How to improve Magento performance? I am writing a series of posts describing different techniques for improving Magento performance. The post can be found at http://www.infotales.com/magento-performance/
The post includes different techniques like MySQL Optimization for Magento Performance and some more to come.
For more Magento related post see http://www.infotales.com/
Well MySQL is full featured, one of the most famous and widely used database server. MySQL is open source it means its free. Being a cross platform server its being used for different OS like Linux, Windows, MAC etc. MySQL features include support for views, stored procedures, replication etc etc.
Most of the free web applications like osCommerce, joomla, magento, durpal etc are using MySQL. MySQL is also being used by large enterprises like Yahoo, Google, FaceBook etc etc.
To see more details visit mysql.com
The post have been moved to new URL http://www.infotales.com/sphinx-recommended-mysql-performance-blog/
For more SPHINX related posts keep visiting my new blog
The post have been moved to new URL http://www.infotales.com/sphinx-distributed-searching/
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Indexes are important tool for speed up selects thus improving performance of your application. Indexes its self can be stored or accessed in different ways. In this post we will look on general characteristics of different type of index storing methods with respect to MySQL.
BTree indexes
- All leaves at the same distance from the root
- Efficient insertions, deletions
- Values are sorted
- Efficient range scans
- Values stored in the leaves
- Ok for most kinds of lookups:
- Exact full value (= xxx)
- Range of values (BETWEEN xx AND yy)
- Column prefix (LIKE ‘xx%’)
- Leftmost prefix
- Ok for sorting too
- But
- Not useful for ‘LIKE %xxx’ or LIKE ‘%xx%’
- You can’t skip columns
Hash indexes
Hash table with hash and pointer to row
| Hash |
Value |
| 234234 |
Link to row 10 |
| 245335 |
Link to row 42 |
| 278788 |
Link to row 30 |
Drawbacks
- Useful only for exact lookups (=, IN)
- Not supported by InnoDB or MyISAM
Benefits
R-Tree and T-Tree indexes
- R-Tree Indexes
- Same principle as B-Tree indexes
- Used for spatial indexes
- Requires the use of GIS functions
- MyISAM only
- T-Tree indexes
- Same principle as B-Tree indexes
- Specialized for in-memory storage engines
- Used in NDB Cluster
by Stéphane Combaudon
The post have been moved to new URL http://www.infotales.com/introduction-to-sphinx-search/
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Have you ever tried to search common words like about, above, used etc using
MATCH (col1,col2,...) AGAINST (expr [search_modifier])
statement in Mysql and found that the query is not returning the proper results?
Mysql have many full-text STOP words. Stop words are different words which are ignored when searched. For example if you search “used cars” using match against statement
MATCH(description) AGAINST ('+used +cars' IN BOOLEAN MODE)
Here the ‘+’ sign indicates that each word must be present in ‘description’ field. Mysql will return results only containing ‘cars’, as it will ignore ‘used’, despite we have include it in query.
You can find full list of full text stop words here
