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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.

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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.

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Utilization

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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
]

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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

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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.

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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.
Parallel execution is powerful but should be used judiciously. Consider Firestore’s rate limits and quotas to avoid potential issues with large-scale operations.