Esempio n. 1
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def demo3():
    # query_finance_category_signs(unusual_id='26', category_classify='01')

    # record = query_finance_shell_daily(unusual_point='13',task_status='doing')

    # records = query_billds_finance_all_targets(unusual_id='14')
    # print(records)

    province_service = ProvinceService()
    # records = province_service.query_province_names(grade='1')
    # print(records)

    origin_name = '东营区'
    origin_province = province_service.query_belong_province(
        area_name=origin_name)
    print(f'origin_province={origin_province}')
cd /you_filed_algos/app

PYTHONIOENCODING=utf-8 nohup /root/anaconda3/bin/python /you_filed_algos/app/report/works/full_add/exec_meeting_linshi_data.py &


"""

log = get_logger(__name__)

dest_dir = '/you_filed_algos/prod_kudu_data/temp'
dest_file = dest_dir + "/meeting_data.txt"
upload_hdfs_path = 'hdfs:///user/hive/warehouse/02_logical_layer_007_h_lf_cw.db/finance_meeting_linshi_analysis/meeting_data.txt'

match_area = MatchArea()
province_service = ProvinceService()
finance_service = FinanceAdministrationService()


def refresh_linshi_table():
    sql = 'REFRESH 02_logical_layer_007_h_lf_cw.finance_meeting_linshi_analysis'
    prod_execute_sql(conn_type=CONN_TYPE, sqltype='insert', sql=sql)


def init_file():
    if not os.path.exists(dest_dir):
        os.makedirs(dest_dir)

    if os.path.exists(dest_file):
        os.remove(dest_file)
Esempio n. 3
0
 def __init__(self):
     self.province_service = ProvinceService()
Esempio n. 4
0
class Check13Service:
    def __init__(self):
        self.province_service = ProvinceService()

    def init_file(self):
        if not os.path.exists(dest_dir):
            os.makedirs(dest_dir)

        if os.path.exists(dest_file):
            os.remove(dest_file)

        os.mknod(dest_file)

    def save_fee_data(self):
        """
        查询超过标准报销费用的住宿费记录
        :return:
        """
        self.init_file()

        sql = f"""
        SELECT a.bill_id, a.city_name, a.city_grade_name, a.emp_name, a.stand_amount_perday, a.hotel_amount_perday
            FROM (
            SELECT DISTINCT
            bill_id, city_name, city_grade_name, emp_name,ROUND(stand_amount, 2) as stand_amount_perday,
            ROUND(hotel_amount/hotel_num , 2) as hotel_amount_perday
            FROM 01_datamart_layer_007_h_cw_df.finance_rma_travel_accomm
            WHERE exp_type_name="差旅费" AND hotel_num > 0
            AND bill_id is not null AND bill_id != ""           
            )as a   {test_limit_cond}        
        """

        count_sql = "select count(b.bill_id) from ({sql}) b".format(sql=sql)
        log.info(count_sql)
        records = prod_execute_sql(conn_type=CONN_TYPE,
                                   sqltype="select",
                                   sql=count_sql)
        count_records = records[0][0]
        print(f"* count_records ==> {count_records}")

        max_size = 10 * 10000
        limit_size = 10000
        select_sql_ls = []
        if count_records >= max_size:
            offset_size = 0
            while offset_size <= count_records:
                if offset_size + limit_size > count_records:
                    limit_size = count_records - offset_size
                    tmp_sql = """
                        SELECT a.bill_id, a.city_name, a.city_grade_name, a.emp_name,a.stand_amount_perday, a.hotel_amount_perday
                            FROM (
                            SELECT DISTINCT
                            bill_id, city_name, city_grade_name, emp_name,ROUND(stand_amount, 2) as stand_amount_perday,
                            ROUND(hotel_amount/hotel_num , 2) as hotel_amount_perday
                            FROM 01_datamart_layer_007_h_cw_df.finance_rma_travel_accomm
                            WHERE exp_type_name="差旅费" AND hotel_num > 0
                            AND bill_id is not null AND bill_id != ""
                            )as a                       
                        order by stand_amount_perday limit {limit_size} offset {offset_size}
                    """.format(limit_size=limit_size, offset_size=offset_size)

                    select_sql_ls.append(tmp_sql)
                    break
                else:
                    tmp_sql = """
                           SELECT a.bill_id, a.city_name, a.city_grade_name, a.emp_name,a.stand_amount_perday, a.hotel_amount_perday
                               FROM (
                               SELECT DISTINCT
                               bill_id, city_name, city_grade_name, emp_name,ROUND(stand_amount, 2) as stand_amount_perday,
                               ROUND(hotel_amount/hotel_num , 2) as hotel_amount_perday
                               FROM 01_datamart_layer_007_h_cw_df.finance_rma_travel_accomm
                               WHERE exp_type_name="差旅费" AND hotel_num > 0
                               AND bill_id is not null AND bill_id != ""
                               )as a                           
                           order by stand_amount_perday limit {limit_size} offset {offset_size}
                           """.format(limit_size=limit_size,
                                      offset_size=offset_size)

                    select_sql_ls.append(tmp_sql)

                offset_size = offset_size + limit_size
        else:
            tmp_sql = f"""           
        SELECT a.bill_id, a.city_name, a.city_grade_name, a.emp_name,a.stand_amount_perday, a.hotel_amount_perday
            FROM (
            SELECT DISTINCT
            bill_id, city_name, city_grade_name, emp_name,ROUND(stand_amount, 2) as stand_amount_perday,
            ROUND(hotel_amount/hotel_num , 2) as hotel_amount_perday
            FROM 01_datamart_layer_007_h_cw_df.finance_rma_travel_accomm  
            WHERE exp_type_name="差旅费" AND hotel_num > 0     
            AND bill_id is not null AND bill_id != ""        
            )as a
        WHERE a.hotel_amount_perday  > a.stand_amount_perday  {test_limit_cond}   
        """
            select_sql_ls.append(tmp_sql)

        log.info(f"* 开始分页查询,一共 {len(select_sql_ls)} 页")
        start_time = time.perf_counter()
        # threadPool = ThreadPoolExecutor(max_workers=10, thread_name_prefix="thr")
        # all_task = [threadPool.submit(self.exec_task, (sel_sql)) for sel_sql in select_sql_ls]
        # wait(all_task, return_when=ALL_COMPLETED)
        # threadPool.shutdown(wait=True)

        pool = Pool(30)
        results = []
        for sel_sql in select_sql_ls:
            rst = pool.spawn(self.exec_task, sel_sql)
            results.append(rst)

        gevent.joinall(results)

        consumed_time = round(time.perf_counter() - start_time)
        log.info(f"* 一共有数据 {count_records} 条,保存数据耗时 {consumed_time} sec")

    def exec_task(self, sql):
        # log.info(sql)

        records = prod_execute_sql(conn_type=CONN_TYPE,
                                   sqltype="select",
                                   sql=sql)

        if records and len(records) > 0:
            for idx, record in enumerate(records):
                bill_id = str(record[0])  # bill_id
                city_name = str(record[1])  # 出差城市名称
                city_grade_name = str(record[2])  # 出差城市等级
                emp_name = str(record[3])  # 员工名字
                stand_amount_perday = float(record[4])  # 每天标准住宿费用
                hotel_amount_perday = float(record[5])  # 每天实际花费的住宿费用

                province = self.province_service.query_belong_province(
                    city_name)  # 出差城市所属的省
                # province = province if province else "******"   # 可能需要补充  01_datamart_layer_007_h_cw_df.finance_province_city 表中的数据

                # city_name = city_name.replace(",", " ")
                # emp_name = emp_name.replace(",", " ")

                if ',' in city_name:
                    city_name = city_name.replace(",", " ")

                if ',' in emp_name:
                    emp_name = emp_name.replace(",", " ")

                record_str = f"{bill_id},{city_name},{province},{city_grade_name},{emp_name},{stand_amount_perday},{hotel_amount_perday}"
                # log.info(f"checkpoint_13 {threading.current_thread().name} is running ")
                # log.info(record_str)

                with open(dest_file, "a+", encoding="utf-8") as file:
                    file.write(record_str + "\n")

    def cal_abnormal_data(self, rd_df, coefficient, query_province):
        # query_province = "江苏省"
        abnormal_rd_df1 = rd_df[
            (rd_df["province"] == query_province)
            & (rd_df["stand_amount_perday"] >= rd_df["hotel_amount_perday"])
            & (rd_df["consume_amount_perday"] > 0)]
        # print("part1 after filter abnormal_rd_df1 ", len(abnormal_rd_df1))
        # print(abnormal_rd_df1.head(10))

        # part1 过滤查询
        # temp = abnormal_rd_df1.describe()[["consume_amount_perday"]]
        # std_val = temp.at["std", "consume_amount_perday"]  # 标准差
        # mean_val = temp.at["mean", "consume_amount_perday"]  # 平均值

        std_val = abnormal_rd_df1.std().at['consume_amount_perday']  # 标准差
        mean_val = abnormal_rd_df1.mean().at['consume_amount_perday']  # 平均值

        # 数据的正常范围为 【mean - 2 × std , mean + 2 × std】
        max_val = mean_val + coefficient * std_val
        min_val = mean_val - coefficient * std_val

        # print(f"{query_province} 方差 => {std_val}, 平均值 => {mean_val}, max_val => {max_val}, min_val => {min_val}")

        bill_id_ls1 = []
        for index, row in abnormal_rd_df1.iterrows():

            hotel_amount_perday = row["hotel_amount_perday"]
            # print("hotel_amount_perday=", hotel_amount_perday)

            if hotel_amount_perday > max_val or hotel_amount_perday < min_val:
                bill_id = row["bill_id"]
                bill_id_ls1.append(bill_id)

        # part2 过滤查询
        abnormal_rd_df2 = rd_df[(rd_df["province"] == query_province) & (
            rd_df["stand_amount_perday"] < rd_df["hotel_amount_perday"])]
        bill_id_ls2 = abnormal_rd_df2["bill_id"].tolist()
        # 对两个列表合并并去重
        rst_ls = list(set(bill_id_ls1 + bill_id_ls2))

        log.info(f"checkpoint_13 {query_province} 异常数量={len(rst_ls)}")
        return rst_ls

    def analyze_data(self, coefficient=2):
        log.info(f"* 开始执行检查点13 coefficient={coefficient} ")
        start_time = time.perf_counter()

        rd_df = pd.read_csv(dest_file,
                            sep=",",
                            header=None,
                            names=[
                                "bill_id", "city_name", "province",
                                "city_grade_name", "emp_name",
                                "stand_amount_perday", "hotel_amount_perday"
                            ])
        rd_df["consume_amount_perday"] = rd_df["stand_amount_perday"] - rd_df[
            "hotel_amount_perday"]
        # print(rd_df.dtypes)

        province_names = self.province_service.query_province_names(grade="1")
        # print(province_names)
        bill_id_ls = []
        for idx, province_name in enumerate(province_names):
            # print(province_name)
            tmp_ls = self.cal_abnormal_data(rd_df=rd_df,
                                            coefficient=coefficient,
                                            query_province=province_name)
            # bill_id_ls.extend(tmp_ls)

            exec_sql(tmp_ls)

        log.info(f"* all results => {len(bill_id_ls)}")
        # targes_bill_id_ls = query_billds_finance_all_targets(unusual_id="13")
        # bill_id_ls = [x for x in bill_id_ls if x not in targes_bill_id_ls]
        # exec_sql(bill_id_ls)

        consumed_time = round(time.perf_counter() - start_time)
        log.info(f"* 执行检查点13的数据共耗时 {consumed_time} sec")