rdblue commented on a change in pull request #1184:
URL: https://github.com/apache/iceberg/pull/1184#discussion_r454036152
##########
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();
+
+ final String parquetPath = temp.getRoot().getAbsolutePath() +
"/parquet_int96";
+ final java.sql.Timestamp ts = java.sql.Timestamp.valueOf("2014-01-01
23:00:01");
+ spark.createDataset(ImmutableList.of(ts),
Encoders.TIMESTAMP()).write().parquet(parquetPath);
Review comment:
Using Spark's `FileFormat` would also make this test easier. You'd be
able to pass in a value in micros and validate that you get the same value
back, unmodified. You'd also not need to locate the Parquet file using `find`.
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