How to make a Search Engine Like Google?
Google has been the most successful company when it comes to search engines. Have you ever thought about creating a full feature search engine like Google? It is amazing the success that Google has had in such a short span of time. Google has managed to make quick technological advancements to become powerful. Makes one think how does it manage fault tolerance? Where does it save all the data of billions of pages?
When you consider an idea of building a search engine like Google, the first thing that comes to mind is its several aspects. Also, it is crucial to understand that a search engine like Google cannot be built overnight. It is a tedious task that may take a few months to years to actually crawl and store the data. Thus, to rank the results and have it crawl the whole web is a time-consuming endeavor. Nonetheless, the search results can be produced within a few weeks.
Next question is where does Google store all its data? Google stores its data on Bigtable, its unique NOSQL (Not Only SQL) database. It works on a distributed system on the unfailing Hadoop Distributed File System.
For a global scale service like Google, MySQL, or even Oracle is not enough. You will need something like Bigtable that works on the HDFS file system. However, let us not forget that Bigtable is a google specific technology that is not available for public use. Google has made Bigtable available but only as a host under Google cloud. The only other option that offers a group of software and tools with bigdata components plus an HDFS file system is Hadoop. It is an open-source by Apache that is endlessly researched as well as developed. It is the best when it comes to running scalable and multimachine apps like analytics or in this case search engines. In order to work as an expandable file system, it links up numerous nodes.
Reliable and Java-based, Hbase is a database that works on NOSQLsystem. It can work over and above Hadoop to store petabytes of data. Another NOSQL database is Hypertable which works on Hadoop. It is based on C++ and has good support. As compared to Hbase, Hypertable suggests its performance is much faster and offers more flexibility on queries. Thus, these are the option for running your search engine.
Google operates data centers around the world. The best option there is to either associate with a hosting company or data center that in a single network can offer a series of nodes. As the nodes expand in the future, having a single network allows for better performance of the search engine.
This is the part we all have been waiting for. The coding is the most tricking and at the same time the most interesting part of building a search engine like Google. Everything is irrelevant — the technology, the infrastructure if the code is not compelling and designed to cope with scalability. The spider must be effective. That is where your originality comes in. This article is not about offering similar features as the Google search engine. What makes your search engine unique will be defined by an algorithm that builds a spider. You can certainly draw inspiration from Inout Spider; a commercial application that works well with Hypertable and Hadoop technologies.
To summarize it all, building something as powerful as Google will take time. It is not an easy undertaking. If it were easy Google would not be Google and there would probably be many more Google clones. However, with the right software, hardware, and technology, this is a dream that is possible.