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
Map<String, String> mergedDynamicTemplates = new HashMap<>(request.getDynamicTemplates());
            mergedDynamicTemplates.putAll(map);
            request.setDynamicTemplates(mergedDynamicTemplates);
        }
    }
    /**
     * Updates an index request based on the source of an ingest document, guarding against self-references if necessary.
     */
    private static void updateIndexRequestSource(final IndexRequest request, final IngestDocument document) {
        boolean ensureNoSelfReferences = document.doNoSelfReferencesCheck();
        request.source(document.getSource(), request.getContentType(), ensureNoSelfReferences);
    }
    /**
     * Grab the @timestamp and store it on the index request so that TSDB can use it without needing to parse
     * the source for this document.
     */
    private static void cacheRawTimestamp(final IndexRequest request, final IngestDocument document) {
        if (request.getRawTimestamp() == null) {
            
            Object rawTimestamp = document.getSource().get(TimestampField.FIXED_TIMESTAMP_FIELD);
            if (rawTimestamp != null) {
                request.setRawTimestamp(rawTimestamp);
            }
        }
    }
    @Override
    public void applyClusterState(final ClusterChangedEvent event) {
        state = event.state();
        if (state.blocks().hasGlobalBlock(GatewayService.STATE_NOT_RECOVERED_BLOCK)) {
            return;