gustavoatt commented on a change in pull request #1184:
URL: https://github.com/apache/iceberg/pull/1184#discussion_r454597256
##########
File path:
spark/src/test/java/org/apache/iceberg/spark/data/TestSparkParquetReader.java
##########
@@ -67,4 +78,49 @@ protected void writeAndValidate(Schema schema) throws
IOException {
Assert.assertFalse("Should not have extra rows", rows.hasNext());
}
}
+
+ protected List<InternalRow> rowsFromFile(InputFile inputFile, Schema schema)
throws IOException {
+ try (CloseableIterable<InternalRow> reader =
+ Parquet.read(inputFile)
+ .project(schema)
+ .createReaderFunc(type -> SparkParquetReaders.buildReader(schema,
type))
+ .build()) {
+ return Lists.newArrayList(reader);
+ }
+ }
+
+ @Test
+ public void testInt96TimestampProducedBySparkIsReadCorrectly() throws
IOException {
+ final SparkSession spark =
+ SparkSession.builder()
+ .master("local[2]")
+ .config("spark.sql.parquet.int96AsTimestamp", "false")
+ .getOrCreate();
Review comment:
Yes, I would much rather avoid creating a `SparkSession` here if
possible. However, looking into
[`ParquetFileFormat`](https://sourcegraph.com/github.com/apache/spark@d6a68e0b67ff7de58073c176dd097070e88ac831/-/blob/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala#L74:1)
it seems like we would still need to pass a `SparkSession` to create the
writer.
I can look at
[`ParquetOutputWriter`](https://sourcegraph.com/github.com/apache/spark@d6a68e0b67ff7de58073c176dd097070e88ac831/-/blob/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetOutputWriter.scala#L32)
but I might need to match the configuration there with what Spark uses to
write int96.
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