xiarixiaoyao commented on a change in pull request #4910: URL: https://github.com/apache/hudi/pull/4910#discussion_r832211880
########## File path: hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkInternalSchemaConverter.java ########## @@ -0,0 +1,500 @@ +/* + * 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.client.utils; + +import org.apache.hudi.common.util.collection.Pair; +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.utils.InternalSchemaUtils; +import org.apache.spark.sql.execution.vectorized.WritableColumnVector; +import org.apache.spark.sql.types.ArrayType; +import org.apache.spark.sql.types.ArrayType$; +import org.apache.spark.sql.types.BinaryType; +import org.apache.spark.sql.types.BinaryType$; +import org.apache.spark.sql.types.BooleanType; +import org.apache.spark.sql.types.BooleanType$; +import org.apache.spark.sql.types.ByteType; +import org.apache.spark.sql.types.CharType; +import org.apache.spark.sql.types.DataType; +import org.apache.spark.sql.types.DateType; +import org.apache.spark.sql.types.DateType$; +import org.apache.spark.sql.types.Decimal; +import org.apache.spark.sql.types.DecimalType; +import org.apache.spark.sql.types.DecimalType$; +import org.apache.spark.sql.types.DoubleType; +import org.apache.spark.sql.types.DoubleType$; +import org.apache.spark.sql.types.FloatType; +import org.apache.spark.sql.types.FloatType$; +import org.apache.spark.sql.types.IntegerType; +import org.apache.spark.sql.types.IntegerType$; +import org.apache.spark.sql.types.LongType; +import org.apache.spark.sql.types.LongType$; +import org.apache.spark.sql.types.MapType; +import org.apache.spark.sql.types.MapType$; +import org.apache.spark.sql.types.Metadata; +import org.apache.spark.sql.types.ShortType; +import org.apache.spark.sql.types.StringType; +import org.apache.spark.sql.types.StringType$; +import org.apache.spark.sql.types.StructField; +import org.apache.spark.sql.types.StructType; +import org.apache.spark.sql.types.StructType$; +import org.apache.spark.sql.types.TimestampType; +import org.apache.spark.sql.types.TimestampType$; +import org.apache.spark.sql.types.UserDefinedType; +import org.apache.spark.sql.types.VarcharType; + +import java.nio.charset.StandardCharsets; +import java.sql.Date; +import java.util.ArrayList; +import java.util.Deque; +import java.util.LinkedList; +import java.util.List; +import java.util.Map; +import java.util.concurrent.atomic.AtomicInteger; +import java.util.stream.Collectors; + +public class SparkInternalSchemaConverter { + private SparkInternalSchemaConverter() { + + } + + public static final String HOODIE_QUERY_SCHEMA = "hoodie.schema.internal.querySchema"; + public static final String HOODIE_TABLE_PATH = "hoodie.tablePath"; + /** + * Converts a spark schema to an hudi internal schema. Fields without IDs are kept and assigned fallback IDs. + * + * @param sparkSchema a spark schema + * @return a matching internal schema for the provided spark schema + */ + public static InternalSchema convertStructTypeToInternalSchema(StructType sparkSchema) { + Type newType = buildTypeFromStructType(sparkSchema, true, new AtomicInteger(0)); + return new InternalSchema(((Types.RecordType)newType).fields()); + } + + public static Type buildTypeFromStructType(DataType sparkType, Boolean firstVisitRoot, AtomicInteger nextId) { + if (sparkType instanceof StructType) { + StructField[] fields = ((StructType) sparkType).fields(); + int nextAssignId = firstVisitRoot ? 0 : nextId.get(); + nextId.set(nextAssignId + fields.length); + List<Type> newTypes = new ArrayList<>(); + for (StructField f : fields) { + newTypes.add(buildTypeFromStructType(f.dataType(), false, nextId)); + } + List<Types.Field> newFields = new ArrayList<>(); + for (int i = 0; i < newTypes.size(); i++) { + StructField f = fields[i]; + newFields.add(Types.Field.get(nextAssignId + i, f.nullable(), f.name(), newTypes.get(i), + f.getComment().isDefined() ? f.getComment().get() : null)); + } + return Types.RecordType.get(newFields); + } else if (sparkType instanceof MapType) { + MapType map = (MapType) sparkType; + DataType keyType = map.keyType(); + DataType valueType = map.valueType(); + int keyId = nextId.get(); + int valueId = keyId + 1; + nextId.set(valueId + 1); + return Types.MapType.get(keyId, valueId, buildTypeFromStructType(keyType, false, nextId), + buildTypeFromStructType(valueType, false, nextId), map.valueContainsNull()); + } else if (sparkType instanceof ArrayType) { + ArrayType array = (ArrayType) sparkType; + DataType et = array.elementType(); + int elementId = nextId.get(); + nextId.set(elementId + 1); + return Types.ArrayType.get(elementId, array.containsNull(), buildTypeFromStructType(et, false, nextId)); + } else if (sparkType instanceof UserDefinedType) { + throw new UnsupportedOperationException("User-defined types are not supported"); + } else if (sparkType instanceof BooleanType) { + return Types.BooleanType.get(); + } else if (sparkType instanceof IntegerType + || sparkType instanceof ShortType + || sparkType instanceof ByteType) { + return Types.IntType.get(); + } else if (sparkType instanceof LongType) { + return Types.LongType.get(); + } else if (sparkType instanceof FloatType) { + return Types.FloatType.get(); + } else if (sparkType instanceof DoubleType) { + return Types.DoubleType.get(); + } else if (sparkType instanceof StringType + || sparkType instanceof CharType + || sparkType instanceof VarcharType) { + return Types.StringType.get(); + } else if (sparkType instanceof DateType) { + return Types.DateType.get(); + // spark 3.3.0 support TimeStampNTZ, to do support spark3.3.0 + } else if (sparkType instanceof TimestampType) { + return Types.TimestampType.get(); + } else if (sparkType instanceof DecimalType) { + return Types.DecimalType.get( + ((DecimalType) sparkType).precision(), + ((DecimalType) sparkType).scale()); + } else if (sparkType instanceof BinaryType) { + return Types.BinaryType.get(); + } else { + throw new UnsupportedOperationException(String.format("Not a supported type: %s", sparkType.catalogString())); + } + } + + /** + * Converts a spark schema to an hudi internal schema, and prunes fields. + * Fields without IDs are kept and assigned fallback IDs. + * + * @param sparkSchema a pruned spark schema + * @param originSchema a internal schema for hoodie table + * @return a pruned internal schema for the provided spark schema + */ + public static InternalSchema convertAndPruneStructTypeToInternalSchema(StructType sparkSchema, InternalSchema originSchema) { + List<String> pruneNames = collectColNamesFromSparkStruct(sparkSchema); + return InternalSchemaUtils.pruneInternalSchema(originSchema, pruneNames); + } + + /** + * collect all the leaf nodes names. + * + * @param sparkSchema a spark schema + * @return leaf nodes full names. + */ + public static List<String> collectColNamesFromSparkStruct(StructType sparkSchema) { + List<String> result = new ArrayList<>(); + collectColNamesFromStructType(sparkSchema, new LinkedList<>(), result); + return result; + } + + private static void collectColNamesFromStructType(DataType sparkType, Deque<String> fieldNames, List<String> resultSet) { + if (sparkType instanceof StructType) { + StructField[] fields = ((StructType) sparkType).fields(); + for (StructField f : fields) { + fieldNames.push(f.name()); + collectColNamesFromStructType(f.dataType(), fieldNames, resultSet); + fieldNames.pop(); + addFullName(f.dataType(), f.name(), fieldNames, resultSet); + } + } else if (sparkType instanceof MapType) { + MapType map = (MapType) sparkType; + DataType keyType = map.keyType(); + DataType valueType = map.valueType(); + // key + fieldNames.push("key"); + collectColNamesFromStructType(keyType, fieldNames, resultSet); + fieldNames.pop(); + addFullName(keyType,"key", fieldNames, resultSet); + // value + fieldNames.push("value"); + collectColNamesFromStructType(valueType, fieldNames, resultSet); + fieldNames.poll(); + addFullName(valueType,"value", fieldNames, resultSet); + } else if (sparkType instanceof ArrayType) { + ArrayType array = (ArrayType) sparkType; + DataType et = array.elementType(); + fieldNames.push("element"); + collectColNamesFromStructType(et, fieldNames, resultSet); + fieldNames.pop(); + addFullName(et, "element", fieldNames, resultSet); + } else if (sparkType instanceof UserDefinedType) { + throw new UnsupportedOperationException("User-defined types are not supported"); + } else { + // do nothings + } + } + + private static void addFullName(DataType sparkType, String name, Deque<String> fieldNames, List<String> resultSet) { + if (!(sparkType instanceof StructType) && !(sparkType instanceof ArrayType) && !(sparkType instanceof MapType)) { + resultSet.add(InternalSchemaUtils.createFullName(name, fieldNames)); + } + } + + public static StructType mergeSchema(InternalSchema fileSchema, InternalSchema querySchema) { + InternalSchema schema = new InternalSchemaMerger(fileSchema, querySchema, true, true).mergeSchema(); + return constructSparkSchemaFromInternalSchema(schema); + } + + public static Map<Integer, Pair<DataType, DataType>> collectTypeChangedCols(InternalSchema schema, InternalSchema other) { + return InternalSchemaUtils + .collectTypeChangedCols(schema, other) + .entrySet() + .stream() + .collect(Collectors.toMap(e -> e.getKey(), e -> Pair.of(constructSparkSchemaFromType(e.getValue().getLeft()), constructSparkSchemaFromType(e.getValue().getRight())))); + } + + public static StructType constructSparkSchemaFromInternalSchema(InternalSchema schema) { + return (StructType) constructSparkSchemaFromType(schema.getRecord()); + } + + private static DataType constructSparkSchemaFromType(Type type) { + switch (type.typeId()) { + case RECORD: + Types.RecordType record = (Types.RecordType) type; + List<Types.Field> fields = record.fields(); + List<StructField> structFields = new ArrayList<>(); + for (Types.Field f : fields) { + DataType dataType = constructSparkSchemaFromType(f.type()); + StructField structField = StructField.apply(f.name(), dataType, f.isOptional(), Metadata.empty()); + structField = f.doc() == null ? structField : structField.withComment(f.doc()); + structFields.add(structField); + } + return StructType$.MODULE$.apply(structFields); + case ARRAY: + Types.ArrayType array = (Types.ArrayType) type; + DataType elementType = constructSparkSchemaFromType(array.elementType()); + return ArrayType$.MODULE$.apply(elementType, array.isElementOptional()); + case MAP: + Types.MapType map = (Types.MapType) type; + DataType keyDataType = constructSparkSchemaFromType(map.keyType()); + DataType valueDataType = constructSparkSchemaFromType(map.valueType()); + return MapType$.MODULE$.apply(keyDataType, valueDataType, map.isValueOptional()); + case BOOLEAN: + return BooleanType$.MODULE$; + case INT: + return IntegerType$.MODULE$; + case LONG: + return LongType$.MODULE$; + case FLOAT: + return FloatType$.MODULE$; + case DOUBLE: + return DoubleType$.MODULE$; + case DATE: + return DateType$.MODULE$; + case TIME: + throw new UnsupportedOperationException(String.format("cannot convert %s type to Spark", type)); + case TIMESTAMP: + // todo support TimeStampNTZ + return TimestampType$.MODULE$; + case STRING: + return StringType$.MODULE$; + case UUID: + return StringType$.MODULE$; + case FIXED: + return BinaryType$.MODULE$; + case BINARY: + return BinaryType$.MODULE$; + case DECIMAL: + Types.DecimalType decimal = (Types.DecimalType) type; + return DecimalType$.MODULE$.apply(decimal.precision(), decimal.scale()); + default: + throw new UnsupportedOperationException(String.format("cannot convert unknown type: %s to Spark", type)); + } + } + + /** + * Convert Int/long type to other Type. + * Now only support int/long -> long/float/double/string + * TODO: support more types + */ + private static boolean convertIntLongType(WritableColumnVector oldV, WritableColumnVector newV, DataType newType, int len) { + boolean isInt = oldV.dataType() instanceof IntegerType; + if (newType instanceof LongType || newType instanceof FloatType + || newType instanceof DoubleType || newType instanceof StringType || newType instanceof DecimalType) { + for (int i = 0; i < len; i++) { + if (oldV.isNullAt(i)) { + newV.putNull(i); + continue; + } + // int/long -> long/float/double/string/decimal + if (newType instanceof LongType) { + newV.putLong(i, isInt ? oldV.getInt(i) : oldV.getLong(i)); + } else if (newType instanceof FloatType) { + newV.putFloat(i, isInt ? oldV.getInt(i) : oldV.getLong(i)); + } else if (newType instanceof DoubleType) { + newV.putDouble(i, isInt ? oldV.getInt(i) : oldV.getLong(i)); + } else if (newType instanceof StringType) { + newV.putByteArray(i, ((isInt ? oldV.getInt(i) : oldV.getLong(i)) + "").getBytes(StandardCharsets.UTF_8)); + } else if (newType instanceof DecimalType) { + Decimal oldDecimal = Decimal.apply(isInt ? oldV.getInt(i) : oldV.getLong(i)); + oldDecimal.changePrecision(((DecimalType) newType).precision(), ((DecimalType) newType).scale()); + newV.putDecimal(i, oldDecimal, ((DecimalType) newType).precision()); + } + } + return true; + } + return false; + } + + /** + * Convert float type to other Type. + * Now only support float -> double/String + * TODO: support more types + */ + private static boolean convertFloatType(WritableColumnVector oldV, WritableColumnVector newV, DataType newType, int len) { + if (newType instanceof DoubleType || newType instanceof StringType || newType instanceof DecimalType) { + for (int i = 0; i < len; i++) { + if (oldV.isNullAt(i)) { + newV.putNull(i); + continue; + } + // float -> double/string/decimal + if (newType instanceof DoubleType) { + newV.putDouble(i, Double.valueOf(oldV.getFloat(i) + "")); + } else if (newType instanceof StringType) { + newV.putByteArray(i, (oldV.getFloat(i) + "").getBytes(StandardCharsets.UTF_8)); + } else if (newType instanceof DecimalType) { + Decimal oldDecimal = Decimal.apply(oldV.getFloat(i)); + oldDecimal.changePrecision(((DecimalType) newType).precision(), ((DecimalType) newType).scale()); + newV.putDecimal(i, oldDecimal, ((DecimalType) newType).precision()); + } + } + return true; + } + return false; + } + + /** + * Convert double type to other Type. + * Now only support Double -> Decimal/String Review comment: in the futureļ¼ maybe we can support Double ->timestamp/date We can add new conversion requirements at any time, which is easy -- This is an automated message from the Apache Git Service. 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