Coverage Report

Created: 2026-06-17 10:33

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
327k
        : _query_id(std::move(query_id)),
144
327k
          _fragment_id(request.fragment_id),
145
327k
          _exec_env(exec_env),
146
327k
          _query_ctx(std::move(query_ctx)),
147
327k
          _call_back(call_back),
148
327k
          _is_report_on_cancel(true),
149
327k
          _params(request),
150
327k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
327k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
327k
                                                               : false) {
153
327k
    _fragment_watcher.start();
154
327k
}
155
156
327k
PipelineFragmentContext::~PipelineFragmentContext() {
157
327k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
327k
            .tag("query_id", print_id(_query_id))
159
327k
            .tag("fragment_id", _fragment_id);
160
327k
    _release_resource();
161
327k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
327k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
327k
        _runtime_state.reset();
165
327k
        _query_ctx.reset();
166
327k
    }
167
327k
}
168
169
54
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
54
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
54
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
54
}
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
8.75k
bool PipelineFragmentContext::notify_close() {
181
8.75k
    bool all_closed = false;
182
8.75k
    bool need_remove = false;
183
8.75k
    {
184
8.75k
        std::lock_guard<std::mutex> l(_task_mutex);
185
8.75k
        if (_closed_tasks >= _total_tasks) {
186
3.45k
            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
3.41k
                need_remove = true;
193
3.41k
            }
194
3.45k
            all_closed = true;
195
3.45k
        }
196
        // make fragment release by self after cancel
197
8.75k
        _need_notify_close = false;
198
8.75k
    }
199
8.75k
    if (need_remove) {
200
3.41k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.41k
    }
202
8.75k
    return all_closed;
203
8.75k
}
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
5.27k
void PipelineFragmentContext::cancel(const Status reason) {
210
5.27k
    LOG_INFO("PipelineFragmentContext::cancel")
211
5.27k
            .tag("query_id", print_id(_query_id))
212
5.27k
            .tag("fragment_id", _fragment_id)
213
5.27k
            .tag("reason", reason.to_string());
214
5.27k
    if (notify_close()) {
215
59
        return;
216
59
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
5.21k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
5.21k
    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
5.22k
    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
5.21k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
5.21k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
5.21k
    _query_ctx->cancel(reason, _fragment_id);
243
5.21k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
177
        _is_report_on_cancel = false;
245
5.04k
    } else {
246
20.4k
        for (auto& id : _fragment_instance_ids) {
247
20.4k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
20.4k
        }
249
5.04k
    }
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
5.21k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
5.21k
    if (stream_load_ctx != nullptr) {
254
31
        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
31
        stream_load_ctx->error_url = get_load_error_url();
259
31
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
31
    }
261
262
21.2k
    for (auto& tasks : _tasks) {
263
47.8k
        for (auto& task : tasks) {
264
47.8k
            task.first->unblock_all_dependencies();
265
47.8k
        }
266
21.2k
    }
267
5.21k
}
268
269
508k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
508k
    PipelineId id = _next_pipeline_id++;
271
508k
    auto pipeline = std::make_shared<Pipeline>(
272
508k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
508k
            parent ? parent->num_tasks() : _num_instances);
274
508k
    if (idx >= 0) {
275
102k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
405k
    } else {
277
405k
        _pipelines.emplace_back(pipeline);
278
405k
    }
279
508k
    if (parent) {
280
180k
        parent->set_children(pipeline);
281
180k
    }
282
508k
    return pipeline;
283
508k
}
284
285
326k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
326k
    {
287
326k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
326k
        auto root_pipeline = add_pipeline();
290
326k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
326k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
326k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
326k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
326k
                                          _params.fragment.output_exprs, _params,
299
326k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
326k
                                          *_desc_tbl, root_pipeline->id()));
301
326k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
326k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
405k
        for (PipelinePtr& pipeline : _pipelines) {
305
405k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
405k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
405k
        }
308
326k
    }
309
    // 4. Build local exchanger
310
326k
    if (_runtime_state->enable_local_shuffle()) {
311
324k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
324k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
324k
                                             _params.bucket_seq_to_instance_idx,
314
324k
                                             _params.shuffle_idx_to_instance_idx));
315
324k
    }
316
317
    // 5. Initialize global states in pipelines.
318
509k
    for (PipelinePtr& pipeline : _pipelines) {
319
509k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
509k
        pipeline->children().clear();
321
509k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
509k
    }
323
324
325k
    {
325
325k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
325k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
325k
    }
329
330
325k
    return Status::OK();
331
325k
}
332
333
327k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
327k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
327k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
327k
        _timeout = _params.query_options.execution_timeout;
339
327k
    }
340
341
327k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
327k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
327k
    SCOPED_TIMER(_prepare_timer);
344
327k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
327k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
327k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
327k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
327k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
327k
    {
350
327k
        SCOPED_TIMER(_init_context_timer);
351
327k
        cast_set(_num_instances, _params.local_params.size());
352
327k
        _total_instances =
353
327k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
327k
        auto* fragment_context = this;
356
357
327k
        if (_params.query_options.__isset.is_report_success) {
358
324k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
324k
        }
360
361
        // 1. Set up the global runtime state.
362
327k
        _runtime_state = RuntimeState::create_unique(
363
327k
                _params.query_id, _params.fragment_id, _params.query_options,
364
327k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
327k
        _runtime_state->set_task_execution_context(shared_from_this());
366
327k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
327k
        if (_params.__isset.backend_id) {
368
324k
            _runtime_state->set_backend_id(_params.backend_id);
369
324k
        }
370
327k
        if (_params.__isset.import_label) {
371
239
            _runtime_state->set_import_label(_params.import_label);
372
239
        }
373
327k
        if (_params.__isset.db_name) {
374
191
            _runtime_state->set_db_name(_params.db_name);
375
191
        }
376
327k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
327k
        if (_params.is_simplified_param) {
381
114k
            _desc_tbl = _query_ctx->desc_tbl;
382
212k
        } else {
383
212k
            DCHECK(_params.__isset.desc_tbl);
384
212k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
212k
                                                  &_desc_tbl));
386
212k
        }
387
327k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
327k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
327k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
327k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
327k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
327k
        const auto target_size = _params.local_params.size();
395
327k
        _fragment_instance_ids.resize(target_size);
396
1.21M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
890k
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
890k
            _fragment_instance_ids[i] = fragment_instance_id;
399
890k
        }
400
327k
    }
401
402
327k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
325k
    _init_next_report_time();
405
406
325k
    _prepared = true;
407
325k
    return Status::OK();
408
327k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
891k
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
891k
    const auto& local_params = _params.local_params[instance_idx];
414
891k
    auto fragment_instance_id = local_params.fragment_instance_id;
415
891k
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
891k
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
891k
    auto get_shared_state = [&](PipelinePtr pipeline)
418
891k
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.46M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.46M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.46M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.46M
                shared_state_map;
423
1.95M
        for (auto& op : pipeline->operators()) {
424
1.95M
            auto source_id = op->operator_id();
425
1.95M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
1.95M
                iter != _op_id_to_shared_state.end()) {
427
607k
                shared_state_map.insert({source_id, iter->second});
428
607k
            }
429
1.95M
        }
430
1.46M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.46M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.46M
                iter != _op_id_to_shared_state.end()) {
433
274k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
274k
            }
435
1.46M
        }
436
1.46M
        return shared_state_map;
437
1.46M
    };
438
439
2.68M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
1.79M
        auto& pipeline = _pipelines[pip_idx];
441
1.79M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.46M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.46M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.46M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.46M
            {
446
                // Initialize runtime state for this task
447
1.46M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.46M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.46M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.46M
                if (_params.__isset.backend_id) {
453
1.46M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.46M
                }
455
1.46M
                if (_params.__isset.import_label) {
456
240
                    task_runtime_state->set_import_label(_params.import_label);
457
240
                }
458
1.46M
                if (_params.__isset.db_name) {
459
192
                    task_runtime_state->set_db_name(_params.db_name);
460
192
                }
461
1.46M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.46M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.46M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.46M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.46M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.46M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.46M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.46M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.46M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.46M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.46M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.46M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.46M
            }
482
1.46M
            auto cur_task_id = _total_tasks++;
483
1.46M
            task_runtime_state->set_task_id(cur_task_id);
484
1.46M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.46M
            auto task = std::make_shared<PipelineTask>(
486
1.46M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.46M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.46M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.46M
                    instance_idx);
490
1.46M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.46M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.46M
            _tasks[instance_idx].emplace_back(
493
1.46M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.46M
                            std::move(task), std::move(task_runtime_state)});
495
1.46M
        }
496
1.79M
    }
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
1.79M
    for (auto& _pipeline : _pipelines) {
516
1.79M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.45M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.45M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.45M
            if (_dag.contains(_pipeline->id())) {
522
916k
                auto& deps = _dag[_pipeline->id()];
523
1.49M
                for (auto& dep : deps) {
524
1.49M
                    if (pipeline_id_to_task.contains(dep)) {
525
837k
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
837k
                        if (ss) {
527
291k
                            task->inject_shared_state(ss);
528
545k
                        } else {
529
545k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
545k
                                    task->get_source_shared_state());
531
545k
                        }
532
837k
                    }
533
1.49M
                }
534
916k
            }
535
1.45M
        }
536
1.79M
    }
537
2.68M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
1.79M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.45M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.45M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.45M
            std::vector<TScanRangeParams> scan_ranges;
542
1.45M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.45M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
230k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
230k
            }
546
1.45M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.45M
                                                             _params.fragment.output_sink));
548
1.45M
        }
549
1.79M
    }
550
896k
    {
551
896k
        std::lock_guard<std::mutex> l(_state_map_lock);
552
896k
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
896k
    }
554
896k
    return Status::OK();
555
891k
}
556
557
326k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
326k
    _total_tasks = 0;
559
326k
    _closed_tasks = 0;
560
326k
    const auto target_size = _params.local_params.size();
561
326k
    _tasks.resize(target_size);
562
326k
    _runtime_filter_mgr_map.resize(target_size);
563
834k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
508k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
508k
    }
566
326k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
326k
    if (target_size > 1 &&
569
326k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
121k
         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
21.3k
        std::vector<Status> prepare_status(target_size);
573
21.3k
        int submitted_tasks = 0;
574
21.3k
        Status submit_status;
575
21.3k
        CountDownLatch latch((int)target_size);
576
243k
        for (int i = 0; i < target_size; i++) {
577
222k
            submit_status = thread_pool->submit_func([&, i]() {
578
222k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
222k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
222k
                latch.count_down();
581
222k
            });
582
222k
            if (LIKELY(submit_status.ok())) {
583
222k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
222k
        }
588
21.3k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
21.3k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
243k
        for (int i = 0; i < submitted_tasks; i++) {
593
222k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
222k
        }
597
304k
    } else {
598
976k
        for (int i = 0; i < target_size; i++) {
599
671k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
671k
        }
601
304k
    }
602
326k
    _pipeline_parent_map.clear();
603
326k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
326k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
326k
    return Status::OK();
608
326k
}
609
610
325k
void PipelineFragmentContext::_init_next_report_time() {
611
325k
    auto interval_s = config::pipeline_status_report_interval;
612
325k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
31.6k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
31.6k
        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
31.6k
        _previous_report_time =
617
31.6k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
31.6k
        _disable_period_report = false;
619
31.6k
    }
620
325k
}
621
622
3.60k
void PipelineFragmentContext::refresh_next_report_time() {
623
3.60k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
3.60k
    DCHECK(disable == true);
625
3.60k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
3.60k
    _disable_period_report.compare_exchange_strong(disable, false);
627
3.60k
}
628
629
5.33M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
5.33M
    if (!_is_report_success) {
631
5.02M
        return;
632
5.02M
    }
633
318k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
318k
    if (disable) {
635
5.29k
        return;
636
5.29k
    }
637
313k
    int32_t interval_s = config::pipeline_status_report_interval;
638
313k
    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
313k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
313k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
313k
    if (MonotonicNanos() > next_report_time) {
646
3.60k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
3.60k
                                                            std::memory_order_acq_rel)) {
648
7
            return;
649
7
        }
650
3.60k
        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
3.60k
        auto st = send_report(false);
667
3.60k
        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
3.60k
    }
673
313k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
323k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
323k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
323k
    int node_idx = 0;
682
683
323k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
323k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
323k
    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
323k
    return Status::OK();
691
323k
}
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
499k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
499k
    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
499k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
499k
    int num_children = tnodes[*node_idx].num_children;
706
499k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
499k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
499k
    OperatorPtr op = nullptr;
710
499k
    OperatorPtr cache_op = nullptr;
711
499k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
499k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
499k
                                     followed_by_shuffled_operator,
714
499k
                                     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
499k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
499k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
176k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
323k
    } else {
723
323k
        *root = op;
724
323k
    }
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
499k
    auto required_data_distribution =
737
499k
            cur_pipe->operators().empty()
738
499k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
499k
                    : op->required_data_distribution(_runtime_state.get());
740
499k
    current_followed_by_shuffled_operator =
741
499k
            ((followed_by_shuffled_operator ||
742
499k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
443k
                                             : op->is_shuffled_operator())) &&
744
499k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
499k
            (followed_by_shuffled_operator &&
746
393k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
499k
    current_require_bucket_distribution =
749
499k
            ((require_bucket_distribution ||
750
499k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
448k
                                             : op->is_colocated_operator())) &&
752
499k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
499k
            (require_bucket_distribution &&
754
399k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
499k
    if (num_children == 0) {
757
337k
        _use_serial_source = op->is_serial_operator();
758
337k
    }
759
    // rely on that tnodes is preorder of the plan
760
676k
    for (int i = 0; i < num_children; i++) {
761
176k
        ++*node_idx;
762
176k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
176k
                                            current_followed_by_shuffled_operator,
764
176k
                                            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
176k
        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
176k
    }
775
776
499k
    return Status::OK();
777
499k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
102k
        PipelinePtr pipe_with_sink) {
782
102k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
102k
    pipe_with_source->set_num_tasks(_num_instances);
784
102k
    pipe_with_source->set_data_distribution(data_distribution);
785
102k
}
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
102k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
102k
    auto& operators = cur_pipe->operators();
793
102k
    const auto downstream_pipeline_id = cur_pipe->id();
794
102k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
102k
    DataSinkOperatorPtr sink;
797
102k
    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
102k
    const bool followed_by_shuffled_operator =
804
102k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
102k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
102k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
102k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
102k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
102k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
102k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
102k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
102k
    if (bucket_seq_to_instance_idx.empty() &&
813
102k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
8
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
8
    }
816
102k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
102k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
102k
                                          num_buckets, use_global_hash_shuffle,
819
102k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
102k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
102k
            LocalExchangeSharedState::create_shared(_num_instances);
824
102k
    switch (data_distribution.distribution_type) {
825
21.1k
    case ExchangeType::HASH_SHUFFLE:
826
21.1k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
21.1k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
21.1k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
21.1k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
21.1k
                        ? cast_set<int>(
831
21.1k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
21.1k
                        : 0);
833
21.1k
        break;
834
488
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
488
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
488
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
488
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
488
                        ? cast_set<int>(
839
488
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
488
                        : 0);
841
488
        break;
842
77.7k
    case ExchangeType::PASSTHROUGH:
843
77.7k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
77.7k
                cur_pipe->num_tasks(), _num_instances,
845
77.7k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
77.7k
                        ? cast_set<int>(
847
77.7k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
77.7k
                        : 0);
849
77.7k
        break;
850
318
    case ExchangeType::BROADCAST:
851
318
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
318
                cur_pipe->num_tasks(), _num_instances,
853
318
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
318
                        ? cast_set<int>(
855
318
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
318
                        : 0);
857
318
        break;
858
2.11k
    case ExchangeType::PASS_TO_ONE:
859
2.11k
        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
1.14k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.14k
                    cur_pipe->num_tasks(), _num_instances,
863
1.14k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.14k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.14k
                                                    .local_exchange_free_blocks_limit)
866
1.14k
                            : 0);
867
1.14k
        } else {
868
972
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
972
                    cur_pipe->num_tasks(), _num_instances,
870
972
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
972
                            ? cast_set<int>(_runtime_state->query_options()
872
972
                                                    .local_exchange_free_blocks_limit)
873
972
                            : 0);
874
972
        }
875
2.11k
        break;
876
922
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
922
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
922
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
922
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
922
                        ? cast_set<int>(
881
922
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
922
                        : 0);
883
922
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
102k
    }
888
102k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
102k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
102k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
102k
    _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
102k
    std::copy(operators.begin(), operators.begin() + idx,
898
102k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
102k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
102k
    OperatorPtr source_op;
905
102k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
102k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
102k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
102k
    if (!operators.empty()) {
909
42.6k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
42.6k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
42.6k
    }
912
102k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
102k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
102k
    std::vector<PipelineId> edges_with_source;
917
119k
    for (auto child : cur_pipe->children()) {
918
119k
        bool found = false;
919
134k
        for (auto op : new_pip->operators()) {
920
134k
            if (child->sink()->node_id() == op->node_id()) {
921
12.2k
                new_pip->set_children(child);
922
12.2k
                found = true;
923
12.2k
            };
924
134k
        }
925
119k
        if (!found) {
926
107k
            new_children.push_back(child);
927
107k
            edges_with_source.push_back(child->id());
928
107k
        }
929
119k
    }
930
102k
    new_children.push_back(new_pip);
931
102k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
102k
    if (!new_pip->children().empty()) {
935
6.78k
        std::vector<PipelineId> edges_with_sink;
936
12.2k
        for (auto child : new_pip->children()) {
937
12.2k
            edges_with_sink.push_back(child->id());
938
12.2k
        }
939
6.78k
        _dag.insert({new_pip->id(), edges_with_sink});
940
6.78k
    }
941
102k
    cur_pipe->set_children(new_children);
942
102k
    _dag[downstream_pipeline_id] = edges_with_source;
943
102k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
102k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
102k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
102k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
102k
    return Status::OK();
950
102k
}
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
152k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
152k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
25.2k
        return Status::OK();
959
25.2k
    }
960
961
127k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
45.8k
        return Status::OK();
963
45.8k
    }
964
81.3k
    *do_local_exchange = true;
965
966
81.3k
    auto& operators = cur_pipe->operators();
967
81.3k
    auto total_op_num = operators.size();
968
81.3k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
81.3k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
81.3k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
81.3k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
18.4E
            << "total_op_num: " << total_op_num
975
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
18.4E
            << " 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
81.4k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
81.3k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
21.2k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
21.2k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
21.2k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
21.2k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
21.2k
                shuffle_idx_to_instance_idx));
990
21.2k
    }
991
81.3k
    return Status::OK();
992
81.3k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
323k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
727k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
403k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
403k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
77.7k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
77.7k
                if (child->sink()->node_id() ==
1003
77.7k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
66.8k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
66.8k
                }
1006
77.7k
            }
1007
74.1k
        }
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
403k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
403k
                                             bucket_seq_to_instance_idx,
1014
403k
                                             shuffle_idx_to_instance_idx));
1015
403k
    }
1016
323k
    return Status::OK();
1017
323k
}
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
402k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
402k
    int idx = 1;
1024
402k
    bool do_local_exchange = false;
1025
445k
    do {
1026
445k
        auto& ops = pip->operators();
1027
445k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
501k
        for (; idx < ops.size();) {
1030
98.8k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
93.4k
                RETURN_IF_ERROR(_add_local_exchange(
1032
93.4k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
93.4k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
93.4k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
93.4k
                        shuffle_idx_to_instance_idx));
1036
93.4k
            }
1037
98.8k
            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
42.8k
                idx = 2;
1043
42.8k
                break;
1044
42.8k
            }
1045
56.0k
            idx++;
1046
56.0k
        }
1047
445k
    } while (do_local_exchange);
1048
402k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
58.9k
        RETURN_IF_ERROR(_add_local_exchange(
1050
58.9k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
58.9k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
58.9k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
58.9k
    }
1054
402k
    return Status::OK();
1055
402k
}
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
326k
                                                  PipelineId cur_pipeline_id) {
1063
326k
    switch (thrift_sink.type) {
1064
113k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
113k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
113k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
113k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
113k
                params.destinations, _fragment_instance_ids);
1071
113k
        break;
1072
113k
    }
1073
182k
    case TDataSinkType::RESULT_SINK: {
1074
182k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
182k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
182k
        int child_node_id = pipeline->operators().back()->node_id();
1080
182k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
182k
                                                      row_desc, output_exprs,
1082
182k
                                                      thrift_sink.result_sink);
1083
182k
        break;
1084
182k
    }
1085
104
    case TDataSinkType::DICTIONARY_SINK: {
1086
104
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
104
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
104
                                                    thrift_sink.dictionary_sink);
1092
104
        break;
1093
104
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
29.0k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
29.0k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
29.0k
        int child_node_id = pipeline->operators().back()->node_id();
1098
29.0k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
29.0k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
29.0k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
58
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
58
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
28.9k
        } else {
1104
28.9k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
28.9k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
28.9k
        }
1107
29.0k
        break;
1108
0
    }
1109
166
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
166
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
166
        DCHECK(state->get_query_ctx() != nullptr);
1112
166
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
166
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
166
                                                                output_exprs);
1115
166
        break;
1116
0
    }
1117
0
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
0
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
0
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
0
                                                         output_exprs);
1123
0
        break;
1124
0
    }
1125
0
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
0
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
0
        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
0
        } else {
1133
0
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
0
                                                                row_desc, output_exprs);
1135
0
        }
1136
0
        break;
1137
0
    }
1138
0
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
0
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
0
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
0
                                                             row_desc, output_exprs);
1144
0
        break;
1145
0
    }
1146
0
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
0
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
0
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
0
                                                            output_exprs);
1152
0
        break;
1153
0
    }
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
0
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
0
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
0
        if (config::enable_java_support) {
1167
0
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
0
                                                             output_exprs);
1169
0
        } 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
0
        break;
1175
0
    }
1176
3
    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
338
    case TDataSinkType::RESULT_FILE_SINK: {
1186
338
        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
338
        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
338
        } else {
1196
338
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
338
                                                              output_exprs);
1198
338
        }
1199
338
        break;
1200
338
    }
1201
634
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
634
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
634
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
634
        auto sink_id = next_sink_operator_id();
1205
634
        const int multi_cast_node_id = sink_id;
1206
634
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
634
        std::vector<int> sources;
1209
2.33k
        for (int i = 0; i < sender_size; ++i) {
1210
1.70k
            auto source_id = next_operator_id();
1211
1.70k
            sources.push_back(source_id);
1212
1.70k
        }
1213
1214
634
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
634
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
2.33k
        for (int i = 0; i < sender_size; ++i) {
1217
1.70k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
1.70k
            RowDescriptor* exchange_row_desc = nullptr;
1220
1.70k
            {
1221
1.70k
                const auto& tmp_row_desc =
1222
1.70k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
1.70k
                                ? RowDescriptor(state->desc_tbl(),
1224
1.70k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
1.70k
                                                         .output_tuple_id})
1226
1.70k
                                : row_desc;
1227
1.70k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
1.70k
            }
1229
1.70k
            auto source_id = sources[i];
1230
1.70k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
1.70k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
1.70k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
1.70k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
1.70k
                    /*operator_id=*/source_id);
1236
1.70k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
1.70k
                    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
1.70k
            DataSinkOperatorPtr sink_op;
1241
1.70k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
1.70k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
1.70k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
1.70k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
1.70k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
1.70k
            {
1248
1.70k
                TDataSink* t = pool->add(new TDataSink());
1249
1.70k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
1.70k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
1.70k
            }
1252
1253
            // 3. set dependency dag
1254
1.70k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
1.70k
        }
1256
634
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
634
        break;
1260
634
    }
1261
634
    case TDataSinkType::BLACKHOLE_SINK: {
1262
3
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
3
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
3
        break;
1268
3
    }
1269
0
    case TDataSinkType::TVF_TABLE_SINK: {
1270
0
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
0
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
0
                                                        output_exprs);
1275
0
        break;
1276
0
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
326k
    }
1280
325k
    return Status::OK();
1281
326k
}
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
503k
                                                 OperatorPtr& cache_op) {
1292
503k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
503k
    Defer defer = Defer([&]() {
1294
503k
        if (op) {
1295
503k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
503k
        }
1297
502k
        for (auto& s : sink_ops) {
1298
77.4k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
77.4k
        }
1300
502k
    });
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
503k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
503k
    std::stringstream error_msg;
1305
503k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
503k
    bool fe_with_old_version = false;
1308
503k
    switch (tnode.node_type) {
1309
162k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
162k
        op = std::make_shared<OlapScanOperatorX>(
1311
162k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
162k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
162k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
162k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
162k
        break;
1316
162k
    }
1317
78
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
78
        DCHECK(_query_ctx != nullptr);
1319
78
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
78
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
78
                                                    _num_instances);
1322
78
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
78
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
78
        break;
1325
78
    }
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
2.66k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
2.66k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
2.66k
                                                 _num_instances);
1342
2.66k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
2.66k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
2.66k
        break;
1345
2.66k
    }
1346
113k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
113k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
113k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
113k
        DCHECK_GT(num_senders, 0);
1351
113k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
113k
                                                       num_senders);
1353
113k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
113k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
113k
        break;
1356
113k
    }
1357
116k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
116k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
116k
            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
116k
        bool need_create_cache_op =
1364
116k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
116k
        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
116k
        const bool group_by_limit_opt =
1385
116k
                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
116k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
116k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
116k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
116k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
116k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
116k
        const bool can_use_distinct_streaming_agg =
1396
116k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
116k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
116k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
116k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
116k
        if (can_use_distinct_streaming_agg) {
1402
84.5k
            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
84.5k
            } else {
1413
84.5k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
84.5k
                                                                     tnode, descs);
1415
84.5k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
84.5k
            }
1417
84.5k
        } else if (is_streaming_agg) {
1418
819
            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
819
            } else {
1428
819
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
819
                                                             descs);
1430
819
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
819
            }
1432
31.1k
        } else {
1433
            // create new pipeline to add query cache operator
1434
31.1k
            PipelinePtr new_pipe;
1435
31.1k
            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
31.1k
            if (enable_spill) {
1441
122
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
122
                                                                     next_operator_id(), descs);
1443
31.0k
            } else {
1444
31.0k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
31.0k
            }
1446
31.1k
            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
31.1k
            } else {
1451
31.1k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
31.1k
            }
1453
1454
31.1k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
31.1k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
29.9k
                _dag.insert({downstream_pipeline_id, {}});
1457
29.9k
            }
1458
31.1k
            cur_pipe = add_pipeline(cur_pipe);
1459
31.1k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
31.1k
            if (enable_spill) {
1462
122
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
122
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
31.0k
            } else {
1465
31.0k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
31.0k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
31.0k
            }
1468
31.1k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
31.1k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
31.1k
        }
1471
116k
        break;
1472
116k
    }
1473
116k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
66
        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
66
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
66
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
66
        const auto downstream_pipeline_id = cur_pipe->id();
1486
66
        if (!_dag.contains(downstream_pipeline_id)) {
1487
66
            _dag.insert({downstream_pipeline_id, {}});
1488
66
        }
1489
66
        cur_pipe = add_pipeline(cur_pipe);
1490
66
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
66
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
66
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
66
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
66
        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
66
        {
1503
66
            auto shared_state = BucketedAggSharedState::create_shared();
1504
66
            shared_state->id = op->operator_id();
1505
66
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
501
            for (int i = 0; i < _num_instances; i++) {
1508
435
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
435
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
435
                sink_dep->set_shared_state(shared_state.get());
1511
435
                shared_state->sink_deps.push_back(sink_dep);
1512
435
            }
1513
66
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
66
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
66
            _op_id_to_shared_state.insert(
1516
66
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
66
        }
1518
66
        break;
1519
66
    }
1520
8.79k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
8.79k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
8.79k
                                       tnode.hash_join_node.is_broadcast_join;
1523
8.79k
        const auto enable_spill = _runtime_state->enable_spill();
1524
8.79k
        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
8.79k
        } else {
1566
8.79k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
8.79k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
8.79k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
8.79k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.12k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.12k
            }
1573
8.79k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
8.79k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
8.79k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
8.79k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
8.79k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
8.79k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
8.79k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
8.79k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
8.79k
        }
1584
8.79k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
1.99k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
1.99k
                    HashJoinSharedState::create_shared(_num_instances);
1587
13.3k
            for (int i = 0; i < _num_instances; i++) {
1588
11.3k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
11.3k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
11.3k
                sink_dep->set_shared_state(shared_state.get());
1591
11.3k
                shared_state->sink_deps.push_back(sink_dep);
1592
11.3k
            }
1593
1.99k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
1.99k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
1.99k
            _op_id_to_shared_state.insert(
1596
1.99k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
1.99k
        }
1598
8.79k
        break;
1599
8.79k
    }
1600
2.14k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
2.14k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
2.14k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
2.14k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
2.14k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
1.91k
            _dag.insert({downstream_pipeline_id, {}});
1607
1.91k
        }
1608
2.14k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
2.14k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
2.14k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
2.14k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
2.14k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
2.14k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
2.14k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
2.14k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
2.14k
        break;
1618
2.14k
    }
1619
49.8k
    case TPlanNodeType::UNION_NODE: {
1620
49.8k
        int child_count = tnode.num_children;
1621
49.8k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
49.8k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
49.8k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
49.8k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
49.4k
            _dag.insert({downstream_pipeline_id, {}});
1627
49.4k
        }
1628
50.8k
        for (int i = 0; i < child_count; i++) {
1629
980
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
980
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
980
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
980
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
980
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
980
            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
980
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
980
        }
1638
49.8k
        break;
1639
49.8k
    }
1640
49.8k
    case TPlanNodeType::SORT_NODE: {
1641
32.6k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
32.6k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
32.6k
        const bool use_local_merge =
1644
32.6k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
32.6k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
32.6k
        } else if (use_local_merge) {
1648
30.7k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
30.7k
                                                                 descs);
1650
30.7k
        } else {
1651
1.87k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
1.87k
        }
1653
32.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
32.6k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
32.6k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
32.5k
            _dag.insert({downstream_pipeline_id, {}});
1658
32.5k
        }
1659
32.6k
        cur_pipe = add_pipeline(cur_pipe);
1660
32.6k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
32.6k
        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
32.6k
        } else {
1666
32.6k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
32.6k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
32.6k
        }
1669
32.6k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
32.6k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
32.6k
        break;
1672
32.6k
    }
1673
32.6k
    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
1.60k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.60k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.60k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.60k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.59k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.59k
        }
1698
1.60k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.60k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.60k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.60k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.60k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.60k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.60k
        break;
1706
1.60k
    }
1707
1.60k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
711
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
711
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
711
        break;
1711
711
    }
1712
711
    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
298
    case TPlanNodeType::REPEAT_NODE: {
1723
298
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
298
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
298
        break;
1726
298
    }
1727
910
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
910
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
910
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
910
        break;
1731
910
    }
1732
910
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
18
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
18
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
18
        break;
1736
18
    }
1737
1.45k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.45k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.45k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.45k
        break;
1741
1.45k
    }
1742
1.45k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
272
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
272
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
272
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
272
        break;
1747
272
    }
1748
1.54k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.54k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.54k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.54k
        break;
1752
1.54k
    }
1753
4.88k
    case TPlanNodeType::META_SCAN_NODE: {
1754
4.88k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
4.88k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
4.88k
        break;
1757
4.88k
    }
1758
4.88k
    case TPlanNodeType::SELECT_NODE: {
1759
618
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
618
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
618
        break;
1762
618
    }
1763
618
    case TPlanNodeType::REC_CTE_NODE: {
1764
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
151
        const auto downstream_pipeline_id = cur_pipe->id();
1768
151
        if (!_dag.contains(downstream_pipeline_id)) {
1769
148
            _dag.insert({downstream_pipeline_id, {}});
1770
148
        }
1771
1772
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
151
        DataSinkOperatorPtr anchor_sink;
1776
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
151
                                                                  op->operator_id(), tnode, descs);
1778
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
151
        DataSinkOperatorPtr rec_sink;
1786
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
151
                                                         tnode, descs);
1788
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
151
        break;
1793
151
    }
1794
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.95k
        break;
1798
1.95k
    }
1799
1.95k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
503k
    }
1803
502k
    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
502k
    return Status::OK();
1809
503k
}
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
322k
Status PipelineFragmentContext::submit() {
1846
322k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
322k
    _submitted = true;
1850
1851
322k
    int submit_tasks = 0;
1852
322k
    Status st;
1853
322k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
893k
    for (auto& task : _tasks) {
1855
1.47M
        for (auto& t : task) {
1856
1.47M
            st = scheduler->submit(t.first);
1857
1.47M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.47M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.47M
            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
1.47M
            submit_tasks++;
1866
1.47M
        }
1867
893k
    }
1868
322k
    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
322k
    } else {
1883
322k
        return st;
1884
322k
    }
1885
322k
}
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
326k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
326k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
326k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
326k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
326k
    if (!_need_notify_close) {
1919
322k
        auto st = send_report(true);
1920
322k
        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
322k
    }
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
326k
    if (_runtime_state->enable_profile() &&
1931
326k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.04k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.04k
         _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
326k
    if (_query_ctx->enable_profile()) {
1953
2.04k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.04k
                                         collect_realtime_load_channel_profile());
1955
2.04k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
326k
    return !_need_notify_close;
1960
326k
}
1961
1962
1.46M
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
1.46M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.46M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
508k
        if (_dag.contains(pipeline_id)) {
1967
285k
            for (auto dep : _dag[pipeline_id]) {
1968
285k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
285k
            }
1970
223k
        }
1971
508k
    }
1972
1.46M
    bool need_remove = false;
1973
1.46M
    {
1974
1.46M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.46M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.46M
        _query_ctx->inc_finished_task_num();
1978
1.46M
        if (_closed_tasks >= _total_tasks) {
1979
326k
            need_remove = _close_fragment_instance();
1980
326k
        }
1981
1.46M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.46M
    if (need_remove) {
1984
323k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
323k
    }
1986
1.46M
}
1987
1988
41.8k
std::string PipelineFragmentContext::get_load_error_url() {
1989
41.8k
    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
89.5k
    for (auto& tasks : _tasks) {
1993
147k
        for (auto& task : tasks) {
1994
147k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
182
                return to_load_error_http_path(str);
1996
182
            }
1997
147k
        }
1998
89.5k
    }
1999
41.7k
    return "";
2000
41.8k
}
2001
2002
41.8k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
41.8k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
89.4k
    for (auto& tasks : _tasks) {
2007
147k
        for (auto& task : tasks) {
2008
147k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
182
                return str;
2010
182
            }
2011
147k
        }
2012
89.4k
    }
2013
41.7k
    return "";
2014
41.8k
}
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
36.6k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
36.6k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
36.6k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
36.6k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
36.6k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
36.6k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
36.6k
    });
2031
2032
36.6k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
36.6k
    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
36.6k
    int callback_retries = 10;
2038
36.6k
    const int sleep_ms = 1000;
2039
36.6k
    Status exec_status = req.status;
2040
36.6k
    Status coord_status;
2041
36.6k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
36.6k
    do {
2043
36.6k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
36.6k
                                                            req.coord_addr, &coord_status);
2045
36.6k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
36.6k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
36.6k
    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
36.6k
    TReportExecStatusParams params;
2059
36.6k
    params.protocol_version = FrontendServiceVersion::V1;
2060
36.6k
    params.__set_query_id(req.query_id);
2061
36.6k
    params.__set_backend_num(req.backend_num);
2062
36.6k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
36.6k
    params.__set_fragment_id(req.fragment_id);
2064
36.6k
    params.__set_status(exec_status.to_thrift());
2065
36.6k
    params.__set_done(req.done);
2066
36.6k
    params.__set_query_type(req.runtime_state->query_type());
2067
36.6k
    params.__isset.profile = false;
2068
2069
36.6k
    DCHECK(req.runtime_state != nullptr);
2070
2071
36.6k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
33.0k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
33.0k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
33.0k
    } else {
2075
3.62k
        DCHECK(!req.runtime_states.empty());
2076
3.62k
        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
3.62k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
3.62k
    }
2086
2087
36.6k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
36.6k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
36.6k
    static std::string s_unselected_rows = "unselected.rows";
2090
36.6k
    int64_t num_rows_load_success = 0;
2091
36.6k
    int64_t num_rows_load_filtered = 0;
2092
36.6k
    int64_t num_rows_load_unselected = 0;
2093
36.6k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
36.6k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
36.6k
        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
36.6k
    } else if (!req.runtime_states.empty()) {
2109
100k
        for (auto* rs : req.runtime_states) {
2110
100k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
100k
                rs->num_finished_range() > 0) {
2112
30.2k
                params.__isset.load_counters = true;
2113
30.2k
                num_rows_load_success += rs->num_rows_load_success();
2114
30.2k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
30.2k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
30.2k
                params.__isset.fragment_instance_reports = true;
2117
30.2k
                TFragmentInstanceReport t;
2118
30.2k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
30.2k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
30.2k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
30.2k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
30.2k
                params.fragment_instance_reports.push_back(t);
2123
30.2k
            }
2124
100k
        }
2125
36.6k
    }
2126
36.6k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
36.6k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
36.6k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
36.6k
    if (!req.load_error_url.empty()) {
2131
167
        params.__set_tracking_url(req.load_error_url);
2132
167
    }
2133
36.6k
    if (!req.first_error_msg.empty()) {
2134
167
        params.__set_first_error_msg(req.first_error_msg);
2135
167
    }
2136
100k
    for (auto* rs : req.runtime_states) {
2137
100k
        if (rs->wal_id() > 0) {
2138
106
            params.__set_txn_id(rs->wal_id());
2139
106
            params.__set_label(rs->import_label());
2140
106
        }
2141
100k
    }
2142
36.6k
    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
36.6k
    } else if (!req.runtime_states.empty()) {
2146
100k
        for (auto* rs : req.runtime_states) {
2147
100k
            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
100k
        }
2154
36.6k
    }
2155
36.6k
    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
36.6k
    } else if (!req.runtime_states.empty()) {
2159
100k
        for (auto* rs : req.runtime_states) {
2160
100k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
25.0k
                params.__isset.commitInfos = true;
2162
25.0k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
25.0k
            }
2164
100k
        }
2165
36.6k
    }
2166
36.6k
    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
36.6k
    } else if (!req.runtime_states.empty()) {
2170
100k
        for (auto* rs : req.runtime_states) {
2171
100k
            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
100k
        }
2177
36.6k
    }
2178
36.6k
    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
36.6k
    } else if (!req.runtime_states.empty()) {
2183
100k
        for (auto* rs : req.runtime_states) {
2184
100k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
0
                params.__isset.hive_partition_updates = true;
2186
0
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
0
                                                     rs_hpu.begin(), rs_hpu.end());
2188
0
            }
2189
100k
        }
2190
36.6k
    }
2191
36.6k
    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
36.6k
    } else if (!req.runtime_states.empty()) {
2196
100k
        for (auto* rs : req.runtime_states) {
2197
100k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
0
                params.__isset.iceberg_commit_datas = true;
2199
0
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
0
                                                   rs_icd.begin(), rs_icd.end());
2201
0
            }
2202
100k
        }
2203
36.6k
    }
2204
2205
36.6k
    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
36.6k
    } else if (!req.runtime_states.empty()) {
2209
100k
        for (auto* rs : req.runtime_states) {
2210
100k
            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
100k
        }
2216
36.6k
    }
2217
2218
36.6k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
36.6k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
36.6k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
36.6k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
36.6k
    }
2224
2225
36.6k
    TReportExecStatusResult res;
2226
36.6k
    Status rpc_status;
2227
2228
36.6k
    VLOG_DEBUG << "reportExecStatus params is "
2229
18
               << apache::thrift::ThriftDebugString(params).c_str();
2230
36.6k
    if (!exec_status.ok()) {
2231
1.53k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.53k
                     << " to coordinator: " << req.coord_addr
2233
1.53k
                     << ", query id: " << print_id(req.query_id);
2234
1.53k
    }
2235
36.6k
    try {
2236
36.6k
        try {
2237
36.6k
            (*coord)->reportExecStatus(res, params);
2238
36.6k
        } 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
36.6k
        rpc_status = Status::create<false>(res.status);
2254
36.6k
    } 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
36.6k
    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
36.6k
}
2265
2266
326k
Status PipelineFragmentContext::send_report(bool done) {
2267
326k
    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
326k
    if (!_is_report_success && done && exec_status.ok()) {
2273
289k
        return Status::OK();
2274
289k
    }
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
36.7k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
110
        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
110
            return Status::OK();
2286
110
        }
2287
0
        return Status::NeedSendAgain("");
2288
110
    }
2289
2290
36.6k
    std::vector<RuntimeState*> runtime_states;
2291
2292
68.3k
    for (auto& tasks : _tasks) {
2293
100k
        for (auto& task : tasks) {
2294
100k
            runtime_states.push_back(task.second.get());
2295
100k
        }
2296
68.3k
    }
2297
2298
36.6k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
36.6k
                                        ? get_load_error_url()
2300
36.6k
                                        : _query_ctx->get_load_error_url();
2301
36.6k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
36.6k
                                          ? get_first_error_msg()
2303
36.6k
                                          : _query_ctx->get_first_error_msg();
2304
2305
36.6k
    ReportStatusRequest req {.status = exec_status,
2306
36.6k
                             .runtime_states = runtime_states,
2307
36.6k
                             .done = done || !exec_status.ok(),
2308
36.6k
                             .coord_addr = _query_ctx->coord_addr,
2309
36.6k
                             .query_id = _query_id,
2310
36.6k
                             .fragment_id = _fragment_id,
2311
36.6k
                             .fragment_instance_id = TUniqueId(),
2312
36.6k
                             .backend_num = -1,
2313
36.6k
                             .runtime_state = _runtime_state.get(),
2314
36.6k
                             .load_error_url = load_eror_url,
2315
36.6k
                             .first_error_msg = first_error_msg,
2316
36.6k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
36.6k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
36.6k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
36.6k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
36.6k
        _coordinator_callback(req);
2321
36.6k
        if (!req.done) {
2322
3.60k
            ctx->refresh_next_report_time();
2323
3.60k
        }
2324
36.6k
    });
2325
36.7k
}
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
55
std::string PipelineFragmentContext::debug_string() {
2365
55
    std::lock_guard<std::mutex> l(_task_mutex);
2366
55
    fmt::memory_buffer debug_string_buffer;
2367
55
    fmt::format_to(debug_string_buffer,
2368
55
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
55
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
55
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
165
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
110
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
502
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
392
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
392
                           _tasks[j][i].first->debug_string());
2376
392
        }
2377
110
    }
2378
2379
55
    return fmt::to_string(debug_string_buffer);
2380
55
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.04k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.04k
    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
2.04k
    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
2.04k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.04k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.04k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
3.76k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
3.76k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
3.76k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
3.76k
        res.push_back(profile_ptr);
2407
3.76k
    }
2408
2409
2.04k
    return res;
2410
2.04k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.04k
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
2.04k
    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
4.50k
    for (const auto& tasks : _tasks) {
2426
9.03k
        for (const auto& task : tasks) {
2427
9.03k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
9.03k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
9.03k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
9.03k
                                                           _runtime_state->profile_level());
2435
9.03k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
9.03k
        }
2437
4.50k
    }
2438
2439
2.04k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.04k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.04k
                                                      _runtime_state->profile_level());
2442
2.04k
    return load_channel_profile;
2443
2.04k
}
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
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
6.82k
    for (const auto& _task : _tasks) {
2455
12.0k
        for (const auto& task : _task) {
2456
12.0k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
12.0k
            result.merge(set);
2458
12.0k
        }
2459
6.82k
    }
2460
3.28k
    if (_runtime_state) {
2461
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.28k
        result.merge(set);
2463
3.28k
    }
2464
3.28k
    return result;
2465
3.28k
}
2466
2467
327k
void PipelineFragmentContext::_release_resource() {
2468
327k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
327k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
327k
    auto st = _query_ctx->exec_status();
2472
894k
    for (auto& _task : _tasks) {
2473
894k
        if (!_task.empty()) {
2474
894k
            _call_back(_task.front().first->runtime_state(), &st);
2475
894k
        }
2476
894k
    }
2477
327k
    _tasks.clear();
2478
327k
    _dag.clear();
2479
327k
    _pip_id_to_pipeline.clear();
2480
327k
    _pipelines.clear();
2481
327k
    _sink.reset();
2482
327k
    _root_op.reset();
2483
327k
    _runtime_filter_mgr_map.clear();
2484
327k
    _op_id_to_shared_state.clear();
2485
327k
}
2486
2487
} // namespace doris