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SNOW-1649161 Fix NaN value handling in schematization #920
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243 changes: 243 additions & 0 deletions
243
...wflake/kafka/connector/internal/streaming/SnowflakeSinkServiceV2AvroSchematizationIT.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,243 @@ | ||
| package com.snowflake.kafka.connector.internal.streaming; | ||
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|
||
| import static com.snowflake.kafka.connector.internal.TestUtils.getTableContentOneRow; | ||
| import static com.snowflake.kafka.connector.internal.streaming.channel.TopicPartitionChannel.NO_OFFSET_TOKEN_REGISTERED_IN_SNOWFLAKE; | ||
| import static org.awaitility.Awaitility.await; | ||
|
|
||
| import com.snowflake.kafka.connector.SnowflakeSinkConnectorConfig; | ||
| import com.snowflake.kafka.connector.dlq.InMemoryKafkaRecordErrorReporter; | ||
| import com.snowflake.kafka.connector.internal.SnowflakeConnectionService; | ||
| import com.snowflake.kafka.connector.internal.SnowflakeSinkService; | ||
| import com.snowflake.kafka.connector.internal.SnowflakeSinkServiceFactory; | ||
| import com.snowflake.kafka.connector.internal.TestUtils; | ||
| import io.confluent.connect.avro.AvroConverter; | ||
| import io.confluent.kafka.schemaregistry.client.MockSchemaRegistryClient; | ||
| import io.confluent.kafka.schemaregistry.client.SchemaRegistryClient; | ||
| import java.time.Duration; | ||
| import java.util.Arrays; | ||
| import java.util.Collections; | ||
| import java.util.HashMap; | ||
| import java.util.Map; | ||
| import java.util.stream.Stream; | ||
| import org.apache.commons.lang3.StringUtils; | ||
| import org.apache.kafka.common.TopicPartition; | ||
| import org.apache.kafka.connect.data.Schema; | ||
| import org.apache.kafka.connect.data.SchemaAndValue; | ||
| import org.apache.kafka.connect.data.SchemaBuilder; | ||
| import org.apache.kafka.connect.data.Struct; | ||
| import org.apache.kafka.connect.sink.SinkRecord; | ||
| import org.junit.jupiter.api.AfterEach; | ||
| import org.junit.jupiter.api.Assertions; | ||
| import org.junit.jupiter.api.BeforeEach; | ||
| import org.junit.jupiter.params.ParameterizedTest; | ||
| import org.junit.jupiter.params.provider.Arguments; | ||
| import org.junit.jupiter.params.provider.MethodSource; | ||
|
|
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| public class SnowflakeSinkServiceV2AvroSchematizationIT { | ||
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|
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| private static final int PARTITION = 0; | ||
| private static final int START_OFFSET = 0; | ||
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| private static final String ID_INT8 = "ID_INT8"; | ||
| private static final String ID_INT8_OPTIONAL = "ID_INT8_OPTIONAL"; | ||
| private static final String ID_INT16 = "ID_INT16"; | ||
| private static final String ID_INT32 = "ID_INT32"; | ||
| private static final String ID_INT64 = "ID_INT64"; | ||
| private static final String FIRST_NAME = "FIRST_NAME"; | ||
| private static final String RATING_FLOAT32 = "RATING_FLOAT32"; | ||
| private static final String FLOAT_NAN = "FLOAT_NAN"; | ||
| private static final String RATING_FLOAT64 = "RATING_FLOAT64"; | ||
| private static final String APPROVAL = "APPROVAL"; | ||
| private static final String INFO_ARRAY_STRING = "INFO_ARRAY_STRING"; | ||
| private static final String INFO_ARRAY_INT = "INFO_ARRAY_INT"; | ||
| private static final String INFO_ARRAY_JSON = "INFO_ARRAY_JSON"; | ||
| private static final String INFO_MAP = "INFO_MAP"; | ||
| private static final String RECORD_METADATA = "RECORD_METADATA"; | ||
|
|
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| private static final Map<String, String> EXPECTED_AVRO_SCHEMA = | ||
| new HashMap<String, String>() { | ||
| { | ||
| put(ID_INT8, "NUMBER"); | ||
| put(ID_INT8_OPTIONAL, "NUMBER"); | ||
| put(ID_INT16, "NUMBER"); | ||
| put(ID_INT32, "NUMBER"); | ||
| put(ID_INT64, "NUMBER"); | ||
| put(FIRST_NAME, "VARCHAR"); | ||
| put(RATING_FLOAT32, "FLOAT"); | ||
| put(FLOAT_NAN, "FLOAT"); | ||
| put(RATING_FLOAT64, "FLOAT"); | ||
| put(APPROVAL, "BOOLEAN"); | ||
| put(INFO_ARRAY_STRING, "ARRAY"); | ||
| put(INFO_ARRAY_INT, "ARRAY"); | ||
| put(INFO_ARRAY_JSON, "ARRAY"); | ||
| put(INFO_MAP, "VARIANT"); | ||
| put(RECORD_METADATA, "VARIANT"); | ||
| } | ||
| }; | ||
|
|
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| private String table; | ||
| private SnowflakeConnectionService conn; | ||
| private String topic; | ||
| private TopicPartition topicPartition; | ||
|
|
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| private SnowflakeSinkService service; | ||
|
|
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| @BeforeEach | ||
| void before() { | ||
| table = TestUtils.randomTableName(); | ||
| topic = table; | ||
| conn = TestUtils.getConnectionServiceForStreaming(); | ||
| topicPartition = new TopicPartition(topic, PARTITION); | ||
| } | ||
|
|
||
| @AfterEach | ||
| void after() { | ||
| service.closeAll(); | ||
| } | ||
|
|
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| @ParameterizedTest(name = "useSingleBuffer: {0}") | ||
| @MethodSource("singleBufferParameters") | ||
| public void testSchematizationWithTableCreationAndAvroInput(boolean useSingleBuffer) | ||
| throws Exception { | ||
| // given | ||
| conn.createTableWithOnlyMetadataColumn(table); | ||
| SinkRecord avroRecordValue = createSinkRecord(); | ||
| service = createService(useSingleBuffer); | ||
|
|
||
| // when | ||
| // The first insert should fail and schema evolution will kick in to update the schema | ||
| service.insert(Collections.singletonList(avroRecordValue)); | ||
|
|
||
| // then | ||
| waitUntilOffsetEquals(NO_OFFSET_TOKEN_REGISTERED_IN_SNOWFLAKE); | ||
| TestUtils.checkTableSchema(table, EXPECTED_AVRO_SCHEMA); | ||
|
|
||
| // when | ||
| // Retry the insert should succeed now with the updated schema | ||
| service.insert(Collections.singletonList(avroRecordValue)); | ||
|
|
||
| // then | ||
| waitUntilOffsetEquals(START_OFFSET + 1); | ||
|
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| Map<String, Object> actual = getTableContentOneRow(topic); | ||
| Assertions.assertEquals(actual.get(ID_INT8), 0L); | ||
| Assertions.assertNull(actual.get(ID_INT8_OPTIONAL)); | ||
| Assertions.assertEquals(actual.get(ID_INT16), 42L); | ||
| Assertions.assertEquals(actual.get(ID_INT32), 42L); | ||
| Assertions.assertEquals(actual.get(ID_INT64), 42L); | ||
| Assertions.assertEquals(actual.get(FIRST_NAME), "zekai"); | ||
| Assertions.assertEquals(actual.get(RATING_FLOAT32), 0.99); | ||
| Assertions.assertEquals( | ||
| actual.get(FLOAT_NAN), Double.NaN); // float is extended to double on SF side | ||
| Assertions.assertEquals(actual.get(RATING_FLOAT64), 0.99); | ||
| Assertions.assertEquals(actual.get(APPROVAL), true); | ||
| Assertions.assertEquals( | ||
| StringUtils.deleteWhitespace(actual.get(INFO_ARRAY_STRING).toString()), "[\"a\",\"b\"]"); | ||
| Assertions.assertEquals( | ||
| StringUtils.deleteWhitespace(actual.get(INFO_ARRAY_INT).toString()), "[1,2]"); | ||
| Assertions.assertEquals( | ||
| StringUtils.deleteWhitespace(actual.get(INFO_ARRAY_JSON).toString()), | ||
| "[null,\"{\\\"a\\\":1,\\\"b\\\":null,\\\"c\\\":null,\\\"d\\\":\\\"89asda9s0a\\\"}\"]"); | ||
| Assertions.assertEquals( | ||
| StringUtils.deleteWhitespace(actual.get(INFO_MAP).toString()), "{\"field\":3}"); | ||
| } | ||
|
|
||
| private SnowflakeSinkService createService(boolean useSingleBuffer) { | ||
| Map<String, String> config = prepareConfig(useSingleBuffer); | ||
| return SnowflakeSinkServiceFactory.builder( | ||
| conn, IngestionMethodConfig.SNOWPIPE_STREAMING, config) | ||
| .setRecordNumber(1) | ||
| .setErrorReporter(new InMemoryKafkaRecordErrorReporter()) | ||
| .setSinkTaskContext(new InMemorySinkTaskContext(Collections.singleton(topicPartition))) | ||
| .addTask(table, new TopicPartition(topic, PARTITION)) | ||
| .build(); | ||
| } | ||
|
|
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| private SinkRecord createSinkRecord() { | ||
| Schema schema = prepareSchema(); | ||
| Struct data = prepareData(schema); | ||
| AvroConverter avroConverter = prepareAvroConverter(); | ||
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| byte[] converted = avroConverter.fromConnectData(topic, data.schema(), data); | ||
| conn.createTableWithOnlyMetadataColumn(table); | ||
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| SchemaAndValue avroInputValue = avroConverter.toConnectData(topic, converted); | ||
|
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| return new SinkRecord( | ||
| topic, | ||
| PARTITION, | ||
| Schema.STRING_SCHEMA, | ||
| "test", | ||
| avroInputValue.schema(), | ||
| avroInputValue.value(), | ||
| START_OFFSET); | ||
| } | ||
|
|
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| private AvroConverter prepareAvroConverter() { | ||
| SchemaRegistryClient schemaRegistry = new MockSchemaRegistryClient(); | ||
| AvroConverter avroConverter = new AvroConverter(schemaRegistry); | ||
| avroConverter.configure( | ||
| Collections.singletonMap("schema.registry.url", "http://fake-url"), false); | ||
| return avroConverter; | ||
| } | ||
|
|
||
| private Map<String, String> prepareConfig(boolean useSingleBuffer) { | ||
| Map<String, String> config = TestUtils.getConfForStreaming(useSingleBuffer); | ||
| config.put(SnowflakeSinkConnectorConfig.ENABLE_SCHEMATIZATION_CONFIG, "true"); | ||
| config.put( | ||
| SnowflakeSinkConnectorConfig.VALUE_CONVERTER_CONFIG_FIELD, | ||
| "io.confluent.connect.avro.AvroConverter"); | ||
| config.put(SnowflakeSinkConnectorConfig.VALUE_SCHEMA_REGISTRY_CONFIG_FIELD, "http://fake-url"); | ||
| SnowflakeSinkConnectorConfig.setDefaultValues(config); | ||
| return config; | ||
| } | ||
|
|
||
| private Schema prepareSchema() { | ||
| SchemaBuilder schemaBuilder = | ||
| SchemaBuilder.struct() | ||
| .field(ID_INT8, Schema.INT8_SCHEMA) | ||
| .field(ID_INT8_OPTIONAL, Schema.OPTIONAL_INT8_SCHEMA) | ||
| .field(ID_INT16, Schema.INT16_SCHEMA) | ||
| .field(ID_INT32, Schema.INT32_SCHEMA) | ||
| .field(ID_INT64, Schema.INT64_SCHEMA) | ||
| .field(FIRST_NAME, Schema.STRING_SCHEMA) | ||
| .field(RATING_FLOAT32, Schema.FLOAT32_SCHEMA) | ||
| .field(FLOAT_NAN, Schema.FLOAT32_SCHEMA) | ||
| .field(RATING_FLOAT64, Schema.FLOAT64_SCHEMA) | ||
| .field(APPROVAL, Schema.BOOLEAN_SCHEMA) | ||
| .field(INFO_ARRAY_STRING, SchemaBuilder.array(Schema.STRING_SCHEMA).build()) | ||
| .field(INFO_ARRAY_INT, SchemaBuilder.array(Schema.INT32_SCHEMA).build()) | ||
| .field(INFO_ARRAY_JSON, SchemaBuilder.array(Schema.OPTIONAL_STRING_SCHEMA).build()) | ||
| .field(INFO_MAP, SchemaBuilder.map(Schema.STRING_SCHEMA, Schema.INT32_SCHEMA).build()); | ||
| return schemaBuilder.build(); | ||
| } | ||
|
|
||
| private Struct prepareData(Schema schema) { | ||
| return new Struct(schema) | ||
| .put(ID_INT8, (byte) 0) | ||
| .put(ID_INT16, (short) 42) | ||
| .put(ID_INT32, 42) | ||
| .put(ID_INT64, 42L) | ||
| .put(FIRST_NAME, "zekai") | ||
| .put(RATING_FLOAT32, 0.99f) | ||
| .put(FLOAT_NAN, Float.NaN) | ||
| .put(RATING_FLOAT64, 0.99d) | ||
| .put(APPROVAL, true) | ||
| .put(INFO_ARRAY_STRING, Arrays.asList("a", "b")) | ||
| .put(INFO_ARRAY_INT, Arrays.asList(1, 2)) | ||
| .put( | ||
| INFO_ARRAY_JSON, | ||
| Arrays.asList(null, "{\"a\": 1, \"b\": null, \"c\": null, \"d\": \"89asda9s0a\"}")) | ||
| .put(INFO_MAP, Collections.singletonMap("field", 3)); | ||
| } | ||
|
|
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| private static Stream<Arguments> singleBufferParameters() { | ||
| return Stream.of(Arguments.of(false), Arguments.of(true)); | ||
| } | ||
|
|
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| private void waitUntilOffsetEquals(long expectedOffset) { | ||
| await() | ||
| .timeout(Duration.ofSeconds(60)) | ||
| .until(() -> service.getOffset(new TopicPartition(topic, PARTITION)) == expectedOffset); | ||
| } | ||
| } | ||
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The logic of this test is the same as before with added
NaNfield. A couple of things I fixed here:StringUtils.deleteWhitespaceinstead of custom code@BeforeEach/@AfterEachcheckTableContentOneRow())So while it still can be better please keep your review bar at reasonable level here :)