kafka ValueAndTimestampSerializer 源码

  • 2022-10-20
  • 浏览 (244)

kafka ValueAndTimestampSerializer 代码

文件路径:/streams/src/main/java/org/apache/kafka/streams/state/internals/ValueAndTimestampSerializer.java

/*
 * 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.kafka.streams.state.internals;

import org.apache.kafka.common.serialization.LongSerializer;
import org.apache.kafka.common.serialization.Serializer;
import org.apache.kafka.streams.kstream.internals.WrappingNullableSerializer;
import org.apache.kafka.streams.processor.internals.SerdeGetter;
import org.apache.kafka.streams.state.ValueAndTimestamp;

import java.nio.ByteBuffer;
import java.util.Map;
import java.util.Objects;

import static org.apache.kafka.streams.kstream.internals.WrappingNullableUtils.initNullableSerializer;

public class ValueAndTimestampSerializer<V> implements WrappingNullableSerializer<ValueAndTimestamp<V>, Void, V> {
    public final Serializer<V> valueSerializer;
    private final Serializer<Long> timestampSerializer;

    ValueAndTimestampSerializer(final Serializer<V> valueSerializer) {
        Objects.requireNonNull(valueSerializer);
        this.valueSerializer = valueSerializer;
        timestampSerializer = new LongSerializer();
    }

    public static boolean valuesAreSameAndTimeIsIncreasing(final byte[] oldRecord, final byte[] newRecord) {
        if (oldRecord == newRecord) {
            // same reference, so they are trivially the same (might both be null)
            return true;
        } else if (oldRecord == null || newRecord == null) {
            // only one is null, so they cannot be the same
            return false;
        } else if (newRecord.length != oldRecord.length) {
            // they are different length, so they cannot be the same
            return false;
        } else if (timeIsDecreasing(oldRecord, newRecord)) {
            // the record time represents the beginning of the validity interval, so if the time
            // moves backwards, we need to do the update regardless of whether the value has changed
            return false;
        } else {
            // all other checks have fallen through, so we actually compare the binary data of the two values
            return valuesAreSame(oldRecord, newRecord);
        }
    }

    @Override
    public void configure(final Map<String, ?> configs,
                          final boolean isKey) {
        valueSerializer.configure(configs, isKey);
        timestampSerializer.configure(configs, isKey);
    }

    @Override
    public byte[] serialize(final String topic,
                            final ValueAndTimestamp<V> data) {
        if (data == null) {
            return null;
        }
        return serialize(topic, data.value(), data.timestamp());
    }

    public byte[] serialize(final String topic,
                            final V data,
                            final long timestamp) {
        if (data == null) {
            return null;
        }
        final byte[] rawValue = valueSerializer.serialize(topic, data);

        // Since we can't control the result of the internal serializer, we make sure that the result
        // is not null as well.
        // Serializing non-null values to null can be useful when working with Optional-like values
        // where the Optional.empty case is serialized to null.
        // See the discussion here: https://github.com/apache/kafka/pull/7679
        if (rawValue == null) {
            return null;
        }

        final byte[] rawTimestamp = timestampSerializer.serialize(topic, timestamp);
        return ByteBuffer
            .allocate(rawTimestamp.length + rawValue.length)
            .put(rawTimestamp)
            .put(rawValue)
            .array();
    }

    @Override
    public void close() {
        valueSerializer.close();
        timestampSerializer.close();
    }

    private static boolean timeIsDecreasing(final byte[] oldRecord, final byte[] newRecord) {
        return extractTimestamp(newRecord) <= extractTimestamp(oldRecord);
    }

    private static long extractTimestamp(final byte[] bytes) {
        final byte[] timestampBytes = new byte[Long.BYTES];
        System.arraycopy(bytes, 0, timestampBytes, 0, Long.BYTES);
        return ByteBuffer.wrap(timestampBytes).getLong();
    }

    private static boolean valuesAreSame(final byte[] left, final byte[] right) {
        for (int i = Long.BYTES; i < left.length; i++) {
            if (left[i] != right[i]) {
                return false;
            }
        }
        return true;
    }

    @Override
    public void setIfUnset(final SerdeGetter getter) {
        // ValueAndTimestampSerializer never wraps a null serializer (or configure would throw),
        // but it may wrap a serializer that itself wraps a null serializer.
        initNullableSerializer(valueSerializer, getter);
    }
}

相关信息

kafka 源码目录

相关文章

kafka AbstractDualSchemaRocksDBSegmentedBytesStore 源码

kafka AbstractMergedSortedCacheStoreIterator 源码

kafka AbstractRocksDBSegmentedBytesStore 源码

kafka AbstractRocksDBTimeOrderedSegmentedBytesStore 源码

kafka AbstractSegments 源码

kafka AbstractStoreBuilder 源码

kafka BatchWritingStore 源码

kafka BlockBasedTableConfigWithAccessibleCache 源码

kafka BufferKey 源码

kafka BufferValue 源码

0  赞