Year: 2011

On generating unique IDs using LAST_INSERT_ID() and other tools

MySQL

There’s a trick for using LAST_INSERT_ID() to generate sequences in MySQL. Quoting from the Manual:

  1. Create a table to hold the sequence counter and initialize it: 
    mysql> CREATE TABLE sequence (id INT NOT NULL);
mysql> INSERT INTO sequence VALUES (0);
  2. Use the table to generate sequence numbers like this: 
    mysql> UPDATE sequence SET id=LAST_INSERT_ID(id+1);
mysql> SELECT LAST_INSERT_ID();

This trick calls for trouble.

Contention

A customer was using this trick to generate unique session IDs for his JBoss sessions. These IDs would eventually be written back to the database in the form of log events. Business go well, and one day the customer adds three new JBoss servers (doubling the amount of webapps). All of a sudden, nothing works quite as it used to. All kinds of queries take long seconds to complete; load average becomes very high. Continue reading » “On generating unique IDs using LAST_INSERT_ID() and other tools”

Generating Google line charts with SQL, part I

MySQL

In this series of posts I wish to show how Google Charts can be generated via SQL. We discuss the Google Charts limitations which must be challenged, and work towards a simple chart.

I’m going to present the algorithm I use in mycheckpoint, a MySQL monitoring utility, which generates Google charts by raw data using views. An example of such chart follows:


http://chart.apis.google.com/chart?cht=lc&chs=370x180&chts=303030,12&chtt=Latest+24+hours:+Nov+9,+05:50++-++Nov+10,+05:50&chf=c,s,ffffff&chdl=Rentals+rate:+custom_1_psec&chdlp=b&chco=ff8c00&chd=s:GDGKGFLFGMJHRLMPPNULJRPLTOPRUMYPPVRNbQUSUSbSNWUOfSWTObVSUVWSVYVPbTPjfTbRTdXReUWhcTQRQZbTWYVYPaVZXdYYWPTabYUTbW99QLgLNIOIRNNMIKRJEHGFHGJGGFIFDFGDK&chxt=x,y&chxr=1,0,8.720000&chxl=0:|+||08:00||+||12:00||+||16:00||+||20:00||+||00:00||+||04:00||&chxs=0,505050,10,0,lt&chg=4.17,25,1,2,0.69,0&chxp=0,0.69,4.86,9.03,13.20,17.37,21.54,25.71,29.88,34.05,38.22,42.39,46.56,50.73,54.90,59.07,63.24,67.41,71.58,75.75,79.92,84.09,88.26,92.43,96.60&tsstart=2010-11-09+05:50:00&tsstep=600

mycheckpoint does not actually call on Google to do the chart rendering, but invokes its own JavaScript code to visualize the URL locally.

Here are some downsides for using Google charts:

  • The URL cannot be as long as you like. 2048 characters is an upper bound you’ll want to keep behind. [Google charts POST method calls are available, which leads to 16K equivalent of URL length — this is still not too helpful due to the nature of POST calls]
  • Features are inconsistent. To specify label or tick positions, one must specify exact positions. To specify grid positions, one must supply with step, offset, etc. There are more such inconsistencies.
  • Google charts are not too friendly. Taking the ticks and grids example from above, there really shouldn’t be a reason why grids would not be automatically generated according to ticks definitions. But we are required to specify positions for the ticks as well as for the grids.
  • There is no support for time-series. One must translate time as x-axis values.
  • Perhaps most intimidating to many people: to generate a Google chart, once must send data to Google. Which is the main reason I used local JavaScript rendering.

Anyway, let’s build a very simple chart. Since I will not cover everything in this post, we make for some relaxed conditions. Continue reading » “Generating Google line charts with SQL, part I”

Multi condition UPDATE query

MySQL

A simple question I’ve been asked:

Is it possible to merge two UPDATE queries, each on different WHERE conditions, into a single query?

For example, is it possible to merge the following two UPDATE statements into one?

mysql> UPDATE film SET rental_duration=rental_duration+1 WHERE rating = 'G';
Query OK, 178 rows affected (0.01 sec)

mysql> UPDATE film SET rental_rate=rental_rate-0.5 WHERE length < 90;
Query OK, 320 rows affected (0.01 sec)

To verify our tests, we take a checksum:

mysql> pager md5sum
PAGER set to 'md5sum'
mysql> SELECT film_id, title, rental_duration, rental_rate FROM film ORDER BY film_id;
c2d253c3919efaa6d11487b1fd5061f3  -

Obviously, the following query is incorrect: Continue reading » “Multi condition UPDATE query”

Another use for “top N records per group” query

MySQL

A few days ago I published SQL: selecting top N records per group. It just dawned on me that the very same query solved another type of problem I was having a couple years ago.

BTW, for reference, Baron Schwartz posted this 4 years ago. There are very interesting approaches in text and in comments. Good to see the ancients already knew of such problems, I should study my history better.

(Kidding, kidding! This is self criticism of course)

In this case I present now I have a table with recurring data, which, to some extent, represents revision of data. For the sake of simplicity let’s describe it as a simple simulation of a revision system:

  • I have text files, whose content I store within a row
  • Each text file uses at least one row in the table
  • Text files can be edited, whereas an edited file is written in a new row (never UPDATEd).

Hold your horses: I’m not really implementing a revision system, I just can’t get into the actual details here.

The table becomes large quickly, and it’s desired to purge rows from the table. The rule is: we must obtain the most recent two versions for each file (if there are indeed more than one). All others can be purged. So the question is: Continue reading » “Another use for “top N records per group” query”

SQL: selecting top N records per group

MySQL

A while back I presented(*) an SQL trick to present with non-aggregated column on a GROUP BY query, without use of subquery or derived tables.

Based on a similar concept, combined with string walking, I now present a query which selects top-n records for each group, ordered by some condition. It will require no subqueries. It executes faster than its more conventional alternatives.

[UPDATE: this is MySQL only. Others can use Window Functions where available]

Using the simple world database, we answer the following question:

What are the top 5 largest (by area) countries for each continent? What are their names, surface area and population?

Similar questions would be:

What were the latest 5 films rented by each customer?

What were the most presented advertisements for each user?

etc.

Step 1: getting the top

We already know how to get a single column’s value for the top country, as presented in the aforementioned post: Continue reading » “SQL: selecting top N records per group”

Speaking at the O’Reilly MySQL Conference 2011

MySQL

I’m very pleased and humbled to announce that my submission to the upcoming O’Reilly MySQL Conference, April 2011, has been accepted.

I will present a 45 minute session titled openark-kit: MySQL utilities for everyday use.

In this session, I will present some of the tools in the openark kit. We’ll discuss some limitations of the MySQL server, and how openark kit tools overcome those limitations and provide with solutions to common maintenance and audit problems.

This will be a technical session and will discuss various topics of the MySQL server: security, execution plans, replication, triggers and more. I do not intend to discuss all tools, nor to cover the various options. Instead, I’ll present the “behind the scenes“, show why the tools work, present common problems and typical use case.

This will be the first time I present at the MySQL Conference (or any conference outside Israel, for that matter). I hope to have a good session. As extra measure of safety, I’ll bring along a couple basketballs; if the sun shines, we can all go outside and have a good time!

The idea to submit this talk (credit Roland Bouman) has given me the inspiration to put effort in making a new release with new and updated tools. So this talk is already a success as far as I’m concerned.

Hope to see you there!

[PS shameless plug: openark kit.]