recommend-emr-dataprocess/qiaojialiang/checkHiveDataUtil.py

# -*- coding: utf-8 -*-
from odps import ODPS
from FeishuBot import FeishuBot

import argparse

ODPS_CONFIG = {
    'ENDPOINT': 'http://service.cn.maxcompute.aliyun.com/api',
    'ACCESSID': 'LTAIWYUujJAm7CbH',
    'ACCESSKEY': 'RfSjdiWwED1sGFlsjXv0DlfTnZTG1P',
}


def check_origin_hive(args):
    project = "loghubods"
    table = args.table
    beginStr = args.beginStr
    endStr = args.endStr
    # 检查从begin到end的每一个小时级分区数据是否存在，有一个存在即算存在可以处理
    # 如果全都为空报警
    time_sequence = generate_time_sequence(beginStr, endStr)
    exist_partition = []
    for time_str in time_sequence:
        result = split_date_time(time_str)
        partitionDt = result[0]
        partitionHh = result[1]
        count = check_data(project, table, partitionDt, partitionHh)
        if count != 0:
            exist_partition.append(f'分区：dt={partitionDt}/hh={partitionHh},数据：{count}')
    if len(exist_partition) == 0:
        print('1')
        exit(1)
    else:
        bot = FeishuBot()
        msg = (
            f'推荐模型数据更新 \n【任务名称】:step1校验hive数据源\n【是否成功】:success\n【信息】:table:{table},beginStr:{beginStr},endStr:{endStr}\n【详细日志】:{exist_partition}')
        bot.send_message(msg)
        print('0')


def check_data(project, table, partitionDt, partitionDtHh) -> int:
    """检查数据是否准备好,输出数据条数"""
    odps = ODPS(
        access_id=ODPS_CONFIG['ACCESSID'],
        secret_access_key=ODPS_CONFIG['ACCESSKEY'],
        project=project,
        endpoint=ODPS_CONFIG['ENDPOINT'],
        # connect_timeout=300000,
        # read_timeout=500000,
        # pool_maxsize=1000,
        # pool_connections=1000
    )
    try:
        t = odps.get_table(name=table)
        # check_res = t.exist_partition(partition_spec=f'dt={partition}')
        # 含有hh分区
        # if not {partitionDtHh}:
        check_res = t.exist_partition(partition_spec=f'dt={partitionDt},hh={partitionDtHh}')
        if check_res:
            sql = f'select * from {project}.{table} where dt = {partitionDt} and hh={partitionDtHh}'
            with odps.execute_sql(sql=sql).open_reader() as reader:
                data_count = reader.count
        else:
            data_count = 0
        # else:
        #     check_res = t.exist_partition(partition_spec=f'dt={partitionDt}')
        #     if check_res:
        #         sql = f'select * from {project}.{table} where dt = {partitionDt}'
        #         with odps.execute_sql(sql=sql).open_reader() as reader:
        #             data_count = reader.count
        #     else:
        #         data_count = 0
    except Exception as e:
        print("error:" + str(e))
        data_count = 0
    return data_count


def generate_time_sequence(beginStr, endStr):
    # 将字符串时间转换为datetime对象
    from datetime import datetime, timedelta

    # 定义时间格式
    time_format = "%Y%m%d%H"

    # 转换字符串为datetime对象
    begin_time = datetime.strptime(beginStr, time_format)
    end_time = datetime.strptime(endStr, time_format)

    # 生成时间序列
    time_sequence = []
    current_time = begin_time
    while current_time <= end_time:
        # 将datetime对象转换回指定格式的字符串
        time_sequence.append(current_time.strftime(time_format))
        # 增加一个小时
        current_time += timedelta(hours=1)

    return time_sequence


def split_date_time(date_time_str):
    # 假设date_time_str是一个长度为12的字符串，格式为YYYYMMDDHH
    # 切片获取日期部分（前8位）和时间部分（后4位中的前2位，因为后两位可能是分钟或秒，但这里只取小时）
    date_part = date_time_str[:8]
    time_part = date_time_str[8:10]  # 只取小时部分

    # 将结果存储在一个数组中（在Python中通常使用列表）
    result = [date_part, time_part]

    return result


if __name__ == '__main__':
    parser = argparse.ArgumentParser(description='脚本utils')
    parser.add_argument('--beginStr', type=str, help='表分区Dt，beginStr')
    parser.add_argument('--endStr', type=str, help='表分区Hh，endStr')
    parser.add_argument('--table', type=str, help='表名')
    argv = parser.parse_args()
    check_origin_hive(argv)