优化、分析Mysql表读写、索引等操作的sql语句效率优化问题

为什么要优化：

随着实际项目的启动，数据库经过一段时间的运行，最初的数据库设置，会与实际数据库运行性能会有一些差异，这时我们 就需要做一个优化调整。

数据库优化这个课题较大，可分为四大类：

》主机性能
》内存使用性能
》网络传输性能
》SQL语句执行性能【软件工程师】
下面列出一些数据库SQL优化方案：

（01）选择最有效率的表名顺序（笔试常考）

数据库的解析器按照从右到左的顺序处理FROM子句中的表名，FROM子句中写在最后的表将被最先处理，在FROM子句中包含多个表的情况下,你必须选择记录条数最少的表放在最后，如果有3个以上的表连接查询,那就需要选择那个被其他表所引用的表放在最后。

例如：查询员工的编号，姓名，工资，工资等级，部门名

select emp.empno,emp.ename,emp.sal,salgrade.grade,dept.dname
from salgrade,dept,emp
where (emp.deptno = dept.deptno) and (emp.sal between salgrade.losal and salgrade.hisal)

1)如果三个表是完全无关系的话，将记录和列名最少的表，写在最后，然后依次类推
2)如果三个表是有关系的话，将引用最多的表，放在最后，然后依次类推

（02）WHERE子句中的连接顺序（笔试常考）

数据库采用自右而左的顺序解析WHERE子句,根据这个原理,表之间的连接必须写在其他WHERE条件之左,那些可以过滤掉最大数量记录的条件必须写在WHERE子句的之右。

例如：查询员工的编号，姓名，工资，部门名

select emp.empno,emp.ename,emp.sal,dept.dname
from emp,dept
where (emp.deptno = dept.deptno) and (emp.sal > 1500)

（03）SELECT子句中避免使用*号

数据库在解析的过程中,会将*依次转换成所有的列名，这个工作是通过查询数据字典完成的，这意味着将耗费更多的时间

select empno,ename from emp;
（04）用TRUNCATE替代DELETE

（05）尽量多使用COMMIT

因为COMMIT会释放回滚点

（06）用WHERE子句替换HAVING子句

WHERE先执行，HAVING后执行

（07）多使用内部函数提高SQL效率

（08）使用表的别名

salgrade s

（09）使用列的别名

ename e

总之，数据库优化不是一天的课题，你得在长期工作实践中，进行反复测试与总结，希望学员们日后好好领会

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_instance
ORDER 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_instance
ORDER 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_type
ORDER 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_table
ORDER 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_latency
FROM performance_schema.table_io_waits_summary_by_index_usage
WHERE index_name IS NOT NULL
ORDER 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_usage
WHERE index_name IS NULL
AND count_read > 0
ORDER BY count_read DESC;
没有使用的index

SELECT object_schema,
object_name,
index_name
FROM performance_schema.table_io_waits_summary_by_index_usage
WHERE index_name IS NOT NULL
AND count_star = 0
AND 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_seen
FROM performance_schema.events_statements_summary_by_digest d
where d
ORDER BY SUM_TIMER_WAIT DESC
limit 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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原文地址：https://www.cnblogs.com/hnsongbiao/p/11070014.html