Initial commit

scripts/combine_folder_multiprocess.py

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+import zstandard
+import os
+import json
+import sys
+import time
+import argparse
+from datetime import datetime
+import logging.handlers
+import multiprocessing
+
+
+# sets up logging to the console as well as a file
+log = logging.getLogger("bot")
+log.setLevel(logging.INFO)
+log_formatter = logging.Formatter('%(asctime)s - %(levelname)s: %(message)s')
+
+log_stderr_handler = logging.StreamHandler()
+log_stderr_handler.setFormatter(log_formatter)
+log.addHandler(log_stderr_handler)
+if not os.path.exists("logs"):
+	os.makedirs("logs")
+log_file_handler = logging.handlers.RotatingFileHandler(
+	os.path.join("logs", "bot.log"), maxBytes=1024*1024*16, backupCount=5)
+log_file_handler.setFormatter(log_formatter)
+log.addHandler(log_file_handler)
+
+
+# this script iterates through zst compressed ndjson files, like the pushshift reddit dumps, loads each line
+# and passes it into the save_obj function, if it function returns true for a line, it's written out into a
+# separate file for that month. After all the ndjson files are processed, it iterates through the resulting
+# files and combines them into a final file.
+
+# once complete, the combined file can easily be processed like
+# with open(file_path, 'r') as file:
+#     for line in file:
+#         obj = json.loads(line)
+
+# features:
+#    - multiple processes in parallel to maximize drive read and decompression
+#    - saves state as it completes each file and picks up where it stopped
+#    - detailed progress indicators
+
+
+# convenience object used to pass status information between processes
+class FileConfig:
+	def __init__(self, input_path, output_path=None, complete=False, lines_processed=0, error_lines=0):
+		self.input_path = input_path
+		self.output_path = output_path
+		self.file_size = os.stat(input_path).st_size
+		self.complete = complete
+		self.bytes_processed = self.file_size if complete else 0
+		self.lines_processed = lines_processed if complete else 0
+		self.error_message = None
+		self.error_lines = error_lines
+
+	def __str__(self):
+		return f"{self.input_path} : {self.output_path} : {self.file_size} : {self.complete} : {self.bytes_processed} : {self.lines_processed}"
+
+
+# used for calculating running average of read speed
+class Queue:
+	def __init__(self, max_size):
+		self.list = []
+		self.max_size = max_size
+
+	def put(self, item):
+		if len(self.list) >= self.max_size:
+			self.list.pop(0)
+		self.list.append(item)
+
+	def peek(self):
+		return self.list[0] if len(self.list) > 0 else None
+
+
+# builds file paths
+def folder_helper(output_folder, output_file_name):
+	working_folder = os.path.join(output_folder, "pushshift_working_dir_" + output_file_name)
+	status_file = os.path.join(working_folder, output_file_name + ".json")
+	return working_folder, status_file
+
+
+# save file information and progress to a json file
+# we don't want to save the whole FileConfig object, since some of the info resets if we restart
+def save_file_list(input_files, output_folder, output_file_name):
+	working_folder, status_json_file_name = folder_helper(output_folder, output_file_name)
+	if not os.path.exists(working_folder):
+		os.makedirs(working_folder)
+	simple_file_list = []
+	for file in input_files:
+		simple_file_list.append([file.input_path, file.output_path, file.complete, file.lines_processed, file.error_lines])
+	with open(status_json_file_name, 'w') as status_json_file:
+		status_json_file.write(json.dumps(simple_file_list, indent=4))
+
+
+# load file information from the json file and recalculate file sizes
+def load_file_list(output_folder, output_file_name):
+	_, status_json_file_name = folder_helper(output_folder, output_file_name)
+	if os.path.exists(status_json_file_name):
+		with open(status_json_file_name, 'r') as status_json_file:
+			simple_file_list = json.load(status_json_file)
+			input_files = []
+			for simple_file in simple_file_list:
+				input_files.append(
+					FileConfig(simple_file[0], simple_file[1], simple_file[2], simple_file[3], simple_file[4])
+				)
+			return input_files
+	else:
+		return None
+
+
+# open a zst compressed ndjson file and yield lines one at a time
+# also passes back file progress
+def read_lines_zst(file_name):
+	with open(file_name, 'rb') as file_handle:
+		buffer = ''
+		reader = zstandard.ZstdDecompressor(max_window_size=2**31).stream_reader(file_handle)
+		while True:
+			chunk = reader.read(2**27).decode()
+			if not chunk:
+				break
+			lines = (buffer + chunk).split("\n")
+
+			for line in lines[:-1]:
+				yield line, file_handle.tell()
+
+			buffer = lines[-1]
+		reader.close()
+
+
+# base of each separate process. Loads a file, iterates through lines and writes out
+# the ones where save_obj() returns true. Also passes status information back to the parent via a queue
+def process_file(file, working_folder, queue, field, value):
+	output_file = None
+	try:
+		for line, file_bytes_processed in read_lines_zst(file.input_path):
+			try:
+				obj = json.loads(line)
+				if obj[field] == value:
+					if output_file is None:
+						if file.output_path is None:
+							created = datetime.utcfromtimestamp(int(obj['created_utc']))
+							file.output_path = os.path.join(working_folder, created.strftime("%Y-%m"))
+						output_file = open(file.output_path, 'w')
+					output_file.write(line)
+					output_file.write("\n")
+			except (KeyError, json.JSONDecodeError) as err:
+				file.error_lines += 1
+			file.lines_processed += 1
+			if file.lines_processed % 1000000 == 0:
+				file.bytes_processed = file_bytes_processed
+				queue.put(file)
+
+		if output_file is not None:
+			output_file.close()
+
+		file.complete = True
+		file.bytes_processed = file.file_size
+	except Exception as err:
+		file.error_message = str(err)
+	queue.put(file)
+
+
+if __name__ == '__main__':
+	parser = argparse.ArgumentParser(description="Use multiple processes to decompress and iterate over pushshift dump files")
+	parser.add_argument("input", help="The input folder to read files from")
+	parser.add_argument("output", help="The output folder to store temporary files in and write the output to")
+	parser.add_argument("--name", help="What to name the output file", default="pushshift")
+	parser.add_argument("--field", help="When deciding what lines to keep, use this field for comparisons", default="subreddit")
+	parser.add_argument("--value", help="When deciding what lines to keep, compare the field to this value", default="pushshift")
+	parser.add_argument("--processes", help="Number of processes to use", default=10, type=int)
+	parser.add_argument(
+		"--error_rate", help=
+		"Percentage as an integer from 0 to 100 of the lines where the field can be missing. For the subreddit field especially, "
+		"there are a number of posts that simply don't have a subreddit attached", default=1, type=int)
+	parser.add_argument("--debug", help="Enable debug logging", action='store_const', const=True, default=False)
+	args = parser.parse_args()
+
+	if args.debug:
+		log.setLevel(logging.DEBUG)
+
+	log.info(f"Loading files from: {args.input}")
+	log.info(f"Writing output to: {(os.path.join(args.output, args.name + '.txt'))}")
+
+	multiprocessing.set_start_method('spawn')
+	queue = multiprocessing.Manager().Queue()
+	input_files = load_file_list(args.output, args.name)
+	working_folder, _ = folder_helper(args.output, args.name)
+	# if the file list wasn't loaded from the json, this is the first run, find what files we need to process
+	if input_files is None:
+		input_files = []
+		for subdir, dirs, files in os.walk(args.input):
+			files.sort()
+			for file_name in files:
+				if file_name.endswith(".zst"):
+					input_path = os.path.join(subdir, file_name)
+					input_files.append(FileConfig(input_path))
+
+		save_file_list(input_files, args.output, args.name)
+
+	files_processed = 0
+	total_bytes = 0
+	total_bytes_processed = 0
+	total_lines_processed = 0
+	files_to_process = []
+	# calculate the total file size for progress reports, build a list of incomplete files to process
+	for file in input_files:
+		total_bytes += file.file_size
+		if file.complete:
+			files_processed += 1
+			total_lines_processed += file.lines_processed
+			total_bytes_processed += file.file_size
+		else:
+			files_to_process.append(file)
+
+	log.info(f"Processed {files_processed} of {len(input_files)} files with {(total_bytes_processed / (2**30)):.2f} of {(total_bytes / (2**30)):.2f} gigabytes")
+
+	start_time = time.time()
+	if len(files_to_process):
+		progress_queue = Queue(40)
+		progress_queue.put([start_time, total_lines_processed, total_bytes_processed])
+		speed_queue = Queue(40)
+		for file in files_to_process:
+			log.debug(f"Processing file: {file.input_path}")
+		# start the workers
+		with multiprocessing.Pool(processes=min(args.processes, len(files_to_process))) as pool:
+			workers = pool.starmap_async(process_file, [(file, working_folder, queue, args.field, args.value) for file in files_to_process], error_callback=log.info)
+			while not workers.ready():
+				# loop until the workers are all done, pulling in status messages as they are sent
+				file_update = queue.get()
+				if file_update.error_message is not None:
+					log.warning(f"File failed {file_update.input_path}: {file_update.error_message}")
+					continue
+				# I'm going to assume that the list of files is short enough that it's no
+				# big deal to just iterate each time since that saves a bunch of work
+				total_lines_processed = 0
+				total_bytes_processed = 0
+				total_lines_errored = 0
+				files_processed = 0
+				i = 0
+				for file in input_files:
+					if file.input_path == file_update.input_path:
+						input_files[i] = file_update
+						file = file_update
+					total_lines_processed += file.lines_processed
+					total_bytes_processed += file.bytes_processed
+					total_lines_errored += file.error_lines
+					files_processed += 1 if file.complete else 0
+					i += 1
+				if file_update.complete:
+					save_file_list(input_files, args.output, args.name)
+				current_time = time.time()
+				progress_queue.put([current_time, total_lines_processed, total_bytes_processed])
+
+				first_time, first_lines, first_bytes = progress_queue.peek()
+				bytes_per_second = int((total_bytes_processed - first_bytes)/(current_time - first_time))
+				speed_queue.put(bytes_per_second)
+				seconds_left = int((total_bytes - total_bytes_processed) / int(sum(speed_queue.list) / len(speed_queue.list)))
+				minutes_left = int(seconds_left / 60)
+				hours_left = int(minutes_left / 60)
+				days_left = int(hours_left / 24)
+
+				log.info(
+					f"{total_lines_processed:,} lines at {(total_lines_processed - first_lines)/(current_time - first_time):,.0f}/s, {total_lines_errored:,} errored : "
+					f"{(total_bytes_processed / (2**30)):.2f} gb at {(bytes_per_second / (2**20)):,.0f} mb/s, {(total_bytes_processed / total_bytes) * 100:.0f}% : "
+					f"{files_processed}/{len(input_files)} files : "
+					f"{(str(days_left) + 'd ' if days_left > 0 else '')}{hours_left - (days_left * 24)}:{minutes_left - (hours_left * 60):02}:{seconds_left - (minutes_left * 60):02} remaining")
+
+	log.info(f"{total_lines_processed:,}, {total_lines_errored} errored : {(total_bytes_processed / (2**30)):.2f} gb, {(total_bytes_processed / total_bytes) * 100:.0f}% : {files_processed}/{len(input_files)}")
+
+	working_file_paths = []
+	count_incomplete = 0
+	# build a list of output files to combine
+	for file in input_files:
+		if not file.complete:
+			log.info(f"File {file.input_path} is not marked as complete")
+			count_incomplete += 1
+		else:
+			if file.error_lines > file.lines_processed * (args.error_rate * 0.01):
+				log.info(
+					f"File {file.input_path} has {file.error_lines:,} errored lines out of {file.lines_processed:,}, "
+					f"{(file.error_lines / file.lines_processed) * (args.error_rate * 0.01):.2f}% which is above the limit of {args.error_rate}%")
+				count_incomplete += 1
+			elif file.output_path is not None:
+				if not os.path.exists(file.output_path):
+					log.info(f"Output file {file.output_path} doesn't exist")
+					count_incomplete += 1
+				else:
+					working_file_paths.append(file.output_path)
+
+	if count_incomplete > 0:
+		log.info(f"{count_incomplete} files were not completed, errored or don't exist, something went wrong. Aborting")
+		sys.exit()
+
+	log.info(f"Processing complete, combining {len(working_file_paths)} result files")
+
+	output_lines = 0
+	output_file_path = os.path.join(args.output, args.name + ".txt")
+	# combine all the output files into the final results file
+	with open(output_file_path, 'w') as output_file:
+		i = 0
+		for working_file_path in working_file_paths:
+			i += 1
+			log.info(f"Reading {i}/{len(working_file_paths)}")
+			with open(working_file_path, 'r') as input_file:
+				for line in input_file.readlines():
+					output_lines += 1
+					output_file.write(line)
+
+	log.info(f"Finished combining files, {output_lines:,} lines written to {output_file_path}")
+
+
+# test file sorting
+# compress results
+# example command line call in comment