Coverage Report

Created: 2026-06-09 07:58

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
9
//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
17
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
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#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
132
#include "util/client_cache.h"
133
#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
448k
        : _query_id(std::move(query_id)),
144
448k
          _fragment_id(request.fragment_id),
145
448k
          _exec_env(exec_env),
146
448k
          _query_ctx(std::move(query_ctx)),
147
448k
          _call_back(call_back),
148
448k
          _is_report_on_cancel(true),
149
448k
          _params(request),
150
448k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
448k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
448k
                                                               : false) {
153
448k
    _fragment_watcher.start();
154
448k
}
155
156
448k
PipelineFragmentContext::~PipelineFragmentContext() {
157
448k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
448k
            .tag("query_id", print_id(_query_id))
159
448k
            .tag("fragment_id", _fragment_id);
160
448k
    _release_resource();
161
448k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
448k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
448k
        _runtime_state.reset();
165
448k
        _query_ctx.reset();
166
448k
    }
167
448k
}
168
169
120
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
120
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
120
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
120
}
175
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// 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
9.65k
bool PipelineFragmentContext::notify_close() {
181
9.65k
    bool all_closed = false;
182
9.65k
    bool need_remove = false;
183
9.65k
    {
184
9.65k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.65k
        if (_closed_tasks >= _total_tasks) {
186
3.46k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
192
3.41k
                need_remove = true;
193
3.41k
            }
194
3.46k
            all_closed = true;
195
3.46k
        }
196
        // make fragment release by self after cancel
197
9.65k
        _need_notify_close = false;
198
9.65k
    }
199
9.65k
    if (need_remove) {
200
3.41k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.41k
    }
202
9.65k
    return all_closed;
203
9.65k
}
204
205
// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
6.16k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.16k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.16k
            .tag("query_id", print_id(_query_id))
212
6.16k
            .tag("fragment_id", _fragment_id)
213
6.16k
            .tag("reason", reason.to_string());
214
6.16k
    if (notify_close()) {
215
67
        return;
216
67
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.10k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
6.10k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
6.10k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
6.10k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
21
        _query_ctx->set_load_error_url(error_url);
236
21
    }
237
238
6.10k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
21
        _query_ctx->set_first_error_msg(first_error_msg);
240
21
    }
241
242
6.10k
    _query_ctx->cancel(reason, _fragment_id);
243
6.10k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
277
        _is_report_on_cancel = false;
245
5.82k
    } else {
246
26.4k
        for (auto& id : _fragment_instance_ids) {
247
26.4k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
26.4k
        }
249
5.82k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
6.10k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.10k
    if (stream_load_ctx != nullptr) {
254
29
        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
29
        stream_load_ctx->error_url = get_load_error_url();
259
29
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
29
    }
261
262
27.0k
    for (auto& tasks : _tasks) {
263
61.0k
        for (auto& task : tasks) {
264
61.0k
            task.first->unblock_all_dependencies();
265
61.0k
        }
266
27.0k
    }
267
6.10k
}
268
269
694k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
694k
    PipelineId id = _next_pipeline_id++;
271
694k
    auto pipeline = std::make_shared<Pipeline>(
272
694k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
694k
            parent ? parent->num_tasks() : _num_instances);
274
694k
    if (idx >= 0) {
275
119k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
575k
    } else {
277
575k
        _pipelines.emplace_back(pipeline);
278
575k
    }
279
694k
    if (parent) {
280
238k
        parent->set_children(pipeline);
281
238k
    }
282
694k
    return pipeline;
283
694k
}
284
285
447k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
447k
    {
287
447k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
447k
        auto root_pipeline = add_pipeline();
290
447k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
447k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
447k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
447k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
447k
                                          _params.fragment.output_exprs, _params,
299
447k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
447k
                                          *_desc_tbl, root_pipeline->id()));
301
447k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
447k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
574k
        for (PipelinePtr& pipeline : _pipelines) {
305
574k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
574k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
574k
        }
308
447k
    }
309
    // 4. Build local exchanger
310
447k
    if (_runtime_state->enable_local_shuffle()) {
311
443k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
443k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
443k
                                             _params.bucket_seq_to_instance_idx,
314
443k
                                             _params.shuffle_idx_to_instance_idx));
315
443k
    }
316
317
    // 5. Initialize global states in pipelines.
318
695k
    for (PipelinePtr& pipeline : _pipelines) {
319
695k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
695k
        pipeline->children().clear();
321
695k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
695k
    }
323
324
446k
    {
325
446k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
446k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
446k
    }
329
330
446k
    return Status::OK();
331
446k
}
332
333
448k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
448k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
448k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
448k
        _timeout = _params.query_options.execution_timeout;
339
448k
    }
340
341
448k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
448k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
448k
    SCOPED_TIMER(_prepare_timer);
344
448k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
448k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
448k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
448k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
448k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
448k
    {
350
448k
        SCOPED_TIMER(_init_context_timer);
351
448k
        cast_set(_num_instances, _params.local_params.size());
352
448k
        _total_instances =
353
448k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
448k
        auto* fragment_context = this;
356
357
448k
        if (_params.query_options.__isset.is_report_success) {
358
446k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
446k
        }
360
361
        // 1. Set up the global runtime state.
362
448k
        _runtime_state = RuntimeState::create_unique(
363
448k
                _params.query_id, _params.fragment_id, _params.query_options,
364
448k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
448k
        _runtime_state->set_task_execution_context(shared_from_this());
366
448k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
448k
        if (_params.__isset.backend_id) {
368
443k
            _runtime_state->set_backend_id(_params.backend_id);
369
443k
        }
370
448k
        if (_params.__isset.import_label) {
371
235
            _runtime_state->set_import_label(_params.import_label);
372
235
        }
373
448k
        if (_params.__isset.db_name) {
374
187
            _runtime_state->set_db_name(_params.db_name);
375
187
        }
376
448k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
448k
        if (_params.is_simplified_param) {
381
149k
            _desc_tbl = _query_ctx->desc_tbl;
382
298k
        } else {
383
298k
            DCHECK(_params.__isset.desc_tbl);
384
298k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
298k
                                                  &_desc_tbl));
386
298k
        }
387
448k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
448k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
448k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
448k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
448k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
448k
        const auto target_size = _params.local_params.size();
395
448k
        _fragment_instance_ids.resize(target_size);
396
1.63M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.18M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.18M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.18M
        }
400
448k
    }
401
402
448k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
447k
    _init_next_report_time();
405
406
447k
    _prepared = true;
407
447k
    return Status::OK();
408
448k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.19M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.19M
    const auto& local_params = _params.local_params[instance_idx];
414
1.19M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.19M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.19M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.19M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.19M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
2.01M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
2.01M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
2.01M
                                std::vector<std::shared_ptr<Dependency>>>>
422
2.01M
                shared_state_map;
423
2.54M
        for (auto& op : pipeline->operators()) {
424
2.54M
            auto source_id = op->operator_id();
425
2.54M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.54M
                iter != _op_id_to_shared_state.end()) {
427
806k
                shared_state_map.insert({source_id, iter->second});
428
806k
            }
429
2.54M
        }
430
2.01M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
2.01M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
2.01M
                iter != _op_id_to_shared_state.end()) {
433
336k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
336k
            }
435
2.01M
        }
436
2.01M
        return shared_state_map;
437
2.01M
    };
438
439
3.65M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.46M
        auto& pipeline = _pipelines[pip_idx];
441
2.46M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
2.00M
            auto task_runtime_state = RuntimeState::create_unique(
443
2.00M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
2.00M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
2.00M
            {
446
                // Initialize runtime state for this task
447
2.00M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
2.00M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
2.00M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
2.00M
                if (_params.__isset.backend_id) {
453
2.00M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
2.00M
                }
455
2.00M
                if (_params.__isset.import_label) {
456
236
                    task_runtime_state->set_import_label(_params.import_label);
457
236
                }
458
2.00M
                if (_params.__isset.db_name) {
459
188
                    task_runtime_state->set_db_name(_params.db_name);
460
188
                }
461
2.00M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
2.00M
                if (_params.__isset.wal_id) {
465
112
                    task_runtime_state->set_wal_id(_params.wal_id);
466
112
                }
467
2.00M
                if (_params.__isset.content_length) {
468
31
                    task_runtime_state->set_content_length(_params.content_length);
469
31
                }
470
471
2.00M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
2.00M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
2.00M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
2.00M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
2.00M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
2.00M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
2.00M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
2.00M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
2.00M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
2.00M
            }
482
2.00M
            auto cur_task_id = _total_tasks++;
483
2.00M
            task_runtime_state->set_task_id(cur_task_id);
484
2.00M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
2.00M
            auto task = std::make_shared<PipelineTask>(
486
2.00M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
2.00M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
2.00M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
2.00M
                    instance_idx);
490
2.00M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
2.00M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
2.00M
            _tasks[instance_idx].emplace_back(
493
2.00M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
2.00M
                            std::move(task), std::move(task_runtime_state)});
495
2.00M
        }
496
2.46M
    }
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
2.46M
    for (auto& _pipeline : _pipelines) {
516
2.46M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.99M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.99M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.99M
            if (_dag.contains(_pipeline->id())) {
522
1.28M
                auto& deps = _dag[_pipeline->id()];
523
2.07M
                for (auto& dep : deps) {
524
2.07M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.13M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.13M
                        if (ss) {
527
469k
                            task->inject_shared_state(ss);
528
667k
                        } else {
529
667k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
667k
                                    task->get_source_shared_state());
531
667k
                        }
532
1.13M
                    }
533
2.07M
                }
534
1.28M
            }
535
1.99M
        }
536
2.46M
    }
537
3.66M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.46M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.99M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.99M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.99M
            std::vector<TScanRangeParams> scan_ranges;
542
1.99M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.99M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
343k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
343k
            }
546
1.99M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.99M
                                                             _params.fragment.output_sink));
548
1.99M
        }
549
2.46M
    }
550
1.19M
    {
551
1.19M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.19M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.19M
    }
554
1.19M
    return Status::OK();
555
1.19M
}
556
557
447k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
447k
    _total_tasks = 0;
559
447k
    _closed_tasks = 0;
560
447k
    const auto target_size = _params.local_params.size();
561
447k
    _tasks.resize(target_size);
562
447k
    _runtime_filter_mgr_map.resize(target_size);
563
1.14M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
694k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
694k
    }
566
447k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
447k
    if (target_size > 1 &&
569
447k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
141k
         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
28.9k
        std::vector<Status> prepare_status(target_size);
573
28.9k
        int submitted_tasks = 0;
574
28.9k
        Status submit_status;
575
28.9k
        CountDownLatch latch((int)target_size);
576
328k
        for (int i = 0; i < target_size; i++) {
577
299k
            submit_status = thread_pool->submit_func([&, i]() {
578
298k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
298k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
298k
                latch.count_down();
581
298k
            });
582
299k
            if (LIKELY(submit_status.ok())) {
583
299k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
299k
        }
588
28.9k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
28.9k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
328k
        for (int i = 0; i < submitted_tasks; i++) {
593
299k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
299k
        }
597
418k
    } else {
598
1.31M
        for (int i = 0; i < target_size; i++) {
599
893k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
893k
        }
601
418k
    }
602
447k
    _pipeline_parent_map.clear();
603
447k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
447k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
447k
    return Status::OK();
608
447k
}
609
610
445k
void PipelineFragmentContext::_init_next_report_time() {
611
445k
    auto interval_s = config::pipeline_status_report_interval;
612
445k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
42.4k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.4k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
42.4k
        _previous_report_time =
617
42.4k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.4k
        _disable_period_report = false;
619
42.4k
    }
620
445k
}
621
622
4.76k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.76k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.76k
    DCHECK(disable == true);
625
4.76k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.76k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.76k
}
628
629
7.38M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.38M
    if (!_is_report_success) {
631
6.94M
        return;
632
6.94M
    }
633
445k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
445k
    if (disable) {
635
7.95k
        return;
636
7.95k
    }
637
437k
    int32_t interval_s = config::pipeline_status_report_interval;
638
437k
    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
437k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
437k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
437k
    if (MonotonicNanos() > next_report_time) {
646
4.78k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.78k
                                                            std::memory_order_acq_rel)) {
648
15
            return;
649
15
        }
650
4.76k
        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
4.76k
        auto st = send_report(false);
667
4.76k
        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
4.76k
    }
673
437k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
444k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
444k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
444k
    int node_idx = 0;
682
683
444k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
444k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
444k
    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
444k
    return Status::OK();
691
444k
}
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
672k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
672k
    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
672k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
672k
    int num_children = tnodes[*node_idx].num_children;
706
672k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
672k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
672k
    OperatorPtr op = nullptr;
710
672k
    OperatorPtr cache_op = nullptr;
711
672k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
672k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
672k
                                     followed_by_shuffled_operator,
714
672k
                                     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
672k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
672k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
226k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
446k
    } else {
723
446k
        *root = op;
724
446k
    }
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
672k
    auto required_data_distribution =
737
672k
            cur_pipe->operators().empty()
738
672k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
672k
                    : op->required_data_distribution(_runtime_state.get());
740
672k
    current_followed_by_shuffled_operator =
741
672k
            ((followed_by_shuffled_operator ||
742
672k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
613k
                                             : op->is_shuffled_operator())) &&
744
672k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
672k
            (followed_by_shuffled_operator &&
746
559k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
672k
    current_require_bucket_distribution =
749
672k
            ((require_bucket_distribution ||
750
672k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
617k
                                             : op->is_colocated_operator())) &&
752
672k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
672k
            (require_bucket_distribution &&
754
566k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
672k
    if (num_children == 0) {
757
464k
        _use_serial_source = op->is_serial_operator();
758
464k
    }
759
    // rely on that tnodes is preorder of the plan
760
899k
    for (int i = 0; i < num_children; i++) {
761
226k
        ++*node_idx;
762
226k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
226k
                                            current_followed_by_shuffled_operator,
764
226k
                                            current_require_bucket_distribution));
765
766
        // we are expecting a child, but have used all nodes
767
        // this means we have been given a bad tree and must fail
768
226k
        if (*node_idx >= tnodes.size()) {
769
0
            return Status::InternalError(
770
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
771
0
                    "nodes: {}",
772
0
                    *node_idx, tnodes.size());
773
0
        }
774
226k
    }
775
776
672k
    return Status::OK();
777
672k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
119k
        PipelinePtr pipe_with_sink) {
782
119k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
119k
    pipe_with_source->set_num_tasks(_num_instances);
784
119k
    pipe_with_source->set_data_distribution(data_distribution);
785
119k
}
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
119k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
119k
    auto& operators = cur_pipe->operators();
793
119k
    const auto downstream_pipeline_id = cur_pipe->id();
794
119k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
119k
    DataSinkOperatorPtr sink;
797
119k
    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
119k
    const bool followed_by_shuffled_operator =
804
119k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
119k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
119k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
119k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
119k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
119k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
119k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
119k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
119k
    if (bucket_seq_to_instance_idx.empty() &&
813
119k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
6
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
6
    }
816
119k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
119k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
119k
                                          num_buckets, use_global_hash_shuffle,
819
119k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
119k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
119k
            LocalExchangeSharedState::create_shared(_num_instances);
824
119k
    switch (data_distribution.distribution_type) {
825
19.5k
    case ExchangeType::HASH_SHUFFLE:
826
19.5k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
19.5k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
19.5k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
19.5k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
19.5k
                        ? cast_set<int>(
831
19.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
19.5k
                        : 0);
833
19.5k
        break;
834
539
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
539
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
539
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
539
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
539
                        ? cast_set<int>(
839
539
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
539
                        : 0);
841
539
        break;
842
95.1k
    case ExchangeType::PASSTHROUGH:
843
95.1k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
95.1k
                cur_pipe->num_tasks(), _num_instances,
845
95.1k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
95.1k
                        ? cast_set<int>(
847
95.0k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
95.1k
                        : 0);
849
95.1k
        break;
850
550
    case ExchangeType::BROADCAST:
851
550
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
550
                cur_pipe->num_tasks(), _num_instances,
853
550
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
550
                        ? cast_set<int>(
855
550
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
550
                        : 0);
857
550
        break;
858
2.69k
    case ExchangeType::PASS_TO_ONE:
859
2.69k
        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
1.33k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.33k
                    cur_pipe->num_tasks(), _num_instances,
863
1.33k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.33k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.33k
                                                    .local_exchange_free_blocks_limit)
866
1.33k
                            : 0);
867
1.35k
        } else {
868
1.35k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.35k
                    cur_pipe->num_tasks(), _num_instances,
870
1.35k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.35k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.35k
                                                    .local_exchange_free_blocks_limit)
873
1.35k
                            : 0);
874
1.35k
        }
875
2.69k
        break;
876
1.00k
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
1.00k
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
1.00k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
1.00k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
1.00k
                        ? cast_set<int>(
881
1.00k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
1.00k
                        : 0);
883
1.00k
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
119k
    }
888
119k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
119k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
119k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
119k
    _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
119k
    std::copy(operators.begin(), operators.begin() + idx,
898
119k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
119k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
119k
    OperatorPtr source_op;
905
119k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
119k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
119k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
119k
    if (!operators.empty()) {
909
43.5k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
43.5k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
43.5k
    }
912
119k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
119k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
119k
    std::vector<PipelineId> edges_with_source;
917
138k
    for (auto child : cur_pipe->children()) {
918
138k
        bool found = false;
919
153k
        for (auto op : new_pip->operators()) {
920
153k
            if (child->sink()->node_id() == op->node_id()) {
921
13.3k
                new_pip->set_children(child);
922
13.3k
                found = true;
923
13.3k
            };
924
153k
        }
925
138k
        if (!found) {
926
125k
            new_children.push_back(child);
927
125k
            edges_with_source.push_back(child->id());
928
125k
        }
929
138k
    }
930
119k
    new_children.push_back(new_pip);
931
119k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
119k
    if (!new_pip->children().empty()) {
935
7.52k
        std::vector<PipelineId> edges_with_sink;
936
13.3k
        for (auto child : new_pip->children()) {
937
13.3k
            edges_with_sink.push_back(child->id());
938
13.3k
        }
939
7.52k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.52k
    }
941
119k
    cur_pipe->set_children(new_children);
942
119k
    _dag[downstream_pipeline_id] = edges_with_source;
943
119k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
119k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
119k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
119k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
119k
    return Status::OK();
950
119k
}
951
952
Status PipelineFragmentContext::_add_local_exchange(
953
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
954
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
955
        const std::map<int, int>& bucket_seq_to_instance_idx,
956
191k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
191k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
45.9k
        return Status::OK();
959
45.9k
    }
960
961
145k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
46.2k
        return Status::OK();
963
46.2k
    }
964
99.3k
    *do_local_exchange = true;
965
966
99.3k
    auto& operators = cur_pipe->operators();
967
99.3k
    auto total_op_num = operators.size();
968
99.3k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
99.3k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
99.3k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
99.3k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
99.3k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
8
            << "total_op_num: " << total_op_num
975
8
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
8
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
99.3k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
99.3k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
20.0k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
20.0k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
20.0k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
20.0k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
20.0k
                shuffle_idx_to_instance_idx));
990
20.0k
    }
991
99.3k
    return Status::OK();
992
99.3k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
442k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.01M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
570k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
570k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
119k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
119k
                if (child->sink()->node_id() ==
1003
119k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
103k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
103k
                }
1006
119k
            }
1007
113k
        }
1008
1009
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1010
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1011
        // still keep colocate plan after local shuffle
1012
570k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
570k
                                             bucket_seq_to_instance_idx,
1014
570k
                                             shuffle_idx_to_instance_idx));
1015
570k
    }
1016
442k
    return Status::OK();
1017
442k
}
1018
1019
Status PipelineFragmentContext::_plan_local_exchange(
1020
        int num_buckets, int pip_idx, PipelinePtr pip,
1021
        const std::map<int, int>& bucket_seq_to_instance_idx,
1022
569k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
569k
    int idx = 1;
1024
569k
    bool do_local_exchange = false;
1025
613k
    do {
1026
613k
        auto& ops = pip->operators();
1027
613k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
676k
        for (; idx < ops.size();) {
1030
107k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
98.7k
                RETURN_IF_ERROR(_add_local_exchange(
1032
98.7k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
98.7k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
98.7k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
98.7k
                        shuffle_idx_to_instance_idx));
1036
98.7k
            }
1037
107k
            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
43.6k
                idx = 2;
1043
43.6k
                break;
1044
43.6k
            }
1045
63.9k
            idx++;
1046
63.9k
        }
1047
613k
    } while (do_local_exchange);
1048
569k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
92.5k
        RETURN_IF_ERROR(_add_local_exchange(
1050
92.5k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
92.5k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
92.5k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
92.5k
    }
1054
569k
    return Status::OK();
1055
569k
}
1056
1057
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1058
                                                  const std::vector<TExpr>& output_exprs,
1059
                                                  const TPipelineFragmentParams& params,
1060
                                                  const RowDescriptor& row_desc,
1061
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1062
447k
                                                  PipelineId cur_pipeline_id) {
1063
447k
    switch (thrift_sink.type) {
1064
147k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
147k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
147k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
147k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
147k
                params.destinations, _fragment_instance_ids);
1071
147k
        break;
1072
147k
    }
1073
258k
    case TDataSinkType::RESULT_SINK: {
1074
258k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
258k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
258k
        int child_node_id = pipeline->operators().back()->node_id();
1080
258k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
258k
                                                      row_desc, output_exprs,
1082
258k
                                                      thrift_sink.result_sink);
1083
258k
        break;
1084
258k
    }
1085
104
    case TDataSinkType::DICTIONARY_SINK: {
1086
104
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
104
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
104
                                                    thrift_sink.dictionary_sink);
1092
104
        break;
1093
104
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
34.4k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
34.4k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
34.4k
        int child_node_id = pipeline->operators().back()->node_id();
1098
34.4k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
34.4k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
34.4k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.90k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.90k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
31.5k
        } else {
1104
31.5k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
31.5k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
31.5k
        }
1107
34.4k
        break;
1108
0
    }
1109
161
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
161
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
161
        DCHECK(state->get_query_ctx() != nullptr);
1112
161
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
161
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
161
                                                                output_exprs);
1115
161
        break;
1116
0
    }
1117
1.48k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.48k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.48k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.48k
                                                         output_exprs);
1123
1.48k
        break;
1124
1.48k
    }
1125
1.72k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.72k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.72k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
1.72k
        } else {
1133
1.72k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.72k
                                                                row_desc, output_exprs);
1135
1.72k
        }
1136
1.72k
        break;
1137
1.72k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
502
    case TDataSinkType::RESULT_FILE_SINK: {
1186
502
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
502
        } else {
1196
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
502
                                                              output_exprs);
1198
502
        }
1199
502
        break;
1200
502
    }
1201
2.62k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.62k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.62k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.62k
        auto sink_id = next_sink_operator_id();
1205
2.62k
        const int multi_cast_node_id = sink_id;
1206
2.62k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.62k
        std::vector<int> sources;
1209
10.3k
        for (int i = 0; i < sender_size; ++i) {
1210
7.68k
            auto source_id = next_operator_id();
1211
7.68k
            sources.push_back(source_id);
1212
7.68k
        }
1213
1214
2.62k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.62k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
10.3k
        for (int i = 0; i < sender_size; ++i) {
1217
7.68k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
7.68k
            RowDescriptor* exchange_row_desc = nullptr;
1220
7.68k
            {
1221
7.68k
                const auto& tmp_row_desc =
1222
7.68k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
7.68k
                                ? RowDescriptor(state->desc_tbl(),
1224
7.68k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
7.68k
                                                         .output_tuple_id})
1226
7.68k
                                : row_desc;
1227
7.68k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
7.68k
            }
1229
7.68k
            auto source_id = sources[i];
1230
7.68k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
7.68k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
7.68k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
7.68k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
7.68k
                    /*operator_id=*/source_id);
1236
7.68k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
7.68k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1238
            // 2. create and set sink operator of data stream sender for new pipeline
1239
1240
7.68k
            DataSinkOperatorPtr sink_op;
1241
7.68k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
7.68k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
7.68k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
7.68k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
7.68k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
7.68k
            {
1248
7.68k
                TDataSink* t = pool->add(new TDataSink());
1249
7.68k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
7.68k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
7.68k
            }
1252
1253
            // 3. set dependency dag
1254
7.68k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
7.68k
        }
1256
2.62k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.62k
        break;
1260
2.62k
    }
1261
2.62k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
13
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
13
        break;
1268
13
    }
1269
156
    case TDataSinkType::TVF_TABLE_SINK: {
1270
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
156
                                                        output_exprs);
1275
156
        break;
1276
156
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
447k
    }
1280
446k
    return Status::OK();
1281
447k
}
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
675k
                                                 OperatorPtr& cache_op) {
1292
675k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
675k
    Defer defer = Defer([&]() {
1294
673k
        if (op) {
1295
673k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
673k
        }
1297
673k
        for (auto& s : sink_ops) {
1298
119k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
119k
        }
1300
673k
    });
1301
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1302
    // Therefore, here we need to use a stack-like structure.
1303
675k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
675k
    std::stringstream error_msg;
1305
675k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
675k
    bool fe_with_old_version = false;
1308
675k
    switch (tnode.node_type) {
1309
219k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
219k
        op = std::make_shared<OlapScanOperatorX>(
1311
219k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
219k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
219k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
219k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
219k
        break;
1316
219k
    }
1317
76
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
76
        DCHECK(_query_ctx != nullptr);
1319
76
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
76
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
76
                                                    _num_instances);
1322
76
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
76
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
76
        break;
1325
76
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
25.8k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
25.8k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
25.8k
                                                 _num_instances);
1342
25.8k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
25.8k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
25.8k
        break;
1345
25.8k
    }
1346
152k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
152k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
152k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
152k
        DCHECK_GT(num_senders, 0);
1351
152k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
152k
                                                       num_senders);
1353
152k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
152k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
152k
        break;
1356
152k
    }
1357
141k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
141k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
141k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1360
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1361
0
                                         ": group by and output is empty");
1362
0
        }
1363
141k
        bool need_create_cache_op =
1364
141k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
141k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1366
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1367
10
            auto cache_source_id = next_operator_id();
1368
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1369
10
                                                        _params.fragment.query_cache_param);
1370
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1371
1372
10
            const auto downstream_pipeline_id = cur_pipe->id();
1373
10
            if (!_dag.contains(downstream_pipeline_id)) {
1374
10
                _dag.insert({downstream_pipeline_id, {}});
1375
10
            }
1376
10
            new_pipe = add_pipeline(cur_pipe);
1377
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1378
1379
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1380
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1381
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1382
10
            return Status::OK();
1383
10
        };
1384
141k
        const bool group_by_limit_opt =
1385
141k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1386
1387
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1388
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1389
141k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
141k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
141k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
141k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
141k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
141k
        const bool can_use_distinct_streaming_agg =
1396
141k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
141k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
141k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
141k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
141k
        if (can_use_distinct_streaming_agg) {
1402
84.6k
            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
84.6k
            } else {
1413
84.6k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
84.6k
                                                                     tnode, descs);
1415
84.6k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
84.6k
            }
1417
84.6k
        } else if (is_streaming_agg) {
1418
1.70k
            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
1.70k
            } else {
1428
1.70k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.70k
                                                             descs);
1430
1.70k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.70k
            }
1432
55.2k
        } else {
1433
            // create new pipeline to add query cache operator
1434
55.2k
            PipelinePtr new_pipe;
1435
55.2k
            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
55.2k
            if (enable_spill) {
1441
127
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
127
                                                                     next_operator_id(), descs);
1443
55.0k
            } else {
1444
55.0k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
55.0k
            }
1446
55.2k
            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
55.2k
            } else {
1451
55.2k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
55.2k
            }
1453
1454
55.2k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
55.2k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
52.2k
                _dag.insert({downstream_pipeline_id, {}});
1457
52.2k
            }
1458
55.2k
            cur_pipe = add_pipeline(cur_pipe);
1459
55.2k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
55.2k
            if (enable_spill) {
1462
127
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
127
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
55.0k
            } else {
1465
55.0k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
55.0k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
55.0k
            }
1468
55.2k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
55.2k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
55.2k
        }
1471
141k
        break;
1472
141k
    }
1473
141k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
64
        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
64
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
64
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
64
        const auto downstream_pipeline_id = cur_pipe->id();
1486
64
        if (!_dag.contains(downstream_pipeline_id)) {
1487
64
            _dag.insert({downstream_pipeline_id, {}});
1488
64
        }
1489
64
        cur_pipe = add_pipeline(cur_pipe);
1490
64
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
64
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
64
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
64
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
64
        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
64
        {
1503
64
            auto shared_state = BucketedAggSharedState::create_shared();
1504
64
            shared_state->id = op->operator_id();
1505
64
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
464
            for (int i = 0; i < _num_instances; i++) {
1508
400
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
400
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
400
                sink_dep->set_shared_state(shared_state.get());
1511
400
                shared_state->sink_deps.push_back(sink_dep);
1512
400
            }
1513
64
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
64
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
64
            _op_id_to_shared_state.insert(
1516
64
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
64
        }
1518
64
        break;
1519
64
    }
1520
9.56k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.56k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.56k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.56k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.56k
        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
9.56k
        } else {
1566
9.56k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.56k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.56k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.56k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.87k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.87k
            }
1573
9.56k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.56k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.56k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.56k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.56k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.56k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.56k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.56k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.56k
        }
1584
9.56k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.63k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.63k
                    HashJoinSharedState::create_shared(_num_instances);
1587
17.3k
            for (int i = 0; i < _num_instances; i++) {
1588
14.6k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
14.6k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
14.6k
                sink_dep->set_shared_state(shared_state.get());
1591
14.6k
                shared_state->sink_deps.push_back(sink_dep);
1592
14.6k
            }
1593
2.63k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.63k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.63k
            _op_id_to_shared_state.insert(
1596
2.63k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.63k
        }
1598
9.56k
        break;
1599
9.56k
    }
1600
6.21k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
6.21k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
6.21k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
6.21k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
6.21k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
5.97k
            _dag.insert({downstream_pipeline_id, {}});
1607
5.97k
        }
1608
6.21k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
6.21k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
6.21k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
6.21k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
6.21k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
6.21k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
6.21k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
6.21k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
6.21k
        break;
1618
6.21k
    }
1619
54.0k
    case TPlanNodeType::UNION_NODE: {
1620
54.0k
        int child_count = tnode.num_children;
1621
54.0k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
54.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
54.0k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
54.0k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
53.2k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.2k
        }
1628
55.4k
        for (int i = 0; i < child_count; i++) {
1629
1.39k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.39k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.39k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.39k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.39k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.39k
            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
1.39k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.39k
        }
1638
54.0k
        break;
1639
54.0k
    }
1640
54.0k
    case TPlanNodeType::SORT_NODE: {
1641
44.9k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
44.9k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
44.9k
        const bool use_local_merge =
1644
44.9k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
44.9k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
44.9k
        } else if (use_local_merge) {
1648
42.5k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
42.5k
                                                                 descs);
1650
42.5k
        } else {
1651
2.35k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.35k
        }
1653
44.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
44.9k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
44.9k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
44.8k
            _dag.insert({downstream_pipeline_id, {}});
1658
44.8k
        }
1659
44.9k
        cur_pipe = add_pipeline(cur_pipe);
1660
44.9k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
44.9k
        if (should_spill) {
1663
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
44.9k
        } else {
1666
44.9k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
44.9k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
44.9k
        }
1669
44.9k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
44.9k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
44.9k
        break;
1672
44.9k
    }
1673
44.9k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.65k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.65k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.65k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.65k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.65k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.63k
        }
1698
1.65k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.65k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.65k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.65k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.65k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.65k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.65k
        break;
1706
1.65k
    }
1707
1.65k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.64k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.64k
        break;
1711
1.64k
    }
1712
1.64k
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
297
    case TPlanNodeType::REPEAT_NODE: {
1723
297
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
297
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
297
        break;
1726
297
    }
1727
913
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
913
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
913
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
913
        break;
1731
913
    }
1732
913
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
218
        break;
1736
218
    }
1737
1.74k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.74k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.74k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.74k
        break;
1741
1.74k
    }
1742
1.74k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
466
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
466
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
466
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
466
        break;
1747
466
    }
1748
2.07k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.07k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.07k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.07k
        break;
1752
2.07k
    }
1753
6.96k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.96k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.96k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.96k
        break;
1757
6.96k
    }
1758
6.96k
    case TPlanNodeType::SELECT_NODE: {
1759
2.62k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.62k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.62k
        break;
1762
2.62k
    }
1763
2.62k
    case TPlanNodeType::REC_CTE_NODE: {
1764
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
151
        const auto downstream_pipeline_id = cur_pipe->id();
1768
151
        if (!_dag.contains(downstream_pipeline_id)) {
1769
149
            _dag.insert({downstream_pipeline_id, {}});
1770
149
        }
1771
1772
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
151
        DataSinkOperatorPtr anchor_sink;
1776
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
151
                                                                  op->operator_id(), tnode, descs);
1778
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
151
        DataSinkOperatorPtr rec_sink;
1786
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
151
                                                         tnode, descs);
1788
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
151
        break;
1793
151
    }
1794
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.95k
        break;
1798
1.95k
    }
1799
1.95k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
675k
    }
1803
672k
    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
672k
    return Status::OK();
1809
675k
}
1810
// NOLINTEND(readability-function-cognitive-complexity)
1811
// NOLINTEND(readability-function-size)
1812
1813
template <bool is_intersect>
1814
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1815
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1816
267
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
267
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
267
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
267
    const auto downstream_pipeline_id = cur_pipe->id();
1821
267
    if (!_dag.contains(downstream_pipeline_id)) {
1822
242
        _dag.insert({downstream_pipeline_id, {}});
1823
242
    }
1824
1825
895
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
628
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
628
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
628
        if (child_id == 0) {
1830
267
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
267
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
361
        } else {
1833
361
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
361
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
361
        }
1836
628
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
628
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
628
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
628
    }
1841
1842
267
    return Status::OK();
1843
267
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
134
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
134
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
134
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
134
    const auto downstream_pipeline_id = cur_pipe->id();
1821
134
    if (!_dag.contains(downstream_pipeline_id)) {
1822
118
        _dag.insert({downstream_pipeline_id, {}});
1823
118
    }
1824
1825
481
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
347
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
347
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
347
        if (child_id == 0) {
1830
134
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
134
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
213
        } else {
1833
213
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
213
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
213
        }
1836
347
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
347
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
347
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
347
    }
1841
1842
134
    return Status::OK();
1843
134
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
133
    const auto downstream_pipeline_id = cur_pipe->id();
1821
133
    if (!_dag.contains(downstream_pipeline_id)) {
1822
124
        _dag.insert({downstream_pipeline_id, {}});
1823
124
    }
1824
1825
414
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
281
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
281
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
281
        if (child_id == 0) {
1830
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
148
        } else {
1833
148
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
148
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
148
        }
1836
281
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
281
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
281
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
281
    }
1841
1842
133
    return Status::OK();
1843
133
}
1844
1845
444k
Status PipelineFragmentContext::submit() {
1846
444k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
444k
    _submitted = true;
1850
1851
444k
    int submit_tasks = 0;
1852
444k
    Status st;
1853
444k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.19M
    for (auto& task : _tasks) {
1855
2.01M
        for (auto& t : task) {
1856
2.01M
            st = scheduler->submit(t.first);
1857
2.01M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
2.01M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
2.01M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
2.01M
            submit_tasks++;
1866
2.01M
        }
1867
1.19M
    }
1868
444k
    if (!st.ok()) {
1869
0
        bool need_remove = false;
1870
0
        {
1871
0
            std::lock_guard<std::mutex> l(_task_mutex);
1872
0
            if (_closed_tasks >= _total_tasks) {
1873
0
                need_remove = _close_fragment_instance();
1874
0
            }
1875
0
        }
1876
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1877
0
        if (need_remove) {
1878
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1879
0
        }
1880
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1881
0
                                     BackendOptions::get_localhost());
1882
444k
    } else {
1883
444k
        return st;
1884
444k
    }
1885
444k
}
1886
1887
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1888
0
    if (_runtime_state->enable_profile()) {
1889
0
        std::stringstream ss;
1890
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1891
0
            runtime_profile_ptr->pretty_print(&ss);
1892
0
        }
1893
1894
0
        if (_runtime_state->load_channel_profile()) {
1895
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1896
0
        }
1897
1898
0
        auto profile_str =
1899
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1900
0
                            this->_fragment_id, extra_info, ss.str());
1901
0
        LOG_LONG_STRING(INFO, profile_str);
1902
0
    }
1903
0
}
1904
// If all pipeline tasks binded to the fragment instance are finished, then we could
1905
// close the fragment instance.
1906
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1907
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1908
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1909
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1910
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1911
// (via debug_string()).
1912
447k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
447k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
447k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
447k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
447k
    if (!_need_notify_close) {
1919
444k
        auto st = send_report(true);
1920
444k
        if (!st) {
1921
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1922
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1923
0
        }
1924
444k
    }
1925
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1926
    // Since stream load does not have someting like coordinator on FE, so
1927
    // backend can not report profile to FE, ant its profile can not be shown
1928
    // in the same way with other query. So we print the profile content to info log.
1929
1930
447k
    if (_runtime_state->enable_profile() &&
1931
447k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.19k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.19k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1934
0
        std::stringstream ss;
1935
        // Compute the _local_time_percent before pretty_print the runtime_profile
1936
        // Before add this operation, the print out like that:
1937
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1938
        // After add the operation, the print out like that:
1939
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1940
        // We can easily know the exec node execute time without child time consumed.
1941
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1942
0
            runtime_profile_ptr->pretty_print(&ss);
1943
0
        }
1944
1945
0
        if (_runtime_state->load_channel_profile()) {
1946
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1947
0
        }
1948
1949
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1950
0
    }
1951
1952
447k
    if (_query_ctx->enable_profile()) {
1953
2.19k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.19k
                                         collect_realtime_load_channel_profile());
1955
2.19k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
447k
    return !_need_notify_close;
1960
447k
}
1961
1962
2.00M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
2.00M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
2.00M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
694k
        if (_dag.contains(pipeline_id)) {
1967
366k
            for (auto dep : _dag[pipeline_id]) {
1968
366k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
366k
            }
1970
289k
        }
1971
694k
    }
1972
2.00M
    bool need_remove = false;
1973
2.00M
    {
1974
2.00M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
2.00M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
2.00M
        _query_ctx->inc_finished_task_num();
1978
2.00M
        if (_closed_tasks >= _total_tasks) {
1979
447k
            need_remove = _close_fragment_instance();
1980
447k
        }
1981
2.00M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
2.00M
    if (need_remove) {
1984
444k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
444k
    }
1986
2.00M
}
1987
1988
54.8k
std::string PipelineFragmentContext::get_load_error_url() {
1989
54.8k
    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
134k
    for (auto& tasks : _tasks) {
1993
205k
        for (auto& task : tasks) {
1994
205k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
183
                return to_load_error_http_path(str);
1996
183
            }
1997
205k
        }
1998
134k
    }
1999
54.6k
    return "";
2000
54.8k
}
2001
2002
54.8k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
54.8k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
134k
    for (auto& tasks : _tasks) {
2007
205k
        for (auto& task : tasks) {
2008
205k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
183
                return str;
2010
183
            }
2011
205k
        }
2012
134k
    }
2013
54.6k
    return "";
2014
54.8k
}
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
48.7k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
48.7k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
48.7k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
48.7k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
48.7k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
48.7k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
48.7k
    });
2031
2032
48.7k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
48.7k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
48.7k
    int callback_retries = 10;
2038
48.7k
    const int sleep_ms = 1000;
2039
48.7k
    Status exec_status = req.status;
2040
48.7k
    Status coord_status;
2041
48.7k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
48.7k
    do {
2043
48.7k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
48.7k
                                                            req.coord_addr, &coord_status);
2045
48.7k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
48.7k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
48.7k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
48.7k
    TReportExecStatusParams params;
2059
48.7k
    params.protocol_version = FrontendServiceVersion::V1;
2060
48.7k
    params.__set_query_id(req.query_id);
2061
48.7k
    params.__set_backend_num(req.backend_num);
2062
48.7k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
48.7k
    params.__set_fragment_id(req.fragment_id);
2064
48.7k
    params.__set_status(exec_status.to_thrift());
2065
48.7k
    params.__set_done(req.done);
2066
48.7k
    params.__set_query_type(req.runtime_state->query_type());
2067
48.7k
    params.__isset.profile = false;
2068
2069
48.7k
    DCHECK(req.runtime_state != nullptr);
2070
2071
48.7k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
44.4k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
44.4k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
44.4k
    } else {
2075
4.29k
        DCHECK(!req.runtime_states.empty());
2076
4.29k
        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
4.29k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.29k
    }
2086
2087
48.7k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
48.7k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
48.7k
    static std::string s_unselected_rows = "unselected.rows";
2090
48.7k
    int64_t num_rows_load_success = 0;
2091
48.7k
    int64_t num_rows_load_filtered = 0;
2092
48.7k
    int64_t num_rows_load_unselected = 0;
2093
48.7k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
48.7k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
48.7k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
48.7k
    } else if (!req.runtime_states.empty()) {
2109
144k
        for (auto* rs : req.runtime_states) {
2110
144k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
144k
                rs->num_finished_range() > 0) {
2112
37.2k
                params.__isset.load_counters = true;
2113
37.2k
                num_rows_load_success += rs->num_rows_load_success();
2114
37.2k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
37.2k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
37.2k
                params.__isset.fragment_instance_reports = true;
2117
37.2k
                TFragmentInstanceReport t;
2118
37.2k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
37.2k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
37.2k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
37.2k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
37.2k
                params.fragment_instance_reports.push_back(t);
2123
37.2k
            }
2124
144k
        }
2125
48.7k
    }
2126
48.7k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
48.7k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
48.7k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
48.7k
    if (!req.load_error_url.empty()) {
2131
171
        params.__set_tracking_url(req.load_error_url);
2132
171
    }
2133
48.7k
    if (!req.first_error_msg.empty()) {
2134
171
        params.__set_first_error_msg(req.first_error_msg);
2135
171
    }
2136
144k
    for (auto* rs : req.runtime_states) {
2137
144k
        if (rs->wal_id() > 0) {
2138
106
            params.__set_txn_id(rs->wal_id());
2139
106
            params.__set_label(rs->import_label());
2140
106
        }
2141
144k
    }
2142
48.7k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
48.7k
    } else if (!req.runtime_states.empty()) {
2146
144k
        for (auto* rs : req.runtime_states) {
2147
144k
            if (!rs->export_output_files().empty()) {
2148
0
                params.__isset.export_files = true;
2149
0
                params.export_files.insert(params.export_files.end(),
2150
0
                                           rs->export_output_files().begin(),
2151
0
                                           rs->export_output_files().end());
2152
0
            }
2153
144k
        }
2154
48.7k
    }
2155
48.7k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
48.7k
    } else if (!req.runtime_states.empty()) {
2159
144k
        for (auto* rs : req.runtime_states) {
2160
144k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
27.9k
                params.__isset.commitInfos = true;
2162
27.9k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
27.9k
            }
2164
144k
        }
2165
48.7k
    }
2166
48.7k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
48.7k
    } else if (!req.runtime_states.empty()) {
2170
144k
        for (auto* rs : req.runtime_states) {
2171
144k
            if (auto rs_eti = rs->error_tablet_infos(); !rs_eti.empty()) {
2172
0
                params.__isset.errorTabletInfos = true;
2173
0
                params.errorTabletInfos.insert(params.errorTabletInfos.end(), rs_eti.begin(),
2174
0
                                               rs_eti.end());
2175
0
            }
2176
144k
        }
2177
48.7k
    }
2178
48.7k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
48.7k
    } else if (!req.runtime_states.empty()) {
2183
144k
        for (auto* rs : req.runtime_states) {
2184
144k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.11k
                params.__isset.hive_partition_updates = true;
2186
2.11k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.11k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.11k
            }
2189
144k
        }
2190
48.7k
    }
2191
48.7k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
48.7k
    } else if (!req.runtime_states.empty()) {
2196
144k
        for (auto* rs : req.runtime_states) {
2197
144k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.08k
                params.__isset.iceberg_commit_datas = true;
2199
2.08k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.08k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.08k
            }
2202
144k
        }
2203
48.7k
    }
2204
2205
48.7k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
48.7k
    } else if (!req.runtime_states.empty()) {
2209
144k
        for (auto* rs : req.runtime_states) {
2210
144k
            if (auto rs_mcd = rs->mc_commit_datas(); !rs_mcd.empty()) {
2211
0
                params.__isset.mc_commit_datas = true;
2212
0
                params.mc_commit_datas.insert(params.mc_commit_datas.end(), rs_mcd.begin(),
2213
0
                                              rs_mcd.end());
2214
0
            }
2215
144k
        }
2216
48.7k
    }
2217
2218
48.7k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
48.7k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
48.7k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
48.7k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
48.7k
    }
2224
2225
48.7k
    TReportExecStatusResult res;
2226
48.7k
    Status rpc_status;
2227
2228
48.7k
    VLOG_DEBUG << "reportExecStatus params is "
2229
11
               << apache::thrift::ThriftDebugString(params).c_str();
2230
48.7k
    if (!exec_status.ok()) {
2231
1.66k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.66k
                     << " to coordinator: " << req.coord_addr
2233
1.66k
                     << ", query id: " << print_id(req.query_id);
2234
1.66k
    }
2235
48.7k
    try {
2236
48.7k
        try {
2237
48.7k
            (*coord)->reportExecStatus(res, params);
2238
48.7k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
48.7k
        rpc_status = Status::create<false>(res.status);
2254
48.7k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
48.7k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
48.7k
}
2265
2266
449k
Status PipelineFragmentContext::send_report(bool done) {
2267
449k
    Status exec_status = _query_ctx->exec_status();
2268
    // If plan is done successfully, but _is_report_success is false,
2269
    // no need to send report.
2270
    // Load will set _is_report_success to true because load wants to know
2271
    // the process.
2272
449k
    if (!_is_report_success && done && exec_status.ok()) {
2273
400k
        return Status::OK();
2274
400k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
48.9k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
245
        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
245
            return Status::OK();
2286
245
        }
2287
0
        return Status::NeedSendAgain("");
2288
245
    }
2289
2290
48.7k
    std::vector<RuntimeState*> runtime_states;
2291
2292
107k
    for (auto& tasks : _tasks) {
2293
145k
        for (auto& task : tasks) {
2294
145k
            runtime_states.push_back(task.second.get());
2295
145k
        }
2296
107k
    }
2297
2298
48.7k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
48.7k
                                        ? get_load_error_url()
2300
48.7k
                                        : _query_ctx->get_load_error_url();
2301
48.7k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
48.7k
                                          ? get_first_error_msg()
2303
48.7k
                                          : _query_ctx->get_first_error_msg();
2304
2305
48.7k
    ReportStatusRequest req {.status = exec_status,
2306
48.7k
                             .runtime_states = runtime_states,
2307
48.7k
                             .done = done || !exec_status.ok(),
2308
48.7k
                             .coord_addr = _query_ctx->coord_addr,
2309
48.7k
                             .query_id = _query_id,
2310
48.7k
                             .fragment_id = _fragment_id,
2311
48.7k
                             .fragment_instance_id = TUniqueId(),
2312
48.7k
                             .backend_num = -1,
2313
48.7k
                             .runtime_state = _runtime_state.get(),
2314
48.7k
                             .load_error_url = load_eror_url,
2315
48.7k
                             .first_error_msg = first_error_msg,
2316
48.7k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
48.7k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
48.7k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
48.7k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
48.7k
        _coordinator_callback(req);
2321
48.7k
        if (!req.done) {
2322
4.76k
            ctx->refresh_next_report_time();
2323
4.76k
        }
2324
48.7k
    });
2325
48.9k
}
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
121
std::string PipelineFragmentContext::debug_string() {
2365
121
    std::lock_guard<std::mutex> l(_task_mutex);
2366
121
    fmt::memory_buffer debug_string_buffer;
2367
121
    fmt::format_to(debug_string_buffer,
2368
121
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
121
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
121
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
351
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
230
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
588
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
358
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
358
                           _tasks[j][i].first->debug_string());
2376
358
        }
2377
230
    }
2378
2379
121
    return fmt::to_string(debug_string_buffer);
2380
121
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.19k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.19k
    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
2.19k
    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
2.19k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.19k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.19k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.00k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.00k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.00k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.00k
        res.push_back(profile_ptr);
2407
4.00k
    }
2408
2409
2.19k
    return res;
2410
2.19k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.19k
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
2.19k
    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
4.32k
    for (const auto& tasks : _tasks) {
2426
8.80k
        for (const auto& task : tasks) {
2427
8.80k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
8.80k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
8.80k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
8.80k
                                                           _runtime_state->profile_level());
2435
8.80k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
8.80k
        }
2437
4.32k
    }
2438
2439
2.19k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.19k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.19k
                                                      _runtime_state->profile_level());
2442
2.19k
    return load_channel_profile;
2443
2.19k
}
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
12.8k
    for (const auto& _task : _tasks) {
2455
19.7k
        for (const auto& task : _task) {
2456
19.7k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
19.7k
            result.merge(set);
2458
19.7k
        }
2459
12.8k
    }
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
449k
void PipelineFragmentContext::_release_resource() {
2468
449k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
449k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
449k
    auto st = _query_ctx->exec_status();
2472
1.19M
    for (auto& _task : _tasks) {
2473
1.19M
        if (!_task.empty()) {
2474
1.19M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.19M
        }
2476
1.19M
    }
2477
449k
    _tasks.clear();
2478
449k
    _dag.clear();
2479
449k
    _pip_id_to_pipeline.clear();
2480
449k
    _pipelines.clear();
2481
449k
    _sink.reset();
2482
449k
    _root_op.reset();
2483
449k
    _runtime_filter_mgr_map.clear();
2484
449k
    _op_id_to_shared_state.clear();
2485
449k
}
2486
2487
} // namespace doris