id: nested_explode_outer_empty
category: schema_nested
difficulty: medium
probes: >
  explode() drops rows whose array is empty or null; explode_outer() keeps them
  with a NULL element. The fixture contains one empty array and one null array,
  so the two functions give different row counts.
tags: [explode, arrays, null_semantics]

prompt: |
  Flatten the tags array in `docs` so there is one row per tag, KEEPING documents
  that have an empty or null tags array (their tag should be null).

  Return columns: doc_id, tag.

fixtures:
  - name: docs
    schema: doc_id INT, tags ARRAY<STRING>
    rows:
      - [1, ["x", "y"]]
      - [2, []]
      - [3, null]
      - [4, ["z"]]

solution: |
  from pyspark.sql import functions as F

  def solve(spark, docs):
      # explode() would silently drop docs 2 and 3.
      return docs.select("doc_id", F.explode_outer("tags").alias("tag"))

compare:
  mode: rows