62 lines
2.3 KiB
Python
62 lines
2.3 KiB
Python
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from pyspark.sql import functions as f
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from pyspark.sql import SparkSession
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from pyspark.sql import Window
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from pyspark.mllib.linalg.distributed import RowMatrix, CoordinateMatrix
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import numpy as np
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import pyarrow
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import pandas as pd
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import fire
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from itertools import islice
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from pathlib import Path
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from similarities_helper import prep_tfidf_entries, read_tfidf_matrix, column_similarities, select_topN
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import scipy
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# outfile='test_similarities_500.feather';
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# min_df = None;
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# included_subreddits=None; topN=100; exclude_phrases=True;
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def term_cosine_similarities(outfile, min_df = None, included_subreddits=None, topN=500, exclude_phrases=False):
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spark = SparkSession.builder.getOrCreate()
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conf = spark.sparkContext.getConf()
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print(outfile)
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print(exclude_phrases)
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tfidf = spark.read.parquet('/gscratch/comdata/output/reddit_similarity/tfidf/subreddit_terms.parquet')
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if included_subreddits is None:
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included_subreddits = select_topN_subreddits(topN)
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else:
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included_subreddits = set(open(included_subreddits))
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if exclude_phrases == True:
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tfidf = tfidf.filter(~f.col(term).contains("_"))
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print("creating temporary parquet with matrix indicies")
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tempdir = prep_tfidf_entries(tfidf, 'term', min_df, included_subreddits)
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tfidf = spark.read.parquet(tempdir.name)
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subreddit_names = tfidf.select(['subreddit','subreddit_id_new']).distinct().toPandas()
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subreddit_names = subreddit_names.sort_values("subreddit_id_new")
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subreddit_names['subreddit_id_new'] = subreddit_names['subreddit_id_new'] - 1
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spark.stop()
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print("loading matrix")
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mat = read_tfidf_matrix(tempdir.name,'term')
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print('computing similarities')
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sims = column_similarities(mat)
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del mat
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sims = pd.DataFrame(sims.todense())
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sims = sims.rename({i:sr for i, sr in enumerate(subreddit_names.subreddit.values)},axis=1)
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sims['subreddit'] = subreddit_names.subreddit.values
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p = Path(outfile)
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output_feather = Path(str(p).replace("".join(p.suffixes), ".feather"))
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output_csv = Path(str(p).replace("".join(p.suffixes), ".csv"))
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output_parquet = Path(str(p).replace("".join(p.suffixes), ".parquet"))
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sims.to_feather(outfile)
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tempdir.cleanup()
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if __name__ == '__main__':
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fire.Fire(term_cosine_similarities)
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