.. Licensed to the Apache Software Foundation (ASF) under one .. or more contributor license agreements. See the NOTICE file .. distributed with this work for additional information .. regarding copyright ownership. The ASF licenses this file .. to you under the Apache License, Version 2.0 (the .. "License"); you may not use this file except in compliance .. with the License. You may obtain a copy of the License at .. http://www.apache.org/licenses/LICENSE-2.0 .. Unless required by applicable law or agreed to in writing, .. software distributed under the License is distributed on an .. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY .. KIND, either express or implied. See the License for the .. specific language governing permissions and limitations .. under the License. Other Data Structures ===================== Our Flatbuffers protocol files have metadata for some other data structures defined to allow other kinds of applications to take advantage of common interprocess communication machinery. These data structures are not considered to be part of the columnar format. An Arrow columnar implementation is not required to implement these types. Tensor (Multi-dimensional Array) -------------------------------- The ``Tensor`` message types provides a way to write a multidimensional array of fixed-size values (such as a NumPy ndarray). When writing a standalone encapsulated tensor message, we use the encapsulated IPC format defined in the :ref:`Columnar Specification `, but additionally align the starting offset of the tensor body to be a multiple of 64 bytes: :: Sparse Tensor ------------- ``SparseTensor`` represents a multidimensional array whose elements are generally almost all zeros. When writing a standalone encapsulated sparse tensor message, we use the encapsulated IPC format defined in the :ref:`Columnar Specification `, but additionally align the starting offsets of the sparse index and the sparse tensor body (if writing to a shared memory region) to be multiples of 64 bytes: :: The contents of the sparse tensor index depends on what kind of sparse format is used.