/// <summary>
/// Returns an <see cref="IEnumerable{RecordBatch}"/> without copying data
/// </summary>
public IEnumerable <RecordBatch> ToArrowRecordBatches()
{
Apache.Arrow.Schema.Builder schemaBuilder = new Apache.Arrow.Schema.Builder();
int columnCount = Columns.Count;
for (int i = 0; i < columnCount; i++)
{
DataFrameColumn column = Columns[i];
Field field = column.GetArrowField();
schemaBuilder.Field(field);
}
Schema schema = schemaBuilder.Build();
List <Apache.Arrow.Array> arrays = new List <Apache.Arrow.Array>();
int recordBatchLength = Int32.MaxValue;
int numberOfRowsInThisRecordBatch = (int)Math.Min(recordBatchLength, RowCount);
long numberOfRowsProcessed = 0;
// Sometimes .NET for Spark passes in DataFrames with no rows. In those cases, we just return a RecordBatch with the right Schema and no rows
do
{
for (int i = 0; i < columnCount; i++)
{
DataFrameColumn column = Columns[i];
numberOfRowsInThisRecordBatch = (int)Math.Min(numberOfRowsInThisRecordBatch, column.GetMaxRecordBatchLength(numberOfRowsProcessed));
}
for (int i = 0; i < columnCount; i++)
{
DataFrameColumn column = Columns[i];
arrays.Add(column.ToArrowArray(numberOfRowsProcessed, numberOfRowsInThisRecordBatch));
}
numberOfRowsProcessed += numberOfRowsInThisRecordBatch;
yield return(new RecordBatch(schema, arrays, numberOfRowsInThisRecordBatch));
} while (numberOfRowsProcessed < RowCount);
}