starburst_estimate: Estimate Cloud Performance and Cost

In starburst: Seamless AWS Cloud Bursting for Parallel R Workloads

Estimate Cloud Performance and Cost

Description

Runs a small sample of tasks locally to estimate cloud execution time and cost. Provides informed prediction before spending money on cloud execution.

Usage

starburst_estimate(
  .x,
  .f,
  workers = 10,
  cpu = 2,
  memory = "8GB",
  platform = "X86_64",
  sample_size = 10,
  region = NULL,
  ...
)

Arguments

.x	A vector or list to iterate over
.f	A function to apply to each element
workers	Number of parallel workers to estimate for
cpu	CPU units per worker (1, 2, 4, 8, or 16)
memory	Memory per worker (e.g., "8GB")
platform	CPU architecture: "X86_64" (default) or "ARM64" (Graviton3)
sample_size	Number of items to run locally for estimation (default: 10)
region	AWS region
...	Additional arguments passed to .f

Value

Invisible list with estimates, prints summary to console

Examples

if (starburst_is_configured()) {
  # Estimate before running
  starburst_estimate(1:1000, expensive_function, workers = 50)

  # Then decide whether to proceed
  results <- starburst_map(1:1000, expensive_function, workers = 50)
}

starburst documentation built on March 19, 2026, 5:08 p.m.