Create parquet datasets of reddit submissions from pushshift.

submissions_2_parquet.py

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+#!/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")