GSI key selection strategy in DynamoDB - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define the partition key for a GSI in DynamoDB.

DynamoDB

KeySchema: [{ AttributeName: '[1]', KeyType: 'HASH' }]

Drag options to blanks, or click blank then click option'

AUserId

BTimestamp

CEmail

DStatus

Attempts:

3 left

💡 Hint

Common Mistakes

Using a sort key attribute as the partition key.

Choosing an attribute with low cardinality.

The partition key for a GSI should be an attribute that evenly distributes data. 'UserId' is a common choice.

2fill in blank

medium

Complete the code to define the sort key for a GSI in DynamoDB.

DynamoDB

KeySchema: [ { AttributeName: 'UserId', KeyType: 'HASH' }, { AttributeName: '[1]', KeyType: 'RANGE' } ]

Drag options to blanks, or click blank then click option'

AOrderId

BUserId

CStatus

DEmail

Attempts:

3 left

💡 Hint

Common Mistakes

Using the same attribute for partition and sort key.

Choosing an attribute that does not help with sorting.

The sort key (RANGE) organizes data within the partition. 'OrderId' is a good choice to sort user orders.

3fill in blank

hard

Fix the error in the GSI attribute definitions by selecting the correct attribute type.

DynamoDB

AttributeDefinitions: [ { AttributeName: 'UserId', AttributeType: '[1]' }, { AttributeName: 'OrderDate', AttributeType: 'S' } ]

Drag options to blanks, or click blank then click option'

ABOOL

BS

CB

DN

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'N' (number) for string attributes.

Using 'BOOL' for non-boolean attributes.

'UserId' is usually a string, so its attribute type should be 'S' for string.

4fill in blank

hard

Fill both blanks to create a GSI that uses 'Status' as partition key and 'CreatedAt' as sort key.

DynamoDB

GlobalSecondaryIndexes: [{ IndexName: 'StatusIndex', KeySchema: [ { AttributeName: '[1]', KeyType: 'HASH' }, { AttributeName: '[2]', KeyType: 'RANGE' } ], Projection: { ProjectionType: 'ALL' } }]

Drag options to blanks, or click blank then click option'

AStatus

BCreatedAt

CUserId

DOrderId

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping partition and sort keys.

Using attributes not defined in AttributeDefinitions.

The GSI uses 'Status' as the partition key and 'CreatedAt' as the sort key to organize items by status and creation time.

5fill in blank

hard

Fill all three blanks to define a GSI with keys and projection type.

DynamoDB

GlobalSecondaryIndexes: [{ IndexName: 'EmailIndex', KeySchema: [ { AttributeName: '[1]', KeyType: 'HASH' }, { AttributeName: '[2]', KeyType: 'RANGE' } ], Projection: { ProjectionType: '[3]' } }]

Drag options to blanks, or click blank then click option'

AEmail

BSignupDate

CALL

DKEYS_ONLY

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong projection types like 'INCLUDE' without specifying attributes.

Mixing up HASH and RANGE keys.

This GSI uses 'Email' as partition key, 'SignupDate' as sort key, and projects all attributes.

Practice

1. What is the main purpose of choosing a good partition key for a Global Secondary Index (GSI) in DynamoDB?

easy

A. To evenly distribute data across partitions for faster queries

B. To store large binary objects efficiently

C. To encrypt data at rest automatically

D. To backup data to another region

Solution

1. Step 1: Understand partition key role in GSI

   The partition key determines how data is spread across storage partitions in DynamoDB.

2. Step 2: Importance of even data distribution

   Choosing a partition key that evenly distributes data avoids hot partitions and improves query speed.

3. Final Answer:

   To evenly distribute data across partitions for faster queries -> Option A

4. Quick Check:

   Partition key = data distribution [OK]

Hint: Partition key controls data spread, pick for balance [OK]

Common Mistakes:

• Thinking partition key orders data inside partitions
• Confusing partition key with sort key
• Assuming partition key encrypts data

2. Which of the following is the correct syntax to define a GSI with a partition key named Category and a sort key named Timestamp in a DynamoDB table creation JSON?

easy

A. {
"IndexName": "CategoryTimestampIndex",
"KeySchema": [
{"AttributeName": "Timestamp", "KeyType": "RANGE"},
{"AttributeName": "Category", "KeyType": "HASH"}
],
"Projection": {"ProjectionType": "ALL"}
}

B. {
"IndexName": "CategoryTimestampIndex",
"KeySchema": [
{"AttributeName": "Category", "KeyType": "HASH"},
{"AttributeName": "Timestamp", "KeyType": "RANGE"}
],
"Projection": {"ProjectionType": "ALL"}
}

C. {
"IndexName": "CategoryTimestampIndex",
"KeySchema": [
{"AttributeName": "Category", "KeyType": "RANGE"},
{"AttributeName": "Timestamp", "KeyType": "HASH"}
],
"Projection": {"ProjectionType": "ALL"}
}

D. {
"IndexName": "CategoryTimestampIndex",
"KeySchema": [
{"AttributeName": "Timestamp", "KeyType": "HASH"},
{"AttributeName": "Category", "KeyType": "RANGE"}
],
"Projection": {"ProjectionType": "ALL"}
}

Solution

1. Step 1: Identify partition and sort key roles

   Partition key uses KeyType "HASH" and sort key uses KeyType "RANGE" in DynamoDB.

2. Step 2: Match keys to correct KeyType

   Category is partition key so it must have KeyType "HASH"; Timestamp is sort key so it must have KeyType "RANGE".

3. Final Answer:

   Correct JSON with Category as HASH and Timestamp as RANGE -> Option B

4. Quick Check:

   Partition key = HASH, Sort key = RANGE [OK]

Hint: Partition key = HASH, sort key = RANGE in KeySchema [OK]

Common Mistakes:

• Swapping HASH and RANGE key types
• Using RANGE for partition key
• Incorrect JSON structure for KeySchema

3. Given a DynamoDB table with a GSI where the partition key is UserId and the sort key is OrderDate, what will be the result of this query?

Query on GSI with UserId = 'user123' and OrderDate between '2023-01-01' and '2023-01-31'

medium

A. All orders by user123 in January 2023 sorted by OrderDate

B. All orders by all users in January 2023

C. All orders by user123 regardless of date

D. Syntax error due to missing filter expression

Solution

1. Step 1: Understand query conditions on GSI keys

   Query uses partition key UserId = 'user123' and a range condition on sort key OrderDate between two dates.

2. Step 2: Result filters by UserId and date range

   Only items with UserId 'user123' and OrderDate in January 2023 are returned, sorted by OrderDate.

3. Final Answer:

   All orders by user123 in January 2023 sorted by OrderDate -> Option A

4. Quick Check:

   Partition key + sort key range = filtered query [OK]

Hint: Query filters partition key exactly, sort key by range [OK]

Common Mistakes:

• Thinking query returns all users' data
• Ignoring sort key range condition
• Assuming syntax error without filter expression

4. You created a GSI with partition key Category and sort key Price. Your queries on this GSI are slow and uneven. What is the most likely cause?

medium

A. Price is not indexed as a sort key

B. The table has no primary key

C. You forgot to project attributes

D. Category has very few distinct values causing hot partitions

Solution

1. Step 1: Analyze partition key distribution

   If Category has few distinct values, many items share the same partition key, causing hot partitions and slow queries.

2. Step 2: Understand impact on query performance

   Hot partitions limit throughput and cause uneven query speed despite having a sort key.

3. Final Answer:

   Category has very few distinct values causing hot partitions -> Option D

4. Quick Check:

   Few partition keys = hot partitions = slow queries [OK]

Hint: Few partition key values cause hot partitions [OK]

Common Mistakes:

• Assuming missing sort key causes slowness
• Ignoring partition key cardinality
• Thinking projection affects partitioning

5. You want to design a GSI to efficiently query orders by CustomerId and sort them by OrderStatus and then by OrderDate. Which key selection strategy is best?

hard

A. Partition key: CustomerId; Sort key: OrderDate only

B. Partition key: OrderStatus; Sort key: CustomerId#OrderDate concatenated string

C. Partition key: CustomerId; Sort key: OrderStatus#OrderDate concatenated string

D. Partition key: OrderDate; Sort key: CustomerId

Solution

1. Step 1: Identify query pattern requirements

   You want to query by CustomerId and sort first by OrderStatus, then by OrderDate.

2. Step 2: Design composite sort key for multi-level sorting

   Concatenate OrderStatus and OrderDate into one sort key string (e.g., 'Shipped#2023-06-01') to sort by status then date.

3. Step 3: Assign keys correctly

   Partition key should be CustomerId for grouping orders by customer; sort key is the concatenated string for sorting.

4. Final Answer:

   Partition key: CustomerId; Sort key: OrderStatus#OrderDate concatenated string -> Option C

5. Quick Check:

   Composite sort key enables multi-level sorting [OK]

Hint: Use composite sort key for multi-level sorting [OK]

Common Mistakes:

• Using OrderStatus as partition key causing uneven distribution
• Not combining sort keys for multi-level order
• Using OrderDate as partition key which breaks grouping