Coverage Report

Created: 2026-05-13 12:59

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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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
433k
        : _query_id(std::move(query_id)),
144
433k
          _fragment_id(request.fragment_id),
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433k
          _exec_env(exec_env),
146
433k
          _query_ctx(std::move(query_ctx)),
147
433k
          _call_back(call_back),
148
433k
          _is_report_on_cancel(true),
149
433k
          _params(request),
150
433k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
433k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
433k
                                                               : false) {
153
433k
    _fragment_watcher.start();
154
433k
}
155
156
433k
PipelineFragmentContext::~PipelineFragmentContext() {
157
433k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
433k
            .tag("query_id", print_id(_query_id))
159
433k
            .tag("fragment_id", _fragment_id);
160
433k
    _release_resource();
161
433k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
433k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
433k
        _runtime_state.reset();
165
433k
        _query_ctx.reset();
166
433k
    }
167
433k
}
168
169
177
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
177
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
177
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
177
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
9.29k
bool PipelineFragmentContext::notify_close() {
181
9.29k
    bool all_closed = false;
182
9.29k
    bool need_remove = false;
183
9.29k
    {
184
9.29k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.29k
        if (_closed_tasks >= _total_tasks) {
186
3.29k
            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
3.23k
                need_remove = true;
193
3.23k
            }
194
3.29k
            all_closed = true;
195
3.29k
        }
196
        // make fragment release by self after cancel
197
9.29k
        _need_notify_close = false;
198
9.29k
    }
199
9.29k
    if (need_remove) {
200
3.23k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.23k
    }
202
9.29k
    return all_closed;
203
9.29k
}
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
6.01k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.01k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.01k
            .tag("query_id", print_id(_query_id))
212
6.01k
            .tag("fragment_id", _fragment_id)
213
6.01k
            .tag("reason", reason.to_string());
214
6.01k
    if (notify_close()) {
215
84
        return;
216
84
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
5.93k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
5.93k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
5.93k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
5.93k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
25
        _query_ctx->set_load_error_url(error_url);
236
25
    }
237
238
5.93k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
25
        _query_ctx->set_first_error_msg(first_error_msg);
240
25
    }
241
242
5.93k
    _query_ctx->cancel(reason, _fragment_id);
243
5.93k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
395
        _is_report_on_cancel = false;
245
5.53k
    } else {
246
25.7k
        for (auto& id : _fragment_instance_ids) {
247
25.7k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
25.7k
        }
249
5.53k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
5.93k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
5.93k
    if (stream_load_ctx != nullptr) {
254
33
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
33
        stream_load_ctx->error_url = get_load_error_url();
259
33
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
33
    }
261
262
26.9k
    for (auto& tasks : _tasks) {
263
59.1k
        for (auto& task : tasks) {
264
59.1k
            task.first->unblock_all_dependencies();
265
59.1k
        }
266
26.9k
    }
267
5.93k
}
268
269
673k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
673k
    PipelineId id = _next_pipeline_id++;
271
673k
    auto pipeline = std::make_shared<Pipeline>(
272
673k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
673k
            parent ? parent->num_tasks() : _num_instances);
274
673k
    if (idx >= 0) {
275
108k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
564k
    } else {
277
564k
        _pipelines.emplace_back(pipeline);
278
564k
    }
279
673k
    if (parent) {
280
233k
        parent->set_children(pipeline);
281
233k
    }
282
673k
    return pipeline;
283
673k
}
284
285
432k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
432k
    {
287
432k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
432k
        auto root_pipeline = add_pipeline();
290
432k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
432k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
432k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
432k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
432k
                                          _params.fragment.output_exprs, _params,
299
432k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
432k
                                          *_desc_tbl, root_pipeline->id()));
301
432k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
432k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
563k
        for (PipelinePtr& pipeline : _pipelines) {
305
563k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
563k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
563k
        }
308
432k
    }
309
    // 4. Build local exchanger
310
432k
    if (_runtime_state->enable_local_shuffle()) {
311
430k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
430k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
430k
                                             _params.bucket_seq_to_instance_idx,
314
430k
                                             _params.shuffle_idx_to_instance_idx));
315
430k
    }
316
317
    // 5. Initialize global states in pipelines.
318
673k
    for (PipelinePtr& pipeline : _pipelines) {
319
673k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
673k
        pipeline->children().clear();
321
673k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
673k
    }
323
324
431k
    {
325
431k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
431k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
431k
    }
329
330
431k
    return Status::OK();
331
431k
}
332
333
433k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
433k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
433k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
433k
        _timeout = _params.query_options.execution_timeout;
339
433k
    }
340
341
433k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
433k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
433k
    SCOPED_TIMER(_prepare_timer);
344
433k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
433k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
433k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
433k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
433k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
433k
    {
350
433k
        SCOPED_TIMER(_init_context_timer);
351
433k
        cast_set(_num_instances, _params.local_params.size());
352
433k
        _total_instances =
353
433k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
433k
        auto* fragment_context = this;
356
357
433k
        if (_params.query_options.__isset.is_report_success) {
358
431k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
431k
        }
360
361
        // 1. Set up the global runtime state.
362
433k
        _runtime_state = RuntimeState::create_unique(
363
433k
                _params.query_id, _params.fragment_id, _params.query_options,
364
433k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
433k
        _runtime_state->set_task_execution_context(shared_from_this());
366
433k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
433k
        if (_params.__isset.backend_id) {
368
430k
            _runtime_state->set_backend_id(_params.backend_id);
369
430k
        }
370
433k
        if (_params.__isset.import_label) {
371
240
            _runtime_state->set_import_label(_params.import_label);
372
240
        }
373
433k
        if (_params.__isset.db_name) {
374
192
            _runtime_state->set_db_name(_params.db_name);
375
192
        }
376
433k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
433k
        if (_params.is_simplified_param) {
381
146k
            _desc_tbl = _query_ctx->desc_tbl;
382
286k
        } else {
383
286k
            DCHECK(_params.__isset.desc_tbl);
384
286k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
286k
                                                  &_desc_tbl));
386
286k
        }
387
433k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
433k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
433k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
433k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
433k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
433k
        const auto target_size = _params.local_params.size();
395
433k
        _fragment_instance_ids.resize(target_size);
396
1.59M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.16M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.16M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.16M
        }
400
433k
    }
401
402
433k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
432k
    _init_next_report_time();
405
406
432k
    _prepared = true;
407
432k
    return Status::OK();
408
433k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.15M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.15M
    const auto& local_params = _params.local_params[instance_idx];
414
1.15M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.15M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.15M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.15M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.15M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.96M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.96M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.96M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.96M
                shared_state_map;
423
2.51M
        for (auto& op : pipeline->operators()) {
424
2.51M
            auto source_id = op->operator_id();
425
2.51M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.51M
                iter != _op_id_to_shared_state.end()) {
427
745k
                shared_state_map.insert({source_id, iter->second});
428
745k
            }
429
2.51M
        }
430
1.96M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.96M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.96M
                iter != _op_id_to_shared_state.end()) {
433
294k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
294k
            }
435
1.96M
        }
436
1.96M
        return shared_state_map;
437
1.96M
    };
438
439
3.56M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.40M
        auto& pipeline = _pipelines[pip_idx];
441
2.40M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.95M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.95M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.95M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.95M
            {
446
                // Initialize runtime state for this task
447
1.95M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.95M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.95M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.95M
                if (_params.__isset.backend_id) {
453
1.95M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.95M
                }
455
1.95M
                if (_params.__isset.import_label) {
456
241
                    task_runtime_state->set_import_label(_params.import_label);
457
241
                }
458
1.95M
                if (_params.__isset.db_name) {
459
193
                    task_runtime_state->set_db_name(_params.db_name);
460
193
                }
461
1.95M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.95M
                if (_params.__isset.wal_id) {
465
112
                    task_runtime_state->set_wal_id(_params.wal_id);
466
112
                }
467
1.95M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.95M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.95M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.95M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.95M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.95M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.95M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.95M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.95M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.95M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.95M
            }
482
1.95M
            auto cur_task_id = _total_tasks++;
483
1.95M
            task_runtime_state->set_task_id(cur_task_id);
484
1.95M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.95M
            auto task = std::make_shared<PipelineTask>(
486
1.95M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.95M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.95M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.95M
                    instance_idx);
490
1.95M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.95M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.95M
            _tasks[instance_idx].emplace_back(
493
1.95M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.95M
                            std::move(task), std::move(task_runtime_state)});
495
1.95M
        }
496
2.40M
    }
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
2.40M
    for (auto& _pipeline : _pipelines) {
516
2.40M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.95M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.95M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.95M
            if (_dag.contains(_pipeline->id())) {
522
1.24M
                auto& deps = _dag[_pipeline->id()];
523
1.96M
                for (auto& dep : deps) {
524
1.96M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.06M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.06M
                        if (ss) {
527
491k
                            task->inject_shared_state(ss);
528
577k
                        } else {
529
577k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
577k
                                    task->get_source_shared_state());
531
577k
                        }
532
1.06M
                    }
533
1.96M
                }
534
1.24M
            }
535
1.95M
        }
536
2.40M
    }
537
3.56M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.40M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.95M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.95M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.95M
            std::vector<TScanRangeParams> scan_ranges;
542
1.95M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.95M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
351k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
351k
            }
546
1.95M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.95M
                                                             _params.fragment.output_sink));
548
1.95M
        }
549
2.40M
    }
550
1.16M
    {
551
1.16M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.16M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.16M
    }
554
1.16M
    return Status::OK();
555
1.15M
}
556
557
432k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
432k
    _total_tasks = 0;
559
432k
    _closed_tasks = 0;
560
432k
    const auto target_size = _params.local_params.size();
561
432k
    _tasks.resize(target_size);
562
432k
    _runtime_filter_mgr_map.resize(target_size);
563
1.10M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
672k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
672k
    }
566
432k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
432k
    if (target_size > 1 &&
569
432k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
139k
         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
22.0k
        std::vector<Status> prepare_status(target_size);
573
22.0k
        int submitted_tasks = 0;
574
22.0k
        Status submit_status;
575
22.0k
        CountDownLatch latch((int)target_size);
576
267k
        for (int i = 0; i < target_size; i++) {
577
245k
            submit_status = thread_pool->submit_func([&, i]() {
578
245k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
245k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
245k
                latch.count_down();
581
245k
            });
582
245k
            if (LIKELY(submit_status.ok())) {
583
245k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
245k
        }
588
22.0k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
22.0k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
267k
        for (int i = 0; i < submitted_tasks; i++) {
593
245k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
245k
        }
597
410k
    } else {
598
1.32M
        for (int i = 0; i < target_size; i++) {
599
916k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
916k
        }
601
410k
    }
602
432k
    _pipeline_parent_map.clear();
603
432k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
432k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
432k
    return Status::OK();
608
432k
}
609
610
431k
void PipelineFragmentContext::_init_next_report_time() {
611
431k
    auto interval_s = config::pipeline_status_report_interval;
612
431k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
41.7k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
41.7k
        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
41.7k
        _previous_report_time =
617
41.7k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
41.7k
        _disable_period_report = false;
619
41.7k
    }
620
431k
}
621
622
4.81k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.81k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.81k
    DCHECK(disable == true);
625
4.81k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.81k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.81k
}
628
629
7.09M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.09M
    if (!_is_report_success) {
631
6.55M
        return;
632
6.55M
    }
633
539k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
539k
    if (disable) {
635
9.09k
        return;
636
9.09k
    }
637
530k
    int32_t interval_s = config::pipeline_status_report_interval;
638
530k
    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
530k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
530k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
530k
    if (MonotonicNanos() > next_report_time) {
646
4.81k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.81k
                                                            std::memory_order_acq_rel)) {
648
7
            return;
649
7
        }
650
4.80k
        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
4.80k
        auto st = send_report(false);
667
4.80k
        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
4.80k
    }
673
530k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
430k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
430k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
430k
    int node_idx = 0;
682
683
430k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
430k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
430k
    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
430k
    return Status::OK();
691
430k
}
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
668k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
668k
    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
668k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
668k
    int num_children = tnodes[*node_idx].num_children;
706
668k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
668k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
668k
    OperatorPtr op = nullptr;
710
668k
    OperatorPtr cache_op = nullptr;
711
668k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
668k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
668k
                                     followed_by_shuffled_operator,
714
668k
                                     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
668k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
668k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
239k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
429k
    } else {
723
429k
        *root = op;
724
429k
    }
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
668k
    auto required_data_distribution =
737
668k
            cur_pipe->operators().empty()
738
668k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
668k
                    : op->required_data_distribution(_runtime_state.get());
740
668k
    current_followed_by_shuffled_operator =
741
668k
            ((followed_by_shuffled_operator ||
742
668k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
611k
                                             : op->is_shuffled_operator())) &&
744
668k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
668k
            (followed_by_shuffled_operator &&
746
560k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
668k
    current_require_bucket_distribution =
749
668k
            ((require_bucket_distribution ||
750
668k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
615k
                                             : op->is_colocated_operator())) &&
752
668k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
668k
            (require_bucket_distribution &&
754
565k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
668k
    if (num_children == 0) {
757
447k
        _use_serial_source = op->is_serial_operator();
758
447k
    }
759
    // rely on that tnodes is preorder of the plan
760
907k
    for (int i = 0; i < num_children; i++) {
761
239k
        ++*node_idx;
762
239k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
239k
                                            current_followed_by_shuffled_operator,
764
239k
                                            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
239k
        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
239k
    }
775
776
668k
    return Status::OK();
777
668k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
109k
        PipelinePtr pipe_with_sink) {
782
109k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
109k
    pipe_with_source->set_num_tasks(_num_instances);
784
109k
    pipe_with_source->set_data_distribution(data_distribution);
785
109k
}
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
108k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
108k
    auto& operators = cur_pipe->operators();
793
108k
    const auto downstream_pipeline_id = cur_pipe->id();
794
108k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
108k
    DataSinkOperatorPtr sink;
797
108k
    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
108k
    const bool followed_by_shuffled_operator =
804
108k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
108k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
108k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
108k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
108k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
108k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
108k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
108k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
108k
    if (bucket_seq_to_instance_idx.empty() &&
813
108k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
8
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
8
    }
816
108k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
108k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
108k
                                          num_buckets, use_global_hash_shuffle,
819
108k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
108k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
108k
            LocalExchangeSharedState::create_shared(_num_instances);
824
108k
    switch (data_distribution.distribution_type) {
825
9.28k
    case ExchangeType::HASH_SHUFFLE:
826
9.28k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
9.28k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
9.28k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
9.28k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
9.28k
                        ? cast_set<int>(
831
9.27k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
9.28k
                        : 0);
833
9.28k
        break;
834
726
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
726
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
726
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
726
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
726
                        ? cast_set<int>(
839
726
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
726
                        : 0);
841
726
        break;
842
94.6k
    case ExchangeType::PASSTHROUGH:
843
94.6k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
94.6k
                cur_pipe->num_tasks(), _num_instances,
845
94.6k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
94.6k
                        ? cast_set<int>(
847
94.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
94.6k
                        : 0);
849
94.6k
        break;
850
562
    case ExchangeType::BROADCAST:
851
562
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
562
                cur_pipe->num_tasks(), _num_instances,
853
562
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
562
                        ? cast_set<int>(
855
562
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
562
                        : 0);
857
562
        break;
858
2.78k
    case ExchangeType::PASS_TO_ONE:
859
2.78k
        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
1.92k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.92k
                    cur_pipe->num_tasks(), _num_instances,
863
1.92k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.92k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.92k
                                                    .local_exchange_free_blocks_limit)
866
1.92k
                            : 0);
867
1.92k
        } else {
868
859
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
859
                    cur_pipe->num_tasks(), _num_instances,
870
859
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
859
                            ? cast_set<int>(_runtime_state->query_options()
872
859
                                                    .local_exchange_free_blocks_limit)
873
859
                            : 0);
874
859
        }
875
2.78k
        break;
876
934
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
934
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
934
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
934
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
934
                        ? cast_set<int>(
881
934
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
934
                        : 0);
883
934
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
108k
    }
888
109k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
109k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
109k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
109k
    _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
109k
    std::copy(operators.begin(), operators.begin() + idx,
898
109k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
109k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
109k
    OperatorPtr source_op;
905
109k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
109k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
109k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
109k
    if (!operators.empty()) {
909
45.9k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
45.9k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
45.9k
    }
912
109k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
109k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
109k
    std::vector<PipelineId> edges_with_source;
917
128k
    for (auto child : cur_pipe->children()) {
918
128k
        bool found = false;
919
143k
        for (auto op : new_pip->operators()) {
920
143k
            if (child->sink()->node_id() == op->node_id()) {
921
13.4k
                new_pip->set_children(child);
922
13.4k
                found = true;
923
13.4k
            };
924
143k
        }
925
128k
        if (!found) {
926
114k
            new_children.push_back(child);
927
114k
            edges_with_source.push_back(child->id());
928
114k
        }
929
128k
    }
930
109k
    new_children.push_back(new_pip);
931
109k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
109k
    if (!new_pip->children().empty()) {
935
7.52k
        std::vector<PipelineId> edges_with_sink;
936
13.4k
        for (auto child : new_pip->children()) {
937
13.4k
            edges_with_sink.push_back(child->id());
938
13.4k
        }
939
7.52k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.52k
    }
941
109k
    cur_pipe->set_children(new_children);
942
109k
    _dag[downstream_pipeline_id] = edges_with_source;
943
109k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
109k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
109k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
109k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
109k
    return Status::OK();
950
109k
}
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
193k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
193k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
46.8k
        return Status::OK();
959
46.8k
    }
960
961
146k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
47.6k
        return Status::OK();
963
47.6k
    }
964
98.9k
    *do_local_exchange = true;
965
966
98.9k
    auto& operators = cur_pipe->operators();
967
98.9k
    auto total_op_num = operators.size();
968
98.9k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
98.9k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
98.9k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
98.9k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
18.4E
            << "total_op_num: " << total_op_num
975
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
98.9k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
98.9k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
10.0k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
10.0k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
10.0k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
10.0k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
10.0k
                shuffle_idx_to_instance_idx));
990
10.0k
    }
991
98.9k
    return Status::OK();
992
98.9k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
429k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
990k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
560k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
560k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
125k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
125k
                if (child->sink()->node_id() ==
1003
125k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
110k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
110k
                }
1006
125k
            }
1007
120k
        }
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
560k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
560k
                                             bucket_seq_to_instance_idx,
1014
560k
                                             shuffle_idx_to_instance_idx));
1015
560k
    }
1016
429k
    return Status::OK();
1017
429k
}
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
560k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
560k
    int idx = 1;
1024
560k
    bool do_local_exchange = false;
1025
606k
    do {
1026
606k
        auto& ops = pip->operators();
1027
606k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
675k
        for (; idx < ops.size();) {
1030
114k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
106k
                RETURN_IF_ERROR(_add_local_exchange(
1032
106k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
106k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
106k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
106k
                        shuffle_idx_to_instance_idx));
1036
106k
            }
1037
114k
            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
46.0k
                idx = 2;
1043
46.0k
                break;
1044
46.0k
            }
1045
68.2k
            idx++;
1046
68.2k
        }
1047
606k
    } while (do_local_exchange);
1048
560k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
87.2k
        RETURN_IF_ERROR(_add_local_exchange(
1050
87.2k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
87.2k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
87.2k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
87.2k
    }
1054
560k
    return Status::OK();
1055
560k
}
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
432k
                                                  PipelineId cur_pipeline_id) {
1063
432k
    switch (thrift_sink.type) {
1064
144k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
144k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
144k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
144k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
144k
                params.destinations, _fragment_instance_ids);
1071
144k
        break;
1072
144k
    }
1073
249k
    case TDataSinkType::RESULT_SINK: {
1074
249k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
249k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
249k
        int child_node_id = pipeline->operators().back()->node_id();
1080
249k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
249k
                                                      row_desc, output_exprs,
1082
249k
                                                      thrift_sink.result_sink);
1083
249k
        break;
1084
249k
    }
1085
104
    case TDataSinkType::DICTIONARY_SINK: {
1086
104
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
104
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
104
                                                    thrift_sink.dictionary_sink);
1092
104
        break;
1093
104
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
31.4k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
31.4k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
31.4k
        int child_node_id = pipeline->operators().back()->node_id();
1098
31.4k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
31.4k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
31.4k
            !config::is_cloud_mode()) {
1101
2.16k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.16k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
29.2k
        } else {
1104
29.2k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
29.2k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
29.2k
        }
1107
31.4k
        break;
1108
0
    }
1109
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
165
        DCHECK(state->get_query_ctx() != nullptr);
1112
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
165
                                                                output_exprs);
1115
165
        break;
1116
0
    }
1117
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.46k
                                                         output_exprs);
1123
1.46k
        break;
1124
1.46k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
1.73k
        } else {
1133
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.73k
                                                                row_desc, output_exprs);
1135
1.73k
        }
1136
1.73k
        break;
1137
1.73k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
502
    case TDataSinkType::RESULT_FILE_SINK: {
1186
502
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
502
        } else {
1196
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
502
                                                              output_exprs);
1198
502
        }
1199
502
        break;
1200
502
    }
1201
2.02k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.02k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.02k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.02k
        auto sink_id = next_sink_operator_id();
1205
2.02k
        const int multi_cast_node_id = sink_id;
1206
2.02k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.02k
        std::vector<int> sources;
1209
7.89k
        for (int i = 0; i < sender_size; ++i) {
1210
5.86k
            auto source_id = next_operator_id();
1211
5.86k
            sources.push_back(source_id);
1212
5.86k
        }
1213
1214
2.02k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.02k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
7.89k
        for (int i = 0; i < sender_size; ++i) {
1217
5.86k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
5.86k
            RowDescriptor* exchange_row_desc = nullptr;
1220
5.86k
            {
1221
5.86k
                const auto& tmp_row_desc =
1222
5.86k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
5.86k
                                ? RowDescriptor(state->desc_tbl(),
1224
5.86k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
5.86k
                                                         .output_tuple_id})
1226
18.4E
                                : row_desc;
1227
5.86k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
5.86k
            }
1229
5.86k
            auto source_id = sources[i];
1230
5.86k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
5.86k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
5.86k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
5.86k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
5.86k
                    /*operator_id=*/source_id);
1236
5.86k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
5.86k
                    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
5.86k
            DataSinkOperatorPtr sink_op;
1241
5.86k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
5.86k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
5.86k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
5.86k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
5.86k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
5.86k
            {
1248
5.86k
                TDataSink* t = pool->add(new TDataSink());
1249
5.86k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
5.86k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
5.86k
            }
1252
1253
            // 3. set dependency dag
1254
5.86k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
5.86k
        }
1256
2.02k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.02k
        break;
1260
2.02k
    }
1261
2.02k
    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
432k
    }
1280
431k
    return Status::OK();
1281
432k
}
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
672k
                                                 OperatorPtr& cache_op) {
1292
672k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
672k
    Defer defer = Defer([&]() {
1294
671k
        if (op) {
1295
671k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
671k
        }
1297
670k
        for (auto& s : sink_ops) {
1298
125k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
125k
        }
1300
670k
    });
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
672k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
672k
    std::stringstream error_msg;
1305
672k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
672k
    bool fe_with_old_version = false;
1308
672k
    switch (tnode.node_type) {
1309
211k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
211k
        op = std::make_shared<OlapScanOperatorX>(
1311
211k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
211k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
211k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
211k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
211k
        break;
1316
211k
    }
1317
81
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
81
        DCHECK(_query_ctx != nullptr);
1319
81
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
81
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
81
                                                    _num_instances);
1322
81
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
81
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
81
        break;
1325
81
    }
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
23.2k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
23.2k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
23.2k
                                                 _num_instances);
1342
23.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
23.2k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
23.2k
        break;
1345
23.2k
    }
1346
148k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
148k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
148k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
148k
        DCHECK_GT(num_senders, 0);
1351
148k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
148k
                                                       num_senders);
1353
148k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
148k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
148k
        break;
1356
148k
    }
1357
158k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
158k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
158k
            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
158k
        bool need_create_cache_op =
1364
158k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
158k
        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
158k
        const bool group_by_limit_opt =
1385
158k
                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
158k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
158k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
158k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
158k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
158k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
158k
        const bool can_use_distinct_streaming_agg =
1396
158k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
158k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
158k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
158k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
158k
        if (can_use_distinct_streaming_agg) {
1402
91.4k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
91.4k
            } else {
1413
91.4k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
91.4k
                                                                     tnode, descs);
1415
91.4k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
91.4k
            }
1417
91.4k
        } else if (is_streaming_agg) {
1418
3.40k
            if (need_create_cache_op) {
1419
0
                PipelinePtr new_pipe;
1420
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1421
0
                cache_op = op;
1422
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
0
                                                             descs);
1424
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1425
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1426
0
                cur_pipe = new_pipe;
1427
3.40k
            } else {
1428
3.40k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
3.40k
                                                             descs);
1430
3.40k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
3.40k
            }
1432
63.4k
        } else {
1433
            // create new pipeline to add query cache operator
1434
63.4k
            PipelinePtr new_pipe;
1435
63.4k
            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
63.4k
            if (enable_spill) {
1441
176
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
176
                                                                     next_operator_id(), descs);
1443
63.2k
            } else {
1444
63.2k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
63.2k
            }
1446
63.4k
            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
63.4k
            } else {
1451
63.4k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
63.4k
            }
1453
1454
63.4k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
63.4k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
60.8k
                _dag.insert({downstream_pipeline_id, {}});
1457
60.8k
            }
1458
63.4k
            cur_pipe = add_pipeline(cur_pipe);
1459
63.4k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
63.4k
            if (enable_spill) {
1462
176
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
176
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
63.2k
            } else {
1465
63.2k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
63.2k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
63.2k
            }
1468
63.4k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
63.4k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
63.4k
        }
1471
158k
        break;
1472
158k
    }
1473
158k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
81
        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
81
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
81
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
81
        const auto downstream_pipeline_id = cur_pipe->id();
1486
81
        if (!_dag.contains(downstream_pipeline_id)) {
1487
81
            _dag.insert({downstream_pipeline_id, {}});
1488
81
        }
1489
81
        cur_pipe = add_pipeline(cur_pipe);
1490
81
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
81
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
81
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
81
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
81
        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
81
        {
1503
81
            auto shared_state = BucketedAggSharedState::create_shared();
1504
81
            shared_state->id = op->operator_id();
1505
81
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
568
            for (int i = 0; i < _num_instances; i++) {
1508
487
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
487
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
487
                sink_dep->set_shared_state(shared_state.get());
1511
487
                shared_state->sink_deps.push_back(sink_dep);
1512
487
            }
1513
81
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
81
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
81
            _op_id_to_shared_state.insert(
1516
81
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
81
        }
1518
81
        break;
1519
81
    }
1520
9.66k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.66k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.66k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.66k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.66k
        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
9.66k
        } else {
1566
9.66k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.66k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.66k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.66k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.95k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.95k
            }
1573
9.66k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.66k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.66k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.66k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.66k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.66k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.66k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.66k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.66k
        }
1584
9.66k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
4.92k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
4.92k
                    HashJoinSharedState::create_shared(_num_instances);
1587
26.7k
            for (int i = 0; i < _num_instances; i++) {
1588
21.8k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
21.8k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
21.8k
                sink_dep->set_shared_state(shared_state.get());
1591
21.8k
                shared_state->sink_deps.push_back(sink_dep);
1592
21.8k
            }
1593
4.92k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
4.92k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
4.92k
            _op_id_to_shared_state.insert(
1596
4.92k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
4.92k
        }
1598
9.66k
        break;
1599
9.66k
    }
1600
4.97k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
4.97k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
4.97k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
4.97k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
4.97k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
4.74k
            _dag.insert({downstream_pipeline_id, {}});
1607
4.74k
        }
1608
4.97k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
4.97k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
4.97k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
4.97k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
4.97k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
4.97k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
4.97k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
4.97k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
4.97k
        break;
1618
4.97k
    }
1619
53.4k
    case TPlanNodeType::UNION_NODE: {
1620
53.4k
        int child_count = tnode.num_children;
1621
53.4k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
53.4k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
53.4k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
53.4k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
52.9k
            _dag.insert({downstream_pipeline_id, {}});
1627
52.9k
        }
1628
54.8k
        for (int i = 0; i < child_count; i++) {
1629
1.40k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.40k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.40k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.40k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.40k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.40k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.40k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.40k
        }
1638
53.4k
        break;
1639
53.4k
    }
1640
53.4k
    case TPlanNodeType::SORT_NODE: {
1641
43.6k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
43.6k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
43.6k
        const bool use_local_merge =
1644
43.6k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
43.6k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
43.6k
        } else if (use_local_merge) {
1648
41.3k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
41.3k
                                                                 descs);
1650
41.3k
        } else {
1651
2.30k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.30k
        }
1653
43.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
43.6k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
43.6k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
43.6k
            _dag.insert({downstream_pipeline_id, {}});
1658
43.6k
        }
1659
43.6k
        cur_pipe = add_pipeline(cur_pipe);
1660
43.6k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
43.6k
        if (should_spill) {
1663
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
43.6k
        } else {
1666
43.6k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
43.6k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
43.6k
        }
1669
43.6k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
43.6k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
43.6k
        break;
1672
43.6k
    }
1673
43.6k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.63k
        }
1698
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.64k
        break;
1706
1.64k
    }
1707
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.60k
        break;
1711
1.60k
    }
1712
1.60k
    case TPlanNodeType::INTERSECT_NODE: {
1713
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
133
                                                                      cur_pipe, sink_ops));
1715
133
        break;
1716
133
    }
1717
133
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
296
    case TPlanNodeType::REPEAT_NODE: {
1723
296
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
296
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
296
        break;
1726
296
    }
1727
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
1.55k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.55k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.55k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.55k
        break;
1741
1.55k
    }
1742
1.55k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
457
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
457
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
457
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
457
        break;
1747
457
    }
1748
2.04k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.04k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.04k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.04k
        break;
1752
2.04k
    }
1753
6.09k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.09k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.09k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.09k
        break;
1757
6.09k
    }
1758
6.09k
    case TPlanNodeType::SELECT_NODE: {
1759
2.01k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.01k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.01k
        break;
1762
2.01k
    }
1763
2.01k
    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
672k
    }
1803
671k
    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
671k
    return Status::OK();
1809
672k
}
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
266
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
266
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
266
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
266
    const auto downstream_pipeline_id = cur_pipe->id();
1821
266
    if (!_dag.contains(downstream_pipeline_id)) {
1822
242
        _dag.insert({downstream_pipeline_id, {}});
1823
242
    }
1824
1825
892
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
626
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
626
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
626
        if (child_id == 0) {
1830
266
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
266
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
360
        } else {
1833
360
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
360
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
360
        }
1836
626
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
626
        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
626
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
626
    }
1841
1842
266
    return Status::OK();
1843
266
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_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
118
        _dag.insert({downstream_pipeline_id, {}});
1823
118
    }
1824
1825
478
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
345
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
345
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
345
        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
212
        } else {
1833
212
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
212
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
212
        }
1836
345
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
345
        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
345
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
345
    }
1841
1842
133
    return Status::OK();
1843
133
}
_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
430k
Status PipelineFragmentContext::submit() {
1846
430k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
430k
    _submitted = true;
1850
1851
430k
    int submit_tasks = 0;
1852
430k
    Status st;
1853
430k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.16M
    for (auto& task : _tasks) {
1855
1.96M
        for (auto& t : task) {
1856
1.96M
            st = scheduler->submit(t.first);
1857
1.96M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.96M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.96M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
1.96M
            submit_tasks++;
1866
1.96M
        }
1867
1.16M
    }
1868
430k
    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
430k
    } else {
1883
430k
        return st;
1884
430k
    }
1885
430k
}
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
432k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
432k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
432k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
432k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
432k
    if (!_need_notify_close) {
1919
429k
        auto st = send_report(true);
1920
429k
        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
429k
    }
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
432k
    if (_runtime_state->enable_profile() &&
1931
432k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.54k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.54k
         _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
432k
    if (_query_ctx->enable_profile()) {
1953
2.54k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.54k
                                         collect_realtime_load_channel_profile());
1955
2.54k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
432k
    return !_need_notify_close;
1960
432k
}
1961
1962
1.95M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
1.95M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.95M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
673k
        if (_dag.contains(pipeline_id)) {
1967
349k
            for (auto dep : _dag[pipeline_id]) {
1968
349k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
349k
            }
1970
282k
        }
1971
673k
    }
1972
1.95M
    bool need_remove = false;
1973
1.95M
    {
1974
1.95M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.95M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.95M
        _query_ctx->inc_finished_task_num();
1978
1.95M
        if (_closed_tasks >= _total_tasks) {
1979
432k
            need_remove = _close_fragment_instance();
1980
432k
        }
1981
1.95M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.95M
    if (need_remove) {
1984
429k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
429k
    }
1986
1.95M
}
1987
1988
54.0k
std::string PipelineFragmentContext::get_load_error_url() {
1989
54.0k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1990
0
        return to_load_error_http_path(str);
1991
0
    }
1992
148k
    for (auto& tasks : _tasks) {
1993
236k
        for (auto& task : tasks) {
1994
236k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
177
                return to_load_error_http_path(str);
1996
177
            }
1997
236k
        }
1998
148k
    }
1999
53.8k
    return "";
2000
54.0k
}
2001
2002
54.0k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
54.0k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
148k
    for (auto& tasks : _tasks) {
2007
236k
        for (auto& task : tasks) {
2008
236k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
177
                return str;
2010
177
            }
2011
236k
        }
2012
148k
    }
2013
53.8k
    return "";
2014
54.0k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
48.0k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
48.0k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
48.0k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
48.0k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
48.0k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
48.0k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
48.0k
    });
2031
2032
48.0k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
48.0k
    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
48.0k
    int callback_retries = 10;
2038
48.0k
    const int sleep_ms = 1000;
2039
48.0k
    Status exec_status = req.status;
2040
48.0k
    Status coord_status;
2041
48.0k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
48.0k
    do {
2043
48.0k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
48.0k
                                                            req.coord_addr, &coord_status);
2045
48.0k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
48.0k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
48.0k
    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
48.0k
    TReportExecStatusParams params;
2059
48.0k
    params.protocol_version = FrontendServiceVersion::V1;
2060
48.0k
    params.__set_query_id(req.query_id);
2061
48.0k
    params.__set_backend_num(req.backend_num);
2062
48.0k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
48.0k
    params.__set_fragment_id(req.fragment_id);
2064
48.0k
    params.__set_status(exec_status.to_thrift());
2065
48.0k
    params.__set_done(req.done);
2066
48.0k
    params.__set_query_type(req.runtime_state->query_type());
2067
48.0k
    params.__isset.profile = false;
2068
2069
48.0k
    DCHECK(req.runtime_state != nullptr);
2070
2071
48.0k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
43.4k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
43.4k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
43.4k
    } else {
2075
4.64k
        DCHECK(!req.runtime_states.empty());
2076
4.64k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
4.64k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.64k
    }
2086
2087
48.0k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
48.0k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
48.0k
    static std::string s_unselected_rows = "unselected.rows";
2090
48.0k
    int64_t num_rows_load_success = 0;
2091
48.0k
    int64_t num_rows_load_filtered = 0;
2092
48.0k
    int64_t num_rows_load_unselected = 0;
2093
48.0k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
48.0k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
48.0k
        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
48.0k
    } else if (!req.runtime_states.empty()) {
2109
177k
        for (auto* rs : req.runtime_states) {
2110
177k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
177k
                rs->num_finished_range() > 0) {
2112
36.2k
                params.__isset.load_counters = true;
2113
36.2k
                num_rows_load_success += rs->num_rows_load_success();
2114
36.2k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
36.2k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
36.2k
                params.__isset.fragment_instance_reports = true;
2117
36.2k
                TFragmentInstanceReport t;
2118
36.2k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
36.2k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
36.2k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
36.2k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
36.2k
                params.fragment_instance_reports.push_back(t);
2123
36.2k
            }
2124
177k
        }
2125
48.0k
    }
2126
48.0k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
48.0k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
48.0k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
48.0k
    if (!req.load_error_url.empty()) {
2131
159
        params.__set_tracking_url(req.load_error_url);
2132
159
    }
2133
48.0k
    if (!req.first_error_msg.empty()) {
2134
159
        params.__set_first_error_msg(req.first_error_msg);
2135
159
    }
2136
177k
    for (auto* rs : req.runtime_states) {
2137
177k
        if (rs->wal_id() > 0) {
2138
113
            params.__set_txn_id(rs->wal_id());
2139
113
            params.__set_label(rs->import_label());
2140
113
        }
2141
177k
    }
2142
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2146
177k
        for (auto* rs : req.runtime_states) {
2147
177k
            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
177k
        }
2154
48.0k
    }
2155
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2159
177k
        for (auto* rs : req.runtime_states) {
2160
177k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
27.1k
                params.__isset.commitInfos = true;
2162
27.1k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
27.1k
            }
2164
177k
        }
2165
48.0k
    }
2166
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2170
177k
        for (auto* rs : req.runtime_states) {
2171
177k
            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
177k
        }
2177
48.0k
    }
2178
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2183
177k
        for (auto* rs : req.runtime_states) {
2184
177k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.12k
                params.__isset.hive_partition_updates = true;
2186
2.12k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.12k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.12k
            }
2189
177k
        }
2190
48.0k
    }
2191
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2196
177k
        for (auto* rs : req.runtime_states) {
2197
177k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.07k
                params.__isset.iceberg_commit_datas = true;
2199
2.07k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.07k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.07k
            }
2202
177k
        }
2203
48.0k
    }
2204
2205
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2209
177k
        for (auto* rs : req.runtime_states) {
2210
177k
            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
177k
        }
2216
48.0k
    }
2217
2218
48.0k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
48.0k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
48.0k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
48.0k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
48.0k
    }
2224
2225
48.0k
    TReportExecStatusResult res;
2226
48.0k
    Status rpc_status;
2227
2228
48.0k
    VLOG_DEBUG << "reportExecStatus params is "
2229
3
               << apache::thrift::ThriftDebugString(params).c_str();
2230
48.0k
    if (!exec_status.ok()) {
2231
1.66k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.66k
                     << " to coordinator: " << req.coord_addr
2233
1.66k
                     << ", query id: " << print_id(req.query_id);
2234
1.66k
    }
2235
48.0k
    try {
2236
48.0k
        try {
2237
48.0k
            (*coord)->reportExecStatus(res, params);
2238
48.0k
        } 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
48.0k
        rpc_status = Status::create<false>(res.status);
2254
48.0k
    } 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
48.0k
    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
48.0k
}
2265
2266
434k
Status PipelineFragmentContext::send_report(bool done) {
2267
434k
    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
434k
    if (!_is_report_success && done && exec_status.ok()) {
2273
386k
        return Status::OK();
2274
386k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
48.3k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
299
        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
299
            return Status::OK();
2286
299
        }
2287
0
        return Status::NeedSendAgain("");
2288
299
    }
2289
2290
48.0k
    std::vector<RuntimeState*> runtime_states;
2291
2292
121k
    for (auto& tasks : _tasks) {
2293
177k
        for (auto& task : tasks) {
2294
177k
            runtime_states.push_back(task.second.get());
2295
177k
        }
2296
121k
    }
2297
2298
48.0k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
48.0k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
48.0k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
48.0k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
48.0k
    ReportStatusRequest req {.status = exec_status,
2306
48.0k
                             .runtime_states = runtime_states,
2307
48.0k
                             .done = done || !exec_status.ok(),
2308
48.0k
                             .coord_addr = _query_ctx->coord_addr,
2309
48.0k
                             .query_id = _query_id,
2310
48.0k
                             .fragment_id = _fragment_id,
2311
48.0k
                             .fragment_instance_id = TUniqueId(),
2312
48.0k
                             .backend_num = -1,
2313
48.0k
                             .runtime_state = _runtime_state.get(),
2314
48.0k
                             .load_error_url = load_eror_url,
2315
48.0k
                             .first_error_msg = first_error_msg,
2316
48.0k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
48.0k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
48.0k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
48.0k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
48.0k
        _coordinator_callback(req);
2321
48.0k
        if (!req.done) {
2322
4.81k
            ctx->refresh_next_report_time();
2323
4.81k
        }
2324
48.0k
    });
2325
48.3k
}
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
178
std::string PipelineFragmentContext::debug_string() {
2365
178
    std::lock_guard<std::mutex> l(_task_mutex);
2366
178
    fmt::memory_buffer debug_string_buffer;
2367
178
    fmt::format_to(debug_string_buffer,
2368
178
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
178
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
178
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
846
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
668
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
1.52k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
854
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
854
                           _tasks[j][i].first->debug_string());
2376
854
        }
2377
668
    }
2378
2379
178
    return fmt::to_string(debug_string_buffer);
2380
178
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.54k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.54k
    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
2.54k
    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
2.54k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.54k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.54k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.64k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.64k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.64k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.64k
        res.push_back(profile_ptr);
2407
4.64k
    }
2408
2409
2.54k
    return res;
2410
2.54k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.54k
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
2.54k
    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
7.76k
    for (const auto& tasks : _tasks) {
2426
15.2k
        for (const auto& task : tasks) {
2427
15.2k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
15.2k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
15.2k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
15.2k
                                                           _runtime_state->profile_level());
2435
15.2k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
15.2k
        }
2437
7.76k
    }
2438
2439
2.54k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.54k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.54k
                                                      _runtime_state->profile_level());
2442
2.54k
    return load_channel_profile;
2443
2.54k
}
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
3.08k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.08k
    std::set<int> result;
2454
4.07k
    for (const auto& _task : _tasks) {
2455
6.54k
        for (const auto& task : _task) {
2456
6.54k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
6.54k
            result.merge(set);
2458
6.54k
        }
2459
4.07k
    }
2460
3.08k
    if (_runtime_state) {
2461
3.08k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.08k
        result.merge(set);
2463
3.08k
    }
2464
3.08k
    return result;
2465
3.08k
}
2466
2467
433k
void PipelineFragmentContext::_release_resource() {
2468
433k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
433k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
433k
    auto st = _query_ctx->exec_status();
2472
1.16M
    for (auto& _task : _tasks) {
2473
1.16M
        if (!_task.empty()) {
2474
1.16M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.16M
        }
2476
1.16M
    }
2477
433k
    _tasks.clear();
2478
433k
    _dag.clear();
2479
433k
    _pip_id_to_pipeline.clear();
2480
433k
    _pipelines.clear();
2481
433k
    _sink.reset();
2482
433k
    _root_op.reset();
2483
433k
    _runtime_filter_mgr_map.clear();
2484
433k
    _op_id_to_shared_state.clear();
2485
433k
}
2486
2487
} // namespace doris