wypoon commented on a change in pull request #1508:
URL: https://github.com/apache/iceberg/pull/1508#discussion_r702205781
##########
File path:
spark/src/test/java/org/apache/iceberg/spark/source/TestIcebergSourceTablesBase.java
##########
@@ -901,6 +915,199 @@ public void testPartitionsTable() {
}
}
+ @Test
+ public synchronized void testSnapshotReadAfterAddColumn() {
+ TableIdentifier tableIdentifier = TableIdentifier.of("db", "table");
+ Table table = createTable(tableIdentifier, SCHEMA,
PartitionSpec.unpartitioned());
+
+ List<Row> expectedRecords = Lists.newArrayList(
+ RowFactory.create(1, "x"),
+ RowFactory.create(2, "y"),
+ RowFactory.create(3, "z"));
+
+ Dataset<Row> inputDf = spark.createDataFrame(expectedRecords,
SparkSchemaUtil.convert(SCHEMA));
+ inputDf.select("id", "data").write()
+ .format("iceberg")
+ .mode(SaveMode.Append)
+ .save(loadLocation(tableIdentifier));
+
+ table.refresh();
+
+ Dataset<Row> resultDf = spark.read()
+ .format("iceberg")
+ .load(loadLocation(tableIdentifier));
+ List<Row> actualRecords = resultDf.orderBy("id")
+ .collectAsList();
+
+ Assert.assertEquals("Records should match", expectedRecords,
actualRecords);
+ Snapshot snapshot1 = table.currentSnapshot();
+
+ table.updateSchema().addColumn("category",
Types.StringType.get()).commit();
+
+ List<Row> newRecords = Lists.newArrayList(
+ RowFactory.create(4, "xy", "B"),
+ RowFactory.create(5, "xyz", "C"));
+
+ Dataset<Row> inputDf2 = spark.createDataFrame(newRecords,
SparkSchemaUtil.convert(SCHEMA2));
+ inputDf2.select("id", "data", "category").write()
+ .format("iceberg")
+ .mode(SaveMode.Append)
+ .save(loadLocation(tableIdentifier));
+
+ table.refresh();
+
+ Dataset<Row> resultDf2 = spark.read()
+ .format("iceberg")
+ .load(loadLocation(tableIdentifier));
+ List<Row> actualRecords2 = resultDf2.orderBy("id")
+ .collectAsList();
+
+ List<Row> expectedRecords2 = Lists.newArrayList(
+ RowFactory.create(1, "x", null),
+ RowFactory.create(2, "y", null),
+ RowFactory.create(3, "z", null),
+ RowFactory.create(4, "xy", "B"),
+ RowFactory.create(5, "xyz", "C"));
+ Assert.assertEquals("Records should match", expectedRecords2,
actualRecords2);
+
+ Dataset<Row> resultDf3 = spark.read()
+ .format("iceberg")
+ .option(SparkReadOptions.SNAPSHOT_ID, snapshot1.snapshotId())
+ .load(loadLocation(tableIdentifier));
+ List<Row> actualRecords3 = resultDf3.orderBy("id")
+ .collectAsList();
+
+ Assert.assertEquals("Records should match", expectedRecords,
actualRecords3);
+ }
+
+ @Test
+ public synchronized void testSnapshotReadAfterDropColumn() {
+ TableIdentifier tableIdentifier = TableIdentifier.of("db", "table");
+ Table table = createTable(tableIdentifier, SCHEMA2,
PartitionSpec.unpartitioned());
+
+ List<Row> expectedRecords = Lists.newArrayList(
+ RowFactory.create(1, "x", "A"),
+ RowFactory.create(2, "y", "A"),
+ RowFactory.create(3, "z", "B"));
+
+ Dataset<Row> inputDf = spark.createDataFrame(expectedRecords,
SparkSchemaUtil.convert(SCHEMA2));
+ inputDf.select("id", "data", "category").write()
+ .format("iceberg")
+ .mode(SaveMode.Append)
+ .save(loadLocation(tableIdentifier));
+
+ table.refresh();
+
+ Dataset<Row> resultDf = spark.read()
+ .format("iceberg")
+ .load(loadLocation(tableIdentifier));
+ List<Row> actualRecords = resultDf.orderBy("id")
+ .collectAsList();
+
+ Assert.assertEquals("Records should match", expectedRecords,
actualRecords);
+
+ long ts1 = System.currentTimeMillis();
Review comment:
Thanks for the tip.
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