// 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.

#include "benchmark/benchmark.h"

#include "parquet/column_reader.h"
#include "parquet/column_writer.h"
#include "parquet/file/reader-internal.h"
#include "parquet/file/writer-internal.h"
#include "parquet/util/memory.h"

namespace parquet {

using schema::PrimitiveNode;

namespace benchmark {

std::unique_ptr<Int64Writer> BuildWriter(int64_t output_size, OutputStream* dst,
    ColumnChunkMetaDataBuilder* metadata, ColumnDescriptor* schema,
    const WriterProperties* properties) {
  std::unique_ptr<SerializedPageWriter> pager(
      new SerializedPageWriter(dst, Compression::UNCOMPRESSED, metadata));
  return std::unique_ptr<Int64Writer>(new Int64Writer(
      metadata, std::move(pager), output_size, Encoding::PLAIN, properties));
}

std::shared_ptr<ColumnDescriptor> Int64Schema(Repetition::type repetition) {
  auto node = PrimitiveNode::Make("int64", repetition, Type::INT64);
  return std::make_shared<ColumnDescriptor>(
      node, repetition != Repetition::REQUIRED, repetition == Repetition::REPEATED);
}

void SetBytesProcessed(::benchmark::State& state, Repetition::type repetition) {
  int64_t bytes_processed = state.iterations() * state.range(0) * sizeof(int64_t);
  if (repetition != Repetition::REQUIRED) {
    bytes_processed += state.iterations() * state.range(0) * sizeof(int16_t);
  }
  if (repetition == Repetition::REPEATED) {
    bytes_processed += state.iterations() * state.range(0) * sizeof(int16_t);
  }
  state.SetBytesProcessed(state.iterations() * state.range(0) * sizeof(int16_t));
}

template <Repetition::type repetition>
static void BM_WriteInt64Column(::benchmark::State& state) {
  format::ColumnChunk thrift_metadata;
  std::vector<int64_t> values(state.range(0), 128);
  std::vector<int16_t> definition_levels(state.range(0), 1);
  std::vector<int16_t> repetition_levels(state.range(0), 0);
  std::shared_ptr<ColumnDescriptor> schema = Int64Schema(repetition);
  std::shared_ptr<WriterProperties> properties = default_writer_properties();
  auto metadata = ColumnChunkMetaDataBuilder::Make(
      properties, schema.get(), reinterpret_cast<uint8_t*>(&thrift_metadata));

  while (state.KeepRunning()) {
    InMemoryOutputStream stream;
    std::unique_ptr<Int64Writer> writer = BuildWriter(
        state.range(0), &stream, metadata.get(), schema.get(), properties.get());
    writer->WriteBatch(
        values.size(), definition_levels.data(), repetition_levels.data(), values.data());
    writer->Close();
  }
  SetBytesProcessed(state, repetition);
}

BENCHMARK_TEMPLATE(BM_WriteInt64Column, Repetition::REQUIRED)->Range(1024, 65536);

BENCHMARK_TEMPLATE(BM_WriteInt64Column, Repetition::OPTIONAL)->Range(1024, 65536);

BENCHMARK_TEMPLATE(BM_WriteInt64Column, Repetition::REPEATED)->Range(1024, 65536);

std::unique_ptr<Int64Reader> BuildReader(
    std::shared_ptr<Buffer>& buffer, int64_t num_values, ColumnDescriptor* schema) {
  std::unique_ptr<InMemoryInputStream> source(new InMemoryInputStream(buffer));
  std::unique_ptr<SerializedPageReader> page_reader(
      new SerializedPageReader(std::move(source), num_values, Compression::UNCOMPRESSED));
  return std::unique_ptr<Int64Reader>(new Int64Reader(schema, std::move(page_reader)));
}

template <Repetition::type repetition>
static void BM_ReadInt64Column(::benchmark::State& state) {
  format::ColumnChunk thrift_metadata;
  std::vector<int64_t> values(state.range(0), 128);
  std::vector<int16_t> definition_levels(state.range(0), 1);
  std::vector<int16_t> repetition_levels(state.range(0), 0);
  std::shared_ptr<ColumnDescriptor> schema = Int64Schema(repetition);
  std::shared_ptr<WriterProperties> properties = default_writer_properties();
  auto metadata = ColumnChunkMetaDataBuilder::Make(
      properties, schema.get(), reinterpret_cast<uint8_t*>(&thrift_metadata));

  InMemoryOutputStream stream;
  std::unique_ptr<Int64Writer> writer = BuildWriter(
      state.range(0), &stream, metadata.get(), schema.get(), properties.get());
  writer->WriteBatch(
      values.size(), definition_levels.data(), repetition_levels.data(), values.data());
  writer->Close();

  std::shared_ptr<Buffer> src = stream.GetBuffer();
  std::vector<int64_t> values_out(state.range(1));
  std::vector<int16_t> definition_levels_out(state.range(1));
  std::vector<int16_t> repetition_levels_out(state.range(1));
  while (state.KeepRunning()) {
    std::unique_ptr<Int64Reader> reader = BuildReader(src, state.range(1), schema.get());
    int64_t values_read = 0;
    for (size_t i = 0; i < values.size(); i += values_read) {
      reader->ReadBatch(values_out.size(), definition_levels_out.data(),
          repetition_levels_out.data(), values_out.data(), &values_read);
    }
  }
  SetBytesProcessed(state, repetition);
}

BENCHMARK_TEMPLATE(BM_ReadInt64Column, Repetition::REQUIRED)
    ->RangePair(1024, 65536, 1, 1024);

BENCHMARK_TEMPLATE(BM_ReadInt64Column, Repetition::OPTIONAL)
    ->RangePair(1024, 65536, 1, 1024);

BENCHMARK_TEMPLATE(BM_ReadInt64Column, Repetition::REPEATED)
    ->RangePair(1024, 65536, 1, 1024);

static void BM_RleEncoding(::benchmark::State& state) {
  std::vector<int16_t> levels(state.range(0), 0);
  int64_t n = 0;
  std::generate(
      levels.begin(), levels.end(), [&state, &n] { return (n++ % state.range(1)) == 0; });
  int16_t max_level = 1;
  int64_t rle_size = LevelEncoder::MaxBufferSize(Encoding::RLE, max_level, levels.size());
  auto buffer_rle = std::make_shared<PoolBuffer>();
  PARQUET_THROW_NOT_OK(buffer_rle->Resize(rle_size));

  while (state.KeepRunning()) {
    LevelEncoder level_encoder;
    level_encoder.Init(Encoding::RLE, max_level, levels.size(),
        buffer_rle->mutable_data(), buffer_rle->size());
    level_encoder.Encode(levels.size(), levels.data());
  }
  state.SetBytesProcessed(state.iterations() * state.range(0) * sizeof(int16_t));
  state.SetItemsProcessed(state.iterations() * state.range(0));
}

BENCHMARK(BM_RleEncoding)->RangePair(1024, 65536, 1, 16);

static void BM_RleDecoding(::benchmark::State& state) {
  LevelEncoder level_encoder;
  std::vector<int16_t> levels(state.range(0), 0);
  int64_t n = 0;
  std::generate(
      levels.begin(), levels.end(), [&state, &n] { return (n++ % state.range(1)) == 0; });
  int16_t max_level = 1;
  int64_t rle_size = LevelEncoder::MaxBufferSize(Encoding::RLE, max_level, levels.size());
  auto buffer_rle = std::make_shared<PoolBuffer>();
  PARQUET_THROW_NOT_OK(buffer_rle->Resize(rle_size + sizeof(int32_t)));
  level_encoder.Init(Encoding::RLE, max_level, levels.size(),
      buffer_rle->mutable_data() + sizeof(int32_t), rle_size);
  level_encoder.Encode(levels.size(), levels.data());
  reinterpret_cast<int32_t*>(buffer_rle->mutable_data())[0] = level_encoder.len();

  while (state.KeepRunning()) {
    LevelDecoder level_decoder;
    level_decoder.SetData(Encoding::RLE, max_level, levels.size(), buffer_rle->data());
    level_decoder.Decode(state.range(0), levels.data());
  }

  state.SetBytesProcessed(state.iterations() * state.range(0) * sizeof(int16_t));
  state.SetItemsProcessed(state.iterations() * state.range(0));
}

BENCHMARK(BM_RleDecoding)->RangePair(1024, 65536, 1, 16);

}  // namespace benchmark

}  // namespace parquet