Add ArrowToParquetSchemaConverter, deprecate arrow_to_parquet_schema

parquet/src/arrow/arrow_writer/mod.rs

@@ -30,12 +30,10 @@ use arrow_array::types::*;
 use arrow_array::{ArrayRef, RecordBatch, RecordBatchWriter};
 use arrow_schema::{ArrowError, DataType as ArrowDataType, Field, IntervalUnit, SchemaRef};
 
-use super::schema::{
-    add_encoded_arrow_schema_to_metadata, arrow_to_parquet_schema,
-    arrow_to_parquet_schema_with_root, decimal_length_from_precision,
-};
+use super::schema::{add_encoded_arrow_schema_to_metadata, decimal_length_from_precision};
 
 use crate::arrow::arrow_writer::byte_array::ByteArrayEncoder;
+use crate::arrow::ArrowToParquetSchemaConverter;
 use crate::column::page::{CompressedPage, PageWriteSpec, PageWriter};
 use crate::column::writer::encoder::ColumnValueEncoder;
 use crate::column::writer::{
@@ -181,10 +179,12 @@ impl<W: Write + Send> ArrowWriter<W> {
         options: ArrowWriterOptions,
     ) -> Result<Self> {
         let mut props = options.properties;
-        let schema = match options.schema_root {
-            Some(s) => arrow_to_parquet_schema_with_root(&arrow_schema, &s, props.coerce_types())?,
-            None => arrow_to_parquet_schema(&arrow_schema, props.coerce_types())?,
-        };
+        let mut converter = ArrowToParquetSchemaConverter::new(&arrow_schema)
+            .with_coerce_types(props.coerce_types());
+        if let Some(s) = &options.schema_root {
+            converter = converter.schema_root(s);
+        }
+        let schema = converter.build()?;
         if !options.skip_arrow_metadata {
             // add serialized arrow schema
             add_encoded_arrow_schema_to_metadata(&arrow_schema, &mut props);
@@ -538,7 +538,7 @@ impl ArrowColumnChunk {
 /// # use std::sync::Arc;
 /// # use arrow_array::*;
 /// # use arrow_schema::*;
-/// # use parquet::arrow::arrow_to_parquet_schema;
+/// # use parquet::arrow::ArrowToParquetSchemaConverter;
 /// # use parquet::arrow::arrow_writer::{ArrowLeafColumn, compute_leaves, get_column_writers};
 /// # use parquet::file::properties::WriterProperties;
 /// # use parquet::file::writer::SerializedFileWriter;
@@ -550,7 +550,10 @@ impl ArrowColumnChunk {
 ///
 /// // Compute the parquet schema
 /// let props = Arc::new(WriterProperties::default());
-/// let parquet_schema = arrow_to_parquet_schema(schema.as_ref(), props.coerce_types()).unwrap();
+/// let parquet_schema = ArrowToParquetSchemaConverter::new(schema.as_ref())
+///   .with_coerce_types(props.coerce_types())
+///   .build()
+///   .unwrap();
 ///
 /// // Create writers for each of the leaf columns
 /// let col_writers = get_column_writers(&parquet_schema, &props, &schema).unwrap();

parquet/src/arrow/mod.rs

@@ -116,9 +116,13 @@ pub use self::async_writer::AsyncArrowWriter;
 use crate::schema::types::SchemaDescriptor;
 use arrow_schema::{FieldRef, Schema};
 
+// continue to export deprecated methods until they are removed
+#[allow(deprecated)]
+pub use self::schema::arrow_to_parquet_schema;
+
 pub use self::schema::{
-    arrow_to_parquet_schema, parquet_to_arrow_field_levels, parquet_to_arrow_schema,
-    parquet_to_arrow_schema_by_columns, FieldLevels,
+    parquet_to_arrow_field_levels, parquet_to_arrow_schema, parquet_to_arrow_schema_by_columns,
+    ArrowToParquetSchemaConverter, FieldLevels,
 };
 
 /// Schema metadata key used to store serialized Arrow IPC schema

parquet/src/arrow/schema/mod.rs

@@ -15,13 +15,7 @@
 // specific language governing permissions and limitations
 // under the License.
 
-//! Provides API for converting parquet schema to arrow schema and vice versa.
-//!
-//! The main interfaces for converting parquet schema to arrow schema  are
-//! `parquet_to_arrow_schema`, `parquet_to_arrow_schema_by_columns` and
-//! `parquet_to_arrow_field`.
-//!
-//! The interfaces for converting arrow schema to parquet schema is coming.
+//! Converting Parquet schema <--> Arrow schema: [`ArrowToParquetSchemaConverter`] and [parquet_to_arrow_schema]
 
 use base64::prelude::BASE64_STANDARD;
 use base64::Engine;
@@ -225,27 +219,133 @@ pub(crate) fn add_encoded_arrow_schema_to_metadata(schema: &Schema, props: &mut
     }
 }
 
-/// Convert arrow schema to parquet schema
+/// Converter for arrow schema to parquet schema
 ///
-/// The name of the root schema element defaults to `"arrow_schema"`, this can be
-/// overridden with [`arrow_to_parquet_schema_with_root`]
-pub fn arrow_to_parquet_schema(schema: &Schema, coerce_types: bool) -> Result<SchemaDescriptor> {
-    arrow_to_parquet_schema_with_root(schema, "arrow_schema", coerce_types)
+/// Example:
+/// ```
+/// # use std::sync::Arc;
+/// # use arrow_schema::{Field, Schema, DataType};
+/// # use parquet::arrow::ArrowToParquetSchemaConverter;
+/// use parquet::schema::types::{SchemaDescriptor, Type};
+/// use parquet::basic; // note there are two `Type`s in the following example
+/// let arrow_schema = Schema::new(vec![
+///   Field::new("a", DataType::Int64, true),
+///   Field::new("b", DataType::Date32, true),
+/// ]);
+///
+/// let parquet_schema = ArrowToParquetSchemaConverter::new(&arrow_schema)
+///   .build()
+///   .unwrap();
+///
+/// let expected_parquet_schema = SchemaDescriptor::new(
+///   Arc::new(
+///     Type::group_type_builder("arrow_schema")
+///       .with_fields(vec![
+///         Arc::new(
+///          Type::primitive_type_builder("a", basic::Type::INT64)
+///           .build().unwrap()
+///         ),
+///         Arc::new(
+///          Type::primitive_type_builder("b", basic::Type::INT32)
+///           .with_converted_type(basic::ConvertedType::DATE)
+///           .with_logical_type(Some(basic::LogicalType::Date))
+///           .build().unwrap()
+///         ),
+///      ])
+///      .build().unwrap()
+///   )
+/// );
+///
+/// assert_eq!(parquet_schema, expected_parquet_schema);
+/// ```
+#[derive(Debug)]
+pub struct ArrowToParquetSchemaConverter<'a> {
+    /// The schema to convert
+    schema: &'a Schema,
+    /// Name of the root schema in Parquet
+    schema_root: &'a str,
+    /// Should we Coerce arrow types to compatible Parquet types?
+    ///
+    /// See docs on [Self::with_coerce_types]`
+    coerce_types: bool,
 }
 
-/// Convert arrow schema to parquet schema specifying the name of the root schema element
-pub fn arrow_to_parquet_schema_with_root(
-    schema: &Schema,
-    root: &str,
-    coerce_types: bool,
-) -> Result<SchemaDescriptor> {
-    let fields = schema
-        .fields()
-        .iter()
-        .map(|field| arrow_to_parquet_type(field, coerce_types).map(Arc::new))
-        .collect::<Result<_>>()?;
-    let group = Type::group_type_builder(root).with_fields(fields).build()?;
-    Ok(SchemaDescriptor::new(Arc::new(group)))
+impl<'a> ArrowToParquetSchemaConverter<'a> {
+    /// Create a new converter
+    pub fn new(schema: &'a Schema) -> Self {
+        Self {
+            schema,
+            schema_root: "arrow_schema",
+            coerce_types: false,
+        }
+    }
+
+    /// Should arrow types be coerced into parquet native types (default `false`).
+    ///
+    /// Setting this option to `true` will result in parquet files that can be
+    /// read by more readers, but may lose precision for arrow types such as
+    /// [`DataType::Date64`] which have no direct corresponding Parquet type.
+    ///
+    /// By default, this converter does not coerce to native parquet types. Enabling type
+    /// coercion allows for meaningful representations that do not require
+    /// downstream readers to consider the embedded Arrow schema, and can allow
+    /// for greater compatibility with other Parquet implementations. However,
+    /// type coercion also prevents data from being losslessly round-tripped.
+    ///
+    /// # Discussion
+    ///
+    /// Some Arrow types such as `Date64`, `Timestamp` and `Interval` have no
+    /// corresponding Parquet logical type. Thus, they can not be losslessly
+    /// round-tripped when stored using the appropriate Parquet logical type.
+    /// For example, some Date64 values may be truncated when stored with
+    /// parquet's native 32 bit date type.
+    ///
+    /// For [`List`] and [`Map`] types, some
+    /// Parquet readers expect certain schema elements to have specific names
+    /// (earlier versions of the spec were somewhat ambiguous on this point).
+    /// Type coercion will use the names prescribed by the Parquet specification,
+    /// potentially losing naming metadata from the Arrow schema.
+    ///
+    /// [`List`]: https://github.com/apache/parquet-format/blob/master/LogicalTypes.md#lists
+    /// [`Map`]: https://github.com/apache/parquet-format/blob/master/LogicalTypes.md#maps
+    ///
+    pub fn with_coerce_types(mut self, coerce_types: bool) -> Self {
+        self.coerce_types = coerce_types;
+        self
+    }
+
+    /// Set the root schema element name (defaults to `"arrow_schema"`).
+    pub fn schema_root(mut self, schema_root: &'a str) -> Self {
+        self.schema_root = schema_root;
+        self
+    }
+
+    /// Build the desired parquet [`SchemaDescriptor`]
+    pub fn build(self) -> Result<SchemaDescriptor> {
+        let Self {
+            schema,
+            schema_root: root_schema_name,
+            coerce_types,
+        } = self;
+        let fields = schema
+            .fields()
+            .iter()
+            .map(|field| arrow_to_parquet_type(field, coerce_types).map(Arc::new))
+            .collect::<Result<_>>()?;
+        let group = Type::group_type_builder(root_schema_name)
+            .with_fields(fields)
+            .build()?;
+        Ok(SchemaDescriptor::new(Arc::new(group)))
+    }
+}
+
+/// Convert arrow schema to parquet schema
+///
+/// The name of the root schema element defaults to `"arrow_schema"`, this can be
+/// overridden with [`ArrowToParquetSchemaConverter`]
+#[deprecated(since = "54.0.0", note = "Use `ArrowToParquetSchemaConverter` instead")]
+pub fn arrow_to_parquet_schema(schema: &Schema) -> Result<SchemaDescriptor> {
+    ArrowToParquetSchemaConverter::new(schema).build()
 }
 
 fn parse_key_value_metadata(
@@ -1487,7 +1587,10 @@ mod tests {
         ";
         let parquet_group_type = parse_message_type(message_type).unwrap();
         let parquet_schema = SchemaDescriptor::new(Arc::new(parquet_group_type));
-        let converted_arrow_schema = arrow_to_parquet_schema(&arrow_schema, true).unwrap();
+        let converted_arrow_schema = ArrowToParquetSchemaConverter::new(&arrow_schema)
+            .with_coerce_types(true)
+            .build()
+            .unwrap();
         assert_eq!(
             parquet_schema.columns().len(),
             converted_arrow_schema.columns().len()
@@ -1511,7 +1614,10 @@ mod tests {
         ";
         let parquet_group_type = parse_message_type(message_type).unwrap();
         let parquet_schema = SchemaDescriptor::new(Arc::new(parquet_group_type));
-        let converted_arrow_schema = arrow_to_parquet_schema(&arrow_schema, false).unwrap();
+        let converted_arrow_schema = ArrowToParquetSchemaConverter::new(&arrow_schema)
+            .with_coerce_types(false)
+            .build()
+            .unwrap();
         assert_eq!(
             parquet_schema.columns().len(),
             converted_arrow_schema.columns().len()
@@ -1667,7 +1773,9 @@ mod tests {
             Field::new("decimal256", DataType::Decimal256(39, 2), false),
         ];
         let arrow_schema = Schema::new(arrow_fields);
-        let converted_arrow_schema = arrow_to_parquet_schema(&arrow_schema, false).unwrap();
+        let converted_arrow_schema = ArrowToParquetSchemaConverter::new(&arrow_schema)
+            .build()
+            .unwrap();
 
         assert_eq!(
             parquet_schema.columns().len(),
@@ -1704,9 +1812,10 @@ mod tests {
             false,
         )];
         let arrow_schema = Schema::new(arrow_fields);
-        let converted_arrow_schema = arrow_to_parquet_schema(&arrow_schema, true);
+        let converted_arrow_schema = ArrowToParquetSchemaConverter::new(&arrow_schema)
+            .with_coerce_types(true)
+            .build();
 
-        assert!(converted_arrow_schema.is_err());
         converted_arrow_schema.unwrap();
     }
 
@@ -1976,7 +2085,9 @@ mod tests {
         // don't pass metadata so field ids are read from Parquet and not from serialized Arrow schema
         let arrow_schema = crate::arrow::parquet_to_arrow_schema(&schema_descriptor, None)?;
 
-        let parq_schema_descr = crate::arrow::arrow_to_parquet_schema(&arrow_schema, true)?;
+        let parq_schema_descr = crate::arrow::ArrowToParquetSchemaConverter::new(&arrow_schema)
+            .with_coerce_types(true)
+            .build()?;
         let parq_fields = parq_schema_descr.root_schema().get_fields();
         assert_eq!(parq_fields.len(), 2);
         assert_eq!(parq_fields[0].get_basic_info().id(), 1);

parquet/src/file/properties.rs

@@ -16,14 +16,13 @@
 // under the License.
 
 //! Configuration via [`WriterProperties`] and [`ReaderProperties`]
-use std::str::FromStr;
-use std::{collections::HashMap, sync::Arc};
-
 use crate::basic::{Compression, Encoding};
 use crate::compression::{CodecOptions, CodecOptionsBuilder};
 use crate::file::metadata::KeyValue;
 use crate::format::SortingColumn;
 use crate::schema::types::ColumnPath;
+use std::str::FromStr;
+use std::{collections::HashMap, sync::Arc};
 
 /// Default value for [`WriterProperties::data_page_size_limit`]
 pub const DEFAULT_PAGE_SIZE: usize = 1024 * 1024;
@@ -780,22 +779,24 @@ impl WriterPropertiesBuilder {
         self
     }
 
-    /// Sets flag to control if type coercion is enabled (defaults to `false`).
+    /// Should the writer coerce types to parquet native types (defaults to `false`).
     ///
-    /// # Notes
-    /// Some Arrow types do not have a corresponding Parquet logical type.
-    /// Affected Arrow data types include `Date64`, `Timestamp` and `Interval`.
-    /// Also, for [`List`] and [`Map`] types, Parquet expects certain schema elements
-    /// to have specific names to be considered fully compliant.
-    /// Writers have the option to coerce these types and names to match those required
-    /// by the Parquet specification.
-    /// This type coercion allows for meaningful representations that do not require
-    /// downstream readers to consider the embedded Arrow schema, and can allow for greater
-    /// compatibility with other Parquet implementations. However, type
-    /// coercion also prevents the data from being losslessly round-tripped.
-    ///
-    /// [`List`]: https://github.com/apache/parquet-format/blob/master/LogicalTypes.md#lists
-    /// [`Map`]: https://github.com/apache/parquet-format/blob/master/LogicalTypes.md#maps
+    /// Leaving this option the default `false` will ensure the exact same data
+    /// written to parquet using this library will be read.
+    ///
+    /// Setting this option to `true` will result in parquet files that can be
+    /// read by more readers, but potentially lose information in the process.
+    ///
+    /// * Types such as [`DataType::Date64`], which have no direct corresponding
+    ///   Parquet type, may be stored with lower precision.
+    ///
+    /// * The internal field names of [`List`] and [`Map`] will be renamed if
+    ///   necessary to match what is required by the newest Parquet specification.
+    ///
+    /// See [`ArrowToParquetSchemaConverter::with_coerce_types`] for more details
+    ///
+    /// [`DataType::Date64`]: arrow_schema::DataType::Date64
+    /// [`ArrowToParquetSchemaConverter::with_coerce_types`]: crate::arrow::ArrowToParquetSchemaConverter::with_coerce_types
     pub fn set_coerce_types(mut self, coerce_types: bool) -> Self {
         self.coerce_types = coerce_types;
         self