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/*
* 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.io.storage;
import org.apache.hudi.common.bloom.BloomFilter;
import org.apache.hudi.common.model.HoodieAvroIndexedRecord;
import org.apache.hudi.common.model.HoodieFileFormat;
import org.apache.hudi.common.model.HoodieRecord;
import org.apache.hudi.common.util.BaseFileUtils;
import org.apache.hudi.common.util.ClosableIterator;
import org.apache.hudi.common.util.MappingIterator;
import org.apache.hudi.common.util.Option;
import org.apache.hudi.common.util.ParquetReaderIterator;
import org.apache.avro.Schema;
import org.apache.avro.generic.IndexedRecord;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.parquet.avro.AvroReadSupport;
import org.apache.parquet.avro.AvroSchemaConverter;
import org.apache.parquet.avro.HoodieAvroParquetReaderBuilder;
import org.apache.parquet.hadoop.ParquetInputFormat;
import org.apache.parquet.hadoop.ParquetReader;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Set;
import static org.apache.hudi.common.util.TypeUtils.unsafeCast;
/**
* {@link HoodieFileReader} implementation for parquet format.
*
* @param Record implementation that permits field access by integer index.
*/
public class HoodieAvroParquetReader extends HoodieAvroFileReaderBase {
private final Path path;
private final Configuration conf;
private final BaseFileUtils parquetUtils;
private final List readerIterators = new ArrayList<>();
public HoodieAvroParquetReader(Configuration configuration, Path path) {
// We have to clone the Hadoop Config as it might be subsequently modified
// by the Reader (for proper config propagation to Parquet components)
this.conf = tryOverrideDefaultConfigs(new Configuration(configuration));
this.path = path;
this.parquetUtils = BaseFileUtils.getInstance(HoodieFileFormat.PARQUET);
}
@Override
public ClosableIterator> getRecordIterator(Schema readerSchema) throws IOException {
// TODO(HUDI-4588) remove after HUDI-4588 is resolved
// NOTE: This is a workaround to avoid leveraging projection w/in [[AvroParquetReader]],
// until schema handling issues (nullability canonicalization, etc) are resolved
ClosableIterator iterator = getIndexedRecordIterator(readerSchema);
return new MappingIterator<>(iterator, data -> unsafeCast(new HoodieAvroIndexedRecord(data)));
}
@Override
public String[] readMinMaxRecordKeys() {
return parquetUtils.readMinMaxRecordKeys(conf, path);
}
@Override
public BloomFilter readBloomFilter() {
return parquetUtils.readBloomFilterFromMetadata(conf, path);
}
@Override
public Set filterRowKeys(Set candidateRowKeys) {
return parquetUtils.filterRowKeys(conf, path, candidateRowKeys);
}
@Override
protected ClosableIterator getIndexedRecordIterator(Schema schema) throws IOException {
return getIndexedRecordIteratorInternal(schema, Option.empty());
}
@Override
protected ClosableIterator getIndexedRecordIterator(Schema readerSchema, Schema requestedSchema) throws IOException {
return getIndexedRecordIteratorInternal(readerSchema, Option.of(requestedSchema));
}
@Override
public Schema getSchema() {
return parquetUtils.readAvroSchema(conf, path);
}
@Override
public void close() {
readerIterators.forEach(ParquetReaderIterator::close);
}
@Override
public long getTotalRecords() {
return parquetUtils.getRowCount(conf, path);
}
private static Configuration tryOverrideDefaultConfigs(Configuration conf) {
// NOTE: Parquet uses elaborate encoding of the arrays/lists with optional types,
// following structure will be representing such list in Parquet:
//
// optional group tip_history (LIST) {
// repeated group list {
// optional group element {
// optional double amount;
// optional binary currency (STRING);
// }
// }
// }
//
// To designate list, special logical-type annotation (`LIST`) is used,
// as well additional [[GroupType]] with the name "list" is wrapping
// the "element" type (representing record stored inside the list itself).
//
// By default [[AvroSchemaConverter]] would be interpreting any {@code REPEATED}
// Parquet [[GroupType]] as list, skipping the checks whether additional [[GroupType]]
// (named "list") is actually wrapping the "element" type therefore incorrectly
// converting it into an additional record-wrapper (instead of simply omitting it).
// To work this around we're
// - Checking whether [[AvroSchemaConverter.ADD_LIST_ELEMENT_RECORDS]] has been
// explicitly set in the Hadoop Config
// - In case it's not, we override the default value from "true" to "false"
//
if (conf.get(AvroSchemaConverter.ADD_LIST_ELEMENT_RECORDS) == null) {
conf.set(AvroSchemaConverter.ADD_LIST_ELEMENT_RECORDS,
"false", "Overriding default treatment of repeated groups in Parquet");
}
if (conf.get(ParquetInputFormat.STRICT_TYPE_CHECKING) == null) {
conf.set(ParquetInputFormat.STRICT_TYPE_CHECKING, "false",
"Overriding default setting of whether type-checking is strict in Parquet reader, "
+ "to enable type promotions (in schema evolution)");
}
return conf;
}
private ClosableIterator getIndexedRecordIteratorInternal(Schema schema, Option requestedSchema) throws IOException {
// NOTE: We have to set both Avro read-schema and projection schema to make
// sure that in case the file-schema is not equal to read-schema we'd still
// be able to read that file (in case projection is a proper one)
if (!requestedSchema.isPresent()) {
AvroReadSupport.setAvroReadSchema(conf, schema);
AvroReadSupport.setRequestedProjection(conf, schema);
} else {
AvroReadSupport.setAvroReadSchema(conf, requestedSchema.get());
AvroReadSupport.setRequestedProjection(conf, requestedSchema.get());
}
ParquetReader reader = new HoodieAvroParquetReaderBuilder(path).withConf(conf).build();
ParquetReaderIterator parquetReaderIterator = new ParquetReaderIterator<>(reader);
readerIterators.add(parquetReaderIterator);
return parquetReaderIterator;
}
}
