Monitoring Your Cluster Using statd

A ClustrixDB instance obtains statistics using statd (/opt/clustrix/bin/statd.py), a cluster-wide statistics aggregation and tracking mechanism. The resulting statistics are used for the graphical displays within the ClustrixGUI Administration UI and may also be queried directly using SQL.

The statd script runs on each node but only active instance is on the node with the highest node ID and collects statistics from internal system tables and populates the tables in the clustrix_statd database:

• hotness_current: table and index read and write stats collected every 5 minutes
• hotness_history: table and index read and write stats aggregated into 5 minute stats with stats older than one day rolled into hourly stats, kept for 7 days
• qpc_current: query stats collected every minute
• qpc_history: query stats aggregated into 5 minute stats, with stats older than one day rolled into hourly stats, kept for 7 days
• statd_current: cluster stats collected every 30 seconds
• statd_history: cluster stats aggregated into 5 minute stats, with stats older than one day rolled into hourly stats, kept for 7 days.

The frequency of statistics gathering is tunable via the statd_config table (see below), but we recommend to leave them with their default values.

In addition, the statd_metadata table contains the current and historical statd IDs and names that can be used to join back to the statd_history data.

Querying statd Statistics

Sample statd_current query

sql> SELECT name, value
     FROM clustrix_statd.statd_current
     NATURAL JOIN clustrix_statd.statd_metadata
     WHERE name LIKE '%nodes_in_quorum%'
     ORDER BY name; 

Sample statd_history query

sql> SELECT timestamp, value, name 
     FROM clustrix_statd.statd_history
     NATURAL JOIN clustrix_statd.statd_metadata 
     WHERE name LIKE 'clustrix.cpu.load_avg%'
       AND timestamp BETWEEN '2019-01-01 09:30:01'
       AND '2019-05-15 10:30:01'
     ORDER BY timestamp, name; 

Sample qpc_history query

The query below looks at queries that have high average rows read between the specified timestamps as queries that read many rows may be candidates for optimizing. 

sql>  SELECT sum(exec_count) as exec_count,
       round(avg(avg_rows_read)) as avg_rows_read,
       sum(rows_read) as rows_read,
       round(avg(avg_exec_ms)) as avg_exec_ms,
       left(statement,60)
     FROM clustrix_statd.qpc_history
     WHERE timestamp BETWEEN '2019-06-01 00:00:00'
     AND '2019-06-01 23:59:59'
     GROUP BY 5 
 ORDER by 2 desc
     LIMIT 20; 

Sample hotness_history query

The query below looks at tables and indexes that have the most reads over the last 24 hours:

sql> SELECT Sum(reads) AS reads, 
       Sum(writes) AS writes, 
       DATABASE, 
       `table`, 
       `index`, 
       total_replicas 
     FROM clustrix_statd.hotness_history 
     WHERE timestamp >now() - INTERVAL 1 day 
     AND DATABASE NOT IN ('clustrix_statd', '_replication', 'clustrix_ui', 'system', 'clustrix_dbi') 
     GROUP BY `table`, `index` 
     ORDER BY 1 desc
     LIMIT 50; 

Useful Statistics

There are numerous statistics collected for your cluster. Use the following query to determine all available statd statistics: 

sql> SELECT name
     FROM clustrix_statd.statd_metadata
     ORDER BY name; 

The following tables highlight useful statistics. Additional stats can be found at statd Metrics.

Performance 

Replication

Data Protection

Cluster Capacity

Tuning the Frequency of statd Collection

The frequency of statistics collection is configurable within the statd_config table. Contact Clustrix Support for assistance in modifying these values.

sql> select * from statd_config order by name;
+---------------------------------------+-------+
| name                                  | value |
+---------------------------------------+-------+
| qpc_current_interval_s                |    60 |
| qpc_history_interval_s                |   300 |
| qpc_history_top_n                     |   100 |
| qpc_rollup_interval_s                 |  3600 |
| repartition_history_interval_s        | 43200 |
| SpaceUsedBreakdown_current_interval_s |   900 |
| stats_current_interval_s              |    30 |
| stats_history_interval_s              |   300 |
+---------------------------------------+-------+
8 rows in set (0.00 sec) 

Data Retention

The hotness_history, qpc_history and statd_history tables are partition tables and data older than 7 days are dropped.  If you need to longer data retention, you can have a cron job to extract the data accordingly and store it elsewhere.

Third Party Plugins

See also information for using:

• Nagios plugin 
• Cacti plugin
• Zabbix
• Grafana