Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/8988#discussion_r41544041
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/CatalystSchemaConverter.scala
---
@@ -347,13 +350,13 @@ private[parquet] class CatalystSchemaConverter(
// NOTE: Spark SQL TimestampType is NOT a well defined type in
Parquet format spec.
//
// As stated in PARQUET-323, Parquet `INT96` was originally
introduced to represent nanosecond
- // timestamp in Impala for some historical reasons, it's not
recommended to be used for any
- // other types and will probably be deprecated in future Parquet
format spec. That's the
- // reason why Parquet format spec only defines `TIMESTAMP_MILLIS`
and `TIMESTAMP_MICROS` which
- // are both logical types annotating `INT64`.
+ // timestamp in Impala for some historical reasons. It's not
recommended to be used for any
+ // other types and will probably be deprecated in some future
version of parquet-format spec.
+ // That's the reason why parquet-format spec only defines
`TIMESTAMP_MILLIS` and
+ // `TIMESTAMP_MICROS` which are both logical types annotating
`INT64`.
//
// Originally, Spark SQL uses the same nanosecond timestamp type as
Impala and Hive. Starting
- // from Spark 1.5.0, we resort to a timestamp type with 100 ns
precision so that we can store
+ // from Spark 1.4.0, we resort to a timestamp type with 100 ns
precision so that we can store
--- End diff --
This should be 1.5
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