JingsongLi commented on a change in pull request #17520: URL: https://github.com/apache/flink/pull/17520#discussion_r739763596
########## File path: flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/AbstractAvroBulkFormat.java ########## @@ -0,0 +1,207 @@ +/* + * 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.flink.formats.avro; + +import org.apache.flink.annotation.Internal; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.connector.file.src.FileSourceSplit; +import org.apache.flink.connector.file.src.reader.BulkFormat; +import org.apache.flink.connector.file.src.util.CheckpointedPosition; +import org.apache.flink.connector.file.src.util.IteratorResultIterator; +import org.apache.flink.connector.file.src.util.Pool; +import org.apache.flink.core.fs.FileSystem; +import org.apache.flink.core.fs.Path; +import org.apache.flink.formats.avro.utils.FSDataInputStreamWrapper; + +import org.apache.avro.Schema; +import org.apache.avro.file.DataFileReader; +import org.apache.avro.file.SeekableInput; +import org.apache.avro.generic.GenericDatumReader; +import org.apache.avro.io.DatumReader; + +import javax.annotation.Nullable; + +import java.io.IOException; +import java.util.Iterator; + +/** Provides a {@link BulkFormat} for Avro records. */ +@Internal +public abstract class AbstractAvroBulkFormat<A, T, SplitT extends FileSourceSplit> + implements BulkFormat<T, SplitT> { + + private static final long serialVersionUID = 1L; + + protected final Schema readerSchema; + + protected AbstractAvroBulkFormat(Schema readerSchema) { + this.readerSchema = readerSchema; + } + + @Override + public AvroReader createReader(Configuration config, SplitT split) throws IOException { + open(split); + return createReader(split); + } + + @Override + public AvroReader restoreReader(Configuration config, SplitT split) throws IOException { + open(split); + return createReader(split); + } + + @Override + public boolean isSplittable() { + return true; + } + + private AvroReader createReader(SplitT split) throws IOException { + long end = split.offset() + split.length(); + if (split.getReaderPosition().isPresent()) { + CheckpointedPosition position = split.getReaderPosition().get(); + return new AvroReader( + split.path(), + split.offset(), + end, + position.getOffset(), + position.getRecordsAfterOffset()); + } else { + return new AvroReader(split.path(), split.offset(), end, -1, 0); + } + } + + protected void open(SplitT split) {} + + protected abstract T convert(A record); + + protected abstract A createReusedAvroRecord(); + + private class AvroReader implements BulkFormat.Reader<T> { + + private final DataFileReader<A> reader; + + private final long end; + private final Pool<A> pool; + + private long currentBlockStart; + private long currentRecordsToSkip; + + private AvroReader(Path path, long offset, long end, long blockStart, long recordsToSkip) + throws IOException { + A reuse = createReusedAvroRecord(); + + this.reader = createReaderFromPath(path); + if (blockStart >= 0) { + reader.seek(blockStart); + } else { + reader.sync(offset); + } + for (int i = 0; i < recordsToSkip; i++) { + reader.next(reuse); + } + + this.end = end; + this.pool = new Pool<>(1); Review comment: +1 to do some benchmark. If we can increase the pool size of parquet is good. But I don't think increasing pool size means increasing performance. When we look at performance, we really look at efficiency, not pure throughput. Flink is a distributed computing system, which means that we can and should increase parallelism to obtain greater throughput, rather than tangle with a single parallelism throughput. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
