introduce optional rle reads from parquet

datafusion/common/src/config.rs

@@ -1381,6 +1381,17 @@ config_namespace! {
         /// Defaults to 20.
         pub max_in_list_size: usize, default = 20
 
+        /// (reading) If true, top-level string and binary Parquet columns with
+        /// dictionary pages are inferred and scanned as
+        /// `Dictionary<Int32, Utf8>` / `Dictionary<Int32, Binary>` instead of
+        /// their plain value type.
+        ///
+        /// This applies only when DataFusion infers the table schema. Tables with
+        /// a user-supplied schema are not promoted because the Parquet footer is
+        /// not read at DDL time, so dictionary pages cannot be detected per column.
+        /// See <https://github.com/apache/datafusion/issues/24112>
+        pub enable_rle_to_dictionary: bool, default = false
+
         // The following options affect writing to parquet files
         // and map to parquet::file::properties::WriterProperties
 

datafusion/common/src/file_options/parquet_writer.rs

@@ -249,6 +249,7 @@ impl ParquetOptions {
             skip_arrow_metadata: _,
             max_predicate_cache_size: _,
             max_in_list_size: _,
+            enable_rle_to_dictionary: _,
         } = self;
 
         let mut builder = WriterProperties::builder()
@@ -509,6 +510,7 @@ mod tests {
             coerce_int96_tz: None,
             max_predicate_cache_size: defaults.max_predicate_cache_size,
             content_defined_chunking: defaults.content_defined_chunking.clone(),
+            enable_rle_to_dictionary: defaults.enable_rle_to_dictionary,
         }
     }
 
@@ -631,6 +633,8 @@ mod tests {
                 coerce_int96: None,
                 coerce_int96_tz: None,
                 content_defined_chunking: props.content_defined_chunking().into(),
+                enable_rle_to_dictionary: global_options_defaults
+                    .enable_rle_to_dictionary,
             },
             column_specific_options,
             key_value_metadata,

datafusion/datasource-parquet/src/file_format.rs

@@ -360,14 +360,16 @@ impl FileFormat for ParquetFormat {
                     &object.location,
                 )
                 .await?;
-                let result = DFParquetMetadata::new(store.as_ref(), object)
+                let meta = DFParquetMetadata::new(store.as_ref(), object)
                     .with_metadata_size_hint(self.metadata_size_hint())
                     .with_decryption_properties(file_decryption_properties)
                     .with_file_metadata_cache(Some(Arc::clone(&file_metadata_cache)))
                     .with_coerce_int96(coerce_int96)
                     .with_coerce_int96_tz(coerce_int96_tz.clone())
-                    .fetch_schema_with_location()
-                    .await?;
+                    .with_enable_rle_to_dictionary(
+                        self.options.global.enable_rle_to_dictionary,
+                    );
+                let result = meta.fetch_schema_with_location().await?;
                 Ok::<_, DataFusionError>(result)
             })
             .boxed() // Workaround https://github.com/rust-lang/rust/issues/64552
@@ -402,7 +404,12 @@ impl FileFormat for ParquetFormat {
         }
         drop(seen);
 
-        let schemas = schemas.into_iter().map(|(_, schema)| schema);
+        // Normalize dict-promoted schemas before merging so mixed dict/plain files merge cleanly.
+        let mut schemas: Vec<Schema> =
+            schemas.into_iter().map(|(_, schema)| schema).collect();
+        if self.options.global.enable_rle_to_dictionary {
+            schemas = crate::schema_coercion::uniform_dict_schemas(schemas);
+        }
 
         let schema = if self.skip_metadata() {
             Schema::try_merge(clear_metadata(schemas))
@@ -524,7 +531,7 @@ impl FileFormat for ParquetFormat {
         source = source.with_parquet_file_reader_factory(cached_parquet_read_factory);
 
         if let Some(metadata_size_hint) = metadata_size_hint {
-            source = source.with_metadata_size_hint(metadata_size_hint)
+            source = source.with_metadata_size_hint(metadata_size_hint);
         }
 
         source = self.set_source_encryption_factory(source, state)?;
@@ -738,6 +745,7 @@ impl From<&ParquetFormatFactory> for protobuf::TableParquetOptions {
             compression_opt: global_options.global.compression.map(|compression| {
                 parquet_options::CompressionOpt::Compression(compression)
             }),
+            enable_rle_to_dictionary: global_options.global.enable_rle_to_dictionary,
             dictionary_enabled_opt: global_options.global.dictionary_enabled.map(|enabled| {
                 parquet_options::DictionaryEnabledOpt::DictionaryEnabled(enabled)
             }),

datafusion/datasource-parquet/src/metadata.rs

@@ -23,11 +23,11 @@ use crate::{Int96Coercer, apply_file_schema_type_coercions};
 use arrow::array::{Array, ArrayRef, BooleanArray};
 use arrow::compute::kernels::cmp::eq;
 use arrow::compute::{and, sum};
-use arrow::datatypes::{DataType, Schema, SchemaRef, TimeUnit};
+use arrow::datatypes::{DataType, Field, Schema, SchemaRef, TimeUnit};
 use datafusion_common::encryption::FileDecryptionProperties;
 use datafusion_common::stats::Precision;
 use datafusion_common::{
-    ColumnStatistics, DataFusionError, HashMap, Result, ScalarValue, Statistics,
+    ColumnStatistics, DataFusionError, HashMap, HashSet, Result, ScalarValue, Statistics,
     internal_datafusion_err,
 };
 use datafusion_execution::cache::cache_manager::{
@@ -146,6 +146,8 @@ pub struct DFParquetMetadata<'a> {
     pub coerce_int96: Option<TimeUnit>,
     /// Optional timezone applied to INT96-coerced timestamps.
     pub coerce_int96_tz: Option<Arc<str>>,
+    /// If true, promote string/binary columns with dictionary pages to `Dictionary(Int32, ...)`.
+    enable_rle_to_dictionary: bool,
 }
 
 impl<'a> DFParquetMetadata<'a> {
@@ -163,9 +165,16 @@ impl<'a> DFParquetMetadata<'a> {
             page_index_policy: None,
             coerce_int96: None,
             coerce_int96_tz: None,
+            enable_rle_to_dictionary: false,
         }
     }
 
+    /// Promote string/binary columns with dictionary pages to `Dictionary(Int32, ...)`.
+    pub fn with_enable_rle_to_dictionary(mut self, enable: bool) -> Self {
+        self.enable_rle_to_dictionary = enable;
+        self
+    }
+
     /// Set a hint for the number of trailing bytes to prefetch from the end
     /// of the file, equivalent to
     /// [`ParquetMetaDataReader::with_prefetch_hint`].
@@ -439,6 +448,68 @@ impl<'a> DFParquetMetadata<'a> {
                     .coerce()
             })
             .unwrap_or(schema);
+
+        let schema = if self.enable_rle_to_dictionary {
+            let schema_descr = file_metadata.schema_descr();
+            // Top-level columns that have a dictionary page in at least one row group.
+            let dict_cols: HashSet<String> = metadata
+                .row_groups()
+                .iter()
+                .flat_map(|rg| {
+                    rg.columns()
+                        .iter()
+                        .enumerate()
+                        .filter_map(|(col_idx, col)| {
+                            col.dictionary_page_offset()?;
+                            let col_desc = schema_descr.column(col_idx);
+                            let parts = col_desc.path().parts();
+                            // Skip nested columns: their leaf name doesn't match the
+                            // Arrow top-level field name.
+                            (parts.len() == 1).then(|| parts[0].clone())
+                        })
+                })
+                .collect();
+            if dict_cols.is_empty() {
+                schema
+            } else {
+                let promoted: Vec<_> = schema
+                    .fields()
+                    .iter()
+                    .map(|field| {
+                        if !dict_cols.contains(field.name()) {
+                            return Arc::clone(field);
+                        }
+                        let dict_value_type = match field.data_type() {
+                            DataType::Utf8 => Some(DataType::Utf8),
+                            DataType::LargeUtf8 => Some(DataType::LargeUtf8),
+                            DataType::Binary => Some(DataType::Binary),
+                            DataType::LargeBinary => Some(DataType::LargeBinary),
+                            _ => None,
+                        };
+                        dict_value_type.map_or_else(
+                            || Arc::clone(field),
+                            |value_type| {
+                                Arc::new(
+                                    Field::new(
+                                        field.name(),
+                                        DataType::Dictionary(
+                                            Box::new(DataType::Int32),
+                                            Box::new(value_type),
+                                        ),
+                                        field.is_nullable(),
+                                    )
+                                    .with_metadata(field.metadata().clone()),
+                                )
+                            },
+                        )
+                    })
+                    .collect();
+                Schema::new_with_metadata(promoted, schema.metadata().clone())
+            }
+        } else {
+            schema
+        };
+
         Ok(schema)
     }
 

datafusion/datasource-parquet/src/opener/mod.rs

@@ -35,7 +35,7 @@ use crate::row_group_filter::{RowGroupAccessPlanFilter, row_group_in_range};
 use crate::{
     BloomFilterStatistics, Int96Coercer, ParquetAccessPlan, ParquetFileMetrics,
     ParquetFileReaderFactory, ParquetRowSelection, ParquetVirtualColumn,
-    apply_file_schema_type_coercions,
+    schema_coercion::apply_file_schema_type_coercions_with_rle,
 };
 use arrow::array::RecordBatch;
 use arrow::datatypes::DataType;
@@ -294,6 +294,8 @@ pub(super) struct ParquetMorselizer {
     /// lists skip container-level pruning. Sourced from
     /// `datafusion.execution.parquet.max_in_list_size`.
     pub max_in_list_size: usize,
+    /// Whether to ask arrow-rs to read promoted dictionary columns directly.
+    pub enable_rle_to_dictionary: bool,
     /// Whether to read row groups in reverse order
     pub reverse_row_groups: bool,
     /// Optional sort order used to reorder row groups by their min/max statistics.
@@ -467,6 +469,7 @@ struct PreparedParquetOpen {
     predicate_creation_errors: Count,
     max_predicate_cache_size: Option<usize>,
     max_in_list_size: usize,
+    enable_rle_to_dictionary: bool,
     reverse_row_groups: bool,
     sort_order_for_reorder: Option<LexOrdering>,
     preserve_order: bool,
@@ -874,6 +877,7 @@ impl ParquetMorselizer {
             predicate_creation_errors,
             max_predicate_cache_size: self.max_predicate_cache_size,
             max_in_list_size: self.max_in_list_size,
+            enable_rle_to_dictionary: self.enable_rle_to_dictionary,
             reverse_row_groups: self.reverse_row_groups,
             sort_order_for_reorder: self.sort_order_for_reorder.clone(),
             preserve_order: self.preserve_order,
@@ -984,9 +988,10 @@ impl MetadataLoadedParquetOpen {
         // desired schema (for example if we want to instruct the parquet
         // reader to read strings using Utf8View instead). Update if necessary
         let mut metadata_dirty = false;
-        if let Some(merged) = apply_file_schema_type_coercions(
+        if let Some(merged) = apply_file_schema_type_coercions_with_rle(
             &prepared.logical_file_schema,
             &physical_file_schema,
+            prepared.enable_rle_to_dictionary,
         ) {
             physical_file_schema = Arc::new(merged);
             options = options.with_schema(Arc::clone(&physical_file_schema));
@@ -1937,6 +1942,7 @@ mod test {
         coerce_int96: Option<TimeUnit>,
         max_predicate_cache_size: Option<usize>,
         max_in_list_size: usize,
+        enable_rle_to_dictionary: bool,
         reverse_row_groups: bool,
         preserve_order: bool,
     }
@@ -2148,6 +2154,7 @@ mod test {
                 coerce_int96: None,
                 max_predicate_cache_size: None,
                 max_in_list_size: MAX_IN_LIST_SIZE,
+                enable_rle_to_dictionary: false,
                 reverse_row_groups: false,
                 preserve_order: false,
             }
@@ -2223,6 +2230,11 @@ mod test {
             self
         }
 
+        fn with_enable_rle_to_dictionary(mut self, enable: bool) -> Self {
+            self.enable_rle_to_dictionary = enable;
+            self
+        }
+
         fn with_metrics(mut self, metrics: ExecutionPlanMetricsSet) -> Self {
             self.metrics = metrics;
             self
@@ -2326,6 +2338,7 @@ mod test {
                 encryption_factory: None,
                 max_predicate_cache_size: self.max_predicate_cache_size,
                 max_in_list_size: self.max_in_list_size,
+                enable_rle_to_dictionary: self.enable_rle_to_dictionary,
                 reverse_row_groups: self.reverse_row_groups,
                 sort_order_for_reorder: None,
                 virtual_state,
@@ -4333,4 +4346,59 @@ mod test {
             assert_eq!(rows, 5);
         }
     }
+
+    async fn collect_batches(
+        morselizer: &ParquetMorselizer,
+        file: PartitionedFile,
+    ) -> Vec<RecordBatch> {
+        let mut stream = open_file(morselizer, file).await.unwrap();
+        let mut batches = Vec::new();
+        while let Some(batch) = stream.next().await {
+            batches.push(batch.unwrap());
+        }
+        batches
+    }
+
+    // Proves the opener passes a promoted binary Dictionary schema to arrow-rs.
+    #[tokio::test]
+    async fn test_rle_binary_column_promotion() {
+        let store = Arc::new(InMemory::new()) as Arc<dyn ObjectStore>;
+        let bin_schema = Arc::new(Schema::new(vec![Field::new(
+            "payload",
+            DataType::Binary,
+            true,
+        )]));
+        let values =
+            Arc::new(arrow::array::BinaryArray::from_vec(vec![b"a", b"b", b"a"]));
+        let batch = RecordBatch::try_new(Arc::clone(&bin_schema), vec![values]).unwrap();
+        let props = WriterProperties::builder()
+            .set_dictionary_enabled(true)
+            .build();
+        let bin_size = write_parquet_batches(
+            Arc::clone(&store),
+            "binary.parquet",
+            vec![batch],
+            Some(props),
+        )
+        .await;
+        let dict_bin_schema = Arc::new(Schema::new(vec![Field::new(
+            "payload",
+            DataType::Dictionary(Box::new(DataType::Int32), Box::new(DataType::Binary)),
+            true,
+        )]));
+        let morselizer = ParquetMorselizerBuilder::new()
+            .with_store(Arc::clone(&store))
+            .with_schema(Arc::clone(&dict_bin_schema))
+            .with_enable_rle_to_dictionary(true)
+            .build();
+        let batches = collect_batches(
+            &morselizer,
+            PartitionedFile::new("binary.parquet".to_string(), bin_size as u64),
+        )
+        .await;
+        assert_eq!(
+            batches[0].schema().field(0).data_type(),
+            &DataType::Dictionary(Box::new(DataType::Int32), Box::new(DataType::Binary))
+        );
+    }
 }