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ResultSetTest.cpp
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/*
* Copyright 2022 HEAVY.AI, 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.
*/
/**
* @file ResultSetTest.cpp
* @brief Unit tests for the result set interface.
*
*/
#include "Tests/ResultSetTestUtils.h"
#include "QueryEngine/Descriptors/RowSetMemoryOwner.h"
#include "QueryEngine/Execute.h"
#include "QueryEngine/ResultSet.h"
#include "QueryEngine/ResultSetReductionJIT.h"
#include "QueryEngine/RuntimeFunctions.h"
#include "QueryRunner/QueryRunner.h"
#include "StringDictionary/StringDictionary.h"
#include "Tests/DataMgrTestHelpers.h"
#include "Tests/TestHelpers.h"
#include <gtest/gtest.h>
#include <algorithm>
#include <queue>
#include <random>
#ifndef BASE_PATH
#define BASE_PATH "./tmp"
#endif
using QR = QueryRunner::QueryRunner;
extern bool g_is_test_env;
bool skip_tests(const ExecutorDeviceType device_type) {
#ifdef HAVE_CUDA
return device_type == ExecutorDeviceType::GPU && !(QR::get()->gpusPresent());
#else
return device_type == ExecutorDeviceType::GPU;
#endif
}
#define SKIP_NO_GPU() \
if (skip_tests(dt)) { \
CHECK(dt == ExecutorDeviceType::GPU); \
LOG(WARNING) << "GPU not available, skipping GPU tests"; \
continue; \
}
TEST(Construct, Allocate) {
std::vector<TargetInfo> target_infos;
QueryMemoryDescriptor query_mem_desc;
auto row_set_mem_owner = std::make_shared<RowSetMemoryOwner>(
Executor::getArenaBlockSize(), Executor::UNITARY_EXECUTOR_ID);
ResultSet result_set(
target_infos, ExecutorDeviceType::CPU, query_mem_desc, row_set_mem_owner, 0, 0);
result_set.allocateStorage();
}
namespace {
using OneRow = std::vector<TargetValue>;
/* This class allows to emulate and evaluate ResultSet and it's reduce function.
* It creates two ResultSet equivalents, populates them with randomly generated data,
* merges them into one, and provides access to the data contained in the merged set.
* Comparing these data with the ones received from the ResultSet code reduce procedure
* run on the same pair of the ResultSet equivalents, allows to evaluate the functionality
* of the ResultSet code.
*/
class ResultSetEmulator {
public:
ResultSetEmulator(int8_t* buff1,
int8_t* buff2,
const std::vector<TargetInfo>& target_infos,
const QueryMemoryDescriptor& query_mem_desc,
NumberGenerator& gen1,
NumberGenerator& gen2,
const size_t perc1,
const size_t perc2,
const size_t flow,
const bool silent)
:
rs1_buff(buff1)
, rs2_buff(buff2)
, rs_target_infos(target_infos)
, rs_query_mem_desc(query_mem_desc)
, rs1_gen(gen1)
, rs2_gen(gen2)
, rs1_perc(perc1)
, rs2_perc(perc2)
, rs_flow(flow)
, rs_entry_count(query_mem_desc.getEntryCount())
, rs_silent(silent) {
rs_entry_count =
query_mem_desc.getEntryCount(); // it's set to 10 in "small" query_mem_descriptor
rs1_groups.resize(rs_entry_count);
std::fill(rs1_groups.begin(), rs1_groups.end(), false);
rs2_groups.resize(rs_entry_count);
std::fill(rs2_groups.begin(), rs2_groups.end(), false);
rs1_values.resize(rs_entry_count);
std::fill(rs1_values.begin(), rs1_values.end(), 0);
rs2_values.resize(rs_entry_count);
std::fill(rs2_values.begin(), rs2_values.end(), 0);
rseReducedGroups.resize(rs_entry_count);
std::fill(rseReducedGroups.begin(), rseReducedGroups.end(), false);
emulateResultSets();
}
~ResultSetEmulator(){};
std::queue<std::vector<int64_t>> getReferenceTable() const { return rseReducedTable; }
std::vector<bool> getReferenceGroupMap() const { return rseReducedGroups; }
bool getReferenceGroupMapElement(size_t idx) {
CHECK_LE(idx, rseReducedGroups.size() - 1);
return rseReducedGroups[idx];
}
std::vector<int64_t> getReferenceRow(bool keep_row = false) {
std::vector<int64_t> rse_reduced_row(rseReducedTable.front());
rseReducedTable.pop();
if (keep_row) {
rseReducedTable.push(rse_reduced_row);
}
return rse_reduced_row;
}
int64_t rse_get_null_val() {
int64_t null_val = 0;
for (const auto& target_info : rs_target_infos) {
null_val = inline_int_null_val(target_info.sql_type);
break; // currently all of TargetInfo's columns used in tests have same type, so
// the they all share same null_val, and that's why the first column is used
// here.
}
return null_val;
}
void print_rse_generated_result_sets() const;
void print_merged_result_sets(const std::vector<OneRow>& result);
private:
void emulateResultSets();
void createResultSet(size_t rs_perc, std::vector<bool>& rs_groups);
void mergeResultSets();
int8_t *rs1_buff, *rs2_buff;
const std::vector<TargetInfo> rs_target_infos;
const QueryMemoryDescriptor rs_query_mem_desc;
NumberGenerator &rs1_gen, &rs2_gen;
size_t rs1_perc, rs2_perc, rs_flow;
size_t rs_entry_count;
bool rs_silent;
std::vector<bool> rs1_groups; // true if group is in ResultSet #1
std::vector<bool> rs2_groups; // true if group is in ResultSet #2
std::vector<bool>
rseReducedGroups; // true if group is in either ResultSet #1 or ResultSet #2
std::vector<int64_t> rs1_values; // generated values for ResultSet #1
std::vector<int64_t> rs2_values; // generated values for ResultSet #2
std::queue<std::vector<int64_t>>
rseReducedTable; // combined/reduced values of ResultSet #1 and ResultSet #2
void rse_fill_storage_buffer_perfect_hash_colwise(int8_t* buff,
NumberGenerator& generator,
const std::vector<bool>& rs_groups,
std::vector<int64_t>& rs_values);
void rse_fill_storage_buffer_perfect_hash_rowwise(int8_t* buff,
NumberGenerator& generator,
const std::vector<bool>& rs_groups,
std::vector<int64_t>& rs_values);
void rse_fill_storage_buffer_baseline_colwise(int8_t* buff,
NumberGenerator& generator,
const std::vector<bool>& rs_groups,
std::vector<int64_t>& rs_values);
void rse_fill_storage_buffer_baseline_rowwise(int8_t* buff,
NumberGenerator& generator,
const std::vector<bool>& rs_groups,
std::vector<int64_t>& rs_values);
void rse_fill_storage_buffer(int8_t* buff,
NumberGenerator& generator,
const std::vector<bool>& rs_groups,
std::vector<int64_t>& rs_values);
void print_emulator_diag();
int64_t rseAggregateKMIN(size_t i);
int64_t rseAggregateKMAX(size_t i);
int64_t rseAggregateKAVG(size_t i);
int64_t rseAggregateKSUM(size_t i);
int64_t rseAggregateKCOUNT(size_t i);
};
/* top level module to create and fill up ResultSets as well as to generate golden values
*/
void ResultSetEmulator::emulateResultSets() {
/* generate topology of ResultSet #1 */
if (!rs_silent) {
printf("\nResultSetEmulator (ResultSet #1): ");
}
createResultSet(rs1_perc, rs1_groups);
if (!rs_silent) {
printf("\n");
for (size_t i = 0; i < rs1_groups.size(); i++) {
if (rs1_groups[i]) {
printf("1");
} else {
printf("0");
}
}
}
/* generate topology of ResultSet #2 */
if (!rs_silent) {
printf("\nResultSetEmulator (ResultSet #2): ");
}
createResultSet(rs2_perc, rs2_groups);
if (!rs_silent) {
printf("\n");
for (size_t i = 0; i < rs2_groups.size(); i++) {
if (rs2_groups[i]) {
printf("1");
} else {
printf("0");
}
}
printf("\n");
}
/* populate both ResultSet's buffers with real data */
// print_emulator_diag();
rse_fill_storage_buffer(rs1_buff, rs1_gen, rs1_groups, rs1_values);
// print_emulator_diag();
rse_fill_storage_buffer(rs2_buff, rs2_gen, rs2_groups, rs2_values);
// print_emulator_diag();
/* merge/reduce data contained in both ResultSets and generate golden values */
mergeResultSets();
}
/* generate ResultSet topology (create rs_groups and rs_groups_idx vectors) */
void ResultSetEmulator::createResultSet(size_t rs_perc, std::vector<bool>& rs_groups) {
std::vector<int> rs_groups_idx;
rs_groups_idx.resize(rs_entry_count);
std::iota(rs_groups_idx.begin(), rs_groups_idx.end(), 0);
std::random_device rs_rd;
std::mt19937 rs_rand_gen(rs_rd());
std::shuffle(rs_groups_idx.begin(), rs_groups_idx.end(), rs_rand_gen);
for (size_t i = 0; i < (rs_entry_count * rs_perc / 100); i++) {
if (!rs_silent) {
printf(" %i", rs_groups_idx[i]);
}
rs_groups[rs_groups_idx[i]] = true;
}
}
/* merge/reduce data contained in both ResultSets and generate golden values */
void ResultSetEmulator::mergeResultSets() {
std::vector<int64_t> rse_reduced_row;
rse_reduced_row.resize(rs_target_infos.size());
for (size_t j = 0; j < rs_entry_count; j++) { // iterates through rows
if (rs1_groups[j] || rs2_groups[j]) {
rseReducedGroups[j] = true;
for (size_t i = 0; i < rs_target_infos.size(); i++) { // iterates through columns
switch (rs_target_infos[i].agg_kind) {
case kMIN: {
rse_reduced_row[i] = rseAggregateKMIN(j);
break;
}
case kMAX: {
rse_reduced_row[i] = rseAggregateKMAX(j);
break;
}
case kAVG: {
rse_reduced_row[i] = rseAggregateKAVG(j);
break;
}
case kSUM: {
rse_reduced_row[i] = rseAggregateKSUM(j);
break;
}
case kCOUNT: {
rse_reduced_row[i] = rseAggregateKCOUNT(j);
break;
}
default:
CHECK(false);
}
}
rseReducedTable.push(rse_reduced_row);
}
}
}
void ResultSetEmulator::rse_fill_storage_buffer_perfect_hash_colwise(
int8_t* buff,
NumberGenerator& generator,
const std::vector<bool>& rs_groups,
std::vector<int64_t>& rs_values) {
const auto key_component_count = rs_query_mem_desc.getKeyCount();
CHECK(rs_query_mem_desc.didOutputColumnar());
// initialize the key buffer(s)
auto col_ptr = buff;
for (size_t key_idx = 0; key_idx < key_component_count; ++key_idx) {
auto key_entry_ptr = col_ptr;
const auto key_bytes = rs_query_mem_desc.groupColWidth(key_idx);
CHECK_EQ(8, key_bytes);
for (size_t i = 0; i < rs_entry_count; i++) {
const auto v = generator.getNextValue();
if (rs_groups[i]) {
// const auto v = generator.getNextValue();
write_key(v, key_entry_ptr, key_bytes);
} else {
write_key(EMPTY_KEY_64, key_entry_ptr, key_bytes);
}
key_entry_ptr += key_bytes;
}
col_ptr = advance_to_next_columnar_key_buff(col_ptr, rs_query_mem_desc, key_idx);
generator.reset();
}
// initialize the value buffer(s)
size_t slot_idx = 0;
for (const auto& target_info : rs_target_infos) {
auto col_entry_ptr = col_ptr;
const auto col_bytes = rs_query_mem_desc.getPaddedSlotWidthBytes(slot_idx);
for (size_t i = 0; i < rs_entry_count; i++) {
int8_t* ptr2{nullptr};
if (target_info.agg_kind == kAVG) {
ptr2 = col_entry_ptr + rs_query_mem_desc.getEntryCount() * col_bytes;
}
const auto v = generator.getNextValue();
if (rs_groups[i]) {
// const auto v = generator.getNextValue();
rs_values[i] = v;
if (rs_flow == 2 && // null_val test-cases
i >= rs_entry_count - 4) { // only the last four rows of RS #1 and RS #2
// exersized for null_val test
rs_values[i] = -1;
fill_one_entry_one_col(col_entry_ptr,
col_bytes,
ptr2,
rs_query_mem_desc.getPaddedSlotWidthBytes(slot_idx + 1),
v,
target_info,
false,
true);
} else {
fill_one_entry_one_col(col_entry_ptr,
col_bytes,
ptr2,
rs_query_mem_desc.getPaddedSlotWidthBytes(slot_idx + 1),
v,
target_info,
false,
false);
}
} else {
if (rs_flow == 2) { // null_val test-cases
if (i >= rs_entry_count - 4) { // only the last four rows of RS #1 and RS #2
// exersized for null_val test
rs_values[i] = -1;
}
fill_one_entry_one_col(col_entry_ptr,
col_bytes,
ptr2,
rs_query_mem_desc.getPaddedSlotWidthBytes(slot_idx + 1),
rs_query_mem_desc.hasKeylessHash() ? 0 : 0xdeadbeef,
target_info,
true,
true);
} else {
fill_one_entry_one_col(col_entry_ptr,
col_bytes,
ptr2,
rs_query_mem_desc.getPaddedSlotWidthBytes(slot_idx + 1),
rs_query_mem_desc.hasKeylessHash() ? 0 : 0xdeadbeef,
target_info,
true,
false);
}
}
col_entry_ptr += col_bytes;
}
col_ptr = advance_to_next_columnar_target_buff(col_ptr, rs_query_mem_desc, slot_idx);
if (target_info.is_agg && target_info.agg_kind == kAVG) {
col_ptr =
advance_to_next_columnar_target_buff(col_ptr, rs_query_mem_desc, slot_idx + 1);
}
slot_idx = advance_slot(slot_idx, target_info, false);
generator.reset();
}
}
void ResultSetEmulator::rse_fill_storage_buffer_perfect_hash_rowwise(
int8_t* buff,
NumberGenerator& generator,
const std::vector<bool>& rs_groups,
std::vector<int64_t>& rs_values) {
const auto key_component_count = rs_query_mem_desc.getKeyCount();
CHECK(!rs_query_mem_desc.didOutputColumnar());
auto key_buff = buff;
CHECK_EQ(rs_groups.size(), rs_query_mem_desc.getEntryCount());
for (size_t i = 0; i < rs_groups.size(); i++) {
const auto v = generator.getNextValue();
if (rs_groups[i]) {
// const auto v = generator.getNextValue();
rs_values[i] = v;
auto key_buff_i64 = reinterpret_cast<int64_t*>(key_buff);
for (size_t key_comp_idx = 0; key_comp_idx < key_component_count; ++key_comp_idx) {
*key_buff_i64++ = v;
}
auto entries_buff = reinterpret_cast<int8_t*>(key_buff_i64);
if (rs_flow == 2) { // null_vall test-cases
if (i >= rs_entry_count - 4) { // only the last four rows of RS #1 and RS #2
// exersized for null_val test
rs_values[i] = -1;
key_buff = fill_one_entry_no_collisions(
entries_buff, rs_query_mem_desc, v, rs_target_infos, false, true);
} else {
key_buff = fill_one_entry_no_collisions(
entries_buff, rs_query_mem_desc, v, rs_target_infos, false, false);
}
} else {
key_buff = fill_one_entry_no_collisions(
entries_buff, rs_query_mem_desc, v, rs_target_infos, false);
}
} else {
auto key_buff_i64 = reinterpret_cast<int64_t*>(key_buff);
for (size_t key_comp_idx = 0; key_comp_idx < key_component_count; ++key_comp_idx) {
*key_buff_i64++ = EMPTY_KEY_64;
}
auto entries_buff = reinterpret_cast<int8_t*>(key_buff_i64);
if (rs_flow == 2) { // null_val test-cases
if (i >= rs_entry_count - 4) { // only the last four rows of RS #1 and RS #2
// exersized for null_val test
rs_values[i] = -1;
}
key_buff = fill_one_entry_no_collisions(
entries_buff, rs_query_mem_desc, 0xdeadbeef, rs_target_infos, true, true);
} else {
key_buff = fill_one_entry_no_collisions(
entries_buff, rs_query_mem_desc, 0xdeadbeef, rs_target_infos, true);
}
}
}
}
void ResultSetEmulator::rse_fill_storage_buffer_baseline_colwise(
int8_t* buff,
NumberGenerator& generator,
const std::vector<bool>& rs_groups,
std::vector<int64_t>& rs_values) {
CHECK(rs_query_mem_desc.didOutputColumnar());
const auto key_component_count = rs_query_mem_desc.getKeyCount();
const auto i64_buff = reinterpret_cast<int64_t*>(buff);
for (size_t i = 0; i < rs_entry_count; i++) {
for (size_t key_comp_idx = 0; key_comp_idx < key_component_count; ++key_comp_idx) {
i64_buff[key_offset_colwise(i, key_comp_idx, rs_entry_count)] = EMPTY_KEY_64;
}
size_t target_slot = 0;
int64_t init_val = 0;
for (const auto& target_info : rs_target_infos) {
if (target_info.agg_kind == kCOUNT) {
init_val = 0;
} else if (!target_info.sql_type.get_notnull() && target_info.skip_null_val &&
(rs_flow == 2)) { // null_val support
init_val = inline_int_null_val(target_info.sql_type);
} else {
init_val = 0xdeadbeef;
}
if (target_info.agg_kind != kAVG) {
i64_buff[slot_offset_colwise(
i, target_slot, key_component_count, rs_entry_count)] = init_val;
} else {
i64_buff[slot_offset_colwise(
i, target_slot, key_component_count, rs_entry_count)] = 0;
}
target_slot++;
}
}
for (size_t i = 0; i < rs_entry_count; i++) {
const auto v = generator.getNextValue();
if (rs_groups[i]) {
bool null_val = false;
if ((rs_flow == 2) &&
(i >= rs_entry_count - 4)) { // null_val test-cases: last four rows
rs_values[i] = -1;
null_val = true;
} else {
rs_values[i] = v;
}
std::vector<int64_t> key(key_component_count, v);
auto value_slots =
get_group_value_columnar(i64_buff, rs_entry_count, &key[0], key.size());
CHECK(value_slots);
for (const auto& target_info : rs_target_infos) {
fill_one_entry_one_col(
value_slots, v, target_info, rs_entry_count, false, null_val);
value_slots += rs_entry_count;
if (target_info.agg_kind == kAVG) {
value_slots += rs_entry_count;
}
}
}
}
}
void ResultSetEmulator::rse_fill_storage_buffer_baseline_rowwise(
int8_t* buff,
NumberGenerator& generator,
const std::vector<bool>& rs_groups,
std::vector<int64_t>& rs_values) {
CHECK(!rs_query_mem_desc.didOutputColumnar());
CHECK_EQ(rs_groups.size(), rs_query_mem_desc.getEntryCount());
const auto key_component_count = rs_query_mem_desc.getKeyCount();
const auto i64_buff = reinterpret_cast<int64_t*>(buff);
const auto target_slot_count = get_slot_count(rs_target_infos);
for (size_t i = 0; i < rs_entry_count; i++) {
const auto first_key_comp_offset =
key_offset_rowwise(i, key_component_count, target_slot_count);
for (size_t key_comp_idx = 0; key_comp_idx < key_component_count; ++key_comp_idx) {
i64_buff[first_key_comp_offset + key_comp_idx] = EMPTY_KEY_64;
}
size_t target_slot = 0;
int64_t init_val = 0;
for (const auto& target_info : rs_target_infos) {
if (target_info.agg_kind == kCOUNT) {
init_val = 0;
} else if (!target_info.sql_type.get_notnull() && target_info.skip_null_val &&
(rs_flow == 2)) { // null_val support
init_val = inline_int_null_val(target_info.sql_type);
} else {
init_val = 0xdeadbeef;
}
i64_buff[slot_offset_rowwise(
i, target_slot, key_component_count, target_slot_count)] = init_val;
target_slot++;
if (target_info.agg_kind == kAVG) {
i64_buff[slot_offset_rowwise(
i, target_slot, key_component_count, target_slot_count)] = 0;
target_slot++;
}
}
}
for (size_t i = 0; i < rs_entry_count; i++) {
const auto v = generator.getNextValue();
if (rs_groups[i]) {
std::vector<int64_t> key(key_component_count, v);
auto value_slots = get_group_value(i64_buff,
rs_entry_count,
&key[0],
key.size(),
sizeof(int64_t),
key_component_count + target_slot_count);
CHECK(value_slots);
if ((rs_flow == 2) &&
(i >= rs_entry_count - 4)) { // null_val test-cases: last four rows
rs_values[i] = -1;
fill_one_entry_baseline(value_slots, v, rs_target_infos, false, true);
} else {
rs_values[i] = v;
fill_one_entry_baseline(value_slots, v, rs_target_infos, false, false);
}
}
}
}
void ResultSetEmulator::rse_fill_storage_buffer(int8_t* buff,
NumberGenerator& generator,
const std::vector<bool>& rs_groups,
std::vector<int64_t>& rs_values) {
switch (rs_query_mem_desc.getQueryDescriptionType()) {
case QueryDescriptionType::GroupByPerfectHash: {
if (rs_query_mem_desc.didOutputColumnar()) {
rse_fill_storage_buffer_perfect_hash_colwise(
buff, generator, rs_groups, rs_values);
} else {
rse_fill_storage_buffer_perfect_hash_rowwise(
buff, generator, rs_groups, rs_values);
}
break;
}
case QueryDescriptionType::GroupByBaselineHash: {
if (rs_query_mem_desc.didOutputColumnar()) {
rse_fill_storage_buffer_baseline_colwise(buff, generator, rs_groups, rs_values);
} else {
rse_fill_storage_buffer_baseline_rowwise(buff, generator, rs_groups, rs_values);
}
break;
}
default:
CHECK(false);
}
CHECK(buff);
}
#ifdef __clang__
#pragma clang diagnostic push
#pragma clang diagnostic ignored "-Wunused-function"
#else
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wunused-function"
#endif
void ResultSetEmulator::print_emulator_diag() {
if (!rs_silent) {
for (size_t j = 0; j < rs_entry_count; j++) {
int g1 = 0, g2 = 0;
if (rs1_groups[j]) {
g1 = 1;
}
if (rs2_groups[j]) {
g2 = 1;
}
printf("\nGroup #%i (%i,%i): Buf1=%lld Buf2=%lld",
(int)j,
g1,
g2,
static_cast<long long>(rs1_values[j]),
static_cast<long long>(rs2_values[j]));
}
}
}
#ifdef __clang__
#pragma clang diagnostic pop
#else
#pragma GCC diagnostic pop
#endif
void ResultSetEmulator::print_rse_generated_result_sets() const {
printf("\nResultSet #1 Final Groups: ");
for (size_t i = 0; i < rs1_groups.size(); i++) {
if (rs1_groups[i]) {
printf("1");
} else {
printf("0");
}
}
printf("\nResultSet #2 Final Groups: ");
for (size_t i = 0; i < rs2_groups.size(); i++) {
if (rs2_groups[i]) {
printf("1");
} else {
printf("0");
}
}
printf("\n");
}
void ResultSetEmulator::print_merged_result_sets(const std::vector<OneRow>& result) {
printf("\n ****** KMIN_DATA_FROM_RS_MERGE_CODE ****** %i", (int)result.size());
size_t j = 0;
for (const auto& row : result) {
const auto ival_0 = v<int64_t>(row[0]); // kMIN
const auto ival_1 = v<int64_t>(row[1]); // kMAX
const auto ival_2 = v<int64_t>(row[2]); // kSUM
const auto ival_3 = v<int64_t>(row[3]); // kCOUNT
const auto ival_4 = v<double>(row[4]); // kAVG
printf("\n Group #%i KMIN/KMAX/KSUM/KCOUNT from RS_MergeCode: %lld %lld %lld %lld %f",
(int)j,
static_cast<long long>(ival_0),
static_cast<long long>(ival_1),
static_cast<long long>(ival_2),
static_cast<long long>(ival_3),
ival_4);
j++;
}
size_t active_group_count = 0;
for (size_t j = 0; j < rseReducedGroups.size(); j++) {
if (rseReducedGroups[j]) {
active_group_count++;
}
}
printf("\n\n ****** KMIN_DATA_FROM_MERGE_BUFFER_CODE ****** Total: %i, Active: %i",
(int)rs_entry_count,
(int)active_group_count);
size_t num_groups = getReferenceTable().size();
for (size_t i = 0; i < num_groups; i++) {
std::vector<int64_t> ref_row = getReferenceRow(true);
int64_t ref_val_0 = ref_row[0]; // kMIN
int64_t ref_val_1 = ref_row[1]; // kMAX
int64_t ref_val_2 = ref_row[2]; // kSUM
int64_t ref_val_3 = ref_row[3]; // kCOUNT
int64_t ref_val_4 = ref_row[4]; // kAVG
printf(
"\n Group #%i KMIN/KMAX/KSUM/KCOUNT from ReducedBuffer: %lld %lld %lld %lld %f",
static_cast<int>(i),
static_cast<long long>(ref_val_0),
static_cast<long long>(ref_val_1),
static_cast<long long>(ref_val_2),
static_cast<long long>(ref_val_3),
static_cast<double>(ref_val_4));
}
printf("\n");
}
int64_t ResultSetEmulator::rseAggregateKMIN(size_t i) {
int64_t result = rse_get_null_val();
if (rs1_groups[i] && rs2_groups[i]) {
if ((rs1_values[i] == -1) && (rs2_values[i] == -1)) {
return result;
} else {
if ((rs1_values[i] != -1) && (rs2_values[i] != -1)) {
result = std::min(rs1_values[i], rs2_values[i]);
} else {
result = std::max(rs1_values[i], rs2_values[i]);
}
}
} else {
if (rs1_groups[i]) {
if (rs1_values[i] != -1) {
result = rs1_values[i];
}
} else {
if (rs2_groups[i]) {
if (rs2_values[i] != -1) {
result = rs2_values[i];
}
}
}
}
return result;
}
int64_t ResultSetEmulator::rseAggregateKMAX(size_t i) {
int64_t result = rse_get_null_val();
if (rs1_groups[i] && rs2_groups[i]) {
if ((rs1_values[i] == -1) && (rs2_values[i] == -1)) {
return result;
} else {
result = std::max(rs1_values[i], rs2_values[i]);
}
} else {
if (rs1_groups[i]) {
if (rs1_values[i] != -1) {
result = rs1_values[i];
}
} else {
if (rs2_groups[i]) {
if (rs2_values[i] != -1) {
result = rs2_values[i];
}
}
}
}
return result;
}
int64_t ResultSetEmulator::rseAggregateKAVG(size_t i) {
double result = 0;
int n1 = 1,
n2 = 1; // for test purposes count of elements in each group is 1 (see proc
// "fill_one_entry_no_collisions")
if (rs1_groups[i] && rs2_groups[i]) {
if ((rs1_values[i] == -1) && (rs2_values[i] == -1)) {
return shared::reinterpret_bits<int64_t>(NULL_DOUBLE);
}
int n = 0;
if (rs1_values[i] != -1) {
result += rs1_values[i] / n1;
n++;
}
if (rs2_values[i] != -1) {
result += rs2_values[i] / n2;
n++;
}
if (n > 1) {
result /= n;
}
} else {
result = NULL_DOUBLE;
if (rs1_groups[i]) {
if (rs1_values[i] != -1) {
result = rs1_values[i] / n1;
}
} else {
if (rs2_groups[i]) {
if (rs2_values[i] != -1) {
result = rs2_values[i] / n2;
}
}
}
}
return shared::reinterpret_bits<int64_t>(result);
}
int64_t ResultSetEmulator::rseAggregateKSUM(size_t i) {
int64_t result = 0;
if (rs1_groups[i] && rs2_groups[i]) {
if ((rs1_values[i] == -1) && (rs2_values[i] == -1)) {
return rse_get_null_val();
}
if (rs1_values[i] != -1) {
result += rs1_values[i];
}
if (rs2_values[i] != -1) {
result += rs2_values[i];
}
} else {
result = rse_get_null_val();
if (rs1_groups[i]) {
if (rs1_values[i] != -1) {
result = rs1_values[i];
}
} else {
if (rs2_groups[i]) {
if (rs2_values[i] != -1) {
result = rs2_values[i];
}
}
}
}
return result;
}
int64_t ResultSetEmulator::rseAggregateKCOUNT(size_t i) {
int64_t result = 0;
if (rs1_groups[i] && rs2_groups[i]) {
if ((rs1_values[i] == -1) && (rs2_values[i] == -1)) {
return 0;
}
if (rs1_values[i] != -1) {
result += rs1_values[i];
}
if (rs2_values[i] != -1) {
result += rs2_values[i];
}
} else {
if (rs1_groups[i]) {
if (rs1_values[i] != -1) {
result = rs1_values[i];
}
} else {
if (rs2_groups[i]) {
if (rs2_values[i] != -1) {
result = rs2_values[i];
}
}
}
}
return result;
}
constexpr double EPS = 0.01;
bool approx_eq(const double v, const double target, const double eps = EPS) {
return target - eps < v && v < target + eps;
}
DictRef invalid_dict_ref{DictRef::InvalidDictRef()};
std::shared_ptr<StringDictionary> g_sd =
std::make_shared<StringDictionary>(invalid_dict_ref, "", false, true);
void test_iterate(const std::vector<TargetInfo>& target_infos,
const QueryMemoryDescriptor& query_mem_desc) {
SQLTypeInfo double_ti(kDOUBLE, false);
auto row_set_mem_owner = std::make_shared<RowSetMemoryOwner>(
Executor::getArenaBlockSize(), Executor::UNITARY_EXECUTOR_ID);
StringDictionaryProxy* sdp =
row_set_mem_owner->addStringDict(g_sd, {0, 1}, g_sd->storageEntryCount());
ResultSet result_set(
target_infos, ExecutorDeviceType::CPU, query_mem_desc, row_set_mem_owner, 0, 0);
for (size_t i = 0; i < query_mem_desc.getEntryCount(); ++i) {
sdp->getOrAddTransient(std::to_string(i));
}
const auto storage = result_set.allocateStorage();
EvenNumberGenerator generator;
fill_storage_buffer(
storage->getUnderlyingBuffer(), target_infos, query_mem_desc, generator, 2);
int64_t ref_val{0};
while (true) {
const auto row = result_set.getNextRow(true, false);
if (row.empty()) {
break;
}
CHECK_EQ(target_infos.size(), row.size());
for (size_t i = 0; i < target_infos.size(); ++i) {
const auto& target_info = target_infos[i];
const auto& ti = target_info.agg_kind == kAVG ? double_ti : target_info.sql_type;
switch (ti.get_type()) {
case kTINYINT:
case kSMALLINT:
case kINT:
case kBIGINT: {
const auto ival = v<int64_t>(row[i]);
ASSERT_EQ(ref_val, ival);
break;
}
case kDOUBLE: {
const auto dval = v<double>(row[i]);
ASSERT_NEAR(ref_val, dval, EPS);
break;
}
case kTEXT: {
const auto sval = v<NullableString>(row[i]);
ASSERT_EQ(std::to_string(ref_val), boost::get<std::string>(sval));
break;
}
default:
CHECK(false);
}
}
ref_val += 2;
}
}
std::vector<TargetInfo> generate_test_target_infos() {
std::vector<TargetInfo> target_infos;
SQLTypeInfo int_ti(kINT, false);
SQLTypeInfo double_ti(kDOUBLE, false);
SQLTypeInfo null_ti(kNULLT, false);
target_infos.push_back(TargetInfo{false, kMIN, int_ti, null_ti, true, false});
target_infos.push_back(TargetInfo{true, kAVG, int_ti, int_ti, true, false});
target_infos.push_back(TargetInfo{true, kSUM, int_ti, int_ti, true, false});
target_infos.push_back(TargetInfo{false, kMIN, double_ti, null_ti, true, false});
{
SQLTypeInfo dict_string_ti(kTEXT, false);
dict_string_ti.set_compression(kENCODING_DICT);
dict_string_ti.set_comp_param(1);
dict_string_ti.setStringDictKey({0, 1});
target_infos.push_back(TargetInfo{false, kMIN, dict_string_ti, null_ti, true, false});
}
return target_infos;
}
std::vector<TargetInfo> generate_random_groups_target_infos() {
std::vector<TargetInfo> target_infos;
SQLTypeInfo int_ti(kINT, true);
SQLTypeInfo double_ti(kDOUBLE, true);
// SQLTypeInfo null_ti(kNULLT, false);
target_infos.push_back(TargetInfo{true, kMIN, int_ti, int_ti, true, false});
target_infos.push_back(TargetInfo{true, kMAX, int_ti, int_ti, true, false});
target_infos.push_back(TargetInfo{true, kSUM, int_ti, int_ti, true, false});
target_infos.push_back(TargetInfo{true, kCOUNT, int_ti, int_ti, true, false});
target_infos.push_back(TargetInfo{true, kAVG, int_ti, double_ti, true, false});
return target_infos;
}
std::vector<TargetInfo> generate_random_groups_nullable_target_infos() {
std::vector<TargetInfo> target_infos;
SQLTypeInfo int_ti(kINT, false);
SQLTypeInfo double_ti(kDOUBLE, false);
target_infos.push_back(TargetInfo{true, kMIN, int_ti, int_ti, true, false});
target_infos.push_back(TargetInfo{true, kMAX, int_ti, int_ti, true, false});
target_infos.push_back(TargetInfo{true, kSUM, int_ti, int_ti, true, false});
target_infos.push_back(TargetInfo{true, kCOUNT, int_ti, int_ti, true, false});
target_infos.push_back(TargetInfo{true, kAVG, int_ti, double_ti, true, false});
return target_infos;
}
std::vector<OneRow> get_rows_sorted_by_col(ResultSet& rs, const size_t col_idx) {
std::list<Analyzer::OrderEntry> order_entries;
order_entries.emplace_back(1, false, false);
rs.sort(order_entries, 0, ExecutorDeviceType::CPU, nullptr);
std::vector<OneRow> result;
while (true) {
const auto row = rs.getNextRow(false, false);
if (row.empty()) {
break;
}
result.push_back(row);
}
return result;
}
#ifndef HAVE_TSAN
void run_reduction(const std::vector<TargetInfo>& target_infos,
const QueryMemoryDescriptor& query_mem_desc,
NumberGenerator& generator1,
NumberGenerator& generator2,
const int step) {
const ResultSetStorage* storage1{nullptr};
const ResultSetStorage* storage2{nullptr};
const auto row_set_mem_owner = std::make_shared<RowSetMemoryOwner>(