Coverage Report

Created: 2026-05-17 19:06

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
11
// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#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"
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#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
434k
        : _query_id(std::move(query_id)),
144
434k
          _fragment_id(request.fragment_id),
145
434k
          _exec_env(exec_env),
146
434k
          _query_ctx(std::move(query_ctx)),
147
434k
          _call_back(call_back),
148
434k
          _is_report_on_cancel(true),
149
434k
          _params(request),
150
434k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
434k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
434k
                                                               : false) {
153
434k
    _fragment_watcher.start();
154
434k
}
155
156
434k
PipelineFragmentContext::~PipelineFragmentContext() {
157
434k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
434k
            .tag("query_id", print_id(_query_id))
159
434k
            .tag("fragment_id", _fragment_id);
160
434k
    _release_resource();
161
434k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
434k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
434k
        _runtime_state.reset();
165
434k
        _query_ctx.reset();
166
434k
    }
167
434k
}
168
169
30
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
30
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
30
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
30
}
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.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
9.89k
bool PipelineFragmentContext::notify_close() {
181
9.89k
    bool all_closed = false;
182
9.89k
    bool need_remove = false;
183
9.89k
    {
184
9.89k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.89k
        if (_closed_tasks >= _total_tasks) {
186
3.44k
            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
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
192
3.38k
                need_remove = true;
193
3.38k
            }
194
3.44k
            all_closed = true;
195
3.44k
        }
196
        // make fragment release by self after cancel
197
9.89k
        _need_notify_close = false;
198
9.89k
    }
199
9.89k
    if (need_remove) {
200
3.38k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.38k
    }
202
9.89k
    return all_closed;
203
9.89k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
6.41k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.41k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.41k
            .tag("query_id", print_id(_query_id))
212
6.41k
            .tag("fragment_id", _fragment_id)
213
6.41k
            .tag("reason", reason.to_string());
214
6.41k
    if (notify_close()) {
215
78
        return;
216
78
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.33k
    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
6.33k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
6.33k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
6.33k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
25
        _query_ctx->set_load_error_url(error_url);
236
25
    }
237
238
6.33k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
25
        _query_ctx->set_first_error_msg(first_error_msg);
240
25
    }
241
242
6.33k
    _query_ctx->cancel(reason, _fragment_id);
243
6.33k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
405
        _is_report_on_cancel = false;
245
5.92k
    } else {
246
31.8k
        for (auto& id : _fragment_instance_ids) {
247
31.8k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
31.8k
        }
249
5.92k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
6.33k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.33k
    if (stream_load_ctx != nullptr) {
254
33
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
33
        stream_load_ctx->error_url = get_load_error_url();
259
33
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
33
    }
261
262
33.7k
    for (auto& tasks : _tasks) {
263
79.6k
        for (auto& task : tasks) {
264
79.6k
            task.first->unblock_all_dependencies();
265
79.6k
        }
266
33.7k
    }
267
6.33k
}
268
269
679k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
679k
    PipelineId id = _next_pipeline_id++;
271
679k
    auto pipeline = std::make_shared<Pipeline>(
272
679k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
679k
            parent ? parent->num_tasks() : _num_instances);
274
679k
    if (idx >= 0) {
275
115k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
564k
    } else {
277
564k
        _pipelines.emplace_back(pipeline);
278
564k
    }
279
679k
    if (parent) {
280
240k
        parent->set_children(pipeline);
281
240k
    }
282
679k
    return pipeline;
283
679k
}
284
285
433k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
433k
    {
287
433k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
433k
        auto root_pipeline = add_pipeline();
290
433k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
433k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
433k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
433k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
433k
                                          _params.fragment.output_exprs, _params,
299
433k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
433k
                                          *_desc_tbl, root_pipeline->id()));
301
433k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
433k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
564k
        for (PipelinePtr& pipeline : _pipelines) {
305
564k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
564k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
564k
        }
308
433k
    }
309
    // 4. Build local exchanger
310
433k
    if (_runtime_state->enable_local_shuffle()) {
311
431k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
431k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
431k
                                             _params.bucket_seq_to_instance_idx,
314
431k
                                             _params.shuffle_idx_to_instance_idx));
315
431k
    }
316
317
    // 5. Initialize global states in pipelines.
318
680k
    for (PipelinePtr& pipeline : _pipelines) {
319
680k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
680k
        pipeline->children().clear();
321
680k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
680k
    }
323
324
432k
    {
325
432k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
432k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
432k
    }
329
330
432k
    return Status::OK();
331
432k
}
332
333
434k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
434k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
434k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
433k
        _timeout = _params.query_options.execution_timeout;
339
433k
    }
340
341
434k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
434k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
434k
    SCOPED_TIMER(_prepare_timer);
344
434k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
434k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
434k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
434k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
434k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
434k
    {
350
434k
        SCOPED_TIMER(_init_context_timer);
351
434k
        cast_set(_num_instances, _params.local_params.size());
352
434k
        _total_instances =
353
434k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
434k
        auto* fragment_context = this;
356
357
434k
        if (_params.query_options.__isset.is_report_success) {
358
433k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
433k
        }
360
361
        // 1. Set up the global runtime state.
362
434k
        _runtime_state = RuntimeState::create_unique(
363
434k
                _params.query_id, _params.fragment_id, _params.query_options,
364
434k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
434k
        _runtime_state->set_task_execution_context(shared_from_this());
366
434k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
434k
        if (_params.__isset.backend_id) {
368
431k
            _runtime_state->set_backend_id(_params.backend_id);
369
431k
        }
370
434k
        if (_params.__isset.import_label) {
371
236
            _runtime_state->set_import_label(_params.import_label);
372
236
        }
373
434k
        if (_params.__isset.db_name) {
374
188
            _runtime_state->set_db_name(_params.db_name);
375
188
        }
376
434k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
434k
        if (_params.is_simplified_param) {
381
147k
            _desc_tbl = _query_ctx->desc_tbl;
382
286k
        } else {
383
286k
            DCHECK(_params.__isset.desc_tbl);
384
286k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
286k
                                                  &_desc_tbl));
386
286k
        }
387
434k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
434k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
434k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
434k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
434k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
434k
        const auto target_size = _params.local_params.size();
395
434k
        _fragment_instance_ids.resize(target_size);
396
1.56M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.13M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.13M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.13M
        }
400
434k
    }
401
402
434k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
432k
    _init_next_report_time();
405
406
432k
    _prepared = true;
407
432k
    return Status::OK();
408
434k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.12M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.12M
    const auto& local_params = _params.local_params[instance_idx];
414
1.12M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.12M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.12M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.12M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.12M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.89M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.89M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.89M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.89M
                shared_state_map;
423
2.41M
        for (auto& op : pipeline->operators()) {
424
2.41M
            auto source_id = op->operator_id();
425
2.41M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.41M
                iter != _op_id_to_shared_state.end()) {
427
757k
                shared_state_map.insert({source_id, iter->second});
428
757k
            }
429
2.41M
        }
430
1.89M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.89M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.89M
                iter != _op_id_to_shared_state.end()) {
433
312k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
312k
            }
435
1.89M
        }
436
1.89M
        return shared_state_map;
437
1.89M
    };
438
439
3.46M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.33M
        auto& pipeline = _pipelines[pip_idx];
441
2.33M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.88M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.88M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.88M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.88M
            {
446
                // Initialize runtime state for this task
447
1.88M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.88M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.88M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.88M
                if (_params.__isset.backend_id) {
453
1.88M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.88M
                }
455
1.88M
                if (_params.__isset.import_label) {
456
237
                    task_runtime_state->set_import_label(_params.import_label);
457
237
                }
458
1.88M
                if (_params.__isset.db_name) {
459
189
                    task_runtime_state->set_db_name(_params.db_name);
460
189
                }
461
1.88M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.88M
                if (_params.__isset.wal_id) {
465
112
                    task_runtime_state->set_wal_id(_params.wal_id);
466
112
                }
467
1.88M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.88M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.88M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.88M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.88M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.88M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.88M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.88M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.88M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.88M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.88M
            }
482
1.88M
            auto cur_task_id = _total_tasks++;
483
1.88M
            task_runtime_state->set_task_id(cur_task_id);
484
1.88M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.88M
            auto task = std::make_shared<PipelineTask>(
486
1.88M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.88M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.88M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.88M
                    instance_idx);
490
1.88M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.88M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.88M
            _tasks[instance_idx].emplace_back(
493
1.88M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.88M
                            std::move(task), std::move(task_runtime_state)});
495
1.88M
        }
496
2.33M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
2.33M
    for (auto& _pipeline : _pipelines) {
516
2.33M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.88M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.88M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.88M
            if (_dag.contains(_pipeline->id())) {
522
1.20M
                auto& deps = _dag[_pipeline->id()];
523
1.94M
                for (auto& dep : deps) {
524
1.94M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.05M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.05M
                        if (ss) {
527
438k
                            task->inject_shared_state(ss);
528
614k
                        } else {
529
614k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
614k
                                    task->get_source_shared_state());
531
614k
                        }
532
1.05M
                    }
533
1.94M
                }
534
1.20M
            }
535
1.88M
        }
536
2.33M
    }
537
3.46M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.33M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.88M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.88M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.88M
            std::vector<TScanRangeParams> scan_ranges;
542
1.88M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.88M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
314k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
314k
            }
546
1.88M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.88M
                                                             _params.fragment.output_sink));
548
1.88M
        }
549
2.33M
    }
550
1.13M
    {
551
1.13M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.13M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.13M
    }
554
1.13M
    return Status::OK();
555
1.12M
}
556
557
433k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
433k
    _total_tasks = 0;
559
433k
    _closed_tasks = 0;
560
433k
    const auto target_size = _params.local_params.size();
561
433k
    _tasks.resize(target_size);
562
433k
    _runtime_filter_mgr_map.resize(target_size);
563
1.11M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
678k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
678k
    }
566
433k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
433k
    if (target_size > 1 &&
569
433k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
140k
         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
26.1k
        std::vector<Status> prepare_status(target_size);
573
26.1k
        int submitted_tasks = 0;
574
26.1k
        Status submit_status;
575
26.1k
        CountDownLatch latch((int)target_size);
576
268k
        for (int i = 0; i < target_size; i++) {
577
242k
            submit_status = thread_pool->submit_func([&, i]() {
578
242k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
242k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
242k
                latch.count_down();
581
242k
            });
582
242k
            if (LIKELY(submit_status.ok())) {
583
242k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
242k
        }
588
26.1k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
26.1k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
268k
        for (int i = 0; i < submitted_tasks; i++) {
593
242k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
242k
        }
597
406k
    } else {
598
1.29M
        for (int i = 0; i < target_size; i++) {
599
887k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
887k
        }
601
406k
    }
602
433k
    _pipeline_parent_map.clear();
603
433k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
433k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
433k
    return Status::OK();
608
433k
}
609
610
432k
void PipelineFragmentContext::_init_next_report_time() {
611
432k
    auto interval_s = config::pipeline_status_report_interval;
612
432k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
41.4k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
41.4k
        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
41.4k
        _previous_report_time =
617
41.4k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
41.4k
        _disable_period_report = false;
619
41.4k
    }
620
432k
}
621
622
4.85k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.85k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.85k
    DCHECK(disable == true);
625
4.85k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.85k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.85k
}
628
629
6.93M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
6.93M
    if (!_is_report_success) {
631
6.48M
        return;
632
6.48M
    }
633
442k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
442k
    if (disable) {
635
8.21k
        return;
636
8.21k
    }
637
434k
    int32_t interval_s = config::pipeline_status_report_interval;
638
434k
    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
434k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
434k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
434k
    if (MonotonicNanos() > next_report_time) {
646
4.86k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.86k
                                                            std::memory_order_acq_rel)) {
648
10
            return;
649
10
        }
650
4.85k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
4.85k
        auto st = send_report(false);
667
4.85k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
4.85k
    }
673
434k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
432k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
432k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
432k
    int node_idx = 0;
682
683
432k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
432k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
432k
    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
432k
    return Status::OK();
691
432k
}
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
673k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
673k
    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
673k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
673k
    int num_children = tnodes[*node_idx].num_children;
706
673k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
673k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
673k
    OperatorPtr op = nullptr;
710
673k
    OperatorPtr cache_op = nullptr;
711
673k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
673k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
673k
                                     followed_by_shuffled_operator,
714
673k
                                     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
673k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
673k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
239k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
433k
    } else {
723
433k
        *root = op;
724
433k
    }
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
673k
    auto required_data_distribution =
737
673k
            cur_pipe->operators().empty()
738
673k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
673k
                    : op->required_data_distribution(_runtime_state.get());
740
673k
    current_followed_by_shuffled_operator =
741
673k
            ((followed_by_shuffled_operator ||
742
673k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
612k
                                             : op->is_shuffled_operator())) &&
744
673k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
673k
            (followed_by_shuffled_operator &&
746
559k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
673k
    current_require_bucket_distribution =
749
673k
            ((require_bucket_distribution ||
750
673k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
616k
                                             : op->is_colocated_operator())) &&
752
673k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
673k
            (require_bucket_distribution &&
754
565k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
673k
    if (num_children == 0) {
757
449k
        _use_serial_source = op->is_serial_operator();
758
449k
    }
759
    // rely on that tnodes is preorder of the plan
760
913k
    for (int i = 0; i < num_children; i++) {
761
240k
        ++*node_idx;
762
240k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
240k
                                            current_followed_by_shuffled_operator,
764
240k
                                            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
240k
        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
240k
    }
775
776
673k
    return Status::OK();
777
673k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
114k
        PipelinePtr pipe_with_sink) {
782
114k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
114k
    pipe_with_source->set_num_tasks(_num_instances);
784
114k
    pipe_with_source->set_data_distribution(data_distribution);
785
114k
}
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
114k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
114k
    auto& operators = cur_pipe->operators();
793
114k
    const auto downstream_pipeline_id = cur_pipe->id();
794
114k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
114k
    DataSinkOperatorPtr sink;
797
114k
    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
114k
    const bool followed_by_shuffled_operator =
804
114k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
114k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
114k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
114k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
114k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
114k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
114k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
114k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
114k
    if (bucket_seq_to_instance_idx.empty() &&
813
114k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
4
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
4
    }
816
114k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
114k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
114k
                                          num_buckets, use_global_hash_shuffle,
819
114k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
114k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
114k
            LocalExchangeSharedState::create_shared(_num_instances);
824
114k
    switch (data_distribution.distribution_type) {
825
17.7k
    case ExchangeType::HASH_SHUFFLE:
826
17.7k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
17.7k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
17.7k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
17.7k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
17.7k
                        ? cast_set<int>(
831
17.7k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
17.7k
                        : 0);
833
17.7k
        break;
834
482
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
482
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
482
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
482
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
482
                        ? cast_set<int>(
839
482
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
482
                        : 0);
841
482
        break;
842
93.2k
    case ExchangeType::PASSTHROUGH:
843
93.2k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
93.2k
                cur_pipe->num_tasks(), _num_instances,
845
93.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
93.2k
                        ? cast_set<int>(
847
93.2k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
93.2k
                        : 0);
849
93.2k
        break;
850
366
    case ExchangeType::BROADCAST:
851
366
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
366
                cur_pipe->num_tasks(), _num_instances,
853
366
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
366
                        ? cast_set<int>(
855
366
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
366
                        : 0);
857
366
        break;
858
2.38k
    case ExchangeType::PASS_TO_ONE:
859
2.38k
        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
1.57k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.57k
                    cur_pipe->num_tasks(), _num_instances,
863
1.57k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.57k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.57k
                                                    .local_exchange_free_blocks_limit)
866
1.57k
                            : 0);
867
1.57k
        } else {
868
806
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
806
                    cur_pipe->num_tasks(), _num_instances,
870
806
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
806
                            ? cast_set<int>(_runtime_state->query_options()
872
806
                                                    .local_exchange_free_blocks_limit)
873
806
                            : 0);
874
806
        }
875
2.38k
        break;
876
693
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
693
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
693
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
693
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
693
                        ? cast_set<int>(
881
693
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
693
                        : 0);
883
693
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
114k
    }
888
115k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
115k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
115k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
115k
    _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
115k
    std::copy(operators.begin(), operators.begin() + idx,
898
115k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
115k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
115k
    OperatorPtr source_op;
905
115k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
115k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
115k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
115k
    if (!operators.empty()) {
909
46.2k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
46.2k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
46.2k
    }
912
115k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
115k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
115k
    std::vector<PipelineId> edges_with_source;
917
130k
    for (auto child : cur_pipe->children()) {
918
130k
        bool found = false;
919
142k
        for (auto op : new_pip->operators()) {
920
142k
            if (child->sink()->node_id() == op->node_id()) {
921
10.9k
                new_pip->set_children(child);
922
10.9k
                found = true;
923
10.9k
            };
924
142k
        }
925
130k
        if (!found) {
926
119k
            new_children.push_back(child);
927
119k
            edges_with_source.push_back(child->id());
928
119k
        }
929
130k
    }
930
115k
    new_children.push_back(new_pip);
931
115k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
115k
    if (!new_pip->children().empty()) {
935
6.49k
        std::vector<PipelineId> edges_with_sink;
936
10.9k
        for (auto child : new_pip->children()) {
937
10.9k
            edges_with_sink.push_back(child->id());
938
10.9k
        }
939
6.49k
        _dag.insert({new_pip->id(), edges_with_sink});
940
6.49k
    }
941
115k
    cur_pipe->set_children(new_children);
942
115k
    _dag[downstream_pipeline_id] = edges_with_source;
943
115k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
115k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
115k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
115k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
115k
    return Status::OK();
950
115k
}
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
191k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
191k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
44.7k
        return Status::OK();
959
44.7k
    }
960
961
146k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
49.5k
        return Status::OK();
963
49.5k
    }
964
96.8k
    *do_local_exchange = true;
965
966
96.8k
    auto& operators = cur_pipe->operators();
967
96.8k
    auto total_op_num = operators.size();
968
96.8k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
96.8k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
96.8k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
96.8k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
96.8k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
108
            << "total_op_num: " << total_op_num
975
108
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
108
            << " 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
96.8k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
96.8k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
18.1k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
18.1k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
18.1k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
18.1k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
18.1k
                shuffle_idx_to_instance_idx));
990
18.1k
    }
991
96.8k
    return Status::OK();
992
96.8k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
431k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
993k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
562k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
562k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
125k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
125k
                if (child->sink()->node_id() ==
1003
125k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
110k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
110k
                }
1006
125k
            }
1007
120k
        }
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
562k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
562k
                                             bucket_seq_to_instance_idx,
1014
562k
                                             shuffle_idx_to_instance_idx));
1015
562k
    }
1016
431k
    return Status::OK();
1017
431k
}
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
561k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
561k
    int idx = 1;
1024
561k
    bool do_local_exchange = false;
1025
607k
    do {
1026
607k
        auto& ops = pip->operators();
1027
607k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
676k
        for (; idx < ops.size();) {
1030
115k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
104k
                RETURN_IF_ERROR(_add_local_exchange(
1032
104k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
104k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
104k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
104k
                        shuffle_idx_to_instance_idx));
1036
104k
            }
1037
115k
            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
46.2k
                idx = 2;
1043
46.2k
                break;
1044
46.2k
            }
1045
68.9k
            idx++;
1046
68.9k
        }
1047
607k
    } while (do_local_exchange);
1048
561k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
86.3k
        RETURN_IF_ERROR(_add_local_exchange(
1050
86.3k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
86.3k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
86.3k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
86.3k
    }
1054
561k
    return Status::OK();
1055
561k
}
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
433k
                                                  PipelineId cur_pipeline_id) {
1063
433k
    switch (thrift_sink.type) {
1064
145k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
145k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
145k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
145k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
145k
                params.destinations, _fragment_instance_ids);
1071
145k
        break;
1072
145k
    }
1073
250k
    case TDataSinkType::RESULT_SINK: {
1074
250k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
250k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
250k
        int child_node_id = pipeline->operators().back()->node_id();
1080
250k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
250k
                                                      row_desc, output_exprs,
1082
250k
                                                      thrift_sink.result_sink);
1083
250k
        break;
1084
250k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
31.4k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
31.4k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
31.4k
        int child_node_id = pipeline->operators().back()->node_id();
1098
31.4k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
31.4k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
31.4k
            !config::is_cloud_mode()) {
1101
2.15k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.15k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
29.2k
        } else {
1104
29.2k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
29.2k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
29.2k
        }
1107
31.4k
        break;
1108
0
    }
1109
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
165
        DCHECK(state->get_query_ctx() != nullptr);
1112
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
165
                                                                output_exprs);
1115
165
        break;
1116
0
    }
1117
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.46k
                                                         output_exprs);
1123
1.46k
        break;
1124
1.46k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
1.73k
        } else {
1133
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.73k
                                                                row_desc, output_exprs);
1135
1.73k
        }
1136
1.73k
        break;
1137
1.73k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
502
    case TDataSinkType::RESULT_FILE_SINK: {
1186
502
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
502
        } else {
1196
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
502
                                                              output_exprs);
1198
502
        }
1199
502
        break;
1200
502
    }
1201
1.99k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
1.99k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
1.99k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
1.99k
        auto sink_id = next_sink_operator_id();
1205
1.99k
        const int multi_cast_node_id = sink_id;
1206
1.99k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
1.99k
        std::vector<int> sources;
1209
7.75k
        for (int i = 0; i < sender_size; ++i) {
1210
5.76k
            auto source_id = next_operator_id();
1211
5.76k
            sources.push_back(source_id);
1212
5.76k
        }
1213
1214
1.99k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
1.99k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
7.75k
        for (int i = 0; i < sender_size; ++i) {
1217
5.76k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
5.76k
            RowDescriptor* exchange_row_desc = nullptr;
1220
5.76k
            {
1221
5.76k
                const auto& tmp_row_desc =
1222
5.76k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
5.76k
                                ? RowDescriptor(state->desc_tbl(),
1224
5.76k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
5.76k
                                                         .output_tuple_id})
1226
5.76k
                                : row_desc;
1227
5.76k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
5.76k
            }
1229
5.76k
            auto source_id = sources[i];
1230
5.76k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
5.76k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
5.76k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
5.76k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
5.76k
                    /*operator_id=*/source_id);
1236
5.76k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
5.76k
                    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
5.76k
            DataSinkOperatorPtr sink_op;
1241
5.76k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
5.76k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
5.76k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
5.76k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
5.76k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
5.76k
            {
1248
5.76k
                TDataSink* t = pool->add(new TDataSink());
1249
5.76k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
5.76k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
5.76k
            }
1252
1253
            // 3. set dependency dag
1254
5.76k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
5.76k
        }
1256
1.99k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
1.99k
        break;
1260
1.99k
    }
1261
1.99k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
13
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
13
        break;
1268
13
    }
1269
156
    case TDataSinkType::TVF_TABLE_SINK: {
1270
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
156
                                                        output_exprs);
1275
156
        break;
1276
156
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
433k
    }
1280
433k
    return Status::OK();
1281
433k
}
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
674k
                                                 OperatorPtr& cache_op) {
1292
674k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
674k
    Defer defer = Defer([&]() {
1294
674k
        if (op) {
1295
674k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
674k
        }
1297
673k
        for (auto& s : sink_ops) {
1298
124k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
124k
        }
1300
673k
    });
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
674k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
674k
    std::stringstream error_msg;
1305
674k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
674k
    bool fe_with_old_version = false;
1308
674k
    switch (tnode.node_type) {
1309
211k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
211k
        op = std::make_shared<OlapScanOperatorX>(
1311
211k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
211k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
211k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
211k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
211k
        break;
1316
211k
    }
1317
77
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
77
        DCHECK(_query_ctx != nullptr);
1319
77
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
77
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
77
                                                    _num_instances);
1322
77
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
77
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
77
        break;
1325
77
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
23.3k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
23.3k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
23.3k
                                                 _num_instances);
1342
23.3k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
23.3k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
23.3k
        break;
1345
23.3k
    }
1346
148k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
148k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
149k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
148k
        DCHECK_GT(num_senders, 0);
1351
148k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
148k
                                                       num_senders);
1353
148k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
148k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
148k
        break;
1356
148k
    }
1357
158k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
158k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
158k
            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
158k
        bool need_create_cache_op =
1364
158k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
158k
        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
158k
        const bool group_by_limit_opt =
1385
158k
                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
158k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
158k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
158k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
158k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
158k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
158k
        const bool can_use_distinct_streaming_agg =
1396
158k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
158k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
158k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
158k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
158k
        if (can_use_distinct_streaming_agg) {
1402
92.4k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
92.4k
            } else {
1413
92.4k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
92.4k
                                                                     tnode, descs);
1415
92.4k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
92.4k
            }
1417
92.4k
        } else if (is_streaming_agg) {
1418
3.13k
            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
3.13k
            } else {
1428
3.13k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
3.13k
                                                             descs);
1430
3.13k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
3.13k
            }
1432
63.0k
        } else {
1433
            // create new pipeline to add query cache operator
1434
63.0k
            PipelinePtr new_pipe;
1435
63.0k
            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
63.0k
            if (enable_spill) {
1441
114
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
114
                                                                     next_operator_id(), descs);
1443
62.8k
            } else {
1444
62.8k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
62.8k
            }
1446
63.0k
            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
63.0k
            } else {
1451
63.0k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
63.0k
            }
1453
1454
63.0k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
63.0k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
60.8k
                _dag.insert({downstream_pipeline_id, {}});
1457
60.8k
            }
1458
63.0k
            cur_pipe = add_pipeline(cur_pipe);
1459
63.0k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
63.0k
            if (enable_spill) {
1462
114
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
114
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
62.8k
            } else {
1465
62.8k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
62.8k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
62.8k
            }
1468
63.0k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
63.0k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
63.0k
        }
1471
158k
        break;
1472
158k
    }
1473
158k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
68
        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
68
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
68
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
68
        const auto downstream_pipeline_id = cur_pipe->id();
1486
68
        if (!_dag.contains(downstream_pipeline_id)) {
1487
68
            _dag.insert({downstream_pipeline_id, {}});
1488
68
        }
1489
68
        cur_pipe = add_pipeline(cur_pipe);
1490
68
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
68
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
68
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
68
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
68
        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
68
        {
1503
68
            auto shared_state = BucketedAggSharedState::create_shared();
1504
68
            shared_state->id = op->operator_id();
1505
68
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
447
            for (int i = 0; i < _num_instances; i++) {
1508
379
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
379
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
379
                sink_dep->set_shared_state(shared_state.get());
1511
379
                shared_state->sink_deps.push_back(sink_dep);
1512
379
            }
1513
68
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
68
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
68
            _op_id_to_shared_state.insert(
1516
68
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
68
        }
1518
68
        break;
1519
68
    }
1520
9.66k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.66k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.66k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.66k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.66k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
9.66k
        } else {
1566
9.66k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.66k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.66k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.66k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.95k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.95k
            }
1573
9.66k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.66k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.66k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.66k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.66k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.66k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.66k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.66k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.66k
        }
1584
9.66k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
4.95k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
4.95k
                    HashJoinSharedState::create_shared(_num_instances);
1587
25.2k
            for (int i = 0; i < _num_instances; i++) {
1588
20.3k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
20.3k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
20.3k
                sink_dep->set_shared_state(shared_state.get());
1591
20.3k
                shared_state->sink_deps.push_back(sink_dep);
1592
20.3k
            }
1593
4.95k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
4.95k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
4.95k
            _op_id_to_shared_state.insert(
1596
4.95k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
4.95k
        }
1598
9.66k
        break;
1599
9.66k
    }
1600
4.88k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
4.88k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
4.88k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
4.88k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
4.88k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
4.65k
            _dag.insert({downstream_pipeline_id, {}});
1607
4.65k
        }
1608
4.88k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
4.88k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
4.88k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
4.88k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
4.88k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
4.88k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
4.88k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
4.88k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
4.88k
        break;
1618
4.88k
    }
1619
53.6k
    case TPlanNodeType::UNION_NODE: {
1620
53.6k
        int child_count = tnode.num_children;
1621
53.6k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
53.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
53.6k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
53.6k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
53.3k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.3k
        }
1628
55.0k
        for (int i = 0; i < child_count; i++) {
1629
1.41k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.41k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.41k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.41k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.41k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.41k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.41k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.41k
        }
1638
53.6k
        break;
1639
53.6k
    }
1640
53.6k
    case TPlanNodeType::SORT_NODE: {
1641
43.7k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
43.7k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
43.7k
        const bool use_local_merge =
1644
43.7k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
43.7k
        if (should_spill) {
1646
7
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
43.7k
        } else if (use_local_merge) {
1648
41.4k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
41.4k
                                                                 descs);
1650
41.4k
        } else {
1651
2.34k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.34k
        }
1653
43.7k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
43.7k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
43.7k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
43.7k
            _dag.insert({downstream_pipeline_id, {}});
1658
43.7k
        }
1659
43.7k
        cur_pipe = add_pipeline(cur_pipe);
1660
43.7k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
43.7k
        if (should_spill) {
1663
7
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
7
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
43.7k
        } else {
1666
43.7k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
43.7k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
43.7k
        }
1669
43.7k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
43.7k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
43.7k
        break;
1672
43.7k
    }
1673
43.7k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.63k
        }
1698
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.64k
        break;
1706
1.64k
    }
1707
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.60k
        break;
1711
1.60k
    }
1712
1.60k
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
296
    case TPlanNodeType::REPEAT_NODE: {
1723
296
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
296
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
296
        break;
1726
296
    }
1727
914
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
914
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
914
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
914
        break;
1731
914
    }
1732
914
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
218
        break;
1736
218
    }
1737
1.55k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.55k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.55k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.55k
        break;
1741
1.55k
    }
1742
1.55k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
459
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
459
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
459
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
459
        break;
1747
459
    }
1748
2.05k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.05k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.05k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.05k
        break;
1752
2.05k
    }
1753
6.41k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.41k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.41k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.41k
        break;
1757
6.41k
    }
1758
6.41k
    case TPlanNodeType::SELECT_NODE: {
1759
1.97k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
1.97k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
1.97k
        break;
1762
1.97k
    }
1763
1.97k
    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
674k
    }
1803
673k
    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
673k
    return Status::OK();
1809
674k
}
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
431k
Status PipelineFragmentContext::submit() {
1846
431k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
431k
    _submitted = true;
1850
1851
431k
    int submit_tasks = 0;
1852
431k
    Status st;
1853
431k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.13M
    for (auto& task : _tasks) {
1855
1.89M
        for (auto& t : task) {
1856
1.89M
            st = scheduler->submit(t.first);
1857
1.89M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.89M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.89M
            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
1.89M
            submit_tasks++;
1866
1.89M
        }
1867
1.13M
    }
1868
431k
    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
431k
    } else {
1883
431k
        return st;
1884
431k
    }
1885
431k
}
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
433k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
433k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
433k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
433k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
433k
    if (!_need_notify_close) {
1919
429k
        auto st = send_report(true);
1920
429k
        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
429k
    }
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
433k
    if (_runtime_state->enable_profile() &&
1931
433k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.23k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.23k
         _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
433k
    if (_query_ctx->enable_profile()) {
1953
2.23k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.23k
                                         collect_realtime_load_channel_profile());
1955
2.23k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
433k
    return !_need_notify_close;
1960
433k
}
1961
1962
1.88M
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
1.88M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.88M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
679k
        if (_dag.contains(pipeline_id)) {
1967
361k
            for (auto dep : _dag[pipeline_id]) {
1968
361k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
361k
            }
1970
289k
        }
1971
679k
    }
1972
1.88M
    bool need_remove = false;
1973
1.88M
    {
1974
1.88M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.88M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.88M
        _query_ctx->inc_finished_task_num();
1978
1.88M
        if (_closed_tasks >= _total_tasks) {
1979
433k
            need_remove = _close_fragment_instance();
1980
433k
        }
1981
1.88M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.88M
    if (need_remove) {
1984
429k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
429k
    }
1986
1.88M
}
1987
1988
54.1k
std::string PipelineFragmentContext::get_load_error_url() {
1989
54.1k
    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
139k
    for (auto& tasks : _tasks) {
1993
224k
        for (auto& task : tasks) {
1994
224k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
179
                return to_load_error_http_path(str);
1996
179
            }
1997
224k
        }
1998
139k
    }
1999
53.9k
    return "";
2000
54.1k
}
2001
2002
54.1k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
54.1k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
138k
    for (auto& tasks : _tasks) {
2007
223k
        for (auto& task : tasks) {
2008
223k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
179
                return str;
2010
179
            }
2011
223k
        }
2012
138k
    }
2013
53.9k
    return "";
2014
54.1k
}
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
47.7k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
47.7k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
47.7k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
47.7k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
47.7k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
47.7k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
47.7k
    });
2031
2032
47.7k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
47.7k
    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
47.7k
    int callback_retries = 10;
2038
47.7k
    const int sleep_ms = 1000;
2039
47.7k
    Status exec_status = req.status;
2040
47.7k
    Status coord_status;
2041
47.7k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
47.7k
    do {
2043
47.7k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
47.7k
                                                            req.coord_addr, &coord_status);
2045
47.7k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
47.7k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
47.7k
    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
47.7k
    TReportExecStatusParams params;
2059
47.7k
    params.protocol_version = FrontendServiceVersion::V1;
2060
47.7k
    params.__set_query_id(req.query_id);
2061
47.7k
    params.__set_backend_num(req.backend_num);
2062
47.7k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
47.7k
    params.__set_fragment_id(req.fragment_id);
2064
47.7k
    params.__set_status(exec_status.to_thrift());
2065
47.7k
    params.__set_done(req.done);
2066
47.7k
    params.__set_query_type(req.runtime_state->query_type());
2067
47.7k
    params.__isset.profile = false;
2068
2069
47.7k
    DCHECK(req.runtime_state != nullptr);
2070
2071
47.7k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
43.4k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
43.4k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
43.4k
    } else {
2075
4.31k
        DCHECK(!req.runtime_states.empty());
2076
4.31k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
4.31k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.31k
    }
2086
2087
47.7k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
47.7k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
47.7k
    static std::string s_unselected_rows = "unselected.rows";
2090
47.7k
    int64_t num_rows_load_success = 0;
2091
47.7k
    int64_t num_rows_load_filtered = 0;
2092
47.7k
    int64_t num_rows_load_unselected = 0;
2093
47.7k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
47.7k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
47.7k
        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
47.7k
    } else if (!req.runtime_states.empty()) {
2109
144k
        for (auto* rs : req.runtime_states) {
2110
144k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
144k
                rs->num_finished_range() > 0) {
2112
36.0k
                params.__isset.load_counters = true;
2113
36.0k
                num_rows_load_success += rs->num_rows_load_success();
2114
36.0k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
36.0k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
36.0k
                params.__isset.fragment_instance_reports = true;
2117
36.0k
                TFragmentInstanceReport t;
2118
36.0k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
36.0k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
36.0k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
36.0k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
36.0k
                params.fragment_instance_reports.push_back(t);
2123
36.0k
            }
2124
144k
        }
2125
47.7k
    }
2126
47.7k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
47.7k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
47.7k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
47.7k
    if (!req.load_error_url.empty()) {
2131
161
        params.__set_tracking_url(req.load_error_url);
2132
161
    }
2133
47.7k
    if (!req.first_error_msg.empty()) {
2134
161
        params.__set_first_error_msg(req.first_error_msg);
2135
161
    }
2136
144k
    for (auto* rs : req.runtime_states) {
2137
144k
        if (rs->wal_id() > 0) {
2138
107
            params.__set_txn_id(rs->wal_id());
2139
107
            params.__set_label(rs->import_label());
2140
107
        }
2141
144k
    }
2142
47.7k
    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
47.7k
    } else if (!req.runtime_states.empty()) {
2146
144k
        for (auto* rs : req.runtime_states) {
2147
144k
            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
144k
        }
2154
47.7k
    }
2155
47.7k
    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
47.7k
    } else if (!req.runtime_states.empty()) {
2159
144k
        for (auto* rs : req.runtime_states) {
2160
144k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
27.0k
                params.__isset.commitInfos = true;
2162
27.0k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
27.0k
            }
2164
144k
        }
2165
47.7k
    }
2166
47.7k
    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
47.7k
    } else if (!req.runtime_states.empty()) {
2170
144k
        for (auto* rs : req.runtime_states) {
2171
144k
            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
144k
        }
2177
47.7k
    }
2178
47.7k
    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
47.7k
    } else if (!req.runtime_states.empty()) {
2183
144k
        for (auto* rs : req.runtime_states) {
2184
144k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.14k
                params.__isset.hive_partition_updates = true;
2186
2.14k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.14k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.14k
            }
2189
144k
        }
2190
47.7k
    }
2191
47.7k
    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
47.7k
    } else if (!req.runtime_states.empty()) {
2196
144k
        for (auto* rs : req.runtime_states) {
2197
144k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.07k
                params.__isset.iceberg_commit_datas = true;
2199
2.07k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.07k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.07k
            }
2202
144k
        }
2203
47.7k
    }
2204
2205
47.7k
    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
47.7k
    } else if (!req.runtime_states.empty()) {
2209
144k
        for (auto* rs : req.runtime_states) {
2210
144k
            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
144k
        }
2216
47.7k
    }
2217
2218
47.7k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
47.7k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
47.7k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
47.7k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
47.7k
    }
2224
2225
47.7k
    TReportExecStatusResult res;
2226
47.7k
    Status rpc_status;
2227
2228
47.7k
    VLOG_DEBUG << "reportExecStatus params is "
2229
6
               << apache::thrift::ThriftDebugString(params).c_str();
2230
47.7k
    if (!exec_status.ok()) {
2231
1.67k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.67k
                     << " to coordinator: " << req.coord_addr
2233
1.67k
                     << ", query id: " << print_id(req.query_id);
2234
1.67k
    }
2235
47.7k
    try {
2236
47.7k
        try {
2237
47.7k
            (*coord)->reportExecStatus(res, params);
2238
47.7k
        } 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
47.7k
        rpc_status = Status::create<false>(res.status);
2254
47.7k
    } 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
47.7k
    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
47.7k
}
2265
2266
434k
Status PipelineFragmentContext::send_report(bool done) {
2267
434k
    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
434k
    if (!_is_report_success && done && exec_status.ok()) {
2273
386k
        return Status::OK();
2274
386k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
48.0k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
309
        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
309
            return Status::OK();
2286
309
        }
2287
0
        return Status::NeedSendAgain("");
2288
309
    }
2289
2290
47.7k
    std::vector<RuntimeState*> runtime_states;
2291
2292
105k
    for (auto& tasks : _tasks) {
2293
144k
        for (auto& task : tasks) {
2294
144k
            runtime_states.push_back(task.second.get());
2295
144k
        }
2296
105k
    }
2297
2298
47.7k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
47.7k
                                        ? get_load_error_url()
2300
47.7k
                                        : _query_ctx->get_load_error_url();
2301
47.7k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
47.7k
                                          ? get_first_error_msg()
2303
47.7k
                                          : _query_ctx->get_first_error_msg();
2304
2305
47.7k
    ReportStatusRequest req {.status = exec_status,
2306
47.7k
                             .runtime_states = runtime_states,
2307
47.7k
                             .done = done || !exec_status.ok(),
2308
47.7k
                             .coord_addr = _query_ctx->coord_addr,
2309
47.7k
                             .query_id = _query_id,
2310
47.7k
                             .fragment_id = _fragment_id,
2311
47.7k
                             .fragment_instance_id = TUniqueId(),
2312
47.7k
                             .backend_num = -1,
2313
47.7k
                             .runtime_state = _runtime_state.get(),
2314
47.7k
                             .load_error_url = load_eror_url,
2315
47.7k
                             .first_error_msg = first_error_msg,
2316
47.7k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
47.7k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
47.7k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
47.7k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
47.7k
        _coordinator_callback(req);
2321
47.7k
        if (!req.done) {
2322
4.85k
            ctx->refresh_next_report_time();
2323
4.85k
        }
2324
47.7k
    });
2325
48.0k
}
2326
2327
4
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
4
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
4
    for (const auto& task_instances : _tasks) {
2332
6
        for (const auto& task : task_instances) {
2333
6
            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
6
            size_t revocable_size = task.first->get_revocable_size();
2342
6
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
2
                res += revocable_size;
2344
2
            }
2345
6
        }
2346
4
    }
2347
4
    return res;
2348
4
}
2349
2350
8
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
8
    std::vector<PipelineTask*> revocable_tasks;
2352
8
    for (const auto& task_instances : _tasks) {
2353
12
        for (const auto& task : task_instances) {
2354
12
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
12
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
4
                revocable_tasks.emplace_back(task.first.get());
2358
4
            }
2359
12
        }
2360
8
    }
2361
8
    return revocable_tasks;
2362
8
}
2363
2364
31
std::string PipelineFragmentContext::debug_string() {
2365
31
    std::lock_guard<std::mutex> l(_task_mutex);
2366
31
    fmt::memory_buffer debug_string_buffer;
2367
31
    fmt::format_to(debug_string_buffer,
2368
31
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
31
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
31
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
301
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
270
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
1.44k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
1.17k
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
1.17k
                           _tasks[j][i].first->debug_string());
2376
1.17k
        }
2377
270
    }
2378
2379
31
    return fmt::to_string(debug_string_buffer);
2380
31
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.23k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.23k
    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
2.23k
    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
2.23k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.23k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.23k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
3.91k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
3.91k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
3.91k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
3.91k
        res.push_back(profile_ptr);
2407
3.91k
    }
2408
2409
2.23k
    return res;
2410
2.23k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.23k
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
2.23k
    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
7.33k
    for (const auto& tasks : _tasks) {
2426
14.3k
        for (const auto& task : tasks) {
2427
14.3k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
14.3k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
14.3k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
14.3k
                                                           _runtime_state->profile_level());
2435
14.3k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
14.3k
        }
2437
7.33k
    }
2438
2439
2.23k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.23k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.23k
                                                      _runtime_state->profile_level());
2442
2.23k
    return load_channel_profile;
2443
2.23k
}
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
12.1k
    for (const auto& _task : _tasks) {
2455
26.6k
        for (const auto& task : _task) {
2456
26.6k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
26.6k
            result.merge(set);
2458
26.6k
        }
2459
12.1k
    }
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
434k
void PipelineFragmentContext::_release_resource() {
2468
434k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
434k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
434k
    auto st = _query_ctx->exec_status();
2472
1.13M
    for (auto& _task : _tasks) {
2473
1.13M
        if (!_task.empty()) {
2474
1.13M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.13M
        }
2476
1.13M
    }
2477
434k
    _tasks.clear();
2478
434k
    _dag.clear();
2479
434k
    _pip_id_to_pipeline.clear();
2480
434k
    _pipelines.clear();
2481
434k
    _sink.reset();
2482
434k
    _root_op.reset();
2483
434k
    _runtime_filter_mgr_map.clear();
2484
434k
    _op_id_to_shared_state.clear();
2485
434k
}
2486
2487
} // namespace doris