1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
import os
import sys
import re
import numpy as np
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 StringType, FloatType, StructType, StructField
from pyspark.sql.window import Window
class DimAsinWeightInfo(Templates):
def __init__(self, site_name='us'):
super().__init__()
self.site_name = site_name
# 初始化self.spark对
self.db_save = 'dim_asin_weight_info'
self.spark = self.create_spark_object(
app_name=f"{self.db_save}: {self.site_name}, {self.date_type}, {self.date_info}")
self.df_asin_weight = self.spark.sql("select 1+1;")
self.df_asin_weight_old = self.spark.sql("select 1+1;")
self.df_save = self.spark.sql("select 1+1;")
schema = StructType([
StructField('weight', FloatType(), True),
StructField('weight_type', StringType(), True),
])
self.u_get_weight = F.udf(self.udf_get_weight, schema)
# 分区参数
self.partitions_by = ['site_name']
self.partitions_num = 20
# 重量类型: 2023-18之前
self.weight_type = 'pounds' if site_name == 'us' else 'grams'
@staticmethod
def udf_get_weight(weight_str, site_name):
if weight_str is None:
# Return some default value or raise an exception.
return (None, None)
weight_type = 'pounds' if site_name == 'us' else 'grams'
if 'pounds' in weight_str:
match = re.search(r"(\d+\.{0,}\d{0,})\D{0,}pounds", weight_str)
val = round(float(match.group(1)), 3) if site_name == 'us' and match else round(
float(match.group(1)) * 1000 * 0.454, 3) if match else np.nan
elif 'ounces' in weight_str:
match = re.search(r"(\d+\.{0,}\d{0,})\D{0,}ounces", weight_str)
val = round(float(match.group(1)) / 16, 3) if site_name == 'us' and match else round(
float(match.group(1)) / 16 * 1000 * 0.454, 3) if match else np.nan
# elif 'kilograms' in weight_str or ' kilogramos' in weight_str:
elif any(substring in weight_str for substring in ['kilogram', ' kg']):
weight_str = weight_str.replace(' kg', ' kilogram')
match = re.search(r"(\d+\.{0,}\d{0,})\D{0,}kilogram", weight_str)
val = round(float(match.group(1)) / 0.454, 3) if site_name == 'us' and match else round(
float(match.group(1)) * 1000, 3) if match else np.nan
# elif 'milligrams' in weight_str:
elif any(substring in weight_str for substring in ['milligrams']):
match = re.search(r"(\d+\.{0,}\d{0,})\D{0,}milligrams", weight_str)
val = round(float(match.group(1)) / 1000 / 1000 / 0.454, 3) if site_name == 'us' and match else round(
float(match.group(1)) / 1000, 3) if match else np.nan
elif ' gram' in weight_str:
match = re.search(r"(\d+\.{0,}\d{0,})\D{0,} gram", weight_str)
val = round(float(match.group(1)) / 1000 / 0.454, 3) if site_name == 'us' and match else round(
float(match.group(1)), 3) if match else np.nan
elif ' g' in weight_str:
match = re.search(r"(\d+\.{0,}\d{0,})\D{0,} g", weight_str)
# val = round(float(match.group(1)) / 1000 / 0.454, 3) if site_name == 'us' else round(float(match.group(1)), 3) if match else np.nan
val = round(float(match.group(1)) / 1000 / 0.454, 3) if site_name == 'us' and match else round(
float(match.group(1)), 3) if match else np.nan
else:
val = 'none'
weight_type = 'none'
# val = val * 1000 * 0.454 if site_name != 'us' and val != 'none' else val
weight = val
return (weight, weight_type)
def read_data(self):
# sql = f"select asin, weight, weight_str, date_info from ods_asin_detail where site_name='{self.site_name}' and date_type='week'" # and date_info>='2023-25'
sql = f"select asin, weight, weight_str, site_name, date_info from ods_asin_detail where site_name='{self.site_name}' and date_type='week' and date_info>='2023-18' and weight_str is not null" # and date_info>='2023-25'
print("sql:", sql)
self.df_asin_weight = self.spark.sql(sqlQuery=sql).cache()
self.df_asin_weight.show(10, truncate=False)
sql = f"select asin, weight, weight_str, site_name, date_info, '{self.weight_type}' as weight_type from ods_asin_detail where site_name='{self.site_name}' and date_type='week' and date_info<='2023-17' and weight is not null" # and date_info>='2023-25'
print("sql:", sql)
self.df_asin_weight_old = self.spark.sql(sqlQuery=sql).cache()
self.df_asin_weight_old.show(10, truncate=False)
def handle_asin_weight(self):
print("开始处理重量数据: 2023-18周之后")
# 将列类型转为字符串并转为小写
self.df_asin_weight = self.df_asin_weight.withColumn("weight_str",
F.lower(F.col("weight_str").cast(StringType())))
# 对weight_str列应用自定义函数get_weight
# get_weight_udf = F.udf(lambda x: get_weight(x, self.site_name), StringType())
# self.df_asin_weight = self.df_asin_weight.withColumn("weight_info", get_weight_udf(F.col("weight_str")))
# 分割weight_info列
# split_col = F.split(self.df_asin_weight['weight_info'], ',')
# self.df_asin_weight = self.df_asin_weight.withColumn('weight', split_col.getItem(0))
# self.df_asin_weight = self.df_asin_weight.withColumn('weight_type', split_col.getItem(1))
# 提取体积字符串中的weight_info, weight_type
self.df_asin_weight = self.df_asin_weight.withColumn('weight_detail',
self.u_get_weight('weight_str', 'site_name'))
self.df_asin_weight = self.df_asin_weight \
.withColumn('weight', self.df_asin_weight.weight_detail.getField('weight')) \
.withColumn('weight_type', self.df_asin_weight.weight_detail.getField('weight_type')) \
.drop('weight_detail')
# 将weight列中的'none'转为null，并转为浮点数类型
self.df_asin_weight = self.df_asin_weight.withColumn("weight",
F.when(F.col("weight") == 'none', None).otherwise(
F.col("weight").cast(FloatType())))
# weight列中小于等于0.001的值设为0.001
self.df_asin_weight = self.df_asin_weight.withColumn("weight",
F.when(F.col("weight") <= 0.001, 0.001).otherwise(
F.col("weight")))
# 将weight_str列中的'none'转为null
self.df_asin_weight = self.df_asin_weight.withColumn("weight_str", F.when(F.col("weight_str") == 'none', None).otherwise(F.col("weight_str")))
# 移除weight_info列
# self.df_asin_weight = self.df_asin_weight.drop('weight_info')
# 添加新列date_info
# self.df_asin_weight = self.df_asin_weight.withColumn('date_info', F.lit(f'{self.year}-{self.week}'))
# self.df_asin_weight.show(20, truncate=False)
def handle_asin_weight_old(self):
print("开始处理重量数据: 2023-18周之前")
window = Window.partitionBy(['asin']).orderBy(self.df_asin_weight_old.date_info.desc())
self.df_asin_weight_old = self.df_asin_weight_old.withColumn(
"row_number", F.row_number().over(window)
)
self.df_asin_weight_old = self.df_asin_weight_old.withColumn('row_number', F.row_number().over(window)) # 使用窗口函数为每个分区的行编号
self.df_asin_weight_old = self.df_asin_weight_old.filter(self.df_asin_weight_old.row_number == 1).drop('row_number') # 只保留每个分区中 row_number 最大的行，并删除 row_number 列
# self.df_asin_weight_old.show(20, truncate=False)
def handle_data(self):
self.handle_asin_weight()
self.handle_asin_weight_old()
print("self.df_asin_weight.columns:", self.df_asin_weight.columns)
print("self.df_asin_weight_old.columns:", self.df_asin_weight_old.columns)
self.df_save = self.df_asin_weight.unionByName(self.df_asin_weight_old, allowMissingColumns=True)
window = Window.partitionBy(['asin']).orderBy(
self.df_save.date_info.desc(),
)
self.df_save = self.df_save.withColumn(
"row_number", F.row_number().over(window)
)
self.df_save = self.df_save.withColumn('row_number', F.row_number().over(window)) # 使用窗口函数为每个分区的行编号
self.df_save = self.df_save.filter(self.df_save.row_number == 1).drop('row_number') # 只保留每个分区中 row_number 最大的行，并删除 row_number 列
self.df_save = self.df_save.withColumn("weight", F.round(self.df_save["weight"], 4))
# self.df_save.show(20, truncate=False)
self.df_save = self.df_save.withColumnRenamed(
"weight_str", "asin_weight_str"
).withColumnRenamed(
"weight", "asin_weight"
).withColumnRenamed(
"weight_type", "asin_weight_type"
)
if __name__ == '__main__':
site_name = sys.argv[1] # 参数1：站点
handle_obj = DimAsinWeightInfo(site_name=site_name)
handle_obj.run()