Flight web searches analytics through big data

The flight search is considered one of the biggest searches on the World Wide Web. This study aims to establish an effective prediction model from a huge data set. This article offers a linear regression model to forecast flight searches using the big data framework SparkML library and statistics. Experiments on realistic data sets of domestic airports reveal that the suggested model's accuracy is close to 90% using the big data framework. Our research is provided an efficient flight web search engine, which can manage through big data.