forked from apache/arrow-rs
/
schema.rs
1718 lines (1593 loc) · 62.5 KB
/
schema.rs
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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the License for the
// 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.
use std::collections::HashMap;
use std::sync::Arc;
use arrow::datatypes::{DataType, Field, Schema, TimeUnit};
use arrow::ipc::writer;
use crate::basic::{
ConvertedType, LogicalType, Repetition, TimeUnit as ParquetTimeUnit,
Type as PhysicalType,
};
use crate::errors::{ParquetError, Result};
use crate::file::{metadata::KeyValue, properties::WriterProperties};
use crate::schema::types::{ColumnDescriptor, SchemaDescriptor, Type, TypePtr};
mod complex;
mod primitive;
use crate::arrow::ProjectionMask;
pub(crate) use complex::{convert_schema, ParquetField, ParquetFieldType};
/// Convert Parquet schema to Arrow schema including optional metadata.
/// Attempts to decode any existing Arrow schema metadata, falling back
/// to converting the Parquet schema column-wise
pub fn parquet_to_arrow_schema(
parquet_schema: &SchemaDescriptor,
key_value_metadata: Option<&Vec<KeyValue>>,
) -> Result<Schema> {
parquet_to_arrow_schema_by_columns(
parquet_schema,
ProjectionMask::all(),
key_value_metadata,
)
}
/// Convert parquet schema to arrow schema including optional metadata,
/// only preserving some leaf columns.
pub fn parquet_to_arrow_schema_by_columns(
parquet_schema: &SchemaDescriptor,
mask: ProjectionMask,
key_value_metadata: Option<&Vec<KeyValue>>,
) -> Result<Schema> {
let mut metadata = parse_key_value_metadata(key_value_metadata).unwrap_or_default();
let maybe_schema = metadata
.remove(super::ARROW_SCHEMA_META_KEY)
.map(|value| get_arrow_schema_from_metadata(&value))
.transpose()?;
// Add the Arrow metadata to the Parquet metadata skipping keys that collide
if let Some(arrow_schema) = &maybe_schema {
arrow_schema.metadata().iter().for_each(|(k, v)| {
metadata.entry(k.clone()).or_insert(v.clone());
});
}
match convert_schema(parquet_schema, mask, maybe_schema.as_ref())? {
Some(field) => match field.arrow_type {
DataType::Struct(fields) => Ok(Schema::new_with_metadata(fields, metadata)),
_ => unreachable!(),
},
None => Ok(Schema::new_with_metadata(vec![], metadata)),
}
}
/// Try to convert Arrow schema metadata into a schema
fn get_arrow_schema_from_metadata(encoded_meta: &str) -> Result<Schema> {
let decoded = base64::decode(encoded_meta);
match decoded {
Ok(bytes) => {
let slice = if bytes[0..4] == [255u8; 4] {
&bytes[8..]
} else {
bytes.as_slice()
};
match arrow::ipc::root_as_message(slice) {
Ok(message) => message
.header_as_schema()
.map(arrow::ipc::convert::fb_to_schema)
.ok_or(arrow_err!("the message is not Arrow Schema")),
Err(err) => {
// The flatbuffers implementation returns an error on verification error.
Err(arrow_err!(
"Unable to get root as message stored in {}: {:?}",
super::ARROW_SCHEMA_META_KEY,
err
))
}
}
}
Err(err) => {
// The C++ implementation returns an error if the schema can't be parsed.
Err(arrow_err!(
"Unable to decode the encoded schema stored in {}, {:?}",
super::ARROW_SCHEMA_META_KEY,
err
))
}
}
}
/// Encodes the Arrow schema into the IPC format, and base64 encodes it
fn encode_arrow_schema(schema: &Schema) -> String {
let options = writer::IpcWriteOptions::default();
let data_gen = arrow::ipc::writer::IpcDataGenerator::default();
let mut serialized_schema = data_gen.schema_to_bytes(schema, &options);
// manually prepending the length to the schema as arrow uses the legacy IPC format
// TODO: change after addressing ARROW-9777
let schema_len = serialized_schema.ipc_message.len();
let mut len_prefix_schema = Vec::with_capacity(schema_len + 8);
len_prefix_schema.append(&mut vec![255u8, 255, 255, 255]);
len_prefix_schema.append((schema_len as u32).to_le_bytes().to_vec().as_mut());
len_prefix_schema.append(&mut serialized_schema.ipc_message);
base64::encode(&len_prefix_schema)
}
/// Mutates writer metadata by storing the encoded Arrow schema.
/// If there is an existing Arrow schema metadata, it is replaced.
pub(crate) fn add_encoded_arrow_schema_to_metadata(
schema: &Schema,
props: &mut WriterProperties,
) {
let encoded = encode_arrow_schema(schema);
let schema_kv = KeyValue {
key: super::ARROW_SCHEMA_META_KEY.to_string(),
value: Some(encoded),
};
let meta = props
.key_value_metadata
.get_or_insert_with(|| Default::default());
// check if ARROW:schema exists, and overwrite it
let schema_meta = meta
.iter()
.enumerate()
.find(|(_, kv)| kv.key.as_str() == super::ARROW_SCHEMA_META_KEY);
match schema_meta {
Some((i, _)) => {
meta.remove(i);
meta.push(schema_kv);
}
None => {
meta.push(schema_kv);
}
}
}
/// Convert arrow schema to parquet schema
pub fn arrow_to_parquet_schema(schema: &Schema) -> Result<SchemaDescriptor> {
let fields: Result<Vec<TypePtr>> = schema
.fields()
.iter()
.map(|field| arrow_to_parquet_type(field).map(Arc::new))
.collect();
let group = Type::group_type_builder("arrow_schema")
.with_fields(&mut fields?)
.build()?;
Ok(SchemaDescriptor::new(Arc::new(group)))
}
fn parse_key_value_metadata(
key_value_metadata: Option<&Vec<KeyValue>>,
) -> Option<HashMap<String, String>> {
match key_value_metadata {
Some(key_values) => {
let map: HashMap<String, String> = key_values
.iter()
.filter_map(|kv| {
kv.value
.as_ref()
.map(|value| (kv.key.clone(), value.clone()))
})
.collect();
if map.is_empty() {
None
} else {
Some(map)
}
}
None => None,
}
}
/// Convert parquet column schema to arrow field.
pub fn parquet_to_arrow_field(parquet_column: &ColumnDescriptor) -> Result<Field> {
let field = complex::convert_type(&parquet_column.self_type_ptr())?;
Ok(Field::new(
parquet_column.name(),
field.arrow_type,
field.nullable,
))
}
pub fn decimal_length_from_precision(precision: usize) -> usize {
(10.0_f64.powi(precision as i32).log2() / 8.0).ceil() as usize
}
/// Convert an arrow field to a parquet `Type`
fn arrow_to_parquet_type(field: &Field) -> Result<Type> {
let name = field.name().as_str();
let repetition = if field.is_nullable() {
Repetition::OPTIONAL
} else {
Repetition::REQUIRED
};
// create type from field
match field.data_type() {
DataType::Null => Type::primitive_type_builder(name, PhysicalType::INT32)
.with_logical_type(Some(LogicalType::Unknown))
.with_repetition(repetition)
.build(),
DataType::Boolean => Type::primitive_type_builder(name, PhysicalType::BOOLEAN)
.with_repetition(repetition)
.build(),
DataType::Int8 => Type::primitive_type_builder(name, PhysicalType::INT32)
.with_logical_type(Some(LogicalType::Integer {
bit_width: 8,
is_signed: true,
}))
.with_repetition(repetition)
.build(),
DataType::Int16 => Type::primitive_type_builder(name, PhysicalType::INT32)
.with_logical_type(Some(LogicalType::Integer {
bit_width: 16,
is_signed: true,
}))
.with_repetition(repetition)
.build(),
DataType::Int32 => Type::primitive_type_builder(name, PhysicalType::INT32)
.with_repetition(repetition)
.build(),
DataType::Int64 => Type::primitive_type_builder(name, PhysicalType::INT64)
.with_repetition(repetition)
.build(),
DataType::UInt8 => Type::primitive_type_builder(name, PhysicalType::INT32)
.with_logical_type(Some(LogicalType::Integer {
bit_width: 8,
is_signed: false,
}))
.with_repetition(repetition)
.build(),
DataType::UInt16 => Type::primitive_type_builder(name, PhysicalType::INT32)
.with_logical_type(Some(LogicalType::Integer {
bit_width: 16,
is_signed: false,
}))
.with_repetition(repetition)
.build(),
DataType::UInt32 => Type::primitive_type_builder(name, PhysicalType::INT32)
.with_logical_type(Some(LogicalType::Integer {
bit_width: 32,
is_signed: false,
}))
.with_repetition(repetition)
.build(),
DataType::UInt64 => Type::primitive_type_builder(name, PhysicalType::INT64)
.with_logical_type(Some(LogicalType::Integer {
bit_width: 64,
is_signed: false,
}))
.with_repetition(repetition)
.build(),
DataType::Float16 => Err(arrow_err!("Float16 arrays not supported")),
DataType::Float32 => Type::primitive_type_builder(name, PhysicalType::FLOAT)
.with_repetition(repetition)
.build(),
DataType::Float64 => Type::primitive_type_builder(name, PhysicalType::DOUBLE)
.with_repetition(repetition)
.build(),
DataType::Timestamp(TimeUnit::Second, _) => {
// Cannot represent seconds in LogicalType
Type::primitive_type_builder(name, PhysicalType::INT64)
.with_repetition(repetition)
.build()
}
DataType::Timestamp(time_unit, tz) => {
Type::primitive_type_builder(name, PhysicalType::INT64)
.with_logical_type(Some(LogicalType::Timestamp {
// If timezone set, values are normalized to UTC timezone
is_adjusted_to_u_t_c: matches!(tz, Some(z) if !z.as_str().is_empty()),
unit: match time_unit {
TimeUnit::Second => unreachable!(),
TimeUnit::Millisecond => {
ParquetTimeUnit::MILLIS(Default::default())
}
TimeUnit::Microsecond => {
ParquetTimeUnit::MICROS(Default::default())
}
TimeUnit::Nanosecond => {
ParquetTimeUnit::NANOS(Default::default())
}
},
}))
.with_repetition(repetition)
.build()
}
DataType::Date32 => Type::primitive_type_builder(name, PhysicalType::INT32)
.with_logical_type(Some(LogicalType::Date))
.with_repetition(repetition)
.build(),
// date64 is cast to date32 (#1666)
DataType::Date64 => Type::primitive_type_builder(name, PhysicalType::INT32)
.with_logical_type(Some(LogicalType::Date))
.with_repetition(repetition)
.build(),
DataType::Time32(TimeUnit::Second) => {
// Cannot represent seconds in LogicalType
Type::primitive_type_builder(name, PhysicalType::INT32)
.with_repetition(repetition)
.build()
}
DataType::Time32(unit) => Type::primitive_type_builder(name, PhysicalType::INT32)
.with_logical_type(Some(LogicalType::Time {
is_adjusted_to_u_t_c: false,
unit: match unit {
TimeUnit::Millisecond => ParquetTimeUnit::MILLIS(Default::default()),
u => unreachable!("Invalid unit for Time32: {:?}", u),
},
}))
.with_repetition(repetition)
.build(),
DataType::Time64(unit) => Type::primitive_type_builder(name, PhysicalType::INT64)
.with_logical_type(Some(LogicalType::Time {
is_adjusted_to_u_t_c: false,
unit: match unit {
TimeUnit::Microsecond => ParquetTimeUnit::MICROS(Default::default()),
TimeUnit::Nanosecond => ParquetTimeUnit::NANOS(Default::default()),
u => unreachable!("Invalid unit for Time64: {:?}", u),
},
}))
.with_repetition(repetition)
.build(),
DataType::Duration(_) => {
Err(arrow_err!("Converting Duration to parquet not supported",))
}
DataType::Interval(_) => {
Type::primitive_type_builder(name, PhysicalType::FIXED_LEN_BYTE_ARRAY)
.with_converted_type(ConvertedType::INTERVAL)
.with_repetition(repetition)
.with_length(12)
.build()
}
DataType::Binary | DataType::LargeBinary => {
Type::primitive_type_builder(name, PhysicalType::BYTE_ARRAY)
.with_repetition(repetition)
.build()
}
DataType::FixedSizeBinary(length) => {
Type::primitive_type_builder(name, PhysicalType::FIXED_LEN_BYTE_ARRAY)
.with_repetition(repetition)
.with_length(*length)
.build()
}
DataType::Decimal(precision, scale) => {
// Decimal precision determines the Parquet physical type to use.
// TODO(ARROW-12018): Enable the below after ARROW-10818 Decimal support
//
// let (physical_type, length) = if *precision > 1 && *precision <= 9 {
// (PhysicalType::INT32, -1)
// } else if *precision <= 18 {
// (PhysicalType::INT64, -1)
// } else {
// (
// PhysicalType::FIXED_LEN_BYTE_ARRAY,
// decimal_length_from_precision(*precision) as i32,
// )
// };
Type::primitive_type_builder(name, PhysicalType::FIXED_LEN_BYTE_ARRAY)
.with_repetition(repetition)
.with_length(decimal_length_from_precision(*precision) as i32)
.with_logical_type(Some(LogicalType::Decimal {
scale: *scale as i32,
precision: *precision as i32,
}))
.with_precision(*precision as i32)
.with_scale(*scale as i32)
.build()
}
DataType::Utf8 | DataType::LargeUtf8 => {
Type::primitive_type_builder(name, PhysicalType::BYTE_ARRAY)
.with_logical_type(Some(LogicalType::String))
.with_repetition(repetition)
.build()
}
DataType::List(f) | DataType::FixedSizeList(f, _) | DataType::LargeList(f) => {
Type::group_type_builder(name)
.with_fields(&mut vec![Arc::new(
Type::group_type_builder("list")
.with_fields(&mut vec![Arc::new(arrow_to_parquet_type(f)?)])
.with_repetition(Repetition::REPEATED)
.build()?,
)])
.with_logical_type(Some(LogicalType::List))
.with_repetition(repetition)
.build()
}
DataType::Struct(fields) => {
if fields.is_empty() {
return Err(
arrow_err!("Parquet does not support writing empty structs",),
);
}
// recursively convert children to types/nodes
let fields: Result<Vec<TypePtr>> = fields
.iter()
.map(|f| arrow_to_parquet_type(f).map(Arc::new))
.collect();
Type::group_type_builder(name)
.with_fields(&mut fields?)
.with_repetition(repetition)
.build()
}
DataType::Map(field, _) => {
if let DataType::Struct(struct_fields) = field.data_type() {
Type::group_type_builder(name)
.with_fields(&mut vec![Arc::new(
Type::group_type_builder(field.name())
.with_fields(&mut vec![
Arc::new(arrow_to_parquet_type(&Field::new(
struct_fields[0].name(),
struct_fields[0].data_type().clone(),
false,
))?),
Arc::new(arrow_to_parquet_type(&Field::new(
struct_fields[1].name(),
struct_fields[1].data_type().clone(),
struct_fields[1].is_nullable(),
))?),
])
.with_repetition(Repetition::REPEATED)
.build()?,
)])
.with_logical_type(Some(LogicalType::Map))
.with_repetition(repetition)
.build()
} else {
Err(arrow_err!(
"DataType::Map should contain a struct field child",
))
}
}
DataType::Union(_, _, _) => unimplemented!("See ARROW-8817."),
DataType::Dictionary(_, ref value) => {
// Dictionary encoding not handled at the schema level
let dict_field = Field::new(name, *value.clone(), field.is_nullable());
arrow_to_parquet_type(&dict_field)
}
}
}
#[cfg(test)]
mod tests {
use super::*;
use std::{collections::HashMap, sync::Arc};
use arrow::datatypes::{DataType, Field, IntervalUnit, TimeUnit};
use crate::file::metadata::KeyValue;
use crate::{
arrow::{ArrowReader, ArrowWriter, ParquetFileArrowReader},
schema::{parser::parse_message_type, types::SchemaDescriptor},
};
#[test]
fn test_flat_primitives() {
let message_type = "
message test_schema {
REQUIRED BOOLEAN boolean;
REQUIRED INT32 int8 (INT_8);
REQUIRED INT32 int16 (INT_16);
REQUIRED INT32 uint8 (INTEGER(8,false));
REQUIRED INT32 uint16 (INTEGER(16,false));
REQUIRED INT32 int32;
REQUIRED INT64 int64 ;
OPTIONAL DOUBLE double;
OPTIONAL FLOAT float;
OPTIONAL BINARY string (UTF8);
OPTIONAL BINARY string_2 (STRING);
}
";
let parquet_group_type = parse_message_type(message_type).unwrap();
let parquet_schema = SchemaDescriptor::new(Arc::new(parquet_group_type));
let converted_arrow_schema =
parquet_to_arrow_schema(&parquet_schema, None).unwrap();
let arrow_fields = vec![
Field::new("boolean", DataType::Boolean, false),
Field::new("int8", DataType::Int8, false),
Field::new("int16", DataType::Int16, false),
Field::new("uint8", DataType::UInt8, false),
Field::new("uint16", DataType::UInt16, false),
Field::new("int32", DataType::Int32, false),
Field::new("int64", DataType::Int64, false),
Field::new("double", DataType::Float64, true),
Field::new("float", DataType::Float32, true),
Field::new("string", DataType::Utf8, true),
Field::new("string_2", DataType::Utf8, true),
];
assert_eq!(&arrow_fields, converted_arrow_schema.fields());
}
#[test]
fn test_byte_array_fields() {
let message_type = "
message test_schema {
REQUIRED BYTE_ARRAY binary;
REQUIRED FIXED_LEN_BYTE_ARRAY (20) fixed_binary;
}
";
let parquet_group_type = parse_message_type(message_type).unwrap();
let parquet_schema = SchemaDescriptor::new(Arc::new(parquet_group_type));
let converted_arrow_schema =
parquet_to_arrow_schema(&parquet_schema, None).unwrap();
let arrow_fields = vec![
Field::new("binary", DataType::Binary, false),
Field::new("fixed_binary", DataType::FixedSizeBinary(20), false),
];
assert_eq!(&arrow_fields, converted_arrow_schema.fields());
}
#[test]
fn test_duplicate_fields() {
let message_type = "
message test_schema {
REQUIRED BOOLEAN boolean;
REQUIRED INT32 int8 (INT_8);
}
";
let parquet_group_type = parse_message_type(message_type).unwrap();
let parquet_schema = SchemaDescriptor::new(Arc::new(parquet_group_type));
let converted_arrow_schema =
parquet_to_arrow_schema(&parquet_schema, None).unwrap();
let arrow_fields = vec![
Field::new("boolean", DataType::Boolean, false),
Field::new("int8", DataType::Int8, false),
];
assert_eq!(&arrow_fields, converted_arrow_schema.fields());
let converted_arrow_schema = parquet_to_arrow_schema_by_columns(
&parquet_schema,
ProjectionMask::all(),
None,
)
.unwrap();
assert_eq!(&arrow_fields, converted_arrow_schema.fields());
}
#[test]
fn test_parquet_lists() {
let mut arrow_fields = Vec::new();
// LIST encoding example taken from parquet-format/LogicalTypes.md
let message_type = "
message test_schema {
REQUIRED GROUP my_list (LIST) {
REPEATED GROUP list {
OPTIONAL BINARY element (UTF8);
}
}
OPTIONAL GROUP my_list (LIST) {
REPEATED GROUP list {
REQUIRED BINARY element (UTF8);
}
}
OPTIONAL GROUP array_of_arrays (LIST) {
REPEATED GROUP list {
REQUIRED GROUP element (LIST) {
REPEATED GROUP list {
REQUIRED INT32 element;
}
}
}
}
OPTIONAL GROUP my_list (LIST) {
REPEATED GROUP element {
REQUIRED BINARY str (UTF8);
}
}
OPTIONAL GROUP my_list (LIST) {
REPEATED INT32 element;
}
OPTIONAL GROUP my_list (LIST) {
REPEATED GROUP element {
REQUIRED BINARY str (UTF8);
REQUIRED INT32 num;
}
}
OPTIONAL GROUP my_list (LIST) {
REPEATED GROUP array {
REQUIRED BINARY str (UTF8);
}
}
OPTIONAL GROUP my_list (LIST) {
REPEATED GROUP my_list_tuple {
REQUIRED BINARY str (UTF8);
}
}
REPEATED INT32 name;
}
";
// // List<String> (list non-null, elements nullable)
// required group my_list (LIST) {
// repeated group list {
// optional binary element (UTF8);
// }
// }
{
arrow_fields.push(Field::new(
"my_list",
DataType::List(Box::new(Field::new("element", DataType::Utf8, true))),
false,
));
}
// // List<String> (list nullable, elements non-null)
// optional group my_list (LIST) {
// repeated group list {
// required binary element (UTF8);
// }
// }
{
arrow_fields.push(Field::new(
"my_list",
DataType::List(Box::new(Field::new("element", DataType::Utf8, false))),
true,
));
}
// Element types can be nested structures. For example, a list of lists:
//
// // List<List<Integer>>
// optional group array_of_arrays (LIST) {
// repeated group list {
// required group element (LIST) {
// repeated group list {
// required int32 element;
// }
// }
// }
// }
{
let arrow_inner_list =
DataType::List(Box::new(Field::new("element", DataType::Int32, false)));
arrow_fields.push(Field::new(
"array_of_arrays",
DataType::List(Box::new(Field::new("element", arrow_inner_list, false))),
true,
));
}
// // List<String> (list nullable, elements non-null)
// optional group my_list (LIST) {
// repeated group element {
// required binary str (UTF8);
// };
// }
{
arrow_fields.push(Field::new(
"my_list",
DataType::List(Box::new(Field::new("str", DataType::Utf8, false))),
true,
));
}
// // List<Integer> (nullable list, non-null elements)
// optional group my_list (LIST) {
// repeated int32 element;
// }
{
arrow_fields.push(Field::new(
"my_list",
DataType::List(Box::new(Field::new("element", DataType::Int32, false))),
true,
));
}
// // List<Tuple<String, Integer>> (nullable list, non-null elements)
// optional group my_list (LIST) {
// repeated group element {
// required binary str (UTF8);
// required int32 num;
// };
// }
{
let arrow_struct = DataType::Struct(vec![
Field::new("str", DataType::Utf8, false),
Field::new("num", DataType::Int32, false),
]);
arrow_fields.push(Field::new(
"my_list",
DataType::List(Box::new(Field::new("element", arrow_struct, false))),
true,
));
}
// // List<OneTuple<String>> (nullable list, non-null elements)
// optional group my_list (LIST) {
// repeated group array {
// required binary str (UTF8);
// };
// }
// Special case: group is named array
{
let arrow_struct =
DataType::Struct(vec![Field::new("str", DataType::Utf8, false)]);
arrow_fields.push(Field::new(
"my_list",
DataType::List(Box::new(Field::new("array", arrow_struct, false))),
true,
));
}
// // List<OneTuple<String>> (nullable list, non-null elements)
// optional group my_list (LIST) {
// repeated group my_list_tuple {
// required binary str (UTF8);
// };
// }
// Special case: group named ends in _tuple
{
let arrow_struct =
DataType::Struct(vec![Field::new("str", DataType::Utf8, false)]);
arrow_fields.push(Field::new(
"my_list",
DataType::List(Box::new(Field::new(
"my_list_tuple",
arrow_struct,
false,
))),
true,
));
}
// One-level encoding: Only allows required lists with required cells
// repeated value_type name
{
arrow_fields.push(Field::new(
"name",
DataType::List(Box::new(Field::new("name", DataType::Int32, false))),
false,
));
}
let parquet_group_type = parse_message_type(message_type).unwrap();
let parquet_schema = SchemaDescriptor::new(Arc::new(parquet_group_type));
let converted_arrow_schema =
parquet_to_arrow_schema(&parquet_schema, None).unwrap();
let converted_fields = converted_arrow_schema.fields();
assert_eq!(arrow_fields.len(), converted_fields.len());
for i in 0..arrow_fields.len() {
assert_eq!(arrow_fields[i], converted_fields[i], "{}", i);
}
}
#[test]
fn test_parquet_list_nullable() {
let mut arrow_fields = Vec::new();
let message_type = "
message test_schema {
REQUIRED GROUP my_list1 (LIST) {
REPEATED GROUP list {
OPTIONAL BINARY element (UTF8);
}
}
OPTIONAL GROUP my_list2 (LIST) {
REPEATED GROUP list {
REQUIRED BINARY element (UTF8);
}
}
REQUIRED GROUP my_list3 (LIST) {
REPEATED GROUP list {
REQUIRED BINARY element (UTF8);
}
}
}
";
// // List<String> (list non-null, elements nullable)
// required group my_list1 (LIST) {
// repeated group list {
// optional binary element (UTF8);
// }
// }
{
arrow_fields.push(Field::new(
"my_list1",
DataType::List(Box::new(Field::new("element", DataType::Utf8, true))),
false,
));
}
// // List<String> (list nullable, elements non-null)
// optional group my_list2 (LIST) {
// repeated group list {
// required binary element (UTF8);
// }
// }
{
arrow_fields.push(Field::new(
"my_list2",
DataType::List(Box::new(Field::new("element", DataType::Utf8, false))),
true,
));
}
// // List<String> (list non-null, elements non-null)
// repeated group my_list3 (LIST) {
// repeated group list {
// required binary element (UTF8);
// }
// }
{
arrow_fields.push(Field::new(
"my_list3",
DataType::List(Box::new(Field::new("element", DataType::Utf8, false))),
false,
));
}
let parquet_group_type = parse_message_type(message_type).unwrap();
let parquet_schema = SchemaDescriptor::new(Arc::new(parquet_group_type));
let converted_arrow_schema =
parquet_to_arrow_schema(&parquet_schema, None).unwrap();
let converted_fields = converted_arrow_schema.fields();
assert_eq!(arrow_fields.len(), converted_fields.len());
for i in 0..arrow_fields.len() {
assert_eq!(arrow_fields[i], converted_fields[i]);
}
}
#[test]
fn test_parquet_maps() {
let mut arrow_fields = Vec::new();
// LIST encoding example taken from parquet-format/LogicalTypes.md
let message_type = "
message test_schema {
REQUIRED group my_map1 (MAP) {
REPEATED group key_value {
REQUIRED binary key (UTF8);
OPTIONAL int32 value;
}
}
OPTIONAL group my_map2 (MAP) {
REPEATED group map {
REQUIRED binary str (UTF8);
REQUIRED int32 num;
}
}
OPTIONAL group my_map3 (MAP_KEY_VALUE) {
REPEATED group map {
REQUIRED binary key (UTF8);
OPTIONAL int32 value;
}
}
}
";
// // Map<String, Integer>
// required group my_map (MAP) {
// repeated group key_value {
// required binary key (UTF8);
// optional int32 value;
// }
// }
{
arrow_fields.push(Field::new(
"my_map1",
DataType::Map(
Box::new(Field::new(
"key_value",
DataType::Struct(vec![
Field::new("key", DataType::Utf8, false),
Field::new("value", DataType::Int32, true),
]),
false,
)),
false,
),
false,
));
}
// // Map<String, Integer> (nullable map, non-null values)
// optional group my_map (MAP) {
// repeated group map {
// required binary str (UTF8);
// required int32 num;
// }
// }
{
arrow_fields.push(Field::new(
"my_map2",
DataType::Map(
Box::new(Field::new(
"map",
DataType::Struct(vec![
Field::new("str", DataType::Utf8, false),
Field::new("num", DataType::Int32, false),
]),
false, // (#1697)
)),
false,
),
true,
));
}
// // Map<String, Integer> (nullable map, nullable values)
// optional group my_map (MAP_KEY_VALUE) {
// repeated group map {
// required binary key (UTF8);
// optional int32 value;
// }
// }
{
arrow_fields.push(Field::new(
"my_map3",
DataType::Map(
Box::new(Field::new(
"map",
DataType::Struct(vec![
Field::new("key", DataType::Utf8, false),
Field::new("value", DataType::Int32, true),
]),
false, // (#1697)
)),
false,
),
true,
));
}
let parquet_group_type = parse_message_type(message_type).unwrap();
let parquet_schema = SchemaDescriptor::new(Arc::new(parquet_group_type));
let converted_arrow_schema =
parquet_to_arrow_schema(&parquet_schema, None).unwrap();
let converted_fields = converted_arrow_schema.fields();
assert_eq!(arrow_fields.len(), converted_fields.len());
for i in 0..arrow_fields.len() {
assert_eq!(arrow_fields[i], converted_fields[i]);
}
}
#[test]
fn test_nested_schema() {
let mut arrow_fields = Vec::new();
{
let group1_fields = vec![
Field::new("leaf1", DataType::Boolean, false),
Field::new("leaf2", DataType::Int32, false),
];
let group1_struct =