What is Hadoop and how does it function like a database?
Hadoop is an open-source, distributed processing framework that runs on large clusters of commodity hardware. It is designed to scale up from a single server to thousands of machines, each offering local computation and storage.
Hadoop functions like a database in the sense that it is able to store and process large amounts of data. However, unlike a traditional database, Hadoop does not require a central server or index. Instead, it relies on a distributed file system that allows it to process data in parallel across the nodes in the cluster.
Hadoop was created by Doug Cutting and Mike Cafarella in 2006. Cutting was the creator of the Apache Lucene search project, and Cafarella was a graduate student working on web search at the time. The original motivation for creating Hadoop was to support the development of the Nutch web search engine. Nutch was built on top of the Lucene search engine and used MapReduce to process large amounts of data in a distributed fashion.
Cutting and Cafarella open sourced the Hadoop project in 2007, and it has since become one of the most popular big data platforms in use today.
Some of the advantages of using Hadoop over traditional RDBMS or BIDW platforms include:
- Hadoop is designed to handle very large data sets, making it ideal for big data applications.
- Hadoop is highly scalable, meaning it can easily be expanded to accommodate more data or more users.
- It’s is designed for parallel processing, which makes it much faster than traditional RDBMS or BIDW platforms.
- It’s is open source, so it is typically less expensive to implement than proprietary platforms.
What are the drawbacks to using Hadoop?
Hadoop is not as good at handling small data sets or data sets that are not well structured. It can also be complex to set up and manage, especially at scale. Finally, Hadoop is not as mature as some of the other big data platforms, so there can be more technical challenges.
How to delete a record from a database in Hadoop
There is no one-size-fits-all answer to this question, as the best way to delete a record from a database in Hadoop will vary depending on the specific database and the way it is implemented. However, some tips on how to delete a record from a database in Hadoop include using the Hadoop Distributed File System (HDFS) to delete files from the database, using the Hadoop MapReduce framework to delete records from the database, and using the Hadoop YARN framework to delete records from the database.