The goal was to make big data analytics algorithms work better on large datasets. They studied how to improve the famous Apriori algorithm using MapReduce. The researchers found a new way to use MapReduce that increased performance by 7%, which is a big deal for data sets with 10,000 to 120,000 transactions. They realized that some algorithms need a different approach in MapReduce to speed up processing. Now they know that for MapReduce to work well, it's crucial to avoid certain types of repetitive tasks.