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Abfragen von Daten in Azure Cosmos DB for MongoDB mithilfe von JavaScript

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GILT FÜR: MongoDB

Verwenden Sie Abfragen und Aggregationspipelines, um Dokumente in einer Sammlung zu finden und zu bearbeiten.

Hinweis

Die Beispielcodeausschnitte sind auf GitHub als JavaScript-Projekt verfügbar.

„API für MongoDB“-Referenzdokumentation | MongoDB-Paket (npm)

Abfragen von Dokumenten

Verwenden Sie zum Suchen von Dokumenten eine Abfrage, um die betreffenden Dokumente zu finden.

// assume doc exists

const product = {
    _id: ObjectId("62b1f43a9446918500c875c5"),
    category: "gear-surf-surfboards",
    name: "Yamba Surfboard 7",
    quantity: 12,
    sale: false
};


// For unsharded database: use id
const query1 = { _id: ObjectId(product._id) };
const foundById = await client.db("adventureworks").collection('products').findOne(query1);
console.log(`Read doc:\t\n${Object.keys(foundById).map(key => `\t${key}: ${foundById[key]}\n`)}`);

// For sharded database: point read doc from collection using the id and partitionKey
const query2 = { _id: ObjectId(product._id), category: product.category };
const foundByIdAndPartitionKey = await client.db("adventureworks").collection('products').findOne(query2);
console.log(`Read doc 2:\t\n${Object.keys(foundByIdAndPartitionKey).map(key => `\t${key}: ${foundByIdAndPartitionKey[key]}\n`)}`);


// Find one by unique doc property value
const query3 = { name: product.name};
const foundByUniqueValue = await client.db("adventureworks").collection('products').findOne(query3);
console.log(`Read doc 3:\t\n${Object.keys(foundByUniqueValue).map(key => `\t${key}: ${foundByUniqueValue[key]}\n`)}`);

// Find one (with many that match query) still returns one doc
const query4 = { category: product.category };
const foundByNonUniqueValue = await client.db("adventureworks").collection('products').findOne(query4);
console.log(`Read doc 4:\t\n${Object.keys(foundByNonUniqueValue).map(key => `\t${key}: ${foundByNonUniqueValue[key]}\n`)}`);

// Find all that match query
const query5 = { category: product.category };
const foundAll = await client.db("adventureworks").collection('products').find(query5).sort({_id: 1}).toArray();
console.log(`Matching all in product category:\n${foundAll.map(doc => `\t${doc._id}: ${doc.name}\n`)}`);

// Find all in collection with empty query {}
const foundAll2 = await client.db("adventureworks").collection('products').find({}).toArray();
console.log(`All docs:\n${foundAll2.map(doc => `\t${doc._id}: ${doc.name}\n`)}`);

// Pagination - next 5 docs
// sort by name require an index on name
const nextFiveDocs = await client.db("adventureworks").collection('products').find({}).sort({name: 1}).skip(5).limit(5).toArray();
console.log(`All docs:\n${foundAll2.map(doc => `\t${doc._id}: ${doc.name}\n`)}`);

Der obige Codeschnipsel zeigt die folgende Beispielausgabe in der Konsole an:

Read doc:
        _id: 62b1f43a9446918500c875c5
,       name: Yamba Surfboard-13
,       category: gear-surf-surfboards
,       quantity: 20
,       sale: false
,       discontinued: true

Read doc 2:
        _id: 62b1f43a9446918500c875c5
,       name: Yamba Surfboard-13
,       category: gear-surf-surfboards
,       quantity: 20
,       sale: false
,       discontinued: true

Read doc 3:
        _id: 62b23a371a09ed6441e5ee31
,       category: gear-surf-surfboards
,       name: Yamba Surfboard 7
,       quantity: 5
,       sale: true
,       discontinued: true

Read doc 4:
        _id: 62b1f43a9446918500c875c5
,       name: Yamba Surfboard-13
,       category: gear-surf-surfboards
,       quantity: 20
,       sale: false
,       discontinued: true

Matching all in product category:
        62b1f43a9446918500c875c5: Yamba Surfboard-13
,       62b1f4670c7af8c2942b7c10: Yamba Surfboard-3
,       62b1f46fa6546d2afb5715ac: Yamba Surfboard-90
,       62b1f474e4b43498c05d295b: Yamba Surfboard-9

All docs:
        62b1f43a9446918500c875c5: Yamba Surfboard-13
,       62b1f4670c7af8c2942b7c10: Yamba Surfboard-3
,       62b1f46fa6546d2afb5715ac: Yamba Surfboard-90
,       62b1f474e4b43498c05d295b: Yamba Surfboard-9
,       62b1f47896aa8cfa280edf2d: Yamba Surfboard-55
,       62b1f47dacbf04e86c8abf25: Yamba Surfboard-11
,       62b1f4804ee53f4c5c44778c: Yamba Surfboard-97
,       62b1f492ff69395b30a03169: Yamba Surfboard-93
,       62b23a371a09ed6441e5ee30: Yamba Surfboard 3
,       62b23a371a09ed6441e5ee31: Yamba Surfboard 7

All docs:
        62b1f43a9446918500c875c5: Yamba Surfboard-13
,       62b1f4670c7af8c2942b7c10: Yamba Surfboard-3
,       62b1f46fa6546d2afb5715ac: Yamba Surfboard-90
,       62b1f474e4b43498c05d295b: Yamba Surfboard-9
,       62b1f47896aa8cfa280edf2d: Yamba Surfboard-55
,       62b1f47dacbf04e86c8abf25: Yamba Surfboard-11
,       62b1f4804ee53f4c5c44778c: Yamba Surfboard-97
,       62b1f492ff69395b30a03169: Yamba Surfboard-93
,       62b23a371a09ed6441e5ee30: Yamba Surfboard 3
,       62b23a371a09ed6441e5ee31: Yamba Surfboard 7

done

Aggregationspipelines

Aggregationspipelines sind nützlich zum Isolieren von kostenintensiven Abfrageberechnungen, Transformationen und anderen Verarbeitungen auf Ihrem Azure Cosmos DB-Server, statt diese Vorgänge auf dem Client durchzuführen.

Spezifische Informationen zur Unterstützung von Aggregationspipelines finden Sie hier:

Syntax einer Aggregationspipeline

Eine Pipeline ist ein Array mit einer Reihe von Stufen in Form von JSON-Objekten.

const pipeline = [
    stage1,
    stage2
]

Syntax einer Pipelinestufe

Eine Stufe definiert den Vorgang und die Daten, auf die dieser angewendet wird, z. B.:

  • $match: Suchen nach Dokumenten
  • $addFields: Fügt dem Cursor ein Feld hinzu, normalerweise aus der vorherigen Stufe
  • $limit: Begrenzt die Anzahl von Ergebnissen, die im Cursor zurückgegeben werden
  • $project: Übergabe neuer oder vorhandener Felder, dies können berechnete Felder sein
  • $group: Gruppieren der Ergebnisse nach einem oder mehreren Feldern in der Pipeline
  • $sort: Sortieren der Ergebnisse
// reduce collection to relative documents
const matchStage = {
    '$match': {
        'categoryName': { $regex: 'Bikes' },
    }
}

// sort documents on field `name`
const sortStage = { 
    '$sort': { 
        "name": 1 
    } 
},

Aggregieren der Pipeline zum Abrufen eines iterierbaren Cursors

Die Pipeline wird aggregiert, um einen iterierbaren Cursor zu erzeugen.

const db = 'adventureworks';
const collection = 'products';

const aggCursor = client.db(databaseName).collection(collectionName).aggregate(pipeline);

await aggCursor.forEach(product => {
    console.log(JSON.stringify(product));
});

Verwenden einer Aggregationspipeline in JavaScript

Verwenden Sie eine Pipeline, um die Daten bis zur Rückgabe an den Client auf dem Server zu verarbeiten.

Beispielproduktdaten

Die nachstehenden Aggregationen verwenden die Beispielproduktsammlung mit Daten in folgender Form:

[
    {
        "_id": "08225A9E-F2B3-4FA3-AB08-8C70ADD6C3C2",
        "categoryId": "75BF1ACB-168D-469C-9AA3-1FD26BB4EA4C",
        "categoryName": "Bikes, Touring Bikes",
        "sku": "BK-T79U-50",
        "name": "Touring-1000 Blue, 50",
        "description": "The product called \"Touring-1000 Blue, 50\"",
        "price": 2384.0700000000002,
        "tags": [
        ]
    },
    {
        "_id": "0F124781-C991-48A9-ACF2-249771D44029",
        "categoryId": "56400CF3-446D-4C3F-B9B2-68286DA3BB99",
        "categoryName": "Bikes, Mountain Bikes",
        "sku": "BK-M68B-42",
        "name": "Mountain-200 Black, 42",
        "description": "The product called \"Mountain-200 Black, 42\"",
        "price": 2294.9899999999998,
        "tags": [
        ]
    },
    {
        "_id": "3FE1A99E-DE14-4D11-B635-F5D39258A0B9",
        "categoryId": "26C74104-40BC-4541-8EF5-9892F7F03D72",
        "categoryName": "Components, Saddles",
        "sku": "SE-T924",
        "name": "HL Touring Seat/Saddle",
        "description": "The product called \"HL Touring Seat/Saddle\"",
        "price": 52.640000000000001,
        "tags": [
        ]
    },
]

Beispiel 1: Produktunterkategorien, Anzahl von Produkten und Durchschnittspreis

Verwenden Sie den folgenden Beispielcode, um den Durchschnittspreis in jeder Produktunterkategorie zu melden.

// Goal: Find the average price of each product subcategory with 
// the number of products in that subcategory.
// Sort by average price descending.

// Read .env file and set environment variables
require('dotenv').config();

// Use official mongodb driver to connect to the server
const { MongoClient } = require('mongodb');

// New instance of MongoClient with connection string
// for Cosmos DB
const url = process.env.COSMOS_CONNECTION_STRING;
const client = new MongoClient(url);

async function main() {

  try {

    // Use connect method to connect to the server
    await client.connect();

    // Group all products by category
    // Find average price of each category
    // Count # of products in each category
    const groupByCategory = {
      '$group': {
        '_id': '$categoryName',
        'averagePrice': {
          '$avg': '$price'
        },
        'countOfProducts': {
          '$sum': 1
        }
      },
    };

    // Round price to 2 decimal places
    // Don't return _id
    // Rename category name help in `_id` to `categoryName`
    // Round prices to 2 decimal places
    // Rename property for countOfProducts to nProducts
    const additionalTransformations = {
      '$project': {
        '_id': 0,
        'category': '$_id',
        'nProducts':'$countOfProducts',
        'averagePrice': { '$round': ['$averagePrice', 2] }
      }
    };

    // Sort by average price descending
    const sort = { '$sort': { '$averagePrice': -1 } };

    // stages execute in order from top to bottom
    const pipeline = [
      groupByCategory,
      additionalTransformations,
      sort
    ];

    const db = 'adventureworks';
    const collection = 'products';

    // Get iterable cursor
    const aggCursor = client.db(db).collection(collection).aggregate(pipeline);

    // Display each item in cursor
    await aggCursor.forEach(product => {
      console.log(JSON.stringify(product));
    });

    return 'done';
  } catch (err) {
    console.log(JSON.stringify(err));
  }
}

main()
  .then(console.log)
  .catch(console.error)
  .finally(() => {
    // Close the db and its underlying connections
    client.close()
  });

// Results:
// {"averagePrice":51.99,"category":"Clothing, Jerseys","nProducts":8}
// {"averagePrice":1683.36,"category":"Bikes, Mountain Bikes","nProducts":32}
// {"averagePrice":1597.45,"category":"Bikes, Road Bikes","nProducts":43}
// {"averagePrice":20.24,"category":"Components, Chains","nProducts":1}
// {"averagePrice":25,"category":"Accessories, Locks","nProducts":1}
// {"averagePrice":631.42,"category":"Components, Touring Frames","nProducts":18}
// {"averagePrice":9.25,"category":"Clothing, Socks","nProducts":4}
// {"averagePrice":125,"category":"Accessories, Panniers","nProducts":1}
// ... remaining fields ...

Beispiel 2: Fahrradtypen mit Preisspanne

Verwenden Sie den folgenden Beispielcode, um Informationen zur Unterkategorie Bikes zu melden.

// Goal: Find the price range for the different bike subcategories. 

// Read .env file and set environment variables
require('dotenv').config();

// Use official mongodb driver to connect to the server
const { MongoClient } = require('mongodb');

// New instance of MongoClient with connection string
// for Cosmos DB
const url = process.env.COSMOS_CONNECTION_STRING;
const client = new MongoClient(url);

async function main() {

  try {

    // Use connect method to connect to the server
    await client.connect();

    const categoryName = 'Bikes';

    const findAllBikes = {
      '$match': {
        'categoryName': { $regex:  categoryName},
      }
    };

    // Convert 'Bikes, Touring Bikes' to ['Bikes', 'Touring Bikes']
    const splitStringIntoCsvArray = {
      $addFields: {
        'categories': { '$split': ['$categoryName', ', '] }
      }
    };

    // Remove first element from array
    // Converts ['Bikes', 'Touring Bikes'] to ['Touring Bikes']
    const removeFirstElement = {
      $addFields: {
        'subcategory': { '$slice': ['$categories', 1, { $subtract: [{ $size: '$categories' }, 1] }] }
      }
    }

    // Group items by book subcategory, and find min, avg, and max price
    const groupBySubcategory = {
      '$group': {
        '_id': '$subcategory',
        'maxPrice': {
          '$max': '$price'
        },
        'averagePrice': {
          '$avg': '$price'
        },
        'minPrice': {
          '$min': '$price'
        },
        'countOfProducts': {
          '$sum': 1
        }
      },
    };

    // Miscellaneous transformations
    // Don't return _id
    // Convert subcategory from array of 1 item to string in `name`
    // Round prices to 2 decimal places
    // Rename property for countOfProducts to nProducts
    const additionalTransformations = {
      '$project': {
        '_id': 0,
        'name': { '$arrayElemAt': ['$_id', 0]},
        'nProducts': '$countOfProducts',
        'min': { '$round': ['$minPrice', 2] },
        'avg': { '$round': ['$averagePrice', 2] },
        'max': { '$round': ['$maxPrice', 2] }
      }
    };

    // Sort by subcategory
    const sortBySubcategory = { '$sort': 
        { 'name': 1 } 
    };

    // stages execute in order from top to bottom
    const pipeline = [
      findAllBikes,
      splitStringIntoCsvArray,
      removeFirstElement,
      groupBySubcategory,
      additionalTransformations,
      sortBySubcategory
    ];

    const db = 'adventureworks';
    const collection = 'products';

    // Get iterable cursor
    const aggCursor = client.db(db).collection(collection).aggregate(pipeline);

    // Display each item in cursor
    await aggCursor.forEach(product => {
      console.log(JSON.stringify(product));
    });

    return 'done';
  } catch (err) {
    console.log(JSON.stringify(err));
  }
}

main()
  .then(console.log)
  .catch(console.error)
  .finally(() => {
    // Close the db and its underlying connections
    client.close();
  });

// Results: 
// {'name':'Mountain Bikes','nProducts':32,'min':539.99,'avg':1683.37,'max':3399.99}
// {'name':'Road Bikes','nProducts':43,'min':539.99,'avg':1597.45,'max':3578.27}
// {'name':'Touring Bikes','nProducts':22,'min':742.35,'avg':1425.25,'max':2384.07}

Siehe auch