danny0405 commented on code in PR #5830:
URL: https://github.com/apache/hudi/pull/5830#discussion_r1033063183
##########
hudi-flink-datasource/hudi-flink/src/main/java/org/apache/hudi/configuration/FlinkOptions.java:
##########
@@ -120,6 +121,12 @@ private FlinkOptions() {
.withDescription("The default partition name in case the dynamic
partition"
+ " column value is null/empty string");
+ public static final ConfigOption<Boolean> SCHEMA_EVOLUTION_ENABLED =
ConfigOptions
+ .key(HoodieCommonConfig.SCHEMA_EVOLUTION_ENABLE.key())
+ .booleanType()
Review Comment:
There is no need to add the option if the key is the same with Hoodie core's.
##########
hudi-flink-datasource/hudi-flink/src/main/java/org/apache/hudi/util/RowDataProjection.java:
##########
@@ -87,4 +88,8 @@ public Object[] projectAsValues(RowData rowData) {
}
return values;
}
+
+ protected @Nullable Object rewriteVal(int pos, @Nullable Object val) {
+ return val;
Review Comment:
`rewriteVal` => `getVal `, usually we do not overwrite impl methods, but
only abstract methods, the override is not very friendly for base class
performance.
##########
hudi-flink-datasource/hudi-flink/src/main/java/org/apache/hudi/table/format/HoodieParquetReader.java:
##########
@@ -0,0 +1,87 @@
+/*
+ * 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.hudi.table.format;
+
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.internal.schema.InternalSchema;
+import org.apache.hudi.table.format.cow.ParquetSplitReaderUtil;
+import org.apache.hudi.util.RowDataProjection;
+
+import org.apache.flink.core.fs.Path;
+import org.apache.flink.table.data.RowData;
+import org.apache.flink.table.types.DataType;
+
+import org.apache.hadoop.conf.Configuration;
+
+import java.io.Closeable;
+import java.io.IOException;
+import java.util.Map;
+
+/**
+ * Base interface for hoodie parquet readers.
+ */
+public interface HoodieParquetReader extends Closeable {
+
+ boolean reachedEnd() throws IOException;
+
+ RowData nextRecord();
+
+ static HoodieParquetReader getReader(
+ InternalSchemaManager internalSchemaManager,
+ boolean utcTimestamp,
+ boolean caseSensitive,
+ Configuration conf,
+ String[] fieldNames,
+ DataType[] fieldTypes,
+ Map<String, Object> partitionSpec,
+ int[] selectedFields,
+ int batchSize,
+ Path path,
+ long splitStart,
+ long splitLength) throws IOException {
+ Option<RowDataProjection> castProjection;
+ InternalSchema fileSchema =
internalSchemaManager.getFileSchema(path.getName());
+ if (fileSchema.isEmptySchema()) {
+ castProjection = Option.empty();
Review Comment:
Can return `HoodieParquetReader` directly here when we know `castProjection`
is empty.
##########
hudi-flink-datasource/hudi-flink/src/test/java/org/apache/hudi/table/format/TestCastMap.java:
##########
@@ -0,0 +1,120 @@
+/*
+ * 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.hudi.table.format;
+
+import org.apache.flink.table.data.DecimalData;
+import org.apache.flink.table.data.binary.BinaryStringData;
+import org.apache.flink.table.types.logical.BigIntType;
+import org.apache.flink.table.types.logical.DateType;
+import org.apache.flink.table.types.logical.DecimalType;
+import org.apache.flink.table.types.logical.DoubleType;
+import org.apache.flink.table.types.logical.FloatType;
+import org.apache.flink.table.types.logical.IntType;
+import org.apache.flink.table.types.logical.VarCharType;
+
+import org.junit.jupiter.api.Test;
+
+import java.math.BigDecimal;
+import java.time.LocalDate;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+/**
+ * Tests for {@link CastMap}.
+ */
+public class TestCastMap {
+
+ @Test
+ public void testCastInt() {
+ CastMap castMap = new CastMap();
+ castMap.add(0, new IntType(), new BigIntType());
+ castMap.add(1, new IntType(), new FloatType());
+ castMap.add(2, new IntType(), new DoubleType());
+ castMap.add(3, new IntType(), new DecimalType());
+ castMap.add(4, new IntType(), new VarCharType());
+ int val = 1;
+ assertEquals(1L, castMap.castIfNeeded(0, val));
+ assertEquals(1.0F, castMap.castIfNeeded(1, val));
+ assertEquals(1.0, castMap.castIfNeeded(2, val));
+ assertEquals(DecimalData.fromBigDecimal(BigDecimal.ONE, 1, 0),
castMap.castIfNeeded(3, val));
+ assertEquals(BinaryStringData.fromString("1"), castMap.castIfNeeded(4,
val));
+ }
+
+ @Test
+ public void testCastLong() {
+ CastMap castMap = new CastMap();
+ castMap.add(0, new BigIntType(), new FloatType());
+ castMap.add(1, new BigIntType(), new DoubleType());
+ castMap.add(2, new BigIntType(), new DecimalType());
+ castMap.add(3, new BigIntType(), new VarCharType());
+ long val = 1L;
+ assertEquals(1.0F, castMap.castIfNeeded(0, val));
+ assertEquals(1.0, castMap.castIfNeeded(1, val));
+ assertEquals(DecimalData.fromBigDecimal(BigDecimal.ONE, 1, 0),
castMap.castIfNeeded(2, val));
+ assertEquals(BinaryStringData.fromString("1"), castMap.castIfNeeded(3,
val));
+ }
+
+ @Test
+ public void testCastFloat() {
+ CastMap castMap = new CastMap();
+ castMap.add(0, new FloatType(), new DoubleType());
+ castMap.add(1, new FloatType(), new DecimalType());
+ castMap.add(2, new FloatType(), new VarCharType());
+ float val = 1F;
+ assertEquals(1.0, castMap.castIfNeeded(0, val));
+ assertEquals(DecimalData.fromBigDecimal(BigDecimal.ONE, 1, 0),
castMap.castIfNeeded(1, val));
+ assertEquals(BinaryStringData.fromString("1.0"), castMap.castIfNeeded(2,
val));
+ }
+
+ @Test
+ public void testCastDouble() {
+ CastMap castMap = new CastMap();
+ castMap.add(0, new DoubleType(), new DecimalType());
+ castMap.add(1, new DoubleType(), new VarCharType());
+ double val = 1;
+ assertEquals(DecimalData.fromBigDecimal(BigDecimal.ONE, 1, 0),
castMap.castIfNeeded(0, val));
+ assertEquals(BinaryStringData.fromString("1.0"), castMap.castIfNeeded(1,
val));
+ }
+
+ @Test
+ public void testCastDecimal() {
+ CastMap castMap = new CastMap();
+ castMap.add(0, new DecimalType(2, 1), new DecimalType(3, 2));
+ castMap.add(1, new DecimalType(), new VarCharType());
+ DecimalData val = DecimalData.fromBigDecimal(BigDecimal.ONE, 2, 1);
+ assertEquals(DecimalData.fromBigDecimal(BigDecimal.ONE, 3, 2),
castMap.castIfNeeded(0, val));
+ assertEquals(BinaryStringData.fromString("1.0"), castMap.castIfNeeded(1,
val));
Review Comment:
For `float`, `double` and `decimal` data types, what is case when the target
data type has precision loss, do we throw exception here ? Exactly what is the
data type precedence(what kind of data type is castable here) for each of the
type ?
##########
hudi-flink-datasource/hudi-flink/src/main/java/org/apache/hudi/table/format/InternalSchemaManager.java:
##########
@@ -0,0 +1,174 @@
+/*
+ * 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.hudi.table.format;
+
+import org.apache.hudi.common.fs.FSUtils;
+import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.table.TableSchemaResolver;
+import org.apache.hudi.common.table.timeline.HoodieInstant;
+import org.apache.hudi.common.util.InternalSchemaCache;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.configuration.FlinkOptions;
+import org.apache.hudi.configuration.HadoopConfigurations;
+import org.apache.hudi.internal.schema.InternalSchema;
+import org.apache.hudi.internal.schema.Type;
+import org.apache.hudi.internal.schema.Types;
+import org.apache.hudi.internal.schema.action.InternalSchemaMerger;
+import org.apache.hudi.internal.schema.convert.AvroInternalSchemaConverter;
+import org.apache.hudi.internal.schema.utils.InternalSchemaUtils;
+import org.apache.hudi.util.AvroSchemaConverter;
+
+import org.apache.flink.configuration.Configuration;
+import org.apache.flink.table.types.DataType;
+import org.apache.flink.util.Preconditions;
+
+import java.io.Serializable;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+import java.util.stream.IntStream;
+
+/**
+ * This class is responsible for calculating names and types of fields that
are actual at a certain point in time.
+ * If field is renamed in queried schema, its old name will be returned, which
is relevant at the provided time.
+ * If type of field is changed, its old type will be returned, and projection
will be created that will convert the old type to the queried one.
+ */
+public class InternalSchemaManager implements Serializable {
+
+ private static final long serialVersionUID = 1L;
+
+ public static final InternalSchemaManager DISABLED = new
InternalSchemaManager(null, null, null, null);
+
+ private final Configuration conf;
+ private final InternalSchema querySchema;
+ private final String validCommits;
+ private final String tablePath;
+ private transient org.apache.hadoop.conf.Configuration hadoopConf;
+
+ public static InternalSchemaManager get(Configuration conf,
HoodieTableMetaClient metaClient) {
+ if (!conf.getBoolean(FlinkOptions.SCHEMA_EVOLUTION_ENABLED)) {
+ return DISABLED;
+ }
+ Option<InternalSchema> internalSchema = new
TableSchemaResolver(metaClient).getTableInternalSchemaFromCommitMetadata();
+ if (!internalSchema.isPresent() || internalSchema.get().isEmptySchema()) {
+ return DISABLED;
+ }
+ String validCommits = metaClient
+ .getCommitsAndCompactionTimeline()
+ .filterCompletedInstants()
+ .getInstants()
+ .map(HoodieInstant::getFileName)
+ .collect(Collectors.joining(","));
+ return new InternalSchemaManager(conf, internalSchema.get(), validCommits,
metaClient.getBasePathV2().toString());
+ }
+
+ public InternalSchemaManager(Configuration conf, InternalSchema querySchema,
String validCommits, String tablePath) {
+ this.conf = conf;
+ this.querySchema = querySchema;
+ this.validCommits = validCommits;
+ this.tablePath = tablePath;
+ }
+
+ public InternalSchema getQuerySchema() {
+ return querySchema != null ? querySchema :
InternalSchema.getEmptyInternalSchema();
+ }
+
+ InternalSchema getFileSchema(String fileName) {
+ InternalSchema querySchema = getQuerySchema();
+ if (querySchema.isEmptySchema()) {
+ return InternalSchema.getEmptyInternalSchema();
+ }
+ long commitInstantTime = Long.parseLong(FSUtils.getCommitTime(fileName));
+ InternalSchema fileSchemaUnmerged =
InternalSchemaCache.getInternalSchemaByVersionId(
+ commitInstantTime, tablePath, getHadoopConf(), validCommits);
+ if (querySchema.equals(fileSchemaUnmerged)) {
+ return InternalSchema.getEmptyInternalSchema();
+ }
+ return new InternalSchemaMerger(fileSchemaUnmerged, querySchema, true,
true).mergeSchema();
+ }
+
+ CastMap getCastMap(InternalSchema fileSchema, String[] queryFieldNames,
DataType[] queryFieldTypes, int[] selectedFields) {
+ assertSchemasAreNotEmpty(getQuerySchema(), fileSchema);
+
+ CastMap castMap = new CastMap();
+ Map<Integer, Integer> posProxy = getPosProxy(fileSchema, queryFieldNames);
+ if (posProxy.isEmpty()) {
+ castMap.setFileFieldTypes(queryFieldTypes);
+ return castMap;
+ }
+ List<Integer> selectedFieldList =
IntStream.of(selectedFields).boxed().collect(Collectors.toList());
+ List<DataType> fileSchemaAsDataTypes =
AvroSchemaConverter.convertToDataType(
+ AvroInternalSchemaConverter.convert(fileSchema,
"tableName")).getChildren();
+ DataType[] fileFieldTypes = new DataType[queryFieldTypes.length];
+ for (int i = 0; i < queryFieldTypes.length; i++) {
+ Integer posOfChangedType = posProxy.get(i);
+ if (posOfChangedType == null) {
+ fileFieldTypes[i] = queryFieldTypes[i];
+ } else {
+ DataType fileType = fileSchemaAsDataTypes.get(posOfChangedType);
+ fileFieldTypes[i] = fileType;
+ int selectedPos = selectedFieldList.indexOf(i);
+ if (selectedPos != -1) {
+ castMap.add(selectedPos, fileType.getLogicalType(),
queryFieldTypes[i].getLogicalType());
+ }
+ }
+ }
+ castMap.setFileFieldTypes(fileFieldTypes);
+ return castMap;
+ }
+
+ String[] getFileFieldNames(InternalSchema fileSchema, String[]
queryFieldNames) {
+ assertSchemasAreNotEmpty(getQuerySchema(), fileSchema);
+
+ Map<String, String> renamedCols =
InternalSchemaUtils.collectRenameCols(fileSchema, getQuerySchema());
+ if (renamedCols.isEmpty()) {
+ return queryFieldNames;
+ }
+ return Arrays.stream(queryFieldNames).map(name ->
renamedCols.getOrDefault(name, name)).toArray(String[]::new);
+ }
+
+ private Map<Integer, Integer> getPosProxy(InternalSchema fileSchema,
String[] queryFieldNames) {
+ Map<Integer, Pair<Type, Type>> changedCols =
InternalSchemaUtils.collectTypeChangedCols(getQuerySchema(), fileSchema);
+ HashMap<Integer, Integer> posProxy = new HashMap<>(changedCols.size());
+ List<String> fieldNameList = Arrays.asList(queryFieldNames);
+ List<Types.Field> columns = getQuerySchema().columns();
+ changedCols.forEach((posInSchema, typePair) -> {
+ String name = columns.get(posInSchema).name();
+ int posInType = fieldNameList.indexOf(name);
+ posProxy.put(posInType, posInSchema);
+ });
+ return Collections.unmodifiableMap(posProxy);
+ }
+
+ private org.apache.hadoop.conf.Configuration getHadoopConf() {
+ if (hadoopConf == null) {
+ hadoopConf = HadoopConfigurations.getHadoopConf(conf);
+ }
+ return hadoopConf;
+ }
+
+ private static void assertSchemasAreNotEmpty(InternalSchema schema1,
InternalSchema schema2) {
+ Preconditions.checkArgument(!schema1.isEmptySchema(), "InternalSchema
cannot be empty here");
Review Comment:
There is no need to bind the schema validation together, and we can give
more details exception msg for different schemas.
##########
hudi-client/hudi-flink-client/src/main/java/org/apache/hudi/table/HoodieFlinkTable.java:
##########
@@ -102,4 +108,9 @@ public <T extends SpecificRecordBase>
Option<HoodieTableMetadataWriter> getMetad
return Option.empty();
}
}
+
+ private static void setLatestInternalSchema(HoodieWriteConfig config,
HoodieTableMetaClient metaClient) {
+ Option<InternalSchema> internalSchema = new
TableSchemaResolver(metaClient).getTableInternalSchemaFromCommitMetadata();
Review Comment:
Add pre-condition check in case of null values.
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