This is much faster on my local machine but the report below shows how well my database optimizations are working on AWS hardware.
Database Instance Class: db.t2.micro Database Engine: Postgres 9.6.2
The test is not a table with a single colum. There are 3 integer columns and 10 string columns. I can't give away too much for information for security purposes.
| table name read imported errors total time | |
| ----------------------- --------- --------- --------- -------------- | |
| fetch 0 0 0 0.008s | |
| ----------------------- --------- --------- --------- -------------- | |
| audience_entries 25612472 25612472 0 12m0.165s | |
| ----------------------- --------- --------- --------- -------------- | |
| Files Processed 26 26 0 0.018s | |
| COPY Threads Completion 78 78 0 9m22.615s | |
| ----------------------- --------- --------- --------- -------------- | |
| Total import time 25612472 25612472 0 9m24.299s |
Same thing happened when I imported a 33 million row file. You can see that my shell returned 12m17s as the execution time. 🤷♂️