Change how a column of type VECTOR is parsed

[achawkins]

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 the SnowflakeColumn object from the from_description class method. This is because the dbt-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 form VECTOR(<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 in dbt-adapters and return a SnowflakeColumn that uses the raw data type as the parsed data type. If it does not, then pass it through to the default from_description method.

Checklist

• I have read the contributing guide and understand what's expected of me
• I have run this code in development and it appears to resolve the stated issue
• This PR includes tests, or tests are not required/relevant for this PR
• This PR has no interface changes (e.g. macros, cli, logs, json artifacts, config files, adapter interface, etc) or this PR has already received feedback and approval from Product or DX

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[colin-rogers-dbt]

@achawkins this looks pretty merge-able, are you able to sign our CLA and add a changelog?

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[achawkins]

@colin-rogers-dbt I must have signed the CLA with a different email before. I resigned it and added the changelog entry.

[colin-rogers-dbt]

@cla-bot check

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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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[cla-bot]

The cla-bot has been summoned, and re-checked this pull request!

[liorchen]

can this be merged? blocking us from moving forward