]> code.communitydata.science - cdsc_reddit.git/blob - submissions_2_parquet_part1.py
Bugfix
[cdsc_reddit.git] / submissions_2_parquet_part1.py
1 #!/usr/bin/env python3
2
3 # two stages:
4 # 1. from gz to arrow parquet (this script) 
5 # 2. from arrow parquet to spark parquet (submissions_2_parquet_part2.py)
6
7 import json
8 from datetime import datetime
9 from multiprocessing import Pool
10 from itertools import islice
11 from helper import find_dumps, open_fileset
12 import pandas as pd
13 import pyarrow as pa
14 import pyarrow.parquet as pq
15
16
17 def parse_submission(post, names = None):
18     if names is None:
19         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']
20
21     try:
22         post = json.loads(post)
23     except (json.decoder.JSONDecodeError, UnicodeDecodeError) as e:
24         #        print(e)
25         #        print(post)
26         row = [None for _ in names]
27         row[-1] = "json.decoder.JSONDecodeError|{0}|{1}".format(e,post)
28         return tuple(row)
29
30     row = []
31
32     for name in names:
33         if name == 'created_utc' or name == 'retrieved_on':
34             val = post.get(name,None)
35             if val is not None:
36                 row.append(datetime.fromtimestamp(int(post[name]),tz=None))
37             else:
38                 row.append(None)
39         elif name == 'edited':
40             val = post[name]
41             if type(val) == bool:
42                 row.append(val)
43                 row.append(None)
44             else:
45                 row.append(True)
46                 row.append(datetime.fromtimestamp(int(val),tz=None))
47         elif name == "time_edited":
48             continue
49         elif name == 'has_media':
50             row.append(post.get('media',None) is not None)
51
52         elif name not in post:
53             row.append(None)
54         else:
55             row.append(post[name])
56     return tuple(row)
57
58 dumpdir = "/gscratch/comdata/raw_data/reddit_dumps/submissions"
59
60 files = list(find_dumps(dumpdir))
61
62 pool = Pool(28)
63
64 stream = open_fileset(files)
65
66 N = 100000
67
68 rows = pool.imap_unordered(parse_submission, stream, chunksize=int(N/28))
69
70 schema = pa.schema([
71     pa.field('id', pa.string(),nullable=True),
72     pa.field('author', pa.string(),nullable=True),
73     pa.field('subreddit', pa.string(),nullable=True),
74     pa.field('title', pa.string(),nullable=True),
75     pa.field('created_utc', pa.timestamp('ms'),nullable=True),
76     pa.field('permalink', pa.string(),nullable=True),
77     pa.field('url', pa.string(),nullable=True),
78     pa.field('domain', pa.string(),nullable=True),
79     pa.field('score', pa.int64(),nullable=True),
80     pa.field('ups', pa.int64(),nullable=True),
81     pa.field('downs', pa.int64(),nullable=True),
82     pa.field('over_18', pa.bool_(),nullable=True),
83     pa.field('has_media',pa.bool_(),nullable=True),
84     pa.field('selftext',pa.string(),nullable=True),
85     pa.field('retrieved_on', pa.timestamp('ms'),nullable=True),
86     pa.field('num_comments', pa.int64(),nullable=True),
87     pa.field('gilded',pa.int64(),nullable=True),
88     pa.field('edited',pa.bool_(),nullable=True),
89     pa.field('time_edited',pa.timestamp('ms'),nullable=True),
90     pa.field('subreddit_type',pa.string(),nullable=True),
91     pa.field('subreddit_id',pa.string(),nullable=True),
92     pa.field('subreddit_subscribers',pa.int64(),nullable=True),
93     pa.field('name',pa.string(),nullable=True),
94     pa.field('is_self',pa.bool_(),nullable=True),
95     pa.field('stickied',pa.bool_(),nullable=True),
96     pa.field('quarantine',pa.bool_(),nullable=True),
97     pa.field('error',pa.string(),nullable=True)])
98
99 with  pq.ParquetWriter("/gscratch/comdata/output/reddit_submissions.parquet_temp",schema=schema,compression='snappy',flavor='spark') as writer:
100     while True:
101         chunk = islice(rows,N)
102         pddf = pd.DataFrame(chunk, columns=schema.names)
103         table = pa.Table.from_pandas(pddf,schema=schema)
104         if table.shape[0] == 0:
105             break
106         writer.write_table(table)
107
108     writer.close()
109

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