yunfengzhou-hub commented on code in PR #6532: URL: https://github.com/apache/paimon/pull/6532#discussion_r2497745736
########## paimon-flink/paimon-flink-cdc/src/main/java/org/apache/paimon/flink/pipeline/cdc/schema/SchemaChangeProvider.java: ########## @@ -0,0 +1,141 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.paimon.flink.pipeline.cdc.schema; + +import org.apache.paimon.flink.pipeline.cdc.util.FlinkCDCToPaimonTypeConverter; +import org.apache.paimon.schema.SchemaChange; + +import org.apache.flink.cdc.common.event.AddColumnEvent; +import org.apache.flink.cdc.common.schema.Column; +import org.apache.flink.cdc.common.types.DataType; + +import java.util.ArrayList; +import java.util.List; +import java.util.Map; +import java.util.Optional; + +/** + * The SchemaChangeProvider class provides static methods to create SchemaChange objects that + * represent different types of schema modifications. + */ +public class SchemaChangeProvider { + + /** + * Creates a SchemaChange object for adding a column without specifying its position. + * + * @param columnWithPosition The ColumnWithPosition object containing the column details and its + * intended position within the schema. + * @return A SchemaChange object representing the addition of a column. + */ + public static List<SchemaChange> add(AddColumnEvent.ColumnWithPosition columnWithPosition) { + List<SchemaChange> result = new ArrayList<>(); + result.add( + SchemaChange.addColumn( + columnWithPosition.getAddColumn().getName(), + FlinkCDCToPaimonTypeConverter.convertFlinkCDCDataTypeToPaimonDataType( + columnWithPosition.getAddColumn().getType()), + columnWithPosition.getAddColumn().getComment())); + // if default value express exists, we need to set the default value to the table + // option + Column column = columnWithPosition.getAddColumn(); + Optional.ofNullable( + FlinkCDCToPaimonTypeConverter.convertFlinkCDCDefaultValueToValidValue( + column.getDefaultValueExpression(), column.getType())) + .ifPresent( + value -> { + result.add( + SchemaChange.updateColumnDefaultValue( + new String[] {column.getName()}, value)); + }); + return result; + } + + /** + * Creates a SchemaChange object for adding a column with a specified position. + * + * @param columnWithPosition The ColumnWithPosition object containing the column details and its + * intended position within the schema. + * @param move The move operation to indicate the column's new position. + * @return A SchemaChange object representing the addition of a column with position + * information. + */ + public static List<SchemaChange> add( + AddColumnEvent.ColumnWithPosition columnWithPosition, SchemaChange.Move move) { + List<SchemaChange> result = new ArrayList<>(); + result.add( + SchemaChange.addColumn( + columnWithPosition.getAddColumn().getName(), + FlinkCDCToPaimonTypeConverter.convertFlinkCDCDataTypeToPaimonDataType( + columnWithPosition.getAddColumn().getType()), + columnWithPosition.getAddColumn().getComment(), + move)); + // if default value express exists, we need to set the default value to the table + // option + Column column = columnWithPosition.getAddColumn(); + Optional.ofNullable( + FlinkCDCToPaimonTypeConverter.convertFlinkCDCDefaultValueToValidValue( + column.getDefaultValueExpression(), column.getType())) + .ifPresent( + value -> { + result.add( + SchemaChange.updateColumnDefaultValue( + new String[] {column.getName()}, value)); + }); + return result; + } + + /** + * Creates a SchemaChange object to update the data type of a column. + * + * @param oldColumnName The name of the column whose data type is to be updated. + * @param newType The new DataType for the column. + * @return A SchemaChange object representing the update of the column's data type. + */ + public static SchemaChange updateColumnType(String oldColumnName, DataType newType) { + return SchemaChange.updateColumnType( + oldColumnName, + FlinkCDCToPaimonTypeConverter.convertFlinkCDCDataTypeToPaimonDataType(newType)); + } + + /** + * Creates a SchemaChange object for renaming a column. + * + * @param oldColumnName The current name of the column to be renamed. + * @param newColumnName The new name for the column. + * @return A SchemaChange object representing the renaming of a column. + */ + public static List<SchemaChange> rename( + String oldColumnName, String newColumnName, Map<String, String> options) { Review Comment: the `options` parameter could be removed ########## paimon-flink/paimon-flink-cdc/src/main/java/org/apache/paimon/flink/pipeline/cdc/util/PaimonToFlinkCDCDataConverter.java: ########## @@ -0,0 +1,160 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.paimon.flink.pipeline.cdc.util; + +import org.apache.paimon.data.InternalRow; + +import org.apache.flink.cdc.common.data.DateData; +import org.apache.flink.cdc.common.data.DecimalData; +import org.apache.flink.cdc.common.data.LocalZonedTimestampData; +import org.apache.flink.cdc.common.data.TimeData; +import org.apache.flink.cdc.common.data.TimestampData; +import org.apache.flink.cdc.common.data.binary.BinaryRecordData; +import org.apache.flink.cdc.common.data.binary.BinaryStringData; +import org.apache.flink.cdc.common.event.DataChangeEvent; +import org.apache.flink.cdc.common.event.TableId; +import org.apache.flink.cdc.common.types.DataType; +import org.apache.flink.cdc.common.types.DataTypeChecks; +import org.apache.flink.cdc.runtime.typeutils.BinaryRecordDataGenerator; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; + +/** Converter from Paimon to Flink CDC data. */ +public class PaimonToFlinkCDCDataConverter { + + /** Convert Paimon row to Flink CDC data. */ + public static DataChangeEvent convertRowToDataChangeEvent( + TableId tableId, + InternalRow row, + List<InternalRow.FieldGetter> fieldGetters, + BinaryRecordDataGenerator recordDataGenerator) { + Object[] objects = new Object[row.getFieldCount()]; + for (int i = 0; i < row.getFieldCount(); i++) { + objects[i] = fieldGetters.get(i).getFieldOrNull(row); + } + BinaryRecordData binaryRecordData = recordDataGenerator.generate(objects); + switch (row.getRowKind()) { + case INSERT: + case UPDATE_AFTER: + { + return DataChangeEvent.insertEvent(tableId, binaryRecordData, new HashMap<>()); + } + case DELETE: + case UPDATE_BEFORE: + { + return DataChangeEvent.deleteEvent(tableId, binaryRecordData, new HashMap<>()); + } + default: + throw new IllegalArgumentException("Unsupported RowKind type: " + row.getRowKind()); + } + } + + public static List<InternalRow.FieldGetter> createFieldGetters(List<DataType> fieldTypes) { + List<InternalRow.FieldGetter> fieldGetters = new ArrayList<>(); + for (int i = 0; i < fieldTypes.size(); i++) { + fieldGetters.add(createFieldGetter(fieldTypes.get(i), i)); + } + return fieldGetters; + } + + public static InternalRow.FieldGetter createFieldGetter(DataType fieldType, int fieldPos) { + final InternalRow.FieldGetter fieldGetter; + // ordered by type root definition + switch (fieldType.getTypeRoot()) { + case CHAR: + case VARCHAR: + fieldGetter = + row -> BinaryStringData.fromString(row.getString(fieldPos).toString()); + break; + case BOOLEAN: + fieldGetter = row -> row.getBoolean(fieldPos); + break; + case BINARY: + case VARBINARY: + fieldGetter = row -> row.getBinary(fieldPos); + break; + case DECIMAL: + final int decimalPrecision = DataTypeChecks.getPrecision(fieldType); + final int decimalScale = DataTypeChecks.getScale(fieldType); + fieldGetter = + row -> + DecimalData.fromBigDecimal( + row.getDecimal(fieldPos, decimalPrecision, decimalScale) + .toBigDecimal(), + decimalPrecision, + decimalScale); + break; + case TINYINT: + fieldGetter = row -> row.getByte(fieldPos); + break; + case SMALLINT: + fieldGetter = row -> row.getShort(fieldPos); + break; + case BIGINT: + fieldGetter = row -> row.getLong(fieldPos); + break; + case FLOAT: + fieldGetter = row -> row.getFloat(fieldPos); + break; + case DOUBLE: + fieldGetter = row -> row.getDouble(fieldPos); + break; + case INTEGER: + fieldGetter = row -> row.getInt(fieldPos); + break; + case DATE: + fieldGetter = row -> DateData.fromEpochDay(row.getInt(fieldPos)); + break; + case TIME_WITHOUT_TIME_ZONE: + fieldGetter = row -> TimeData.fromMillisOfDay(row.getInt(fieldPos)); + break; + case TIMESTAMP_WITHOUT_TIME_ZONE: + fieldGetter = + row -> + TimestampData.fromTimestamp( + row.getTimestamp( + fieldPos, + DataTypeChecks.getPrecision(fieldType)) + .toSQLTimestamp()); + break; + case TIMESTAMP_WITH_LOCAL_TIME_ZONE: + fieldGetter = + row -> + LocalZonedTimestampData.fromInstant( + row.getTimestamp( + fieldPos, + DataTypeChecks.getPrecision(fieldType)) + .toInstant()); + break; + default: Review Comment: Shall we support nested types like ROW, ARRAY and MAP? ########## paimon-flink/paimon-flink-cdc/src/main/java/org/apache/flink/cdc/connectors/base/relational/connection/JdbcConnectionPools.java: ########## @@ -0,0 +1,95 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.flink.cdc.connectors.base.relational.connection; + +import com.zaxxer.hikari.HikariDataSource; +import org.apache.flink.cdc.common.annotation.VisibleForTesting; +import org.apache.flink.cdc.connectors.base.config.JdbcSourceConfig; +import org.apache.flink.util.FlinkRuntimeException; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.IOException; +import java.util.HashMap; +import java.util.Map; + +/** + * Copied from Flink CDC 3.5.0: {@code + * org/apache/flink/cdc/connectors/base/relational/connection/JdbcConnectionPools.java}. Modified + * method {@link JdbcConnectionPools#clear()} at line 92 ~ 94. Review Comment: Maybe better to add a stable link that points to the 3.5.0 branch/tag, instead of pointing to the master branch. ########## paimon-flink/paimon-flink-cdc/src/main/java/org/apache/paimon/flink/pipeline/cdc/util/PaimonToFlinkCDCDataConverter.java: ########## @@ -0,0 +1,160 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.paimon.flink.pipeline.cdc.util; + +import org.apache.paimon.data.InternalRow; + +import org.apache.flink.cdc.common.data.DateData; +import org.apache.flink.cdc.common.data.DecimalData; +import org.apache.flink.cdc.common.data.LocalZonedTimestampData; +import org.apache.flink.cdc.common.data.TimeData; +import org.apache.flink.cdc.common.data.TimestampData; +import org.apache.flink.cdc.common.data.binary.BinaryRecordData; +import org.apache.flink.cdc.common.data.binary.BinaryStringData; +import org.apache.flink.cdc.common.event.DataChangeEvent; +import org.apache.flink.cdc.common.event.TableId; +import org.apache.flink.cdc.common.types.DataType; +import org.apache.flink.cdc.common.types.DataTypeChecks; +import org.apache.flink.cdc.runtime.typeutils.BinaryRecordDataGenerator; + +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; + +/** Converter from Paimon to Flink CDC data. */ +public class PaimonToFlinkCDCDataConverter { + + /** Convert Paimon row to Flink CDC data. */ + public static DataChangeEvent convertRowToDataChangeEvent( + TableId tableId, + InternalRow row, + List<InternalRow.FieldGetter> fieldGetters, + BinaryRecordDataGenerator recordDataGenerator) { + Object[] objects = new Object[row.getFieldCount()]; + for (int i = 0; i < row.getFieldCount(); i++) { + objects[i] = fieldGetters.get(i).getFieldOrNull(row); + } + BinaryRecordData binaryRecordData = recordDataGenerator.generate(objects); + switch (row.getRowKind()) { + case INSERT: + case UPDATE_AFTER: + { + return DataChangeEvent.insertEvent(tableId, binaryRecordData, new HashMap<>()); Review Comment: When rowkind == UPDATE_AFTER, I'm not sure whether `insertEvent` should be a better choice than `updateEvent`. ########## paimon-flink/paimon-flink-cdc/src/test/java/org/apache/paimon/flink/pipeline/cdc/util/DataConvertTest.java: ########## @@ -0,0 +1,215 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.paimon.flink.pipeline.cdc.util; + +import org.apache.paimon.data.InternalRow; +import org.apache.paimon.types.RowKind; +import org.apache.paimon.utils.InternalRowUtils; + +import org.apache.flink.cdc.common.data.DateData; +import org.apache.flink.cdc.common.data.DecimalData; +import org.apache.flink.cdc.common.data.LocalZonedTimestampData; +import org.apache.flink.cdc.common.data.RecordData; +import org.apache.flink.cdc.common.data.TimeData; +import org.apache.flink.cdc.common.data.TimestampData; +import org.apache.flink.cdc.common.data.binary.BinaryStringData; +import org.apache.flink.cdc.common.event.DataChangeEvent; +import org.apache.flink.cdc.common.event.TableId; +import org.apache.flink.cdc.common.schema.Schema; +import org.apache.flink.cdc.common.types.DataType; +import org.apache.flink.cdc.common.types.DataTypes; +import org.apache.flink.cdc.common.utils.SchemaUtils; +import org.apache.flink.cdc.runtime.typeutils.BinaryRecordDataGenerator; +import org.assertj.core.api.Assertions; +import org.junit.jupiter.api.Test; + +import java.math.BigDecimal; +import java.util.ArrayList; +import java.util.Arrays; +import java.util.List; +import java.util.Objects; + +/** + * Data convert test for {@link PaimonToFlinkCDCDataConverter} and {@link + * FlinkCDCToPaimonDataConverter}. + */ +public class DataConvertTest { + + @Test + void testFullTypesConversion() { + Schema fullTypesSchema = + Schema.newBuilder() + .physicalColumn("pk_string", DataTypes.STRING().notNull()) + .physicalColumn("boolean", DataTypes.BOOLEAN()) + .physicalColumn("binary", DataTypes.BINARY(3)) + .physicalColumn("varbinary", DataTypes.VARBINARY(10)) + .physicalColumn("bytes", DataTypes.BYTES()) + .physicalColumn("tinyint", DataTypes.TINYINT()) + .physicalColumn("smallint", DataTypes.SMALLINT()) + .physicalColumn("int", DataTypes.INT()) + .physicalColumn("bigint", DataTypes.BIGINT()) + .physicalColumn("float", DataTypes.FLOAT()) + .physicalColumn("double", DataTypes.DOUBLE()) + .physicalColumn("decimal", DataTypes.DECIMAL(6, 3)) + .physicalColumn("char", DataTypes.CHAR(5)) + .physicalColumn("varchar", DataTypes.VARCHAR(10)) + .physicalColumn("string", DataTypes.STRING()) + .physicalColumn("date", DataTypes.DATE()) + .physicalColumn("time", DataTypes.TIME()) + .physicalColumn("time_with_precision", DataTypes.TIME(6)) + .physicalColumn("timestamp", DataTypes.TIMESTAMP()) + .physicalColumn("timestamp_with_precision_3", DataTypes.TIMESTAMP(3)) + .physicalColumn("timestamp_with_precision_6", DataTypes.TIMESTAMP(6)) + .physicalColumn("timestamp_with_precision_9", DataTypes.TIMESTAMP(9)) + .physicalColumn("timestamp_ltz", DataTypes.TIMESTAMP_LTZ()) + .physicalColumn( + "timestamp_ltz_with_precision_3", DataTypes.TIMESTAMP_LTZ(3)) + .physicalColumn( + "timestamp_ltz_with_precision_6", DataTypes.TIMESTAMP_LTZ(6)) + .physicalColumn( + "timestamp_ltz_with_precision_9", DataTypes.TIMESTAMP_LTZ(9)) + .primaryKey("pk_string") + .partitionKey("boolean") + .build(); + + Object[] testData = + new Object[] { + BinaryStringData.fromString("pk_string"), + true, + new byte[] {1, 2, 3}, + new byte[] {4, 5, 6}, + new byte[] {7, 8, 9}, + (byte) 1, + (short) 2, + 3, + 4L, + 5.1f, + 6.2, + DecimalData.fromBigDecimal(new BigDecimal("7.123"), 6, 3), + BinaryStringData.fromString("test1"), + BinaryStringData.fromString("test2"), + BinaryStringData.fromString("test3"), + DateData.fromEpochDay(1000), + TimeData.fromMillisOfDay(200), + TimeData.fromMillisOfDay(300), + TimestampData.fromMillis(100, 1), + TimestampData.fromMillis(200, 2), + TimestampData.fromMillis(300, 3), + TimestampData.fromMillis(400, 4), + LocalZonedTimestampData.fromEpochMillis(300, 3), + LocalZonedTimestampData.fromEpochMillis(400, 4), + LocalZonedTimestampData.fromEpochMillis(500, 5), + LocalZonedTimestampData.fromEpochMillis(600, 6), + }; + testConvertBackAndForth( + fullTypesSchema, + testData, + "[pk_string, true, [1, 2, 3], [4, 5, 6], [7, 8, 9], 1, 2, 3, 4, 5.1, 6.2, 7.123, test1, test2, test3, 1000, 200, 300, 1970-01-01T00:00:00.100000001, 1970-01-01T00:00:00.200000002, 1970-01-01T00:00:00.300000003, 1970-01-01T00:00:00.400000004, 1970-01-01T00:00:00.300000003, 1970-01-01T00:00:00.400000004, 1970-01-01T00:00:00.500000005, 1970-01-01T00:00:00.600000006]"); Review Comment: Would it be better to directly validate against the original objects or a Paimon InternalRow, instead of the string representation of them? ########## paimon-flink/paimon-flink-cdc/src/main/java/org/apache/paimon/flink/action/cdc/postgres/PostgresActionUtils.java: ########## @@ -186,7 +186,7 @@ public static JdbcIncrementalSource<CdcSourceRecord> buildPostgresSource( customConverterConfigs.put(JsonConverterConfig.DECIMAL_FORMAT_CONFIG, "numeric"); CdcDebeziumDeserializationSchema schema = new CdcDebeziumDeserializationSchema(true, customConverterConfigs); - return sourceBuilder.deserializer(schema).includeSchemaChanges(true).build(); + return sourceBuilder.deserializer(schema).build(); Review Comment: Is this change the result of some Flink CDC version update? ########## paimon-flink/paimon-flink-cdc/src/test/java/org/apache/paimon/flink/pipeline/cdc/schema/PaimonMetadataApplierTest.java: ########## @@ -0,0 +1,609 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.paimon.flink.pipeline.cdc.schema; + +import org.apache.paimon.CoreOptions; +import org.apache.paimon.catalog.Catalog; +import org.apache.paimon.catalog.FileSystemCatalogFactory; +import org.apache.paimon.catalog.Identifier; +import org.apache.paimon.flink.FlinkCatalogFactory; +import org.apache.paimon.flink.pipeline.cdc.util.FlinkCDCToPaimonTypeConverter; +import org.apache.paimon.options.CatalogOptions; +import org.apache.paimon.options.Options; +import org.apache.paimon.table.Table; +import org.apache.paimon.types.DataField; +import org.apache.paimon.types.DataTypes; +import org.apache.paimon.types.RowType; + +import org.apache.flink.cdc.common.event.AddColumnEvent; +import org.apache.flink.cdc.common.event.AlterColumnTypeEvent; +import org.apache.flink.cdc.common.event.CreateTableEvent; +import org.apache.flink.cdc.common.event.DropColumnEvent; +import org.apache.flink.cdc.common.event.RenameColumnEvent; +import org.apache.flink.cdc.common.event.TableId; +import org.apache.flink.cdc.common.exceptions.SchemaEvolveException; +import org.apache.flink.cdc.common.schema.Column; +import org.apache.flink.cdc.common.sink.MetadataApplier; +import org.apache.flink.cdc.common.types.DataType; +import org.assertj.core.api.Assertions; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import org.junit.jupiter.api.io.TempDir; + +import java.io.File; +import java.util.ArrayList; +import java.util.Arrays; +import java.util.Collections; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.UUID; + +/** Tests for {@link PaimonMetadataApplier}. */ +class PaimonMetadataApplierTest { + + @TempDir public static java.nio.file.Path temporaryFolder; + + private static Catalog catalog; + + private static Options catalogOptions; + + private static MetadataApplier metadataApplier; + + @BeforeAll + public static void initialize() { + catalogOptions = new Options(); + catalogOptions.setString( + CatalogOptions.METASTORE.key(), FileSystemCatalogFactory.IDENTIFIER); + catalogOptions.setString( + CatalogOptions.WAREHOUSE.key(), + new File(temporaryFolder.toFile(), UUID.randomUUID().toString()).toString()); + catalogOptions.set(CatalogOptions.CACHE_ENABLED.key(), "false"); + catalog = FlinkCatalogFactory.createPaimonCatalog(catalogOptions); + + Map<String, String> tableOptions = new HashMap<>(); + tableOptions.put(CoreOptions.BUCKET.key(), "-1"); + metadataApplier = new PaimonMetadataApplier(catalogOptions, tableOptions, new HashMap<>()); + } + + @AfterAll + public static void close() throws Exception { + if (catalog != null) { + catalog.close(); + } + metadataApplier.close(); + } + + @Test + void testApplySchemaChange() throws Catalog.TableNotExistException, SchemaEvolveException { + String databaseName = "test_" + UUID.randomUUID(); + TableId tableId = TableId.tableId(databaseName, "table1"); + CreateTableEvent createTableEvent = + new CreateTableEvent( + tableId, + org.apache.flink.cdc.common.schema.Schema.newBuilder() + .physicalColumn( + "col1", + org.apache.flink.cdc.common.types.DataTypes.STRING() + .notNull()) + .physicalColumn( + "col2", org.apache.flink.cdc.common.types.DataTypes.INT()) + .primaryKey("col1") + .build()); + metadataApplier.applySchemaChange(createTableEvent); + RowType tableSchema = Review Comment: Better to change `tableSchema` into `rowType` to avoid confusion. ########## paimon-flink/paimon-flink-cdc/src/test/java/org/apache/paimon/flink/pipeline/cdc/util/DataConvertTest.java: ########## @@ -0,0 +1,215 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.paimon.flink.pipeline.cdc.util; + +import org.apache.paimon.data.InternalRow; +import org.apache.paimon.types.RowKind; +import org.apache.paimon.utils.InternalRowUtils; + +import org.apache.flink.cdc.common.data.DateData; +import org.apache.flink.cdc.common.data.DecimalData; +import org.apache.flink.cdc.common.data.LocalZonedTimestampData; +import org.apache.flink.cdc.common.data.RecordData; +import org.apache.flink.cdc.common.data.TimeData; +import org.apache.flink.cdc.common.data.TimestampData; +import org.apache.flink.cdc.common.data.binary.BinaryStringData; +import org.apache.flink.cdc.common.event.DataChangeEvent; +import org.apache.flink.cdc.common.event.TableId; +import org.apache.flink.cdc.common.schema.Schema; +import org.apache.flink.cdc.common.types.DataType; +import org.apache.flink.cdc.common.types.DataTypes; +import org.apache.flink.cdc.common.utils.SchemaUtils; +import org.apache.flink.cdc.runtime.typeutils.BinaryRecordDataGenerator; +import org.assertj.core.api.Assertions; +import org.junit.jupiter.api.Test; + +import java.math.BigDecimal; +import java.util.ArrayList; +import java.util.Arrays; +import java.util.List; +import java.util.Objects; + +/** + * Data convert test for {@link PaimonToFlinkCDCDataConverter} and {@link + * FlinkCDCToPaimonDataConverter}. + */ +public class DataConvertTest { + + @Test + void testFullTypesConversion() { + Schema fullTypesSchema = + Schema.newBuilder() + .physicalColumn("pk_string", DataTypes.STRING().notNull()) + .physicalColumn("boolean", DataTypes.BOOLEAN()) + .physicalColumn("binary", DataTypes.BINARY(3)) + .physicalColumn("varbinary", DataTypes.VARBINARY(10)) + .physicalColumn("bytes", DataTypes.BYTES()) + .physicalColumn("tinyint", DataTypes.TINYINT()) + .physicalColumn("smallint", DataTypes.SMALLINT()) + .physicalColumn("int", DataTypes.INT()) + .physicalColumn("bigint", DataTypes.BIGINT()) + .physicalColumn("float", DataTypes.FLOAT()) + .physicalColumn("double", DataTypes.DOUBLE()) + .physicalColumn("decimal", DataTypes.DECIMAL(6, 3)) + .physicalColumn("char", DataTypes.CHAR(5)) + .physicalColumn("varchar", DataTypes.VARCHAR(10)) + .physicalColumn("string", DataTypes.STRING()) + .physicalColumn("date", DataTypes.DATE()) + .physicalColumn("time", DataTypes.TIME()) + .physicalColumn("time_with_precision", DataTypes.TIME(6)) + .physicalColumn("timestamp", DataTypes.TIMESTAMP()) + .physicalColumn("timestamp_with_precision_3", DataTypes.TIMESTAMP(3)) + .physicalColumn("timestamp_with_precision_6", DataTypes.TIMESTAMP(6)) + .physicalColumn("timestamp_with_precision_9", DataTypes.TIMESTAMP(9)) + .physicalColumn("timestamp_ltz", DataTypes.TIMESTAMP_LTZ()) + .physicalColumn( + "timestamp_ltz_with_precision_3", DataTypes.TIMESTAMP_LTZ(3)) + .physicalColumn( + "timestamp_ltz_with_precision_6", DataTypes.TIMESTAMP_LTZ(6)) + .physicalColumn( + "timestamp_ltz_with_precision_9", DataTypes.TIMESTAMP_LTZ(9)) + .primaryKey("pk_string") + .partitionKey("boolean") Review Comment: Let's also add tests for nested types like MAP and ARRAY. -- This is an automated message from the Apache Git Service. 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