110 lines
3.9 KiB
Python
Executable File
110 lines
3.9 KiB
Python
Executable File
#!/usr/bin/env python3
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# two stages:
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# 1. from gz to arrow parquet (this script)
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# 2. from arrow parquet to spark parquet (submissions_2_parquet_part2.py)
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import json
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from datetime import datetime
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from multiprocessing import Pool
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from itertools import islice
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from helper import find_dumps, open_fileset
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import pandas as pd
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import pyarrow as pa
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import pyarrow.parquet as pq
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def parse_submission(post, names = None):
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if names is None:
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names = ['id','author','subreddit','title','created_utc','permalink','url','domain','score','ups','downs','over_18','has_media','selftext','retrieved_on','num_comments','gilded','edited','time_edited','subreddit_type','subreddit_id','subreddit_subscribers','name','is_self','stickied','quarantine','error']
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try:
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post = json.loads(post)
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except (json.decoder.JSONDecodeError, UnicodeDecodeError) as e:
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# print(e)
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# print(post)
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row = [None for _ in names]
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row[-1] = "json.decoder.JSONDecodeError|{0}|{1}".format(e,post)
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return tuple(row)
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row = []
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for name in names:
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if name == 'created_utc' or name == 'retrieved_on':
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val = post.get(name,None)
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if val is not None:
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row.append(datetime.fromtimestamp(int(post[name]),tz=None))
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else:
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row.append(None)
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elif name == 'edited':
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val = post[name]
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if type(val) == bool:
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row.append(val)
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row.append(None)
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else:
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row.append(True)
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row.append(datetime.fromtimestamp(int(val),tz=None))
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elif name == "time_edited":
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continue
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elif name == 'has_media':
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row.append(post.get('media',None) is not None)
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elif name not in post:
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row.append(None)
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else:
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row.append(post[name])
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return tuple(row)
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dumpdir = "/gscratch/comdata/raw_data/reddit_dumps/submissions"
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files = list(find_dumps(dumpdir))
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pool = Pool(28)
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stream = open_fileset(files)
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N = 100000
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rows = pool.imap_unordered(parse_submission, stream, chunksize=int(N/28))
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schema = pa.schema([
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pa.field('id', pa.string(),nullable=True),
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pa.field('author', pa.string(),nullable=True),
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pa.field('subreddit', pa.string(),nullable=True),
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pa.field('title', pa.string(),nullable=True),
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pa.field('created_utc', pa.timestamp('ms'),nullable=True),
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pa.field('permalink', pa.string(),nullable=True),
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pa.field('url', pa.string(),nullable=True),
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pa.field('domain', pa.string(),nullable=True),
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pa.field('score', pa.int64(),nullable=True),
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pa.field('ups', pa.int64(),nullable=True),
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pa.field('downs', pa.int64(),nullable=True),
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pa.field('over_18', pa.bool_(),nullable=True),
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pa.field('has_media',pa.bool_(),nullable=True),
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pa.field('selftext',pa.string(),nullable=True),
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pa.field('retrieved_on', pa.timestamp('ms'),nullable=True),
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pa.field('num_comments', pa.int64(),nullable=True),
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pa.field('gilded',pa.int64(),nullable=True),
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pa.field('edited',pa.bool_(),nullable=True),
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pa.field('time_edited',pa.timestamp('ms'),nullable=True),
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pa.field('subreddit_type',pa.string(),nullable=True),
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pa.field('subreddit_id',pa.string(),nullable=True),
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pa.field('subreddit_subscribers',pa.int64(),nullable=True),
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pa.field('name',pa.string(),nullable=True),
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pa.field('is_self',pa.bool_(),nullable=True),
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pa.field('stickied',pa.bool_(),nullable=True),
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pa.field('quarantine',pa.bool_(),nullable=True),
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pa.field('error',pa.string(),nullable=True)])
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with pq.ParquetWriter("/gscratch/comdata/output/reddit_submissions.parquet_temp",schema=schema,compression='snappy',flavor='spark') as writer:
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while True:
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chunk = islice(rows,N)
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pddf = pd.DataFrame(chunk, columns=schema.names)
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table = pa.Table.from_pandas(pddf,schema=schema)
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if table.shape[0] == 0:
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break
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writer.write_table(table)
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writer.close()
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