diff --git a/spark/passed_rain_analyse.py b/spark/passed_rain_analyse.py
deleted file mode 100644
index 4a1997b..0000000
--- a/spark/passed_rain_analyse.py
+++ /dev/null
@@ -1,25 +0,0 @@
-from pyspark.sql.types import DecimalType
-from pyspark.sql import functions
-
-from client import spark_app
-from data.data import data_hour_hdfs, mysql_jdbc_uri, mysql_jdbc_prop
-
-
-def passed_rain_analyse():
-    print("计算各个城市过去24小时累积雨量")
-    app = spark_app("passed_rain_analyse")
-    print("start")
-    df = app.read.csv(data_hour_hdfs, header=True)
-    df_rain = df.select(df['city_index'], df['city_name'], df['rain1h'].cast(DecimalType(scale=1))) \
-        .filter(df['rain1h'] < 1000)  # 筛选数据，去除无效数据
-    df_rain_sum = df_rain.groupBy("city_index", "city_name") \
-        .agg(functions.sum("rain1h").alias("rain24h")) \
-        .sort(functions.desc("rain24h"))  # 分组、求和、排序
-    df_rain_sum.cache()
-    df_rain_sum.coalesce(1).write.jdbc(mysql_jdbc_uri, "passed_rain_analyse", "ignore", mysql_jdbc_prop)
-    print("各个城市过去24小时累积雨量计算完毕")
-    return df_rain_sum.head(20)
-
-
-if __name__ == "__main__":
-    passed_rain_analyse()
diff --git a/spark/rain_24h_analyse.py b/spark/rain_24h_analyse.py
new file mode 100644
index 0000000..901242b
--- /dev/null
+++ b/spark/rain_24h_analyse.py
@@ -0,0 +1,30 @@
+from pyspark.sql.types import DecimalType
+from pyspark.sql import functions
+
+from client import spark_app
+from data.data import data_hour_hdfs, mysql_jdbc_uri, mysql_jdbc_prop
+
+
+def rain_24h_analyse():
+    print("计算重庆市各个区县过去24小时累积雨量")
+    app = spark_app("rain_24h_analyse")
+    print("创建应用完成，开始读取数据")
+    df = app.read.csv(data_hour_hdfs, header=True)
+    print("读取数据完成，开始处理数据")
+    # 取出数据
+    df_rain_data = df.select(
+        df['city_index'], df['city_name'], df['rain1h'].cast(DecimalType(scale=1))
+    ).filter(df['rain1h'] < 9999)
+    # 分组、聚合、排序
+    df_rain_sum_data = (df_rain_data.groupBy("city_index", "city_name")
+        .agg(functions.sum("rain1h").alias("rain24h"))
+        .sort(functions.desc("rain24h")))
+    df_rain_sum_data.cache()
+    print("处理完成，保存数据到数据库")
+    df_rain_sum_data.coalesce(1).write.jdbc(mysql_jdbc_uri, "rain_24h_analyse", "ignore", mysql_jdbc_prop)
+    print("各个城市过去24小时累积雨量计算完毕")
+    return df_rain_sum_data.head(20)
+
+
+if __name__ == "__main__":
+    rain_24h_analyse()
diff --git a/spark/tem_2024_analyse.py b/spark/tem_2024_analyse.py
new file mode 100644
index 0000000..4ae80ca
--- /dev/null
+++ b/spark/tem_2024_analyse.py
@@ -0,0 +1,40 @@
+from pyspark.sql.types import IntegerType
+from pyspark.sql import functions
+
+from client import spark_app
+from data.data import data_day_hdfs, mysql_jdbc_uri, mysql_jdbc_prop
+
+
+def tem_2024_analyse():
+    print("计算重庆市各个区县 2024 年 每天的 最高气温，最低气温，平均气温")
+    app = spark_app("tem_2024_analyse")
+    print("创建应用完成，开始读取数据")
+    df = app.read.csv(data_day_hdfs, header=True)
+    print("读取数据完成，开始处理数据")
+    # 取出数据
+    df_rain_data = df.select(
+        df['city'], df['date'], df['hmax'].cast(IntegerType()), df['hmin'].cast(IntegerType())
+    )
+    # 求平均
+    df_rain_data = df_rain_data.withColumn("havg", (functions.col("hmax") + functions.col("hmin")) / 2)
+    # 转换 'date' 列的日期格式
+    df_rain_data = df_rain_data.withColumn(
+        'date',
+         functions.date_format(functions.from_unixtime(
+             functions.unix_timestamp('date', 'yyyyMMdd')), 'yyyyMM').cast(IntegerType())
+    )
+    # 分组、聚合
+    df_rain_data = (df_rain_data.groupBy("city", "date")
+        .agg(functions.max("hmax").alias("hmax"),
+             functions.min("hmin").alias("hmin"),
+             functions.round(functions.avg("havg"), 2).alias("havg"))
+        .sort("city", df_rain_data.date.desc()))
+    df_rain_data.cache()
+    print("处理完成，保存数据到数据库")
+    df_rain_data.coalesce(1).write.jdbc(mysql_jdbc_uri, "tem_2024_analyse", "ignore", mysql_jdbc_prop)
+    print("各个区县 2024 年 每天的 最高气温，最低气温，平均气温计算完毕")
+    return df_rain_data.head(20)
+
+
+if __name__ == "__main__":
+    tem_2024_analyse()