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Google Big Data Architecture

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Big Data Architecture

Google was first to invent ‘Big Data Architecture' to serve millions of users with their specific queries. The search-engine gathered and organized all the web information with the goal to serve relevant information and further prioritized online advertisements on behalf of clients. To accomplish, all this, it created web crawling agents which follows links and copy all the web-pages content. Furthermore, sorts or index it so that users can search it effectively.

The Internet data is growing exponentially; hence Google developed a scale-art architecture which could linearly increase its storage capacity by inserting additional computers in its computer network. The information gets distributed over a large number of machines in the cluster.

The Google File system was the precursor of HDFS (Hadoop distributed file system), columnar database system HBase, a quering tool Hive, storm, and Y-shaped architecture.

The ‘Big Data Architecture' features include secure, cost-effective, resilient, and adaptive to new needs and environment.

Google Cloud Platform (GCP): The range of public cloud computing hosting services for computing, storage, networking, big data, machine learning and the internet of things (IoT), as well as cloud management, security, developer tools and application development that run on Google hardware. The Google Cloud Platform services accessed by software developers, cloud administrators and other enterprises IT professionals include:

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