Hey, everyone. We're dealing with a weird bug here and we have no idea how to fix it. Basically, we have a task that's not finishing. We run a workflow with 8 tasks, and at the very last one it hangs. All of its code is being executed (a lot of `print`s from the very start all the way to the the

return

statement confirm that), but it hangs at the end and never actually finishes. We were able to reproduce it in our remote server and locally. On the remote server, none of the prints (or logs) are being shown on Stackdriver. What could be happening?

so IIUC, you are returning from your code and you are saying that the return completes, but hangs after this?

Yeah, I'm not sure the return completes since I can't execute anything after it 😅 but the code right after it does.

and you said you can reproduce this locally?

Weirdly enough, this task is the only one that returns

None

, and that does not send its return value to another variable in the workflow spec. The workflow also returns

None

.

is there anything unusual about the task? Can you share its overall structure?

yeah, this screenshot I sent is from

pyflyte run

sounds like a bug? can you change it to

return 5

and make the signature an int?

This is the overall structure of the task:

@extended_task(integrations=['gcloud'], requests=Resources(mem='4Gi'))
def update_bq_table(
    amnt_dataframe: pd.DataFrame,
    gcs_config_path: str
) -> None:
    config_dict = read_file(gcs_config_path)
    update_gbq_table(    # Function that calls pandas_gbq.to_gbq()
        amnt_dataframe,
        config_dict['table_schema'],
        config_dict['table_destination']
    )

@extended_task

is a special decorator we use that does some pre and post-processing on tasks. Other tasks with it are running fine; the

7 None

on my screenshot above is being called on the wrapper, after a

output = task_func(*args, **kwargs)

and before a

return output

.

can you try changing it to int?

The workflow looks like this:

@workflow
def main_workflow(
        hotel_amnt_sql_path: str,
        config_path: str,
        config_pre_process_path: str,
        model_config_path: str
) -> None:
    preview_amnt = ...

    # Some other tasks, all with <output> = <function call>

    update_bq_table(
        amnt_dataframe = hotel_topics,
        gcs_config_path = config_path
    )

Hey! I work with @sparse-window-1536. We changed it to int, but it didn't work 😕

@sparse-window-1536 @abundant-night-96152 hop on call?

yeah, send us the link

yeah I'll try it

ah nice

still hanging

how big is this dataframe? Does it hang if you try with only a few rows ?

so describe is failing. yeah how big is this

237857 rows x 2 columns

that’s not that big…

5,7MB

are you able to run describe outside of flyte

one of our columns is the "topics" and it has list for each row of the dataframe. Is it possible to be the problem?

the whole dataframe is 5.7 MBs?

message has been deleted

let me play around with this tonight.

just to confirm, I can see the python process get stuck when running this:

❯ ipython
Python 3.8.13 (default, Mar 28 2022, 11:38:47)
Type 'copyright', 'credits' or 'license' for more information
IPython 8.5.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import pandas as pd

In [2]: pd.read_parquet("/home/eduardo/Downloads/amnt_dataframe.parquet.gzip")
Out[2]:
                      generic_sku                                           topics
0       HT-0008-0-0-0-0-0-0-0-0-0                  [ST5, ST6, ST2, ST13, ST4, ST3]
1       HT-000M-0-0-0-0-0-0-0-0-0             [ST5, ST6, ST2, ST7, ST13, ST4, ST3]
2       HT-000W-0-0-0-0-0-0-0-0-0            [ST5, ST6, ST12, ST10, ST7, ST4, ST1]
3       HT-000X-0-0-0-0-0-0-0-0-0                       [ST5, ST6, ST13, ST4, ST1]
4       HT-000Z-0-0-0-0-0-0-0-0-0                 [ST5, ST10, ST13, ST4, ST1, ST3]
...                           ...                                              ...
237852  HT-ZZY9-0-0-0-0-0-0-0-0-0                                       [ST1, ST4]
237853  HT-ZZYC-0-0-0-0-0-0-0-0-0  [ST5, ST6, ST2, ST12, ST7, ST13, ST4, ST1, ST3]
237854  HT-ZZYZ-0-0-0-0-0-0-0-0-0                      [ST5, ST10, ST13, ST4, ST1]
237855  HT-ZZZ2-0-0-0-0-0-0-0-0-0                  [ST5, ST12, ST7, ST4, ST1, ST3]
237856  HT-ZZZJ-0-0-0-0-0-0-0-0-0                             [ST4, ST5, ST6, ST2]

[237857 rows x 2 columns]

In [3]: df = pd.read_parquet("/home/eduardo/Downloads/amnt_dataframe.parquet.gzip")

In [4]: df.describe()

Yeah, me too. It takes a few seconds for my PC to describe 1k lines, that's why it's taking hours to describe the entire dataset.

Ya, describing whole dataframe as html does not seem like a good idea

@sparse-window-1536, no, what Yee proposed (using the

TopFrameRenderer

) does not run

describe

, instead it turns a fixed number of rows directly into html: https://github.com/flyteorg/flytekit/blob/3cf063955907957de65b035066fe415503a9bd65/flytekit/deck/renderer.py#L17-L27

We're on flytekit 1.2.0 & are noticing similar behavior; we have a a 60k row DF w/ ~1.5k columns that we read from our data warehouse & return as a

DataFrame

in a task. We were previously able to run this in ~2 mins on flytekit 1.1.x, but since upgrading this stage is stalling for over 2-3 hrs. It also takes ~90 seconds to read this dataframe in a jupyter notebook We're noticing an interesting memory usage pattern here as well w/ memory inching upwards as the task executes. The CPU (currently 1) is maxed out towards the start of execution Any thoughts on what might have caused this? We're also about to try rolling back flytekit to see if that resolves things

@elegant-australia-91422, interesting. In this particular case we narrowed this down to a pandas behavior (more specifically, the call to

describe

takes a long time to run). Can you say more about what you're seeing (in a separate thread)?