Fix GCP BigQuery Load Parquet Errors
When working with GCP BigQuery, you may encounter a configuration error that prevents your data pipeline or messaging system from working. This guide explains the most common mistake with load parquet and shows the exact fix.
A Common Mistake
Loading a Parquet file with column names containing unsupported characters (spaces, special chars), causing load failures.
The incorrect command:
bq load --source_format=PARQUET my_project:my_dataset.my_table data.parquet
# Parquet column: 'Customer Name' (with space)
Error output:
Error: Invalid field name: "Customer Name". BigQuery field names must contain only letters, numbers, and underscores. Spaces, hyphens, and special characters are not allowed in column names.
The Correct Approach
The right way to configure load parquet in GCP BigQuery:
# Rename column in Spark/Pandas before writing Parquet:
# df = df.withColumnRenamed("Customer Name", "customer_name")
# df.write.parquet("data.parquet")
bq load --source_format=PARQUET my_project:my_dataset.my_table data.parquet
Successful result:
Loaded 100000 rows successfully.
Column name 'customer_name' is valid. BigQuery enforces strict naming conventions for all loaded data.
How to Prevent This
Use valid column names: letters, numbers, underscores only. Max 300 characters. Rename columns before export to Parquet. Parquet supports nested and repeated types, compression (snappy, gzip, zstd), and columnar pruning for efficient loading.
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