BigQuery加载和传输作业文件限制。在使用BigQuery加载或传输作业时，文件大小和数量都有限制。要解决这个问题，可以分割文件或使用Cloud Storage作为中介。

代码示例：

使用Cloud Storage作为中介：

from google.cloud import bigquery

client = bigquery.Client()

# Set the configuration options.
job_config = bigquery.LoadJobConfig(
    source_format=bigquery.SourceFormat.NEWLINE_DELIMITED_JSON,
    write_disposition=bigquery.WriteDisposition.WRITE_TRUNCATE,
    create_disposition=bigquery.CreateDisposition.CREATE_IF_NEEDED,
)

# Set the destination table.
table_ref = client.dataset('my_dataset').table('my_table')

# Set the Cloud Storage URL.
uri = 'gs://my_bucket/my_file_*.json'

# Load the data from Cloud Storage.
load_job = client.load_table_from_uri(
    uri,
    table_ref,
    job_config=job_config,
)

# Wait for the job to complete.
load_job.result()

文件分割：

from google.cloud import bigquery

client = bigquery.Client()

# Set the configuration options.
job_config = bigquery.LoadJobConfig(
    source_format=bigquery.SourceFormat.NEWLINE_DELIMITED_JSON,
    write_disposition=bigquery.WriteDisposition.WRITE_TRUNCATE,
    create_disposition=bigquery.CreateDisposition.CREATE_IF_NEEDED,
)

# Set the destination table.
table_ref = client.dataset('my_dataset').table('my_table')

# Load the data from multiple files.
load_jobs = []
for i in range(10):
    filename = 'my_file_{0}.json'.format(i)
    with open(filename, 'rb') as source_file:
        load_job = client.load_table_from_file(
            source_file,
            table_ref,
            job_config=job_config,
        )
    load_jobs.append(load_job)

# Wait for the jobs to complete.
for load_job in load_jobs:
    load_job.result()