Change implementation of ApproxCountDistinctForIntervals to TypedImperativeAggregate

The current implementation of `ApproxCountDistinctForIntervals` is `ImperativeAggregate`. The number of `aggBufferAttributes` is the number of total words in the hllppHelper array. Each hllppHelper has 52 words by default relativeSD.

Since this aggregate function is used in equi-height histogram generation, and the number of buckets in histogram is usually hundreds, the number of `aggBufferAttributes` can easily reach tens of thousands or even more.

This leads to a huge method in codegen and causes errors such as `org.codehaus.janino.JaninoRuntimeException: Code of method "apply(Lorg/apache/spark/sql/catalyst/InternalRow;)Lorg/apache/spark/sql/catalyst/expressions/UnsafeRow;" of class "org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection" grows beyond 64 KB`.

Besides, huge generated methods also result in performance regression.