--- /dev/null
+#!/usr/bin/env python3
+
+# two stages:
+# 1. from gz to arrow parquet
+# 2. from arrow parquet to spark parquet
+
+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
+
+
+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']
+
+ try:
+ post = json.loads(post)
+ except (json.decoder.JSONDecodeError, UnicodeDecodeError) as e:
+ # print(e)
+ # print(post)
+ row = [None for _ in names]
+ row[-1] = "json.decoder.JSONDecodeError|{0}|{1}".format(e,post)
+ return tuple(row)
+
+ row = []
+
+ for name in names:
+ if name == 'created_utc' or name == 'retrieved_on':
+ val = post.get(name,None)
+ if val is not None:
+ row.append(datetime.fromtimestamp(int(post[name]),tz=None))
+ else:
+ row.append(None)
+ elif name == 'edited':
+ val = post[name]
+ if type(val) == bool:
+ row.append(val)
+ row.append(None)
+ else:
+ row.append(True)
+ row.append(datetime.fromtimestamp(int(val),tz=None))
+ elif name == "time_edited":
+ continue
+ elif name == 'has_media':
+ row.append(post.get('media',None) is not None)
+
+ elif name not in post:
+ row.append(None)
+ else:
+ 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()
+
+import pyspark
+from pyspark.sql import functions as f
+from pyspark.sql.types import *
+from pyspark import SparkConf, SparkContext
+from pyspark.sql import SparkSession, SQLContext
+
+spark = SparkSession.builder.getOrCreate()
+sc = spark.sparkContext
+
+conf = SparkConf().setAppName("Reddit submissions to parquet")
+conf = conf.set('spark.sql.crossJoin.enabled',"true")
+
+sqlContext = pyspark.SQLContext(sc)
+
+df = spark.read.parquet("/gscratch/comdata/output/reddit_submissions.parquet_temp")
+
+df = df.withColumn("subreddit_2", f.lower(f.col('subreddit')))
+df = df.drop('subreddit')
+df = df.withColumnRenamed('subreddit_2','subreddit')
+df = df.withColumnRenamed("created_utc","CreatedAt")
+df = df.withColumn("Month",f.month(f.col("CreatedAt")))
+df = df.withColumn("Year",f.year(f.col("CreatedAt")))
+df = df.withColumn("Day",f.dayofmonth(f.col("CreatedAt")))
+df = df.withColumn("subreddit_hash",f.sha2(f.col("subreddit"), 256)[0:3])
+
+# next we gotta resort it all.
+df2 = df.sort(["subreddit","author","id","Year","Month","Day"],ascending=True)
+df2.write.parquet("/gscratch/comdata/output/reddit_submissions_by_subreddit.parquet", partitionBy=["Year",'Month'], mode='overwrite')
+
+
+# we also want to have parquet files sorted by author then reddit.
+df3 = df.sort(["author","subreddit","id","Year","Month","Day"],ascending=True)
+df3.write.parquet("/gscratch/comdata/output/reddit_submissions_by_author.parquet", partitionBy=["Year",'Month'], mode='overwrite')
+
+os.remove("/gscratch/comdata/output/reddit_submissions.parquet_temp")