rename 'idf' files to 'tfidf'

[cdsc_reddit.git] / tfidf_authors.py

diff --git a/tfidf_authors.py b/tfidf_authors.py
new file mode 100644 (file)
index 0000000..92a4965
--- /dev/null
+++ b/tfidf_authors.py
@@ -0,0 +1,43 @@
+from pyspark.sql import functions as f
+from pyspark.sql import SparkSession
+
+spark = SparkSession.builder.getOrCreate()
+df = spark.read.parquet("/gscratch/comdata/users/nathante/reddit_tfidf_test_authors.parquet_temp/")
+
+max_subreddit_week_authors = df.groupby(['subreddit','week']).max('tf')
+max_subreddit_week_authors = max_subreddit_week_authors.withColumnRenamed('max(tf)','sr_week_max_tf')
+
+df = df.join(max_subreddit_week_authors, ['subreddit','week'])
+
+df = df.withColumn("relative_tf", df.tf / df.sr_week_max_tf)
+
+# group by term / week
+idf = df.groupby(['author','week']).count()
+
+idf = idf.withColumnRenamed('count','idf')
+
+# output: term | week | df
+#idf.write.parquet("/gscratch/comdata/users/nathante/reddit_tfidf_test_sorted_tf.parquet_temp",mode='overwrite',compression='snappy')
+
+# collect the dictionary to make a pydict of terms to indexes
+authors = idf.select('author').distinct()
+authors = authors.withColumn('author_id',f.monotonically_increasing_id())
+
+
+# map terms to indexes in the tfs and the idfs
+df = df.join(authors,on='author')
+
+idf = idf.join(authors,on='author')
+
+# join on subreddit/term/week to create tf/dfs indexed by term
+df = df.join(idf, on=['author_id','week','author'])
+
+# agg terms by subreddit to make sparse tf/df vectors
+df = df.withColumn("tf_idf",df.relative_tf / df.sr_week_max_tf)
+ 
+df = df.groupby(['subreddit','week']).agg(f.collect_list(f.struct('author_id','tf_idf')).alias('tfidf_maps'))
+ 
+df = df.withColumn('tfidf_vec', f.map_from_entries('tfidf_maps'))
+
+# output: subreddit | week | tf/df
+df.write.json('/gscratch/comdata/users/nathante/test_tfidf_authors.parquet',mode='overwrite',compression='snappy')