I am writing Python code with the BigQuery Client API, and attempting to use the async query code (written everywhere as a code sample), and it is failing at the fetch_data() method call. Python errors out with the error:
ValueError: too many values to unpack
So, the 3 return values (rows, total_count, page_token) seem to be the incorrect number of return values. But, I cannot find any documentation about what this method is supposed to return -- besides the numerous code examples that only show these 3 return results.
Here is a snippet of code that shows what I'm doing (not including the initialization of the 'client' variable or the imported libraries, which happen earlier in my code).
#---> Set up and start the async query job
job_id = str(uuid.uuid4())
job = client.run_async_query(job_id, query)
job.destination = temp_tbl
job.write_disposition = 'WRITE_TRUNCATE'
job.begin()
print 'job started...'
#---> Monitor the job for completion
retry_count = 360
while retry_count > 0 and job.state != 'DONE':
print 'waiting for job to complete...'
retry_count -= 1
time.sleep(1)
job.reload()
if job.state == 'DONE':
print 'job DONE.'
page_token = None
total_count = None
rownum = 0
job_results = job.results()
while True:
# ---- Next line of code errors out...
rows, total_count, page_token = job_results.fetch_data( max_results=10, page_token=page_token )
for row in rows:
rownum += 1
print "Row number %d" % rownum
if page_token is None:
print 'end of batch.'
break
What are the specific return results I should expect from the job_results.fetch_data(...) method call on an async query job?
Looks like you are right! The code no longer return these 3 parameters.
As you can see in this commit from the public repository, fetch_data now returns an instance of the HTTPIterator class (guess I didn't realize this before as I have a docker image with an older version of the bigquery client installed where it does return the 3 values).
The only way that I found to return the results was doing something like this:
iterator = job_results.fetch_data()
data = []
for page in iterator._page_iter(False):
data.extend([page.next() for i in range(page.num_items)])
Notice that now we don't have to manage pageTokens
anymore, it's been automated for the most part.
[EDIT]:
I just realized you can get results by doing:
results = list(job_results.fetch_data())
Got to admit it's way easier now then it was before!
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