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Showing entries 1 to 23

Displaying posts with tag: syntax (reset)

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Had a case recently where I had to merge data from two identically structured tables containing nearly identical data.

"Nearly identical" meaning most table data is identical in both; sometimes a row is missing from one of the tables; sometimes same row (according to PK) appears in both, but some columns are NULL is one tables (while others can be NULL in the second).

Otherwise no contradicting data: it was not possible for some data to be "3" in one table and "4" in the other.

How do you create a merge of the tables, such that all missing rows are completed, and NULLs replaced by actual values when possible?

pt-table-sync comes to mind: one can do a bidirectional syncing of two tables, and actually stating how to resolve ambiguities (like "greater value

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Pop quiz: funny syntax
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The following questions are of little importance, yet I find them entertaining. I stumbled upon these while developing QueryScript.

Can you guess the results of the following statements?

Pop quiz 1

SET @x := 7;
SELECT ++@x;

What is the computation result? What will be the value of @x?

Pop quiz 2

SET @ := 4;
SELECT @ + @'' + @``

What is the computation result?

Pop quiz 3

SET @a := 2;
SELECT @a = @'a' = @`a`

Do we get TRUE or FALSE? When?


Consider the following queries as hints to the above questions:

SELECT +++++-@x;
SELECT @ = @'', @ = @``
SELECT (@a = @'a') = @`a`


  • Pop quiz
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Using CURDATE() the wrong way
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It has been a while since I wrote on this blog. Basically I had too much on my mind (expanding my department, holidays, etc) to actually write here and I’ll promise to post more regularly from now onwards. ;)

Anyway, as the title already suggests: I found out how you can use CURDATE() in a wrong way. One of the developers in my company asked me to help him out as his code all of a sudden did not work properly anymore. Or even better: it used to process several thousands of rows and all of a sudden it processed none.

I looked at his code snippet and it was quite a long query with a lot of brackets:

SELECT SUM(some_count_col), logdate, loghour FROM logs

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MySQL joins: ON vs. USING vs. Theta-style
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What is the difference between the following three syntaxes?

SELECT * FROM film JOIN film_actor ON (film.film_id = film_actor.film_id)
SELECT * FROM film JOIN film_actor USING (film_id)
SELECT * FROM film, film_actor WHERE film.film_id = film_actor.film_id

The difference is mostly syntactic sugar, but with a couple interesting notes.

To put names, the first two are called "ANSI-style" while the third is called "Theta-style".

Theta style

On the FROM clause, tables are listed as if with Cartesian products, and the WHERE clause specifies how the join should take place.

This is considered to be the "old" style. It is somewhat confusing to read. Consider the following query:

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Syntax of the day: IS TRUE and IS FALSE
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What makes for a true statement?

We usually test statements using a WHERE clause:

SELECT * FROM world.City WHERE Population > 1000000

The "Population > 1000000" statement makes for a boolean expression. Using WHERE is just one way of evaluating it. One can also test with IF():

SET @val := 7;
SELECT IF(@val > 2, 'Yes', 'No')


The two are keywords. They also map for the numerals 1 and 0, as follows:

|    1 |     0 |


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Quoting text JavaScript/Python style
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Unless your MySQL is configured to use ANSI_QUOTES in sql_mode, you are able to quote your text in one of two forms: using single quotes or double quotes:

UPDATE world.Country SET HeadOfState = 'Willy Wonka' WHERE Code='USA'
UPDATE world.Country SET HeadOfState = "Willy Wonka" WHERE Code="USA"

This makes for JavaScript- or Python-style quoting: you quote by your needs. Say you have a text which includes single quotes:

It is what you read when you don't have to that determines what you will be when you can't help it. - Oscar Wilde

You wish to insert this text to some tables. You could go through

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MySQL terminology: processes, threads & connections
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There’s some confusion in the MySQL terminology for processes, threads & connections, which I will try to resolve. I can’t explain the full nature of what processes and threads are; please see Wikipedia [1] [2] for that. But here’s some basics with regard to MySQL:

  • MySQL server is a single process application.
  • It is multithreaded.
  • It (usually) acts as a TCP/IP server, accepting connections.
  • Each connection gets a dedicated thread.
  • These threads are sometimes named processes, and sometimes they’re referred to as connections.

The last part is where confusion arises, so let me discuss again the use of threads and connections in MySQL.


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SQL: good comments conventions
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I happened upon a customer who left me in awe and admiration. The reason: excellent comments for their SQL code.

I list four major places where SQL comments are helpful. I’ll use the sakila database. It is originally scarcely commented; I’ll present it now enhanced with comments, to illustrate.

Table definitions

The CREATE TABLE statement allows for a comment, intended to describe the nature of the table:

CREATE TABLE `film_text` (
 `film_id` smallint(6) NOT NULL,
 `title` varchar(255) NOT NULL,
 `description` text,
 PRIMARY KEY (`film_id`),
 FULLTEXT KEY `idx_title_description` (`title`,`description`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8 COMMENT='Reflection of `film`, used for FULLTEXT search.'

It’s too

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MySQL Idiosyncrasies That Bite
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The following are my slides that I presented at ODTUG Kaleidoscope 2010. This presentation talks about the MySQL defaults including a non-transactional state, silent data truncations, date management, and transaction isolation options. These are all critical for data integrity and consistency. I also cover in-depth topics including SQL_MODE, character sets and collations.

MySQL Idiosyncrasies That Bite View more presentations from Ronald Bradford.
Views: better performance with condition pushdown
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Justin’s A workaround for the performance problems of TEMPTABLE views post on mysqlperformanceblog.com reminded me of a solution I once saw on a customer’s site.

The customer was using nested views structure, up to depth of some 8-9 views. There were a lot of aggregations along the way, and even the simplest query resulted with a LOT of subqueries, temporary tables, and vast amounts of data, even if only to return with a couple of rows.

While we worked to solve this, a developer showed me his own trick. His trick is now impossible to implement, but there’s a hack around this.

Let’s use the world database to illustrate. Look at the following view

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Discovery of the day: GROUP BY … DESC
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I happened on a query where, by mistake, an


was written as


And it took me by surprise to realize GROUP BY x DESC is a valid statement. I looked it up: yep! It’s documented.

In MySQL, GROUP BY results are sorted according to the group statement. You can override this by adding ORDER BY NULL (see past post). I wasn’t aware you can actually control the sort order.

But I DO want MySQL to say “ERROR”!
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MySQL is known for its willingness to accept invalid queries, data values. It can silently commit your transaction, truncate your data.

  • Using GROUP_CONCAT with a small group_concat_max_len setting? Your result will be silently truncated (make sure to check the warnings though).
  • Calling CREATE TEMPORARY TABLE? You get silent commit.
  • Issuing a ROLLBACK on non-transactional involved engines? Have a warning; no error.
  • Using LOCK IN SHARE MODE on non transactional tables? Not a problem. Nothing reported.
  • Adding a FOREIGN KEY on a MyISAM table? Good for you; no action actually taken.
  • Inserting 300 to a TINYINT column in a
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Proper SQL table alias use conventions
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After seeing quite some SQL statements over the years, something is bugging me: there is no consistent convention as for how to write an SQL query.

I’m going to leave formatting, upper/lower-case issues aside, and discuss a small part of the SQL syntax: table aliases. Looking at three different queries, I will describe what I find to be problematic table alias use.

Using the sakila database, take a look at the following queries:

Query #1

 R.rental_date, C.customer_id, C.first_name, C.last_name
 rental R
 JOIN customer C USING (customer_id)
 R.rental_date >= DATE('2005-10-01')
 AND C.store_id=1;

The above looks for film

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MySQL Wishlist
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While I worked on several web projects I collected a few wishes for MySQL (this collection is more user specific - a MySQL internal wishlist will come later) - which I use in most cases. I still fixed a few things, but don't know if they are good enough for production (because I just started hacking MySQL).

Read the rest »

7 ways to convince MySQL to use the right index
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Sometimes MySQL gets it wrong. It doesn’t use the right index.

It happens that MySQL generates a query plan which is really bad (EXPLAIN says it’s going to explore some 10,000,000 rows), when another plan (soon to show how was generated) says: “Sure, I can do that with 100 rows using a key”.

A true story

A customer had issues with his database. Queries were taking 15 minutes to complete, and the db in general was not responsive. Looking at the slow query log, I found the criminal query. Allow me to bring you up to speed:

A table is defined like this:

  level TINYINT unsigned,
  KEY `type` (type)

The offending query was this:

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`;`.`*`.`.` is a valid column name
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And the following query:

SELECT `;`.`*`.`.` FROM `;`.`*`;

is valid as well. So are the following:

CREATE TABLE `;`.`*` (`.` INT);
CREATE TABLE `;`.```` (`.` INT);
CREATE TABLE `;`.`$(ls)` (`.` INT);

So, on my Linux machine:

root@mymachine:/usr/local/mysql/data# ls -l
total 30172
drwx------ 2 mysql mysql     4096 2009-01-11 08:00 ;
-rw-rw---- 1 mysql mysql 18874368 2009-01-09 19:08 ibdata1
-rw-rw---- 1 mysql mysql  5242880 2009-01-09 19:08 ib_logfile0
-rw-rw---- 1 mysql mysql  5242880 2009-01-09 19:08 ib_logfile1
drwxr-x--- 2 mysql mysql     4096 2008-12-09 11:38 mysql
-rw-rw---- 1 mysql mysql  1423612 2009-01-11 08:00 mysql-bin.000001
-rw-rw---- 1 mysql mysql       19 2009-01-04 09:05 mysql-bin.index
drwx------ 2 mysql mysql
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REPLACE INTO: think twice
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The REPLACE [INTO] syntax allows us to INSERT a row into a table, except that if a UNIQUE KEY (including PRIMARY KEY) violation occurs, the old row is deleted prior to the new INSERT, hence no violation.

Sounds very attractive, and has a nice syntax as well: the same syntax as a normal INSERT INTO’s. It certainly has a nicer syntax than INSERT INTO … ON DUPLICATE KEY UPDATE, and it’s certainly shorter than using a SELECT to see if a row exists, then doing either INSERT or UPDATE.

But weak hearted people as myself should be aware of the following: it is a heavyweight solution. It may be just what you were looking for in terms of ease of use, but the fact is that on duplicate keys, a DELETE and INSERT are performed,

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MySQL’s character sets and collations demystified
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MySQL’s character sets and collations are often considered as a mystery, and many users either completely disregard them and keep with the defaults, or set everything to UTF8.

This post will attempt to shed some light on the mystery, and provide with some best practices for use with text columns with regard to character sets.

Character Sets

A thorough discussion of how the character sets have evolved through history is beyond the scope of this post. While the Unicode standard is gaining recognition, the “older” character sets are still around. Understanding the difference between Unicode and local character sets is crucial.

Consider, for example, MySQL’s latin1 character set. In this character set there are 256 different characters, represented by one byte. The first 128 characters map to ASCII, the standard “ABCabc012 dot

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Dynamic sequencing with a single query
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It is a known trick to use a session variables for dynamically counting/sequencing rows. The way to go is to SET a variable to zero, then use arithmetic within assignment to increment its value for each row in the SELECTed rows.

For example, the following query lists the top 10 populated countries, using MySQL’s world database:

SELECT Code, Name, Population
FROM Country ORDER BY Population DESC LIMIT 10;

| Code | Name               | Population |
| CHN  | China              | 1277558000 |
| IND  | India              | 1013662000 |
| USA  | United States      |  278357000 |
| IDN  | Indonesia          |  212107000 |
| BRA  | Brazil             | 
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Selecting a specific non aggregated column data in GROUP BY
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In a GROUP BY query, MySQL may allow specifying non aggregated columns. For example, using MySQL’s world database, I wish to get the number of countries per continent, along with a “sample” country:

SELECT Continent, COUNT(*), Name
FROM `Country` GROUP BY Continent

| Continent     | COUNT(*) | Name           |
| Asia          |       51 | Afghanistan    |
| Europe        |       46 | Albania        |
| North America |       37 | Aruba          |
| Africa        |       58 | Angola         |
| Oceania       |       28 | American Samoa |
| Antarctica    |        5 | Antarctica     |
| South America |       14 | Argentina      |
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Useful database analysis queries with INFORMATION_SCHEMA
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A set of useful queries on INFORMATION_SCHEMA follows. These queries can be used when approaching a new database, to learn about some of its properties, or they can be regularly used on an existing schema, so as to verify its integrity.

I will present queries for:

  • Checking on database engines and size
  • Locating duplicate and redundant indexes
  • Checking on character sets for columns and tables, looking for variances
  • Checking on processes and long queries (only with MySQL 5.1)


The following query returns the total size per engine per database. For example, it is common that in a given database, all tables are InnoDB. But once in a while, and even though default-engine is set to InnoDB, someone creates a MyISAM table. This may break transactional behavior, or may cause a mysqldump --single-transaction to be ineffective.

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Less known SQL syntax and functions in MySQL
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“Standard SQL” is something you read about. All popular databases have modified version of SQL. Each database adds its own flavor and features to the standard. MySQL is no different.

Some deviations are storage engine dependent. Others are more general. Many, such as INSERT IGNORE, are commonly used. Here’s a list of some MySQL deviations to SQL, which are not so well known.

I’ll be using MySQL’s world database for demonstration.


Assume the following query: SELECT CountryCode, COUNT(*) FROM City GROUP BY CountryCode, which selects the number of cities per country, using MySQL’s world database. It is possible to get a name for one “sample” city per country using standard SQL: SELECT

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How To Add A File Extension To vim Syntax Highlighting
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Today I was asked a question about defining custom extensions for vim syntax highlighting such that, for example, vim would know that example.lmx is actually of type xml and apply xml syntax highlighting to it. I know vim already automatically does it not just based on extension but by looking for certain strings inside the text, like

After digging around I found the solution. Add the following to ~/.vimrc (the vim configuration file):

syntax on
filetype on
au BufNewFile,BufRead *.lmx set filetype=xml

After applying it, my .lmx file is highlighted:

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Showing entries 1 to 23

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