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https://issues.apache.org/jira/browse/SPARK-57581?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Max Gekk updated SPARK-57581:
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    Affects Version/s: 4.2.0
                           (was: 4.3.0)

> Encode the TIME data type in Avro with a unit-correct logical type
> ------------------------------------------------------------------
>
>                 Key: SPARK-57581
>                 URL: https://issues.apache.org/jira/browse/SPARK-57581
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SQL
>    Affects Versions: 4.2.0
>            Reporter: Max Gekk
>            Priority: Major
>              Labels: pull-request-available
>
> h2. What
> Spark's Avro encoding for the TIME data type writes the internal value 
> (nanoseconds since midnight, INT64) but annotates the column with the Avro 
> {{time-micros}} logical type. The declared unit (microseconds) does not match 
> the stored unit (nanoseconds).
> Relevant code:
> * {{SchemaConverters.scala}}: {{case t: TimeType => 
> LogicalTypes.timeMicros().addToSchema(...)}} plus a {{spark.sql.catalyst.type 
> = time(p)}} property.
> * {{AvroSerializer.scala}}: {{case (_: TimeType, LONG) => 
> getter.getLong(ordinal)}} (writes raw nanos).
> * {{AvroDeserializer.scala}}: {{case (LONG, _: TimeType) => 
> updater.setLong(ordinal, value)}} (reads raw nanos).
> Spark-to-Spark round-trips are correct because both the writer and reader 
> treat the value as a raw Long and recover the precision from the 
> {{spark.sql.catalyst.type}} property. However, the value is mislabeled for 
> any consumer that honors the Avro {{time-micros}} logical type.
> h2. Why
> An external Avro reader (Hive, Trino, Flink, fastavro, etc.) decoding a 
> Spark-written TIME column interprets the INT64 as 
> microseconds-since-midnight, while it is actually nanoseconds-since-midnight 
> - a 1000x error that also falls outside the valid micros-of-day range. This 
> affects *all* precisions (0-9), not only 7-9, because even TIME(6) stores 
> nanoseconds under {{time-micros}}.
> For comparison, the Parquet path is unit-correct: it emits TIME(MICROS) with 
> a microsecond value for precision 0-6 and TIME(NANOS) with a nanosecond value 
> for precision 7-9 (SPARK-57551), so Parquet files are interpretable by 
> external tools.
> h2. Scope
> * Write path: emit a logical type whose unit matches the written value:
> ** precision 0-6: {{time-micros}}, write microseconds (nanos -> micros).
> ** precision 7-9: {{time-nanos}}, write nanoseconds (if the bundled Avro 
> version exposes a nanosecond TIME logical type; otherwise document/choose an 
> alternative encoding).
> * Read path: convert by the declared unit - {{time-micros}} -> micros -> 
> nanos, {{time-nanos}} -> nanos (truncated to the requested precision). Keep 
> honoring the {{spark.sql.catalyst.type}} property for precision fidelity.
> * Tests: assert that a plain (non-Spark) Avro decode yields the correct 
> hour/minute/second/fraction, in addition to the existing Spark round-trip 
> tests.
> h2. Backward compatibility (important)
> Changing the on-disk encoding is a format change. Avro files already written 
> by current Spark store nanoseconds under {{time-micros}}; a new unit-correct 
> reader would misread those legacy files (treating nanoseconds as 
> microseconds). The fix must define how legacy files are detected/handled - 
> e.g. keying off the {{spark.sql.catalyst.type}} property or a writer-version 
> marker, or accepting the break given how recently TIME-in-Avro shipped. This 
> migration question is the main design decision for the ticket.
> h2. Out of scope
> * The TIME precision extension itself (SPARK-57551).
> * Non-Avro datasources (Parquet/ORC already correct).



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