In massively parallel processing (MPP) database systems, does each processing node require its own operating system instance resident in the node’s local memory?
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AApplies — each MPP node runs its own OS instance
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BDoes not apply — a single shared OS image serves all nodes
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CApplies only to SMP, not MPP
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DApplies only in virtualized environments
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EApplies only when using in-memory databases
Answer
Correct Answer: Applies — each MPP node runs its own OS instance
Explanation
Introduction / Context:MPP architectures distribute data and queries across many independent nodes. Each node has its own CPU, memory, and storage and executes parts of a query in parallel. This independence extends to the operating system: each node boots and runs its own OS.
Given Data / Assumptions:
- Each node has dedicated memory and local resources.
- Communication happens over a high-speed network fabric.
- Contrast with SMP (shared-memory) systems where CPUs share memory and a single OS instance.
Concept / Approach:Because MPP nodes are loosely coupled, the OS image (and DBMS process) resides on each node, managing the node’s resources. The DBMS coordinates parallel tasks across nodes via messaging, but the OS is not shared across the cluster as a single image.
Step-by-Step Solution:Provision node hardware or VMs with CPU, memory, and storage.Install/boot an OS instance on each node.Install DBMS worker/segment processes per node.Distribute data and assign query fragments to nodes in parallel.Aggregate results via interconnect to return to the coordinator.
Verification / Alternative check:Vendor documentation for MPP databases (e.g., Teradata-like architectures) describes per-node OS instances managing local memory and processes, validating the statement.
Why Other Options Are Wrong:A single shared OS image (option b) describes SSI or SMP-like models, not classic MPP. Options c–e mis-scope the concept; MPP is about node independence regardless of virtualization or in-memory features.
Common Pitfalls:Confusing MPP with shared-nothing vs. shared-memory; assuming OS-level memory sharing across nodes; underestimating network bottlenecks in shuffle phases.
Final Answer:Applies — each MPP node runs its own OS instance