The available listing describes “Combined Reaction Volume” as an SQL interview tutorial associated with Meta, but it does not reveal the interview prompt, schema, or expected output. That means there is no reliable way to provide a definitive query. Here’s what the listing establishes, what is missing, and how to reason about the problem without mistaking an example for Meta’s answer.
What the available listing actually establishes
A Dev Community search-result listing identifies a three-minute SQL interview tutorial by Rahman titled “Meta’s ‘Combined Reaction Volume’ SQL Question, Explained Simply.” It does not establish that Meta published, uses, or endorses the question. The listing is not the original prompt or an official Meta source. View the Dev Community database-topic listing.
Why there isn’t a definitive SQL answer yet
The indexed entry does not expose the question itself. The table names, columns, join keys, requested result, and definition of “combined reaction volume” are therefore unknown. The phrase alone could mean combining reaction categories, data from multiple sources, or another aggregation specified by the prompt; none of those interpretations is confirmed.
Those missing details determine the query. For example, a question asking for a total by post requires a different grouping from one asking for totals by user or date. The data representation matters too: reaction counts might appear in separate columns, as individual rows, or across multiple source tables. Without the prompt and schema, a query presented as the answer would be a guess.
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How to solve the question once you have its wording and schema
- Identify the output grain. Determine whether the result should contain one row per post, user, date, or another unit. That determines the grouping.
- Inspect how reactions are stored. Establish whether categories are separate columns, individual records, or data in multiple tables.
- Clarify what “combined” means in the prompt. Check which categories or sources should be included, and whether any filters apply.
- Confirm join keys and missing-value rules. If tables must be joined, use the keys specified by the schema. Determine how absent reactions or categories should affect the total.
- Aggregate to the requested grain. Sum or otherwise combine the relevant values, then group by the dimensions requested in the prompt.
- Check the result against the wording. Verify that the query includes the intended categories and filters and returns only the requested level of detail.
These are general SQL problem-solving steps, not a reconstruction of the unavailable interview question.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What a hypothetical query can—and cannot—show
For illustration only, suppose a table named post_reactions has one row per post and the integer columns like_count and love_count. If a hypothetical task asks for the combined count of those two categories per post, a query could be:
SELECT post_id,
COALESCE(like_count, 0) + COALESCE(love_count, 0) AS combined_reactions
FROM post_reactions;This example assumes the categories are stored in separate columns and the output requires one row per post. COALESCE treats a null count as zero in this illustration. The actual prompt may use different tables, columns, categories, null-handling rules, or output grain; this is not established as Meta’s question or its expected solution.
Quick Recap
What to verify before relying on an answer
- The full prompt is available, not just the indexed title.
- The schema and column meanings match the query.
- The query groups results at the requested grain.
- The definition of “combined” and any filters are explicit.
- Nulls, missing categories, and joins are handled according to the prompt.
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