Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/20116#discussion_r159469632
--- Diff:
sql/core/src/main/java/org/apache/spark/sql/vectorized/ColumnarBatch.java ---
@@ -14,26 +14,18 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
-package org.apache.spark.sql.execution.vectorized;
+package org.apache.spark.sql.vectorized;
import java.util.*;
import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.execution.vectorized.MutableColumnarRow;
import org.apache.spark.sql.types.StructType;
/**
- * This class is the in memory representation of rows as they are streamed
through operators. It
- * is designed to maximize CPU efficiency and not storage footprint. Since
it is expected that
- * each operator allocates one of these objects, the storage footprint on
the task is negligible.
- *
- * The layout is a columnar with values encoded in their native format.
Each RowBatch contains
- * a horizontal partitioning of the data, split into columns.
- *
- * The ColumnarBatch supports either on heap or offheap modes with
(mostly) the identical API.
- *
- * TODO:
- * - There are many TODOs for the existing APIs. They should throw a not
implemented exception.
- * - Compaction: The batch and columns should be able to compact based on
a selection vector.
+ * This class is a wrapper of multiple ColumnVectors and represents a
logical table-like data
--- End diff --
How about?
> This class wraps multiple ColumnVectors as a row-wise table
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