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Change how a column of type VECTOR is parsed #1169
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Thank you for your pull request and welcome to our community. We could not parse the GitHub identity of the following contributors: Andrew Hawkins.
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Thank you for your pull request and welcome to our community. We could not parse the GitHub identity of the following contributors: Andrew Hawkins.
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@achawkins this looks pretty merge-able, are you able to sign our CLA and add a changelog? |
Thank you for your pull request and welcome to our community. We could not parse the GitHub identity of the following contributors: Andrew Hawkins.
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@colin-rogers-dbt I must have signed the CLA with a different email before. I resigned it and added the changelog entry. |
@cla-bot check |
Thank you for your pull request and welcome to our community. We could not parse the GitHub identity of the following contributors: Andrew Hawkins.
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The cla-bot has been summoned, and re-checked this pull request! |
can this be merged? blocking us from moving forward |
Is there any update on this PR status? |
resolves #1098
docs dbt-labs/docs.getdbt.com/#
Problem
When an incremental (maybe other materializations, but I have not checked) model with a
VECTOR
type is run, it will fail to create theSnowflakeColumn
object from thefrom_description
class method. This is because thedbt-adapters
Column.from_description
method does some parsing to extract the precision and scale of a numeric type and tries to cast both values within parenthesis to integers. The Snowflake vector is of the formVECTOR(<data_type>, <dimension>)
, so the<data_type>
will fail to be cast as an integer.Solution
If the data type has the word
VECTOR
in it, bypass the additional parsing done indbt-adapters
and return aSnowflakeColumn
that uses the raw data type as the parsed data type. If it does not, then pass it through to the defaultfrom_description
method.Checklist