AWS CLI for DynamoDB - Step-by-Step Execution

Concept Flow - AWS CLI for DynamoDB

Start AWS CLI Command

↓

Parse Command & Parameters

↓

Send Request to DynamoDB Service

↓

DynamoDB Processes Request

↓

Receive Response

↓

Display Output to User

↓

End

The AWS CLI command is parsed and sent to DynamoDB, which processes it and returns a response shown to the user.

Execution Sample

DynamoDB

aws dynamodb create-table \
  --table-name Music \
  --attribute-definitions AttributeName=Artist,AttributeType=S \
  --key-schema AttributeName=Artist,KeyType=HASH \
  --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5

This command creates a DynamoDB table named 'Music' with 'Artist' as the primary key.

Execution Table

Step	Action	Parameters	DynamoDB Response	Output to User
1	Parse CLI command	create-table Music with Artist as HASH key	N/A	Preparing request
2	Send request to DynamoDB	TableName=Music, KeySchema=Artist HASH, ProvisionedThroughput=5/5	Processing request	Request sent
3	DynamoDB creates table	N/A	Table Music created successfully	Success message displayed
4	End	N/A	N/A	Command complete

💡 Table created successfully, command execution ends.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
Command	N/A	create-table Music ...	create-table Music ...	create-table Music ...	complete
Request Status	N/A	parsed	sent	processed	done
Response	N/A	N/A	processing	success	success

Key Moments - 2 Insights

Why does the command need attribute definitions and key schema?

Because DynamoDB needs to know which attribute is the primary key to organize data. See execution_table step 1 where parameters include these.

What happens if the table already exists?

DynamoDB returns an error response instead of success at step 3, and the CLI shows an error message instead of success.

Visual Quiz - 3 Questions

Look at the execution_table, what is the DynamoDB response at step 3?

A Preparing request

B Table Music created successfully

C Request sent

D Command complete

💡 Hint

Check the 'DynamoDB Response' column in row for step 3.

At which step is the CLI command parsed?

A Step 1

B Step 2

C Step 3

D Step 4

💡 Hint

Look at the 'Action' column for parsing in execution_table.

If the provisioned throughput is changed to 10 read units, how does the request status change after step 2?

A Request status becomes 'failed'

B Request status becomes 'pending'

C Request status remains 'sent'

D Request status becomes 'parsed'

💡 Hint

Request status changes to 'sent' after sending request regardless of throughput value, see variable_tracker.

Concept Snapshot

AWS CLI for DynamoDB:
Use 'aws dynamodb' commands to manage tables and data.
Commands include create-table, put-item, get-item, delete-table.
Specify parameters like --table-name, --attribute-definitions, --key-schema.
CLI sends request to DynamoDB service and shows response.
Success or error messages appear after execution.

Full Transcript

This visual execution shows how an AWS CLI command for DynamoDB runs step-by-step. First, the CLI parses the command and parameters like table name and key schema. Then it sends a request to DynamoDB. DynamoDB processes the request and creates the table. Finally, the CLI displays a success message. Variables like command text, request status, and response change through these steps. Key points include the need for attribute definitions and key schema to define the table's primary key. The execution table and variable tracker help visualize the flow and state changes clearly.

Practice

1. What does the AWS CLI command aws dynamodb list-tables do?

easy

A. It shows all DynamoDB tables in your AWS account and region.

B. It deletes all DynamoDB tables in your AWS account.

C. It creates a new DynamoDB table.

D. It updates the items in a DynamoDB table.

Solution

1. Step 1: Understand the command purpose

   The command aws dynamodb list-tables is designed to list existing tables, not modify or delete them.

2. Step 2: Match command to action

   Listing tables means showing all table names in your current AWS region and account.

3. Final Answer:

   It shows all DynamoDB tables in your AWS account and region. -> Option A

4. Quick Check:

   List tables = Show tables [OK]

Hint: List tables command always shows existing tables [OK]

Common Mistakes:

• Confusing list-tables with delete-table
• Thinking it creates or updates tables
• Assuming it shows table data instead of names

2. Which AWS CLI command syntax correctly adds an item to a DynamoDB table named Books with a primary key ISBN and a title attribute?

easy

A. aws dynamodb add-item --table Books --item '{ISBN: 12345, Title: Cloud Basics}'

B. aws dynamodb put-item --table-name Books --item '{"ISBN": {"S": "12345"}, "Title": {"S": "Cloud Basics"}}'

C. aws dynamodb insert-item --table-name Books --item '{"ISBN": "12345", "Title": "Cloud Basics"}'

D. aws dynamodb put-item --table Books --data '{"ISBN": "12345", "Title": "Cloud Basics"}'

Solution

1. Step 1: Identify correct command and parameters

   The correct command to add an item is put-item with --table-name and --item parameters.

2. Step 2: Check JSON format for item

   The item must be a JSON string with attribute names and types, e.g., {"ISBN": {"S": "12345"}} where "S" means string type.

3. Final Answer:

   aws dynamodb put-item --table-name Books --item '{"ISBN": {"S": "12345"}, "Title": {"S": "Cloud Basics"}}' -> Option B

4. Quick Check:

   Put-item + correct JSON format = aws dynamodb put-item --table-name Books --item '{"ISBN": {"S": "12345"}, "Title": {"S": "Cloud Basics"}}' [OK]

Hint: Use put-item with --item JSON including data types [OK]

Common Mistakes:

• Using wrong command like add-item or insert-item
• Missing data types in JSON attributes
• Using --table instead of --table-name

3. What will be the output of this AWS CLI command?

aws dynamodb get-item --table-name Users --key '{"UserId": {"S": "user123"}}' --projection-expression "Name, Age"

Assuming the table has an item with UserId 'user123', Name 'Alice', Age 30, and Email '[e-mail]'.

medium

A. Returns only the Email attribute.

B. Returns all attributes including Email.

C. Returns an error because projection-expression is invalid.

D. Returns only the Name and Age attributes of the item.

Solution

1. Step 1: Understand get-item with projection-expression

   The --projection-expression limits returned attributes to those listed, here "Name, Age".

2. Step 2: Check expected output

   Since Email is not in projection-expression, it will not be returned. Only Name and Age appear.

3. Final Answer:

   Returns only the Name and Age attributes of the item. -> Option D

4. Quick Check:

   Projection-expression filters attributes = Returns only the Name and Age attributes of the item. [OK]

Hint: Projection-expression returns only listed attributes [OK]

Common Mistakes:

• Assuming all attributes return by default
• Thinking projection-expression causes error
• Confusing projection-expression with filter-expression

4. You run this command but get an error:

aws dynamodb put-item --table-name Products --item '{"ProductId": "123", "Name": "Pen"}'

What is the likely cause of the error?

medium

A. The item JSON is missing data types for attributes.

B. The table name is incorrect.

C. The AWS CLI is not installed.

D. The command should use --update-item instead of --put-item.

Solution

1. Step 1: Check item JSON format requirements

   DynamoDB requires attribute values to specify data types, e.g., {"S": "123"} for string.

2. Step 2: Identify missing data types in JSON

   The command uses plain strings without data types, causing a syntax error.

3. Final Answer:

   The item JSON is missing data types for attributes. -> Option A

4. Quick Check:

   Missing data types in item JSON causes error [OK]

Hint: Always include data types like {"S": "value"} in item JSON [OK]

Common Mistakes:

• Ignoring data type syntax in item JSON
• Assuming --put-item is invalid command
• Not verifying table name correctness

5. You want to create a DynamoDB table named Orders with a primary key OrderId (string) and a sort key OrderDate (string). Which AWS CLI command is correct?

hard

A. aws dynamodb create-table --table-name Orders --attribute-definitions OrderId=S OrderDate=S --key-schema OrderId=HASH OrderDate=RANGE --provisioned-throughput Read=5,Write=5

B. aws dynamodb create-table --table Orders --attributes OrderId=S,OrderDate=S --keys OrderId=HASH,OrderDate=RANGE --throughput 5 5

C. aws dynamodb create-table --table-name Orders --attribute-definitions AttributeName=OrderId,AttributeType=S AttributeName=OrderDate,AttributeType=S --key-schema AttributeName=OrderId,KeyType=HASH AttributeName=OrderDate,KeyType=RANGE --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5

D. aws dynamodb create-table --table-name Orders --attributes OrderId S OrderDate S --key-schema OrderId HASH OrderDate RANGE --capacity 5 5

Solution

1. Step 1: Identify correct command syntax for create-table

   The correct syntax uses --attribute-definitions with AttributeName and AttributeType, and --key-schema with AttributeName and KeyType (HASH for partition key, RANGE for sort key).

2. Step 2: Check provisioned throughput format

   Provisioned throughput requires ReadCapacityUnits and WriteCapacityUnits with numeric values.

3. Final Answer:

   aws dynamodb create-table --table-name Orders --attribute-definitions AttributeName=OrderId,AttributeType=S AttributeName=OrderDate,AttributeType=S --key-schema AttributeName=OrderId,KeyType=HASH AttributeName=OrderDate,KeyType=RANGE --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5 -> Option C

4. Quick Check:

   Create-table syntax with attribute-definitions and key-schema = aws dynamodb create-table --table-name Orders --attribute-definitions AttributeName=OrderId,AttributeType=S AttributeName=OrderDate,AttributeType=S --key-schema AttributeName=OrderId,KeyType=HASH AttributeName=OrderDate,KeyType=RANGE --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5 [OK]

Hint: Use --attribute-definitions and --key-schema with correct keys [OK]

Common Mistakes:

• Using wrong flags like --table or --attributes
• Incorrect key schema format
• Wrong provisioned throughput parameter names