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DynamoDBquery~30 mins

Table creation with AWS SDK in DynamoDB - Mini Project: Build & Apply

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Table creation with AWS SDK
📖 Scenario: You are setting up a database table in AWS DynamoDB to store user information for a new web application.
🎯 Goal: Create a DynamoDB table named Users with a primary key UserId of type string using the AWS SDK.
📋 What You'll Learn
Create a variable called tableName with the value "Users".
Create a variable called keySchema defining the primary key with AttributeName as UserId and KeyType as HASH.
Create a variable called attributeDefinitions defining the attribute UserId with type S (string).
Create a variable called provisionedThroughput with ReadCapacityUnits and WriteCapacityUnits both set to 5.
Create a variable called params that combines all the above variables into a single object for table creation.
💡 Why This Matters
🌍 Real World
Creating DynamoDB tables is a common task when building serverless applications or cloud-native apps that need fast, scalable NoSQL databases.
💼 Career
Understanding how to configure and create DynamoDB tables using the AWS SDK is essential for cloud developers, DevOps engineers, and backend engineers working with AWS.
Progress0 / 4 steps
1
Create table name and key schema
Create a variable called tableName and set it to "Users". Then create a variable called keySchema as a list with one object that has AttributeName set to "UserId" and KeyType set to "HASH".
DynamoDB
Hint

Use const to declare variables. The keySchema is an array with one object describing the primary key.

2
Define attribute definitions
Create a variable called attributeDefinitions as a list with one object that has AttributeName set to "UserId" and AttributeType set to "S".
DynamoDB
Hint

The attributeDefinitions array describes the data type of each key attribute.

3
Set provisioned throughput
Create a variable called provisionedThroughput as an object with ReadCapacityUnits set to 5 and WriteCapacityUnits set to 5.
DynamoDB
Hint

Provisioned throughput sets how many reads and writes your table can handle per second.

4
Combine all into params object
Create a variable called params as an object that includes TableName set to tableName, KeySchema set to keySchema, AttributeDefinitions set to attributeDefinitions, and ProvisionedThroughput set to provisionedThroughput.
DynamoDB
Hint

The params object is what you pass to the AWS SDK to create the table.

Practice

(1/5)
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