AlenkaF commented on code in PR #40064:
URL: https://github.com/apache/arrow/pull/40064#discussion_r1508491813
##########
cpp/src/arrow/record_batch.cc:
##########
@@ -247,6 +248,97 @@ Result<std::shared_ptr<StructArray>>
RecordBatch::ToStructArray() const {
/*offset=*/0);
}
+template <typename DataType>
+inline void ConvertColumnsToTensor(const RecordBatch& batch, uint8_t* out) {
+ using CType = typename arrow::TypeTraits<DataType>::CType;
+ auto* out_values = reinterpret_cast<CType*>(out);
+
+ // Loop through all of the columns
+ for (int i = 0; i < batch.num_columns(); ++i) {
+ const auto* in_values = batch.column(i)->data()->GetValues<CType>(1);
+
+ // Copy data of each column
+ memcpy(out_values, in_values, sizeof(CType) * batch.num_rows());
+ out_values += batch.num_rows();
+ } // End loop through columns
+}
+
+Result<std::shared_ptr<Tensor>> RecordBatch::ToTensor(MemoryPool* pool) const {
+ if (num_columns() == 0) {
+ return Status::TypeError(
+ "Conversion to Tensor for RecordBatches without columns/schema is not "
+ "supported.");
+ }
+ const auto& type = column(0)->type();
+ // Check for supported data types
+ if (!is_integer(type->id()) && !is_floating(type->id())) {
+ return Status::TypeError("DataType is not supported: ", type->ToString());
+ }
+ // Check for uniform data type
+ // Check for no validity bitmap of each field
+ for (int i = 0; i < num_columns(); ++i) {
+ if (column(i)->null_count() > 0) {
+ return Status::TypeError("Can only convert a RecordBatch with no
nulls.");
+ }
+ if (column(i)->type() != type) {
Review Comment:
I will work on this in a separate issue, see
https://github.com/apache/arrow/issues/40060.
There is already a working branch, with a diff (compared to this PR's
branch) available here:
https://github.com/apache/arrow/commit/9090b5ca5e7ead83ba0d4145c48189b53b34c70b
There are two separate code paths in the proposed change I linked here, one
for uniform data types and separate for mixed which includes casting.
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