flyrain commented on code in PR #4683:
URL: https://github.com/apache/iceberg/pull/4683#discussion_r868259919
##########
spark/v3.2/spark/src/test/java/org/apache/iceberg/spark/source/TestSparkReaderDeletes.java:
##########
@@ -262,4 +271,191 @@ public void testPosDeletesAllRowsInBatch() throws
IOException {
Assert.assertEquals("Table should contain expected rows", expected,
actual);
}
+
+ @Test
+ public void testPosDeletesWithDeletedColumn() throws IOException {
+ // read.parquet.vectorization.batch-size is set to 4, so the 4 rows in the
first batch are all deleted.
+ List<Pair<CharSequence, Long>> deletes = Lists.newArrayList(
+ Pair.of(dataFile.path(), 0L), // id = 29
+ Pair.of(dataFile.path(), 1L), // id = 43
+ Pair.of(dataFile.path(), 2L), // id = 61
+ Pair.of(dataFile.path(), 3L) // id = 89
+ );
+
+ Pair<DeleteFile, CharSequenceSet> posDeletes = FileHelpers.writeDeleteFile(
+ table, Files.localOutput(temp.newFile()), TestHelpers.Row.of(0),
deletes);
+
+ table.newRowDelta()
+ .addDeletes(posDeletes.first())
+ .validateDataFilesExist(posDeletes.second())
+ .commit();
+
+ StructLikeSet expected = expectedRowSet(29, 43, 61, 89);
+ StructLikeSet actual = rowSet(tableName, table, "id", "data", "_deleted");
+
+ validate(expected, actual);
+ }
+
+ @Test
+ public void testEqualityDeleteWithDeletedColumn() throws IOException {
+ String tableName = table.name().substring(table.name().lastIndexOf(".") +
1);
+ Schema deleteRowSchema = table.schema().select("data");
+ Record dataDelete = GenericRecord.create(deleteRowSchema);
+ List<Record> dataDeletes = Lists.newArrayList(
+ dataDelete.copy("data", "a"), // id = 29
+ dataDelete.copy("data", "d"), // id = 89
+ dataDelete.copy("data", "g") // id = 122
+ );
+
+ DeleteFile eqDeletes = FileHelpers.writeDeleteFile(
+ table, Files.localOutput(temp.newFile()), TestHelpers.Row.of(0),
dataDeletes, deleteRowSchema);
+
+ table.newRowDelta()
+ .addDeletes(eqDeletes)
+ .commit();
+
+ StructLikeSet actual = rowSet(tableName, table, "id", "data", "_deleted");
+ validate(expectedRowSet(29, 89, 122), actual);
+ }
+
+ @Test
+ public void testMixedPosAndEqDeletesWithDeletedColumn() throws IOException {
+ Schema dataSchema = table.schema().select("data");
+ Record dataDelete = GenericRecord.create(dataSchema);
+ List<Record> dataDeletes = Lists.newArrayList(
+ dataDelete.copy("data", "a"), // id = 29
+ dataDelete.copy("data", "d"), // id = 89
+ dataDelete.copy("data", "g") // id = 122
+ );
+
+ DeleteFile eqDeletes = FileHelpers.writeDeleteFile(
+ table, Files.localOutput(temp.newFile()), TestHelpers.Row.of(0),
dataDeletes, dataSchema);
+
+ List<Pair<CharSequence, Long>> deletes = Lists.newArrayList(
+ Pair.of(dataFile.path(), 3L), // id = 89
+ Pair.of(dataFile.path(), 5L) // id = 121
+ );
+
+ Pair<DeleteFile, CharSequenceSet> posDeletes = FileHelpers.writeDeleteFile(
+ table, Files.localOutput(temp.newFile()), TestHelpers.Row.of(0),
deletes);
+
+ table.newRowDelta()
+ .addDeletes(eqDeletes)
+ .addDeletes(posDeletes.first())
+ .validateDataFilesExist(posDeletes.second())
+ .commit();
+
+ StructLikeSet expected = expectedRowSet(29, 89, 121, 122);
+ StructLikeSet actual = rowSet(tableName, table, "id", "data", "_deleted");
+
+ validate(expected, actual);
+ }
+
+ @Test
+ public void testFilterOnDeletedMetadataColumn() throws IOException {
+ List<Pair<CharSequence, Long>> deletes = Lists.newArrayList(
+ Pair.of(dataFile.path(), 0L), // id = 29
+ Pair.of(dataFile.path(), 1L), // id = 43
+ Pair.of(dataFile.path(), 2L), // id = 61
+ Pair.of(dataFile.path(), 3L) // id = 89
+ );
+
+ Pair<DeleteFile, CharSequenceSet> posDeletes = FileHelpers.writeDeleteFile(
+ table, Files.localOutput(temp.newFile()), TestHelpers.Row.of(0),
deletes);
+
+ table.newRowDelta()
+ .addDeletes(posDeletes.first())
+ .validateDataFilesExist(posDeletes.second())
+ .commit();
+
+ // get undeleted rows
+ StructLikeSet expected = expectedRowSet(true, false, 29, 43, 61, 89);
+
+ Dataset<Row> df = spark.read()
+ .format("iceberg")
+ .load(TableIdentifier.of("default", tableName).toString())
+ .select("id", "data", "_deleted")
+ .filter("_deleted = false");
+
+ Types.StructType projection = table.schema().select("id", "data",
"_deleted").asStruct();
+ StructLikeSet actual = StructLikeSet.create(projection);
+ df.collectAsList().forEach(row -> {
+ SparkStructLike rowWrapper = new SparkStructLike(projection);
+ actual.add(rowWrapper.wrap(row));
+ });
+
+ validate(expected, actual);
+
+ // get deleted rows
+ expected = expectedRowSet(false, true, 29, 43, 61, 89);
+
+ df = spark.read()
+ .format("iceberg")
+ .load(TableIdentifier.of("default", tableName).toString())
+ .select("id", "data", "_deleted")
+ .filter("_deleted = true");
+
+ StructLikeSet actualDeleted = StructLikeSet.create(projection);
+ df.collectAsList().forEach(row -> {
+ SparkStructLike rowWrapper = new SparkStructLike(projection);
+ actualDeleted.add(rowWrapper.wrap(row));
+ });
+
+ validate(expected, actualDeleted);
+ }
+
+ private static final Schema PROJECTION_SCHEMA = new Schema(
+ required(100, "id", Types.LongType.get()),
Review Comment:
It doesn't matter. I will use the same id.
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