blob: 22f7ddfe15d72ed45be2db9d44885ab451a3f8f9 [file] [log] [blame]
/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
Licensed 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.
==============================================================================*/
#include "tensorflow/contrib/bigtable/kernels/bigtable_lib.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/lib/core/refcount.h"
namespace tensorflow {
namespace data {
namespace {
class BigtableRangeKeyDatasetOp : public DatasetOpKernel {
public:
using DatasetOpKernel::DatasetOpKernel;
void MakeDataset(OpKernelContext* ctx, DatasetBase** output) override {
tstring start_key;
OP_REQUIRES_OK(ctx,
ParseScalarArgument<tstring>(ctx, "start_key", &start_key));
tstring end_key;
OP_REQUIRES_OK(ctx, ParseScalarArgument<tstring>(ctx, "end_key", &end_key));
core::RefCountPtr<BigtableTableResource> resource;
OP_REQUIRES_OK(ctx,
LookupResource(ctx, HandleFromInput(ctx, 0), &resource));
*output = new Dataset(ctx, resource.get(), std::move(start_key),
std::move(end_key));
}
private:
class Dataset : public DatasetBase {
public:
explicit Dataset(OpKernelContext* ctx, BigtableTableResource* table,
string start_key, string end_key)
: DatasetBase(DatasetContext(ctx)),
table_(table),
start_key_(std::move(start_key)),
end_key_(std::move(end_key)) {
table_->Ref();
}
~Dataset() override { table_->Unref(); }
std::unique_ptr<IteratorBase> MakeIteratorInternal(
const string& prefix) const override {
return std::unique_ptr<IteratorBase>(
new Iterator({this, strings::StrCat(prefix, "::BigtableRangeKey")}));
}
const DataTypeVector& output_dtypes() const override {
static DataTypeVector* dtypes = new DataTypeVector({DT_STRING});
return *dtypes;
}
const std::vector<PartialTensorShape>& output_shapes() const override {
static std::vector<PartialTensorShape>* shapes =
new std::vector<PartialTensorShape>({{}});
return *shapes;
}
string DebugString() const override {
return "BigtableRangeKeyDatasetOp::Dataset";
}
BigtableTableResource* table() const { return table_; }
Status CheckExternalState() const override {
return errors::FailedPrecondition(DebugString(),
" depends on external state.");
}
protected:
Status AsGraphDefInternal(SerializationContext* ctx,
DatasetGraphDefBuilder* b,
Node** output) const override {
return errors::Unimplemented(DebugString(),
" does not support serialization");
}
private:
class Iterator : public BigtableReaderDatasetIterator<Dataset> {
public:
explicit Iterator(const Params& params)
: BigtableReaderDatasetIterator<Dataset>(params) {}
::google::cloud::bigtable::RowRange MakeRowRange() override {
return ::google::cloud::bigtable::RowRange::Range(dataset()->start_key_,
dataset()->end_key_);
}
::google::cloud::bigtable::Filter MakeFilter() override {
return ::google::cloud::bigtable::Filter::Chain(
::google::cloud::bigtable::Filter::CellsRowLimit(1),
::google::cloud::bigtable::Filter::StripValueTransformer());
}
Status ParseRow(IteratorContext* ctx,
const ::google::cloud::bigtable::Row& row,
std::vector<Tensor>* out_tensors) override {
Tensor output_tensor(ctx->allocator({}), DT_STRING, {});
output_tensor.scalar<tstring>()() = tstring(row.row_key());
out_tensors->emplace_back(std::move(output_tensor));
return Status::OK();
}
};
BigtableTableResource* const table_;
const string start_key_;
const string end_key_;
};
};
REGISTER_KERNEL_BUILDER(Name("BigtableRangeKeyDataset").Device(DEVICE_CPU),
BigtableRangeKeyDatasetOp);
} // namespace
} // namespace data
} // namespace tensorflow