final class ColumnarBatch extends AutoCloseable
This class wraps multiple ColumnVectors as a row-wise table. It provides a row view of this batch so that Spark can access the data row by row. Instance of it is meant to be reused during the entire data loading process.
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new
ColumnarBatch(columns: Array[ColumnVector], numRows: Int)
Create a new batch from existing column vectors.
Create a new batch from existing column vectors.
- columns
The columns of this batch
- numRows
The number of rows in this batch
- new ColumnarBatch(columns: Array[ColumnVector])
Value Members
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def
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def
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def
close(): Unit
Called to close all the columns in this batch.
Called to close all the columns in this batch. It is not valid to access the data after calling this. This must be called at the end to clean up memory allocations.
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- ColumnarBatch → AutoCloseable
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def
column(ordinal: Int): ColumnVector
Returns the column at
ordinal. -
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def
getRow(rowId: Int): InternalRow
Returns the row in this batch at
rowId.Returns the row in this batch at
rowId. Returned row is reused across calls. -
def
hashCode(): Int
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notifyAll(): Unit
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def
numCols(): Int
Returns the number of columns that make up this batch.
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def
numRows(): Int
Returns the number of rows for read, including filtered rows.
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def
rowIterator(): Iterator[InternalRow]
Returns an iterator over the rows in this batch.
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def
setNumRows(numRows: Int): Unit
Sets the number of rows in this batch.
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