Table creation with AWS SDK in DynamoDB

Introduction

We create tables in DynamoDB to store and organize data in the cloud. Tables help keep data safe and easy to find.

When you want to save user information for a web app.

When you need to store product details for an online store.

When you want to keep track of orders or transactions.

When you need a fast and scalable database for your app.

When you want to organize data by categories or keys.

Syntax

DynamoDB

const AWS = require('aws-sdk');
AWS.config.update({ region: 'us-east-1' });
const dynamodb = new AWS.DynamoDB();

const params = {
  TableName: 'YourTableName',
  KeySchema: [
    { AttributeName: 'PrimaryKey', KeyType: 'HASH' }
  ],
  AttributeDefinitions: [
    { AttributeName: 'PrimaryKey', AttributeType: 'S' }
  ],
  ProvisionedThroughput: {
    ReadCapacityUnits: 5,
    WriteCapacityUnits: 5
  }
};

dynamodb.createTable(params, function(err, data) {
  if (err) console.log(err);
  else console.log('Table created:', data);
});

KeySchema defines the primary key for the table.

ProvisionedThroughput sets how much read and write capacity the table has.

Examples

This example creates a table named 'Users' with 'UserId' as the primary key of type string.

DynamoDB

const params = {
  TableName: 'Users',
  KeySchema: [
    { AttributeName: 'UserId', KeyType: 'HASH' }
  ],
  AttributeDefinitions: [
    { AttributeName: 'UserId', AttributeType: 'S' }
  ],
  ProvisionedThroughput: {
    ReadCapacityUnits: 5,
    WriteCapacityUnits: 5
  }
};

This example creates a table named 'Orders' with a composite key: 'OrderId' as the partition key and 'OrderDate' as the sort key.

DynamoDB

const params = {
  TableName: 'Orders',
  KeySchema: [
    { AttributeName: 'OrderId', KeyType: 'HASH' },
    { AttributeName: 'OrderDate', KeyType: 'RANGE' }
  ],
  AttributeDefinitions: [
    { AttributeName: 'OrderId', AttributeType: 'S' },
    { AttributeName: 'OrderDate', AttributeType: 'S' }
  ],
  ProvisionedThroughput: {
    ReadCapacityUnits: 10,
    WriteCapacityUnits: 5
  }
};

Sample Program

This program creates a DynamoDB table named 'Books' with 'ISBN' as the primary key. It sets read and write capacity to 5 units each.

DynamoDB

const AWS = require('aws-sdk');
AWS.config.update({ region: 'us-east-1' });

const dynamodb = new AWS.DynamoDB();

const params = {
  TableName: 'Books',
  KeySchema: [
    { AttributeName: 'ISBN', KeyType: 'HASH' }
  ],
  AttributeDefinitions: [
    { AttributeName: 'ISBN', AttributeType: 'S' }
  ],
  ProvisionedThroughput: {
    ReadCapacityUnits: 5,
    WriteCapacityUnits: 5
  }
};

dynamodb.createTable(params, function(err, data) {
  if (err) {
    console.log('Error:', err.message);
  } else {
    console.log('Table created:', data.TableDescription.TableName);
  }
});

Important Notes

Make sure your AWS credentials and region are set correctly before running the code.

Table creation can take a few seconds; the callback confirms when it's ready.

Use meaningful table and key names to keep your data organized.

Summary

DynamoDB tables store data with a primary key to organize it.

Use AWS SDK to create tables by defining name, keys, and capacity.

Check the output to confirm the table was created successfully.

Practice

1. What is the main purpose of specifying a primary key when creating a DynamoDB table using the AWS SDK?

easy

A. To set the table's read and write capacity

B. To specify the table's encryption settings

C. To define the table's region

D. To uniquely identify each item in the table

Solution

1. Step 1: Understand the role of a primary key in DynamoDB

   The primary key uniquely identifies each item in the table, ensuring no duplicates.

2. Step 2: Differentiate from other table settings

   Read/write capacity, region, and encryption are important but unrelated to item uniqueness.

3. Final Answer:

   To uniquely identify each item in the table -> Option D

4. Quick Check:

   Primary key = unique item ID [OK]

Hint: Primary key means unique ID for each item [OK]

Common Mistakes:

• Confusing primary key with capacity settings
• Thinking primary key sets region or encryption
• Ignoring the uniqueness requirement

2. Which of the following is the correct way to specify the primary key attribute when creating a DynamoDB table using AWS SDK for JavaScript?

easy

A. "KeySchema": [{ "AttributeName": "UserId", "KeyType": "HASH" }]

B. "KeySchema": [{ "AttributeName": "UserId", "KeyType": "PRIMARY" }]

C. "KeySchema": [{ "AttributeName": "UserId", "KeyType": "PRIMARY_KEY" }]

D. "KeySchema": [{ "AttributeName": "UserId", "KeyType": "KEY" }]

Solution

1. Step 1: Recall AWS SDK syntax for KeySchema

   The correct key type for the partition key is "HASH" in the KeySchema array.

2. Step 2: Identify incorrect key types

   "PRIMARY", "PRIMARY_KEY", and "KEY" are not valid KeyType values in AWS SDK.

3. Final Answer:

   "KeySchema": [{ "AttributeName": "UserId", "KeyType": "HASH" }] -> Option A

4. Quick Check:

   KeyType for partition key = HASH [OK]

Hint: Use "HASH" for partition key in KeySchema [OK]

Common Mistakes:

• Using invalid KeyType values like PRIMARY or KEY
• Confusing KeyType with attribute types
• Missing the array structure for KeySchema

3. Given the following AWS SDK code snippet for creating a DynamoDB table, what will be the output if the table creation is successful?

const params = {
  TableName: "Products",
  KeySchema: [
    { AttributeName: "ProductId", KeyType: "HASH" }
  ],
  AttributeDefinitions: [
    { AttributeName: "ProductId", AttributeType: "S" }
  ],
  ProvisionedThroughput: {
    ReadCapacityUnits: 5,
    WriteCapacityUnits: 5
  }
};

const result = await dynamodb.createTable(params).promise();
console.log(result.TableDescription.TableName);

medium

A. Products

B. Table creation failed

C. undefined

D. Error: Missing KeySchema

Solution

1. Step 1: Understand the createTable response structure

   On success, createTable returns an object with TableDescription including TableName.

2. Step 2: Check the console.log statement

   It prints result.TableDescription.TableName, which is "Products" as specified.

3. Final Answer:

   Products -> Option A

4. Quick Check:

   Successful createTable logs table name [OK]

Hint: Successful createTable returns TableDescription with TableName [OK]

Common Mistakes:

• Expecting error messages on success
• Confusing undefined with valid output
• Missing await causing promise object logging

4. You try to create a DynamoDB table with the following parameters but get an error. What is the most likely cause?

const params = {
  TableName: "Orders",
  KeySchema: [
    { AttributeName: "OrderId", KeyType: "HASH" },
    { AttributeName: "OrderDate", KeyType: "RANGE" }
  ],
  AttributeDefinitions: [
    { AttributeName: "OrderId", AttributeType: "S" }
  ],
  ProvisionedThroughput: {
    ReadCapacityUnits: 10,
    WriteCapacityUnits: 10
  }
};

await dynamodb.createTable(params).promise();

medium

A. TableName is invalid

B. Missing AttributeDefinition for "OrderDate"

C. ProvisionedThroughput values are too high

D. KeyType "RANGE" is not allowed

Solution

1. Step 1: Check KeySchema and AttributeDefinitions consistency

   Both "OrderId" and "OrderDate" are in KeySchema, but only "OrderId" is defined in AttributeDefinitions.

2. Step 2: Identify missing attribute definition

   "OrderDate" must be defined in AttributeDefinitions to avoid error.

3. Final Answer:

   Missing AttributeDefinition for "OrderDate" -> Option B

4. Quick Check:

   All key attributes need AttributeDefinitions [OK]

Hint: Define all key attributes in AttributeDefinitions [OK]

Common Mistakes:

• Forgetting to define all key attributes
• Assuming RANGE is invalid KeyType
• Blaming ProvisionedThroughput or TableName

5. You want to create a DynamoDB table named "Employees" with a composite primary key consisting of "EmployeeId" (string) as the partition key and "Department" (string) as the sort key. You also want to set the read capacity to 3 and write capacity to 2. Which of the following AWS SDK parameter objects correctly creates this table?

hard

A. { TableName: "Employees", KeySchema: [{ AttributeName: "EmployeeId", KeyType: "HASH" }], AttributeDefinitions: [{ AttributeName: "EmployeeId", AttributeType: "S" }, { AttributeName: "Department", AttributeType: "S" }], ProvisionedThroughput: { ReadCapacityUnits: 3, WriteCapacityUnits: 2 } }

B. { TableName: "Employees", KeySchema: [{ AttributeName: "EmployeeId", KeyType: "RANGE" }, { AttributeName: "Department", KeyType: "HASH" }], AttributeDefinitions: [{ AttributeName: "EmployeeId", AttributeType: "S" }, { AttributeName: "Department", AttributeType: "S" }], ProvisionedThroughput: { ReadCapacityUnits: 3, WriteCapacityUnits: 2 } }

C. { TableName: "Employees", KeySchema: [{ AttributeName: "EmployeeId", KeyType: "HASH" }, { AttributeName: "Department", KeyType: "RANGE" }], AttributeDefinitions: [{ AttributeName: "EmployeeId", AttributeType: "S" }, { AttributeName: "Department", AttributeType: "S" }], ProvisionedThroughput: { ReadCapacityUnits: 3, WriteCapacityUnits: 2 } }

D. { TableName: "Employees", KeySchema: [{ AttributeName: "EmployeeId", KeyType: "HASH" }, { AttributeName: "Department", KeyType: "RANGE" }], AttributeDefinitions: [{ AttributeName: "EmployeeId", AttributeType: "N" }, { AttributeName: "Department", AttributeType: "S" }], ProvisionedThroughput: { ReadCapacityUnits: 3, WriteCapacityUnits: 2 } }

Solution

1. Step 1: Verify KeySchema order and types

   Partition key must have KeyType "HASH" and sort key "RANGE" in correct order: EmployeeId (HASH), Department (RANGE).

2. Step 2: Check AttributeDefinitions types

   Both EmployeeId and Department are strings, so AttributeType "S" is correct for both.

3. Step 3: Confirm ProvisionedThroughput values

   ReadCapacityUnits: 3 and WriteCapacityUnits: 2 match the requirement.

4. Final Answer:

   { TableName: "Employees", KeySchema: [{ AttributeName: "EmployeeId", KeyType: "HASH" }, { AttributeName: "Department", KeyType: "RANGE" }], AttributeDefinitions: [{ AttributeName: "EmployeeId", AttributeType: "S" }, { AttributeName: "Department", AttributeType: "S" }], ProvisionedThroughput: { ReadCapacityUnits: 3, WriteCapacityUnits: 2 } } -> Option C

5. Quick Check:

   Correct key order and attribute types = { TableName: "Employees", KeySchema: [{ AttributeName: "EmployeeId", KeyType: "HASH" }, { AttributeName: "Department", KeyType: "RANGE" }], AttributeDefinitions: [{ AttributeName: "EmployeeId", AttributeType: "S" }, { AttributeName: "Department", AttributeType: "S" }], ProvisionedThroughput: { ReadCapacityUnits: 3, WriteCapacityUnits: 2 } } [OK]

Hint: Partition key = HASH, sort key = RANGE, types must match [OK]

Common Mistakes:

• Swapping HASH and RANGE key types
• Mismatching attribute types (string vs number)
• Omitting sort key in KeySchema