Python for Athena not working

[jmon-fluent]

Here's a link to the post I made on the DBT help site: https://discourse.getdbt.com/t/python-dbt-fal-with-athena-error-database-does-not-exist/8051/4

Describe the bug I tried following the directions here(dbt with AWS Athena and Python models. 1), but I’m getting an error.

I have dbt-fal (v 1.4.7) and dbt-athena-community (v1.4.3) installed in my conda environment

Your environment

• OS: WSL Ubuntu 22.04
• Paste the following commands output:

  fal --version
  dbt --version
  # Core:
  #  - installed: 1.4.6
  #  - latest:    1.5.0 - Update available!
  # Plugins:
  #  - postgres:         1.4.5 - Update available!
  #  - fal:              1.4.7 - Update available!
  #  - athena:           1.4.3 - Ahead of latest version!
  #  - fal_experimental: 1.4.7 - Could not determine latest version

How to reproduce Pretty much just run dbt run with your python model for Athena

Expected behavior A new table in the specified location in Athena

Actual behavior I get this error sqlalchemy.exc.OperationalError: (pyathena.error.OperationalError) [ErrorCategory:USER_ERROR, ErrorCode:SYNTAX_ERROR], Detail:FAILED: SemanticException [Error 10072]: Database does not exist: awsdatacatalog

What I noticed So I went to the athena.py script in the athena/fal_experimental/support path and started tinkering with the code. I was actually able to get it to "work" by changing some of the variables. I put work in quotes because I don't know if there are any other effects that my code has changed.

But pretty much needed to change references to "schema" to "table" in some places and then I needed to add a blackslash to the staging directory.

I don't mind doing this work and creating a PR, but I've never contributed to someone else's github before, so I'm a little apprehensive to do so.

[burkaygur]

Hi @jmon-fluent ! Feel free to do a PR and we will help you merge it.

[jmon-fluent]

Hi @jmon-fluent ! Feel free to do a PR and we will help you merge it.

Thanks! I actually just realized some things that maybe I should discuss first

• The final table (after the temp table), seems to get placed in a the s3_stagng_directory instead of the full table path, like the sql tables
  • E.g. SQL table location= s3://staging_directory/tables/table_name vs Python table location = s3://staging_directory
  • Would it make sense to update the code so that it matches the SQL s3 location?
• I realize that with python, the temp table is created by inserting the data frame values in 1 by 1. One alternative would be to have the data frame write directly to the s3 location as a csv or parquet file, and the temp Athena table just needs to point at this location. Are there any reasons the latter method would be undesirable?
  • One reason I ask is because "Drop Table" in Athena just removes the table reference, but the data still persists, so when we call drop_relation_if_it_exists(adapter, temp_relation) and then dataframe.to_sql(...), the temp table has all the old records and the new records
  • If we just overwrite the file, we'd make sure the temp table has only the new records
• I haven't checked what incremental mode looks like, so I'll probably ask about that when I get to that Please let me know any thoughts or concerns any of you might have

[occulkot]

Just for update, dbt-fal-1.5.9 is still unable to work with dbt-athena-community. Currently problem appears on resolving database/schema/table in ref/source functions. For me it claims table does not exist and in compiled code it shows quoted reference: refs = {"v_enrolled": "\"awsdatacatalog\".\"partner_dashboards\".\"v_enrolled\""} or sources = {"analytics.user_programs": "\"awsdatacatalog\".\"analytics\".\"user_programs\""}

Similar issue was found in here https://github.com/fal-ai/dbt-fal/pull/781