Which functions are described as resource-heavy?

Aggregation functions are described as resource-heavy because they involve processing large volumes of data to summarize or compute metrics based on that data. When an aggregation function is applied, especially over large data sets, it typically requires significant memory and CPU resources to calculate the results. These functions require the system to evaluate the data in order to produce a single output for potentially many input records, which can lead to increased computational strain.

In the context of data operations, filtering and transformation functions may also require processing resources, but they generally do not impose the same level of resource demand as aggregation functions because filtering typically selects a subset of data based on criteria without needing to summarize it, and transformation applies changes without necessarily condensing the data. Sorting functions, while they can also be resource-intensive depending on the size of the dataset, operate differently by ordering data rather than aggregating it.

Therefore, the classification of aggregation functions as resource-heavy aligns with their nature of summarizing data, which inherently makes them more demanding in terms of computational resources.