kafka KStreamKTableJoinProcessor 源码

kafka KStreamKTableJoinProcessor 代码

文件路径：/streams/src/main/java/org/apache/kafka/streams/kstream/internals/KStreamKTableJoinProcessor.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.kstream.internals;

import org.apache.kafka.common.metrics.Sensor;
import org.apache.kafka.streams.kstream.KeyValueMapper;
import org.apache.kafka.streams.kstream.ValueJoinerWithKey;
import org.apache.kafka.streams.processor.api.ContextualProcessor;
import org.apache.kafka.streams.processor.api.ProcessorContext;
import org.apache.kafka.streams.processor.api.Record;
import org.apache.kafka.streams.processor.api.RecordMetadata;
import org.apache.kafka.streams.processor.internals.metrics.StreamsMetricsImpl;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import static org.apache.kafka.streams.processor.internals.metrics.TaskMetrics.droppedRecordsSensor;
import static org.apache.kafka.streams.state.ValueAndTimestamp.getValueOrNull;

class KStreamKTableJoinProcessor<K1, K2, V1, V2, VOut> extends ContextualProcessor<K1, V1, K1, VOut> {
    private static final Logger LOG = LoggerFactory.getLogger(KStreamKTableJoin.class);

    private final KTableValueGetter<K2, V2> valueGetter;
    private final KeyValueMapper<? super K1, ? super V1, ? extends K2> keyMapper;
    private final ValueJoinerWithKey<? super K1, ? super V1, ? super V2, ? extends VOut> joiner;
    private final boolean leftJoin;
    private Sensor droppedRecordsSensor;

    KStreamKTableJoinProcessor(final KTableValueGetter<K2, V2> valueGetter,
                               final KeyValueMapper<? super K1, ? super V1, ? extends K2> keyMapper,
                               final ValueJoinerWithKey<? super K1, ? super V1, ? super V2, ? extends VOut> joiner,
                               final boolean leftJoin) {
        this.valueGetter = valueGetter;
        this.keyMapper = keyMapper;
        this.joiner = joiner;
        this.leftJoin = leftJoin;
    }

    @Override
    public void init(final ProcessorContext<K1, VOut> context) {
        super.init(context);
        final StreamsMetricsImpl metrics = (StreamsMetricsImpl) context.metrics();
        droppedRecordsSensor = droppedRecordsSensor(Thread.currentThread().getName(), context.taskId().toString(), metrics);
        valueGetter.init(context);
    }

    @Override
    public void process(final Record<K1, V1> record) {
        // we do join iff the join keys are equal, thus, if {@code keyMapper} returns {@code null} we
        // cannot join and just ignore the record. Note for KTables, this is the same as having a null key
        // since keyMapper just returns the key, but for GlobalKTables we can have other keyMappers
        //
        // we also ignore the record if value is null, because in a key-value data model a null-value indicates
        // an empty message (ie, there is nothing to be joined) -- this contrast SQL NULL semantics
        // furthermore, on left/outer joins 'null' in ValueJoiner#apply() indicates a missing record --
        // thus, to be consistent and to avoid ambiguous null semantics, null values are ignored
        final K2 mappedKey = keyMapper.apply(record.key(), record.value());
        if (mappedKey == null || record.value() == null) {
            if (context().recordMetadata().isPresent()) {
                final RecordMetadata recordMetadata = context().recordMetadata().get();
                LOG.warn(
                    "Skipping record due to null join key or value. "
                        + "topic=[{}] partition=[{}] offset=[{}]",
                    recordMetadata.topic(), recordMetadata.partition(), recordMetadata.offset()
                );
            } else {
                LOG.warn(
                    "Skipping record due to null join key or value. Topic, partition, and offset not known."
                );
            }
            droppedRecordsSensor.record();
        } else {
            final V2 value2 = getValueOrNull(valueGetter.get(mappedKey));
            if (leftJoin || value2 != null) {
                context().forward(record.withValue(joiner.apply(record.key(), record.value(), value2)));
            }
        }
    }

    @Override
    public void close() {
        valueGetter.close();
    }
}

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