Excel power query - aggregate continuous "transitive" overlapping time intervals

Question

I'm trying to aggregate the below given table 1 to table 2 with Excel power queries.

The goal is to merge continuous time intervals of the same group into a single row. For direct overlappings like event 5 and 6 this was quite easy. But this approach only merged event 1 and 2 and 2 and 3 resulting in two entries (see Table 1b).

The problem is the "transitive" dependence of e.g. event 1 with event 3 via event 2. This dependence can span more than 3 rows. So the transitive closure must be determined.

Programming it could iteratively apply the current solution until no more changes occur. But how to do it in power query?

Table 1 (original):

Event ID	Group	Start	End
1	A	20.01.2022 12:00:00	20.01.2022 12:02:00
2	A	20.01.2022 12:01:00	20.01.2022 12:04:20
3	A	20.01.2022 12:03:10	20.01.2022 12:06:00
4	A	20.01.2022 12:08:00	20.01.2022 12:10:00
5	B	20.01.2022 12:00:50	20.01.2022 12:02:00
6	B	20.01.2022 12:01:00	20.01.2022 12:05:00
7	B	20.01.2022 12:06:00	20.01.2022 12:11:00

Table 1b (current intermediate solution):

Event ID	Group	Start	End
1	A	20.01.2022 12:00:00	20.01.2022 12:04:20
2	A	20.01.2022 12:01:00	20.01.2022 12:06:00
4	A	20.01.2022 12:08:00	20.01.2022 12:10:00
5	B	20.01.2022 12:00:50	20.01.2022 12:05:00
7	B	20.01.2022 12:06:00	20.01.2022 12:11:00

Table 2 (desired result):

Event ID	Group	Start	End
1	A	20.01.2022 12:00:00	20.01.2022 12:06:00
4	A	20.01.2022 12:08:00	20.01.2022 12:10:00
5	B	20.01.2022 12:00:50	20.01.2022 12:05:00
7	B	20.01.2022 12:06:00	20.01.2022 12:11:00

Edit

Example which wasn't aggregated fully with the provided solution:

Event ID	Group	Start	End
1	A	20.01.2022 12:02:12	20.01.2022 12:05:34
2	A	20.01.2022 12:02:54	20.01.2022 12:05:37
3	A	20.01.2022 12:05:36	20.01.2022 12:05:49
4	A	20.01.2022 12:05:45	20.01.2022 12:07:22
5	A	20.01.2022 12:06:03	20.01.2022 12:06:10

results in (previous solution):

Event ID	Group	Start	End
1	A	20.01.2022 12:02:12	20.01.2022 12:07:22
5	A	20.01.2022 12:02:54	20.01.2022 12:07:22

results in (accepted answer):

Event ID	Group	Start	End
1	A	20.01.2022 12:02:12	20.01.2022 12:07:22

horseyride · Accepted Answer · 2023-07-18T12:27:38.290

EDIT See better later answer at Aggregate overlapping time intervals, calculate outage times, improve performance

Step 1: Create separate query, name it process, close and load it before proceeding

(xtable)=>
// for each group, compare each list against all lists in column Custom, and merge those that overlap
let Source= Table.Buffer(xtable),
#"Added Custom"= Table.AddColumn( 
     Source,
    "Custom2",
        each let
        begin = [Custom]
    in 
    List.Accumulate (
         Source[Custom],
         begin,
        (state,current)=> if List.ContainsAny(state,current) then List.Distinct(List.Combine({current,state})) else state
    )
),
// count the number of changes made from original version. If this is not zero, we will recurse the changes
x= List.Sum(List.Transform(List.Positions(#"Added Custom"[Custom]), each if #"Added Custom"[Custom]{_} = #"Added Custom"[Custom2]{_} then 0 else 1)),
RemovePrioCustom= Table.RemoveColumns(#"Added Custom",{"Custom"}),
AddNewCustom= Table.RenameColumns(RemovePrioCustom,{{"Custom2", "Custom"}}),
recursive = if x=0 then AddNewCustom else @process( AddNewCustom)
in recursive

Step 2: Code for table that uses above function:

let Source = Excel.CurrentWorkbook(){[Name="Table1"]}[Content],
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Start", type datetime}, {"End", type datetime}}),
#"Grouped Rows" = Table.Group(#"Changed Type" , {"Group"}, {{"data", each 
    let  #"AddIndex" = Table.AddIndexColumn(_, "Index", 0, 1, Int64.Type),
    #"Round1" = Table.AddColumn(#"AddIndex", "Custom",  (i)=>Table.SelectRows(#"AddIndex", each ([Start]>=i[Start] and [Start]<=i[End]) or  ([Start]<=i[Start] and [End]>=i[Start]) )[Index]),
    #"Round2"= process(#"Round1"),
    #"GetStart" = Table.AddColumn(#"Round2", "StartMin", each List.Min(List.Transform([Custom], each #"Round2"[Start]{_})),type datetime),
    #"GetEnd"= Table.AddColumn(#"GetStart", "EndMax", each List.Max(List.Transform([Custom], each #"GetStart"[End]{_})), type datetime),
    #"RemoveColumns" = Table.RemoveColumns(#"GetEnd",{"Start", "End", "Index", "Custom"}),
    #"CleanUp" = Table.Distinct(#"RemoveColumns", {"Group", "StartMin", "EndMax"})
    in #"CleanUp", type table }}),
    #"Expanded data" = Table.ExpandTableColumn(#"Grouped Rows", "data", {"Event ID", "StartMin", "EndMax"}, {"Event ID", "StartMin", "EndMax"})
in #"Expanded data"

The function calls itself until no more changes can be made, so should work as deep as needed

Thank you for the solution, it works near perfect. I found one example where the aggregation could be improved even more. which can be found in my initial post. I haven't yet figured out what makes this example special that it can not be fully aggregated with your solution. Do you have an idea? — user2653422, Feb 21 '22 at 09:39

Excel power query - aggregate continuous "transitive" overlapping time intervals

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