Mysql Improve Search Performance with wildcards (%%)

sql like wildcard performance
sql optimize like statement
mysql like performance
how to avoid like operator in sql server
mysql full-text search
oracle wildcard search performance
alternative for like operator in sql server 2012
sql server full-text search wildcard

Below is a query I use for searching a person by email

  SELECT *
    FROM phppos_customers
    JOIN phppos_people ON phppos_customers.person_id = phppos_people.person_id
   WHERE deleted = 0
     AND email LIKE '%f%'
ORDER BY email ASC

Will adding an index on "email" speed up the query?


No, because MySQL will not be able to utilize the index when you have a leading wildcard. If you changed your LIKE to 'f%', then it would be able to use the index.

Improve MySQL Search Performance with wildcards (%%)?, No, MySQL won't improve search performance whenever you have leading wildcards because MySQL will be unable to use the index. MySQL MySQLi Database No, MySQL won’t improve search performance whenever you have leading wildcards because MySQL will be unable to use the index. If you change to ‘anyLetter%’ then it will be able to use index The below syntax is better to use with trailing wildcards.


No, Mysql will not use the index because LIKE argument (%f%) starts with the wildcard character %. If it starts with a constant, index will be used.

More info: 7.5.3. How MySQL Uses Indexes

Indexing SQL LIKE Filters, Not all LIKE filters are slow: the performance depends on the position of the wild card characters inside the search term. A visual explanation. Therefore, optimizing query performance is essential. MySQL comes with tools that help us in the optimization of queries. Let’s have a look at the most important and useful tips to improve MySQL Query for speed and performance. Optimize Database; Use Full-Text Searches; Avoid Like Expressions With Leading Wildcards


Wildcarding the left side of a LIKE operation ensures that an index, if one exists on the email column, can not be used.

Full Text Search (FTS) is preferred syntax for finding strings within text via SQL. MySQL has native FTS functionality, using the MATCH/AGAINST syntax (Requires the table to use the MyISAM engine for v.5.5 and below. InnoDB FTS supported on v.5.6+):

  SELECT c.*, p.*
    FROM PHPPOS_CUSTOMERS c
    JOIN PHPPOS_PEOPLE p ON p.person_id = c..person_id
   WHERE deleted = 0
     AND MATCH(email) AGAINST('f')
ORDER BY email 

But there are third party FTS technology, such as Sphinx.

One way to get an index seek for a leading %wildcard in SQL Server, A performance issue I see often is when users need to match part of a string with a query like the following: WHERE SomeColumn LIKE N'%  Performance tuning MySQL depends on a number of factors. For one thing, MySQL runs on various operating systems. For another, there are a variety of storage engines and file formats—each with their own nuances. In this tutorial, you’ll learn about performance tuning MySQL. But first, you need to narrow the problem down to MySQL.


In my post here I describe, in detail, a technique that allows you to use the index with LIKE for fast %infix% search, at the cost of some extra storage:

https://stackoverflow.com/a/22531268/543814

As long as the strings are relatively small, the storage requirement is generally acceptable.

According to Google, the average e-mail address is 25 characters long. This increases your required storage by a factor 12.5 on average, and gives you fast indexed search in return. (See my post for the calculations.)

From my perspective, if you are storing 10'000 e-mail addresses, you should be fine storing (the equivalent of) about 100'000 e-mail addresses, too. If this is what it takes to allow you to use an index, that seems like an acceptable trade-off. Often, disk space is cheap, while non-indexed searches are unaffordable.

If you choose to take this approach, I suggest that you limit the input length of e-mail addresses to 64 characters. Those rare (or attacker) e-mail addresses of such length will require up to 32 times the usual storage. This gives you:

  1. Protection against an attacker trying to flood your database, since these still aren't very impressive amounts of data.
  2. The expectation that most e-mail addresses are not of this length anyway.

If you consider 64 characters too harsh a requirement, use 255 instead, for a worst-case storage increase factor of 127.5. Ridiculous? Possibly. Likely? No. Fast? Very.

How to Speed Up Pattern Matching Queries, MySQL cannot use pattern matching queries with conditions like this: With the following query, we can find all the email addresses with  Table of Content. The Benefits of MySQL Performance Tuning. Optimize Queries With MySQL Query Optimization Guidelines Avoid using functions in predicates. Avoid using wildcard (%) in the beginning of a predicate. Avoid unnecessary columns in SELECT clause. Use inner join, instead of outer join if possible.


You will not be able to make it faster with LIKE just like everyone says (about the % at the beginning), but you can improve it a little by joining after you filter your people first.

SELECT *
  FROM (SELECT * 
          FROM `phppos_customers`
         WHERE `deleted` = 0
           AND  `email`  LIKE '%f%') `t_customers`
  JOIN `phppos_people` ON `t_customers`.`person_id`=`phppos_people`.`person_id`
 ORDER BY `email` asc

MySQL: Can I speed up LIKE queries by adding an index , For string columns, MySQL indexes the left side of a string. That means an index can speed a like query that has a wildcard on the right side: Copy. SELECT  How to improve query performance and avoid syntax errors by expanding wildcards in SQL statements. ApexSQL Search. ApexSQL Search for MySQL.


Performance analysis of MySQL's FULLTEXT indexes and LIKE , Performance analysis of MySQL's FULLTEXT indexes and LIKE queries for full text search. When searching for text in a MySQL table, you have two choices:. As with most software, not all tools work on all versions of MySQL. We will examine three utilities to evaluate your MySQL database and recommend changes to improve performance. The first is tuning-primer. This tool is a bit older, designed for MySQL 5.5 – 5.7. It can analyze your database and suggest settings to improve performance.


How to make SQL Server Wildcard Searches Faster, For example, searching on a character field with 'abc%' is not an issue if the column has an index, but searching '%abc' is always slow because it  Let's take a look at how to optimize MySQL queries for speed and performance on Alibaba Cloud ECS. You can deploy fast, secure, and trusted MySQL database instances on Alibaba Cloud. Alibaba has


Full text search using mysql - Noteworthy, The above query's performance downgrades with the increase in data. the wild card character position in the query determines if the search