上次我们说到mysql的一些sql查询方面的优化，包括查看explain执行计划，分析索引等等。今天我们分享一些 分析mysql表读写、索引等等操作的sql语句。

闲话不多说，直接上代码：

反映表的读写压力

SELECT file_name AS file,count_read,sum_number_of_bytes_read AS total_read,count_write,sum_number_of_bytes_write AS total_written,(sum_number_of_bytes_read + sum_number_of_bytes_write) AS total FROM performance_schema.file_summary_by_instanceORDER BY sum_number_of_bytes_read+ sum_number_of_bytes_write DESC;

反映文件的延迟

SELECT (file_name) AS file,count_star AS total,CONCAT(ROUND(sum_timer_wait / 3600000000000000, 2), 'h') AS total_latency,count_read,CONCAT(ROUND(sum_timer_read / 1000000000000, 2), 's') AS read_latency,count_write,CONCAT(ROUND(sum_timer_write / 3600000000000000, 2), 'h')AS write_latency FROM performance_schema.file_summary_by_instanceORDER BY sum_timer_wait DESC;

table 的读写延迟

SELECT object_schema AS table_schema, object_name AS table_name, count_star AS total, CONCAT(ROUND(sum_timer_wait / 3600000000000000, 2), 'h') as total_latency, CONCAT(ROUND((sum_timer_wait / count_star) / 1000000, 2), 'us') AS avg_latency, CONCAT(ROUND(max_timer_wait / 1000000000, 2), 'ms') AS max_latency FROM performance_schema.objects_summary_global_by_typeORDER BY sum_timer_wait DESC;

查看表操作频度

SELECT object_schema AS table_schema,object_name AS table_name,count_star AS rows_io_total,count_read AS rows_read,count_write AS rows_write,count_fetch AS rows_fetchs,count_insert AS rows_inserts,count_update AS rows_updates,count_delete AS rows_deletes, CONCAT(ROUND(sum_timer_fetch / 3600000000000000, 2), 'h') AS fetch_latency, CONCAT(ROUND(sum_timer_insert / 3600000000000000, 2), 'h') AS insert_latency, CONCAT(ROUND(sum_timer_update / 3600000000000000, 2), 'h') AS update_latency, CONCAT(ROUND(sum_timer_delete / 3600000000000000, 2), 'h') AS delete_latency FROM performance_schema.table_io_waits_summary_by_tableORDER BY sum_timer_wait DESC ;

索引状况

SELECT OBJECT_SCHEMA AS table_schema,OBJECT_NAME AS table_name,INDEX_NAME as index_name,COUNT_FETCH AS rows_fetched,CONCAT(ROUND(SUM_TIMER_FETCH / 3600000000000000, 2), 'h') AS select_latency,COUNT_INSERT AS rows_inserted,CONCAT(ROUND(SUM_TIMER_INSERT / 3600000000000000, 2), 'h') AS insert_latency,COUNT_UPDATE AS rows_updated,CONCAT(ROUND(SUM_TIMER_UPDATE / 3600000000000000, 2), 'h') AS update_latency,COUNT_DELETE AS rows_deleted,CONCAT(ROUND(SUM_TIMER_DELETE / 3600000000000000, 2), 'h')AS delete_latencyFROM performance_schema.table_io_waits_summary_by_index_usageWHERE index_name IS NOT NULLORDER BY sum_timer_wait DESC;

全表扫描情况

SELECT object_schema,object_name,count_read AS rows_full_scanned FROM performance_schema.table_io_waits_summary_by_index_usageWHERE index_name IS NULLAND count_read > 0ORDER BY count_read DESC;

没有使用的index

SELECT object_schema,object_name,index_nameFROM performance_schema.table_io_waits_summary_by_index_usage WHERE index_name IS NOT NULLAND count_star = 0AND object_schema not in ('mysql','v_monitor')AND index_name <> 'PRIMARY' ORDER BY object_schema, object_name;

糟糕的sql问题摘要

SELECT (DIGEST_TEXT) AS query,SCHEMA_NAME AS db,IF(SUM_NO_GOOD_INDEX_USED > 0 OR SUM_NO_INDEX_USED > 0, '*', '') AS full_scan,COUNT_STAR AS exec_count,SUM_ERRORS AS err_count,SUM_WARNINGS AS warn_count,(SUM_TIMER_WAIT) AS total_latency,(MAX_TIMER_WAIT) AS max_latency,(AVG_TIMER_WAIT) AS avg_latency,(SUM_LOCK_TIME) AS lock_latency,format(SUM_ROWS_SENT,0) AS rows_sent,ROUND(IFNULL(SUM_ROWS_SENT / NULLIF(COUNT_STAR, 0), 0)) AS rows_sent_avg,SUM_ROWS_EXAMINED AS rows_examined,ROUND(IFNULL(SUM_ROWS_EXAMINED / NULLIF(COUNT_STAR, 0), 0)) AS rows_examined_avg,SUM_CREATED_TMP_TABLES AS tmp_tables,SUM_CREATED_TMP_DISK_TABLES AS tmp_disk_tables,SUM_SORT_ROWS AS rows_sorted,SUM_SORT_MERGE_PASSES AS sort_merge_passes,DIGEST AS digest,FIRST_SEEN AS first_seen,LAST_SEEN as last_seenFROM performance_schema.events_statements_summary_by_digest dwhere dORDER BY SUM_TIMER_WAIT DESClimit 20;

掌握这些sql，你能轻松知道你的库那些表存在问题，然后考虑怎么去优化。

总结

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