Coverage Report

Created: 2026-05-23 05:15

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
1
// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
3
// distributed with this work for additional information
4
// regarding copyright ownership.  The ASF licenses this file
5
// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
7
// with the License.  You may obtain a copy of the License at
8
//
9
//   http://www.apache.org/licenses/LICENSE-2.0
10
//
11
// Unless required by applicable law or agreed to in writing,
12
// software distributed under the License is distributed on an
13
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
14
// KIND, either express or implied.  See the License for the
15
// specific language governing permissions and limitations
16
// under the License.
17
18
#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
114
#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
132
#include "util/client_cache.h"
133
#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
503k
        : _query_id(std::move(query_id)),
144
503k
          _fragment_id(request.fragment_id),
145
503k
          _exec_env(exec_env),
146
503k
          _query_ctx(std::move(query_ctx)),
147
503k
          _call_back(call_back),
148
503k
          _is_report_on_cancel(true),
149
503k
          _params(request),
150
503k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
503k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
503k
                                                               : false) {
153
503k
    _fragment_watcher.start();
154
503k
}
155
156
503k
PipelineFragmentContext::~PipelineFragmentContext() {
157
503k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
503k
            .tag("query_id", print_id(_query_id))
159
503k
            .tag("fragment_id", _fragment_id);
160
503k
    _release_resource();
161
503k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
503k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
503k
        _runtime_state.reset();
165
503k
        _query_ctx.reset();
166
503k
    }
167
503k
}
168
169
76
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
76
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
76
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
76
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
179
// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
9.79k
bool PipelineFragmentContext::notify_close() {
181
9.79k
    bool all_closed = false;
182
9.79k
    bool need_remove = false;
183
9.79k
    {
184
9.79k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.79k
        if (_closed_tasks >= _total_tasks) {
186
3.28k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
190
                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
192
3.23k
                need_remove = true;
193
3.23k
            }
194
3.28k
            all_closed = true;
195
3.28k
        }
196
        // make fragment release by self after cancel
197
9.79k
        _need_notify_close = false;
198
9.79k
    }
199
9.79k
    if (need_remove) {
200
3.23k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.23k
    }
202
9.79k
    return all_closed;
203
9.79k
}
204
205
// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
6.44k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.44k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.44k
            .tag("query_id", print_id(_query_id))
212
6.44k
            .tag("fragment_id", _fragment_id)
213
6.44k
            .tag("reason", reason.to_string());
214
6.44k
    if (notify_close()) {
215
71
        return;
216
71
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.37k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
14
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
14
                                   debug_string());
221
14
        LOG_LONG_STRING(WARNING, dbg_str);
222
14
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
6.37k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
6.37k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
6.37k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
25
        _query_ctx->set_load_error_url(error_url);
236
25
    }
237
238
6.37k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
25
        _query_ctx->set_first_error_msg(first_error_msg);
240
25
    }
241
242
6.37k
    _query_ctx->cancel(reason, _fragment_id);
243
6.37k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
354
        _is_report_on_cancel = false;
245
6.02k
    } else {
246
29.3k
        for (auto& id : _fragment_instance_ids) {
247
29.3k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
29.3k
        }
249
6.02k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
6.37k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.37k
    if (stream_load_ctx != nullptr) {
254
33
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
33
        stream_load_ctx->error_url = get_load_error_url();
259
33
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
33
    }
261
262
30.2k
    for (auto& tasks : _tasks) {
263
72.1k
        for (auto& task : tasks) {
264
72.1k
            task.first->unblock_all_dependencies();
265
72.1k
        }
266
30.2k
    }
267
6.37k
}
268
269
864k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
864k
    PipelineId id = _next_pipeline_id++;
271
864k
    auto pipeline = std::make_shared<Pipeline>(
272
864k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
864k
            parent ? parent->num_tasks() : _num_instances);
274
864k
    if (idx >= 0) {
275
113k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
751k
    } else {
277
751k
        _pipelines.emplace_back(pipeline);
278
751k
    }
279
864k
    if (parent) {
280
322k
        parent->set_children(pipeline);
281
322k
    }
282
864k
    return pipeline;
283
864k
}
284
285
503k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
503k
    {
287
503k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
503k
        auto root_pipeline = add_pipeline();
290
503k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
503k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
503k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
503k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
503k
                                          _params.fragment.output_exprs, _params,
299
503k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
503k
                                          *_desc_tbl, root_pipeline->id()));
301
503k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
503k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
750k
        for (PipelinePtr& pipeline : _pipelines) {
305
750k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
750k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
750k
        }
308
503k
    }
309
    // 4. Build local exchanger
310
503k
    if (_runtime_state->enable_local_shuffle()) {
311
499k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
499k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
499k
                                             _params.bucket_seq_to_instance_idx,
314
499k
                                             _params.shuffle_idx_to_instance_idx));
315
499k
    }
316
317
    // 5. Initialize global states in pipelines.
318
866k
    for (PipelinePtr& pipeline : _pipelines) {
319
866k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
866k
        pipeline->children().clear();
321
866k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
866k
    }
323
324
501k
    {
325
501k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
501k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
501k
    }
329
330
501k
    return Status::OK();
331
501k
}
332
333
503k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
503k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
503k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
503k
        _timeout = _params.query_options.execution_timeout;
339
503k
    }
340
341
503k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
503k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
503k
    SCOPED_TIMER(_prepare_timer);
344
503k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
503k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
503k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
503k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
503k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
503k
    {
350
503k
        SCOPED_TIMER(_init_context_timer);
351
503k
        cast_set(_num_instances, _params.local_params.size());
352
503k
        _total_instances =
353
503k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
503k
        auto* fragment_context = this;
356
357
503k
        if (_params.query_options.__isset.is_report_success) {
358
501k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
501k
        }
360
361
        // 1. Set up the global runtime state.
362
503k
        _runtime_state = RuntimeState::create_unique(
363
503k
                _params.query_id, _params.fragment_id, _params.query_options,
364
503k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
503k
        _runtime_state->set_task_execution_context(shared_from_this());
366
503k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
503k
        if (_params.__isset.backend_id) {
368
499k
            _runtime_state->set_backend_id(_params.backend_id);
369
499k
        }
370
503k
        if (_params.__isset.import_label) {
371
236
            _runtime_state->set_import_label(_params.import_label);
372
236
        }
373
503k
        if (_params.__isset.db_name) {
374
188
            _runtime_state->set_db_name(_params.db_name);
375
188
        }
376
503k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
503k
        if (_params.is_simplified_param) {
381
211k
            _desc_tbl = _query_ctx->desc_tbl;
382
291k
        } else {
383
291k
            DCHECK(_params.__isset.desc_tbl);
384
291k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
291k
                                                  &_desc_tbl));
386
291k
        }
387
503k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
503k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
503k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
503k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
503k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
503k
        const auto target_size = _params.local_params.size();
395
503k
        _fragment_instance_ids.resize(target_size);
396
1.70M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.20M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.20M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.20M
        }
400
503k
    }
401
402
503k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
502k
    _init_next_report_time();
405
406
502k
    _prepared = true;
407
502k
    return Status::OK();
408
503k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.20M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.20M
    const auto& local_params = _params.local_params[instance_idx];
414
1.20M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.20M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.20M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.20M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.20M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
2.08M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
2.08M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
2.08M
                                std::vector<std::shared_ptr<Dependency>>>>
422
2.08M
                shared_state_map;
423
2.63M
        for (auto& op : pipeline->operators()) {
424
2.63M
            auto source_id = op->operator_id();
425
2.63M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.63M
                iter != _op_id_to_shared_state.end()) {
427
756k
                shared_state_map.insert({source_id, iter->second});
428
756k
            }
429
2.63M
        }
430
2.11M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
2.11M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
2.11M
                iter != _op_id_to_shared_state.end()) {
433
300k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
300k
            }
435
2.11M
        }
436
2.08M
        return shared_state_map;
437
2.08M
    };
438
439
3.74M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.53M
        auto& pipeline = _pipelines[pip_idx];
441
2.53M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
2.08M
            auto task_runtime_state = RuntimeState::create_unique(
443
2.08M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
2.08M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
2.08M
            {
446
                // Initialize runtime state for this task
447
2.08M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
2.08M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
2.08M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
2.08M
                if (_params.__isset.backend_id) {
453
2.08M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
2.08M
                }
455
2.08M
                if (_params.__isset.import_label) {
456
237
                    task_runtime_state->set_import_label(_params.import_label);
457
237
                }
458
2.08M
                if (_params.__isset.db_name) {
459
189
                    task_runtime_state->set_db_name(_params.db_name);
460
189
                }
461
2.08M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
2.08M
                if (_params.__isset.wal_id) {
465
112
                    task_runtime_state->set_wal_id(_params.wal_id);
466
112
                }
467
2.08M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
2.08M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
2.08M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
2.08M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
2.08M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
2.08M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
2.08M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
2.08M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
2.08M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
2.08M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
2.08M
            }
482
2.08M
            auto cur_task_id = _total_tasks++;
483
2.08M
            task_runtime_state->set_task_id(cur_task_id);
484
2.08M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
2.08M
            auto task = std::make_shared<PipelineTask>(
486
2.08M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
2.08M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
2.08M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
2.08M
                    instance_idx);
490
2.08M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
2.08M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
2.08M
            _tasks[instance_idx].emplace_back(
493
2.08M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
2.08M
                            std::move(task), std::move(task_runtime_state)});
495
2.08M
        }
496
2.53M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
2.53M
    for (auto& _pipeline : _pipelines) {
516
2.53M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
2.08M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
2.08M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
2.08M
            if (_dag.contains(_pipeline->id())) {
522
1.32M
                auto& deps = _dag[_pipeline->id()];
523
2.07M
                for (auto& dep : deps) {
524
2.07M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.16M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.16M
                        if (ss) {
527
570k
                            task->inject_shared_state(ss);
528
590k
                        } else {
529
590k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
590k
                                    task->get_source_shared_state());
531
590k
                        }
532
1.16M
                    }
533
2.07M
                }
534
1.32M
            }
535
2.08M
        }
536
2.53M
    }
537
3.74M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.53M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
2.08M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
2.08M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
2.08M
            std::vector<TScanRangeParams> scan_ranges;
542
2.08M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
2.08M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
329k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
329k
            }
546
2.08M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
2.08M
                                                             _params.fragment.output_sink));
548
2.08M
        }
549
2.53M
    }
550
1.20M
    {
551
1.20M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.20M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.20M
    }
554
1.20M
    return Status::OK();
555
1.20M
}
556
557
502k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
502k
    _total_tasks = 0;
559
502k
    _closed_tasks = 0;
560
502k
    const auto target_size = _params.local_params.size();
561
502k
    _tasks.resize(target_size);
562
502k
    _runtime_filter_mgr_map.resize(target_size);
563
1.36M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
864k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
864k
    }
566
502k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
502k
    if (target_size > 1 &&
569
502k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
141k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
571
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
572
19.2k
        std::vector<Status> prepare_status(target_size);
573
19.2k
        int submitted_tasks = 0;
574
19.2k
        Status submit_status;
575
19.2k
        CountDownLatch latch((int)target_size);
576
193k
        for (int i = 0; i < target_size; i++) {
577
174k
            submit_status = thread_pool->submit_func([&, i]() {
578
174k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
174k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
174k
                latch.count_down();
581
174k
            });
582
174k
            if (LIKELY(submit_status.ok())) {
583
174k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
174k
        }
588
19.2k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
19.2k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
193k
        for (int i = 0; i < submitted_tasks; i++) {
593
174k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
174k
        }
597
483k
    } else {
598
1.51M
        for (int i = 0; i < target_size; i++) {
599
1.03M
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
1.03M
        }
601
483k
    }
602
502k
    _pipeline_parent_map.clear();
603
502k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
502k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
502k
    return Status::OK();
608
502k
}
609
610
500k
void PipelineFragmentContext::_init_next_report_time() {
611
500k
    auto interval_s = config::pipeline_status_report_interval;
612
500k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
42.3k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.3k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
42.3k
        _previous_report_time =
617
42.3k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.3k
        _disable_period_report = false;
619
42.3k
    }
620
500k
}
621
622
4.84k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.84k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.84k
    DCHECK(disable == true);
625
4.84k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.84k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.84k
}
628
629
7.66M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.66M
    if (!_is_report_success) {
631
7.20M
        return;
632
7.20M
    }
633
462k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
462k
    if (disable) {
635
8.87k
        return;
636
8.87k
    }
637
453k
    int32_t interval_s = config::pipeline_status_report_interval;
638
453k
    if (interval_s <= 0) {
639
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
640
0
                        "trigger "
641
0
                        "report.";
642
0
    }
643
453k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
453k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
453k
    if (MonotonicNanos() > next_report_time) {
646
4.84k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.84k
                                                            std::memory_order_acq_rel)) {
648
10
            return;
649
10
        }
650
4.83k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
4.83k
        auto st = send_report(false);
667
4.83k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
4.83k
    }
673
453k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
499k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
499k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
499k
    int node_idx = 0;
682
683
499k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
499k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
499k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
687
0
        return Status::InternalError(
688
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
689
0
    }
690
499k
    return Status::OK();
691
499k
}
692
693
Status PipelineFragmentContext::_create_tree_helper(
694
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
695
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
696
860k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
860k
    if (*node_idx >= tnodes.size()) {
699
0
        return Status::InternalError(
700
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
701
0
                *node_idx, tnodes.size());
702
0
    }
703
860k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
860k
    int num_children = tnodes[*node_idx].num_children;
706
860k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
860k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
860k
    OperatorPtr op = nullptr;
710
860k
    OperatorPtr cache_op = nullptr;
711
860k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
860k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
860k
                                     followed_by_shuffled_operator,
714
860k
                                     current_require_bucket_distribution, cache_op));
715
    // Initialization must be done here. For example, group by expressions in agg will be used to
716
    // decide if a local shuffle should be planed, so it must be initialized here.
717
860k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
860k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
361k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
498k
    } else {
723
498k
        *root = op;
724
498k
    }
725
    /**
726
     * `ExchangeType::HASH_SHUFFLE` should be used if an operator is followed by a shuffled operator (shuffled hash join, union operator followed by co-located operators).
727
     *
728
     * For plan:
729
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
730
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
731
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
732
     *
733
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
734
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
735
     */
736
860k
    auto required_data_distribution =
737
860k
            cur_pipe->operators().empty()
738
860k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
860k
                    : op->required_data_distribution(_runtime_state.get());
740
860k
    current_followed_by_shuffled_operator =
741
860k
            ((followed_by_shuffled_operator ||
742
860k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
793k
                                             : op->is_shuffled_operator())) &&
744
860k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
860k
            (followed_by_shuffled_operator &&
746
732k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
860k
    current_require_bucket_distribution =
749
860k
            ((require_bucket_distribution ||
750
860k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
797k
                                             : op->is_colocated_operator())) &&
752
860k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
860k
            (require_bucket_distribution &&
754
738k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
860k
    if (num_children == 0) {
757
540k
        _use_serial_source = op->is_serial_operator();
758
540k
    }
759
    // rely on that tnodes is preorder of the plan
760
1.22M
    for (int i = 0; i < num_children; i++) {
761
361k
        ++*node_idx;
762
361k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
361k
                                            current_followed_by_shuffled_operator,
764
361k
                                            current_require_bucket_distribution));
765
766
        // we are expecting a child, but have used all nodes
767
        // this means we have been given a bad tree and must fail
768
361k
        if (*node_idx >= tnodes.size()) {
769
0
            return Status::InternalError(
770
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
771
0
                    "nodes: {}",
772
0
                    *node_idx, tnodes.size());
773
0
        }
774
361k
    }
775
776
860k
    return Status::OK();
777
860k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
113k
        PipelinePtr pipe_with_sink) {
782
113k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
113k
    pipe_with_source->set_num_tasks(_num_instances);
784
113k
    pipe_with_source->set_data_distribution(data_distribution);
785
113k
}
786
787
Status PipelineFragmentContext::_add_local_exchange_impl(
788
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
789
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
790
        const std::map<int, int>& bucket_seq_to_instance_idx,
791
113k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
113k
    auto& operators = cur_pipe->operators();
793
113k
    const auto downstream_pipeline_id = cur_pipe->id();
794
113k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
113k
    DataSinkOperatorPtr sink;
797
113k
    auto sink_id = next_sink_operator_id();
798
799
    /**
800
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
801
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
802
     */
803
113k
    const bool followed_by_shuffled_operator =
804
113k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
113k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
113k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
113k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
113k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
113k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
113k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
113k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
113k
    if (bucket_seq_to_instance_idx.empty() &&
813
113k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
1
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
1
    }
816
113k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
113k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
113k
                                          num_buckets, use_global_hash_shuffle,
819
113k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
113k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
113k
            LocalExchangeSharedState::create_shared(_num_instances);
824
113k
    switch (data_distribution.distribution_type) {
825
14.0k
    case ExchangeType::HASH_SHUFFLE:
826
14.0k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
14.0k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
14.0k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
14.0k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
14.0k
                        ? cast_set<int>(
831
14.0k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
14.0k
                        : 0);
833
14.0k
        break;
834
429
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
429
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
429
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
429
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
429
                        ? cast_set<int>(
839
429
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
429
                        : 0);
841
429
        break;
842
95.2k
    case ExchangeType::PASSTHROUGH:
843
95.2k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
95.2k
                cur_pipe->num_tasks(), _num_instances,
845
95.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
95.2k
                        ? cast_set<int>(
847
95.1k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
95.2k
                        : 0);
849
95.2k
        break;
850
331
    case ExchangeType::BROADCAST:
851
331
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
331
                cur_pipe->num_tasks(), _num_instances,
853
331
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
331
                        ? cast_set<int>(
855
331
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
331
                        : 0);
857
331
        break;
858
2.58k
    case ExchangeType::PASS_TO_ONE:
859
2.58k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
860
            // If shared hash table is enabled for BJ, hash table will be built by only one task
861
1.74k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.74k
                    cur_pipe->num_tasks(), _num_instances,
863
1.74k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.74k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.74k
                                                    .local_exchange_free_blocks_limit)
866
1.74k
                            : 0);
867
1.74k
        } else {
868
843
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
843
                    cur_pipe->num_tasks(), _num_instances,
870
843
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
843
                            ? cast_set<int>(_runtime_state->query_options()
872
843
                                                    .local_exchange_free_blocks_limit)
873
843
                            : 0);
874
843
        }
875
2.58k
        break;
876
886
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
886
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
886
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
886
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
886
                        ? cast_set<int>(
881
886
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
886
                        : 0);
883
886
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
113k
    }
888
113k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
113k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
113k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
113k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
892
893
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
894
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
895
896
    // 3.1 Initialize new pipeline's operator list.
897
113k
    std::copy(operators.begin(), operators.begin() + idx,
898
113k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
113k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
113k
    OperatorPtr source_op;
905
113k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
113k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
113k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
113k
    if (!operators.empty()) {
909
45.1k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
45.1k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
45.1k
    }
912
113k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
113k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
113k
    std::vector<PipelineId> edges_with_source;
917
131k
    for (auto child : cur_pipe->children()) {
918
131k
        bool found = false;
919
145k
        for (auto op : new_pip->operators()) {
920
145k
            if (child->sink()->node_id() == op->node_id()) {
921
12.5k
                new_pip->set_children(child);
922
12.5k
                found = true;
923
12.5k
            };
924
145k
        }
925
131k
        if (!found) {
926
119k
            new_children.push_back(child);
927
119k
            edges_with_source.push_back(child->id());
928
119k
        }
929
131k
    }
930
113k
    new_children.push_back(new_pip);
931
113k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
113k
    if (!new_pip->children().empty()) {
935
7.19k
        std::vector<PipelineId> edges_with_sink;
936
12.5k
        for (auto child : new_pip->children()) {
937
12.5k
            edges_with_sink.push_back(child->id());
938
12.5k
        }
939
7.19k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.19k
    }
941
113k
    cur_pipe->set_children(new_children);
942
113k
    _dag[downstream_pipeline_id] = edges_with_source;
943
113k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
113k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
113k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
113k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
113k
    return Status::OK();
950
113k
}
951
952
Status PipelineFragmentContext::_add_local_exchange(
953
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
954
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
955
        const std::map<int, int>& bucket_seq_to_instance_idx,
956
243k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
243k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
98.1k
        return Status::OK();
959
98.1k
    }
960
961
145k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
46.0k
        return Status::OK();
963
46.0k
    }
964
99.3k
    *do_local_exchange = true;
965
966
99.3k
    auto& operators = cur_pipe->operators();
967
99.3k
    auto total_op_num = operators.size();
968
99.3k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
99.3k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
99.3k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
99.3k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
99.3k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
200
            << "total_op_num: " << total_op_num
975
200
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
200
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
99.3k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
99.3k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
14.4k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
14.4k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
14.4k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
14.4k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
14.4k
                shuffle_idx_to_instance_idx));
990
14.4k
    }
991
99.3k
    return Status::OK();
992
99.3k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
499k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.24M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
748k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
748k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
209k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
209k
                if (child->sink()->node_id() ==
1003
209k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
172k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
172k
                }
1006
209k
            }
1007
193k
        }
1008
1009
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1010
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1011
        // still keep colocate plan after local shuffle
1012
748k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
748k
                                             bucket_seq_to_instance_idx,
1014
748k
                                             shuffle_idx_to_instance_idx));
1015
748k
    }
1016
499k
    return Status::OK();
1017
499k
}
1018
1019
Status PipelineFragmentContext::_plan_local_exchange(
1020
        int num_buckets, int pip_idx, PipelinePtr pip,
1021
        const std::map<int, int>& bucket_seq_to_instance_idx,
1022
747k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
747k
    int idx = 1;
1024
747k
    bool do_local_exchange = false;
1025
792k
    do {
1026
792k
        auto& ops = pip->operators();
1027
792k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
899k
        for (; idx < ops.size();) {
1030
152k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
125k
                RETURN_IF_ERROR(_add_local_exchange(
1032
125k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
125k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
125k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
125k
                        shuffle_idx_to_instance_idx));
1036
125k
            }
1037
152k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
45.2k
                idx = 2;
1043
45.2k
                break;
1044
45.2k
            }
1045
107k
            idx++;
1046
107k
        }
1047
792k
    } while (do_local_exchange);
1048
747k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
117k
        RETURN_IF_ERROR(_add_local_exchange(
1050
117k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
117k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
117k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
117k
    }
1054
747k
    return Status::OK();
1055
747k
}
1056
1057
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1058
                                                  const std::vector<TExpr>& output_exprs,
1059
                                                  const TPipelineFragmentParams& params,
1060
                                                  const RowDescriptor& row_desc,
1061
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1062
503k
                                                  PipelineId cur_pipeline_id) {
1063
503k
    switch (thrift_sink.type) {
1064
198k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
198k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
198k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
198k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
198k
                params.destinations, _fragment_instance_ids);
1071
198k
        break;
1072
198k
    }
1073
254k
    case TDataSinkType::RESULT_SINK: {
1074
254k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
254k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
254k
        int child_node_id = pipeline->operators().back()->node_id();
1080
254k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
254k
                                                      row_desc, output_exprs,
1082
254k
                                                      thrift_sink.result_sink);
1083
254k
        break;
1084
254k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
32.9k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
32.9k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
32.9k
        int child_node_id = pipeline->operators().back()->node_id();
1098
32.9k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
32.9k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
32.9k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.66k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.66k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
30.2k
        } else {
1104
30.2k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
30.2k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
30.2k
        }
1107
32.9k
        break;
1108
0
    }
1109
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
165
        DCHECK(state->get_query_ctx() != nullptr);
1112
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
165
                                                                output_exprs);
1115
165
        break;
1116
0
    }
1117
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.46k
                                                         output_exprs);
1123
1.46k
        break;
1124
1.46k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
1.73k
        } else {
1133
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.73k
                                                                row_desc, output_exprs);
1135
1.73k
        }
1136
1.73k
        break;
1137
1.73k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
502
    case TDataSinkType::RESULT_FILE_SINK: {
1186
502
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
502
        } else {
1196
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
502
                                                              output_exprs);
1198
502
        }
1199
502
        break;
1200
502
    }
1201
13.0k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
13.0k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
13.0k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
13.0k
        auto sink_id = next_sink_operator_id();
1205
13.0k
        const int multi_cast_node_id = sink_id;
1206
13.0k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
13.0k
        std::vector<int> sources;
1209
52.1k
        for (int i = 0; i < sender_size; ++i) {
1210
39.0k
            auto source_id = next_operator_id();
1211
39.0k
            sources.push_back(source_id);
1212
39.0k
        }
1213
1214
13.0k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
13.0k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
52.1k
        for (int i = 0; i < sender_size; ++i) {
1217
39.0k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
39.0k
            RowDescriptor* exchange_row_desc = nullptr;
1220
39.0k
            {
1221
39.0k
                const auto& tmp_row_desc =
1222
39.0k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
39.0k
                                ? RowDescriptor(state->desc_tbl(),
1224
39.0k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
39.0k
                                                         .output_tuple_id})
1226
39.0k
                                : row_desc;
1227
39.0k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
39.0k
            }
1229
39.0k
            auto source_id = sources[i];
1230
39.0k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
39.0k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
39.0k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
39.0k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
39.0k
                    /*operator_id=*/source_id);
1236
39.0k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
39.0k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1238
            // 2. create and set sink operator of data stream sender for new pipeline
1239
1240
39.0k
            DataSinkOperatorPtr sink_op;
1241
39.0k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
39.0k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
39.0k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
39.0k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
39.0k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
39.0k
            {
1248
39.0k
                TDataSink* t = pool->add(new TDataSink());
1249
39.0k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
39.0k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
39.0k
            }
1252
1253
            // 3. set dependency dag
1254
39.0k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
39.0k
        }
1256
13.0k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
13.0k
        break;
1260
13.0k
    }
1261
13.0k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
13
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
13
        break;
1268
13
    }
1269
156
    case TDataSinkType::TVF_TABLE_SINK: {
1270
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
156
                                                        output_exprs);
1275
156
        break;
1276
156
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
503k
    }
1280
501k
    return Status::OK();
1281
503k
}
1282
1283
// NOLINTBEGIN(readability-function-size)
1284
// NOLINTBEGIN(readability-function-cognitive-complexity)
1285
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1286
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1287
                                                 PipelinePtr& cur_pipe, int parent_idx,
1288
                                                 int child_idx,
1289
                                                 const bool followed_by_shuffled_operator,
1290
                                                 const bool require_bucket_distribution,
1291
865k
                                                 OperatorPtr& cache_op) {
1292
865k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
865k
    Defer defer = Defer([&]() {
1294
863k
        if (op) {
1295
863k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
863k
        }
1297
862k
        for (auto& s : sink_ops) {
1298
209k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
209k
        }
1300
862k
    });
1301
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1302
    // Therefore, here we need to use a stack-like structure.
1303
865k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
865k
    std::stringstream error_msg;
1305
865k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
865k
    bool fe_with_old_version = false;
1308
865k
    switch (tnode.node_type) {
1309
214k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
214k
        op = std::make_shared<OlapScanOperatorX>(
1311
214k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
214k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
214k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
214k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
214k
        break;
1316
214k
    }
1317
77
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
77
        DCHECK(_query_ctx != nullptr);
1319
77
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
77
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
77
                                                    _num_instances);
1322
77
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
77
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
77
        break;
1325
77
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
24.6k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
24.6k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
24.6k
                                                 _num_instances);
1342
24.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
24.6k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
24.6k
        break;
1345
24.6k
    }
1346
235k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
235k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
235k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
235k
        DCHECK_GT(num_senders, 0);
1351
235k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
235k
                                                       num_senders);
1353
235k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
235k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
235k
        break;
1356
235k
    }
1357
213k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
213k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
213k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1360
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1361
0
                                         ": group by and output is empty");
1362
0
        }
1363
213k
        bool need_create_cache_op =
1364
213k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
213k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1366
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1367
10
            auto cache_source_id = next_operator_id();
1368
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1369
10
                                                        _params.fragment.query_cache_param);
1370
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1371
1372
10
            const auto downstream_pipeline_id = cur_pipe->id();
1373
10
            if (!_dag.contains(downstream_pipeline_id)) {
1374
10
                _dag.insert({downstream_pipeline_id, {}});
1375
10
            }
1376
10
            new_pipe = add_pipeline(cur_pipe);
1377
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1378
1379
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1380
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1381
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1382
10
            return Status::OK();
1383
10
        };
1384
213k
        const bool group_by_limit_opt =
1385
213k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1386
1387
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1388
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1389
213k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
213k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
213k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
213k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
213k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
213k
        const bool can_use_distinct_streaming_agg =
1396
213k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
213k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
213k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
213k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
213k
        if (can_use_distinct_streaming_agg) {
1402
92.2k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
92.2k
            } else {
1413
92.2k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
92.2k
                                                                     tnode, descs);
1415
92.2k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
92.2k
            }
1417
120k
        } else if (is_streaming_agg) {
1418
7.25k
            if (need_create_cache_op) {
1419
0
                PipelinePtr new_pipe;
1420
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1421
0
                cache_op = op;
1422
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
0
                                                             descs);
1424
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1425
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1426
0
                cur_pipe = new_pipe;
1427
7.25k
            } else {
1428
7.25k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
7.25k
                                                             descs);
1430
7.25k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
7.25k
            }
1432
113k
        } else {
1433
            // create new pipeline to add query cache operator
1434
113k
            PipelinePtr new_pipe;
1435
113k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
113k
            if (enable_spill) {
1441
184
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
184
                                                                     next_operator_id(), descs);
1443
113k
            } else {
1444
113k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
113k
            }
1446
113k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
113k
            } else {
1451
113k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
113k
            }
1453
1454
113k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
113k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
99.6k
                _dag.insert({downstream_pipeline_id, {}});
1457
99.6k
            }
1458
113k
            cur_pipe = add_pipeline(cur_pipe);
1459
113k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
113k
            if (enable_spill) {
1462
184
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
184
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
113k
            } else {
1465
113k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
113k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
113k
            }
1468
113k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
113k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
113k
        }
1471
213k
        break;
1472
213k
    }
1473
213k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
88
        if (tnode.bucketed_agg_node.grouping_exprs.empty()) {
1475
0
            return Status::InternalError(
1476
0
                    "Bucketed aggregation node {} should not be used without group by keys",
1477
0
                    tnode.node_id);
1478
0
        }
1479
1480
        // Create source operator (goes on the current / downstream pipeline).
1481
88
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
88
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
88
        const auto downstream_pipeline_id = cur_pipe->id();
1486
88
        if (!_dag.contains(downstream_pipeline_id)) {
1487
88
            _dag.insert({downstream_pipeline_id, {}});
1488
88
        }
1489
88
        cur_pipe = add_pipeline(cur_pipe);
1490
88
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
88
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
88
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
88
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
88
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1497
1498
        // Pre-register a single shared state for ALL instances so that every
1499
        // sink instance writes its per-instance hash table into the same
1500
        // BucketedAggSharedState and every source instance can merge across
1501
        // all of them.
1502
88
        {
1503
88
            auto shared_state = BucketedAggSharedState::create_shared();
1504
88
            shared_state->id = op->operator_id();
1505
88
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
483
            for (int i = 0; i < _num_instances; i++) {
1508
395
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
395
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
395
                sink_dep->set_shared_state(shared_state.get());
1511
395
                shared_state->sink_deps.push_back(sink_dep);
1512
395
            }
1513
88
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
88
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
88
            _op_id_to_shared_state.insert(
1516
88
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
88
        }
1518
88
        break;
1519
88
    }
1520
9.65k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.65k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.65k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.65k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.65k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
9.65k
        } else {
1566
9.65k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.65k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.65k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.65k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.90k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.90k
            }
1573
9.65k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.65k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.65k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.65k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.65k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.65k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.65k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.65k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.65k
        }
1584
9.65k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
4.83k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
4.83k
                    HashJoinSharedState::create_shared(_num_instances);
1587
24.3k
            for (int i = 0; i < _num_instances; i++) {
1588
19.4k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
19.4k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
19.4k
                sink_dep->set_shared_state(shared_state.get());
1591
19.4k
                shared_state->sink_deps.push_back(sink_dep);
1592
19.4k
            }
1593
4.83k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
4.83k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
4.83k
            _op_id_to_shared_state.insert(
1596
4.83k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
4.83k
        }
1598
9.65k
        break;
1599
9.65k
    }
1600
27.4k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
27.4k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
27.4k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
27.4k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
27.4k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
27.2k
            _dag.insert({downstream_pipeline_id, {}});
1607
27.2k
        }
1608
27.4k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
27.4k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
27.4k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
27.4k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
27.4k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
27.4k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
27.4k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
27.4k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
27.4k
        break;
1618
27.4k
    }
1619
53.7k
    case TPlanNodeType::UNION_NODE: {
1620
53.7k
        int child_count = tnode.num_children;
1621
53.7k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
53.7k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
53.7k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
53.7k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
53.2k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.2k
        }
1628
55.1k
        for (int i = 0; i < child_count; i++) {
1629
1.41k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.41k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.41k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.41k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.41k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.41k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.41k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.41k
        }
1638
53.7k
        break;
1639
53.7k
    }
1640
55.1k
    case TPlanNodeType::SORT_NODE: {
1641
55.1k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
55.1k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
55.1k
        const bool use_local_merge =
1644
55.1k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
55.1k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
55.1k
        } else if (use_local_merge) {
1648
52.8k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
52.8k
                                                                 descs);
1650
52.8k
        } else {
1651
2.34k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.34k
        }
1653
55.1k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
55.1k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
55.1k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
55.0k
            _dag.insert({downstream_pipeline_id, {}});
1658
55.0k
        }
1659
55.1k
        cur_pipe = add_pipeline(cur_pipe);
1660
55.1k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
55.1k
        if (should_spill) {
1663
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
55.1k
        } else {
1666
55.1k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
55.1k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
55.1k
        }
1669
55.1k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
55.1k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
55.1k
        break;
1672
55.1k
    }
1673
55.1k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.63k
        }
1698
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.64k
        break;
1706
1.64k
    }
1707
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.60k
        break;
1711
1.60k
    }
1712
1.60k
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
296
    case TPlanNodeType::REPEAT_NODE: {
1723
296
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
296
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
296
        break;
1726
296
    }
1727
914
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
914
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
914
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
914
        break;
1731
914
    }
1732
914
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
218
        break;
1736
218
    }
1737
1.95k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.95k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.95k
        break;
1741
1.95k
    }
1742
1.95k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
463
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
463
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
463
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
463
        break;
1747
463
    }
1748
2.05k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.05k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.05k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.05k
        break;
1752
2.05k
    }
1753
6.79k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.79k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.79k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.79k
        break;
1757
6.79k
    }
1758
12.9k
    case TPlanNodeType::SELECT_NODE: {
1759
12.9k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
12.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
12.9k
        break;
1762
12.9k
    }
1763
12.9k
    case TPlanNodeType::REC_CTE_NODE: {
1764
134
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
134
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
134
        const auto downstream_pipeline_id = cur_pipe->id();
1768
134
        if (!_dag.contains(downstream_pipeline_id)) {
1769
133
            _dag.insert({downstream_pipeline_id, {}});
1770
133
        }
1771
1772
134
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
134
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
134
        DataSinkOperatorPtr anchor_sink;
1776
134
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
134
                                                                  op->operator_id(), tnode, descs);
1778
134
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
134
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
134
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
134
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
134
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
134
        DataSinkOperatorPtr rec_sink;
1786
134
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
134
                                                         tnode, descs);
1788
134
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
134
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
134
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
134
        break;
1793
134
    }
1794
1.85k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.85k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.85k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.85k
        break;
1798
1.85k
    }
1799
1.85k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
865k
    }
1803
862k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1804
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1805
0
        op->set_serial_operator();
1806
0
    }
1807
1808
862k
    return Status::OK();
1809
865k
}
1810
// NOLINTEND(readability-function-cognitive-complexity)
1811
// NOLINTEND(readability-function-size)
1812
1813
template <bool is_intersect>
1814
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1815
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1816
267
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
267
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
267
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
267
    const auto downstream_pipeline_id = cur_pipe->id();
1821
267
    if (!_dag.contains(downstream_pipeline_id)) {
1822
242
        _dag.insert({downstream_pipeline_id, {}});
1823
242
    }
1824
1825
895
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
628
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
628
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
628
        if (child_id == 0) {
1830
267
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
267
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
361
        } else {
1833
361
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
361
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
361
        }
1836
628
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
628
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
628
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
628
    }
1841
1842
267
    return Status::OK();
1843
267
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
134
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
134
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
134
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
134
    const auto downstream_pipeline_id = cur_pipe->id();
1821
134
    if (!_dag.contains(downstream_pipeline_id)) {
1822
118
        _dag.insert({downstream_pipeline_id, {}});
1823
118
    }
1824
1825
481
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
347
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
347
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
347
        if (child_id == 0) {
1830
134
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
134
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
213
        } else {
1833
213
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
213
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
213
        }
1836
347
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
347
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
347
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
347
    }
1841
1842
134
    return Status::OK();
1843
134
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
133
    const auto downstream_pipeline_id = cur_pipe->id();
1821
133
    if (!_dag.contains(downstream_pipeline_id)) {
1822
124
        _dag.insert({downstream_pipeline_id, {}});
1823
124
    }
1824
1825
414
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
281
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
281
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
281
        if (child_id == 0) {
1830
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
148
        } else {
1833
148
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
148
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
148
        }
1836
281
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
281
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
281
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
281
    }
1841
1842
133
    return Status::OK();
1843
133
}
1844
1845
500k
Status PipelineFragmentContext::submit() {
1846
500k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
500k
    _submitted = true;
1850
1851
500k
    int submit_tasks = 0;
1852
500k
    Status st;
1853
500k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.20M
    for (auto& task : _tasks) {
1855
2.08M
        for (auto& t : task) {
1856
2.08M
            st = scheduler->submit(t.first);
1857
2.08M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
2.08M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
2.08M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
2.08M
            submit_tasks++;
1866
2.08M
        }
1867
1.20M
    }
1868
500k
    if (!st.ok()) {
1869
0
        bool need_remove = false;
1870
0
        {
1871
0
            std::lock_guard<std::mutex> l(_task_mutex);
1872
0
            if (_closed_tasks >= _total_tasks) {
1873
0
                need_remove = _close_fragment_instance();
1874
0
            }
1875
0
        }
1876
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1877
0
        if (need_remove) {
1878
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1879
0
        }
1880
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1881
0
                                     BackendOptions::get_localhost());
1882
500k
    } else {
1883
500k
        return st;
1884
500k
    }
1885
500k
}
1886
1887
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1888
0
    if (_runtime_state->enable_profile()) {
1889
0
        std::stringstream ss;
1890
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1891
0
            runtime_profile_ptr->pretty_print(&ss);
1892
0
        }
1893
1894
0
        if (_runtime_state->load_channel_profile()) {
1895
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1896
0
        }
1897
1898
0
        auto profile_str =
1899
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1900
0
                            this->_fragment_id, extra_info, ss.str());
1901
0
        LOG_LONG_STRING(INFO, profile_str);
1902
0
    }
1903
0
}
1904
// If all pipeline tasks binded to the fragment instance are finished, then we could
1905
// close the fragment instance.
1906
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1907
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1908
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1909
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1910
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1911
// (via debug_string()).
1912
502k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
502k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
502k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
502k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
502k
    if (!_need_notify_close) {
1919
499k
        auto st = send_report(true);
1920
499k
        if (!st) {
1921
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1922
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1923
0
        }
1924
499k
    }
1925
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1926
    // Since stream load does not have someting like coordinator on FE, so
1927
    // backend can not report profile to FE, ant its profile can not be shown
1928
    // in the same way with other query. So we print the profile content to info log.
1929
1930
502k
    if (_runtime_state->enable_profile() &&
1931
502k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.55k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.55k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1934
0
        std::stringstream ss;
1935
        // Compute the _local_time_percent before pretty_print the runtime_profile
1936
        // Before add this operation, the print out like that:
1937
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1938
        // After add the operation, the print out like that:
1939
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1940
        // We can easily know the exec node execute time without child time consumed.
1941
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1942
0
            runtime_profile_ptr->pretty_print(&ss);
1943
0
        }
1944
1945
0
        if (_runtime_state->load_channel_profile()) {
1946
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1947
0
        }
1948
1949
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1950
0
    }
1951
1952
502k
    if (_query_ctx->enable_profile()) {
1953
2.55k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.55k
                                         collect_realtime_load_channel_profile());
1955
2.55k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
502k
    return !_need_notify_close;
1960
502k
}
1961
1962
2.07M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
2.07M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
2.07M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
865k
        if (_dag.contains(pipeline_id)) {
1967
475k
            for (auto dep : _dag[pipeline_id]) {
1968
475k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
475k
            }
1970
393k
        }
1971
865k
    }
1972
2.07M
    bool need_remove = false;
1973
2.07M
    {
1974
2.07M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
2.07M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
2.07M
        _query_ctx->inc_finished_task_num();
1978
2.07M
        if (_closed_tasks >= _total_tasks) {
1979
502k
            need_remove = _close_fragment_instance();
1980
502k
        }
1981
2.07M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
2.07M
    if (need_remove) {
1984
499k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
499k
    }
1986
2.07M
}
1987
1988
55.0k
std::string PipelineFragmentContext::get_load_error_url() {
1989
55.0k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1990
0
        return to_load_error_http_path(str);
1991
0
    }
1992
140k
    for (auto& tasks : _tasks) {
1993
224k
        for (auto& task : tasks) {
1994
224k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
176
                return to_load_error_http_path(str);
1996
176
            }
1997
224k
        }
1998
140k
    }
1999
54.9k
    return "";
2000
55.0k
}
2001
2002
55.0k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
55.0k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
140k
    for (auto& tasks : _tasks) {
2007
224k
        for (auto& task : tasks) {
2008
224k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
176
                return str;
2010
176
            }
2011
224k
        }
2012
140k
    }
2013
54.9k
    return "";
2014
55.0k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
48.6k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
48.6k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
48.6k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
48.6k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
48.6k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
48.6k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
48.6k
    });
2031
2032
48.6k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
48.6k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
48.6k
    int callback_retries = 10;
2038
48.6k
    const int sleep_ms = 1000;
2039
48.6k
    Status exec_status = req.status;
2040
48.6k
    Status coord_status;
2041
48.6k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
48.6k
    do {
2043
48.6k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
48.6k
                                                            req.coord_addr, &coord_status);
2045
48.6k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
48.6k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
48.6k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
48.6k
    TReportExecStatusParams params;
2059
48.6k
    params.protocol_version = FrontendServiceVersion::V1;
2060
48.6k
    params.__set_query_id(req.query_id);
2061
48.6k
    params.__set_backend_num(req.backend_num);
2062
48.6k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
48.6k
    params.__set_fragment_id(req.fragment_id);
2064
48.6k
    params.__set_status(exec_status.to_thrift());
2065
48.6k
    params.__set_done(req.done);
2066
48.6k
    params.__set_query_type(req.runtime_state->query_type());
2067
48.6k
    params.__isset.profile = false;
2068
2069
48.6k
    DCHECK(req.runtime_state != nullptr);
2070
2071
48.6k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
44.0k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
44.0k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
44.0k
    } else {
2075
4.69k
        DCHECK(!req.runtime_states.empty());
2076
4.69k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
4.69k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.69k
    }
2086
2087
48.6k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
48.6k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
48.6k
    static std::string s_unselected_rows = "unselected.rows";
2090
48.6k
    int64_t num_rows_load_success = 0;
2091
48.6k
    int64_t num_rows_load_filtered = 0;
2092
48.6k
    int64_t num_rows_load_unselected = 0;
2093
48.6k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
48.6k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
48.6k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
48.6k
    } else if (!req.runtime_states.empty()) {
2109
152k
        for (auto* rs : req.runtime_states) {
2110
152k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
152k
                rs->num_finished_range() > 0) {
2112
37.0k
                params.__isset.load_counters = true;
2113
37.0k
                num_rows_load_success += rs->num_rows_load_success();
2114
37.0k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
37.0k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
37.0k
                params.__isset.fragment_instance_reports = true;
2117
37.0k
                TFragmentInstanceReport t;
2118
37.0k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
37.0k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
37.0k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
37.0k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
37.0k
                params.fragment_instance_reports.push_back(t);
2123
37.0k
            }
2124
152k
        }
2125
48.6k
    }
2126
48.6k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
48.6k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
48.6k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
48.6k
    if (!req.load_error_url.empty()) {
2131
158
        params.__set_tracking_url(req.load_error_url);
2132
158
    }
2133
48.6k
    if (!req.first_error_msg.empty()) {
2134
158
        params.__set_first_error_msg(req.first_error_msg);
2135
158
    }
2136
152k
    for (auto* rs : req.runtime_states) {
2137
152k
        if (rs->wal_id() > 0) {
2138
109
            params.__set_txn_id(rs->wal_id());
2139
109
            params.__set_label(rs->import_label());
2140
109
        }
2141
152k
    }
2142
48.6k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
48.6k
    } else if (!req.runtime_states.empty()) {
2146
152k
        for (auto* rs : req.runtime_states) {
2147
152k
            if (!rs->export_output_files().empty()) {
2148
0
                params.__isset.export_files = true;
2149
0
                params.export_files.insert(params.export_files.end(),
2150
0
                                           rs->export_output_files().begin(),
2151
0
                                           rs->export_output_files().end());
2152
0
            }
2153
152k
        }
2154
48.6k
    }
2155
48.6k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
48.6k
    } else if (!req.runtime_states.empty()) {
2159
152k
        for (auto* rs : req.runtime_states) {
2160
152k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
27.6k
                params.__isset.commitInfos = true;
2162
27.6k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
27.6k
            }
2164
152k
        }
2165
48.6k
    }
2166
48.6k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
48.6k
    } else if (!req.runtime_states.empty()) {
2170
152k
        for (auto* rs : req.runtime_states) {
2171
152k
            if (auto rs_eti = rs->error_tablet_infos(); !rs_eti.empty()) {
2172
0
                params.__isset.errorTabletInfos = true;
2173
0
                params.errorTabletInfos.insert(params.errorTabletInfos.end(), rs_eti.begin(),
2174
0
                                               rs_eti.end());
2175
0
            }
2176
152k
        }
2177
48.6k
    }
2178
48.6k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
48.6k
    } else if (!req.runtime_states.empty()) {
2183
152k
        for (auto* rs : req.runtime_states) {
2184
152k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.12k
                params.__isset.hive_partition_updates = true;
2186
2.12k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.12k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.12k
            }
2189
152k
        }
2190
48.6k
    }
2191
48.6k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
48.6k
    } else if (!req.runtime_states.empty()) {
2196
152k
        for (auto* rs : req.runtime_states) {
2197
152k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.07k
                params.__isset.iceberg_commit_datas = true;
2199
2.07k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.07k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.07k
            }
2202
152k
        }
2203
48.6k
    }
2204
2205
48.6k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
48.6k
    } else if (!req.runtime_states.empty()) {
2209
152k
        for (auto* rs : req.runtime_states) {
2210
152k
            if (auto rs_mcd = rs->mc_commit_datas(); !rs_mcd.empty()) {
2211
0
                params.__isset.mc_commit_datas = true;
2212
0
                params.mc_commit_datas.insert(params.mc_commit_datas.end(), rs_mcd.begin(),
2213
0
                                              rs_mcd.end());
2214
0
            }
2215
152k
        }
2216
48.6k
    }
2217
2218
48.6k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
48.6k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
48.6k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
48.6k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
48.6k
    }
2224
2225
48.6k
    TReportExecStatusResult res;
2226
48.6k
    Status rpc_status;
2227
2228
48.6k
    VLOG_DEBUG << "reportExecStatus params is "
2229
24
               << apache::thrift::ThriftDebugString(params).c_str();
2230
48.6k
    if (!exec_status.ok()) {
2231
1.69k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.69k
                     << " to coordinator: " << req.coord_addr
2233
1.69k
                     << ", query id: " << print_id(req.query_id);
2234
1.69k
    }
2235
48.6k
    try {
2236
48.6k
        try {
2237
48.6k
            (*coord)->reportExecStatus(res, params);
2238
48.6k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
48.6k
        rpc_status = Status::create<false>(res.status);
2254
48.6k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
48.6k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
48.6k
}
2265
2266
504k
Status PipelineFragmentContext::send_report(bool done) {
2267
504k
    Status exec_status = _query_ctx->exec_status();
2268
    // If plan is done successfully, but _is_report_success is false,
2269
    // no need to send report.
2270
    // Load will set _is_report_success to true because load wants to know
2271
    // the process.
2272
504k
    if (!_is_report_success && done && exec_status.ok()) {
2273
455k
        return Status::OK();
2274
455k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
48.9k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
299
        if (done) {
2284
            // if done is true, which means the query is finished successfully, we can safely close the fragment instance without sending report to FE, and just return OK status here.
2285
299
            return Status::OK();
2286
299
        }
2287
0
        return Status::NeedSendAgain("");
2288
299
    }
2289
2290
48.6k
    std::vector<RuntimeState*> runtime_states;
2291
2292
110k
    for (auto& tasks : _tasks) {
2293
152k
        for (auto& task : tasks) {
2294
152k
            runtime_states.push_back(task.second.get());
2295
152k
        }
2296
110k
    }
2297
2298
48.6k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
48.6k
                                        ? get_load_error_url()
2300
48.6k
                                        : _query_ctx->get_load_error_url();
2301
48.6k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
48.6k
                                          ? get_first_error_msg()
2303
48.6k
                                          : _query_ctx->get_first_error_msg();
2304
2305
48.6k
    ReportStatusRequest req {.status = exec_status,
2306
48.6k
                             .runtime_states = runtime_states,
2307
48.6k
                             .done = done || !exec_status.ok(),
2308
48.6k
                             .coord_addr = _query_ctx->coord_addr,
2309
48.6k
                             .query_id = _query_id,
2310
48.6k
                             .fragment_id = _fragment_id,
2311
48.6k
                             .fragment_instance_id = TUniqueId(),
2312
48.6k
                             .backend_num = -1,
2313
48.6k
                             .runtime_state = _runtime_state.get(),
2314
48.6k
                             .load_error_url = load_eror_url,
2315
48.6k
                             .first_error_msg = first_error_msg,
2316
48.6k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
48.6k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
48.6k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
48.6k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
48.6k
        _coordinator_callback(req);
2321
48.6k
        if (!req.done) {
2322
4.84k
            ctx->refresh_next_report_time();
2323
4.84k
        }
2324
48.6k
    });
2325
48.9k
}
2326
2327
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
0
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
0
    for (const auto& task_instances : _tasks) {
2332
0
        for (const auto& task : task_instances) {
2333
0
            if (task.first->is_running()) {
2334
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2335
0
                                      << " is running, task: " << (void*)task.first.get()
2336
0
                                      << ", is_running: " << task.first->is_running();
2337
0
                *has_running_task = true;
2338
0
                return 0;
2339
0
            }
2340
2341
0
            size_t revocable_size = task.first->get_revocable_size();
2342
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
0
                res += revocable_size;
2344
0
            }
2345
0
        }
2346
0
    }
2347
0
    return res;
2348
0
}
2349
2350
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
0
    std::vector<PipelineTask*> revocable_tasks;
2352
0
    for (const auto& task_instances : _tasks) {
2353
0
        for (const auto& task : task_instances) {
2354
0
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
0
                revocable_tasks.emplace_back(task.first.get());
2358
0
            }
2359
0
        }
2360
0
    }
2361
0
    return revocable_tasks;
2362
0
}
2363
2364
90
std::string PipelineFragmentContext::debug_string() {
2365
90
    std::lock_guard<std::mutex> l(_task_mutex);
2366
90
    fmt::memory_buffer debug_string_buffer;
2367
90
    fmt::format_to(debug_string_buffer,
2368
90
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
90
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
90
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
348
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
258
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
876
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
618
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
618
                           _tasks[j][i].first->debug_string());
2376
618
        }
2377
258
    }
2378
2379
90
    return fmt::to_string(debug_string_buffer);
2380
90
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.55k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.55k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2385
2386
    // we do not have mutex to protect pipeline_id_to_profile
2387
    // so we need to make sure this funciton is invoked after fragment context
2388
    // has already been prepared.
2389
2.55k
    if (!_prepared) {
2390
0
        std::string msg =
2391
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2392
0
        DCHECK(false) << msg;
2393
0
        LOG_ERROR(msg);
2394
0
        return res;
2395
0
    }
2396
2397
    // Make sure first profile is fragment level profile
2398
2.55k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.55k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.55k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.66k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.66k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.66k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.66k
        res.push_back(profile_ptr);
2407
4.66k
    }
2408
2409
2.55k
    return res;
2410
2.55k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.55k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2414
    // we do not have mutex to protect pipeline_id_to_profile
2415
    // so we need to make sure this funciton is invoked after fragment context
2416
    // has already been prepared.
2417
2.55k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
8.14k
    for (const auto& tasks : _tasks) {
2426
16.0k
        for (const auto& task : tasks) {
2427
16.0k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
16.0k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
16.0k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
16.0k
                                                           _runtime_state->profile_level());
2435
16.0k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
16.0k
        }
2437
8.14k
    }
2438
2439
2.55k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.55k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.55k
                                                      _runtime_state->profile_level());
2442
2.55k
    return load_channel_profile;
2443
2.55k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.18k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.18k
    std::set<int> result;
2454
11.7k
    for (const auto& _task : _tasks) {
2455
25.8k
        for (const auto& task : _task) {
2456
25.8k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
25.8k
            result.merge(set);
2458
25.8k
        }
2459
11.7k
    }
2460
3.18k
    if (_runtime_state) {
2461
3.18k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.18k
        result.merge(set);
2463
3.18k
    }
2464
3.18k
    return result;
2465
3.18k
}
2466
2467
504k
void PipelineFragmentContext::_release_resource() {
2468
504k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
504k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
504k
    auto st = _query_ctx->exec_status();
2472
1.20M
    for (auto& _task : _tasks) {
2473
1.20M
        if (!_task.empty()) {
2474
1.20M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.20M
        }
2476
1.20M
    }
2477
504k
    _tasks.clear();
2478
504k
    _dag.clear();
2479
504k
    _pip_id_to_pipeline.clear();
2480
504k
    _pipelines.clear();
2481
504k
    _sink.reset();
2482
504k
    _root_op.reset();
2483
504k
    _runtime_filter_mgr_map.clear();
2484
504k
    _op_id_to_shared_state.clear();
2485
504k
}
2486
2487
} // namespace doris