Error on invalid type/logicalType

[stampy88]

• Ran into a nasty issue where I had incorrectly used a time.Duration with a long Avro type and timestamp-millis. Hamba was encoding the entire int64 for this case instead of erroring on an invalid schema. When Spark/SQL tried to convert this into a microseconds (it wants everything as micros), it eventually tries to do this:

def millisToMicros(millis: Long): Long = {
    Math.multiplyExact(millis, MICROS_PER_MILLIS)
}

And Math.multiplyExact detects an overflow because it is trying to multiply the long by 1000, which doesn't fit. This fix will give the user an error if they use the logicalType incorrectly. The error will look something like avro: time.Duration is unsupported for Avro long and logicalType timestamp-micros.

[hhromic]

Hey, I know this has been merged already but I had a question. Sorry to hijack this PR conversation!

I don't see why using a time.Duration is invalid for a long Avro type annotated with either a timestamp-millis or timestamp-micros logical type. While I do agree that it was incorrect for time.Duration to be encoded blindly as int64 (and thus nanos), I think there is no reason for hamba/avro to not do the correct conversion automatically.

• If logical type is timestamp-millis then convert from Duration.Milliseconds().
• If logical type is timestamp-micros then convert from Duration.Microseconds().

At least that is what I would expect the encoder to do because it has everything necessary to do the conversion automatically.

Is there any reason why this behaviour is not desired? I can contribute with it if you feel is a good idea.

EDIT: Ah, sorry, I just realized that time.Duration is not a timestamp to begin with, so is invalid no matter the logical type. Apologies for the noise!