What's the easiest way to delete 50k customer reco...
# ask-stanley-ai
e
What's the easiest way to delete 50k customer records in bulk?
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AI generated answer (using internal Slack threads):
The easiest way to delete 50k customer records in bulk in NetSuite would be to use a combination of saved searches and SuiteScript. Here are the steps: 1. Create a saved search that identifies the records you want to delete. This could be based on any criteria that isolates the records you want to delete. 2. Write a Map/Reduce SuiteScript that takes the results of the saved search and deletes the records. Here's a basic example of what the script might look like:
Copy code
javascript
/**
 * @NApiVersion 2.x
 * @NScriptType MapReduceScript
 */
define(['N/search', 'N/record'], function(search, record) {
    function getInputData() {
        return search.load({
            id: 'customsearch_my_saved_search'
        });
    }

    function map(context) {
        var searchResult = JSON.parse(context.value);
        record.delete({
            type: record.Type.CUSTOMER,
            id: searchResult.id
        });
    }

    return {
        getInputData: getInputData,
        map: map
    };
});
Please replace
'customsearch_my_saved_search'
with the ID of your saved search. This script will load the saved search, iterate over the results, and delete each record. Remember, this is a destructive operation and cannot be undone. Always double-check your saved search criteria to ensure you're deleting the correct records. ****** Disclaimer: This response was generated by an artificial intelligence assistant based on previous conversations from multiple Slack channels, and may contain inaccuracies or mistakes. ******
Slack thread 1: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.847547889
Slack thread 2: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.847152829
Slack thread 3: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.831443965
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