YARN Optimizer Architecture
The Pulse YARN Optimizer leverages lightweight Pulse YARN Agents deployed across all YARN NodeManager nodes within a cluster to monitor and analyze real-time container metrics.
For example, in a large-scale environment with 1000+ NodeManager nodes running Spark and Tez/Hive workloads, these agents installed and managed via the Pulse Command Line Interface (Accelo) collect performance data from containers scheduled by the YARN ResourceManager.
Using this data, the YARN Optimizer service identifies unused or underutilized memory and CPU and provides insights to improve container scheduling efficiency. This leads to better resource allocation, increased concurrency, and reduced job queuing caused by unavailable NodeManager slots.
Prerequisites
Before enabling the YARN Optimizer, ensure:
- A functional cluster with YARN ResourceManager and NodeManager components is operational.
- Each YARN Metrics Agent requires approximately 10 MB of memory per node.
- The YARN Optimizer microservice running on the Pulse node requires at least 30 MB of free memory.
Architecture Design
The Pulse YARN Optimizer is built on a modular, data-driven architecture that integrates seamlessly with existing YARN infrastructure.
YARN Metrics Agent
The YARN Metrics Collector Agent runs on each NodeManager node in the YARN cluster. It collects key system and job-level metrics, including:
- Memory utilization
- CPU consumption
- Container execution statistics for active YARN processes
- Job-level performance data for workloads such as Spark and Hive/Tez.
These metrics are securely transmitted to the YARN Optimizer Service, which runs within the Pulse Environment. Also, this agent applies the optimizations to YARN once the optimizer service does the calculation.
YARN Optimizer Service
The YARN Optimizer Service collects and analyzes cluster metrics to improve resource utilization and performance. It performs the following key functions:
- Identifies underutilized or idle resources.
- Applies intelligent algorithms to optimize memory and CPU allocation.
- Generates insights and automatically applies optimized resource configurations to improve cluster efficiency.
The service communicates with the YARN ResourceManager through an Agent to apply optimized resource distribution strategies.
Alfred Service
The Alfred Service works with the YARN Optimizer to process and analyze performance fingerprints of YARN applications.
Key functions:
- Collects and stores fingerprint and runtime data.
- Analyzes performance patterns for optimization insights.
- Supports historical trend analysis for resource tuning.
- Integrates with Pulse for visualization and reporting.
Together, the Alfred Service and YARN Optimizer form the core of the Pulse optimization framework, automating resource tuning and improving cluster efficiency.
This architecture ensures continuous, intelligent optimization of YARN workloads across distributed environments, minimizing waste and maximizing throughput.