A data engineer is working on a Streaming DataFrame streaming_df with the given streaming data:Which...

[Reference: Databricks Structured Streaming Guide – Unsupported Operations., B. groupby("Id").count()Supported — Streaming aggregations over a key (like groupBy("Id")) are supported. Spark maintains intermediate state for each key.Reference: Databricks Docs → Aggregations in Structured Streaming (https://docs.databricks.com/structured-streaming/aggregation.html), C. orderBy("timestamp").limit(4) Not allowed — Sorting and limiting require a full view of the stream (which is infinite), so this is unsupported in streaming DataFrames.Reference: Spark Structured Streaming – Unsupported Operations (ordering without watermark/window not allowed)., D. filter(col("count") < 30).show() Not allowed — show() is a blocking operation used for debugging batch DataFrames; it's not allowed on streaming DataFrames.Reference: Structured Streaming Programming Guide – Output operations like show() are not supported., , Reference Extract from Official Guide:, “Operations like orderBy, limit, show, and countDistinct are not supported in Structured Streaming because they require the full dataset to compute a result. Use groupBy(...).agg(...) instead for incremental aggregations.”— Databricks Structured Streaming Programming Guide]