标签：between date 工程 回滚 upd update ann 连接查询 等等
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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优化、分析Mysql表读写、索引等操作的sql语句效率优化问题
标签：between date 工程 回滚 upd update ann 连接查询 等等
原文地址：https://www.cnblogs.com/hnsongbiao/p/11070014.html
