195 lines
6.8 KiB
Markdown
195 lines
6.8 KiB
Markdown
# With-Items Batch Processing Implementation
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**Date**: 2024-01-XX
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**Component**: Workflow Executor
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**Status**: Completed ✅
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## Overview
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Implemented batch processing functionality for workflow `with-items` iteration to enable consistent parameter passing and efficient processing of large datasets.
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## Problem Statement
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Previously, the `with-items` workflow feature lacked batch processing capabilities. The requirement was to:
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1. **Maintain backward compatibility**: Continue processing items individually by default
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2. **Add batch processing**: Enable grouping items into batches when `batch_size` is specified
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3. **Efficient bulk operations**: Allow actions to process multiple items at once when supported
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## Solution
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Modified the workflow task executor to support two modes based on the presence of `batch_size`:
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### Key Changes
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1. **Individual Processing (default)**: Without `batch_size`, items are processed one at a time (backward compatible)
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2. **Batch Processing**: When `batch_size` is specified, items are grouped into arrays and processed as batches
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3. **Flexible Batch Sizes**: The final batch can be smaller than `batch_size`
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4. **Concurrency Control**: Both modes respect the `concurrency` setting for parallel execution
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## Implementation Details
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### Code Changes
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**File**: `crates/executor/src/workflow/task_executor.rs`
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- **Modified `execute_with_items()` method**:
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- Split into two execution paths based on `batch_size` presence
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- **Without `batch_size`**: Iterates over items individually (original behavior)
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- **With `batch_size`**: Creates batches and processes them as arrays
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- The `item` context variable receives either a single value or an array depending on mode
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- The `index` context variable receives either item index or batch index depending on mode
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### Algorithm
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```rust
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if let Some(batch_size) = task.batch_size {
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// Batch mode: split items into batches and pass as arrays
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let batches: Vec<Vec<JsonValue>> = items
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.chunks(batch_size)
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.map(|chunk| chunk.to_vec())
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.collect();
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for (batch_idx, batch) in batches.into_iter().enumerate() {
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// Set current_item to the batch array
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context.set_current_item(json!(batch), batch_idx);
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// Execute action with batch
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}
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} else {
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// Individual mode: process each item separately
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for (item_idx, item) in items.into_iter().enumerate() {
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// Set current_item to the individual item
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context.set_current_item(item, item_idx);
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// Execute action with single item
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}
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}
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```
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## Usage Examples
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### Without batch_size (individual processing)
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```yaml
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tasks:
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- name: deploy_to_regions
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action: cloud.deploy_instance
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with_items: "{{ parameters.regions }}"
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input:
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region: "{{ item }}" # Single region value
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```
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### With batch_size (batch processing)
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```yaml
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tasks:
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- name: process_large_dataset
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action: data.transform
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with_items: "{{ vars.records }}"
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batch_size: 100 # Process 100 items at a time
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concurrency: 5 # Process 5 batches concurrently
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input:
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records: "{{ item }}" # Array of up to 100 records (batch)
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```
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### Comparison
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```yaml
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# Individual: one API call per region
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- with_items: "{{ parameters.regions }}"
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input:
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region: "{{ item }}" # "us-east-1"
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# Batch: one API call per 10 regions
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- with_items: "{{ parameters.regions }}"
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batch_size: 10
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input:
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regions: "{{ item }}" # ["us-east-1", "us-west-2", ...]
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```
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## Testing
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### Unit Tests Added
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**File**: `crates/executor/src/workflow/task_executor.rs`
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1. **`test_with_items_batch_creation`**: Verifies batches are created correctly with specified batch_size
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2. **`test_with_items_no_batch_size_individual_processing`**: Verifies items processed individually when batch_size not specified
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3. **`test_with_items_batch_vs_individual`**: Verifies different behavior between batch and individual modes
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### Test Results
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```
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test workflow::task_executor::tests::test_with_items_batch_creation ... ok
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test workflow::task_executor::tests::test_with_items_no_batch_size_individual_processing ... ok
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test workflow::task_executor::tests::test_with_items_batch_vs_individual ... ok
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```
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All existing executor tests pass (55 unit tests, 35 integration tests).
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## Documentation Updates
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**File**: `docs/workflow-orchestration.md`
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- Updated section 2.2 "Iteration (with-items)" with batch processing behavior
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- Clarified that `item` is individual value without `batch_size`, array with `batch_size`
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- Updated special variables section to explain different modes
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- Added comparison examples showing individual vs batch processing
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## Benefits
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1. **Backward Compatible**: Existing workflows continue to work without changes
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2. **Efficiency**: Batch processing reduces overhead for large datasets when enabled
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3. **Flexibility**: Choose between individual or batch processing per task
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4. **Performance**: Bulk API operations can process multiple items in one call
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## Breaking Changes
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✅ **No Breaking Changes**: This implementation is fully backward compatible.
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### Migration Not Required
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Existing workflows continue to work without modification:
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- Without `batch_size`: items processed individually (existing behavior)
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- With `batch_size`: opt-in to batch processing for new workflows
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**To enable batch processing**:
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```yaml
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# Add batch_size to existing with-items task
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with_items: "{{ parameters.regions }}"
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batch_size: 10 # New parameter
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input:
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regions: "{{ item }}" # Now receives array instead of single value
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```
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## Performance Considerations
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- **Trade-offs**: Individual processing gives fine-grained control; batch processing improves throughput
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- **Concurrency**: Both modes support parallel execution via `concurrency` parameter
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- **Memory**: Batch processing uses more memory per task but fewer total tasks
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- **API efficiency**: Use batching when APIs support bulk operations to reduce network overhead
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## Future Enhancements
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Potential improvements for future consideration:
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1. **Adaptive batching**: Automatically adjust batch size based on item size
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2. **Partial batch retry**: Retry only failed items within a batch
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3. **Streaming batches**: Support lazy evaluation for very large datasets
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4. **Batch result aggregation**: Built-in functions to aggregate batch results
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## References
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- Task executor implementation: `crates/executor/src/workflow/task_executor.rs`
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- Workflow context: `crates/executor/src/workflow/context.rs`
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- Documentation: `docs/workflow-orchestration.md`
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- Data models: `crates/common/src/workflow/parser.rs`
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## Completion Checklist
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- [x] Implementation completed (both individual and batch modes)
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- [x] Unit tests added and passing
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- [x] Documentation updated
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- [x] All existing tests passing (backward compatible)
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- [x] No breaking changes - fully backward compatible
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- [x] Performance optimized with concurrency support
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- [ ] Performance benchmarking (future work) |