Why do returned values in the Metrics API grow larger for a larger timeframe?

The correct choice highlights that results are aggregated over longer periods when using the Metrics API. When querying metrics over an extended timeframe, the system compiles and consolidates data points to provide a summary for that duration. This aggregation process means that instead of retrieving every individual data point—such as every second or minute—across a larger timeframe, the API will compress those data points into broader summaries, like hourly or daily averages, totals, or maximum values.

This aggregation allows for a more manageable volume of data and can provide a clearer overview of trends, rather than overwhelming users with excessive granularity that might not be needed for long-term analysis. As a result, the returned values reflect a more synthesized and summarized version of the data, leading to larger values that represent the cumulative insights gathered over the specified timeframe.

The other options don't accurately depict this aggregation process. Although inefficient queries could lead to performance issues, they don't directly correlate to the data size increase over time. Data quality typically remains consistent regardless of the timeframe; it doesn't inherently decrease over longer periods within the context of how the Metrics API retrieves and aggregates data. Lastly, while it's true that different aggregation methods may be employed at larger timeframes, this is more of a byproduct of the aggregation