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Currently the only supported INT64 DateTimeFormat is for a ConvertedType of TIMESTAMP_MILLIS.
Per https://spark.apache.org/docs/latest/sql-ref-datetime-pattern.html and https://spark.apache.org/docs/3.4.1/configuration.html#runtime-sql-configuration it seems the preference for Spark (ie what underlies DataBricks) is to use Parquet's LogicalType TimestampType(isAdjustedToUTC = true, unit = MICROS) (ie ConvertedType TIMESTAMP_MICROS) as truncation likely occurs when ingesting nanos or exporting millis.
Is it possible to add additional INT64 timestamp support to include MICROS?
The text was updated successfully, but these errors were encountered:
I'm willing to add UTC = true, unit = NANOS once MICROS is done
UTC = true, unit = NANOS
MICROS
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aloneguid
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Issue description
Currently the only supported INT64 DateTimeFormat is for a ConvertedType of TIMESTAMP_MILLIS.
Per https://spark.apache.org/docs/latest/sql-ref-datetime-pattern.html and https://spark.apache.org/docs/3.4.1/configuration.html#runtime-sql-configuration it seems the preference for Spark (ie what underlies DataBricks) is to use Parquet's LogicalType TimestampType(isAdjustedToUTC = true, unit = MICROS) (ie ConvertedType TIMESTAMP_MICROS) as truncation likely occurs when ingesting nanos or exporting millis.
Is it possible to add additional INT64 timestamp support to include MICROS?
The text was updated successfully, but these errors were encountered: