Steps to run program:
- Use scripts below to create 4 (author_sum, author_name, error and success) views.
- Run python3 log_anaylsis.py
view: Count of articles w/ author ID
create view author_sum as select slug, author, count(log.path)::numeric as sum from articles, log where log.path = '/article/' || articles.slug group by articles.author, articles.slug order by articles.author;
| Column | Type |
|---|---|
| slug | text |
| sum | bigint |
author_name view: Link author ID to real name.
create view author_name as select authors.name, articles.slug from authors, articles where authors.id=articles.author group by authors.name, articles.slug;
| Column | Type |
|---|---|
| name | text |
| slug | text |
error view: Count days with errors in the connections
create view error as select date(time), count(*) as errors from log where status not like '200%' group by date(time) order by date(time);
| Column | Type |
|---|---|
| date_part | double precision |
| errors | bigint |
success view: Count days with errors in the connections
create view success as select date(time), count(*) as success from log where status like '200%' group by date(time) order by date(time);
| Column | Type |
|---|---|
| date_part | double precision |
| success | bigint |