fuzzysearch | : crystal_ball : Tiny and blazing-fast fuzzy search | Search Engine library

Scenario

I have a number of enterprise datasets that I must find missing links between, and one of the ways I use for finding potential matches is joining on first and last name. The complication is that we have a significant number of people who use their legal name in one dataset (employee records), but they use either a nickname or (worse yet) their middle name in others (i.e., EAD, training, PIV card, etc.). I am looking for a way to match up these potentially disparate names across the various datasets.

Simplified Example

Here is an overly simplified example of what I am trying to do, but I think it conveys my thought process. I begin with the employee table:

Employees table employee_id first_name last_name 052451 Robert Armsden 442896 Jacob Craxford 054149 Grant Keeting 025747 Gabrielle Renton 071238 Margaret Seifenmacher

and try to find the matching data from the PIV card dataset:

Cards table card_id first_name last_name 1008571527 Bobbie Armsden 1009599982 Jake Craxford 1004786477 Gabi Renton 1000628540 Maggy Seifenmacher Desired Result

After trying to match these datasets on first name and last name, I would like to end up with the following:

Employees_Cards table emp_employee_id emp_first_name emp_last_name crd_card_id crd_first_name crd_last_name 052451 Robert Armsden 1008571527 Bobbie Armsden 442896 Jacob Craxford 1009599982 Jake Craxford 054149 Grant Keeting NULL NULL NULL 025747 Gabrielle Renton 1004786477 Gabi Renton 071238 Margaret Seifenmacher 1000628540 Maggy Seifenmacher

As you can see, I would like to make the following matches:

Gabrielle -> Gabi
Jacob -> Jacob
Margaret -> Maggy
Robert -> Bobbie

My initial thought was to find a common names dataset along the lines of:

Name_Aliases table name1 name2 name3 name4 Gabrielle Gabi NULL NULL Jacob Jake NULL NULL Margaret Maggy Maggie Meg Michael Mike Mikey Mick Robert Bobbie Bob Rob

and use something like this for the JOIN:

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I have a dnd selection tab with search functionality to filter the items available. Once an item is selected from draggable section it should be removed from that section and dropped to the droppable section and vice versa. The link to my code is https://codesandbox.io/s/dnd-search-select-sort-xfdtn When an item say "Apple" is selected it is going to the droppable section but when I search for "Apple" again in the draggable section search bar it reappears again and I can again move that to the droppable section which should not be the case. Once it is selected it should not appear again on the list. Below is the corresponding code.

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I'm building a help page with Gatsby and have a search bar (Searchbar.js) where I'm trying to pass the user's input in the field (search bar is always present within the page--think like Evernote's help page) to a component that conducts the search (search.js), which then passes that output to the actual results page (SearchResults.js).

When I do gatsby develop everything works as it should, but when I do a gatsby build I get an error where it says it cant read the property "query" because its undefined (line 63 of search.js: var search = location.state.query.trim()). Why is this failing on build?

Searchbar.js

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I have couple of questions here.

I want to search a term jumps

With Fuzzy search, I can do jump~ With wild card search, I can do jump* With stemmer I can do, jump

My understanding is that, fuzzy search gives pump. Wildcard search gives jumping as well. Stemmer gives "jumper" also.

I totally agree with the results.

1. What is the performance of thes three?

   • Wild card is not recommended if it is at the beginning of the term - my understanding as it has to match with all the tokens in the index - But in this case, it would be all the tokens which starts jump

   • Fuzzy search gives me unpredicted results - It has to do something kind of spellcheck I assume.

   • Stemmer suits only particular scenarios like it can;t match pumps.

2. How should I use these things which can give more relevant results?

I probably more confused about all these because of this section. Any suggestions please?

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