Coverage Report

Created: 2026-05-28 10:49

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
11
// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
114
#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
132
#include "util/client_cache.h"
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
450k
        : _query_id(std::move(query_id)),
144
450k
          _fragment_id(request.fragment_id),
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450k
          _exec_env(exec_env),
146
450k
          _query_ctx(std::move(query_ctx)),
147
450k
          _call_back(call_back),
148
450k
          _is_report_on_cancel(true),
149
450k
          _params(request),
150
450k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
450k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
450k
                                                               : false) {
153
450k
    _fragment_watcher.start();
154
450k
}
155
156
450k
PipelineFragmentContext::~PipelineFragmentContext() {
157
450k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
450k
            .tag("query_id", print_id(_query_id))
159
450k
            .tag("fragment_id", _fragment_id);
160
450k
    _release_resource();
161
450k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
450k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
450k
        _runtime_state.reset();
165
450k
        _query_ctx.reset();
166
450k
    }
167
450k
}
168
169
39
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
39
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
39
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
39
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
10.3k
bool PipelineFragmentContext::notify_close() {
181
10.3k
    bool all_closed = false;
182
10.3k
    bool need_remove = false;
183
10.3k
    {
184
10.3k
        std::lock_guard<std::mutex> l(_task_mutex);
185
10.3k
        if (_closed_tasks >= _total_tasks) {
186
3.49k
            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
3.42k
                need_remove = true;
193
3.42k
            }
194
3.49k
            all_closed = true;
195
3.49k
        }
196
        // make fragment release by self after cancel
197
10.3k
        _need_notify_close = false;
198
10.3k
    }
199
10.3k
    if (need_remove) {
200
3.42k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.42k
    }
202
10.3k
    return all_closed;
203
10.3k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
6.89k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.89k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.89k
            .tag("query_id", print_id(_query_id))
212
6.89k
            .tag("fragment_id", _fragment_id)
213
6.89k
            .tag("reason", reason.to_string());
214
6.89k
    if (notify_close()) {
215
86
        return;
216
86
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.80k
    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
6.80k
    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
6.81k
    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
6.80k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
6.80k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
6.80k
    _query_ctx->cancel(reason, _fragment_id);
243
6.80k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
359
        _is_report_on_cancel = false;
245
6.45k
    } else {
246
36.4k
        for (auto& id : _fragment_instance_ids) {
247
36.4k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
36.4k
        }
249
6.45k
    }
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
6.80k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.80k
    if (stream_load_ctx != nullptr) {
254
30
        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
30
        stream_load_ctx->error_url = get_load_error_url();
259
30
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
30
    }
261
262
37.2k
    for (auto& tasks : _tasks) {
263
82.2k
        for (auto& task : tasks) {
264
82.2k
            task.first->unblock_all_dependencies();
265
82.2k
        }
266
37.2k
    }
267
6.80k
}
268
269
704k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
704k
    PipelineId id = _next_pipeline_id++;
271
704k
    auto pipeline = std::make_shared<Pipeline>(
272
704k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
704k
            parent ? parent->num_tasks() : _num_instances);
274
704k
    if (idx >= 0) {
275
110k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
593k
    } else {
277
593k
        _pipelines.emplace_back(pipeline);
278
593k
    }
279
704k
    if (parent) {
280
247k
        parent->set_children(pipeline);
281
247k
    }
282
704k
    return pipeline;
283
704k
}
284
285
450k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
450k
    {
287
450k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
450k
        auto root_pipeline = add_pipeline();
290
450k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
450k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
450k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
450k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
450k
                                          _params.fragment.output_exprs, _params,
299
450k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
450k
                                          *_desc_tbl, root_pipeline->id()));
301
450k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
450k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
592k
        for (PipelinePtr& pipeline : _pipelines) {
305
592k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
592k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
592k
        }
308
450k
    }
309
    // 4. Build local exchanger
310
450k
    if (_runtime_state->enable_local_shuffle()) {
311
446k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
446k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
446k
                                             _params.bucket_seq_to_instance_idx,
314
446k
                                             _params.shuffle_idx_to_instance_idx));
315
446k
    }
316
317
    // 5. Initialize global states in pipelines.
318
705k
    for (PipelinePtr& pipeline : _pipelines) {
319
705k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
705k
        pipeline->children().clear();
321
705k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
705k
    }
323
324
448k
    {
325
448k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
448k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
448k
    }
329
330
448k
    return Status::OK();
331
448k
}
332
333
450k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
450k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
450k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
450k
        _timeout = _params.query_options.execution_timeout;
339
450k
    }
340
341
450k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
450k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
450k
    SCOPED_TIMER(_prepare_timer);
344
450k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
450k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
450k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
450k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
450k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
450k
    {
350
450k
        SCOPED_TIMER(_init_context_timer);
351
450k
        cast_set(_num_instances, _params.local_params.size());
352
450k
        _total_instances =
353
450k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
450k
        auto* fragment_context = this;
356
357
450k
        if (_params.query_options.__isset.is_report_success) {
358
448k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
448k
        }
360
361
        // 1. Set up the global runtime state.
362
450k
        _runtime_state = RuntimeState::create_unique(
363
450k
                _params.query_id, _params.fragment_id, _params.query_options,
364
450k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
450k
        _runtime_state->set_task_execution_context(shared_from_this());
366
450k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
450k
        if (_params.__isset.backend_id) {
368
446k
            _runtime_state->set_backend_id(_params.backend_id);
369
446k
        }
370
450k
        if (_params.__isset.import_label) {
371
241
            _runtime_state->set_import_label(_params.import_label);
372
241
        }
373
450k
        if (_params.__isset.db_name) {
374
193
            _runtime_state->set_db_name(_params.db_name);
375
193
        }
376
450k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
450k
        if (_params.is_simplified_param) {
381
154k
            _desc_tbl = _query_ctx->desc_tbl;
382
296k
        } else {
383
296k
            DCHECK(_params.__isset.desc_tbl);
384
296k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
296k
                                                  &_desc_tbl));
386
296k
        }
387
450k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
450k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
450k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
450k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
450k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
450k
        const auto target_size = _params.local_params.size();
395
450k
        _fragment_instance_ids.resize(target_size);
396
1.62M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.17M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.17M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.17M
        }
400
450k
    }
401
402
450k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
449k
    _init_next_report_time();
405
406
449k
    _prepared = true;
407
449k
    return Status::OK();
408
450k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.17M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.17M
    const auto& local_params = _params.local_params[instance_idx];
414
1.17M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.17M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.17M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.17M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.17M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.93M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.93M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.93M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.93M
                shared_state_map;
423
2.45M
        for (auto& op : pipeline->operators()) {
424
2.45M
            auto source_id = op->operator_id();
425
2.45M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.45M
                iter != _op_id_to_shared_state.end()) {
427
734k
                shared_state_map.insert({source_id, iter->second});
428
734k
            }
429
2.45M
        }
430
1.93M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.93M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.93M
                iter != _op_id_to_shared_state.end()) {
433
272k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
272k
            }
435
1.93M
        }
436
1.93M
        return shared_state_map;
437
1.93M
    };
438
439
3.56M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.39M
        auto& pipeline = _pipelines[pip_idx];
441
2.39M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.93M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.93M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.93M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.93M
            {
446
                // Initialize runtime state for this task
447
1.93M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.93M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.93M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.93M
                if (_params.__isset.backend_id) {
453
1.93M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.93M
                }
455
1.93M
                if (_params.__isset.import_label) {
456
242
                    task_runtime_state->set_import_label(_params.import_label);
457
242
                }
458
1.93M
                if (_params.__isset.db_name) {
459
194
                    task_runtime_state->set_db_name(_params.db_name);
460
194
                }
461
1.93M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.93M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.93M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.93M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.93M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.93M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.93M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.93M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.93M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.93M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.93M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.93M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.93M
            }
482
1.93M
            auto cur_task_id = _total_tasks++;
483
1.93M
            task_runtime_state->set_task_id(cur_task_id);
484
1.93M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.93M
            auto task = std::make_shared<PipelineTask>(
486
1.93M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.93M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.93M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.93M
                    instance_idx);
490
1.93M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.93M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.93M
            _tasks[instance_idx].emplace_back(
493
1.93M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.93M
                            std::move(task), std::move(task_runtime_state)});
495
1.93M
        }
496
2.39M
    }
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
2.39M
    for (auto& _pipeline : _pipelines) {
516
2.39M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.93M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.93M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.93M
            if (_dag.contains(_pipeline->id())) {
522
1.22M
                auto& deps = _dag[_pipeline->id()];
523
1.93M
                for (auto& dep : deps) {
524
1.93M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.01M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.01M
                        if (ss) {
527
477k
                            task->inject_shared_state(ss);
528
538k
                        } else {
529
538k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
538k
                                    task->get_source_shared_state());
531
538k
                        }
532
1.01M
                    }
533
1.93M
                }
534
1.22M
            }
535
1.93M
        }
536
2.39M
    }
537
3.56M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.39M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.93M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.93M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.93M
            std::vector<TScanRangeParams> scan_ranges;
542
1.93M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.93M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
336k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
336k
            }
546
1.93M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.93M
                                                             _params.fragment.output_sink));
548
1.93M
        }
549
2.39M
    }
550
1.17M
    {
551
1.17M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.17M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.17M
    }
554
1.17M
    return Status::OK();
555
1.17M
}
556
557
449k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
449k
    _total_tasks = 0;
559
449k
    _closed_tasks = 0;
560
449k
    const auto target_size = _params.local_params.size();
561
449k
    _tasks.resize(target_size);
562
449k
    _runtime_filter_mgr_map.resize(target_size);
563
1.15M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
703k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
703k
    }
566
449k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
449k
    if (target_size > 1 &&
569
449k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
146k
         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
10.2k
        std::vector<Status> prepare_status(target_size);
573
10.2k
        int submitted_tasks = 0;
574
10.2k
        Status submit_status;
575
10.2k
        CountDownLatch latch((int)target_size);
576
137k
        for (int i = 0; i < target_size; i++) {
577
127k
            submit_status = thread_pool->submit_func([&, i]() {
578
127k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
127k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
127k
                latch.count_down();
581
127k
            });
582
127k
            if (LIKELY(submit_status.ok())) {
583
127k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
127k
        }
588
10.2k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
10.2k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
137k
        for (int i = 0; i < submitted_tasks; i++) {
593
127k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
127k
        }
597
439k
    } else {
598
1.48M
        for (int i = 0; i < target_size; i++) {
599
1.04M
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
1.04M
        }
601
439k
    }
602
449k
    _pipeline_parent_map.clear();
603
449k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
449k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
449k
    return Status::OK();
608
449k
}
609
610
448k
void PipelineFragmentContext::_init_next_report_time() {
611
448k
    auto interval_s = config::pipeline_status_report_interval;
612
448k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
42.5k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.5k
        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
42.5k
        _previous_report_time =
617
42.5k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.5k
        _disable_period_report = false;
619
42.5k
    }
620
448k
}
621
622
4.84k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.84k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.84k
    DCHECK(disable == true);
625
4.84k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.84k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.84k
}
628
629
7.13M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.13M
    if (!_is_report_success) {
631
6.67M
        return;
632
6.67M
    }
633
462k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
462k
    if (disable) {
635
8.34k
        return;
636
8.34k
    }
637
454k
    int32_t interval_s = config::pipeline_status_report_interval;
638
454k
    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
454k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
454k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
454k
    if (MonotonicNanos() > next_report_time) {
646
4.85k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.85k
                                                            std::memory_order_acq_rel)) {
648
10
            return;
649
10
        }
650
4.84k
        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
4.84k
        auto st = send_report(false);
667
4.84k
        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
4.84k
    }
673
454k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
446k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
446k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
446k
    int node_idx = 0;
682
683
446k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
446k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
446k
    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
446k
    return Status::OK();
691
446k
}
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
700k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
700k
    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
700k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
700k
    int num_children = tnodes[*node_idx].num_children;
706
700k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
700k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
700k
    OperatorPtr op = nullptr;
710
700k
    OperatorPtr cache_op = nullptr;
711
700k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
700k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
700k
                                     followed_by_shuffled_operator,
714
700k
                                     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
700k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
700k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
252k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
448k
    } else {
723
448k
        *root = op;
724
448k
    }
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
700k
    auto required_data_distribution =
737
700k
            cur_pipe->operators().empty()
738
700k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
700k
                    : op->required_data_distribution(_runtime_state.get());
740
700k
    current_followed_by_shuffled_operator =
741
700k
            ((followed_by_shuffled_operator ||
742
700k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
641k
                                             : op->is_shuffled_operator())) &&
744
700k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
700k
            (followed_by_shuffled_operator &&
746
587k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
700k
    current_require_bucket_distribution =
749
700k
            ((require_bucket_distribution ||
750
700k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
645k
                                             : op->is_colocated_operator())) &&
752
700k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
700k
            (require_bucket_distribution &&
754
593k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
700k
    if (num_children == 0) {
757
465k
        _use_serial_source = op->is_serial_operator();
758
465k
    }
759
    // rely on that tnodes is preorder of the plan
760
952k
    for (int i = 0; i < num_children; i++) {
761
252k
        ++*node_idx;
762
252k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
252k
                                            current_followed_by_shuffled_operator,
764
252k
                                            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
252k
        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
252k
    }
775
776
700k
    return Status::OK();
777
700k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
110k
        PipelinePtr pipe_with_sink) {
782
110k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
110k
    pipe_with_source->set_num_tasks(_num_instances);
784
110k
    pipe_with_source->set_data_distribution(data_distribution);
785
110k
}
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
110k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
110k
    auto& operators = cur_pipe->operators();
793
110k
    const auto downstream_pipeline_id = cur_pipe->id();
794
110k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
110k
    DataSinkOperatorPtr sink;
797
110k
    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
110k
    const bool followed_by_shuffled_operator =
804
110k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
110k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
110k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
110k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
110k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
110k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
110k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
110k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
110k
    if (bucket_seq_to_instance_idx.empty() &&
813
110k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
6
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
6
    }
816
110k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
110k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
110k
                                          num_buckets, use_global_hash_shuffle,
819
110k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
110k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
110k
            LocalExchangeSharedState::create_shared(_num_instances);
824
110k
    switch (data_distribution.distribution_type) {
825
10.9k
    case ExchangeType::HASH_SHUFFLE:
826
10.9k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
10.9k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
10.9k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
10.9k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
10.9k
                        ? cast_set<int>(
831
10.9k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
10.9k
                        : 0);
833
10.9k
        break;
834
496
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
496
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
496
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
496
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
496
                        ? cast_set<int>(
839
496
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
496
                        : 0);
841
496
        break;
842
95.6k
    case ExchangeType::PASSTHROUGH:
843
95.6k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
95.6k
                cur_pipe->num_tasks(), _num_instances,
845
95.6k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
95.6k
                        ? cast_set<int>(
847
95.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
95.6k
                        : 0);
849
95.6k
        break;
850
345
    case ExchangeType::BROADCAST:
851
345
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
345
                cur_pipe->num_tasks(), _num_instances,
853
345
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
345
                        ? cast_set<int>(
855
345
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
345
                        : 0);
857
345
        break;
858
2.49k
    case ExchangeType::PASS_TO_ONE:
859
2.49k
        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
1.50k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.50k
                    cur_pipe->num_tasks(), _num_instances,
863
1.50k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.50k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.50k
                                                    .local_exchange_free_blocks_limit)
866
1.50k
                            : 0);
867
1.50k
        } else {
868
991
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
991
                    cur_pipe->num_tasks(), _num_instances,
870
991
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
991
                            ? cast_set<int>(_runtime_state->query_options()
872
991
                                                    .local_exchange_free_blocks_limit)
873
991
                            : 0);
874
991
        }
875
2.49k
        break;
876
901
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
901
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
901
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
901
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
901
                        ? cast_set<int>(
881
901
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
901
                        : 0);
883
901
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
110k
    }
888
110k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
110k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
110k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
110k
    _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
110k
    std::copy(operators.begin(), operators.begin() + idx,
898
110k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
110k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
110k
    OperatorPtr source_op;
905
110k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
110k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
110k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
110k
    if (!operators.empty()) {
909
47.2k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
47.2k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
47.2k
    }
912
110k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
110k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
110k
    std::vector<PipelineId> edges_with_source;
917
128k
    for (auto child : cur_pipe->children()) {
918
128k
        bool found = false;
919
143k
        for (auto op : new_pip->operators()) {
920
143k
            if (child->sink()->node_id() == op->node_id()) {
921
12.7k
                new_pip->set_children(child);
922
12.7k
                found = true;
923
12.7k
            };
924
143k
        }
925
128k
        if (!found) {
926
115k
            new_children.push_back(child);
927
115k
            edges_with_source.push_back(child->id());
928
115k
        }
929
128k
    }
930
110k
    new_children.push_back(new_pip);
931
110k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
110k
    if (!new_pip->children().empty()) {
935
7.33k
        std::vector<PipelineId> edges_with_sink;
936
12.7k
        for (auto child : new_pip->children()) {
937
12.7k
            edges_with_sink.push_back(child->id());
938
12.7k
        }
939
7.33k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.33k
    }
941
110k
    cur_pipe->set_children(new_children);
942
110k
    _dag[downstream_pipeline_id] = edges_with_source;
943
110k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
110k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
110k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
110k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
110k
    return Status::OK();
950
110k
}
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
197k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
197k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
46.7k
        return Status::OK();
959
46.7k
    }
960
961
150k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
50.8k
        return Status::OK();
963
50.8k
    }
964
99.6k
    *do_local_exchange = true;
965
966
99.6k
    auto& operators = cur_pipe->operators();
967
99.6k
    auto total_op_num = operators.size();
968
99.6k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
99.6k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
99.6k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
99.6k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
99.6k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
139
            << "total_op_num: " << total_op_num
975
139
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
139
            << " 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
99.6k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
99.6k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
11.2k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
11.2k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
11.2k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
11.2k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
11.2k
                shuffle_idx_to_instance_idx));
990
11.2k
    }
991
99.6k
    return Status::OK();
992
99.6k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
445k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.03M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
589k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
589k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
136k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
136k
                if (child->sink()->node_id() ==
1003
136k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
120k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
120k
                }
1006
136k
            }
1007
130k
        }
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
589k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
589k
                                             bucket_seq_to_instance_idx,
1014
589k
                                             shuffle_idx_to_instance_idx));
1015
589k
    }
1016
445k
    return Status::OK();
1017
445k
}
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
588k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
588k
    int idx = 1;
1024
588k
    bool do_local_exchange = false;
1025
635k
    do {
1026
635k
        auto& ops = pip->operators();
1027
635k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
704k
        for (; idx < ops.size();) {
1030
116k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
104k
                RETURN_IF_ERROR(_add_local_exchange(
1032
104k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
104k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
104k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
104k
                        shuffle_idx_to_instance_idx));
1036
104k
            }
1037
116k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
47.5k
                idx = 2;
1043
47.5k
                break;
1044
47.5k
            }
1045
69.0k
            idx++;
1046
69.0k
        }
1047
635k
    } while (do_local_exchange);
1048
588k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
92.3k
        RETURN_IF_ERROR(_add_local_exchange(
1050
92.3k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
92.3k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
92.3k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
92.3k
    }
1054
588k
    return Status::OK();
1055
588k
}
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
449k
                                                  PipelineId cur_pipeline_id) {
1063
449k
    switch (thrift_sink.type) {
1064
151k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
151k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
151k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
151k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
151k
                params.destinations, _fragment_instance_ids);
1071
151k
        break;
1072
151k
    }
1073
257k
    case TDataSinkType::RESULT_SINK: {
1074
257k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
257k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
257k
        int child_node_id = pipeline->operators().back()->node_id();
1080
257k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
257k
                                                      row_desc, output_exprs,
1082
257k
                                                      thrift_sink.result_sink);
1083
257k
        break;
1084
257k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
33.7k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
33.7k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
33.7k
        int child_node_id = pipeline->operators().back()->node_id();
1098
33.7k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
33.7k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
33.7k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.82k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.82k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
30.8k
        } else {
1104
30.8k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
30.8k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
30.8k
        }
1107
33.7k
        break;
1108
0
    }
1109
166
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
166
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
166
        DCHECK(state->get_query_ctx() != nullptr);
1112
166
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
166
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
166
                                                                output_exprs);
1115
166
        break;
1116
0
    }
1117
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.46k
                                                         output_exprs);
1123
1.46k
        break;
1124
1.46k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
1.73k
        } else {
1133
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.73k
                                                                row_desc, output_exprs);
1135
1.73k
        }
1136
1.73k
        break;
1137
1.73k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
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
2.41k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.41k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.41k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.41k
        auto sink_id = next_sink_operator_id();
1205
2.41k
        const int multi_cast_node_id = sink_id;
1206
2.41k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.41k
        std::vector<int> sources;
1209
9.45k
        for (int i = 0; i < sender_size; ++i) {
1210
7.04k
            auto source_id = next_operator_id();
1211
7.04k
            sources.push_back(source_id);
1212
7.04k
        }
1213
1214
2.41k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.41k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
9.45k
        for (int i = 0; i < sender_size; ++i) {
1217
7.04k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
7.04k
            RowDescriptor* exchange_row_desc = nullptr;
1220
7.04k
            {
1221
7.04k
                const auto& tmp_row_desc =
1222
7.04k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
7.04k
                                ? RowDescriptor(state->desc_tbl(),
1224
7.04k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
7.04k
                                                         .output_tuple_id})
1226
7.04k
                                : row_desc;
1227
7.04k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
7.04k
            }
1229
7.04k
            auto source_id = sources[i];
1230
7.04k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
7.04k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
7.04k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
7.04k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
7.04k
                    /*operator_id=*/source_id);
1236
7.04k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
7.04k
                    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
7.04k
            DataSinkOperatorPtr sink_op;
1241
7.04k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
7.04k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
7.04k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
7.04k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
7.04k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
7.04k
            {
1248
7.04k
                TDataSink* t = pool->add(new TDataSink());
1249
7.04k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
7.04k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
7.04k
            }
1252
1253
            // 3. set dependency dag
1254
7.04k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
7.04k
        }
1256
2.41k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.41k
        break;
1260
2.41k
    }
1261
2.41k
    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
449k
    }
1280
449k
    return Status::OK();
1281
449k
}
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
703k
                                                 OperatorPtr& cache_op) {
1292
703k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
703k
    Defer defer = Defer([&]() {
1294
701k
        if (op) {
1295
701k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
701k
        }
1297
701k
        for (auto& s : sink_ops) {
1298
136k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
136k
        }
1300
701k
    });
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
703k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
703k
    std::stringstream error_msg;
1305
703k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
703k
    bool fe_with_old_version = false;
1308
703k
    switch (tnode.node_type) {
1309
218k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
218k
        op = std::make_shared<OlapScanOperatorX>(
1311
218k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
218k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
218k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
218k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
218k
        break;
1316
218k
    }
1317
80
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
80
        DCHECK(_query_ctx != nullptr);
1319
80
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
80
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
80
                                                    _num_instances);
1322
80
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
80
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
80
        break;
1325
80
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
25.3k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
25.3k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
25.3k
                                                 _num_instances);
1342
25.3k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
25.3k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
25.3k
        break;
1345
25.3k
    }
1346
156k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
156k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
156k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
156k
        DCHECK_GT(num_senders, 0);
1351
156k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
156k
                                                       num_senders);
1353
156k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
156k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
156k
        break;
1356
156k
    }
1357
167k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
167k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
167k
            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
167k
        bool need_create_cache_op =
1364
167k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
167k
        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
167k
        const bool group_by_limit_opt =
1385
167k
                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
167k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
167k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
167k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
167k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
167k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
167k
        const bool can_use_distinct_streaming_agg =
1396
167k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
167k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
167k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
167k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
167k
        if (can_use_distinct_streaming_agg) {
1402
91.9k
            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
91.8k
            } else {
1413
91.8k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
91.8k
                                                                     tnode, descs);
1415
91.8k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
91.8k
            }
1417
91.9k
        } else if (is_streaming_agg) {
1418
3.62k
            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
3.62k
            } else {
1428
3.62k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
3.62k
                                                             descs);
1430
3.62k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
3.62k
            }
1432
72.2k
        } else {
1433
            // create new pipeline to add query cache operator
1434
72.2k
            PipelinePtr new_pipe;
1435
72.2k
            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
72.2k
            if (enable_spill) {
1441
170
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
170
                                                                     next_operator_id(), descs);
1443
72.1k
            } else {
1444
72.1k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
72.1k
            }
1446
72.2k
            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
72.2k
            } else {
1451
72.2k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
72.2k
            }
1453
1454
72.2k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
72.2k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
69.4k
                _dag.insert({downstream_pipeline_id, {}});
1457
69.4k
            }
1458
72.2k
            cur_pipe = add_pipeline(cur_pipe);
1459
72.2k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
72.2k
            if (enable_spill) {
1462
170
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
170
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
72.1k
            } else {
1465
72.1k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
72.1k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
72.1k
            }
1468
72.2k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
72.2k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
72.2k
        }
1471
167k
        break;
1472
167k
    }
1473
167k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
76
        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
76
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
76
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
76
        const auto downstream_pipeline_id = cur_pipe->id();
1486
76
        if (!_dag.contains(downstream_pipeline_id)) {
1487
76
            _dag.insert({downstream_pipeline_id, {}});
1488
76
        }
1489
76
        cur_pipe = add_pipeline(cur_pipe);
1490
76
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
76
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
76
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
76
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
76
        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
76
        {
1503
76
            auto shared_state = BucketedAggSharedState::create_shared();
1504
76
            shared_state->id = op->operator_id();
1505
76
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
374
            for (int i = 0; i < _num_instances; i++) {
1508
298
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
298
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
298
                sink_dep->set_shared_state(shared_state.get());
1511
298
                shared_state->sink_deps.push_back(sink_dep);
1512
298
            }
1513
76
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
76
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
76
            _op_id_to_shared_state.insert(
1516
76
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
76
        }
1518
76
        break;
1519
76
    }
1520
9.74k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.74k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.74k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.74k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.74k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
9.74k
        } else {
1566
9.74k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.74k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.74k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.74k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
8.03k
                _dag.insert({downstream_pipeline_id, {}});
1572
8.03k
            }
1573
9.74k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.74k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.74k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.74k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.74k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.74k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.74k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.74k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.74k
        }
1584
9.74k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.60k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.60k
                    HashJoinSharedState::create_shared(_num_instances);
1587
17.4k
            for (int i = 0; i < _num_instances; i++) {
1588
14.8k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
14.8k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
14.8k
                sink_dep->set_shared_state(shared_state.get());
1591
14.8k
                shared_state->sink_deps.push_back(sink_dep);
1592
14.8k
            }
1593
2.60k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.60k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.60k
            _op_id_to_shared_state.insert(
1596
2.60k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.60k
        }
1598
9.74k
        break;
1599
9.74k
    }
1600
5.77k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
5.77k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
5.77k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
5.77k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
5.77k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
5.55k
            _dag.insert({downstream_pipeline_id, {}});
1607
5.55k
        }
1608
5.77k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
5.77k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
5.77k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
5.77k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
5.77k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
5.77k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
5.77k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
5.77k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
5.77k
        break;
1618
5.77k
    }
1619
53.7k
    case TPlanNodeType::UNION_NODE: {
1620
53.7k
        int child_count = tnode.num_children;
1621
53.7k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
53.7k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
53.7k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
53.7k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
53.2k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.2k
        }
1628
55.2k
        for (int i = 0; i < child_count; i++) {
1629
1.40k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.40k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.40k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.40k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.40k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.40k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.40k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.40k
        }
1638
53.7k
        break;
1639
53.7k
    }
1640
53.7k
    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
2.39k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.39k
        }
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
44.9k
            _dag.insert({downstream_pipeline_id, {}});
1658
44.9k
        }
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
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.63k
        }
1698
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.64k
        break;
1706
1.64k
    }
1707
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.60k
        break;
1711
1.60k
    }
1712
1.60k
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
297
    case TPlanNodeType::REPEAT_NODE: {
1723
297
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
297
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
297
        break;
1726
297
    }
1727
914
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
914
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
914
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
914
        break;
1731
914
    }
1732
914
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
218
        break;
1736
218
    }
1737
1.69k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.69k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.69k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.69k
        break;
1741
1.69k
    }
1742
1.69k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
464
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
464
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
464
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
464
        break;
1747
464
    }
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
6.92k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.92k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.92k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.92k
        break;
1757
6.92k
    }
1758
6.92k
    case TPlanNodeType::SELECT_NODE: {
1759
2.41k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.41k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.41k
        break;
1762
2.41k
    }
1763
2.41k
    case TPlanNodeType::REC_CTE_NODE: {
1764
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
151
        const auto downstream_pipeline_id = cur_pipe->id();
1768
151
        if (!_dag.contains(downstream_pipeline_id)) {
1769
148
            _dag.insert({downstream_pipeline_id, {}});
1770
148
        }
1771
1772
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
151
        DataSinkOperatorPtr anchor_sink;
1776
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
151
                                                                  op->operator_id(), tnode, descs);
1778
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
151
        DataSinkOperatorPtr rec_sink;
1786
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
151
                                                         tnode, descs);
1788
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
151
        break;
1793
151
    }
1794
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.95k
        break;
1798
1.95k
    }
1799
1.95k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
703k
    }
1803
700k
    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
700k
    return Status::OK();
1809
703k
}
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
447k
Status PipelineFragmentContext::submit() {
1846
447k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
447k
    _submitted = true;
1850
1851
447k
    int submit_tasks = 0;
1852
447k
    Status st;
1853
447k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.17M
    for (auto& task : _tasks) {
1855
1.93M
        for (auto& t : task) {
1856
1.93M
            st = scheduler->submit(t.first);
1857
1.93M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.93M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.93M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
1.93M
            submit_tasks++;
1866
1.93M
        }
1867
1.17M
    }
1868
447k
    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
447k
    } else {
1883
447k
        return st;
1884
447k
    }
1885
447k
}
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
449k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
449k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
449k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
449k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
449k
    if (!_need_notify_close) {
1919
446k
        auto st = send_report(true);
1920
446k
        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
446k
    }
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
449k
    if (_runtime_state->enable_profile() &&
1931
449k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.56k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.56k
         _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
449k
    if (_query_ctx->enable_profile()) {
1953
2.56k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.56k
                                         collect_realtime_load_channel_profile());
1955
2.56k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
449k
    return !_need_notify_close;
1960
449k
}
1961
1962
1.92M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
1.92M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.92M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
704k
        if (_dag.contains(pipeline_id)) {
1967
365k
            for (auto dep : _dag[pipeline_id]) {
1968
365k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
365k
            }
1970
296k
        }
1971
704k
    }
1972
1.92M
    bool need_remove = false;
1973
1.92M
    {
1974
1.92M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.92M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.92M
        _query_ctx->inc_finished_task_num();
1978
1.92M
        if (_closed_tasks >= _total_tasks) {
1979
449k
            need_remove = _close_fragment_instance();
1980
449k
        }
1981
1.92M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.92M
    if (need_remove) {
1984
446k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
446k
    }
1986
1.92M
}
1987
1988
55.7k
std::string PipelineFragmentContext::get_load_error_url() {
1989
55.7k
    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
148k
    for (auto& tasks : _tasks) {
1993
235k
        for (auto& task : tasks) {
1994
235k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
172
                return to_load_error_http_path(str);
1996
172
            }
1997
235k
        }
1998
148k
    }
1999
55.5k
    return "";
2000
55.7k
}
2001
2002
55.7k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
55.7k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
148k
    for (auto& tasks : _tasks) {
2007
235k
        for (auto& task : tasks) {
2008
235k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
172
                return str;
2010
172
            }
2011
235k
        }
2012
148k
    }
2013
55.5k
    return "";
2014
55.7k
}
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
48.9k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
48.9k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
48.9k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
48.9k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
48.9k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
48.9k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
48.9k
    });
2031
2032
48.9k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
48.9k
    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
48.9k
    int callback_retries = 10;
2038
48.9k
    const int sleep_ms = 1000;
2039
48.9k
    Status exec_status = req.status;
2040
48.9k
    Status coord_status;
2041
48.9k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
48.9k
    do {
2043
48.9k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
48.9k
                                                            req.coord_addr, &coord_status);
2045
48.9k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
48.9k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
48.9k
    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
48.9k
    TReportExecStatusParams params;
2059
48.9k
    params.protocol_version = FrontendServiceVersion::V1;
2060
48.9k
    params.__set_query_id(req.query_id);
2061
48.9k
    params.__set_backend_num(req.backend_num);
2062
48.9k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
48.9k
    params.__set_fragment_id(req.fragment_id);
2064
48.9k
    params.__set_status(exec_status.to_thrift());
2065
48.9k
    params.__set_done(req.done);
2066
48.9k
    params.__set_query_type(req.runtime_state->query_type());
2067
48.9k
    params.__isset.profile = false;
2068
2069
48.9k
    DCHECK(req.runtime_state != nullptr);
2070
2071
48.9k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
44.2k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
44.2k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
44.2k
    } else {
2075
4.66k
        DCHECK(!req.runtime_states.empty());
2076
4.66k
        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
4.66k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.66k
    }
2086
2087
48.9k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
48.9k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
48.9k
    static std::string s_unselected_rows = "unselected.rows";
2090
48.9k
    int64_t num_rows_load_success = 0;
2091
48.9k
    int64_t num_rows_load_filtered = 0;
2092
48.9k
    int64_t num_rows_load_unselected = 0;
2093
48.9k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
48.9k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
48.9k
        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
48.9k
    } else if (!req.runtime_states.empty()) {
2109
153k
        for (auto* rs : req.runtime_states) {
2110
153k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
153k
                rs->num_finished_range() > 0) {
2112
36.9k
                params.__isset.load_counters = true;
2113
36.9k
                num_rows_load_success += rs->num_rows_load_success();
2114
36.9k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
36.9k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
36.9k
                params.__isset.fragment_instance_reports = true;
2117
36.9k
                TFragmentInstanceReport t;
2118
36.9k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
36.9k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
36.9k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
36.9k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
36.9k
                params.fragment_instance_reports.push_back(t);
2123
36.9k
            }
2124
153k
        }
2125
48.9k
    }
2126
48.9k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
48.9k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
48.9k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
48.9k
    if (!req.load_error_url.empty()) {
2131
158
        params.__set_tracking_url(req.load_error_url);
2132
158
    }
2133
48.9k
    if (!req.first_error_msg.empty()) {
2134
158
        params.__set_first_error_msg(req.first_error_msg);
2135
158
    }
2136
153k
    for (auto* rs : req.runtime_states) {
2137
153k
        if (rs->wal_id() > 0) {
2138
105
            params.__set_txn_id(rs->wal_id());
2139
105
            params.__set_label(rs->import_label());
2140
105
        }
2141
153k
    }
2142
48.9k
    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
48.9k
    } else if (!req.runtime_states.empty()) {
2146
153k
        for (auto* rs : req.runtime_states) {
2147
153k
            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
153k
        }
2154
48.9k
    }
2155
48.9k
    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
48.9k
    } else if (!req.runtime_states.empty()) {
2159
153k
        for (auto* rs : req.runtime_states) {
2160
153k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
27.8k
                params.__isset.commitInfos = true;
2162
27.8k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
27.8k
            }
2164
153k
        }
2165
48.9k
    }
2166
48.9k
    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
48.9k
    } else if (!req.runtime_states.empty()) {
2170
153k
        for (auto* rs : req.runtime_states) {
2171
153k
            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
153k
        }
2177
48.9k
    }
2178
48.9k
    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
48.9k
    } else if (!req.runtime_states.empty()) {
2183
153k
        for (auto* rs : req.runtime_states) {
2184
153k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.14k
                params.__isset.hive_partition_updates = true;
2186
2.14k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.14k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.14k
            }
2189
153k
        }
2190
48.9k
    }
2191
48.9k
    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
48.9k
    } else if (!req.runtime_states.empty()) {
2196
153k
        for (auto* rs : req.runtime_states) {
2197
153k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.05k
                params.__isset.iceberg_commit_datas = true;
2199
2.05k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.05k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.05k
            }
2202
153k
        }
2203
48.9k
    }
2204
2205
48.9k
    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
48.9k
    } else if (!req.runtime_states.empty()) {
2209
153k
        for (auto* rs : req.runtime_states) {
2210
153k
            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
153k
        }
2216
48.9k
    }
2217
2218
48.9k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
48.9k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
48.9k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
48.9k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
48.9k
    }
2224
2225
48.9k
    TReportExecStatusResult res;
2226
48.9k
    Status rpc_status;
2227
2228
48.9k
    VLOG_DEBUG << "reportExecStatus params is "
2229
6
               << apache::thrift::ThriftDebugString(params).c_str();
2230
48.9k
    if (!exec_status.ok()) {
2231
1.69k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.69k
                     << " to coordinator: " << req.coord_addr
2233
1.69k
                     << ", query id: " << print_id(req.query_id);
2234
1.69k
    }
2235
48.9k
    try {
2236
48.9k
        try {
2237
48.9k
            (*coord)->reportExecStatus(res, params);
2238
48.9k
        } 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
48.9k
        rpc_status = Status::create<false>(res.status);
2254
48.9k
    } 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
48.9k
    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
48.9k
}
2265
2266
451k
Status PipelineFragmentContext::send_report(bool done) {
2267
451k
    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
451k
    if (!_is_report_success && done && exec_status.ok()) {
2273
402k
        return Status::OK();
2274
402k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
49.2k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
312
        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
312
            return Status::OK();
2286
312
        }
2287
0
        return Status::NeedSendAgain("");
2288
312
    }
2289
2290
48.8k
    std::vector<RuntimeState*> runtime_states;
2291
2292
111k
    for (auto& tasks : _tasks) {
2293
153k
        for (auto& task : tasks) {
2294
153k
            runtime_states.push_back(task.second.get());
2295
153k
        }
2296
111k
    }
2297
2298
48.8k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
48.9k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
48.8k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
48.9k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
48.8k
    ReportStatusRequest req {.status = exec_status,
2306
48.8k
                             .runtime_states = runtime_states,
2307
48.8k
                             .done = done || !exec_status.ok(),
2308
48.8k
                             .coord_addr = _query_ctx->coord_addr,
2309
48.8k
                             .query_id = _query_id,
2310
48.8k
                             .fragment_id = _fragment_id,
2311
48.8k
                             .fragment_instance_id = TUniqueId(),
2312
48.8k
                             .backend_num = -1,
2313
48.8k
                             .runtime_state = _runtime_state.get(),
2314
48.8k
                             .load_error_url = load_eror_url,
2315
48.8k
                             .first_error_msg = first_error_msg,
2316
48.8k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
48.8k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
48.9k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
48.9k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
48.9k
        _coordinator_callback(req);
2321
48.9k
        if (!req.done) {
2322
4.84k
            ctx->refresh_next_report_time();
2323
4.84k
        }
2324
48.9k
    });
2325
49.2k
}
2326
2327
8
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
8
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
8
    for (const auto& task_instances : _tasks) {
2332
12
        for (const auto& task : task_instances) {
2333
12
            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
12
            size_t revocable_size = task.first->get_revocable_size();
2342
12
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
4
                res += revocable_size;
2344
4
            }
2345
12
        }
2346
8
    }
2347
8
    return res;
2348
8
}
2349
2350
16
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
16
    std::vector<PipelineTask*> revocable_tasks;
2352
16
    for (const auto& task_instances : _tasks) {
2353
24
        for (const auto& task : task_instances) {
2354
24
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
24
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
8
                revocable_tasks.emplace_back(task.first.get());
2358
8
            }
2359
24
        }
2360
16
    }
2361
16
    return revocable_tasks;
2362
16
}
2363
2364
40
std::string PipelineFragmentContext::debug_string() {
2365
40
    std::lock_guard<std::mutex> l(_task_mutex);
2366
40
    fmt::memory_buffer debug_string_buffer;
2367
40
    fmt::format_to(debug_string_buffer,
2368
40
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
40
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
40
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
315
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
275
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
770
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
495
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
495
                           _tasks[j][i].first->debug_string());
2376
495
        }
2377
275
    }
2378
2379
40
    return fmt::to_string(debug_string_buffer);
2380
40
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.56k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.56k
    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
2.56k
    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
2.56k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.56k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.56k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.69k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.69k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.69k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.69k
        res.push_back(profile_ptr);
2407
4.69k
    }
2408
2409
2.56k
    return res;
2410
2.56k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.56k
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
2.56k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
7.56k
    for (const auto& tasks : _tasks) {
2426
14.9k
        for (const auto& task : tasks) {
2427
14.9k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
14.9k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
14.9k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
14.9k
                                                           _runtime_state->profile_level());
2435
14.9k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
14.9k
        }
2437
7.56k
    }
2438
2439
2.56k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.56k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.56k
                                                      _runtime_state->profile_level());
2442
2.56k
    return load_channel_profile;
2443
2.56k
}
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
5.06k
    for (const auto& _task : _tasks) {
2455
8.24k
        for (const auto& task : _task) {
2456
8.24k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
8.24k
            result.merge(set);
2458
8.24k
        }
2459
5.06k
    }
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
451k
void PipelineFragmentContext::_release_resource() {
2468
451k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
451k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
451k
    auto st = _query_ctx->exec_status();
2472
1.17M
    for (auto& _task : _tasks) {
2473
1.17M
        if (!_task.empty()) {
2474
1.17M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.17M
        }
2476
1.17M
    }
2477
451k
    _tasks.clear();
2478
451k
    _dag.clear();
2479
451k
    _pip_id_to_pipeline.clear();
2480
451k
    _pipelines.clear();
2481
451k
    _sink.reset();
2482
451k
    _root_op.reset();
2483
451k
    _runtime_filter_mgr_map.clear();
2484
451k
    _op_id_to_shared_state.clear();
2485
451k
}
2486
2487
} // namespace doris