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[BUG] Structured Dataset create with remote uri and read directly will fail #5954
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Hi @Future-Outlier, If I'm not mistaken, steps to reproduce the error are described as follows:
Error MessageDoes this match your experience? Thanks. |
yes and this will not work in local too. |
my suggestion is that we should make local execution work first. |
For the local run, do you mean loading the parquet file from the local file system, instead of s3? Some Observations
As suggested here, |
I mean make my example above works in the local execution.
|
Okay, let me try it, thanks! |
Follow-up IssuesAfter testing some cases, I observe two more errors:
@task
def return_sd() -> StructuredDataset:
sd = StructuredDataset(
df=pd.DataFrame({
"name": ["hanru", "jiawei"],
"height": [190, 172]
})
)
print("sd:", sd.open(pd.DataFrame).all())
return sd
@task
def return_sd() -> StructuredDataset:
sd = StructuredDataset(
uri="./tmp/df.parquet",
file_format="parquet"
)
print("sd:", sd.open(pd.DataFrame).all())
return sd Both of the cases are expected to work. I think they're highly related to this issue. But, I will fix the main error in the original proposal first. |
Very nice, let's push it this week, will reach out you |
in the follow-up issues, i think the second one is more important than the first. The first is a bit odd, esp if the type of the dataframe is different (polars, etc.) Yeah, to what @pingsutw said, this issue affects files and folders also. cc @eapolinario since he's trying to spend some time on this. I think this is not so much a bug (it is that too) as it is a failure in ux design. |
Hi @wild-endeavor, Thanks for your reply. The newly merged PR focuses on solving the local run of |
Describe the bug
This case should work.
Expected behavior
This should work.
Additional context to reproduce
Screenshots
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