Create a Detached Starburst Session — starburst

Creates a new detached session that can run computations independently of your R session. You can close R and reattach later to collect results.

Usage

starburst_session(
  workers = 10,
  cpu = 4,
  memory = "8GB",
  region = NULL,
  timeout = 3600,
  session_timeout = 3600,
  absolute_timeout = 86400,
  launch_type = "FARGATE",
  instance_type = "c6a.large",
  use_spot = FALSE,
  warm_pool_timeout = 3600
)

Arguments

workers: Number of parallel workers (default: 10)
cpu: vCPUs per worker (default: 4)
memory: Memory per worker, e.g., "8GB" (default: "8GB")
region: AWS region (default: from config or "us-east-1")
timeout: Task timeout in seconds (default: 3600)
session_timeout: Active timeout in seconds (default: 3600)
absolute_timeout: Maximum session lifetime in seconds (default: 86400)
launch_type: "FARGATE" or "EC2" (default: "FARGATE")
instance_type: EC2 instance type for EC2 launch (default: "c6a.large")
use_spot: Use spot instances for EC2 (default: FALSE)
warm_pool_timeout: EC2 warm pool timeout in seconds (default: 3600)

Value

A StarburstSession object with methods:

submit(expr, ...) - Submit a task to the session
status() - Get progress summary
collect(wait = FALSE) - Collect completed results
extend(seconds = 3600) - Extend timeout
cleanup() - Terminate and cleanup

Examples

if (FALSE) { # \dontrun{
# Create detached session
session <- starburst_session(workers = 10)

# Submit tasks
task_ids <- lapply(1:100, function(i) {
  session$submit(quote(expensive_computation(i)))
})

# Close R and come back later...
session_id <- session$session_id

# Reattach
session <- starburst_session_attach(session_id)

# Collect results
results <- session$collect(wait = TRUE)
} # }