#!/usr/bin/env python3 import os import json from datetime import datetime from multiprocessing import Pool from itertools import islice from helper import open_input_file, find_dumps import pandas as pd import pyarrow as pa import pyarrow.parquet as pq from pathlib import Path import fire def parse_comment(comment, names= None): if names is None: names = ["id","subreddit","link_id","parent_id","created_utc","author","ups","downs","score","edited","subreddit_type","subreddit_id","stickied","is_submitter","body","error"] try: comment = json.loads(comment) except json.decoder.JSONDecodeError as e: print(e) print(comment) row = [None for _ in names] row[-1] = "json.decoder.JSONDecodeError|{0}|{1}".format(e,comment) return tuple(row) row = [] for name in names: if name == 'created_utc': row.append(datetime.fromtimestamp(int(comment['created_utc']),tz=None)) elif name == 'edited': val = comment[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 not in comment: row.append(None) else: row.append(comment[name]) return tuple(row) # 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')]) def parse_dump(partition): dumpdir = f"/gscratch/comdata/raw_data/reddit_dumps/comments/{partition}" stream = open_input_file(dumpdir) rows = map(parse_comment, stream) schema = pa.schema([ pa.field('id', pa.string(), nullable=True), pa.field('subreddit', pa.string(), nullable=True), pa.field('link_id', pa.string(), nullable=True), pa.field('parent_id', pa.string(), nullable=True), pa.field('created_utc', pa.timestamp('ms'), nullable=True), pa.field('author', pa.string(), nullable=True), pa.field('ups', pa.int64(), nullable=True), pa.field('downs', pa.int64(), nullable=True), pa.field('score', 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('stickied', pa.bool_(), nullable=True), pa.field('is_submitter', pa.bool_(), nullable=True), pa.field('body', pa.string(), nullable=True), pa.field('error', pa.string(), nullable=True), ]) p = Path("/gscratch/comdata/output/temp/reddit_comments.parquet") p.mkdir(exist_ok=True,parents=True) N=10000 with pq.ParquetWriter(f"/gscratch/comdata/output/temp/reddit_comments.parquet/{partition}.parquet", 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/comments", overwrite=True): files = list(find_dumps(dumpdir,base_pattern="RC_20*.*")) with open("comments_task_list.sh",'w') as of: for fpath in files: partition = os.path.split(fpath)[1] if (not Path(f"/gscratch/comdata/output/temp/reddit_comments.parquet/{partition}.parquet").exists()) or (overwrite is True): of.write(f'python3 comments_2_parquet_part1.py parse_dump {partition}\n') if __name__ == '__main__': fire.Fire({'parse_dump':parse_dump, 'gen_task_list':gen_task_list})