revious example: Connection 1> ANALYZE SELECT ... ; Connection 2> SHOW ANALYZE FORMAT=JSON FOR ; ANALYZE { "r_query_time_in_progress_ms": 30727, "query_block": { "select_id": 1, "r_loops": 1, "nested_loop": [ { "table": { "table_name": "customer", "access_type": "ALL", "possible_keys": ["PRIMARY"], "r_loops": 1, "rows": 199786, "r_rows": 109994, "r_table_time_ms": 232.699, "r_other_time_ms": 46.355, ^ Now, ANALYZE prints timing information in members named r_..._time_ms. One can see that so far, out of 30 seconds, only 232 millisecond were spent in reading the customer table. The bottleneck is elsewhere... "filtered": 100, "r_filtered": 9.085950143, "attached_condition": "customer.`status` = 'GOLD'" } }, { "table": { "table_name": "orders", "access_type": "ref", "possible_keys": ["cust_id"], "key": "cust_id", "key_length": "5", "used_key_parts": ["cust_id"], "ref": ["test.customer.cust_id"], "r_loops": 9994, "rows": 1, "r_rows": 99.99779868, "r_table_time_ms": 29460.609, "r_other_time_ms": 986.842, ^ 29.4 seconds were spent reading the orders table (and 0.986 seconds in processing the obtained rows). Now we can see where the query is spending time. "filtered": 100, "r_filtered": 100 } } ] } } URL: https://mariadb.com/kb/en/show-analyze/https://mariadb.com/kb/en/show-analyze/