crates/clawhdf5-format/src/chunk_grid.rs

@@ -147,7 +147,6 @@ impl ChunkGrid {
 
     /// Linear index of the chunk with scaled coordinates `scaled`
     /// (`offset / chunk_dim` per dimension, in dataset order).
-    #[allow(dead_code)] // used by the writer
     pub(crate) fn linear_index(&self, scaled: &[u64]) -> u64 {
         self.order
             .iter()

crates/clawhdf5-format/src/chunked_write.rs

@@ -8,6 +8,7 @@ use alloc::{vec, vec::Vec};
 
 use crate::checksum::jenkins_lookup3;
 use crate::chunk_cache::{CACHE_LINE_SIZE, align_to_cache_line};
+use crate::chunk_grid::ChunkGrid;
 use crate::ea_writer;
 use crate::error::FormatError;
 use crate::filter_pipeline::{
@@ -699,7 +700,8 @@ pub fn build_chunked_data_from_precompressed(
     pre: &PrecompressedChunks,
     base_address: u64,
     maxshape: Option<&[u64]>,
-) -> ChunkedDataResult {
+) -> Result<ChunkedDataResult, FormatError> {
+    let index = ChunkIndexPlan::new(&pre.shape, maxshape, &pre.chunk_dims)?;
     let offset_size: u8 = 8;
     let length_size: u8 = 8;
     let num_chunks = pre.chunks.len();
@@ -725,16 +727,15 @@ pub fn build_chunked_data_from_precompressed(
     }
 
     let chunk_dims_u32: Vec<u32> = pre.chunk_dims.iter().map(|&d| d as u32).collect();
-    let use_extensible = maxshape.is_some_and(|ms| ms.contains(&u64::MAX));
 
     let aligned_idx = align_to_cache_line(data_buf.len());
     if aligned_idx > data_buf.len() {
         data_buf.resize(aligned_idx, 0u8);
     }
 
-    let layout_message = if use_extensible {
+    let layout_message = if let ChunkIndexPlan::ExtensibleArray(grid) = &index {
         let ea_address = base_address + data_buf.len() as u64;
-        let slots: Vec<Option<WrittenChunk>> = written_chunks.iter().cloned().map(Some).collect();
+        let slots = index_slots(grid, &pre.shape, &pre.chunk_dims, &written_chunks, None)?;
         let ea_bytes = ea_writer::build_extensible_array_at(
             &slots,
             offset_size,
@@ -749,7 +750,7 @@ pub fn build_chunked_data_from_precompressed(
             offset_size,
             element_size as u32,
         )
-    } else if num_chunks == 1 {
+    } else if matches!(index, ChunkIndexPlan::SingleChunk) {
         let chunk_addr = written_chunks[0].address;
         let filtered_size = if pre.has_filters {
             Some(written_chunks[0].compressed_size)
@@ -765,9 +766,15 @@ pub fn build_chunked_data_from_precompressed(
             offset_size,
             element_size as u32,
         )
-    } else {
+    } else if let ChunkIndexPlan::FixedArray(grid, nslots) = &index {
         let fa_address = base_address + data_buf.len() as u64;
-        let slots: Vec<Option<WrittenChunk>> = written_chunks.iter().cloned().map(Some).collect();
+        let slots = index_slots(
+            grid,
+            &pre.shape,
+            &pre.chunk_dims,
+            &written_chunks,
+            Some(*nslots),
+        )?;
         let fa_bytes = build_fixed_array_at(
             &slots,
             offset_size,
@@ -783,15 +790,123 @@ pub fn build_chunked_data_from_precompressed(
             element_size as u32,
             FA_PAGE_BITS,
         )
+    } else {
+        unreachable!("every chunk index plan is handled above")
     };
 
-    ChunkedDataResult {
+    Ok(ChunkedDataResult {
         data_bytes: data_buf,
         layout_message,
         pipeline_message: pre.pipeline_message.clone(),
+    })
+}
+
+/// Most slots a Fixed Array index may have before we refuse to build it: its
+/// data block holds one element per chunk of the *maximum* extent, so a huge
+/// finite maxshape with small chunks would otherwise exhaust memory.
+const MAX_FIXED_ARRAY_SLOTS: u64 = 1 << 26;
+
+/// Which chunk index a dataset gets, following the library's choice in
+/// `H5D__layout_set_latest_indexing`: Extensible Array for exactly one
+/// unlimited dimension, Fixed Array for a finite maxshape, Single Chunk when
+/// the whole maximum extent is one chunk.
+enum ChunkIndexPlan {
+    SingleChunk,
+    /// The grid and the number of array elements (chunks of the max extent).
+    FixedArray(ChunkGrid, usize),
+    ExtensibleArray(ChunkGrid),
+}
+
+impl ChunkIndexPlan {
+    fn new(
+        shape: &[u64],
+        maxshape: Option<&[u64]>,
+        chunk_dims: &[u64],
+    ) -> Result<Self, FormatError> {
+        let bad = |what: &str| FormatError::ChunkedReadError(format!("maxshape: {what}"));
+        if let Some(ms) = maxshape {
+            if ms.len() != shape.len() {
+                return Err(bad("rank differs from the shape"));
+            }
+            if ms.iter().zip(shape).any(|(&m, &s)| m < s) {
+                return Err(bad("smaller than the shape"));
+            }
+        }
+        let max = maxshape.unwrap_or(shape);
+        let nunlim = max.iter().filter(|&&d| d == u64::MAX).count();
+        match nunlim {
+            0 => {
+                let nslots = max
+                    .iter()
+                    .zip(chunk_dims)
+                    .try_fold(1u64, |acc, (&m, &c)| acc.checked_mul(m.div_ceil(c.max(1))))
+                    .filter(|&n| n <= MAX_FIXED_ARRAY_SLOTS)
+                    .ok_or_else(|| {
+                        bad("too many chunks for a Fixed Array index; \
+                             use larger chunks or an unlimited dimension")
+                    })?;
+                // A Single Chunk index needs that one chunk to exist; an
+                // empty dataset gets an all-unallocated Fixed Array instead.
+                let empty = shape.contains(&0);
+                if nslots == 1 && !empty {
+                    Ok(Self::SingleChunk)
+                } else {
+                    let grid = ChunkGrid::fixed_array(shape, Some(max), chunk_dims)?;
+                    Ok(Self::FixedArray(grid, nslots as usize))
+                }
+            }
+            1 => Ok(Self::ExtensibleArray(ChunkGrid::extensible_array(
+                shape,
+                Some(max),
+                chunk_dims,
+            )?)),
+            _ => Err(bad(
+                "more than one unlimited dimension needs a B-tree v2 chunk index, \
+                 which the writer does not support",
+            )),
+        }
     }
 }
 
+/// Place each written chunk at its linear index in `grid`. `chunks` are in
+/// row-major order over the chunks of the current extent (`split_into_chunks`).
+/// `len` fixes the slot count (Fixed Array); otherwise it is one past the
+/// highest index used.
+fn index_slots(
+    grid: &ChunkGrid,
+    shape: &[u64],
+    chunk_dims: &[u64],
+    chunks: &[WrittenChunk],
+    len: Option<usize>,
+) -> Result<Vec<Option<WrittenChunk>>, FormatError> {
+    let rank = shape.len();
+    let cur: Vec<u64> = shape
+        .iter()
+        .zip(chunk_dims)
+        .map(|(&s, &c)| s.div_ceil(c))
+        .collect();
+    let mut placed: Vec<(usize, &WrittenChunk)> = Vec::with_capacity(chunks.len());
+    let mut scaled = vec![0u64; rank];
+    for (i, chunk) in chunks.iter().enumerate() {
+        let mut rem = i as u64;
+        for d in (0..rank).rev() {
+            scaled[d] = rem % cur[d];
+            rem /= cur[d];
+        }
+        let idx = usize::try_from(grid.linear_index(&scaled))
+            .map_err(|_| FormatError::Overflow("chunk index slot".into()))?;
+        placed.push((idx, chunk));
+    }
+    let n = len.unwrap_or_else(|| placed.iter().map(|&(i, _)| i + 1).max().unwrap_or(0));
+    let mut slots = vec![None; n];
+    for (idx, chunk) in placed {
+        *slots
+            .get_mut(idx)
+            .ok_or_else(|| FormatError::Overflow("chunk index slot".into()))? = Some(chunk.clone());
+    }
+    Ok(slots)
+}
+
 /// Build chunked data with absolute addresses.
 /// If `maxshape` has unlimited dims, uses Extensible Array index.
 pub fn build_chunked_data_at(
@@ -824,11 +939,7 @@ pub fn build_chunked_data_at_ext(
     maxshape: Option<&[u64]>,
 ) -> Result<ChunkedDataResult, FormatError> {
     let pre = precompress_chunks(raw_data, shape, chunk_dims, element_size, options)?;
-    Ok(build_chunked_data_from_precompressed(
-        &pre,
-        base_address,
-        maxshape,
-    ))
+    build_chunked_data_from_precompressed(&pre, base_address, maxshape)
 }
 
 /// Write selected elements into an existing in-memory dataset buffer.

crates/clawhdf5-format/src/file_writer.rs

@@ -1244,7 +1244,7 @@ impl FileWriter {
                     &pre,
                     dummy_cursor,
                     d.maxshape.as_deref(),
-                );
+                )?;
                 dummy_cursor += result.data_bytes.len() as u64;
                 let dense_blob = if ds_dense[i] {
                     Some(build_dense_attrs(&d.attrs, 0))
@@ -1424,7 +1424,7 @@ impl FileWriter {
                         .expect("chunked dataset missing precompressed cache"),
                     base_address,
                     d.maxshape.as_deref(),
-                );
+                )?;
                 cursor2 += result.data_bytes.len();
                 let oh = build_chunked_dataset_oh(
                     &d.dt,

crates/clawhdf5/tests/chunk_index_interop.rs

@@ -373,6 +373,73 @@ fn check_we_write(cases: &[WriteCase]) {
             "h5dump failed: {stderr}"
         );
     }
+
+    // Let libhdf5 grow every resizable dataset by two chunks per dimension
+    // (capped at the maxshape) and rewrite it, which updates our index in
+    // place and inserts new chunks into it. Then both readers must agree.
+    let script = format!(
+        r#"
+import h5py, numpy as np
+grown = {{}}
+with h5py.File(r'{path_str}', 'r+') as f:
+    for name in f:
+        d = f[name]
+        if d.chunks is None:
+            continue
+        new = tuple(s + 2 * c if m is None else min(m, s + 2 * c)
+                    for s, m, c in zip(d.shape, d.maxshape, d.chunks))
+        if new == d.shape:
+            continue
+        old = d[()]
+        full = np.full(new, -7, 'i4')
+        full[tuple(slice(0, s) for s in old.shape)] = old
+        d.resize(new)
+        d[...] = full
+        grown[name] = (list(old.shape), list(new))
+with h5py.File(r'{path_str}', 'r') as f:
+    for name, (old, new) in grown.items():
+        want = np.full(new, -7, 'i4')
+        want[tuple(slice(0, s) for s in old)] = np.arange(int(np.prod(old)), dtype='i4').reshape(old)
+        assert np.array_equal(f[name][()], want), name
+for name, (old, new) in grown.items():
+    print(name, ','.join(map(str, old)), ','.join(map(str, new)))
+"#
+    );
+    let out = run_python(&script);
+    let growable = cases
+        .iter()
+        .filter(|c| c.maxshape.as_ref().is_some_and(|m| *m != c.shape))
+        .count();
+    assert_eq!(out.lines().count(), growable, "libhdf5 grew: {out}");
+    let dims = |s: &str| -> Vec<usize> { s.split(',').map(|x| x.parse().unwrap()).collect() };
+    let file = File::open(&path).unwrap();
+    for line in out.lines() {
+        let mut parts = line.split(' ');
+        let (name, old, new) = (
+            parts.next().unwrap(),
+            dims(parts.next().unwrap()),
+            dims(parts.next().unwrap()),
+        );
+        let got = file.dataset(name).unwrap().read_i32().unwrap();
+        let n: usize = new.iter().product();
+        let mut want = vec![-7i32; n];
+        for (flat, w) in want.iter_mut().enumerate() {
+            let mut rem = flat;
+            let mut coords = vec![0usize; new.len()];
+            for d in (0..new.len()).rev() {
+                coords[d] = rem % new[d];
+                rem /= new[d];
+            }
+            if coords.iter().zip(&old).all(|(c, o)| c < o) {
+                *w = coords.iter().zip(&old).fold(0, |acc, (c, o)| acc * o + c) as i32;
+            }
+        }
+        let bad = got.iter().zip(&want).filter(|(a, b)| a != b).count();
+        assert!(
+            got.len() == n && bad == 0,
+            "{name}: after libhdf5 grew it, our reader got {bad} of {n} values wrong"
+        );
+    }
 }
 
 /// A Fixed Array with more than 1024 elements must be paged, or libhdf5
@@ -411,3 +478,53 @@ fn we_write_extensible_array_past_index_block() {
     cases.push(wcase("ea_140000", &[140_000], &[1], Some(unl)));
     check_we_write(&cases);
 }
+
+/// A maxshape larger than the shape: the index must be laid out over the
+/// chunks of the maximum extent (libhdf5 read our Fixed Array past its end:
+/// "addr overflow"), and an Extensible Array whose unlimited dimension is not
+/// the first must swizzle it to the slowest position (libhdf5 read our
+/// `(20, None)` dataset scrambled).
+#[test]
+fn we_write_maxshape_larger_than_shape() {
+    const U: u64 = u64::MAX;
+    let mut cases = vec![
+        // Fixed Array over the maximum extent.
+        wcase("fa2d_finite_max", &[20, 30], &[5, 5], Some(&[40, 60])),
+        wcase("fa1d_finite_max", &[40], &[4], Some(&[100])),
+        wcase("fa3d_edges", &[6, 7, 8], &[4, 3, 5], Some(&[10, 9, 20])),
+        wcase("fa_paged_max", &[30, 50], &[1, 1], Some(&[40, 60])),
+        wcase("fa_one_chunk_now", &[5], &[5], Some(&[50])),
+        // Extensible Array, unlimited dimension first (no swizzle) ...
+        wcase("ea2d_unl_fin", &[20, 30], &[5, 5], Some(&[U, 30])),
+        wcase("ea2d_unl_fin_max", &[20, 30], &[5, 5], Some(&[U, 60])),
+        // ... and not first (swizzled).
+        wcase("ea2d_fin_unl", &[20, 30], &[5, 5], Some(&[20, U])),
+        wcase("ea2d_fin_max_unl", &[20, 30], &[5, 5], Some(&[40, U])),
+        wcase("ea3d_mid", &[6, 7, 8], &[4, 3, 5], Some(&[10, U, 20])),
+        // Past the index block and into super blocks, swizzled.
+        wcase("ea2d_many", &[3, 2000], &[1, 1], Some(&[4, U])),
+    ];
+    let mut filtered = wcase(
+        "ea3d_last_deflate",
+        &[6, 7, 8],
+        &[4, 3, 5],
+        Some(&[6, 8, U]),
+    );
+    filtered.deflate = true;
+    cases.push(filtered);
+    check_we_write(&cases);
+}
+
+/// More than one unlimited dimension needs a B-tree v2 chunk index; the
+/// writer must not produce a file libhdf5 cannot open.
+#[test]
+fn two_unlimited_dims_are_refused() {
+    let mut b = FileBuilder::new();
+    b.create_dataset("d")
+        .with_i32_data(&(0..600).collect::<Vec<i32>>())
+        .with_shape(&[20, 30])
+        .with_chunks(&[5, 5])
+        .with_maxshape(&[u64::MAX, u64::MAX]);
+    let dir = tempfile::tempdir().unwrap();
+    assert!(b.write(dir.path().join("unl_unl.h5")).is_err());
+}