From: Nate E TeBlunthuis Date: Mon, 6 Jul 2020 06:20:17 +0000 (-0700) Subject: Create parquet datasets of reddit submissions from pushshift. X-Git-Url: https://code.communitydata.science/cdsc_reddit.git/commitdiff_plain/6d4344355b256f7df3c3f60f891ea44d453f4d6c?ds=inline Create parquet datasets of reddit submissions from pushshift. --- diff --git a/submissions_2_parquet.py b/submissions_2_parquet.py new file mode 100755 index 0000000..6e46970 --- /dev/null +++ b/submissions_2_parquet.py @@ -0,0 +1,207 @@ +#!/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")