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
&& currentIngestMetadata.getPipelines().containsKey(request.getId())) {
            var pipelineConfig = XContentHelper.convertToMap(request.getSource(), false, request.getXContentType()).v2();
            var currentPipeline = currentIngestMetadata.getPipelines().get(request.getId());
            if (currentPipeline.getConfigAsMap().equals(pipelineConfig)) {
                return true;
            }
        }
        return false;
    }
    /**
     * Returns the pipeline by the specified id
     */
    public Pipeline getPipeline(String id) {
        PipelineHolder holder = pipelines.get(id);
        if (holder != null) {
            return holder.pipeline;
        } else {
            return null;
        }
    }
    public Map<String, Processor.Factory> getProcessorFactories() {
        return processorFactories;
    }
    @Override
    public IngestInfo info() {
        Map<String, Processor.Factory> processorFactories = getProcessorFactories();
        List<ProcessorInfo> processorInfoList = new ArrayList<>(processorFactories.size());
        for (Map.Entry<String, Processor.Factory> entry : processorFactories.entrySet()) {
            processorInfoList.add(new ProcessorInfo(entry.getKey()));
        }