Index capacity and cost in DynamoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is an index in DynamoDB?

An index in DynamoDB is a data structure that improves the speed of data retrieval operations on a table by allowing queries on non-primary key attributes.

intermediate

How does a Global Secondary Index (GSI) affect capacity in DynamoDB?

A GSI consumes additional read and write capacity units because it maintains a copy of data with different key attributes, increasing the cost of operations.

intermediate

What is the difference in write capacity cost between a table and its Local Secondary Index (LSI)?

Writes to a table also consume write capacity units for its LSI because the index is updated synchronously, but LSIs do not consume separate read capacity units since they share the table's read capacity.

beginner

Why can adding too many indexes increase your DynamoDB costs?

Because each index requires additional storage and capacity units for writes and reads, more indexes mean more resources used, which increases your overall cost.

intermediate

How can you reduce the cost impact of indexes in DynamoDB?

You can reduce costs by limiting the number of indexes, choosing only necessary attributes to project, and using on-demand capacity mode to pay only for what you use.

Which type of index in DynamoDB requires separate read and write capacity units?

A Global Secondary Index (GSI)

B Local Secondary Index (LSI)

C Primary Key

D No index requires capacity units

Global Secondary Indexes consume separate read and write capacity units because they maintain a separate copy of data.

What happens to write capacity units when you write to a table with a Local Secondary Index?

A Write capacity units are consumed for both the table and the LSI

B Only the table consumes write capacity units

C Only the LSI consumes write capacity units

D No write capacity units are consumed

Writes to the table also consume write capacity units for the LSI because it updates synchronously.

Which of the following increases DynamoDB costs the most?

A Projecting only keys in indexes

B Using only the primary key

C Using on-demand capacity mode

D Adding multiple Global Secondary Indexes

Multiple GSIs increase costs because each requires additional capacity and storage.

How can you reduce read capacity costs for an index?

A Add more GSIs

B Project only necessary attributes

C Use larger read capacity units

D Avoid using indexes

Projecting only necessary attributes reduces the size of data read, lowering read capacity costs.

Which index type shares read capacity units with the base table?

A Primary Key

B Global Secondary Index (GSI)

C Local Secondary Index (LSI)

D None

LSIs share the table's read capacity units, unlike GSIs which have separate capacity.

Explain how Global Secondary Indexes affect DynamoDB capacity and cost.

Think about how GSIs duplicate data and require extra resources.

Describe strategies to manage and reduce the cost impact of indexes in DynamoDB.

Focus on minimizing resource use and paying only for what you need.

Practice

1. What is the main reason to use indexes in DynamoDB?

easy

A. To speed up query performance by allowing efficient data access

B. To reduce the storage size of the table

C. To automatically backup data

D. To encrypt data at rest

Solution

1. Step 1: Understand the purpose of indexes

   Indexes in DynamoDB are designed to speed up queries by providing alternate ways to access data efficiently.

2. Step 2: Eliminate unrelated options

   Options about storage size, backup, and encryption are unrelated to index functionality.

3. Final Answer:

   To speed up query performance by allowing efficient data access -> Option A

4. Quick Check:

   Indexes improve query speed = B [OK]

Hint: Indexes speed queries, not reduce storage or backup [OK]

Common Mistakes:

• Thinking indexes reduce storage cost
• Confusing indexes with backup features
• Assuming indexes encrypt data

2. Which of the following is the correct way to specify a Global Secondary Index (GSI) in a DynamoDB table creation JSON?

easy

A. {
"LocalSecondaryIndexes": [
{
"IndexName": "MyGSI",
"KeySchema": [
{"AttributeName": "UserId", "KeyType": "HASH"}
],
"Projection": {"ProjectionType": "ALL"}
}
]
}

B. {
"GlobalSecondaryIndexes": [
{
"IndexName": "MyGSI",
"KeySchema": [
{"AttributeName": "UserId", "KeyType": "HASH"}
],
"Projection": {"ProjectionType": "ALL"},
"ProvisionedThroughput": {"ReadCapacityUnits": 5, "WriteCapacityUnits": 5}
}
]
}

C. {
"GlobalSecondaryIndexes": {
"IndexName": "MyGSI"
}
}

D. {
"Indexes": [
{
"Name": "MyGSI"
}
]
}

Solution

1. Step 1: Identify correct GSI syntax

   Global Secondary Indexes require an array under "GlobalSecondaryIndexes" with full details: IndexName, KeySchema, Projection, and ProvisionedThroughput.

2. Step 2: Compare options

   { "GlobalSecondaryIndexes": [ { "IndexName": "MyGSI", "KeySchema": [ {"AttributeName": "UserId", "KeyType": "HASH"} ], "Projection": {"ProjectionType": "ALL"}, "ProvisionedThroughput": {"ReadCapacityUnits": 5, "WriteCapacityUnits": 5} } ] } correctly uses "GlobalSecondaryIndexes" as an array with all required fields. Others use wrong keys or incomplete structures.

3. Final Answer:

   { "GlobalSecondaryIndexes": [ { "IndexName": "MyGSI", "KeySchema": [ {"AttributeName": "UserId", "KeyType": "HASH"} ], "Projection": {"ProjectionType": "ALL"}, "ProvisionedThroughput": {"ReadCapacityUnits": 5, "WriteCapacityUnits": 5} } ] } -> Option B

4. Quick Check:

   GSI syntax requires array with full details = A [OK]

Hint: GSIs need full details in GlobalSecondaryIndexes array [OK]

Common Mistakes:

• Using LocalSecondaryIndexes instead of GlobalSecondaryIndexes
• Providing object instead of array for GSIs
• Omitting ProvisionedThroughput for GSIs

3. Given a DynamoDB table with a provisioned write capacity of 10 units and a Global Secondary Index (GSI) with 5 write capacity units, what is the total write capacity units consumed when writing one item to the table and the GSI?

medium

A. 5 units

B. 10 units

C. 15 units

D. 20 units

Solution

1. Step 1: Understand write capacity consumption

   Writing one item consumes write capacity units on the main table plus on each index that is updated.

2. Step 2: Add main table and GSI write units

   Main table uses 10 units, GSI uses 5 units, total = 10 + 5 = 15 units.

3. Final Answer:

   15 units -> Option C

4. Quick Check:

   Total write capacity = main + GSI = 15 [OK]

Hint: Add main table and index write units for total cost [OK]

Common Mistakes:

• Counting only main table write units
• Counting only GSI write units
• Multiplying instead of adding capacities

4. You notice your DynamoDB table's write capacity is being exceeded even though your application writes only a few items per second. Which of the following is the most likely cause related to indexes?

medium

A. You have a Global Secondary Index with high write capacity units causing extra cost

B. You forgot to create any indexes

C. Your table has no read capacity units set

D. You are using Local Secondary Indexes which do not affect write capacity

Solution

1. Step 1: Analyze write capacity usage

   Writes to the table also consume write capacity on GSIs, increasing total usage.

2. Step 2: Identify cause of exceeded capacity

   If GSIs have high write capacity or many writes, they can cause capacity to be exceeded even if main table writes are low.

3. Final Answer:

   You have a Global Secondary Index with high write capacity units causing extra cost -> Option A

4. Quick Check:

   GSIs increase write capacity usage = C [OK]

Hint: Check GSIs for hidden write capacity usage [OK]

Common Mistakes:

• Assuming no indexes means no extra capacity
• Confusing read and write capacity units
• Thinking Local Secondary Indexes increase write capacity

5. You want to optimize costs for a DynamoDB table with a Global Secondary Index (GSI). The table has 20 write capacity units and the GSI has 10 write capacity units. If your application writes 5 items per second, how can you reduce costs without affecting query performance on the GSI?

hard

A. Disable the table's write capacity units

B. Remove the GSI to save all index costs

C. Increase the table write capacity units to 30

D. Reduce the GSI write capacity units to 5 and enable auto scaling

Solution

1. Step 1: Understand cost drivers

   Write capacity units on both table and GSI affect cost. Reducing GSI units lowers cost but must still handle write load.

2. Step 2: Apply auto scaling and adjust capacity

   Reducing GSI write units to match actual writes (5) and enabling auto scaling balances cost and performance.

3. Final Answer:

   Reduce the GSI write capacity units to 5 and enable auto scaling -> Option D

4. Quick Check:

   Lower GSI units + auto scaling = cost optimization [OK]

Hint: Match GSI capacity to writes and use auto scaling [OK]

Common Mistakes:

• Removing GSI and losing query performance
• Increasing table capacity unnecessarily
• Disabling write capacity causing failures