DuckDB provides a set of metrics that can be used to monitor the performance and health of the database. Metrics are named `⟨group⟩.⟨metric⟩`, e.g., `query.total_time` or `operator.timing`. The set of collected metrics is controlled with the [`tracked_metrics` setting](/docs/2.0/dev/profiling.html#pragmas), which takes a list of glob patterns, e.g., `['query.*', 'operator.timing']`. By default, all metrics are collected (`['*']`). The available metrics, along with their types and units, can be listed with the `duckdb_available_metrics()` table function: ```sql SELECT metric_name, metric_type, unit FROM duckdb_available_metrics(); ``` ## Examples The following example enables profiling, sets the output to a file and only collects the total query time along with the operator metrics. ```sql CREATE TABLE students (name VARCHAR, sid INTEGER); CREATE TABLE exams (eid INTEGER, subject VARCHAR, sid INTEGER); INSERT INTO students VALUES ('Mark', 1), ('Joe', 2), ('Matthew', 3); INSERT INTO exams VALUES (10, 'Physics', 1), (20, 'Chemistry', 2), (30, 'Literature', 3); SET enable_profiling = 'json'; SET profiling_output = '/path/to/file.json'; SET tracked_metrics = ['query.total_time', 'operator.*']; SELECT name FROM students JOIN exams USING (sid) WHERE name LIKE 'Ma%'; ``` The file's content after executing the query: ```json { "operator": [ { "extra_info": {}, "intermediate_rows": 0, "intermediate_size_bytes": 0, "timing": 5.458e-06, "type": "RESULT_COLLECTOR", "children": [ { "extra_info": { "Projections": "name", "Estimated Cardinality": "1" }, "intermediate_rows": 2, "intermediate_size_bytes": 40, "timing": 8.3e-08, "type": "PROJECTION", "children": [ { "extra_info": { "Join Type": "INNER", "Conditions": "sid = sid", "Estimated Cardinality": "1" }, "intermediate_rows": 2, "intermediate_size_bytes": 48, "timing": 4.4209e-05, "type": "HASH_JOIN", "children": [ ... "query": { "total_time": 0.001491167 } } ``` The second example collects all `query` and `planner` metrics, as well as the total time spent in the optimizers. ```sql SET tracked_metrics = ['query.*', 'planner.*', 'optimizer.total_time']; SELECT name FROM students JOIN exams USING (sid) WHERE name LIKE 'Ma%'; ``` The contents of the output file: ```json { "optimizer": { "total_time": 0.000179833 }, "planner": { "binding_time": 5e-05, "total_time": 6.8959e-05 }, "query": { "cpu_time": 5.8541999999999996e-05, "sql": "SELECT name FROM students JOIN exams USING (sid) WHERE name LIKE 'Ma%';\n", "total_intermediate_rows": 8, "total_intermediate_size_bytes": 136, "total_row_groups_scanned": 2, "total_row_groups_to_scan": 2, "total_rows_scanned": 6, "total_time": 0.001529 } } ```