我有两个表,需要分别对表名和文件名应用join。问题是与表2中的文件名相比,表名有一些额外的字符串。
使用正则表达式,如何从表\u name中删除额外的字符串以使其与表2的文件\u name兼容?
TABLE 1:
table_name audit_record_count
Immunology_COVID-19_Treatment_202006221630_01.csv 1260124
Immunology_COVID-19_Trial_Design_202006221630_01.csv 2173762
Immunology_COVID-19_Planned_Treatment_202006221630_01.csv 1350135
Immunology_COVID-19_Patient_Characteristic_202006221630_01.csv 2173762
Immunology_COVID-19_Intervention_Type_202006221630_01.csv 2173762
Immunology_COVID-19_Arm_202006221630_01.csv 4
Immunology_COVID-19_Actual_Treatment_202006221630_01.csv 2173762
Immunology_COVID-19_Publication_202006221630_01.csv 2173762
Immunology_COVID-19_Outcome_202006221630_01.csv 2173762
Immunology_COVID-19_Intervention_Type_Factor_202006221630_01.csv 2173762
Immunology_COVID-19_Inclusion_Criteria_202006221630_01.csv 2173762
Immunology_COVID-19_Curation_202006221630_01.csv 2173762
TABLE 2:
file_name csv_record_count
Treatment 1260124
Trial_Design 2173762
Planned_Treatment 1350135
Patient_Characteristic 2173762
Intervention_Type 2173762
Arm 4
Actual_Treatment 2173762
Publication 2173762
Outcome 2173762
Intervention_Type_Factor 2173762
Inclusion_Criteria 2173762
Curation 2173762
我尝试过:
audit_file_df = spark.read.csv(
f"s3://{config['raw_bucket']}/{config['landing_directory']}/{config['audit_file']}/{watermark_timestamp}*.csv",
header=False, inferSchema=True) \
.withColumnRenamed("_c0", "table_name").withColumnRenamed("_c1", "audit_record_count")\
.selectExpr("regexp_extract(table_name, '^(.(?!(\\\\d{12}_\\\\d{2,4}.csv|\\\\d{12}.csv)))*', 0) AS table_name",'audit_record_count')
print("audit_file_df :",audit_file_df)
audit_file_df.show()
validation_df = audit_file_df.join(schema_validation_df, how='inner', on=audit_file_df['table_name'] == schema_validation_df['file_name']).withColumn("count_match",
col=col(
'audit_record_count') == col(
'csv_record_count'))
print("Record validation result")
validation_df.show()
我可以从表\u name中删除时间戳,但无法提取文件\u name以使连接条件工作。
加法
免疫学\u covid-19未修复它可能会更改为另一个文件,表\u name的格式为:
TA_Indication_data_timestamp_nn.csv
1条答案
按热度按时间rqenqsqc1#
在表1中创建一个包含
data
零件:给予
然后可以使用
table1.data
以及table2.file_name
继续你在问题中已经给出的审计检查。regexp的棘手部分是使用非贪婪限定符,例如
data
部件本身可以包含下划线字符。