Starting and viewing data type assessments (Legacy) - AWS Database Migration Service

Starting and viewing data type assessments (Legacy)

Note

This section describes legacy content. We recommend that you use premigration assessment runs, described prior in Specifying, starting, and viewing premigration assessment runs.

Data type assessments are not available in the console. You can only run data type assessments using the API or CLI, and you can only view the results of a data type assessment in the task's S3 bucket.

A data type assessment identifies data types in a source database that might not get migrated correctly because the target doesn't support them. During this assessment, AWS DMS reads the source database schemas for a migration task and creates a list of the column data types. It then compares this list to a predefined list of data types supported by AWS DMS. If your migration task has unsupported data types, AWS DMS creates a report that you can look at to see if your migration task has any unsupported data types. AWS DMS doesn't create a report if your migration task doesn't have any unsupported data types.

AWS DMS supports creating data type assessment reports for the following relational databases:

  • Oracle

  • SQL Server

  • PostgreSQL

  • MySQL

  • MariaDB

  • Amazon Aurora

You can start and view a data type assessment report using the CLI and SDKs to access the AWS DMS API:

The data type assessment report is a single JSON file that includes a summary that lists the unsupported data types and the column count for each one. It includes a list of data structures for each unsupported data type including the schemas, tables, and columns that have the unsupported data type. You can use the report to modify the source data types and improve the migration success.

There are two levels of unsupported data types. Data types that appear on the report as not supported can't be migrated. Data types that appear on the report as partially supported might be converted to another data type, but not migrate as you expect.

The following example shows a sample data type assessment report that you might view.

{
    "summary":{
        "task-name":"test15",
        "not-supported":{
            "data-type": [
                "sql-variant"
            ],
            "column-count":3
        },
        "partially-supported":{
            "data-type":[
                "float8",
                "jsonb"
            ],
            "column-count":2
        }
    },
    "types":[  
        {  
            "data-type":"float8",
            "support-level":"partially-supported",
            "schemas":[  
                {      
                    "schema-name":"schema1",
                    "tables":[  
                        {  
                            "table-name":"table1",
                            "columns":[  
                                "column1",
                                "column2"
                            ]
                        },
                        {  
                            "table-name":"table2",
                            "columns":[  
                                "column3",
                                "column4"
                            ]
                        }
                    ]
                },
                {  
                    "schema-name":"schema2",
                    "tables":[  
                        {  
                            "table-name":"table3",
                            "columns":[  
                                "column5",
                                "column6"
                            ]
                        },
                        {  
                            "table-name":"table4",
                            "columns":[  
                                "column7",
                                "column8"
                            ]
                        }
                    ]
                }
            ]
        },
        {  
            "datatype":"int8",
            "support-level":"partially-supported",
            "schemas":[  
                {  
                    "schema-name":"schema1",
                    "tables":[  
                        {  
                            "table-name":"table1",
                            "columns":[  
                                "column9",
                                "column10"
                            ]
                        },
                        {  
                            "table-name":"table2",
                            "columns":[  
                                "column11",
                                "column12"
                            ]
                        }
                    ]
                }
            ]
        }
    ]
}

AWS DMS stores the latest and all previous data type assessments in an Amazon S3 bucket created by AWS DMS in your account. The Amazon S3 bucket name has the following format, where customerId is your customer ID and customerDNS is an internal identifier.

dms-customerId-customerDNS
Note

By default, you can create up to 100 Amazon S3 buckets in each of your AWS accounts. Because AWS DMS creates a bucket in your account, make sure that it doesn't exceed your bucket limit. Otherwise, the data type assessment fails.

All data type assessment reports for a given migration task are stored in a bucket folder named with the task identifier. Each report's file name is the date of the data type assessment in the format yyyy-mm-dd-hh-mm. You can view and compare previous data type assessment reports from the Amazon S3 Management Console.

AWS DMS also creates an AWS Identity and Access Management (IAM) role to allow access to the S3 bucket created for these reports. The role name is dms-access-for-tasks. The role uses the AmazonDMSRedshiftS3Role policy. If a ResourceNotFoundFault error occurs when you run StartReplicationTaskAssessment, see ResourceNotFoundFault in the Troubleshooting section for information about creating the dms-access-for-tasks role manually.