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 = createWithProcessors(
            Map.of(
                "mock",
                (factories, tag, description, config) -> mockCompoundProcessor(),
                "set",
                (factories, tag, description, config) -> new FakeProcessor(
                    "set",
                    tag,
                    description,
                    
                    (ingestDocument) -> ingestDocument.setFieldValue(TimestampField.FIXED_TIMESTAMP_FIELD, 100)
                )
            )
        );
        PutPipelineRequest putRequest1 = new PutPipelineRequest(
            "_id1",
            new BytesArray("{\"processors\": [{\"mock\" : {}}]}"),
            XContentType.JSON
        );
        PutPipelineRequest putRequest2 = new PutPipelineRequest(
            "_id2",
            new BytesArray("{\"processors\": [{\"set\" : {}}]}"),
            XContentType.JSON
        );
        ClusterState clusterState = ClusterState.builder(new ClusterName("_name")).build(); 
        ClusterState previousClusterState = clusterState;
        clusterState = executePut(putRequest1, clusterState);
        clusterState = executePut(putRequest2, clusterState);
        ingestService.applyClusterState(new ClusterChangedEvent("", clusterState, previousClusterState));