[oalex] change to add a thread to monitor the number of operations done by affro up to a certain point

strings.py

@@ -1,11 +1,11 @@
-import json
+import time
 
 from pyspark.sql.types import StringType, ArrayType, StructType, StructField, DoubleType
-
+from threading import Thread
 from affro_cluster import *
 
 from pyspark.sql import SparkSession
-from pyspark.sql.functions import col, explode, first, collect_set, udf
+from pyspark.sql.functions import col, explode, first, collect_list, udf, collect_set
 import sys
 
 spark = SparkSession.builder.appName("JSONProcessing").getOrCreate()
@@ -23,10 +23,14 @@ matchings_schema = ArrayType(
     ])
 )
 
-def oalex_affro_2(aff_string):
+operation_counter = spark.sparkContext.accumulator(0)
+
+#Version of affro application on a single raw_aff_string and returns just the Matchins set
+def oalex_affro(aff_string):
+    global operation_counter
     try:
         matchings = affro(aff_string)
-
+        operation_counter += 1
         # Ensure matchings is a list, even if affro returns a single dict
         if not isinstance(matchings, list):
             matchings = [matchings]
@@ -49,18 +53,15 @@ def oalex_affro_2(aff_string):
         print(f"Error processing affiliation string {aff_string}: {str(e)}")
         return ()
 
-#Version of affro application on a single raw_aff_string and returns just the Matchins set
-def oalex_affro(aff_string):
-    try:
-        matchings = affro(aff_string)
-        if not isinstance(matchings, list):
-            matchings = [matchings]
-        return matchings
-    except Exception as e:
-        print(f"Error processing affiliation string {aff_string}: {str(e)}")
-        return []
+oalex_affro_udf = udf(oalex_affro, matchings_schema)
+monitor_done = False
 
-oalex_affro_udf = udf(oalex_affro_2, matchings_schema)
+def monitor_counter(interval):
+    while True:
+        print(f"Number of calls to AffRo: {operation_counter.value}")
+        time.sleep(interval)
+        if monitor_done:
+            break
 
 exploded = spark.read.json(folder_path) \
     .filter(col("doi").isNotNull()) \
@@ -69,6 +70,10 @@ exploded = spark.read.json(folder_path) \
     col("rors").alias("OAlex"),
     explode(col("raw_aff_string")).alias("affiliation") #this allows to split all the raw_aff_string and to parallelize better
 )
+
+monitor_thread = Thread(target=monitor_counter, args=(600,), daemon=True)
+monitor_thread.start()
+
 affs = exploded \
     .select("affiliation") \
     .distinct() \
@@ -87,3 +92,6 @@ affs.join(exploded, on="affiliation") \
     .mode("overwrite") \
     .option("compression","gzip") \
     .json(hdfs_output_path)
+
+monitor_done = True
+monitor_thread.join()