Cloud-Based Big Data Engineering
Please write about Big Data Engineering using Hadoop and Cloud (GCP/Azure) Technologies.
Big Data Engineering using Hadoop and Cloud technologies (such as Google Cloud Platform – GCP and Microsoft Azure) involves leveraging scalable infrastructure and tools to manage, process, and analyze vast amounts of data efficiently. Here’s an overview of how these technologies work together in the context of Big Data Engineering:
1. Hadoop Ecosystem:
Components:
- Hadoop Distributed File System (HDFS): A distributed storage system that provides high-throughput access to data across clusters of commodity hardware.
- MapReduce: A programming model for processing and generating large data sets with a parallel, distributed algorithm on a cluster.
- Apache Hive and Apache Pig: Higher-level abstractions that allow SQL-like querying (Hive) and data flow scripting (Pig) over Hadoop.
- Apache Spark: A fast and general-purpose cluster computing system that provides APIs in Scala, Java, Python, and R. It can run on top of Hadoop YARN or Apache Mesos…
Big Data Engineering using Hadoop and Cloud technologies (such as Google Cloud Platform – GCP and Microsoft Azure) involves leveraging scalable infrastructure and tools to manage, process, and analyze vast amounts of data efficiently. Here’s an overview of how these technologies work together in the context of Big Data Engineering:
1. Hadoop Ecosystem:
Components:
- Hadoop Distributed File System (HDFS): A distributed storage system that provides high-throughput access to data across clusters of commodity hardware.
- MapReduce: A programming model for processing and generating large data sets with a parallel, distributed algorithm on a cluster.
- Apache Hive and Apache Pig: Higher-level abstractions that allow SQL-like querying (Hive) and data flow scripting (Pig) over Hadoop.
- Apache Spark: A fast and general-purpose cluster computing system that provides APIs in Scala, Java, Python, and R. It can run on top of Hadoop YARN or Apache Mesos…
- Hadoop Distributed File System (HDFS): A distributed storage system that provides high-throughput access to data across clusters of commodity hardware.
- MapReduce: A programming model for processing and generating large data sets with a parallel, distributed algorithm on a cluster.
- Apache Hive and Apache Pig: Higher-level abstractions that allow SQL-like querying (Hive) and data flow scripting (Pig) over Hadoop. Cloud-Based Big Data Engineering
- Apache Spark: A fast and general-purpose cluster computing system that provides APIs in Scala, Java, Python, and R. It can run on top of Hadoop YARN or Apache Mesos…
