15.144', port=3306, database='test_ims', user='spkjz_writer', password='Ur#7cmoP3QDtueVJQj2q4Az', save_dir=None, logger:logging.Logger=None, ): self.save_dir = save_dir self.logger = logger self.db_helper = MySqlHelper( host=host, port=port, database=database, user=user, password=password, logger=logger ) # 创建子目录 if self.save_dir is not None and not os.path.exists(self.save_dir): os.makedirs(self.save_dir) self.vars_helper = None if GlobalShareArgs.get_args_value('debug'): self.vars_helper = VarsHelper('./hjx/data/vars/IMSGetDatas') # 把超时时间保存到文件,注释该行即可停掉,只用于调试 def close(self): '''关闭连接''' self.db_helper.close_conn() def get_last_time(self, key_name) -> bool: '''获取是否超时''' # 转静态路径,确保唯一性 key_name = os.path.abspath(key_name) if self.vars_helper is not None and self.vars_helper.has_key('IMSGetDatasBase.time_list'): IMSGetDatasBase.time_dict = self.vars_helper.get_value('IMSGetDatasBase.time_list') timeout = 12 # 12小时 if GlobalShareArgs.get_args_value('debug'): timeout = 24 # 24小时 get_data_timeout = False if key_name not in IMSGetDatasBase.time_dict.keys() or (datetime.datetime.today() - IMSGetDatasBase.time_dict[key_name]).total_seconds()>(4*60*60): self.logger.info('超时%d小时,重新查数据:%s', timeout, key_name) # IMSGetDatasBase.time_list[key_name] = datetime.datetime.today() get_data_timeout = True else: self.logger.info('未超时%d小时,跳过查数据:%s', timeout, key_name) # if self.vars_helper is not None : # self.vars_helper.set_value('IMSGetDatasBase.time_list', IMSGetDatasBase.time_list) IMSGetDatasBase.get_data_timeout_dict[key_name] = get_data_timeout return get_data_timeout def save_last_time(self, key_name): '''更新状态超时''' # 转静态路径,确保唯一性 key_name = os.path.abspath(key_name) if IMSGetDatasBase.get_data_timeout_dict[key_name]: IMSGetDatasBase.time_dict[key_name] = datetime.datetime.today() if self.vars_helper is not None : IMSGetDatasBase.time_dict[key_name] = datetime.datetime.today() self.vars_helper.set_value('IMSGetDatasBase.time_list', IMSGetDatasBase.time_dict) def get_lock(self, key_name) -> threading.Lock: '''获取锁''' # 转静态路径,确保唯一性 key_name = os.path.abspath(key_name) if key_name not in IMSGetDatasBase.lock_dict.keys(): IMSGetDatasBase.lock_dict[key_name] = threading.Lock() return IMSGetDatasBase.lock_dict[key_name] def get_data_of_date( self, save_dir, sql, sort_columns:List[str], del_index_list=[-1], # 删除最后下标 start_date = datetime.datetime(2017, 1, 1), # 开始时间 offset = relativedelta(months=3), # 时间间隔 date_format_fun = lambda d: '%04d%02d01' % (d.year, d.month), # 查询语句中替代时间参数的格式化 filename_format_fun = lambda d: '%04d%02d.csv' % (d.year, d.month), # 查询语句中替代时间参数的格式化 stop_date = '20700101', # 超过时间则停止 ): '''分时间增量读取数据''' # 创建文件夹 if not os.path.exists(save_dir): os.makedirs(save_dir) else: #删除最后一个文件 file_list = os.listdir(save_dir) if len(file_list)>0: file_list.sort() for del_index in del_index_list: os.remove(os.path.join(save_dir,file_list[del_index])) print('删除最后一个文件:', file_list[del_index]) select_index = -1 # start_date = datetime.datetime(2017, 1, 1) while True: end_date = start_date + offset start_date_str = date_format_fun(start_date) end_date_str = date_format_fun(end_date) self.logger.info('date: %s-%s', start_date_str, end_date_str) file_path = os.path.join(save_dir, filename_format_fun(start_date)) # self.logger.info('file_path: %s', file_path) if not os.path.exists(file_path): data:pd.DataFrame = self.db_helper.get_data(sql % (start_date_str, end_date_str)) if data is None: break self.logger.info('data: %d', len(data)) # self.logger.info('data: %d', data.columns) if len(data)>0: select_index+=1 # 排序 data = data.sort_values(sort_columns) data.to_csv(file_path) elif select_index!=-1: break elif stop_date < start_date_str: raise Exception("读取数据异常,时间超出最大值!") start_date = end_date pass class CustomIMSGetDatas(IMSGetDatasBase): def __init__( self, host='192.168.13.134', port=4000, database='test_ims', user='root', password='rootimmsadmin', save_dir='./hjx/data/export_ims_data', logger:logging.Logger=None ): self.save_dir = save_dir self.logger = logger super().__init__( host=host, port=port, database=database, user=user, password=password, save_dir=save_dir, logger=logger ) def get_ims_w_amt_pro(self): '''年月系列占比数据''' file_path = os.path.join(self.save_dir,'ims_w_amt_pro.csv') now_lock = self.get_lock(file_path) now_lock.acquire() # 加锁 try: # 设置超时4小时才重新查数据 # if not self.get_last_time(file_path): # return sql = 'SELECT * FROM ims_w_amt_pro' data:pd.DataFrame = self.db_helper.get_data(sql) data = data.rename(columns={ 'serial_forecast_proportion': 'forecast_proportion', }) data.to_csv(file_path) # # 更新超时时间 # self.save_last_time(file_path) except Exception as ex: self.logger.exception(ex) raise ex # 往外抛出异常 finally: now_lock.release() # 释放锁 pass def get_datas( host='192.168.13.134', port=4000, database='test_ims', user='root', password='rootimmsadmin', save_dir='./hjx/data/export_ims_data', logger:logging.Logger=None ): ur_bi_get_datas = CustomIMSGetDatas( host=host, port=port, database=database, user=user, password=password, save_dir=save_dir, logger=logger ) try: # 年月系列占比数据 logger.info('正在查询年月系列占比数据...') ur_bi_get_datas.get_ims_w_amt_pro() logger.info('查询年月系列占比数据完成!') except Exception as ex: logger.exception(ex) raise ex # 往外抛出异常 finally: ur_bi_get_datas.close() pass def getdata_export_ims( host='192.168.13.134', port=4000, database='test_ims', user='root', password='rootimmsadmin', save_dir='./hjx/data/export_ims_data', logger:logging.Logger=None ): get_datas( host=host, port=port, database=database, user=user, password=password, save_dir=save_dir, logger=logger ) pass
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MySQL 有免费的社区版和收费的企业版。社区版可免费使用和修改,但支持有限,适合稳定性要求不高、技术能力强的应用。企业版提供全面商业支持,适合需要稳定可靠、高性能数据库且愿意为支持买单的应用。选择版本时考虑的因素包括应用关键性、预算和技术技能。没有完美的选项,只有最合适的方案,需根据具体情况谨慎选择。

文章介绍了MySQL数据库的上手操作。首先,需安装MySQL客户端,如MySQLWorkbench或命令行客户端。1.使用mysql-uroot-p命令连接服务器,并使用root账户密码登录;2.使用CREATEDATABASE创建数据库,USE选择数据库;3.使用CREATETABLE创建表,定义字段及数据类型;4.使用INSERTINTO插入数据,SELECT查询数据,UPDATE更新数据,DELETE删除数据。熟练掌握这些步骤,并学习处理常见问题和优化数据库性能,才能高效使用MySQL。

MySQL安装失败的原因主要有:1.权限问题,需以管理员身份运行或使用sudo命令;2.依赖项缺失,需安装相关开发包;3.端口冲突,需关闭占用3306端口的程序或修改配置文件;4.安装包损坏,需重新下载并验证完整性;5.环境变量配置错误,需根据操作系统正确配置环境变量。解决这些问题,仔细检查每个步骤,就能顺利安装MySQL。

MySQL下载文件损坏,咋整?哎,下载个MySQL都能遇到文件损坏,这年头真是不容易啊!这篇文章就来聊聊怎么解决这个问题,让大家少走弯路。读完之后,你不仅能修复损坏的MySQL安装包,还能对下载和安装过程有更深入的理解,避免以后再踩坑。先说说为啥下载文件会损坏这原因可多了去了,网络问题是罪魁祸首,下载过程中断、网络不稳定都可能导致文件损坏。还有就是下载源本身的问题,服务器文件本身就坏了,你下载下来当然也是坏的。另外,一些杀毒软件过度“热情”的扫描也可能造成文件损坏。诊断问题:确定文件是否真的损坏

MySQL拒启动?别慌,咱来排查!很多朋友安装完MySQL后,发现服务死活启动不了,心里那个急啊!别急,这篇文章带你从容应对,揪出幕后黑手!读完后,你不仅能解决这个问题,还能提升对MySQL服务的理解,以及排查问题的思路,成为一名更强大的数据库管理员!MySQL服务启动失败,原因五花八门,从简单的配置错误到复杂的系统问题都有可能。咱们先从最常见的几个方面入手。基础知识:服务启动流程简述MySQL服务启动,简单来说,就是操作系统加载MySQL相关的文件,然后启动MySQL守护进程。这其中涉及到配置

MySQL性能优化需从安装配置、索引及查询优化、监控与调优三个方面入手。1.安装后需根据服务器配置调整my.cnf文件,例如innodb_buffer_pool_size参数,并关闭query_cache_size;2.创建合适的索引,避免索引过多,并优化查询语句,例如使用EXPLAIN命令分析执行计划;3.利用MySQL自带监控工具(SHOWPROCESSLIST,SHOWSTATUS)监控数据库运行状况,定期备份和整理数据库。通过这些步骤,持续优化,才能提升MySQL数据库性能。

MySQL数据库性能优化指南在资源密集型应用中,MySQL数据库扮演着至关重要的角色,负责管理海量事务。然而,随着应用规模的扩大,数据库性能瓶颈往往成为制约因素。本文将探讨一系列行之有效的MySQL性能优化策略,确保您的应用在高负载下依然保持高效响应。我们将结合实际案例,深入讲解索引、查询优化、数据库设计以及缓存等关键技术。1.数据库架构设计优化合理的数据库架构是MySQL性能优化的基石。以下是一些核心原则:选择合适的数据类型选择最小的、符合需求的数据类型,既能节省存储空间,又能提升数据处理速度

MySQL 可在无需网络连接的情况下运行,进行基本的数据存储和管理。但是,对于与其他系统交互、远程访问或使用高级功能(如复制和集群)的情况,则需要网络连接。此外,安全措施(如防火墙)、性能优化(选择合适的网络连接)和数据备份对于连接到互联网的 MySQL 数据库至关重要。
