[FEAT] [Scan Operator] Add ChunkSpec for specifying format-specific per-file row subset selection for ScanTasks.

daft/daft.pyi

@@ -178,7 +178,7 @@ class ParquetSourceConfig:
     Configuration of a Parquet data source.
     """
 
-    def __init__(self, coerce_int96_timestamp_unit: PyTimeUnit | None = None, row_groups: list[int] | None = None): ...
+    def __init__(self, coerce_int96_timestamp_unit: PyTimeUnit | None = None): ...
 
 class CsvSourceConfig:
     """
@@ -424,7 +424,7 @@ def read_parquet_bulk(
     columns: list[str] | None = None,
     start_offset: int | None = None,
     num_rows: int | None = None,
-    row_groups: list[list[int]] | None = None,
+    row_groups: list[list[int] | None] | None = None,
     io_config: IOConfig | None = None,
     num_parallel_tasks: int | None = 128,
     multithreaded_io: bool | None = None,
@@ -450,7 +450,7 @@ def read_parquet_into_pyarrow_bulk(
     columns: list[str] | None = None,
     start_offset: int | None = None,
     num_rows: int | None = None,
-    row_groups: list[list[int]] | None = None,
+    row_groups: list[list[int] | None] | None = None,
     io_config: IOConfig | None = None,
     num_parallel_tasks: int | None = 128,
     multithreaded_io: bool | None = None,
@@ -804,7 +804,7 @@ class PyMicroPartition:
         columns: list[str] | None = None,
         start_offset: int | None = None,
         num_rows: int | None = None,
-        row_groups: list[list[int]] | None = None,
+        row_groups: list[list[int] | None] | None = None,
         io_config: IOConfig | None = None,
         num_parallel_tasks: int | None = None,
         multithreaded_io: bool | None = None,

daft/table/micropartition.py

@@ -328,7 +328,7 @@ def read_parquet_bulk(
         columns: list[str] | None = None,
         start_offset: int | None = None,
         num_rows: int | None = None,
-        row_groups_per_path: list[list[int]] | None = None,
+        row_groups_per_path: list[list[int] | None] | None = None,
         io_config: IOConfig | None = None,
         num_parallel_tasks: int | None = 128,
         multithreaded_io: bool | None = None,

daft/table/table.py

@@ -407,7 +407,7 @@ def read_parquet_bulk(
         columns: list[str] | None = None,
         start_offset: int | None = None,
         num_rows: int | None = None,
-        row_groups_per_path: list[list[int]] | None = None,
+        row_groups_per_path: list[list[int] | None] | None = None,
         io_config: IOConfig | None = None,
         num_parallel_tasks: int | None = 128,
         multithreaded_io: bool | None = None,
@@ -532,7 +532,7 @@ def read_parquet_into_pyarrow_bulk(
     columns: list[str] | None = None,
     start_offset: int | None = None,
     num_rows: int | None = None,
-    row_groups_per_path: list[list[int]] | None = None,
+    row_groups_per_path: list[list[int] | None] | None = None,
     io_config: IOConfig | None = None,
     num_parallel_tasks: int | None = 128,
     multithreaded_io: bool | None = None,

src/daft-micropartition/src/micropartition.rs

@@ -13,7 +13,7 @@ use daft_parquet::read::{
 };
 use daft_scan::file_format::{CsvSourceConfig, FileFormatConfig, ParquetSourceConfig};
 use daft_scan::storage_config::{NativeStorageConfig, StorageConfig};
-use daft_scan::{DataFileSource, ScanTask};
+use daft_scan::{ChunkSpec, DataFileSource, ScanTask};
 use daft_table::Table;
 
 use snafu::ResultExt;
@@ -107,20 +107,17 @@ fn materialize_scan_task(
                 // ********************
                 FileFormatConfig::Parquet(ParquetSourceConfig {
                     coerce_int96_timestamp_unit,
-                    // TODO(Clark): Support different row group specification per file.
-                    row_groups,
                 }) => {
                     let inference_options =
                         ParquetSchemaInferenceOptions::new(Some(*coerce_int96_timestamp_unit));
                     let urls = urls.collect::<Vec<_>>();
+                    let row_groups = parquet_sources_to_row_groups(scan_task.sources.as_slice());
                     daft_parquet::read::read_parquet_bulk(
                         urls.as_slice(),
                         column_names.as_deref(),
                         None,
                         scan_task.limit,
-                        row_groups
-                            .as_ref()
-                            .map(|row_groups| vec![row_groups.clone(); urls.len()]),
+                        row_groups,
                         io_client.clone(),
                         io_stats,
                         8,
@@ -209,7 +206,7 @@ fn materialize_scan_task(
                             py,
                             url,
                             *has_headers,
-                            delimiter,
+                            delimiter.as_str(),
                             *double_quote,
                             cast_to_schema.clone().into(),
                             scan_task.storage_config.clone().into(),
@@ -320,30 +317,26 @@ impl MicroPartition {
                 _,
                 FileFormatConfig::Parquet(ParquetSourceConfig {
                     coerce_int96_timestamp_unit,
-                    row_groups,
                 }),
                 StorageConfig::Native(cfg),
             ) => {
+                let uris = scan_task
+                    .sources
+                    .iter()
+                    .map(|s| s.get_path())
+                    .collect::<Vec<_>>();
                 let columns = scan_task
                     .columns
                     .as_ref()
                     .map(|cols| cols.iter().map(|s| s.as_str()).collect::<Vec<&str>>());
 
+                let row_groups = parquet_sources_to_row_groups(scan_task.sources.as_slice());
                 read_parquet_into_micropartition(
-                    scan_task
-                        .sources
-                        .iter()
-                        .map(|s| s.get_path())
-                        .collect::<Vec<_>>()
-                        .as_slice(),
+                    uris.as_slice(),
                     columns.as_deref(),
                     None,
                     scan_task.limit,
-                    row_groups.clone().map(|rg| {
-                        std::iter::repeat(rg)
-                            .take(scan_task.sources.len())
-                            .collect::<Vec<_>>()
-                    }), // HACK: Properly propagate multi-file row_groups
+                    row_groups,
                     cfg.io_config
                         .clone()
                         .map(|c| Arc::new(c.clone()))
@@ -510,6 +503,24 @@ fn prune_fields_from_schema_ref(
     }
 }
 
+fn parquet_sources_to_row_groups(sources: &[DataFileSource]) -> Option<Vec<Option<Vec<i64>>>> {
+    let row_groups = sources
+        .iter()
+        .map(|s| {
+            if let Some(ChunkSpec::Parquet(row_group)) = s.get_chunk_spec() {
+                Some(row_group.clone())
+            } else {
+                None
+            }
+        })
+        .collect::<Vec<_>>();
+    if row_groups.iter().any(|rgs| rgs.is_some()) {
+        Some(row_groups)
+    } else {
+        None
+    }
+}
+
 #[allow(clippy::too_many_arguments)]
 pub(crate) fn read_csv_into_micropartition(
     uris: &[&str],
@@ -586,7 +597,7 @@ pub(crate) fn read_parquet_into_micropartition(
     columns: Option<&[&str]>,
     start_offset: Option<usize>,
     num_rows: Option<usize>,
-    row_groups: Option<Vec<Vec<i64>>>,
+    row_groups: Option<Vec<Option<Vec<i64>>>>,
     io_config: Arc<IOConfig>,
     io_stats: Option<IOStatsRef>,
     num_parallel_tasks: usize,
@@ -646,10 +657,12 @@ pub(crate) fn read_parquet_into_micropartition(
         Some(row_groups) => metadata
             .iter()
             .zip(row_groups.iter())
-            .map(|(fm, rg)| {
-                rg.iter()
+            .map(|(fm, rg)| match rg {
+                Some(rg) => rg
+                    .iter()
                     .map(|rg_idx| fm.row_groups.get(*rg_idx as usize).unwrap().num_rows())
-                    .sum::<usize>()
+                    .sum::<usize>(),
+                None => fm.num_rows,
             })
             .sum(),
     };
@@ -670,8 +683,13 @@ pub(crate) fn read_parquet_into_micropartition(
         let scan_task = ScanTask::new(
             owned_urls
                 .into_iter()
-                .map(|url| DataFileSource::AnonymousDataFile {
+                .zip(
+                    row_groups
+                        .unwrap_or_else(|| std::iter::repeat(None).take(uris.len()).collect()),
+                )
+                .map(|(url, rgs)| DataFileSource::AnonymousDataFile {
                     path: url,
+                    chunk_spec: rgs.map(ChunkSpec::Parquet),
                     size_bytes: Some(size_bytes),
                     metadata: None,
                     partition_spec: None,
@@ -680,7 +698,6 @@ pub(crate) fn read_parquet_into_micropartition(
                 .collect::<Vec<_>>(),
             FileFormatConfig::Parquet(ParquetSourceConfig {
                 coerce_int96_timestamp_unit: schema_infer_options.coerce_int96_timestamp_unit,
-                row_groups: None,
             })
             .into(),
             daft_schema.clone(),

src/daft-micropartition/src/python.rs

@@ -438,7 +438,7 @@ impl PyMicroPartition {
                 columns.as_deref(),
                 start_offset,
                 num_rows,
-                row_groups.map(|rg| vec![rg]),
+                row_groups.map(|rg| vec![Some(rg)]),
                 io_config,
                 Some(io_stats),
                 1,
@@ -457,7 +457,7 @@ impl PyMicroPartition {
         columns: Option<Vec<&str>>,
         start_offset: Option<usize>,
         num_rows: Option<usize>,
-        row_groups: Option<Vec<Vec<i64>>>,
+        row_groups: Option<Vec<Option<Vec<i64>>>>,
         io_config: Option<IOConfig>,
         num_parallel_tasks: Option<i64>,
         multithreaded_io: Option<bool>,

src/daft-parquet/src/python.rs

@@ -126,7 +126,7 @@ pub mod pylib {
         columns: Option<Vec<&str>>,
         start_offset: Option<usize>,
         num_rows: Option<usize>,
-        row_groups: Option<Vec<Vec<i64>>>,
+        row_groups: Option<Vec<Option<Vec<i64>>>>,
         io_config: Option<IOConfig>,
         num_parallel_tasks: Option<i64>,
         multithreaded_io: Option<bool>,
@@ -170,7 +170,7 @@ pub mod pylib {
         columns: Option<Vec<&str>>,
         start_offset: Option<usize>,
         num_rows: Option<usize>,
-        row_groups: Option<Vec<Vec<i64>>>,
+        row_groups: Option<Vec<Option<Vec<i64>>>>,
         io_config: Option<IOConfig>,
         num_parallel_tasks: Option<i64>,
         multithreaded_io: Option<bool>,

src/daft-parquet/src/read.rs

@@ -372,7 +372,7 @@ pub fn read_parquet_bulk(
     columns: Option<&[&str]>,
     start_offset: Option<usize>,
     num_rows: Option<usize>,
-    row_groups: Option<Vec<Vec<i64>>>,
+    row_groups: Option<Vec<Option<Vec<i64>>>>,
     io_client: Arc<IOClient>,
     io_stats: Option<IOStatsRef>,
     num_parallel_tasks: usize,
@@ -395,10 +395,7 @@ pub fn read_parquet_bulk(
             let task_stream = futures::stream::iter(uris.iter().enumerate().map(|(i, uri)| {
                 let uri = uri.to_string();
                 let owned_columns = owned_columns.clone();
-                let owned_row_group = match &row_groups {
-                    None => None,
-                    Some(v) => v.get(i).cloned(),
-                };
+                let owned_row_group = row_groups.as_ref().and_then(|rgs| rgs[i].clone());
 
                 let io_client = io_client.clone();
                 let io_stats = io_stats.clone();
@@ -441,7 +438,7 @@ pub fn read_parquet_into_pyarrow_bulk(
     columns: Option<&[&str]>,
     start_offset: Option<usize>,
     num_rows: Option<usize>,
-    row_groups: Option<Vec<Vec<i64>>>,
+    row_groups: Option<Vec<Option<Vec<i64>>>>,
     io_client: Arc<IOClient>,
     io_stats: Option<IOStatsRef>,
     num_parallel_tasks: usize,
@@ -466,10 +463,7 @@ pub fn read_parquet_into_pyarrow_bulk(
                 let uri = uri.to_string();
                 let owned_columns = owned_columns.clone();
                 let schema_infer_options = schema_infer_options;
-                let owned_row_group = match &row_groups {
-                    None => None,
-                    Some(v) => v.get(i).cloned(),
-                };
+                let owned_row_group = row_groups.as_ref().and_then(|rgs| rgs[i].clone());
 
                 let io_client = io_client.clone();
                 let io_stats = io_stats.clone();

src/daft-scan/src/anonymous.rs

@@ -70,6 +70,7 @@ impl ScanOperator for AnonymousScanOperator {
             Ok(ScanTask::new(
                 vec![DataFileSource::AnonymousDataFile {
                     path: f.to_string(),
+                    chunk_spec: None,
                     size_bytes: None,
                     metadata: None,
                     partition_spec: None,

src/daft-scan/src/file_format.rs

@@ -79,28 +79,21 @@ impl FileFormatConfig {
 #[cfg_attr(feature = "python", pyclass(module = "daft.daft"))]
 pub struct ParquetSourceConfig {
     pub coerce_int96_timestamp_unit: TimeUnit,
-    pub row_groups: Option<Vec<i64>>,
 }
 
 #[cfg(feature = "python")]
 #[pymethods]
 impl ParquetSourceConfig {
     /// Create a config for a Parquet data source.
     #[new]
-    fn new(coerce_int96_timestamp_unit: Option<PyTimeUnit>, row_groups: Option<Vec<i64>>) -> Self {
+    fn new(coerce_int96_timestamp_unit: Option<PyTimeUnit>) -> Self {
         Self {
             coerce_int96_timestamp_unit: coerce_int96_timestamp_unit
                 .unwrap_or(TimeUnit::Nanoseconds.into())
                 .into(),
-            row_groups,
         }
     }
 
-    #[getter]
-    fn row_groups(&self) -> PyResult<Option<Vec<i64>>> {
-        Ok(self.row_groups.clone())
-    }
-
     #[getter]
     fn coerce_int96_timestamp_unit(&self) -> PyResult<PyTimeUnit> {
         Ok(self.coerce_int96_timestamp_unit.into())

src/daft-scan/src/glob.rs

@@ -156,7 +156,6 @@ impl GlobScanOperator {
                 let inferred_schema = match file_format_config.as_ref() {
                     FileFormatConfig::Parquet(ParquetSourceConfig {
                         coerce_int96_timestamp_unit,
-                        ..
                     }) => {
                         let io_stats = IOStatsContext::new(format!(
                             "GlobScanOperator constructor read_parquet_schema: for uri {first_filepath}"
@@ -289,6 +288,7 @@ impl ScanOperator for GlobScanOperator {
             Ok(ScanTask::new(
                 vec![DataFileSource::AnonymousDataFile {
                     path: path.to_string(),
+                    chunk_spec: None,
                     size_bytes,
                     metadata: None,
                     partition_spec: None,

src/daft-scan/src/lib.rs

@@ -47,17 +47,26 @@ impl From<Error> for pyo3::PyErr {
     }
 }
 
+/// Specification of a subset of a file to be read.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub enum ChunkSpec {
+    /// Selection of Parquet row groups.
+    Parquet(Vec<i64>),
+}
+
 #[derive(Debug, Clone, Serialize, Deserialize)]
 pub enum DataFileSource {
     AnonymousDataFile {
         path: String,
+        chunk_spec: Option<ChunkSpec>,
         size_bytes: Option<u64>,
         metadata: Option<TableMetadata>,
         partition_spec: Option<PartitionSpec>,
         statistics: Option<TableStatistics>,
     },
     CatalogDataFile {
         path: String,
+        chunk_spec: Option<ChunkSpec>,
         size_bytes: Option<u64>,
         metadata: TableMetadata,
         partition_spec: PartitionSpec,
@@ -71,12 +80,21 @@ impl DataFileSource {
             Self::AnonymousDataFile { path, .. } | Self::CatalogDataFile { path, .. } => path,
         }
     }
+
+    pub fn get_chunk_spec(&self) -> Option<&ChunkSpec> {
+        match self {
+            Self::AnonymousDataFile { chunk_spec, .. }
+            | Self::CatalogDataFile { chunk_spec, .. } => chunk_spec.as_ref(),
+        }
+    }
+
     pub fn get_size_bytes(&self) -> Option<u64> {
         match self {
             Self::AnonymousDataFile { size_bytes, .. }
             | Self::CatalogDataFile { size_bytes, .. } => *size_bytes,
         }
     }
+
     pub fn get_metadata(&self) -> Option<&TableMetadata> {
         match self {
             Self::AnonymousDataFile { metadata, .. } => metadata.as_ref(),