Add support for Spark Connect (SQL models)

[vakarisbk]

partially resolves #814
docs dbt-labs/docs.getdbt.com/#

Problem

dbt-spark has limited options for open-source Spark integrations. Currently, the only available method to run dbt with open-source Spark in production is through a Thrift connection. However, a Thrift connection isn't suitable for all use cases. For instance, it doesn't support thrift over HTTP. Also, the PyHive project, that dbt thrift relies on, is unsupported (at least according to their GitHub page).

Solution

Propose introducing support for Spark Connect (for SQL models only).

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

How to test locally?

1. Follow the instructions in the Spark documentation to download Spark distribution. https://spark.apache.org/docs/latest/spark-connect-overview.html
2. Start spark connect server with Hive metastore enabled ./start-connect-server.sh --packages org.apache.spark:spark-connect_2.12:3.5.0 --conf spark.sql.catalogImplementation=hive
3. Add the Spark Connect configuration to your profiles.yml:

spark_connect:
  outputs:
    dev:
      host: localhost
      method: connect
      port: 15002
      schema: default
      type: spark
  target: dev

Known issues: #901

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[cla-bot]

Thank you for your pull request and welcome to our community. We could not parse the GitHub identity of the following contributors: Vakaris.
This is most likely caused by a git client misconfiguration; please make sure to:

1. check if your git client is configured with an email to sign commits git config --list | grep email
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[ben-schreiber]

Can we support pyspark>=3.4.0,<4, or at least pyspark>=3.5.0,<4?

[vakarisbk]

pyspark>=3.5.0,<4 added.
3.4.0 connect module has an issue where temporary views are not shared between queries. If one dbt query creates a temp view, another query cannot see it. Can't find a spark issue # now

[vakarisbk]

Seeing as there is some recent activity on Issue #814, and knowing that there are at least a couple of people actively using this fork, I've updated it. Looking forward for any insights regarding the implementation, as well as the likelihood of this pr getting merged.