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/**
* @file quickstart_sparse.cc
*
* @section LICENSE
*
* The MIT License
*
* @copyright Copyright (c) 2018-2020 TileDB, Inc.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*
* @section DESCRIPTION
*
* When run, this program will create a simple 2D sparse array, write some data
* to it, and read a slice of the data back.
*/
#include <iostream>
#include <tiledb/tiledb>
using namespace tiledb;
// Name of array.
std::string array_name("quickstart_sparse_array");
void create_array() {
// Create a TileDB context.
Context ctx;
// The array will be 4x4 with dimensions "rows" and "cols", with domain [1,4].
Domain domain(ctx);
domain.add_dimension(Dimension::create<int>(ctx, "rows", {{1, 4}}, 4))
.add_dimension(Dimension::create<int>(ctx, "cols", {{1, 4}}, 4));
// The array will be sparse.
ArraySchema schema(ctx, TILEDB_SPARSE);
schema.set_domain(domain).set_order({{TILEDB_ROW_MAJOR, TILEDB_ROW_MAJOR}});
// Add a single attribute "a" so each (i,j) cell can store an integer.
schema.add_attribute(Attribute::create<int>(ctx, "a"));
// Create the (empty) array on disk.
Array::create(array_name, schema);
}
void write_array() {
Context ctx;
// Write some simple data to cells (1, 1), (2, 4) and (2, 3).
std::vector<int> coords_rows = {1, 2, 2};
std::vector<int> coords_cols = {1, 4, 3};
std::vector<int> data = {1, 2, 3};
// Open the array for writing and create the query.
Array array(ctx, array_name, TILEDB_WRITE);
Query query(ctx, array, TILEDB_WRITE);
query.set_layout(TILEDB_UNORDERED)
.set_buffer("a", data)
.set_buffer("rows", coords_rows)
.set_buffer("cols", coords_cols);
// Perform the write and close the array.
query.submit();
array.close();
}
void read_array() {
Context ctx;
// Prepare the array for reading
Array array(ctx, array_name, TILEDB_READ);
// Slice only rows 1, 2 and cols 2, 3, 4
const std::vector<int> subarray = {1, 2, 2, 4};
// Prepare the vector that will hold the result.
// We take an upper bound on the result size, as we do not
// know a priori how big it is (since the array is sparse)
std::vector<int> data(3);
std::vector<int> coords_rows(3);
std::vector<int> coords_cols(3);
// Prepare the query
Query query(ctx, array, TILEDB_READ);
query.set_subarray(subarray)
.set_layout(TILEDB_ROW_MAJOR)
.set_buffer("a", data)
.set_buffer("rows", coords_rows)
.set_buffer("cols", coords_cols);
// Submit the query and close the array.
query.submit();
array.close();
// Print out the results.
auto result_num = (int)query.result_buffer_elements()["a"].second;
for (int r = 0; r < result_num; r++) {
int i = coords_rows[r];
int j = coords_cols[r];
int a = data[r];
std::cout << "Cell (" << i << ", " << j << ") has data " << a << "\n";
}
}
int main() {
Context ctx;
if (Object::object(ctx, array_name).type() != Object::Type::Array) {
create_array();
write_array();
}
read_array();
return 0;
}
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