Coverage Report

Created: 2026-06-22 17:38

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
114
#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
132
#include "util/client_cache.h"
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#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
386k
        : _query_id(std::move(query_id)),
144
386k
          _fragment_id(request.fragment_id),
145
386k
          _exec_env(exec_env),
146
386k
          _query_ctx(std::move(query_ctx)),
147
386k
          _call_back(call_back),
148
386k
          _is_report_on_cancel(true),
149
386k
          _params(request),
150
386k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
386k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
386k
                                                               : false) {
153
386k
    _fragment_watcher.start();
154
386k
}
155
156
386k
PipelineFragmentContext::~PipelineFragmentContext() {
157
386k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
386k
            .tag("query_id", print_id(_query_id))
159
386k
            .tag("fragment_id", _fragment_id);
160
386k
    _release_resource();
161
386k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
386k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
386k
        _runtime_state.reset();
165
386k
        _query_ctx.reset();
166
386k
    }
167
386k
}
168
169
58
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
58
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
58
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
58
}
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
9.26k
bool PipelineFragmentContext::notify_close() {
181
9.26k
    bool all_closed = false;
182
9.26k
    bool need_remove = false;
183
9.26k
    {
184
9.26k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.26k
        if (_closed_tasks >= _total_tasks) {
186
3.44k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
192
3.40k
                need_remove = true;
193
3.40k
            }
194
3.44k
            all_closed = true;
195
3.44k
        }
196
        // make fragment release by self after cancel
197
9.26k
        _need_notify_close = false;
198
9.26k
    }
199
9.26k
    if (need_remove) {
200
3.40k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.40k
    }
202
9.26k
    return all_closed;
203
9.26k
}
204
205
// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
5.79k
void PipelineFragmentContext::cancel(const Status reason) {
210
5.79k
    LOG_INFO("PipelineFragmentContext::cancel")
211
5.79k
            .tag("query_id", print_id(_query_id))
212
5.79k
            .tag("fragment_id", _fragment_id)
213
5.79k
            .tag("reason", reason.to_string());
214
5.79k
    if (notify_close()) {
215
56
        return;
216
56
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
5.73k
    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
5.73k
    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
5.73k
    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
5.73k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
25
        _query_ctx->set_load_error_url(error_url);
236
25
    }
237
238
5.73k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
25
        _query_ctx->set_first_error_msg(first_error_msg);
240
25
    }
241
242
5.73k
    _query_ctx->cancel(reason, _fragment_id);
243
5.73k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
219
        _is_report_on_cancel = false;
245
5.51k
    } else {
246
27.0k
        for (auto& id : _fragment_instance_ids) {
247
27.0k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
27.0k
        }
249
5.51k
    }
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
5.73k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
5.73k
    if (stream_load_ctx != nullptr) {
254
33
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
33
        stream_load_ctx->error_url = get_load_error_url();
259
33
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
33
    }
261
262
27.6k
    for (auto& tasks : _tasks) {
263
61.8k
        for (auto& task : tasks) {
264
61.8k
            task.first->unblock_all_dependencies();
265
61.8k
        }
266
27.6k
    }
267
5.73k
}
268
269
604k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
604k
    PipelineId id = _next_pipeline_id++;
271
604k
    auto pipeline = std::make_shared<Pipeline>(
272
604k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
604k
            parent ? parent->num_tasks() : _num_instances);
274
604k
    if (idx >= 0) {
275
117k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
487k
    } else {
277
487k
        _pipelines.emplace_back(pipeline);
278
487k
    }
279
604k
    if (parent) {
280
214k
        parent->set_children(pipeline);
281
214k
    }
282
604k
    return pipeline;
283
604k
}
284
285
385k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
385k
    {
287
385k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
385k
        auto root_pipeline = add_pipeline();
290
385k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
385k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
385k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
385k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
385k
                                          _params.fragment.output_exprs, _params,
299
385k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
385k
                                          *_desc_tbl, root_pipeline->id()));
301
385k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
385k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
486k
        for (PipelinePtr& pipeline : _pipelines) {
305
486k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
486k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
486k
        }
308
385k
    }
309
    // 4. Build local exchanger
310
385k
    if (_runtime_state->enable_local_shuffle()) {
311
382k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
382k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
382k
                                             _params.bucket_seq_to_instance_idx,
314
382k
                                             _params.shuffle_idx_to_instance_idx));
315
382k
    }
316
317
    // 5. Initialize global states in pipelines.
318
605k
    for (PipelinePtr& pipeline : _pipelines) {
319
605k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
605k
        pipeline->children().clear();
321
605k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
605k
    }
323
324
384k
    {
325
384k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
384k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
384k
    }
329
330
384k
    return Status::OK();
331
384k
}
332
333
386k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
386k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
386k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
386k
        _timeout = _params.query_options.execution_timeout;
339
386k
    }
340
341
386k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
386k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
386k
    SCOPED_TIMER(_prepare_timer);
344
386k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
386k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
386k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
386k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
386k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
386k
    {
350
386k
        SCOPED_TIMER(_init_context_timer);
351
386k
        cast_set(_num_instances, _params.local_params.size());
352
386k
        _total_instances =
353
386k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
386k
        auto* fragment_context = this;
356
357
386k
        if (_params.query_options.__isset.is_report_success) {
358
384k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
384k
        }
360
361
        // 1. Set up the global runtime state.
362
386k
        _runtime_state = RuntimeState::create_unique(
363
386k
                _params.query_id, _params.fragment_id, _params.query_options,
364
386k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
386k
        _runtime_state->set_task_execution_context(shared_from_this());
366
386k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
386k
        if (_params.__isset.backend_id) {
368
382k
            _runtime_state->set_backend_id(_params.backend_id);
369
382k
        }
370
386k
        if (_params.__isset.import_label) {
371
235
            _runtime_state->set_import_label(_params.import_label);
372
235
        }
373
386k
        if (_params.__isset.db_name) {
374
187
            _runtime_state->set_db_name(_params.db_name);
375
187
        }
376
386k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
386k
        if (_params.is_simplified_param) {
381
130k
            _desc_tbl = _query_ctx->desc_tbl;
382
255k
        } else {
383
255k
            DCHECK(_params.__isset.desc_tbl);
384
255k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
255k
                                                  &_desc_tbl));
386
255k
        }
387
386k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
386k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
386k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
386k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
386k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
386k
        const auto target_size = _params.local_params.size();
395
386k
        _fragment_instance_ids.resize(target_size);
396
1.46M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.08M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.08M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.08M
        }
400
386k
    }
401
402
386k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
385k
    _init_next_report_time();
405
406
385k
    _prepared = true;
407
385k
    return Status::OK();
408
386k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.08M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.08M
    const auto& local_params = _params.local_params[instance_idx];
414
1.08M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.08M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.08M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.08M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.08M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.81M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.81M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.81M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.81M
                shared_state_map;
423
2.35M
        for (auto& op : pipeline->operators()) {
424
2.35M
            auto source_id = op->operator_id();
425
2.35M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.35M
                iter != _op_id_to_shared_state.end()) {
427
761k
                shared_state_map.insert({source_id, iter->second});
428
761k
            }
429
2.35M
        }
430
1.81M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.81M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.81M
                iter != _op_id_to_shared_state.end()) {
433
332k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
332k
            }
435
1.81M
        }
436
1.81M
        return shared_state_map;
437
1.81M
    };
438
439
3.31M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.23M
        auto& pipeline = _pipelines[pip_idx];
441
2.23M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.80M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.80M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.80M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.80M
            {
446
                // Initialize runtime state for this task
447
1.80M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.80M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.80M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.80M
                if (_params.__isset.backend_id) {
453
1.80M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.80M
                }
455
1.80M
                if (_params.__isset.import_label) {
456
236
                    task_runtime_state->set_import_label(_params.import_label);
457
236
                }
458
1.80M
                if (_params.__isset.db_name) {
459
188
                    task_runtime_state->set_db_name(_params.db_name);
460
188
                }
461
1.80M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.80M
                if (_params.__isset.wal_id) {
465
112
                    task_runtime_state->set_wal_id(_params.wal_id);
466
112
                }
467
1.80M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.80M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.80M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.80M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.80M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.80M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.80M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.80M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.80M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.80M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.80M
            }
482
1.80M
            auto cur_task_id = _total_tasks++;
483
1.80M
            task_runtime_state->set_task_id(cur_task_id);
484
1.80M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.80M
            auto task = std::make_shared<PipelineTask>(
486
1.80M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.80M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.80M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.80M
                    instance_idx);
490
1.80M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.80M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.80M
            _tasks[instance_idx].emplace_back(
493
1.80M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.80M
                            std::move(task), std::move(task_runtime_state)});
495
1.80M
        }
496
2.23M
    }
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
2.23M
    for (auto& _pipeline : _pipelines) {
516
2.23M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.80M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.80M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.80M
            if (_dag.contains(_pipeline->id())) {
522
1.16M
                auto& deps = _dag[_pipeline->id()];
523
1.89M
                for (auto& dep : deps) {
524
1.89M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.04M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.04M
                        if (ss) {
527
383k
                            task->inject_shared_state(ss);
528
660k
                        } else {
529
660k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
660k
                                    task->get_source_shared_state());
531
660k
                        }
532
1.04M
                    }
533
1.89M
                }
534
1.16M
            }
535
1.80M
        }
536
2.23M
    }
537
3.32M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.23M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.80M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.80M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.80M
            std::vector<TScanRangeParams> scan_ranges;
542
1.80M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.80M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
284k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
284k
            }
546
1.80M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.80M
                                                             _params.fragment.output_sink));
548
1.80M
        }
549
2.23M
    }
550
1.08M
    {
551
1.08M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.08M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.08M
    }
554
1.08M
    return Status::OK();
555
1.08M
}
556
557
385k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
385k
    _total_tasks = 0;
559
385k
    _closed_tasks = 0;
560
385k
    const auto target_size = _params.local_params.size();
561
385k
    _tasks.resize(target_size);
562
385k
    _runtime_filter_mgr_map.resize(target_size);
563
989k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
603k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
603k
    }
566
385k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
385k
    if (target_size > 1 &&
569
385k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
132k
         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
23.8k
        std::vector<Status> prepare_status(target_size);
573
23.8k
        int submitted_tasks = 0;
574
23.8k
        Status submit_status;
575
23.8k
        CountDownLatch latch((int)target_size);
576
286k
        for (int i = 0; i < target_size; i++) {
577
262k
            submit_status = thread_pool->submit_func([&, i]() {
578
262k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
262k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
262k
                latch.count_down();
581
262k
            });
582
262k
            if (LIKELY(submit_status.ok())) {
583
262k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
262k
        }
588
23.8k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
23.8k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
286k
        for (int i = 0; i < submitted_tasks; i++) {
593
262k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
262k
        }
597
361k
    } else {
598
1.18M
        for (int i = 0; i < target_size; i++) {
599
823k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
823k
        }
601
361k
    }
602
385k
    _pipeline_parent_map.clear();
603
385k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
385k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
385k
    return Status::OK();
608
385k
}
609
610
384k
void PipelineFragmentContext::_init_next_report_time() {
611
384k
    auto interval_s = config::pipeline_status_report_interval;
612
384k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
37.2k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
37.2k
        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
37.2k
        _previous_report_time =
617
37.2k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
37.2k
        _disable_period_report = false;
619
37.2k
    }
620
384k
}
621
622
4.39k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.39k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.39k
    DCHECK(disable == true);
625
4.39k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.39k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.39k
}
628
629
6.46M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
6.46M
    if (!_is_report_success) {
631
6.08M
        return;
632
6.08M
    }
633
383k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
383k
    if (disable) {
635
6.64k
        return;
636
6.64k
    }
637
377k
    int32_t interval_s = config::pipeline_status_report_interval;
638
377k
    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
377k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
377k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
377k
    if (MonotonicNanos() > next_report_time) {
646
4.40k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.40k
                                                            std::memory_order_acq_rel)) {
648
15
            return;
649
15
        }
650
4.39k
        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
4.39k
        auto st = send_report(false);
667
4.39k
        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
4.39k
    }
673
377k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
383k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
383k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
383k
    int node_idx = 0;
682
683
383k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
383k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
383k
    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
383k
    return Status::OK();
691
383k
}
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
582k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
582k
    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
582k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
582k
    int num_children = tnodes[*node_idx].num_children;
706
582k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
582k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
582k
    OperatorPtr op = nullptr;
710
582k
    OperatorPtr cache_op = nullptr;
711
582k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
582k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
582k
                                     followed_by_shuffled_operator,
714
582k
                                     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
582k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
582k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
199k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
383k
    } else {
723
383k
        *root = op;
724
383k
    }
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
582k
    auto required_data_distribution =
737
582k
            cur_pipe->operators().empty()
738
582k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
582k
                    : op->required_data_distribution(_runtime_state.get());
740
582k
    current_followed_by_shuffled_operator =
741
582k
            ((followed_by_shuffled_operator ||
742
582k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
524k
                                             : op->is_shuffled_operator())) &&
744
582k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
582k
            (followed_by_shuffled_operator &&
746
472k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
582k
    current_require_bucket_distribution =
749
582k
            ((require_bucket_distribution ||
750
582k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
529k
                                             : op->is_colocated_operator())) &&
752
582k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
582k
            (require_bucket_distribution &&
754
479k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
582k
    if (num_children == 0) {
757
399k
        _use_serial_source = op->is_serial_operator();
758
399k
    }
759
    // rely on that tnodes is preorder of the plan
760
781k
    for (int i = 0; i < num_children; i++) {
761
199k
        ++*node_idx;
762
199k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
199k
                                            current_followed_by_shuffled_operator,
764
199k
                                            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
199k
        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
199k
    }
775
776
582k
    return Status::OK();
777
582k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
117k
        PipelinePtr pipe_with_sink) {
782
117k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
117k
    pipe_with_source->set_num_tasks(_num_instances);
784
117k
    pipe_with_source->set_data_distribution(data_distribution);
785
117k
}
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
117k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
117k
    auto& operators = cur_pipe->operators();
793
117k
    const auto downstream_pipeline_id = cur_pipe->id();
794
117k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
117k
    DataSinkOperatorPtr sink;
797
117k
    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
117k
    const bool followed_by_shuffled_operator =
804
117k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
117k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
117k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
117k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
117k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
117k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
117k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
117k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
117k
    if (bucket_seq_to_instance_idx.empty() &&
813
117k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
10
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
10
    }
816
117k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
117k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
117k
                                          num_buckets, use_global_hash_shuffle,
819
117k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
117k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
117k
            LocalExchangeSharedState::create_shared(_num_instances);
824
117k
    switch (data_distribution.distribution_type) {
825
25.2k
    case ExchangeType::HASH_SHUFFLE:
826
25.2k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
25.2k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
25.2k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
25.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
25.2k
                        ? cast_set<int>(
831
25.2k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
18.4E
                        : 0);
833
25.2k
        break;
834
722
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
722
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
722
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
722
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
722
                        ? cast_set<int>(
839
722
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
722
                        : 0);
841
722
        break;
842
87.2k
    case ExchangeType::PASSTHROUGH:
843
87.2k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
87.2k
                cur_pipe->num_tasks(), _num_instances,
845
87.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
87.2k
                        ? cast_set<int>(
847
87.1k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
87.2k
                        : 0);
849
87.2k
        break;
850
449
    case ExchangeType::BROADCAST:
851
449
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
449
                cur_pipe->num_tasks(), _num_instances,
853
449
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
449
                        ? cast_set<int>(
855
449
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
449
                        : 0);
857
449
        break;
858
2.60k
    case ExchangeType::PASS_TO_ONE:
859
2.60k
        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
1.37k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.37k
                    cur_pipe->num_tasks(), _num_instances,
863
1.37k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.37k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.37k
                                                    .local_exchange_free_blocks_limit)
866
1.37k
                            : 0);
867
1.37k
        } else {
868
1.22k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.22k
                    cur_pipe->num_tasks(), _num_instances,
870
1.22k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.22k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.22k
                                                    .local_exchange_free_blocks_limit)
873
1.22k
                            : 0);
874
1.22k
        }
875
2.60k
        break;
876
917
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
917
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
917
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
917
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
917
                        ? cast_set<int>(
881
917
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
917
                        : 0);
883
917
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
117k
    }
888
117k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
117k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
117k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
117k
    _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
117k
    std::copy(operators.begin(), operators.begin() + idx,
898
117k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
117k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
117k
    OperatorPtr source_op;
905
117k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
117k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
117k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
117k
    if (!operators.empty()) {
909
43.4k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
43.4k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
43.4k
    }
912
117k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
117k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
117k
    std::vector<PipelineId> edges_with_source;
917
135k
    for (auto child : cur_pipe->children()) {
918
135k
        bool found = false;
919
150k
        for (auto op : new_pip->operators()) {
920
150k
            if (child->sink()->node_id() == op->node_id()) {
921
13.0k
                new_pip->set_children(child);
922
13.0k
                found = true;
923
13.0k
            };
924
150k
        }
925
135k
        if (!found) {
926
122k
            new_children.push_back(child);
927
122k
            edges_with_source.push_back(child->id());
928
122k
        }
929
135k
    }
930
117k
    new_children.push_back(new_pip);
931
117k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
117k
    if (!new_pip->children().empty()) {
935
7.26k
        std::vector<PipelineId> edges_with_sink;
936
13.0k
        for (auto child : new_pip->children()) {
937
13.0k
            edges_with_sink.push_back(child->id());
938
13.0k
        }
939
7.26k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.26k
    }
941
117k
    cur_pipe->set_children(new_children);
942
117k
    _dag[downstream_pipeline_id] = edges_with_source;
943
117k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
117k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
117k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
117k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
117k
    return Status::OK();
950
117k
}
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
172k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
172k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
35.4k
        return Status::OK();
959
35.4k
    }
960
961
137k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
45.8k
        return Status::OK();
963
45.8k
    }
964
91.3k
    *do_local_exchange = true;
965
966
91.3k
    auto& operators = cur_pipe->operators();
967
91.3k
    auto total_op_num = operators.size();
968
91.3k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
91.3k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
91.3k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
91.3k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
18.4E
            << "total_op_num: " << total_op_num
975
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
91.4k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
91.3k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
25.6k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
25.6k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
25.6k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
25.6k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
25.6k
                shuffle_idx_to_instance_idx));
990
25.6k
    }
991
91.3k
    return Status::OK();
992
91.3k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
381k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
865k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
483k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
483k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
97.1k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
97.1k
                if (child->sink()->node_id() ==
1003
97.1k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
84.1k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
84.1k
                }
1006
97.1k
            }
1007
92.5k
        }
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
483k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
483k
                                             bucket_seq_to_instance_idx,
1014
483k
                                             shuffle_idx_to_instance_idx));
1015
483k
    }
1016
381k
    return Status::OK();
1017
381k
}
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
483k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
483k
    int idx = 1;
1024
483k
    bool do_local_exchange = false;
1025
526k
    do {
1026
526k
        auto& ops = pip->operators();
1027
526k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
585k
        for (; idx < ops.size();) {
1030
102k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
95.7k
                RETURN_IF_ERROR(_add_local_exchange(
1032
95.7k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
95.7k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
95.7k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
95.7k
                        shuffle_idx_to_instance_idx));
1036
95.7k
            }
1037
102k
            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
43.5k
                idx = 2;
1043
43.5k
                break;
1044
43.5k
            }
1045
59.1k
            idx++;
1046
59.1k
        }
1047
526k
    } while (do_local_exchange);
1048
483k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
76.8k
        RETURN_IF_ERROR(_add_local_exchange(
1050
76.8k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
76.8k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
76.8k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
76.8k
    }
1054
483k
    return Status::OK();
1055
483k
}
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
385k
                                                  PipelineId cur_pipeline_id) {
1063
385k
    switch (thrift_sink.type) {
1064
129k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
129k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
129k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
129k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
129k
                params.destinations, _fragment_instance_ids);
1071
129k
        break;
1072
129k
    }
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
31.7k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
31.7k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
31.7k
        int child_node_id = pipeline->operators().back()->node_id();
1098
31.7k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
31.7k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
31.7k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
1.44k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
1.44k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
30.2k
        } else {
1104
30.2k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
30.2k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
30.2k
        }
1107
31.7k
        break;
1108
0
    }
1109
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
165
        DCHECK(state->get_query_ctx() != nullptr);
1112
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
165
                                                                output_exprs);
1115
165
        break;
1116
0
    }
1117
740
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
740
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
740
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
740
                                                         output_exprs);
1123
740
        break;
1124
740
    }
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
2
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
2
                                                                     row_desc, output_exprs);
1132
864
        } else {
1133
864
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
864
                                                                row_desc, output_exprs);
1135
864
        }
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
418
    case TDataSinkType::RESULT_FILE_SINK: {
1186
418
        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
419
        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
418
        } else {
1196
418
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
418
                                                              output_exprs);
1198
418
        }
1199
418
        break;
1200
418
    }
1201
1.43k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
1.43k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
1.43k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
1.43k
        auto sink_id = next_sink_operator_id();
1205
1.43k
        const int multi_cast_node_id = sink_id;
1206
1.43k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
1.43k
        std::vector<int> sources;
1209
5.55k
        for (int i = 0; i < sender_size; ++i) {
1210
4.11k
            auto source_id = next_operator_id();
1211
4.11k
            sources.push_back(source_id);
1212
4.11k
        }
1213
1214
1.43k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
1.43k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
5.55k
        for (int i = 0; i < sender_size; ++i) {
1217
4.11k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
4.11k
            RowDescriptor* exchange_row_desc = nullptr;
1220
4.11k
            {
1221
4.11k
                const auto& tmp_row_desc =
1222
4.11k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
4.11k
                                ? RowDescriptor(state->desc_tbl(),
1224
4.11k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
4.11k
                                                         .output_tuple_id})
1226
4.11k
                                : row_desc;
1227
4.11k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
4.11k
            }
1229
4.11k
            auto source_id = sources[i];
1230
4.11k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
4.11k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
4.11k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
4.11k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
4.11k
                    /*operator_id=*/source_id);
1236
4.11k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
4.11k
                    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
4.11k
            DataSinkOperatorPtr sink_op;
1241
4.11k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
4.11k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
4.11k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
4.11k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
4.11k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
4.11k
            {
1248
4.11k
                TDataSink* t = pool->add(new TDataSink());
1249
4.11k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
4.11k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
4.11k
            }
1252
1253
            // 3. set dependency dag
1254
4.11k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
4.11k
        }
1256
1.43k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
1.43k
        break;
1260
1.43k
    }
1261
1.43k
    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
385k
    }
1280
384k
    return Status::OK();
1281
385k
}
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
585k
                                                 OperatorPtr& cache_op) {
1292
585k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
585k
    Defer defer = Defer([&]() {
1294
584k
        if (op) {
1295
584k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
584k
        }
1297
583k
        for (auto& s : sink_ops) {
1298
96.8k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
96.8k
        }
1300
583k
    });
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
585k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
585k
    std::stringstream error_msg;
1305
585k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
585k
    bool fe_with_old_version = false;
1308
585k
    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
76
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
76
        DCHECK(_query_ctx != nullptr);
1319
76
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
76
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
76
                                                    _num_instances);
1322
76
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
76
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
76
        break;
1325
76
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
14.3k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
14.3k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
14.3k
                                                 _num_instances);
1342
14.3k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
14.3k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
14.3k
        break;
1345
14.3k
    }
1346
131k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
131k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
131k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
131k
                                  : 0;
1350
131k
        DCHECK_GT(num_senders, 0);
1351
131k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
131k
                                                       num_senders);
1353
131k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
131k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
131k
        break;
1356
131k
    }
1357
127k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
127k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
127k
            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
127k
        bool need_create_cache_op =
1364
127k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
127k
        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
127k
        const bool group_by_limit_opt =
1385
127k
                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
127k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
127k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
127k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
127k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
127k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
127k
        const bool can_use_distinct_streaming_agg =
1396
127k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
127k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
127k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
127k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
127k
        if (can_use_distinct_streaming_agg) {
1402
84.7k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
84.7k
            } else {
1413
84.7k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
84.7k
                                                                     tnode, descs);
1415
84.7k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
84.7k
            }
1417
84.7k
        } else if (is_streaming_agg) {
1418
1.20k
            if (need_create_cache_op) {
1419
0
                PipelinePtr new_pipe;
1420
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1421
0
                cache_op = op;
1422
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
0
                                                             descs);
1424
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1425
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1426
0
                cur_pipe = new_pipe;
1427
1.20k
            } else {
1428
1.20k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.20k
                                                             descs);
1430
1.20k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.20k
            }
1432
42.0k
        } else {
1433
            // create new pipeline to add query cache operator
1434
42.0k
            PipelinePtr new_pipe;
1435
42.0k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
42.0k
            if (enable_spill) {
1441
76
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
76
                                                                     next_operator_id(), descs);
1443
41.9k
            } else {
1444
41.9k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
41.9k
            }
1446
42.0k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
41.9k
            } else {
1451
41.9k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
41.9k
            }
1453
1454
42.0k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
42.0k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
40.3k
                _dag.insert({downstream_pipeline_id, {}});
1457
40.3k
            }
1458
42.0k
            cur_pipe = add_pipeline(cur_pipe);
1459
42.0k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
42.0k
            if (enable_spill) {
1462
76
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
76
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
41.9k
            } else {
1465
41.9k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
41.9k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
41.9k
            }
1468
42.0k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
42.0k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
42.0k
        }
1471
127k
        break;
1472
127k
    }
1473
127k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
61
        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
61
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
61
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
61
        const auto downstream_pipeline_id = cur_pipe->id();
1486
61
        if (!_dag.contains(downstream_pipeline_id)) {
1487
61
            _dag.insert({downstream_pipeline_id, {}});
1488
61
        }
1489
61
        cur_pipe = add_pipeline(cur_pipe);
1490
61
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
61
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
61
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
61
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
61
        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
61
        {
1503
61
            auto shared_state = BucketedAggSharedState::create_shared();
1504
61
            shared_state->id = op->operator_id();
1505
61
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
414
            for (int i = 0; i < _num_instances; i++) {
1508
353
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
353
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
353
                sink_dep->set_shared_state(shared_state.get());
1511
353
                shared_state->sink_deps.push_back(sink_dep);
1512
353
            }
1513
61
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
61
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
61
            _op_id_to_shared_state.insert(
1516
61
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
61
        }
1518
61
        break;
1519
61
    }
1520
9.22k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.22k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.22k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.22k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.22k
        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
9.22k
        } else {
1566
9.22k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.22k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.22k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.22k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.53k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.53k
            }
1573
9.22k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.22k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.22k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.22k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.22k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.22k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.22k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.22k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.22k
        }
1584
9.22k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.39k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.39k
                    HashJoinSharedState::create_shared(_num_instances);
1587
16.1k
            for (int i = 0; i < _num_instances; i++) {
1588
13.7k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
13.7k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
13.7k
                sink_dep->set_shared_state(shared_state.get());
1591
13.7k
                shared_state->sink_deps.push_back(sink_dep);
1592
13.7k
            }
1593
2.39k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.39k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.39k
            _op_id_to_shared_state.insert(
1596
2.39k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.39k
        }
1598
9.22k
        break;
1599
9.22k
    }
1600
3.78k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
3.78k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
3.78k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
3.78k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
3.78k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
3.55k
            _dag.insert({downstream_pipeline_id, {}});
1607
3.55k
        }
1608
3.78k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
3.78k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
3.78k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
3.78k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
3.78k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
3.78k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
3.78k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
3.78k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
3.78k
        break;
1618
3.78k
    }
1619
52.0k
    case TPlanNodeType::UNION_NODE: {
1620
52.0k
        int child_count = tnode.num_children;
1621
52.0k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
52.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
52.0k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
52.0k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
51.7k
            _dag.insert({downstream_pipeline_id, {}});
1627
51.7k
        }
1628
53.2k
        for (int i = 0; i < child_count; i++) {
1629
1.19k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.19k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.19k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.19k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.19k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.19k
            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
1.19k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.19k
        }
1638
52.0k
        break;
1639
52.0k
    }
1640
52.0k
    case TPlanNodeType::SORT_NODE: {
1641
38.4k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
38.4k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
38.4k
        const bool use_local_merge =
1644
38.4k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
38.4k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
38.4k
        } else if (use_local_merge) {
1648
36.3k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
36.3k
                                                                 descs);
1650
36.3k
        } else {
1651
2.08k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.08k
        }
1653
38.4k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
38.4k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
38.4k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
38.3k
            _dag.insert({downstream_pipeline_id, {}});
1658
38.3k
        }
1659
38.4k
        cur_pipe = add_pipeline(cur_pipe);
1660
38.4k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
38.4k
        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
38.4k
        } else {
1666
38.4k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
38.4k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
38.4k
        }
1669
38.4k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
38.4k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
38.4k
        break;
1672
38.4k
    }
1673
38.4k
    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
1.62k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.62k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.62k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.62k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.62k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.61k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.61k
        }
1698
1.62k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.62k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.62k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.62k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.62k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.62k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.62k
        break;
1706
1.62k
    }
1707
1.62k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.17k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.17k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.17k
        break;
1711
1.17k
    }
1712
1.17k
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
296
    case TPlanNodeType::REPEAT_NODE: {
1723
296
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
296
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
296
        break;
1726
296
    }
1727
911
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
911
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
911
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
911
        break;
1731
911
    }
1732
911
    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
371
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
371
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
371
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
371
        break;
1747
371
    }
1748
1.82k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.82k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.82k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.82k
        break;
1752
1.82k
    }
1753
5.71k
    case TPlanNodeType::META_SCAN_NODE: {
1754
5.71k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
5.71k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
5.71k
        break;
1757
5.71k
    }
1758
5.71k
    case TPlanNodeType::SELECT_NODE: {
1759
1.44k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
1.44k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
1.44k
        break;
1762
1.44k
    }
1763
1.44k
    case TPlanNodeType::REC_CTE_NODE: {
1764
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
151
        const auto downstream_pipeline_id = cur_pipe->id();
1768
151
        if (!_dag.contains(downstream_pipeline_id)) {
1769
148
            _dag.insert({downstream_pipeline_id, {}});
1770
148
        }
1771
1772
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
151
        DataSinkOperatorPtr anchor_sink;
1776
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
151
                                                                  op->operator_id(), tnode, descs);
1778
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
151
        DataSinkOperatorPtr rec_sink;
1786
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
151
                                                         tnode, descs);
1788
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
151
        break;
1793
151
    }
1794
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.95k
        break;
1798
1.95k
    }
1799
1.95k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
585k
    }
1803
583k
    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
583k
    return Status::OK();
1809
585k
}
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
383k
Status PipelineFragmentContext::submit() {
1846
383k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
383k
    _submitted = true;
1850
1851
383k
    int submit_tasks = 0;
1852
383k
    Status st;
1853
383k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.08M
    for (auto& task : _tasks) {
1855
1.81M
        for (auto& t : task) {
1856
1.81M
            st = scheduler->submit(t.first);
1857
1.81M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.81M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.81M
            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
1.81M
            submit_tasks++;
1866
1.81M
        }
1867
1.08M
    }
1868
383k
    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
383k
    } else {
1883
383k
        return st;
1884
383k
    }
1885
383k
}
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
385k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
385k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
385k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
385k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
385k
    if (!_need_notify_close) {
1919
382k
        auto st = send_report(true);
1920
382k
        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
382k
    }
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
385k
    if (_runtime_state->enable_profile() &&
1931
385k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.27k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.27k
         _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
385k
    if (_query_ctx->enable_profile()) {
1953
2.27k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.27k
                                         collect_realtime_load_channel_profile());
1955
2.27k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
385k
    return !_need_notify_close;
1960
385k
}
1961
1962
1.80M
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
1.80M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.80M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
604k
        if (_dag.contains(pipeline_id)) {
1967
335k
            for (auto dep : _dag[pipeline_id]) {
1968
335k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
335k
            }
1970
260k
        }
1971
604k
    }
1972
1.80M
    bool need_remove = false;
1973
1.80M
    {
1974
1.80M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.80M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.80M
        _query_ctx->inc_finished_task_num();
1978
1.80M
        if (_closed_tasks >= _total_tasks) {
1979
385k
            need_remove = _close_fragment_instance();
1980
385k
        }
1981
1.80M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.80M
    if (need_remove) {
1984
382k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
382k
    }
1986
1.80M
}
1987
1988
48.8k
std::string PipelineFragmentContext::get_load_error_url() {
1989
48.8k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1990
0
        return to_load_error_http_path(str);
1991
0
    }
1992
117k
    for (auto& tasks : _tasks) {
1993
189k
        for (auto& task : tasks) {
1994
189k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
196
                return to_load_error_http_path(str);
1996
196
            }
1997
189k
        }
1998
117k
    }
1999
48.6k
    return "";
2000
48.8k
}
2001
2002
48.8k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
48.8k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
117k
    for (auto& tasks : _tasks) {
2007
189k
        for (auto& task : tasks) {
2008
189k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
196
                return str;
2010
196
            }
2011
189k
        }
2012
117k
    }
2013
48.6k
    return "";
2014
48.8k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
43.0k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
43.0k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
43.0k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
43.0k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
43.0k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
43.0k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
43.0k
    });
2031
2032
43.0k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
43.0k
    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
43.0k
    int callback_retries = 10;
2038
43.0k
    const int sleep_ms = 1000;
2039
43.0k
    Status exec_status = req.status;
2040
43.0k
    Status coord_status;
2041
43.0k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
43.0k
    do {
2043
43.0k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
43.0k
                                                            req.coord_addr, &coord_status);
2045
43.0k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
43.0k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
43.0k
    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
43.0k
    TReportExecStatusParams params;
2059
43.0k
    params.protocol_version = FrontendServiceVersion::V1;
2060
43.0k
    params.__set_query_id(req.query_id);
2061
43.0k
    params.__set_backend_num(req.backend_num);
2062
43.0k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
43.0k
    params.__set_fragment_id(req.fragment_id);
2064
43.0k
    params.__set_status(exec_status.to_thrift());
2065
43.0k
    params.__set_done(req.done);
2066
43.0k
    params.__set_query_type(req.runtime_state->query_type());
2067
43.0k
    params.__isset.profile = false;
2068
2069
43.0k
    DCHECK(req.runtime_state != nullptr);
2070
2071
43.0k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
38.9k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
38.9k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
38.9k
    } else {
2075
4.14k
        DCHECK(!req.runtime_states.empty());
2076
4.14k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
4.14k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.14k
    }
2086
2087
43.0k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
43.0k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
43.0k
    static std::string s_unselected_rows = "unselected.rows";
2090
43.0k
    int64_t num_rows_load_success = 0;
2091
43.0k
    int64_t num_rows_load_filtered = 0;
2092
43.0k
    int64_t num_rows_load_unselected = 0;
2093
43.0k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
43.0k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
43.0k
        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
43.0k
    } 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
34.2k
                params.__isset.load_counters = true;
2113
34.2k
                num_rows_load_success += rs->num_rows_load_success();
2114
34.2k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
34.2k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
34.2k
                params.__isset.fragment_instance_reports = true;
2117
34.2k
                TFragmentInstanceReport t;
2118
34.2k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
34.2k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
34.2k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
34.2k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
34.2k
                params.fragment_instance_reports.push_back(t);
2123
34.2k
            }
2124
128k
        }
2125
43.0k
    }
2126
43.0k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
43.0k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
43.0k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
43.0k
    if (!req.load_error_url.empty()) {
2131
178
        params.__set_tracking_url(req.load_error_url);
2132
178
    }
2133
43.0k
    if (!req.first_error_msg.empty()) {
2134
178
        params.__set_first_error_msg(req.first_error_msg);
2135
178
    }
2136
127k
    for (auto* rs : req.runtime_states) {
2137
127k
        if (rs->wal_id() > 0) {
2138
116
            params.__set_txn_id(rs->wal_id());
2139
116
            params.__set_label(rs->import_label());
2140
116
        }
2141
127k
    }
2142
43.0k
    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
43.0k
    } else if (!req.runtime_states.empty()) {
2146
127k
        for (auto* rs : req.runtime_states) {
2147
127k
            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
127k
        }
2154
43.0k
    }
2155
43.0k
    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
43.0k
    } 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
26.5k
                params.__isset.commitInfos = true;
2162
26.5k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
26.5k
            }
2164
128k
        }
2165
43.0k
    }
2166
43.0k
    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
43.0k
    } 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
43.0k
    }
2178
43.0k
    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
43.0k
    } else if (!req.runtime_states.empty()) {
2183
127k
        for (auto* rs : req.runtime_states) {
2184
127k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
1.06k
                params.__isset.hive_partition_updates = true;
2186
1.06k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
1.06k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
1.06k
            }
2189
127k
        }
2190
43.0k
    }
2191
43.0k
    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
43.0k
    } else if (!req.runtime_states.empty()) {
2196
127k
        for (auto* rs : req.runtime_states) {
2197
127k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
1.05k
                params.__isset.iceberg_commit_datas = true;
2199
1.05k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
1.05k
                                                   rs_icd.begin(), rs_icd.end());
2201
1.05k
            }
2202
127k
        }
2203
43.0k
    }
2204
2205
43.0k
    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
43.0k
    } 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
43.0k
    }
2217
2218
43.0k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
43.0k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
43.0k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
43.0k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
43.0k
    }
2224
2225
43.0k
    TReportExecStatusResult res;
2226
43.0k
    Status rpc_status;
2227
2228
43.0k
    VLOG_DEBUG << "reportExecStatus params is "
2229
10
               << apache::thrift::ThriftDebugString(params).c_str();
2230
43.0k
    if (!exec_status.ok()) {
2231
1.61k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.61k
                     << " to coordinator: " << req.coord_addr
2233
1.61k
                     << ", query id: " << print_id(req.query_id);
2234
1.61k
    }
2235
43.0k
    try {
2236
43.0k
        try {
2237
43.0k
            (*coord)->reportExecStatus(res, params);
2238
43.0k
        } 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
43.0k
        rpc_status = Status::create<false>(res.status);
2254
43.0k
    } 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
43.0k
    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
43.0k
}
2265
2266
386k
Status PipelineFragmentContext::send_report(bool done) {
2267
386k
    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
386k
    if (!_is_report_success && done && exec_status.ok()) {
2273
343k
        return Status::OK();
2274
343k
    }
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
43.1k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
181
        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
181
            return Status::OK();
2286
181
        }
2287
0
        return Status::NeedSendAgain("");
2288
181
    }
2289
2290
43.0k
    std::vector<RuntimeState*> runtime_states;
2291
2292
90.4k
    for (auto& tasks : _tasks) {
2293
128k
        for (auto& task : tasks) {
2294
128k
            runtime_states.push_back(task.second.get());
2295
128k
        }
2296
90.4k
    }
2297
2298
43.0k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
43.0k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
43.0k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
43.0k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
43.0k
    ReportStatusRequest req {.status = exec_status,
2306
43.0k
                             .runtime_states = runtime_states,
2307
43.0k
                             .done = done || !exec_status.ok(),
2308
43.0k
                             .coord_addr = _query_ctx->coord_addr,
2309
43.0k
                             .query_id = _query_id,
2310
43.0k
                             .fragment_id = _fragment_id,
2311
43.0k
                             .fragment_instance_id = TUniqueId(),
2312
43.0k
                             .backend_num = -1,
2313
43.0k
                             .runtime_state = _runtime_state.get(),
2314
43.0k
                             .load_error_url = load_eror_url,
2315
43.0k
                             .first_error_msg = first_error_msg,
2316
43.0k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
43.0k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
43.0k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
43.0k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
43.0k
        _coordinator_callback(req);
2321
43.0k
        if (!req.done) {
2322
4.39k
            ctx->refresh_next_report_time();
2323
4.39k
        }
2324
43.0k
    });
2325
43.1k
}
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
59
std::string PipelineFragmentContext::debug_string() {
2365
59
    std::lock_guard<std::mutex> l(_task_mutex);
2366
59
    fmt::memory_buffer debug_string_buffer;
2367
59
    fmt::format_to(debug_string_buffer,
2368
59
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
59
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
59
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
264
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
205
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
635
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
430
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
430
                           _tasks[j][i].first->debug_string());
2376
430
        }
2377
205
    }
2378
2379
59
    return fmt::to_string(debug_string_buffer);
2380
59
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.27k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.27k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2385
2386
    // we do not have mutex to protect pipeline_id_to_profile
2387
    // so we need to make sure this funciton is invoked after fragment context
2388
    // has already been prepared.
2389
2.27k
    if (!_prepared) {
2390
0
        std::string msg =
2391
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2392
0
        DCHECK(false) << msg;
2393
0
        LOG_ERROR(msg);
2394
0
        return res;
2395
0
    }
2396
2397
    // Make sure first profile is fragment level profile
2398
2.27k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.27k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.27k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.14k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.14k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.14k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.14k
        res.push_back(profile_ptr);
2407
4.14k
    }
2408
2409
2.27k
    return res;
2410
2.27k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.27k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2414
    // we do not have mutex to protect pipeline_id_to_profile
2415
    // so we need to make sure this funciton is invoked after fragment context
2416
    // has already been prepared.
2417
2.27k
    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
5.63k
    for (const auto& tasks : _tasks) {
2426
11.3k
        for (const auto& task : tasks) {
2427
11.3k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
11.3k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
11.3k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
11.3k
                                                           _runtime_state->profile_level());
2435
11.3k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
11.3k
        }
2437
5.63k
    }
2438
2439
2.27k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.27k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.27k
                                                      _runtime_state->profile_level());
2442
2.27k
    return load_channel_profile;
2443
2.27k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
12.4k
    for (const auto& _task : _tasks) {
2455
20.7k
        for (const auto& task : _task) {
2456
20.7k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
20.7k
            result.merge(set);
2458
20.7k
        }
2459
12.4k
    }
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
386k
void PipelineFragmentContext::_release_resource() {
2468
386k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
386k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
386k
    auto st = _query_ctx->exec_status();
2472
1.08M
    for (auto& _task : _tasks) {
2473
1.08M
        if (!_task.empty()) {
2474
1.08M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.08M
        }
2476
1.08M
    }
2477
386k
    _tasks.clear();
2478
386k
    _dag.clear();
2479
386k
    _pip_id_to_pipeline.clear();
2480
386k
    _pipelines.clear();
2481
386k
    _sink.reset();
2482
386k
    _root_op.reset();
2483
386k
    _runtime_filter_mgr_map.clear();
2484
386k
    _op_id_to_shared_state.clear();
2485
386k
}
2486
2487
} // namespace doris