Coverage Report

Created: 2026-05-20 12:27

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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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
504k
        : _query_id(std::move(query_id)),
144
504k
          _fragment_id(request.fragment_id),
145
504k
          _exec_env(exec_env),
146
504k
          _query_ctx(std::move(query_ctx)),
147
504k
          _call_back(call_back),
148
504k
          _is_report_on_cancel(true),
149
504k
          _params(request),
150
504k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
504k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
504k
                                                               : false) {
153
504k
    _fragment_watcher.start();
154
504k
}
155
156
504k
PipelineFragmentContext::~PipelineFragmentContext() {
157
504k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
504k
            .tag("query_id", print_id(_query_id))
159
504k
            .tag("fragment_id", _fragment_id);
160
504k
    _release_resource();
161
504k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
504k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
504k
        _runtime_state.reset();
165
504k
        _query_ctx.reset();
166
504k
    }
167
504k
}
168
169
10
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
10
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
10
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
10
}
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.
179
// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
10.2k
bool PipelineFragmentContext::notify_close() {
181
10.2k
    bool all_closed = false;
182
10.2k
    bool need_remove = false;
183
10.2k
    {
184
10.2k
        std::lock_guard<std::mutex> l(_task_mutex);
185
10.2k
        if (_closed_tasks >= _total_tasks) {
186
3.51k
            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
3.44k
                need_remove = true;
193
3.44k
            }
194
3.51k
            all_closed = true;
195
3.51k
        }
196
        // make fragment release by self after cancel
197
10.2k
        _need_notify_close = false;
198
10.2k
    }
199
10.2k
    if (need_remove) {
200
3.44k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.44k
    }
202
10.2k
    return all_closed;
203
10.2k
}
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
6.77k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.77k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.77k
            .tag("query_id", print_id(_query_id))
212
6.77k
            .tag("fragment_id", _fragment_id)
213
6.77k
            .tag("reason", reason.to_string());
214
6.77k
    if (notify_close()) {
215
85
        return;
216
85
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.69k
    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
6.69k
    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
6.69k
    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
6.69k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
25
        _query_ctx->set_load_error_url(error_url);
236
25
    }
237
238
6.69k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
25
        _query_ctx->set_first_error_msg(first_error_msg);
240
25
    }
241
242
6.69k
    _query_ctx->cancel(reason, _fragment_id);
243
6.69k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
434
        _is_report_on_cancel = false;
245
6.25k
    } else {
246
36.3k
        for (auto& id : _fragment_instance_ids) {
247
36.3k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
36.3k
        }
249
6.25k
    }
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
6.69k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.69k
    if (stream_load_ctx != nullptr) {
254
31
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
31
        stream_load_ctx->error_url = get_load_error_url();
259
31
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
31
    }
261
262
37.6k
    for (auto& tasks : _tasks) {
263
81.2k
        for (auto& task : tasks) {
264
81.2k
            task.first->unblock_all_dependencies();
265
81.2k
        }
266
37.6k
    }
267
6.69k
}
268
269
867k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
867k
    PipelineId id = _next_pipeline_id++;
271
867k
    auto pipeline = std::make_shared<Pipeline>(
272
867k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
867k
            parent ? parent->num_tasks() : _num_instances);
274
867k
    if (idx >= 0) {
275
113k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
754k
    } else {
277
754k
        _pipelines.emplace_back(pipeline);
278
754k
    }
279
867k
    if (parent) {
280
323k
        parent->set_children(pipeline);
281
323k
    }
282
867k
    return pipeline;
283
867k
}
284
285
504k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
504k
    {
287
504k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
504k
        auto root_pipeline = add_pipeline();
290
504k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
504k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
504k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
504k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
504k
                                          _params.fragment.output_exprs, _params,
299
504k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
504k
                                          *_desc_tbl, root_pipeline->id()));
301
504k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
504k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
753k
        for (PipelinePtr& pipeline : _pipelines) {
305
753k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
753k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
753k
        }
308
504k
    }
309
    // 4. Build local exchanger
310
504k
    if (_runtime_state->enable_local_shuffle()) {
311
501k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
501k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
501k
                                             _params.bucket_seq_to_instance_idx,
314
501k
                                             _params.shuffle_idx_to_instance_idx));
315
501k
    }
316
317
    // 5. Initialize global states in pipelines.
318
868k
    for (PipelinePtr& pipeline : _pipelines) {
319
868k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
868k
        pipeline->children().clear();
321
868k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
868k
    }
323
324
502k
    {
325
502k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
502k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
502k
    }
329
330
502k
    return Status::OK();
331
502k
}
332
333
504k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
504k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
504k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
504k
        _timeout = _params.query_options.execution_timeout;
339
504k
    }
340
341
504k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
504k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
504k
    SCOPED_TIMER(_prepare_timer);
344
504k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
504k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
504k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
504k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
504k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
504k
    {
350
504k
        SCOPED_TIMER(_init_context_timer);
351
504k
        cast_set(_num_instances, _params.local_params.size());
352
504k
        _total_instances =
353
504k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
504k
        auto* fragment_context = this;
356
357
504k
        if (_params.query_options.__isset.is_report_success) {
358
503k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
503k
        }
360
361
        // 1. Set up the global runtime state.
362
504k
        _runtime_state = RuntimeState::create_unique(
363
504k
                _params.query_id, _params.fragment_id, _params.query_options,
364
504k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
504k
        _runtime_state->set_task_execution_context(shared_from_this());
366
504k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
504k
        if (_params.__isset.backend_id) {
368
500k
            _runtime_state->set_backend_id(_params.backend_id);
369
500k
        }
370
504k
        if (_params.__isset.import_label) {
371
239
            _runtime_state->set_import_label(_params.import_label);
372
239
        }
373
504k
        if (_params.__isset.db_name) {
374
191
            _runtime_state->set_db_name(_params.db_name);
375
191
        }
376
504k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
504k
        if (_params.is_simplified_param) {
381
213k
            _desc_tbl = _query_ctx->desc_tbl;
382
291k
        } else {
383
291k
            DCHECK(_params.__isset.desc_tbl);
384
291k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
291k
                                                  &_desc_tbl));
386
291k
        }
387
504k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
504k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
504k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
504k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
504k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
504k
        const auto target_size = _params.local_params.size();
395
504k
        _fragment_instance_ids.resize(target_size);
396
1.77M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.26M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.26M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.26M
        }
400
504k
    }
401
402
504k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
503k
    _init_next_report_time();
405
406
503k
    _prepared = true;
407
503k
    return Status::OK();
408
504k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.26M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.26M
    const auto& local_params = _params.local_params[instance_idx];
414
1.26M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.26M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.26M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.26M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.26M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
2.14M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
2.14M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
2.14M
                                std::vector<std::shared_ptr<Dependency>>>>
422
2.14M
                shared_state_map;
423
2.72M
        for (auto& op : pipeline->operators()) {
424
2.72M
            auto source_id = op->operator_id();
425
2.72M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.72M
                iter != _op_id_to_shared_state.end()) {
427
755k
                shared_state_map.insert({source_id, iter->second});
428
755k
            }
429
2.72M
        }
430
2.16M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
2.16M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
2.16M
                iter != _op_id_to_shared_state.end()) {
433
259k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
259k
            }
435
2.16M
        }
436
2.14M
        return shared_state_map;
437
2.14M
    };
438
439
3.89M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.63M
        auto& pipeline = _pipelines[pip_idx];
441
2.63M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
2.14M
            auto task_runtime_state = RuntimeState::create_unique(
443
2.14M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
2.14M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
2.14M
            {
446
                // Initialize runtime state for this task
447
2.14M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
2.14M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
2.14M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
2.14M
                if (_params.__isset.backend_id) {
453
2.14M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
2.14M
                }
455
2.14M
                if (_params.__isset.import_label) {
456
240
                    task_runtime_state->set_import_label(_params.import_label);
457
240
                }
458
2.14M
                if (_params.__isset.db_name) {
459
192
                    task_runtime_state->set_db_name(_params.db_name);
460
192
                }
461
2.14M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
2.14M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
2.14M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
2.14M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
2.14M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
2.14M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
2.14M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
2.14M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
2.14M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
2.14M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
2.14M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
2.14M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
2.14M
            }
482
2.14M
            auto cur_task_id = _total_tasks++;
483
2.14M
            task_runtime_state->set_task_id(cur_task_id);
484
2.14M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
2.14M
            auto task = std::make_shared<PipelineTask>(
486
2.14M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
2.14M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
2.14M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
2.14M
                    instance_idx);
490
2.14M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
2.14M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
2.14M
            _tasks[instance_idx].emplace_back(
493
2.14M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
2.14M
                            std::move(task), std::move(task_runtime_state)});
495
2.14M
        }
496
2.63M
    }
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
2.63M
    for (auto& _pipeline : _pipelines) {
516
2.63M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
2.13M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
2.13M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
2.13M
            if (_dag.contains(_pipeline->id())) {
522
1.36M
                auto& deps = _dag[_pipeline->id()];
523
2.10M
                for (auto& dep : deps) {
524
2.10M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.11M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.11M
                        if (ss) {
527
605k
                            task->inject_shared_state(ss);
528
605k
                        } else {
529
513k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
513k
                                    task->get_source_shared_state());
531
513k
                        }
532
1.11M
                    }
533
2.10M
                }
534
1.36M
            }
535
2.13M
        }
536
2.63M
    }
537
3.90M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.63M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
2.13M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
2.13M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
2.13M
            std::vector<TScanRangeParams> scan_ranges;
542
2.13M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
2.13M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
325k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
325k
            }
546
2.13M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
2.13M
                                                             _params.fragment.output_sink));
548
2.13M
        }
549
2.63M
    }
550
1.26M
    {
551
1.26M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.26M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.26M
    }
554
1.26M
    return Status::OK();
555
1.26M
}
556
557
503k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
503k
    _total_tasks = 0;
559
503k
    _closed_tasks = 0;
560
503k
    const auto target_size = _params.local_params.size();
561
503k
    _tasks.resize(target_size);
562
503k
    _runtime_filter_mgr_map.resize(target_size);
563
1.37M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
867k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
867k
    }
566
503k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
503k
    if (target_size > 1 &&
569
503k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
142k
         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
14.1k
        std::vector<Status> prepare_status(target_size);
573
14.1k
        int submitted_tasks = 0;
574
14.1k
        Status submit_status;
575
14.1k
        CountDownLatch latch((int)target_size);
576
193k
        for (int i = 0; i < target_size; i++) {
577
179k
            submit_status = thread_pool->submit_func([&, i]() {
578
179k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
179k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
179k
                latch.count_down();
581
179k
            });
582
179k
            if (LIKELY(submit_status.ok())) {
583
179k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
179k
        }
588
14.1k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
14.1k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
193k
        for (int i = 0; i < submitted_tasks; i++) {
593
179k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
179k
        }
597
489k
    } else {
598
1.57M
        for (int i = 0; i < target_size; i++) {
599
1.08M
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
1.08M
        }
601
489k
    }
602
503k
    _pipeline_parent_map.clear();
603
503k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
503k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
503k
    return Status::OK();
608
503k
}
609
610
502k
void PipelineFragmentContext::_init_next_report_time() {
611
502k
    auto interval_s = config::pipeline_status_report_interval;
612
502k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
42.6k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.6k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
42.6k
        _previous_report_time =
617
42.6k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.6k
        _disable_period_report = false;
619
42.6k
    }
620
502k
}
621
622
4.87k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.87k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.87k
    DCHECK(disable == true);
625
4.87k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.87k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.87k
}
628
629
7.93M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.93M
    if (!_is_report_success) {
631
7.47M
        return;
632
7.47M
    }
633
454k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
454k
    if (disable) {
635
8.28k
        return;
636
8.28k
    }
637
446k
    int32_t interval_s = config::pipeline_status_report_interval;
638
446k
    if (interval_s <= 0) {
639
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
640
0
                        "trigger "
641
0
                        "report.";
642
0
    }
643
446k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
446k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
446k
    if (MonotonicNanos() > next_report_time) {
646
4.87k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.87k
                                                            std::memory_order_acq_rel)) {
648
4
            return;
649
4
        }
650
4.87k
        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
4.87k
        auto st = send_report(false);
667
4.87k
        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
4.87k
    }
673
446k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
502k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
502k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
502k
    int node_idx = 0;
682
683
502k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
502k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
502k
    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
502k
    return Status::OK();
691
502k
}
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
865k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
865k
    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
865k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
865k
    int num_children = tnodes[*node_idx].num_children;
706
865k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
865k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
865k
    OperatorPtr op = nullptr;
710
865k
    OperatorPtr cache_op = nullptr;
711
865k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
865k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
865k
                                     followed_by_shuffled_operator,
714
865k
                                     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
865k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
865k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
363k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
501k
    } else {
723
501k
        *root = op;
724
501k
    }
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
865k
    auto required_data_distribution =
737
865k
            cur_pipe->operators().empty()
738
865k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
865k
                    : op->required_data_distribution(_runtime_state.get());
740
865k
    current_followed_by_shuffled_operator =
741
865k
            ((followed_by_shuffled_operator ||
742
865k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
796k
                                             : op->is_shuffled_operator())) &&
744
865k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
865k
            (followed_by_shuffled_operator &&
746
735k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
865k
    current_require_bucket_distribution =
749
865k
            ((require_bucket_distribution ||
750
865k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
800k
                                             : op->is_colocated_operator())) &&
752
865k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
865k
            (require_bucket_distribution &&
754
741k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
865k
    if (num_children == 0) {
757
542k
        _use_serial_source = op->is_serial_operator();
758
542k
    }
759
    // rely on that tnodes is preorder of the plan
760
1.22M
    for (int i = 0; i < num_children; i++) {
761
363k
        ++*node_idx;
762
363k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
363k
                                            current_followed_by_shuffled_operator,
764
363k
                                            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
363k
        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
363k
    }
775
776
865k
    return Status::OK();
777
865k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
113k
        PipelinePtr pipe_with_sink) {
782
113k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
113k
    pipe_with_source->set_num_tasks(_num_instances);
784
113k
    pipe_with_source->set_data_distribution(data_distribution);
785
113k
}
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
113k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
113k
    auto& operators = cur_pipe->operators();
793
113k
    const auto downstream_pipeline_id = cur_pipe->id();
794
113k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
113k
    DataSinkOperatorPtr sink;
797
113k
    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
113k
    const bool followed_by_shuffled_operator =
804
113k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
113k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
113k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
113k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
113k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
113k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
113k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
113k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
113k
    if (bucket_seq_to_instance_idx.empty() &&
813
113k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
9
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
9
    }
816
113k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
113k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
113k
                                          num_buckets, use_global_hash_shuffle,
819
113k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
113k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
113k
            LocalExchangeSharedState::create_shared(_num_instances);
824
113k
    switch (data_distribution.distribution_type) {
825
11.9k
    case ExchangeType::HASH_SHUFFLE:
826
11.9k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
11.9k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
11.9k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
11.9k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
11.9k
                        ? cast_set<int>(
831
11.9k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
18.4E
                        : 0);
833
11.9k
        break;
834
508
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
508
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
508
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
508
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
508
                        ? cast_set<int>(
839
508
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
508
                        : 0);
841
508
        break;
842
96.3k
    case ExchangeType::PASSTHROUGH:
843
96.3k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
96.3k
                cur_pipe->num_tasks(), _num_instances,
845
96.3k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
96.3k
                        ? cast_set<int>(
847
96.3k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
96.3k
                        : 0);
849
96.3k
        break;
850
517
    case ExchangeType::BROADCAST:
851
517
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
517
                cur_pipe->num_tasks(), _num_instances,
853
517
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
517
                        ? cast_set<int>(
855
517
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
517
                        : 0);
857
517
        break;
858
2.81k
    case ExchangeType::PASS_TO_ONE:
859
2.81k
        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
1.59k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.59k
                    cur_pipe->num_tasks(), _num_instances,
863
1.59k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.59k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.59k
                                                    .local_exchange_free_blocks_limit)
866
1.59k
                            : 0);
867
1.59k
        } else {
868
1.22k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.22k
                    cur_pipe->num_tasks(), _num_instances,
870
1.22k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.22k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.22k
                                                    .local_exchange_free_blocks_limit)
873
1.22k
                            : 0);
874
1.22k
        }
875
2.81k
        break;
876
907
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
907
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
907
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
907
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
907
                        ? cast_set<int>(
881
907
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
907
                        : 0);
883
907
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
113k
    }
888
113k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
113k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
113k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
113k
    _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
113k
    std::copy(operators.begin(), operators.begin() + idx,
898
113k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
113k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
113k
    OperatorPtr source_op;
905
113k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
113k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
113k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
113k
    if (!operators.empty()) {
909
45.4k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
45.4k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
45.4k
    }
912
113k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
113k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
113k
    std::vector<PipelineId> edges_with_source;
917
132k
    for (auto child : cur_pipe->children()) {
918
132k
        bool found = false;
919
147k
        for (auto op : new_pip->operators()) {
920
147k
            if (child->sink()->node_id() == op->node_id()) {
921
13.1k
                new_pip->set_children(child);
922
13.1k
                found = true;
923
13.1k
            };
924
147k
        }
925
132k
        if (!found) {
926
119k
            new_children.push_back(child);
927
119k
            edges_with_source.push_back(child->id());
928
119k
        }
929
132k
    }
930
113k
    new_children.push_back(new_pip);
931
113k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
113k
    if (!new_pip->children().empty()) {
935
7.25k
        std::vector<PipelineId> edges_with_sink;
936
13.1k
        for (auto child : new_pip->children()) {
937
13.1k
            edges_with_sink.push_back(child->id());
938
13.1k
        }
939
7.25k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.25k
    }
941
113k
    cur_pipe->set_children(new_children);
942
113k
    _dag[downstream_pipeline_id] = edges_with_source;
943
113k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
113k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
113k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
113k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
113k
    return Status::OK();
950
113k
}
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
249k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
249k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
101k
        return Status::OK();
959
101k
    }
960
961
148k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
47.3k
        return Status::OK();
963
47.3k
    }
964
100k
    *do_local_exchange = true;
965
966
100k
    auto& operators = cur_pipe->operators();
967
100k
    auto total_op_num = operators.size();
968
100k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
100k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
100k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
100k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
100k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
294
            << "total_op_num: " << total_op_num
975
294
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
294
            << " 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
100k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
100k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
12.5k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
12.5k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
12.5k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
12.5k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
12.5k
                shuffle_idx_to_instance_idx));
990
12.5k
    }
991
100k
    return Status::OK();
992
100k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
500k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.25M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
750k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
750k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
211k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
211k
                if (child->sink()->node_id() ==
1003
211k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
173k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
173k
                }
1006
211k
            }
1007
194k
        }
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
750k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
750k
                                             bucket_seq_to_instance_idx,
1014
750k
                                             shuffle_idx_to_instance_idx));
1015
750k
    }
1016
500k
    return Status::OK();
1017
500k
}
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
750k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
750k
    int idx = 1;
1024
750k
    bool do_local_exchange = false;
1025
795k
    do {
1026
795k
        auto& ops = pip->operators();
1027
795k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
903k
        for (; idx < ops.size();) {
1030
153k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
130k
                RETURN_IF_ERROR(_add_local_exchange(
1032
130k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
130k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
130k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
130k
                        shuffle_idx_to_instance_idx));
1036
130k
            }
1037
153k
            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
45.5k
                idx = 2;
1043
45.5k
                break;
1044
45.5k
            }
1045
107k
            idx++;
1046
107k
        }
1047
795k
    } while (do_local_exchange);
1048
750k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
118k
        RETURN_IF_ERROR(_add_local_exchange(
1050
118k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
118k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
118k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
118k
    }
1054
750k
    return Status::OK();
1055
750k
}
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
503k
                                                  PipelineId cur_pipeline_id) {
1063
503k
    switch (thrift_sink.type) {
1064
199k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
199k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
199k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
199k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
199k
                params.destinations, _fragment_instance_ids);
1071
199k
        break;
1072
199k
    }
1073
253k
    case TDataSinkType::RESULT_SINK: {
1074
253k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
253k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
253k
        int child_node_id = pipeline->operators().back()->node_id();
1080
253k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
253k
                                                      row_desc, output_exprs,
1082
253k
                                                      thrift_sink.result_sink);
1083
253k
        break;
1084
253k
    }
1085
55
    case TDataSinkType::DICTIONARY_SINK: {
1086
55
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
55
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
55
                                                    thrift_sink.dictionary_sink);
1092
55
        break;
1093
55
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
32.9k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
32.9k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
32.9k
        int child_node_id = pipeline->operators().back()->node_id();
1098
32.9k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
32.9k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
32.9k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.70k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.70k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
30.2k
        } else {
1104
30.2k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
30.2k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
30.2k
        }
1107
32.9k
        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
13.1k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
13.1k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
13.1k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
13.1k
        auto sink_id = next_sink_operator_id();
1205
13.1k
        const int multi_cast_node_id = sink_id;
1206
13.1k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
13.1k
        std::vector<int> sources;
1209
52.5k
        for (int i = 0; i < sender_size; ++i) {
1210
39.3k
            auto source_id = next_operator_id();
1211
39.3k
            sources.push_back(source_id);
1212
39.3k
        }
1213
1214
13.1k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
13.1k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
52.5k
        for (int i = 0; i < sender_size; ++i) {
1217
39.3k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
39.3k
            RowDescriptor* exchange_row_desc = nullptr;
1220
39.3k
            {
1221
39.3k
                const auto& tmp_row_desc =
1222
39.3k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
39.3k
                                ? RowDescriptor(state->desc_tbl(),
1224
39.3k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
39.3k
                                                         .output_tuple_id})
1226
39.3k
                                : row_desc;
1227
39.3k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
39.3k
            }
1229
39.3k
            auto source_id = sources[i];
1230
39.3k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
39.3k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
39.3k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
39.3k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
39.3k
                    /*operator_id=*/source_id);
1236
39.3k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
39.3k
                    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
39.3k
            DataSinkOperatorPtr sink_op;
1241
39.3k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
39.3k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
39.3k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
39.3k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
39.3k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
39.3k
            {
1248
39.3k
                TDataSink* t = pool->add(new TDataSink());
1249
39.3k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
39.3k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
39.3k
            }
1252
1253
            // 3. set dependency dag
1254
39.3k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
39.3k
        }
1256
13.1k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
13.1k
        break;
1260
13.1k
    }
1261
13.1k
    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
503k
    }
1280
502k
    return Status::OK();
1281
503k
}
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
867k
                                                 OperatorPtr& cache_op) {
1292
867k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
867k
    Defer defer = Defer([&]() {
1294
867k
        if (op) {
1295
867k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
867k
        }
1297
867k
        for (auto& s : sink_ops) {
1298
210k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
210k
        }
1300
867k
    });
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
867k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
867k
    std::stringstream error_msg;
1305
867k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
867k
    bool fe_with_old_version = false;
1308
867k
    switch (tnode.node_type) {
1309
214k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
214k
        op = std::make_shared<OlapScanOperatorX>(
1311
214k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
214k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
214k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
214k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
214k
        break;
1316
214k
    }
1317
78
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
78
        DCHECK(_query_ctx != nullptr);
1319
78
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
78
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
78
                                                    _num_instances);
1322
78
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
78
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
78
        break;
1325
78
    }
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
24.6k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
24.6k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
24.6k
                                                 _num_instances);
1342
24.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
24.6k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
24.6k
        break;
1345
24.6k
    }
1346
237k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
237k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
237k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
237k
                                  : 0;
1350
237k
        DCHECK_GT(num_senders, 0);
1351
237k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
237k
                                                       num_senders);
1353
237k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
237k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
237k
        break;
1356
237k
    }
1357
214k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
214k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
214k
            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
214k
        bool need_create_cache_op =
1364
214k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
214k
        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
214k
        const bool group_by_limit_opt =
1385
214k
                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
214k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
214k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
214k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
214k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
214k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
214k
        const bool can_use_distinct_streaming_agg =
1396
214k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
214k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
214k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
214k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
214k
        if (can_use_distinct_streaming_agg) {
1402
92.3k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
92.3k
            } else {
1413
92.3k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
92.3k
                                                                     tnode, descs);
1415
92.3k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
92.3k
            }
1417
121k
        } else if (is_streaming_agg) {
1418
7.55k
            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
7.55k
            } else {
1428
7.55k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
7.55k
                                                             descs);
1430
7.55k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
7.55k
            }
1432
114k
        } else {
1433
            // create new pipeline to add query cache operator
1434
114k
            PipelinePtr new_pipe;
1435
114k
            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
114k
            if (enable_spill) {
1441
215
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
215
                                                                     next_operator_id(), descs);
1443
114k
            } else {
1444
114k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
114k
            }
1446
114k
            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
114k
            } else {
1451
114k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
114k
            }
1453
1454
114k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
114k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
100k
                _dag.insert({downstream_pipeline_id, {}});
1457
100k
            }
1458
114k
            cur_pipe = add_pipeline(cur_pipe);
1459
114k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
114k
            if (enable_spill) {
1462
215
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
215
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
114k
            } else {
1465
114k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
114k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
114k
            }
1468
114k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
114k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
114k
        }
1471
214k
        break;
1472
214k
    }
1473
214k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
90
        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
90
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
90
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
90
        const auto downstream_pipeline_id = cur_pipe->id();
1486
90
        if (!_dag.contains(downstream_pipeline_id)) {
1487
90
            _dag.insert({downstream_pipeline_id, {}});
1488
90
        }
1489
90
        cur_pipe = add_pipeline(cur_pipe);
1490
90
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
90
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
90
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
90
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
90
        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
90
        {
1503
90
            auto shared_state = BucketedAggSharedState::create_shared();
1504
90
            shared_state->id = op->operator_id();
1505
90
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
537
            for (int i = 0; i < _num_instances; i++) {
1508
447
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
447
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
447
                sink_dep->set_shared_state(shared_state.get());
1511
447
                shared_state->sink_deps.push_back(sink_dep);
1512
447
            }
1513
90
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
90
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
90
            _op_id_to_shared_state.insert(
1516
90
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
90
        }
1518
90
        break;
1519
90
    }
1520
9.88k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.88k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.88k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.88k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.88k
        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
9.88k
        } else {
1566
9.88k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.88k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.88k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.88k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
8.05k
                _dag.insert({downstream_pipeline_id, {}});
1572
8.05k
            }
1573
9.88k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.88k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.88k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.88k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.88k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.88k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.88k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.88k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.88k
        }
1584
9.88k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.87k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.87k
                    HashJoinSharedState::create_shared(_num_instances);
1587
18.8k
            for (int i = 0; i < _num_instances; i++) {
1588
15.9k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
15.9k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
15.9k
                sink_dep->set_shared_state(shared_state.get());
1591
15.9k
                shared_state->sink_deps.push_back(sink_dep);
1592
15.9k
            }
1593
2.87k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.87k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.87k
            _op_id_to_shared_state.insert(
1596
2.87k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.87k
        }
1598
9.88k
        break;
1599
9.88k
    }
1600
27.6k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
27.6k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
27.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
27.6k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
27.6k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
27.4k
            _dag.insert({downstream_pipeline_id, {}});
1607
27.4k
        }
1608
27.6k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
27.6k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
27.6k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
27.6k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
27.6k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
27.6k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
27.6k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
27.6k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
27.6k
        break;
1618
27.6k
    }
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
53.4k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.4k
        }
1628
55.1k
        for (int i = 0; i < child_count; i++) {
1629
1.42k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.42k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.42k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.42k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.42k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.42k
            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
1.42k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.42k
        }
1638
53.7k
        break;
1639
53.7k
    }
1640
55.3k
    case TPlanNodeType::SORT_NODE: {
1641
55.3k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
55.3k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
55.3k
        const bool use_local_merge =
1644
55.3k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
55.3k
        if (should_spill) {
1646
7
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
55.3k
        } else if (use_local_merge) {
1648
53.0k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
53.0k
                                                                 descs);
1650
53.0k
        } else {
1651
2.35k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.35k
        }
1653
55.3k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
55.3k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
55.3k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
55.3k
            _dag.insert({downstream_pipeline_id, {}});
1658
55.3k
        }
1659
55.3k
        cur_pipe = add_pipeline(cur_pipe);
1660
55.3k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
55.3k
        if (should_spill) {
1663
7
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
7
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
55.3k
        } else {
1666
55.3k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
55.3k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
55.3k
        }
1669
55.3k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
55.3k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
55.3k
        break;
1672
55.3k
    }
1673
55.3k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
63
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
63
        const auto downstream_pipeline_id = cur_pipe->id();
1678
63
        if (!_dag.contains(downstream_pipeline_id)) {
1679
63
            _dag.insert({downstream_pipeline_id, {}});
1680
63
        }
1681
63
        cur_pipe = add_pipeline(cur_pipe);
1682
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
63
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
63
        break;
1689
63
    }
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
1.61k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.61k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.61k
        break;
1711
1.61k
    }
1712
1.61k
    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
314
    case TPlanNodeType::REPEAT_NODE: {
1723
314
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
314
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
314
        break;
1726
314
    }
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
1.94k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.94k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.94k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.94k
        break;
1741
1.94k
    }
1742
1.94k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
463
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
463
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
463
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
463
        break;
1747
463
    }
1748
2.02k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.02k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.02k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.02k
        break;
1752
2.02k
    }
1753
6.54k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.54k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.54k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.54k
        break;
1757
6.54k
    }
1758
13.0k
    case TPlanNodeType::SELECT_NODE: {
1759
13.0k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
13.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
13.0k
        break;
1762
13.0k
    }
1763
13.0k
    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
867k
    }
1803
866k
    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
866k
    return Status::OK();
1809
867k
}
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
501k
Status PipelineFragmentContext::submit() {
1846
501k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
501k
    _submitted = true;
1850
1851
501k
    int submit_tasks = 0;
1852
501k
    Status st;
1853
501k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.26M
    for (auto& task : _tasks) {
1855
2.14M
        for (auto& t : task) {
1856
2.14M
            st = scheduler->submit(t.first);
1857
2.14M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
2.14M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
2.14M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
2.14M
            submit_tasks++;
1866
2.14M
        }
1867
1.26M
    }
1868
501k
    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
501k
    } else {
1883
501k
        return st;
1884
501k
    }
1885
501k
}
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
503k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
503k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
503k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
503k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
503k
    if (!_need_notify_close) {
1919
500k
        auto st = send_report(true);
1920
500k
        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
500k
    }
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
503k
    if (_runtime_state->enable_profile() &&
1931
503k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.86k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.86k
         _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
503k
    if (_query_ctx->enable_profile()) {
1953
2.86k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.86k
                                         collect_realtime_load_channel_profile());
1955
2.86k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
503k
    return !_need_notify_close;
1960
503k
}
1961
1962
2.13M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
2.13M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
2.13M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
867k
        if (_dag.contains(pipeline_id)) {
1967
476k
            for (auto dep : _dag[pipeline_id]) {
1968
476k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
476k
            }
1970
394k
        }
1971
867k
    }
1972
2.13M
    bool need_remove = false;
1973
2.13M
    {
1974
2.13M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
2.13M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
2.13M
        _query_ctx->inc_finished_task_num();
1978
2.13M
        if (_closed_tasks >= _total_tasks) {
1979
503k
            need_remove = _close_fragment_instance();
1980
503k
        }
1981
2.13M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
2.13M
    if (need_remove) {
1984
500k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
500k
    }
1986
2.13M
}
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
146k
    for (auto& tasks : _tasks) {
1993
230k
        for (auto& task : tasks) {
1994
230k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
175
                return to_load_error_http_path(str);
1996
175
            }
1997
230k
        }
1998
146k
    }
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
146k
    for (auto& tasks : _tasks) {
2007
230k
        for (auto& task : tasks) {
2008
230k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
175
                return str;
2010
175
            }
2011
230k
        }
2012
146k
    }
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
49.0k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
49.0k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
49.0k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
49.0k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
49.0k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
49.0k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
49.0k
    });
2031
2032
49.0k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
49.0k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
49.0k
    int callback_retries = 10;
2038
49.0k
    const int sleep_ms = 1000;
2039
49.0k
    Status exec_status = req.status;
2040
49.0k
    Status coord_status;
2041
49.0k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
49.0k
    do {
2043
49.0k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
49.0k
                                                            req.coord_addr, &coord_status);
2045
49.0k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
49.0k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
49.0k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
49.0k
    TReportExecStatusParams params;
2059
49.0k
    params.protocol_version = FrontendServiceVersion::V1;
2060
49.0k
    params.__set_query_id(req.query_id);
2061
49.0k
    params.__set_backend_num(req.backend_num);
2062
49.0k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
49.0k
    params.__set_fragment_id(req.fragment_id);
2064
49.0k
    params.__set_status(exec_status.to_thrift());
2065
49.0k
    params.__set_done(req.done);
2066
49.0k
    params.__set_query_type(req.runtime_state->query_type());
2067
49.0k
    params.__isset.profile = false;
2068
2069
49.0k
    DCHECK(req.runtime_state != nullptr);
2070
2071
49.0k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
43.9k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
43.9k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
43.9k
    } else {
2075
5.04k
        DCHECK(!req.runtime_states.empty());
2076
5.04k
        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
5.04k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
5.04k
    }
2086
2087
49.0k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
49.0k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
49.0k
    static std::string s_unselected_rows = "unselected.rows";
2090
49.0k
    int64_t num_rows_load_success = 0;
2091
49.0k
    int64_t num_rows_load_filtered = 0;
2092
49.0k
    int64_t num_rows_load_unselected = 0;
2093
49.0k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
49.0k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
49.0k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
49.0k
    } else if (!req.runtime_states.empty()) {
2109
149k
        for (auto* rs : req.runtime_states) {
2110
149k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
149k
                rs->num_finished_range() > 0) {
2112
36.5k
                params.__isset.load_counters = true;
2113
36.5k
                num_rows_load_success += rs->num_rows_load_success();
2114
36.5k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
36.5k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
36.5k
                params.__isset.fragment_instance_reports = true;
2117
36.5k
                TFragmentInstanceReport t;
2118
36.5k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
36.5k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
36.5k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
36.5k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
36.5k
                params.fragment_instance_reports.push_back(t);
2123
36.5k
            }
2124
149k
        }
2125
49.0k
    }
2126
49.0k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
49.0k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
49.0k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
49.0k
    if (!req.load_error_url.empty()) {
2131
158
        params.__set_tracking_url(req.load_error_url);
2132
158
    }
2133
49.0k
    if (!req.first_error_msg.empty()) {
2134
158
        params.__set_first_error_msg(req.first_error_msg);
2135
158
    }
2136
149k
    for (auto* rs : req.runtime_states) {
2137
149k
        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
149k
    }
2142
49.0k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
49.0k
    } else if (!req.runtime_states.empty()) {
2146
149k
        for (auto* rs : req.runtime_states) {
2147
149k
            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
149k
        }
2154
48.9k
    }
2155
49.0k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
49.0k
    } else if (!req.runtime_states.empty()) {
2159
149k
        for (auto* rs : req.runtime_states) {
2160
149k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
27.6k
                params.__isset.commitInfos = true;
2162
27.6k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
27.6k
            }
2164
149k
        }
2165
49.0k
    }
2166
49.0k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
49.0k
    } else if (!req.runtime_states.empty()) {
2170
149k
        for (auto* rs : req.runtime_states) {
2171
149k
            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
149k
        }
2177
49.0k
    }
2178
49.0k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
49.0k
    } else if (!req.runtime_states.empty()) {
2183
149k
        for (auto* rs : req.runtime_states) {
2184
149k
            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
149k
        }
2190
49.0k
    }
2191
49.0k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
49.0k
    } else if (!req.runtime_states.empty()) {
2196
149k
        for (auto* rs : req.runtime_states) {
2197
149k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.06k
                params.__isset.iceberg_commit_datas = true;
2199
2.06k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.06k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.06k
            }
2202
149k
        }
2203
49.0k
    }
2204
2205
49.0k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
49.0k
    } else if (!req.runtime_states.empty()) {
2209
149k
        for (auto* rs : req.runtime_states) {
2210
149k
            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
149k
        }
2216
49.0k
    }
2217
2218
49.0k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
49.0k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
49.0k
    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
49.0k
    TReportExecStatusResult res;
2226
49.0k
    Status rpc_status;
2227
2228
49.0k
    VLOG_DEBUG << "reportExecStatus params is "
2229
30
               << apache::thrift::ThriftDebugString(params).c_str();
2230
49.0k
    if (!exec_status.ok()) {
2231
1.69k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.69k
                     << " to coordinator: " << req.coord_addr
2233
1.69k
                     << ", query id: " << print_id(req.query_id);
2234
1.69k
    }
2235
49.0k
    try {
2236
49.0k
        try {
2237
49.0k
            (*coord)->reportExecStatus(res, params);
2238
49.0k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
49.0k
        rpc_status = Status::create<false>(res.status);
2254
49.0k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
49.0k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
49.0k
}
2265
2266
505k
Status PipelineFragmentContext::send_report(bool done) {
2267
505k
    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
505k
    if (!_is_report_success && done && exec_status.ok()) {
2273
456k
        return Status::OK();
2274
456k
    }
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
49.3k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
350
        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
350
            return Status::OK();
2286
350
        }
2287
0
        return Status::NeedSendAgain("");
2288
350
    }
2289
2290
49.0k
    std::vector<RuntimeState*> runtime_states;
2291
2292
108k
    for (auto& tasks : _tasks) {
2293
149k
        for (auto& task : tasks) {
2294
149k
            runtime_states.push_back(task.second.get());
2295
149k
        }
2296
108k
    }
2297
2298
49.0k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
49.0k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
49.0k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
49.0k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
49.0k
    ReportStatusRequest req {.status = exec_status,
2306
49.0k
                             .runtime_states = runtime_states,
2307
49.0k
                             .done = done || !exec_status.ok(),
2308
49.0k
                             .coord_addr = _query_ctx->coord_addr,
2309
49.0k
                             .query_id = _query_id,
2310
49.0k
                             .fragment_id = _fragment_id,
2311
49.0k
                             .fragment_instance_id = TUniqueId(),
2312
49.0k
                             .backend_num = -1,
2313
49.0k
                             .runtime_state = _runtime_state.get(),
2314
49.0k
                             .load_error_url = load_eror_url,
2315
49.0k
                             .first_error_msg = first_error_msg,
2316
49.0k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
49.0k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
49.0k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
49.0k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
49.0k
        _coordinator_callback(req);
2321
49.0k
        if (!req.done) {
2322
4.87k
            ctx->refresh_next_report_time();
2323
4.87k
        }
2324
49.0k
    });
2325
49.3k
}
2326
2327
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
0
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
0
    for (const auto& task_instances : _tasks) {
2332
0
        for (const auto& task : task_instances) {
2333
0
            if (task.first->is_running()) {
2334
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2335
0
                                      << " is running, task: " << (void*)task.first.get()
2336
0
                                      << ", is_running: " << task.first->is_running();
2337
0
                *has_running_task = true;
2338
0
                return 0;
2339
0
            }
2340
2341
0
            size_t revocable_size = task.first->get_revocable_size();
2342
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
0
                res += revocable_size;
2344
0
            }
2345
0
        }
2346
0
    }
2347
0
    return res;
2348
0
}
2349
2350
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
0
    std::vector<PipelineTask*> revocable_tasks;
2352
0
    for (const auto& task_instances : _tasks) {
2353
0
        for (const auto& task : task_instances) {
2354
0
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
0
                revocable_tasks.emplace_back(task.first.get());
2358
0
            }
2359
0
        }
2360
0
    }
2361
0
    return revocable_tasks;
2362
0
}
2363
2364
11
std::string PipelineFragmentContext::debug_string() {
2365
11
    std::lock_guard<std::mutex> l(_task_mutex);
2366
11
    fmt::memory_buffer debug_string_buffer;
2367
11
    fmt::format_to(debug_string_buffer,
2368
11
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
11
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
11
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
58
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
47
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
262
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
215
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
215
                           _tasks[j][i].first->debug_string());
2376
215
        }
2377
47
    }
2378
2379
11
    return fmt::to_string(debug_string_buffer);
2380
11
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.86k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.86k
    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
2.86k
    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
2.86k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.86k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.86k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
5.34k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
5.34k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
5.34k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
5.34k
        res.push_back(profile_ptr);
2407
5.34k
    }
2408
2409
2.86k
    return res;
2410
2.86k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.86k
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
2.86k
    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
7.65k
    for (const auto& tasks : _tasks) {
2426
15.7k
        for (const auto& task : tasks) {
2427
15.7k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
15.7k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
15.7k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
15.7k
                                                           _runtime_state->profile_level());
2435
15.7k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
15.7k
        }
2437
7.65k
    }
2438
2439
2.86k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.86k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.86k
                                                      _runtime_state->profile_level());
2442
2.86k
    return load_channel_profile;
2443
2.86k
}
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
5.80k
    for (const auto& _task : _tasks) {
2455
10.0k
        for (const auto& task : _task) {
2456
10.0k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
10.0k
            result.merge(set);
2458
10.0k
        }
2459
5.80k
    }
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
505k
void PipelineFragmentContext::_release_resource() {
2468
505k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
505k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
505k
    auto st = _query_ctx->exec_status();
2472
1.26M
    for (auto& _task : _tasks) {
2473
1.26M
        if (!_task.empty()) {
2474
1.26M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.26M
        }
2476
1.26M
    }
2477
505k
    _tasks.clear();
2478
505k
    _dag.clear();
2479
505k
    _pip_id_to_pipeline.clear();
2480
505k
    _pipelines.clear();
2481
505k
    _sink.reset();
2482
505k
    _root_op.reset();
2483
505k
    _runtime_filter_mgr_map.clear();
2484
505k
    _op_id_to_shared_state.clear();
2485
505k
}
2486
2487
} // namespace doris