Forum Discussion
Fuzzy Merge - With Two Columns (one with exacth match and other with fuzzy match)
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...)
Super UserTo do this, you need to apply the fuzzy merge based on Employee_Name only, then in the resulted rows, filter (by using Table.SelectRows) the resulted rows with the same Department_Id.
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Thank you!
Thanks Omid_Motamedise
I was thinking about same solution but my data is huge (100K+ rows) and concenred about performance issue with fuzzy merge based on Employee_Name only but not by Department_Id wise.
Step#1: Initial process takes time to merge across all departments
Step#2: Each row comparison to check for department ids are same or not
Step#3: Filterout rows where department ids are not same
Step#4: Final output filter out rows with same employee id within each row
Also I'm expecting results to match with Excel Fuzzy Lookup Add-In output (department_id - exacth match, employee_name - default).
Best Regards,
Vinod
- Omid_Motamedise
When dealing with large datasets, using fuzzy merge can become time-consuming. Before opting for fuzzy merge, consider extracting the similar parts directly, as this may simplify the process and solve the problem in one step. If possible, please provide a sample of the data so I can offer more tailored assistance.Additionally, you can use Table.Buffer to improve filtering performance, though its effectiveness also depends on your data structure.
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
- PwerQueryKees
At my laptop again.
I took a different approach now.
- I first group the data in Employees by Department_ID with "keep all rows"
- This produces a Column Employees
- Then I create a new colum containing the fuzzy match of all employees of that department only
- I then in each fuzzy matched table i remove all matches of employees to themselves
- Finaly I remove all EDepartments with any matches
I tested it with a 100000 row Employee table.
This loads at about 60 rows per second. My test datset has 25 people in each department. Making departments larger or smaller may give different results.My original query loaded a 6 rows/sec. So about a 10-fold speed improvement.
Here the M Code.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) // Create a table with matching employee names Matched = Table.FuzzyNestedJoin([Employees], {"Employee_Name"}, [Employees], {"Employee_Name"}, "Fuzzy Matched Employees", JoinKind.LeftOuter, [IgnoreCase=true, IgnoreSpace=false, Threshold=0.2]), // 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"- PwerQueryKees
Total load time for 8069 matches was 2:35. So on average 52 matches per second.
