dwt_merchantwords_merge.py

import os
import sys


sys.path.append(os.path.dirname(sys.path[0]))  # 上级目录
from utils.templates import Templates
from pyspark.sql import functions as F
from pyspark.sql.window import Window
from utils.hdfs_utils import HdfsUtils
from utils.spark_util import SparkUtil
from pyspark.storagelevel import StorageLevel


class DwtMerchantwordsMerge(Templates):

    def __init__(self, site_name='us', batch='2024-00-00'):
        super().__init__()
        self.site_name = site_name
        self.batch = batch
        self.db_save = 'dwt_merchantwords_merge'
        self.spark = self.create_spark_object(app_name=f"DwtMerchantwordsMerge: {self.site_name}, {self.batch}")
        self.partitions_num = 120
        self.partitions_by = ['site_name', 'batch']
        self.df_partition = self.spark.sql(f"select 1+1;")
        self.df_save = self.spark.sql(f"select 1+1;")
        hdfs_path = f"/home/{SparkUtil.DEF_USE_DB}/dwt/{self.db_save}/site_name={self.site_name}/batch={self.batch}"
        print(f"清除hdfs目录中.....{hdfs_path}")
        HdfsUtils.delete_hdfs_file(hdfs_path)

    def read_data(self):
        print("读取dwd_merchantwords_measure_v2的分区数据")
        sql = f"""
        select 
            keyword,
            lang,
            st_ao_val,
            st_zr_flow_proportion,
            volume,
            avg_3m,
            avg_12m,
            asin_total_num,
            asin_num,
            self_asin_num,
            self_asin_proportion,
            st_sp_counts,
            st_zr_counts,
            st_monthly_sales,
            listing_sales_avg,
            reviews_avg,
            rating_avg,
            price_avg,
            depth,
            results_count,
            sponsored_ads_count,
            page_1_reviews,
            appearance,
            last_seen,
            update_time,
            last_batch,
            package_quantity,
            batch as measure_batch
        from dwd_merchantwords_measure_v2 
        where site_name = '{self.site_name}';
        """
        self.df_partition = self.spark.sql(sqlQuery=sql)
        self.df_partition = self.df_partition.repartition(80).persist(StorageLevel.MEMORY_ONLY)
        self.df_partition.show(10, truncate=True)

    def handle_data(self):
        window = Window.partitionBy('keyword').orderBy(
            F.desc_nulls_last('measure_batch')
        )
        self.df_partition = self.df_partition.withColumn("u_rank", F.row_number().over(window=window))
        self.df_partition = self.df_partition.filter('u_rank=1').drop('u_rank')
        self.df_partition = self.df_partition.filter('asin_num>0')
        self.df_save = self.df_partition.withColumn(
            'volume',
            F.when(F.col('last_batch') == '2023-1', 0)
                .otherwise(F.col('volume'))
        ).withColumn(
            'asin_total_num',
            F.greatest('asin_total_num', 'results_count')
        ).withColumn(
            'site_name',
            F.lit(self.site_name)
        ).withColumn(
            'batch',
            F.lit(self.batch)
        )


if __name__ == '__main__':
    site_name = sys.argv[1]
    batch = sys.argv[2]
    handle_obj = DwtMerchantwordsMerge(site_name=site_name, batch=batch)
    handle_obj.run()