Coverage Report

Created: 2026-06-23 05:22

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
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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"
114
#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
132
#include "util/client_cache.h"
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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
448k
        : _query_id(std::move(query_id)),
144
448k
          _fragment_id(request.fragment_id),
145
448k
          _exec_env(exec_env),
146
448k
          _query_ctx(std::move(query_ctx)),
147
448k
          _call_back(call_back),
148
448k
          _is_report_on_cancel(true),
149
448k
          _params(request),
150
448k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
448k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
448k
                                                               : false) {
153
448k
    _fragment_watcher.start();
154
448k
}
155
156
448k
PipelineFragmentContext::~PipelineFragmentContext() {
157
448k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
448k
            .tag("query_id", print_id(_query_id))
159
448k
            .tag("fragment_id", _fragment_id);
160
448k
    _release_resource();
161
448k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
448k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
448k
        _runtime_state.reset();
165
448k
        _query_ctx.reset();
166
448k
    }
167
448k
}
168
169
51
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
51
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
51
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
51
}
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
9.85k
bool PipelineFragmentContext::notify_close() {
181
9.85k
    bool all_closed = false;
182
9.85k
    bool need_remove = false;
183
9.85k
    {
184
9.85k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.85k
        if (_closed_tasks >= _total_tasks) {
186
3.46k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
192
3.41k
                need_remove = true;
193
3.41k
            }
194
3.46k
            all_closed = true;
195
3.46k
        }
196
        // make fragment release by self after cancel
197
9.85k
        _need_notify_close = false;
198
9.85k
    }
199
9.85k
    if (need_remove) {
200
3.41k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.41k
    }
202
9.85k
    return all_closed;
203
9.85k
}
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
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// There maybe dead lock.
209
6.37k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.37k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.37k
            .tag("query_id", print_id(_query_id))
212
6.37k
            .tag("fragment_id", _fragment_id)
213
6.37k
            .tag("reason", reason.to_string());
214
6.37k
    if (notify_close()) {
215
66
        return;
216
66
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.31k
    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
6.31k
    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
6.31k
    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
6.31k
    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
6.31k
    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
6.31k
    _query_ctx->cancel(reason, _fragment_id);
243
6.31k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
315
        _is_report_on_cancel = false;
245
5.99k
    } else {
246
26.8k
        for (auto& id : _fragment_instance_ids) {
247
26.8k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
26.8k
        }
249
5.99k
    }
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
6.31k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.31k
    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
27.6k
    for (auto& tasks : _tasks) {
263
70.2k
        for (auto& task : tasks) {
264
70.2k
            task.first->unblock_all_dependencies();
265
70.2k
        }
266
27.6k
    }
267
6.31k
}
268
269
701k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
701k
    PipelineId id = _next_pipeline_id++;
271
701k
    auto pipeline = std::make_shared<Pipeline>(
272
701k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
701k
            parent ? parent->num_tasks() : _num_instances);
274
701k
    if (idx >= 0) {
275
126k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
574k
    } else {
277
574k
        _pipelines.emplace_back(pipeline);
278
574k
    }
279
701k
    if (parent) {
280
245k
        parent->set_children(pipeline);
281
245k
    }
282
701k
    return pipeline;
283
701k
}
284
285
448k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
448k
    {
287
448k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
448k
        auto root_pipeline = add_pipeline();
290
448k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
448k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
448k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
448k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
448k
                                          _params.fragment.output_exprs, _params,
299
448k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
448k
                                          *_desc_tbl, root_pipeline->id()));
301
448k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
448k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
574k
        for (PipelinePtr& pipeline : _pipelines) {
305
574k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
574k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
574k
        }
308
448k
    }
309
    // 4. Build local exchanger
310
448k
    if (_runtime_state->enable_local_shuffle()) {
311
443k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
443k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
443k
                                             _params.bucket_seq_to_instance_idx,
314
443k
                                             _params.shuffle_idx_to_instance_idx));
315
443k
    }
316
317
    // 5. Initialize global states in pipelines.
318
701k
    for (PipelinePtr& pipeline : _pipelines) {
319
701k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
701k
        pipeline->children().clear();
321
701k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
701k
    }
323
324
447k
    {
325
447k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
447k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
447k
    }
329
330
447k
    return Status::OK();
331
447k
}
332
333
448k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
448k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
448k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
448k
        _timeout = _params.query_options.execution_timeout;
339
448k
    }
340
341
448k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
448k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
448k
    SCOPED_TIMER(_prepare_timer);
344
448k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
448k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
448k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
448k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
448k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
448k
    {
350
448k
        SCOPED_TIMER(_init_context_timer);
351
448k
        cast_set(_num_instances, _params.local_params.size());
352
448k
        _total_instances =
353
448k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
448k
        auto* fragment_context = this;
356
357
448k
        if (_params.query_options.__isset.is_report_success) {
358
448k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
448k
        }
360
361
        // 1. Set up the global runtime state.
362
448k
        _runtime_state = RuntimeState::create_unique(
363
448k
                _params.query_id, _params.fragment_id, _params.query_options,
364
448k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
448k
        _runtime_state->set_task_execution_context(shared_from_this());
366
448k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
448k
        if (_params.__isset.backend_id) {
368
443k
            _runtime_state->set_backend_id(_params.backend_id);
369
443k
        }
370
448k
        if (_params.__isset.import_label) {
371
241
            _runtime_state->set_import_label(_params.import_label);
372
241
        }
373
448k
        if (_params.__isset.db_name) {
374
193
            _runtime_state->set_db_name(_params.db_name);
375
193
        }
376
448k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
448k
        if (_params.is_simplified_param) {
381
149k
            _desc_tbl = _query_ctx->desc_tbl;
382
299k
        } else {
383
299k
            DCHECK(_params.__isset.desc_tbl);
384
299k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
299k
                                                  &_desc_tbl));
386
299k
        }
387
448k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
448k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
448k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
448k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
448k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
448k
        const auto target_size = _params.local_params.size();
395
448k
        _fragment_instance_ids.resize(target_size);
396
1.65M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.20M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.20M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.20M
        }
400
448k
    }
401
402
448k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
447k
    _init_next_report_time();
405
406
447k
    _prepared = true;
407
447k
    return Status::OK();
408
448k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.20M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.20M
    const auto& local_params = _params.local_params[instance_idx];
414
1.20M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.20M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.20M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.20M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.20M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
2.02M
                                       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
2.56M
        for (auto& op : pipeline->operators()) {
424
2.56M
            auto source_id = op->operator_id();
425
2.56M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.56M
                iter != _op_id_to_shared_state.end()) {
427
819k
                shared_state_map.insert({source_id, iter->second});
428
819k
            }
429
2.56M
        }
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
336k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
336k
            }
435
2.03M
        }
436
2.02M
        return shared_state_map;
437
2.02M
    };
438
439
3.71M
    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
242
                    task_runtime_state->set_import_label(_params.import_label);
457
242
                }
458
2.02M
                if (_params.__isset.db_name) {
459
194
                    task_runtime_state->set_db_name(_params.db_name);
460
194
                }
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
2.02M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
2.02M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
2.02M
            if (_dag.contains(_pipeline->id())) {
522
1.30M
                auto& deps = _dag[_pipeline->id()];
523
2.09M
                for (auto& dep : deps) {
524
2.09M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.13M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.13M
                        if (ss) {
527
472k
                            task->inject_shared_state(ss);
528
665k
                        } else {
529
665k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
665k
                                    task->get_source_shared_state());
531
665k
                        }
532
1.13M
                    }
533
2.09M
                }
534
1.30M
            }
535
2.02M
        }
536
2.50M
    }
537
3.70M
    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
2.02M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
2.02M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
2.02M
            std::vector<TScanRangeParams> scan_ranges;
542
2.02M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
2.02M
            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
2.02M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
2.02M
                                                             _params.fragment.output_sink));
548
2.02M
        }
549
2.50M
    }
550
1.20M
    {
551
1.20M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.20M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.20M
    }
554
1.20M
    return Status::OK();
555
1.20M
}
556
557
447k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
447k
    _total_tasks = 0;
559
447k
    _closed_tasks = 0;
560
447k
    const auto target_size = _params.local_params.size();
561
447k
    _tasks.resize(target_size);
562
447k
    _runtime_filter_mgr_map.resize(target_size);
563
1.14M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
700k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
700k
    }
566
447k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
447k
    if (target_size > 1 &&
569
447k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
150k
         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
18.8k
        std::vector<Status> prepare_status(target_size);
573
18.8k
        int submitted_tasks = 0;
574
18.8k
        Status submit_status;
575
18.8k
        CountDownLatch latch((int)target_size);
576
222k
        for (int i = 0; i < target_size; i++) {
577
204k
            submit_status = thread_pool->submit_func([&, i]() {
578
203k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
203k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
203k
                latch.count_down();
581
203k
            });
582
204k
            if (LIKELY(submit_status.ok())) {
583
204k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
204k
        }
588
18.8k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
18.8k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
222k
        for (int i = 0; i < submitted_tasks; i++) {
593
204k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
204k
        }
597
428k
    } else {
598
1.43M
        for (int i = 0; i < target_size; i++) {
599
1.00M
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
1.00M
        }
601
428k
    }
602
447k
    _pipeline_parent_map.clear();
603
447k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
447k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
447k
    return Status::OK();
608
447k
}
609
610
447k
void PipelineFragmentContext::_init_next_report_time() {
611
447k
    auto interval_s = config::pipeline_status_report_interval;
612
447k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
42.8k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.8k
        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
42.8k
        _previous_report_time =
617
42.8k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.8k
        _disable_period_report = false;
619
42.8k
    }
620
447k
}
621
622
4.98k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.98k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.98k
    DCHECK(disable == true);
625
4.98k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.98k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.98k
}
628
629
7.32M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.32M
    if (!_is_report_success) {
631
6.87M
        return;
632
6.87M
    }
633
455k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
455k
    if (disable) {
635
8.99k
        return;
636
8.99k
    }
637
446k
    int32_t interval_s = config::pipeline_status_report_interval;
638
446k
    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
446k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
446k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
446k
    if (MonotonicNanos() > next_report_time) {
646
5.00k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
5.00k
                                                            std::memory_order_acq_rel)) {
648
19
            return;
649
19
        }
650
4.98k
        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
4.98k
        auto st = send_report(false);
667
4.98k
        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
4.98k
    }
673
446k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
447k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
447k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
447k
    int node_idx = 0;
682
683
447k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
447k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
447k
    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
447k
    return Status::OK();
691
447k
}
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
678k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
678k
    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
678k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
678k
    int num_children = tnodes[*node_idx].num_children;
706
678k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
678k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
678k
    OperatorPtr op = nullptr;
710
678k
    OperatorPtr cache_op = nullptr;
711
678k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
678k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
678k
                                     followed_by_shuffled_operator,
714
678k
                                     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
678k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
678k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
230k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
447k
    } else {
723
447k
        *root = op;
724
447k
    }
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
678k
    auto required_data_distribution =
737
678k
            cur_pipe->operators().empty()
738
678k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
678k
                    : op->required_data_distribution(_runtime_state.get());
740
678k
    current_followed_by_shuffled_operator =
741
678k
            ((followed_by_shuffled_operator ||
742
678k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
616k
                                             : op->is_shuffled_operator())) &&
744
678k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
678k
            (followed_by_shuffled_operator &&
746
562k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
678k
    current_require_bucket_distribution =
749
678k
            ((require_bucket_distribution ||
750
678k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
621k
                                             : op->is_colocated_operator())) &&
752
678k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
678k
            (require_bucket_distribution &&
754
569k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
678k
    if (num_children == 0) {
757
464k
        _use_serial_source = op->is_serial_operator();
758
464k
    }
759
    // rely on that tnodes is preorder of the plan
760
909k
    for (int i = 0; i < num_children; i++) {
761
230k
        ++*node_idx;
762
230k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
230k
                                            current_followed_by_shuffled_operator,
764
230k
                                            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
230k
        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
230k
    }
775
776
678k
    return Status::OK();
777
678k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
126k
        PipelinePtr pipe_with_sink) {
782
126k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
126k
    pipe_with_source->set_num_tasks(_num_instances);
784
126k
    pipe_with_source->set_data_distribution(data_distribution);
785
126k
}
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
126k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
126k
    auto& operators = cur_pipe->operators();
793
126k
    const auto downstream_pipeline_id = cur_pipe->id();
794
126k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
126k
    DataSinkOperatorPtr sink;
797
126k
    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
126k
    const bool followed_by_shuffled_operator =
804
126k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
126k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
126k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
126k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
126k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
126k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
126k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
126k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
126k
    if (bucket_seq_to_instance_idx.empty() &&
813
126k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
12
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
12
    }
816
126k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
126k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
126k
                                          num_buckets, use_global_hash_shuffle,
819
126k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
126k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
126k
            LocalExchangeSharedState::create_shared(_num_instances);
824
126k
    switch (data_distribution.distribution_type) {
825
22.6k
    case ExchangeType::HASH_SHUFFLE:
826
22.6k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
22.6k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
22.6k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
22.6k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
22.6k
                        ? cast_set<int>(
831
22.6k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
22.6k
                        : 0);
833
22.6k
        break;
834
577
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
577
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
577
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
577
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
577
                        ? cast_set<int>(
839
577
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
577
                        : 0);
841
577
        break;
842
98.9k
    case ExchangeType::PASSTHROUGH:
843
98.9k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
98.9k
                cur_pipe->num_tasks(), _num_instances,
845
98.9k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
98.9k
                        ? cast_set<int>(
847
98.9k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
98.9k
                        : 0);
849
98.9k
        break;
850
535
    case ExchangeType::BROADCAST:
851
535
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
535
                cur_pipe->num_tasks(), _num_instances,
853
535
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
535
                        ? cast_set<int>(
855
535
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
535
                        : 0);
857
535
        break;
858
2.85k
    case ExchangeType::PASS_TO_ONE:
859
2.85k
        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
1.61k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.61k
                    cur_pipe->num_tasks(), _num_instances,
863
1.61k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.61k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.61k
                                                    .local_exchange_free_blocks_limit)
866
1.61k
                            : 0);
867
1.61k
        } else {
868
1.23k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.23k
                    cur_pipe->num_tasks(), _num_instances,
870
1.23k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.23k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.23k
                                                    .local_exchange_free_blocks_limit)
873
1.23k
                            : 0);
874
1.23k
        }
875
2.85k
        break;
876
1.04k
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
1.04k
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
1.04k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
1.04k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
1.04k
                        ? cast_set<int>(
881
1.04k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
1.04k
                        : 0);
883
1.04k
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
126k
    }
888
126k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
126k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
126k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
126k
    _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
126k
    std::copy(operators.begin(), operators.begin() + idx,
898
126k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
126k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
126k
    OperatorPtr source_op;
905
126k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
126k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
126k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
126k
    if (!operators.empty()) {
909
47.1k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
47.1k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
47.1k
    }
912
126k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
126k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
126k
    std::vector<PipelineId> edges_with_source;
917
145k
    for (auto child : cur_pipe->children()) {
918
145k
        bool found = false;
919
160k
        for (auto op : new_pip->operators()) {
920
160k
            if (child->sink()->node_id() == op->node_id()) {
921
13.3k
                new_pip->set_children(child);
922
13.3k
                found = true;
923
13.3k
            };
924
160k
        }
925
145k
        if (!found) {
926
132k
            new_children.push_back(child);
927
132k
            edges_with_source.push_back(child->id());
928
132k
        }
929
145k
    }
930
126k
    new_children.push_back(new_pip);
931
126k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
126k
    if (!new_pip->children().empty()) {
935
7.59k
        std::vector<PipelineId> edges_with_sink;
936
13.3k
        for (auto child : new_pip->children()) {
937
13.3k
            edges_with_sink.push_back(child->id());
938
13.3k
        }
939
7.59k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.59k
    }
941
126k
    cur_pipe->set_children(new_children);
942
126k
    _dag[downstream_pipeline_id] = edges_with_source;
943
126k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
126k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
126k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
126k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
126k
    return Status::OK();
950
126k
}
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
198k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
198k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
43.5k
        return Status::OK();
959
43.5k
    }
960
961
154k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
51.4k
        return Status::OK();
963
51.4k
    }
964
103k
    *do_local_exchange = true;
965
966
103k
    auto& operators = cur_pipe->operators();
967
103k
    auto total_op_num = operators.size();
968
103k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
103k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
103k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
103k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
103k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
69
            << "total_op_num: " << total_op_num
975
69
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
69
            << " 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
103k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
103k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
23.1k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
23.1k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
23.1k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
23.1k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
23.1k
                shuffle_idx_to_instance_idx));
990
23.1k
    }
991
103k
    return Status::OK();
992
103k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
443k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.01M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
569k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
569k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
119k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
119k
                if (child->sink()->node_id() ==
1003
119k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
103k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
103k
                }
1006
119k
            }
1007
113k
        }
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
569k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
569k
                                             bucket_seq_to_instance_idx,
1014
569k
                                             shuffle_idx_to_instance_idx));
1015
569k
    }
1016
443k
    return Status::OK();
1017
443k
}
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
569k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
569k
    int idx = 1;
1024
569k
    bool do_local_exchange = false;
1025
616k
    do {
1026
616k
        auto& ops = pip->operators();
1027
616k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
681k
        for (; idx < ops.size();) {
1030
111k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
105k
                RETURN_IF_ERROR(_add_local_exchange(
1032
105k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
105k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
105k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
105k
                        shuffle_idx_to_instance_idx));
1036
105k
            }
1037
111k
            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
47.1k
                idx = 2;
1043
47.1k
                break;
1044
47.1k
            }
1045
64.4k
            idx++;
1046
64.4k
        }
1047
616k
    } while (do_local_exchange);
1048
569k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
93.3k
        RETURN_IF_ERROR(_add_local_exchange(
1050
93.3k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
93.3k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
93.3k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
93.3k
    }
1054
569k
    return Status::OK();
1055
569k
}
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
448k
                                                  PipelineId cur_pipeline_id) {
1063
448k
    switch (thrift_sink.type) {
1064
147k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
147k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
147k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
147k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
147k
                params.destinations, _fragment_instance_ids);
1071
147k
        break;
1072
147k
    }
1073
260k
    case TDataSinkType::RESULT_SINK: {
1074
260k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
260k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
260k
        int child_node_id = pipeline->operators().back()->node_id();
1080
260k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
260k
                                                      row_desc, output_exprs,
1082
260k
                                                      thrift_sink.result_sink);
1083
260k
        break;
1084
260k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
34.5k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
34.5k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
34.5k
        int child_node_id = pipeline->operators().back()->node_id();
1098
34.5k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
34.5k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
34.5k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.90k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.90k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
31.6k
        } else {
1104
31.6k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
31.6k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
31.6k
        }
1107
34.5k
        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
1.48k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.48k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.48k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.48k
                                                         output_exprs);
1123
1.48k
        break;
1124
1.48k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
4
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
4
                                                                     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
1.73k
        break;
1137
1.73k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
503
    case TDataSinkType::RESULT_FILE_SINK: {
1186
503
        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
503
        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
503
        } else {
1196
503
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
503
                                                              output_exprs);
1198
503
        }
1199
503
        break;
1200
503
    }
1201
2.44k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.44k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.44k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.44k
        auto sink_id = next_sink_operator_id();
1205
2.44k
        const int multi_cast_node_id = sink_id;
1206
2.44k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.44k
        std::vector<int> sources;
1209
9.58k
        for (int i = 0; i < sender_size; ++i) {
1210
7.13k
            auto source_id = next_operator_id();
1211
7.13k
            sources.push_back(source_id);
1212
7.13k
        }
1213
1214
2.44k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.44k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
9.58k
        for (int i = 0; i < sender_size; ++i) {
1217
7.13k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
7.13k
            RowDescriptor* exchange_row_desc = nullptr;
1220
7.13k
            {
1221
7.13k
                const auto& tmp_row_desc =
1222
7.13k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
7.13k
                                ? RowDescriptor(state->desc_tbl(),
1224
7.13k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
7.13k
                                                         .output_tuple_id})
1226
18.4E
                                : row_desc;
1227
7.13k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
7.13k
            }
1229
7.13k
            auto source_id = sources[i];
1230
7.13k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
7.13k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
7.13k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
7.13k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
7.13k
                    /*operator_id=*/source_id);
1236
7.13k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
7.13k
                    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
7.13k
            DataSinkOperatorPtr sink_op;
1241
7.13k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
7.13k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
7.13k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
7.13k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
7.13k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
7.13k
            {
1248
7.13k
                TDataSink* t = pool->add(new TDataSink());
1249
7.13k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
7.13k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
7.13k
            }
1252
1253
            // 3. set dependency dag
1254
7.13k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
7.13k
        }
1256
2.44k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.44k
        break;
1260
2.44k
    }
1261
2.44k
    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
448k
    }
1280
448k
    return Status::OK();
1281
448k
}
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
679k
                                                 OperatorPtr& cache_op) {
1292
679k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
679k
    Defer defer = Defer([&]() {
1294
679k
        if (op) {
1295
679k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
679k
        }
1297
678k
        for (auto& s : sink_ops) {
1298
118k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
118k
        }
1300
678k
    });
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
679k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
679k
    std::stringstream error_msg;
1305
679k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
679k
    bool fe_with_old_version = false;
1308
679k
    switch (tnode.node_type) {
1309
220k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
220k
        op = std::make_shared<OlapScanOperatorX>(
1311
220k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
220k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
220k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
220k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
220k
        break;
1316
220k
    }
1317
80
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
80
        DCHECK(_query_ctx != nullptr);
1319
80
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
80
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
80
                                                    _num_instances);
1322
80
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
80
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
80
        break;
1325
80
    }
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
26.0k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
26.0k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
26.0k
                                                 _num_instances);
1342
26.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
26.0k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
26.0k
        break;
1345
26.0k
    }
1346
152k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
152k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
152k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
152k
        DCHECK_GT(num_senders, 0);
1351
152k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
152k
                                                       num_senders);
1353
152k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
152k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
152k
        break;
1356
152k
    }
1357
145k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
145k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
145k
            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
145k
        bool need_create_cache_op =
1364
145k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
145k
        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
145k
        const bool group_by_limit_opt =
1385
145k
                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
145k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
145k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
145k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
145k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
145k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
145k
        const bool can_use_distinct_streaming_agg =
1396
145k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
145k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
145k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
145k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
145k
        if (can_use_distinct_streaming_agg) {
1402
89.2k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
89.2k
            } else {
1413
89.2k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
89.2k
                                                                     tnode, descs);
1415
89.2k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
89.2k
            }
1417
89.2k
        } else if (is_streaming_agg) {
1418
1.40k
            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
1.40k
            } else {
1428
1.40k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.40k
                                                             descs);
1430
1.40k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.40k
            }
1432
54.6k
        } else {
1433
            // create new pipeline to add query cache operator
1434
54.6k
            PipelinePtr new_pipe;
1435
54.6k
            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
54.6k
            if (enable_spill) {
1441
53
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
53
                                                                     next_operator_id(), descs);
1443
54.6k
            } else {
1444
54.6k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
54.6k
            }
1446
54.6k
            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
54.6k
            } else {
1451
54.6k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
54.6k
            }
1453
1454
54.6k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
54.6k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
52.2k
                _dag.insert({downstream_pipeline_id, {}});
1457
52.2k
            }
1458
54.6k
            cur_pipe = add_pipeline(cur_pipe);
1459
54.6k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
54.6k
            if (enable_spill) {
1462
53
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
53
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
54.6k
            } else {
1465
54.6k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
54.6k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
54.6k
            }
1468
54.6k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
54.6k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
54.6k
        }
1471
145k
        break;
1472
145k
    }
1473
145k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
85
        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
85
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
85
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
85
        const auto downstream_pipeline_id = cur_pipe->id();
1486
85
        if (!_dag.contains(downstream_pipeline_id)) {
1487
85
            _dag.insert({downstream_pipeline_id, {}});
1488
85
        }
1489
85
        cur_pipe = add_pipeline(cur_pipe);
1490
85
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
85
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
85
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
85
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
85
        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
85
        {
1503
85
            auto shared_state = BucketedAggSharedState::create_shared();
1504
85
            shared_state->id = op->operator_id();
1505
85
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
543
            for (int i = 0; i < _num_instances; i++) {
1508
458
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
458
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
458
                sink_dep->set_shared_state(shared_state.get());
1511
458
                shared_state->sink_deps.push_back(sink_dep);
1512
458
            }
1513
85
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
85
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
85
            _op_id_to_shared_state.insert(
1516
85
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
85
        }
1518
85
        break;
1519
85
    }
1520
9.74k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.74k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.74k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.74k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.74k
        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
9.74k
        } else {
1566
9.74k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.74k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.74k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.74k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
8.04k
                _dag.insert({downstream_pipeline_id, {}});
1572
8.04k
            }
1573
9.74k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.74k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.74k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.74k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.74k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.74k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.74k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.74k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.74k
        }
1584
9.74k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.81k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.81k
                    HashJoinSharedState::create_shared(_num_instances);
1587
20.7k
            for (int i = 0; i < _num_instances; i++) {
1588
17.8k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
17.8k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
17.8k
                sink_dep->set_shared_state(shared_state.get());
1591
17.8k
                shared_state->sink_deps.push_back(sink_dep);
1592
17.8k
            }
1593
2.81k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.81k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.81k
            _op_id_to_shared_state.insert(
1596
2.81k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.81k
        }
1598
9.74k
        break;
1599
9.74k
    }
1600
5.87k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
5.87k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
5.87k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
5.87k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
5.87k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
5.63k
            _dag.insert({downstream_pipeline_id, {}});
1607
5.63k
        }
1608
5.87k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
5.87k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
5.87k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
5.87k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
5.87k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
5.87k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
5.87k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
5.87k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
5.87k
        break;
1618
5.87k
    }
1619
54.5k
    case TPlanNodeType::UNION_NODE: {
1620
54.5k
        int child_count = tnode.num_children;
1621
54.5k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
54.5k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
54.5k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
54.5k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
54.2k
            _dag.insert({downstream_pipeline_id, {}});
1627
54.2k
        }
1628
55.9k
        for (int i = 0; i < child_count; i++) {
1629
1.43k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.43k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.43k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.43k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.43k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.43k
            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
1.43k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.43k
        }
1638
54.5k
        break;
1639
54.5k
    }
1640
54.5k
    case TPlanNodeType::SORT_NODE: {
1641
44.7k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
44.7k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
44.7k
        const bool use_local_merge =
1644
44.7k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
44.7k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
44.7k
        } else if (use_local_merge) {
1648
42.4k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
42.4k
                                                                 descs);
1650
42.4k
        } else {
1651
2.34k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.34k
        }
1653
44.7k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
44.7k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
44.7k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
44.7k
            _dag.insert({downstream_pipeline_id, {}});
1658
44.7k
        }
1659
44.7k
        cur_pipe = add_pipeline(cur_pipe);
1660
44.7k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
44.7k
        if (should_spill) {
1663
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
44.7k
        } else {
1666
44.7k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
44.7k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
44.7k
        }
1669
44.7k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
44.7k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
44.7k
        break;
1672
44.7k
    }
1673
44.7k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.65k
    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
1.64k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.64k
        break;
1711
1.64k
    }
1712
1.64k
    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
297
    case TPlanNodeType::REPEAT_NODE: {
1723
297
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
297
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
297
        break;
1726
297
    }
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
1.71k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.71k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.71k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.71k
        break;
1741
1.71k
    }
1742
1.71k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
470
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
470
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
470
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
470
        break;
1747
470
    }
1748
2.08k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.08k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.08k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.08k
        break;
1752
2.08k
    }
1753
6.53k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.53k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.53k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.53k
        break;
1757
6.53k
    }
1758
6.53k
    case TPlanNodeType::SELECT_NODE: {
1759
2.44k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.44k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.44k
        break;
1762
2.44k
    }
1763
2.44k
    case TPlanNodeType::REC_CTE_NODE: {
1764
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
151
        const auto downstream_pipeline_id = cur_pipe->id();
1768
151
        if (!_dag.contains(downstream_pipeline_id)) {
1769
148
            _dag.insert({downstream_pipeline_id, {}});
1770
148
        }
1771
1772
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
151
        DataSinkOperatorPtr anchor_sink;
1776
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
151
                                                                  op->operator_id(), tnode, descs);
1778
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
151
        DataSinkOperatorPtr rec_sink;
1786
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
151
                                                         tnode, descs);
1788
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
151
        break;
1793
151
    }
1794
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.95k
        break;
1798
1.95k
    }
1799
1.95k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
679k
    }
1803
678k
    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
678k
    return Status::OK();
1809
679k
}
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
446k
Status PipelineFragmentContext::submit() {
1846
446k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
446k
    _submitted = true;
1850
1851
446k
    int submit_tasks = 0;
1852
446k
    Status st;
1853
446k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.20M
    for (auto& task : _tasks) {
1855
2.02M
        for (auto& t : task) {
1856
2.02M
            st = scheduler->submit(t.first);
1857
2.02M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
2.02M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
2.02M
            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
2.02M
            submit_tasks++;
1866
2.02M
        }
1867
1.20M
    }
1868
446k
    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
446k
    } else {
1883
446k
        return st;
1884
446k
    }
1885
446k
}
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
447k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
447k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
447k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
447k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
447k
    if (!_need_notify_close) {
1919
444k
        auto st = send_report(true);
1920
444k
        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
444k
    }
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
447k
    if (_runtime_state->enable_profile() &&
1931
447k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.50k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.50k
         _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
447k
    if (_query_ctx->enable_profile()) {
1953
2.50k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.50k
                                         collect_realtime_load_channel_profile());
1955
2.50k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
447k
    return !_need_notify_close;
1960
447k
}
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
700k
        if (_dag.contains(pipeline_id)) {
1967
379k
            for (auto dep : _dag[pipeline_id]) {
1968
379k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
379k
            }
1970
295k
        }
1971
700k
    }
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
447k
            need_remove = _close_fragment_instance();
1980
447k
        }
1981
2.01M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
2.01M
    if (need_remove) {
1984
444k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
444k
    }
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
139k
    for (auto& tasks : _tasks) {
1993
221k
        for (auto& task : tasks) {
1994
221k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
192
                return to_load_error_http_path(str);
1996
192
            }
1997
221k
        }
1998
139k
    }
1999
55.4k
    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
139k
    for (auto& tasks : _tasks) {
2007
221k
        for (auto& task : tasks) {
2008
221k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
192
                return str;
2010
192
            }
2011
221k
        }
2012
139k
    }
2013
55.4k
    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
49.3k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
49.3k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
49.3k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
49.3k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
49.3k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
49.3k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
49.3k
    });
2031
2032
49.3k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
49.3k
    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
49.3k
    int callback_retries = 10;
2038
49.3k
    const int sleep_ms = 1000;
2039
49.3k
    Status exec_status = req.status;
2040
49.3k
    Status coord_status;
2041
49.3k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
49.3k
    do {
2043
49.3k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
49.3k
                                                            req.coord_addr, &coord_status);
2045
49.3k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
49.3k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
49.3k
    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
49.3k
    TReportExecStatusParams params;
2059
49.3k
    params.protocol_version = FrontendServiceVersion::V1;
2060
49.3k
    params.__set_query_id(req.query_id);
2061
49.3k
    params.__set_backend_num(req.backend_num);
2062
49.3k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
49.3k
    params.__set_fragment_id(req.fragment_id);
2064
49.3k
    params.__set_status(exec_status.to_thrift());
2065
49.3k
    params.__set_done(req.done);
2066
49.3k
    params.__set_query_type(req.runtime_state->query_type());
2067
49.3k
    params.__isset.profile = false;
2068
2069
49.3k
    DCHECK(req.runtime_state != nullptr);
2070
2071
49.3k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
44.7k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
44.7k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
44.7k
    } else {
2075
4.63k
        DCHECK(!req.runtime_states.empty());
2076
4.63k
        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
4.63k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.63k
    }
2086
2087
49.3k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
49.3k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
49.3k
    static std::string s_unselected_rows = "unselected.rows";
2090
49.3k
    int64_t num_rows_load_success = 0;
2091
49.3k
    int64_t num_rows_load_filtered = 0;
2092
49.3k
    int64_t num_rows_load_unselected = 0;
2093
49.3k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
49.3k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
49.3k
        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
49.3k
    } else if (!req.runtime_states.empty()) {
2109
151k
        for (auto* rs : req.runtime_states) {
2110
151k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
151k
                rs->num_finished_range() > 0) {
2112
38.2k
                params.__isset.load_counters = true;
2113
38.2k
                num_rows_load_success += rs->num_rows_load_success();
2114
38.2k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
38.2k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
38.2k
                params.__isset.fragment_instance_reports = true;
2117
38.2k
                TFragmentInstanceReport t;
2118
38.2k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
38.2k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
38.2k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
38.2k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
38.2k
                params.fragment_instance_reports.push_back(t);
2123
38.2k
            }
2124
151k
        }
2125
49.3k
    }
2126
49.3k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
49.3k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
49.3k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
49.3k
    if (!req.load_error_url.empty()) {
2131
177
        params.__set_tracking_url(req.load_error_url);
2132
177
    }
2133
49.3k
    if (!req.first_error_msg.empty()) {
2134
177
        params.__set_first_error_msg(req.first_error_msg);
2135
177
    }
2136
151k
    for (auto* rs : req.runtime_states) {
2137
151k
        if (rs->wal_id() > 0) {
2138
105
            params.__set_txn_id(rs->wal_id());
2139
105
            params.__set_label(rs->import_label());
2140
105
        }
2141
151k
    }
2142
49.3k
    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
49.3k
    } else if (!req.runtime_states.empty()) {
2146
151k
        for (auto* rs : req.runtime_states) {
2147
151k
            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
151k
        }
2154
49.3k
    }
2155
49.3k
    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
49.3k
    } else if (!req.runtime_states.empty()) {
2159
151k
        for (auto* rs : req.runtime_states) {
2160
151k
            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
151k
        }
2165
49.3k
    }
2166
49.3k
    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
49.3k
    } else if (!req.runtime_states.empty()) {
2170
151k
        for (auto* rs : req.runtime_states) {
2171
151k
            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
151k
        }
2177
49.3k
    }
2178
49.3k
    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
49.3k
    } else if (!req.runtime_states.empty()) {
2183
151k
        for (auto* rs : req.runtime_states) {
2184
151k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.15k
                params.__isset.hive_partition_updates = true;
2186
2.15k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.15k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.15k
            }
2189
151k
        }
2190
49.3k
    }
2191
49.3k
    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
49.3k
    } else if (!req.runtime_states.empty()) {
2196
151k
        for (auto* rs : req.runtime_states) {
2197
151k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.09k
                params.__isset.iceberg_commit_datas = true;
2199
2.09k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.09k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.09k
            }
2202
151k
        }
2203
49.3k
    }
2204
2205
49.3k
    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
49.3k
    } else if (!req.runtime_states.empty()) {
2209
151k
        for (auto* rs : req.runtime_states) {
2210
151k
            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
151k
        }
2216
49.3k
    }
2217
2218
49.3k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
49.3k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
49.3k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
49.3k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
49.3k
    }
2224
2225
49.3k
    TReportExecStatusResult res;
2226
49.3k
    Status rpc_status;
2227
2228
49.3k
    VLOG_DEBUG << "reportExecStatus params is "
2229
10
               << apache::thrift::ThriftDebugString(params).c_str();
2230
49.3k
    if (!exec_status.ok()) {
2231
1.69k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.69k
                     << " to coordinator: " << req.coord_addr
2233
1.69k
                     << ", query id: " << print_id(req.query_id);
2234
1.69k
    }
2235
49.3k
    try {
2236
49.3k
        try {
2237
49.3k
            (*coord)->reportExecStatus(res, params);
2238
49.3k
        } 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
49.3k
        rpc_status = Status::create<false>(res.status);
2254
49.3k
    } 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
49.3k
    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
49.3k
}
2265
2266
449k
Status PipelineFragmentContext::send_report(bool done) {
2267
449k
    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
449k
    if (!_is_report_success && done && exec_status.ok()) {
2273
399k
        return Status::OK();
2274
399k
    }
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
49.6k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
261
        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
261
            return Status::OK();
2286
261
        }
2287
0
        return Status::NeedSendAgain("");
2288
261
    }
2289
2290
49.3k
    std::vector<RuntimeState*> runtime_states;
2291
2292
112k
    for (auto& tasks : _tasks) {
2293
151k
        for (auto& task : tasks) {
2294
151k
            runtime_states.push_back(task.second.get());
2295
151k
        }
2296
112k
    }
2297
2298
49.3k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
49.3k
                                        ? get_load_error_url()
2300
49.3k
                                        : _query_ctx->get_load_error_url();
2301
49.3k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
49.3k
                                          ? get_first_error_msg()
2303
49.3k
                                          : _query_ctx->get_first_error_msg();
2304
2305
49.3k
    ReportStatusRequest req {.status = exec_status,
2306
49.3k
                             .runtime_states = runtime_states,
2307
49.3k
                             .done = done || !exec_status.ok(),
2308
49.3k
                             .coord_addr = _query_ctx->coord_addr,
2309
49.3k
                             .query_id = _query_id,
2310
49.3k
                             .fragment_id = _fragment_id,
2311
49.3k
                             .fragment_instance_id = TUniqueId(),
2312
49.3k
                             .backend_num = -1,
2313
49.3k
                             .runtime_state = _runtime_state.get(),
2314
49.3k
                             .load_error_url = load_eror_url,
2315
49.3k
                             .first_error_msg = first_error_msg,
2316
49.3k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
49.3k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
49.3k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
49.3k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
49.3k
        _coordinator_callback(req);
2321
49.3k
        if (!req.done) {
2322
4.98k
            ctx->refresh_next_report_time();
2323
4.98k
        }
2324
49.3k
    });
2325
49.6k
}
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
52
std::string PipelineFragmentContext::debug_string() {
2365
52
    std::lock_guard<std::mutex> l(_task_mutex);
2366
52
    fmt::memory_buffer debug_string_buffer;
2367
52
    fmt::format_to(debug_string_buffer,
2368
52
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
52
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
52
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
263
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
211
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
1.15k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
945
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
945
                           _tasks[j][i].first->debug_string());
2376
945
        }
2377
211
    }
2378
2379
52
    return fmt::to_string(debug_string_buffer);
2380
52
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.50k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.50k
    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
2.50k
    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
2.50k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.50k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.50k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.66k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.66k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.66k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.66k
        res.push_back(profile_ptr);
2407
4.66k
    }
2408
2409
2.50k
    return res;
2410
2.50k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.50k
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
2.50k
    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
6.15k
    for (const auto& tasks : _tasks) {
2426
12.3k
        for (const auto& task : tasks) {
2427
12.3k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
12.3k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
12.3k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
12.3k
                                                           _runtime_state->profile_level());
2435
12.3k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
12.3k
        }
2437
6.15k
    }
2438
2439
2.50k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.50k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.50k
                                                      _runtime_state->profile_level());
2442
2.50k
    return load_channel_profile;
2443
2.50k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
6.40k
    for (const auto& _task : _tasks) {
2455
10.3k
        for (const auto& task : _task) {
2456
10.3k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
10.3k
            result.merge(set);
2458
10.3k
        }
2459
6.40k
    }
2460
3.28k
    if (_runtime_state) {
2461
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.28k
        result.merge(set);
2463
3.28k
    }
2464
3.28k
    return result;
2465
3.28k
}
2466
2467
448k
void PipelineFragmentContext::_release_resource() {
2468
448k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
448k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
448k
    auto st = _query_ctx->exec_status();
2472
1.20M
    for (auto& _task : _tasks) {
2473
1.20M
        if (!_task.empty()) {
2474
1.20M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.20M
        }
2476
1.20M
    }
2477
448k
    _tasks.clear();
2478
448k
    _dag.clear();
2479
448k
    _pip_id_to_pipeline.clear();
2480
448k
    _pipelines.clear();
2481
448k
    _sink.reset();
2482
448k
    _root_op.reset();
2483
448k
    _runtime_filter_mgr_map.clear();
2484
448k
    _op_id_to_shared_state.clear();
2485
448k
}
2486
2487
} // namespace doris