I believe this is a huge optimization for a heavily implemented Web 2.0 idea.
This article makes simple work of groups of queues. An example of this would be “the most recent 10 people to view an article,” so each article has a queue of up to 10 items in it. This method eliminates the need for multiple SQL statements or using TRIGGERS to check to see if the queue is full.
I bow down to Baron Schwartz, aka Xarpb, for his article on how to implement a queue in SQL:
I am very excited because this also works for groups of objects, and we’re about to implement something at work that needs this idea. The idea of “the most recent x things” or “the top x things” is huge, especially in social networking, and probably one of the most often sought after features.
The biggest issue is that in order to display, say, the most recent posts, a query has to find the time of all the posts and only get the most recent 10. This can be made easy by the logic that the 10 most recent posts are the last 10 rows in the table. Any logic is also added, as in “the last 10 rows in the table viewable and for this guest/login.”
What if you want to track the last 10 people to view the post? Aha, this gets trickier. Convention would say that when a person views a post, have an SQL transaction that adds the information (person x viewed post y at time z and anyo other info, such as browser type, IP, etc) and if there are more than 10 entries for that post, delete the oldest ones until you have 10 entries. This transaction could be done via the application code or via triggers in MySQL 5.0 and up.
However, both those methods use multiple SQL queries, and in the case that an article has been viewed fewer than 10 times, the queries are unnecessary. And given each article has a different popularity — some are viewed lots more than others — running multiple queries ends up being a waste of cycles for articles whose last 10 viewers change infrequently.
These commands were tested on MySQL 4.1.19-standard-log. I use REPLACE INTO because it’s shorter than SELECT…ON DUPLICATE KEY UPDATE, and yes, those aren’t
Let’s say you have a New Year’s Resolution to eat 5 servings of fruits and 5 servings of vegetables per day. The only thing that changes from Baron’s example is that we add a group field (called ‘kind’). The “fruit” field was changed to “edible” and will still contain the name of the edible.
As Baron does, I will use a MySQL-specific command. However, he used
SELECT...ON DUPLICATE KEY and I will use
REPLACE, as it is smaller in syntax.
CREATE TABLE q (
id int NOT NULL,
modulo int NOT NULL,
kind char(1) NOT NULL,
food varchar(10) NOT NULL,
The basic statement is below — I’ve added
AS clauses to make the variables more clear. The modulus is, in this case, 5, but in the article case above would be 10. The “kind” is either “f” or “v”, these are your groups of queues. In this case they stand for “fruits” and “vegetables” but they might be numbers referring to articles. The “food” stands for the type of food eaten, but in the article scenario would represent the username or user id of the customer viewing the article.
REPLACE INTO q (id, modulo, kind, food)
(COALESCE(MAX(id), -1) + 1) AS id,
(COALESCE(MAX(id), -1) + 1) MOD 5 AS modulo,
'f' AS kind,
'apple' AS food
FROM q WHERE kind='f';