PGBadger | Postgresql log analysis made easy

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The need for postgresql log analysis?#

While writing sql for any flow, primary focus is on the correctness of the query and not on the performance of the query. Performance issues creep in when updating/iterating a flow iteratively over multiple development cycles.Query performance is important to analyze during scaling. This is where query log analysis comes in.

In one of our cases, a complicated workflow was significantly slow when we load tested it. We were trying to figure out the bottleneck both in code structure and with query performance. Our go-to tool for query performance analysis became pgBadger.

What is a postgresql query log?#

A query log is a log of all the executed db queries. A good practice is to enable query logging on the database server. This helps in debugging and performance analysis. The query log contains the following information:

  • Query
  • database user
  • database name
  • date and time of query execution
  • time taken to execute the query etc.

What is pgBadger?#

The most succinct description comes from pgBadger itself:

pgBadger is a PostgreSQL log analyzer built for speed with fully detailed reports and professional rendering. It outperforms any other PostgreSQL log analyzer.

links -

How to use pgBadger#

Install pgBadger#

brew install pgbadger Link

Set up logging in postgresql#

There are multiple ways to do it (You can refer to pgbadger documentation for more details pgBadger postgres configuration ):

1. Edit postgresql.conf

Edit the postgresql.conf file to enable logging. Either edit the file directly or use the ALTER SYSTEM command.

# Edit postgresql.conf
vim /usr/local/var/postgres/postgresql.conf

# OR

# Edit postgresql.conf using ALTER SYSTEM
psql -U postgres -c "ALTER SYSTEM SET log_destination = 'stderr';"
psql -U postgres -c "ALTER SYSTEM SET logging_collector = 'on';"
psql -U postgres -c "ALTER SYSTEM SET log_directory = 'logs';"
psql -U postgres -c "ALTER SYSTEM SET log_filename = 'postgresql.log';"
psql -U postgres -c "ALTER SYSTEM SET log_min_duration_statement = 0;"
psql -U postgres -c "ALTER SYSTEM SET log_line_prefix = '%t [%p]: [%l-1] user=%u,db=%d,app=%a,client=%h ';"
psql -U postgres -c "ALTER SYSTEM SET log_checkpoints = 'on';"
psql -U postgres -c "ALTER SYSTEM SET log_connections = 'on';"
psql -U postgres -c "ALTER SYSTEM SET log_disconnections = 'on';"
psql -U postgres -c "ALTER SYSTEM SET log_lock_waits = 'on';"
psql -U postgres -c "ALTER SYSTEM SET log_temp_files = 0;"
psql -U postgres -c "ALTER SYSTEM SET log_autovacuum_min_duration = 0;"
psql -U postgres -c "ALTER SYSTEM SET log_error_verbosity = 'verbose';"

Make sure you edit the postgresql.conf file and not the file. Postgres generates file and the file will be overwritten when the server restarts.


2. Update docker-compose.yml

Update docker-compose.yaml file to add the following logging configuration:

  image: 'postgres:11'
    - '5432:5432' # machine:image
      'log_line_prefix=%t [%p]: [%l-1] user=%u,db=%d,app=%a,client=%h ',
  TZ: 'Europe/Stockholm'
POSTGRES_USER: 'postgres'
POSTGRES_DB: 'db_dev'
  - database-data:/var/lib/postgresql/data/ # persist data even if container shuts down
  - ./:/var/lib/postgresql/data/logs/ # persist logs even if container shuts down, logs will show up in the current directory
  - ./postgresql.conf:/etc/postgresql/postgresql.conf # custom postgresql config
  - default

Restart the database

docker-compose down && docker-compose up -d Link

Generate some queries#

Start using application and generate some logs. Alternatively, generate some logs by running some queries manually OR even running load tests if available.

Run pgBadger#

Just ask pgBadger to digest logs and create a report at ./report.html.

pgbadger -I -O ./report.html ./postgresql.log Link

View the report#

Open the report in your browser and you will see something like this:

pgbadger report

It has heaps of information. You can see the top queries, slow queries, errors, etc.


pgBadger is a great tool to analyze postgresql query logs. It is easy to use and provides a lot of information. It is a must-have tool for any postgresql developer.

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