Forum Discussion
Inefficient function?
- 10 years ago
Hi Aaron,
if that's lightning-fast, let's make match just one row. Therefore you have to create "TeamLookup"-Table like this:
let fnFillDateIntervalls = (Table as table, DateColumn as text, FillUpUntil as date)=> let //DebugParameters: //Table = #"Staff Movements", //DateColumn = "Joined", Source = Table, #"Sorted Rows" = Table.Sort(Source,{{DateColumn, Order.Descending}}), Index = Table.AddIndexColumn(#"Sorted Rows", "Index", 0, 1), Change = Table.TransformColumnTypes(Index,{{DateColumn, Int64.Type}}), #"Added Custom" = Table.AddColumn(Change, "Custom", each [Index]+1), #"Merged Queries" = Table.NestedJoin(#"Added Custom",{"Index"},#"Added Custom",{"Custom"},"NewColumn",JoinKind.LeftOuter), #"Expanded NewColumn" = Table.ExpandTableColumn(#"Merged Queries", "NewColumn", {DateColumn}, {"NewColumn.Date"}), #"Added Custom1" = Table.AddColumn(#"Expanded NewColumn", "Custom.1", each try {Record.Field(_,DateColumn)..[NewColumn.Date]} otherwise {Record.Field(_,DateColumn)..Number.From(FillUpUntil)}), #"Removed Columns" = Table.RemoveColumns(#"Added Custom1",{DateColumn, "Index", "Custom", "NewColumn.Date"}), #"Expanded Custom.1" = Table.ExpandListColumn(#"Removed Columns", "Custom.1"), #"Renamed Columns" = Table.RenameColumns(#"Expanded Custom.1",{{"Custom.1", DateColumn}}), #"Changed Type" = Table.TransformColumnTypes(#"Renamed Columns",{{DateColumn, type date}}) in #"Changed Type", Source = #"Staff Movements", #"Grouped Rows" = Table.Group(Source, {"Name"}, {{"All", each fnFillDateIntervalls(_, "Joined", Date.From(DateTime.LocalNow())), type table}}), #"Expanded All" = Table.ExpandTableColumn(#"Grouped Rows", "All", {"Joined", "Team"}, {"Joined", "Team"}) in #"Expanded All"This query transforms your "Staff Movements"-table into a table with one row for each day. You should disable load to the datamodel. So although this lengthens your table considerably, the result is still very fast, as it used the simple query you mentioned in your last post.
Edit: Don't use Internet-Explorer or Edge to copy this code but preferrably Firefox. Otherwise the code will break (this time will greet you with a request for a comma where there is already one) !!!
There are some things you can try:
1) Group your fact table (Timesheets) on Name and return "All Rows" (Edit: See description here: https://blog.crossjoin.co.uk/2015/05/11/nested-calculations-in-power-query/). This will sort-of partition your big table: Returning only those rows of the table whith that name. You can then omit that condition in the SelectRows-step.
I would think that this will speed up considerably and no further actions necessary.
Other ideas: The sorting is expensive - so you could sort the lookup-table once as a start, pass an index-column to it and buffer that before passing to the function. You then select the MAX index-column instead in your last step.
- ImkeF10 years agoCommunity Champion
Also: I've never used Table.IsEmpty - maybe Table.Countrows is faster - but just a vague guess.
- tempranello10 years agoAdvocate I
Hi ImkeF
Thank you for your input. It's been very helpful. I reviewed the link and I had a bash and the resulting query is a little faster. I wonder if it's not too much to ask for your opinion of how I complete the code? I've found that grouping the data by name does, as you say, chunk the table up nicely. It allows me to operate on a table per Name, which is great!
My problem is that I've not found a way to then work through each row of the table, comparing the Date with the Joined date of the Staff Movements table. The only way I can do that is to still make a call to the original function that now doesn't require the Text.Contains([Name], lookup_name) and is therefore a bit faster.
As the result remains quite slow, am I missing a more elegant way to check the Timesheets.Date against the Staff Movements.Joined field?
My Timesheets query:
let Source = Sql.Databases("XXXX"), SystemDB = Source{[Name="SystemDB"]}[Data], dbo_Timesheets = SystemDB{[Schema="dbo",Item="Timesheets"]}[Data], //UNIMPORTANT CLEAN UP STEPS HERE #"Changed Type" = Table.TransformColumnTypes(dbo_Timesheets,{{"Date", type date}}), //Group by Name GroupedByName = Table.Group(#"Changed Type", {"Name"}, {{"AllRows", each _, type table}}), FindTeamFunction = (tabletopopulate as table) as table => let AssignTeam = Table.AddColumn(tabletopopulate, "Team", each if [Name] <> "" then fnLookupTeam([Date],"Team",#"Staff movements lookup") else "NO TEAM", type text) in AssignTeam, //Apply the function to the AllRows column AddedTeam = Table.TransformColumns(GroupedByName, {"AllRows", each FindTeamFunction(_)}), #"Expanded AllRows" = Table.ExpandTableColumn(AddedTeam, "AllRows", {"Name", "Project", "Date", "Team"}) in #"Expanded AllRows"I've modified the fnLookupTeam function to omit the Name search:
(lookup_date as date, return_column as text, lookup_table as table) as any => let /*FilterTable = Table.SelectRows(lookup_table, each Text.Contains([Name], lookup_name) and [Joined] <= lookup_date),*/ FilterTable = Table.SelectRows(lookup_table, each [Joined] <= lookup_date), ReturnResult = if Table.IsEmpty(FilterTable)=true /*if Table.RowCount(FilterTable)=0*/ then "NO TEAM" else Record.Field(Table.First(Table.Sort(FilterTable,{"Joined",Order.Descending})), return_column) in ReturnResultIf I've reached the limit of what can be done, then it's cool as I'll still have the DAX workaround; it's just a bummer as I'd much prefer to have Timesheets.Team in place in the query rather than in the table later.
Thanks for your help!
Aaron
- tempranello10 years agoAdvocate I
Ah, this is interesting.
(paraphrasing)
Question:
Which way there will be a better performance:
1) If I use Table.NestedJoin
2) if I use Table.SelectRowsAnswer:
Table.NestedJoin is probably the way to go. Table.SelectRows will end up scanning Table2 once for each row of Table1
I'm a bit stumped at how to make Table.NestedJoin work as the Formula Reference has no example of how the keyEqualityComparers work.
I'll keep bashing away at this.
- tempranello10 years agoAdvocate I
I wonder if I'm on the right track here: I've attempted a nested join, which seems to be lightning-fast but leaves me stumped on how to filter the result by date.
let Source = Timesheets, TeamLookup = #"Staff Movements", AssignTeam = Table.NestedJoin(Source, {"Name"}, TeamLookup, {"Name"},"Team",JoinKind.LeftOuter) in AssignTeamReminder of the tables I have
Timesheets
Name Project Date
Joe Bloggs Project X 01/01/2014
Joe Bloggs Project Y 10/04/2015
Fred Jones Project A 01/02/2016
Staff Movements
Name Team Date Joined
Joe Bloggs Project Office 01/01/2014
Joe Bloggs HR 10/04/2015
Fred Jones Finance 30/12/2015
The code above works beautifully if a staff member has only one entry in the Staff Movements table, ie. if I expand the new "Team" column, I'd get a single row for Timesheet entries for Fred Jones as he's only one team. However, for people like Joe Bloggs, he nested join understandably returns two rows.
What I'm struggling with here is how to introduce a filter to the new "Team" column to reduce the number of rows it returns to be only one, ie. where the Timesheets.Date value >= Staff Movements.Date Joined.
Any ideas?
Thanks!
Aaron