- class ray.data.block.BlockAccessor[source]#
Provides accessor methods for a specific block.
Ideally, we wouldn’t need a separate accessor classes for blocks. However, this is needed if we want to support storing
pyarrow.Tabledirectly as a top-level Ray object, without a wrapping class (issue #17186).
There are three types of block accessors:
SimpleBlockAccessor, which operates over a plain Python list,
DeveloperAPI: This API may change across minor Ray releases.
aggregate_combined_blocks(blocks, key, agg)
Aggregate partially combined and sorted blocks.
Create a block from user-facing data formats.
Create a builder for this block type.
Combine rows with the same key into an accumulator.
Create a block accessor for the given block.
Create a metadata object from this block.
Iterate over the rows of this block.
merge_sorted_blocks(blocks, key, descending)
Return a sorted block by merging a list of sorted blocks.
Return the number of rows contained in this block.
Randomly shuffle this block.
Return a random sample of items from this block.
Return the Python type or pyarrow schema of this block.
Return a new block containing the provided columns.
Return the approximate size in bytes of this block.
slice(start, end, copy)
Return a slice of this block.
sort_and_partition(boundaries, key, descending)
Return a list of sorted partitions of this block.
Return a new block containing the provided row indices.
Convert this block into an Arrow table.
Convert this block into the provided batch format.
Return the base block that this accessor wraps.
Return the default data format for this accessor.
Convert this block (or columns of block) into a NumPy ndarray.
Convert this block into a Pandas dataframe.
Zip this block with another block of the same type and size.