A Microsoft Fabric Livy batch job — FabricLivyBatch • fabricQueryR

Represents a Spark application submitted with fabric_livy_batch_submit() Use $wait() to wait for completion, $result() or $logs() to inspect the outcome, and $cancel() to request cancellation. Most users do not need to call this 'R6' class directly. These lifecycle methods do not have separate free-function wrappers

Format

An R6::R6Class generator

Value

The FabricLivyBatch 'R6' generator.

Public fields

id: Fabric batch ID
url: Batch lifecycle URL
state: Latest batch state
response: Latest raw service response
cancel_requested: Whether $cancel() was called successfully
submitted_local: Local submission timestamp
completed_local: Local completion timestamp
verbose: Whether lifecycle messages are enabled

Methods

`FabricLivyBatch$new()`

Internal constructor used by fabric_livy_batch_submit()

Usage

FabricLivyBatch$new(response, url, credential, verbose = TRUE)

Arguments

response: Initial batch response
url: Batch collection URL
credential: Internal authentication credential
verbose: Whether to emit lifecycle messages

Returns

A new batch object

`FabricLivyBatch$print()`

Print a concise batch summary

Usage

FabricLivyBatch$print(...)

Arguments

...: Unused

Returns

self, invisibly

`FabricLivyBatch$status()`

Retrieve current batch metadata

Usage

FabricLivyBatch$status(refresh = TRUE, deadline = NULL)

Arguments

refresh: Whether to retrieve current state from Fabric
deadline: Internal wall-clock deadline for the status request

Returns

The raw batch response list

`FabricLivyBatch$wait()`

Wait for the batch to reach a terminal state

Usage

FabricLivyBatch$wait(
  timeout = 1200,
  poll_interval = 5,
  error_on_failure = TRUE,
  cancel_on_timeout = FALSE
)

Arguments

timeout: Maximum wait in seconds
poll_interval: Polling interval in seconds
error_on_failure: Raise a structured error for a failed batch
cancel_on_timeout: Request cancellation before raising a timeout

Returns

self, invisibly

`FabricLivyBatch$logs()`

Return available Spark driver log lines

Usage

FabricLivyBatch$logs(refresh = TRUE)

Arguments

refresh: Whether to retrieve current state from Fabric

Returns

A character vector

`FabricLivyBatch$result()`

Return structured batch metadata and logs

Usage

FabricLivyBatch$result(refresh = TRUE, error_on_failure = TRUE)

Arguments

refresh: Whether to retrieve current state from Fabric
error_on_failure: Raise a structured error for a failed batch

Returns

A fabric_livy_batch_result list

`FabricLivyBatch$cancel()`

Request batch cancellation

Usage

FabricLivyBatch$cancel(deadline = NULL)

Arguments

deadline: Internal wall-clock deadline for the cancellation request

Returns

TRUE, invisibly, after Fabric accepts the request

Examples

if (FALSE) { # \dontrun{
# fabric_livy_batch_submit() returns this class for a submitted Spark job
workspace <- fabric_workspaces()[[1L]]
lakehouse <- fabric_lakehouses(workspace)[[1L]]
scripts <- fabric_onelake_list(workspace, lakehouse, "Files/jobs")
script <- scripts[grepl("[.]py$", scripts$path), ][1L, ]
script_uri <- paste0(
  "abfss://", workspace$id, "@onelake.dfs.fabric.microsoft.com/",
  lakehouse$id, "/", script$path[[1L]]
)
batch <- fabric_livy_batch_submit(
  lakehouse,
  file = script_uri
)
inherits(batch, "FabricLivyBatch")

# Wait for completion, then inspect the application result and logs
batch$wait()
batch$result()
batch$logs()
} # }