feat: add timestamp normalization for BigQuery artifacts

[niccoloalexander]

Issues:

• Problem parsing hyphenated BigQuery dataset names e.g. "project-name" when using dbt Fusion
• dbt artifact timestamps that elementary writes to BigQuery and parses as timestamps have incompatible nanosecond-level granularity

Changes:

• Introduced a new macro normalize_artifact_timestamp_precision to ensure timestamp precision for BigQuery.
• Updated existing macros to utilize this new function for execute_started_at, execute_completed_at, compile_started_at, and compile_completed_at fields in upload_run_results.sql and upload_source_freshness.sql.
• Enhanced schema existence checks for BigQuery in create_elementary_tests_schema.sql and get_elementary_tests_schema.sql to improve compatibility.

Summary by CodeRabbit

• Bug Fixes
  • Normalize timestamp precision for artifact timing fields to prevent overly‑precise fractional seconds (improves BigQuery compatibility).
  • Improve schema-existence checks and validation logic to handle BigQuery information schema correctly, reducing false negatives when creating or detecting test schemas.

[github-actions]

👋 @niccoloalexander
Thank you for raising your pull request.
Please make sure to add tests and document all user-facing changes.
You can do this by editing the docs files in the elementary repository.

[coderabbitai]

No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Pro

Run ID: e759373d-f019-4688-9d95-a74d94d09d58

📥 Commits

Reviewing files that changed from the base of the PR and between 7e1be1b and 8a7967c.

📒 Files selected for processing (2)

• macros/edr/tests/on_run_start/create_elementary_tests_schema.sql
• macros/edr/tests/test_utils/get_elementary_tests_schema.sql

🚧 Files skipped from review as they are similar to previous changes (1)

• macros/edr/tests/on_run_start/create_elementary_tests_schema.sql

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📝 Walkthrough

Walkthrough

Normalize timestamp precision for BigQuery artifacts and switch to BigQuery-specific INFORMATION_SCHEMA schema existence checks while retaining adapter-based checks for other targets across EDR and test utility macros.

Changes

Cohort / File(s)	Summary
Timestamp Precision Normalization macros/edr/dbt_artifacts/upload_run_results.sql, macros/edr/dbt_artifacts/upload_source_freshness.sql	Added normalize_artifact_timestamp_precision(timestamp_value) and updated flatten_run_result / flatten_source_freshness to pass execute_*_at and compile_*_at through the normalizer for BigQuery targets.
BigQuery Schema Existence Checks macros/edr/tests/on_run_start/create_elementary_tests_schema.sql, macros/edr/tests/test_utils/get_elementary_tests_schema.sql	Replaced unconditional adapter.check_schema_exists(...) calls with a branch: for target.type == "bigquery", run an INFORMATION_SCHEMA.SCHEMATA COUNT(*) query (case-insensitive) and derive existence from the count; otherwise keep the adapter check.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

Poem

Hop-hop, I trim the timestamps neat,
Six tiny ticks make records sweet.
I peek in schemas, count with care,
BigQuery answers — none elsewhere. 🐇✨

🚥 Pre-merge checks | ✅ 3

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The pull request title accurately describes the main change: adding timestamp normalization functionality specifically for BigQuery artifacts, which is the primary focus across multiple modified files.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.

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[coderabbitai]

Actionable comments posted: 2

🧹 Nitpick comments (1)

macros/edr/tests/on_run_start/create_elementary_tests_schema.sql (1)

9-23: Consider extracting this BigQuery schema-exists check into a shared macro.

This logic is duplicated in macros/edr/tests/test_utils/get_elementary_tests_schema.sql (same SQL + result parsing pattern). A shared helper would keep behavior consistent and reduce drift.

🤖 Prompt for AI Agents

Verify each finding against the current code and only fix it if needed.

In `@macros/edr/tests/on_run_start/create_elementary_tests_schema.sql` around
lines 9 - 23, Extract the BigQuery schema-exists logic (the block that builds
schema_exists_sql, calls elementary.run_query into schema_exists_result, and
computes schema_exists) into a shared macro (e.g.,
get_elementary_tests_schema_exists) and use that macro from both
create_elementary_tests_schema.sql and get_elementary_tests_schema.sql; the
macro should accept database_name and tests_schema_name, run the same
INFORMATION_SCHEMA query via elementary.run_query, parse rows[0][0] to an int
boolean, and return the boolean so you can replace the duplicated
schema_exists_sql/schema_exists_result/schema_exists code with a single macro
call.

🤖 Prompt for all review comments with AI agents

Verify each finding against the current code and only fix it if needed.

Inline comments:
In `@macros/edr/tests/on_run_start/create_elementary_tests_schema.sql`:
- Around line 15-20: The current check reads schema_exists_result.rows[0][0]
directly which breaks in Fusion; replace the direct rows access by converting
the run_query result with elementary.agate_to_dicts(schema_exists_result) and
then inspect the first dict/value to determine existence (update the logic
around schema_exists_result and schema_exists); apply the same change in both
locations referencing elementary.run_query in create_elementary_tests_schema.sql
and get_elementary_tests_schema.sql so the code uses
elementary.agate_to_dicts(...) instead of schema_exists_result.rows[0][0].

In `@macros/edr/tests/test_utils/get_elementary_tests_schema.sql`:
- Around line 24-29: The current legacy_schema_exists computation reads
legacy_schema_exists_result.rows[0][0] which breaks in dbt Fusion because
elementary.run_query() can return a different shape; update the logic that sets
legacy_schema_exists (and the variable legacy_schema_exists_result from
elementary.run_query(legacy_schema_exists_sql)) to normalize the result via
elementary.agate_to_dicts(legacy_schema_exists_result) (or the equivalent
conversion) and then check the first row/value safely via the normalized
dict/list structure so both legacy and Fusion run_query() result shapes are
supported.

---

Nitpick comments:
In `@macros/edr/tests/on_run_start/create_elementary_tests_schema.sql`:
- Around line 9-23: Extract the BigQuery schema-exists logic (the block that
builds schema_exists_sql, calls elementary.run_query into schema_exists_result,
and computes schema_exists) into a shared macro (e.g.,
get_elementary_tests_schema_exists) and use that macro from both
create_elementary_tests_schema.sql and get_elementary_tests_schema.sql; the
macro should accept database_name and tests_schema_name, run the same
INFORMATION_SCHEMA query via elementary.run_query, parse rows[0][0] to an int
boolean, and return the boolean so you can replace the duplicated
schema_exists_sql/schema_exists_result/schema_exists code with a single macro
call.

🪄 Autofix (Beta)

Fix all unresolved CodeRabbit comments on this PR:

• Push a commit to this branch (recommended)
• Create a new PR with the fixes

---

ℹ️ Review info

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Pro

Run ID: 99ee226d-2fc5-4e5e-86f8-97a52e265b73

📥 Commits

Reviewing files that changed from the base of the PR and between b8c7ab0 and 7e1be1b.

📒 Files selected for processing (4)

• macros/edr/dbt_artifacts/upload_run_results.sql
• macros/edr/dbt_artifacts/upload_source_freshness.sql
• macros/edr/tests/on_run_start/create_elementary_tests_schema.sql
• macros/edr/tests/test_utils/get_elementary_tests_schema.sql