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[HUDI-121] Fix licensing issues found during RC voting by general incubator group

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This commit is contained in:
Balaji Varadarajan
2019-10-11 23:00:55 -07:00
committed by Balaji Varadarajan
parent 8c13340062
commit 77f4e73615
19 changed files with 830 additions and 1657 deletions
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6
DISCLAIMER
View File

@@ -1,6 +0,0 @@
Apache Hudi (incubating) is an effort undergoing incubation at The Apache Software Foundation
(ASF), sponsored by the Apache Incubator PMC. Incubation is required of all newly accepted
projects until a further review indicates that the infrastructure, communications, and decision
making process have stabilized in a manner consistent with other successful ASF projects. While
incubation status is not necessarily a reflection of the completeness or stability of the code,
it does indicate that the project has yet to be fully endorsed by the ASF.

26
DISCLAIMER-WIP Normal file
View File

@@ -0,0 +1,26 @@
Apache Hudi (incubating) is an effort undergoing incubation
at The Apache Software Foundation (ASF), sponsored by the Apache Incubator.
Incubation is required of all newly accepted projects until a further review
indicates that the infrastructure, communications, and decision making process
have stabilized in a manner consistent with other successful ASF projects.
While incubation status is not necessarily a reflection of the
completeness or stability of the code, it does indicate that the
project has yet to be fully endorsed by the ASF.
Some of the incubating project's releases may not be fully compliant
with ASF policy. For example, releases may have incomplete or
un-reviewed licensing conditions. What follows is a list of known
issues the project is currently aware of (note that this list, by
definition, is likely to be incomplete):
* The LICENSE and NOTICE files may not be complete and will be fixed with the next release.
If you are planning to incorporate this work into your
product or project, please be aware that you will need to conduct a
thorough licensing review to determine the overall implications of
including this work. For the current status of this project through the Apache
Incubator visit:
http://incubator.apache.org/projects/hudi.html

118
LICENSE
View File

@@ -175,3 +175,121 @@
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. We also recommend that a
file or class name and description of purpose be included on the
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright [yyyy] [name of copyright owner]
Licensed 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.
--------------------------------------------------------------------------------
This product includes code from Apache Hive.
* org.apache.hadoop.hive.ql.io.CombineHiveInputFormat copied to org.apache.hudi.hadoop.hive.HoodieCombineHiveInputFormat
Copyright: 2011-2019 The Apache Software Foundation
Home page: http://hive.apache.org/
License: http://www.apache.org/licenses/LICENSE-2.0
--------------------------------------------------------------------------------
This product includes code from Apache SystemML.
* org.apache.hudi.func.LazyIterableIterator adapted from org/apache/sysml/runtime/instructions/spark/data/LazyIterableIterator
Copyright: 2015-2018 The Apache Software Foundation
Home page: https://systemml.apache.org/
License: http://www.apache.org/licenses/LICENSE-2.0
--------------------------------------------------------------------------------
This product includes code from https://github.com/twitter/commons/blob/master/src/java/com/twitter/common/objectsize/ObjectSizeCalculator.java with the following license
=================================================================================================
Copyright 2011 Twitter, Inc.
-------------------------------------------------------------------------------------------------
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this work except in compliance with the License.
You may obtain a copy of the License in the LICENSE file, or 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.
=================================================================================================
This product includes code from Databricks spark-avro with the below license
* org.apache.hudi.AvroConversionHelper copied from classes in com/databricks/spark/avro package
Copyright 2014 Databricks
Licensed 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.
--------------------------------------------------------------------------------
This product includes code from https://github.com/big-data-europe/README
* docker/hoodie/hadoop/base/entrypoint.sh copied from https://github.com/big-data-europe/docker-hadoop/blob/master/base/entrypoint.sh
which is under the MIT license (https://github.com/big-data-europe/README#license)
The MIT License (MIT)
Copyright (c) 2015 TENFORCE BVBA, INSTITUT FUR ANGEWANDTE INFORMATIK EV,
NATIONAL CENTER FOR SCIENTIFIC RESEARCH "DEMOKRITOS", SEMANTIC WEB COMPANY
GMBH, FRAUNHOFER-GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V,
ETHNIKO KAI KAPODISTRIAKO PANEPISTIMIO ATHINON, GEIE ERCIM
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
-------------------------------------------------------------------------------

11
hudi-cli/src/main/scala/org/apache/hudi/cli/SparkHelpers.scala
View File

@@ -17,6 +17,9 @@
package org.apache.hudi.cli
import java.util
import java.util.Map
import org.apache.avro.Schema
import org.apache.avro.generic.IndexedRecord
import org.apache.hadoop.conf.Configuration
@@ -54,11 +57,6 @@ object SparkHelpers {
}
writer.close
}
def getBloomFilter(file: String, conf: Configuration): String = {
val footer = ParquetFileReader.readFooter(conf, new Path(file));
return footer.getFileMetaData().getKeyValueMetaData().get(HoodieAvroWriteSupport.HOODIE_AVRO_BLOOM_FILTER_METADATA_KEY)
}
}
@@ -124,8 +122,7 @@ class SparkHelper(sqlContext: SQLContext, fs: FileSystem) {
* @return
*/
def fileKeysAgainstBF(conf: Configuration, sqlContext: SQLContext, file: String): Boolean = {
val bfStr = SparkHelpers.getBloomFilter(file, conf)
val bf = new BloomFilter(bfStr)
val bf = ParquetUtils.readBloomFilterFromParquetMetadata(conf, new Path(file))
val foundCount = sqlContext.parquetFile(file)
.select(s"`${HoodieRecord.RECORD_KEY_METADATA_FIELD}`")
.collect().count(r => !bf.mightContain(r.getString(0)))

4
hudi-client/src/test/java/org/apache/hudi/common/TestRawTripPayload.java
View File

@@ -95,8 +95,8 @@ public class TestRawTripPayload implements HoodieRecordPayload<TestRawTripPayloa
if (isDeleted) {
return Option.empty();
} else {
MercifulJsonConverter jsonConverter = new MercifulJsonConverter(schema);
return Option.of(jsonConverter.convert(getJsonData()));
MercifulJsonConverter jsonConverter = new MercifulJsonConverter();
return Option.of(jsonConverter.convert(getJsonData(), schema));
}
}

2
hudi-common/src/main/java/org/apache/hudi/avro/HoodieAvroWriteSupport.java
View File

@@ -34,7 +34,7 @@ public class HoodieAvroWriteSupport extends AvroWriteSupport {
private String minRecordKey;
private String maxRecordKey;
public static final String OLD_HOODIE_AVRO_BLOOM_FILTER_METADATA_KEY = "com.uber.hoodie.bloomfilter";
public static final String HOODIE_AVRO_BLOOM_FILTER_METADATA_KEY = "org.apache.hudi.bloomfilter";
public static final String HOODIE_MIN_RECORD_KEY_FOOTER = "hoodie_min_record_key";
public static final String HOODIE_MAX_RECORD_KEY_FOOTER = "hoodie_max_record_key";

302
hudi-common/src/main/java/org/apache/hudi/avro/MercifulJsonConverter.java
View File

@@ -19,52 +19,99 @@
package org.apache.hudi.avro;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.google.common.collect.ImmutableMap;
import java.io.IOException;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import org.apache.avro.Schema;
import org.apache.avro.Schema.Type;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericRecord;
import org.apache.hudi.common.util.collection.Pair;
import org.apache.hudi.exception.HoodieException;
import org.apache.hudi.exception.HoodieIOException;
/**
* Marjority of this is copied from
* https://github.com/jwills/avro-json/blob/master/src/main/java/com/cloudera/science/avro/ common/JsonConverter.java
* Adjusted for expected behavior of our use cases
* Converts Json record to Avro Generic Record
*/
public class MercifulJsonConverter {
private final ObjectMapper mapper = new ObjectMapper();
private final Schema baseSchema;
private static final Map<Schema.Type, JsonToAvroFieldProcessor> fieldTypeProcessors = getFieldTypeProcessors();
public MercifulJsonConverter(Schema schema) {
this.baseSchema = schema;
private final ObjectMapper mapper;
/**
* Build type processor map for each avro type.
*/
private static Map<Schema.Type, JsonToAvroFieldProcessor> getFieldTypeProcessors() {
Map<Schema.Type, JsonToAvroFieldProcessor> processorMap =
new ImmutableMap.Builder<Schema.Type, JsonToAvroFieldProcessor>().put(Type.STRING, generateStringTypeHandler())
.put(Type.BOOLEAN, generateBooleanTypeHandler()).put(Type.DOUBLE, generateDoubleTypeHandler())
.put(Type.FLOAT, generateFloatTypeHandler()).put(Type.INT, generateIntTypeHandler())
.put(Type.LONG, generateLongTypeHandler()).put(Type.ARRAY, generateArrayTypeHandler())
.put(Type.RECORD, generateRecordTypeHandler()).put(Type.ENUM, generateEnumTypeHandler())
.put(Type.MAP, generateMapTypeHandler()).put(Type.BYTES, generateBytesTypeHandler())
.put(Type.FIXED, generateFixedTypeHandler()).build();
return processorMap;
}
/**
* Uses a default objectMapper to deserialize a json string
*/
public MercifulJsonConverter() {
this(new ObjectMapper());
}
public GenericRecord convert(String json) throws IOException {
/**
* Allows a configured ObjectMapper to be passed for converting json records to avro record
*/
public MercifulJsonConverter(ObjectMapper mapper) {
this.mapper = mapper;
}
/**
* Converts json to Avro generic record
*
* @param json Json record
* @param schema Schema
*/
public GenericRecord convert(String json, Schema schema) {
try {
return convert(mapper.readValue(json, Map.class), baseSchema);
Map<String, Object> jsonObjectMap = mapper.readValue(json, Map.class);
return convertJsonToAvro(jsonObjectMap, schema);
} catch (IOException e) {
throw new IOException("Failed to parse as Json: " + json + "\n\n" + e.getMessage());
throw new HoodieIOException(e.getMessage(), e);
}
}
private GenericRecord convert(Map<String, Object> raw, Schema schema) throws IOException {
GenericRecord result = new GenericData.Record(schema);
private static GenericRecord convertJsonToAvro(Map<String, Object> inputJson, Schema schema) {
GenericRecord avroRecord = new GenericData.Record(schema);
for (Schema.Field f : schema.getFields()) {
String name = f.name();
Object rawValue = raw.get(name);
if (rawValue != null) {
result.put(f.pos(), typeConvert(rawValue, name, f.schema()));
Object val = inputJson.get(f.name());
if (val != null) {
avroRecord.put(f.pos(), convertJsonToAvroField(val, f.name(), f.schema()));
}
}
return result;
return avroRecord;
}
private Object typeConvert(Object value, String name, Schema schema) throws IOException {
private static Schema getNonNull(Schema schema) {
List<Schema> types = schema.getTypes();
Schema.Type firstType = types.get(0).getType();
return firstType.equals(Schema.Type.NULL) ? types.get(1) : types.get(0);
}
private static boolean isOptional(Schema schema) {
return schema.getType().equals(Schema.Type.UNION) && schema.getTypes().size() == 2
&& (schema.getTypes().get(0).getType().equals(Schema.Type.NULL)
|| schema.getTypes().get(1).getType().equals(Schema.Type.NULL));
}
private static Object convertJsonToAvroField(Object value, String name, Schema schema) {
if (isOptional(schema)) {
if (value == null) {
return null;
@@ -73,83 +120,204 @@ public class MercifulJsonConverter {
}
} else if (value == null) {
// Always fail on null for non-nullable schemas
throw new JsonConversionException(null, name, schema);
throw new HoodieJsonToAvroConversionException(null, name, schema);
}
switch (schema.getType()) {
case BOOLEAN:
JsonToAvroFieldProcessor processor = fieldTypeProcessors.get(schema.getType());
if (null != processor) {
return processor.convertToAvro(value, name, schema);
}
throw new IllegalArgumentException("JsonConverter cannot handle type: " + schema.getType());
}
/**
* Base Class for converting json to avro fields
*/
private abstract static class JsonToAvroFieldProcessor implements Serializable {
public Object convertToAvro(Object value, String name, Schema schema) {
Pair<Boolean, Object> res = convert(value, name, schema);
if (!res.getLeft()) {
throw new HoodieJsonToAvroConversionException(value, name, schema);
}
return res.getRight();
}
protected abstract Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException;
}
private static JsonToAvroFieldProcessor generateBooleanTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
if (value instanceof Boolean) {
return value;
return Pair.of(true, value);
}
break;
case DOUBLE:
return Pair.of(false, null);
}
};
}
private static JsonToAvroFieldProcessor generateIntTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
if (value instanceof Number) {
return ((Number) value).doubleValue();
return Pair.of(true, ((Number) value).intValue());
} else if (value instanceof String) {
return Pair.of(true, Integer.valueOf((String) value));
}
break;
case FLOAT:
return Pair.of(false, null);
}
};
}
private static JsonToAvroFieldProcessor generateDoubleTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
if (value instanceof Number) {
return ((Number) value).floatValue();
return Pair.of(true, ((Number) value).doubleValue());
} else if (value instanceof String) {
return Pair.of(true, Double.valueOf((String) value));
}
break;
case INT:
return Pair.of(false, null);
}
};
}
private static JsonToAvroFieldProcessor generateFloatTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
if (value instanceof Number) {
return ((Number) value).intValue();
return Pair.of(true, ((Number) value).floatValue());
} else if (value instanceof String) {
return Pair.of(true, Float.valueOf((String) value));
}
break;
case LONG:
return Pair.of(false, null);
}
};
}
private static JsonToAvroFieldProcessor generateLongTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
if (value instanceof Number) {
return ((Number) value).longValue();
return Pair.of(true, ((Number) value).longValue());
} else if (value instanceof String) {
return Pair.of(true, Long.valueOf((String) value));
}
break;
case STRING:
return value.toString();
case ENUM:
return Pair.of(false, null);
}
};
}
private static JsonToAvroFieldProcessor generateStringTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
return Pair.of(true, value.toString());
}
};
}
private static JsonToAvroFieldProcessor generateBytesTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
return Pair.of(true, value.toString().getBytes());
}
};
}
private static JsonToAvroFieldProcessor generateFixedTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
byte[] src = value.toString().getBytes();
byte[] dst = new byte[schema.getFixedSize()];
System.arraycopy(src, 0, dst, 0, Math.min(schema.getFixedSize(), src.length));
return Pair.of(true, dst);
}
};
}
private static JsonToAvroFieldProcessor generateEnumTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
if (schema.getEnumSymbols().contains(value.toString())) {
return new GenericData.EnumSymbol(schema, value.toString());
return Pair.of(true, new GenericData.EnumSymbol(schema, value.toString()));
}
throw new JsonConversionException(String.format("Symbol %s not in enum", value.toString()),
throw new HoodieJsonToAvroConversionException(String.format("Symbol %s not in enum", value.toString()),
schema.getFullName(), schema);
case RECORD:
return convert((Map<String, Object>) value, schema);
case ARRAY:
}
};
}
private static JsonToAvroFieldProcessor generateRecordTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
GenericRecord result = new GenericData.Record(schema);
return Pair.of(true, convertJsonToAvro((Map<String, Object>) value, schema));
}
};
}
private static JsonToAvroFieldProcessor generateArrayTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
Schema elementSchema = schema.getElementType();
List listRes = new ArrayList();
for (Object v : (List) value) {
listRes.add(typeConvert(v, name, elementSchema));
listRes.add(convertJsonToAvroField(v, name, elementSchema));
}
return listRes;
case MAP:
return Pair.of(true, listRes);
}
};
}
private static JsonToAvroFieldProcessor generateMapTypeHandler() {
return new JsonToAvroFieldProcessor() {
@Override
public Pair<Boolean, Object> convert(Object value, String name, Schema schema)
throws HoodieJsonToAvroConversionException {
Schema valueSchema = schema.getValueType();
Map<String, Object> mapRes = new HashMap<String, Object>();
for (Map.Entry<String, Object> v : ((Map<String, Object>) value).entrySet()) {
mapRes.put(v.getKey(), typeConvert(v.getValue(), name, valueSchema));
mapRes.put(v.getKey(), convertJsonToAvroField(v.getValue(), name, valueSchema));
}
return mapRes;
default:
throw new IllegalArgumentException("JsonConverter cannot handle type: " + schema.getType());
}
throw new JsonConversionException(value, name, schema);
return Pair.of(true, mapRes);
}
};
}
private boolean isOptional(Schema schema) {
return schema.getType().equals(Schema.Type.UNION) && schema.getTypes().size() == 2
&& (schema.getTypes().get(0).getType().equals(Schema.Type.NULL)
|| schema.getTypes().get(1).getType().equals(Schema.Type.NULL));
}
private Schema getNonNull(Schema schema) {
List<Schema> types = schema.getTypes();
return types.get(0).getType().equals(Schema.Type.NULL) ? types.get(1) : types.get(0);
}
public static class JsonConversionException extends RuntimeException {
/**
* Exception Class for any schema conversion issue
*/
public static class HoodieJsonToAvroConversionException extends HoodieException {
private Object value;
private String fieldName;
private Schema schema;
public JsonConversionException(Object value, String fieldName, Schema schema) {
public HoodieJsonToAvroConversionException(Object value, String fieldName, Schema schema) {
this.value = value;
this.fieldName = fieldName;
this.schema = schema;
@@ -157,7 +325,7 @@ public class MercifulJsonConverter {
@Override
public String toString() {
return String.format("Type conversion error for field %s, %s for %s", fieldName, value, schema);
return String.format("Json to Avro Type conversion error for field %s, %s for %s", fieldName, value, schema);
}
}
}

4
hudi-common/src/main/java/org/apache/hudi/common/HoodieJsonPayload.java
View File

@@ -56,8 +56,8 @@ public class HoodieJsonPayload implements HoodieRecordPayload<HoodieJsonPayload>
@Override
public Option<IndexedRecord> getInsertValue(Schema schema) throws IOException {
MercifulJsonConverter jsonConverter = new MercifulJsonConverter(schema);
return Option.of(jsonConverter.convert(getJsonData()));
MercifulJsonConverter jsonConverter = new MercifulJsonConverter();
return Option.of(jsonConverter.convert(getJsonData(), schema));
}
private String getJsonData() throws IOException {

19
hudi-common/src/main/java/org/apache/hudi/common/util/ObjectSizeCalculator.java
View File

@@ -1,22 +1,3 @@
/*
* 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.
*/
// COPIED FROM https://github.com/twitter/commons/blob/master/src/java/com/twitter/common/objectsize/
// ObjectSizeCalculator.java
// =================================================================================================
// Copyright 2011 Twitter, Inc.
// -------------------------------------------------------------------------------------------------

361
hudi-common/src/main/java/org/apache/hudi/common/util/Option.java
View File

@@ -24,291 +24,122 @@ import java.util.Objects;
import java.util.Optional;
import java.util.function.Consumer;
import java.util.function.Function;
import java.util.function.Predicate;
import java.util.function.Supplier;
/**
* Copied from java.util.Optional and made Serializable along with methods to convert to/from standard Option
* Provides functionality same as java.util.Optional but is also made Serializable. Additional APIs are provided to
* convert to/from java.util.Optional
*/
public final class Option<T> implements Serializable {
private static final long serialVersionUID = 0L;
/**
* Common instance for {@code empty()}.
*/
private static final Option<?> EMPTY = new Option<>();
private static final Option<?> NULL_VAL = new Option<>();
/**
* If non-null, the value; if null, indicates no value is present
*/
private final T value;
/**
* Constructs an empty instance.
*
* @implNote Generally only one empty instance, {@link Option#EMPTY}, should exist per VM.
*/
private Option() {
this.value = null;
}
/**
* Returns an empty {@code Option} instance. No value is present for this Option.
*
* @param <T> Type of the non-existent value
* @return an empty {@code Option}
* @apiNote Though it may be tempting to do so, avoid testing if an object is empty by comparing with {@code ==}
* against instances returned by {@code Option.empty()}. There is no guarantee that it is a singleton.
* Instead, use {@link #isPresent()}.
*/
public static <T> Option<T> empty() {
@SuppressWarnings("unchecked")
Option<T> t = (Option<T>) EMPTY;
return t;
}
/**
* Constructs an instance with the value present.
*
* @param value the non-null value to be present
* @throws NullPointerException if value is null
*/
private Option(T value) {
this.value = Objects.requireNonNull(value);
}
/**
* Returns an {@code Option} with the specified present non-null value.
*
* @param <T> the class of the value
* @param value the value to be present, which must be non-null
* @return an {@code Option} with the value present
* @throws NullPointerException if value is null
*/
public static <T> Option<T> of(T value) {
return new Option<>(value);
}
/**
* Returns an {@code Option} describing the specified value, if non-null, otherwise returns an empty {@code Option}.
*
* @param <T> the class of the value
* @param value the possibly-null value to describe
* @return an {@code Option} with a present value if the specified value is non-null, otherwise an empty {@code
* Option}
*/
public static <T> Option<T> ofNullable(T value) {
return value == null ? empty() : of(value);
}
/**
* If a value is present in this {@code Option}, returns the value, otherwise throws {@code NoSuchElementException}.
*
* @return the non-null value held by this {@code Option}
* @throws NoSuchElementException if there is no value present
* @see Option#isPresent()
*/
public T get() {
if (value == null) {
throw new NoSuchElementException("No value present");
}
return value;
}
/**
* Return {@code true} if there is a value present, otherwise {@code false}.
*
* @return {@code true} if there is a value present, otherwise {@code false}
*/
public boolean isPresent() {
return value != null;
}
/**
* If a value is present, invoke the specified consumer with the value, otherwise do nothing.
*
* @param consumer block to be executed if a value is present
* @throws NullPointerException if value is present and {@code consumer} is null
*/
public void ifPresent(Consumer<? super T> consumer) {
if (value != null) {
consumer.accept(value);
}
}
/**
* If a value is present, and the value matches the given predicate, return an {@code Option} describing the value,
* otherwise return an empty {@code Option}.
*
* @param predicate a predicate to apply to the value, if present
* @return an {@code Option} describing the value of this {@code Option} if a value is present and the value matches
* the given predicate, otherwise an empty {@code Option}
* @throws NullPointerException if the predicate is null
*/
public Option<T> filter(Predicate<? super T> predicate) {
Objects.requireNonNull(predicate);
if (!isPresent()) {
return this;
} else {
return predicate.test(value) ? this : empty();
}
}
/**
* If a value is present, apply the provided mapping function to it, and if the result is non-null, return an {@code
* Option} describing the result. Otherwise return an empty {@code Option}.
*
* @param <U> The type of the result of the mapping function
* @param mapper a mapping function to apply to the value, if present
* @return an {@code Option} describing the result of applying a mapping function to the value of this {@code Option},
* if a value is present, otherwise an empty {@code Option}
* @throws NullPointerException if the mapping function is null
* @apiNote This method supports post-processing on optional values, without the need to explicitly check for a return
* status. For example, the following code traverses a stream of file names, selects one that has not yet
* been processed, and then opens that file, returning an {@code Option<FileInputStream>}:
*
* <pre>
* {@code
* Option<FileInputStream> fis =
* names.stream().filter(name -> !isProcessedYet(name))
* .findFirst()
* .map(name -> new FileInputStream(name));
* }
* </pre>
*
* Here, {@code findFirst} returns an {@code Option<String>}, and then {@code map} returns an {@code
* Option<FileInputStream>} for the desired file if one exists.
*/
public <U> Option<U> map(Function<? super T, ? extends U> mapper) {
Objects.requireNonNull(mapper);
if (!isPresent()) {
return empty();
} else {
return Option.ofNullable(mapper.apply(value));
}
}
/**
* If a value is present, apply the provided {@code Option}-bearing mapping function to it, return that result,
* otherwise return an empty {@code Option}. This method is similar to {@link #map(Function)}, but the provided mapper
* is one whose result is already an {@code Option}, and if invoked, {@code flatMap} does not wrap it with an
* additional {@code Option}.
*
* @param <U> The type parameter to the {@code Option} returned by
* @param mapper a mapping function to apply to the value, if present the mapping function
* @return the result of applying an {@code Option}-bearing mapping function to the value of this {@code Option}, if a
* value is present, otherwise an empty {@code Option}
* @throws NullPointerException if the mapping function is null or returns a null result
*/
public <U> Option<U> flatMap(Function<? super T, Option<U>> mapper) {
Objects.requireNonNull(mapper);
if (!isPresent()) {
return empty();
} else {
return Objects.requireNonNull(mapper.apply(value));
}
}
/**
* Return the value if present, otherwise return {@code other}.
*
* @param other the value to be returned if there is no value present, may be null
* @return the value, if present, otherwise {@code other}
*/
public T orElse(T other) {
return value != null ? value : other;
}
/**
* Return the value if present, otherwise invoke {@code other} and return the result of that invocation.
*
* @param other a {@code Supplier} whose result is returned if no value is present
* @return the value if present otherwise the result of {@code other.get()}
* @throws NullPointerException if value is not present and {@code other} is null
*/
public T orElseGet(Supplier<? extends T> other) {
return value != null ? value : other.get();
}
/**
* Return the contained value, if present, otherwise throw an exception to be created by the provided supplier.
*
* @param <X> Type of the exception to be thrown
* @param exceptionSupplier The supplier which will return the exception to be thrown
* @return the present value
* @throws X if there is no value present
* @throws NullPointerException if no value is present and {@code exceptionSupplier} is null
* @apiNote A method reference to the exception constructor with an empty argument list can be used as the supplier.
* For example, {@code IllegalStateException::new}
*/
public <X extends Throwable> T orElseThrow(Supplier<? extends X> exceptionSupplier) throws X {
if (value != null) {
return value;
} else {
throw exceptionSupplier.get();
}
}
/**
* Indicates whether some other object is "equal to" this Option. The other object is considered equal if:
* <ul>
* <li>it is also an {@code Option} and;
* <li>both instances have no value present or;
* <li>the present values are "equal to" each other via {@code equals()}.
* </ul>
*
* @param obj an object to be tested for equality
* @return {code true} if the other object is "equal to" this object otherwise {@code false}
*/
@Override
public boolean equals(Object obj) {
if (this == obj) {
return true;
}
if (!(obj instanceof Option)) {
return false;
}
Option<?> other = (Option<?>) obj;
return Objects.equals(value, other.value);
}
/**
* Returns the hash code value of the present value, if any, or 0 (zero) if no value is present.
*
* @return hash code value of the present value or 0 if no value is present
*/
@Override
public int hashCode() {
return Objects.hashCode(value);
}
/**
* Returns a non-empty string representation of this Option suitable for debugging. The exact presentation format is
* unspecified and may vary between implementations and versions.
*
* @return the string representation of this instance
* @implSpec If a value is present the result must include its string representation in the result. Empty and present
* Optionals must be unambiguously differentiable.
*/
@Override
public String toString() {
return value != null ? String.format("Option[%s]", value) : "Option.empty";
}
private final T val;
/**
* Convert to java Optional
*/
public Optional<T> toJavaOptional() {
return Optional.ofNullable(value);
return Optional.ofNullable(val);
}
/**
* Convert from java.util.Optional
*
* @param v java.util.Optional object
* @param <T> type of the value stored in java.util.Optional object
* @return Option
*/
public static <T> Option<T> fromJavaOptional(Optional<T> v) {
return Option.ofNullable(v.orElse(null));
}
private Option() {
this.val = null;
}
private Option(T val) {
if (null == val) {
throw new NullPointerException("Expected a non-null value. Got null");
}
this.val = val;
}
public static <T> Option<T> empty() {
return (Option<T>) NULL_VAL;
}
public static <T> Option<T> of(T value) {
return new Option<>(value);
}
public static <T> Option<T> ofNullable(T value) {
return null == value ? empty() : of(value);
}
public boolean isPresent() {
return null != val;
}
public T get() {
if (null == val) {
throw new NoSuchElementException("No value present in Option");
}
return val;
}
public void ifPresent(Consumer<? super T> consumer) {
if (val != null) {
// process the value
consumer.accept(val);
}
}
public <U> Option<U> map(Function<? super T, ? extends U> mapper) {
if (!isPresent()) {
return empty();
} else {
return Option.ofNullable(mapper.apply(val));
}
}
public T orElse(T other) {
return val != null ? val : other;
}
public T orElseGet(Supplier<? extends T> other) {
return val != null ? val : other.get();
}
public <X extends Throwable> T orElseThrow(Supplier<? extends X> exceptionSupplier) throws X {
if (val != null) {
return val;
} else {
throw exceptionSupplier.get();
}
}
@Override
public boolean equals(Object o) {
if (this == o) {
return true;
}
if (o == null || getClass() != o.getClass()) {
return false;
}
Option<?> option = (Option<?>) o;
return Objects.equals(val, option.val);
}
@Override
public int hashCode() {
return Objects.hash(val);
}
@Override
public String toString() {
return "Option{" + "val=" + val + '}';
}
}

30
hudi-common/src/main/java/org/apache/hudi/common/util/ParquetUtils.java
View File

@@ -20,6 +20,7 @@ package org.apache.hudi.common.util;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
@@ -116,15 +117,15 @@ public class ParquetUtils {
return readMetadata(configuration, parquetFilePath).getFileMetaData().getSchema();
}
private static List<String> readParquetFooter(Configuration configuration, Path parquetFilePath,
String... footerNames) {
List<String> footerVals = new ArrayList<>();
private static Map<String, String> readParquetFooter(Configuration configuration, boolean required,
Path parquetFilePath, String... footerNames) {
Map<String, String> footerVals = new HashMap<>();
ParquetMetadata footer = readMetadata(configuration, parquetFilePath);
Map<String, String> metadata = footer.getFileMetaData().getKeyValueMetaData();
for (String footerName : footerNames) {
if (metadata.containsKey(footerName)) {
footerVals.add(metadata.get(footerName));
} else {
footerVals.put(footerName, metadata.get(footerName));
} else if (required) {
throw new MetadataNotFoundException(
"Could not find index in Parquet footer. " + "Looked for key " + footerName + " in " + parquetFilePath);
}
@@ -140,21 +141,28 @@ public class ParquetUtils {
* Read out the bloom filter from the parquet file meta data.
*/
public static BloomFilter readBloomFilterFromParquetMetadata(Configuration configuration, Path parquetFilePath) {
String footerVal =
readParquetFooter(configuration, parquetFilePath, HoodieAvroWriteSupport.HOODIE_AVRO_BLOOM_FILTER_METADATA_KEY)
.get(0);
return new BloomFilter(footerVal);
Map<String, String> footerVals =
readParquetFooter(configuration, false, parquetFilePath,
HoodieAvroWriteSupport.HOODIE_AVRO_BLOOM_FILTER_METADATA_KEY,
HoodieAvroWriteSupport.OLD_HOODIE_AVRO_BLOOM_FILTER_METADATA_KEY);
String footerVal = footerVals.get(HoodieAvroWriteSupport.HOODIE_AVRO_BLOOM_FILTER_METADATA_KEY);
if (null == footerVal) {
// We use old style key "com.uber.hoodie.bloomfilter"
footerVal = footerVals.get(HoodieAvroWriteSupport.OLD_HOODIE_AVRO_BLOOM_FILTER_METADATA_KEY);
}
return footerVal != null ? new BloomFilter(footerVal) : null;
}
public static String[] readMinMaxRecordKeys(Configuration configuration, Path parquetFilePath) {
List<String> minMaxKeys = readParquetFooter(configuration, parquetFilePath,
Map<String, String> minMaxKeys = readParquetFooter(configuration, true, parquetFilePath,
HoodieAvroWriteSupport.HOODIE_MIN_RECORD_KEY_FOOTER, HoodieAvroWriteSupport.HOODIE_MAX_RECORD_KEY_FOOTER);
if (minMaxKeys.size() != 2) {
throw new HoodieException(
String.format("Could not read min/max record key out of footer correctly from %s. read) : %s",
parquetFilePath, minMaxKeys));
}
return new String[] {minMaxKeys.get(0), minMaxKeys.get(1)};
return new String[] {minMaxKeys.get(HoodieAvroWriteSupport.HOODIE_MIN_RECORD_KEY_FOOTER),
minMaxKeys.get(HoodieAvroWriteSupport.HOODIE_MAX_RECORD_KEY_FOOTER)};
}
/**

4
hudi-common/src/test/java/org/apache/hudi/common/util/SchemaTestUtil.java
View File

@@ -167,7 +167,7 @@ public class SchemaTestUtil {
public static GenericRecord generateAvroRecordFromJson(Schema schema, int recordNumber, String commitTime,
String fileId) throws IOException {
TestRecord record = new TestRecord(commitTime, recordNumber, fileId);
MercifulJsonConverter converter = new MercifulJsonConverter(schema);
return converter.convert(record.toJsonString());
MercifulJsonConverter converter = new MercifulJsonConverter();
return converter.convert(record.toJsonString(), schema);
}
}

302
hudi-spark/src/main/scala/org/apache/hudi/AvroConversionHelper.scala Normal file
View File

@@ -0,0 +1,302 @@
/*
* This code is copied from com.databricks:spark-avro with following license
*
* Copyright 2014 Databricks
*
* Licensed 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
import java.nio.ByteBuffer
import java.sql.{Date, Timestamp}
import java.util
import com.databricks.spark.avro.SchemaConverters
import com.databricks.spark.avro.SchemaConverters.IncompatibleSchemaException
import org.apache.avro.{Schema, SchemaBuilder}
import org.apache.avro.Schema.Type._
import org.apache.avro.generic.GenericData.{Fixed, Record}
import org.apache.avro.generic.{GenericData, GenericRecord}
import org.apache.hudi.AvroConversionUtils.getNewRecordNamespace
import org.apache.spark.sql.Row
import org.apache.spark.sql.catalyst.expressions.GenericRow
import org.apache.spark.sql.types._
import scala.collection.JavaConverters._
object AvroConversionHelper {
/**
*
* Returns a converter function to convert row in avro format to GenericRow of catalyst.
*
* @param sourceAvroSchema Source schema before conversion inferred from avro file by passed in
* by user.
* @param targetSqlType Target catalyst sql type after the conversion.
* @return returns a converter function to convert row in avro format to GenericRow of catalyst.
*/
def createConverterToRow(sourceAvroSchema: Schema,
targetSqlType: DataType): AnyRef => AnyRef = {
def createConverter(avroSchema: Schema, sqlType: DataType, path: List[String]): AnyRef => AnyRef = {
val avroType = avroSchema.getType
(sqlType, avroType) match {
// Avro strings are in Utf8, so we have to call toString on them
case (StringType, STRING) | (StringType, ENUM) =>
(item: AnyRef) => if (item == null) null else item.toString
// Byte arrays are reused by avro, so we have to make a copy of them.
case (IntegerType, INT) | (BooleanType, BOOLEAN) | (DoubleType, DOUBLE) |
(FloatType, FLOAT) | (LongType, LONG) =>
identity
case (BinaryType, FIXED) =>
(item: AnyRef) =>
if (item == null) {
null
} else {
item.asInstanceOf[Fixed].bytes().clone()
}
case (BinaryType, BYTES) =>
(item: AnyRef) =>
if (item == null) {
null
} else {
val byteBuffer = item.asInstanceOf[ByteBuffer]
val bytes = new Array[Byte](byteBuffer.remaining)
byteBuffer.get(bytes)
bytes
}
case (struct: StructType, RECORD) =>
val length = struct.fields.length
val converters = new Array[AnyRef => AnyRef](length)
val avroFieldIndexes = new Array[Int](length)
var i = 0
while (i < length) {
val sqlField = struct.fields(i)
val avroField = avroSchema.getField(sqlField.name)
if (avroField != null) {
val converter = createConverter(avroField.schema(), sqlField.dataType,
path :+ sqlField.name)
converters(i) = converter
avroFieldIndexes(i) = avroField.pos()
} else if (!sqlField.nullable) {
throw new IncompatibleSchemaException(
s"Cannot find non-nullable field ${sqlField.name} at path ${path.mkString(".")} " +
"in Avro schema\n" +
s"Source Avro schema: $sourceAvroSchema.\n" +
s"Target Catalyst type: $targetSqlType")
}
i += 1
}
(item: AnyRef) => {
if (item == null) {
null
} else {
val record = item.asInstanceOf[GenericRecord]
val result = new Array[Any](length)
var i = 0
while (i < converters.length) {
if (converters(i) != null) {
val converter = converters(i)
result(i) = converter(record.get(avroFieldIndexes(i)))
}
i += 1
}
new GenericRow(result)
}
}
case (arrayType: ArrayType, ARRAY) =>
val elementConverter = createConverter(avroSchema.getElementType, arrayType.elementType,
path)
val allowsNull = arrayType.containsNull
(item: AnyRef) => {
if (item == null) {
null
} else {
item.asInstanceOf[java.lang.Iterable[AnyRef]].asScala.map { element =>
if (element == null && !allowsNull) {
throw new RuntimeException(s"Array value at path ${path.mkString(".")} is not " +
"allowed to be null")
} else {
elementConverter(element)
}
}
}
}
case (mapType: MapType, MAP) if mapType.keyType == StringType =>
val valueConverter = createConverter(avroSchema.getValueType, mapType.valueType, path)
val allowsNull = mapType.valueContainsNull
(item: AnyRef) => {
if (item == null) {
null
} else {
item.asInstanceOf[java.util.Map[AnyRef, AnyRef]].asScala.map { x =>
if (x._2 == null && !allowsNull) {
throw new RuntimeException(s"Map value at path ${path.mkString(".")} is not " +
"allowed to be null")
} else {
(x._1.toString, valueConverter(x._2))
}
}.toMap
}
}
case (sqlType, UNION) =>
if (avroSchema.getTypes.asScala.exists(_.getType == NULL)) {
val remainingUnionTypes = avroSchema.getTypes.asScala.filterNot(_.getType == NULL)
if (remainingUnionTypes.size == 1) {
createConverter(remainingUnionTypes.head, sqlType, path)
} else {
createConverter(Schema.createUnion(remainingUnionTypes.asJava), sqlType, path)
}
} else avroSchema.getTypes.asScala.map(_.getType) match {
case Seq(t1) => createConverter(avroSchema.getTypes.get(0), sqlType, path)
case Seq(a, b) if Set(a, b) == Set(INT, LONG) && sqlType == LongType =>
(item: AnyRef) => {
item match {
case null => null
case l: java.lang.Long => l
case i: java.lang.Integer => new java.lang.Long(i.longValue())
}
}
case Seq(a, b) if Set(a, b) == Set(FLOAT, DOUBLE) && sqlType == DoubleType =>
(item: AnyRef) => {
item match {
case null => null
case d: java.lang.Double => d
case f: java.lang.Float => new java.lang.Double(f.doubleValue())
}
}
case other =>
sqlType match {
case t: StructType if t.fields.length == avroSchema.getTypes.size =>
val fieldConverters = t.fields.zip(avroSchema.getTypes.asScala).map {
case (field, schema) =>
createConverter(schema, field.dataType, path :+ field.name)
}
(item: AnyRef) =>
if (item == null) {
null
} else {
val i = GenericData.get().resolveUnion(avroSchema, item)
val converted = new Array[Any](fieldConverters.length)
converted(i) = fieldConverters(i)(item)
new GenericRow(converted)
}
case _ => throw new IncompatibleSchemaException(
s"Cannot convert Avro schema to catalyst type because schema at path " +
s"${path.mkString(".")} is not compatible " +
s"(avroType = $other, sqlType = $sqlType). \n" +
s"Source Avro schema: $sourceAvroSchema.\n" +
s"Target Catalyst type: $targetSqlType")
}
}
case (left, right) =>
throw new IncompatibleSchemaException(
s"Cannot convert Avro schema to catalyst type because schema at path " +
s"${path.mkString(".")} is not compatible (avroType = $left, sqlType = $right). \n" +
s"Source Avro schema: $sourceAvroSchema.\n" +
s"Target Catalyst type: $targetSqlType")
}
}
createConverter(sourceAvroSchema, targetSqlType, List.empty[String])
}
def createConverterToAvro(dataType: DataType,
structName: String,
recordNamespace: String): Any => Any = {
dataType match {
case BinaryType => (item: Any) =>
item match {
case null => null
case bytes: Array[Byte] => ByteBuffer.wrap(bytes)
}
case IntegerType | LongType |
FloatType | DoubleType | StringType | BooleanType => identity
case ByteType => (item: Any) =>
if (item == null) null else item.asInstanceOf[Byte].intValue
case ShortType => (item: Any) =>
if (item == null) null else item.asInstanceOf[Short].intValue
case _: DecimalType => (item: Any) => if (item == null) null else item.toString
case TimestampType => (item: Any) =>
if (item == null) null else item.asInstanceOf[Timestamp].getTime
case DateType => (item: Any) =>
if (item == null) null else item.asInstanceOf[Date].getTime
case ArrayType(elementType, _) =>
val elementConverter = createConverterToAvro(
elementType,
structName,
getNewRecordNamespace(elementType, recordNamespace, structName))
(item: Any) => {
if (item == null) {
null
} else {
val sourceArray = item.asInstanceOf[Seq[Any]]
val sourceArraySize = sourceArray.size
val targetList = new util.ArrayList[Any](sourceArraySize)
var idx = 0
while (idx < sourceArraySize) {
targetList.add(elementConverter(sourceArray(idx)))
idx += 1
}
targetList
}
}
case MapType(StringType, valueType, _) =>
val valueConverter = createConverterToAvro(
valueType,
structName,
getNewRecordNamespace(valueType, recordNamespace, structName))
(item: Any) => {
if (item == null) {
null
} else {
val javaMap = new util.HashMap[String, Any]()
item.asInstanceOf[Map[String, Any]].foreach { case (key, value) =>
javaMap.put(key, valueConverter(value))
}
javaMap
}
}
case structType: StructType =>
val builder = SchemaBuilder.record(structName).namespace(recordNamespace)
val schema: Schema = SchemaConverters.convertStructToAvro(
structType, builder, recordNamespace)
val fieldConverters = structType.fields.map(field =>
createConverterToAvro(
field.dataType,
field.name,
getNewRecordNamespace(field.dataType, recordNamespace, field.name)))
(item: Any) => {
if (item == null) {
null
} else {
val record = new Record(schema)
val convertersIterator = fieldConverters.iterator
val fieldNamesIterator = dataType.asInstanceOf[StructType].fieldNames.iterator
val rowIterator = item.asInstanceOf[Row].toSeq.iterator
while (convertersIterator.hasNext) {
val converter = convertersIterator.next()
record.put(fieldNamesIterator.next(), converter(rowIterator.next()))
}
record
}
}
}
}
}

289
hudi-spark/src/main/scala/org/apache/hudi/AvroConversionUtils.scala
View File

@@ -17,24 +17,14 @@
package org.apache.hudi
import java.nio.ByteBuffer
import java.sql.{Date, Timestamp}
import java.util
import com.databricks.spark.avro.SchemaConverters
import com.databricks.spark.avro.SchemaConverters.IncompatibleSchemaException
import org.apache.avro.Schema.Type._
import org.apache.avro.generic.GenericData.{Fixed, Record}
import org.apache.avro.generic.{GenericData, GenericRecord}
import org.apache.avro.generic.GenericRecord
import org.apache.avro.{Schema, SchemaBuilder}
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.encoders.RowEncoder
import org.apache.spark.sql.catalyst.expressions.GenericRow
import org.apache.spark.sql.types._
import org.apache.spark.sql.{DataFrame, Dataset, Row, SparkSession}
import scala.collection.JavaConverters._
object AvroConversionUtils {
@@ -43,15 +33,15 @@ object AvroConversionUtils {
val encoder = RowEncoder.apply(dataType).resolveAndBind()
df.queryExecution.toRdd.map(encoder.fromRow)
.mapPartitions { records =>
if (records.isEmpty) Iterator.empty
else {
val convertor = createConverterToAvro(dataType, structName, recordNamespace)
records.map { x => convertor(x).asInstanceOf[GenericRecord] }
if (records.isEmpty) Iterator.empty
else {
val convertor = AvroConversionHelper.createConverterToAvro(dataType, structName, recordNamespace)
records.map { x => convertor(x).asInstanceOf[GenericRecord] }
}
}
}
}
def createDataFrame(rdd: RDD[GenericRecord], schemaStr: String, ss : SparkSession): Dataset[Row] = {
def createDataFrame(rdd: RDD[GenericRecord], schemaStr: String, ss: SparkSession): Dataset[Row] = {
if (rdd.isEmpty()) {
ss.emptyDataFrame
} else {
@@ -60,7 +50,7 @@ object AvroConversionUtils {
else {
val schema = Schema.parse(schemaStr)
val dataType = convertAvroSchemaToStructType(schema)
val convertor = createConverterToRow(schema, dataType)
val convertor = AvroConversionHelper.createConverterToRow(schema, dataType)
records.map { x => convertor(x).asInstanceOf[Row] }
}
}, convertAvroSchemaToStructType(Schema.parse(schemaStr))).asInstanceOf[Dataset[Row]]
@@ -77,269 +67,6 @@ object AvroConversionUtils {
}
}
/**
* NOTE : This part of code is copied from com.databricks.spark.avro.SchemaConverters.scala (133:310) (spark-avro)
*
* Returns a converter function to convert row in avro format to GenericRow of catalyst.
*
* @param sourceAvroSchema Source schema before conversion inferred from avro file by passed in
* by user.
* @param targetSqlType Target catalyst sql type after the conversion.
* @return returns a converter function to convert row in avro format to GenericRow of catalyst.
*/
def createConverterToRow(sourceAvroSchema: Schema,
targetSqlType: DataType): AnyRef => AnyRef = {
def createConverter(avroSchema: Schema,
sqlType: DataType, path: List[String]): AnyRef => AnyRef = {
val avroType = avroSchema.getType
(sqlType, avroType) match {
// Avro strings are in Utf8, so we have to call toString on them
case (StringType, STRING) | (StringType, ENUM) =>
(item: AnyRef) => if (item == null) null else item.toString
// Byte arrays are reused by avro, so we have to make a copy of them.
case (IntegerType, INT) | (BooleanType, BOOLEAN) | (DoubleType, DOUBLE) |
(FloatType, FLOAT) | (LongType, LONG) =>
identity
case (BinaryType, FIXED) =>
(item: AnyRef) =>
if (item == null) {
null
} else {
item.asInstanceOf[Fixed].bytes().clone()
}
case (BinaryType, BYTES) =>
(item: AnyRef) =>
if (item == null) {
null
} else {
val byteBuffer = item.asInstanceOf[ByteBuffer]
val bytes = new Array[Byte](byteBuffer.remaining)
byteBuffer.get(bytes)
bytes
}
case (struct: StructType, RECORD) =>
val length = struct.fields.length
val converters = new Array[AnyRef => AnyRef](length)
val avroFieldIndexes = new Array[Int](length)
var i = 0
while (i < length) {
val sqlField = struct.fields(i)
val avroField = avroSchema.getField(sqlField.name)
if (avroField != null) {
val converter = createConverter(avroField.schema(), sqlField.dataType,
path :+ sqlField.name)
converters(i) = converter
avroFieldIndexes(i) = avroField.pos()
} else if (!sqlField.nullable) {
throw new IncompatibleSchemaException(
s"Cannot find non-nullable field ${sqlField.name} at path ${path.mkString(".")} " +
"in Avro schema\n" +
s"Source Avro schema: $sourceAvroSchema.\n" +
s"Target Catalyst type: $targetSqlType")
}
i += 1
}
(item: AnyRef) => {
if (item == null) {
null
} else {
val record = item.asInstanceOf[GenericRecord]
val result = new Array[Any](length)
var i = 0
while (i < converters.length) {
if (converters(i) != null) {
val converter = converters(i)
result(i) = converter(record.get(avroFieldIndexes(i)))
}
i += 1
}
new GenericRow(result)
}
}
case (arrayType: ArrayType, ARRAY) =>
val elementConverter = createConverter(avroSchema.getElementType, arrayType.elementType,
path)
val allowsNull = arrayType.containsNull
(item: AnyRef) => {
if (item == null) {
null
} else {
item.asInstanceOf[java.lang.Iterable[AnyRef]].asScala.map { element =>
if (element == null && !allowsNull) {
throw new RuntimeException(s"Array value at path ${path.mkString(".")} is not " +
"allowed to be null")
} else {
elementConverter(element)
}
}
}
}
case (mapType: MapType, MAP) if mapType.keyType == StringType =>
val valueConverter = createConverter(avroSchema.getValueType, mapType.valueType, path)
val allowsNull = mapType.valueContainsNull
(item: AnyRef) => {
if (item == null) {
null
} else {
item.asInstanceOf[java.util.Map[AnyRef, AnyRef]].asScala.map { x =>
if (x._2 == null && !allowsNull) {
throw new RuntimeException(s"Map value at path ${path.mkString(".")} is not " +
"allowed to be null")
} else {
(x._1.toString, valueConverter(x._2))
}
}.toMap
}
}
case (sqlType, UNION) =>
if (avroSchema.getTypes.asScala.exists(_.getType == NULL)) {
val remainingUnionTypes = avroSchema.getTypes.asScala.filterNot(_.getType == NULL)
if (remainingUnionTypes.size == 1) {
createConverter(remainingUnionTypes.head, sqlType, path)
} else {
createConverter(Schema.createUnion(remainingUnionTypes.asJava), sqlType, path)
}
} else avroSchema.getTypes.asScala.map(_.getType) match {
case Seq(t1) => createConverter(avroSchema.getTypes.get(0), sqlType, path)
case Seq(a, b) if Set(a, b) == Set(INT, LONG) && sqlType == LongType =>
(item: AnyRef) => {
item match {
case null => null
case l: java.lang.Long => l
case i: java.lang.Integer => new java.lang.Long(i.longValue())
}
}
case Seq(a, b) if Set(a, b) == Set(FLOAT, DOUBLE) && sqlType == DoubleType =>
(item: AnyRef) => {
item match {
case null => null
case d: java.lang.Double => d
case f: java.lang.Float => new java.lang.Double(f.doubleValue())
}
}
case other =>
sqlType match {
case t: StructType if t.fields.length == avroSchema.getTypes.size =>
val fieldConverters = t.fields.zip(avroSchema.getTypes.asScala).map {
case (field, schema) =>
createConverter(schema, field.dataType, path :+ field.name)
}
(item: AnyRef) => if (item == null) {
null
} else {
val i = GenericData.get().resolveUnion(avroSchema, item)
val converted = new Array[Any](fieldConverters.length)
converted(i) = fieldConverters(i)(item)
new GenericRow(converted)
}
case _ => throw new IncompatibleSchemaException(
s"Cannot convert Avro schema to catalyst type because schema at path " +
s"${path.mkString(".")} is not compatible " +
s"(avroType = $other, sqlType = $sqlType). \n" +
s"Source Avro schema: $sourceAvroSchema.\n" +
s"Target Catalyst type: $targetSqlType")
}
}
case (left, right) =>
throw new IncompatibleSchemaException(
s"Cannot convert Avro schema to catalyst type because schema at path " +
s"${path.mkString(".")} is not compatible (avroType = $left, sqlType = $right). \n" +
s"Source Avro schema: $sourceAvroSchema.\n" +
s"Target Catalyst type: $targetSqlType")
}
}
createConverter(sourceAvroSchema, targetSqlType, List.empty[String])
}
def createConverterToAvro(dataType: DataType,
structName: String,
recordNamespace: String): Any => Any = {
dataType match {
case BinaryType => (item: Any) =>
item match {
case null => null
case bytes: Array[Byte] => ByteBuffer.wrap(bytes)
}
case IntegerType | LongType |
FloatType | DoubleType | StringType | BooleanType => identity
case ByteType => (item: Any) =>
if (item == null) null else item.asInstanceOf[Byte].intValue
case ShortType => (item: Any) =>
if (item == null) null else item.asInstanceOf[Short].intValue
case _: DecimalType => (item: Any) => if (item == null) null else item.toString
case TimestampType => (item: Any) =>
if (item == null) null else item.asInstanceOf[Timestamp].getTime
case DateType => (item: Any) =>
if (item == null) null else item.asInstanceOf[Date].getTime
case ArrayType(elementType, _) =>
val elementConverter = createConverterToAvro(
elementType,
structName,
getNewRecordNamespace(elementType, recordNamespace, structName))
(item: Any) => {
if (item == null) {
null
} else {
val sourceArray = item.asInstanceOf[Seq[Any]]
val sourceArraySize = sourceArray.size
val targetList = new util.ArrayList[Any](sourceArraySize)
var idx = 0
while (idx < sourceArraySize) {
targetList.add(elementConverter(sourceArray(idx)))
idx += 1
}
targetList
}
}
case MapType(StringType, valueType, _) =>
val valueConverter = createConverterToAvro(
valueType,
structName,
getNewRecordNamespace(valueType, recordNamespace, structName))
(item: Any) => {
if (item == null) {
null
} else {
val javaMap = new util.HashMap[String, Any]()
item.asInstanceOf[Map[String, Any]].foreach { case (key, value) =>
javaMap.put(key, valueConverter(value))
}
javaMap
}
}
case structType: StructType =>
val builder = SchemaBuilder.record(structName).namespace(recordNamespace)
val schema: Schema = SchemaConverters.convertStructToAvro(
structType, builder, recordNamespace)
val fieldConverters = structType.fields.map(field =>
createConverterToAvro(
field.dataType,
field.name,
getNewRecordNamespace(field.dataType, recordNamespace, field.name)))
(item: Any) => {
if (item == null) {
null
} else {
val record = new Record(schema)
val convertersIterator = fieldConverters.iterator
val fieldNamesIterator = dataType.asInstanceOf[StructType].fieldNames.iterator
val rowIterator = item.asInstanceOf[Row].toSeq.iterator
while (convertersIterator.hasNext) {
val converter = convertersIterator.next()
record.put(fieldNamesIterator.next(), converter(rowIterator.next()))
}
record
}
}
}
}
def convertStructTypeToAvroSchema(structType: StructType,
structName: String,
recordNamespace: String): Schema = {

4
hudi-utilities/src/main/java/org/apache/hudi/utilities/sources/helpers/AvroConvertor.java
View File

@@ -75,7 +75,7 @@ public class AvroConvertor implements Serializable {
private void initJsonConvertor() {
if (jsonConverter == null) {
jsonConverter = new MercifulJsonConverter(schema);
jsonConverter = new MercifulJsonConverter();
}
}
@@ -83,7 +83,7 @@ public class AvroConvertor implements Serializable {
public GenericRecord fromJson(String json) throws IOException {
initSchema();
initJsonConvertor();
return jsonConverter.convert(json);
return jsonConverter.convert(json, schema);
}
public Schema getSchema() {

31
hudi-utilities/src/test/java/org/apache/hudi/utilities/TestHoodieDeltaStreamer.java
View File

@@ -25,6 +25,7 @@ import static org.junit.Assert.fail;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
import java.util.concurrent.TimeUnit;
@@ -529,31 +530,17 @@ public class TestHoodieDeltaStreamer extends UtilitiesTestBase {
public static class DistanceUDF implements UDF4<Double, Double, Double, Double, Double> {
/**
* Taken from https://stackoverflow.com/questions/3694380/calculating-distance-between-two-points-using-latitude-
* longitude-what-am-i-doi Calculate distance between two points in latitude and longitude taking into account
* height difference. If you are not interested in height difference pass 0.0. Uses Haversine method as its base.
*
* lat1, lon1 Start point lat2, lon2 End point el1 Start altitude in meters el2 End altitude in meters
*
* @returns Distance in Meters
* Returns some random number as distance between the points
*
* @param lat1 Latitiude of source
* @param lat2 Latitude of destination
* @param lon1 Longitude of source
* @param lon2 Longitude of destination
* @return
*/
@Override
public Double call(Double lat1, Double lat2, Double lon1, Double lon2) {
final int R = 6371; // Radius of the earth
double latDistance = Math.toRadians(lat2 - lat1);
double lonDistance = Math.toRadians(lon2 - lon1);
double a = Math.sin(latDistance / 2) * Math.sin(latDistance / 2) + Math.cos(Math.toRadians(lat1))
* Math.cos(Math.toRadians(lat2)) * Math.sin(lonDistance / 2) * Math.sin(lonDistance / 2);
double c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1 - a));
double distance = R * c * 1000; // convert to meters
double height = 0;
distance = Math.pow(distance, 2) + Math.pow(height, 2);
return Math.sqrt(distance);
return new Random().nextDouble();
}
}

7
pom.xml
View File

@@ -170,6 +170,8 @@
</execution>
</executions>
</plugin>
<!--
See https://jira.apache.org/jira/browse/HUDI-304
<plugin>
<groupId>com.diffplug.spotless</groupId>
<artifactId>spotless-maven-plugin</artifactId>
@@ -182,13 +184,11 @@
</eclipse>
</java>
<scala>
<!--<endWithNewLine/>-->
<trimTrailingWhitespace/>
</scala>
</configuration>
<executions>
<execution>
<!-- Runs in compile phase to fail fast in case of formatting issues.-->
<id>spotless-check</id>
<phase>compile</phase>
<goals>
@@ -197,6 +197,7 @@
</execution>
</executions>
</plugin>
-->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
@@ -345,7 +346,7 @@
<exclude>**/dependency-reduced-pom.xml</exclude>
<exclude>**/test/resources/*.data</exclude>
<exclude>**/target/**</exclude>
<excludes>**/generated-sources/**</excludes>
<exclude>**/generated-sources/**</exclude>
</excludes>
</configuration>
<executions>

353
style/eclipse-java-google-style.xml
View File

@@ -1,353 +0,0 @@
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<!--
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.
-->
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</profile>
</profiles>

614
style/intellij-java-google-style.xml
View File

@@ -1,614 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<!--
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
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