I was looking at a flame graph of an ingestion workload with @dliappis, and it looks like we parse the JSON representation of the index request twice when a document has both a pipeline and a final pipeline.

It's hard to know how much we would save on this benchmark since not all data streams in this benchmark had both a pipeline and a final pipeline, but the cost of parsing index request into maps of maps via IngestService represented 4.06% of overall CPU time according to the flame graph, so this might not be negligible.
server/src/test/java/org/elasticsearch/ingest/IngestServiceTests.java
import org.elasticsearch.threadpool.ThreadPool.Names;
import org.elasticsearch.xcontent.XContentBuilder;
import org.elasticsearch.xcontent.XContentType;
import org.elasticsearch.xcontent.cbor.CborXContent;
import org.junit.Before;
import org.mockito.ArgumentMatcher;
import org.mockito.invocation.InvocationOnMock;
import java.io.OutputStream;
import java.nio.charset.StandardCharsets;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Comparator;
import java.util.HashMap;
import java.util.List;
import java.util.Locale;
import java.util.Map;
import java.util.Objects;
import java.util.Set;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.atomic.AtomicReference;
import java.util.function.BiConsumer;
import java.util.function.Consumer;
import java.util.function.IntConsumer;
import java.util.function.LongSupplier;
import java.util.stream.Collectors;
import static org.elasticsearch.cluster.service.ClusterStateTaskExecutorUtils.executeAndAssertSuccessful;
import static org.elasticsearch.core.Tuple.tuple;
import static org.hamcrest.Matchers.containsInAnyOrder;