Introducing a New Architecture to Optimize HaoLap by Hadoop

Introducing a New Architecture to Optimize HaoLap by Hadoop

To improve OLAP as a popular tool to analyze data, several new tools are under development that HaoLap is one of the most efficient and comprehensive tools among them. HaoLap utilizes a multidimensional model of OLAP called MOLAP, in which the MapReduce distributed file system is used as a new solution for big data. HaoLap architecture can be defined as utilizing OLAP within the Hadoop framework using the distributed file system HDFS, where the MapReduce algorithm is used for the main operation. This paper explains a novel architecture in which YARN, one of the Hadoop-associated tools, is utilized beside Hadoop for OLAP operation. According to the results, this new architecture not only improves the operation time but also facilitates using other Hadoop framework tools in the HaoLap structure. Operation time is reduced between 12% and 46% depending on the case, which shows the capability of the method to heighten the performance of the HaoLap.