# pg_statviz `pg_statviz` is a minimalist extension and utility pair for time series analysis and visualization of PostgreSQL internal statistics. Created for snapshotting PostgreSQL's cumulative and dynamic statistics and performing time series analysis on them. The accompanying utility can produce visualizations for selected time ranges on the stored stats snapshots, enabling the user to track PostgreSQL performance over time and potentially perform tuning or troubleshooting. ## Design Philosophy Designed with the [K.I.S.S.](https://en.wikipedia.org/wiki/KISS_principle) and [UNIX](https://en.wikipedia.org/wiki/Unix_philosophy) philosophies in mind, `pg_statviz` aims to be a modular, minimal and unobtrusive tool that does only what it's meant for: create snapshots of PostgreSQL statistics for visualization and analysis. To this end, a utility is provided for retrieving the stored snapshots and creating with them simple visualizations using [pandas](https://pandas.pydata.org/) and [Matplotlib](https://github.com/matplotlib/matplotlib). ## Installing the extension ### Red Hat Enterprise Linux (v8.0+) / Fedora (37+) 1. Configure the PostgreSQL Yum repository for your Linux distribution, as [explained here](https://www.postgresql.org/download/linux/redhat). 2. Use `dnf` or `yum` to install the extension for your PostgreSQL version: sudo dnf install pg_statviz_extension- OR sudo yum install pg_statviz_extension- ### PGXN (PostgreSQL Extension Network) The extension is available on [PGXN](https://pgxn.org/dist/pg_statviz/). To install from PGXN, either download the zip file and install manually or use the [PGXN Client](https://pgxn.github.io/pgxnclient/) to install: pgxn install pg_statviz ### Manual installation To install manually, clone this repository locally: git clone https://github.com/vyruss/pg_statviz.git This will install the extension in the appropriate location for your system (`$SHAREDIR/extension`): cd pg_statviz sudo make install ### Enabling the extension The extension can now be enabled inside the appropriate database like this, e.g. from `psql`: \c mydatabase CREATE EXTENSION pg_statviz; This will create the needed tables and functions under schema `pgstatviz` (note the lack of underscore in the schema name). ## Installing the utility The visualization utility can be installed from [PyPi](https://pypi.org/project/pg_statviz/): pip install pg_statviz The utility is also available in the [PostgreSQL Yum Repository](https://www.postgresql.org/download/linux/redhat/) and can be installed using `dnf` or `yum`: sudo dnf install pg_statviz OR sudo yum install pg_statviz ### Requirements Python 3.9+ is required for the visualization utility. ## Usage The extension can be used by superusers, or any user that has `pg_monitor` role privileges. To take a snapshot, e.g. from `psql`: SELECT pgstatviz.snapshot(); [comment]:: NOTICE: created pg_statviz snapshot snapshot ------------------------------- 2024-06-27 11:04:58.055453+00 (1 row) Older snapshots and their associated data can be removed using any time expression. For example, to remove data more than 90 days old: DELETE FROM pgstatviz.snapshots WHERE snapshot_tstamp < CURRENT_DATE - 90; Or all snapshots can be removed like this: SELECT pgstatviz.delete_snapshots(); [comment]:: NOTICE: truncating table "snapshots" NOTICE: truncate cascades to table "buf" NOTICE: truncate cascades to table "conf" NOTICE: truncate cascades to table "conn" NOTICE: truncate cascades to table "lock" NOTICE: truncate cascades to table "io" NOTICE: truncate cascades to table "wait" NOTICE: truncate cascades to table "wal" NOTICE: truncate cascades to table "db" delete_snapshots ------------------ (1 row) The `pg_monitor` role can be assigned to any user: GRANT pg_monitor TO myuser; ## Scheduling Periodic snapshots can be set up with any job scheduler. For example with `cron`: crontab -e -u postgres Inside the `postgres` user's crontab, add this line to take a snapshot every 15 minutes: */15 * * * * psql -c -d mydatabase "SELECT pgstatviz.snapshot()" >/dev/null 2>&1 ## Visualization Potentially very large numbers of data points can be visualized with the aid of pandas resampling, displaying the mean value over 100 plot points as a default. The visualization utility can be called like a PostgreSQL command line tool: pg_statviz --help [comment]:: usage: pg_statviz [--help] [--version] [--dbname DBNAME] [-h HOSTNAME] [--port PORT] [-u USERNAME] [--password] [--daterange FROM TO] [-o OUTPUTDIR] {analyze,buf,cache,checkp,conn, io,lock,tuple,wait,wal,xact} ... run all analysis modules positional arguments: {analyze,buf,cache,checkp,conn,io,lock,tuple,wait,wal,xact} analyze run all analysis modules buf run buffers written analysis module cache run cache hit ratio analysis module checkp run checkpoint analysis module conn run connection count analysis module io run I/O analysis module lock run locks analysis module tuple run tuple count analysis module wait run wait events analysis module wal run WAL generation analysis module xact run transaction count analysis module options: --help --version show program's version number and exit -d DBNAME, --dbname DBNAME database name to analyze (default: 'myuser') -h HOSTNAME, --host HOSTNAME database server host or socket directory (default: '/var/run/postgresql') -p PORT, --port PORT database server port (default: '5432') -U USERNAME, --username USERNAME database user name (default: 'myuser') -W, --password force password prompt (should happen automatically) (default: False) -D FROM TO, --daterange FROM TO date range to be analyzed in ISO 8601 format e.g. 2024-01-01T00:00 2024-01-01T23:59 (default: []) -O OUTPUTDIR, --outputdir OUTPUTDIR output directory (default: -) ### Specific module usage pg_statviz conn --help [comment]:: usage: pg_statviz conn [-h] [-d DBNAME] [--host HOSTNAME] [-p PORT] [-U USERNAME] [-W] [-D FROM TO] [-O OUTPUTDIR] [-u [USERS ...]] run connection count analysis module options: -h, --help show this help message and exit -d DBNAME, --dbname DBNAME database name to analyze (default: 'myuser') --host HOSTNAME database server host or socket directory (default: '/var/run/postgresql') -p PORT, --port PORT database server port (default: '5432') -U USERNAME, --username USERNAME database user name (default: 'myuser') -W, --password force password prompt (should happen automatically) (default: False) -D FROM TO, --daterange FROM TO date range to be analyzed in ISO 8601 format e.g. 2024-01-01T00:00 2024-01-01T23:59 (default: []) -O OUTPUTDIR, --outputdir OUTPUTDIR output directory (default: -) -u [USERS ...], --users [USERS ...] user name(s) to plot in analysis (default: []) ### Example: pg_statviz buf --host localhost -d postgres -U postgres -D 2024-06-24T23:00 2024-06-26 ### Produces: ![buf output sample](src/pg_statviz/libs/pg_statviz_localhost_5432_buf.png) [comment]:: ![buf output sample (rate)](src/pg_statviz/libs/pg_statviz_localhost_5432_buf_rate.png) ## Schema The `pg_statviz` extension stores its data in the following tables: Table | Description --- | --- `pgstatviz.snapshots` | Timestamped snapshots `pgstatviz.buf` | Buffer, checkpointer and background writer data `pgstatviz.conf` | PostgreSQL server configuration data `pgstatviz.conn` | Connection data `pgstatviz.db` | PostgreSQL server and database statistics `pgstatviz.io` | I/O stats data `pgstatviz.lock` | Locks data `pgstatviz.wait` | Wait events data `pgstatviz.wal` | WAL generation data ## Export data To dump the captured data, e.g. for analysis on a different machine, run: pg_dump -d -a -O -t pgstatviz.* > pg_statviz_data.dump Load it like this on the target database (which should have `pg_statviz` installed) : psql -d -f pg_statviz_data.dump Alternatively, `pg_statviz` internal tables can also be exported to a tab separated values (TSV) file for use by other tools: psql -d -c "COPY pgstatviz.conn TO STDOUT CSV HEADER DELIMITER E'\t'" > conn.tsv These can then be loaded into another database like this, provided the tables exist (installing the extension will create them): psql -d -c "COPY pgstatviz.conn FROM STDIN CSV HEADER DELIMITER E'\t'" < conn.tsv