Coverage Report

Created: 2026-05-15 05:27

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
9
//   http://www.apache.org/licenses/LICENSE-2.0
10
//
11
// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
13
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
17
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
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
436k
        : _query_id(std::move(query_id)),
144
436k
          _fragment_id(request.fragment_id),
145
436k
          _exec_env(exec_env),
146
436k
          _query_ctx(std::move(query_ctx)),
147
436k
          _call_back(call_back),
148
436k
          _is_report_on_cancel(true),
149
436k
          _params(request),
150
436k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
436k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
436k
                                                               : false) {
153
436k
    _fragment_watcher.start();
154
436k
}
155
156
436k
PipelineFragmentContext::~PipelineFragmentContext() {
157
436k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
436k
            .tag("query_id", print_id(_query_id))
159
436k
            .tag("fragment_id", _fragment_id);
160
436k
    _release_resource();
161
436k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
436k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
436k
        _runtime_state.reset();
165
436k
        _query_ctx.reset();
166
436k
    }
167
436k
}
168
169
21
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
21
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
21
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
21
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
179
// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
10.1k
bool PipelineFragmentContext::notify_close() {
181
10.1k
    bool all_closed = false;
182
10.1k
    bool need_remove = false;
183
10.1k
    {
184
10.1k
        std::lock_guard<std::mutex> l(_task_mutex);
185
10.1k
        if (_closed_tasks >= _total_tasks) {
186
3.22k
            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
190
                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
192
3.12k
                need_remove = true;
193
3.12k
            }
194
3.22k
            all_closed = true;
195
3.22k
        }
196
        // make fragment release by self after cancel
197
10.1k
        _need_notify_close = false;
198
10.1k
    }
199
10.1k
    if (need_remove) {
200
3.12k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.12k
    }
202
10.1k
    return all_closed;
203
10.1k
}
204
205
// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
6.84k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.84k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.84k
            .tag("query_id", print_id(_query_id))
212
6.84k
            .tag("fragment_id", _fragment_id)
213
6.84k
            .tag("reason", reason.to_string());
214
6.84k
    if (notify_close()) {
215
108
        return;
216
108
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.73k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
6.73k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
6.73k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
6.73k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
6.73k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
6.73k
    _query_ctx->cancel(reason, _fragment_id);
243
6.73k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
406
        _is_report_on_cancel = false;
245
6.32k
    } else {
246
39.7k
        for (auto& id : _fragment_instance_ids) {
247
39.7k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
39.7k
        }
249
6.32k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
6.73k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.73k
    if (stream_load_ctx != nullptr) {
254
31
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
31
        stream_load_ctx->error_url = get_load_error_url();
259
31
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
31
    }
261
262
41.2k
    for (auto& tasks : _tasks) {
263
89.8k
        for (auto& task : tasks) {
264
89.8k
            task.first->unblock_all_dependencies();
265
89.8k
        }
266
41.2k
    }
267
6.73k
}
268
269
685k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
685k
    PipelineId id = _next_pipeline_id++;
271
685k
    auto pipeline = std::make_shared<Pipeline>(
272
685k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
685k
            parent ? parent->num_tasks() : _num_instances);
274
685k
    if (idx >= 0) {
275
117k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
568k
    } else {
277
568k
        _pipelines.emplace_back(pipeline);
278
568k
    }
279
685k
    if (parent) {
280
243k
        parent->set_children(pipeline);
281
243k
    }
282
685k
    return pipeline;
283
685k
}
284
285
435k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
435k
    {
287
435k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
435k
        auto root_pipeline = add_pipeline();
290
435k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
435k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
435k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
435k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
435k
                                          _params.fragment.output_exprs, _params,
299
435k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
435k
                                          *_desc_tbl, root_pipeline->id()));
301
435k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
435k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
567k
        for (PipelinePtr& pipeline : _pipelines) {
305
567k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
567k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
567k
        }
308
435k
    }
309
    // 4. Build local exchanger
310
435k
    if (_runtime_state->enable_local_shuffle()) {
311
433k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
433k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
433k
                                             _params.bucket_seq_to_instance_idx,
314
433k
                                             _params.shuffle_idx_to_instance_idx));
315
433k
    }
316
317
    // 5. Initialize global states in pipelines.
318
686k
    for (PipelinePtr& pipeline : _pipelines) {
319
686k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
686k
        pipeline->children().clear();
321
686k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
686k
    }
323
324
434k
    {
325
434k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
434k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
434k
    }
329
330
434k
    return Status::OK();
331
434k
}
332
333
436k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
436k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
436k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
436k
        _timeout = _params.query_options.execution_timeout;
339
436k
    }
340
341
436k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
436k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
436k
    SCOPED_TIMER(_prepare_timer);
344
436k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
436k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
436k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
436k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
436k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
436k
    {
350
436k
        SCOPED_TIMER(_init_context_timer);
351
436k
        cast_set(_num_instances, _params.local_params.size());
352
436k
        _total_instances =
353
436k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
436k
        auto* fragment_context = this;
356
357
436k
        if (_params.query_options.__isset.is_report_success) {
358
433k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
433k
        }
360
361
        // 1. Set up the global runtime state.
362
436k
        _runtime_state = RuntimeState::create_unique(
363
436k
                _params.query_id, _params.fragment_id, _params.query_options,
364
436k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
436k
        _runtime_state->set_task_execution_context(shared_from_this());
366
436k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
436k
        if (_params.__isset.backend_id) {
368
432k
            _runtime_state->set_backend_id(_params.backend_id);
369
432k
        }
370
436k
        if (_params.__isset.import_label) {
371
239
            _runtime_state->set_import_label(_params.import_label);
372
239
        }
373
436k
        if (_params.__isset.db_name) {
374
191
            _runtime_state->set_db_name(_params.db_name);
375
191
        }
376
436k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
436k
        if (_params.is_simplified_param) {
381
148k
            _desc_tbl = _query_ctx->desc_tbl;
382
287k
        } else {
383
287k
            DCHECK(_params.__isset.desc_tbl);
384
287k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
287k
                                                  &_desc_tbl));
386
287k
        }
387
436k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
436k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
436k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
436k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
436k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
436k
        const auto target_size = _params.local_params.size();
395
436k
        _fragment_instance_ids.resize(target_size);
396
1.76M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.32M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.32M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.32M
        }
400
436k
    }
401
402
436k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
434k
    _init_next_report_time();
405
406
434k
    _prepared = true;
407
434k
    return Status::OK();
408
436k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.33M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.33M
    const auto& local_params = _params.local_params[instance_idx];
414
1.33M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.33M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.33M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.33M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.33M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
2.19M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
2.19M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
2.19M
                                std::vector<std::shared_ptr<Dependency>>>>
422
2.19M
                shared_state_map;
423
2.90M
        for (auto& op : pipeline->operators()) {
424
2.90M
            auto source_id = op->operator_id();
425
2.90M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.90M
                iter != _op_id_to_shared_state.end()) {
427
859k
                shared_state_map.insert({source_id, iter->second});
428
859k
            }
429
2.90M
        }
430
2.20M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
2.20M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
2.20M
                iter != _op_id_to_shared_state.end()) {
433
325k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
325k
            }
435
2.20M
        }
436
2.19M
        return shared_state_map;
437
2.19M
    };
438
439
4.05M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.72M
        auto& pipeline = _pipelines[pip_idx];
441
2.72M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
2.19M
            auto task_runtime_state = RuntimeState::create_unique(
443
2.19M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
2.19M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
2.19M
            {
446
                // Initialize runtime state for this task
447
2.19M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
2.19M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
2.19M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
2.19M
                if (_params.__isset.backend_id) {
453
2.19M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
2.19M
                }
455
2.19M
                if (_params.__isset.import_label) {
456
240
                    task_runtime_state->set_import_label(_params.import_label);
457
240
                }
458
2.19M
                if (_params.__isset.db_name) {
459
192
                    task_runtime_state->set_db_name(_params.db_name);
460
192
                }
461
2.19M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
2.19M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
2.19M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
2.19M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
2.19M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
2.19M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
2.19M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
2.19M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
2.19M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
2.19M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
2.19M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
2.19M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
2.19M
            }
482
2.19M
            auto cur_task_id = _total_tasks++;
483
2.19M
            task_runtime_state->set_task_id(cur_task_id);
484
2.19M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
2.19M
            auto task = std::make_shared<PipelineTask>(
486
2.19M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
2.19M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
2.19M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
2.19M
                    instance_idx);
490
2.19M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
2.19M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
2.19M
            _tasks[instance_idx].emplace_back(
493
2.19M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
2.19M
                            std::move(task), std::move(task_runtime_state)});
495
2.19M
        }
496
2.72M
    }
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
2.72M
    for (auto& _pipeline : _pipelines) {
516
2.72M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
2.18M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
2.18M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
2.18M
            if (_dag.contains(_pipeline->id())) {
522
1.39M
                auto& deps = _dag[_pipeline->id()];
523
2.23M
                for (auto& dep : deps) {
524
2.23M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.17M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.17M
                        if (ss) {
527
526k
                            task->inject_shared_state(ss);
528
643k
                        } else {
529
643k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
643k
                                    task->get_source_shared_state());
531
643k
                        }
532
1.17M
                    }
533
2.23M
                }
534
1.39M
            }
535
2.18M
        }
536
2.72M
    }
537
4.05M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.72M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
2.18M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
2.18M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
2.18M
            std::vector<TScanRangeParams> scan_ranges;
542
2.18M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
2.18M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
348k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
348k
            }
546
2.18M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
2.18M
                                                             _params.fragment.output_sink));
548
2.18M
        }
549
2.72M
    }
550
1.33M
    {
551
1.33M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.33M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.33M
    }
554
1.33M
    return Status::OK();
555
1.33M
}
556
557
435k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
435k
    _total_tasks = 0;
559
435k
    _closed_tasks = 0;
560
435k
    const auto target_size = _params.local_params.size();
561
435k
    _tasks.resize(target_size);
562
435k
    _runtime_filter_mgr_map.resize(target_size);
563
1.12M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
684k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
684k
    }
566
435k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
435k
    if (target_size > 1 &&
569
435k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
146k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
571
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
572
27.4k
        std::vector<Status> prepare_status(target_size);
573
27.4k
        int submitted_tasks = 0;
574
27.4k
        Status submit_status;
575
27.4k
        CountDownLatch latch((int)target_size);
576
341k
        for (int i = 0; i < target_size; i++) {
577
313k
            submit_status = thread_pool->submit_func([&, i]() {
578
313k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
313k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
313k
                latch.count_down();
581
313k
            });
582
313k
            if (LIKELY(submit_status.ok())) {
583
313k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
313k
        }
588
27.4k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
27.4k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
341k
        for (int i = 0; i < submitted_tasks; i++) {
593
313k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
313k
        }
597
407k
    } else {
598
1.42M
        for (int i = 0; i < target_size; i++) {
599
1.02M
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
1.02M
        }
601
407k
    }
602
435k
    _pipeline_parent_map.clear();
603
435k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
435k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
435k
    return Status::OK();
608
435k
}
609
610
433k
void PipelineFragmentContext::_init_next_report_time() {
611
433k
    auto interval_s = config::pipeline_status_report_interval;
612
433k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
18.4E
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.1k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
42.1k
        _previous_report_time =
617
42.1k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.1k
        _disable_period_report = false;
619
42.1k
    }
620
433k
}
621
622
5.05k
void PipelineFragmentContext::refresh_next_report_time() {
623
5.05k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
5.05k
    DCHECK(disable == true);
625
5.05k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
5.05k
    _disable_period_report.compare_exchange_strong(disable, false);
627
5.05k
}
628
629
7.89M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.89M
    if (!_is_report_success) {
631
7.36M
        return;
632
7.36M
    }
633
523k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
523k
    if (disable) {
635
8.53k
        return;
636
8.53k
    }
637
515k
    int32_t interval_s = config::pipeline_status_report_interval;
638
515k
    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
515k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
515k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
515k
    if (MonotonicNanos() > next_report_time) {
646
5.06k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
5.06k
                                                            std::memory_order_acq_rel)) {
648
11
            return;
649
11
        }
650
5.05k
        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
5.05k
        auto st = send_report(false);
667
5.05k
        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
5.05k
    }
673
515k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
432k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
432k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
432k
    int node_idx = 0;
682
683
432k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
432k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
432k
    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
432k
    return Status::OK();
691
432k
}
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
673k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
673k
    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
673k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
673k
    int num_children = tnodes[*node_idx].num_children;
706
673k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
673k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
673k
    OperatorPtr op = nullptr;
710
673k
    OperatorPtr cache_op = nullptr;
711
673k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
673k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
673k
                                     followed_by_shuffled_operator,
714
673k
                                     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
673k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
673k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
241k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
432k
    } else {
723
432k
        *root = op;
724
432k
    }
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
673k
    auto required_data_distribution =
737
673k
            cur_pipe->operators().empty()
738
673k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
673k
                    : op->required_data_distribution(_runtime_state.get());
740
673k
    current_followed_by_shuffled_operator =
741
673k
            ((followed_by_shuffled_operator ||
742
673k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
615k
                                             : op->is_shuffled_operator())) &&
744
673k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
673k
            (followed_by_shuffled_operator &&
746
563k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
673k
    current_require_bucket_distribution =
749
673k
            ((require_bucket_distribution ||
750
673k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
620k
                                             : op->is_colocated_operator())) &&
752
673k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
673k
            (require_bucket_distribution &&
754
569k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
673k
    if (num_children == 0) {
757
451k
        _use_serial_source = op->is_serial_operator();
758
451k
    }
759
    // rely on that tnodes is preorder of the plan
760
915k
    for (int i = 0; i < num_children; i++) {
761
241k
        ++*node_idx;
762
241k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
241k
                                            current_followed_by_shuffled_operator,
764
241k
                                            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
241k
        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
241k
    }
775
776
673k
    return Status::OK();
777
673k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
117k
        PipelinePtr pipe_with_sink) {
782
117k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
117k
    pipe_with_source->set_num_tasks(_num_instances);
784
117k
    pipe_with_source->set_data_distribution(data_distribution);
785
117k
}
786
787
Status PipelineFragmentContext::_add_local_exchange_impl(
788
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
789
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
790
        const std::map<int, int>& bucket_seq_to_instance_idx,
791
117k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
117k
    auto& operators = cur_pipe->operators();
793
117k
    const auto downstream_pipeline_id = cur_pipe->id();
794
117k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
117k
    DataSinkOperatorPtr sink;
797
117k
    auto sink_id = next_sink_operator_id();
798
799
    /**
800
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
801
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
802
     */
803
117k
    const bool followed_by_shuffled_operator =
804
117k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
117k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
117k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
117k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
117k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
117k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
117k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
117k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
117k
    if (bucket_seq_to_instance_idx.empty() &&
813
117k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
37
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
37
    }
816
117k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
117k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
117k
                                          num_buckets, use_global_hash_shuffle,
819
117k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
117k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
117k
            LocalExchangeSharedState::create_shared(_num_instances);
824
117k
    switch (data_distribution.distribution_type) {
825
15.1k
    case ExchangeType::HASH_SHUFFLE:
826
15.1k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
15.1k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
15.1k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
15.1k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
15.1k
                        ? cast_set<int>(
831
15.1k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
15.1k
                        : 0);
833
15.1k
        break;
834
556
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
556
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
556
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
556
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
556
                        ? cast_set<int>(
839
556
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
556
                        : 0);
841
556
        break;
842
97.5k
    case ExchangeType::PASSTHROUGH:
843
97.5k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
97.5k
                cur_pipe->num_tasks(), _num_instances,
845
97.5k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
97.5k
                        ? cast_set<int>(
847
97.4k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
97.5k
                        : 0);
849
97.5k
        break;
850
497
    case ExchangeType::BROADCAST:
851
497
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
497
                cur_pipe->num_tasks(), _num_instances,
853
497
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
497
                        ? cast_set<int>(
855
497
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
497
                        : 0);
857
497
        break;
858
2.82k
    case ExchangeType::PASS_TO_ONE:
859
2.82k
        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
1.62k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.62k
                    cur_pipe->num_tasks(), _num_instances,
863
1.62k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.62k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.62k
                                                    .local_exchange_free_blocks_limit)
866
1.62k
                            : 0);
867
1.62k
        } else {
868
1.19k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.19k
                    cur_pipe->num_tasks(), _num_instances,
870
1.19k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.19k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.19k
                                                    .local_exchange_free_blocks_limit)
873
1.19k
                            : 0);
874
1.19k
        }
875
2.82k
        break;
876
957
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
957
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
957
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
957
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
957
                        ? cast_set<int>(
881
957
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
957
                        : 0);
883
957
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
117k
    }
888
117k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
117k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
117k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
117k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
892
893
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
894
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
895
896
    // 3.1 Initialize new pipeline's operator list.
897
117k
    std::copy(operators.begin(), operators.begin() + idx,
898
117k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
117k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
117k
    OperatorPtr source_op;
905
117k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
117k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
117k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
117k
    if (!operators.empty()) {
909
48.6k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
48.6k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
48.6k
    }
912
117k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
117k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
117k
    std::vector<PipelineId> edges_with_source;
917
135k
    for (auto child : cur_pipe->children()) {
918
135k
        bool found = false;
919
150k
        for (auto op : new_pip->operators()) {
920
150k
            if (child->sink()->node_id() == op->node_id()) {
921
12.7k
                new_pip->set_children(child);
922
12.7k
                found = true;
923
12.7k
            };
924
150k
        }
925
135k
        if (!found) {
926
123k
            new_children.push_back(child);
927
123k
            edges_with_source.push_back(child->id());
928
123k
        }
929
135k
    }
930
117k
    new_children.push_back(new_pip);
931
117k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
117k
    if (!new_pip->children().empty()) {
935
7.29k
        std::vector<PipelineId> edges_with_sink;
936
12.7k
        for (auto child : new_pip->children()) {
937
12.7k
            edges_with_sink.push_back(child->id());
938
12.7k
        }
939
7.29k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.29k
    }
941
117k
    cur_pipe->set_children(new_children);
942
117k
    _dag[downstream_pipeline_id] = edges_with_source;
943
117k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
117k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
117k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
117k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
117k
    return Status::OK();
950
117k
}
951
952
Status PipelineFragmentContext::_add_local_exchange(
953
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
954
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
955
        const std::map<int, int>& bucket_seq_to_instance_idx,
956
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
39.2k
        return Status::OK();
959
39.2k
    }
960
961
153k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
51.7k
        return Status::OK();
963
51.7k
    }
964
102k
    *do_local_exchange = true;
965
966
102k
    auto& operators = cur_pipe->operators();
967
102k
    auto total_op_num = operators.size();
968
102k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
102k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
102k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
102k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
102k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
239
            << "total_op_num: " << total_op_num
975
239
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
239
            << " 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
102k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
102k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
15.6k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
15.6k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
15.6k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
15.6k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
15.6k
                shuffle_idx_to_instance_idx));
990
15.6k
    }
991
102k
    return Status::OK();
992
102k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
432k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
998k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
565k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
565k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
126k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
126k
                if (child->sink()->node_id() ==
1003
126k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
111k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
111k
                }
1006
126k
            }
1007
121k
        }
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
565k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
565k
                                             bucket_seq_to_instance_idx,
1014
565k
                                             shuffle_idx_to_instance_idx));
1015
565k
    }
1016
432k
    return Status::OK();
1017
432k
}
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
565k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
565k
    int idx = 1;
1024
565k
    bool do_local_exchange = false;
1025
613k
    do {
1026
613k
        auto& ops = pip->operators();
1027
613k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
680k
        for (; idx < ops.size();) {
1030
115k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
104k
                RETURN_IF_ERROR(_add_local_exchange(
1032
104k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
104k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
104k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
104k
                        shuffle_idx_to_instance_idx));
1036
104k
            }
1037
115k
            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
48.7k
                idx = 2;
1043
48.7k
                break;
1044
48.7k
            }
1045
66.8k
            idx++;
1046
66.8k
        }
1047
613k
    } while (do_local_exchange);
1048
565k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
88.0k
        RETURN_IF_ERROR(_add_local_exchange(
1050
88.0k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
88.0k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
88.0k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
88.0k
    }
1054
565k
    return Status::OK();
1055
565k
}
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
435k
                                                  PipelineId cur_pipeline_id) {
1063
435k
    switch (thrift_sink.type) {
1064
146k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
146k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
146k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
146k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
146k
                params.destinations, _fragment_instance_ids);
1071
146k
        break;
1072
146k
    }
1073
251k
    case TDataSinkType::RESULT_SINK: {
1074
251k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
251k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
251k
        int child_node_id = pipeline->operators().back()->node_id();
1080
251k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
251k
                                                      row_desc, output_exprs,
1082
251k
                                                      thrift_sink.result_sink);
1083
251k
        break;
1084
251k
    }
1085
100
    case TDataSinkType::DICTIONARY_SINK: {
1086
100
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
100
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
100
                                                    thrift_sink.dictionary_sink);
1092
100
        break;
1093
100
    }
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
2.19k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.19k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
29.3k
        } else {
1104
29.3k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
29.3k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
29.3k
        }
1107
31.4k
        break;
1108
0
    }
1109
166
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
166
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
166
        DCHECK(state->get_query_ctx() != nullptr);
1112
166
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
166
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
166
                                                                output_exprs);
1115
166
        break;
1116
0
    }
1117
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.46k
                                                         output_exprs);
1123
1.46k
        break;
1124
1.46k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
1.73k
        } else {
1133
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.73k
                                                                row_desc, output_exprs);
1135
1.73k
        }
1136
1.73k
        break;
1137
1.73k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
502
    case TDataSinkType::RESULT_FILE_SINK: {
1186
502
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
502
        } else {
1196
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
502
                                                              output_exprs);
1198
502
        }
1199
502
        break;
1200
502
    }
1201
2.06k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.06k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.06k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.06k
        auto sink_id = next_sink_operator_id();
1205
2.06k
        const int multi_cast_node_id = sink_id;
1206
2.06k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.06k
        std::vector<int> sources;
1209
8.04k
        for (int i = 0; i < sender_size; ++i) {
1210
5.97k
            auto source_id = next_operator_id();
1211
5.97k
            sources.push_back(source_id);
1212
5.97k
        }
1213
1214
2.06k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.06k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
8.04k
        for (int i = 0; i < sender_size; ++i) {
1217
5.97k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
5.97k
            RowDescriptor* exchange_row_desc = nullptr;
1220
5.97k
            {
1221
5.97k
                const auto& tmp_row_desc =
1222
5.97k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
5.97k
                                ? RowDescriptor(state->desc_tbl(),
1224
5.97k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
5.97k
                                                         .output_tuple_id})
1226
5.97k
                                : row_desc;
1227
5.97k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
5.97k
            }
1229
5.97k
            auto source_id = sources[i];
1230
5.97k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
5.97k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
5.97k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
5.97k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
5.97k
                    /*operator_id=*/source_id);
1236
5.97k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
5.97k
                    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
5.97k
            DataSinkOperatorPtr sink_op;
1241
5.97k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
5.97k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
5.97k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
5.97k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
5.97k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
5.97k
            {
1248
5.97k
                TDataSink* t = pool->add(new TDataSink());
1249
5.97k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
5.97k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
5.97k
            }
1252
1253
            // 3. set dependency dag
1254
5.97k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
5.97k
        }
1256
2.06k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.06k
        break;
1260
2.06k
    }
1261
2.06k
    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
435k
    }
1280
434k
    return Status::OK();
1281
435k
}
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
677k
                                                 OperatorPtr& cache_op) {
1292
677k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
677k
    Defer defer = Defer([&]() {
1294
677k
        if (op) {
1295
677k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
677k
        }
1297
676k
        for (auto& s : sink_ops) {
1298
126k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
126k
        }
1300
676k
    });
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
677k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
677k
    std::stringstream error_msg;
1305
677k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
677k
    bool fe_with_old_version = false;
1308
677k
    switch (tnode.node_type) {
1309
212k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
212k
        op = std::make_shared<OlapScanOperatorX>(
1311
212k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
212k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
212k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
212k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
212k
        break;
1316
212k
    }
1317
78
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
78
        DCHECK(_query_ctx != nullptr);
1319
78
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
78
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
78
                                                    _num_instances);
1322
78
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
78
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
78
        break;
1325
78
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
23.3k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
23.3k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
23.3k
                                                 _num_instances);
1342
23.3k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
23.3k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
23.3k
        break;
1345
23.3k
    }
1346
150k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
150k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
150k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
150k
        DCHECK_GT(num_senders, 0);
1351
150k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
150k
                                                       num_senders);
1353
150k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
150k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
150k
        break;
1356
150k
    }
1357
159k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
159k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
159k
            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
159k
        bool need_create_cache_op =
1364
159k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
159k
        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
159k
        const bool group_by_limit_opt =
1385
159k
                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
159k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
159k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
159k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
159k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
159k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
159k
        const bool can_use_distinct_streaming_agg =
1396
159k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
159k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
159k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
159k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
159k
        if (can_use_distinct_streaming_agg) {
1402
91.9k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
91.9k
            } else {
1413
91.9k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
91.9k
                                                                     tnode, descs);
1415
91.9k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
91.9k
            }
1417
91.9k
        } else if (is_streaming_agg) {
1418
3.57k
            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
3.57k
            } else {
1428
3.57k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
3.57k
                                                             descs);
1430
3.57k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
3.57k
            }
1432
63.5k
        } else {
1433
            // create new pipeline to add query cache operator
1434
63.5k
            PipelinePtr new_pipe;
1435
63.5k
            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
63.5k
            if (enable_spill) {
1441
176
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
176
                                                                     next_operator_id(), descs);
1443
63.3k
            } else {
1444
63.3k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
63.3k
            }
1446
63.5k
            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
63.5k
            } else {
1451
63.5k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
63.5k
            }
1453
1454
63.5k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
63.5k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
61.0k
                _dag.insert({downstream_pipeline_id, {}});
1457
61.0k
            }
1458
63.5k
            cur_pipe = add_pipeline(cur_pipe);
1459
63.5k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
63.5k
            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
63.3k
            } else {
1465
63.3k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
63.3k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
63.3k
            }
1468
63.5k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
63.5k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
63.5k
        }
1471
159k
        break;
1472
159k
    }
1473
159k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
70
        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
70
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
70
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
70
        const auto downstream_pipeline_id = cur_pipe->id();
1486
70
        if (!_dag.contains(downstream_pipeline_id)) {
1487
70
            _dag.insert({downstream_pipeline_id, {}});
1488
70
        }
1489
70
        cur_pipe = add_pipeline(cur_pipe);
1490
70
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
70
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
70
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
70
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
70
        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
70
        {
1503
70
            auto shared_state = BucketedAggSharedState::create_shared();
1504
70
            shared_state->id = op->operator_id();
1505
70
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
547
            for (int i = 0; i < _num_instances; i++) {
1508
477
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
477
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
477
                sink_dep->set_shared_state(shared_state.get());
1511
477
                shared_state->sink_deps.push_back(sink_dep);
1512
477
            }
1513
70
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
70
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
70
            _op_id_to_shared_state.insert(
1516
70
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
70
        }
1518
70
        break;
1519
70
    }
1520
9.74k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.74k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.74k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.74k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.74k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
9.74k
        } else {
1566
9.74k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.74k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.74k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.74k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
8.02k
                _dag.insert({downstream_pipeline_id, {}});
1572
8.02k
            }
1573
9.74k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.74k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.74k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.74k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.74k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.74k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.74k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.74k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.74k
        }
1584
9.74k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.61k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.61k
                    HashJoinSharedState::create_shared(_num_instances);
1587
19.3k
            for (int i = 0; i < _num_instances; i++) {
1588
16.7k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
16.7k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
16.7k
                sink_dep->set_shared_state(shared_state.get());
1591
16.7k
                shared_state->sink_deps.push_back(sink_dep);
1592
16.7k
            }
1593
2.61k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.61k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.61k
            _op_id_to_shared_state.insert(
1596
2.61k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.61k
        }
1598
9.74k
        break;
1599
9.74k
    }
1600
5.05k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
5.05k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
5.05k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
5.05k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
5.05k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
4.82k
            _dag.insert({downstream_pipeline_id, {}});
1607
4.82k
        }
1608
5.05k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
5.05k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
5.05k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
5.05k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
5.05k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
5.05k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
5.05k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
5.05k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
5.05k
        break;
1618
5.05k
    }
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
53.2k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.2k
        }
1628
54.9k
        for (int i = 0; i < child_count; i++) {
1629
1.42k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.42k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.42k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.42k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.42k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.42k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.42k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.42k
        }
1638
53.4k
        break;
1639
53.4k
    }
1640
53.4k
    case TPlanNodeType::SORT_NODE: {
1641
44.4k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
44.4k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
44.4k
        const bool use_local_merge =
1644
44.4k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
44.4k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
44.4k
        } else if (use_local_merge) {
1648
42.1k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
42.1k
                                                                 descs);
1650
42.1k
        } else {
1651
2.33k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.33k
        }
1653
44.4k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
44.4k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
44.4k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
44.4k
            _dag.insert({downstream_pipeline_id, {}});
1658
44.4k
        }
1659
44.4k
        cur_pipe = add_pipeline(cur_pipe);
1660
44.4k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
44.4k
        if (should_spill) {
1663
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
44.4k
        } else {
1666
44.4k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
44.4k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
44.4k
        }
1669
44.4k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
44.4k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
44.4k
        break;
1672
44.4k
    }
1673
44.4k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.63k
        }
1698
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.64k
        break;
1706
1.64k
    }
1707
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.60k
        break;
1711
1.60k
    }
1712
1.60k
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
309
    case TPlanNodeType::REPEAT_NODE: {
1723
309
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
309
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
309
        break;
1726
309
    }
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
459
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
459
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
459
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
459
        break;
1747
459
    }
1748
2.05k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.05k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.05k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.05k
        break;
1752
2.05k
    }
1753
6.71k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.71k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.71k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.71k
        break;
1757
6.71k
    }
1758
6.71k
    case TPlanNodeType::SELECT_NODE: {
1759
2.04k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.04k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.04k
        break;
1762
2.04k
    }
1763
2.04k
    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
677k
    }
1803
675k
    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
675k
    return Status::OK();
1809
677k
}
1810
// NOLINTEND(readability-function-cognitive-complexity)
1811
// NOLINTEND(readability-function-size)
1812
1813
template <bool is_intersect>
1814
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1815
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1816
267
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
267
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
267
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
267
    const auto downstream_pipeline_id = cur_pipe->id();
1821
267
    if (!_dag.contains(downstream_pipeline_id)) {
1822
242
        _dag.insert({downstream_pipeline_id, {}});
1823
242
    }
1824
1825
895
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
628
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
628
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
628
        if (child_id == 0) {
1830
267
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
267
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
361
        } else {
1833
361
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
361
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
361
        }
1836
628
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
628
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
628
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
628
    }
1841
1842
267
    return Status::OK();
1843
267
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
134
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
134
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
134
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
134
    const auto downstream_pipeline_id = cur_pipe->id();
1821
134
    if (!_dag.contains(downstream_pipeline_id)) {
1822
118
        _dag.insert({downstream_pipeline_id, {}});
1823
118
    }
1824
1825
481
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
347
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
347
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
347
        if (child_id == 0) {
1830
134
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
134
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
213
        } else {
1833
213
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
213
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
213
        }
1836
347
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
347
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
347
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
347
    }
1841
1842
134
    return Status::OK();
1843
134
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
133
    const auto downstream_pipeline_id = cur_pipe->id();
1821
133
    if (!_dag.contains(downstream_pipeline_id)) {
1822
124
        _dag.insert({downstream_pipeline_id, {}});
1823
124
    }
1824
1825
414
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
281
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
281
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
281
        if (child_id == 0) {
1830
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
148
        } else {
1833
148
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
148
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
148
        }
1836
281
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
281
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
281
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
281
    }
1841
1842
133
    return Status::OK();
1843
133
}
1844
1845
432k
Status PipelineFragmentContext::submit() {
1846
432k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
432k
    _submitted = true;
1850
1851
432k
    int submit_tasks = 0;
1852
432k
    Status st;
1853
432k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.33M
    for (auto& task : _tasks) {
1855
2.20M
        for (auto& t : task) {
1856
2.20M
            st = scheduler->submit(t.first);
1857
2.20M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
2.20M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
2.20M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
2.20M
            submit_tasks++;
1866
2.20M
        }
1867
1.33M
    }
1868
432k
    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
432k
    } else {
1883
432k
        return st;
1884
432k
    }
1885
432k
}
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
435k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
435k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
435k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
435k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
435k
    if (!_need_notify_close) {
1919
432k
        auto st = send_report(true);
1920
432k
        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
432k
    }
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
435k
    if (_runtime_state->enable_profile() &&
1931
435k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.84k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.84k
         _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
435k
    if (_query_ctx->enable_profile()) {
1953
2.84k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.84k
                                         collect_realtime_load_channel_profile());
1955
2.84k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
435k
    return !_need_notify_close;
1960
435k
}
1961
1962
2.19M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
2.19M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
2.19M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
685k
        if (_dag.contains(pipeline_id)) {
1967
367k
            for (auto dep : _dag[pipeline_id]) {
1968
367k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
367k
            }
1970
292k
        }
1971
685k
    }
1972
2.19M
    bool need_remove = false;
1973
2.19M
    {
1974
2.19M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
2.19M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
2.19M
        _query_ctx->inc_finished_task_num();
1978
2.19M
        if (_closed_tasks >= _total_tasks) {
1979
435k
            need_remove = _close_fragment_instance();
1980
435k
        }
1981
2.19M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
2.19M
    if (need_remove) {
1984
432k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
432k
    }
1986
2.19M
}
1987
1988
55.4k
std::string PipelineFragmentContext::get_load_error_url() {
1989
55.4k
    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
162k
    for (auto& tasks : _tasks) {
1993
265k
        for (auto& task : tasks) {
1994
265k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
173
                return to_load_error_http_path(str);
1996
173
            }
1997
265k
        }
1998
162k
    }
1999
55.2k
    return "";
2000
55.4k
}
2001
2002
55.4k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
55.4k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
162k
    for (auto& tasks : _tasks) {
2007
266k
        for (auto& task : tasks) {
2008
266k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
173
                return str;
2010
173
            }
2011
266k
        }
2012
162k
    }
2013
55.2k
    return "";
2014
55.4k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
48.7k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
48.7k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
48.7k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
48.7k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
48.7k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
48.7k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
48.7k
    });
2031
2032
48.7k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
48.7k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
48.7k
    int callback_retries = 10;
2038
48.7k
    const int sleep_ms = 1000;
2039
48.7k
    Status exec_status = req.status;
2040
48.7k
    Status coord_status;
2041
48.7k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
48.7k
    do {
2043
48.7k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
48.7k
                                                            req.coord_addr, &coord_status);
2045
48.7k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
48.7k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
48.7k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
48.7k
    TReportExecStatusParams params;
2059
48.7k
    params.protocol_version = FrontendServiceVersion::V1;
2060
48.7k
    params.__set_query_id(req.query_id);
2061
48.7k
    params.__set_backend_num(req.backend_num);
2062
48.7k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
48.7k
    params.__set_fragment_id(req.fragment_id);
2064
48.7k
    params.__set_status(exec_status.to_thrift());
2065
48.7k
    params.__set_done(req.done);
2066
48.7k
    params.__set_query_type(req.runtime_state->query_type());
2067
48.7k
    params.__isset.profile = false;
2068
2069
48.7k
    DCHECK(req.runtime_state != nullptr);
2070
2071
48.7k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
43.6k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
43.6k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
43.6k
    } else {
2075
5.02k
        DCHECK(!req.runtime_states.empty());
2076
5.02k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
5.02k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
5.02k
    }
2086
2087
48.7k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
48.7k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
48.7k
    static std::string s_unselected_rows = "unselected.rows";
2090
48.7k
    int64_t num_rows_load_success = 0;
2091
48.7k
    int64_t num_rows_load_filtered = 0;
2092
48.7k
    int64_t num_rows_load_unselected = 0;
2093
48.7k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
48.7k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
48.7k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
48.7k
    } else if (!req.runtime_states.empty()) {
2109
176k
        for (auto* rs : req.runtime_states) {
2110
176k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
176k
                rs->num_finished_range() > 0) {
2112
36.6k
                params.__isset.load_counters = true;
2113
36.6k
                num_rows_load_success += rs->num_rows_load_success();
2114
36.6k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
36.6k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
36.6k
                params.__isset.fragment_instance_reports = true;
2117
36.6k
                TFragmentInstanceReport t;
2118
36.6k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
36.6k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
36.6k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
36.6k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
36.6k
                params.fragment_instance_reports.push_back(t);
2123
36.6k
            }
2124
176k
        }
2125
48.6k
    }
2126
48.7k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
48.7k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
48.7k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
48.7k
    if (!req.load_error_url.empty()) {
2131
158
        params.__set_tracking_url(req.load_error_url);
2132
158
    }
2133
48.7k
    if (!req.first_error_msg.empty()) {
2134
158
        params.__set_first_error_msg(req.first_error_msg);
2135
158
    }
2136
176k
    for (auto* rs : req.runtime_states) {
2137
176k
        if (rs->wal_id() > 0) {
2138
111
            params.__set_txn_id(rs->wal_id());
2139
111
            params.__set_label(rs->import_label());
2140
111
        }
2141
176k
    }
2142
48.7k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
48.7k
    } else if (!req.runtime_states.empty()) {
2146
176k
        for (auto* rs : req.runtime_states) {
2147
176k
            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
176k
        }
2154
48.6k
    }
2155
48.7k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
48.7k
    } else if (!req.runtime_states.empty()) {
2159
176k
        for (auto* rs : req.runtime_states) {
2160
176k
            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
176k
        }
2165
48.6k
    }
2166
48.7k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
48.7k
    } else if (!req.runtime_states.empty()) {
2170
176k
        for (auto* rs : req.runtime_states) {
2171
176k
            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
176k
        }
2177
48.6k
    }
2178
48.7k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
48.7k
    } else if (!req.runtime_states.empty()) {
2183
176k
        for (auto* rs : req.runtime_states) {
2184
176k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.07k
                params.__isset.hive_partition_updates = true;
2186
2.07k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.07k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.07k
            }
2189
176k
        }
2190
48.6k
    }
2191
48.7k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
48.7k
    } else if (!req.runtime_states.empty()) {
2196
176k
        for (auto* rs : req.runtime_states) {
2197
176k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.05k
                params.__isset.iceberg_commit_datas = true;
2199
2.05k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.05k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.05k
            }
2202
176k
        }
2203
48.6k
    }
2204
2205
48.7k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
48.7k
    } else if (!req.runtime_states.empty()) {
2209
176k
        for (auto* rs : req.runtime_states) {
2210
176k
            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
176k
        }
2216
48.6k
    }
2217
2218
48.7k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
48.7k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
48.7k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
48.6k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
48.6k
    }
2224
2225
48.7k
    TReportExecStatusResult res;
2226
48.7k
    Status rpc_status;
2227
2228
48.7k
    VLOG_DEBUG << "reportExecStatus params is "
2229
18
               << apache::thrift::ThriftDebugString(params).c_str();
2230
48.7k
    if (!exec_status.ok()) {
2231
1.68k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.68k
                     << " to coordinator: " << req.coord_addr
2233
1.68k
                     << ", query id: " << print_id(req.query_id);
2234
1.68k
    }
2235
48.7k
    try {
2236
48.7k
        try {
2237
48.7k
            (*coord)->reportExecStatus(res, params);
2238
48.7k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
48.6k
        rpc_status = Status::create<false>(res.status);
2254
48.6k
    } 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
48.6k
    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
48.6k
}
2265
2266
437k
Status PipelineFragmentContext::send_report(bool done) {
2267
437k
    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
437k
    if (!_is_report_success && done && exec_status.ok()) {
2273
388k
        return Status::OK();
2274
388k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
48.9k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
312
        if (done) {
2284
            // if done is true, which means the query is finished successfully, we can safely close the fragment instance without sending report to FE, and just return OK status here.
2285
312
            return Status::OK();
2286
312
        }
2287
0
        return Status::NeedSendAgain("");
2288
312
    }
2289
2290
48.6k
    std::vector<RuntimeState*> runtime_states;
2291
2292
121k
    for (auto& tasks : _tasks) {
2293
176k
        for (auto& task : tasks) {
2294
176k
            runtime_states.push_back(task.second.get());
2295
176k
        }
2296
121k
    }
2297
2298
48.6k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
48.6k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
48.6k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
48.6k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
48.6k
    ReportStatusRequest req {.status = exec_status,
2306
48.6k
                             .runtime_states = runtime_states,
2307
48.6k
                             .done = done || !exec_status.ok(),
2308
48.6k
                             .coord_addr = _query_ctx->coord_addr,
2309
48.6k
                             .query_id = _query_id,
2310
48.6k
                             .fragment_id = _fragment_id,
2311
48.6k
                             .fragment_instance_id = TUniqueId(),
2312
48.6k
                             .backend_num = -1,
2313
48.6k
                             .runtime_state = _runtime_state.get(),
2314
48.6k
                             .load_error_url = load_eror_url,
2315
48.6k
                             .first_error_msg = first_error_msg,
2316
48.6k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
48.6k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
48.7k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
48.7k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
48.7k
        _coordinator_callback(req);
2321
48.7k
        if (!req.done) {
2322
5.05k
            ctx->refresh_next_report_time();
2323
5.05k
        }
2324
48.7k
    });
2325
48.9k
}
2326
2327
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
0
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
0
    for (const auto& task_instances : _tasks) {
2332
0
        for (const auto& task : task_instances) {
2333
0
            if (task.first->is_running()) {
2334
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2335
0
                                      << " is running, task: " << (void*)task.first.get()
2336
0
                                      << ", is_running: " << task.first->is_running();
2337
0
                *has_running_task = true;
2338
0
                return 0;
2339
0
            }
2340
2341
0
            size_t revocable_size = task.first->get_revocable_size();
2342
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
0
                res += revocable_size;
2344
0
            }
2345
0
        }
2346
0
    }
2347
0
    return res;
2348
0
}
2349
2350
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
0
    std::vector<PipelineTask*> revocable_tasks;
2352
0
    for (const auto& task_instances : _tasks) {
2353
0
        for (const auto& task : task_instances) {
2354
0
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
0
                revocable_tasks.emplace_back(task.first.get());
2358
0
            }
2359
0
        }
2360
0
    }
2361
0
    return revocable_tasks;
2362
0
}
2363
2364
22
std::string PipelineFragmentContext::debug_string() {
2365
22
    std::lock_guard<std::mutex> l(_task_mutex);
2366
22
    fmt::memory_buffer debug_string_buffer;
2367
22
    fmt::format_to(debug_string_buffer,
2368
22
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
22
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
22
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
66
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
44
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
142
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
98
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
98
                           _tasks[j][i].first->debug_string());
2376
98
        }
2377
44
    }
2378
2379
22
    return fmt::to_string(debug_string_buffer);
2380
22
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.84k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.84k
    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
2.84k
    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
2.84k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.84k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.84k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
5.11k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
5.11k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
5.11k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
5.11k
        res.push_back(profile_ptr);
2407
5.11k
    }
2408
2409
2.84k
    return res;
2410
2.84k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.84k
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
2.84k
    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
6.24k
    for (const auto& tasks : _tasks) {
2426
12.3k
        for (const auto& task : tasks) {
2427
12.3k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
12.3k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
12.3k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
12.3k
                                                           _runtime_state->profile_level());
2435
12.3k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
12.3k
        }
2437
6.24k
    }
2438
2439
2.84k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.84k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.84k
                                                      _runtime_state->profile_level());
2442
2.84k
    return load_channel_profile;
2443
2.84k
}
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
4.06k
    for (const auto& _task : _tasks) {
2455
7.10k
        for (const auto& task : _task) {
2456
7.10k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
7.10k
            result.merge(set);
2458
7.10k
        }
2459
4.06k
    }
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
436k
void PipelineFragmentContext::_release_resource() {
2468
436k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
436k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
436k
    auto st = _query_ctx->exec_status();
2472
1.33M
    for (auto& _task : _tasks) {
2473
1.33M
        if (!_task.empty()) {
2474
1.33M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.33M
        }
2476
1.33M
    }
2477
436k
    _tasks.clear();
2478
436k
    _dag.clear();
2479
436k
    _pip_id_to_pipeline.clear();
2480
436k
    _pipelines.clear();
2481
436k
    _sink.reset();
2482
436k
    _root_op.reset();
2483
436k
    _runtime_filter_mgr_map.clear();
2484
436k
    _op_id_to_shared_state.clear();
2485
436k
}
2486
2487
} // namespace doris