netsuite Searches with large number of results Using dedicated Map/Reduce script

Example

For really huge search results, you can use dedicated Map/Reduce script. It is much more inconvenient, but sometimes unavoidable. And sometimes could be very handy.
The trick here is, that in Get Input Data stage, you can provide to the NS engine not the actual data (i.e. script result), but just the definition of the search. NS will execute the search for you without counting the governance units. Then each single result row will be passed to the Map stage.
Of course, there is a limitation: The total persisted size of data for a map/reduce script is not allowed to exceed 50MB. In a search result, each key and the serialized size of each value is counted towards the total size. "Serialized" means, that the search result row is converted to string with JSON.stringify. Thus, the value size is proportional to the number of search result columns in a result set. If you get to trouble with STORAGE_SIZE_EXCEEDED error, consider reducing the columns, combining to formulas, grouping the result or even splitting the search to multiple sub-searches, which could be executed in Map or Reduce stages.

    /**
     * @NApiVersion 2.0
     * @NScriptType MapReduceScript
     */
    define(['N/search'], function(search) {

    function getInputData()
    {
        return search.create({
            type: search.Type.TRANSACTION,
            columns : ['entity','amount'],
            filters : [] 
        });
    }

    function map(context)
    {
        var searchResult = JSON.parse(context.value);
        // you have the result row. use it like this....
        var transId = searchResult.id;
        var entityId = searchResult.values.entity.value;
        var entityName = searchResult.values.entity.text;
        var amount = searchResult.values.amount.value;
        
        // if you want to pass some part of the search result to the next stage
        // write it to context:
        context.write(entityId, transId);
    }

    function reduce(context)
    {
       // your code here ...
    }

    function summarize(summary)
    {
        // your code here ...
    }

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

Of course the example here is simplified, without error handling and is given just to be compared with others. More examples are available at Map/Reduce Script Type examples in NS Help Center