With time, the amount of data available has become so vast that we need more dynamic ways of finding information. Now these challenges are faced by almost every organization each organization now deals with huge data every day. As time passed, the explosion of data was not limited to cutting-edge technology companies. Google was the first to publicize MapReduce-a system used to scale their data processing needs. So most of them created proprietary products. These companies felt the existing tools, were becoming inadequate to process large data sets. At that time, they had to go through terabytes and petabytes of data to identify which websites were popular, what books were in demand, and what kinds of ads appealed to people. Some 10 years back this growing data presented challenges to cutting-edge businesses such as Google, Yahoo, Amazon, and Microsoft. These all things lead to the exponential growth of data. Machines, too, are generating and keeping more and more data. Each of these operations results in bulk of data. We upload documents, send text messages, update social channels, send emails, publish blogs and so forth. We use computers, internet, intranet, and mobile phones extensively. Why Lucene: understanding the need of Lucene This VOX DC post is based on my years of experience of using Lucene library, and should provide a quick and pointed guide to using Lucene. It is supported by the Apache Software Foundation, and is released under the Apache Software License. And developers want documentation we can trust.Īpache Lucene is a free and open-source information retrieval (IR) software library, originally written completely in Java by Doug Cutting. There is lot of material on Lucene freely available on the internet already, though most of the material is either formal (lengthy, too detailed, and dull) or informal (mostly incomplete, and often scattered).
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