To see how this optimization works, consider first how an index scan proceeds when Index Condition Pushdown is not used:
-
Get the next row, first by reading the index tuple, and then by using the index tuple to locate and read the full table row.
-
Test the part of the
WHEREcondition that applies to this table. Accept or reject the row based on the test result.
When Index Condition Pushdown is used, the scan proceeds like this instead:
-
Get the next row's index tuple (but not the full table row).
-
Test the part of the
WHEREcondition that applies to this table and can be checked using only index columns. If the condition is not satisfied, proceed to the index tuple for the next row. -
If the condition is satisfied, use the index tuple to locate and read the full table row.
-
Test the remaining part of the
WHEREcondition that applies to this table. Accept or reject the row based on the test result.
举例如下:
Suppose that we have a table containing information about people and their addresses and that the table has an index defined as INDEX (zipcode, lastname, firstname). If we know a person's zipcode value but are not sure about the last name, we can search like this:
SELECT * FROM people WHERE zipcode='95054' AND lastname LIKE '%etrunia%' AND address LIKE '%Main Street%';
people表中(zipcode,lastname,firstname)构成一个索引。
如果没有使用索引下推技术,则MySQL会通过zipcode='95054'从存储引擎中查询对应的元祖,返回到MySQL服务端,然后MySQL服务端基于lastname LIKE '%etrunia%'和
address LIKE '%Main Street%'来判断元祖是否符合条件。
如果使用了索引下推技术,则MYSQL首先会返回符合zipcode='95054'的索引,然后根据lastname LIKE '%etrunia%'和address LIKE '%Main Street%'来判断索引是否符合
条件。如果符合条件,则根据该索引来定位对应的元祖,如果不符合,则直接reject掉。
本文介绍了数据库查询处理中的索引下推优化技术。通过将部分WHERE条件的筛选工作交给存储引擎来完成,减少不必要的全记录加载,从而提高查询效率。以MySQL为例,对比了使用与未使用索引下推技术时查询过程的区别。
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