18 lines
1.1 KiB
Python
18 lines
1.1 KiB
Python
import pyarrow.dataset as ds
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import pyarrow as pa
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# A pyarrow dataset abstracts reading, writing, or filtering a parquet file. It does not read dataa into memory.
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#dataset = ds.dataset(pathlib.Path('/gscratch/comdata/output/reddit_submissions_by_subreddit.parquet/'), format='parquet', partitioning='hive')
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dataset = ds.dataset('/gscratch/comdata/output/reddit_submissions_by_subreddit.parquet/', format='parquet', partitioning='hive')
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# let's get all the comments to two subreddits:
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subreddits_to_pull = ['seattle','seattlewa']
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# a table is a low-level structured data format. This line pulls data into memory. Setting metadata_n_threads > 1 gives a little speed boost.
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table = dataset.to_table(filter = ds.field('subreddit').isin(subreddits_to_pull), columns=['id','subreddit','CreatedAt','author','ups','downs','score','subreddit_id','stickied','title','url','is_self','selftext'])
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# Since data from just these 2 subreddits fits in memory we can just turn our table into a pandas dataframe.
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df = table.to_pandas()
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# We should save this smaller dataset so we don't have to wait 15 min to pull from parquet next time.
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df.to_csv("mydataset.csv")
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