/** Tests the case where we try to convert a string to a long incorrectly. */
@Test(
expected = org.apache.nifi.processors.kite.AvroRecordConverter.AvroConversionException.class)
public void testIllegalConversion() throws Exception {
// We will convert s1 from string to long (or leave it null), ignore s2,
// convert l1 from long to string, and leave l2 the same.
Schema input =
SchemaBuilder.record("Input")
.namespace("com.cloudera.edh")
.fields()
.nullableString("s1", "")
.requiredString("s2")
.optionalLong("l1")
.requiredLong("l2")
.endRecord();
Schema output =
SchemaBuilder.record("Output")
.namespace("com.cloudera.edh")
.fields()
.optionalLong("s1")
.optionalString("l1")
.requiredLong("l2")
.endRecord();
AvroRecordConverter converter = new AvroRecordConverter(input, output, EMPTY_MAPPING);
Record inputRecord = new Record(input);
inputRecord.put("s1", "blah");
inputRecord.put("s2", "blah");
inputRecord.put("l1", null);
inputRecord.put("l2", 5L);
converter.convert(inputRecord);
}
@Test
public void testDeepCopyGeneric() {
Record record = new Record(Person.SCHEMA$);
record.put("name", "John Doe");
record.put("age", 42);
record.put("siblingnames", Lists.newArrayList());
Record deepCopyRecord =
new AvroDeepCopier.AvroGenericDeepCopier(Person.SCHEMA$).deepCopy(record);
assertEquals(record, deepCopyRecord);
assertNotSame(record, deepCopyRecord);
}
/** Tests the case where we don't use a mapping file and just map records by name. */
@Test
public void testDefaultConversion() throws Exception {
// We will convert s1 from string to long (or leave it null), ignore s2,
// convert s3 to from string to double, convert l1 from long to string,
// and leave l2 the same.
Schema input =
SchemaBuilder.record("Input")
.namespace("com.cloudera.edh")
.fields()
.nullableString("s1", "")
.requiredString("s2")
.requiredString("s3")
.optionalLong("l1")
.requiredLong("l2")
.endRecord();
Schema output =
SchemaBuilder.record("Output")
.namespace("com.cloudera.edh")
.fields()
.optionalLong("s1")
.optionalString("l1")
.requiredLong("l2")
.requiredDouble("s3")
.endRecord();
AvroRecordConverter converter =
new AvroRecordConverter(input, output, EMPTY_MAPPING, LocaleUtils.toLocale("en_US"));
Record inputRecord = new Record(input);
inputRecord.put("s1", null);
inputRecord.put("s2", "blah");
inputRecord.put("s3", "5.5");
inputRecord.put("l1", null);
inputRecord.put("l2", 5L);
Record outputRecord = converter.convert(inputRecord);
assertNull(outputRecord.get("s1"));
assertNull(outputRecord.get("l1"));
assertEquals(5L, outputRecord.get("l2"));
assertEquals(5.5, outputRecord.get("s3"));
inputRecord.put("s1", "500");
inputRecord.put("s2", "blah");
inputRecord.put("s3", "5.5e-5");
inputRecord.put("l1", 100L);
inputRecord.put("l2", 2L);
outputRecord = converter.convert(inputRecord);
assertEquals(500L, outputRecord.get("s1"));
assertEquals("100", outputRecord.get("l1"));
assertEquals(2L, outputRecord.get("l2"));
assertEquals(5.5e-5, outputRecord.get("s3"));
}
@Test
public void testUseReaderSchema() throws IOException {
// Create a schema with only a username, so we can test reading it
// with an enhanced record structure.
Schema oldRecordSchema =
SchemaBuilder.record("org.kitesdk.data.user.OldUserRecord")
.fields()
.requiredString("username")
.endRecord();
// create the dataset
Dataset<Record> in =
repo.create("ns", "in", new DatasetDescriptor.Builder().schema(oldRecordSchema).build());
Dataset<Record> out =
repo.create("ns", "out", new DatasetDescriptor.Builder().schema(oldRecordSchema).build());
Record oldUser = new Record(oldRecordSchema);
oldUser.put("username", "user");
DatasetWriter<Record> writer = in.newWriter();
try {
writer.write(oldUser);
} finally {
writer.close();
}
Pipeline pipeline = new MRPipeline(TestCrunchDatasets.class);
// read data from updated dataset that has the new schema.
// At this point, User class has the old schema
PCollection<NewUserRecord> data =
pipeline.read(CrunchDatasets.asSource(in.getUri(), NewUserRecord.class));
PCollection<NewUserRecord> processed =
data.parallelDo(new UserRecordIdentityFn(), Avros.records(NewUserRecord.class));
pipeline.write(processed, CrunchDatasets.asTarget(out));
DatasetReader reader = out.newReader();
Assert.assertTrue("Pipeline failed.", pipeline.run().succeeded());
try {
// there should be one record that is equal to our old user generic record.
Assert.assertEquals(oldUser, reader.next());
Assert.assertFalse(reader.hasNext());
} finally {
reader.close();
}
}
/** Tests the case where we want to default map one field and explicitly map another. */
@Test
public void testExplicitMapping() throws Exception {
// We will convert s1 from string to long (or leave it null), ignore s2,
// convert l1 from long to string, and leave l2 the same.
Schema input = NESTED_RECORD_SCHEMA;
Schema parent = NESTED_PARENT_SCHEMA;
Schema output = UNNESTED_OUTPUT_SCHEMA;
Map<String, String> mapping = ImmutableMap.of("parent.id", "parentId");
AvroRecordConverter converter = new AvroRecordConverter(input, output, mapping);
Record inputRecord = new Record(input);
inputRecord.put("l1", 5L);
inputRecord.put("s1", "1000");
Record parentRecord = new Record(parent);
parentRecord.put("id", 200L);
parentRecord.put("name", "parent");
inputRecord.put("parent", parentRecord);
Record outputRecord = converter.convert(inputRecord);
assertEquals(5L, outputRecord.get("l1"));
assertEquals(1000L, outputRecord.get("s1"));
assertEquals(200L, outputRecord.get("parentId"));
}