distributed data processing Synonyms
No Synonyms and anytonyms found
distributed data processing Meaning
distributed data processing (n)
data processing in which some of the functions are performed in different places and connected by transmission facilities
distributed data processing Sentence Examples
- Distributed data processing involves breaking down a task into smaller, independent subtasks that can be processed concurrently on multiple computers.
- In distributed data processing, each computer or node in the network is responsible for processing a portion of the data.
- Distributed data processing is commonly used in big data analytics and high-performance computing applications where large datasets are processed.
- Hadoop, Spark, and Flink are popular open-source frameworks for distributed data processing.
- Distributed data processing systems typically use a master-slave or cluster architecture, where a central node coordinates the tasks and allocates them to worker nodes.
- Load balancing is a key challenge in distributed data processing, as data and tasks need to be evenly distributed among the compute nodes to optimize performance.
- Fault tolerance is another important aspect of distributed data processing, as the system needs to be able to handle failures of individual nodes without losing data or interrupting the processing.
- Distributed data processing allows for scalability and elasticity, enabling systems to handle increasing workloads by adding more nodes to the network.
- Distributed data processing can improve the overall performance and efficiency of data processing tasks, especially for large-scale datasets and complex computations.
- Distributed data processing is becoming increasingly important in various fields, including artificial intelligence, machine learning, financial analysis, and scientific research.
FAQs About the word distributed data processing
data processing in which some of the functions are performed in different places and connected by transmission facilities
No synonyms found.
No antonyms found.
Distributed data processing involves breaking down a task into smaller, independent subtasks that can be processed concurrently on multiple computers.
In distributed data processing, each computer or node in the network is responsible for processing a portion of the data.
Distributed data processing is commonly used in big data analytics and high-performance computing applications where large datasets are processed.
Hadoop, Spark, and Flink are popular open-source frameworks for distributed data processing.
