laskoviymishka commented on code in PR #3058:
URL: https://github.com/apache/iceberg-rust/pull/3058#discussion_r3842877062
##########
crates/iceberg/src/arrow/reader/pipeline.rs:
##########
@@ -1453,6 +1510,523 @@ 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)]);
Review Comment:
Every `_row_id` test here writes a single row group, so nothing exercises
the case that actually makes `first_row_id + pos` correct: `_pos` has to be the
global file position, not a per-row-group offset. If parquet-rs's RowNumber
ever resets per row group (or does so under some row-selection config), a 2+
row-group file would hand group 1 the same ids as group 0 and we'd silently
emit duplicate row ids — the hardest guarantee `_row_id` has to make, and every
test here would still pass.
I'd add a test that writes with a small `max_row_group_size` (say 2) over 5
rows, `first_row_id = Some(0)`, and asserts `[0,1,2,3,4]` — specifically that
group 1 continues the count rather than restarting. wdyt?
##########
crates/iceberg/src/arrow/record_batch_transformer.rs:
##########
@@ -263,6 +276,11 @@ pub(crate) enum ColumnConstant {
/// per-row value is null (e.g. `_last_updated_sequence_number` on a file
that
/// carries the column, falling back to the data sequence number).
CoalesceLastUpdatedSeq(Datum),
+ /// The `_row_id` metadata column. `Some(first_row_id)` synthesizes it
(the per-row
+ /// value where the file physically carries `_row_id`, else `first_row_id`
plus the
+ /// row's position); `None` produces an all-null column (a file with a null
+ /// `first_row_id`).
+ RowId(Option<i64>),
Review Comment:
`RowId(Some(_))` isn't really a constant — every other `ColumnConstant`
variant is row-invariant, but this one triggers `RowIdSynthesis`, which reads
two other columns and produces a per-row result. Since `with_row_id_column`
stashes it in `constant_fields`, anyone auditing `constant_fields` or
pattern-matching on `ColumnConstant` later is going to be misled about what's
actually constant.
I'd pull the synthesis rules into their own map — something like
`synthesis_rules: HashMap<i32, SynthesisRule>` with `SynthesisRule::RowId {
first_row_id }` — or rename `ColumnConstant` to something like `ColumnBinding`
and document that it covers per-row computation. Not a correctness issue, but
it's the kind of abstraction leak that gets expensive later. wdyt?
##########
crates/iceberg/src/arrow/reader/pipeline.rs:
##########
@@ -289,6 +298,28 @@ impl FileScanTaskReader {
let coalesce_last_updated_seq_leaf = phys_last_updated_seq_leaf
.filter(|_| task.first_row_id.is_some() &&
task.data_sequence_number.is_some());
+ let phys_row_id_leaf = if project_row_id {
+ find_leaf_by_field_id(
+ record_batch_stream_builder.parquet_schema(),
+ RESERVED_FIELD_ID_ROW_ID,
+ )
+ } else {
+ None
+ };
+
+ // Present by name but without the embedded id: unthreadable, rejected
below.
+ let row_id_present_by_name_only = project_row_id
Review Comment:
This keys the name-only rejection purely on the column name. A file read
through positional fallback gets synthetic field ids from 1 upward that never
match the reserved `_row_id` id, so `phys_row_id_leaf` is `None` — but if that
file happens to have a legitimate user column named `_row_id`, this flags
`row_id_present_by_name_only` and we reject valid user data with
`FeatureUnsupported`. Java and PyIceberg don't hit this because they key on the
reserved field id, not the name.
Could we scope this so a name collision on a fallback file is treated as a
user column rather than a rejection? wdyt?
##########
crates/iceberg/src/arrow/reader/pipeline.rs:
##########
@@ -421,6 +456,27 @@ impl FileScanTaskReader {
};
}
+ if project_row_id {
+ // Synthesize the column, gated on `first_row_id`. Java gates it
the same way
+ // (`ValueReaders.rowIds` returns nulls when the base row id is
null); unlike
+ // `_last_updated_sequence_number` there is no
data-sequence-number dependency.
+ // Reject a name-only physical column, but only when we would read
it.
+ if task.first_row_id.is_some() && row_id_present_by_name_only {
Review Comment:
The `task.first_row_id.is_some() &&` here means a file with a
`_row_id`-named column that's missing the embedded field id gets silently
turned into an all-null column when `first_row_id` is absent, instead of the
error we raise when it's present. That name-only shape is evidence of a
write-side bug either way, and someone debugging it would see all-null and
conclude the feature just isn't supported.
I'd at least `tracing::warn!` on the name-only + null-`first_row_id` path so
it's not silent — or reject unconditionally, since a name-only `_row_id` never
threads regardless of `first_row_id`. wdyt?
##########
crates/iceberg/src/arrow/reader/pipeline.rs:
##########
@@ -1453,6 +1510,523 @@ 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() {
Review Comment:
Nice that this asserts physical positions `[100, 102]` rather than dense
`[100, 101]` — that's the right invariant. The one path it doesn't cover is
delete-file-based selection: predicate row selection
(`get_row_selection_for_filter_predicate`) and positional-delete selection
(`build_deletes_row_selection` + intersection) reach the reader through
different code, so a positional-delete case would close that explicitly.
I'd add a test with an actual positional delete file dropping the middle row
of 3 and assert `_row_id == [first_row_id, first_row_id + 2]`. wdyt?
##########
crates/iceberg/src/arrow/reader/pipeline.rs:
##########
@@ -314,25 +345,29 @@ impl FileScanTaskReader {
// which `get_arrow_projection_mask` maps to "read all columns" (so
`COUNT(*)` still
// gets a row count). Downgrade that to "read no data columns" when a
row-count
// source exists independently of the data columns: the RowNumber
virtual column
- // (installed above under `project_pos`) or a physical metadata leaf
unioned in
- // below. Pure-constant / `COUNT(*)` projections have neither and must
keep reading
- // all columns to preserve the row count. Any future physical metadata
leaf (e.g. a
- // `_row_id` read path) is likewise a row source.
+ // (installed above under `need_row_number`, which covers `_pos` and
`_row_id`
+ // synthesis) or a physical `_last_updated_sequence_number` leaf
unioned in below
+ // (that column does not install RowNumber, so it is a separate
source). Pure-constant
+ // / `COUNT(*)` projections have neither and must keep reading all
columns to preserve
+ // the row count.
//
- // This runs BEFORE the union so the physical leaf is added onto a
`none` base,
- // pruning the read to just that leaf (`union` with an `all` base
stays `all`).
+ // This runs BEFORE the union so the physical leaves are added onto a
`none` base,
+ // pruning the read to just those leaves (`union` with an `all` base
stays `all`).
if project_field_ids_without_metadata.is_empty()
- && (project_pos || coalesce_last_updated_seq_leaf.is_some())
+ && (need_row_number || coalesce_last_updated_seq_leaf.is_some())
Review Comment:
When only `_row_id` is projected and `first_row_id` is `None`,
`need_row_number` is false and there's no coalesce leaf, so this guard stays
false and the mask falls back to `all()` — we read every data column just to
emit an all-null `_row_id`. `SELECT _row_id ...` over any pre-V3 file pays full
column I/O for a null output.
Not a correctness bug, and the same gap already exists for
`_last_updated_sequence_number` with a null `first_row_id`, so I'm fine leaving
it — but I'd extend the guard with something like `|| (project_row_id &&
task.first_row_id.is_none())` to prune to a row-count source, or drop a comment
marking it as a known follow-up. wdyt?
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