One of the attributes of big data analytics is its velocity. In the modern world of information technology, speed is one of the crucial factors of any successful organization because even delays measured in seconds can cost money. Big data must move at extremely high velocities no matter how much we scale or what workloads our store must handle. The data handling hoops of Hadoop or NoSQL solutions put a serious drag on performance. That's why Hunk has a powerful feature that can speed up analytics and help immediately derive business insight from a vast amount of data.
In this chapter, we will learn about the report acceleration technique of Hunk, create new virtual indexes, and compare the performance of the same search with and without acceleration.
Despite the fact that, with modern technology, we can handle any big data issue, we still to have spend some time waiting for our questions to be answered. For example, we collect data and store it in Hadoop, then we deploy Hunk and configure a data provider, create a virtual index, and start to ask business questions by creating a query and running search commands. We should wait before the MapReduce job is finished. The following diagram illustrates this situation:
Moreover, if we want to ask the question over and over again by modifying the initial query, we will lose much time and money.
It would be superb if we could just run the search and immediately get the answer, as in the following diagram:
Yes, this is possible with Hunk, because it allows us to accelerate the report and get an answer to our business question very quickly. Let's learn how to do it.