Since #87849 and #88534 it is possible that anomaly detection jobs and datafeeds will encounter the `aggregate_metric_double` type.

We need to investigate how this will affect certain aspects of their behaviour:

1. Specifying detector fields when the datafeed is using an aggregation
2. Specifying detector fields when the datafeed is not using an aggregation
3. Ability to switch a datafeed between using an aggregation and not using an aggregation without deleting and recreating the job
4. Correct identification of whether to use `_source` or doc values to get values from `aggregate_metric_double` fields
5. How to appropriately set `summary_count_field` when using `aggregate_metric_double`

Based on this investigation decide what changes we should make to either code or documentation.
x-pack/plugin/ml/qa/native-multi-node-tests/src/javaRestTest/java/org/elasticsearch/xpack/ml/integration/DatafeedJobsIT.java
job.getId() + "-datafeed",
            job.getId(),
            Collections.singletonList("datafeed_data_stream")
        );
        putDatafeed(datafeedConfig);
        startDatafeed(datafeedConfig.getId(), 0L, now);
        assertBusy(() -> {
            DataCounts dataCounts = getDataCounts(job.getId());
            assertThat(dataCounts.getProcessedRecordCount(), equalTo(numDocs));
            assertThat(dataCounts.getOutOfOrderTimeStampCount(), equalTo(0L));
            GetDatafeedsStatsAction.Request request = new GetDatafeedsStatsAction.Request(datafeedConfig.getId());
            GetDatafeedsStatsAction.Response response = client().execute(GetDatafeedsStatsAction.INSTANCE, request).actionGet();
            assertThat(response.getResponse().results().get(0).getDatafeedState(), equalTo(DatafeedState.STOPPED));
        }, 60, TimeUnit.SECONDS);
        waitUntilJobIsClosed(job.getId());
    }
    public void testLookbackOnlyRuntimeMapping() throws Exception {
        client().admin().indices().prepareCreate("data-1").setMapping("time", "type=date").get();
        long numDocs = randomIntBetween(32, 2048);
        long now = System.currentTimeMillis();
        long oneWeekAgo = now - 604800000;
        long twoWeeksAgo = oneWeekAgo - 604800000;
        indexDocs(logger, "data-1", numDocs, twoWeeksAgo, oneWeekAgo);
        DataDescription.Builder dataDescription = new DataDescription.Builder();
        Detector.Builder d = new Detector.Builder("count", null);
        
        
        d.setByFieldName("day_of_week");
        AnalysisConfig.Builder analysisConfig = new AnalysisConfig.Builder(Collections.singletonList(d.build()));
        analysisConfig.setBucketSpan(TimeValue.timeValueHours(1));