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
IngestService ingestService = new IngestService(
            mock(ClusterService.class),
            threadPool,
            null,
            null,
            null,
            List.of(DUMMY_PLUGIN),
            client
        );
        final IndexRequest indexRequest = new IndexRequest("_index").id("_id")
            .source(Map.of())
            .setPipeline("_id")
            .setFinalPipeline("_none");
        final SetOnce<Boolean> failure = new SetOnce<>();
        final BiConsumer<Integer, Exception> failureHandler = (slot, e) -> {
            failure.set(true);
            assertThat(slot, equalTo(0));
            assertThat(e, instanceOf(IllegalArgumentException.class));
            assertThat(e.getMessage(), equalTo("pipeline with id [_id] does not exist"));
        };
        @SuppressWarnings("unchecked")
        final BiConsumer<Thread, Exception> completionHandler = mock(BiConsumer.class);
        ingestService.executeBulkRequest(1, List.of(indexRequest), indexReq -> {}, failureHandler, completionHandler, Names.WRITE);
        assertTrue(failure.get());
        verify(completionHandler, times(1)).accept(Thread.currentThread(), null);
    }
    public void testUpdatePipelines() {
        IngestService ingestService = createWithProcessors();
        ClusterState clusterState = ClusterState.builder(new ClusterName("_name")).build();
        ClusterState previousClusterState = clusterState;