refactor: replace streaming param with order=ScanOrder in concurrent …

…tests and docs

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

mkdocs/docs/api.md

@@ -371,19 +371,21 @@ for buf in tbl.scan().to_arrow_batch_reader(order=ScanOrder.ARRIVAL, batch_size=
     print(f"Buffer contains {len(buf)} rows")
 ```
 
-For maximum throughput, use `concurrent_files` to read multiple files in parallel while streaming. Batches are yielded as they arrive from any file — ordering across files is not guaranteed:
+For maximum throughput, use `concurrent_files` to read multiple files in parallel with arrival order. Batches are yielded as they arrive from any file — ordering across files is not guaranteed:
 
 ```python
-for buf in tbl.scan().to_arrow_batch_reader(streaming=True, concurrent_files=4, batch_size=1000):
+from pyiceberg.table import ScanOrder
+
+for buf in tbl.scan().to_arrow_batch_reader(order=ScanOrder.ARRIVAL, concurrent_files=4, batch_size=1000):
     print(f"Buffer contains {len(buf)} rows")
 ```
 
 **Ordering semantics:**
 
 | Configuration | File ordering | Within-file ordering |
 |---|---|---|
-| Default (`streaming=False`) | Batches grouped by file, in task submission order | Row order |
-| `streaming=True` | Interleaved across files (no grouping guarantee) | Row order within each file |
+| `ScanOrder.TASK` (default) | Batches grouped by file, in task submission order | Row order |
+| `ScanOrder.ARRIVAL` | Interleaved across files (no grouping guarantee) | Row order within each file |
 
 Within each file, batch ordering always follows row order. The `limit` parameter is enforced correctly regardless of configuration.
 
@@ -1671,13 +1673,15 @@ table.scan(
 ).to_arrow_batch_reader(order=ScanOrder.ARRIVAL)
 ```
 
-For concurrent file reads with streaming, use `concurrent_files`. Note that batch ordering across files is not guaranteed:
+For concurrent file reads with arrival order, use `concurrent_files`. Note that batch ordering across files is not guaranteed:
 
 ```python
+from pyiceberg.table import ScanOrder
+
 table.scan(
     row_filter=GreaterThanOrEqual("trip_distance", 10.0),
     selected_fields=("VendorID", "tpep_pickup_datetime", "tpep_dropoff_datetime"),
-).to_arrow_batch_reader(streaming=True, concurrent_files=4)
+).to_arrow_batch_reader(order=ScanOrder.ARRIVAL, concurrent_files=4)
 ```
 
 When using `concurrent_files > 1`, batches from different files may be interleaved. Within each file, batches are always in row order. See the ordering semantics table in the [Apache Arrow section](#apache-arrow) above for details.

tests/io/test_pyarrow.py

@@ -3277,7 +3277,7 @@ def test_task_order_with_positional_deletes(tmpdir: str) -> None:
 
 
 def test_concurrent_files_with_positional_deletes(tmpdir: str) -> None:
-    """Test that streaming=True with concurrent_files correctly applies positional deletes."""
+    """Test that order=ScanOrder.ARRIVAL with concurrent_files correctly applies positional deletes."""
     # 4 files, 10 rows each; delete different rows per file
     scan, tasks = _create_scan_and_tasks(
         tmpdir,
@@ -3286,7 +3286,7 @@ def test_concurrent_files_with_positional_deletes(tmpdir: str) -> None:
         delete_rows_per_file=[[0, 9], [4, 5], [0, 1, 2], []],
     )
 
-    batches = list(scan.to_record_batches(tasks, streaming=True, concurrent_files=2))
+    batches = list(scan.to_record_batches(tasks, order=ScanOrder.ARRIVAL, concurrent_files=2))
 
     total_rows = sum(len(b) for b in batches)
     assert total_rows == 33  # 40 - 7 deletes
@@ -3310,7 +3310,7 @@ def test_concurrent_files_with_positional_deletes_and_limit(tmpdir: str) -> None
         delete_rows_per_file=[[0], [0], [0], [0]],
     )
 
-    batches = list(scan.to_record_batches(tasks, streaming=True, concurrent_files=2))
+    batches = list(scan.to_record_batches(tasks, order=ScanOrder.ARRIVAL, concurrent_files=2))
 
     total_rows = sum(len(b) for b in batches)
     assert total_rows == 20
@@ -3321,7 +3321,7 @@ def test_concurrent_files_invalid_value(tmpdir: str) -> None:
     scan, tasks = _create_scan_and_tasks(tmpdir, num_files=1, rows_per_file=10)
 
     with pytest.raises(ValueError, match="concurrent_files must be >= 1"):
-        list(scan.to_record_batches(tasks, streaming=True, concurrent_files=0))
+        list(scan.to_record_batches(tasks, order=ScanOrder.ARRIVAL, concurrent_files=0))
 
 
 def test_parse_location_defaults() -> None: