# 1. from gz to arrow parquet (this script)
# 2. from arrow parquet to spark parquet (submissions_2_parquet_part2.py)
-from collections import defaultdict
-from os import path
-import glob
-import json
-import re
from datetime import datetime
-from subprocess import Popen, PIPE
-from multiprocessing import Pool, SimpleQueue
-
-dumpdir = "/gscratch/comdata/raw_data/reddit_dumps/submissions"
-
-def find_json_files(dumpdir):
- base_pattern = "RS_20*.*"
-
- files = glob.glob(path.join(dumpdir,base_pattern))
-
- # build a dictionary of possible extensions for each dump
- dumpext = defaultdict(list)
- for fpath in files:
- fname, ext = path.splitext(fpath)
- dumpext[fname].append(ext)
-
- ext_priority = ['.zst','.xz','.bz2']
-
- for base, exts in dumpext.items():
- found = False
- if len(exts) == 1:
- yield base + exts[0]
- found = True
- else:
- for ext in ext_priority:
- if ext in exts:
- yield base + ext
- found = True
- assert(found == True)
-
-files = list(find_json_files(dumpdir))
-
-def read_file(fh):
- lines = open_input_file(fh)
- for line in lines:
- yield line
-
-def open_fileset(files):
- for fh in files:
- print(fh)
- lines = open_input_file(fh)
- for line in lines:
- yield line
-
-def open_input_file(input_filename):
- if re.match(r'.*\.7z$', input_filename):
- cmd = ["7za", "x", "-so", input_filename, '*']
- elif re.match(r'.*\.gz$', input_filename):
- cmd = ["zcat", input_filename]
- elif re.match(r'.*\.bz2$', input_filename):
- cmd = ["bzcat", "-dk", input_filename]
- elif re.match(r'.*\.bz', input_filename):
- cmd = ["bzcat", "-dk", input_filename]
- elif re.match(r'.*\.xz', input_filename):
- cmd = ["xzcat",'-dk', '-T 20',input_filename]
- elif re.match(r'.*\.zst',input_filename):
- cmd = ['zstd','-dck', input_filename]
- try:
- input_file = Popen(cmd, stdout=PIPE).stdout
- except NameError as e:
- print(e)
- input_file = open(input_filename, 'r')
- return input_file
+from multiprocessing import Pool
+from itertools import islice
+from helper import find_dumps, open_fileset
+import pandas as pd
+import pyarrow as pa
+import pyarrow.parquet as pq
+import simdjson
+import fire
+import os
+parser = simdjson.Parser()
def parse_submission(post, names = None):
if names is None:
- 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','is_submitter','quarantine','error']
+ 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']
try:
- post = json.loads(post)
- except (json.decoder.JSONDecodeError, UnicodeDecodeError) as e:
+ post = parser.parse(post)
+ except (ValueError) as e:
# print(e)
# print(post)
row = [None for _ in names]
- row[-1] = "json.decoder.JSONDecodeError|{0}|{1}".format(e,post)
+ row[-1] = "Error parsing json|{0}|{1}".format(e,post)
return tuple(row)
row = []
row.append(post[name])
return tuple(row)
-pool = Pool(28)
-
-stream = open_fileset(files)
-
-N = 100000
-
-rows = pool.imap_unordered(parse_submission, stream, chunksize=int(N/28))
-
-from itertools import islice
-import pandas as pd
-import pyarrow as pa
-import pyarrow.parquet as pq
-
-schema = pa.schema([
- pa.field('id', pa.string(),nullable=True),
- pa.field('author', pa.string(),nullable=True),
- pa.field('subreddit', pa.string(),nullable=True),
- pa.field('title', pa.string(),nullable=True),
- pa.field('created_utc', pa.timestamp('ms'),nullable=True),
- pa.field('permalink', pa.string(),nullable=True),
- pa.field('url', pa.string(),nullable=True),
- pa.field('domain', pa.string(),nullable=True),
- pa.field('score', pa.int64(),nullable=True),
- pa.field('ups', pa.int64(),nullable=True),
- pa.field('downs', pa.int64(),nullable=True),
- pa.field('over_18', pa.bool_(),nullable=True),
- pa.field('has_media',pa.bool_(),nullable=True),
- pa.field('selftext',pa.string(),nullable=True),
- pa.field('retrieved_on', pa.timestamp('ms'),nullable=True),
- pa.field('num_comments', pa.int64(),nullable=True),
- pa.field('gilded',pa.int64(),nullable=True),
- pa.field('edited',pa.bool_(),nullable=True),
- pa.field('time_edited',pa.timestamp('ms'),nullable=True),
- pa.field('subreddit_type',pa.string(),nullable=True),
- pa.field('subreddit_id',pa.string(),nullable=True),
- pa.field('subreddit_subscribers',pa.int64(),nullable=True),
- pa.field('name',pa.string(),nullable=True),
- pa.field('is_self',pa.bool_(),nullable=True),
- pa.field('stickied',pa.bool_(),nullable=True),
- pa.field('is_submitter',pa.bool_(),nullable=True),
- pa.field('quarantine',pa.bool_(),nullable=True),
- pa.field('error',pa.string(),nullable=True)])
-
-with pq.ParquetWriter("/gscratch/comdata/output/reddit_submissions.parquet_temp",schema=schema,compression='snappy',flavor='spark') as writer:
- while True:
- chunk = islice(rows,N)
- pddf = pd.DataFrame(chunk, columns=schema.names)
- table = pa.Table.from_pandas(pddf,schema=schema)
- if table.shape[0] == 0:
- break
- writer.write_table(table)
-
- writer.close()
-
+def parse_dump(partition):
+
+ N=10000
+ stream = open_fileset([f"/gscratch/comdata/raw_data/reddit_dumps/submissions/{partition}"])
+ rows = map(parse_submission,stream)
+ schema = pa.schema([
+ pa.field('id', pa.string(),nullable=True),
+ pa.field('author', pa.string(),nullable=True),
+ pa.field('subreddit', pa.string(),nullable=True),
+ pa.field('title', pa.string(),nullable=True),
+ pa.field('created_utc', pa.timestamp('ms'),nullable=True),
+ pa.field('permalink', pa.string(),nullable=True),
+ pa.field('url', pa.string(),nullable=True),
+ pa.field('domain', pa.string(),nullable=True),
+ pa.field('score', pa.int64(),nullable=True),
+ pa.field('ups', pa.int64(),nullable=True),
+ pa.field('downs', pa.int64(),nullable=True),
+ pa.field('over_18', pa.bool_(),nullable=True),
+ pa.field('has_media',pa.bool_(),nullable=True),
+ pa.field('selftext',pa.string(),nullable=True),
+ pa.field('retrieved_on', pa.timestamp('ms'),nullable=True),
+ pa.field('num_comments', pa.int64(),nullable=True),
+ pa.field('gilded',pa.int64(),nullable=True),
+ pa.field('edited',pa.bool_(),nullable=True),
+ pa.field('time_edited',pa.timestamp('ms'),nullable=True),
+ pa.field('subreddit_type',pa.string(),nullable=True),
+ pa.field('subreddit_id',pa.string(),nullable=True),
+ pa.field('subreddit_subscribers',pa.int64(),nullable=True),
+ pa.field('name',pa.string(),nullable=True),
+ pa.field('is_self',pa.bool_(),nullable=True),
+ pa.field('stickied',pa.bool_(),nullable=True),
+ pa.field('quarantine',pa.bool_(),nullable=True),
+ pa.field('error',pa.string(),nullable=True)])
+
+ if not os.path.exists("/gscratch/comdata/output/temp/reddit_submissions.parquet/"):
+ os.mkdir("/gscratch/comdata/output/temp/reddit_submissions.parquet/")
+
+ with pq.ParquetWriter(f"/gscratch/comdata/output/temp/reddit_submissions.parquet/{partition}",schema=schema,compression='snappy',flavor='spark') as writer:
+ while True:
+ chunk = islice(rows,N)
+ pddf = pd.DataFrame(chunk, columns=schema.names)
+ table = pa.Table.from_pandas(pddf,schema=schema)
+ if table.shape[0] == 0:
+ break
+ writer.write_table(table)
+
+ writer.close()
+
+def gen_task_list(dumpdir="/gscratch/comdata/raw_data/reddit_dumps/submissions"):
+ files = list(find_dumps(dumpdir,base_pattern="RS_20*.*"))
+ with open("parse_submissions_task_list",'w') as of:
+ for fpath in files:
+ partition = os.path.split(fpath)[1]
+ of.write(f'python3 submissions_2_parquet_part1.py parse_dump {partition}\n')
+
+if __name__ == "__main__":
+ fire.Fire({'parse_dump':parse_dump,
+ 'gen_task_list':gen_task_list})
projects / cdsc_reddit.git / blobdiff