#!/usr/bin/env python3

# two stages:
# 1. from gz to arrow parquet (this script) 
# 2. from arrow parquet to spark parquet (submissions_2_parquet_part2.py)

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()