Forum Discussion
Fuzzy Merge - With Two Columns (one with exacth match and other with fuzzy match)
- 1 year ago
So I understood correctly that you have 100K employees.
But he size of the departments (companies) is 10 times as large as I assumed.So I tested with 100K employees in 288 departments with on average around 350 emplyees each. I used a normal ditribution for the number of employees per department so that 90% is between 300 and 400 employees.
And I have some good news for you!It is even quicker! It is now about 1 minute on my laptop.
So the performace of the FuzzyJoin is not lineair with the number of comparisons it needs to make, but gets relatively more efficient with a bigger dataset.
Here the final query:
let Source = #"Employee Data", #"Grouped Rows" = Table.Group(Source, {"Department_Id"}, {{"Employees", each _, type table [Department_Id=nullable number, Employee_Id=nullable number, Employee_Name=nullable text]}}), #"Added Custom" = Table.AddColumn(#"Grouped Rows", "Custom", each // the following executes for each row. let // to break up a otherwise complex fromula (does not impact perfomance) // load this department employees in memory employee_buffer = [Employees], // Table.Buffer([Employees]), // tried buffering, but did not make any difference // Create a table with matching employee names Matched = Table.FuzzyNestedJoin(employee_buffer, {"Employee_Name"}, employee_buffer, {"Employee_Name"}, "Fuzzy Matched Employees", JoinKind.LeftOuter, [IgnoreCase=true, IgnoreSpace=false, Threshold=0.9, NumberOfMatches=1]), // Add the Employee Id's and Employee Names of the matches expanded = Table.ExpandTableColumn(Matched, "Fuzzy Matched Employees", {"Department_Id", "Employee_Id", "Employee_Name"}, {"Fuzzy Matched Employees.Department_Id", "Fuzzy Matched Employees.Employee_Id", "Fuzzy Matched Employees.Employee_Name"}) in // Select only the employees not matching themselves and return the outcome Table.SelectRows(expanded, each [Fuzzy Matched Employees.Employee_Id] <> [Employee_Id]) ), // Get the Employee_id and Employee Names into the departments table #"Expanded Custom" = Table.ExpandTableColumn(#"Added Custom", "Custom", {"Employee_Id", "Employee_Name", "Fuzzy Matched Employees.Employee_Id", "Fuzzy Matched Employees.Employee_Name"}, {"Employee_Id", "Employee_Name", "Fuzzy Matched Employees.Employee_Id", "Fuzzy Matched Employees.Employee_Name"}), #"Filtered Rows" = Table.SelectRows(#"Expanded Custom", each [Employee_Id] <> null) in #"Filtered Rows"Please mark this as solution if you can use it (even if it only helps you to decide NOT to use PowerQuery for the fuzzy matching...)
Could you please be more detailed what exactly you mean "consider extracting the similar parts directly, as this may simplify the process"?
Are you saying run the process in batch wise for group of dempartment_ids?
Best Regards,
Vinod
Copy the following code and past it in advance editor.
let
Table1 = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WilDSUTI01DUEUUqxOnABIyBlBBaIRKgwBgtEIVSYKMXGAgA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Department_Id = _t, Employee_Name = _t, Column1 = _t]),
Table2 = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WilDSUTI0NFSK1YGxjcDsSCTxKJh4LAA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Department_Id = _t, Employee_Name = _t]),
#"Merged Queries" = Table.FuzzyNestedJoin(Table2, {"Employee_Name"}, Table1, {"Employee_Name"}, "Table2", JoinKind.LeftOuter, [IgnoreCase=true, IgnoreSpace=true]),
#"Added Custom" = Table.AddColumn(#"Merged Queries", "Custom", each Table.SelectRows([Table2], (x)=> x[Department_Id]=[Department_Id]))
in
#"Added Custom"
This is the first solution I mentino.
If this answer helped resolve your issue, please consider marking it as the accepted answer. And if you found my response helpful, I'd appreciate it if you could give me kudos. Thank you!