Estimate Cloud Performance and Cost — starburst

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 (FALSE) { # \dontrun{
# 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)
} # }