Coverage Report

Created: 2026-05-31 08:39

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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//
9
//   http://www.apache.org/licenses/LICENSE-2.0
10
//
11
// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
13
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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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"
133
#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
389k
        : _query_id(std::move(query_id)),
144
389k
          _fragment_id(request.fragment_id),
145
389k
          _exec_env(exec_env),
146
389k
          _query_ctx(std::move(query_ctx)),
147
389k
          _call_back(call_back),
148
389k
          _is_report_on_cancel(true),
149
389k
          _params(request),
150
389k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
389k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
389k
                                                               : false) {
153
389k
    _fragment_watcher.start();
154
389k
}
155
156
390k
PipelineFragmentContext::~PipelineFragmentContext() {
157
390k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
390k
            .tag("query_id", print_id(_query_id))
159
390k
            .tag("fragment_id", _fragment_id);
160
390k
    _release_resource();
161
390k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
390k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
390k
        _runtime_state.reset();
165
390k
        _query_ctx.reset();
166
390k
    }
167
390k
}
168
169
202
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
202
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
202
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
202
}
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
9.28k
bool PipelineFragmentContext::notify_close() {
181
9.28k
    bool all_closed = false;
182
9.28k
    bool need_remove = false;
183
9.28k
    {
184
9.28k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.28k
        if (_closed_tasks >= _total_tasks) {
186
3.48k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
190
                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
192
3.43k
                need_remove = true;
193
3.43k
            }
194
3.48k
            all_closed = true;
195
3.48k
        }
196
        // make fragment release by self after cancel
197
9.28k
        _need_notify_close = false;
198
9.28k
    }
199
9.28k
    if (need_remove) {
200
3.43k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.43k
    }
202
9.28k
    return all_closed;
203
9.28k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
5.80k
void PipelineFragmentContext::cancel(const Status reason) {
210
5.80k
    LOG_INFO("PipelineFragmentContext::cancel")
211
5.80k
            .tag("query_id", print_id(_query_id))
212
5.80k
            .tag("fragment_id", _fragment_id)
213
5.80k
            .tag("reason", reason.to_string());
214
5.80k
    if (notify_close()) {
215
75
        return;
216
75
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
5.72k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
5.72k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
5.72k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
5.72k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
5.72k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
5.72k
    _query_ctx->cancel(reason, _fragment_id);
243
5.72k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
243
        _is_report_on_cancel = false;
245
5.48k
    } else {
246
27.1k
        for (auto& id : _fragment_instance_ids) {
247
27.1k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
27.1k
        }
249
5.48k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
5.72k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
5.72k
    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
27.8k
    for (auto& tasks : _tasks) {
263
60.6k
        for (auto& task : tasks) {
264
60.6k
            task.first->unblock_all_dependencies();
265
60.6k
        }
266
27.8k
    }
267
5.72k
}
268
269
620k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
620k
    PipelineId id = _next_pipeline_id++;
271
620k
    auto pipeline = std::make_shared<Pipeline>(
272
620k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
620k
            parent ? parent->num_tasks() : _num_instances);
274
620k
    if (idx >= 0) {
275
111k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
508k
    } else {
277
508k
        _pipelines.emplace_back(pipeline);
278
508k
    }
279
620k
    if (parent) {
280
225k
        parent->set_children(pipeline);
281
225k
    }
282
620k
    return pipeline;
283
620k
}
284
285
389k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
389k
    {
287
389k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
389k
        auto root_pipeline = add_pipeline();
290
389k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
389k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
389k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
389k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
389k
                                          _params.fragment.output_exprs, _params,
299
389k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
389k
                                          *_desc_tbl, root_pipeline->id()));
301
389k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
389k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
506k
        for (PipelinePtr& pipeline : _pipelines) {
305
506k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
506k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
506k
        }
308
389k
    }
309
    // 4. Build local exchanger
310
389k
    if (_runtime_state->enable_local_shuffle()) {
311
386k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
386k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
386k
                                             _params.bucket_seq_to_instance_idx,
314
386k
                                             _params.shuffle_idx_to_instance_idx));
315
386k
    }
316
317
    // 5. Initialize global states in pipelines.
318
620k
    for (PipelinePtr& pipeline : _pipelines) {
319
620k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
620k
        pipeline->children().clear();
321
620k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
620k
    }
323
324
388k
    {
325
388k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
388k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
388k
    }
329
330
388k
    return Status::OK();
331
388k
}
332
333
389k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
389k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
389k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
389k
        _timeout = _params.query_options.execution_timeout;
339
389k
    }
340
341
389k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
389k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
389k
    SCOPED_TIMER(_prepare_timer);
344
389k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
389k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
389k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
389k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
389k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
389k
    {
350
389k
        SCOPED_TIMER(_init_context_timer);
351
389k
        cast_set(_num_instances, _params.local_params.size());
352
389k
        _total_instances =
353
389k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
389k
        auto* fragment_context = this;
356
357
389k
        if (_params.query_options.__isset.is_report_success) {
358
388k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
388k
        }
360
361
        // 1. Set up the global runtime state.
362
389k
        _runtime_state = RuntimeState::create_unique(
363
389k
                _params.query_id, _params.fragment_id, _params.query_options,
364
389k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
389k
        _runtime_state->set_task_execution_context(shared_from_this());
366
389k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
389k
        if (_params.__isset.backend_id) {
368
386k
            _runtime_state->set_backend_id(_params.backend_id);
369
386k
        }
370
389k
        if (_params.__isset.import_label) {
371
238
            _runtime_state->set_import_label(_params.import_label);
372
238
        }
373
389k
        if (_params.__isset.db_name) {
374
190
            _runtime_state->set_db_name(_params.db_name);
375
190
        }
376
389k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
389k
        if (_params.is_simplified_param) {
381
135k
            _desc_tbl = _query_ctx->desc_tbl;
382
254k
        } else {
383
254k
            DCHECK(_params.__isset.desc_tbl);
384
254k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
254k
                                                  &_desc_tbl));
386
254k
        }
387
389k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
389k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
389k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
389k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
389k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
389k
        const auto target_size = _params.local_params.size();
395
389k
        _fragment_instance_ids.resize(target_size);
396
1.46M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.07M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.07M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.07M
        }
400
389k
    }
401
402
389k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
388k
    _init_next_report_time();
405
406
388k
    _prepared = true;
407
388k
    return Status::OK();
408
389k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.07M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.07M
    const auto& local_params = _params.local_params[instance_idx];
414
1.07M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.07M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.07M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.07M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.07M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.84M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.84M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.84M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.84M
                shared_state_map;
423
2.36M
        for (auto& op : pipeline->operators()) {
424
2.36M
            auto source_id = op->operator_id();
425
2.36M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.36M
                iter != _op_id_to_shared_state.end()) {
427
747k
                shared_state_map.insert({source_id, iter->second});
428
747k
            }
429
2.36M
        }
430
1.84M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.84M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.84M
                iter != _op_id_to_shared_state.end()) {
433
327k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
327k
            }
435
1.84M
        }
436
1.84M
        return shared_state_map;
437
1.84M
    };
438
439
3.32M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.25M
        auto& pipeline = _pipelines[pip_idx];
441
2.25M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.83M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.83M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.83M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.83M
            {
446
                // Initialize runtime state for this task
447
1.83M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.83M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.83M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.84M
                if (_params.__isset.backend_id) {
453
1.84M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.84M
                }
455
1.83M
                if (_params.__isset.import_label) {
456
239
                    task_runtime_state->set_import_label(_params.import_label);
457
239
                }
458
1.83M
                if (_params.__isset.db_name) {
459
191
                    task_runtime_state->set_db_name(_params.db_name);
460
191
                }
461
1.83M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.83M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.83M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.83M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.83M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.83M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.83M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.83M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.83M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.83M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.83M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.83M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.83M
            }
482
1.83M
            auto cur_task_id = _total_tasks++;
483
1.83M
            task_runtime_state->set_task_id(cur_task_id);
484
1.83M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.83M
            auto task = std::make_shared<PipelineTask>(
486
1.83M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.83M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.83M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.83M
                    instance_idx);
490
1.83M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.83M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.83M
            _tasks[instance_idx].emplace_back(
493
1.83M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.83M
                            std::move(task), std::move(task_runtime_state)});
495
1.83M
        }
496
2.25M
    }
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
2.25M
    for (auto& _pipeline : _pipelines) {
516
2.25M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.83M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.83M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.83M
            if (_dag.contains(_pipeline->id())) {
522
1.19M
                auto& deps = _dag[_pipeline->id()];
523
1.91M
                for (auto& dep : deps) {
524
1.91M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.07M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.07M
                        if (ss) {
527
432k
                            task->inject_shared_state(ss);
528
646k
                        } else {
529
646k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
646k
                                    task->get_source_shared_state());
531
646k
                        }
532
1.07M
                    }
533
1.91M
                }
534
1.19M
            }
535
1.83M
        }
536
2.25M
    }
537
3.33M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.25M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.83M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.83M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.83M
            std::vector<TScanRangeParams> scan_ranges;
542
1.83M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.83M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
282k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
282k
            }
546
1.83M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.83M
                                                             _params.fragment.output_sink));
548
1.83M
        }
549
2.25M
    }
550
1.07M
    {
551
1.07M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.07M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.07M
    }
554
1.07M
    return Status::OK();
555
1.07M
}
556
557
389k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
389k
    _total_tasks = 0;
559
389k
    _closed_tasks = 0;
560
389k
    const auto target_size = _params.local_params.size();
561
389k
    _tasks.resize(target_size);
562
389k
    _runtime_filter_mgr_map.resize(target_size);
563
1.00M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
619k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
619k
    }
566
389k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
389k
    if (target_size > 1 &&
569
389k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
128k
         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
12.2k
        std::vector<Status> prepare_status(target_size);
573
12.2k
        int submitted_tasks = 0;
574
12.2k
        Status submit_status;
575
12.2k
        CountDownLatch latch((int)target_size);
576
155k
        for (int i = 0; i < target_size; i++) {
577
143k
            submit_status = thread_pool->submit_func([&, i]() {
578
143k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
143k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
143k
                latch.count_down();
581
143k
            });
582
143k
            if (LIKELY(submit_status.ok())) {
583
143k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
143k
        }
588
12.2k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
12.2k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
155k
        for (int i = 0; i < submitted_tasks; i++) {
593
143k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
143k
        }
597
376k
    } else {
598
1.30M
        for (int i = 0; i < target_size; i++) {
599
930k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
930k
        }
601
376k
    }
602
389k
    _pipeline_parent_map.clear();
603
389k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
389k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
389k
    return Status::OK();
608
389k
}
609
610
387k
void PipelineFragmentContext::_init_next_report_time() {
611
387k
    auto interval_s = config::pipeline_status_report_interval;
612
387k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
36.6k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
36.6k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
36.6k
        _previous_report_time =
617
36.6k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
36.6k
        _disable_period_report = false;
619
36.6k
    }
620
387k
}
621
622
4.09k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.09k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.09k
    DCHECK(disable == true);
625
4.09k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.09k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.09k
}
628
629
6.58M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
6.58M
    if (!_is_report_success) {
631
6.18M
        return;
632
6.18M
    }
633
397k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
397k
    if (disable) {
635
7.18k
        return;
636
7.18k
    }
637
390k
    int32_t interval_s = config::pipeline_status_report_interval;
638
390k
    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
390k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
390k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
390k
    if (MonotonicNanos() > next_report_time) {
646
4.09k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.09k
                                                            std::memory_order_acq_rel)) {
648
5
            return;
649
5
        }
650
4.09k
        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
4.09k
        auto st = send_report(false);
667
4.09k
        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
4.09k
    }
673
390k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
387k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
387k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
387k
    int node_idx = 0;
682
683
387k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
387k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
387k
    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
387k
    return Status::OK();
691
387k
}
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
611k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
611k
    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
611k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
611k
    int num_children = tnodes[*node_idx].num_children;
706
611k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
611k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
611k
    OperatorPtr op = nullptr;
710
611k
    OperatorPtr cache_op = nullptr;
711
611k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
611k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
611k
                                     followed_by_shuffled_operator,
714
611k
                                     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
611k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
611k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
225k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
386k
    } else {
723
386k
        *root = op;
724
386k
    }
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
611k
    auto required_data_distribution =
737
611k
            cur_pipe->operators().empty()
738
611k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
611k
                    : op->required_data_distribution(_runtime_state.get());
740
611k
    current_followed_by_shuffled_operator =
741
611k
            ((followed_by_shuffled_operator ||
742
611k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
554k
                                             : op->is_shuffled_operator())) &&
744
611k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
611k
            (followed_by_shuffled_operator &&
746
502k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
611k
    current_require_bucket_distribution =
749
611k
            ((require_bucket_distribution ||
750
611k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
559k
                                             : op->is_colocated_operator())) &&
752
611k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
611k
            (require_bucket_distribution &&
754
509k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
611k
    if (num_children == 0) {
757
402k
        _use_serial_source = op->is_serial_operator();
758
402k
    }
759
    // rely on that tnodes is preorder of the plan
760
837k
    for (int i = 0; i < num_children; i++) {
761
225k
        ++*node_idx;
762
225k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
225k
                                            current_followed_by_shuffled_operator,
764
225k
                                            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
225k
        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
225k
    }
775
776
611k
    return Status::OK();
777
611k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
111k
        PipelinePtr pipe_with_sink) {
782
111k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
111k
    pipe_with_source->set_num_tasks(_num_instances);
784
111k
    pipe_with_source->set_data_distribution(data_distribution);
785
111k
}
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
111k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
111k
    auto& operators = cur_pipe->operators();
793
111k
    const auto downstream_pipeline_id = cur_pipe->id();
794
111k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
111k
    DataSinkOperatorPtr sink;
797
111k
    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
111k
    const bool followed_by_shuffled_operator =
804
111k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
111k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
111k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
111k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
111k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
111k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
111k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
111k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
111k
    if (bucket_seq_to_instance_idx.empty() &&
813
111k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
11
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
11
    }
816
111k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
111k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
111k
                                          num_buckets, use_global_hash_shuffle,
819
111k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
111k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
111k
            LocalExchangeSharedState::create_shared(_num_instances);
824
111k
    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
18.4E
                        : 0);
833
22.6k
        break;
834
540
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
540
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
540
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
540
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
540
                        ? cast_set<int>(
839
540
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
540
                        : 0);
841
540
        break;
842
85.2k
    case ExchangeType::PASSTHROUGH:
843
85.2k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
85.2k
                cur_pipe->num_tasks(), _num_instances,
845
85.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
85.2k
                        ? cast_set<int>(
847
85.2k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
85.2k
                        : 0);
849
85.2k
        break;
850
255
    case ExchangeType::BROADCAST:
851
255
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
255
                cur_pipe->num_tasks(), _num_instances,
853
255
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
255
                        ? cast_set<int>(
855
255
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
255
                        : 0);
857
255
        break;
858
2.19k
    case ExchangeType::PASS_TO_ONE:
859
2.19k
        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
1.36k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.36k
                    cur_pipe->num_tasks(), _num_instances,
863
1.36k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.36k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.36k
                                                    .local_exchange_free_blocks_limit)
866
1.36k
                            : 0);
867
1.36k
        } else {
868
833
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
833
                    cur_pipe->num_tasks(), _num_instances,
870
833
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
833
                            ? cast_set<int>(_runtime_state->query_options()
872
833
                                                    .local_exchange_free_blocks_limit)
873
833
                            : 0);
874
833
        }
875
2.19k
        break;
876
846
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
846
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
846
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
846
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
846
                        ? cast_set<int>(
881
846
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
846
                        : 0);
883
846
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
111k
    }
888
111k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
111k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
111k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
111k
    _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
111k
    std::copy(operators.begin(), operators.begin() + idx,
898
111k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
111k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
111k
    OperatorPtr source_op;
905
111k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
111k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
111k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
111k
    if (!operators.empty()) {
909
41.0k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
41.0k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
41.0k
    }
912
111k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
111k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
111k
    std::vector<PipelineId> edges_with_source;
917
128k
    for (auto child : cur_pipe->children()) {
918
128k
        bool found = false;
919
142k
        for (auto op : new_pip->operators()) {
920
142k
            if (child->sink()->node_id() == op->node_id()) {
921
12.2k
                new_pip->set_children(child);
922
12.2k
                found = true;
923
12.2k
            };
924
142k
        }
925
128k
        if (!found) {
926
116k
            new_children.push_back(child);
927
116k
            edges_with_source.push_back(child->id());
928
116k
        }
929
128k
    }
930
111k
    new_children.push_back(new_pip);
931
111k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
111k
    if (!new_pip->children().empty()) {
935
7.07k
        std::vector<PipelineId> edges_with_sink;
936
12.2k
        for (auto child : new_pip->children()) {
937
12.2k
            edges_with_sink.push_back(child->id());
938
12.2k
        }
939
7.07k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.07k
    }
941
111k
    cur_pipe->set_children(new_children);
942
111k
    _dag[downstream_pipeline_id] = edges_with_source;
943
111k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
111k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
111k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
111k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
111k
    return Status::OK();
950
111k
}
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
178k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
178k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
45.1k
        return Status::OK();
959
45.1k
    }
960
961
133k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
44.3k
        return Status::OK();
963
44.3k
    }
964
88.8k
    *do_local_exchange = true;
965
966
88.8k
    auto& operators = cur_pipe->operators();
967
88.8k
    auto total_op_num = operators.size();
968
88.8k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
88.8k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
88.8k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
88.8k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
18.4E
            << "total_op_num: " << total_op_num
975
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
88.9k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
88.8k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
22.8k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
22.8k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
22.8k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
22.8k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
22.8k
                shuffle_idx_to_instance_idx));
990
22.8k
    }
991
88.8k
    return Status::OK();
992
88.8k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
385k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
890k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
504k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
504k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
114k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
114k
                if (child->sink()->node_id() ==
1003
114k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
100k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
100k
                }
1006
114k
            }
1007
109k
        }
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
504k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
504k
                                             bucket_seq_to_instance_idx,
1014
504k
                                             shuffle_idx_to_instance_idx));
1015
504k
    }
1016
385k
    return Status::OK();
1017
385k
}
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
504k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
504k
    int idx = 1;
1024
504k
    bool do_local_exchange = false;
1025
545k
    do {
1026
545k
        auto& ops = pip->operators();
1027
545k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
616k
        for (; idx < ops.size();) {
1030
111k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
102k
                RETURN_IF_ERROR(_add_local_exchange(
1032
102k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
102k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
102k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
102k
                        shuffle_idx_to_instance_idx));
1036
102k
            }
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
41.1k
                idx = 2;
1043
41.1k
                break;
1044
41.1k
            }
1045
70.7k
            idx++;
1046
70.7k
        }
1047
545k
    } while (do_local_exchange);
1048
504k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
75.8k
        RETURN_IF_ERROR(_add_local_exchange(
1050
75.8k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
75.8k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
75.8k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
75.8k
    }
1054
504k
    return Status::OK();
1055
504k
}
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
389k
                                                  PipelineId cur_pipeline_id) {
1063
389k
    switch (thrift_sink.type) {
1064
133k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
133k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
133k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
133k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
133k
                params.destinations, _fragment_instance_ids);
1071
133k
        break;
1072
133k
    }
1073
220k
    case TDataSinkType::RESULT_SINK: {
1074
220k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
220k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
220k
        int child_node_id = pipeline->operators().back()->node_id();
1080
220k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
220k
                                                      row_desc, output_exprs,
1082
220k
                                                      thrift_sink.result_sink);
1083
220k
        break;
1084
220k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
31.2k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
31.2k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
31.2k
        int child_node_id = pipeline->operators().back()->node_id();
1098
31.2k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
31.2k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
31.2k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
1.46k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
1.46k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
29.8k
        } else {
1104
29.8k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
29.8k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
29.8k
        }
1107
31.2k
        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
734
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
734
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
734
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
734
                                                         output_exprs);
1123
734
        break;
1124
734
    }
1125
866
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
866
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
866
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
866
        } else {
1133
866
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
866
                                                                row_desc, output_exprs);
1135
866
        }
1136
866
        break;
1137
866
    }
1138
10
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
10
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
10
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
10
                                                             row_desc, output_exprs);
1144
10
        break;
1145
10
    }
1146
40
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
40
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
40
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
40
                                                            output_exprs);
1152
40
        break;
1153
40
    }
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
44
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
44
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
44
        if (config::enable_java_support) {
1167
44
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
44
                                                             output_exprs);
1169
44
        } 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
44
        break;
1175
44
    }
1176
44
    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
420
    case TDataSinkType::RESULT_FILE_SINK: {
1186
420
        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
420
        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
420
        } else {
1196
420
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
420
                                                              output_exprs);
1198
420
        }
1199
420
        break;
1200
420
    }
1201
1.58k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
1.58k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
1.58k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
1.58k
        auto sink_id = next_sink_operator_id();
1205
1.58k
        const int multi_cast_node_id = sink_id;
1206
1.58k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
1.58k
        std::vector<int> sources;
1209
6.14k
        for (int i = 0; i < sender_size; ++i) {
1210
4.55k
            auto source_id = next_operator_id();
1211
4.55k
            sources.push_back(source_id);
1212
4.55k
        }
1213
1214
1.58k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
1.58k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
6.14k
        for (int i = 0; i < sender_size; ++i) {
1217
4.55k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
4.55k
            RowDescriptor* exchange_row_desc = nullptr;
1220
4.55k
            {
1221
4.55k
                const auto& tmp_row_desc =
1222
4.55k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
4.55k
                                ? RowDescriptor(state->desc_tbl(),
1224
4.55k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
4.55k
                                                         .output_tuple_id})
1226
4.55k
                                : row_desc;
1227
4.55k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
4.55k
            }
1229
4.55k
            auto source_id = sources[i];
1230
4.55k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
4.55k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
4.55k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
4.55k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
4.55k
                    /*operator_id=*/source_id);
1236
4.55k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
4.55k
                    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
4.55k
            DataSinkOperatorPtr sink_op;
1241
4.55k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
4.55k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
4.55k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
4.55k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
4.55k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
4.55k
            {
1248
4.55k
                TDataSink* t = pool->add(new TDataSink());
1249
4.55k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
4.55k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
4.55k
            }
1252
1253
            // 3. set dependency dag
1254
4.55k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
4.55k
        }
1256
1.58k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
1.58k
        break;
1260
1.58k
    }
1261
1.58k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
8
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
8
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
8
        break;
1268
8
    }
1269
78
    case TDataSinkType::TVF_TABLE_SINK: {
1270
78
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
78
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
78
                                                        output_exprs);
1275
78
        break;
1276
78
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
389k
    }
1280
388k
    return Status::OK();
1281
389k
}
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
614k
                                                 OperatorPtr& cache_op) {
1292
614k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
614k
    Defer defer = Defer([&]() {
1294
614k
        if (op) {
1295
614k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
614k
        }
1297
613k
        for (auto& s : sink_ops) {
1298
113k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
113k
        }
1300
613k
    });
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
614k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
614k
    std::stringstream error_msg;
1305
614k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
614k
    bool fe_with_old_version = false;
1308
614k
    switch (tnode.node_type) {
1309
190k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
190k
        op = std::make_shared<OlapScanOperatorX>(
1311
190k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
190k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
190k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
190k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
190k
        break;
1316
190k
    }
1317
77
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
77
        DCHECK(_query_ctx != nullptr);
1319
77
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
77
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
77
                                                    _num_instances);
1322
77
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
77
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
77
        break;
1325
77
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
13.9k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
13.9k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
13.9k
                                                 _num_instances);
1342
13.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
13.9k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
13.9k
        break;
1345
13.9k
    }
1346
135k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
135k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
136k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
135k
        DCHECK_GT(num_senders, 0);
1351
135k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
135k
                                                       num_senders);
1353
135k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
135k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
135k
        break;
1356
135k
    }
1357
152k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
152k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
152k
            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
152k
        bool need_create_cache_op =
1364
152k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
152k
        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
152k
        const bool group_by_limit_opt =
1385
152k
                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
152k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
152k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
152k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
152k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
152k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
152k
        const bool can_use_distinct_streaming_agg =
1396
152k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
152k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
152k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
152k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
152k
        if (can_use_distinct_streaming_agg) {
1402
92.2k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
92.2k
            } else {
1413
92.2k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
92.2k
                                                                     tnode, descs);
1415
92.2k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
92.2k
            }
1417
92.2k
        } else if (is_streaming_agg) {
1418
2.32k
            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
2.32k
            } else {
1428
2.32k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
2.32k
                                                             descs);
1430
2.32k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
2.32k
            }
1432
58.1k
        } else {
1433
            // create new pipeline to add query cache operator
1434
58.1k
            PipelinePtr new_pipe;
1435
58.1k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
58.1k
            if (enable_spill) {
1441
283
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
283
                                                                     next_operator_id(), descs);
1443
57.8k
            } else {
1444
57.8k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
57.8k
            }
1446
58.1k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
58.1k
            } else {
1451
58.1k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
58.1k
            }
1453
1454
58.1k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
58.1k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
56.3k
                _dag.insert({downstream_pipeline_id, {}});
1457
56.3k
            }
1458
58.1k
            cur_pipe = add_pipeline(cur_pipe);
1459
58.1k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
58.1k
            if (enable_spill) {
1462
283
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
283
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
57.8k
            } else {
1465
57.8k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
57.8k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
57.8k
            }
1468
58.1k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
58.1k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
58.1k
        }
1471
152k
        break;
1472
152k
    }
1473
152k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
73
        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
73
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
73
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
73
        const auto downstream_pipeline_id = cur_pipe->id();
1486
73
        if (!_dag.contains(downstream_pipeline_id)) {
1487
73
            _dag.insert({downstream_pipeline_id, {}});
1488
73
        }
1489
73
        cur_pipe = add_pipeline(cur_pipe);
1490
73
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
73
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
73
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
73
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
73
        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
73
        {
1503
73
            auto shared_state = BucketedAggSharedState::create_shared();
1504
73
            shared_state->id = op->operator_id();
1505
73
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
502
            for (int i = 0; i < _num_instances; i++) {
1508
429
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
429
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
429
                sink_dep->set_shared_state(shared_state.get());
1511
429
                shared_state->sink_deps.push_back(sink_dep);
1512
429
            }
1513
73
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
73
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
73
            _op_id_to_shared_state.insert(
1516
73
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
73
        }
1518
73
        break;
1519
73
    }
1520
9.25k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.25k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.25k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.25k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.25k
        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
9.25k
        } else {
1566
9.25k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.25k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.25k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.25k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.53k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.53k
            }
1573
9.25k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.25k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.25k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.25k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.25k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.25k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.25k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.25k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.25k
        }
1584
9.25k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
4.61k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
4.61k
                    HashJoinSharedState::create_shared(_num_instances);
1587
21.7k
            for (int i = 0; i < _num_instances; i++) {
1588
17.1k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
17.1k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
17.1k
                sink_dep->set_shared_state(shared_state.get());
1591
17.1k
                shared_state->sink_deps.push_back(sink_dep);
1592
17.1k
            }
1593
4.61k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
4.61k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
4.61k
            _op_id_to_shared_state.insert(
1596
4.61k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
4.61k
        }
1598
9.25k
        break;
1599
9.25k
    }
1600
4.10k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
4.10k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
4.10k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
4.10k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
4.10k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
3.87k
            _dag.insert({downstream_pipeline_id, {}});
1607
3.87k
        }
1608
4.10k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
4.10k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
4.10k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
4.10k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
4.10k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
4.10k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
4.10k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
4.10k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
4.10k
        break;
1618
4.10k
    }
1619
51.7k
    case TPlanNodeType::UNION_NODE: {
1620
51.7k
        int child_count = tnode.num_children;
1621
51.7k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
51.7k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
51.7k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
51.7k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
51.4k
            _dag.insert({downstream_pipeline_id, {}});
1627
51.4k
        }
1628
52.9k
        for (int i = 0; i < child_count; i++) {
1629
1.21k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.21k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.21k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.21k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.21k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.21k
            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
1.21k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.21k
        }
1638
51.7k
        break;
1639
51.7k
    }
1640
51.7k
    case TPlanNodeType::SORT_NODE: {
1641
39.0k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
39.0k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
39.0k
        const bool use_local_merge =
1644
39.0k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
39.0k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
38.9k
        } else if (use_local_merge) {
1648
36.9k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
36.9k
                                                                 descs);
1650
36.9k
        } else {
1651
2.05k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.05k
        }
1653
39.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
39.0k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
39.0k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
38.9k
            _dag.insert({downstream_pipeline_id, {}});
1658
38.9k
        }
1659
39.0k
        cur_pipe = add_pipeline(cur_pipe);
1660
39.0k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
39.0k
        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
38.9k
        } else {
1666
38.9k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
38.9k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
38.9k
        }
1669
39.0k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
39.0k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
39.0k
        break;
1672
39.0k
    }
1673
39.0k
    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
1.56k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.56k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.56k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.56k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.56k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.54k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.54k
        }
1698
1.56k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.56k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.56k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.56k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.56k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.56k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.56k
        break;
1706
1.56k
    }
1707
1.56k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.12k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.12k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.12k
        break;
1711
1.12k
    }
1712
1.12k
    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
912
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
912
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
912
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
912
        break;
1731
912
    }
1732
912
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
118
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
118
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
118
        break;
1736
118
    }
1737
1.57k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.57k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.57k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.57k
        break;
1741
1.57k
    }
1742
1.57k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
369
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
369
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
369
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
369
        break;
1747
369
    }
1748
1.80k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.80k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.80k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.80k
        break;
1752
1.80k
    }
1753
6.42k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.42k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.42k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.42k
        break;
1757
6.42k
    }
1758
6.42k
    case TPlanNodeType::SELECT_NODE: {
1759
1.57k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
1.57k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
1.57k
        break;
1762
1.57k
    }
1763
1.57k
    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
614k
    }
1803
612k
    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
612k
    return Status::OK();
1809
614k
}
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
386k
Status PipelineFragmentContext::submit() {
1846
386k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
386k
    _submitted = true;
1850
1851
386k
    int submit_tasks = 0;
1852
386k
    Status st;
1853
386k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.07M
    for (auto& task : _tasks) {
1855
1.84M
        for (auto& t : task) {
1856
1.84M
            st = scheduler->submit(t.first);
1857
1.84M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.84M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.84M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
1.84M
            submit_tasks++;
1866
1.84M
        }
1867
1.07M
    }
1868
386k
    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
386k
    } else {
1883
386k
        return st;
1884
386k
    }
1885
386k
}
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
389k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
389k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
389k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
389k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
389k
    if (!_need_notify_close) {
1919
385k
        auto st = send_report(true);
1920
385k
        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
385k
    }
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
389k
    if (_runtime_state->enable_profile() &&
1931
389k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
1.94k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
1.94k
         _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
389k
    if (_query_ctx->enable_profile()) {
1953
1.94k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
1.94k
                                         collect_realtime_load_channel_profile());
1955
1.94k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
389k
    return !_need_notify_close;
1960
389k
}
1961
1962
1.83M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
1.83M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.83M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
619k
        if (_dag.contains(pipeline_id)) {
1967
342k
            for (auto dep : _dag[pipeline_id]) {
1968
342k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
342k
            }
1970
272k
        }
1971
619k
    }
1972
1.83M
    bool need_remove = false;
1973
1.83M
    {
1974
1.83M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.83M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.83M
        _query_ctx->inc_finished_task_num();
1978
1.83M
        if (_closed_tasks >= _total_tasks) {
1979
389k
            need_remove = _close_fragment_instance();
1980
389k
        }
1981
1.83M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.83M
    if (need_remove) {
1984
385k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
385k
    }
1986
1.83M
}
1987
1988
47.9k
std::string PipelineFragmentContext::get_load_error_url() {
1989
47.9k
    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
118k
    for (auto& tasks : _tasks) {
1993
188k
        for (auto& task : tasks) {
1994
188k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
169
                return to_load_error_http_path(str);
1996
169
            }
1997
188k
        }
1998
118k
    }
1999
47.7k
    return "";
2000
47.9k
}
2001
2002
47.9k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
47.9k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
118k
    for (auto& tasks : _tasks) {
2007
188k
        for (auto& task : tasks) {
2008
188k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
169
                return str;
2010
169
            }
2011
188k
        }
2012
118k
    }
2013
47.7k
    return "";
2014
47.9k
}
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
42.1k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
42.1k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
42.1k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
42.1k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
42.1k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
42.1k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
42.1k
    });
2031
2032
42.1k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
42.1k
    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
42.1k
    int callback_retries = 10;
2038
42.1k
    const int sleep_ms = 1000;
2039
42.1k
    Status exec_status = req.status;
2040
42.1k
    Status coord_status;
2041
42.1k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
42.1k
    do {
2043
42.1k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
42.1k
                                                            req.coord_addr, &coord_status);
2045
42.1k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
42.1k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
42.1k
    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
42.1k
    TReportExecStatusParams params;
2059
42.1k
    params.protocol_version = FrontendServiceVersion::V1;
2060
42.1k
    params.__set_query_id(req.query_id);
2061
42.1k
    params.__set_backend_num(req.backend_num);
2062
42.1k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
42.1k
    params.__set_fragment_id(req.fragment_id);
2064
42.1k
    params.__set_status(exec_status.to_thrift());
2065
42.1k
    params.__set_done(req.done);
2066
42.1k
    params.__set_query_type(req.runtime_state->query_type());
2067
42.1k
    params.__isset.profile = false;
2068
2069
42.1k
    DCHECK(req.runtime_state != nullptr);
2070
2071
42.1k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
38.4k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
38.4k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
38.4k
    } else {
2075
3.77k
        DCHECK(!req.runtime_states.empty());
2076
3.77k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
3.77k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
3.77k
    }
2086
2087
42.1k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
42.1k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
42.1k
    static std::string s_unselected_rows = "unselected.rows";
2090
42.1k
    int64_t num_rows_load_success = 0;
2091
42.1k
    int64_t num_rows_load_filtered = 0;
2092
42.1k
    int64_t num_rows_load_unselected = 0;
2093
42.1k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
42.1k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
42.1k
        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
42.1k
    } else if (!req.runtime_states.empty()) {
2109
128k
        for (auto* rs : req.runtime_states) {
2110
128k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
128k
                rs->num_finished_range() > 0) {
2112
33.4k
                params.__isset.load_counters = true;
2113
33.4k
                num_rows_load_success += rs->num_rows_load_success();
2114
33.4k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
33.4k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
33.4k
                params.__isset.fragment_instance_reports = true;
2117
33.4k
                TFragmentInstanceReport t;
2118
33.4k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
33.4k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
33.4k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
33.4k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
33.4k
                params.fragment_instance_reports.push_back(t);
2123
33.4k
            }
2124
128k
        }
2125
42.1k
    }
2126
42.1k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
42.1k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
42.1k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
42.1k
    if (!req.load_error_url.empty()) {
2131
154
        params.__set_tracking_url(req.load_error_url);
2132
154
    }
2133
42.1k
    if (!req.first_error_msg.empty()) {
2134
154
        params.__set_first_error_msg(req.first_error_msg);
2135
154
    }
2136
128k
    for (auto* rs : req.runtime_states) {
2137
128k
        if (rs->wal_id() > 0) {
2138
114
            params.__set_txn_id(rs->wal_id());
2139
114
            params.__set_label(rs->import_label());
2140
114
        }
2141
128k
    }
2142
42.1k
    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
42.1k
    } else if (!req.runtime_states.empty()) {
2146
128k
        for (auto* rs : req.runtime_states) {
2147
128k
            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
128k
        }
2154
42.1k
    }
2155
42.1k
    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
42.1k
    } else if (!req.runtime_states.empty()) {
2159
128k
        for (auto* rs : req.runtime_states) {
2160
128k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
26.3k
                params.__isset.commitInfos = true;
2162
26.3k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
26.3k
            }
2164
128k
        }
2165
42.1k
    }
2166
42.1k
    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
42.1k
    } else if (!req.runtime_states.empty()) {
2170
128k
        for (auto* rs : req.runtime_states) {
2171
128k
            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
128k
        }
2177
42.1k
    }
2178
42.1k
    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
42.1k
    } else if (!req.runtime_states.empty()) {
2183
128k
        for (auto* rs : req.runtime_states) {
2184
128k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
1.03k
                params.__isset.hive_partition_updates = true;
2186
1.03k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
1.03k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
1.03k
            }
2189
128k
        }
2190
42.1k
    }
2191
42.1k
    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
42.1k
    } else if (!req.runtime_states.empty()) {
2196
128k
        for (auto* rs : req.runtime_states) {
2197
128k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
1.03k
                params.__isset.iceberg_commit_datas = true;
2199
1.03k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
1.03k
                                                   rs_icd.begin(), rs_icd.end());
2201
1.03k
            }
2202
128k
        }
2203
42.1k
    }
2204
2205
42.1k
    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
42.1k
    } else if (!req.runtime_states.empty()) {
2209
128k
        for (auto* rs : req.runtime_states) {
2210
128k
            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
128k
        }
2216
42.1k
    }
2217
2218
42.1k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
42.1k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
42.1k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
42.1k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
42.1k
    }
2224
2225
42.1k
    TReportExecStatusResult res;
2226
42.1k
    Status rpc_status;
2227
2228
42.1k
    VLOG_DEBUG << "reportExecStatus params is "
2229
5
               << apache::thrift::ThriftDebugString(params).c_str();
2230
42.1k
    if (!exec_status.ok()) {
2231
1.62k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.62k
                     << " to coordinator: " << req.coord_addr
2233
1.62k
                     << ", query id: " << print_id(req.query_id);
2234
1.62k
    }
2235
42.1k
    try {
2236
42.1k
        try {
2237
42.1k
            (*coord)->reportExecStatus(res, params);
2238
42.1k
        } 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
42.1k
        rpc_status = Status::create<false>(res.status);
2254
42.1k
    } 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
42.1k
    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
42.1k
}
2265
2266
390k
Status PipelineFragmentContext::send_report(bool done) {
2267
390k
    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
390k
    if (!_is_report_success && done && exec_status.ok()) {
2273
347k
        return Status::OK();
2274
347k
    }
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
42.3k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
197
        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
197
            return Status::OK();
2286
197
        }
2287
0
        return Status::NeedSendAgain("");
2288
197
    }
2289
2290
42.1k
    std::vector<RuntimeState*> runtime_states;
2291
2292
90.6k
    for (auto& tasks : _tasks) {
2293
128k
        for (auto& task : tasks) {
2294
128k
            runtime_states.push_back(task.second.get());
2295
128k
        }
2296
90.6k
    }
2297
2298
42.1k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
42.1k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
42.1k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
42.1k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
42.1k
    ReportStatusRequest req {.status = exec_status,
2306
42.1k
                             .runtime_states = runtime_states,
2307
42.1k
                             .done = done || !exec_status.ok(),
2308
42.1k
                             .coord_addr = _query_ctx->coord_addr,
2309
42.1k
                             .query_id = _query_id,
2310
42.1k
                             .fragment_id = _fragment_id,
2311
42.1k
                             .fragment_instance_id = TUniqueId(),
2312
42.1k
                             .backend_num = -1,
2313
42.1k
                             .runtime_state = _runtime_state.get(),
2314
42.1k
                             .load_error_url = load_eror_url,
2315
42.1k
                             .first_error_msg = first_error_msg,
2316
42.1k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
42.1k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
42.1k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
42.1k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
42.1k
        _coordinator_callback(req);
2321
42.1k
        if (!req.done) {
2322
4.09k
            ctx->refresh_next_report_time();
2323
4.09k
        }
2324
42.1k
    });
2325
42.3k
}
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
203
std::string PipelineFragmentContext::debug_string() {
2365
203
    std::lock_guard<std::mutex> l(_task_mutex);
2366
203
    fmt::memory_buffer debug_string_buffer;
2367
203
    fmt::format_to(debug_string_buffer,
2368
203
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
203
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
203
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
1.07k
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
872
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
1.87k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
1.00k
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
1.00k
                           _tasks[j][i].first->debug_string());
2376
1.00k
        }
2377
872
    }
2378
2379
203
    return fmt::to_string(debug_string_buffer);
2380
203
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
1.94k
PipelineFragmentContext::collect_realtime_profile() const {
2384
1.94k
    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
1.94k
    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
1.94k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
1.94k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
1.94k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
3.61k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
3.61k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
3.61k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
3.61k
        res.push_back(profile_ptr);
2407
3.61k
    }
2408
2409
1.94k
    return res;
2410
1.94k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
1.94k
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
1.94k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
7.32k
    for (const auto& tasks : _tasks) {
2426
14.7k
        for (const auto& task : tasks) {
2427
14.7k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
14.7k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
14.7k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
14.7k
                                                           _runtime_state->profile_level());
2435
14.7k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
14.7k
        }
2437
7.32k
    }
2438
2439
1.94k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
1.94k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
1.94k
                                                      _runtime_state->profile_level());
2442
1.94k
    return load_channel_profile;
2443
1.94k
}
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
4.60k
    for (const auto& _task : _tasks) {
2455
7.65k
        for (const auto& task : _task) {
2456
7.65k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
7.65k
            result.merge(set);
2458
7.65k
        }
2459
4.60k
    }
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
390k
void PipelineFragmentContext::_release_resource() {
2468
390k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
390k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
390k
    auto st = _query_ctx->exec_status();
2472
1.07M
    for (auto& _task : _tasks) {
2473
1.07M
        if (!_task.empty()) {
2474
1.07M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.07M
        }
2476
1.07M
    }
2477
390k
    _tasks.clear();
2478
390k
    _dag.clear();
2479
390k
    _pip_id_to_pipeline.clear();
2480
390k
    _pipelines.clear();
2481
390k
    _sink.reset();
2482
390k
    _root_op.reset();
2483
390k
    _runtime_filter_mgr_map.clear();
2484
390k
    _op_id_to_shared_state.clear();
2485
390k
}
2486
2487
} // namespace doris