Went with a self-join on the same table comparing dates.
Use a window function to compute the most recent status before each event for each seller, then filter for 'block' or 'suspend' events where the prior status was 'reinstate'. Alternatively, use a self-join to compare each event with the latest preceding event of a different status. Ensure the solution handles multiple events per seller and considers only the immediately preceding status.
Pro tip: Clarify the definition of 'after'—whether it means immediately after or any time after—and confirm if multiple blocks/suspends after a reinstate should be deduplicated. Also, mention that you'd test edge cases like sellers with no reinstate or multiple reinstates.
Identify the table schema (seller_id, status, event_time) and clarify what 'after' means (immediately or any time). Confirm if the result should be distinct seller IDs.
Use event_time to order events per seller. If ties exist, define a tie-breaker (e.g., event_id).
Use LAG() window function partitioned by seller_id and ordered by event_time to get the previous status. Alternatively, use a self-join with a subquery to find the latest event before the current one.
Select rows where current status is 'block' or 'suspend' and previous status is 'reinstate'. Return distinct seller_id.
Check for edge cases (e.g., first event, multiple reinstates) and consider indexing on (seller_id, event_time) for performance.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This tripped me up more than it should have.
Use a window function to rank events per seller by timestamp descending, then filter for the most recent 'reinstate' event and find the first subsequent status. Alternatively, use a correlated subquery or self-join to identify the next event after the latest reinstate per seller.
Pro tip: Clarify edge cases upfront: what if there is no 'reinstate' event for a seller, or no status after it? Discuss how to handle ties in timestamps and whether 'status' includes the reinstate event itself.
Identify the table structure: seller_id, event_type (e.g., 'reinstate', 'status'), timestamp, and status value. Clarify that 'first status after' means the earliest event with a status type that occurs after the most recent reinstate.
Use a subquery or window function (e.g., ROW_NUMBER() OVER (PARTITION BY seller_id ORDER BY timestamp DESC)) to get the latest 'reinstate' event for each seller.
For each seller, find the event with the smallest timestamp greater than the reinstate timestamp, filtering for status events. This can be done with a correlated subquery or a join with a condition on timestamp.
Decide how to handle sellers with no reinstate or no subsequent status (e.g., exclude them or return NULL). Ensure the final query returns seller_id and the status value.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Use two separate filtered aggregations (one for product 'A' in 2010, one for product 'B' in 2018) and then find the intersection of customer IDs. This can be done with INTERSECT, INNER JOIN, or EXISTS subqueries. Ensure you handle date ranges correctly and consider performance by filtering early.
Pro tip: Mention that if the table is large, you can optimize by using EXISTS or INNER JOIN on indexed columns, and that INTERSECT may not be supported in all databases (e.g., MySQL). Also, clarify whether 'bought' means quantity > 0 or just presence of a row.
Confirm the table schema (e.g., columns: customer_id, product, purchase_date, quantity) and define what 'bought' means (e.g., at least one row, or quantity > 0). Also confirm date ranges: 2010-01-01 to 2010-12-31 and 2018-01-01 to 2018-12-31.
Write a subquery or CTE that selects distinct customer IDs where product = 'A' and purchase_date is within 2010.
Write a similar subquery or CTE that selects distinct customer IDs where product = 'B' and purchase_date is within 2018.
Use INTERSECT, INNER JOIN, or EXISTS to return only customer IDs that appear in both result sets. Ensure the final output is distinct customer IDs.
Discuss indexing on (product, purchase_date) or (customer_id, product, purchase_date), and handle cases where a customer bought multiple times or in different years.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.