RussellSpitzer commented on code in PR #11419:
URL: https://github.com/apache/iceberg/pull/11419#discussion_r1828011849
##########
spark/v3.3/spark/src/test/java/org/apache/iceberg/spark/source/TestDataFrameWriterV2.java:
##########
@@ -226,4 +229,100 @@ public void testWriteWithCaseSensitiveOption() throws
NoSuchTableException, Pars
fields = Spark3Util.loadIcebergTable(sparkSession,
tableName).schema().asStruct().fields();
Assert.assertEquals(4, fields.size());
}
+
+ @Test
+ public void testMergeSchemaIgnoreDowncast() throws Exception {
+ //// test long to int ignore case
+ sql(
+ "ALTER TABLE %s SET TBLPROPERTIES ('%s'='true')",
+ tableName, TableProperties.SPARK_WRITE_ACCEPT_ANY_SCHEMA);
+
+ Dataset<Row> bigintDF =
+ jsonToDF(
+ "id bigint, data string",
+ "{ \"id\": 1, \"data\": \"a\" }",
+ "{ \"id\": 2, \"data\": \"b\" }");
+
+ bigintDF.writeTo(tableName).append();
+
+ assertEquals(
+ "Should have initial rows with long column",
+ ImmutableList.of(row(1L, "a"), row(2L, "b")),
+ sql("select * from %s order by id", tableName));
+
+ Dataset<Row> intDF =
+ jsonToDF(
+ "id int, data string",
+ "{ \"id\": 3, \"data\": \"c\" }",
+ "{ \"id\": 4, \"data\": \"d\" }");
+
+ try {
+ intDF.writeTo(tableName).option("merge-schema", "true").append();
+ } catch (IllegalArgumentException e) {
+ Assert.fail(String.format("Should not throw exception: %s", e));
+ }
+
+ assertEquals(
+ "Should include new rows with unchanged long column type",
+ ImmutableList.of(row(1L, "a"), row(2L, "b"), row(3L, "c"), row(4L,
"d")),
+ sql("select * from %s order by id", tableName));
+
+ // verify the column type did not change
+ String[] tblNameSplit = tableName.split("\\.");
Review Comment:
May be easier to use the Spark Helpers here, although the validation catalog
is also fine to check but I don't think it matters much in this case.
```java
Spark3Util.loadIcebergTable(spark, tableName).schema()
```
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