1. Lighthouse

Level 7 · Nobody has ever skipped the website?

The request

From Ashley Rivera, Web Content Lead

“I want to know which customers have never had a session on our website, split by segment. This query returns nothing, so apparently every single customer has visited. I don't believe it. Can you fix it?”

Your goal

Fix the query. For customers with no row at all in web_sessions, return one row per segment with: segment, customers (number of such customers) and with_orders (how many of them have at least one order of any status).

  • Read from the customers tablenot done yet
  • Read from the orders tablenot done yet
  • Show exactly segment customers with_ordersnot done yet

Your query

SQL

Loading the editor…

    ResultPreview of customers · press Run to see yours
    Preview of customers
    customer_idfirst_namelast_nameemailcity
    1OwenHudsonowen.hudson@icloud.comSan Francisco
    2DouglasMendozadmendoza69@gmail.comAtlanta
    3HenryBrookshbrooks@lakesidecafe.comLos Angeles
    4BrianGrahambgraham@bluecedarhomes.comSeattle

    Mote checks your result

    Press Run. Each row that matches the goal becomes a firefly in your lantern.

    Tables

    Harbor & Pine store data, ready to query.

    customers2,018 rows · 9 columns
    • customer_idinteger
    • first_namevarchar
    • last_namevarchar
    • emailvarchar
    • cityvarchar
    • statevarchar
    • signup_datedate
    • segmentvarchar
    • referral_sourcevarchar
    First 5 rows of customers
    customer_idfirst_namelast_nameemailcitystatesignup_datesegmentreferral_source
    1OwenHudsonowen.hudson@icloud.comSan FranciscoCA2022-06-02consumersearch
    2DouglasMendozadmendoza69@gmail.comAtlantaGA2022-06-02consumerNULL
    3HenryBrookshbrooks@lakesidecafe.comLos AngelesCA2022-06-04businessNULL
    4BrianGrahambgraham@bluecedarhomes.comSeattleWA2022-06-06businesspinterest
    5KyleJimenezkjimenez27@yahoo.comIndianapolisIN2022-06-07consumerNULL
    orders12,000 rows · 7 columns
    • order_idinteger
    • customer_idinteger
    • order_datetimestamp
    • statusvarchar
    • channelvarchar
    • shipping_feedecimal
    • coupon_codevarchar
    First 5 rows of orders
    order_idcustomer_idorder_datestatuschannelshipping_feecoupon_code
    10011252023-01-01 20:51:19completedweb0.00NULL
    10021562023-01-02 07:58:46completedweb0.00NULL
    1003222023-01-02 10:25:27completedmarketplace4.99WELCOME10
    1004482023-01-02 11:21:51completedmarketplace4.99WELCOME10
    1005822023-01-02 11:43:36completedweb0.00WELCOME10
    web_sessions40,000 rows · 7 columns
    • session_idinteger
    • customer_idinteger
    • started_attimestamp
    • devicevarchar
    • sourcevarchar
    • pages_viewedinteger
    • convertedboolean
    First 5 rows of web_sessions
    session_idcustomer_idstarted_atdevicesourcepages_viewedconverted
    1NULL2023-01-01 23:02:24mobilepaid1false
    2182023-01-01 15:07:49desktoppaid1false
    3NULL2023-01-01 16:55:46desktopdirect7false
    4NULL2023-01-01 12:43:28mobileorganic3false
    5NULL2023-01-01 13:06:21mobilesocial2false
    products120 rows · 8 columns
    • product_idinteger
    • namevarchar
    • categoryvarchar
    • subcategoryvarchar
    • unit_pricedecimal
    • unit_costdecimal
    • launched_ondate
    • is_activeboolean
    First 5 rows of products
    product_idnamecategorysubcategoryunit_priceunit_costlaunched_onis_active
    101Vale Velvet LoveseatFurnitureSofas1659.00NULL2023-09-11true
    102Alder Oak Coffee TableFurnitureTables919.00503.502024-05-16true
    103Orchard Rattan Dining ChairFurnitureChairs789.00429.872023-05-27true
    104Upland Oak BookcaseFurnitureStorage429.00214.702022-12-20true
    105Avery Leather Bed FrameFurnitureBeds449.00232.702021-08-31true
    order_items30,338 rows · 6 columns
    • order_item_idinteger
    • order_idinteger
    • product_idinteger
    • quantityinteger
    • unit_pricedecimal
    • discount_pctdecimal
    First 5 rows of order_items
    order_item_idorder_idproduct_idquantityunit_pricediscount_pct
    11001121931.990.00
    21001154311.990.00
    31002154411.990.00
    410021941149.000.00
    51002193219.990.00
    returns1,673 rows · 5 columns
    • return_idinteger
    • order_item_idinteger
    • returned_ondate
    • reasonvarchar
    • refund_amountdecimal
    First 5 rows of returns
    return_idorder_item_idreturned_onreasonrefund_amount
    1142023-01-10damaged83.69
    2422023-01-10wrong_item19.99
    31052023-01-14wrong_item10.99
    4242023-01-16changed_mind26.99
    51262023-01-16late20.99
    employees60 rows · 8 columns
    • employee_idinteger
    • first_namevarchar
    • last_namevarchar
    • departmentvarchar
    • titlevarchar
    • manager_idinteger
    • hire_datedate
    • salaryinteger
    First 5 rows of employees
    employee_idfirst_namelast_namedepartmenttitlemanager_idhire_datesalary
    1CatherineHaleExecutiveChief Executive OfficerNULL2016-03-01285000
    2RobertKimExecutiveChief Operating Officer12017-01-09235000
    3MeganCollinsSalesHead of Sales12018-04-16172000
    4ChloeGutierrezSalesAccount Executive32020-01-2172000
    5FrankBellSalesAccount Executive32023-05-2173000
    marketing_spend3,276 rows · 3 columns
    • spend_datedate
    • channelvarchar
    • amountdecimal
    First 5 rows of marketing_spend
    spend_datechannelamount
    2023-01-01paid492.99
    2023-01-01email37.38
    2023-01-01social200.53
    2023-01-02paid709.13
    2023-01-02email64.13

    The lesson

    An empty result is a result too. The starter says no customer ever skipped the website, and that is exactly what a NOT IN bug looks like.

    Why one NULL empties the result

    x NOT IN (a, b, c) means x <> a AND x <> b AND x <> c. If one of the values is NULL, x <> NULL is not true or false but unknown, and an AND chain that contains an unknown can never be true. The row is filtered out.

    web_sessions has 23,002 anonymous sessions with customer_id NULL. So for every customer, customer_id NOT IN (SELECT customer_id FROM web_sessions) is unknown, and the query returns nothing. Note that IN does not have this problem: a match is a match, whatever else is in the list. That is why the with_orders column in the starter is fine.

    How to spot it

    • An anti-join (NOT IN, “never”, “without”) that returns zero rows is suspicious on its own.
    • Check the subquery column for NULLs: SELECT COUNT(*) FROM web_sessions WHERE customer_id IS NULL returns 23,002.
    • Count the other side: 1,813 distinct customers have a session, out of 2,018 customers. The answer cannot be zero.

    The fix

    NOT EXISTS looks for a matching row, and a NULL never matches:

    WHERE NOT EXISTS (
      SELECT 1 FROM web_sessions AS w
      WHERE w.customer_id = c.customer_id
    )

    The result: 205 customers, 29 business and 176 consumer. Of those, 20 business and 101 consumer customers have placed an order, so they buy without ever showing up in web tracking (on the app or a marketplace, for example).

    Filtering the NULLs out also works: NOT IN (SELECT customer_id FROM web_sessions WHERE customer_id IS NOT NULL) returns the same 205. A LEFT JOIN ... WHERE w.session_id IS NULL works as well, but NOT EXISTS states the intent most clearly.

    Common mistakes

    • Adding COALESCE(customer_id, 0) inside the subquery: it works only as long as no real id is 0.
    • Testing the NOT IN on a small sample without anonymous sessions, where it seems to work.
    • Reporting “zero” without checking it. An empty anti-join deserves the same suspicion as a total that doubled.

    In SQL Server

    The behavior is identical under the default ANSI_NULLS ON: one NULL in the list and NOT IN returns nothing. The same NOT EXISTS works as written, and ISNULL(x, 0) is T-SQL’s two-argument cousin of COALESCE, with the same caveat as above.

    Interview note

    “Why does this NOT IN query return no rows?” is a classic. The answer is three-valued logic with NULL, and the fix is NOT EXISTS.

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