Creating a DynamoDB table in AWS - Practice Exercises

Challenge - 5 Problems

❓ Configuration

intermediate

DynamoDB Table Partition Key Type

You want to create a DynamoDB table with a partition key named CustomerId that stores string values. Which option correctly defines the partition key attribute in the AWS CLI command?

A aws dynamodb create-table --table-name Customers --attribute-definitions AttributeName=CustomerId,AttributeType=S --key-schema AttributeName=CustomerId,KeyType=HASH --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5

B aws dynamodb create-table --table-name Customers --attribute-definitions AttributeName=CustomerId,AttributeType=BOOL --key-schema AttributeName=CustomerId,KeyType=HASH --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5

C aws dynamodb create-table --table-name Customers --attribute-definitions AttributeName=CustomerId,AttributeType=B --key-schema AttributeName=CustomerId,KeyType=HASH --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5

D aws dynamodb create-table --table-name Customers --attribute-definitions AttributeName=CustomerId,AttributeType=N --key-schema AttributeName=CustomerId,KeyType=HASH --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5

💡 Hint

The partition key type must match the data type you plan to store. 'S' stands for string.

DynamoDB attribute types include 'S' for string, 'N' for number, and 'B' for binary. 'BOOL' is not a valid attribute type for keys. Since CustomerId stores strings, 'S' is correct.

❓ Architecture

intermediate

Choosing a Sort Key for Efficient Queries

You are designing a DynamoDB table to store orders. Each order has a unique OrderId and a timestamp when it was placed. You want to efficiently query all orders for a customer sorted by time. Which key schema is best?

A Partition key: OrderTimestamp (number), Sort key: CustomerId (string)

B Partition key: OrderId (string), Sort key: CustomerId (string)

C Partition key: CustomerId (string), Sort key: OrderTimestamp (number)

D Partition key: CustomerId (string) only, no sort key

💡 Hint

Think about how to group orders by customer and sort them by time.

Using CustomerId as partition key groups all orders per customer. Adding OrderTimestamp as sort key allows sorting orders by time within each customer group.

❓ security

advanced

IAM Policy for DynamoDB Table Access

You want to create an IAM policy that allows read-only access to a DynamoDB table named Orders. Which policy statement correctly grants this permission?

A {"Effect": "Allow", "Action": ["dynamodb:PutItem", "dynamodb:UpdateItem"], "Resource": "arn:aws:dynamodb:*:*:table/Orders"}

B {"Effect": "Allow", "Action": ["dynamodb:DeleteItem"], "Resource": "arn:aws:dynamodb:*:*:table/Orders"}

C {"Effect": "Deny", "Action": ["dynamodb:GetItem"], "Resource": "arn:aws:dynamodb:*:*:table/Orders"}

D {"Effect": "Allow", "Action": ["dynamodb:GetItem", "dynamodb:Query", "dynamodb:Scan"], "Resource": "arn:aws:dynamodb:*:*:table/Orders"}

💡 Hint

Read-only actions include GetItem, Query, and Scan.

To allow read-only access, the policy must allow GetItem, Query, and Scan actions. PutItem, UpdateItem, and DeleteItem are write actions. Deny effect blocks access.

❓ service_behavior

advanced

DynamoDB Provisioned Throughput Behavior

You create a DynamoDB table with provisioned throughput of 5 read capacity units and 5 write capacity units. What happens if your application suddenly tries to perform 20 writes per second?

A DynamoDB queues the extra write requests and processes them later without errors.

B DynamoDB throttles the write requests exceeding 5 per second, causing some requests to fail with a ProvisionedThroughputExceededException.

C All 20 write requests succeed without delay or error.

D DynamoDB automatically increases the write capacity units to 20 to handle the load.

💡 Hint

Provisioned throughput limits the number of reads and writes per second.

If the application exceeds provisioned capacity, DynamoDB throttles excess requests and returns errors. It does not auto-scale unless auto-scaling is configured.

✅ Best Practice

expert

Designing a DynamoDB Table for High Write Throughput

You expect a very high number of writes per second to your DynamoDB table. Which design choice helps avoid hot partitions and ensures even write distribution?

A Use a partition key with high cardinality and add a random suffix to distribute writes evenly.

B Use a single fixed partition key value for all items to simplify queries.

C Use only a sort key without a partition key to distribute writes.

D Use a partition key with low cardinality and rely on sort key for uniqueness.

💡 Hint

Think about how DynamoDB partitions data and distributes load.

DynamoDB partitions data by partition key. High cardinality keys spread writes across partitions. Adding randomness helps avoid hot spots. Single fixed keys cause hot partitions.