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# Apache Arrow .NET

An implementation of Arrow targeting .NET.

See our current [feature matrix](https://github.com/apache/arrow/blob/main/docs/source/status.rst)
for currently available features.

## Implementation

- Arrow specification 1.0.0. (Support for reading 0.11+.)
- C# 11
- .NET Standard 2.0, .NET 6.0, .NET 8.0 and .NET Framework 4.6.2
- Asynchronous I/O
- Uses modern .NET runtime features such as **Span&lt;T&gt;**, **Memory&lt;T&gt;**, **MemoryManager&lt;T&gt;**, and **System.Buffers** primitives for memory allocation, memory storage, and fast serialization.
- Uses **Acyclic Visitor Pattern** for array types and arrays to facilitate serialization, record batch traversal, and format growth.

## Known Issues

- Cannot read Arrow files containing tensors.
- Cannot easily modify allocation strategy without implementing a custom memory pool. All allocations are currently 64-byte aligned and padded to 8-bytes.
- Default memory allocation strategy uses an over-allocation strategy with pointer fixing, which results in significant memory overhead for small buffers. A buffer that requires a single byte for storage may be backed by an allocation of up to 64-bytes to satisfy alignment requirements.
- There are currently few builder APIs available for specific array types. Arrays must be built manually with an arrow buffer builder abstraction.
- FlatBuffer code generation is not included in the build process.
- Serialization implementation does not perform exhaustive validation checks during deserialization in every scenario.
- Throws exceptions with vague, inconsistent, or non-localized messages in many situations
- Throws exceptions that are non-specific to the Arrow implementation in some circumstances where it probably should (eg. does not throw ArrowException exceptions)
- Lack of code documentation
- Lack of usage examples

## Usage

Example demonstrating reading [RecordBatches](xref:Apache.Arrow.RecordBatch) from an Arrow IPC file using an
[ArrowFileReader](xref:Apache.Arrow.Ipc.ArrowFileReader):

    using System.Diagnostics;
    using System.IO;
    using System.Threading.Tasks;
    using Apache.Arrow;
    using Apache.Arrow.Ipc;

    public static async Task<RecordBatch> ReadArrowAsync(string filename)
    {
        using (var stream = File.OpenRead(filename))
        using (var reader = new ArrowFileReader(stream))
        {
            var recordBatch = await reader.ReadNextRecordBatchAsync();
            Debug.WriteLine("Read record batch with {0} column(s)", recordBatch.ColumnCount);
            return recordBatch;
        }
    }


## Status

### Memory Management

- Allocations are 64-byte aligned and padded to 8-bytes.
- Allocations are automatically garbage collected

### Arrays

#### Primitive Types

- [Int8](xref:Apache.Arrow.Types.Int8Type), [Int16](xref:Apache.Arrow.Types.Int16Type), [Int32](xref:Apache.Arrow.Types.Int32Type), [Int64](xref:Apache.Arrow.Types.Int64Type)
- [UInt8](xref:Apache.Arrow.Types.UInt8Type), [UInt16](xref:Apache.Arrow.Types.UInt16Type), [UInt32](xref:Apache.Arrow.Types.UInt32Type), [UInt64](xref:Apache.Arrow.Types.UInt64Type)
- [Float](xref:Apache.Arrow.Types.FloatType), [Double](xref:Apache.Arrow.Types.DoubleType), [Half-float](xref:Apache.Arrow.Types.HalfFloatType) (.NET 6+)
- [Binary](xref:Apache.Arrow.Types.BinaryType) (variable-length)
- [String](xref:Apache.Arrow.Types.StringType) (utf-8)
- [Null](xref:Apache.Arrow.Types.NullType)

#### Parametric Types

- [Timestamp](xref:Apache.Arrow.Types.TimestampType)
- [Date32](xref:Apache.Arrow.Types.Date32Type), [Date64](xref:Apache.Arrow.Types.Date64Type)
- [Decimal32](xref:Apache.Arrow.Types.Decimal32Type), [Decimal64](xref:Apache.Arrow.Types.Decimal64Type), [Decimal128](xref:Apache.Arrow.Types.Decimal128Type), [Decimal256](xref:Apache.Arrow.Types.Decimal256Type)
- [Time32](xref:Apache.Arrow.Types.Time32Type), [Time64](xref:Apache.Arrow.Types.Time64Type)
- [Binary](xref:Apache.Arrow.Types.BinaryType) (fixed-length)
- [List](xref:Apache.Arrow.Types.ListType)
- [Struct](xref:Apache.Arrow.Types.StructType)
- [Union](xref:Apache.Arrow.Types.UnionType)
- [Map](xref:Apache.Arrow.Types.MapType)
- [Duration](xref:Apache.Arrow.Types.DurationType)
- [Interval](xref:Apache.Arrow.Types.IntervalType)

#### Type Metadata

- Data Types
- [Fields](xref:Apache.Arrow.Field)
- [Schema](xref:Apache.Arrow.Schema)

#### Serialization

- File [Reader](xref:Apache.Arrow.Ipc.ArrowFileReader) and [Writer](xref:Apache.Arrow.Ipc.ArrowFileWriter)
- Stream [Reader](xref:Apache.Arrow.Ipc.ArrowStreamReader) and [Writer](xref:Apache.Arrow.Ipc.ArrowStreamWriter)

### IPC Format

#### Compression

- Buffer compression and decompression is supported, but requires installing the `Apache.Arrow.Compression` package.
  When reading compressed data, you must pass an [CompressionCodecFactory](xref:Apache.Arrow.Compression.CompressionCodecFactory)
  instance to the [ArrowFileReader](xref:Apache.Arrow.Ipc.ArrowFileReader) or
  [ArrowStreamReader](xref:Apache.Arrow.Ipc.ArrowStreamReader) constructor, and when writing compressed data a
  [CompressionCodecFactory](xref:Apache.Arrow.Compression.CompressionCodecFactory) must be set in the
  [IpcOptions](xref:Apache.Arrow.Ipc.IpcOptions).
  Alternatively, a custom implementation of [ICompressionCodecFactory](xref:Apache.Arrow.Ipc.ICompressionCodecFactory) can be used.

### Not Implemented

- Serialization
    - Exhaustive validation
- Types
    - Tensor
- Arrays
    - Large Arrays. There are large array types provided to help with interoperability with other libraries,
      but these do not support buffers larger than 2 GiB and an exception will be raised if trying to import an array that is too large.
        - [Large Binary](xref:Apache.Arrow.Types.LargeBinaryType)
        - [Large List](xref:Apache.Arrow.Types.LargeListType)
        - [Large String](xref:Apache.Arrow.Types.LargeStringType)
    - Views
        - [Binary View](xref:Apache.Arrow.Types.BinaryViewType)
        - [List View](xref:Apache.Arrow.Types.ListViewType)
        - [String View](xref:Apache.Arrow.Types.StringViewType)
- Array Operations
    - Equality / Comparison
    - Casting
- Compute
    - There is currently no API available for a compute / kernel abstraction.