laskoviymishka commented on code in PR #3058:
URL: https://github.com/apache/iceberg-rust/pull/3058#discussion_r3866075566
##########
crates/iceberg/src/arrow/reader/pipeline.rs:
##########
@@ -421,6 +467,25 @@ impl FileScanTaskReader {
};
}
+ if project_row_id {
+ // A name-only physical `_row_id` can't be threaded (synthesis
keys the physical
+ // leaf by its reserved field id), and no conformant writer emits
it, so reject
+ // it -- regardless of `first_row_id`, since it never threads
either way.
+ if row_id_present_by_name_only {
Review Comment:
I think this rejects too eagerly. The physical column is only read when
`first_row_id.is_some()` (`coalesce_row_id_leaf` is gated on it), so with a
null `first_row_id` there's nothing to thread — the column gets nulled out
anyway. But this guard fires before we look at `first_row_id`, so a pre-v3 file
that happens to carry a user column named `_row_id` (legal before v3 reserved
the name) would hard-error on scan instead of returning nulls. That breaks
reads on migrated tables.
The `_last_updated_sequence_number` guard sidesteps this by living inside
its `(Some(_), Some(seq))` arm. I'd mirror that and gate the reject on
`first_row_id.is_some()`:
```rust
if project_row_id {
if task.first_row_id.is_some() && row_id_present_by_name_only {
return Err(...);
}
record_batch_transformer_builder =
record_batch_transformer_builder.with_virtual_field(RESERVED_FIELD_ID_ROW_ID);
}
```
The comment says the reject is intentional "regardless of `first_row_id`" —
is there a case where a null-`first_row_id` file with a name-only `_row_id`
should error rather than null out? If so I'd spell it out; otherwise I'd gate
it. wdyt?
##########
crates/iceberg/src/arrow/reader/pipeline.rs:
##########
@@ -1453,6 +1520,680 @@ mod tests {
);
}
+ /// A scan task projecting `id` + `_row_id`, with the given `first_row_id`.
+ fn row_id_task(file_path: String, first_row_id: Option<i64>) ->
FileScanTask {
+ let schema = Arc::new(
+ Schema::builder()
+ .with_schema_id(1)
+ .with_fields(vec![
+ NestedField::required(1, "id",
Type::Primitive(PrimitiveType::Int)).into(),
+ ])
+ .build()
+ .unwrap(),
+ );
+
+ FileScanTask::builder()
+
.with_file_size_in_bytes(std::fs::metadata(&file_path).unwrap().len())
+ .with_start(0)
+ .with_length(0)
+ .with_data_file_path(file_path)
+ .with_data_file_format(DataFileFormat::Parquet)
+ .with_schema(schema)
+ .with_project_field_ids(vec![1, RESERVED_FIELD_ID_ROW_ID])
+ .with_first_row_id(first_row_id)
+ .with_case_sensitive(false)
+ .build()
+ }
+
+ /// Asserts the logical per-row values of the `_row_id` column across all
batches,
+ /// independent of the physical (run-end) encoding.
+ fn assert_row_id_column(batches: &[RecordBatch], expected: &[Option<i64>])
{
+ use arrow_array::cast::AsArray;
+ use arrow_cast::cast;
+ use arrow_schema::DataType;
+
+ let mut actual = Vec::new();
+ for batch in batches {
+ let col = batch
+ .column_by_name(RESERVED_COL_NAME_ROW_ID)
+ .expect("_row_id column should be present");
+ let logical = cast(col, &DataType::Int64).unwrap();
+ let values =
logical.as_primitive::<arrow_array::types::Int64Type>();
+ for i in 0..values.len() {
+ actual.push((!values.is_null(i)).then(|| values.value(i)));
+ }
+ }
+ assert_eq!(actual, expected);
+ }
+
+ /// A parquet field carrying the embedded `_row_id` field id.
+ fn physical_row_id_field() -> Field {
+ Field::new(RESERVED_COL_NAME_ROW_ID, DataType::Int64,
true).with_metadata(HashMap::from([
+ (
+ PARQUET_FIELD_ID_META_KEY.to_string(),
+ RESERVED_FIELD_ID_ROW_ID.to_string(),
+ ),
+ ]))
+ }
+
+ #[tokio::test]
+ async fn test_row_id_synthesized_from_first_row_id_and_pos() {
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+ let file_path = write_plain_parquet(dir, "row_id_synth.parquet",
vec![], vec![]);
+
+ // No physical column: every row is first_row_id + pos.
+ let task = row_id_task(file_path, Some(100));
+
+ let reader = ArrowReaderBuilder::new(FileIO::new_with_fs(),
Runtime::current()).build();
+ let tasks = Box::pin(futures::stream::iter(vec![Ok(task)])) as
FileScanTaskStream;
+ let batches: Vec<RecordBatch> = reader
+ .read(tasks)
+ .unwrap()
+ .stream()
+ .try_collect()
+ .await
+ .unwrap();
+
+ assert_row_id_column(&batches, &[Some(100), Some(101), Some(102)]);
+ }
+
+ #[tokio::test]
+ async fn test_row_id_physical_column_coalesced() {
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+ // A file that physically carries `_row_id`, as written when carrying
rows forward
+ // across a rewrite: some rows have a stored value, some are null.
+ let id_col = Arc::new(Int64Array::from(vec![Some(5), None, Some(8)]))
as ArrayRef;
+ let file_path = write_plain_parquet(
+ dir,
+ "row_id_phys.parquet",
+ vec![physical_row_id_field()],
+ vec![id_col],
+ );
+
+ let task = row_id_task(file_path, Some(100));
+
+ let reader = ArrowReaderBuilder::new(FileIO::new_with_fs(),
Runtime::current()).build();
+ let tasks = Box::pin(futures::stream::iter(vec![Ok(task)])) as
FileScanTaskStream;
+ let batches: Vec<RecordBatch> = reader
+ .read(tasks)
+ .unwrap()
+ .stream()
+ .try_collect()
+ .await
+ .unwrap();
+
+ // Per-row value where non-null; first_row_id + pos (101) where null.
+ assert_row_id_column(&batches, &[Some(5), Some(101), Some(8)]);
+ }
+
+ #[tokio::test]
+ async fn test_row_id_only_synthesis_reads_no_data_columns() {
+ // The common v3 case: a new-row file with `first_row_id` set and NO
physically
+ // stored `_row_id`, projecting only `_row_id`. `_row_id` synthesis
installs the
+ // RowNumber virtual column (via `need_row_number`), so the row count
comes from it
+ // -- the scan must read no data columns, not fall back to reading
everything.
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+
+ let mut meta_only = metadata_projection_task(
+ write_parquet_with_wide_column(dir, "row_id_only.parquet", vec![],
vec![]),
+ id_and_wide_schema(),
+ vec![RESERVED_FIELD_ID_ROW_ID],
+ );
+ meta_only.first_row_id = Some(100);
+ let (batches, meta_only_bytes) = scan_task(meta_only).await;
+
+ assert_eq!(batches[0].num_columns(), 1);
+ assert_row_id_column(&batches, &[Some(100), Some(101), Some(102)]);
+
+ // A scan that also projects the wide data column must read materially
more.
+ let mut with_data = metadata_projection_task(
+ write_parquet_with_wide_column(dir, "row_id_only_ref.parquet",
vec![], vec![]),
+ id_and_wide_schema(),
+ vec![2, RESERVED_FIELD_ID_ROW_ID],
+ );
+ with_data.first_row_id = Some(100);
+ let (_, with_data_bytes) = scan_task(with_data).await;
+
+ assert!(
+ meta_only_bytes < with_data_bytes,
+ "_row_id-only synthesis should read fewer bytes than a scan of the
wide column: \
+ {meta_only_bytes} vs {with_data_bytes}"
+ );
+ }
+
+ #[tokio::test]
+ async fn test_row_id_resolves_alongside_id_less_leaf() {
+ // A file with an id-less leaf (mimicking a Variant column's internal
metadata/value
+ // leaves, which the spec requires to have no field id) plus a
physical `_row_id`
+ // that carries its embedded id. The reserved id must still resolve --
an
+ // all-or-nothing field map would bail on the id-less leaf and wrongly
reject the file.
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+ let idless_field = Field::new("variant_internal", DataType::Utf8,
true);
+ let idless_col = Arc::new(StringArray::from(vec!["a", "b", "c"])) as
ArrayRef;
+ let row_id_col = Arc::new(Int64Array::from(vec![Some(5), None,
Some(8)])) as ArrayRef;
+ let file_path = write_plain_parquet(
+ dir,
+ "row_id_with_idless_leaf.parquet",
+ vec![idless_field, physical_row_id_field()],
+ vec![idless_col, row_id_col],
+ );
+
+ let task = row_id_task(file_path, Some(100));
+
+ let reader = ArrowReaderBuilder::new(FileIO::new_with_fs(),
Runtime::current()).build();
+ let tasks = Box::pin(futures::stream::iter(vec![Ok(task)])) as
FileScanTaskStream;
+ let batches: Vec<RecordBatch> = reader
+ .read(tasks)
+ .unwrap()
+ .stream()
+ .try_collect()
+ .await
+ .unwrap();
+
+ // Physical value where non-null; first_row_id + pos (101) where null.
+ assert_row_id_column(&batches, &[Some(5), Some(101), Some(8)]);
+ }
+
+ #[tokio::test]
+ async fn test_row_id_and_last_updated_seq_co_projected() {
+ use
crate::metadata_columns::RESERVED_FIELD_ID_LAST_UPDATED_SEQUENCE_NUMBER;
+
+ // Both lineage columns projected together over a file carrying both
physical
+ // leaves. Each must materialize independently -- neither leaf's mask
clobbers the
+ // other, and the two synthesized columns keep their own values.
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+ let row_id_col = Arc::new(Int64Array::from(vec![Some(5), None,
Some(8)])) as ArrayRef;
+ let seq_col = Arc::new(Int64Array::from(vec![Some(50), None,
Some(70)])) as ArrayRef;
+ let file_path = write_plain_parquet(
+ dir,
+ "row_id_and_seq.parquet",
+ vec![physical_row_id_field(), physical_last_updated_seq_field()],
+ vec![row_id_col, seq_col],
+ );
+
+ let schema = Arc::new(
+ Schema::builder()
+ .with_schema_id(1)
+ .with_fields(vec![
+ NestedField::required(1, "id",
Type::Primitive(PrimitiveType::Int)).into(),
+ ])
+ .build()
+ .unwrap(),
+ );
+ let task = FileScanTask::builder()
+
.with_file_size_in_bytes(std::fs::metadata(&file_path).unwrap().len())
+ .with_start(0)
+ .with_length(0)
+ .with_data_file_path(file_path)
+ .with_data_file_format(DataFileFormat::Parquet)
+ .with_schema(schema)
+ .with_project_field_ids(vec![
+ 1,
+ RESERVED_FIELD_ID_ROW_ID,
+ RESERVED_FIELD_ID_LAST_UPDATED_SEQUENCE_NUMBER,
+ ])
+ .with_first_row_id(Some(100))
+ .with_data_sequence_number(Some(9))
+ .with_case_sensitive(false)
+ .build();
+
+ let reader = ArrowReaderBuilder::new(FileIO::new_with_fs(),
Runtime::current()).build();
+ let tasks = Box::pin(futures::stream::iter(vec![Ok(task)])) as
FileScanTaskStream;
+ let batches: Vec<RecordBatch> = reader
+ .read(tasks)
+ .unwrap()
+ .stream()
+ .try_collect()
+ .await
+ .unwrap();
+
+ // _row_id: physical value where non-null, else first_row_id + pos
(101).
+ assert_row_id_column(&batches, &[Some(5), Some(101), Some(8)]);
+ // _last_updated_sequence_number: physical value where non-null, else
data seq (9).
+ assert_last_updated_seq_column(&batches, &[Some(50), Some(9),
Some(70)]);
+ }
+
+ #[tokio::test]
+ async fn test_row_id_null_when_no_first_row_id() {
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+ // Physically carries `_row_id`, but the file has a null first_row_id.
+ let id_col = Arc::new(Int64Array::from(vec![Some(5), Some(6),
Some(7)])) as ArrayRef;
+ let file_path = write_plain_parquet(
+ dir,
+ "row_id_no_first.parquet",
+ vec![physical_row_id_field()],
+ vec![id_col],
+ );
+
+ // Null first_row_id: the whole column is null; the physical values
are not read.
+ let task = row_id_task(file_path, None);
+
+ let reader = ArrowReaderBuilder::new(FileIO::new_with_fs(),
Runtime::current()).build();
+ let tasks = Box::pin(futures::stream::iter(vec![Ok(task)])) as
FileScanTaskStream;
+ let batches: Vec<RecordBatch> = reader
+ .read(tasks)
+ .unwrap()
+ .stream()
+ .try_collect()
+ .await
+ .unwrap();
+
+ assert_row_id_column(&batches, &[None, None, None]);
+ }
+
+ #[tokio::test]
+ async fn test_row_id_with_pos_column() {
+ use crate::metadata_columns::RESERVED_COL_NAME_POS;
+
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+ let id_col = Arc::new(Int64Array::from(vec![Some(5), None, Some(8)]))
as ArrayRef;
+ let file_path = write_plain_parquet(
+ dir,
+ "row_id_and_pos.parquet",
+ vec![physical_row_id_field()],
+ vec![id_col],
+ );
+
+ // Co-project `_pos` and `_row_id`. `_row_id` synthesis consumes the
position, and
+ // `_pos` is also emitted -- the RowNumber column must be added once
and the two
+ // must not interfere.
+ let schema = Arc::new(
+ Schema::builder()
+ .with_schema_id(1)
+ .with_fields(vec![
+ NestedField::required(1, "id",
Type::Primitive(PrimitiveType::Int)).into(),
+ ])
+ .build()
+ .unwrap(),
+ );
+ let task = FileScanTask::builder()
+
.with_file_size_in_bytes(std::fs::metadata(&file_path).unwrap().len())
+ .with_start(0)
+ .with_length(0)
+ .with_data_file_path(file_path)
+ .with_data_file_format(DataFileFormat::Parquet)
+ .with_schema(schema)
+ .with_project_field_ids(vec![1, RESERVED_FIELD_ID_POS,
RESERVED_FIELD_ID_ROW_ID])
+ .with_first_row_id(Some(100))
+ .with_case_sensitive(false)
+ .build();
+
+ let reader = ArrowReaderBuilder::new(FileIO::new_with_fs(),
Runtime::current()).build();
+ let tasks = Box::pin(futures::stream::iter(vec![Ok(task)])) as
FileScanTaskStream;
+ let batches: Vec<RecordBatch> = reader
+ .read(tasks)
+ .unwrap()
+ .stream()
+ .try_collect()
+ .await
+ .unwrap();
+
+ // `_row_id` coalesces correctly...
+ assert_row_id_column(&batches, &[Some(5), Some(101), Some(8)]);
+ // ...and `_pos` is the row position, not double-counted.
+ let pos_col = batches[0]
+ .column_by_name(RESERVED_COL_NAME_POS)
+ .expect("_pos column should be present")
+ .as_primitive::<arrow_array::types::Int64Type>();
+ assert_eq!(pos_col.values(), &[0, 1, 2]);
+ }
+
+ #[tokio::test]
+ async fn test_row_id_mixed_files_share_schema() {
+ use arrow_select::concat::concat_batches;
+
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+
+ // Three files in one scan exercising all three column paths, which
must all
+ // produce the SAME Arrow type (plain Int64) or concatenation fails:
+ // - synthesis: first_row_id set, no physical column -> first_row_id
+ pos
+ // - null gate: no first_row_id -> null column
+ // - coalesce: first_row_id set, physical column present -> per-row
+ fallback
+ let synth = row_id_task(
+ write_plain_parquet(dir, "row_id_synth2.parquet", vec![], vec![]),
+ Some(42),
+ );
+ let nulled = row_id_task(
+ write_plain_parquet(dir, "row_id_null2.parquet", vec![], vec![]),
+ None,
+ );
+ let coalesced = row_id_task(
+ write_plain_parquet(
+ dir,
+ "row_id_coalesced2.parquet",
+ vec![physical_row_id_field()],
+ vec![Arc::new(Int64Array::from(vec![Some(5), None, Some(8)]))
as ArrayRef],
+ ),
+ Some(50),
+ );
+
+ let reader = ArrowReaderBuilder::new(FileIO::new_with_fs(),
Runtime::current()).build();
+ let tasks = Box::pin(futures::stream::iter(vec![
+ Ok(synth),
+ Ok(nulled),
+ Ok(coalesced),
+ ])) as FileScanTaskStream;
+ let batches: Vec<RecordBatch> = reader
+ .read(tasks)
+ .unwrap()
+ .stream()
+ .try_collect()
+ .await
+ .unwrap();
+
+ assert_eq!(batches.len(), 3);
+ let schema = batches[0].schema();
+ concat_batches(&schema, &batches)
+ .expect("synthesis, null and coalesce files must share one column
type");
+ }
+
+ #[tokio::test]
+ async fn test_row_id_present_by_name_without_id_unsupported() {
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+ // Column present by name but WITHOUT the embedded field id. The
transformer keys
+ // the source column by field id, so this shape can't be threaded and
is rejected.
+ let id_field = Field::new(RESERVED_COL_NAME_ROW_ID, DataType::Int64,
true);
+ let id_col = Arc::new(Int64Array::from(vec![Some(5), None, Some(8)]))
as ArrayRef;
+ let file_path =
+ write_plain_parquet(dir, "row_id_by_name.parquet", vec![id_field],
vec![id_col]);
+
+ let task = row_id_task(file_path, Some(100));
+
+ let reader = ArrowReaderBuilder::new(FileIO::new_with_fs(),
Runtime::current()).build();
+ let tasks = Box::pin(futures::stream::iter(vec![Ok(task)])) as
FileScanTaskStream;
+ let result: Result<Vec<RecordBatch>, _> =
+ reader.read(tasks).unwrap().stream().try_collect().await;
+
+ let err = result.unwrap_err();
+ assert_eq!(err.kind(), crate::ErrorKind::FeatureUnsupported);
+ assert!(
+ format!("{err}").contains("without an embedded field id"),
+ "unexpected error: {err}"
+ );
+ }
+
+ /// Builds a `row_id_task` (see above) that additionally carries a bound
predicate,
+ /// so a `RowSelection` is applied when the reader has row selection
enabled.
+ fn row_id_task_with_predicate(
+ file_path: String,
+ first_row_id: Option<i64>,
+ extra_project_field_ids: Vec<i32>,
+ predicate: crate::expr::Predicate,
+ ) -> FileScanTask {
+ use crate::expr::Bind;
+
+ let schema = Arc::new(
+ Schema::builder()
+ .with_schema_id(1)
+ .with_fields(vec![
+ NestedField::required(1, "id",
Type::Primitive(PrimitiveType::Int)).into(),
+ ])
+ .build()
+ .unwrap(),
+ );
+ let bound = predicate.bind(Arc::clone(&schema), false).unwrap();
+
+ let mut project_field_ids = vec![1];
+ project_field_ids.extend(extra_project_field_ids);
+ project_field_ids.push(RESERVED_FIELD_ID_ROW_ID);
+
+ FileScanTask::builder()
+
.with_file_size_in_bytes(std::fs::metadata(&file_path).unwrap().len())
+ .with_start(0)
+ .with_length(0)
+ .with_data_file_path(file_path)
+ .with_data_file_format(DataFileFormat::Parquet)
+ .with_schema(schema)
+ .with_project_field_ids(project_field_ids)
+ .with_predicate(Some(bound))
+ .with_first_row_id(first_row_id)
+ .with_case_sensitive(false)
+ .build()
+ }
+
+ #[tokio::test]
+ async fn test_row_id_stable_under_row_selection() {
+ use crate::expr::Reference;
+ use crate::spec::Datum;
+
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+ // id = [1, 2, 3]; drop the middle physical row via a predicate + row
selection.
+ let file_path = write_plain_parquet(dir, "row_id_selection.parquet",
vec![], vec![]);
+
+ let task = row_id_task_with_predicate(
+ file_path,
+ Some(100),
+ vec![],
+ Reference::new("id").not_equal_to(Datum::int(2)),
+ );
+
+ // Row selection must be enabled for the predicate to produce a
RowSelection.
+ let reader = ArrowReaderBuilder::new(FileIO::new_with_fs(),
Runtime::current())
+ .with_row_selection_enabled(true)
+ .build();
+ let tasks = Box::pin(futures::stream::iter(vec![Ok(task)])) as
FileScanTaskStream;
+ let batches: Vec<RecordBatch> = reader
+ .read(tasks)
+ .unwrap()
+ .stream()
+ .try_collect()
+ .await
+ .unwrap();
+
+ // The survivors are physical rows 0 and 2, so their _row_id is
first_row_id + the
+ // PHYSICAL position: [100, 102]. A dense output index would wrongly
give [100, 101].
+ assert_row_id_column(&batches, &[Some(100), Some(102)]);
+ }
+
+ #[tokio::test]
+ async fn test_row_id_coalesce_stable_under_row_selection() {
+ use crate::expr::Reference;
+ use crate::spec::Datum;
+
+ let tmp_dir = TempDir::new().unwrap();
+ let dir = tmp_dir.path().to_str().unwrap();
+ // Physical _row_id = [Some(5), None, Some(8)] over id = [1, 2, 3].
Dropping the
+ // middle row must keep the physical column and the RowNumber fallback
row-aligned.
+ let id_col = Arc::new(Int64Array::from(vec![Some(5), None, Some(8)]))
as ArrayRef;
+ let file_path = write_plain_parquet(
+ dir,
+ "row_id_coalesce_selection.parquet",
+ vec![physical_row_id_field()],
+ vec![id_col],
+ );
+
+ let task = row_id_task_with_predicate(
+ file_path,
+ Some(100),
+ vec![],
+ Reference::new("id").not_equal_to(Datum::int(2)),
+ );
+
+ let reader = ArrowReaderBuilder::new(FileIO::new_with_fs(),
Runtime::current())
+ .with_row_selection_enabled(true)
+ .build();
+ let tasks = Box::pin(futures::stream::iter(vec![Ok(task)])) as
FileScanTaskStream;
+ let batches: Vec<RecordBatch> = reader
+ .read(tasks)
+ .unwrap()
+ .stream()
+ .try_collect()
+ .await
+ .unwrap();
+
+ // Rows 0 and 2 survive: their stored values (5, 8) pass through. The
dropped
+ // row's null (which would have fallen back to 100 + 1) is gone --
proving the
+ // physical column and the positional fallback are filtered by the
same selection.
+ assert_row_id_column(&batches, &[Some(5), Some(8)]);
+ }
+
+ #[tokio::test]
+ async fn test_row_id_global_across_row_groups() {
Review Comment:
This proves `_pos` is global when all row groups are read in order. It
doesn't cover pruning — a byte-range split or a predicate eliminating row group
0 goes through `with_row_groups()`, not the `RowSelection` path — which is
where a per-group RowNumber restart would silently produce duplicate ids. Not a
blocker, but I'd add a sibling that prunes group 0 and asserts the survivors
start at `first_row_id + 2`.
##########
crates/iceberg/src/arrow/reader/row_lineage.rs:
##########
@@ -0,0 +1,286 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+//! Reader-level synthesis of the v3 `_row_id` metadata column.
+//!
+//! `_row_id` is `first_row_id + pos`, overridden by a physically-stored
`_row_id` where the
+//! file carries one. The position comes from the reader-produced `_pos`
(`RowNumber`)
+//! column, which is the true global file position under filter pushdown,
row-group pruning,
+//! and page-index pruning -- so synthesis is done here, over the record-batch
stream, using
+//! that position rather than recomputing it.
+
+use std::sync::Arc;
+
+use arrow_arith::boolean::is_not_null;
+use arrow_arith::numeric::add;
+use arrow_array::{Array, ArrayRef, Int64Array, RecordBatch};
+use arrow_schema::{DataType, Field, Schema};
+use arrow_select::zip::zip;
+use parquet::arrow::PARQUET_FIELD_ID_META_KEY;
+
+use crate::metadata_columns::{
+ RESERVED_COL_NAME_ROW_ID, RESERVED_FIELD_ID_POS, RESERVED_FIELD_ID_ROW_ID,
+};
+use crate::{Error, ErrorKind, Result};
+
+/// Appends the synthesized `_row_id` column to `batch`.
+///
+/// - `first_row_id == None`: the file carries no row lineage, so `_row_id` is
all-null
+/// (matching Java `ValueReaders.rowIds`).
+/// - `first_row_id == Some(base)`: `_row_id` is the physically-stored value
where the file
+/// carries one and it is non-null, else `base + pos` (from the
`_pos`/`RowNumber` column).
+///
+/// A physically-stored `_row_id` leaf already in `batch` is replaced by the
synthesized
+/// column (its values are folded in via the coalesce), so the result carries
exactly one
+/// column tagged with the reserved `_row_id` field id.
+pub(crate) fn synthesize_row_id_column(
+ batch: RecordBatch,
+ first_row_id: Option<i64>,
+) -> Result<RecordBatch> {
+ let row_id: ArrayRef = match first_row_id {
+ None => Arc::new(Int64Array::new_null(batch.num_rows())),
+ Some(base) => {
+ let pos = column_by_field_id(&batch,
RESERVED_FIELD_ID_POS).ok_or_else(|| {
+ Error::new(
+ ErrorKind::Unexpected,
+ "_row_id synthesis requires the _pos position column in
the record batch",
+ )
+ })?;
+ if pos.data_type() != &DataType::Int64 {
+ return Err(Error::new(
+ ErrorKind::Unexpected,
+ format!(
+ "_pos position column must be Int64, got {}",
+ pos.data_type()
+ ),
+ ));
+ }
+
+ // base + pos, the fallback for every row.
+ let fallback = add(pos, &Int64Array::new_scalar(base))?;
+ match column_by_field_id(&batch, RESERVED_FIELD_ID_ROW_ID) {
+ Some(id) => {
+ if id.data_type() != &DataType::Int64 {
+ return Err(Error::new(
+ ErrorKind::DataInvalid,
+ format!("_row_id source must be Int64, got {}",
id.data_type()),
+ ));
+ }
+
+ zip(&is_not_null(id)?, id, &fallback)?
+ }
+ None => fallback,
+ }
+ }
+ };
+
+ append_row_id(batch, row_id)
+}
+
+/// Returns the batch column tagged with `field_id` (via
`PARQUET_FIELD_ID_META_KEY`), if any.
+fn column_by_field_id(batch: &RecordBatch, field_id: i32) -> Option<&ArrayRef>
{
+ batch
+ .schema()
+ .fields()
+ .iter()
+ .position(|f| field_id_of(f) == Some(field_id))
+ .map(|idx| batch.column(idx))
+}
+
+fn field_id_of(field: &Field) -> Option<i32> {
+ field
+ .metadata()
+ .get(PARQUET_FIELD_ID_META_KEY)
+ .and_then(|id| id.parse::<i32>().ok())
+}
+
+/// Rebuilds `batch` with `row_id` as its `_row_id` column: any existing
`_row_id`-tagged
+/// column is dropped (already folded into `row_id`) and the synthesized
column is appended.
+fn append_row_id(batch: RecordBatch, row_id: ArrayRef) -> Result<RecordBatch> {
+ let schema = batch.schema();
+ let mut fields: Vec<Arc<Field>> = Vec::with_capacity(schema.fields().len()
+ 1);
+ let mut columns: Vec<ArrayRef> = Vec::with_capacity(schema.fields().len()
+ 1);
+
+ for (idx, field) in schema.fields().iter().enumerate() {
+ if field_id_of(field) != Some(RESERVED_FIELD_ID_ROW_ID) {
+ fields.push(field.clone());
+ columns.push(batch.column(idx).clone());
+ }
+ }
+
+ fields.push(Arc::new(
+ Field::new(RESERVED_COL_NAME_ROW_ID, DataType::Int64,
true).with_metadata(
+ [(
+ PARQUET_FIELD_ID_META_KEY.to_string(),
+ RESERVED_FIELD_ID_ROW_ID.to_string(),
+ )]
+ .into(),
+ ),
+ ));
+ columns.push(row_id);
+
+ Ok(RecordBatch::try_new(
+ Arc::new(Schema::new(fields)),
Review Comment:
`Schema::new(fields)` drops `batch.schema().metadata()` — the rest of the
projection module rebuilds with `new_with_metadata`. `schema` is already live
above, so: `Schema::new_with_metadata(fields, schema.metadata().clone())`.
##########
crates/iceberg/src/arrow/reader/row_lineage.rs:
##########
@@ -0,0 +1,286 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+//! Reader-level synthesis of the v3 `_row_id` metadata column.
+//!
+//! `_row_id` is `first_row_id + pos`, overridden by a physically-stored
`_row_id` where the
+//! file carries one. The position comes from the reader-produced `_pos`
(`RowNumber`)
+//! column, which is the true global file position under filter pushdown,
row-group pruning,
+//! and page-index pruning -- so synthesis is done here, over the record-batch
stream, using
+//! that position rather than recomputing it.
+
+use std::sync::Arc;
+
+use arrow_arith::boolean::is_not_null;
+use arrow_arith::numeric::add;
+use arrow_array::{Array, ArrayRef, Int64Array, RecordBatch};
+use arrow_schema::{DataType, Field, Schema};
+use arrow_select::zip::zip;
+use parquet::arrow::PARQUET_FIELD_ID_META_KEY;
+
+use crate::metadata_columns::{
+ RESERVED_COL_NAME_ROW_ID, RESERVED_FIELD_ID_POS, RESERVED_FIELD_ID_ROW_ID,
+};
+use crate::{Error, ErrorKind, Result};
+
+/// Appends the synthesized `_row_id` column to `batch`.
+///
+/// - `first_row_id == None`: the file carries no row lineage, so `_row_id` is
all-null
+/// (matching Java `ValueReaders.rowIds`).
+/// - `first_row_id == Some(base)`: `_row_id` is the physically-stored value
where the file
+/// carries one and it is non-null, else `base + pos` (from the
`_pos`/`RowNumber` column).
+///
+/// A physically-stored `_row_id` leaf already in `batch` is replaced by the
synthesized
+/// column (its values are folded in via the coalesce), so the result carries
exactly one
+/// column tagged with the reserved `_row_id` field id.
+pub(crate) fn synthesize_row_id_column(
+ batch: RecordBatch,
+ first_row_id: Option<i64>,
+) -> Result<RecordBatch> {
+ let row_id: ArrayRef = match first_row_id {
+ None => Arc::new(Int64Array::new_null(batch.num_rows())),
+ Some(base) => {
+ let pos = column_by_field_id(&batch,
RESERVED_FIELD_ID_POS).ok_or_else(|| {
+ Error::new(
+ ErrorKind::Unexpected,
+ "_row_id synthesis requires the _pos position column in
the record batch",
+ )
+ })?;
+ if pos.data_type() != &DataType::Int64 {
+ return Err(Error::new(
+ ErrorKind::Unexpected,
+ format!(
+ "_pos position column must be Int64, got {}",
+ pos.data_type()
+ ),
+ ));
+ }
+
+ // base + pos, the fallback for every row.
+ let fallback = add(pos, &Int64Array::new_scalar(base))?;
Review Comment:
Non-blocker: `add` wraps rather than checked-adds, so `first_row_id + pos`
would silently wrap to a negative id at the i64::MAX extreme. A checked add
that errors on overflow, or just a note that we're relying on the range never
being reached, would cover it.
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