Writing.md

Writing Parquet files

The low-level ParquetSharp API provides the ParquetSharp.ParquetFileWriter class for writing Parquet files.

Defining the schema

When writing a Parquet file, you must define the schema up-front, which specifies all of the columns in the file along with their names and types.

ParquetSharp provides a convenient higher level API for defining the schema as an array of ParquetSharp.Column objects. A Column can be constructed using only a name and a type parameter that is used to determine the logical Parquet type to write:

var columns = new Column[]
{
    new Column<DateTime>("Timestamp"),
    new Column<int>("ObjectId"),
    new Column<float>("Value")
};

using var file = new ParquetFileWriter("float_timeseries.parquet", columns);

The schema can also be defined using a graph of ParquetSharp.Schema.Node instances, starting from a root ParquetSharp.Schema.GroupNode. For concrete examples, see How to write a file with nested columns.

Overriding logical types

For more control over how values are represented in the Parquet file, you can pass a ParquetSharp.LogicalType instance as the logicalTypeOverride parameter of the Column constructor.

For example, you may wish to write times or timestamps with millisecond resolution rather than the default microsecond resolution:

var timestampColumn = new Column<DateTime>(
        "Timestamp", LogicalType.Timestamp(isAdjustedToUtc: true, timeUnit: TimeUnit.Millis));
var timeColumn = new Column<TimeSpan>(
        "Time", LogicalType.Time(isAdjustedToUtc: true, timeUnit: TimeUnit.Millis));

When writing decimal values, you must provide a logicalTypeOverride to define the precision and scale type parameters. Currently the precision must be 29.

var decimalColumn = new Column<decimal>("Values", LogicalType.Decimal(precision: 29, scale: 3);

Metadata

As well as defining the file schema, you may optionally provide key-value metadata that is stored in the file when creating a ParquetSharp.ParquetFileWriter:

var metadata = new Dictionary<string, string>
{
    {"foo": "bar"},
};
using var file = new ParquetFileWriter("float_timeseries.parquet", columns, keyValueMetadata: metadata);

ParquetFileWriter constructor overrides are provided that allow specifying the type of compression to use, or for more fine-grained control over how files are written, you can provide a ParquetSharp.WriterProperties instance, which can be constructed with a ParquetSharp.WriterPropertiesBuilder. This allows defining the compression and encoding on a per-column basis for example, or configuring file encryption.

Writing to a stream

As well as writing to a file path, ParquetSharp supports writing to a .NET System.IO.Stream using a ParquetSharp.IO.ManagedOutputStream:

using (var stream = new FileStream("float_timeseries.parquet", FileMode.Create))
{
    using var writer = new IO.ManagedOutputStream(stream);
    using var fileWriter = new ParquetFileWriter(writer, columns);
}

Writing column data

Parquet data is written in batches of column data named row groups. To begin writing data, you first create a new row group:

using RowGroupWriter rowGroup = file.AppendRowGroup();

You must then write each column's data in the order in which the columns are defined in the schema:

using (var timestampWriter = rowGroup.NextColumn().LogicalWriter<DateTime>())
{
    timestampWriter.WriteBatch(timestamps);
}
using (var objectIdWriter = rowGroup.NextColumn().LogicalWriter<int>())
{
    objectIdWriter.WriteBatch(objectIds);
}
using (var valueWriter = rowGroup.NextColumn().LogicalWriter<float>())
{
    valueWriter.WriteBatch(values);
}

Once all data for a row group has been written and the ParquetSharp.RowGroupWriter disposed, you may append another row group to the file and repeat the row group writing process.

The NextColumn method of RowGroupWriter returns a ParquetSharp.ColumnWriter, which writes physical values to the file, and can write definition level and repetition level data to support nullable and array values.

Using LogicalColumnWriter

Rather than working with a ColumnWriter directly, it's usually more convenient to create a ParquetSharp.LogicalColumnWriter with the ColumnWriter.LogicalWriter<TElement> method. This allows writing an array or ReadOnlySpan of TElement to the column data, where TElement is the .NET type corresponding to the column's logical element type.

There is also a ColumnWriter.LogicalWriterOverride method, which supports writing data using a different type to the default .NET type corresponding to the column's logical type. For more information on how to use this, see the type factories documentation.

If you don't know ahead of time the column types that will be written, you can implement the ILogicalColumnWriterVisitor<TReturn> interface to handle writing data in a type-safe way:

sealed class ExampleWriter : ILogicalColumnWriterVisitor<bool>
{
    public bool OnLogicalColumnWriter<TValue>(LogicalColumnWriter<TValue> columnWriter)
    {
        TValue[] values = GetValues();
        columnWriter.WriteBatch(values);
        return true;
    }
}

using RowGroupWriter rowGroup = file.AppendRowGroup();
for (int columnIndex = 0; columnIndex < file.NumColumns; ++columnIndex)
{
    using var columnWriter = rowGroup.NextColumn();
    using var logicalWriter = columnWriter.LogicalWriter();
    var returnVal = logicalWriter.Apply(new ExampleWriter());
}

Closing the ParquetFileWriter

Note that it's important to explicitly call Close on the ParquetFileWriter when writing is complete, as otherwise any errors encountered when writing may be silently ignored:

file.Close();