From: | Merlin Moncure <mmoncure(at)gmail(dot)com> |
---|---|
To: | Adam Brusselback <adambrusselback(at)gmail(dot)com> |
Cc: | Allan Kamau <kamauallan(at)gmail(dot)com>, "Igal (at) Lucee(dot)org" <igal(at)lucee(dot)org>, Postgres General Postgres General <pgsql-general(at)postgresql(dot)org> |
Subject: | Re: Migrating money column from MS SQL Server to Postgres |
Date: | 2017-11-09 16:19:32 |
Message-ID: | CAHyXU0xt4c_N7jAkcGm+OBVYrDazxVStBQs_8kOudH=r-w=Rjw@mail.gmail.com |
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Lists: | pgsql-general |
On Thu, Nov 9, 2017 at 8:22 AM, Adam Brusselback
<adambrusselback(at)gmail(dot)com> wrote:
>> Since you are migrating data into a staging table in PostgreSQL, you may set
>> the field data type as TEXT for each field where you have noticed or
>> anticipate issues.
>> Then after population perform the datatype transformation query on the given
>> fields to determine the actual field value that could not be gracefully
>> transformed.
>
> This is the approach I have come to as the most successful for data migrations.
>
> I will use tools like Kettle / Talend to get data into a staging table
> with every column as text, then use SQL to migrate that to a properly
> typed table. Works much better than trying to work within the
> constraints of these tools.
YES
I call the approach 'ELT', (Extract, Load, Trasform). You are much
better off writing transformations in SQL than inside of an ETL tool.
This is a perfect example of why.
merlin
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