GroupByAndAggregate.cpp

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/*
 * Copyright 2017 MapD Technologies, Inc.
 *
 * 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 "GroupByAndAggregate.h"
#include "AggregateUtils.h"
#include "Allocators/CudaAllocator.h"

#include "CardinalityEstimator.h"
#include "CodeGenerator.h"
#include "Descriptors/QueryMemoryDescriptor.h"
#include "ExpressionRange.h"
#include "ExpressionRewrite.h"
#include "GpuInitGroups.h"
#include "InPlaceSort.h"
#include "LLVMFunctionAttributesUtil.h"
#include "MaxwellCodegenPatch.h"
#include "OutputBufferInitialization.h"
#include "TargetExprBuilder.h"

#include "../CudaMgr/CudaMgr.h"
#include "../Shared/checked_alloc.h"
#include "../Utils/ChunkIter.h"
#include "DataMgr/BufferMgr/BufferMgr.h"
#include "Execute.h"
#include "QueryTemplateGenerator.h"
#include "RuntimeFunctions.h"
#include "StreamingTopN.h"
#include "TopKSort.h"
#include "WindowContext.h"

#include <llvm/Transforms/Utils/BasicBlockUtils.h>

#include <numeric>
#include <thread>

bool g_cluster{false};
bool g_bigint_count{false};
int g_hll_precision_bits{11};
extern size_t g_leaf_count;

namespace {

int32_t get_agg_count(const std::vector<Analyzer::Expr*>& target_exprs) {
  int32_t agg_count{0};
  for (auto target_expr : target_exprs) {
    CHECK(target_expr);
    const auto agg_expr = dynamic_cast<Analyzer::AggExpr*>(target_expr);
    if (!agg_expr || agg_expr->get_aggtype() == kSAMPLE) {
      const auto& ti = target_expr->get_type_info();
      // TODO(pavan): or if is_geometry()
      if (ti.is_array() || (ti.is_string() && ti.get_compression() == kENCODING_NONE)) {
        agg_count += 2;
      } else if (ti.is_geometry()) {
        agg_count += ti.get_physical_coord_cols() * 2;
      } else {
        ++agg_count;
      }
      continue;
    }
    if (agg_expr && agg_expr->get_aggtype() == kAVG) {
      agg_count += 2;
    } else {
      ++agg_count;
    }
  }
  return agg_count;
}

bool expr_is_rowid(const Analyzer::Expr* expr, const Catalog_Namespace::Catalog& cat) {
  const auto col = dynamic_cast<const Analyzer::ColumnVar*>(expr);
  if (!col) {
    return false;
  }
  const auto cd =
      get_column_descriptor_maybe(col->get_column_id(), col->get_table_id(), cat);
  if (!cd || !cd->isVirtualCol) {
    return false;
  }
  CHECK_EQ("rowid", cd->columnName);
  return true;
}

bool has_count_distinct(const RelAlgExecutionUnit& ra_exe_unit) {
  for (const auto& target_expr : ra_exe_unit.target_exprs) {
    const auto agg_info = get_target_info(target_expr, g_bigint_count);
    if (agg_info.is_agg && is_distinct_target(agg_info)) {
      return true;
    }
  }
  return false;
}

bool is_column_range_too_big_for_perfect_hash(const ColRangeInfo& col_range_info,
                                              const int64_t max_entry_count) {
  try {
    return static_cast<int64_t>(checked_int64_t(col_range_info.max) -
                                checked_int64_t(col_range_info.min)) >= max_entry_count;
  } catch (...) {
    return true;
  }
}

}  // namespace

ColRangeInfo GroupByAndAggregate::getColRangeInfo() {
  // Use baseline layout more eagerly on the GPU if the query uses count distinct,
  // because our HyperLogLog implementation is 4x less memory efficient on GPU.
  // Technically, this only applies to APPROX_COUNT_DISTINCT, but in practice we
  // can expect this to be true anyway for grouped queries since the precise version
  // uses significantly more memory.
  const int64_t baseline_threshold =
      has_count_distinct(ra_exe_unit_)
          ? (device_type_ == ExecutorDeviceType::GPU ? (Executor::baseline_threshold / 4)
                                                     : Executor::baseline_threshold)
          : Executor::baseline_threshold;
  if (ra_exe_unit_.groupby_exprs.size() != 1) {
    try {
      checked_int64_t cardinality{1};
      bool has_nulls{false};
      for (const auto groupby_expr : ra_exe_unit_.groupby_exprs) {
        auto col_range_info = getExprRangeInfo(groupby_expr.get());
        if (col_range_info.hash_type_ != QueryDescriptionType::GroupByPerfectHash) {
          // going through baseline hash if a non-integer type is encountered
          return {QueryDescriptionType::GroupByBaselineHash, 0, 0, 0, false};
        }
        auto crt_col_cardinality = getBucketedCardinality(col_range_info);
        CHECK_GE(crt_col_cardinality, 0);
        cardinality *= crt_col_cardinality;
        if (col_range_info.has_nulls) {
          has_nulls = true;
        }
      }
      // For zero or high cardinalities, use baseline layout.
      if (!cardinality || cardinality > baseline_threshold) {
        return {QueryDescriptionType::GroupByBaselineHash, 0, 0, 0, false};
      }
      return {QueryDescriptionType::GroupByPerfectHash,
              0,
              int64_t(cardinality),
              0,
              has_nulls};
    } catch (...) {  // overflow when computing cardinality
      return {QueryDescriptionType::GroupByBaselineHash, 0, 0, 0, false};
    }
  }
  // For single column groupby on high timestamps, force baseline hash due to wide ranges
  // we are likely to encounter when applying quals to the expression range
  // TODO: consider allowing TIMESTAMP(9) (nanoseconds) with quals to use perfect hash if
  // the range is small enough
  if (ra_exe_unit_.groupby_exprs.front() &&
      ra_exe_unit_.groupby_exprs.front()->get_type_info().is_high_precision_timestamp() &&
      ra_exe_unit_.simple_quals.size() > 0) {
    return {QueryDescriptionType::GroupByBaselineHash, 0, 0, 0, false};
  }
  const auto col_range_info = getExprRangeInfo(ra_exe_unit_.groupby_exprs.front().get());
  if (!ra_exe_unit_.groupby_exprs.front()) {
    return col_range_info;
  }
  static const int64_t MAX_BUFFER_SIZE = 1 << 30;
  const int64_t col_count =
      ra_exe_unit_.groupby_exprs.size() + ra_exe_unit_.target_exprs.size();
  int64_t max_entry_count = MAX_BUFFER_SIZE / (col_count * sizeof(int64_t));
  if (has_count_distinct(ra_exe_unit_)) {
    max_entry_count = std::min(max_entry_count, baseline_threshold);
  }
  if ((!ra_exe_unit_.groupby_exprs.front()->get_type_info().is_string() &&
       !expr_is_rowid(ra_exe_unit_.groupby_exprs.front().get(), *executor_->catalog_)) &&
      is_column_range_too_big_for_perfect_hash(col_range_info, max_entry_count) &&
      !col_range_info.bucket) {
    return {QueryDescriptionType::GroupByBaselineHash,
            col_range_info.min,
            col_range_info.max,
            0,
            col_range_info.has_nulls};
  }
  return col_range_info;
}

ColRangeInfo GroupByAndAggregate::getExprRangeInfo(const Analyzer::Expr* expr) const {
  if (!expr) {
    return {QueryDescriptionType::Projection, 0, 0, 0, false};
  }

  const auto expr_range = getExpressionRange(
      expr, query_infos_, executor_, boost::make_optional(ra_exe_unit_.simple_quals));
  switch (expr_range.getType()) {
    case ExpressionRangeType::Integer:
      return {QueryDescriptionType::GroupByPerfectHash,
              expr_range.getIntMin(),
              expr_range.getIntMax(),
              expr_range.getBucket(),
              expr_range.hasNulls()};
    case ExpressionRangeType::Float:
    case ExpressionRangeType::Double:
    case ExpressionRangeType::Invalid:
      return ColRangeInfo{QueryDescriptionType::GroupByBaselineHash, 0, 0, 0, false};
    default:
      CHECK(false);
  }
  CHECK(false);
  return {QueryDescriptionType::NonGroupedAggregate, 0, 0, 0, false};
}

int64_t GroupByAndAggregate::getBucketedCardinality(const ColRangeInfo& col_range_info) {
  checked_int64_t crt_col_cardinality =
      checked_int64_t(col_range_info.max) - checked_int64_t(col_range_info.min);
  if (col_range_info.bucket) {
    crt_col_cardinality /= col_range_info.bucket;
  }
  return static_cast<int64_t>(crt_col_cardinality +
                              (1 + (col_range_info.has_nulls ? 1 : 0)));
}

#define LL_CONTEXT executor_->cgen_state_->context_
#define LL_BUILDER executor_->cgen_state_->ir_builder_
#define LL_BOOL(v) executor_->cgen_state_->llBool(v)
#define LL_INT(v) executor_->cgen_state_->llInt(v)
#define LL_FP(v) executor_->cgen_state_->llFp(v)
#define ROW_FUNC executor_->cgen_state_->row_func_

GroupByAndAggregate::GroupByAndAggregate(
    Executor* executor,
    const ExecutorDeviceType device_type,
    const RelAlgExecutionUnit& ra_exe_unit,
    const std::vector<InputTableInfo>& query_infos,
    std::shared_ptr<RowSetMemoryOwner> row_set_mem_owner)
    : executor_(executor)
    , ra_exe_unit_(ra_exe_unit)
    , query_infos_(query_infos)
    , row_set_mem_owner_(row_set_mem_owner)
    , device_type_(device_type) {
  for (const auto groupby_expr : ra_exe_unit_.groupby_exprs) {
    if (!groupby_expr) {
      continue;
    }
    const auto& groupby_ti = groupby_expr->get_type_info();
    if (groupby_ti.is_string() && groupby_ti.get_compression() != kENCODING_DICT) {
      throw std::runtime_error(
          "Cannot group by string columns which are not dictionary encoded.");
    }
    if (groupby_ti.is_array()) {
      throw std::runtime_error("Group by array not supported");
    }
    if (groupby_ti.is_geometry()) {
      throw std::runtime_error("Group by geometry not supported");
    }
  }
}

int64_t GroupByAndAggregate::getShardedTopBucket(const ColRangeInfo& col_range_info,
                                                 const size_t shard_count) const {
  size_t device_count{0};
  if (device_type_ == ExecutorDeviceType::GPU) {
    device_count = executor_->getCatalog()->getDataMgr().getCudaMgr()->getDeviceCount();
    CHECK_GT(device_count, 0u);
  }

  int64_t bucket{col_range_info.bucket};

  if (shard_count) {
    CHECK(!col_range_info.bucket);
    /*
      when a node has fewer devices than shard count,
      a) In a distributed setup, the minimum distance between two keys would be
      device_count because shards are stored consecutively across the physical tables, i.e
      if a shard column has values 0 to 9, and 3 shards on each leaf, then node 1 would
      have values: 0,1,2,6,7,8 and node 2 would have values: 3,4,5,9. If each leaf node
      has only 1 device, in this case, all the keys from each node are loaded on the
      device each.

      b) In a single node setup, the distance would be minimum of device_count or
      difference of device_count - shard_count. For example: If a single node server
      running on 3 devices a shard column has values 0 to 9 in a table with 4 shards,
      device to fragment keys mapping would be: device 1 - 4,8,3,7 device 2 - 1,5,9 device
      3 - 2, 6 The bucket value would be 4(shards) - 3(devices) = 1 i.e. minimum of
      device_count or difference.

      When a node has device count equal to or more than shard count then the
      minimum distance is always at least shard_count * no of leaf nodes.
    */
    if (device_count < shard_count) {
      bucket = g_leaf_count ? std::max(device_count, static_cast<size_t>(1))
                            : std::min(device_count, shard_count - device_count);
    } else {
      bucket = shard_count * std::max(g_leaf_count, static_cast<size_t>(1));
    }
  }

  return bucket;
}

std::unique_ptr<QueryMemoryDescriptor> GroupByAndAggregate::initQueryMemoryDescriptor(
    const bool allow_multifrag,
    const size_t max_groups_buffer_entry_count,
    const int8_t crt_min_byte_width,
    RenderInfo* render_info,
    const bool output_columnar_hint) {
  const auto shard_count =
      device_type_ == ExecutorDeviceType::GPU
          ? shard_count_for_top_groups(ra_exe_unit_, *executor_->getCatalog())
          : 0;
  bool sort_on_gpu_hint =
      device_type_ == ExecutorDeviceType::GPU && allow_multifrag &&
      !ra_exe_unit_.sort_info.order_entries.empty() &&
      gpuCanHandleOrderEntries(ra_exe_unit_.sort_info.order_entries) && !shard_count;
  // must_use_baseline_sort is true iff we'd sort on GPU with the old algorithm
  // but the total output buffer size would be too big or it's a sharded top query.
  // For the sake of managing risk, use the new result set way very selectively for
  // this case only (alongside the baseline layout we've enabled for a while now).
  bool must_use_baseline_sort = shard_count;
  std::unique_ptr<QueryMemoryDescriptor> query_mem_desc;
  while (true) {
    query_mem_desc = initQueryMemoryDescriptorImpl(allow_multifrag,
                                                   max_groups_buffer_entry_count,
                                                   crt_min_byte_width,
                                                   sort_on_gpu_hint,
                                                   render_info,
                                                   must_use_baseline_sort,
                                                   output_columnar_hint);
    CHECK(query_mem_desc);
    if (query_mem_desc->sortOnGpu() &&
        (query_mem_desc->getBufferSizeBytes(device_type_) +
         align_to_int64(query_mem_desc->getEntryCount() * sizeof(int32_t))) >
            2 * 1024 * 1024 * 1024L) {
      must_use_baseline_sort = true;
      sort_on_gpu_hint = false;
    } else {
      break;
    }
  }
  return query_mem_desc;
}

std::unique_ptr<QueryMemoryDescriptor> GroupByAndAggregate::initQueryMemoryDescriptorImpl(
    const bool allow_multifrag,
    const size_t max_groups_buffer_entry_count,
    const int8_t crt_min_byte_width,
    const bool sort_on_gpu_hint,
    RenderInfo* render_info,
    const bool must_use_baseline_sort,
    const bool output_columnar_hint) {
  addTransientStringLiterals();

  const auto count_distinct_descriptors = initCountDistinctDescriptors();

  auto group_col_widths = get_col_byte_widths(ra_exe_unit_.groupby_exprs, {});

  const bool is_group_by{!ra_exe_unit_.groupby_exprs.empty()};

  auto col_range_info_nosharding = getColRangeInfo();

  const auto shard_count =
      device_type_ == ExecutorDeviceType::GPU
          ? shard_count_for_top_groups(ra_exe_unit_, *executor_->getCatalog())
          : 0;

  const auto col_range_info =
      ColRangeInfo{col_range_info_nosharding.hash_type_,
                   col_range_info_nosharding.min,
                   col_range_info_nosharding.max,
                   getShardedTopBucket(col_range_info_nosharding, shard_count),
                   col_range_info_nosharding.has_nulls};

  // Non-grouped aggregates do not support accessing aggregated ranges
  // Keyless hash is currently only supported with single-column perfect hash
  const auto keyless_info =
      !(is_group_by &&
        col_range_info.hash_type_ == QueryDescriptionType::GroupByPerfectHash &&
        ra_exe_unit_.groupby_exprs.size() == 1)
          ? KeylessInfo{false, -1, false}
          : getKeylessInfo(ra_exe_unit_.target_exprs, is_group_by);

  if (g_enable_watchdog &&
      ((col_range_info.hash_type_ == QueryDescriptionType::GroupByBaselineHash &&
        max_groups_buffer_entry_count > 120000000) ||
       (col_range_info.hash_type_ == QueryDescriptionType::GroupByPerfectHash &&
        ra_exe_unit_.groupby_exprs.size() == 1 &&
        (col_range_info.max - col_range_info.min) /
                std::max(col_range_info.bucket, int64_t(1)) >
            130000000))) {
    throw WatchdogException("Query would use too much memory");
  }
  return QueryMemoryDescriptor::init(executor_,
                                     ra_exe_unit_,
                                     query_infos_,
                                     col_range_info,
                                     keyless_info,
                                     allow_multifrag,
                                     device_type_,
                                     crt_min_byte_width,
                                     sort_on_gpu_hint,
                                     shard_count,
                                     max_groups_buffer_entry_count,
                                     render_info,
                                     count_distinct_descriptors,
                                     must_use_baseline_sort,
                                     output_columnar_hint);
}

void GroupByAndAggregate::addTransientStringLiterals() {
  addTransientStringLiterals(ra_exe_unit_, executor_, row_set_mem_owner_);
}

namespace {

void add_transient_string_literals_for_expression(
    const Analyzer::Expr* expr,
    Executor* executor,
    std::shared_ptr<RowSetMemoryOwner> row_set_mem_owner) {
  if (!expr) {
    return;
  }

  const auto array_expr = dynamic_cast<const Analyzer::ArrayExpr*>(expr);
  if (array_expr) {
    for (size_t i = 0; i < array_expr->getElementCount(); i++) {
      add_transient_string_literals_for_expression(
          array_expr->getElement(i), executor, row_set_mem_owner);
    }
    return;
  }

  const auto cast_expr = dynamic_cast<const Analyzer::UOper*>(expr);
  const auto& expr_ti = expr->get_type_info();
  if (cast_expr && cast_expr->get_optype() == kCAST && expr_ti.is_string()) {
    CHECK_EQ(kENCODING_DICT, expr_ti.get_compression());
    auto sdp = executor->getStringDictionaryProxy(
        expr_ti.get_comp_param(), row_set_mem_owner, true);
    CHECK(sdp);
    const auto str_lit_expr =
        dynamic_cast<const Analyzer::Constant*>(cast_expr->get_operand());
    if (str_lit_expr && str_lit_expr->get_constval().stringval) {
      sdp->getOrAddTransient(*str_lit_expr->get_constval().stringval);
    }
    return;
  }
  const auto case_expr = dynamic_cast<const Analyzer::CaseExpr*>(expr);
  if (!case_expr) {
    return;
  }
  Analyzer::DomainSet domain_set;
  case_expr->get_domain(domain_set);
  if (domain_set.empty()) {
    return;
  }
  if (expr_ti.is_string()) {
    CHECK_EQ(kENCODING_DICT, expr_ti.get_compression());
    auto sdp = executor->getStringDictionaryProxy(
        expr_ti.get_comp_param(), row_set_mem_owner, true);
    CHECK(sdp);
    for (const auto domain_expr : domain_set) {
      const auto cast_expr = dynamic_cast<const Analyzer::UOper*>(domain_expr);
      const auto str_lit_expr =
          cast_expr && cast_expr->get_optype() == kCAST
              ? dynamic_cast<const Analyzer::Constant*>(cast_expr->get_operand())
              : dynamic_cast<const Analyzer::Constant*>(domain_expr);
      if (str_lit_expr && str_lit_expr->get_constval().stringval) {
        sdp->getOrAddTransient(*str_lit_expr->get_constval().stringval);
      }
    }
  }
}

}  // namespace

void GroupByAndAggregate::addTransientStringLiterals(
    const RelAlgExecutionUnit& ra_exe_unit,
    Executor* executor,
    std::shared_ptr<RowSetMemoryOwner> row_set_mem_owner) {
  for (const auto group_expr : ra_exe_unit.groupby_exprs) {
    add_transient_string_literals_for_expression(
        group_expr.get(), executor, row_set_mem_owner);
  }
  for (const auto target_expr : ra_exe_unit.target_exprs) {
    const auto& target_type = target_expr->get_type_info();
    if (target_type.is_string() && target_type.get_compression() != kENCODING_DICT) {
      continue;
    }
    const auto agg_expr = dynamic_cast<const Analyzer::AggExpr*>(target_expr);
    if (agg_expr) {
      if (agg_expr->get_aggtype() == kSINGLE_VALUE ||
          agg_expr->get_aggtype() == kSAMPLE) {
        add_transient_string_literals_for_expression(
            agg_expr->get_arg(), executor, row_set_mem_owner);
      }
    } else {
      add_transient_string_literals_for_expression(
          target_expr, executor, row_set_mem_owner);
    }
  }
  row_set_mem_owner->addLiteralStringDictProxy(executor->lit_str_dict_proxy_);
}

CountDistinctDescriptors GroupByAndAggregate::initCountDistinctDescriptors() {
  CountDistinctDescriptors count_distinct_descriptors;
  for (const auto target_expr : ra_exe_unit_.target_exprs) {
    auto agg_info = get_target_info(target_expr, g_bigint_count);
    if (is_distinct_target(agg_info)) {
      CHECK(agg_info.is_agg);
      CHECK(agg_info.agg_kind == kCOUNT || agg_info.agg_kind == kAPPROX_COUNT_DISTINCT);
      const auto agg_expr = static_cast<const Analyzer::AggExpr*>(target_expr);
      const auto& arg_ti = agg_expr->get_arg()->get_type_info();
      if (arg_ti.is_string() && arg_ti.get_compression() != kENCODING_DICT) {
        throw std::runtime_error(
            "Strings must be dictionary-encoded for COUNT(DISTINCT).");
      }
      if (agg_info.agg_kind == kAPPROX_COUNT_DISTINCT && arg_ti.is_array()) {
        throw std::runtime_error("APPROX_COUNT_DISTINCT on arrays not supported yet");
      }
      if (agg_info.agg_kind == kAPPROX_COUNT_DISTINCT && arg_ti.is_geometry()) {
        throw std::runtime_error(
            "APPROX_COUNT_DISTINCT on geometry columns not supported");
      }
      if (agg_info.is_distinct && arg_ti.is_geometry()) {
        throw std::runtime_error("COUNT DISTINCT on geometry columns not supported");
      }
      ColRangeInfo no_range_info{QueryDescriptionType::Projection, 0, 0, 0, false};
      auto arg_range_info =
          arg_ti.is_fp() ? no_range_info : getExprRangeInfo(agg_expr->get_arg());
      CountDistinctImplType count_distinct_impl_type{CountDistinctImplType::StdSet};
      int64_t bitmap_sz_bits{0};
      if (agg_info.agg_kind == kAPPROX_COUNT_DISTINCT) {
        const auto error_rate = agg_expr->get_error_rate();
        if (error_rate) {
          CHECK(error_rate->get_type_info().get_type() == kINT);
          CHECK_GE(error_rate->get_constval().intval, 1);
          bitmap_sz_bits = hll_size_for_rate(error_rate->get_constval().smallintval);
        } else {
          bitmap_sz_bits = g_hll_precision_bits;
        }
      }
      if (arg_range_info.hash_type_ == QueryDescriptionType::GroupByPerfectHash &&
          !(arg_ti.is_array() || arg_ti.is_geometry())) {  // TODO(alex): allow bitmap
                                                           // implementation for arrays
        if (arg_range_info.isEmpty()) {
          count_distinct_descriptors.emplace_back(
              CountDistinctDescriptor{CountDistinctImplType::Bitmap,
                                      0,
                                      64,
                                      agg_info.agg_kind == kAPPROX_COUNT_DISTINCT,
                                      device_type_,
                                      1});
          continue;
        }
        count_distinct_impl_type = CountDistinctImplType::Bitmap;
        if (agg_info.agg_kind == kCOUNT) {
          bitmap_sz_bits = arg_range_info.max - arg_range_info.min + 1;
          const int64_t MAX_BITMAP_BITS{8 * 1000 * 1000 * 1000L};
          if (bitmap_sz_bits <= 0 || bitmap_sz_bits > MAX_BITMAP_BITS) {
            count_distinct_impl_type = CountDistinctImplType::StdSet;
          }
        }
      }
      if (agg_info.agg_kind == kAPPROX_COUNT_DISTINCT &&
          count_distinct_impl_type == CountDistinctImplType::StdSet &&
          !(arg_ti.is_array() || arg_ti.is_geometry())) {
        count_distinct_impl_type = CountDistinctImplType::Bitmap;
      }
      if (g_enable_watchdog &&
          count_distinct_impl_type == CountDistinctImplType::StdSet) {
        throw WatchdogException("Cannot use a fast path for COUNT distinct");
      }
      const auto sub_bitmap_count =
          get_count_distinct_sub_bitmap_count(bitmap_sz_bits, ra_exe_unit_, device_type_);
      count_distinct_descriptors.emplace_back(
          CountDistinctDescriptor{count_distinct_impl_type,
                                  arg_range_info.min,
                                  bitmap_sz_bits,
                                  agg_info.agg_kind == kAPPROX_COUNT_DISTINCT,
                                  device_type_,
                                  sub_bitmap_count});
    } else {
      count_distinct_descriptors.emplace_back(CountDistinctDescriptor{
          CountDistinctImplType::Invalid, 0, 0, false, device_type_, 0});
    }
  }
  return count_distinct_descriptors;
}

KeylessInfo GroupByAndAggregate::getKeylessInfo(
    const std::vector<Analyzer::Expr*>& target_expr_list,
    const bool is_group_by) const {
  bool keyless{true}, found{false}, shared_mem_support{false},
      shared_mem_valid_data_type{true};
  /* Currently support shared memory usage for a limited subset of possible aggregate
   * operations. shared_mem_support and
   * shared_mem_valid_data_type are declared to ensure such support. */
  int32_t num_agg_expr{0};  // used for shared memory support on the GPU
  int32_t index{0};
  for (const auto target_expr : target_expr_list) {
    const auto agg_info = get_target_info(target_expr, g_bigint_count);
    const auto chosen_type = get_compact_type(agg_info);
    // TODO(Saman): should be eventually removed, once I make sure what data types can
    // be used in this shared memory setting.

    shared_mem_valid_data_type =
        shared_mem_valid_data_type && supportedTypeForGpuSharedMemUsage(chosen_type);

    if (agg_info.is_agg) {
      num_agg_expr++;
    }
    if (!found && agg_info.is_agg && !is_distinct_target(agg_info)) {
      auto agg_expr = dynamic_cast<const Analyzer::AggExpr*>(target_expr);
      CHECK(agg_expr);
      const auto arg_expr = agg_arg(target_expr);
      const bool float_argument_input = takes_float_argument(agg_info);
      switch (agg_info.agg_kind) {
        case kAVG:
          ++index;
          if (arg_expr && !arg_expr->get_type_info().get_notnull()) {
            auto expr_range_info = getExpressionRange(arg_expr, query_infos_, executor_);
            if (expr_range_info.getType() == ExpressionRangeType::Invalid ||
                expr_range_info.hasNulls()) {
              break;
            }
          }
          found = true;
          break;
        case kCOUNT:
          if (arg_expr && !arg_expr->get_type_info().get_notnull()) {
            auto expr_range_info = getExpressionRange(arg_expr, query_infos_, executor_);
            if (expr_range_info.getType() == ExpressionRangeType::Invalid ||
                expr_range_info.hasNulls()) {
              break;
            }
          }
          found = true;
          if (!agg_info.skip_null_val) {
            shared_mem_support = true;  // currently just support 8 bytes per group
          }
          break;
        case kSUM: {
          auto arg_ti = arg_expr->get_type_info();
          if (constrained_not_null(arg_expr, ra_exe_unit_.quals)) {
            arg_ti.set_notnull(true);
          }
          if (!arg_ti.get_notnull()) {
            auto expr_range_info = getExpressionRange(arg_expr, query_infos_, executor_);
            if (expr_range_info.getType() != ExpressionRangeType::Invalid &&
                !expr_range_info.hasNulls()) {
              found = true;
            }
          } else {
            auto expr_range_info = getExpressionRange(arg_expr, query_infos_, executor_);
            switch (expr_range_info.getType()) {
              case ExpressionRangeType::Float:
              case ExpressionRangeType::Double:
                if (expr_range_info.getFpMax() < 0 || expr_range_info.getFpMin() > 0) {
                  found = true;
                }
                break;
              case ExpressionRangeType::Integer:
                if (expr_range_info.getIntMax() < 0 || expr_range_info.getIntMin() > 0) {
                  found = true;
                }
                break;
              default:
                break;
            }
          }
          break;
        }
        case kMIN: {
          CHECK(agg_expr && agg_expr->get_arg());
          const auto& arg_ti = agg_expr->get_arg()->get_type_info();
          if (arg_ti.is_string() || arg_ti.is_array()) {
            break;
          }
          auto expr_range_info =
              getExpressionRange(agg_expr->get_arg(), query_infos_, executor_);
          auto init_max = get_agg_initial_val(agg_info.agg_kind,
                                              chosen_type,
                                              is_group_by || float_argument_input,
                                              float_argument_input ? sizeof(float) : 8);
          switch (expr_range_info.getType()) {
            case ExpressionRangeType::Float:
            case ExpressionRangeType::Double: {
              auto double_max =
                  *reinterpret_cast<const double*>(may_alias_ptr(&init_max));
              if (expr_range_info.getFpMax() < double_max) {
                found = true;
              }
              break;
            }
            case ExpressionRangeType::Integer:
              if (expr_range_info.getIntMax() < init_max) {
                found = true;
              }
              break;
            default:
              break;
          }
          break;
        }
        case kMAX: {
          CHECK(agg_expr && agg_expr->get_arg());
          const auto& arg_ti = agg_expr->get_arg()->get_type_info();
          if (arg_ti.is_string() || arg_ti.is_array()) {
            break;
          }
          auto expr_range_info =
              getExpressionRange(agg_expr->get_arg(), query_infos_, executor_);
          // NULL sentinel and init value for kMAX are identical, which results in
          // ambiguity in detecting empty keys in presence of nulls.
          if (expr_range_info.getType() == ExpressionRangeType::Invalid ||
              expr_range_info.hasNulls()) {
            break;
          }
          auto init_min = get_agg_initial_val(agg_info.agg_kind,
                                              chosen_type,
                                              is_group_by || float_argument_input,
                                              float_argument_input ? sizeof(float) : 8);
          switch (expr_range_info.getType()) {
            case ExpressionRangeType::Float:
            case ExpressionRangeType::Double: {
              auto double_min =
                  *reinterpret_cast<const double*>(may_alias_ptr(&init_min));
              if (expr_range_info.getFpMin() > double_min) {
                found = true;
              }
              break;
            }
            case ExpressionRangeType::Integer:
              if (expr_range_info.getIntMin() > init_min) {
                found = true;
              }
              break;
            default:
              break;
          }
          break;
        }
        default:
          keyless = false;
          break;
      }
    }
    if (!keyless) {
      break;
    }
    if (!found) {
      ++index;
    }
  }

  // shouldn't use keyless for projection only
  return {keyless && found,
          index,
          ((num_agg_expr == 1) && (target_expr_list.size() <= 2))
              ? shared_mem_support && shared_mem_valid_data_type
              : false};
}

bool GroupByAndAggregate::supportedTypeForGpuSharedMemUsage(
    const SQLTypeInfo& target_type_info) const {
  bool result = false;
  switch (target_type_info.get_type()) {
    case SQLTypes::kTINYINT:
    case SQLTypes::kSMALLINT:
    case SQLTypes::kINT:
      result = true;
      break;
    case SQLTypes::kTEXT:
      if (target_type_info.get_compression() == EncodingType::kENCODING_DICT) {
        result = true;
      }
      break;
    default:
      break;
  }
  return result;
}

// TODO(Saman): this function is temporary and all these limitations should eventually
// be removed.
bool GroupByAndAggregate::supportedExprForGpuSharedMemUsage(Analyzer::Expr* expr) {
  /*
  UNNEST operations follow a slightly different internal memory layout compared to other
  keyless aggregates Currently, we opt out of using shared memory if there is any UNNEST
  operation involved.
  */
  if (dynamic_cast<Analyzer::UOper*>(expr) &&
      static_cast<Analyzer::UOper*>(expr)->get_optype() == kUNNEST) {
    return false;
  }
  return true;
}

bool GroupByAndAggregate::gpuCanHandleOrderEntries(
    const std::list<Analyzer::OrderEntry>& order_entries) {
  if (order_entries.size() > 1) {  // TODO(alex): lift this restriction
    return false;
  }
  for (const auto order_entry : order_entries) {
    CHECK_GE(order_entry.tle_no, 1);
    CHECK_LE(static_cast<size_t>(order_entry.tle_no), ra_exe_unit_.target_exprs.size());
    const auto target_expr = ra_exe_unit_.target_exprs[order_entry.tle_no - 1];
    if (!dynamic_cast<Analyzer::AggExpr*>(target_expr)) {
      return false;
    }
    // TODO(alex): relax the restrictions
    auto agg_expr = static_cast<Analyzer::AggExpr*>(target_expr);
    if (agg_expr->get_is_distinct() || agg_expr->get_aggtype() == kAVG ||
        agg_expr->get_aggtype() == kMIN || agg_expr->get_aggtype() == kMAX ||
        agg_expr->get_aggtype() == kAPPROX_COUNT_DISTINCT) {
      return false;
    }
    if (agg_expr->get_arg()) {
      const auto& arg_ti = agg_expr->get_arg()->get_type_info();
      if (arg_ti.is_fp()) {
        return false;
      }
      auto expr_range_info = getExprRangeInfo(agg_expr->get_arg());
      // TOD(adb): QMD not actually initialized here?
      if ((!(expr_range_info.hash_type_ == QueryDescriptionType::GroupByPerfectHash &&
             /* query_mem_desc.getGroupbyColCount() == 1 */ false) ||
           expr_range_info.has_nulls) &&
          order_entry.is_desc == order_entry.nulls_first) {
        return false;
      }
    }
    const auto& target_ti = target_expr->get_type_info();
    CHECK(!target_ti.is_array());
    if (!target_ti.is_integer()) {
      return false;
    }
  }
  return true;
}

GroupByAndAggregate::DiamondCodegen::DiamondCodegen(
    llvm::Value* cond,
    Executor* executor,
    const bool chain_to_next,
    const std::string& label_prefix,
    DiamondCodegen* parent,
    const bool share_false_edge_with_parent)
    : executor_(executor), chain_to_next_(chain_to_next), parent_(parent) {
  if (parent_) {
    CHECK(!chain_to_next_);
  }
  cond_true_ = llvm::BasicBlock::Create(LL_CONTEXT, label_prefix + "_true", ROW_FUNC);
  if (share_false_edge_with_parent) {
    CHECK(parent);
    orig_cond_false_ = cond_false_ = parent_->cond_false_;
  } else {
    orig_cond_false_ = cond_false_ =
        llvm::BasicBlock::Create(LL_CONTEXT, label_prefix + "_false", ROW_FUNC);
  }

  LL_BUILDER.CreateCondBr(cond, cond_true_, cond_false_);
  LL_BUILDER.SetInsertPoint(cond_true_);
}

void GroupByAndAggregate::DiamondCodegen::setChainToNext() {
  CHECK(!parent_);
  chain_to_next_ = true;
}

void GroupByAndAggregate::DiamondCodegen::setFalseTarget(llvm::BasicBlock* cond_false) {
  CHECK(!parent_ || orig_cond_false_ != parent_->cond_false_);
  cond_false_ = cond_false;
}

GroupByAndAggregate::DiamondCodegen::~DiamondCodegen() {
  if (parent_ && orig_cond_false_ != parent_->cond_false_) {
    LL_BUILDER.CreateBr(parent_->cond_false_);
  } else if (chain_to_next_) {
    LL_BUILDER.CreateBr(cond_false_);
  }
  if (!parent_ || (!chain_to_next_ && cond_false_ != parent_->cond_false_)) {
    LL_BUILDER.SetInsertPoint(orig_cond_false_);
  }
}

bool GroupByAndAggregate::codegen(llvm::Value* filter_result,
                                  llvm::BasicBlock* sc_false,
                                  const QueryMemoryDescriptor& query_mem_desc,
                                  const CompilationOptions& co) {
  CHECK(filter_result);

  bool can_return_error = false;
  llvm::BasicBlock* filter_false{nullptr};

  {
    const bool is_group_by = !ra_exe_unit_.groupby_exprs.empty();

    if (executor_->isArchMaxwell(co.device_type_)) {
      prependForceSync();
    }
    DiamondCodegen filter_cfg(filter_result,
                              executor_,
                              !is_group_by || query_mem_desc.usesGetGroupValueFast(),
                              "filter",
                              nullptr,
                              false);
    filter_false = filter_cfg.cond_false_;

    if (is_group_by) {
      if (query_mem_desc.getQueryDescriptionType() == QueryDescriptionType::Projection &&
          !use_streaming_top_n(ra_exe_unit_, query_mem_desc.didOutputColumnar())) {
        const auto crt_matched = get_arg_by_name(ROW_FUNC, "crt_matched");
        LL_BUILDER.CreateStore(LL_INT(int32_t(1)), crt_matched);
        auto total_matched_ptr = get_arg_by_name(ROW_FUNC, "total_matched");
        llvm::Value* old_total_matched_val{nullptr};
        if (co.device_type_ == ExecutorDeviceType::GPU) {
          old_total_matched_val =
              LL_BUILDER.CreateAtomicRMW(llvm::AtomicRMWInst::Add,
                                         total_matched_ptr,
                                         LL_INT(int32_t(1)),
                                         llvm::AtomicOrdering::Monotonic);
        } else {
          old_total_matched_val = LL_BUILDER.CreateLoad(total_matched_ptr);
          LL_BUILDER.CreateStore(
              LL_BUILDER.CreateAdd(old_total_matched_val, LL_INT(int32_t(1))),
              total_matched_ptr);
        }
        auto old_total_matched_ptr = get_arg_by_name(ROW_FUNC, "old_total_matched");
        LL_BUILDER.CreateStore(old_total_matched_val, old_total_matched_ptr);
      }

      auto agg_out_ptr_w_idx = codegenGroupBy(query_mem_desc, co, filter_cfg);
      if (query_mem_desc.usesGetGroupValueFast() ||
          query_mem_desc.getQueryDescriptionType() ==
              QueryDescriptionType::GroupByPerfectHash) {
        if (query_mem_desc.getGroupbyColCount() > 1) {
          filter_cfg.setChainToNext();
        }
        // Don't generate null checks if the group slot is guaranteed to be non-null,
        // as it's the case for get_group_value_fast* family.
        can_return_error =
            codegenAggCalls(agg_out_ptr_w_idx, {}, query_mem_desc, co, filter_cfg);
      } else {
        {
          llvm::Value* nullcheck_cond{nullptr};
          if (query_mem_desc.didOutputColumnar()) {
            nullcheck_cond = LL_BUILDER.CreateICmpSGE(std::get<1>(agg_out_ptr_w_idx),
                                                      LL_INT(int32_t(0)));
          } else {
            nullcheck_cond = LL_BUILDER.CreateICmpNE(
                std::get<0>(agg_out_ptr_w_idx),
                llvm::ConstantPointerNull::get(
                    llvm::PointerType::get(get_int_type(64, LL_CONTEXT), 0)));
          }
          DiamondCodegen nullcheck_cfg(
              nullcheck_cond, executor_, false, "groupby_nullcheck", &filter_cfg, false);
          codegenAggCalls(agg_out_ptr_w_idx, {}, query_mem_desc, co, filter_cfg);
        }
        can_return_error = true;
        if (query_mem_desc.getQueryDescriptionType() ==
                QueryDescriptionType::Projection &&
            use_streaming_top_n(ra_exe_unit_, query_mem_desc.didOutputColumnar())) {
          // Ignore rejection on pushing current row to top-K heap.
          LL_BUILDER.CreateRet(LL_INT(int32_t(0)));
        } else {
          CodeGenerator code_generator(executor_);
          LL_BUILDER.CreateRet(LL_BUILDER.CreateNeg(LL_BUILDER.CreateTrunc(
              // TODO(alex): remove the trunc once pos is converted to 32 bits
              code_generator.posArg(nullptr),
              get_int_type(32, LL_CONTEXT))));
        }
      }
    } else {
      if (ra_exe_unit_.estimator) {
        std::stack<llvm::BasicBlock*> array_loops;
        codegenEstimator(array_loops, filter_cfg, query_mem_desc, co);
      } else {
        auto arg_it = ROW_FUNC->arg_begin();
        std::vector<llvm::Value*> agg_out_vec;
        for (int32_t i = 0; i < get_agg_count(ra_exe_unit_.target_exprs); ++i) {
          agg_out_vec.push_back(&*arg_it++);
        }
        can_return_error = codegenAggCalls(std::make_tuple(nullptr, nullptr),
                                           agg_out_vec,
                                           query_mem_desc,
                                           co,
                                           filter_cfg);
      }
    }
  }

  if (ra_exe_unit_.join_quals.empty()) {
    executor_->cgen_state_->ir_builder_.CreateRet(LL_INT(int32_t(0)));
  } else if (sc_false) {
    const auto saved_insert_block = LL_BUILDER.GetInsertBlock();
    LL_BUILDER.SetInsertPoint(sc_false);
    LL_BUILDER.CreateBr(filter_false);
    LL_BUILDER.SetInsertPoint(saved_insert_block);
  }

  return can_return_error;
}

llvm::Value* GroupByAndAggregate::codegenOutputSlot(
    llvm::Value* groups_buffer,
    const QueryMemoryDescriptor& query_mem_desc,
    const CompilationOptions& co,
    DiamondCodegen& diamond_codegen) {
  CHECK(query_mem_desc.getQueryDescriptionType() == QueryDescriptionType::Projection);
  CHECK_EQ(size_t(1), ra_exe_unit_.groupby_exprs.size());
  const auto group_expr = ra_exe_unit_.groupby_exprs.front();
  CHECK(!group_expr);
  if (!query_mem_desc.didOutputColumnar()) {
    CHECK_EQ(size_t(0), query_mem_desc.getRowSize() % sizeof(int64_t));
  }
  const int32_t row_size_quad = query_mem_desc.didOutputColumnar()
                                    ? 0
                                    : query_mem_desc.getRowSize() / sizeof(int64_t);
  CodeGenerator code_generator(executor_);
  if (use_streaming_top_n(ra_exe_unit_, query_mem_desc.didOutputColumnar())) {
    const auto& only_order_entry = ra_exe_unit_.sort_info.order_entries.front();
    CHECK_GE(only_order_entry.tle_no, int(1));
    const size_t target_idx = only_order_entry.tle_no - 1;
    CHECK_LT(target_idx, ra_exe_unit_.target_exprs.size());
    const auto order_entry_expr = ra_exe_unit_.target_exprs[target_idx];
    const auto chosen_bytes =
        static_cast<size_t>(query_mem_desc.getPaddedSlotWidthBytes(target_idx));
    auto order_entry_lv = executor_->cgen_state_->castToTypeIn(
        code_generator.codegen(order_entry_expr, true, co).front(), chosen_bytes * 8);
    const uint32_t n = ra_exe_unit_.sort_info.offset + ra_exe_unit_.sort_info.limit;
    std::string fname = "get_bin_from_k_heap";
    const auto& oe_ti = order_entry_expr->get_type_info();
    llvm::Value* null_key_lv = nullptr;
    if (oe_ti.is_integer() || oe_ti.is_decimal() || oe_ti.is_time()) {
      const size_t bit_width = order_entry_lv->getType()->getIntegerBitWidth();
      switch (bit_width) {
        case 32:
          null_key_lv = LL_INT(static_cast<int32_t>(inline_int_null_val(oe_ti)));
          break;
        case 64:
          null_key_lv = LL_INT(static_cast<int64_t>(inline_int_null_val(oe_ti)));
          break;
        default:
          CHECK(false);
      }
      fname += "_int" + std::to_string(bit_width) + "_t";
    } else {
      CHECK(oe_ti.is_fp());
      if (order_entry_lv->getType()->isDoubleTy()) {
        null_key_lv = LL_FP(static_cast<double>(inline_fp_null_val(oe_ti)));
      } else {
        null_key_lv = LL_FP(static_cast<float>(inline_fp_null_val(oe_ti)));
      }
      fname += order_entry_lv->getType()->isDoubleTy() ? "_double" : "_float";
    }
    const auto key_slot_idx =
        get_heap_key_slot_index(ra_exe_unit_.target_exprs, target_idx);
    return emitCall(
        fname,
        {groups_buffer,
         LL_INT(n),
         LL_INT(row_size_quad),
         LL_INT(static_cast<uint32_t>(query_mem_desc.getColOffInBytes(key_slot_idx))),
         LL_BOOL(only_order_entry.is_desc),
         LL_BOOL(!order_entry_expr->get_type_info().get_notnull()),
         LL_BOOL(only_order_entry.nulls_first),
         null_key_lv,
         order_entry_lv});
  } else {
    llvm::Value* output_buffer_entry_count_lv{nullptr};
    if (ra_exe_unit_.use_bump_allocator) {
      output_buffer_entry_count_lv =
          LL_BUILDER.CreateLoad(get_arg_by_name(ROW_FUNC, "max_matched"));
      CHECK(output_buffer_entry_count_lv);
    }
    const auto group_expr_lv =
        LL_BUILDER.CreateLoad(get_arg_by_name(ROW_FUNC, "old_total_matched"));
    std::vector<llvm::Value*> args{
        groups_buffer,
        output_buffer_entry_count_lv
            ? output_buffer_entry_count_lv
            : LL_INT(static_cast<int32_t>(query_mem_desc.getEntryCount())),
        group_expr_lv,
        code_generator.posArg(nullptr)};
    if (query_mem_desc.didOutputColumnar()) {
      const auto columnar_output_offset =
          emitCall("get_columnar_scan_output_offset", args);
      return columnar_output_offset;
    }
    args.push_back(LL_INT(row_size_quad));
    return emitCall("get_scan_output_slot", args);
  }
}

std::tuple<llvm::Value*, llvm::Value*> GroupByAndAggregate::codegenGroupBy(
    const QueryMemoryDescriptor& query_mem_desc,
    const CompilationOptions& co,
    DiamondCodegen& diamond_codegen) {
  auto arg_it = ROW_FUNC->arg_begin();
  auto groups_buffer = arg_it++;

  std::stack<llvm::BasicBlock*> array_loops;

  // TODO(Saman): move this logic outside of this function.
  if (query_mem_desc.getQueryDescriptionType() == QueryDescriptionType::Projection) {
    if (query_mem_desc.didOutputColumnar()) {
      return std::make_tuple(
          &*groups_buffer,
          codegenOutputSlot(&*groups_buffer, query_mem_desc, co, diamond_codegen));
    } else {
      return std::make_tuple(
          codegenOutputSlot(&*groups_buffer, query_mem_desc, co, diamond_codegen),
          nullptr);
    }
  }

  CHECK(query_mem_desc.getQueryDescriptionType() ==
            QueryDescriptionType::GroupByBaselineHash ||
        query_mem_desc.getQueryDescriptionType() ==
            QueryDescriptionType::GroupByPerfectHash);

  const int32_t row_size_quad = query_mem_desc.didOutputColumnar()
                                    ? 0
                                    : query_mem_desc.getRowSize() / sizeof(int64_t);

  const auto col_width_size = query_mem_desc.isSingleColumnGroupByWithPerfectHash()
                                  ? sizeof(int64_t)
                                  : query_mem_desc.getEffectiveKeyWidth();
  // for multi-column group by
  llvm::Value* group_key = nullptr;
  llvm::Value* key_size_lv = nullptr;

  if (!query_mem_desc.isSingleColumnGroupByWithPerfectHash()) {
    key_size_lv = LL_INT(static_cast<int32_t>(query_mem_desc.getGroupbyColCount()));
    if (query_mem_desc.getQueryDescriptionType() ==
        QueryDescriptionType::GroupByPerfectHash) {
      group_key =
          LL_BUILDER.CreateAlloca(llvm::Type::getInt64Ty(LL_CONTEXT), key_size_lv);
    } else if (query_mem_desc.getQueryDescriptionType() ==
               QueryDescriptionType::GroupByBaselineHash) {
      group_key =
          col_width_size == sizeof(int32_t)
              ? LL_BUILDER.CreateAlloca(llvm::Type::getInt32Ty(LL_CONTEXT), key_size_lv)
              : LL_BUILDER.CreateAlloca(llvm::Type::getInt64Ty(LL_CONTEXT), key_size_lv);
    }
    CHECK(group_key);
    CHECK(key_size_lv);
  }

  int32_t subkey_idx = 0;
  CHECK(query_mem_desc.getGroupbyColCount() == ra_exe_unit_.groupby_exprs.size());
  for (const auto group_expr : ra_exe_unit_.groupby_exprs) {
    const auto col_range_info = getExprRangeInfo(group_expr.get());
    const auto translated_null_value = static_cast<int64_t>(
        query_mem_desc.isSingleColumnGroupByWithPerfectHash()
            ? checked_int64_t(query_mem_desc.getMaxVal()) +
                  (query_mem_desc.getBucket() ? query_mem_desc.getBucket() : 1)
            : checked_int64_t(col_range_info.max) +
                  (col_range_info.bucket ? col_range_info.bucket : 1));

    const bool col_has_nulls =
        query_mem_desc.getQueryDescriptionType() ==
                QueryDescriptionType::GroupByPerfectHash
            ? (query_mem_desc.isSingleColumnGroupByWithPerfectHash()
                   ? query_mem_desc.hasNulls()
                   : col_range_info.has_nulls)
            : false;

    const auto group_expr_lvs =
        executor_->groupByColumnCodegen(group_expr.get(),
                                        col_width_size,
                                        co,
                                        col_has_nulls,
                                        translated_null_value,
                                        diamond_codegen,
                                        array_loops,
                                        query_mem_desc.threadsShareMemory());
    const auto group_expr_lv = group_expr_lvs.translated_value;
    if (query_mem_desc.isSingleColumnGroupByWithPerfectHash()) {
      CHECK_EQ(size_t(1), ra_exe_unit_.groupby_exprs.size());
      return codegenSingleColumnPerfectHash(query_mem_desc,
                                            co,
                                            &*groups_buffer,
                                            group_expr_lv,
                                            group_expr_lvs.original_value,
                                            row_size_quad);
    } else {
      // store the sub-key to the buffer
      LL_BUILDER.CreateStore(group_expr_lv,
                             LL_BUILDER.CreateGEP(group_key, LL_INT(subkey_idx++)));
    }
  }
  if (query_mem_desc.getQueryDescriptionType() ==
      QueryDescriptionType::GroupByPerfectHash) {
    CHECK(ra_exe_unit_.groupby_exprs.size() != 1);
    return codegenMultiColumnPerfectHash(
        &*groups_buffer, group_key, key_size_lv, query_mem_desc, row_size_quad);
  } else if (query_mem_desc.getQueryDescriptionType() ==
             QueryDescriptionType::GroupByBaselineHash) {
    return codegenMultiColumnBaselineHash(co,
                                          &*groups_buffer,
                                          group_key,
                                          key_size_lv,
                                          query_mem_desc,
                                          col_width_size,
                                          row_size_quad);
  }
  CHECK(false);
  return std::make_tuple(nullptr, nullptr);
}

std::tuple<llvm::Value*, llvm::Value*>
GroupByAndAggregate::codegenSingleColumnPerfectHash(
    const QueryMemoryDescriptor& query_mem_desc,
    const CompilationOptions& co,
    llvm::Value* groups_buffer,
    llvm::Value* group_expr_lv_translated,
    llvm::Value* group_expr_lv_original,
    const int32_t row_size_quad) {
  CHECK(query_mem_desc.usesGetGroupValueFast());
  std::string get_group_fn_name{query_mem_desc.didOutputColumnar()
                                    ? "get_columnar_group_bin_offset"
                                    : "get_group_value_fast"};
  if (!query_mem_desc.didOutputColumnar() && query_mem_desc.hasKeylessHash()) {
    get_group_fn_name += "_keyless";
  }
  if (query_mem_desc.interleavedBins(co.device_type_)) {
    CHECK(!query_mem_desc.didOutputColumnar());
    CHECK(query_mem_desc.hasKeylessHash());
    get_group_fn_name += "_semiprivate";
  }
  std::vector<llvm::Value*> get_group_fn_args{&*groups_buffer,
                                              &*group_expr_lv_translated};
  if (group_expr_lv_original && get_group_fn_name == "get_group_value_fast" &&
      query_mem_desc.mustUseBaselineSort()) {
    get_group_fn_name += "_with_original_key";
    get_group_fn_args.push_back(group_expr_lv_original);
  }
  get_group_fn_args.push_back(LL_INT(query_mem_desc.getMinVal()));
  get_group_fn_args.push_back(LL_INT(query_mem_desc.getBucket()));
  if (!query_mem_desc.hasKeylessHash()) {
    if (!query_mem_desc.didOutputColumnar()) {
      get_group_fn_args.push_back(LL_INT(row_size_quad));
    }
  } else {
    if (!query_mem_desc.didOutputColumnar()) {
      get_group_fn_args.push_back(LL_INT(row_size_quad));
    }
    if (query_mem_desc.interleavedBins(co.device_type_)) {
      auto warp_idx = emitCall("thread_warp_idx", {LL_INT(executor_->warpSize())});
      get_group_fn_args.push_back(warp_idx);
      get_group_fn_args.push_back(LL_INT(executor_->warpSize()));
    }
  }
  if (get_group_fn_name == "get_columnar_group_bin_offset") {
    return std::make_tuple(&*groups_buffer,
                           emitCall(get_group_fn_name, get_group_fn_args));
  }
  return std::make_tuple(emitCall(get_group_fn_name, get_group_fn_args), nullptr);
}

std::tuple<llvm::Value*, llvm::Value*> GroupByAndAggregate::codegenMultiColumnPerfectHash(
    llvm::Value* groups_buffer,
    llvm::Value* group_key,
    llvm::Value* key_size_lv,
    const QueryMemoryDescriptor& query_mem_desc,
    const int32_t row_size_quad) {
  CHECK(query_mem_desc.getQueryDescriptionType() ==
        QueryDescriptionType::GroupByPerfectHash);
  // compute the index (perfect hash)
  auto perfect_hash_func = codegenPerfectHashFunction();
  auto hash_lv =
      LL_BUILDER.CreateCall(perfect_hash_func, std::vector<llvm::Value*>{group_key});

  if (query_mem_desc.didOutputColumnar()) {
    const std::string set_matching_func_name{
        "set_matching_group_value_perfect_hash_columnar"};
    const std::vector<llvm::Value*> set_matching_func_arg{
        groups_buffer,
        hash_lv,
        group_key,
        key_size_lv,
        llvm::ConstantInt::get(get_int_type(32, LL_CONTEXT),
                               query_mem_desc.getEntryCount())};
    emitCall(set_matching_func_name, set_matching_func_arg);
    return std::make_tuple(groups_buffer, hash_lv);
  } else {
    return std::make_tuple(
        emitCall("get_matching_group_value_perfect_hash",
                 {groups_buffer, hash_lv, group_key, key_size_lv, LL_INT(row_size_quad)}),
        nullptr);
  }
}

std::tuple<llvm::Value*, llvm::Value*>
GroupByAndAggregate::codegenMultiColumnBaselineHash(
    const CompilationOptions& co,
    llvm::Value* groups_buffer,
    llvm::Value* group_key,
    llvm::Value* key_size_lv,
    const QueryMemoryDescriptor& query_mem_desc,
    const size_t key_width,
    const int32_t row_size_quad) {
  auto arg_it = ROW_FUNC->arg_begin();  // groups_buffer
  ++arg_it;                             // current match count
  ++arg_it;                             // total match count
  ++arg_it;                             // old match count
  ++arg_it;                             // output buffer slots count
  ++arg_it;                             // aggregate init values
  CHECK(arg_it->getName() == "agg_init_val");
  if (group_key->getType() != llvm::Type::getInt64PtrTy(LL_CONTEXT)) {
    CHECK(key_width == sizeof(int32_t));
    group_key =
        LL_BUILDER.CreatePointerCast(group_key, llvm::Type::getInt64PtrTy(LL_CONTEXT));
  }
  std::vector<llvm::Value*> func_args{
      groups_buffer,
      LL_INT(static_cast<int32_t>(query_mem_desc.getEntryCount())),
      &*group_key,
      &*key_size_lv,
      LL_INT(static_cast<int32_t>(key_width))};
  std::string func_name{"get_group_value"};
  if (query_mem_desc.didOutputColumnar()) {
    func_name += "_columnar_slot";
  } else {
    func_args.push_back(LL_INT(row_size_quad));
    func_args.push_back(&*arg_it);
  }
  if (co.with_dynamic_watchdog_) {
    func_name += "_with_watchdog";
  }
  if (query_mem_desc.didOutputColumnar()) {
    return std::make_tuple(groups_buffer, emitCall(func_name, func_args));
  } else {
    return std::make_tuple(emitCall(func_name, func_args), nullptr);
  }
}

llvm::Function* GroupByAndAggregate::codegenPerfectHashFunction() {
  CHECK_GT(ra_exe_unit_.groupby_exprs.size(), size_t(1));
  auto ft = llvm::FunctionType::get(
      get_int_type(32, LL_CONTEXT),
      std::vector<llvm::Type*>{llvm::PointerType::get(get_int_type(64, LL_CONTEXT), 0)},
      false);
  auto key_hash_func = llvm::Function::Create(ft,
                                              llvm::Function::ExternalLinkage,
                                              "perfect_key_hash",
                                              executor_->cgen_state_->module_);
  executor_->cgen_state_->helper_functions_.push_back(key_hash_func);
  mark_function_always_inline(key_hash_func);
  auto& key_buff_arg = *key_hash_func->args().begin();
  llvm::Value* key_buff_lv = &key_buff_arg;
  auto bb = llvm::BasicBlock::Create(LL_CONTEXT, "entry", key_hash_func);
  llvm::IRBuilder<> key_hash_func_builder(bb);
  llvm::Value* hash_lv{llvm::ConstantInt::get(get_int_type(64, LL_CONTEXT), 0)};
  std::vector<int64_t> cardinalities;
  for (const auto groupby_expr : ra_exe_unit_.groupby_exprs) {
    auto col_range_info = getExprRangeInfo(groupby_expr.get());
    CHECK(col_range_info.hash_type_ == QueryDescriptionType::GroupByPerfectHash);
    cardinalities.push_back(getBucketedCardinality(col_range_info));
  }
  size_t dim_idx = 0;
  for (const auto groupby_expr : ra_exe_unit_.groupby_exprs) {
    auto key_comp_lv = key_hash_func_builder.CreateLoad(
        key_hash_func_builder.CreateGEP(key_buff_lv, LL_INT(dim_idx)));
    auto col_range_info = getExprRangeInfo(groupby_expr.get());
    auto crt_term_lv =
        key_hash_func_builder.CreateSub(key_comp_lv, LL_INT(col_range_info.min));
    if (col_range_info.bucket) {
      crt_term_lv =
          key_hash_func_builder.CreateSDiv(crt_term_lv, LL_INT(col_range_info.bucket));
    }
    for (size_t prev_dim_idx = 0; prev_dim_idx < dim_idx; ++prev_dim_idx) {
      crt_term_lv = key_hash_func_builder.CreateMul(crt_term_lv,
                                                    LL_INT(cardinalities[prev_dim_idx]));
    }
    hash_lv = key_hash_func_builder.CreateAdd(hash_lv, crt_term_lv);
    ++dim_idx;
  }
  key_hash_func_builder.CreateRet(
      key_hash_func_builder.CreateTrunc(hash_lv, get_int_type(32, LL_CONTEXT)));
  return key_hash_func;
}

llvm::Value* GroupByAndAggregate::convertNullIfAny(const SQLTypeInfo& arg_type,
                                                   const TargetInfo& agg_info,
                                                   llvm::Value* target) {
  const auto& agg_type = agg_info.sql_type;
  const size_t chosen_bytes = agg_type.get_size();

  bool need_conversion{false};
  llvm::Value* arg_null{nullptr};
  llvm::Value* agg_null{nullptr};
  llvm::Value* target_to_cast{target};
  if (arg_type.is_fp()) {
    arg_null = executor_->cgen_state_->inlineFpNull(arg_type);
    if (agg_type.is_fp()) {
      agg_null = executor_->cgen_state_->inlineFpNull(agg_type);
      if (!static_cast<llvm::ConstantFP*>(arg_null)->isExactlyValue(
              static_cast<llvm::ConstantFP*>(agg_null)->getValueAPF())) {
        need_conversion = true;
      }
    } else {
      CHECK(agg_info.agg_kind == kCOUNT || agg_info.agg_kind == kAPPROX_COUNT_DISTINCT);
      return target;
    }
  } else {
    arg_null = executor_->cgen_state_->inlineIntNull(arg_type);
    if (agg_type.is_fp()) {
      agg_null = executor_->cgen_state_->inlineFpNull(agg_type);
      need_conversion = true;
      target_to_cast = executor_->castToFP(target);
    } else {
      agg_null = executor_->cgen_state_->inlineIntNull(agg_type);
      if ((static_cast<llvm::ConstantInt*>(arg_null)->getBitWidth() !=
           static_cast<llvm::ConstantInt*>(agg_null)->getBitWidth()) ||
          (static_cast<llvm::ConstantInt*>(arg_null)->getValue() !=
           static_cast<llvm::ConstantInt*>(agg_null)->getValue())) {
        need_conversion = true;
      }
    }
  }
  if (need_conversion) {
    auto cmp = arg_type.is_fp() ? LL_BUILDER.CreateFCmpOEQ(target, arg_null)
                                : LL_BUILDER.CreateICmpEQ(target, arg_null);
    return LL_BUILDER.CreateSelect(
        cmp,
        agg_null,
        executor_->cgen_state_->castToTypeIn(target_to_cast, chosen_bytes << 3));
  } else {
    return target;
  }
}

llvm::Value* GroupByAndAggregate::codegenWindowRowPointer(
    const Analyzer::WindowFunction* window_func,
    const QueryMemoryDescriptor& query_mem_desc,
    const CompilationOptions& co,
    DiamondCodegen& diamond_codegen) {
  const auto window_func_context =
      WindowProjectNodeContext::getActiveWindowFunctionContext();
  if (window_func_context && window_function_is_aggregate(window_func->getKind())) {
    const int32_t row_size_quad = query_mem_desc.didOutputColumnar()
                                      ? 0
                                      : query_mem_desc.getRowSize() / sizeof(int64_t);
    auto arg_it = ROW_FUNC->arg_begin();
    auto groups_buffer = arg_it++;
    CodeGenerator code_generator(executor_);
    if (!window_func_context->getRowNumber()) {
      CHECK(window_func->getKind() == SqlWindowFunctionKind::COUNT);
      window_func_context->setRowNumber(emitCall(
          "row_number_window_func",
          {LL_INT(reinterpret_cast<const int64_t>(window_func_context->output())),
           code_generator.posArg(nullptr)}));
    }
    const auto pos_in_window = LL_BUILDER.CreateTrunc(window_func_context->getRowNumber(),
                                                      get_int_type(32, LL_CONTEXT));
    llvm::Value* entry_count_lv =
        LL_INT(static_cast<int32_t>(query_mem_desc.getEntryCount()));
    std::vector<llvm::Value*> args{
        &*groups_buffer, entry_count_lv, pos_in_window, code_generator.posArg(nullptr)};
    if (query_mem_desc.didOutputColumnar()) {
      const auto columnar_output_offset =
          emitCall("get_columnar_scan_output_offset", args);
      return LL_BUILDER.CreateSExt(columnar_output_offset, get_int_type(64, LL_CONTEXT));
    }
    args.push_back(LL_INT(row_size_quad));
    return emitCall("get_scan_output_slot", args);
  }
  auto arg_it = ROW_FUNC->arg_begin();
  auto groups_buffer = arg_it++;
  return codegenOutputSlot(&*groups_buffer, query_mem_desc, co, diamond_codegen);
}

bool GroupByAndAggregate::codegenAggCalls(
    const std::tuple<llvm::Value*, llvm::Value*>& agg_out_ptr_w_idx_in,
    const std::vector<llvm::Value*>& agg_out_vec,
    const QueryMemoryDescriptor& query_mem_desc,
    const CompilationOptions& co,
    DiamondCodegen& diamond_codegen) {
  auto agg_out_ptr_w_idx = agg_out_ptr_w_idx_in;
  // TODO(alex): unify the two cases, the output for non-group by queries
  //             should be a contiguous buffer
  const bool is_group_by{std::get<0>(agg_out_ptr_w_idx)};
  bool can_return_error = false;
  if (is_group_by) {
    CHECK(agg_out_vec.empty());
  } else {
    CHECK(!agg_out_vec.empty());
  }

  // output buffer is casted into a byte stream to be able to handle data elements of
  // different sizes (only used when actual column width sizes are used)
  llvm::Value* output_buffer_byte_stream{nullptr};
  llvm::Value* out_row_idx{nullptr};
  if (query_mem_desc.didOutputColumnar() && !g_cluster &&
      query_mem_desc.getQueryDescriptionType() == QueryDescriptionType::Projection) {
    output_buffer_byte_stream = LL_BUILDER.CreateBitCast(
        std::get<0>(agg_out_ptr_w_idx),
        llvm::PointerType::get(llvm::Type::getInt8Ty(LL_CONTEXT), 0));
    output_buffer_byte_stream->setName("out_buff_b_stream");
    CHECK(std::get<1>(agg_out_ptr_w_idx));
    out_row_idx = LL_BUILDER.CreateZExt(std::get<1>(agg_out_ptr_w_idx),
                                        llvm::Type::getInt64Ty(LL_CONTEXT));
    out_row_idx->setName("out_row_idx");
  }

  TargetExprCodegenBuilder target_builder(query_mem_desc, ra_exe_unit_, is_group_by);
  for (size_t target_idx = 0; target_idx < ra_exe_unit_.target_exprs.size();
       ++target_idx) {
    auto target_expr = ra_exe_unit_.target_exprs[target_idx];
    CHECK(target_expr);

    target_builder(target_expr, executor_, co);
  }

  target_builder.codegen(this,
                         executor_,
                         query_mem_desc,
                         co,
                         agg_out_ptr_w_idx,
                         agg_out_vec,
                         output_buffer_byte_stream,
                         out_row_idx,
                         diamond_codegen);

  for (auto target_expr : ra_exe_unit_.target_exprs) {
    CHECK(target_expr);
    executor_->plan_state_->isLazyFetchColumn(target_expr);
  }

  return can_return_error;
}

llvm::Value* GroupByAndAggregate::codegenAggColumnPtr(
    llvm::Value* output_buffer_byte_stream,
    llvm::Value* out_row_idx,
    const std::tuple<llvm::Value*, llvm::Value*>& agg_out_ptr_w_idx,
    const QueryMemoryDescriptor& query_mem_desc,
    const size_t chosen_bytes,
    const size_t agg_out_off,
    const size_t target_idx) {
  llvm::Value* agg_col_ptr{nullptr};
  if (query_mem_desc.didOutputColumnar()) {
    // TODO(Saman): remove the second columnar branch, and support all query description
    // types through the first branch. Then, input arguments should also be cleaned up
    if (!g_cluster &&
        query_mem_desc.getQueryDescriptionType() == QueryDescriptionType::Projection) {
      CHECK(chosen_bytes == 1 || chosen_bytes == 2 || chosen_bytes == 4 ||
            chosen_bytes == 8);
      CHECK(output_buffer_byte_stream);
      CHECK(out_row_idx);
      uint32_t col_off = query_mem_desc.getColOffInBytes(agg_out_off);
      // multiplying by chosen_bytes, i.e., << log2(chosen_bytes)
      auto out_per_col_byte_idx =
          LL_BUILDER.CreateShl(out_row_idx, __builtin_ffs(chosen_bytes) - 1);
      auto byte_offset = LL_BUILDER.CreateAdd(out_per_col_byte_idx,
                                              LL_INT(static_cast<int64_t>(col_off)));
      byte_offset->setName("out_byte_off_target_" + std::to_string(target_idx));
      auto output_ptr = LL_BUILDER.CreateGEP(output_buffer_byte_stream, byte_offset);
      agg_col_ptr = LL_BUILDER.CreateBitCast(
          output_ptr,
          llvm::PointerType::get(get_int_type((chosen_bytes << 3), LL_CONTEXT), 0));
      agg_col_ptr->setName("out_ptr_target_" + std::to_string(target_idx));
    } else {
      uint32_t col_off = query_mem_desc.getColOffInBytes(agg_out_off);
      CHECK_EQ(size_t(0), col_off % chosen_bytes);
      col_off /= chosen_bytes;
      CHECK(std::get<1>(agg_out_ptr_w_idx));
      auto offset = LL_BUILDER.CreateAdd(std::get<1>(agg_out_ptr_w_idx), LL_INT(col_off));
      agg_col_ptr = LL_BUILDER.CreateGEP(
          LL_BUILDER.CreateBitCast(
              std::get<0>(agg_out_ptr_w_idx),
              llvm::PointerType::get(get_int_type((chosen_bytes << 3), LL_CONTEXT), 0)),
          offset);
    }
  } else {
    uint32_t col_off = query_mem_desc.getColOnlyOffInBytes(agg_out_off);
    CHECK_EQ(size_t(0), col_off % chosen_bytes);
    col_off /= chosen_bytes;
    agg_col_ptr = LL_BUILDER.CreateGEP(
        LL_BUILDER.CreateBitCast(
            std::get<0>(agg_out_ptr_w_idx),
            llvm::PointerType::get(get_int_type((chosen_bytes << 3), LL_CONTEXT), 0)),
        LL_INT(col_off));
  }
  CHECK(agg_col_ptr);
  return agg_col_ptr;
}

void GroupByAndAggregate::codegenEstimator(
    std::stack<llvm::BasicBlock*>& array_loops,
    GroupByAndAggregate::DiamondCodegen& diamond_codegen,
    const QueryMemoryDescriptor& query_mem_desc,
    const CompilationOptions& co) {
  const auto& estimator_arg = ra_exe_unit_.estimator->getArgument();
  auto estimator_comp_count_lv = LL_INT(static_cast<int32_t>(estimator_arg.size()));
  auto estimator_key_lv = LL_BUILDER.CreateAlloca(llvm::Type::getInt64Ty(LL_CONTEXT),
                                                  estimator_comp_count_lv);
  int32_t subkey_idx = 0;
  for (const auto estimator_arg_comp : estimator_arg) {
    const auto estimator_arg_comp_lvs =
        executor_->groupByColumnCodegen(estimator_arg_comp.get(),
                                        query_mem_desc.getEffectiveKeyWidth(),
                                        co,
                                        false,
                                        0,
                                        diamond_codegen,
                                        array_loops,
                                        true);
    CHECK(!estimator_arg_comp_lvs.original_value);
    const auto estimator_arg_comp_lv = estimator_arg_comp_lvs.translated_value;
    // store the sub-key to the buffer
    LL_BUILDER.CreateStore(estimator_arg_comp_lv,
                           LL_BUILDER.CreateGEP(estimator_key_lv, LL_INT(subkey_idx++)));
  }
  const auto int8_ptr_ty = llvm::PointerType::get(get_int_type(8, LL_CONTEXT), 0);
  const auto bitmap = LL_BUILDER.CreateBitCast(&*ROW_FUNC->arg_begin(), int8_ptr_ty);
  const auto key_bytes = LL_BUILDER.CreateBitCast(estimator_key_lv, int8_ptr_ty);
  const auto estimator_comp_bytes_lv =
      LL_INT(static_cast<int32_t>(estimator_arg.size() * sizeof(int64_t)));
  const auto bitmap_size_lv =
      LL_INT(static_cast<uint32_t>(ra_exe_unit_.estimator->getBufferSize()));
  emitCall(ra_exe_unit_.estimator->getRuntimeFunctionName(),
           {bitmap, &*bitmap_size_lv, key_bytes, &*estimator_comp_bytes_lv});
}

extern "C" void agg_count_distinct(int64_t* agg, const int64_t val) {
  reinterpret_cast<std::set<int64_t>*>(*agg)->insert(val);
}

extern "C" void agg_count_distinct_skip_val(int64_t* agg,
                                            const int64_t val,
                                            const int64_t skip_val) {
  if (val != skip_val) {
    agg_count_distinct(agg, val);
  }
}

void GroupByAndAggregate::codegenCountDistinct(
    const size_t target_idx,
    const Analyzer::Expr* target_expr,
    std::vector<llvm::Value*>& agg_args,
    const QueryMemoryDescriptor& query_mem_desc,
    const ExecutorDeviceType device_type) {
  const auto agg_info = get_target_info(target_expr, g_bigint_count);
  const auto& arg_ti =
      static_cast<const Analyzer::AggExpr*>(target_expr)->get_arg()->get_type_info();
  if (arg_ti.is_fp()) {
    agg_args.back() = executor_->cgen_state_->ir_builder_.CreateBitCast(
        agg_args.back(), get_int_type(64, executor_->cgen_state_->context_));
  }
  const auto& count_distinct_descriptor =
      query_mem_desc.getCountDistinctDescriptor(target_idx);
  CHECK(count_distinct_descriptor.impl_type_ != CountDistinctImplType::Invalid);
  if (agg_info.agg_kind == kAPPROX_COUNT_DISTINCT) {
    CHECK(count_distinct_descriptor.impl_type_ == CountDistinctImplType::Bitmap);
    agg_args.push_back(LL_INT(int32_t(count_distinct_descriptor.bitmap_sz_bits)));
    if (device_type == ExecutorDeviceType::GPU) {
      const auto base_dev_addr = getAdditionalLiteral(-1);
      const auto base_host_addr = getAdditionalLiteral(-2);
      agg_args.push_back(base_dev_addr);
      agg_args.push_back(base_host_addr);
      emitCall("agg_approximate_count_distinct_gpu", agg_args);
    } else {
      emitCall("agg_approximate_count_distinct", agg_args);
    }
    return;
  }
  std::string agg_fname{"agg_count_distinct"};
  if (count_distinct_descriptor.impl_type_ == CountDistinctImplType::Bitmap) {
    agg_fname += "_bitmap";
    agg_args.push_back(LL_INT(static_cast<int64_t>(count_distinct_descriptor.min_val)));
  }
  if (agg_info.skip_null_val) {
    auto null_lv = executor_->cgen_state_->castToTypeIn(
        (arg_ti.is_fp()
             ? static_cast<llvm::Value*>(executor_->cgen_state_->inlineFpNull(arg_ti))
             : static_cast<llvm::Value*>(executor_->cgen_state_->inlineIntNull(arg_ti))),
        64);
    null_lv = executor_->cgen_state_->ir_builder_.CreateBitCast(
        null_lv, get_int_type(64, executor_->cgen_state_->context_));
    agg_fname += "_skip_val";
    agg_args.push_back(null_lv);
  }
  if (device_type == ExecutorDeviceType::GPU) {
    CHECK(count_distinct_descriptor.impl_type_ == CountDistinctImplType::Bitmap);
    agg_fname += "_gpu";
    const auto base_dev_addr = getAdditionalLiteral(-1);
    const auto base_host_addr = getAdditionalLiteral(-2);
    agg_args.push_back(base_dev_addr);
    agg_args.push_back(base_host_addr);
    agg_args.push_back(LL_INT(int64_t(count_distinct_descriptor.sub_bitmap_count)));
    CHECK_EQ(size_t(0),
             count_distinct_descriptor.bitmapPaddedSizeBytes() %
                 count_distinct_descriptor.sub_bitmap_count);
    agg_args.push_back(LL_INT(int64_t(count_distinct_descriptor.bitmapPaddedSizeBytes() /
                                      count_distinct_descriptor.sub_bitmap_count)));
  }
  if (count_distinct_descriptor.impl_type_ == CountDistinctImplType::Bitmap) {
    emitCall(agg_fname, agg_args);
  } else {
    executor_->cgen_state_->emitExternalCall(
        agg_fname, llvm::Type::getVoidTy(LL_CONTEXT), agg_args);
  }
}

llvm::Value* GroupByAndAggregate::getAdditionalLiteral(const int32_t off) {
  CHECK_LT(off, 0);
  const auto lit_buff_lv = get_arg_by_name(ROW_FUNC, "literals");
  return LL_BUILDER.CreateLoad(LL_BUILDER.CreateGEP(
      LL_BUILDER.CreateBitCast(lit_buff_lv,
                               llvm::PointerType::get(get_int_type(64, LL_CONTEXT), 0)),
      LL_INT(off)));
}

std::vector<llvm::Value*> GroupByAndAggregate::codegenAggArg(
    const Analyzer::Expr* target_expr,
    const CompilationOptions& co) {
  const auto agg_expr = dynamic_cast<const Analyzer::AggExpr*>(target_expr);
  // TODO(alex): handle arrays uniformly?
  CodeGenerator code_generator(executor_);
  if (target_expr) {
    const auto& target_ti = target_expr->get_type_info();
    if (target_ti.is_array() && !executor_->plan_state_->isLazyFetchColumn(target_expr)) {
      const auto target_lvs =
          agg_expr ? code_generator.codegen(agg_expr->get_arg(), true, co)
                   : code_generator.codegen(
                         target_expr, !executor_->plan_state_->allow_lazy_fetch_, co);
      if (target_ti.isChunkIteratorPackaging()) {
        // Something with the chunk transport is code that was generated from a source
        // other than an ARRAY[] expression
        CHECK_EQ(size_t(1), target_lvs.size());
        CHECK(!agg_expr || agg_expr->get_aggtype() == kSAMPLE);
        const auto i32_ty = get_int_type(32, executor_->cgen_state_->context_);
        const auto i8p_ty =
            llvm::PointerType::get(get_int_type(8, executor_->cgen_state_->context_), 0);
        const auto& elem_ti = target_ti.get_elem_type();
        return {
            executor_->cgen_state_->emitExternalCall(
                "array_buff",
                i8p_ty,
                {target_lvs.front(), code_generator.posArg(target_expr)}),
            executor_->cgen_state_->emitExternalCall(
                "array_size",
                i32_ty,
                {target_lvs.front(),
                 code_generator.posArg(target_expr),
                 executor_->cgen_state_->llInt(log2_bytes(elem_ti.get_logical_size()))})};
      } else if (target_ti.isStandardBufferPackaging()) {
        if (agg_expr) {
          throw std::runtime_error(
              "Using array[] operator as argument to an aggregate operator is not "
              "supported");
        }
        return {target_lvs[0], target_lvs[1]};
      }
    }
    if (target_ti.is_geometry() &&
        !executor_->plan_state_->isLazyFetchColumn(target_expr)) {
      auto generate_coord_lvs =
          [&](auto* selected_target_expr,
              bool const fetch_columns) -> std::vector<llvm::Value*> {
        const auto target_lvs =
            code_generator.codegen(selected_target_expr, fetch_columns, co);
        const auto geo_expr = dynamic_cast<const Analyzer::GeoExpr*>(target_expr);
        if (geo_expr) {
          CHECK_EQ(2 * static_cast<size_t>(target_ti.get_physical_coord_cols()),
                   target_lvs.size());
          return target_lvs;
        }
        CHECK_EQ(static_cast<size_t>(target_ti.get_physical_coord_cols()),
                 target_lvs.size());

        const auto i32_ty = get_int_type(32, executor_->cgen_state_->context_);
        const auto i8p_ty =
            llvm::PointerType::get(get_int_type(8, executor_->cgen_state_->context_), 0);
        std::vector<llvm::Value*> coords;
        size_t ctr = 0;
        for (const auto& target_lv : target_lvs) {
          // TODO(adb): consider adding a utility to sqltypes so we can get the types of
          // the physical coords cols based on the sqltype (e.g. TINYINT for col 0, INT
          // for col 1 for pols / mpolys, etc). Hardcoding for now. first array is the
          // coords array (TINYINT). Subsequent arrays are regular INT.

          const size_t elem_sz = ctr == 0 ? 1 : 4;
          ctr++;
          int32_t fixlen = -1;
          if (target_ti.get_type() == kPOINT) {
            const auto col_var = dynamic_cast<const Analyzer::ColumnVar*>(target_expr);
            if (col_var) {
              const auto coords_cd = executor_->getPhysicalColumnDescriptor(col_var, 1);
              if (coords_cd && coords_cd->columnType.get_type() == kARRAY) {
                fixlen = coords_cd->columnType.get_size();
              }
            }
          }
          if (fixlen > 0) {
            coords.push_back(executor_->cgen_state_->emitExternalCall(
                "fast_fixlen_array_buff",
                i8p_ty,
                {target_lv, code_generator.posArg(selected_target_expr)}));
            coords.push_back(executor_->cgen_state_->llInt(int64_t(fixlen)));
            continue;
          }
          coords.push_back(executor_->cgen_state_->emitExternalCall(
              "array_buff",
              i8p_ty,
              {target_lv, code_generator.posArg(selected_target_expr)}));
          coords.push_back(executor_->cgen_state_->emitExternalCall(
              "array_size",
              i32_ty,
              {target_lv,
               code_generator.posArg(selected_target_expr),
               executor_->cgen_state_->llInt(log2_bytes(elem_sz))}));
        }
        return coords;
      };

      if (agg_expr) {
        return generate_coord_lvs(agg_expr->get_arg(), true);
      } else {
        return generate_coord_lvs(target_expr,
                                  !executor_->plan_state_->allow_lazy_fetch_);
      }
    }
  }
  return agg_expr ? code_generator.codegen(agg_expr->get_arg(), true, co)
                  : code_generator.codegen(
                        target_expr, !executor_->plan_state_->allow_lazy_fetch_, co);
}

llvm::Value* GroupByAndAggregate::emitCall(const std::string& fname,
                                           const std::vector<llvm::Value*>& args) {
  return executor_->cgen_state_->emitCall(fname, args);
}

void GroupByAndAggregate::checkErrorCode(llvm::Value* retCode) {
  auto zero_const = llvm::ConstantInt::get(retCode->getType(), 0, true);
  auto rc_check_condition = executor_->cgen_state_->ir_builder_.CreateICmp(
      llvm::ICmpInst::ICMP_EQ, retCode, zero_const);

  executor_->cgen_state_->emitErrorCheck(rc_check_condition, retCode, "rc");
}

#undef ROW_FUNC
#undef LL_FP
#undef LL_INT
#undef LL_BOOL
#undef LL_BUILDER
#undef LL_CONTEXT

size_t GroupByAndAggregate::shard_count_for_top_groups(
    const RelAlgExecutionUnit& ra_exe_unit,
    const Catalog_Namespace::Catalog& catalog) {
  if (ra_exe_unit.sort_info.order_entries.size() != 1 || !ra_exe_unit.sort_info.limit) {
    return 0;
  }
  for (const auto& group_expr : ra_exe_unit.groupby_exprs) {
    const auto grouped_col_expr =
        dynamic_cast<const Analyzer::ColumnVar*>(group_expr.get());
    if (!grouped_col_expr) {
      continue;
    }
    if (grouped_col_expr->get_table_id() <= 0) {
      return 0;
    }
    const auto td = catalog.getMetadataForTable(grouped_col_expr->get_table_id());
    if (td->shardedColumnId == grouped_col_expr->get_column_id()) {
      return td->nShards;
    }
  }
  return 0;
}