You pay for what you get! Getting things started with Iceberg on AWS was a beeeze. I was actaully plesantly supprised to find out the Iceberg is a first class table format along with AWS Glue. They must be seing promise with the technology.

Setup

1. AWS Glue can create Iceberg Tables directily

1. Setup a bucket
2. Setting up a schema

   [
     {
   "Name": "NAME_FIRST",
   "Type": "string",
   "Comment": ""
     },
     {
   "Name": "NAME_MIDDLE",
   "Type": "string",
   "Comment": ""
     },
     {
   "Name": "NAME_LAST",
   "Type": "string",
   "Comment": ""
     },
     {
   "Name": "NAME_INITIALS",
   "Type": "string",
   "Comment": ""
     },
     {
   "Name": "SEX",
   "Type": "string",
   "Comment": ""
     },
     {
   "Name": "LANGUAGE",
   "Type": "string",
   "Comment": ""
     },
     {
   "Name": "PHONENUMBER",
   "Type": "string",
   "Comment": ""
     },
     {
   "Name": "EMAILADDRESS",
   "Type": "string",
   "Comment": ""
     },
     {
   "Name": "LOGINNAME",
   "Type": "string",
   "Comment": ""
     },
     {
   "Name": "ADDRESSID",
   "Type": "int",
   "Comment": ""
     },
     {
   "Name": "VALIDITY_STARTDATE",
   "Type": "int",
   "Comment": ""
     },
     {
   "Name": "VALIDITY_ENDDATE",
   "Type": "int",
   "Comment": ""
     }
   ]
   

   AWS automatically create a folder called metadata

Use Athena Query Editor to interact with the table (Note: I adjuested some names.

DESCRIBE AWSDataCatalog.com_kfn_study_aws_iceberg_play_database_erp.employees;

INSERT INTO AWSDataCatalog.com_kfn_study_aws_iceberg_play_database_erp.employees VALUES (
    'name_first', 'name_middle', 'name_last', 'name_initials', 'sex',
    'language', 'phonenumber', 'emailaddress', 'loginname', 
    1234345, 20241010, 20241212 
);

SELECT * FROM AWSDataCatalog.com_kfn_study_aws_iceberg_play_database_erp.employees;

There is a new folder created in the bucket along with the metadata folder