跟踪 MySQL 中的最后读取记录

Question

我在 MySQL 中有 2 个数据库：

1) 输入 Latitude-Longitude_dB ('latlong_db', 此后)：它具有来自 GPS 跟踪设备的每个读数的纬度和经度。

2) Weather_db：我从 dB1 读取输入纬度，并计算每对纬度的“当前”天气数据（例如：湿度，cloud_coverage）。此天气数据被写入 Weather_db。

问题是：我需要跟踪最后读取的记录（哪个“输入 latlong”）。这样我就不会为我已经介绍过的纬度重新计算weather_data。如何跟踪上次读取的 input_latlong？

非常感谢。

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编辑： 1）对于那些一直在询问“数据库v / s表”问题的人，答案是我正在从第一个数据库读取并写入第二个数据库。连接2个数据库的'config.json'如下：

{
"Tracker_ds_locallatlongdb": {
        "database": "ds_testdb1",
        "host": "XXXXXXXXXXX",
        "port": XXXX,
        "user": "XXXX",
        "password": "XXXXX"
    },
    "Tracker_ds_localweatherdb": {
    "database": "ds_testdb2",
        "host": "XXXXXXX",
        "port": XXXX,
        "user": "XXXX",
        "password": "XXXXX"
    }
}

2) 我从input_latlong_db 读取并写入weather_db 的Python 脚本概述如下。我正在使用 OpenWeatherMap API 来计算给定纬度和经度的天气数据：

from pyowm import OWM
import json
import time
import pprint
import pandas as pd

import mysql.connector
from mysql.connector import Error



api_key = 'your api key'

def get_weather_data(my_lat, my_long):
    owm= OWM(api_key)
    obs= owm.weather_at_coords(my_lat.item() , my_long.item() )   #Use: <numpy.ndarray>.item:
    w= obs.get_weather()
    l= obs.get_location()

    city= l.get_name()
    cloud_coverage =w.get_clouds()
    .
    .
    .
    w_datatoinsert= [my_lat, my_long, w_latitude, w_longitude, city, weather_time_gmt,call_time_torontotime,
    short_status, detailed_status,
    temp_celsius, cloud_coverage, humidity, wind_deg, wind_speed,
    snow, rain, atm_pressure, sea_level_pressure,sunset_time_gmt ] #15 + act_latitude + act_longitude
    return w_datatoinsert

# ------------------------------------------------------------------------------------------------------------------------------------
spec_creds_1= {}
spec_creds_2= {}
def operation():
    with open('C:/Users/config.json') as config_file:
        creds_dict= json.load(config_file)
        spec_creds_1= creds_dict['Tracker_ds_locallatlongdb'] 
        spec_creds_2= creds_dict['Tracker_ds_localweatherdb']
        try:
            my_conn_1= mysql.connector.connect(**spec_creds_1 )
            if (my_conn_1.is_connected()):
                info_1= my_conn_1.get_server_info()
                print("Connected ..now reading the local input_latlong_db: ", info_1)
                try:
                    my_conn_2= mysql.connector.connect(**spec_creds_2)
                    if (my_conn_2.is_connected()):
                        info_2= my_conn_2.get_server_info()
                        print('Connected to write into the local weather_db: ', info_2)
                        cursor_2= my_conn_2.cursor()
                        readings_df= pd.read_sql("SELECT latitude, longitude FROM readings_table_19cols;", con= my_conn_1)
                        for index, row in readings_df.iterrows():
                            gwd= get_weather_data(row['latitude'], row['longitude'])
                            q= "INSERT INTO weather_table_19cols VALUES(" +        ",".join(["%s"]*len(gwd))     +    " ); "
                            cursor_2.execute(q, gwd)
                            my_conn_2.commit()
                except Error as e:
                    print("Error while connecting to write into the local weather_db: ", e)
                finally:
                    if (my_conn_2.is_connected()):
                        cursor_2.close()
                        my_conn_2.close()
                        print("Wrote 1 record to the local weather_db.")
        except Error as e:
            print("Error connecting to the local input latlong_db: ", e)
        finally:
            if (my_conn_1.is_connected()):
                my_conn_1.close() # no cursor present for 'my_conn_1'
                print("Finished reading all the input latlongs ...and finished inserting ALL the weather data.")


#-------------------------------------------------------------------------------



if __name__=="__main__":
    operation()

Answer 1

1. 在 Input_latlong_table-readings_table_19cols 中：我创建了一个 Autoincremented readings_id 作为主键，以及一个名为 read_flag 的列，其默认值为 0。

2. 在weather_table_19cols 中：我创建了一个自动递增的weather_id 作为主键。

3. 由于我的方法涉及读取输入的经纬度记录并将其天气数据相应地写入weather_table，因此我比较了readings_table_19cols 和weather_table_19cols 的索引。如果它们匹配，则意味着输入记录已被读取，我会将 read_flag 设置为 1。

..

for index_1, row_1 in readings_df_1.iterrows():

                            gwd= get_weather_data(row_1['imei'], row_1['reading_id'] ,row_1['send_time'],row_1['latitude'], row_1['longitude'])

                            q_2= "INSERT INTO weather_table_23cols(my_imei, my_reading_id, actual_latitude, actual_longitude, w_latitude, w_longitude, city, weather_time_gmt, OBD_send_time_gmt, call_time_torontotime, \
                            short_status, detailed_status, \
                            temp_celsius, cloud_coverage, humidity, wind_deg, wind_speed, \
                            snow, rain, atm_pressure, sea_level_pressure,sunset_time_gmt) VALUES("  +  ",".join(["%s"]*len(gwd))     +    " ); "

                            q_1b= "UPDATE ds_testdb1.readings_table_22cols re,  ds_testdb2.weather_table_23cols we \
                             SET re.read_flag=1 WHERE (re.reading_id= we.weather_id);"  # use the prefix 'db_name.table_name' if 1 cursor is being used for 2 different db's

                            cursor_2.execute(q_2, gwd)
                            my_conn_2.commit()
                            cursor_1.execute(q_1b) # use Cursor_1 for 1st query 
                            my_conn_1.commit()