how to use and call function map in netsuite?

AI generated answer (using internal Slack threads):

In NetSuite, the Map/Reduce script is a server-side script that is designed to process a large number of records. It is based on the Map/Reduce principle in functional programming, which is a method for distributing a task across multiple nodes or processors. Here is a basic structure of a Map/Reduce script:

javascript
/**
 *@NApiVersion 2.x
 *@NScriptType MapReduceScript
 */
define(['N/search', 'N/record', 'N/email', 'N/runtime'], function(search, record, email, runtime) {
   function getInputData() {
      // Your code here
   }

   function map(context) {
      // Your code here
   }

   function reduce(context) {
      // Your code here
   }

   function summarize(summary) {
      // Your code here
   }

   return {
      getInputData: getInputData,
      map: map,
      reduce: reduce,
      summarize: summarize
   };
});

The

getInputData

function is used to gather the data that you want to process. This could be a search, a list of records, etc. The

map

function is where you process each individual record. The output of this function is passed to the

reduce

function. The

reduce

function is where you aggregate or summarize the data. This could be summing values, counting records, etc. The

summarize

function is called at the end of your script execution. It's a good place to check for errors and to send out any notifications if necessary. To call a Map/Reduce script, you can use the

N/task

module. Here is an example:

javascript
var mapReduceTask = task.create({taskType: task.TaskType.MAP_REDUCE});
mapReduceTask.scriptId = 'customscript_my_map_reduce';
mapReduceTask.deploymentId = 'customdeploy_my_map_reduce';
var mapReduceTaskId = mapReduceTask.submit();

In this example,

customscript_my_map_reduce

is the script ID of your Map/Reduce script, and

customdeploy_my_map_reduce

is the deployment ID. ****** Disclaimer: This response was generated by an artificial intelligence assistant based on previous conversations from multiple Slack channels, and may contain inaccuracies or mistakes. ******