Different default behaviors of skipping empty buckets in timeseries queries by Druid native query and Druid SQL

Question

According to the document of Apache Druid about native query

Timeseries queries normally fill empty interior time buckets with zeroes. For example, if you issue a "day" granularity timeseries query for the interval 2012-01-01/2012-01-04, and no data exists for 2012-01-02, you will receive:

[
  {
    "timestamp": "2012-01-01T00:00:00.000Z",
    "result": { "sample_name1": <some_value> }
  },
  {
   "timestamp": "2012-01-02T00:00:00.000Z",
   "result": { "sample_name1": 0 }
  },
  {
    "timestamp": "2012-01-03T00:00:00.000Z",
    "result": { "sample_name1": <some_value> }
  }
]

This could be controlled by the value of context flag "skipEmptyBuckets", and the default value is false (do not skip the empty bucket by zero-filling).

However, when querying timeseries data with Druid SQL, the default behavior is to skip all empty buckets. I have to set query context explicitly to get the results I want.

  "context": {
    "skipEmptyBuckets": true
  }

This troubles me a lot because I need zero-filling to show all buckets in Apache Superset's timeseries charts. But there's no way to set the query context.

As far as I know, the SQL statement internally is translated to native query, so why is the inconsistency?