OverviewTeaching: 30 min
Exercises: 30 minQuestions
How do you aggregate records in SQL?Objectives
to understand how to aggregate records in SQL
Aggregation allows us to combine results by grouping records based on value and calculating combined values in groups.
Let’s go to the articles table and find out how many entries there are. Using the wildcard simply counts the number of records (rows)
SELECT COUNT(*) FROM articles;
We can also find out how many authors have participated in these articles.
SELECT COUNT(*), SUM(author_count) FROM articles;
There are many other aggregate functions included in SQL including
Write a query that returns: total, average, the min and max number of citations for each journal. Can you modify it so that it outputs only journals with more than 5 citations in average?
Now, let’s see how many articles were published in each journal. We do this
GROUP BY clause
SELECT issns, COUNT( * ) FROM articles GROUP BY issns;
GROUP BY tells SQL what field or fields we want to use to aggregate the data.
If we want to group by multiple fields, we give
GROUP BY a comma separated list.
Write queries that return:
- How many articles were counted each month. a) in total; b) per each journal.
- Average number of citations of each journal in each month. Can you modify the above queries combining them into one?
In the previous lesson, we have seen the keywords
WHERE, allowing to
filter the results according to some criteria. SQL offers a mechanism to
filter the results based on aggregate functions, through the
For example, we can adapt the last request we wrote to only return information about articles with a 10 or more published articles:
SELECT issns, COUNT( * ) FROM articles GROUP BY issns HAVING COUNT( * ) >= 10;
HAVING keyword works exactly like the
WHERE keyword, but uses
aggregate functions instead of database fields.
If you use
AS in your query to rename a column,
HAVING can use this
information to make the query more readable. For example, in the above
query, we can call the
COUNT(*) by another name, like
occurrences. This can be written this way:
SELECT issns, COUNT( * ) AS occurrences FROM articles GROUP BY issns HAVING occurrences >= 10;
Note that in both queries,
HAVING comes after
GROUP BY. One way to
think about this is: the data are retrieved (
SELECT), can be filtered
WHERE), then joined in groups (
GROUP BY); finally, we only select some
of these groups (
Write a query that returns, from the
articlestable, the average number of
citationsfor each journal, only for the journals with 5 or more citations on average.
We can order the results of our aggregation by a specific column, including the aggregated column. Let’s count the number of articles published in each journal, ordered by the count
SELECT issns, COUNT( * ) FROM articles GROUP BY issns ORDER BY COUNT( * ) DESC;
It is not uncommon to repeat the same operation more than once, for example for monitoring or reporting purposes. SQL comes with a very powerful mechanism to do this: views. Views are a form of query that is saved in the database, and can be used to look at, filter, and even update information. One way to think of views is as a table, that can read, aggregate, and filter information from several places before showing it to you.
Creating a view from a query requires to add
CREATE VIEW viewname AS
before the query itself. For example, if we want to save the query giving
the number of journals in a view, we can write
CREATE VIEW journal_counts AS SELECT issns, COUNT(*) FROM articles GROUP BY issns;
Now, we will be able to access these results with a much shorter notation:
SELECT * FROM journal_counts;
Assuming we do not need this view anymore, we can remove it from the database almost as we would a table:
DROP VIEW journal_counts;
You can also add a view using Create View in the View menu and see the results in the Views tab just like a table
Write a query that returns the number of articles published in each journal on each month, sorted from most popular journal to the ones with least publications each month starting from the most recent records. Save this query as a
SQL is ideal for aggregating database records