Arrow IPC binary fetch path for DataFrame execution#1489
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Codecov Report❌ Patch coverage is Additional details and impacted files@@ Coverage Diff @@
## master #1489 +/- ##
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+ Coverage 78.13% 78.38% +0.25%
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Files 228 230 +2
Lines 14926 15212 +286
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+ Hits 11662 11924 +262
- Misses 3264 3288 +24 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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packages/gooddata-sdk/pyproject.toml
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| [project.optional-dependencies] | ||
| arrow = ["pyarrow>=16.1.0"] |
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Nitpick: this is a new dependency. Consider setting the threshold higher e.g., pyarrow>=23.0.1
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packages/gooddata-sdk/src/gooddata_sdk/compute/model/execution.py
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Switch read_result_arrow to explicitly request application/vnd.apache.arrow.stream via Accept header and pipe the HTTP response directly into ipc.open_stream(), eliminating the intermediate BytesIO buffer. Update tests accordingly.
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Summary
Adds a native Arrow IPC binary fetch path to gooddata-pandas, providing a faster alternative to the existing JSON-paged AFM path for large result sets.
What changed
gooddata-sdk — binary fetch
gooddata-pandas — Arrow→DataFrame conversion
Why
The JSON paging path serialises every result to JSON and pages it in chunks — it is CPU-heavy and slow for wide or deep result sets. Arrow IPC transfers binary columnar
data in a single round-trip. End-to-end benchmarks against the GoodData demo workspace show 1.3×–33× speedup depending on table shape, with larger tables benefiting most .
Test coverage