Jump to content

Connect Leeroopedia MCP: Equip your AI agents to search best practices, build plans, verify code, diagnose failures, and look up hyperparameter defaults.

Principle:Apache Spark Cluster Installation

From Leeroopedia


Field Value
Domains Deployment, Infrastructure
Type Principle
Related Implementation:Apache_Spark_Distribution_Placement

Overview

A deployment pattern that ensures identical software installations across all nodes in a distributed cluster through synchronized file placement and SSH-based management.

Description

Distributed systems require identical software deployments on every cluster node. The cluster installation pattern uses a shared-nothing architecture where each node has its own copy of the software at an identical filesystem path. Nodes are enumerated in a configuration file and managed via SSH for coordinated operations.

The key properties of this pattern are:

  • Homogeneous deployment -- every node in the cluster runs the same software version at the same filesystem location
  • Inventory-driven management -- a central configuration file (the cluster manifest) enumerates all participating nodes
  • SSH-based coordination -- the master node orchestrates operations on workers through secure shell connections
  • Shared-nothing storage -- each node maintains its own independent copy of the software, avoiding shared filesystem dependencies

Usage

Use when deploying a Spark standalone cluster on bare-metal or VMs where each node needs the same Spark distribution. This pattern applies to:

  • Initial cluster setup -- placing the Spark distribution on all nodes for the first time
  • Version upgrades -- rolling out a new Spark version across the cluster
  • Node expansion -- adding new worker nodes to an existing cluster

Theoretical Basis

The installation pattern follows symmetric node deployment logic:

for each node in cluster_manifest:
    ensure(software_at_path) AND ensure(ssh_connectivity)

The conf/workers file acts as a cluster inventory, defining the set of machines that participate in the cluster. This approach provides:

  • Idempotency -- running the deployment process multiple times produces the same result
  • Verifiability -- each node can be independently checked for correct installation
  • Scalability -- adding nodes requires only appending to the inventory and replicating the software
Component Role
conf/workers Cluster inventory file listing all worker hostnames
SPARK_HOME Canonical filesystem path for the Spark installation on every node
SSH keys Authentication mechanism for passwordless master-to-worker communication

Related

Page Connections

Double-click a node to navigate. Hold to expand connections.
Principle
Implementation
Heuristic
Environment