93 lines
3.3 KiB
Python
Executable File
93 lines
3.3 KiB
Python
Executable File
#!/usr/bin/env python3
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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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globstr_base = "/gscratch/comdata/reddit_dumps/comments/RC_20*"
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def parse_comment(comment, names= None):
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if names is None:
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names = ["id","subreddit","link_id","parent_id","created_utc","author","ups","downs","score","edited","subreddit_type","subreddit_id","stickied","is_submitter","body","error"]
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try:
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comment = json.loads(comment)
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except json.decoder.JSONDecodeError as e:
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print(e)
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print(comment)
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row = [None for _ in names]
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row[-1] = "json.decoder.JSONDecodeError|{0}|{1}".format(e,comment)
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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':
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row.append(datetime.fromtimestamp(int(comment['created_utc']),tz=None))
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elif name == 'edited':
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val = comment[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 not in comment:
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row.append(None)
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else:
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row.append(comment[name])
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return tuple(row)
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# conf = sc._conf.setAll([('spark.executor.memory', '20g'), ('spark.app.name', 'extract_reddit_timeline'), ('spark.executor.cores', '26'), ('spark.cores.max', '26'), ('spark.driver.memory','84g'),('spark.driver.maxResultSize','0'),('spark.local.dir','/gscratch/comdata/spark_tmp')])
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dumpdir = "/gscratch/comdata/raw_data/reddit_dumps/comments"
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files = list(find_dumps(dumpdir, base_pattern="RC_20*.*"))
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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_comment, 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('subreddit', pa.string(), nullable=True),
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pa.field('link_id', pa.string(), nullable=True),
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pa.field('parent_id', pa.string(), nullable=True),
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pa.field('created_utc', pa.timestamp('ms'), nullable=True),
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pa.field('author', pa.string(), 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('score', 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('stickied', pa.bool_(), nullable=True),
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pa.field('is_submitter', pa.bool_(), nullable=True),
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pa.field('body', pa.string(), nullable=True),
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pa.field('error', pa.string(), nullable=True),
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])
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with pq.ParquetWriter("/gscratch/comdata/output/reddit_comments.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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