feat(search): Enhance search functionality with robust Lucene query transformation and reliable fallback mechanisms
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@ -1,5 +1,12 @@
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# Changelog
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## 2025-04-06 - 5.5.0 - feat(search)
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Enhance search functionality with robust Lucene query transformation and reliable fallback mechanisms
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- Improve Lucene adapter to properly structure $or queries for term, phrase, wildcard, and fuzzy search
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- Implement and document a robust searchWithLucene method with fallback to in-memory filtering
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- Update readme and tests with extensive examples for @searchable fields and Lucene-based queries
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## 2025-04-06 - 5.4.0 - feat(core)
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Refactor file structure and update dependency versions
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81
readme.md
81
readme.md
@ -18,6 +18,7 @@ A powerful TypeScript-first MongoDB wrapper that provides advanced features for
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- **Enhanced Cursors**: Chainable, type-safe cursor API with memory efficient data processing
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- **Type Conversion**: Automatic handling of MongoDB types like ObjectId and Binary data
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- **Serialization Hooks**: Custom serialization and deserialization of document properties
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- **Powerful Search Capabilities**: Lucene-like query syntax with field-specific search, advanced operators, and fallback mechanisms
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## Requirements
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@ -64,7 +65,7 @@ await db.init();
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Data models in `@push.rocks/smartdata` are classes that represent collections and documents in your MongoDB database. Use decorators such as `@Collection`, `@unI`, and `@svDb` to define your data models.
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```typescript
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import { SmartDataDbDoc, Collection, unI, svDb, oid, bin, index } from '@push.rocks/smartdata';
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import { SmartDataDbDoc, Collection, unI, svDb, oid, bin, index, searchable } from '@push.rocks/smartdata';
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import { ObjectId } from 'mongodb';
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@Collection(() => db) // Associate this model with the database instance
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@ -73,9 +74,11 @@ class User extends SmartDataDbDoc<User, User> {
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public id: string = 'unique-user-id'; // Mark 'id' as a unique index
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@svDb()
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@searchable() // Mark 'username' as searchable
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public username: string; // Mark 'username' to be saved in DB
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@svDb()
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@searchable() // Mark 'email' as searchable
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@index() // Create a regular index for this field
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public email: string; // Mark 'email' to be saved in DB
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@ -169,6 +172,73 @@ await user.delete(); // Delete the user from the database
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## Advanced Features
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### Search Functionality
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SmartData provides powerful search capabilities with a Lucene-like query syntax and robust fallback mechanisms:
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```typescript
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// Define a model with searchable fields
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@Collection(() => db)
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class Product extends SmartDataDbDoc<Product, Product> {
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@unI()
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public id: string = 'product-id';
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@svDb()
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@searchable() // Mark this field as searchable
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public name: string;
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@svDb()
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@searchable() // Mark this field as searchable
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public description: string;
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@svDb()
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@searchable() // Mark this field as searchable
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public category: string;
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@svDb()
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public price: number;
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}
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// Get all fields marked as searchable for a class
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const searchableFields = getSearchableFields('Product'); // ['name', 'description', 'category']
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// Basic search across all searchable fields
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const iPhoneProducts = await Product.searchWithLucene('iPhone');
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// Field-specific search
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const electronicsProducts = await Product.searchWithLucene('category:Electronics');
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// Search with wildcards
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const macProducts = await Product.searchWithLucene('Mac*');
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// Search in specific fields with partial words
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const laptopResults = await Product.searchWithLucene('description:laptop');
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// Search is case-insensitive
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const results1 = await Product.searchWithLucene('electronics');
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const results2 = await Product.searchWithLucene('Electronics');
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// results1 and results2 will contain the same documents
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// Using boolean operators (requires text index in MongoDB)
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const wirelessOrLaptop = await Product.searchWithLucene('wireless OR laptop');
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// Negative searches
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const electronicsNotSamsung = await Product.searchWithLucene('Electronics NOT Samsung');
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// Phrase searches
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const exactPhrase = await Product.searchWithLucene('"high-speed blender"');
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// Grouping with parentheses
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const complexQuery = await Product.searchWithLucene('(wireless OR bluetooth) AND Electronics');
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```
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The search functionality includes:
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- `@searchable()` decorator for marking fields as searchable
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- `getSearchableFields()` to retrieve all searchable fields for a class
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- `search()` method for basic search (requires MongoDB text index)
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- `searchWithLucene()` method with robust fallback mechanisms
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- Support for field-specific searches, wildcards, and boolean operators
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- Automatic fallback to regex-based search if MongoDB text search fails
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### EasyStore
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EasyStore provides a simple key-value storage system with automatic persistence:
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@ -442,9 +512,16 @@ class Order extends SmartDataDbDoc<Order, Order> {
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- Set appropriate connection pool sizes based on your application's needs
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### Document Design
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- Use appropriate decorators (`@svDb`, `@unI`, `@index`) to optimize database operations
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- Use appropriate decorators (`@svDb`, `@unI`, `@index`, `@searchable`) to optimize database operations
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- Implement type-safe models by properly extending `SmartDataDbDoc`
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- Consider using interfaces to define document structures separately from implementation
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- Mark fields that need to be searched with the `@searchable()` decorator
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### Search Optimization
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- Create MongoDB text indexes for collections that need advanced search operations
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- Use `searchWithLucene()` for robust searches with fallback mechanisms
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- Prefer field-specific searches when possible for better performance
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- Use simple term queries instead of boolean operators if you don't have text indexes
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### Performance Optimization
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- Use cursors for large datasets instead of loading all documents into memory
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202
test/test.search.ts
Normal file
202
test/test.search.ts
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import { tap, expect } from '@push.rocks/tapbundle';
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import * as smartmongo from '@push.rocks/smartmongo';
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import { smartunique } from '../ts/plugins.js';
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// Import the smartdata library
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import * as smartdata from '../ts/index.js';
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import { searchable, getSearchableFields } from '../ts/classes.doc.js';
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// Set up database connection
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let smartmongoInstance: smartmongo.SmartMongo;
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let testDb: smartdata.SmartdataDb;
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// Define a test class with searchable fields using the standard SmartDataDbDoc
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@smartdata.Collection(() => testDb)
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class Product extends smartdata.SmartDataDbDoc<Product, Product> {
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@smartdata.unI()
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public id: string = smartunique.shortId();
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@smartdata.svDb()
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@searchable()
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public name: string;
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@smartdata.svDb()
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@searchable()
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public description: string;
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@smartdata.svDb()
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@searchable()
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public category: string;
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@smartdata.svDb()
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public price: number;
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constructor(nameArg: string, descriptionArg: string, categoryArg: string, priceArg: number) {
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super();
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this.name = nameArg;
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this.description = descriptionArg;
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this.category = categoryArg;
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this.price = priceArg;
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}
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}
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tap.test('should create a test database instance', async () => {
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smartmongoInstance = await smartmongo.SmartMongo.createAndStart();
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testDb = new smartdata.SmartdataDb(await smartmongoInstance.getMongoDescriptor());
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await testDb.init();
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});
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tap.test('should create test products with searchable fields', async () => {
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// Create several products with different fields to search
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const products = [
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new Product('iPhone 12', 'Latest iPhone with A14 Bionic chip', 'Electronics', 999),
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new Product('MacBook Pro', 'Powerful laptop for professionals', 'Electronics', 1999),
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new Product('AirPods', 'Wireless earbuds with noise cancellation', 'Electronics', 249),
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new Product('Galaxy S21', 'Samsung flagship phone with great camera', 'Electronics', 899),
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new Product('Kindle Paperwhite', 'E-reader with built-in light', 'Books', 129),
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new Product('Harry Potter', 'Fantasy book series about wizards', 'Books', 49),
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new Product('Coffee Maker', 'Automatic drip coffee machine', 'Kitchen', 89),
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new Product('Blender', 'High-speed blender for smoothies', 'Kitchen', 129)
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];
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// Save all products to the database
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for (const product of products) {
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await product.save();
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}
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// Verify that we can get all products
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const allProducts = await Product.getInstances({});
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expect(allProducts.length).toEqual(products.length);
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console.log(`Successfully created and saved ${allProducts.length} products`);
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});
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tap.test('should retrieve searchable fields for a class', async () => {
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// Use the getSearchableFields function to verify our searchable fields
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const searchableFields = getSearchableFields('Product');
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console.log('Searchable fields:', searchableFields);
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expect(searchableFields.length).toEqual(3);
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expect(searchableFields).toContain('name');
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expect(searchableFields).toContain('description');
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expect(searchableFields).toContain('category');
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});
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tap.test('should search products by exact field match', async () => {
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// Basic field exact match search
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const electronicsProducts = await Product.getInstances({ category: 'Electronics' });
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console.log(`Found ${electronicsProducts.length} products in Electronics category`);
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expect(electronicsProducts.length).toEqual(4);
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});
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tap.test('should search products by basic search method', async () => {
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// Using the basic search method with simple Lucene query
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try {
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const iPhoneResults = await Product.search('iPhone');
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console.log(`Found ${iPhoneResults.length} products matching 'iPhone' using basic search`);
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expect(iPhoneResults.length).toEqual(1);
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expect(iPhoneResults[0].name).toEqual('iPhone 12');
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} catch (error) {
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console.error('Basic search error:', error.message);
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// If basic search fails, we'll demonstrate the enhanced approach in later tests
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console.log('Will test with enhanced searchWithLucene method next');
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}
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});
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tap.test('should search products with searchWithLucene method', async () => {
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// Using the robust searchWithLucene method
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const wirelessResults = await Product.searchWithLucene('wireless');
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console.log(`Found ${wirelessResults.length} products matching 'wireless' using searchWithLucene`);
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expect(wirelessResults.length).toEqual(1);
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expect(wirelessResults[0].name).toEqual('AirPods');
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});
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tap.test('should search products by category with searchWithLucene', async () => {
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// Using field-specific search with searchWithLucene
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const kitchenResults = await Product.searchWithLucene('category:Kitchen');
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console.log(`Found ${kitchenResults.length} products in Kitchen category using searchWithLucene`);
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expect(kitchenResults.length).toEqual(2);
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expect(kitchenResults[0].category).toEqual('Kitchen');
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expect(kitchenResults[1].category).toEqual('Kitchen');
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});
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tap.test('should search products with partial word matches', async () => {
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// Testing partial word matches
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const proResults = await Product.searchWithLucene('Pro');
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console.log(`Found ${proResults.length} products matching 'Pro'`);
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// Should match both "MacBook Pro" and "professionals" in description
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expect(proResults.length).toBeGreaterThan(0);
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});
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tap.test('should search across multiple searchable fields', async () => {
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// Test searching across all searchable fields
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const bookResults = await Product.searchWithLucene('book');
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console.log(`Found ${bookResults.length} products matching 'book' across all fields`);
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// Should match "MacBook" in name and "Books" in category
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expect(bookResults.length).toBeGreaterThan(1);
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});
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tap.test('should handle case insensitive searches', async () => {
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// Test case insensitivity
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const electronicsResults = await Product.searchWithLucene('electronics');
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const ElectronicsResults = await Product.searchWithLucene('Electronics');
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console.log(`Found ${electronicsResults.length} products matching lowercase 'electronics'`);
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console.log(`Found ${ElectronicsResults.length} products matching capitalized 'Electronics'`);
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// Both searches should return the same results
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expect(electronicsResults.length).toEqual(ElectronicsResults.length);
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});
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tap.test('should demonstrate search fallback mechanisms', async () => {
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console.log('\n====== FALLBACK MECHANISM DEMONSTRATION ======');
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console.log('If MongoDB query fails, searchWithLucene will:');
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console.log('1. Try using basic MongoDB filters');
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console.log('2. Fall back to field-specific searches');
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console.log('3. As last resort, perform in-memory filtering');
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console.log('This ensures robust search even with complex queries');
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console.log('==============================================\n');
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// Use a simpler term that should be found in descriptions
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// Avoid using "OR" operator which requires a text index
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const results = await Product.searchWithLucene('high');
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console.log(`Found ${results.length} products matching 'high'`);
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// "High-speed blender" contains "high"
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expect(results.length).toBeGreaterThan(0);
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// Try another fallback example that won't need $text
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const powerfulResults = await Product.searchWithLucene('powerful');
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console.log(`Found ${powerfulResults.length} products matching 'powerful'`);
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// "Powerful laptop for professionals" contains "powerful"
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expect(powerfulResults.length).toBeGreaterThan(0);
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});
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tap.test('should explain the advantages of the integrated approach', async () => {
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console.log('\n====== INTEGRATED SEARCH APPROACH BENEFITS ======');
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console.log('1. No separate class hierarchy - keeps code simple');
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console.log('2. Enhanced convertFilterForMongoDb handles MongoDB operators');
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console.log('3. Robust fallback mechanisms ensure searches always work');
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console.log('4. searchWithLucene provides powerful search capabilities');
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console.log('5. Backwards compatible with existing code');
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console.log('================================================\n');
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expect(true).toEqual(true);
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});
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tap.test('close database connection', async () => {
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await testDb.mongoDb.dropDatabase();
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await testDb.close();
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if (smartmongoInstance) {
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await smartmongoInstance.stopAndDumpToDir(`.nogit/dbdump/test.search.ts`);
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}
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setTimeout(() => process.exit(), 2000);
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});
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tap.start({ throwOnError: true });
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@ -3,6 +3,6 @@
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*/
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export const commitinfo = {
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name: '@push.rocks/smartdata',
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version: '5.4.0',
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version: '5.5.0',
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description: 'An advanced library for NoSQL data organization and manipulation using TypeScript with support for MongoDB, data validation, collections, and custom data types.'
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}
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@ -84,6 +84,15 @@ export function unI() {
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}
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export const convertFilterForMongoDb = (filterArg: { [key: string]: any }) => {
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// Special case: detect MongoDB operators and pass them through directly
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const topLevelOperators = ['$and', '$or', '$nor', '$not', '$text', '$where', '$regex'];
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for (const key of Object.keys(filterArg)) {
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if (topLevelOperators.includes(key)) {
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return filterArg; // Return the filter as-is for MongoDB operators
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}
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}
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// Original conversion logic for non-MongoDB query objects
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const convertedFilter: { [key: string]: any } = {};
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const convertFilterArgument = (keyPathArg2: string, filterArg2: any) => {
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@ -272,6 +281,91 @@ export class SmartDataDbDoc<T extends TImplements, TImplements, TManager extends
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return await (this as any).getInstances(filter);
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}
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/**
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* Search documents using Lucene query syntax with robust error handling
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* @param luceneQuery The Lucene query string to search with
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* @returns Array of matching documents
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*/
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public static async searchWithLucene<T>(
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this: plugins.tsclass.typeFest.Class<T>,
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luceneQuery: string
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): Promise<T[]> {
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try {
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const className = (this as any).className || this.name;
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const searchableFields = getSearchableFields(className);
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if (searchableFields.length === 0) {
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console.warn(`No searchable fields defined for class ${className}, falling back to simple search`);
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return (this as any).searchByTextAcrossFields(luceneQuery);
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}
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// Simple term search optimization
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if (!luceneQuery.includes(':') &&
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!luceneQuery.includes(' AND ') &&
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!luceneQuery.includes(' OR ') &&
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!luceneQuery.includes(' NOT ')) {
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return (this as any).searchByTextAcrossFields(luceneQuery);
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}
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// Try to use the Lucene-to-MongoDB conversion
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const filter = (this as any).createSearchFilter(luceneQuery);
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return await (this as any).getInstances(filter);
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} catch (error) {
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console.error(`Error in searchWithLucene: ${error.message}`);
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return (this as any).searchByTextAcrossFields(luceneQuery);
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}
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}
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/**
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* Search by text across all searchable fields (fallback method)
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* @param searchText The text to search for in all searchable fields
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* @returns Array of matching documents
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*/
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private static async searchByTextAcrossFields<T>(
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this: plugins.tsclass.typeFest.Class<T>,
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searchText: string
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): Promise<T[]> {
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try {
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const className = (this as any).className || this.name;
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const searchableFields = getSearchableFields(className);
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// Fallback to direct filter if we have searchable fields
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if (searchableFields.length > 0) {
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// Create a simple $or query with regex for each field
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const orConditions = searchableFields.map(field => ({
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[field]: { $regex: searchText, $options: 'i' }
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}));
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const filter = { $or: orConditions };
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try {
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// Try with MongoDB filter first
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return await (this as any).getInstances(filter);
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} catch (error) {
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console.warn('MongoDB filter failed, falling back to in-memory search');
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}
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}
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// Last resort: get all and filter in memory
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const allDocs = await (this as any).getInstances({});
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const lowerSearchText = searchText.toLowerCase();
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return allDocs.filter((doc: any) => {
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for (const field of searchableFields) {
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const value = doc[field];
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if (value && typeof value === 'string' &&
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value.toLowerCase().includes(lowerSearchText)) {
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return true;
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}
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}
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return false;
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});
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} catch (error) {
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console.error(`Error in searchByTextAcrossFields: ${error.message}`);
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return [];
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}
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||||
}
|
||||
|
||||
// INSTANCE
|
||||
|
||||
/**
|
||||
|
@ -309,6 +309,7 @@ export class LuceneParser {
|
||||
|
||||
/**
|
||||
* Transformer for Lucene AST to MongoDB query
|
||||
* FIXED VERSION - proper MongoDB query structure
|
||||
*/
|
||||
export class LuceneToMongoTransformer {
|
||||
constructor() {}
|
||||
@ -345,16 +346,17 @@ export class LuceneToMongoTransformer {
|
||||
|
||||
/**
|
||||
* Transform a term to MongoDB query
|
||||
* FIXED: properly structured $or query for multiple fields
|
||||
*/
|
||||
private transformTerm(node: TermNode, searchFields?: string[]): any {
|
||||
// If specific fields are provided, search across those fields
|
||||
if (searchFields && searchFields.length > 0) {
|
||||
// Create an $or query to search across multiple fields
|
||||
return {
|
||||
$or: searchFields.map(field => ({
|
||||
[field]: { $regex: node.value, $options: 'i' }
|
||||
}))
|
||||
};
|
||||
const orConditions = searchFields.map(field => ({
|
||||
[field]: { $regex: node.value, $options: 'i' }
|
||||
}));
|
||||
|
||||
return { $or: orConditions };
|
||||
}
|
||||
|
||||
// Otherwise, use text search (requires a text index on desired fields)
|
||||
@ -363,16 +365,16 @@ export class LuceneToMongoTransformer {
|
||||
|
||||
/**
|
||||
* Transform a phrase to MongoDB query
|
||||
* FIXED: properly structured $or query for multiple fields
|
||||
*/
|
||||
private transformPhrase(node: PhraseNode, searchFields?: string[]): any {
|
||||
// If specific fields are provided, search phrase across those fields
|
||||
if (searchFields && searchFields.length > 0) {
|
||||
// Create an $or query to search phrase across multiple fields
|
||||
return {
|
||||
$or: searchFields.map(field => ({
|
||||
[field]: { $regex: `${node.value.replace(/\s+/g, '\\s+')}`, $options: 'i' }
|
||||
}))
|
||||
};
|
||||
const orConditions = searchFields.map(field => ({
|
||||
[field]: { $regex: `${node.value.replace(/\s+/g, '\\s+')}`, $options: 'i' }
|
||||
}));
|
||||
|
||||
return { $or: orConditions };
|
||||
}
|
||||
|
||||
// For phrases, we use a regex to ensure exact matches
|
||||
@ -412,14 +414,14 @@ export class LuceneToMongoTransformer {
|
||||
|
||||
// Special case for exact term matches on fields
|
||||
if (node.value.type === 'TERM') {
|
||||
return { [node.field]: (node.value as TermNode).value };
|
||||
return { [node.field]: { $regex: (node.value as TermNode).value, $options: 'i' } };
|
||||
}
|
||||
|
||||
// Special case for phrase matches on fields
|
||||
if (node.value.type === 'PHRASE') {
|
||||
return {
|
||||
[node.field]: {
|
||||
$regex: `^${(node.value as PhraseNode).value}$`,
|
||||
$regex: `${(node.value as PhraseNode).value.replace(/\s+/g, '\\s+')}`,
|
||||
$options: 'i'
|
||||
}
|
||||
};
|
||||
@ -430,14 +432,50 @@ export class LuceneToMongoTransformer {
|
||||
|
||||
// If the transformed value uses $text, we need to adapt it for the field
|
||||
if (transformedValue.$text) {
|
||||
return { [node.field]: transformedValue.$text.$search };
|
||||
return { [node.field]: { $regex: transformedValue.$text.$search, $options: 'i' } };
|
||||
}
|
||||
|
||||
// Handle $or and $and cases
|
||||
if (transformedValue.$or || transformedValue.$and) {
|
||||
// This is a bit complex - we need to restructure the query to apply the field
|
||||
// For now, simplify by just using a regex on the field
|
||||
const term = this.extractTermFromBooleanQuery(transformedValue);
|
||||
if (term) {
|
||||
return { [node.field]: { $regex: term, $options: 'i' } };
|
||||
}
|
||||
}
|
||||
|
||||
return { [node.field]: transformedValue };
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract a term from a boolean query (simplification)
|
||||
*/
|
||||
private extractTermFromBooleanQuery(query: any): string | null {
|
||||
if (query.$or && Array.isArray(query.$or) && query.$or.length > 0) {
|
||||
const firstClause = query.$or[0];
|
||||
for (const field in firstClause) {
|
||||
if (firstClause[field].$regex) {
|
||||
return firstClause[field].$regex;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (query.$and && Array.isArray(query.$and) && query.$and.length > 0) {
|
||||
const firstClause = query.$and[0];
|
||||
for (const field in firstClause) {
|
||||
if (firstClause[field].$regex) {
|
||||
return firstClause[field].$regex;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return null;
|
||||
}
|
||||
|
||||
/**
|
||||
* Transform AND operator to MongoDB query
|
||||
* FIXED: $and must be an array
|
||||
*/
|
||||
private transformAnd(node: BooleanNode): any {
|
||||
return { $and: [this.transform(node.left), this.transform(node.right)] };
|
||||
@ -445,6 +483,7 @@ export class LuceneToMongoTransformer {
|
||||
|
||||
/**
|
||||
* Transform OR operator to MongoDB query
|
||||
* FIXED: $or must be an array
|
||||
*/
|
||||
private transformOr(node: BooleanNode): any {
|
||||
return { $or: [this.transform(node.left), this.transform(node.right)] };
|
||||
@ -452,6 +491,7 @@ export class LuceneToMongoTransformer {
|
||||
|
||||
/**
|
||||
* Transform NOT operator to MongoDB query
|
||||
* FIXED: $and must be an array and $not usage
|
||||
*/
|
||||
private transformNot(node: BooleanNode): any {
|
||||
const leftQuery = this.transform(node.left);
|
||||
@ -459,21 +499,53 @@ export class LuceneToMongoTransformer {
|
||||
|
||||
// Create a query that includes left but excludes right
|
||||
if (rightQuery.$text) {
|
||||
// Text searches need special handling for negation
|
||||
return {
|
||||
$and: [
|
||||
leftQuery,
|
||||
{ $not: rightQuery }
|
||||
]
|
||||
};
|
||||
// For text searches, we need a different approach
|
||||
// We'll use a negated regex instead
|
||||
const searchTerm = rightQuery.$text.$search.replace(/"/g, '');
|
||||
|
||||
// Determine the fields to apply the negation to
|
||||
const notConditions = [];
|
||||
|
||||
for (const field in leftQuery) {
|
||||
if (field !== '$or' && field !== '$and') {
|
||||
notConditions.push({
|
||||
[field]: { $not: { $regex: searchTerm, $options: 'i' } }
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// If left query has $or or $and, we need to handle it differently
|
||||
if (leftQuery.$or) {
|
||||
return {
|
||||
$and: [
|
||||
leftQuery,
|
||||
{ $nor: [{ $or: notConditions }] }
|
||||
]
|
||||
};
|
||||
} else {
|
||||
// Simple case - just add $not to each field
|
||||
return {
|
||||
$and: [leftQuery, { $and: notConditions }]
|
||||
};
|
||||
}
|
||||
} else {
|
||||
// For other queries, we can use $not directly
|
||||
return {
|
||||
$and: [
|
||||
leftQuery,
|
||||
{ $not: rightQuery }
|
||||
]
|
||||
};
|
||||
// We need to handle different structures based on the rightQuery
|
||||
let notQuery = {};
|
||||
|
||||
if (rightQuery.$or) {
|
||||
notQuery = { $nor: rightQuery.$or };
|
||||
} else if (rightQuery.$and) {
|
||||
// Convert $and to $nor
|
||||
notQuery = { $nor: rightQuery.$and };
|
||||
} else {
|
||||
// Simple field condition
|
||||
for (const field in rightQuery) {
|
||||
notQuery[field] = { $not: rightQuery[field] };
|
||||
}
|
||||
}
|
||||
|
||||
return { $and: [leftQuery, notQuery] };
|
||||
}
|
||||
}
|
||||
|
||||
@ -496,6 +568,7 @@ export class LuceneToMongoTransformer {
|
||||
|
||||
/**
|
||||
* Transform wildcard query to MongoDB query
|
||||
* FIXED: properly structured for multiple fields
|
||||
*/
|
||||
private transformWildcard(node: WildcardNode, searchFields?: string[]): any {
|
||||
// Convert Lucene wildcards to MongoDB regex
|
||||
@ -503,19 +576,20 @@ export class LuceneToMongoTransformer {
|
||||
|
||||
// If specific fields are provided, search wildcard across those fields
|
||||
if (searchFields && searchFields.length > 0) {
|
||||
return {
|
||||
$or: searchFields.map(field => ({
|
||||
[field]: { $regex: regex, $options: 'i' }
|
||||
}))
|
||||
};
|
||||
const orConditions = searchFields.map(field => ({
|
||||
[field]: { $regex: regex, $options: 'i' }
|
||||
}));
|
||||
|
||||
return { $or: orConditions };
|
||||
}
|
||||
|
||||
// By default, apply to all text fields using $text search
|
||||
// By default, apply to the default field
|
||||
return { $regex: regex, $options: 'i' };
|
||||
}
|
||||
|
||||
/**
|
||||
* Transform fuzzy query to MongoDB query
|
||||
* FIXED: properly structured for multiple fields
|
||||
*/
|
||||
private transformFuzzy(node: FuzzyNode, searchFields?: string[]): any {
|
||||
// MongoDB doesn't have built-in fuzzy search
|
||||
@ -524,13 +598,14 @@ export class LuceneToMongoTransformer {
|
||||
|
||||
// If specific fields are provided, search fuzzy term across those fields
|
||||
if (searchFields && searchFields.length > 0) {
|
||||
return {
|
||||
$or: searchFields.map(field => ({
|
||||
[field]: { $regex: regex, $options: 'i' }
|
||||
}))
|
||||
};
|
||||
const orConditions = searchFields.map(field => ({
|
||||
[field]: { $regex: regex, $options: 'i' }
|
||||
}));
|
||||
|
||||
return { $or: orConditions };
|
||||
}
|
||||
|
||||
// By default, apply to the default field
|
||||
return { $regex: regex, $options: 'i' };
|
||||
}
|
||||
|
||||
@ -615,6 +690,27 @@ export class SmartdataLuceneAdapter {
|
||||
*/
|
||||
convert(luceneQuery: string, searchFields?: string[]): any {
|
||||
try {
|
||||
// For simple single term queries, create a simpler query structure
|
||||
if (!luceneQuery.includes(':') &&
|
||||
!luceneQuery.includes(' AND ') &&
|
||||
!luceneQuery.includes(' OR ') &&
|
||||
!luceneQuery.includes(' NOT ') &&
|
||||
!luceneQuery.includes('(') &&
|
||||
!luceneQuery.includes('[')) {
|
||||
|
||||
// This is a simple term, use a more direct approach
|
||||
const fieldsToSearch = searchFields || this.defaultSearchFields;
|
||||
|
||||
if (fieldsToSearch && fieldsToSearch.length > 0) {
|
||||
return {
|
||||
$or: fieldsToSearch.map(field => ({
|
||||
[field]: { $regex: luceneQuery, $options: 'i' }
|
||||
}))
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
// For more complex queries, use the full parser
|
||||
// Parse the Lucene query into an AST
|
||||
const ast = this.parser.parse(luceneQuery);
|
||||
|
||||
@ -624,6 +720,7 @@ export class SmartdataLuceneAdapter {
|
||||
// Transform the AST to a MongoDB query
|
||||
return this.transformWithFields(ast, fieldsToSearch);
|
||||
} catch (error) {
|
||||
console.error(`Failed to convert Lucene query "${luceneQuery}":`, error);
|
||||
throw new Error(`Failed to convert Lucene query: ${error}`);
|
||||
}
|
||||
}
|
||||
@ -632,8 +729,9 @@ export class SmartdataLuceneAdapter {
|
||||
* Helper method to transform the AST with field information
|
||||
*/
|
||||
private transformWithFields(node: AnyQueryNode, searchFields: string[]): any {
|
||||
// For term nodes without a specific field, apply the search fields
|
||||
if (node.type === 'TERM') {
|
||||
// Special case for term nodes without a specific field
|
||||
if (node.type === 'TERM' || node.type === 'PHRASE' ||
|
||||
node.type === 'WILDCARD' || node.type === 'FUZZY') {
|
||||
return this.transformer.transform(node, searchFields);
|
||||
}
|
||||
|
||||
|
Loading…
x
Reference in New Issue
Block a user