Data not getting reflected in transform index

[jainesh_singh]

Hi Team,
We have configured Elasticsearch along with logstash.

Our setup is:
There is a data stream with the following mapping:

@timestamp (ingest generated by logstash) 
	{

		"id": "1", 	    
		"activityTime": "2023-03-09T02:11:57.000Z",   
		"activity": "activity_1", //This will be unique values
		"@timestamp": "2023-04-19T20:11:00.547341200Z"
	}

We have a monthly transform:

	PUT _transform/irm-activity-index-monthly-transform
		{
			"description": "IRM transform for monthly data",
			"source": {
				"index": [
					"sourve_name"
				]
			},
			"dest": {
				"index": "dest_name"
			},
			"frequency": "60s",
			"sync": {
				"time": {
					"field": "@timestamp",
					"delay": "60s"
				}
			},
			"pivot": 
			{
				"group_by": 
				{
					"activityTime": {
						"date_histogram": {
							"field": "activityTime",
							"calendar_interval": "1M"
						}
					},
					"activity": {
						"terms": {
							"field": "activity"
						}
					}
				},
				"aggregations": {
					"totalActivitiesCount": {
						"value_count": {
							"field": "activity"
						}
					}
				}
			},
			"retention_policy": {
				"time": {
					"field": "activityTime",
					"max_age": "248d"
				}
			}
		}

Point to note:
	The sync is on @timestamp field and the date histogram on per month is configured on activityTime as given above.
	@timestamp is generated by logstash. Also a point to note for miliseconds, In some cases it is upto 9 digit precision whereas in some cases it is upto 6 digit  precision.
	Activitytime is not sequential. Backdated activities can also come.

Issue:
Lets say we have following activites in the following format:
"activityTime" : "2023-01-01T04:33:15.000Z"
"activityTime" : "2023-01-02T04:33:15.000Z"
"activityTime" : "2023-01-29T04:33:15.000Z"
"activityTime" : "2023-01-30T04:33:15.000Z"
This get correctly aggregated.
But in next cycle if the following activity comes,
"activityTime" :"2023-01-15T04:33:15.000Z"
Then the transform contains only 3 entries, i.e. for 1Jan,2Jan and 15 Jan.
It does not consider 29th and 30th Jan while computing which is leading to incorrect aggregation result.