Table creation with AWS SDK in DynamoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the primary purpose of creating a table in DynamoDB using the AWS SDK?

To define a structured container where data items are stored with a unique primary key, enabling fast and scalable access.

beginner

Which key attribute must be specified when creating a DynamoDB table?

The primary key, which can be a partition key alone or a combination of partition key and sort key.

intermediate

What does the 'ProvisionedThroughput' setting control in a DynamoDB table?

It controls the read and write capacity units allocated to the table, affecting performance and cost.

intermediate

In AWS SDK for JavaScript v3, which client is used to create a DynamoDB table?

The DynamoDBClient along with the CreateTableCommand is used to create a table.

beginner

Why is it important to wait for the table status to become 'ACTIVE' after creation?

Because the table is not ready to accept read or write operations until it is fully active.

Which attribute is mandatory when creating a DynamoDB table?

A Provisioned throughput

B Secondary index

C Primary key

D Stream specification

A DynamoDB table must have a primary key defined to uniquely identify items.

What does the 'AttributeDefinitions' parameter specify in table creation?

A The data types of key attributes

B The table's read/write capacity

C The table's billing mode

D The table's encryption settings

AttributeDefinitions define the names and data types of attributes used as keys.

Which AWS SDK command is used to create a DynamoDB table in JavaScript v3?

A CreateTableCommand

B PutItemCommand

C UpdateTableCommand

D DeleteTableCommand

CreateTableCommand is the command to create a new DynamoDB table.

What happens if you try to write data before the table status is 'ACTIVE'?

A The write will succeed but data may be lost

B The write operation will fail

C The data will be queued automatically

D The table will auto-activate

Writes are rejected until the table is fully active.

Which billing mode allows you to pay only for the read/write you use without provisioning capacity?

A Provisioned

B Free tier

C Reserved

D On-demand

On-demand billing mode charges based on actual usage without capacity settings.

Explain the key steps to create a DynamoDB table using the AWS SDK.

Think about what information the table needs and how the SDK command is structured.

Describe why the primary key is essential in DynamoDB table creation and what types it can have.

Consider how you find a single item in a big collection.

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