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Produce additional bip update specific files

This commit is contained in:
Ilias Kanellos 2023-07-21 17:42:46 +03:00
parent 0f96af5d56
commit 2374f445a9
1 changed files with 15 additions and 0 deletions
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15
dhp-workflows/dhp-impact-indicators/src/main/resources/eu/dnetlib/dhp/oa/graph/impact_indicators/oozie_app/map_scores_to_dois.py
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@ -15,6 +15,8 @@ from pyspark.sql.types import *
# Import sql functions with shorthand alias
import pyspark.sql.functions as F
from pyspark.sql.functions import max
# from pyspark.sql.functions import udf
#################################################################################################
#################################################################################################
@ -128,6 +130,10 @@ for offset, input_file in enumerate(input_file_list):
# Load file to dataframe
ranking_df = spark.read.schema(schema).option('delimiter', '\t').csv(input_file).repartition(num_partitions, 'id')
# Get max score
max_score = ranking_df.select(max('score').alias('max')).collect()[0]['max']
print ("Max Score for " + str(input_file) + " is " + str(max_score))
# TESTING
# print ("Loaded df sample:")
# ranking_df.show(1000, False)
@ -138,6 +144,15 @@ for offset, input_file in enumerate(input_file_list):
output_file = output_file_list[offset]
print ("Writing to: " + output_file)
doi_score_df.write.mode('overwrite').option('delimiter','\t').option('header',False).csv(output_file, compression='gzip')
# Creata another file for the bip update process
ranking_df = ranking_df.select('id', 'score', F.lit(F.col('score')/max_score).alias('normalized_score'), 'class', F.col('class').alias('class_dup'))
doi_score_df = synonym_df.join(ranking_df, ['id']).select('doi', 'score', 'normalized_score', 'class', 'class_dup').repartition(num_partitions, 'doi').cache()
output_file = output_file.replace(".txt.gz", "_for_bip_update.txt.gz")
print ("Writing bip update to: " + output_file)
doi_score_df.write.mode('overwrite').option('delimiter','\t').option('header',False).csv(output_file, compression='gzip')
# Free memory?
ranking_df.unpersist(True)