Database - Index interview FAQ

Q & A is based on known data structures.

1. What indexes are?

• Index value in the database is one or more columns in the table is sorted a configuration.

2. Why use the data index?

• Enhance the retrieval speed, accelerating the connection between the table and the table

3. What types of indexes?

• FULLTEXT full-text index can be created on the full-text index (MyISAM, Innodb5.6 +) CHAR, VARCHAR, TEXT columns
• HASH hash index (MEMORY support)
• BTREE B-tree index
• B + TREE B + tree index
• RTREE R-tree index

4. What type index? What are the characteristics?

• Ordinary Index: speed up queries
• The only index: speed up queries + + unique column values ​​may be null
• Primary key index: the acceleration column value uniquely query + + + null is not only a table
• Composite index: a multi-column index value of the composition, a combination of dedicated to searching, combined efficiency is greater than the index
• Full-text indexing: the content of the text word segmentation, search

5. What data should add an index?

• Where clause field frequently used index should be created
• Grouping field or sort field should create an index
• Connect field two tables should create an index
• Storage space is more suitable for fixed keyword text field type of field selected as the index compared, char type is more suitable
• Take up less storage space is more suitable for field selected as a keyword index compared with the string, integer field more suitable
• Long article index data should consider using the index short, if the majority of the front of the field is different, then specify a prefix length.

6. What data is not suitable as an index?

• Frequently updated fields are not suitable for creating an index
• It does not appear in the where clause field

7. What is the data structure of the index mysql?

• The general use of B + tree indexing

8. Do you know other index type?

• Hash index B-tree index

9. Hash and time complexity index B + tree index is how much?

• o (1) the sum o (logN)

10. Why mysql hash index is faster but also with B + TREE indexed?

• This and related business scenarios. Only a selected data, hash faster (o (1)). Database often choose the N if using a hash index that is o (n), this time due to the B + tree index order (o (logn)), and have linked list on the leaf node, its query efficiency than hash to faster a.
• On the hard disk, the index itself generally large index store, not all at once stored in memory, the B + tree design may allow for batch loading data, while the lower height of the tree, to find the high efficiency.
• We all know that the hard disk I / O speed is very slow compared to memory, and the index is used to speed up queries, the need to reduce I / O operations, memory, and disk units of pages to exchange data, in order to reduce I / O, when a new node index, apply directly a page space, memory allocation is page-aligned, to achieve a first node I / O.