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/main/java/org/elasticsearch/ingest/IngestService.java
import org.elasticsearch.index.analysis.AnalysisRegistry;
import org.elasticsearch.node.ReportingService;
import org.elasticsearch.plugins.IngestPlugin;
import org.elasticsearch.script.ScriptService;
import org.elasticsearch.threadpool.ThreadPool;
import org.elasticsearch.xcontent.XContentBuilder;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.LinkedList;
import java.util.List;
import java.util.Locale;
import java.util.Map;
import java.util.Objects;
import java.util.Set;
import java.util.concurrent.CopyOnWriteArrayList;
import java.util.function.BiConsumer;
import java.util.function.Consumer;
import java.util.function.IntConsumer;
import java.util.function.Predicate;
import java.util.stream.Collectors;
import static org.elasticsearch.core.Strings.format;
/**
 * Holder class for several ingest related services.
 */
public class IngestService implements ClusterStateApplier, ReportingService<IngestInfo> {