Datasets:
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Error code: StreamingRowsError Exception: TypeError Message: Couldn't cast array of type string to null Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise return get_rows( File "/src/libs/libcommon/src/libcommon/utils.py", line 197, in decorator return func(*args, **kwargs) File "/src/services/worker/src/worker/utils.py", line 77, in get_rows rows_plus_one = list(itertools.islice(ds, rows_max_number + 1)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__ for key, pa_table in self.generate_tables_fn(**gen_kwags): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 93, in _generate_tables yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 71, in _cast_table pa_table = table_cast(pa_table, self.info.features.arrow_schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2245, in cast_table_to_schema arrays = [ File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2246, in <listcomp> cast_array_to_feature( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in wrapper return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in <listcomp> return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2102, in cast_array_to_feature return array_cast( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1797, in wrapper return func(array, *args, **kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1948, in array_cast raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}") TypeError: Couldn't cast array of type string to null
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Dataset Card for Flickr
217.646.487 images with lat lon coordinates from Flickr. This repo is a filtered version of https://huggingface.co/datasets/bigdata-pw/Flickr for all rows containing a valid lat lon pair.
Filter Process
It was harder than expected. The main problem is that sometimes the connection to HF hub breaks. Afaik DuckDB cannot quite deal with this very well, so this code does not work:
import duckdb
duckdb.sql("INSTALL httpfs;LOAD httpfs;") # required extension
df = duckdb.sql(f"SELECT latitude, longitude FROM 'hf://datasets/bigdata-pw/Flickr/*.parquet' WHERE latitude IS NOT NULL AND longitude IS NOT NULL").df()
Instead, I used a more granular process to make sure I really got all the files.
import duckdb
import pandas as pd
from tqdm import tqdm
import os
# Create a directory to store the reduced parquet files
output_dir = "reduced_flickr_data"
if not os.path.exists(output_dir):
os.makedirs(output_dir)
# Install and load the httpfs extension (only needs to be done once)
try:
duckdb.sql("INSTALL httpfs; LOAD httpfs;") # required extension
except Exception as e:
print(f"httpfs most likely already installed/loaded: {e}") # most likely already installed
duckdb.sql("SET enable_progress_bar = false;")
# Get a list of already downloaded files to make the script idempotent
downloaded_files = set(os.listdir(output_dir))
for i in tqdm(range(0, 5150), desc="Downloading and processing files"):
part_number = str(i).zfill(5) # Pad with zeros to get 00000 format
file_name = f"part-{part_number}.parquet"
output_path = os.path.join(output_dir, file_name)
# Skip if the file already exists
if file_name in downloaded_files:
#print(f"Skipping {file_name} (already downloaded)") # Optional: Uncomment for more verbose output.
continue
try:
# Construct the DuckDB query, suppressing the built-in progress bar
query = f"""
SELECT *
FROM 'hf://datasets/bigdata-pw/Flickr/{file_name}'
WHERE latitude IS NOT NULL
AND longitude IS NOT NULL
AND (
(
TRY_CAST(latitude AS DOUBLE) IS NOT NULL AND
TRY_CAST(longitude AS DOUBLE) IS NOT NULL AND
(TRY_CAST(latitude AS DOUBLE) != 0.0 OR TRY_CAST(longitude AS DOUBLE) != 0.0)
)
OR
(
TRY_CAST(latitude AS VARCHAR) IS NOT NULL AND
TRY_CAST(longitude AS VARCHAR) IS NOT NULL AND
(latitude != '0' AND latitude != '0.0' AND longitude != '0' AND longitude != '0.0')
)
)
"""
df = duckdb.sql(query).df()
# Save the filtered data to a parquet file, creating the directory if needed.
df.to_parquet(output_path)
#print(f"saved part {part_number}") # optional, for logging purposes
except Exception as e:
print(f"Error processing {file_name}: {e}")
continue # Continue to the next iteration even if an error occurs
print("Finished processing all files.")
The first run took roughly 15 hours on my connection. When finished a handfull of files will have failed, for me less than 5. Rerun the script to add the missing files; it will finish in a minute.
Below the rest of the original dataset card.
Dataset Details
Dataset Description
Approximately 5 billion images from Flickr. Entries include URLs to images at various resolutions and available metadata such as license, geolocation, dates, description and machine tags (camera info).
- Curated by: hlky
- License: Open Data Commons Attribution License (ODC-By) v1.0
Citation Information
@misc{flickr,
author = {hlky},
title = {Flickr},
year = {2024},
publisher = {hlky},
journal = {Hugging Face repository},
howpublished = {\url{[https://huggingface.co/datasets/bigdata-pw/Flickr](https://huggingface.co/datasets/bigdata-pw/Flickr)}}
}
Attribution Information
Contains information from [Flickr](https://huggingface.co/datasets/bigdata-pw/Flickr) which is made available
under the [ODC Attribution License](https://opendatacommons.org/licenses/by/1-0/).
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