46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
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from pyspark.sql import functions as f
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from pyspark.sql import Window
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from pyspark.sql import SparkSession
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import numpy as np
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spark = SparkSession.builder.getOrCreate()
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df = spark.read.text("/gscratch/comdata/users/nathante/reddit_comment_ngrams_10p_sample/")
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df = df.withColumnRenamed("value","phrase")
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# count overall
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N = df.count()
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print(f'analyzing PMI on a sample of {N} phrases')
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logN = np.log(N)
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# count phrase occurrances
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phrases = df.groupby('phrase').count()
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phrases = phrases.withColumnRenamed('count','phraseCount')
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phrases = phrases.withColumn("phraseLogProb", f.log(f.col("phraseCount")) - logN)
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# count term occurrances
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phrases = phrases.withColumn('terms',f.split(f.col('phrase'),' '))
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terms = phrases.select(['phrase','phraseCount','phraseLogProb',f.explode(phrases.terms).alias('term')])
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win = Window.partitionBy('term')
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terms = terms.withColumn('termCount',f.sum('phraseCount').over(win))
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terms = terms.withColumnRenamed('count','termCount')
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terms = terms.withColumn('termLogProb',f.log(f.col('termCount')) - logN)
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terms = terms.groupBy(terms.phrase, terms.phraseLogProb, terms.phraseCount).sum('termLogProb')
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terms = terms.withColumnRenamed('sum(termLogProb)','termsLogProb')
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terms = terms.withColumn("phrasePWMI", f.col('phraseLogProb') - f.col('termsLogProb'))
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# join phrases to term counts
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df = terms.select(['phrase','phraseCount','phraseLogProb','phrasePWMI'])
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df = df.repartition('phrasePWMI')
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df = df.sort(['phrasePWMI'],descending=True)
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df = df.sortWithinPartitions(['phrasePWMI'],descending=True)
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df.write.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet/",mode='overwrite',compression='snappy')
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df.write.csv("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.csv/",mode='overwrite',compression='none')
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