Is it a good idea to index datetime field in mysql?
MysqlIndexingMysql Problem Overview
I am working on designing a large database. In my application I will have many rows for example I currently have one table with 4 million records. Most of my queries use datetime clause to select data. Is it a good idea to index datetime fields in mysql database?
Select field1, field2,.....,field15
from table where field 20 between now() and now + 30 days
I am trying to keep my database working good and queries being run smoothly
More, what idea do you think I should have to create a high efficiency database?
Mysql Solutions
Solution 1 - Mysql
MySQL recommends using indexes for a variety of reasons including elimination of rows between conditions: http://dev.mysql.com/doc/refman/5.0/en/mysql-indexes.html
This makes your datetime column an excellent candidate for an index if you are going to be using it in conditions frequently in queries. If your only condition is BETWEEN NOW() AND DATE_ADD(NOW(), INTERVAL 30 DAY) and you have no other index in the condition, MySQL will have to do a full table scan on every query. I'm not sure how many rows are generated in 30 days, but as long as it's less than about 1/3 of the total rows it will be more efficient to use an index on the column.
Your question about creating an efficient database is very broad. I'd say to just make sure that it's normalized and all appropriate columns are indexed (i.e. ones used in joins and where clauses).
Solution 2 - Mysql
Here author performed tests showed that integer unix timestamp is better than DateTime. Note, he used MySql. But I feel no matter what DB engine you use comparing integers are slightly faster than comparing dates so int index is better than DateTime index. Take T1 - time of comparing 2 dates, T2 - time of comparing 2 integers. Search on indexed field takes approximately O(log(rows)) time because index based on some balanced tree - it may be different for different DB engines but anyway Log(rows) is common estimation. (if you not use bitmask or r-tree based index). So difference is (T2-T1)*Log(rows) - may play role if you perform your query oftenly.