public ProducerRecord serialize()

in flink-connector-kafka/src/main/java/org/apache/flink/streaming/connectors/kafka/table/DynamicKafkaRecordSerializationSchema.java [75:130]
51 lines of code
7 McCabe index (conditional complexity)

    public ProducerRecord<byte[], byte[]> serialize(
            RowData consumedRow, KafkaSinkContext context, Long timestamp) {
        // shortcut in case no input projection is required
        if (keySerialization == null && !hasMetadata) {
            final byte[] valueSerialized = valueSerialization.serialize(consumedRow);
            return new ProducerRecord<>(
                    topic,
                    extractPartition(
                            consumedRow,
                            null,
                            valueSerialized,
                            context.getPartitionsForTopic(topic)),
                    null,
                    valueSerialized);
        }
        final byte[] keySerialized;
        if (keySerialization == null) {
            keySerialized = null;
        } else {
            final RowData keyRow = createProjectedRow(consumedRow, RowKind.INSERT, keyFieldGetters);
            keySerialized = keySerialization.serialize(keyRow);
        }

        final byte[] valueSerialized;
        final RowKind kind = consumedRow.getRowKind();
        if (upsertMode) {
            if (kind == RowKind.DELETE || kind == RowKind.UPDATE_BEFORE) {
                // transform the message as the tombstone message
                valueSerialized = null;
            } else {
                // make the message to be INSERT to be compliant with the INSERT-ONLY format
                final RowData valueRow =
                        DynamicKafkaRecordSerializationSchema.createProjectedRow(
                                consumedRow, kind, valueFieldGetters);
                valueRow.setRowKind(RowKind.INSERT);
                valueSerialized = valueSerialization.serialize(valueRow);
            }
        } else {
            final RowData valueRow =
                    DynamicKafkaRecordSerializationSchema.createProjectedRow(
                            consumedRow, kind, valueFieldGetters);
            valueSerialized = valueSerialization.serialize(valueRow);
        }

        return new ProducerRecord<>(
                topic,
                extractPartition(
                        consumedRow,
                        keySerialized,
                        valueSerialized,
                        context.getPartitionsForTopic(topic)),
                readMetadata(consumedRow, KafkaDynamicSink.WritableMetadata.TIMESTAMP),
                keySerialized,
                valueSerialized,
                readMetadata(consumedRow, KafkaDynamicSink.WritableMetadata.HEADERS));
    }