Parallel Execution

​

Introduction

Performing multiple Firestore operations sequentially can be time-consuming, especially when dealing with a large number of documents. executeFirestoreParallel addresses this challenge by executing operations in parallel, enhancing the efficiency of your Firestore interactions.

​

Key Features

• Concurrent Operations: Executes Firestore operations simultaneously, rather than one after another.
• Chunking for Performance: Splits operations into manageable chunks to optimize performance and avoid overloading Firestore’s limits.
• Comprehensive Error Handling: In case of a failure in any operation, the function rejects with an error, ensuring robust error handling.

​

Utilization

​

Defining Firestore Operations

Prepare an array of FirestoreOperation objects, each specifying the operation type, target document reference, and necessary data:

import {
  FirestoreOperation,
  executeFirestoreParallel,
} from 'path-to-your-utilities'

// Example Firestore operations
const operations: FirestoreOperation[] = [
  {
    type: 'set',
    ref: firestore().doc('path/to/doc1'),
    data: {
      /* your data */
    },
  },
  {
    type: 'update',
    ref: firestore().doc('path/to/doc2'),
    data: {
      /* your data */
    },
  },
  // Add more operations as needed
]

​

Executing Operations in Parallel

Invoke executeFirestoreParallel with the array of operations. Operations are automatically chunked for optimal performance:

// Execute operations in parallel
await executeFirestoreParallel(operations, 25) // 25 is the chunk size

​

Handling Large Operation Sets

For handling a large number of operations, executeFirestoreParallel splits them into smaller groups (chunks) to maintain efficient performance and conform to Firestore’s limitations.

​

Best Practices

• Adjust the chunk size based on the complexity and number of operations to balance performance and resource usage.
• Ensure all operations are independent of each other to avoid conflicts during parallel execution.
• Implement comprehensive error handling to manage partial failures in operation sets.