collective/cdsc_reddit
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Finish generating multiword expressions.

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This commit is contained in:
Nate E TeBlunthuis 2020-08-09 22:42:23 -07:00
parent 529b7f0511
commit 57951050c0
1 changed files with 21 additions and 8 deletions
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29
top_comment_phrases.py
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@ -8,18 +8,19 @@ df = spark.read.text("/gscratch/comdata/users/nathante/reddit_comment_ngrams_10p
df = df.withColumnRenamed("value","phrase") df = df.withColumnRenamed("value","phrase")
# count overall
N = df.count()
print(f'analyzing PMI on a sample of {N} phrases')
logN = np.log(N)
# count phrase occurrances # count phrase occurrances
phrases = df.groupby('phrase').count() phrases = df.groupby('phrase').count()
phrases = phrases.withColumnRenamed('count','phraseCount') phrases = phrases.withColumnRenamed('count','phraseCount')
phrases = phrases.withColumn("phraseLogProb", f.log(f.col("phraseCount")) - logN) phrases = phrases.filter(phrases.phraseCount > 10)
# count overall
N = phrases.select(f.sum(phrases.phraseCount).alias("phraseCount")).collect()[0].phraseCount
print(f'analyzing PMI on a sample of {N} phrases')
logN = np.log(N)
phrases = phrases.withColumn("phraseLogProb", f.log(f.col("phraseCount")) - logN)
# count term occurrances # count term occurrances
phrases = phrases.withColumn('terms',f.split(f.col('phrase'),' ')) phrases = phrases.withColumn('terms',f.split(f.col('phrase'),' '))
terms = phrases.select(['phrase','phraseCount','phraseLogProb',f.explode(phrases.terms).alias('term')]) terms = phrases.select(['phrase','phraseCount','phraseLogProb',f.explode(phrases.terms).alias('term')])
@ -38,8 +39,20 @@ terms = terms.withColumn("phrasePWMI", f.col('phraseLogProb') - f.col('termsLogP
df = terms.select(['phrase','phraseCount','phraseLogProb','phrasePWMI']) df = terms.select(['phrase','phraseCount','phraseLogProb','phrasePWMI'])
df = df.repartition('phrasePWMI')
df = df.sort(['phrasePWMI'],descending=True) df = df.sort(['phrasePWMI'],descending=True)
df = df.sortWithinPartitions(['phrasePWMI'],descending=True) df = df.sortWithinPartitions(['phrasePWMI'],descending=True)
df.write.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet/",mode='overwrite',compression='snappy') df.write.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet/",mode='overwrite',compression='snappy')
df = spark.read.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet/")
df.write.csv("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.csv/",mode='overwrite',compression='none') df.write.csv("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.csv/",mode='overwrite',compression='none')
df = spark.read.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet")
df = df.select('phrase','phraseCount','phraseLogProb','phrasePWMI')
# choosing phrases occurring at least 3500 times in the 10% sample (35000 times) and then with a PWMI of at least 3 yeids about 65000 expressions.
#
df = df.filter(f.col('phraseCount') > 3500).filter(f.col("phrasePWMI")>3)
df = df.toPandas()
df.to_feather("/gscratch/comdata/users/nathante/reddit_multiword_expressions.feather")
df.to_csv("/gscratch/comdata/users/nathante/reddit_multiword_expressions.csv")