diff --git a/arrow/format-0ed34c83.patch b/arrow/format-0ed34c83.patch deleted file mode 100644 index 5da0a0c51f00..000000000000 --- a/arrow/format-0ed34c83.patch +++ /dev/null @@ -1,220 +0,0 @@ -// 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. - -diff --git a/format/Message.fbs b/format/Message.fbs -index 1a7e0dfff..f1c18d765 100644 ---- a/format/Message.fbs -+++ b/format/Message.fbs -@@ -28,7 +28,7 @@ namespace org.apache.arrow.flatbuf; - /// Metadata about a field at some level of a nested type tree (but not - /// its children). - /// --/// For example, a List with values [[1, 2, 3], null, [4], [5, 6], null] -+/// For example, a List with values `[[1, 2, 3], null, [4], [5, 6], null]` - /// would have {length: 5, null_count: 2} for its List node, and {length: 6, - /// null_count: 0} for its Int16 node, as separate FieldNode structs - struct FieldNode { -diff --git a/format/Schema.fbs b/format/Schema.fbs -index 3b37e5d85..3b00dd478 100644 ---- a/format/Schema.fbs -+++ b/format/Schema.fbs -@@ -110,10 +110,11 @@ table FixedSizeList { - /// not enforced. - /// - /// Map -+/// ```text - /// - child[0] entries: Struct - /// - child[0] key: K - /// - child[1] value: V --/// -+/// ``` - /// Neither the "entries" field nor the "key" field may be nullable. - /// - /// The metadata is structured so that Arrow systems without special handling -@@ -129,7 +130,7 @@ enum UnionMode:short { Sparse, Dense } - /// A union is a complex type with children in Field - /// By default ids in the type vector refer to the offsets in the children - /// optionally typeIds provides an indirection between the child offset and the type id --/// for each child typeIds[offset] is the id used in the type vector -+/// for each child `typeIds[offset]` is the id used in the type vector - table Union { - mode: UnionMode; - typeIds: [ int ]; // optional, describes typeid of each child. -diff --git a/format/SparseTensor.fbs b/format/SparseTensor.fbs -index 3fe8a7582..a6fd2f9e7 100644 ---- a/format/SparseTensor.fbs -+++ b/format/SparseTensor.fbs -@@ -37,21 +37,21 @@ namespace org.apache.arrow.flatbuf; - /// - /// For example, let X be a 2x3x4x5 tensor, and it has the following - /// 6 non-zero values: --/// -+/// ```text - /// X[0, 1, 2, 0] := 1 - /// X[1, 1, 2, 3] := 2 - /// X[0, 2, 1, 0] := 3 - /// X[0, 1, 3, 0] := 4 - /// X[0, 1, 2, 1] := 5 - /// X[1, 2, 0, 4] := 6 --/// -+/// ``` - /// In COO format, the index matrix of X is the following 4x6 matrix: --/// -+/// ```text - /// [[0, 0, 0, 0, 1, 1], - /// [1, 1, 1, 2, 1, 2], - /// [2, 2, 3, 1, 2, 0], - /// [0, 1, 0, 0, 3, 4]] --/// -+/// ``` - /// When isCanonical is true, the indices is sorted in lexicographical order - /// (row-major order), and it does not have duplicated entries. Otherwise, - /// the indices may not be sorted, or may have duplicated entries. -@@ -86,26 +86,27 @@ table SparseMatrixIndexCSX { - - /// indptrBuffer stores the location and size of indptr array that - /// represents the range of the rows. -- /// The i-th row spans from indptr[i] to indptr[i+1] in the data. -+ /// The i-th row spans from `indptr[i]` to `indptr[i+1]` in the data. - /// The length of this array is 1 + (the number of rows), and the type - /// of index value is long. - /// - /// For example, let X be the following 6x4 matrix: -- /// -+ /// ```text - /// X := [[0, 1, 2, 0], - /// [0, 0, 3, 0], - /// [0, 4, 0, 5], - /// [0, 0, 0, 0], - /// [6, 0, 7, 8], - /// [0, 9, 0, 0]]. -- /// -+ /// ``` - /// The array of non-zero values in X is: -- /// -+ /// ```text - /// values(X) = [1, 2, 3, 4, 5, 6, 7, 8, 9]. -- /// -+ /// ``` - /// And the indptr of X is: -- /// -+ /// ```text - /// indptr(X) = [0, 2, 3, 5, 5, 8, 10]. -+ /// ``` - indptrBuffer: Buffer (required); - - /// The type of values in indicesBuffer -@@ -116,9 +117,9 @@ table SparseMatrixIndexCSX { - /// The type of index value is long. - /// - /// For example, the indices of the above X is: -- /// -+ /// ```text - /// indices(X) = [1, 2, 2, 1, 3, 0, 2, 3, 1]. -- /// -+ /// ``` - /// Note that the indices are sorted in lexicographical order for each row. - indicesBuffer: Buffer (required); - } -@@ -126,7 +127,7 @@ table SparseMatrixIndexCSX { - /// Compressed Sparse Fiber (CSF) sparse tensor index. - table SparseTensorIndexCSF { - /// CSF is a generalization of compressed sparse row (CSR) index. -- /// See [smith2017knl]: http://shaden.io/pub-files/smith2017knl.pdf -+ /// See [smith2017knl](http://shaden.io/pub-files/smith2017knl.pdf) - /// - /// CSF index recursively compresses each dimension of a tensor into a set - /// of prefix trees. Each path from a root to leaf forms one tensor -@@ -135,7 +136,7 @@ table SparseTensorIndexCSF { - /// - /// For example, let X be a 2x3x4x5 tensor and let it have the following - /// 8 non-zero values: -- /// -+ /// ```text - /// X[0, 0, 0, 1] := 1 - /// X[0, 0, 0, 2] := 2 - /// X[0, 1, 0, 0] := 3 -@@ -144,9 +145,9 @@ table SparseTensorIndexCSF { - /// X[1, 1, 1, 0] := 6 - /// X[1, 1, 1, 1] := 7 - /// X[1, 1, 1, 2] := 8 -- /// -+ /// ``` - /// As a prefix tree this would be represented as: -- /// -+ /// ```text - /// 0 1 - /// / \ | - /// 0 1 1 -@@ -154,24 +155,24 @@ table SparseTensorIndexCSF { - /// 0 0 1 1 - /// /| /| | /| | - /// 1 2 0 2 0 0 1 2 -- -+ /// ``` - /// The type of values in indptrBuffers - indptrType: Int (required); - - /// indptrBuffers stores the sparsity structure. - /// Each two consecutive dimensions in a tensor correspond to a buffer in -- /// indptrBuffers. A pair of consecutive values at indptrBuffers[dim][i] -- /// and indptrBuffers[dim][i + 1] signify a range of nodes in -- /// indicesBuffers[dim + 1] who are children of indicesBuffers[dim][i] node. -+ /// indptrBuffers. A pair of consecutive values at `indptrBuffers[dim][i]` -+ /// and `indptrBuffers[dim][i + 1]` signify a range of nodes in -+ /// `indicesBuffers[dim + 1]` who are children of `indicesBuffers[dim][i]` node. - /// - /// For example, the indptrBuffers for the above X is: -- /// -+ /// ```text - /// indptrBuffer(X) = [ - /// [0, 2, 3], - /// [0, 1, 3, 4], - /// [0, 2, 4, 5, 8] - /// ]. -- /// -+ /// ``` - indptrBuffers: [Buffer] (required); - - /// The type of values in indicesBuffers -@@ -180,22 +181,22 @@ table SparseTensorIndexCSF { - /// indicesBuffers stores values of nodes. - /// Each tensor dimension corresponds to a buffer in indicesBuffers. - /// For example, the indicesBuffers for the above X is: -- /// -+ /// ```text - /// indicesBuffer(X) = [ - /// [0, 1], - /// [0, 1, 1], - /// [0, 0, 1, 1], - /// [1, 2, 0, 2, 0, 0, 1, 2] - /// ]. -- /// -+ /// ``` - indicesBuffers: [Buffer] (required); - - /// axisOrder stores the sequence in which dimensions were traversed to - /// produce the prefix tree. - /// For example, the axisOrder for the above X is: -- /// -+ /// ```text - /// axisOrder(X) = [0, 1, 2, 3]. -- /// -+ /// ``` - axisOrder: [int] (required); - } -