HardSQL challenge #226WINDOW FUNCTIONLAGANALYTICS

Calculate the Difference from the Previous Order with LAG()

Return each order with the change in total compared with the order before it.

The challenge runs on the SQLabHub practice database (SQLite) and uses the orders table. You can solve it in the browser, with nothing to install.

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The task

Find difference between current and previous order.

A correct answer returns 200 rows with 3 columns: id, total, diff.

Tables used in this challenge

orders 200 rows

id INTEGER (PK) · user_id INTEGER · total REAL · discount REAL · item_count INTEGER · status TEXT · order_date TEXT · shipped_date TEXT · shipping_city TEXT · shipping_country TEXT

First 3 rows of the orders table
iduser_idtotaldiscountitem_countstatusorder_dateshipped_dateshipping_cityshipping_country
1432638.110.253cancelled2024-04-24NULLLos AngelesUSA
2829470.195delivered2024-03-152023-04-09ChicagoUSA
3136683.240.082delivered2023-02-152023-07-10Los AngelesUSA

The first rows of each table are shown. See how all the tables relate on the database schema page.

Expected output

Expected output of the challenge
idtotaldiff
581843.49NULL
43920.442076.95
891152.13-2768.31
1013391.662239.5299999999997
84163.77772.1100000000006

First 5 of 200 rows. This is the output of the model solution on the practice database. The task does not fix a sort order, so your rows may come back in a different order.

What you practise

  • Reading the previous row's value with LAG()
  • Deriving a new column from an expression and naming it with an alias

Hint and approach

Try the challenge first. Open these only when you need them.

Show the hint

LAG(total)

Show the step-by-step approach

How the model solution is built, in the order the database evaluates it:

  1. Read from the orders table.
  2. Fetch total from the previous row with LAG(), ordered by order_date. Where there is no such row the value is NULL.
  3. Combine those values into diff: total - LAG(total) OVER (ORDER BY order_date).

Model solution

Checking your session…

What to watch for

LAG(total) OVER (ORDER BY order_date) fetches the prior row's total. The first row has no predecessor, so its difference is NULL; LAG(total, 1, 0) supplies a default instead. Orders sharing a date have no defined order between them here.

  • LAG(). LAG() returns NULL for the first row of each partition, and any arithmetic with that NULL is NULL too. Supply a default as the third argument if you need a number.
  • Calculated columns. Dividing one integer by another truncates the result in SQLite. Multiply one side by 1.0 to get decimals.
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Same technique, other tables

More practice on this pattern with different columns:

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