rdblue commented on code in PR #4614:
URL: https://github.com/apache/iceberg/pull/4614#discussion_r857184074
##########
spark/v2.4/spark/src/test/java/org/apache/iceberg/spark/source/TestIcebergSourceTablesBase.java:
##########
@@ -1415,6 +1415,89 @@ public void testRemoveOrphanFilesActionSupport() throws
InterruptedException {
Assert.assertEquals("Rows must match", records, actualRecords);
}
+ @Test
+ public void testOverwritePartition() {
+ TableIdentifier tableIdentifier = TableIdentifier.of("db", "entries_test");
+ Table table = createTable(tableIdentifier, SCHEMA,
PartitionSpec.builderFor(SCHEMA).identity("id").build());
+
+ Dataset<Row> df1 = spark.createDataFrame(Lists.newArrayList(new
SimpleRecord(1, "a")), SimpleRecord.class);
+ df1.select("id", "data").write()
+ .format("iceberg")
+ .mode("append")
+ .save(loadLocation(tableIdentifier));
+
+ List<SimpleRecord> result = spark.read()
+ .format("iceberg")
+ .load(loadLocation(tableIdentifier))
+ .as(Encoders.bean(SimpleRecord.class))
+ .collectAsList();
+ Assert.assertEquals(result, Lists.newArrayList(new SimpleRecord(1, "a")));
+
+ // Now, we try to overwrite the partition id=1
+ Dataset<Row> df2 = spark.createDataFrame(Lists.newArrayList(new
SimpleRecord(1, "b")), SimpleRecord.class);
+ df2.select("id", "data").write()
+ .format("iceberg")
+ .mode("overwrite")
+ .option("overwrite-partitions", "id=1")
+ .save(loadLocation(tableIdentifier));
+
+ result = spark.read()
+ .format("iceberg")
+ .load(loadLocation(tableIdentifier))
+ .as(Encoders.bean(SimpleRecord.class))
+ .collectAsList();
+ Assert.assertEquals(result, Lists.newArrayList(new SimpleRecord(1, "b")));
+ }
+
+ @Test
+ public void testOverwritePartitionFilterMultipleSpecs() {
+ TableIdentifier identifier = TableIdentifier.of("db", "table");
+ Schema schema = new Schema(
+ Types.NestedField.optional(1, "ds", Types.StringType.get()),
+ Types.NestedField.optional(2, "data", Types.IntegerType.get()));
+ PartitionSpec originalSpec =
PartitionSpec.builderFor(schema).identity("ds").build();
+ Table table = createTable(identifier, schema, originalSpec);
+
+ List<Row> records = Lists.newArrayList(
+ RowFactory.create("2021-01-01", 1),
+ RowFactory.create("2021-01-02", 2)
+ );
+ StructType originalSparkSchema = SparkSchemaUtil.convert(schema);
+ Dataset<Row> inputDf = spark.createDataFrame(records, originalSparkSchema);
+
+ inputDf.select("ds", "data").write()
+ .format("iceberg")
+ .mode(SaveMode.Overwrite)
+ .save(loadLocation(identifier));
+
+
+ Dataset<Row> readInputDf = spark.read()
+ .format("iceberg")
+ .load(loadLocation(identifier));
+ Assert.assertEquals(2, readInputDf.count());
+
+ // Now let's alter the partition spec.
+ table.updateSpec().addField("data").commit();
+
+ List<Row> insertRecords = Lists.newArrayList(
+ RowFactory.create("2021-01-01", 100)
+ );
+ spark.createDataFrame(insertRecords, originalSparkSchema)
+ .select("ds", "data")
+ .write()
+ .format("iceberg")
+ .option("overwrite-partitions", "ds='2021-01-01'")
+ .mode(SaveMode.Overwrite)
+ .save(loadLocation(identifier));
+
+ // When reading we should only see two rows still
+ readInputDf = spark.read()
+ .format("iceberg")
+ .load(loadLocation(identifier));
+ Assert.assertEquals(2, readInputDf.count());
Review Comment:
It would be better to assert that the records match the expected ones.
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