introduce binary_as_string parquet option

benchmarks/src/clickbench.rs

@@ -115,12 +115,15 @@ impl RunOpt {
             None => queries.min_query_id()..=queries.max_query_id(),
         };
 
+        // configure parquet options
         let mut config = self.common.config();
-        config
-            .options_mut()
-            .execution
-            .parquet
-            .schema_force_view_types = self.common.force_view_types;
+        {
+            let parquet_options = &mut config.options_mut().execution.parquet;
+            parquet_options.schema_force_view_types = self.common.force_view_types;
+            // The hits_partitioned dataset specifies string columns
+            // as binary due to how it was written. Force it to strings
+            parquet_options.binary_as_string = true;
+        }
 
         let ctx = SessionContext::new_with_config(config);
         self.register_hits(&ctx).await?;
@@ -148,7 +151,7 @@ impl RunOpt {
         Ok(())
     }
 
-    /// Registrs the `hits.parquet` as a table named `hits`
+    /// Registers the `hits.parquet` as a table named `hits`
     async fn register_hits(&self, ctx: &SessionContext) -> Result<()> {
         let options = Default::default();
         let path = self.path.as_os_str().to_str().unwrap();

datafusion/common/src/config.rs

@@ -390,6 +390,14 @@ config_namespace! {
         /// and `Binary/BinaryLarge` with `BinaryView`.
         pub schema_force_view_types: bool, default = false
 
+        /// (reading) If true, parquet reader will read columns of
+        /// `Binary/LargeBinary` with `Utf8`, and `BinaryView` with `Utf8View`.
+        ///
+        /// Parquet files generated by some legacy writers do not correctly set
+        /// the UTF8 flag for strings, causing string columns to be loaded as
+        /// BLOB instead.
+        pub binary_as_string: 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

@@ -176,6 +176,7 @@ impl ParquetOptions {
             maximum_buffered_record_batches_per_stream: _,
             bloom_filter_on_read: _, // reads not used for writer props
             schema_force_view_types: _,
+            binary_as_string: _, // not used for writer props
         } = self;
 
         let mut builder = WriterProperties::builder()
@@ -442,6 +443,7 @@ mod tests {
                 .maximum_buffered_record_batches_per_stream,
             bloom_filter_on_read: defaults.bloom_filter_on_read,
             schema_force_view_types: defaults.schema_force_view_types,
+            binary_as_string: defaults.binary_as_string,
         }
     }
 
@@ -543,6 +545,7 @@ mod tests {
                     .maximum_buffered_record_batches_per_stream,
                 bloom_filter_on_read: global_options_defaults.bloom_filter_on_read,
                 schema_force_view_types: global_options_defaults.schema_force_view_types,
+                binary_as_string: global_options_defaults.binary_as_string,
             },
             column_specific_options,
             key_value_metadata,

datafusion/core/src/datasource/file_format/mod.rs

@@ -42,7 +42,7 @@ use crate::error::Result;
 use crate::execution::context::SessionState;
 use crate::physical_plan::{ExecutionPlan, Statistics};
 
-use arrow_schema::{DataType, Field, Schema};
+use arrow_schema::{DataType, Field, FieldRef, Schema};
 use datafusion_common::file_options::file_type::FileType;
 use datafusion_common::{internal_err, not_impl_err, GetExt};
 use datafusion_expr::Expr;
@@ -235,20 +235,26 @@ pub fn file_type_to_format(
     }
 }
 
+/// Create a new field with the specified data type, copying the other
+/// properties from the input field
+fn field_with_new_type(field: &FieldRef, new_type: DataType) -> FieldRef {
+    Arc::new(field.as_ref().clone().with_data_type(new_type))
+}
+
 /// Transform a schema to use view types for Utf8 and Binary
+///
+/// See [parquet::ParquetFormat::force_view_types] for details
 pub fn transform_schema_to_view(schema: &Schema) -> Schema {
     let transformed_fields: Vec<Arc<Field>> = schema
         .fields
         .iter()
         .map(|field| match field.data_type() {
-            DataType::Utf8 | DataType::LargeUtf8 => Arc::new(
-                Field::new(field.name(), DataType::Utf8View, field.is_nullable())
-                    .with_metadata(field.metadata().to_owned()),
-            ),
-            DataType::Binary | DataType::LargeBinary => Arc::new(
-                Field::new(field.name(), DataType::BinaryView, field.is_nullable())
-                    .with_metadata(field.metadata().to_owned()),
-            ),
+            DataType::Utf8 | DataType::LargeUtf8 => {
+                field_with_new_type(field, DataType::Utf8View)
+            }
+            DataType::Binary | DataType::LargeBinary => {
+                field_with_new_type(field, DataType::BinaryView)
+            }
             _ => field.clone(),
         })
         .collect();
@@ -274,6 +280,7 @@ pub(crate) fn coerce_file_schema_to_view_type(
             (f.name(), dt)
         })
         .collect();
+
     if !transform {
         return None;
     }
@@ -283,14 +290,13 @@ pub(crate) fn coerce_file_schema_to_view_type(
         .iter()
         .map(
             |field| match (table_fields.get(field.name()), field.data_type()) {
-                (Some(DataType::Utf8View), DataType::Utf8)
-                | (Some(DataType::Utf8View), DataType::LargeUtf8) => Arc::new(
-                    Field::new(field.name(), DataType::Utf8View, field.is_nullable()),
-                ),
-                (Some(DataType::BinaryView), DataType::Binary)
-                | (Some(DataType::BinaryView), DataType::LargeBinary) => Arc::new(
-                    Field::new(field.name(), DataType::BinaryView, field.is_nullable()),
-                ),
+                (Some(DataType::Utf8View), DataType::Utf8 | DataType::LargeUtf8) => {
+                    field_with_new_type(field, DataType::Utf8View)
+                }
+                (
+                    Some(DataType::BinaryView),
+                    DataType::Binary | DataType::LargeBinary,
+                ) => field_with_new_type(field, DataType::BinaryView),
                 _ => field.clone(),
             },
         )
@@ -302,6 +308,78 @@ pub(crate) fn coerce_file_schema_to_view_type(
     ))
 }
 
+/// Transform a schema so that any binary types are strings
+pub fn transform_binary_to_string(schema: &Schema) -> Schema {
+    let transformed_fields: Vec<Arc<Field>> = schema
+        .fields
+        .iter()
+        .map(|field| match field.data_type() {
+            DataType::Binary => field_with_new_type(field, DataType::Utf8),
+            DataType::LargeBinary => field_with_new_type(field, DataType::LargeUtf8),
+            DataType::BinaryView => field_with_new_type(field, DataType::Utf8View),
+            _ => field.clone(),
+        })
+        .collect();
+    Schema::new_with_metadata(transformed_fields, schema.metadata.clone())
+}
+
+/// If the table schema uses a string type, coerce the file schema to use a string type.
+///
+/// See [parquet::ParquetFormat::binary_as_string] for details
+pub(crate) fn coerce_file_schema_to_string_type(
+    table_schema: &Schema,
+    file_schema: &Schema,
+) -> Option<Schema> {
+    let mut transform = false;
+    let table_fields: HashMap<_, _> = table_schema
+        .fields
+        .iter()
+        .map(|f| (f.name(), f.data_type()))
+        .collect();
+    let transformed_fields: Vec<Arc<Field>> = file_schema
+        .fields
+        .iter()
+        .map(
+            |field| match (table_fields.get(field.name()), field.data_type()) {
+                // table schema uses string type, coerce the file schema to use string type
+                (
+                    Some(DataType::Utf8),
+                    DataType::Binary | DataType::LargeBinary | DataType::BinaryView,
+                ) => {
+                    transform = true;
+                    field_with_new_type(field, DataType::Utf8)
+                }
+                // table schema uses large string type, coerce the file schema to use large string type
+                (
+                    Some(DataType::LargeUtf8),
+                    DataType::Binary | DataType::LargeBinary | DataType::BinaryView,
+                ) => {
+                    transform = true;
+                    field_with_new_type(field, DataType::LargeUtf8)
+                }
+                // table schema uses string view type, coerce the file schema to use view type
+                (
+                    Some(DataType::Utf8View),
+                    DataType::Binary | DataType::LargeBinary | DataType::BinaryView,
+                ) => {
+                    transform = true;
+                    field_with_new_type(field, DataType::Utf8View)
+                }
+                _ => field.clone(),
+            },
+        )
+        .collect();
+
+    if !transform {
+        None
+    } else {
+        Some(Schema::new_with_metadata(
+            transformed_fields,
+            file_schema.metadata.clone(),
+        ))
+    }
+}
+
 #[cfg(test)]
 pub(crate) mod test_util {
     use std::ops::Range;

datafusion/core/src/datasource/file_format/parquet.rs

@@ -26,8 +26,9 @@ use std::sync::Arc;
 use super::write::demux::start_demuxer_task;
 use super::write::{create_writer, SharedBuffer};
 use super::{
-    coerce_file_schema_to_view_type, transform_schema_to_view, FileFormat,
-    FileFormatFactory, FilePushdownSupport, FileScanConfig,
+    coerce_file_schema_to_string_type, coerce_file_schema_to_view_type,
+    transform_binary_to_string, transform_schema_to_view, FileFormat, FileFormatFactory,
+    FilePushdownSupport, FileScanConfig,
 };
 use crate::arrow::array::RecordBatch;
 use crate::arrow::datatypes::{Fields, Schema, SchemaRef};
@@ -253,13 +254,29 @@ impl ParquetFormat {
         self.options.global.schema_force_view_types
     }
 
-    /// If true, will use view types (StringView and BinaryView).
-    ///
-    /// Refer to [`Self::force_view_types`].
+    /// If true, will use view types. See [`Self::force_view_types`] for details
     pub fn with_force_view_types(mut self, use_views: bool) -> Self {
         self.options.global.schema_force_view_types = use_views;
         self
     }
+
+    /// Return `true` if binary types will be read as strings.
+    ///
+    /// If this returns true, DataFusion will instruct the parquet reader
+    /// to read binary columns such as `Binary` or `BinaryView` as the
+    /// corresponding string type such as `Utf8` or `LargeUtf8`.
+    /// The parquet reader has special optimizations for `Utf8` and `LargeUtf8`
+    /// validation, and such queries are significantly faster than reading
+    /// binary columns and then casting to string columns.
+    pub fn binary_as_string(&self) -> bool {
+        self.options.global.binary_as_string
+    }
+
+    /// If true, will read binary types as strings. See [`Self::binary_as_string`] for details
+    pub fn with_binary_as_string(mut self, binary_as_string: bool) -> Self {
+        self.options.global.binary_as_string = binary_as_string;
+        self
+    }
 }
 
 /// Clears all metadata (Schema level and field level) on an iterator
@@ -350,6 +367,12 @@ impl FileFormat for ParquetFormat {
             Schema::try_merge(schemas)
         }?;
 
+        let schema = if self.binary_as_string() {
+            transform_binary_to_string(&schema)
+        } else {
+            schema
+        };
+
         let schema = if self.force_view_types() {
             transform_schema_to_view(&schema)
         } else {
@@ -552,6 +575,10 @@ pub fn statistics_from_parquet_meta_calc(
         file_metadata.schema_descr(),
         file_metadata.key_value_metadata(),
     )?;
+    if let Some(merged) = coerce_file_schema_to_string_type(&table_schema, &file_schema) {
+        file_schema = merged;
+    }
+
     if let Some(merged) = coerce_file_schema_to_view_type(&table_schema, &file_schema) {
         file_schema = merged;
     }

datafusion/core/src/datasource/physical_plan/parquet/opener.rs

@@ -17,7 +17,9 @@
 
 //! [`ParquetOpener`] for opening Parquet files
 
-use crate::datasource::file_format::coerce_file_schema_to_view_type;
+use crate::datasource::file_format::{
+    coerce_file_schema_to_string_type, coerce_file_schema_to_view_type,
+};
 use crate::datasource::physical_plan::parquet::page_filter::PagePruningAccessPlanFilter;
 use crate::datasource::physical_plan::parquet::row_group_filter::RowGroupAccessPlanFilter;
 use crate::datasource::physical_plan::parquet::{
@@ -80,7 +82,7 @@ pub(super) struct ParquetOpener {
 }
 
 impl FileOpener for ParquetOpener {
-    fn open(&self, file_meta: FileMeta) -> datafusion_common::Result<FileOpenFuture> {
+    fn open(&self, file_meta: FileMeta) -> Result<FileOpenFuture> {
         let file_range = file_meta.range.clone();
         let extensions = file_meta.extensions.clone();
         let file_name = file_meta.location().to_string();
@@ -121,7 +123,14 @@ impl FileOpener for ParquetOpener {
             let mut metadata_timer = file_metrics.metadata_load_time.timer();
             let metadata =
                 ArrowReaderMetadata::load_async(&mut reader, options.clone()).await?;
-            let mut schema = metadata.schema().clone();
+            let mut schema = Arc::clone(metadata.schema());
+
+            if let Some(merged) =
+                coerce_file_schema_to_string_type(&table_schema, &schema)
+            {
+                schema = Arc::new(merged);
+            }
+
             // read with view types
             if let Some(merged) = coerce_file_schema_to_view_type(&table_schema, &schema)
             {
@@ -130,16 +139,16 @@ impl FileOpener for ParquetOpener {
 
             let options = ArrowReaderOptions::new()
                 .with_page_index(enable_page_index)
-                .with_schema(schema.clone());
+                .with_schema(Arc::clone(&schema));
             let metadata =
-                ArrowReaderMetadata::try_new(metadata.metadata().clone(), options)?;
+                ArrowReaderMetadata::try_new(Arc::clone(metadata.metadata()), options)?;
 
             metadata_timer.stop();
 
             let mut builder =
                 ParquetRecordBatchStreamBuilder::new_with_metadata(reader, metadata);
 
-            let file_schema = builder.schema().clone();
+            let file_schema = Arc::clone(builder.schema());
 
             let (schema_mapping, adapted_projections) =
                 schema_adapter.map_schema(&file_schema)?;
@@ -177,7 +186,7 @@ impl FileOpener for ParquetOpener {
 
             // Determine which row groups to actually read. The idea is to skip
             // as many row groups as possible based on the metadata and query
-            let file_metadata = builder.metadata().clone();
+            let file_metadata = Arc::clone(builder.metadata());
             let predicate = pruning_predicate.as_ref().map(|p| p.as_ref());
             let rg_metadata = file_metadata.row_groups();
             // track which row groups to actually read

datafusion/proto-common/proto/datafusion_common.proto

@@ -494,6 +494,7 @@ message ParquetOptions {
   bool bloom_filter_on_read = 26; // default = true
   bool bloom_filter_on_write = 27; // default = false
   bool schema_force_view_types = 28; // default = false
+  bool binary_as_string = 29; // default = false
 
   oneof metadata_size_hint_opt {
     uint64 metadata_size_hint = 4;