Challenges of Pipeline in Query Processing
- Pipeline Stall: The inability of some stages to process the data or to deliver the data to other stages that are ready to process can lead to pipeline stalls where some units are waiting idly for completion.
- Optimization Overhead: Besides the deserialization penalty, query parsing and optimization tasks need to be accomplished in conjunction with pipeline coordination and control. A major concern is whether the enhancement of the architecture will affect system performance.
- Data Skew: Lack of homogenous distribution of the data on the different stages of the processing can result in the unfair loading of the work and low utilization of resources; this, in turn, can cause issues of query performance and scalability.
- Pipeline Balancing: The variables of balanced workload distribution and the optimization of pipeline stages for a smooth sailing rate’s achievement with minimal bottlenecks largely rely on precise tuning and harmonic changes.
Pipeline in Query Processing in DBMS
Database system processing in a satisfactory manner encompasses providing fast responses to data retrieval and manipulation tasks, with two of the keywords being performance and responsiveness. A concept that acts as the foundational element in improving batch processing performance is called “pipeline.” In this article, the network of rungs or pipes that organize the fetching of data from queries for display will be discussed, (their structure, functioning, pros, and cons).