Step 1 - Create the employees table for global secondary index key overloading

Run the following AWS CLI command to create the employees table.

aws dynamodb create-table --table-name employees \
--attribute-definitions AttributeName=PK,AttributeType=S AttributeName=SK,AttributeType=S \
AttributeName=GSI_1_PK,AttributeType=S AttributeName=GSI_1_SK,AttributeType=S \
--key-schema AttributeName=PK,KeyType=HASH AttributeName=SK,KeyType=RANGE \
--provisioned-throughput ReadCapacityUnits=100,WriteCapacityUnits=100 \
--tags Key=workshop-design-patterns,Value=targeted-for-cleanup \
--global-secondary-indexes "IndexName=GSI_1,\
KeySchema=[{AttributeName=GSI_1_PK,KeyType=HASH},{AttributeName=GSI_1_SK,KeyType=RANGE}],\
Projection={ProjectionType=ALL},\
ProvisionedThroughput={ReadCapacityUnits=100,WriteCapacityUnits=100}"

Run the following command to wait until the table becomes active.

aws dynamodb wait table-exists --table-name employees

Let’s take a closer look at the create-table command. You are creating a table named employees. The partition key on the table is PK and it holds the employee ID. The sort key is SK, which contains a derived value that you choose in the Python script. (We’ll revisit this shortly.) You will create a global secondary index on this table and name it GSI_1; This will be an overloaded global secondary index. The partition key on the global secondary index is GSI_1_PK, and holds the same value as the sort key SK on the base table. The GSI_1 sort key value is name, and its attribute name is GSI_1_SK.

Table: employees

• Key schema: HASH, RANGE (partition and sort key)
• Table read capacity units (RCUs) = 100
• Table write capacity units (WCUs) = 100
• Global secondary index:
  • GSI_1 (100 RCUs, 100 WCUs) - Allows for querying by host IP address.