OmniSciDB  c0231cc57d
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Macros Groups Pages
InputMetadata.cpp
Go to the documentation of this file.
1 /*
2  * Copyright 2022 HEAVY.AI, Inc.
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  * http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16 
17 #include "InputMetadata.h"
18 #include "Execute.h"
19 
20 #include "../Fragmenter/Fragmenter.h"
21 
22 #include <tbb/parallel_for.h>
23 #include <tbb/task_arena.h>
24 #include <future>
25 
26 extern bool g_enable_data_recycler;
27 extern bool g_use_chunk_metadata_cache;
28 
29 InputTableInfoCache::InputTableInfoCache(Executor* executor) : executor_(executor) {}
30 
31 namespace {
32 
34  const Fragmenter_Namespace::TableInfo& table_info) {
35  Fragmenter_Namespace::TableInfo table_info_copy;
36  table_info_copy.chunkKeyPrefix = table_info.chunkKeyPrefix;
37  table_info_copy.fragments = table_info.fragments;
38  table_info_copy.setPhysicalNumTuples(table_info.getPhysicalNumTuples());
39  return table_info_copy;
40 }
41 
42 } // namespace
43 
45  const std::vector<const TableDescriptor*>& shard_tables) {
46  size_t total_number_of_tuples{0};
47  Fragmenter_Namespace::TableInfo table_info_all_shards;
48  for (const TableDescriptor* shard_table : shard_tables) {
49  CHECK(shard_table->fragmenter);
50  const auto& shard_metainfo = shard_table->fragmenter->getFragmentsForQuery();
51  total_number_of_tuples += shard_metainfo.getPhysicalNumTuples();
52  table_info_all_shards.fragments.reserve(table_info_all_shards.fragments.size() +
53  shard_metainfo.fragments.size());
54  table_info_all_shards.fragments.insert(table_info_all_shards.fragments.end(),
55  shard_metainfo.fragments.begin(),
56  shard_metainfo.fragments.end());
57  }
58  table_info_all_shards.setPhysicalNumTuples(total_number_of_tuples);
59  return table_info_all_shards;
60 }
61 
63  const auto it = cache_.find(table_id);
64  if (it != cache_.end()) {
65  const auto& table_info = it->second;
66  return copy_table_info(table_info);
67  }
68  const auto cat = executor_->getCatalog();
69  CHECK(cat);
70  const auto td = cat->getMetadataForTable(table_id);
71  CHECK(td);
72  const auto shard_tables = cat->getPhysicalTablesDescriptors(td);
73  auto table_info = build_table_info(shard_tables);
74  auto it_ok = cache_.emplace(table_id, copy_table_info(table_info));
75  CHECK(it_ok.second);
76  return copy_table_info(table_info);
77 }
78 
80  decltype(cache_)().swap(cache_);
81 }
82 
83 namespace {
84 
85 bool uses_int_meta(const SQLTypeInfo& col_ti) {
86  return col_ti.is_integer() || col_ti.is_decimal() || col_ti.is_time() ||
87  col_ti.is_boolean() ||
88  (col_ti.is_string() && col_ti.get_compression() == kENCODING_DICT);
89 }
90 
92  std::vector<Fragmenter_Namespace::FragmentInfo> result;
93  if (rows) {
94  result.resize(1);
95  auto& fragment = result.front();
96  fragment.fragmentId = 0;
97  fragment.deviceIds.resize(3);
98  fragment.resultSet = rows.get();
99  fragment.resultSetMutex.reset(new std::mutex());
100  }
102  table_info.fragments = result;
103  return table_info;
104 }
105 
106 void collect_table_infos(std::vector<InputTableInfo>& table_infos,
107  const std::vector<InputDescriptor>& input_descs,
108  Executor* executor) {
109  const auto temporary_tables = executor->getTemporaryTables();
110  const auto cat = executor->getCatalog();
111  CHECK(cat);
112  std::unordered_map<int, size_t> info_cache;
113  for (const auto& input_desc : input_descs) {
114  const auto table_id = input_desc.getTableId();
115  const auto cached_index_it = info_cache.find(table_id);
116  if (cached_index_it != info_cache.end()) {
117  CHECK_LT(cached_index_it->second, table_infos.size());
118  table_infos.push_back(
119  {table_id, copy_table_info(table_infos[cached_index_it->second].info)});
120  continue;
121  }
122  if (input_desc.getSourceType() == InputSourceType::RESULT) {
123  CHECK_LT(table_id, 0);
124  CHECK(temporary_tables);
125  const auto it = temporary_tables->find(table_id);
126  LOG_IF(FATAL, it == temporary_tables->end())
127  << "Failed to find previous query result for node " << -table_id;
128  table_infos.push_back({table_id, synthesize_table_info(it->second)});
129  } else {
130  CHECK(input_desc.getSourceType() == InputSourceType::TABLE);
131  table_infos.push_back({table_id, executor->getTableInfo(table_id)});
132  }
133  CHECK(!table_infos.empty());
134  info_cache.insert(std::make_pair(table_id, table_infos.size() - 1));
135  }
136 }
137 
138 } // namespace
139 
140 template <typename T>
142  std::shared_ptr<ChunkMetadata>& chunk_metadata,
143  const T* col_buffer,
144  const T null_val) {
145  const size_t row_count = chunk_metadata->numElements;
146  T min_val{std::numeric_limits<T>::max()};
147  T max_val{std::numeric_limits<T>::lowest()};
148  bool has_nulls{false};
149  constexpr size_t parallel_stats_compute_threshold = 20000UL;
150  if (row_count < parallel_stats_compute_threshold) {
151  for (size_t row_idx = 0; row_idx < row_count; ++row_idx) {
152  const T cell_val = col_buffer[row_idx];
153  if (cell_val == null_val) {
154  has_nulls = true;
155  continue;
156  }
157  if (cell_val < min_val) {
158  min_val = cell_val;
159  }
160  if (cell_val > max_val) {
161  max_val = cell_val;
162  }
163  }
164  } else {
165  const size_t max_thread_count = std::thread::hardware_concurrency();
166  const size_t max_inputs_per_thread = 20000;
167  const size_t min_grain_size = max_inputs_per_thread / 2;
168  const size_t num_threads =
169  std::min(max_thread_count,
170  ((row_count + max_inputs_per_thread - 1) / max_inputs_per_thread));
171 
172  std::vector<T> threads_local_mins(num_threads, std::numeric_limits<T>::max());
173  std::vector<T> threads_local_maxes(num_threads, std::numeric_limits<T>::lowest());
174  std::vector<bool> threads_local_has_nulls(num_threads, false);
175  tbb::task_arena limited_arena(num_threads);
176 
177  limited_arena.execute([&] {
179  tbb::blocked_range<size_t>(0, row_count, min_grain_size),
180  [&](const tbb::blocked_range<size_t>& r) {
181  const size_t start_idx = r.begin();
182  const size_t end_idx = r.end();
183  T local_min_val = std::numeric_limits<T>::max();
184  T local_max_val = std::numeric_limits<T>::lowest();
185  bool local_has_nulls = false;
186  for (size_t row_idx = start_idx; row_idx < end_idx; ++row_idx) {
187  const T cell_val = col_buffer[row_idx];
188  if (cell_val == null_val) {
189  local_has_nulls = true;
190  continue;
191  }
192  if (cell_val < local_min_val) {
193  local_min_val = cell_val;
194  }
195  if (cell_val > local_max_val) {
196  local_max_val = cell_val;
197  }
198  }
199  size_t thread_idx = tbb::this_task_arena::current_thread_index();
200  if (local_min_val < threads_local_mins[thread_idx]) {
201  threads_local_mins[thread_idx] = local_min_val;
202  }
203  if (local_max_val > threads_local_maxes[thread_idx]) {
204  threads_local_maxes[thread_idx] = local_max_val;
205  }
206  if (local_has_nulls) {
207  threads_local_has_nulls[thread_idx] = true;
208  }
209  },
210  tbb::simple_partitioner());
211  });
212 
213  for (size_t thread_idx = 0; thread_idx < num_threads; ++thread_idx) {
214  if (threads_local_mins[thread_idx] < min_val) {
215  min_val = threads_local_mins[thread_idx];
216  }
217  if (threads_local_maxes[thread_idx] > max_val) {
218  max_val = threads_local_maxes[thread_idx];
219  }
220  has_nulls |= threads_local_has_nulls[thread_idx];
221  }
222  }
223  chunk_metadata->fillChunkStats(min_val, max_val, has_nulls);
224 }
225 
227  CHECK(rows->getQueryMemDesc().getQueryDescriptionType() ==
229  CHECK(rows->didOutputColumnar());
230  CHECK(!(rows->areAnyColumnsLazyFetched()));
231  const size_t col_count = rows->colCount();
232  const auto row_count = rows->entryCount();
233 
234  ChunkMetadataMap chunk_metadata_map;
235 
236  for (size_t col_idx = 0; col_idx < col_count; ++col_idx) {
237  const int8_t* columnar_buffer = const_cast<int8_t*>(rows->getColumnarBuffer(col_idx));
238  const auto col_sql_type_info = rows->getColType(col_idx);
239  const auto col_type = col_sql_type_info.get_type();
240  if (col_type != kTEXT) {
241  CHECK(col_sql_type_info.get_compression() == kENCODING_NONE);
242  } else {
243  CHECK(col_sql_type_info.get_compression() == kENCODING_DICT);
244  CHECK_EQ(col_sql_type_info.get_size(), sizeof(int32_t));
245  }
246  std::shared_ptr<ChunkMetadata> chunk_metadata = std::make_shared<ChunkMetadata>();
247  chunk_metadata->sqlType = col_sql_type_info;
248  chunk_metadata->numBytes = row_count * col_sql_type_info.get_size();
249  chunk_metadata->numElements = row_count;
250 
251  switch (col_sql_type_info.get_type()) {
252  case kBOOLEAN:
253  case kTINYINT:
255  chunk_metadata,
256  columnar_buffer,
257  static_cast<int8_t>(inline_fixed_encoding_null_val(col_sql_type_info)));
258  break;
259  case kSMALLINT:
261  chunk_metadata,
262  reinterpret_cast<const int16_t*>(columnar_buffer),
263  static_cast<int16_t>(inline_fixed_encoding_null_val(col_sql_type_info)));
264  break;
265  case kINT:
267  chunk_metadata,
268  reinterpret_cast<const int32_t*>(columnar_buffer),
269  static_cast<int32_t>(inline_fixed_encoding_null_val(col_sql_type_info)));
270  break;
271  case kBIGINT:
272  case kTIMESTAMP:
274  chunk_metadata,
275  reinterpret_cast<const int64_t*>(columnar_buffer),
276  static_cast<int64_t>(inline_fixed_encoding_null_val(col_sql_type_info)));
277  break;
278  case kFLOAT:
279  // For float use the typed null accessor as the generic one converts to double,
280  // and do not want to risk loss of precision
282  chunk_metadata,
283  reinterpret_cast<const float*>(columnar_buffer),
285  break;
286  case kDOUBLE:
288  chunk_metadata,
289  reinterpret_cast<const double*>(columnar_buffer),
291  break;
292  case kTEXT:
294  chunk_metadata,
295  reinterpret_cast<const int32_t*>(columnar_buffer),
296  static_cast<int32_t>(inline_fixed_encoding_null_val(col_sql_type_info)));
297  break;
298  default:
299  UNREACHABLE();
300  }
301  chunk_metadata_map.emplace(col_idx, chunk_metadata);
302  }
303  return chunk_metadata_map;
304 }
305 
306 ChunkMetadataMap synthesize_metadata(const ResultSet* rows) {
307  auto timer = DEBUG_TIMER(__func__);
308  ChunkMetadataMap metadata_map;
309 
310  if (rows->definitelyHasNoRows()) {
311  // resultset has no valid storage, so we fill dummy metadata and return early
312  std::vector<std::unique_ptr<Encoder>> decoders;
313  for (size_t i = 0; i < rows->colCount(); ++i) {
314  decoders.emplace_back(Encoder::Create(nullptr, rows->getColType(i)));
315  const auto it_ok =
316  metadata_map.emplace(i, decoders.back()->getMetadata(rows->getColType(i)));
317  CHECK(it_ok.second);
318  }
319  return metadata_map;
320  }
321 
322  std::vector<std::vector<std::unique_ptr<Encoder>>> dummy_encoders;
323  const size_t worker_count =
325  for (size_t worker_idx = 0; worker_idx < worker_count; ++worker_idx) {
326  dummy_encoders.emplace_back();
327  for (size_t i = 0; i < rows->colCount(); ++i) {
328  const auto& col_ti = rows->getColType(i);
329  dummy_encoders.back().emplace_back(Encoder::Create(nullptr, col_ti));
330  }
331  }
332 
333  if (rows->getQueryMemDesc().getQueryDescriptionType() ==
336  }
337  rows->moveToBegin();
338  const auto do_work = [rows](const std::vector<TargetValue>& crt_row,
339  std::vector<std::unique_ptr<Encoder>>& dummy_encoders) {
340  for (size_t i = 0; i < rows->colCount(); ++i) {
341  const auto& col_ti = rows->getColType(i);
342  const auto& col_val = crt_row[i];
343  const auto scalar_col_val = boost::get<ScalarTargetValue>(&col_val);
344  CHECK(scalar_col_val);
345  if (uses_int_meta(col_ti)) {
346  const auto i64_p = boost::get<int64_t>(scalar_col_val);
347  CHECK(i64_p);
348  dummy_encoders[i]->updateStats(*i64_p, *i64_p == inline_int_null_val(col_ti));
349  } else if (col_ti.is_fp()) {
350  switch (col_ti.get_type()) {
351  case kFLOAT: {
352  const auto float_p = boost::get<float>(scalar_col_val);
353  CHECK(float_p);
354  dummy_encoders[i]->updateStats(*float_p,
355  *float_p == inline_fp_null_val(col_ti));
356  break;
357  }
358  case kDOUBLE: {
359  const auto double_p = boost::get<double>(scalar_col_val);
360  CHECK(double_p);
361  dummy_encoders[i]->updateStats(*double_p,
362  *double_p == inline_fp_null_val(col_ti));
363  break;
364  }
365  default:
366  CHECK(false);
367  }
368  } else {
369  throw std::runtime_error(col_ti.get_type_name() +
370  " is not supported in temporary table.");
371  }
372  }
373  };
375  const size_t worker_count = cpu_threads();
376  std::vector<std::future<void>> compute_stats_threads;
377  const auto entry_count = rows->entryCount();
378  for (size_t i = 0,
379  start_entry = 0,
380  stride = (entry_count + worker_count - 1) / worker_count;
381  i < worker_count && start_entry < entry_count;
382  ++i, start_entry += stride) {
383  const auto end_entry = std::min(start_entry + stride, entry_count);
384  compute_stats_threads.push_back(std::async(
386  [rows, &do_work, &dummy_encoders](
387  const size_t start, const size_t end, const size_t worker_idx) {
388  for (size_t i = start; i < end; ++i) {
389  const auto crt_row = rows->getRowAtNoTranslations(i);
390  if (!crt_row.empty()) {
391  do_work(crt_row, dummy_encoders[worker_idx]);
392  }
393  }
394  },
395  start_entry,
396  end_entry,
397  i));
398  }
399  for (auto& child : compute_stats_threads) {
400  child.wait();
401  }
402  for (auto& child : compute_stats_threads) {
403  child.get();
404  }
405  } else {
406  while (true) {
407  auto crt_row = rows->getNextRow(false, false);
408  if (crt_row.empty()) {
409  break;
410  }
411  do_work(crt_row, dummy_encoders[0]);
412  }
413  }
414  rows->moveToBegin();
415  for (size_t worker_idx = 1; worker_idx < worker_count; ++worker_idx) {
416  CHECK_LT(worker_idx, dummy_encoders.size());
417  const auto& worker_encoders = dummy_encoders[worker_idx];
418  for (size_t i = 0; i < rows->colCount(); ++i) {
419  dummy_encoders[0][i]->reduceStats(*worker_encoders[i]);
420  }
421  }
422  for (size_t i = 0; i < rows->colCount(); ++i) {
423  const auto it_ok =
424  metadata_map.emplace(i, dummy_encoders[0][i]->getMetadata(rows->getColType(i)));
425  CHECK(it_ok.second);
426  }
427  return metadata_map;
428 }
429 
430 size_t get_frag_count_of_table(const int table_id, Executor* executor) {
431  const auto temporary_tables = executor->getTemporaryTables();
432  CHECK(temporary_tables);
433  auto it = temporary_tables->find(table_id);
434  if (it != temporary_tables->end()) {
435  CHECK_GE(int(0), table_id);
436  return size_t(1);
437  } else {
438  const auto table_info = executor->getTableInfo(table_id);
439  return table_info.fragments.size();
440  }
441 }
442 
443 std::vector<InputTableInfo> get_table_infos(
444  const std::vector<InputDescriptor>& input_descs,
445  Executor* executor) {
446  std::vector<InputTableInfo> table_infos;
447  collect_table_infos(table_infos, input_descs, executor);
448  return table_infos;
449 }
450 
451 std::vector<InputTableInfo> get_table_infos(const RelAlgExecutionUnit& ra_exe_unit,
452  Executor* executor) {
454  std::vector<InputTableInfo> table_infos;
455  collect_table_infos(table_infos, ra_exe_unit.input_descs, executor);
456  return table_infos;
457 }
458 
461  bool need_to_compute_metadata = true;
462  // we disable chunk metadata recycler when filter pushdown is enabled
463  // since re-executing the query invalidates the cached metdata
464  // todo(yoonmin): relax this
465  bool enable_chunk_metadata_cache = g_enable_data_recycler &&
469  if (enable_chunk_metadata_cache) {
470  std::optional<ChunkMetadataMap> cached =
471  executor->getRecultSetRecyclerHolder().getCachedChunkMetadata(
472  resultSet->getQueryPlanHash());
473  if (cached) {
474  chunkMetadataMap = *cached;
475  need_to_compute_metadata = false;
476  }
477  }
478  if (need_to_compute_metadata) {
480  if (enable_chunk_metadata_cache && !chunkMetadataMap.empty()) {
481  executor->getRecultSetRecyclerHolder().putChunkMetadataToCache(
482  resultSet->getQueryPlanHash(),
483  resultSet->getInputTableKeys(),
485  }
486  }
488  }
489  return chunkMetadataMap;
490 }
491 
493  const {
494  ChunkMetadataMap metadata_map;
495  for (const auto& [column_id, chunk_metadata] : chunkMetadataMap) {
496  metadata_map[column_id] = std::make_shared<ChunkMetadata>(*chunk_metadata);
497  }
498  return metadata_map;
499 }
500 
502  std::unique_ptr<std::lock_guard<std::mutex>> lock;
503  if (resultSetMutex) {
504  lock.reset(new std::lock_guard<std::mutex>(*resultSetMutex));
505  }
506  CHECK_EQ(!!resultSet, !!resultSetMutex);
507  if (resultSet && !synthesizedNumTuplesIsValid) {
508  numTuples = resultSet->rowCount();
509  synthesizedNumTuplesIsValid = true;
510  }
511  return numTuples;
512 }
513 
515  if (!fragments.empty() && fragments.front().resultSet) {
516  return fragments.front().getNumTuples();
517  }
518  return numTuples;
519 }
520 
522  if (!fragments.empty() && fragments.front().resultSet) {
523  return fragments.front().resultSet->entryCount();
524  }
525  return numTuples;
526 }
527 
529  if (!fragments.empty() && fragments.front().resultSet) {
530  return fragments.front().resultSet->entryCount();
531  }
532  size_t fragment_num_tupples_upper_bound = 0;
533  for (const auto& fragment : fragments) {
534  fragment_num_tupples_upper_bound =
535  std::max(fragment.getNumTuples(), fragment_num_tupples_upper_bound);
536  }
537  return fragment_num_tupples_upper_bound;
538 }
ChunkMetadataMap synthesize_metadata_table_function(const ResultSet *rows)
#define CHECK_EQ(x, y)
Definition: Logger.h:230
ChunkMetadataMap getChunkMetadataMapPhysicalCopy() const
std::string cat(Ts &&...args)
Fragmenter_Namespace::TableInfo copy_table_info(const Fragmenter_Namespace::TableInfo &table_info)
ChunkMetadataMap synthesize_metadata(const ResultSet *rows)
static Encoder * Create(Data_Namespace::AbstractBuffer *buffer, const SQLTypeInfo sqlType)
Definition: Encoder.cpp:26
Executor * executor_
Definition: InputMetadata.h:48
std::vector< InputDescriptor > input_descs
#define UNREACHABLE()
Definition: Logger.h:266
#define CHECK_GE(x, y)
Definition: Logger.h:235
std::shared_ptr< ResultSet > ResultSetPtr
std::vector< FragmentInfo > fragments
Definition: Fragmenter.h:171
std::vector< int > chunkKeyPrefix
Definition: Fragmenter.h:170
bool g_enable_data_recycler
Definition: Execute.cpp:146
const size_t max_inputs_per_thread
double inline_fp_null_val(const SQL_TYPE_INFO &ti)
bool is_time() const
Definition: sqltypes.h:606
#define LOG_IF(severity, condition)
Definition: Logger.h:312
Fragmenter_Namespace::TableInfo build_table_info(const std::vector< const TableDescriptor * > &shard_tables)
bool g_use_chunk_metadata_cache
Definition: Execute.cpp:149
static std::shared_ptr< Executor > getExecutor(const ExecutorId id, const std::string &debug_dir="", const std::string &debug_file="", const SystemParameters &system_parameters=SystemParameters())
Definition: Execute.cpp:477
std::map< int, std::shared_ptr< ChunkMetadata >> ChunkMetadataMap
bool use_parallel_algorithms(const ResultSet &rows)
Definition: ResultSet.cpp:1482
size_t getPhysicalNumTuples() const
Definition: Fragmenter.h:164
Fragmenter_Namespace::TableInfo getTableInfo(const int table_id)
future< Result > async(Fn &&fn, Args &&...args)
bool uses_int_meta(const SQLTypeInfo &col_ti)
bool is_integer() const
Definition: sqltypes.h:602
#define INJECT_TIMER(DESC)
Definition: measure.h:93
void compute_table_function_col_chunk_stats(std::shared_ptr< ChunkMetadata > &chunk_metadata, const T *col_buffer, const T null_val)
size_t getFragmentNumTuplesUpperBound() const
Fragmenter_Namespace::TableInfo synthesize_table_info(const ResultSetPtr &rows)
const ChunkMetadataMap & getChunkMetadataMap() const
bool is_boolean() const
Definition: sqltypes.h:607
#define CHECK_LT(x, y)
Definition: Logger.h:232
Definition: sqltypes.h:66
HOST DEVICE EncodingType get_compression() const
Definition: sqltypes.h:412
constexpr float inline_fp_null_value< float >()
InputTableInfoCache(Executor *executor)
constexpr double inline_fp_null_value< double >()
void parallel_for(const blocked_range< Int > &range, const Body &body, const Partitioner &p=Partitioner())
bool g_enable_filter_push_down
Definition: Execute.cpp:95
#define CHECK(condition)
Definition: Logger.h:222
std::vector< InputTableInfo > get_table_infos(const std::vector< InputDescriptor > &input_descs, Executor *executor)
#define DEBUG_TIMER(name)
Definition: Logger.h:371
void setPhysicalNumTuples(const size_t physNumTuples)
Definition: Fragmenter.h:166
int64_t inline_int_null_val(const SQL_TYPE_INFO &ti)
int64_t inline_fixed_encoding_null_val(const SQL_TYPE_INFO &ti)
void collect_table_infos(std::vector< InputTableInfo > &table_infos, const std::vector< InputDescriptor > &input_descs, Executor *executor)
Definition: sqltypes.h:59
bool is_string() const
Definition: sqltypes.h:600
std::unordered_map< int, Fragmenter_Namespace::TableInfo > cache_
Definition: InputMetadata.h:47
size_t get_frag_count_of_table(const int table_id, Executor *executor)
int cpu_threads()
Definition: thread_count.h:25
bool is_decimal() const
Definition: sqltypes.h:603
DEVICE void swap(ARGS &&...args)
Definition: gpu_enabled.h:114
static const ExecutorId UNITARY_EXECUTOR_ID
Definition: Execute.h:376