Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
/*
* 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.internal.schema.utils;
import org.apache.avro.Schema;
import org.apache.hudi.internal.schema.InternalSchema;
import org.apache.hudi.internal.schema.action.TableChanges;
import java.util.List;
import java.util.Map;
import java.util.TreeMap;
import java.util.stream.Collectors;
import static org.apache.hudi.common.config.HoodieCommonConfig.MAKE_NEW_COLUMNS_NULLABLE;
import static org.apache.hudi.common.util.CollectionUtils.reduce;
import static org.apache.hudi.internal.schema.convert.AvroInternalSchemaConverter.convert;
/**
* Utility methods to support evolve old avro schema based on a given schema.
*/
public class AvroSchemaEvolutionUtils {
/**
* Support reconcile from a new avroSchema.
* 1) incoming data has missing columns that were already defined in the table –> null values will be injected into missing columns
* 2) incoming data contains new columns not defined yet in the table -> columns will be added to the table schema (incoming dataframe?)
* 3) incoming data has missing columns that are already defined in the table and new columns not yet defined in the table ->
* new columns will be added to the table schema, missing columns will be injected with null values
* 4) support type change
* 5) support nested schema change.
* Notice:
* the incoming schema should not have delete/rename semantics.
* for example: incoming schema: int a, int b, int d; oldTableSchema int a, int b, int c, int d
* we must guarantee the column c is missing semantic, instead of delete semantic.
* @param incomingSchema implicitly evolution of avro when hoodie write operation
* @param oldTableSchema old internalSchema
* @return reconcile Schema
*/
public static InternalSchema reconcileSchema(Schema incomingSchema, InternalSchema oldTableSchema) {
InternalSchema inComingInternalSchema = convert(incomingSchema);
// check column add/missing
List colNamesFromIncoming = inComingInternalSchema.getAllColsFullName();
List colNamesFromOldSchema = oldTableSchema.getAllColsFullName();
List diffFromOldSchema = colNamesFromOldSchema.stream().filter(f -> !colNamesFromIncoming.contains(f)).collect(Collectors.toList());
List diffFromEvolutionColumns = colNamesFromIncoming.stream().filter(f -> !colNamesFromOldSchema.contains(f)).collect(Collectors.toList());
// check type change.
List typeChangeColumns = colNamesFromIncoming
.stream()
.filter(f -> colNamesFromOldSchema.contains(f) && !inComingInternalSchema.findType(f).equals(oldTableSchema.findType(f)))
.collect(Collectors.toList());
if (colNamesFromIncoming.size() == colNamesFromOldSchema.size() && diffFromOldSchema.size() == 0 && typeChangeColumns.isEmpty()) {
return oldTableSchema;
}
// Remove redundancy from diffFromEvolutionSchema.
// for example, now we add a struct col in evolvedSchema, the struct col is " user struct "
// when we do diff operation: user, user.name, user.age will appeared in the resultSet which is redundancy, user.name and user.age should be excluded.
// deal with add operation
TreeMap finalAddAction = new TreeMap<>();
for (int i = 0; i < diffFromEvolutionColumns.size(); i++) {
String name = diffFromEvolutionColumns.get(i);
int splitPoint = name.lastIndexOf(".");
String parentName = splitPoint > 0 ? name.substring(0, splitPoint) : "";
if (!parentName.isEmpty() && diffFromEvolutionColumns.contains(parentName)) {
// find redundancy, skip it
continue;
}
finalAddAction.put(inComingInternalSchema.findIdByName(name), name);
}
TableChanges.ColumnAddChange addChange = TableChanges.ColumnAddChange.get(oldTableSchema);
finalAddAction.entrySet().stream().forEach(f -> {
String name = f.getValue();
int splitPoint = name.lastIndexOf(".");
String parentName = splitPoint > 0 ? name.substring(0, splitPoint) : "";
String rawName = splitPoint > 0 ? name.substring(splitPoint + 1) : name;
// try to infer add position.
java.util.Optional inferPosition =
colNamesFromIncoming.stream().filter(c ->
c.lastIndexOf(".") == splitPoint
&& c.startsWith(parentName)
&& inComingInternalSchema.findIdByName(c) > inComingInternalSchema.findIdByName(name)
&& oldTableSchema.findIdByName(c) > 0).sorted((s1, s2) -> oldTableSchema.findIdByName(s1) - oldTableSchema.findIdByName(s2)).findFirst();
addChange.addColumns(parentName, rawName, inComingInternalSchema.findType(name), null);
inferPosition.map(i -> addChange.addPositionChange(name, i, "before"));
});
// do type evolution.
InternalSchema internalSchemaAfterAddColumns = SchemaChangeUtils.applyTableChanges2Schema(oldTableSchema, addChange);
TableChanges.ColumnUpdateChange typeChange = TableChanges.ColumnUpdateChange.get(internalSchemaAfterAddColumns);
typeChangeColumns.stream().filter(f -> !inComingInternalSchema.findType(f).isNestedType()).forEach(col -> {
typeChange.updateColumnType(col, inComingInternalSchema.findType(col));
});
return SchemaChangeUtils.applyTableChanges2Schema(internalSchemaAfterAddColumns, typeChange);
}
/**
* Reconciles nullability requirements b/w {@code source} and {@code target} schemas,
* by adjusting these of the {@code source} schema to be in-line with the ones of the
* {@code target} one
*
* @param sourceSchema source schema that needs reconciliation
* @param targetSchema target schema that source schema will be reconciled against
* @param opts config options
* @return schema (based off {@code source} one) that has nullability constraints reconciled
*/
public static Schema reconcileNullability(Schema sourceSchema, Schema targetSchema, Map opts) {
if (sourceSchema.getFields().isEmpty() || targetSchema.getFields().isEmpty()) {
return sourceSchema;
}
InternalSchema sourceInternalSchema = convert(sourceSchema);
InternalSchema targetInternalSchema = convert(targetSchema);
List colNamesSourceSchema = sourceInternalSchema.getAllColsFullName();
List colNamesTargetSchema = targetInternalSchema.getAllColsFullName();
List candidateUpdateCols = colNamesSourceSchema.stream()
.filter(f -> (("true".equals(opts.get(MAKE_NEW_COLUMNS_NULLABLE.key())) && !colNamesTargetSchema.contains(f))
|| colNamesTargetSchema.contains(f) && sourceInternalSchema.findField(f).isOptional() != targetInternalSchema.findField(f).isOptional()
)
).collect(Collectors.toList());
if (candidateUpdateCols.isEmpty()) {
return sourceSchema;
}
// Reconcile nullability constraints (by executing phony schema change)
TableChanges.ColumnUpdateChange schemaChange =
reduce(candidateUpdateCols, TableChanges.ColumnUpdateChange.get(sourceInternalSchema),
(change, field) -> change.updateColumnNullability(field, true));
return convert(SchemaChangeUtils.applyTableChanges2Schema(sourceInternalSchema, schemaChange), sourceSchema.getFullName());
}
}