Eventual-Inc/Daft - CodSpeed

Daft

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Latest Results

refactor(iceberg): validate the name mapping with PyIceberg at planning time

YuangGao:feat/iceberg-name-mapping

13 minutes ago

fix ci and cleanup

slade/remove-s3-options

3 hours ago

refactor(udf)!: remove legacy @daft.udf API (#7482) ## Summary - Remove the legacy `@daft.udf` API end to end. It was deprecated in 0.7.0 in favor of `@daft.func`, `@daft.cls`, and `@daft.method` (with `.batch` variants). Closes #7405. - Rust: delete `LegacyPythonUDF` / `MaybeInitializedUDF`; collapse `MapGroupsFn` into `AggExpr::MapGroups` holding `PyScalarFn` directly; `is_udf` / `is_actor_pool_udf` now route through `ScalarFn::Python` only. - Migrate `split_udfs` / optimizer test fixtures and the affected Python tests to v2 UDFs. - Docs: the legacy UDF page is now a "removed in 0.8.0" notice pointing at the migration guide; other pages link to `@daft.func` / `@daft.cls` instead. **BREAKING CHANGE:** `@daft.udf`, `daft.udf.UDF`, and `daft.functions.llm_generate` are removed. Use `@daft.func` / `@daft.cls` — see `docs/custom-code/migration.md`. Closes #7405 --------- Co-authored-by: xiyan.tr <xiyan.tr@alibaba-inc.com> Co-authored-by: Everett Kleven <145285237+everettVT@users.noreply.github.com>

main

4 hours ago

fix(parquet): reject name_mapping without field_id_mapping

YuangGao:feat/iceberg-name-mapping

6 hours ago

fix(ai): bound a long row's chunk requests by the same limits An input over `input_text_token_limit` is split into chunks, and every chunk went out in a single request. The per-request limits bind that request like any other: a row of roughly 1.2 MB chunks into enough pieces to exceed `batch_token_limit`, so it failed with an HTTP 400. That is true on `main` too - this path has never respected either limit. The chunks now go through the same fullness check as ordinary rows. A row that already succeeded keeps its embedding bit for bit, since the weighted average is taken over the same chunks with the same weights, only gathered from more than one response. A row between roughly 0.9 MB and 1.2 MB now takes two requests where it took one, because the three-characters-per-token estimate is more conservative than the server's tokenizer.

FANNG1:fix/ai-embed-batch-size-default

23 hours ago

fix(parquet): resolve legacy two-level list groups under name mapping

YuangGao:feat/iceberg-name-mapping

24 hours ago

feat(iceberg): read data files without field IDs via schema.name-mapping.default

YuangGao:feat/iceberg-name-mapping

24 hours ago

chore(ai): drop the embed option defaults that never applied Both text embedder descriptors declared `batch_size=64, max_retries=3, on_error="raise"` through a `default_factory`, but a provider always passes `embed_options` explicitly - an empty dict when the caller supplied no options - and an explicitly passed argument wins over `default_factory`. The declaration was therefore unreachable through `embed_text` and only misled readers. With the input cap enforced in the embedder, nothing depends on it. Whether `embed_text` should ship a default UDF `batch_size` is a separate question: it changes the request count for every existing caller, so it wants throughput benchmarks rather than a default that silently starts applying.

FANNG1:fix/ai-embed-batch-size-default

2 days ago

Latest Branches

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feat(iceberg): read data files without field IDs via schema.name-mapping.default#7618

25 minutes ago

0a3f482

YuangGao:feat/iceberg-name-mapping

0%

fix!: Remove unused `S3Config` options#7612

3 hours ago

6c222be

slade/remove-s3-options

0%

fix(ai): bound embedding requests by input count, not just tokens#7616

24 hours ago

8859bcf

FANNG1:fix/ai-embed-batch-size-default

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