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import ast
import os
import sys
import pandas as pd
os.environ["PYARROW_IGNORE_TIMEZONE"] = "1"
sys.path.append(os.path.dirname(sys.path[0])) # 上级目录
from utils.templates import Templates
# from ..utils.templates import Templates
from pyspark.sql import functions as F
from pyspark.sql.types import ArrayType, FloatType
class PicturesDimFeaturesSlice(Templates):
def __init__(self, site_name='us'):
super(PicturesDimFeaturesSlice, self).__init__()
self.site_name = site_name
self.db_save = f'pictures_dim_features_slice'
self.spark = self.create_spark_object(
app_name=f"{self.db_save}: {self.site_name}")
self.df_asin_features = self.spark.sql(f"select 1+1;")
self.df_save = self.spark.sql(f"select 1+1;")
# self.partitions_by = ['site_name', 'block']
self.partitions_by = ['site_name']
self.partitions_num = 1000
def read_data(self):
# sql = f"select id, asin, img_vector as embedding from ods_asin_extract_features;"
sql = f"select id, asin, features as embedding from pictures_ods_features;"
print("sql:", sql)
self.df_save = self.spark.sql(sql).cache()
self.df_save.show(10)
# 由于不需要在这一步生成array类型
# partitions_num = self.df_asin_features.rdd.getNumPartitions()
# print("分区数量:", partitions_num) # 642
# # self.partitions_num = 1000
# self.df_save = self.df_save.repartition(self.partitions_num)
# print("重置分区数量:", self.partitions_num) # 642
def handle_data(self):
# 定义一个将字符串转换为列表的UDF
# str_to_list_udf = F.udf(lambda s: ast.literal_eval(s), ArrayType(FloatType()))
# # 对DataFrame中的列应用这个UDF
# self.df_save = self.df_save.withColumn("embedding", str_to_list_udf(self.df_save["embedding"]))
self.df_save = self.df_save.withColumn('site_name', F.lit(self.site_name))
if __name__ == '__main__':
site_name = sys.argv[1] # 参数1：站点
handle_obj = PicturesDimFeaturesSlice(site_name=site_name)
handle_obj.run()