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import os
import sys
from pyspark.sql.window import Window
sys.path.append(os.path.dirname(sys.path[0])) # 上级目录
from pyspark.storagelevel import StorageLevel
from utils.templates import Templates
# from ..utils.templates import Templates
from pyspark.sql import functions as F
class DwdStMeasure(Templates):
def __init__(self, site_name='us', date_type="month", date_info='2022-01'):
super().__init__()
self.site_name = site_name
self.date_type = date_type
self.date_info = date_info
self.db_save = f'dwd_st_rank'
self.spark = self.create_spark_object(
app_name=f"{self.db_save}: {self.site_name}, {self.date_type}, {self.date_info}")
# self.df_date = self.get_year_week_tuple() # pandas的df对象
self.df_st_month = self.spark.sql(f"select 1+1;")
self.df_st_week = self.spark.sql(f"select 1+1;")
def read_data(self):
sql_month = f"SELECT search_term, st_brand_label from dwt_aba_st_analytics WHERE site_name ='us' and date_type ='month' and date_info BETWEEN '2023-04' and '2023-09';"
self.df_st_month = self.spark.sql(sql_month).cache()
self.df_st_month.show(20, truncate=False)
print("month:", self.df_st_month.count())
sql_week = f"SELECT search_term, st_brand_label from dwt_aba_st_analytics WHERE site_name ='us' and date_type ='week' and date_info BETWEEN '2023-14' and '2023-39';"
self.df_st_week = self.spark.sql(sql_week).cache()
self.df_st_week.show(20, truncate=False)
print("week:", self.df_st_week.count())
def handle_data(self):
# 合并两个DataFrame
df_combined = self.df_st_month.union(self.df_st_week)
# 定义开窗函数
windowSpec = Window.partitionBy("search_term").orderBy(F.desc("st_brand_label"))
# 使用 row_number 生成每个分区的行号
df_combined = df_combined.withColumn("row_number", F.row_number().over(windowSpec))
# 只选择 row_number 为 1 的行
df_unique = df_combined.filter(df_combined.row_number == 1).drop("row_number")
self.df_combined_unique = df_unique
self.df_combined_unique.show(20, truncate=False)
print("combined:", self.df_combined_unique.count())
def save_data(self):
# 转换为 Pandas DataFrame
pdf = self.df_combined_unique.toPandas()
# 根据需求将每100万行数据保存为一个CSV文件
num_rows_per_file = 1000000
num_files = (len(pdf) // num_rows_per_file) + (1 if len(pdf) % num_rows_per_file != 0 else 0)
for i in range(num_files):
start_idx = i * num_rows_per_file
end_idx = start_idx + num_rows_per_file
output_path = os.path.join("/root", f"output_{i + 1}.csv")
# 将子集保存为CSV
pdf.iloc[start_idx:end_idx].to_csv(output_path, index=False)
print(f"Data saved into {num_files} CSV files.")
if __name__ == '__main__':
handle_obj = DwdStMeasure()
handle_obj.run()