Coverage Report

Created: 2026-06-08 08:15

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
2
// 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
13
// "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.
17
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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"
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#include "util/client_cache.h"
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#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
447k
        : _query_id(std::move(query_id)),
144
447k
          _fragment_id(request.fragment_id),
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447k
          _exec_env(exec_env),
146
447k
          _query_ctx(std::move(query_ctx)),
147
447k
          _call_back(call_back),
148
447k
          _is_report_on_cancel(true),
149
447k
          _params(request),
150
447k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
447k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
447k
                                                               : false) {
153
447k
    _fragment_watcher.start();
154
447k
}
155
156
447k
PipelineFragmentContext::~PipelineFragmentContext() {
157
447k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
447k
            .tag("query_id", print_id(_query_id))
159
447k
            .tag("fragment_id", _fragment_id);
160
447k
    _release_resource();
161
447k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
447k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
447k
        _runtime_state.reset();
165
447k
        _query_ctx.reset();
166
447k
    }
167
447k
}
168
169
86
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
86
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
86
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
86
}
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
9.56k
bool PipelineFragmentContext::notify_close() {
181
9.56k
    bool all_closed = false;
182
9.56k
    bool need_remove = false;
183
9.56k
    {
184
9.56k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.56k
        if (_closed_tasks >= _total_tasks) {
186
3.05k
            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
2.99k
                need_remove = true;
193
2.99k
            }
194
3.05k
            all_closed = true;
195
3.05k
        }
196
        // make fragment release by self after cancel
197
9.56k
        _need_notify_close = false;
198
9.56k
    }
199
9.56k
    if (need_remove) {
200
2.99k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
2.99k
    }
202
9.56k
    return all_closed;
203
9.56k
}
204
205
// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
6.28k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.28k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.28k
            .tag("query_id", print_id(_query_id))
212
6.28k
            .tag("fragment_id", _fragment_id)
213
6.28k
            .tag("reason", reason.to_string());
214
6.28k
    if (notify_close()) {
215
77
        return;
216
77
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.21k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
6.21k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
6.21k
    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
6.21k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
6.21k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
6.21k
    _query_ctx->cancel(reason, _fragment_id);
243
6.21k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
417
        _is_report_on_cancel = false;
245
5.79k
    } else {
246
30.3k
        for (auto& id : _fragment_instance_ids) {
247
30.3k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
30.3k
        }
249
5.79k
    }
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
6.21k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.21k
    if (stream_load_ctx != nullptr) {
254
31
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
31
        stream_load_ctx->error_url = get_load_error_url();
259
31
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
31
    }
261
262
31.9k
    for (auto& tasks : _tasks) {
263
75.2k
        for (auto& task : tasks) {
264
75.2k
            task.first->unblock_all_dependencies();
265
75.2k
        }
266
31.9k
    }
267
6.21k
}
268
269
694k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
694k
    PipelineId id = _next_pipeline_id++;
271
694k
    auto pipeline = std::make_shared<Pipeline>(
272
694k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
694k
            parent ? parent->num_tasks() : _num_instances);
274
694k
    if (idx >= 0) {
275
122k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
572k
    } else {
277
572k
        _pipelines.emplace_back(pipeline);
278
572k
    }
279
694k
    if (parent) {
280
240k
        parent->set_children(pipeline);
281
240k
    }
282
694k
    return pipeline;
283
694k
}
284
285
446k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
446k
    {
287
446k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
446k
        auto root_pipeline = add_pipeline();
290
446k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
446k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
446k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
446k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
446k
                                          _params.fragment.output_exprs, _params,
299
446k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
446k
                                          *_desc_tbl, root_pipeline->id()));
301
446k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
446k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
571k
        for (PipelinePtr& pipeline : _pipelines) {
305
571k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
571k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
571k
        }
308
446k
    }
309
    // 4. Build local exchanger
310
446k
    if (_runtime_state->enable_local_shuffle()) {
311
442k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
442k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
442k
                                             _params.bucket_seq_to_instance_idx,
314
442k
                                             _params.shuffle_idx_to_instance_idx));
315
442k
    }
316
317
    // 5. Initialize global states in pipelines.
318
695k
    for (PipelinePtr& pipeline : _pipelines) {
319
695k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
695k
        pipeline->children().clear();
321
695k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
695k
    }
323
324
445k
    {
325
445k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
445k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
445k
    }
329
330
445k
    return Status::OK();
331
445k
}
332
333
447k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
447k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
447k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
447k
        _timeout = _params.query_options.execution_timeout;
339
447k
    }
340
341
447k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
447k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
447k
    SCOPED_TIMER(_prepare_timer);
344
447k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
447k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
447k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
447k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
447k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
447k
    {
350
447k
        SCOPED_TIMER(_init_context_timer);
351
447k
        cast_set(_num_instances, _params.local_params.size());
352
447k
        _total_instances =
353
447k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
447k
        auto* fragment_context = this;
356
357
447k
        if (_params.query_options.__isset.is_report_success) {
358
444k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
444k
        }
360
361
        // 1. Set up the global runtime state.
362
447k
        _runtime_state = RuntimeState::create_unique(
363
447k
                _params.query_id, _params.fragment_id, _params.query_options,
364
447k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
447k
        _runtime_state->set_task_execution_context(shared_from_this());
366
447k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
447k
        if (_params.__isset.backend_id) {
368
441k
            _runtime_state->set_backend_id(_params.backend_id);
369
441k
        }
370
447k
        if (_params.__isset.import_label) {
371
237
            _runtime_state->set_import_label(_params.import_label);
372
237
        }
373
447k
        if (_params.__isset.db_name) {
374
189
            _runtime_state->set_db_name(_params.db_name);
375
189
        }
376
447k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
447k
        if (_params.is_simplified_param) {
381
149k
            _desc_tbl = _query_ctx->desc_tbl;
382
298k
        } else {
383
298k
            DCHECK(_params.__isset.desc_tbl);
384
298k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
298k
                                                  &_desc_tbl));
386
298k
        }
387
447k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
447k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
447k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
447k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
447k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
447k
        const auto target_size = _params.local_params.size();
395
447k
        _fragment_instance_ids.resize(target_size);
396
1.67M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.22M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.22M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.22M
        }
400
447k
    }
401
402
447k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
446k
    _init_next_report_time();
405
406
446k
    _prepared = true;
407
446k
    return Status::OK();
408
447k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.22M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.22M
    const auto& local_params = _params.local_params[instance_idx];
414
1.22M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.22M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.22M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.22M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.22M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
2.02M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
2.02M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
2.02M
                                std::vector<std::shared_ptr<Dependency>>>>
422
2.02M
                shared_state_map;
423
2.59M
        for (auto& op : pipeline->operators()) {
424
2.59M
            auto source_id = op->operator_id();
425
2.59M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.59M
                iter != _op_id_to_shared_state.end()) {
427
810k
                shared_state_map.insert({source_id, iter->second});
428
810k
            }
429
2.59M
        }
430
2.03M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
2.03M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
2.03M
                iter != _op_id_to_shared_state.end()) {
433
321k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
321k
            }
435
2.03M
        }
436
2.02M
        return shared_state_map;
437
2.02M
    };
438
439
3.73M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.50M
        auto& pipeline = _pipelines[pip_idx];
441
2.50M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
2.02M
            auto task_runtime_state = RuntimeState::create_unique(
443
2.02M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
2.02M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
2.02M
            {
446
                // Initialize runtime state for this task
447
2.02M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
2.02M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
2.02M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
2.02M
                if (_params.__isset.backend_id) {
453
2.02M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
2.02M
                }
455
2.02M
                if (_params.__isset.import_label) {
456
238
                    task_runtime_state->set_import_label(_params.import_label);
457
238
                }
458
2.02M
                if (_params.__isset.db_name) {
459
190
                    task_runtime_state->set_db_name(_params.db_name);
460
190
                }
461
2.02M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
2.02M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
2.02M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
2.02M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
2.02M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
2.02M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
2.02M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
2.02M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
2.02M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
2.02M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
2.02M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
2.02M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
2.02M
            }
482
2.02M
            auto cur_task_id = _total_tasks++;
483
2.02M
            task_runtime_state->set_task_id(cur_task_id);
484
2.02M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
2.02M
            auto task = std::make_shared<PipelineTask>(
486
2.02M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
2.02M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
2.02M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
2.02M
                    instance_idx);
490
2.02M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
2.02M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
2.02M
            _tasks[instance_idx].emplace_back(
493
2.02M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
2.02M
                            std::move(task), std::move(task_runtime_state)});
495
2.02M
        }
496
2.50M
    }
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
2.50M
    for (auto& _pipeline : _pipelines) {
516
2.50M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
2.01M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
2.01M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
2.01M
            if (_dag.contains(_pipeline->id())) {
522
1.28M
                auto& deps = _dag[_pipeline->id()];
523
2.06M
                for (auto& dep : deps) {
524
2.06M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.09M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.09M
                        if (ss) {
527
465k
                            task->inject_shared_state(ss);
528
633k
                        } else {
529
633k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
633k
                                    task->get_source_shared_state());
531
633k
                        }
532
1.09M
                    }
533
2.06M
                }
534
1.28M
            }
535
2.01M
        }
536
2.50M
    }
537
3.74M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.50M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
2.01M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
2.01M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
2.01M
            std::vector<TScanRangeParams> scan_ranges;
542
2.01M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
2.01M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
338k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
338k
            }
546
2.01M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
2.01M
                                                             _params.fragment.output_sink));
548
2.01M
        }
549
2.50M
    }
550
1.23M
    {
551
1.23M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.23M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.23M
    }
554
1.23M
    return Status::OK();
555
1.22M
}
556
557
446k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
446k
    _total_tasks = 0;
559
446k
    _closed_tasks = 0;
560
446k
    const auto target_size = _params.local_params.size();
561
446k
    _tasks.resize(target_size);
562
446k
    _runtime_filter_mgr_map.resize(target_size);
563
1.14M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
694k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
694k
    }
566
446k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
446k
    if (target_size > 1 &&
569
446k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
144k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
571
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
572
21.5k
        std::vector<Status> prepare_status(target_size);
573
21.5k
        int submitted_tasks = 0;
574
21.5k
        Status submit_status;
575
21.5k
        CountDownLatch latch((int)target_size);
576
291k
        for (int i = 0; i < target_size; i++) {
577
269k
            submit_status = thread_pool->submit_func([&, i]() {
578
269k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
269k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
269k
                latch.count_down();
581
269k
            });
582
269k
            if (LIKELY(submit_status.ok())) {
583
269k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
269k
        }
588
21.5k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
21.5k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
291k
        for (int i = 0; i < submitted_tasks; i++) {
593
269k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
269k
        }
597
424k
    } else {
598
1.38M
        for (int i = 0; i < target_size; i++) {
599
961k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
961k
        }
601
424k
    }
602
446k
    _pipeline_parent_map.clear();
603
446k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
446k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
446k
    return Status::OK();
608
446k
}
609
610
444k
void PipelineFragmentContext::_init_next_report_time() {
611
444k
    auto interval_s = config::pipeline_status_report_interval;
612
444k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
42.9k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.9k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
42.9k
        _previous_report_time =
617
42.9k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.9k
        _disable_period_report = false;
619
42.9k
    }
620
444k
}
621
622
4.94k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.94k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.94k
    DCHECK(disable == true);
625
4.94k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.94k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.94k
}
628
629
7.42M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.42M
    if (!_is_report_success) {
631
6.94M
        return;
632
6.94M
    }
633
480k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
480k
    if (disable) {
635
9.67k
        return;
636
9.67k
    }
637
471k
    int32_t interval_s = config::pipeline_status_report_interval;
638
471k
    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
471k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
471k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
471k
    if (MonotonicNanos() > next_report_time) {
646
4.95k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.95k
                                                            std::memory_order_acq_rel)) {
648
13
            return;
649
13
        }
650
4.94k
        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
4.94k
        auto st = send_report(false);
667
4.94k
        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
4.94k
    }
673
471k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
443k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
443k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
443k
    int node_idx = 0;
682
683
443k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
443k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
443k
    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
443k
    return Status::OK();
691
443k
}
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
670k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
670k
    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
670k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
670k
    int num_children = tnodes[*node_idx].num_children;
706
670k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
670k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
670k
    OperatorPtr op = nullptr;
710
670k
    OperatorPtr cache_op = nullptr;
711
670k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
670k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
670k
                                     followed_by_shuffled_operator,
714
670k
                                     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
670k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
670k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
226k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
444k
    } else {
723
444k
        *root = op;
724
444k
    }
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
670k
    auto required_data_distribution =
737
670k
            cur_pipe->operators().empty()
738
670k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
670k
                    : op->required_data_distribution(_runtime_state.get());
740
670k
    current_followed_by_shuffled_operator =
741
670k
            ((followed_by_shuffled_operator ||
742
670k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
611k
                                             : op->is_shuffled_operator())) &&
744
670k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
670k
            (followed_by_shuffled_operator &&
746
557k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
670k
    current_require_bucket_distribution =
749
670k
            ((require_bucket_distribution ||
750
670k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
615k
                                             : op->is_colocated_operator())) &&
752
670k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
670k
            (require_bucket_distribution &&
754
564k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
670k
    if (num_children == 0) {
757
462k
        _use_serial_source = op->is_serial_operator();
758
462k
    }
759
    // rely on that tnodes is preorder of the plan
760
896k
    for (int i = 0; i < num_children; i++) {
761
226k
        ++*node_idx;
762
226k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
226k
                                            current_followed_by_shuffled_operator,
764
226k
                                            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
226k
        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
226k
    }
775
776
670k
    return Status::OK();
777
670k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
122k
        PipelinePtr pipe_with_sink) {
782
122k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
122k
    pipe_with_source->set_num_tasks(_num_instances);
784
122k
    pipe_with_source->set_data_distribution(data_distribution);
785
122k
}
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
122k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
122k
    auto& operators = cur_pipe->operators();
793
122k
    const auto downstream_pipeline_id = cur_pipe->id();
794
122k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
122k
    DataSinkOperatorPtr sink;
797
122k
    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
122k
    const bool followed_by_shuffled_operator =
804
122k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
122k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
122k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
122k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
122k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
122k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
122k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
122k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
122k
    if (bucket_seq_to_instance_idx.empty() &&
813
122k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
9
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
9
    }
816
122k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
122k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
122k
                                          num_buckets, use_global_hash_shuffle,
819
122k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
122k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
122k
            LocalExchangeSharedState::create_shared(_num_instances);
824
122k
    switch (data_distribution.distribution_type) {
825
21.8k
    case ExchangeType::HASH_SHUFFLE:
826
21.8k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
21.8k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
21.8k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
21.8k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
21.8k
                        ? cast_set<int>(
831
21.7k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
21.8k
                        : 0);
833
21.8k
        break;
834
489
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
489
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
489
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
489
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
489
                        ? cast_set<int>(
839
489
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
489
                        : 0);
841
489
        break;
842
95.5k
    case ExchangeType::PASSTHROUGH:
843
95.5k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
95.5k
                cur_pipe->num_tasks(), _num_instances,
845
95.5k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
95.5k
                        ? cast_set<int>(
847
95.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
95.5k
                        : 0);
849
95.5k
        break;
850
377
    case ExchangeType::BROADCAST:
851
377
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
377
                cur_pipe->num_tasks(), _num_instances,
853
377
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
377
                        ? cast_set<int>(
855
377
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
377
                        : 0);
857
377
        break;
858
2.73k
    case ExchangeType::PASS_TO_ONE:
859
2.73k
        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
1.75k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.75k
                    cur_pipe->num_tasks(), _num_instances,
863
1.75k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.75k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.75k
                                                    .local_exchange_free_blocks_limit)
866
1.75k
                            : 0);
867
1.75k
        } else {
868
973
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
973
                    cur_pipe->num_tasks(), _num_instances,
870
973
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
973
                            ? cast_set<int>(_runtime_state->query_options()
872
973
                                                    .local_exchange_free_blocks_limit)
873
973
                            : 0);
874
973
        }
875
2.73k
        break;
876
981
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
981
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
981
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
981
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
981
                        ? cast_set<int>(
881
981
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
981
                        : 0);
883
981
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
122k
    }
888
122k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
122k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
122k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
122k
    _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
122k
    std::copy(operators.begin(), operators.begin() + idx,
898
122k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
122k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
122k
    OperatorPtr source_op;
905
122k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
122k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
122k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
122k
    if (!operators.empty()) {
909
44.7k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
44.7k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
44.7k
    }
912
122k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
122k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
122k
    std::vector<PipelineId> edges_with_source;
917
140k
    for (auto child : cur_pipe->children()) {
918
140k
        bool found = false;
919
154k
        for (auto op : new_pip->operators()) {
920
154k
            if (child->sink()->node_id() == op->node_id()) {
921
12.6k
                new_pip->set_children(child);
922
12.6k
                found = true;
923
12.6k
            };
924
154k
        }
925
140k
        if (!found) {
926
127k
            new_children.push_back(child);
927
127k
            edges_with_source.push_back(child->id());
928
127k
        }
929
140k
    }
930
122k
    new_children.push_back(new_pip);
931
122k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
122k
    if (!new_pip->children().empty()) {
935
7.19k
        std::vector<PipelineId> edges_with_sink;
936
12.6k
        for (auto child : new_pip->children()) {
937
12.6k
            edges_with_sink.push_back(child->id());
938
12.6k
        }
939
7.19k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.19k
    }
941
122k
    cur_pipe->set_children(new_children);
942
122k
    _dag[downstream_pipeline_id] = edges_with_source;
943
122k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
122k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
122k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
122k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
122k
    return Status::OK();
950
122k
}
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
193k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
193k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
46.3k
        return Status::OK();
959
46.3k
    }
960
961
147k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
47.6k
        return Status::OK();
963
47.6k
    }
964
99.6k
    *do_local_exchange = true;
965
966
99.6k
    auto& operators = cur_pipe->operators();
967
99.6k
    auto total_op_num = operators.size();
968
99.6k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
99.6k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
99.6k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
99.6k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
18.4E
            << "total_op_num: " << total_op_num
975
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
99.7k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
99.6k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
22.1k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
22.1k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
22.1k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
22.1k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
22.1k
                shuffle_idx_to_instance_idx));
990
22.1k
    }
991
99.6k
    return Status::OK();
992
99.6k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
441k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.00M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
567k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
567k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
118k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
118k
                if (child->sink()->node_id() ==
1003
118k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
103k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
103k
                }
1006
118k
            }
1007
112k
        }
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
567k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
567k
                                             bucket_seq_to_instance_idx,
1014
567k
                                             shuffle_idx_to_instance_idx));
1015
567k
    }
1016
441k
    return Status::OK();
1017
441k
}
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
566k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
566k
    int idx = 1;
1024
566k
    bool do_local_exchange = false;
1025
611k
    do {
1026
611k
        auto& ops = pip->operators();
1027
611k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
675k
        for (; idx < ops.size();) {
1030
108k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
101k
                RETURN_IF_ERROR(_add_local_exchange(
1032
101k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
101k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
101k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
101k
                        shuffle_idx_to_instance_idx));
1036
101k
            }
1037
108k
            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
44.8k
                idx = 2;
1043
44.8k
                break;
1044
44.8k
            }
1045
63.4k
            idx++;
1046
63.4k
        }
1047
611k
    } while (do_local_exchange);
1048
566k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
91.8k
        RETURN_IF_ERROR(_add_local_exchange(
1050
91.8k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
91.8k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
91.8k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
91.8k
    }
1054
566k
    return Status::OK();
1055
566k
}
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
446k
                                                  PipelineId cur_pipeline_id) {
1063
446k
    switch (thrift_sink.type) {
1064
146k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
146k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
146k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
146k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
146k
                params.destinations, _fragment_instance_ids);
1071
146k
        break;
1072
146k
    }
1073
258k
    case TDataSinkType::RESULT_SINK: {
1074
258k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
258k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
258k
        int child_node_id = pipeline->operators().back()->node_id();
1080
258k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
258k
                                                      row_desc, output_exprs,
1082
258k
                                                      thrift_sink.result_sink);
1083
258k
        break;
1084
258k
    }
1085
106
    case TDataSinkType::DICTIONARY_SINK: {
1086
106
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
106
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
106
                                                    thrift_sink.dictionary_sink);
1092
106
        break;
1093
106
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
34.4k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
34.4k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
34.4k
        int child_node_id = pipeline->operators().back()->node_id();
1098
34.4k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
34.4k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
34.4k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.85k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.85k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
31.5k
        } else {
1104
31.5k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
31.5k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
31.5k
        }
1107
34.4k
        break;
1108
0
    }
1109
166
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
166
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
166
        DCHECK(state->get_query_ctx() != nullptr);
1112
166
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
166
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
166
                                                                output_exprs);
1115
166
        break;
1116
0
    }
1117
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
1.72k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.72k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.72k
        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
1.72k
        } else {
1133
1.72k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.72k
                                                                row_desc, output_exprs);
1135
1.72k
        }
1136
1.72k
        break;
1137
1.72k
    }
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
2.43k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.43k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.43k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.43k
        auto sink_id = next_sink_operator_id();
1205
2.43k
        const int multi_cast_node_id = sink_id;
1206
2.43k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.43k
        std::vector<int> sources;
1209
9.53k
        for (int i = 0; i < sender_size; ++i) {
1210
7.10k
            auto source_id = next_operator_id();
1211
7.10k
            sources.push_back(source_id);
1212
7.10k
        }
1213
1214
2.43k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.43k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
9.53k
        for (int i = 0; i < sender_size; ++i) {
1217
7.10k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
7.10k
            RowDescriptor* exchange_row_desc = nullptr;
1220
7.10k
            {
1221
7.10k
                const auto& tmp_row_desc =
1222
7.10k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
7.10k
                                ? RowDescriptor(state->desc_tbl(),
1224
7.10k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
7.10k
                                                         .output_tuple_id})
1226
7.10k
                                : row_desc;
1227
7.10k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
7.10k
            }
1229
7.10k
            auto source_id = sources[i];
1230
7.10k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
7.10k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
7.10k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
7.10k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
7.10k
                    /*operator_id=*/source_id);
1236
7.10k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
7.10k
                    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
7.10k
            DataSinkOperatorPtr sink_op;
1241
7.10k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
7.10k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
7.10k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
7.10k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
7.10k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
7.10k
            {
1248
7.10k
                TDataSink* t = pool->add(new TDataSink());
1249
7.10k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
7.10k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
7.10k
            }
1252
1253
            // 3. set dependency dag
1254
7.10k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
7.10k
        }
1256
2.43k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.43k
        break;
1260
2.43k
    }
1261
2.43k
    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
446k
    }
1280
445k
    return Status::OK();
1281
446k
}
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
673k
                                                 OperatorPtr& cache_op) {
1292
673k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
673k
    Defer defer = Defer([&]() {
1294
672k
        if (op) {
1295
672k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
672k
        }
1297
672k
        for (auto& s : sink_ops) {
1298
118k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
118k
        }
1300
672k
    });
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
673k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
673k
    std::stringstream error_msg;
1305
673k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
673k
    bool fe_with_old_version = false;
1308
673k
    switch (tnode.node_type) {
1309
219k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
219k
        op = std::make_shared<OlapScanOperatorX>(
1311
219k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
219k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
219k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
219k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
219k
        break;
1316
219k
    }
1317
76
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
76
        DCHECK(_query_ctx != nullptr);
1319
76
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
76
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
76
                                                    _num_instances);
1322
76
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
76
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
76
        break;
1325
76
    }
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
25.8k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
25.8k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
25.8k
                                                 _num_instances);
1342
25.8k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
25.8k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
25.8k
        break;
1345
25.8k
    }
1346
151k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
151k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
151k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
151k
        DCHECK_GT(num_senders, 0);
1351
151k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
151k
                                                       num_senders);
1353
151k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
151k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
151k
        break;
1356
151k
    }
1357
141k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
141k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
141k
            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
141k
        bool need_create_cache_op =
1364
141k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
141k
        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
141k
        const bool group_by_limit_opt =
1385
141k
                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
141k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
141k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
141k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
141k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
141k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
141k
        const bool can_use_distinct_streaming_agg =
1396
141k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
141k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
141k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
141k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
141k
        if (can_use_distinct_streaming_agg) {
1402
85.5k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
85.5k
            } else {
1413
85.5k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
85.5k
                                                                     tnode, descs);
1415
85.5k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
85.5k
            }
1417
85.5k
        } else if (is_streaming_agg) {
1418
1.74k
            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
1.74k
            } else {
1428
1.74k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.74k
                                                             descs);
1430
1.74k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.74k
            }
1432
54.3k
        } else {
1433
            // create new pipeline to add query cache operator
1434
54.3k
            PipelinePtr new_pipe;
1435
54.3k
            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
54.3k
            if (enable_spill) {
1441
119
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
119
                                                                     next_operator_id(), descs);
1443
54.2k
            } else {
1444
54.2k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
54.2k
            }
1446
54.3k
            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
54.3k
            } else {
1451
54.3k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
54.3k
            }
1453
1454
54.3k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
54.3k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
51.3k
                _dag.insert({downstream_pipeline_id, {}});
1457
51.3k
            }
1458
54.3k
            cur_pipe = add_pipeline(cur_pipe);
1459
54.3k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
54.3k
            if (enable_spill) {
1462
119
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
119
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
54.2k
            } else {
1465
54.2k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
54.2k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
54.2k
            }
1468
54.3k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
54.3k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
54.3k
        }
1471
141k
        break;
1472
141k
    }
1473
141k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
62
        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
62
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
62
        const auto downstream_pipeline_id = cur_pipe->id();
1486
62
        if (!_dag.contains(downstream_pipeline_id)) {
1487
62
            _dag.insert({downstream_pipeline_id, {}});
1488
62
        }
1489
62
        cur_pipe = add_pipeline(cur_pipe);
1490
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
62
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
62
        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
62
        {
1503
62
            auto shared_state = BucketedAggSharedState::create_shared();
1504
62
            shared_state->id = op->operator_id();
1505
62
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
427
            for (int i = 0; i < _num_instances; i++) {
1508
365
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
365
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
365
                sink_dep->set_shared_state(shared_state.get());
1511
365
                shared_state->sink_deps.push_back(sink_dep);
1512
365
            }
1513
62
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
62
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
62
            _op_id_to_shared_state.insert(
1516
62
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
62
        }
1518
62
        break;
1519
62
    }
1520
9.75k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.75k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.75k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.75k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.75k
        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
9.75k
        } else {
1566
9.75k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.75k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.75k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.75k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
8.06k
                _dag.insert({downstream_pipeline_id, {}});
1572
8.06k
            }
1573
9.75k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.75k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.75k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.75k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.75k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.75k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.75k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.75k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.75k
        }
1584
9.75k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
4.66k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
4.66k
                    HashJoinSharedState::create_shared(_num_instances);
1587
23.6k
            for (int i = 0; i < _num_instances; i++) {
1588
18.9k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
18.9k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
18.9k
                sink_dep->set_shared_state(shared_state.get());
1591
18.9k
                shared_state->sink_deps.push_back(sink_dep);
1592
18.9k
            }
1593
4.66k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
4.66k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
4.66k
            _op_id_to_shared_state.insert(
1596
4.66k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
4.66k
        }
1598
9.75k
        break;
1599
9.75k
    }
1600
5.82k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
5.82k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
5.82k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
5.82k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
5.82k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
5.59k
            _dag.insert({downstream_pipeline_id, {}});
1607
5.59k
        }
1608
5.82k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
5.82k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
5.82k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
5.82k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
5.82k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
5.82k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
5.82k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
5.82k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
5.82k
        break;
1618
5.82k
    }
1619
53.9k
    case TPlanNodeType::UNION_NODE: {
1620
53.9k
        int child_count = tnode.num_children;
1621
53.9k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
53.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
53.9k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
53.9k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
53.4k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.4k
        }
1628
55.3k
        for (int i = 0; i < child_count; i++) {
1629
1.40k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.40k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.40k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.40k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.40k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.40k
            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
1.40k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.40k
        }
1638
53.9k
        break;
1639
53.9k
    }
1640
53.9k
    case TPlanNodeType::SORT_NODE: {
1641
45.1k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
45.1k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
45.1k
        const bool use_local_merge =
1644
45.1k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
45.1k
        if (should_spill) {
1646
7
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
45.1k
        } else if (use_local_merge) {
1648
42.7k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
42.7k
                                                                 descs);
1650
42.7k
        } else {
1651
2.35k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.35k
        }
1653
45.1k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
45.1k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
45.1k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
45.0k
            _dag.insert({downstream_pipeline_id, {}});
1658
45.0k
        }
1659
45.1k
        cur_pipe = add_pipeline(cur_pipe);
1660
45.1k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
45.1k
        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
45.1k
        } else {
1666
45.1k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
45.1k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
45.1k
        }
1669
45.1k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
45.1k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
45.1k
        break;
1672
45.1k
    }
1673
45.1k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
63
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
63
        const auto downstream_pipeline_id = cur_pipe->id();
1678
63
        if (!_dag.contains(downstream_pipeline_id)) {
1679
63
            _dag.insert({downstream_pipeline_id, {}});
1680
63
        }
1681
63
        cur_pipe = add_pipeline(cur_pipe);
1682
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
63
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
63
        break;
1689
63
    }
1690
1.65k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.65k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.65k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.65k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.65k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.63k
        }
1698
1.65k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.65k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.65k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.65k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.65k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.65k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.65k
        break;
1706
1.65k
    }
1707
1.65k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.62k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.62k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.62k
        break;
1711
1.62k
    }
1712
1.62k
    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
314
    case TPlanNodeType::REPEAT_NODE: {
1723
314
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
314
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
314
        break;
1726
314
    }
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
1.70k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.70k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.70k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.70k
        break;
1741
1.70k
    }
1742
1.70k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
466
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
466
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
466
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
466
        break;
1747
466
    }
1748
2.09k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.09k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.09k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.09k
        break;
1752
2.09k
    }
1753
6.80k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.80k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.80k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.80k
        break;
1757
6.80k
    }
1758
6.80k
    case TPlanNodeType::SELECT_NODE: {
1759
2.43k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.43k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.43k
        break;
1762
2.43k
    }
1763
2.43k
    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
149
            _dag.insert({downstream_pipeline_id, {}});
1770
149
        }
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
673k
    }
1803
671k
    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
671k
    return Status::OK();
1809
673k
}
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
444k
Status PipelineFragmentContext::submit() {
1846
444k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
444k
    _submitted = true;
1850
1851
444k
    int submit_tasks = 0;
1852
444k
    Status st;
1853
444k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.23M
    for (auto& task : _tasks) {
1855
2.03M
        for (auto& t : task) {
1856
2.03M
            st = scheduler->submit(t.first);
1857
2.03M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
2.03M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
2.03M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
2.03M
            submit_tasks++;
1866
2.03M
        }
1867
1.23M
    }
1868
444k
    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
444k
    } else {
1883
444k
        return st;
1884
444k
    }
1885
444k
}
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
446k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
446k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
446k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
446k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
446k
    if (!_need_notify_close) {
1919
443k
        auto st = send_report(true);
1920
443k
        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
443k
    }
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
446k
    if (_runtime_state->enable_profile() &&
1931
446k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.80k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.80k
         _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
446k
    if (_query_ctx->enable_profile()) {
1953
2.80k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.80k
                                         collect_realtime_load_channel_profile());
1955
2.80k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
446k
    return !_need_notify_close;
1960
446k
}
1961
1962
2.01M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
2.01M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
2.01M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
694k
        if (_dag.contains(pipeline_id)) {
1967
370k
            for (auto dep : _dag[pipeline_id]) {
1968
370k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
370k
            }
1970
290k
        }
1971
694k
    }
1972
2.01M
    bool need_remove = false;
1973
2.01M
    {
1974
2.01M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
2.01M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
2.01M
        _query_ctx->inc_finished_task_num();
1978
2.01M
        if (_closed_tasks >= _total_tasks) {
1979
446k
            need_remove = _close_fragment_instance();
1980
446k
        }
1981
2.01M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
2.01M
    if (need_remove) {
1984
443k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
443k
    }
1986
2.01M
}
1987
1988
55.6k
std::string PipelineFragmentContext::get_load_error_url() {
1989
55.6k
    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
145k
    for (auto& tasks : _tasks) {
1993
232k
        for (auto& task : tasks) {
1994
232k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
175
                return to_load_error_http_path(str);
1996
175
            }
1997
232k
        }
1998
145k
    }
1999
55.5k
    return "";
2000
55.6k
}
2001
2002
55.6k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
55.6k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
144k
    for (auto& tasks : _tasks) {
2007
232k
        for (auto& task : tasks) {
2008
232k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
175
                return str;
2010
175
            }
2011
232k
        }
2012
144k
    }
2013
55.5k
    return "";
2014
55.6k
}
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
49.4k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
49.4k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
49.4k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
49.4k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
49.4k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
49.4k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
49.4k
    });
2031
2032
49.4k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
49.4k
    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
49.4k
    int callback_retries = 10;
2038
49.4k
    const int sleep_ms = 1000;
2039
49.4k
    Status exec_status = req.status;
2040
49.4k
    Status coord_status;
2041
49.4k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
49.4k
    do {
2043
49.4k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
49.4k
                                                            req.coord_addr, &coord_status);
2045
49.4k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
49.4k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
49.4k
    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
49.4k
    TReportExecStatusParams params;
2059
49.4k
    params.protocol_version = FrontendServiceVersion::V1;
2060
49.4k
    params.__set_query_id(req.query_id);
2061
49.4k
    params.__set_backend_num(req.backend_num);
2062
49.4k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
49.4k
    params.__set_fragment_id(req.fragment_id);
2064
49.4k
    params.__set_status(exec_status.to_thrift());
2065
49.4k
    params.__set_done(req.done);
2066
49.4k
    params.__set_query_type(req.runtime_state->query_type());
2067
49.4k
    params.__isset.profile = false;
2068
2069
49.4k
    DCHECK(req.runtime_state != nullptr);
2070
2071
49.4k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
44.5k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
44.5k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
44.5k
    } else {
2075
4.95k
        DCHECK(!req.runtime_states.empty());
2076
4.95k
        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
4.95k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.95k
    }
2086
2087
49.4k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
49.4k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
49.4k
    static std::string s_unselected_rows = "unselected.rows";
2090
49.4k
    int64_t num_rows_load_success = 0;
2091
49.4k
    int64_t num_rows_load_filtered = 0;
2092
49.4k
    int64_t num_rows_load_unselected = 0;
2093
49.4k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
49.4k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
49.4k
        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
49.4k
    } else if (!req.runtime_states.empty()) {
2109
157k
        for (auto* rs : req.runtime_states) {
2110
157k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
157k
                rs->num_finished_range() > 0) {
2112
37.5k
                params.__isset.load_counters = true;
2113
37.5k
                num_rows_load_success += rs->num_rows_load_success();
2114
37.5k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
37.5k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
37.5k
                params.__isset.fragment_instance_reports = true;
2117
37.5k
                TFragmentInstanceReport t;
2118
37.5k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
37.5k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
37.5k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
37.5k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
37.5k
                params.fragment_instance_reports.push_back(t);
2123
37.5k
            }
2124
157k
        }
2125
49.4k
    }
2126
49.4k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
49.4k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
49.4k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
49.4k
    if (!req.load_error_url.empty()) {
2131
160
        params.__set_tracking_url(req.load_error_url);
2132
160
    }
2133
49.4k
    if (!req.first_error_msg.empty()) {
2134
160
        params.__set_first_error_msg(req.first_error_msg);
2135
160
    }
2136
157k
    for (auto* rs : req.runtime_states) {
2137
157k
        if (rs->wal_id() > 0) {
2138
113
            params.__set_txn_id(rs->wal_id());
2139
113
            params.__set_label(rs->import_label());
2140
113
        }
2141
157k
    }
2142
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2146
157k
        for (auto* rs : req.runtime_states) {
2147
157k
            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
157k
        }
2154
49.4k
    }
2155
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2159
157k
        for (auto* rs : req.runtime_states) {
2160
157k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
28.0k
                params.__isset.commitInfos = true;
2162
28.0k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
28.0k
            }
2164
157k
        }
2165
49.4k
    }
2166
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2170
157k
        for (auto* rs : req.runtime_states) {
2171
157k
            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
157k
        }
2177
49.4k
    }
2178
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2183
157k
        for (auto* rs : req.runtime_states) {
2184
157k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.12k
                params.__isset.hive_partition_updates = true;
2186
2.12k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.12k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.12k
            }
2189
157k
        }
2190
49.4k
    }
2191
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2196
157k
        for (auto* rs : req.runtime_states) {
2197
157k
            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
157k
        }
2203
49.4k
    }
2204
2205
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2209
157k
        for (auto* rs : req.runtime_states) {
2210
157k
            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
157k
        }
2216
49.4k
    }
2217
2218
49.4k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
49.4k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
49.4k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
49.4k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
49.4k
    }
2224
2225
49.4k
    TReportExecStatusResult res;
2226
49.4k
    Status rpc_status;
2227
2228
49.4k
    VLOG_DEBUG << "reportExecStatus params is "
2229
15
               << apache::thrift::ThriftDebugString(params).c_str();
2230
49.4k
    if (!exec_status.ok()) {
2231
1.68k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.68k
                     << " to coordinator: " << req.coord_addr
2233
1.68k
                     << ", query id: " << print_id(req.query_id);
2234
1.68k
    }
2235
49.4k
    try {
2236
49.4k
        try {
2237
49.4k
            (*coord)->reportExecStatus(res, params);
2238
49.4k
        } 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
49.4k
        rpc_status = Status::create<false>(res.status);
2254
49.4k
    } 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
49.4k
    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
49.4k
}
2265
2266
448k
Status PipelineFragmentContext::send_report(bool done) {
2267
448k
    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
448k
    if (!_is_report_success && done && exec_status.ok()) {
2273
398k
        return Status::OK();
2274
398k
    }
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
49.7k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
326
        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
326
            return Status::OK();
2286
326
        }
2287
0
        return Status::NeedSendAgain("");
2288
326
    }
2289
2290
49.4k
    std::vector<RuntimeState*> runtime_states;
2291
2292
113k
    for (auto& tasks : _tasks) {
2293
157k
        for (auto& task : tasks) {
2294
157k
            runtime_states.push_back(task.second.get());
2295
157k
        }
2296
113k
    }
2297
2298
49.4k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
49.4k
                                        ? get_load_error_url()
2300
49.4k
                                        : _query_ctx->get_load_error_url();
2301
49.4k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
49.4k
                                          ? get_first_error_msg()
2303
49.4k
                                          : _query_ctx->get_first_error_msg();
2304
2305
49.4k
    ReportStatusRequest req {.status = exec_status,
2306
49.4k
                             .runtime_states = runtime_states,
2307
49.4k
                             .done = done || !exec_status.ok(),
2308
49.4k
                             .coord_addr = _query_ctx->coord_addr,
2309
49.4k
                             .query_id = _query_id,
2310
49.4k
                             .fragment_id = _fragment_id,
2311
49.4k
                             .fragment_instance_id = TUniqueId(),
2312
49.4k
                             .backend_num = -1,
2313
49.4k
                             .runtime_state = _runtime_state.get(),
2314
49.4k
                             .load_error_url = load_eror_url,
2315
49.4k
                             .first_error_msg = first_error_msg,
2316
49.4k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
49.4k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
49.4k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
49.4k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
49.4k
        _coordinator_callback(req);
2321
49.4k
        if (!req.done) {
2322
4.94k
            ctx->refresh_next_report_time();
2323
4.94k
        }
2324
49.4k
    });
2325
49.7k
}
2326
2327
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
0
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
0
    for (const auto& task_instances : _tasks) {
2332
0
        for (const auto& task : task_instances) {
2333
0
            if (task.first->is_running()) {
2334
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2335
0
                                      << " is running, task: " << (void*)task.first.get()
2336
0
                                      << ", is_running: " << task.first->is_running();
2337
0
                *has_running_task = true;
2338
0
                return 0;
2339
0
            }
2340
2341
0
            size_t revocable_size = task.first->get_revocable_size();
2342
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
0
                res += revocable_size;
2344
0
            }
2345
0
        }
2346
0
    }
2347
0
    return res;
2348
0
}
2349
2350
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
0
    std::vector<PipelineTask*> revocable_tasks;
2352
0
    for (const auto& task_instances : _tasks) {
2353
0
        for (const auto& task : task_instances) {
2354
0
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
0
                revocable_tasks.emplace_back(task.first.get());
2358
0
            }
2359
0
        }
2360
0
    }
2361
0
    return revocable_tasks;
2362
0
}
2363
2364
87
std::string PipelineFragmentContext::debug_string() {
2365
87
    std::lock_guard<std::mutex> l(_task_mutex);
2366
87
    fmt::memory_buffer debug_string_buffer;
2367
87
    fmt::format_to(debug_string_buffer,
2368
87
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
87
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
87
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
262
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
175
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
427
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
252
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
252
                           _tasks[j][i].first->debug_string());
2376
252
        }
2377
175
    }
2378
2379
87
    return fmt::to_string(debug_string_buffer);
2380
87
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.80k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.80k
    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
2.80k
    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
2.80k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.80k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.80k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
5.26k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
5.26k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
5.26k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
5.26k
        res.push_back(profile_ptr);
2407
5.26k
    }
2408
2409
2.80k
    return res;
2410
2.80k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.80k
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
2.80k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
8.32k
    for (const auto& tasks : _tasks) {
2426
17.1k
        for (const auto& task : tasks) {
2427
17.1k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
17.1k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
17.1k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
17.1k
                                                           _runtime_state->profile_level());
2435
17.1k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
17.1k
        }
2437
8.32k
    }
2438
2439
2.80k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.80k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.80k
                                                      _runtime_state->profile_level());
2442
2.80k
    return load_channel_profile;
2443
2.80k
}
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
3.08k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.08k
    std::set<int> result;
2454
4.90k
    for (const auto& _task : _tasks) {
2455
8.40k
        for (const auto& task : _task) {
2456
8.40k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
8.40k
            result.merge(set);
2458
8.40k
        }
2459
4.90k
    }
2460
3.08k
    if (_runtime_state) {
2461
3.08k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.08k
        result.merge(set);
2463
3.08k
    }
2464
3.08k
    return result;
2465
3.08k
}
2466
2467
447k
void PipelineFragmentContext::_release_resource() {
2468
447k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
447k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
447k
    auto st = _query_ctx->exec_status();
2472
1.23M
    for (auto& _task : _tasks) {
2473
1.23M
        if (!_task.empty()) {
2474
1.23M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.23M
        }
2476
1.23M
    }
2477
447k
    _tasks.clear();
2478
447k
    _dag.clear();
2479
447k
    _pip_id_to_pipeline.clear();
2480
447k
    _pipelines.clear();
2481
447k
    _sink.reset();
2482
447k
    _root_op.reset();
2483
447k
    _runtime_filter_mgr_map.clear();
2484
447k
    _op_id_to_shared_state.clear();
2485
447k
}
2486
2487
} // namespace doris