Batch Processing Patterns

Patterns for processing large volumes of records reliably, at scale, and without overwhelming downstream systems.

Choose based on your throughput requirements, record set size, and whether you need rate limiting or maximum parallelism.

When to use which pattern

Pattern	Record set size	Parallelism model	Workflow-based rate control
Basic Workflow	Small (up to a few hundred records)	Sequential or parallel activities in one Workflow	No
Fan-Out with Child Workflows	Up to ~4M records	Fixed concurrency (one child per chunk)	No
Batch Iterator	Unlimited	Limited (activities per page)	Yes — fixed page rate
Sliding Window	Unlimited	Bounded window of concurrent children	Yes — configurable window
MapReduce Tree	Unlimited	Fully parallel recursive tree	No — maximum speed

Fan-Out with Child Workflows

Splits a record set into fixed-size chunks and assigns each to an independent child Workflow. Simple to reason about; best for record sets up to ~4M items.

Batch Iterator

Processes one page of records per Workflow run and continues as new with the next page offset. Handles unlimited record sets while controlling downstream traffic.

Sliding Window

Maintains a fixed-size window of concurrent child Workflows. As each child completes it signals the parent, which immediately starts a replacement — maximizing throughput within a concurrency budget.

MapReduce Tree

Recursively splits a record set into chunks, fans out to leaf Workflows for parallel processing, and signals results back up the tree. Maximizes speed for embarrassingly parallel workloads.

Schedules

Schedules allow Workflows to be executed on a recurring basis — think of them as a more powerful cron.

Supports start / pause / stop / update / backfill of scheduled Workflow executions
Configurable Overlap Policies control what happens when the previous run is still running
Full execution history visibility in the Temporal UI
Schedules can be created via the UI, CLI, or SDK

bash

temporal schedule create \
  --schedule-id 'your-schedule-id' \
  --workflow-id 'your-workflow-id' \
  --task-queue 'your-task-queue' \
  --workflow-type 'YourWorkflowType'

References:

Basic Workflow (single-tier fan-out)

The simplest form of batch processing: the Workflow fetches or receives record IDs and executes one Activity per record.

Activities can be executed sequentially or concurrently (using the SDK's async primitives)
Limit: 2,000 in-flight Activities per Workflow run (aim for 500)
If total event count is likely to exceed 2,000 (hard limit: 50,000), use the Batch Iterator instead

Pros: Simple
Cons: Hard cap on concurrent Activities; all-or-nothing failure model; can overwhelm downstream systems

Batch Signalling

The Temporal CLI lets you signal, reset, cancel, or terminate multiple Workflows with a single command using a visibility query.

1 running batch job per namespace
50 Workflows per second per batch

bash

# Signal all running Workflows of a given type
temporal workflow signal \
  --name MySignal \
  --input '{"Input": "As-JSON"}' \
  --query 'ExecutionStatus = "Running" AND WorkflowType="YourWorkflow"' \
  --reason "Testing"

# Terminate all running Workflows of a given type
temporal workflow terminate \
  --query 'ExecutionStatus = "Running" AND WorkflowType="SomeWorkflowType"' \
  --reason "Terminate Test Workflows"

Reference: CLI batch commands

Key Limits

Full reference: Temporal Cloud limits

Limit	Value
Unfinished actions per Workflow	2,000 max (aim for 500). Includes Activities, Signals, Child Workflows, cancellation requests
Events per Workflow history	50,000 events max (aim for 2,000) or 50 MB total history size
Signals per Workflow	10,000
Updates per Workflow	10 in-flight, 2,000 total
Batch Signalling	1 batch job per namespace; 50 Workflows/sec per batch

Batch Processing Patterns ​

When to use which pattern ​

Schedules ​

Basic Workflow (single-tier fan-out) ​