Extract variables from pushshift comment to parquet
A spark script
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								reddit_bz2_2parquet.py
									
									
									
									
									
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								reddit_bz2_2parquet.py
									
									
									
									
									
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							| @ -0,0 +1,128 @@ | |||||||
|  | 
 | ||||||
|  | #!/usr/bin/env python3 | ||||||
|  | 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 | ||||||
|  | 
 | ||||||
|  | conf = SparkConf().setAppName("Reddit to bz2") | ||||||
|  | conf = conf.set('spark.sql.crossJoin.enabled',"true") | ||||||
|  | 
 | ||||||
|  | spark = SparkSession.builder.getOrCreate() | ||||||
|  | sc = spark.sparkContext | ||||||
|  | 
 | ||||||
|  | globstr = "/gscratch/comdata/raw_data/reddit_dumps/RC_20*.bz2" | ||||||
|  | 
 | ||||||
|  | import re | ||||||
|  | import glob | ||||||
|  | import json | ||||||
|  | from subprocess import Popen, PIPE | ||||||
|  | from datetime import datetime | ||||||
|  | import pandas as pd | ||||||
|  | from multiprocessing import Pool | ||||||
|  | 
 | ||||||
|  | def open_fileset(globstr): | ||||||
|  |     files = glob.glob(globstr) | ||||||
|  |     for fh in files: | ||||||
|  |         print(fh) | ||||||
|  |         lines = open_input_file(fh) | ||||||
|  |         for line in lines: | ||||||
|  |             yield json.loads(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',input_filename] | ||||||
|  |     try: | ||||||
|  |         input_file = Popen(cmd, stdout=PIPE).stdout | ||||||
|  |     except NameError: | ||||||
|  |         input_file = open(input_filename, 'r') | ||||||
|  |     return input_file | ||||||
|  | 
 | ||||||
|  | def include_row(comment, subreddits_to_track = []): | ||||||
|  |      | ||||||
|  |     subreddit = comment['subreddit'].lower() | ||||||
|  | 
 | ||||||
|  |     return subreddit in subreddits_to_track | ||||||
|  | 
 | ||||||
|  | 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')]) | ||||||
|  |      | ||||||
|  | sqlContext = pyspark.SQLContext(sc) | ||||||
|  | 
 | ||||||
|  | comments = sc.textFile(globstr) | ||||||
|  | 
 | ||||||
|  | schema = StructType().add("id", StringType(), True) | ||||||
|  | schema = schema.add("subreddit", StringType(), True) | ||||||
|  | schema = schema.add("link_id", StringType(), True) | ||||||
|  | schema = schema.add("parent_id", StringType(), True) | ||||||
|  | schema = schema.add("created_utc", DateType(), True) | ||||||
|  | schema = schema.add("author", StringType(), True) | ||||||
|  | schema = schema.add("ups", LongType(), True) | ||||||
|  | schema = schema.add("downs", LongType(), True) | ||||||
|  | schema = schema.add("score", LongType(), True) | ||||||
|  | schema = schema.add("edited", BooleanType(), True) | ||||||
|  | schema = schema.add("time_edited", DateType(), True) | ||||||
|  | schema = schema.add("subreddit_type", StringType(), True) | ||||||
|  | schema = schema.add("subreddit_id", StringType(), True) | ||||||
|  | schema = schema.add("stickied", BooleanType(), True) | ||||||
|  | schema = schema.add("is_submitter", BooleanType(), True) | ||||||
|  | schema = schema.add("body", StringType(), True) | ||||||
|  | schema = schema.add("error", StringType(), True) | ||||||
|  | 
 | ||||||
|  | rows = comments.map(lambda c: parse_comment(c, schema.fieldNames())) | ||||||
|  | #!/usr/bin/env python3 | ||||||
|  | 
 | ||||||
|  | df =  sqlContext.createDataFrame(rows, schema) | ||||||
|  | 
 | ||||||
|  | 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]) | ||||||
|  | df = df.sort(["subreddit","author","link_id","parent_id","Year","Month","Day"],ascending=True) | ||||||
|  | df.write.parquet("/gscratch/comdata/output/reddit_dumps/reddit_comments.parquet", partitionBy=["Year",'Month'],mode='overwrite') | ||||||
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