BatchGetItem in DynamoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

What is the output of this BatchGetItem request?

Given a DynamoDB table Users with items having UserId as the primary key, consider this BatchGetItem request:

{
  "RequestItems": {
    "Users": {
      "Keys": [
        {"UserId": {"S": "user1"}},
        {"UserId": {"S": "user3"}}
      ]
    }
  }
}

If the table contains these items:

• UserId: user1, Name: Alice
• UserId: user2, Name: Bob
• UserId: user3, Name: Charlie

What will the response contain?

A {"Responses": {"Users": [{"UserId": {"S": "user1"}, "Name": {"S": "Alice"}}, {"UserId": {"S": "user3"}, "Name": {"S": "Charlie"}}]}}

B {"Responses": {"Users": [{"UserId": {"S": "user1"}, "Name": {"S": "Alice"}}]}}

C {"Responses": {"Users": [{"UserId": {"S": "user2"}, "Name": {"S": "Bob"}}]}}

D {"Responses": {"Users": []}}

💡 Hint

BatchGetItem returns all requested items that exist in the table.

The BatchGetItem request asks for user1 and user3. Both exist, so both are returned in the response.

🧠 Conceptual

intermediate

Which statement about BatchGetItem is true?

Choose the correct statement about DynamoDB's BatchGetItem operation.

A BatchGetItem can only retrieve items from one table per request.

B BatchGetItem can retrieve items from multiple tables in a single request.

C BatchGetItem automatically updates items after retrieval.

D BatchGetItem requires a scan operation to find items.

💡 Hint

Think about how BatchGetItem handles multiple tables.

BatchGetItem supports retrieving items from multiple tables by specifying keys for each table in the request.

📝 Syntax

advanced

Which BatchGetItem request is syntactically correct?

Identify the syntactically valid BatchGetItem JSON request.

A

{
  "RequestItems": {
    "Products": {
      "Keys": {
        "ProductId": {"S": "p1"}
      }
    }
  }
}

B

{
  "RequestItems": {
    "Products": [
      {"ProductId": {"S": "p1"}},
      {"ProductId": {"S": "p2"}}
    ]
  }
}

C

{
  "RequestItems": {
    "Products": {
      "Key": [
        {"ProductId": {"S": "p1"}}
      ]
    }
  }
}

D

{
  "RequestItems": {
    "Products": {
      "Keys": [
        {"ProductId": {"S": "p1"}},
        {"ProductId": {"S": "p2"}}
      ]
    }
  }
}

💡 Hint

Check the structure of the Keys attribute.

The Keys attribute must be an array of key objects. Option D correctly uses an array under Keys.

❓ optimization

advanced

How to optimize BatchGetItem for large key sets?

You need to retrieve 150 items from a DynamoDB table using BatchGetItem. What is the best approach to avoid request size limits?

A Use Query operation with a filter to retrieve all 150 items in one request.

B Send all 150 keys in a single BatchGetItem request; DynamoDB handles large requests automatically.

C Split the keys into batches of 100 or fewer and send multiple BatchGetItem requests.

D Use Scan operation instead of BatchGetItem to get all items at once.

💡 Hint

Remember DynamoDB limits BatchGetItem to 100 items per request.

DynamoDB limits BatchGetItem to 100 items per request. Splitting keys into batches avoids errors and respects limits.

🔧 Debug

expert

Why does this BatchGetItem request return unprocessed keys?

Consider this BatchGetItem request to table Orders:

{
  "RequestItems": {
    "Orders": {
      "Keys": [
        {"OrderId": {"S": "o1"}},
        {"OrderId": {"S": "o2"}},
        {"OrderId": {"S": "o3"}}
      ],
      "ConsistentRead": true
    }
  }
}

The response contains UnprocessedKeys with some keys. What is the most likely reason?

A The request exceeded the provisioned throughput, causing throttling and unprocessed keys.

B The keys specified do not exist in the table, so they appear as unprocessed.

C ConsistentRead cannot be used with BatchGetItem, causing the request to fail partially.

D The table is in a locked state, preventing any keys from being processed.

💡 Hint

Think about DynamoDB limits and throttling behavior.

When BatchGetItem exceeds provisioned throughput, DynamoDB returns unprocessed keys to retry later. This is normal behavior under throttling.