]> code.communitydata.science - cdsc_reddit.git/blobdiff - comments_2_parquet_part1.py
add note to try other tf normalization strategies.
[cdsc_reddit.git] / comments_2_parquet_part1.py
diff --git a/comments_2_parquet_part1.py b/comments_2_parquet_part1.py
deleted file mode 100755 (executable)
index faea040..0000000
+++ /dev/null
@@ -1,92 +0,0 @@
-#!/usr/bin/env python3
-import json
-from datetime import datetime
-from multiprocessing import Pool
-from itertools import islice
-from helper import find_dumps, open_fileset
-import pandas as pd
-import pyarrow as pa
-import pyarrow.parquet as pq
-
-globstr_base = "/gscratch/comdata/reddit_dumps/comments/RC_20*"
-
-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')])
-
-dumpdir = "/gscratch/comdata/raw_data/reddit_dumps/comments"
-
-files = list(find_dumps(dumpdir, base_pattern="RC_20*.*"))
-
-pool = Pool(28)
-
-stream = open_fileset(files)
-
-N = 100000
-
-rows = pool.imap_unordered(parse_comment, stream, chunksize=int(N/28))
-
-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),
-])
-
-with pq.ParquetWriter("/gscratch/comdata/output/reddit_comments.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()

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