To monitor the Parser performance in ClickHouse, you can use the system.query_log system table, which contains information about all queries executed in the cluster. Here’s an example SQL code that you can use to monitor the Parser performance:
SELECT
query,
query_duration_ms,
parse_duration_ns,
total_rows_approx,
read_rows_approx,
written_rows_approx
FROM system.query_log
WHERE type = 1
ORDER BY event_time DESC
LIMIT 100
In this code, we select several columns from the system.query_log table, including the query text, query duration, parse duration, and the approximate number of total, read, and written rows for the query. We filter the results using the type = 1 condition, corresponding to queries parsed successfully. Finally, we sort the results by event time in descending order and limit the output to the last 100 queries.
By monitoring the Parser performance in this way, you can gain insights into the efficiency of the parsing process and identify any performance bottlenecks or issues. For example, if you notice that the parse duration is consistently high for certain queries, you may need to investigate and optimize the query structure or workload to improve performance.