集合索引

// List the indexes on the collection and output them as an array
const result = await collection.listIndexes().toArray();
// Print the list of indexes
console.log("Existing indexes:\n");
for(const doc in result){
    console.log(doc);
}

const database = client.db("sample_mflix");
const movies = database.collection("movies");
// Create an ascending index on the "title" field in the
// "movies" collection.
const result = await movies.createIndex({ title: 1 });
console.log(`Index created: ${result}`);

// Define the query parameters
const query = { title: "Batman" }
const sort = { title: 1 };
const projection = { _id: 0, title: 1 };
// Execute the query using the defined parameters
const cursor = movies
  .find(query)
  .sort(sort)
  .project(projection);
for await (const doc of cursor) {
  console.log(doc);
}

// Connect to the "sample_mflix" database
const database = client.db("sample_mflix");
// Access the database's "movies" collection
const movies = database.collection("movies");
// Create an ascending index on the "type" and "genre" fields
// in the "movies" collection.
const result = await movies.createIndex({ type: 1, genre: 1 });
console.log(`Index created: ${result}`);

// Define a query to find movies in the "Drama" genre
const query = { type: "movie", genre: "Drama" };
// Define sorting criteria for the query results
const sort = { type: 1, genre: 1 };
// Include only the type and genre fields in the query results
const projection = { _id: 0, type: 1, genre: 1 };
// Execute the query using the defined criteria and projection
const cursor = movies
  .find(query)
  .sort(sort)
  .project(projection);
for await (const doc of cursor) {
  console.log(doc);
}

const database = client.db("sample_mflix");
const movies = database.collection("movies");
// Create a multikey index on the "cast" field in the "movies" collection
const result = await movies.createIndex({ cast: 1 });

const query = { cast: "Viola Davis" };
const projection = { _id: 0, cast: 1 , title: 1 };
// Perform a find operation with the preceding filter and projection
const cursor = movies
  .find(query)
  .project(projection);
for await (const doc of cursor) {
  console.log(doc);
}

const db = client.db('tea');
await db.createCollection('ratings', {
  clusteredIndex: {
    key: { _id: 1 },
    unique: true
  }
});

// Get the database and collection on which to create the index 
const myDB = client.db("testDB");
const myColl = myDB.collection("blogPosts");
// Create a text index on the "title" and "body" fields
const result = await myColl.createIndex(
  { title: "text", body: "text" },
  {
     default_language: "english",
     weights: { body: 10, title: 3 }
  }
);

// Query for documents where body or title contain "life ahead"
const query = { $text: { $search: "life ahead" } };
// Show only the title field
const projection = { _id: 0, title: 1 };
// Execute the find operation
const cursor = myColl.find(query).project(projection);
for await (const doc of cursor) {
  console.log(doc);
}

const database = client.db("sample_mflix");
const movies = database.collection("movies");
/* Create a 2dsphere index on the "location.geo" field in the
"movies" collection */
const result = await movies.createIndex({ "location.geo": "2dsphere" });
// Print the result of the index creation
console.log(`Index created: ${result}`);

const database = client.db("sample_mflix");
const movies = database.collection("movies");
// Create a unique index on the "theaterId" field in the "theaters" collection.
const result = await movies.createIndex({ theaterId: 1 }, { unique: true });
console.log(`Index created: ${result}`);

// Creates a MongoDB Search index
const index1 = {
    name: "search1",
    definition: {
        "mappings": {
            "dynamic": true
        }
    }
}
await collection.createSearchIndex(index1);

// Creates a MongoDB Vector Search index
const vectorSearchIdx = {
    name: "vsidx1",
    type: "vectorSearch",
    definition: {
        fields: [{
            type: "vector",
            numDimensions: 384,
            path: "summary",
            similarity: "dotProduct"
        }]
    }
}
await collection.createSearchIndex(vectorSearchIdx);

// Lists search indexes
const result = await collection.listSearchIndexes().toArray();
console.log("Existing search indexes:\n");
for (const doc in result) {
    console.log(doc);
}

// Updates a search index
const index2 = {
    "mappings": {
        "dynamic": true,
        "fields": {
            "description": {
                "type": "string"
            }
        }
    }
}
await collection.updateSearchIndex("search1", index2);

// Drops (deletes) a search index
await collection.dropSearchIndex("search1");