Displaying Active Offers by Day of the Year: A Deep Dive into SQLite Queries

Understanding the Problem Statement

The problem at hand is to retrieve the number of active loan offers for each day of 2020. The OFFERS table contains information about loan offers, with each offer having an identifier (offer_id), start date, and expiration date. An offer is considered valid on a given date if that date falls between the offer’s start date and end date.

Data Structure and Sample Data

The OFFERS table has three columns: offer_id, start_date, and end_date. The data looks like this:

offer_id | start_date       | end_date
---------|------------------|---------
123      | 2020-05-01       | 2020-05-17
5432     | 2020-12-01       | 2020-09-19

Recursive Query Approach

One possible approach to solving this problem is to generate all days of the year using a recursive query and then bring in the relevant data from the OFFERS table. This method involves creating a temporary table with dates, joining it with the OFFERS table, and grouping the results by date.

Recursive Query Example

Here’s an example of how this might be implemented in SQLite:

with recursive dates as (
    select '2020-01-01' dt
    union all
    select date(dt, '1 day') from dates where date(dt, '1 day') < '2021-01-01'
)
select d.dt, count(o.offer_id) cnt_active_offers
from dates d
left join offers o on d.dt between o.start_date and o.end_date
group by d.dt

Let’s break down this query step by step:

• The with recursive clause defines a temporary table named dates. This table contains all dates from January 1, 2020 to December 31, 2020.
• The first part of the query uses a union all operator to create the initial row with the date ‘2020-01-01’. Then, it recursively selects the next day by adding one day to the current date using the date(dt, '1 day') function. This continues until December 31, 2020.
• The outer query joins the temporary table dates with the OFFERS table on the condition that the join date falls between the offer’s start and end dates.
• Finally, the results are grouped by date, counting the number of active offers for each day.

Non-Recursive Approach

While recursive queries can be an elegant solution to problems like this, they may not be feasible or efficient for very large datasets. In such cases, a non-recursive approach might be more suitable.

Non-Recursive Query Example

Here’s an example of how the query could be rewritten using a non-recursive approach:

with dates as (
    select '2020-01-01' date
    union all
    select add 1 month date
    from dates
    where date < '2021-01-01'
)
select 
    d.date, 
    count(o.offer_id) cnt_active_offers
from 
    dates d 
left join 
    offers o on d.date between o.start_date and o.end_date
group by 
    d.date

In this version of the query:

• We create a temporary table dates that contains all dates from January 1, 2020 to December 31, 2020 using a single union all statement.
• The outer query joins the temporary table dates with the OFFERS table and groups the results by date.
• We use the add 1 month expression to incrementally select dates from January to December.

SQL vs. PostgreSQL

While both SQLite and PostgreSQL support recursive queries, there are some differences in their syntax:

PostgreSQL Recursive Query Syntax

In PostgreSQL, you need to specify a row version number (RVN) for each table in the recursive query. Here’s an example of how the same query might be implemented in PostgreSQL:

with dates as (
    select '2020-01-01' date, 1 rvn
    from generate_series('2020-01-01', '2020-12-31', '1 day') as ts (date)
),
offers as (
    select offer_id, start_date, end_date, row_number() over (partition by year(start_date) order by start_date) as rvn
    from offers
)
select 
    d.date, 
    count(o.offer_id) cnt_active_offers
from 
    dates d 
left join 
    offers o on d.date between o.start_date and o.end_date and o.rvn = d.rvn
group by 
    d.date

In this PostgreSQL version of the query:

• We define a temporary table dates that contains all dates from January 1, 2020 to December 31, 2020 using the generate_series function.
• We create another temporary table offers that contains the offer data with row numbers based on the year and start date.

Last modified on 2024-10-12