From: | "Igal (at) Lucee(dot)org" <igal(at)lucee(dot)org> |
---|---|
To: | Merlin Moncure <mmoncure(at)gmail(dot)com>, Adam Brusselback <adambrusselback(at)gmail(dot)com> |
Cc: | Allan Kamau <kamauallan(at)gmail(dot)com>, 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 23:41:58 |
Message-ID: | 76a6857b-e488-7509-81fd-c6543fe949ee@lucee.org |
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Thread: | |
Lists: | pgsql-general |
On 11/9/2017 8:19 AM, Merlin Moncure wrote:
> 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.
All sound advice. Thanks.
Igal Sapir
Lucee Core Developer
Lucee.org <http://lucee.org/>
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