Why table design determines performance in DynamoDB - Quick Recap

Recall & Review

beginner

What is the main reason table design affects performance in DynamoDB?

Table design affects how efficiently DynamoDB can find and retrieve data. Good design means fewer reads and faster queries.

beginner

How does choosing the right partition key improve performance?

A good partition key evenly distributes data across partitions, preventing hot spots and allowing parallel processing.

intermediate

Why should you avoid large items or many attributes in a single DynamoDB table?

Large items or many attributes increase read/write costs and slow down queries because more data is processed each time.

intermediate

What role do secondary indexes play in table design and performance?

Secondary indexes let you query data in different ways without scanning the whole table, improving query speed.

beginner

How does access pattern influence DynamoDB table design?

Designing tables based on how you access data helps avoid expensive scans and makes queries faster and cheaper.

What happens if your partition key causes uneven data distribution?

A The table automatically fixes it

B Data is evenly spread, improving speed

C It reduces storage costs

D Some partitions get overloaded, slowing performance

Uneven data distribution causes hot partitions that slow down reads and writes.

Which is a benefit of using secondary indexes?

A They reduce the size of the table

B They allow querying data without scanning the whole table

C They automatically backup data

D They increase write speed

Secondary indexes let you query efficiently by alternative keys.

Why should you design your table based on access patterns?

A To avoid expensive scans and speed up queries

B To store more data

C To make backups easier

D To reduce network traffic

Access pattern-based design helps DynamoDB serve queries faster and cheaper.

What is a consequence of having very large items in a DynamoDB table?

A No effect on performance

B Faster queries

C Higher read and write costs and slower performance

D Automatic compression

Large items require more resources to read and write, slowing down operations.

How does a well-chosen partition key help DynamoDB?

A It spreads data evenly for better parallel processing

B It reduces the number of attributes

C It increases the table size

D It automatically creates backups

Even data distribution allows DynamoDB to handle requests efficiently.

Explain why table design is critical for DynamoDB performance.

Think about how DynamoDB finds and reads data quickly.

Describe how access patterns influence your decisions when designing a DynamoDB table.

Consider how you will ask for data before designing the table.