[tae898]

Closes #228

On the native wheel, append_samples turned every column into a list with .tolist(), walked the timestamps again with int(), and sent the chunk as one JSON text. In the untimed probe of the l4 lane shape (100,000-point chunks, numpy columns, primitive=True), glue plus encode was 46.7% of the load wall (numbers in the issue). This PR sends the numeric columns by address.

What changes: a new library entry arcadedb_n_async_bin(handle, op, json, table, n_table) next to arcadedb_n_async. For append_samples, a one-dimensional numpy int, float or bool column, and an int or datetime64[ns] timestamp array, cross in an address table of (address, count) longs (the convention of arcadedb_n_insert_colp), and the JSON holds only a kind marker per column ("q" int64, "d" float64) and the sample count. The host tag column and every shape the text path converts differently keep the text: lists, float timestamps, other datetime64 units, 2-D and empty arrays, uint64 past the int64 range, a column whose length differs from the timestamps. Python side: codec.sample_array decides per column, NativeAsyncExecutor.append_samples builds the table. Java side: NativeExtras.asyncImpl (the old body of async, now shared by both entries) builds the same long[] and boxed Object[] columns the text gave and calls the same appendSamples.

What does not change: the stored samples are bit-identical to the text path (a float32 or float16 array widens to float64 exactly, a bool array is 0 and 1, a NaN is the canonical NaN the text gives, an int array into a DOUBLE column and a float array into a LONG column go through the same Number conversions). primitive=True keeps its meaning on the native build: the same length check, before the crossing, with the same message. A library without the entry (the loader sets lib.TS_BIN false) or ARCADEDB_NATIVE_TS_BIN=0 keeps the text path. The JVM wheel is not touched.

Tests (tests/test_native_timeseries_binary.py, native only, collected through conftest.py like the other native observers, no skips): the lane's shape takes arcadedb_n_async_bin once per chunk and its text holds no number of a numeric column, and the stored samples are read back by count, sums and a window; a matrix of dtypes (float64 with -0.0, NaN, infinities, 1e300 and 5e-324, float32, float16, int32 into DOUBLE, int64 extremes, uint8, bool, float into LONG) is stored bit-equal to the text path of the same call; timestamp arrays of int32, uint16, uint64, datetime64[ns] and a strided view are stored equal; non-contiguous and big-endian columns are stored as values; the entry choice for lists, float timestamps, datetime64[ms] (still a TypeError), a column of another length, primitive=True and a library without the entry; sample_array for 24 dtype cases; and the Java checks of a wrong address table (nothing is written). The CI run ids are in the first comment.

Not claimed: no speed number. A wheel-versus-wheel timed A/B (DECISIONS #240) runs on the laptop after the CI wheel exists; its verdict goes on this PR. The Java side still boxes each value once, the engine's TimeSeriesBatch route is a possible follow-up. This PR and #224 both touch lib.py and extras.py (a flag, a signature line, an import); the conflicts are textual.

🤖 Generated with Claude Code

[tae898]

CI on head 4cb904dbdb, read at 06:16 KST on 2026-11-04. The native build has compiled the new entry: the dispatch run of test-native.yml (41716062800) built and gated the wheels for linux-x86_64, linux-aarch64 and windows-x64; macos-arm64 was still building, and the parity tests (which include tests/test_native_timeseries_binary.py) start after the wheel jobs, so they have not run yet. The pull_request JVM run (41716066631) is green: the new test file is collected on the native backend only. The pull_request native run (41716066558) was skipped because the PR is a draft.

The test results will be added here when the dispatch run finishes. The timed A/B (DECISIONS #240, wheel versus wheel) is prepared and not started.