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
);
        {
            
            final IngestStats ingestStats = ingestService.stats();
            assertThat(ingestStats.getPipelineStats().size(), equalTo(0));
            assertStats(ingestStats.getTotalStats(), 0, 0, 0);
        }
        
        PutPipelineRequest putRequest1 = new PutPipelineRequest(
            "_id1",
            new BytesArray("{\"processors\": [{\"mock\" : {}}]}"),
            XContentType.JSON
        );
        
        PutPipelineRequest putRequest2 = new PutPipelineRequest(
            "_id2",
            new BytesArray("{\"processors\": [{\"pipeline\" : {}}]}"),
            XContentType.JSON
        );
        PutPipelineRequest putRequest3 = new PutPipelineRequest(
            "_id3",
            new BytesArray("{\"processors\": [{\"mock\" : {}}]}"),
            XContentType.JSON
        );
        ClusterState clusterState = ClusterState.builder(new ClusterName("_name")).build(); 
        ClusterState previousClusterState = clusterState;
        clusterState = executePut(putRequest1, clusterState);
        clusterState = executePut(putRequest2, clusterState);
        clusterState = executePut(putRequest3, clusterState);
        ingestService.applyClusterState(new ClusterChangedEvent("", clusterState, previousClusterState));