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
if (type.equals(oldType)) {
                                metric.add(oldMetric);
                            }
                        }
                    }
                }
            } catch (ElasticsearchParseException e) {
                Pipeline pipeline = substitutePipeline(newConfiguration.getId(), e);
                newPipelines.put(newConfiguration.getId(), new PipelineHolder(newConfiguration, pipeline));
                if (exceptions == null) {
                    exceptions = new ArrayList<>();
                }
                exceptions.add(e);
            } catch (Exception e) {
                ElasticsearchParseException parseException = new ElasticsearchParseException(
                    "Error updating pipeline with id [" + newConfiguration.getId() + "]",
                    e
                );
                Pipeline pipeline = substitutePipeline(newConfiguration.getId(), parseException);
                newPipelines.put(newConfiguration.getId(), new PipelineHolder(newConfiguration, pipeline));
                if (exceptions == null) {
                    exceptions = new ArrayList<>();
                }
                exceptions.add(parseException);
            }
        }
        
        
        for (Map.Entry<String, PipelineHolder> entry : existingPipelines.entrySet()) {
            if (newIngestMetadata.getPipelines().get(entry.getKey()) == null) {