Multi-attribute keys pattern - Amazon DynamoDB
OverviewApplication exampleData modelPrerequisitesImplementationPattern variationsComplete exampleAdditional resources

Multi-attribute keys pattern

Overview

Multi-attribute keys allow you to create Global Secondary Index (GSI) partition and sort keys composed of up to four attributes each. This reduces client-side code and makes it easier to initially model data and add new access patterns later.

Consider a common scenario: to create a GSI that queries items by multiple hierarchical attributes, you would traditionally need to create synthetic keys by concatenating values. For example, in a gaming app, to query tournament matches by tournament, region, and round, you might create a synthetic GSI partition key like TOURNAMENT#WINTER2024#REGION#NA-EAST and a synthetic sort key like ROUND#SEMIFINALS#BRACKET#UPPER. This approach works, but requires string concatenation when writing data, parsing when reading, and backfilling synthetic keys across all existing items if you're adding the GSI to an existing table. This makes code more cluttered and challenging to maintain type safety on individual key components.

Multi-attribute keys solve this problem for GSIs. You define your GSI partition key using multiple existing attributes like tournamentId and region. DynamoDB handles the composite key logic automatically, hashing them together for data distribution. You write items using natural attributes from your domain model, and the GSI automatically indexes them. No concatenation, no parsing, no backfilling. Your code stays clean, your data stays typed, and your queries stay simple. This approach is particularly useful when you have hierarchical data with natural attribute groupings (like tournament → region → round, or organization → department → team).

Application example

This guide walks through building a tournament match tracking system for an esports platform. The platform needs to efficiently query matches across multiple dimensions: by tournament and region for bracket management, by player for match history, and by date for scheduling.

Data model

In this walkthrough, the tournament match tracking system supports three primary access patterns, each requiring a different key structure:

Access pattern 1: Look up a specific match by its unique ID

  • Solution: Base table with matchId as partition key

Access pattern 2: Query all matches for a specific tournament and region, optionally filtering by round, bracket, or match

  • Solution: Global Secondary Index with multi-attribute partition key (tournamentId + region) and multi-attribute sort key (round + bracket + matchId)

  • Example queries: "All WINTER2024 matches in NA-EAST region" or "All SEMIFINALS matches in UPPER bracket for WINTER2024/NA-EAST"

Access pattern 3: Query a player's match history, optionally filtering by date range or tournament round

  • Solution: Global Secondary Index with single partition key (player1Id) and multi-attribute sort key (matchDate + round)

  • Example queries: "All matches for player 101" or "Player 101's matches in January 2024"

The key difference between traditional and multi-attribute approaches becomes clear when examining the item structure:

Traditional Global Secondary Index approach (concatenated keys):

// Manual concatenation required for GSI keys
const item = {
    matchId: 'match-001',                                          // Base table PK
    tournamentId: 'WINTER2024',
    region: 'NA-EAST',
    round: 'SEMIFINALS',
    bracket: 'UPPER',
    player1Id: '101',
    // Synthetic keys needed for GSI
    GSI_PK: `TOURNAMENT#${tournamentId}#REGION#${region}`,       // Must concatenate
    GSI_SK: `${round}#${bracket}#${matchId}`,                    // Must concatenate
    // ... other attributes
};

Multi-attribute Global Secondary Index approach (native keys):

// Use existing attributes directly - no concatenation needed
const item = {
    matchId: 'match-001',                                          // Base table PK
    tournamentId: 'WINTER2024',
    region: 'NA-EAST',
    round: 'SEMIFINALS',
    bracket: 'UPPER',
    player1Id: '101',
    matchDate: '2024-01-18',
    // No synthetic keys needed - GSI uses existing attributes directly
    // ... other attributes
};

With multi-attribute keys, you write items once with natural domain attributes. DynamoDB automatically indexes them across multiple GSIs without requiring synthetic concatenated keys.

Base table schema:

  • Partition key: matchId (1 attribute)

Global Secondary Index Schema (TournamentRegionIndex with multi-attribute keys):

  • Partition key: tournamentId, region (2 attributes)

  • Sort key: round, bracket, matchId (3 attributes)

Global Secondary Index Schema (PlayerMatchHistoryIndex with multi-attribute keys):

  • Partition key: player1Id (1 attribute)

  • Sort key: matchDate, round (2 attributes)

Base table: TournamentMatches

matchId (PK) tournamentId region round bracket player1Id player2Id matchDate winner score
match-001 WINTER2024 NA-EAST FINALS CHAMPIONSHIP 101 103 2024-01-20 101 3-1
match-002 WINTER2024 NA-EAST SEMIFINALS UPPER 101 105 2024-01-18 101 3-2
match-003 WINTER2024 NA-EAST SEMIFINALS UPPER 103 107 2024-01-18 103 3-0
match-004 WINTER2024 NA-EAST QUARTERFINALS UPPER 101 109 2024-01-15 101 3-1
match-005 WINTER2024 NA-WEST FINALS CHAMPIONSHIP 102 104 2024-01-20 102 3-2
match-006 WINTER2024 NA-WEST SEMIFINALS UPPER 102 106 2024-01-18 102 3-1
match-007 SPRING2024 NA-EAST QUARTERFINALS UPPER 101 108 2024-03-15 101 3-0
match-008 SPRING2024 NA-EAST QUARTERFINALS LOWER 103 110 2024-03-15 103 3-2

GSI: TournamentRegionIndex (multi-attribute keys)

tournamentId (PK) region (PK) round (SK) bracket (SK) matchId (SK) player1Id player2Id matchDate winner score
WINTER2024 NA-EAST FINALS CHAMPIONSHIP match-001 101 103 2024-01-20 101 3-1
WINTER2024 NA-EAST QUARTERFINALS UPPER match-004 101 109 2024-01-15 101 3-1
WINTER2024 NA-EAST SEMIFINALS UPPER match-002 101 105 2024-01-18 101 3-2
WINTER2024 NA-EAST SEMIFINALS UPPER match-003 103 107 2024-01-18 103 3-0
WINTER2024 NA-WEST FINALS CHAMPIONSHIP match-005 102 104 2024-01-20 102 3-2
WINTER2024 NA-WEST SEMIFINALS UPPER match-006 102 106 2024-01-18 102 3-1
SPRING2024 NA-EAST QUARTERFINALS LOWER match-008 103 110 2024-03-15 103 3-2
SPRING2024 NA-EAST QUARTERFINALS UPPER match-007 101 108 2024-03-15 101 3-0

GSI: PlayerMatchHistoryIndex (multi-attribute keys)

player1Id (PK) matchDate (SK) round (SK) tournamentId region bracket matchId player2Id winner score
101 2024-01-15 QUARTERFINALS WINTER2024 NA-EAST UPPER match-004 109 101 3-1
101 2024-01-18 SEMIFINALS WINTER2024 NA-EAST UPPER match-002 105 101 3-2
101 2024-01-20 FINALS WINTER2024 NA-EAST CHAMPIONSHIP match-001 103 101 3-1
101 2024-03-15 QUARTERFINALS SPRING2024 NA-EAST UPPER match-007 108 101 3-0
102 2024-01-18 SEMIFINALS WINTER2024 NA-WEST UPPER match-006 106 102 3-1
102 2024-01-20 FINALS WINTER2024 NA-WEST CHAMPIONSHIP match-005 104 102 3-2
103 2024-01-18 SEMIFINALS WINTER2024 NA-EAST UPPER match-003 107 103 3-0
103 2024-03-15 QUARTERFINALS SPRING2024 NA-EAST LOWER match-008 110 103 3-2

Prerequisites

Before you begin, ensure you have:

Account and permissions

  • An active AWS account (create one here if needed)

  • IAM permissions for DynamoDB operations:

    • dynamodb:CreateTable

    • dynamodb:DeleteTable

    • dynamodb:DescribeTable

    • dynamodb:PutItem

    • dynamodb:Query

    • dynamodb:BatchWriteItem

Note

Security Note: For production use, create a custom IAM policy with only the permissions you need. For this tutorial, you can use the AWS managed policy AmazonDynamoDBFullAccessV2.

Development Environment

  • Node.js installed on your machine

  • AWS credentials configured using one of these methods:

Option 1: AWS CLI

aws configure

Option 2: Environment Variables

export AWS_ACCESS_KEY_ID=your_access_key_here
export AWS_SECRET_ACCESS_KEY=your_secret_key_here
export AWS_DEFAULT_REGION=us-east-1

Install Required Packages

npm install @aws-sdk/client-dynamodb @aws-sdk/lib-dynamodb

Implementation

Step 1: Create table with GSIs using multi-attribute keys

Create a table with a simple base key structure and GSIs that use multi-attribute keys.

import { DynamoDBClient, CreateTableCommand } from "@aws-sdk/client-dynamodb";

const client = new DynamoDBClient({ region: 'us-west-2' });

const response = await client.send(new CreateTableCommand({
    TableName: 'TournamentMatches',
    
    // Base table: Simple partition key
    KeySchema: [
        { AttributeName: 'matchId', KeyType: 'HASH' }              // Simple PK
    ],
    
    AttributeDefinitions: [
        { AttributeName: 'matchId', AttributeType: 'S' },
        { AttributeName: 'tournamentId', AttributeType: 'S' },
        { AttributeName: 'region', AttributeType: 'S' },
        { AttributeName: 'round', AttributeType: 'S' },
        { AttributeName: 'bracket', AttributeType: 'S' },
        { AttributeName: 'player1Id', AttributeType: 'S' },
        { AttributeName: 'matchDate', AttributeType: 'S' }
    ],
    
    // GSIs with multi-attribute keys
    GlobalSecondaryIndexes: [
        {
            IndexName: 'TournamentRegionIndex',
            KeySchema: [
                { AttributeName: 'tournamentId', KeyType: 'HASH' },    // GSI PK attribute 1
                { AttributeName: 'region', KeyType: 'HASH' },          // GSI PK attribute 2
                { AttributeName: 'round', KeyType: 'RANGE' },          // GSI SK attribute 1
                { AttributeName: 'bracket', KeyType: 'RANGE' },        // GSI SK attribute 2
                { AttributeName: 'matchId', KeyType: 'RANGE' }         // GSI SK attribute 3
            ],
            Projection: { ProjectionType: 'ALL' }
        },
        {
            IndexName: 'PlayerMatchHistoryIndex',
            KeySchema: [
                { AttributeName: 'player1Id', KeyType: 'HASH' },       // GSI PK
                { AttributeName: 'matchDate', KeyType: 'RANGE' },      // GSI SK attribute 1
                { AttributeName: 'round', KeyType: 'RANGE' }           // GSI SK attribute 2
            ],
            Projection: { ProjectionType: 'ALL' }
        }
    ],
    
    BillingMode: 'PAY_PER_REQUEST'
}));

console.log("Table with multi-attribute GSI keys created successfully");

Key design decisions:

Base table: The base table uses a simple matchId partition key for direct match lookups, keeping the base table structure straightforward while the GSIs provide the complex query patterns.

TournamentRegionIndex Global Secondary Index: The TournamentRegionIndex Global Secondary Index uses tournamentId + region as a multi-attribute partition key, creating tournament-region isolation where data is distributed by the hash of both attributes combined, enabling efficient queries within a specific tournament-region context. The multi-attribute sort key (round + bracket + matchId) provides hierarchical sorting that supports queries at any level of the hierarchy with natural ordering from general (round) to specific (match ID).

PlayerMatchHistoryIndex Global Secondary Index: The PlayerMatchHistoryIndex Global Secondary Index reorganizes data by player using player1Id as the partition key, enabling cross-tournament queries for a specific player. The multi-attribute sort key (matchDate + round) provides chronological ordering with the ability to filter by date ranges or specific tournament rounds.

Step 2: Insert data with native attributes

Add tournament match data using natural attributes. The GSI will automatically index these attributes without requiring synthetic keys.

import { DynamoDBClient } from "@aws-sdk/client-dynamodb";
import { DynamoDBDocumentClient, PutCommand } from "@aws-sdk/lib-dynamodb";

const client = new DynamoDBClient({ region: 'us-west-2' });
const docClient = DynamoDBDocumentClient.from(client);

// Tournament match data - no synthetic keys needed for GSIs
const matches = [
    // Winter 2024 Tournament, NA-EAST region
    {
        matchId: 'match-001',
        tournamentId: 'WINTER2024',
        region: 'NA-EAST',
        round: 'FINALS',
        bracket: 'CHAMPIONSHIP',
        player1Id: '101',
        player2Id: '103',
        matchDate: '2024-01-20',
        winner: '101',
        score: '3-1'
    },
    {
        matchId: 'match-002',
        tournamentId: 'WINTER2024',
        region: 'NA-EAST',
        round: 'SEMIFINALS',
        bracket: 'UPPER',
        player1Id: '101',
        player2Id: '105',
        matchDate: '2024-01-18',
        winner: '101',
        score: '3-2'
    },
    {
        matchId: 'match-003',
        tournamentId: 'WINTER2024',
        region: 'NA-EAST',
        round: 'SEMIFINALS',
        bracket: 'UPPER',
        player1Id: '103',
        player2Id: '107',
        matchDate: '2024-01-18',
        winner: '103',
        score: '3-0'
    },
    {
        matchId: 'match-004',
        tournamentId: 'WINTER2024',
        region: 'NA-EAST',
        round: 'QUARTERFINALS',
        bracket: 'UPPER',
        player1Id: '101',
        player2Id: '109',
        matchDate: '2024-01-15',
        winner: '101',
        score: '3-1'
    },
    
    // Winter 2024 Tournament, NA-WEST region
    {
        matchId: 'match-005',
        tournamentId: 'WINTER2024',
        region: 'NA-WEST',
        round: 'FINALS',
        bracket: 'CHAMPIONSHIP',
        player1Id: '102',
        player2Id: '104',
        matchDate: '2024-01-20',
        winner: '102',
        score: '3-2'
    },
    {
        matchId: 'match-006',
        tournamentId: 'WINTER2024',
        region: 'NA-WEST',
        round: 'SEMIFINALS',
        bracket: 'UPPER',
        player1Id: '102',
        player2Id: '106',
        matchDate: '2024-01-18',
        winner: '102',
        score: '3-1'
    },
    
    // Spring 2024 Tournament, NA-EAST region
    {
        matchId: 'match-007',
        tournamentId: 'SPRING2024',
        region: 'NA-EAST',
        round: 'QUARTERFINALS',
        bracket: 'UPPER',
        player1Id: '101',
        player2Id: '108',
        matchDate: '2024-03-15',
        winner: '101',
        score: '3-0'
    },
    {
        matchId: 'match-008',
        tournamentId: 'SPRING2024',
        region: 'NA-EAST',
        round: 'QUARTERFINALS',
        bracket: 'LOWER',
        player1Id: '103',
        player2Id: '110',
        matchDate: '2024-03-15',
        winner: '103',
        score: '3-2'
    }
];

// Insert all matches
for (const match of matches) {
    await docClient.send(new PutCommand({
        TableName: 'TournamentMatches',
        Item: match
    }));
    
    console.log(`Added: ${match.matchId} - ${match.tournamentId}/${match.region} - ${match.round} ${match.bracket}`);
}

console.log(`\nInserted ${matches.length} tournament matches`);
console.log("No synthetic keys created - GSIs use native attributes automatically");

Data structure explained:

Natural attribute usage: Each attribute represents a real tournament concept with no string concatenation or parsing required, providing direct mapping to the domain model.

Automatic Global Secondary Index indexing: The GSIs automatically index items using the existing attributes (tournamentId, region, round, bracket, matchId for TournamentRegionIndex and player1Id, matchDate, round for PlayerMatchHistoryIndex) without requiring synthetic concatenated keys.

No backfilling needed: When you add a new Global Secondary Index with multi-attribute keys to an existing table, DynamoDB automatically indexes all existing items using their natural attributes—no need to update items with synthetic keys.

Step 3: Query TournamentRegionIndex Global Secondary Index with all partition key attributes

This example queries the TournamentRegionIndex Global Secondary Index which has a multi-attribute partition key (tournamentId + region). All partition key attributes must be specified with equality conditions in queries—you cannot query with just tournamentId alone or use inequality operators on partition key attributes.

import { DynamoDBClient } from "@aws-sdk/client-dynamodb";
import { DynamoDBDocumentClient, QueryCommand } from "@aws-sdk/lib-dynamodb";

const client = new DynamoDBClient({ region: 'us-west-2' });
const docClient = DynamoDBDocumentClient.from(client);

// Query GSI: All matches for WINTER2024 tournament in NA-EAST region
const response = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'TournamentRegionIndex',
    KeyConditionExpression: 'tournamentId = :tournament AND #region = :region',
    ExpressionAttributeNames: {
        '#region': 'region',  // 'region' is a reserved keyword
        '#tournament': 'tournament'
    },
    ExpressionAttributeValues: {
        ':tournament': 'WINTER2024',
        ':region': 'NA-EAST'
    }
}));

console.log(`Found ${response.Items.length} matches for WINTER2024/NA-EAST:\n`);
response.Items.forEach(match => {
    console.log(`  ${match.round} | ${match.bracket} | ${match.matchId}`);
    console.log(`    Players: ${match.player1Id} vs ${match.player2Id}`);
    console.log(`    Winner: ${match.winner}, Score: ${match.score}\n`);
});

Expected output:

Found 4 matches for WINTER2024/NA-EAST:

  FINALS | CHAMPIONSHIP | match-001
    Players: 101 vs 103
    Winner: 101, Score: 3-1

  QUARTERFINALS | UPPER | match-004
    Players: 101 vs 109
    Winner: 101, Score: 3-1

  SEMIFINALS | UPPER | match-002
    Players: 101 vs 105
    Winner: 101, Score: 3-2

  SEMIFINALS | UPPER | match-003
    Players: 103 vs 107
    Winner: 103, Score: 3-0

Invalid queries:

// Missing region attribute
KeyConditionExpression: 'tournamentId = :tournament'

// Using inequality on partition key attribute
KeyConditionExpression: 'tournamentId = :tournament AND #region > :region'

Performance: Multi-attribute partition keys are hashed together, providing the same O(1) lookup performance as single-attribute keys.

Step 4: Query Global Secondary Index sort keys left-to-right

Sort key attributes must be queried left-to-right in the order they're defined in the Global Secondary Index. This example demonstrates querying the TournamentRegionIndex at different hierarchy levels: filtering by just round, by round + bracket, or by all three sort key attributes. You cannot skip attributes in the middle—for example, you cannot query by round and matchId while skipping bracket.

import { DynamoDBClient } from "@aws-sdk/client-dynamodb";
import { DynamoDBDocumentClient, QueryCommand } from "@aws-sdk/lib-dynamodb";

const client = new DynamoDBClient({ region: 'us-west-2' });
const docClient = DynamoDBDocumentClient.from(client);

// Query 1: Filter by first sort key attribute (round)
console.log("Query 1: All SEMIFINALS matches");
const query1 = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'TournamentRegionIndex',
    KeyConditionExpression: 'tournamentId = :tournament AND #region = :region AND round = :round',
    ExpressionAttributeNames: {
        '#region': 'region'  // 'region' is a reserved keyword
    },
    ExpressionAttributeValues: {
        ':tournament': 'WINTER2024',
        ':region': 'NA-EAST',
        ':round': 'SEMIFINALS'
    }
}));
console.log(`  Found ${query1.Items.length} matches\n`);

// Query 2: Filter by first two sort key attributes (round + bracket)
console.log("Query 2: SEMIFINALS UPPER bracket matches");
const query2 = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'TournamentRegionIndex',
    KeyConditionExpression: 'tournamentId = :tournament AND #region = :region AND round = :round AND bracket = :bracket',
    ExpressionAttributeNames: {
        '#region': 'region'  // 'region' is a reserved keyword
    },
    ExpressionAttributeValues: {
        ':tournament': 'WINTER2024',
        ':region': 'NA-EAST',
        ':round': 'SEMIFINALS',
        ':bracket': 'UPPER'
    }
}));
console.log(`  Found ${query2.Items.length} matches\n`);

// Query 3: Filter by all three sort key attributes (round + bracket + matchId)
console.log("Query 3: Specific match in SEMIFINALS UPPER bracket");
const query3 = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'TournamentRegionIndex',
    KeyConditionExpression: 'tournamentId = :tournament AND #region = :region AND round = :round AND bracket = :bracket AND matchId = :matchId',
    ExpressionAttributeNames: {
        '#region': 'region'  // 'region' is a reserved keyword
    },
    ExpressionAttributeValues: {
        ':tournament': 'WINTER2024',
        ':region': 'NA-EAST',
        ':round': 'SEMIFINALS',
        ':bracket': 'UPPER',
        ':matchId': 'match-002'
    }
}));
console.log(`  Found ${query3.Items.length} matches\n`);

// Query 4: INVALID - skipping round
console.log("Query 4: Attempting to skip first sort key attribute (WILL FAIL)");
try {
    const query4 = await docClient.send(new QueryCommand({
        TableName: 'TournamentMatches',
        IndexName: 'TournamentRegionIndex',
        KeyConditionExpression: 'tournamentId = :tournament AND #region = :region AND bracket = :bracket',
        ExpressionAttributeNames: {
            '#region': 'region'  // 'region' is a reserved keyword
        },
        ExpressionAttributeValues: {
            ':tournament': 'WINTER2024',
            ':region': 'NA-EAST',
            ':bracket': 'UPPER'
        }
    }));
} catch (error) {
    console.log(`  Error: ${error.message}`);
    console.log(`  Cannot skip sort key attributes - must query left-to-right\n`);
}

Expected output:

Query 1: All SEMIFINALS matches
  Found 2 matches

Query 2: SEMIFINALS UPPER bracket matches
  Found 2 matches

Query 3: Specific match in SEMIFINALS UPPER bracket
  Found 1 matches

Query 4: Attempting to skip first sort key attribute (WILL FAIL)
  Error: Query key condition not supported
  Cannot skip sort key attributes - must query left-to-right

Left-to-right query rules: You must query attributes in order from left to right, without skipping any.

Valid patterns:

  • First attribute only: round = 'SEMIFINALS'

  • First two attributes: round = 'SEMIFINALS' AND bracket = 'UPPER'

  • All three attributes: round = 'SEMIFINALS' AND bracket = 'UPPER' AND matchId = 'match-002'

Invalid patterns:

  • Skipping the first attribute: bracket = 'UPPER' (skips round)

  • Querying out of order: matchId = 'match-002' AND round = 'SEMIFINALS'

  • Leaving gaps: round = 'SEMIFINALS' AND matchId = 'match-002' (skips bracket)

Note

Design tip: Order sort key attributes from most general to most specific to maximize query flexibility.

Step 5: Use inequality conditions on Global Secondary Index sort keys

Inequality conditions must be the last condition in your query. This example demonstrates using comparison operators (>=, BETWEEN) and prefix matching (begins_with()) on sort key attributes. Once you use an inequality operator, you cannot add any additional sort key conditions after it—the inequality must be the final condition in your key condition expression.

import { DynamoDBClient } from "@aws-sdk/client-dynamodb";
import { DynamoDBDocumentClient, QueryCommand } from "@aws-sdk/lib-dynamodb";

const client = new DynamoDBClient({ region: 'us-west-2' });
const docClient = DynamoDBDocumentClient.from(client);

// Query 1: Round comparison (inequality on first sort key attribute)
console.log("Query 1: Matches from QUARTERFINALS onwards");
const query1 = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'TournamentRegionIndex',
    KeyConditionExpression: 'tournamentId = :tournament AND #region = :region AND round >= :round',
    ExpressionAttributeNames: {
        '#region': 'region'  // 'region' is a reserved keyword
    },
    ExpressionAttributeValues: {
        ':tournament': 'WINTER2024',
        ':region': 'NA-EAST',
        ':round': 'QUARTERFINALS'
    }
}));
console.log(`  Found ${query1.Items.length} matches\n`);

// Query 2: Round range with BETWEEN
console.log("Query 2: Matches between QUARTERFINALS and SEMIFINALS");
const query2 = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'TournamentRegionIndex',
    KeyConditionExpression: 'tournamentId = :tournament AND #region = :region AND round BETWEEN :start AND :end',
    ExpressionAttributeNames: {
        '#region': 'region'  // 'region' is a reserved keyword
    },
    ExpressionAttributeValues: {
        ':tournament': 'WINTER2024',
        ':region': 'NA-EAST',
        ':start': 'QUARTERFINALS',
        ':end': 'SEMIFINALS'
    }
}));
console.log(`  Found ${query2.Items.length} matches\n`);

// Query 3: Prefix matching with begins_with (treated as inequality)
console.log("Query 3: Matches in brackets starting with 'U'");
const query3 = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'TournamentRegionIndex',
    KeyConditionExpression: 'tournamentId = :tournament AND #region = :region AND round = :round AND begins_with(bracket, :prefix)',
    ExpressionAttributeNames: {
        '#region': 'region'  // 'region' is a reserved keyword
    },
    ExpressionAttributeValues: {
        ':tournament': 'WINTER2024',
        ':region': 'NA-EAST',
        ':round': 'SEMIFINALS',
        ':prefix': 'U'
    }
}));
console.log(`  Found ${query3.Items.length} matches\n`);

// Query 4: INVALID - condition after inequality
console.log("Query 4: Attempting condition after inequality (WILL FAIL)");
try {
    const query4 = await docClient.send(new QueryCommand({
        TableName: 'TournamentMatches',
        IndexName: 'TournamentRegionIndex',
        KeyConditionExpression: 'tournamentId = :tournament AND #region = :region AND round > :round AND bracket = :bracket',
        ExpressionAttributeNames: {
            '#region': 'region'  // 'region' is a reserved keyword
        },
        ExpressionAttributeValues: {
            ':tournament': 'WINTER2024',
            ':region': 'NA-EAST',
            ':round': 'QUARTERFINALS',
            ':bracket': 'UPPER'
        }
    }));
} catch (error) {
    console.log(`  Error: ${error.message}`);
    console.log(`  Cannot add conditions after inequality - it must be last\n`);
}

Inequality operator rules: You can use comparison operators (>, >=, <, <=), BETWEEN for range queries, and begins_with() for prefix matching. The inequality must be the last condition in your query.

Valid patterns:

  • Equality conditions followed by inequality: round = 'SEMIFINALS' AND bracket = 'UPPER' AND matchId > 'match-001'

  • Inequality on first attribute: round BETWEEN 'QUARTERFINALS' AND 'SEMIFINALS'

  • Prefix matching as final condition: round = 'SEMIFINALS' AND begins_with(bracket, 'U')

Invalid patterns:

  • Adding conditions after an inequality: round > 'QUARTERFINALS' AND bracket = 'UPPER'

  • Using multiple inequalities: round > 'QUARTERFINALS' AND bracket > 'L'

Important

begins_with() is treated as an inequality condition, so no additional sort key conditions can follow it.

Step 6: Query PlayerMatchHistoryIndex Global Secondary Index with multi-attribute sort key

This example queries the PlayerMatchHistoryIndex which has a single partition key (player1Id) and a multi-attribute sort key (matchDate + round). This enables cross-tournament analysis by querying all matches for a specific player without knowing tournament IDs—whereas the base table would require separate queries per tournament-region combination.

import { DynamoDBClient } from "@aws-sdk/client-dynamodb";
import { DynamoDBDocumentClient, QueryCommand } from "@aws-sdk/lib-dynamodb";

const client = new DynamoDBClient({ region: 'us-west-2' });
const docClient = DynamoDBDocumentClient.from(client);

// Query 1: All matches for Player 101 across all tournaments
console.log("Query 1: All matches for Player 101");
const query1 = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'PlayerMatchHistoryIndex',
    KeyConditionExpression: 'player1Id = :player',
    ExpressionAttributeValues: {
        ':player': '101'
    }
}));

console.log(`  Found ${query1.Items.length} matches for Player 101:`);
query1.Items.forEach(match => {
    console.log(`    ${match.tournamentId}/${match.region} - ${match.matchDate} - ${match.round}`);
});
console.log();

// Query 2: Player 101 matches on specific date
console.log("Query 2: Player 101 matches on 2024-01-18");
const query2 = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'PlayerMatchHistoryIndex',
    KeyConditionExpression: 'player1Id = :player AND matchDate = :date',
    ExpressionAttributeValues: {
        ':player': '101',
        ':date': '2024-01-18'
    }
}));

console.log(`  Found ${query2.Items.length} matches\n`);

// Query 3: Player 101 SEMIFINALS matches on specific date
console.log("Query 3: Player 101 SEMIFINALS matches on 2024-01-18");
const query3 = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'PlayerMatchHistoryIndex',
    KeyConditionExpression: 'player1Id = :player AND matchDate = :date AND round = :round',
    ExpressionAttributeValues: {
        ':player': '101',
        ':date': '2024-01-18',
        ':round': 'SEMIFINALS'
    }
}));

console.log(`  Found ${query3.Items.length} matches\n`);

// Query 4: Player 101 matches in date range
console.log("Query 4: Player 101 matches in January 2024");
const query4 = await docClient.send(new QueryCommand({
    TableName: 'TournamentMatches',
    IndexName: 'PlayerMatchHistoryIndex',
    KeyConditionExpression: 'player1Id = :player AND matchDate BETWEEN :start AND :end',
    ExpressionAttributeValues: {
        ':player': '101',
        ':start': '2024-01-01',
        ':end': '2024-01-31'
    }
}));

console.log(`  Found ${query4.Items.length} matches\n`);

Pattern variations

Time-series data with multi-attribute keys

Optimize for time-series queries with hierarchical time attributes

{
    TableName: 'IoTReadings',
    // Base table: Simple partition key
    KeySchema: [
        { AttributeName: 'readingId', KeyType: 'HASH' }
    ],
    AttributeDefinitions: [
        { AttributeName: 'readingId', AttributeType: 'S' },
        { AttributeName: 'deviceId', AttributeType: 'S' },
        { AttributeName: 'locationId', AttributeType: 'S' },
        { AttributeName: 'year', AttributeType: 'S' },
        { AttributeName: 'month', AttributeType: 'S' },
        { AttributeName: 'day', AttributeType: 'S' },
        { AttributeName: 'timestamp', AttributeType: 'S' }
    ],
    // GSI with multi-attribute keys for time-series queries
    GlobalSecondaryIndexes: [{
        IndexName: 'DeviceLocationTimeIndex',
        KeySchema: [
            { AttributeName: 'deviceId', KeyType: 'HASH' },
            { AttributeName: 'locationId', KeyType: 'HASH' },
            { AttributeName: 'year', KeyType: 'RANGE' },
            { AttributeName: 'month', KeyType: 'RANGE' },
            { AttributeName: 'day', KeyType: 'RANGE' },
            { AttributeName: 'timestamp', KeyType: 'RANGE' }
        ],
        Projection: { ProjectionType: 'ALL' }
    }],
    BillingMode: 'PAY_PER_REQUEST'
}

// Query patterns enabled via GSI:
// - All readings for device in location
// - Readings for specific year
// - Readings for specific month in year
// - Readings for specific day
// - Readings in time range

Benefits: Natural time hierarchy (year → month → day → timestamp) enables efficient queries at any time granularity without date parsing or manipulation. Global Secondary Index automatically indexes all readings using their natural time attributes.

E-commerce orders with multi-attribute keys

Track orders with multiple dimensions

{
    TableName: 'Orders',
    // Base table: Simple partition key
    KeySchema: [
        { AttributeName: 'orderId', KeyType: 'HASH' }
    ],
    AttributeDefinitions: [
        { AttributeName: 'orderId', AttributeType: 'S' },
        { AttributeName: 'sellerId', AttributeType: 'S' },
        { AttributeName: 'region', AttributeType: 'S' },
        { AttributeName: 'orderDate', AttributeType: 'S' },
        { AttributeName: 'category', AttributeType: 'S' },
        { AttributeName: 'customerId', AttributeType: 'S' },
        { AttributeName: 'orderStatus', AttributeType: 'S' }
    ],
    GlobalSecondaryIndexes: [
        {
            IndexName: 'SellerRegionIndex',
            KeySchema: [
                { AttributeName: 'sellerId', KeyType: 'HASH' },
                { AttributeName: 'region', KeyType: 'HASH' },
                { AttributeName: 'orderDate', KeyType: 'RANGE' },
                { AttributeName: 'category', KeyType: 'RANGE' },
                { AttributeName: 'orderId', KeyType: 'RANGE' }
            ],
            Projection: { ProjectionType: 'ALL' }
        },
        {
            IndexName: 'CustomerOrdersIndex',
            KeySchema: [
                { AttributeName: 'customerId', KeyType: 'HASH' },
                { AttributeName: 'orderDate', KeyType: 'RANGE' },
                { AttributeName: 'orderStatus', KeyType: 'RANGE' }
            ],
            Projection: { ProjectionType: 'ALL' }
        }
    ],
    BillingMode: 'PAY_PER_REQUEST'
}

// SellerRegionIndex GSI queries:
// - Orders by seller and region
// - Orders by seller, region, and date
// - Orders by seller, region, date, and category

// CustomerOrdersIndex GSI queries:
// - Customer's orders
// - Customer's orders by date
// - Customer's orders by date and status

Hierarchical organization data

Model organizational hierarchies

{
    TableName: 'Employees',
    // Base table: Simple partition key
    KeySchema: [
        { AttributeName: 'employeeId', KeyType: 'HASH' }
    ],
    AttributeDefinitions: [
        { AttributeName: 'employeeId', AttributeType: 'S' },
        { AttributeName: 'companyId', AttributeType: 'S' },
        { AttributeName: 'divisionId', AttributeType: 'S' },
        { AttributeName: 'departmentId', AttributeType: 'S' },
        { AttributeName: 'teamId', AttributeType: 'S' },
        { AttributeName: 'skillCategory', AttributeType: 'S' },
        { AttributeName: 'skillLevel', AttributeType: 'S' },
        { AttributeName: 'yearsExperience', AttributeType: 'N' }
    ],
    GlobalSecondaryIndexes: [
        {
            IndexName: 'OrganizationIndex',
            KeySchema: [
                { AttributeName: 'companyId', KeyType: 'HASH' },
                { AttributeName: 'divisionId', KeyType: 'HASH' },
                { AttributeName: 'departmentId', KeyType: 'RANGE' },
                { AttributeName: 'teamId', KeyType: 'RANGE' },
                { AttributeName: 'employeeId', KeyType: 'RANGE' }
            ],
            Projection: { ProjectionType: 'ALL' }
        },
        {
            IndexName: 'SkillsIndex',
            KeySchema: [
                { AttributeName: 'skillCategory', KeyType: 'HASH' },
                { AttributeName: 'skillLevel', KeyType: 'RANGE' },
                { AttributeName: 'yearsExperience', KeyType: 'RANGE' }
            ],
            Projection: { ProjectionType: 'INCLUDE', NonKeyAttributes: ['employeeId', 'name'] }
        }
    ],
    BillingMode: 'PAY_PER_REQUEST'
}

// OrganizationIndex GSI query patterns:
// - All employees in company/division
// - Employees in specific department
// - Employees in specific team

// SkillsIndex GSI query patterns:
// - Employees by skill and experience level

Sparse multi-attribute keys

Combine multi-attribute keys to make a sparse GSI

{
    TableName: 'Products',
    // Base table: Simple partition key
    KeySchema: [
        { AttributeName: 'productId', KeyType: 'HASH' }
    ],
    AttributeDefinitions: [
        { AttributeName: 'productId', AttributeType: 'S' },
        { AttributeName: 'categoryId', AttributeType: 'S' },
        { AttributeName: 'subcategoryId', AttributeType: 'S' },
        { AttributeName: 'averageRating', AttributeType: 'N' },
        { AttributeName: 'reviewCount', AttributeType: 'N' }
    ],
    GlobalSecondaryIndexes: [
        {
            IndexName: 'CategoryIndex',
            KeySchema: [
                { AttributeName: 'categoryId', KeyType: 'HASH' },
                { AttributeName: 'subcategoryId', KeyType: 'HASH' },
                { AttributeName: 'productId', KeyType: 'RANGE' }
            ],
            Projection: { ProjectionType: 'ALL' }
        },
        {
            IndexName: 'ReviewedProductsIndex',
            KeySchema: [
                { AttributeName: 'categoryId', KeyType: 'HASH' },
                { AttributeName: 'averageRating', KeyType: 'RANGE' },  // Optional attribute
                { AttributeName: 'reviewCount', KeyType: 'RANGE' }     // Optional attribute
            ],
            Projection: { ProjectionType: 'ALL' }
        }
    ],
    BillingMode: 'PAY_PER_REQUEST'
}

// Only products with reviews appear in ReviewedProductsIndex GSI
// Automatic filtering without application logic
// Multi-attribute sort key enables rating and count queries

SaaS multi-tenancy

Multi-tenant SaaS platform with customer isolation

// Table design
{
    TableName: 'SaasData',
    // Base table: Simple partition key
    KeySchema: [
        { AttributeName: 'resourceId', KeyType: 'HASH' }
    ],
    AttributeDefinitions: [
        { AttributeName: 'resourceId', AttributeType: 'S' },
        { AttributeName: 'tenantId', AttributeType: 'S' },
        { AttributeName: 'customerId', AttributeType: 'S' },
        { AttributeName: 'resourceType', AttributeType: 'S' }
    ],
    // GSI with multi-attribute keys for tenant-customer isolation
    GlobalSecondaryIndexes: [{
        IndexName: 'TenantCustomerIndex',
        KeySchema: [
            { AttributeName: 'tenantId', KeyType: 'HASH' },
            { AttributeName: 'customerId', KeyType: 'HASH' },
            { AttributeName: 'resourceType', KeyType: 'RANGE' },
            { AttributeName: 'resourceId', KeyType: 'RANGE' }
        ],
        Projection: { ProjectionType: 'ALL' }
    }],
    BillingMode: 'PAY_PER_REQUEST'
}

// Query GSI: All resources for tenant T001, customer C001
const resources = await docClient.send(new QueryCommand({
    TableName: 'SaasData',
    IndexName: 'TenantCustomerIndex',
    KeyConditionExpression: 'tenantId = :tenant AND customerId = :customer',
    ExpressionAttributeValues: {
        ':tenant': 'T001',
        ':customer': 'C001'
    }
}));

// Query GSI: Specific resource type for tenant/customer
const documents = await docClient.send(new QueryCommand({
    TableName: 'SaasData',
    IndexName: 'TenantCustomerIndex',
    KeyConditionExpression: 'tenantId = :tenant AND customerId = :customer AND resourceType = :type',
    ExpressionAttributeValues: {
        ':tenant': 'T001',
        ':customer': 'C001',
        ':type': 'document'
    }
}));

Benefits: Efficient queries within tenant-customer context and natural data organization.

Financial transactions

Banking system tracking account transactions using GSIs

// Table design
{
    TableName: 'BankTransactions',
    // Base table: Simple partition key
    KeySchema: [
        { AttributeName: 'transactionId', KeyType: 'HASH' }
    ],
    AttributeDefinitions: [
        { AttributeName: 'transactionId', AttributeType: 'S' },
        { AttributeName: 'accountId', AttributeType: 'S' },
        { AttributeName: 'year', AttributeType: 'S' },
        { AttributeName: 'month', AttributeType: 'S' },
        { AttributeName: 'day', AttributeType: 'S' },
        { AttributeName: 'transactionType', AttributeType: 'S' }
    ],
    GlobalSecondaryIndexes: [
        {
            IndexName: 'AccountTimeIndex',
            KeySchema: [
                { AttributeName: 'accountId', KeyType: 'HASH' },
                { AttributeName: 'year', KeyType: 'RANGE' },
                { AttributeName: 'month', KeyType: 'RANGE' },
                { AttributeName: 'day', KeyType: 'RANGE' },
                { AttributeName: 'transactionId', KeyType: 'RANGE' }
            ],
            Projection: { ProjectionType: 'ALL' }
        },
        {
            IndexName: 'TransactionTypeIndex',
            KeySchema: [
                { AttributeName: 'accountId', KeyType: 'HASH' },
                { AttributeName: 'transactionType', KeyType: 'RANGE' },
                { AttributeName: 'year', KeyType: 'RANGE' },
                { AttributeName: 'month', KeyType: 'RANGE' }
            ],
            Projection: { ProjectionType: 'ALL' }
        }
    ],
    BillingMode: 'PAY_PER_REQUEST'
}

// Query AccountTimeIndex GSI: All transactions for account in 2023
const yearTransactions = await docClient.send(new QueryCommand({
    TableName: 'BankTransactions',
    IndexName: 'AccountTimeIndex',
    KeyConditionExpression: 'accountId = :account AND #year = :year',
    ExpressionAttributeNames: { '#year': 'year' },
    ExpressionAttributeValues: {
        ':account': 'ACC-12345',
        ':year': '2023'
    }
}));

// Query AccountTimeIndex GSI: Transactions in specific month
const monthTransactions = await docClient.send(new QueryCommand({
    TableName: 'BankTransactions',
    IndexName: 'AccountTimeIndex',
    KeyConditionExpression: 'accountId = :account AND #year = :year AND #month = :month',
    ExpressionAttributeNames: { '#year': 'year', '#month': 'month' },
    ExpressionAttributeValues: {
        ':account': 'ACC-12345',
        ':year': '2023',
        ':month': '11'
    }
}));

// Query TransactionTypeIndex GSI: Deposits in 2023
const deposits = await docClient.send(new QueryCommand({
    TableName: 'BankTransactions',
    IndexName: 'TransactionTypeIndex',
    KeyConditionExpression: 'accountId = :account AND transactionType = :type AND #year = :year',
    ExpressionAttributeNames: { '#year': 'year' },
    ExpressionAttributeValues: {
        ':account': 'ACC-12345',
        ':type': 'deposit',
        ':year': '2023'
    }
}));

Complete example

The following example demonstrates multi-attribute keys from setup to cleanup:

import { 
    DynamoDBClient, 
    CreateTableCommand, 
    DeleteTableCommand, 
    waitUntilTableExists 
} from "@aws-sdk/client-dynamodb";
import { 
    DynamoDBDocumentClient, 
    PutCommand, 
    QueryCommand 
} from "@aws-sdk/lib-dynamodb";

const client = new DynamoDBClient({ region: 'us-west-2' });
const docClient = DynamoDBDocumentClient.from(client);

async function multiAttributeKeysDemo() {
    console.log("Starting Multi-Attribute GSI Keys Demo\n");
    
    // Step 1: Create table with GSIs using multi-attribute keys
    console.log("1. Creating table with multi-attribute GSI keys...");
    await client.send(new CreateTableCommand({
        TableName: 'TournamentMatches',
        KeySchema: [
            { AttributeName: 'matchId', KeyType: 'HASH' }
        ],
        AttributeDefinitions: [
            { AttributeName: 'matchId', AttributeType: 'S' },
            { AttributeName: 'tournamentId', AttributeType: 'S' },
            { AttributeName: 'region', AttributeType: 'S' },
            { AttributeName: 'round', AttributeType: 'S' },
            { AttributeName: 'bracket', AttributeType: 'S' },
            { AttributeName: 'player1Id', AttributeType: 'S' },
            { AttributeName: 'matchDate', AttributeType: 'S' }
        ],
        GlobalSecondaryIndexes: [
            {
                IndexName: 'TournamentRegionIndex',
                KeySchema: [
                    { AttributeName: 'tournamentId', KeyType: 'HASH' },
                    { AttributeName: 'region', KeyType: 'HASH' },
                    { AttributeName: 'round', KeyType: 'RANGE' },
                    { AttributeName: 'bracket', KeyType: 'RANGE' },
                    { AttributeName: 'matchId', KeyType: 'RANGE' }
                ],
                Projection: { ProjectionType: 'ALL' }
            },
            {
                IndexName: 'PlayerMatchHistoryIndex',
                KeySchema: [
                    { AttributeName: 'player1Id', KeyType: 'HASH' },
                    { AttributeName: 'matchDate', KeyType: 'RANGE' },
                    { AttributeName: 'round', KeyType: 'RANGE' }
                ],
                Projection: { ProjectionType: 'ALL' }
            }
        ],
        BillingMode: 'PAY_PER_REQUEST'
    }));
    
    await waitUntilTableExists({ client, maxWaitTime: 120 }, { TableName: 'TournamentMatches' });
    console.log("Table created\n");
    
    // Step 2: Insert tournament matches
    console.log("2. Inserting tournament matches...");
    const matches = [
        { matchId: 'match-001', tournamentId: 'WINTER2024', region: 'NA-EAST', round: 'FINALS', bracket: 'CHAMPIONSHIP', player1Id: '101', player2Id: '103', matchDate: '2024-01-20', winner: '101', score: '3-1' },
        { matchId: 'match-002', tournamentId: 'WINTER2024', region: 'NA-EAST', round: 'SEMIFINALS', bracket: 'UPPER', player1Id: '101', player2Id: '105', matchDate: '2024-01-18', winner: '101', score: '3-2' },
        { matchId: 'match-003', tournamentId: 'WINTER2024', region: 'NA-WEST', round: 'FINALS', bracket: 'CHAMPIONSHIP', player1Id: '102', player2Id: '104', matchDate: '2024-01-20', winner: '102', score: '3-2' },
        { matchId: 'match-004', tournamentId: 'SPRING2024', region: 'NA-EAST', round: 'QUARTERFINALS', bracket: 'UPPER', player1Id: '101', player2Id: '108', matchDate: '2024-03-15', winner: '101', score: '3-0' }
    ];
    
    for (const match of matches) {
        await docClient.send(new PutCommand({ TableName: 'TournamentMatches', Item: match }));
    }
    console.log(`Inserted ${matches.length} tournament matches\n`);
    
    // Step 3: Query GSI with multi-attribute partition key
    console.log("3. Query TournamentRegionIndex GSI: WINTER2024/NA-EAST matches");
    const gsiQuery1 = await docClient.send(new QueryCommand({
        TableName: 'TournamentMatches',
        IndexName: 'TournamentRegionIndex',
        KeyConditionExpression: 'tournamentId = :tournament AND #region = :region',
        ExpressionAttributeNames: { '#region': 'region' },
        ExpressionAttributeValues: { ':tournament': 'WINTER2024', ':region': 'NA-EAST' }
    }));
    
    console.log(`  Found ${gsiQuery1.Items.length} matches:`);
    gsiQuery1.Items.forEach(match => {
        console.log(`    ${match.round} - ${match.bracket} - ${match.winner} won`);
    });
    
    // Step 4: Query GSI with multi-attribute sort key
    console.log("\n4. Query PlayerMatchHistoryIndex GSI: All matches for Player 101");
    const gsiQuery2 = await docClient.send(new QueryCommand({
        TableName: 'TournamentMatches',
        IndexName: 'PlayerMatchHistoryIndex',
        KeyConditionExpression: 'player1Id = :player',
        ExpressionAttributeValues: { ':player': '101' }
    }));
    
    console.log(`  Found ${gsiQuery2.Items.length} matches for Player 101:`);
    gsiQuery2.Items.forEach(match => {
        console.log(`    ${match.tournamentId}/${match.region} - ${match.matchDate} - ${match.round}`);
    });
    
    console.log("\nDemo complete");
    console.log("No synthetic keys needed - GSIs use native attributes automatically");
}

async function cleanup() {
    console.log("Deleting table...");
    await client.send(new DeleteTableCommand({ TableName: 'TournamentMatches' }));
    console.log("Table deleted");
}

// Run demo
multiAttributeKeysDemo().catch(console.error);

// Uncomment to cleanup:
// cleanup().catch(console.error);

Minimal code scaffold

// 1. Create table with GSI using multi-attribute keys
await client.send(new CreateTableCommand({
    TableName: 'MyTable',
    KeySchema: [
        { AttributeName: 'id', KeyType: 'HASH' }        // Simple base table PK
    ],
    AttributeDefinitions: [
        { AttributeName: 'id', AttributeType: 'S' },
        { AttributeName: 'attr1', AttributeType: 'S' },
        { AttributeName: 'attr2', AttributeType: 'S' },
        { AttributeName: 'attr3', AttributeType: 'S' },
        { AttributeName: 'attr4', AttributeType: 'S' }
    ],
    GlobalSecondaryIndexes: [{
        IndexName: 'MyGSI',
        KeySchema: [
            { AttributeName: 'attr1', KeyType: 'HASH' },    // GSI PK attribute 1
            { AttributeName: 'attr2', KeyType: 'HASH' },    // GSI PK attribute 2
            { AttributeName: 'attr3', KeyType: 'RANGE' },   // GSI SK attribute 1
            { AttributeName: 'attr4', KeyType: 'RANGE' }    // GSI SK attribute 2
        ],
        Projection: { ProjectionType: 'ALL' }
    }],
    BillingMode: 'PAY_PER_REQUEST'
}));

// 2. Insert items with native attributes (no concatenation needed for GSI)
await docClient.send(new PutCommand({
    TableName: 'MyTable',
    Item: {
        id: 'item-001',
        attr1: 'value1',
        attr2: 'value2',
        attr3: 'value3',
        attr4: 'value4',
        // ... other attributes
    }
}));

// 3. Query GSI with all partition key attributes
await docClient.send(new QueryCommand({
    TableName: 'MyTable',
    IndexName: 'MyGSI',
    KeyConditionExpression: 'attr1 = :v1 AND attr2 = :v2',
    ExpressionAttributeValues: {
        ':v1': 'value1',
        ':v2': 'value2'
    }
}));

// 4. Query GSI with sort key attributes (left-to-right)
await docClient.send(new QueryCommand({
    TableName: 'MyTable',
    IndexName: 'MyGSI',
    KeyConditionExpression: 'attr1 = :v1 AND attr2 = :v2 AND attr3 = :v3',
    ExpressionAttributeValues: {
        ':v1': 'value1',
        ':v2': 'value2',
        ':v3': 'value3'
    }
}));

// Note: If any attribute name is a DynamoDB reserved keyword, use ExpressionAttributeNames:
// KeyConditionExpression: 'attr1 = :v1 AND #attr2 = :v2'
// ExpressionAttributeNames: { '#attr2': 'attr2' }

Additional resources