Decoding step is terribly slow #1224

In which file did you encounter the issue?

https://github.com/GoogleCloudPlatform/python-docs-samples/blob/master/bigtable/hello/main.py

Did you change the file? If so, how?

I pointed the code to my custom bigtable instance containing time series data. The data ingested was much larger than that used in the sample.

Describe the issue

The decoding loop in the scan takes a long time in python

# [START scanning_all_rows]
print('Scanning for all greetings:')
partial_rows = table.read_rows()
partial_rows.consume_all()

for row_key, row in partial_rows.rows.items():
    key = row_key.decode('utf-8')
    cell = row.cells[column_family_id][column_id][0]
    value = cell.value.decode('utf-8')
    print('\t{}: {}'.format(key, value))
# [END scanning_all_rows]

Up until partial_rows.consume_all() takes only 1 second. The following loop where the partial rows are decoded into a python data structure takes 2 seconds, tripling the total access time. I have tried condensing the data into into a single row to see if performance would improve, but it did not help much. Is there a faster way to get the decoded data out of the big table row structure and into another python data structure (such as a pandas dataframe or a numpy array of floats)?