I'm having issues executing the copy command to load data from S3 to Amazon's Redshift from python.
I have the following copy command:
copy moves from 's3://<my_bucket_name>/moves_data/2013-03-24/18/moves'
credentials 'aws_access_key_id=<key_id>;aws_secret_access_key=<key_secret>'
removequotes
delimiter ',';
When I execute this command using SQL Workbench/j everything works as expected, however when I try to execute this with python and psycopg2 the command pass OK but no data is loaded and no error is thrown.
tried the following two options (assume psycopg2 connection is OK because it is):
cursor.execute(copy_command)
cursor.copy_expert(copy_command, sys.stdout)
both pass with no warning yet data isn't loaded
Ideas?
Thanks
if you are using sqlalchemy, copy command will not auto commit by itself. this worked for me:
I have used this exact setup (psycopg2 + redshift + COPY) successfully. Did you commit afterwards? SQL Workbench defaults to auto-commit while psycopg2 defaults to opening a transaction, so the data won't be visible until you call commit() on your connection.
The full workflow is:
I don't believe that copy_expert() or any of the cursor.copy_* commands work with Redshift.
The syntax should be similar to DDL statements
First, make sure the transaction is committed.
you can ensure a transaction-commit with following way as well (ensuring releasing the resources),
When a connection exits the with block, if no exception has been raised by the block, the transaction is committed. In case of exception the transaction is rolled back.
Secondly, even doing commit does not help when the data to be loaded takes some long time and exceeds connect_timeout (and can't commit). So when explicit commit doesn't help, try with an increased timeout.