changes for archiving.

[cdsc_reddit.git] / examples / pyarrow_streaming.py

diff --git a/examples/pyarrow_streaming.py b/examples/pyarrow_streaming.py
deleted file mode 100644 (file)
index 512e63f..0000000
--- a/examples/pyarrow_streaming.py
+++ /dev/null
@@ -1,32 +0,0 @@
-import pyarrow.dataset as ds
-from itertools import chain, groupby, islice
-
-# A pyarrow dataset abstracts reading, writing, or filtering a parquet file. It does not read dataa into memory. 
-#dataset = ds.dataset(pathlib.Path('/gscratch/comdata/output/reddit_submissions_by_subreddit.parquet/'), format='parquet', partitioning='hive')
-dataset = ds.dataset('/gscratch/comdata/output/reddit_submissions_by_author.parquet', format='parquet', partitioning='hive')
-
-# let's get all the comments to two subreddits:
-subreddits_to_pull = ['seattlewa','seattle']
-
-# instead of loading the data into a pandas dataframe all at once we can stream it. This lets us start working with it while it is read.
-scan_tasks = dataset.scan(filter = ds.field('subreddit').isin(subreddits_to_pull), columns=['id','subreddit','CreatedAt','author','ups','downs','score','subreddit_id','stickied','title','url','is_self','selftext'])
-
-# simple function to execute scantasks and create a stream of pydict rows 
-def execute_scan_task(st):
-    # an executed scan task yields an iterator of record_batches
-    def unroll_record_batch(rb):
-        df = rb.to_pandas()
-        return df.itertuples()
-
-    for rb in st.execute():
-        yield unroll_record_batch(rb)
-
-
-# now we just need to flatten and we have our iterator
-row_iter = chain.from_iterable(chain.from_iterable(map(lambda st: execute_scan_task(st), scan_tasks)))
-
-# now we can use python's groupby function to read one author at a time
-# note that the same author can appear more than once since the record batches may not be in the correct order.
-author_submissions = groupby(row_iter, lambda row: row.author)
-for auth, posts in author_submissions:
-    print(f"{auth} has {len(list(posts))} posts")