The query runs normally for the public dataset, but returns an error for the private dataset.
%bigquery
#standardSQL
select idn
from privit_table
-> output : SQL Execution returned an error!
(However, this query is not a query problem because it outputs normal results when running on a big query.)
%bigquery
#standardSQL
SELECT departure_airport,count(case when departure_delay>0 then 1 else 0 end) as no_of_delays
FROM `bigquery-samples.airline_ontime_data.flights`
group by departure_airport
order by 2 desc
limit 10
-> output : The query results are successfully output.
I'm currently running zeppelin-daemon on ubuntu and connecting from a remote server, and I set the environment variable for key.json through export GOOGLE_APPLICATION_CREDENTIALS.
The https://zeppelin.apache.org/docs/latest/storage/storage.html#notebook-storage-in-gcs link written as a reference in the official DOCS document is not currently working, so I have no reference.
Why does it work well on public datasets and only on private datasets get SQL Execution returned an error!? There was someone in StackOverflow who was in the same situation, but the replies didn't help. Please help me!
Hi @sseozy ,
Since queries against public datasets are working, your core setup is likely sound. The trouble seems to be specifically related to the permissions or configuration needed for private datasets.
Troubleshooting Steps:
Authentication & Authorization
echo $GOOGLE_APPLICATION_CREDENTIALS
Network Considerations
Diagnostic Tests:
gcloud auth activate-service-account --key-file=path/to/your/key.json
gcloud projects list
bq query --use_legacy_sql=false 'SELECT * FROM `your-project.your-dataset.private_table` LIMIT 10'
Logging for Insights
Additional Tips
Command-line Validation works very successfully. We also checked that the BigQuery project charges bytes when running bigquery on zeppelin. However, only SQLExecution returned an error! is still displayed on the web.
I was sure it wasn't a big query issue with your response. I'll take advantage of the Zeppelin community. Thank you!
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