Coverage Report

Created: 2026-04-27 08:40

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
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
9
//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
114
#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
132
#include "util/client_cache.h"
133
#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
433k
        : _query_id(std::move(query_id)),
144
433k
          _fragment_id(request.fragment_id),
145
433k
          _exec_env(exec_env),
146
433k
          _query_ctx(std::move(query_ctx)),
147
433k
          _call_back(call_back),
148
433k
          _is_report_on_cancel(true),
149
433k
          _params(request),
150
433k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
433k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
433k
                                                               : false) {
153
433k
    _fragment_watcher.start();
154
433k
}
155
156
433k
PipelineFragmentContext::~PipelineFragmentContext() {
157
433k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
433k
            .tag("query_id", print_id(_query_id))
159
433k
            .tag("fragment_id", _fragment_id);
160
433k
    _release_resource();
161
433k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
433k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
433k
        _runtime_state.reset();
165
433k
        _query_ctx.reset();
166
433k
    }
167
433k
}
168
169
83
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
83
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
83
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
83
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
9.48k
bool PipelineFragmentContext::notify_close() {
181
9.48k
    bool all_closed = false;
182
9.48k
    bool need_remove = false;
183
9.48k
    {
184
9.48k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.48k
        if (_closed_tasks >= _total_tasks) {
186
3.18k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
192
3.10k
                need_remove = true;
193
3.10k
            }
194
3.18k
            all_closed = true;
195
3.18k
        }
196
        // make fragment release by self after cancel
197
9.48k
        _need_notify_close = false;
198
9.48k
    }
199
9.48k
    if (need_remove) {
200
3.10k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.10k
    }
202
9.48k
    return all_closed;
203
9.48k
}
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
6.21k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.21k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.21k
            .tag("query_id", print_id(_query_id))
212
6.21k
            .tag("fragment_id", _fragment_id)
213
6.21k
            .tag("reason", reason.to_string());
214
6.21k
    if (notify_close()) {
215
92
        return;
216
92
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.11k
    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
6.11k
    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
6.11k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
54
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
54
    }
233
234
6.11k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
25
        _query_ctx->set_load_error_url(error_url);
236
25
    }
237
238
6.11k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
25
        _query_ctx->set_first_error_msg(first_error_msg);
240
25
    }
241
242
6.11k
    _query_ctx->cancel(reason, _fragment_id);
243
6.11k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
451
        _is_report_on_cancel = false;
245
5.66k
    } else {
246
26.8k
        for (auto& id : _fragment_instance_ids) {
247
26.8k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
26.8k
        }
249
5.66k
    }
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
6.11k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.11k
    if (stream_load_ctx != nullptr) {
254
30
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
30
        stream_load_ctx->error_url = get_load_error_url();
259
30
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
30
    }
261
262
28.3k
    for (auto& tasks : _tasks) {
263
65.7k
        for (auto& task : tasks) {
264
65.7k
            task.first->unblock_all_dependencies();
265
65.7k
        }
266
28.3k
    }
267
6.11k
}
268
269
672k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
672k
    PipelineId id = _next_pipeline_id++;
271
672k
    auto pipeline = std::make_shared<Pipeline>(
272
672k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
672k
            parent ? parent->num_tasks() : _num_instances);
274
672k
    if (idx >= 0) {
275
109k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
563k
    } else {
277
563k
        _pipelines.emplace_back(pipeline);
278
563k
    }
279
672k
    if (parent) {
280
234k
        parent->set_children(pipeline);
281
234k
    }
282
672k
    return pipeline;
283
672k
}
284
285
432k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
432k
    {
287
432k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
432k
        auto root_pipeline = add_pipeline();
290
432k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
432k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
432k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
432k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
432k
                                          _params.fragment.output_exprs, _params,
299
432k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
432k
                                          *_desc_tbl, root_pipeline->id()));
301
432k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
432k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
562k
        for (PipelinePtr& pipeline : _pipelines) {
305
562k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
562k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
562k
        }
308
432k
    }
309
    // 4. Build local exchanger
310
432k
    if (_runtime_state->enable_local_shuffle()) {
311
430k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
430k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
430k
                                             _params.bucket_seq_to_instance_idx,
314
430k
                                             _params.shuffle_idx_to_instance_idx));
315
430k
    }
316
317
    // 5. Initialize global states in pipelines.
318
673k
    for (PipelinePtr& pipeline : _pipelines) {
319
673k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
673k
        pipeline->children().clear();
321
673k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
673k
    }
323
324
431k
    {
325
431k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
431k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
431k
    }
329
330
431k
    return Status::OK();
331
431k
}
332
333
433k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
433k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
433k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
432k
        _timeout = _params.query_options.execution_timeout;
339
432k
    }
340
341
433k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
433k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
433k
    SCOPED_TIMER(_prepare_timer);
344
433k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
433k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
433k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
433k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
433k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
433k
    {
350
433k
        SCOPED_TIMER(_init_context_timer);
351
433k
        cast_set(_num_instances, _params.local_params.size());
352
433k
        _total_instances =
353
433k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
433k
        auto* fragment_context = this;
356
357
433k
        if (_params.query_options.__isset.is_report_success) {
358
431k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
431k
        }
360
361
        // 1. Set up the global runtime state.
362
433k
        _runtime_state = RuntimeState::create_unique(
363
433k
                _params.query_id, _params.fragment_id, _params.query_options,
364
433k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
433k
        _runtime_state->set_task_execution_context(shared_from_this());
366
433k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
433k
        if (_params.__isset.backend_id) {
368
429k
            _runtime_state->set_backend_id(_params.backend_id);
369
429k
        }
370
433k
        if (_params.__isset.import_label) {
371
240
            _runtime_state->set_import_label(_params.import_label);
372
240
        }
373
433k
        if (_params.__isset.db_name) {
374
192
            _runtime_state->set_db_name(_params.db_name);
375
192
        }
376
433k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
433k
        if (_params.is_simplified_param) {
381
146k
            _desc_tbl = _query_ctx->desc_tbl;
382
286k
        } else {
383
286k
            DCHECK(_params.__isset.desc_tbl);
384
286k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
286k
                                                  &_desc_tbl));
386
286k
        }
387
433k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
433k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
433k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
433k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
433k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
433k
        const auto target_size = _params.local_params.size();
395
433k
        _fragment_instance_ids.resize(target_size);
396
1.59M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.16M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.16M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.16M
        }
400
433k
    }
401
402
433k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
431k
    _init_next_report_time();
405
406
431k
    _prepared = true;
407
431k
    return Status::OK();
408
433k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.16M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.16M
    const auto& local_params = _params.local_params[instance_idx];
414
1.16M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.16M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.16M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.16M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.16M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.97M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.97M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.97M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.97M
                shared_state_map;
423
2.53M
        for (auto& op : pipeline->operators()) {
424
2.53M
            auto source_id = op->operator_id();
425
2.53M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.53M
                iter != _op_id_to_shared_state.end()) {
427
744k
                shared_state_map.insert({source_id, iter->second});
428
744k
            }
429
2.53M
        }
430
1.97M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.97M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.97M
                iter != _op_id_to_shared_state.end()) {
433
301k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
301k
            }
435
1.97M
        }
436
1.97M
        return shared_state_map;
437
1.97M
    };
438
439
3.58M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.41M
        auto& pipeline = _pipelines[pip_idx];
441
2.41M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.97M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.97M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.97M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.97M
            {
446
                // Initialize runtime state for this task
447
1.97M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.97M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.97M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.97M
                if (_params.__isset.backend_id) {
453
1.97M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.97M
                }
455
1.97M
                if (_params.__isset.import_label) {
456
241
                    task_runtime_state->set_import_label(_params.import_label);
457
241
                }
458
1.97M
                if (_params.__isset.db_name) {
459
193
                    task_runtime_state->set_db_name(_params.db_name);
460
193
                }
461
1.97M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.97M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.97M
                if (_params.__isset.content_length) {
468
31
                    task_runtime_state->set_content_length(_params.content_length);
469
31
                }
470
471
1.97M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.97M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.97M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.97M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.97M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.97M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.97M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.97M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.97M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.97M
            }
482
1.97M
            auto cur_task_id = _total_tasks++;
483
1.97M
            task_runtime_state->set_task_id(cur_task_id);
484
1.97M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.97M
            auto task = std::make_shared<PipelineTask>(
486
1.97M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.97M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.97M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.97M
                    instance_idx);
490
1.97M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.97M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.97M
            _tasks[instance_idx].emplace_back(
493
1.97M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.97M
                            std::move(task), std::move(task_runtime_state)});
495
1.97M
        }
496
2.41M
    }
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
2.41M
    for (auto& _pipeline : _pipelines) {
516
2.41M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.97M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.97M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.97M
            if (_dag.contains(_pipeline->id())) {
522
1.25M
                auto& deps = _dag[_pipeline->id()];
523
1.98M
                for (auto& dep : deps) {
524
1.98M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.09M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.09M
                        if (ss) {
527
499k
                            task->inject_shared_state(ss);
528
598k
                        } else {
529
598k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
598k
                                    task->get_source_shared_state());
531
598k
                        }
532
1.09M
                    }
533
1.98M
                }
534
1.25M
            }
535
1.97M
        }
536
2.41M
    }
537
3.58M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.41M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.97M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.97M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.97M
            std::vector<TScanRangeParams> scan_ranges;
542
1.97M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.97M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
344k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
344k
            }
546
1.97M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.97M
                                                             _params.fragment.output_sink));
548
1.97M
        }
549
2.41M
    }
550
1.16M
    {
551
1.16M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.16M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.16M
    }
554
1.16M
    return Status::OK();
555
1.16M
}
556
557
432k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
432k
    _total_tasks = 0;
559
432k
    _closed_tasks = 0;
560
432k
    const auto target_size = _params.local_params.size();
561
432k
    _tasks.resize(target_size);
562
432k
    _runtime_filter_mgr_map.resize(target_size);
563
1.10M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
671k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
671k
    }
566
432k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
432k
    if (target_size > 1 &&
569
432k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
131k
         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
9.66k
        std::vector<Status> prepare_status(target_size);
573
9.66k
        int submitted_tasks = 0;
574
9.66k
        Status submit_status;
575
9.66k
        CountDownLatch latch((int)target_size);
576
144k
        for (int i = 0; i < target_size; i++) {
577
134k
            submit_status = thread_pool->submit_func([&, i]() {
578
134k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
134k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
134k
                latch.count_down();
581
134k
            });
582
134k
            if (LIKELY(submit_status.ok())) {
583
134k
                submitted_tasks++;
584
134k
            } else {
585
0
                break;
586
0
            }
587
134k
        }
588
9.66k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
9.66k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
144k
        for (int i = 0; i < submitted_tasks; i++) {
593
134k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
134k
        }
597
422k
    } else {
598
1.45M
        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
422k
    }
602
432k
    _pipeline_parent_map.clear();
603
432k
    _op_id_to_shared_state.clear();
604
605
432k
    return Status::OK();
606
432k
}
607
608
431k
void PipelineFragmentContext::_init_next_report_time() {
609
431k
    auto interval_s = config::pipeline_status_report_interval;
610
431k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
611
42.0k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
612
42.0k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
613
        // We don't want to wait longer than it takes to run the entire fragment.
614
42.0k
        _previous_report_time =
615
42.0k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
616
42.0k
        _disable_period_report = false;
617
42.0k
    }
618
431k
}
619
620
5.00k
void PipelineFragmentContext::refresh_next_report_time() {
621
5.00k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
622
5.00k
    DCHECK(disable == true);
623
5.00k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
624
5.00k
    _disable_period_report.compare_exchange_strong(disable, false);
625
5.00k
}
626
627
7.23M
void PipelineFragmentContext::trigger_report_if_necessary() {
628
7.23M
    if (!_is_report_success) {
629
6.67M
        return;
630
6.67M
    }
631
553k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
632
553k
    if (disable) {
633
10.2k
        return;
634
10.2k
    }
635
542k
    int32_t interval_s = config::pipeline_status_report_interval;
636
542k
    if (interval_s <= 0) {
637
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
638
0
                        "trigger "
639
0
                        "report.";
640
0
    }
641
542k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
642
542k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
643
542k
    if (MonotonicNanos() > next_report_time) {
644
5.01k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
645
5.01k
                                                            std::memory_order_acq_rel)) {
646
7
            return;
647
7
        }
648
5.00k
        if (VLOG_FILE_IS_ON) {
649
0
            VLOG_FILE << "Reporting "
650
0
                      << "profile for query_id " << print_id(_query_id)
651
0
                      << ", fragment id: " << _fragment_id;
652
653
0
            std::stringstream ss;
654
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
655
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
656
0
            if (_runtime_state->load_channel_profile()) {
657
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
658
0
            }
659
660
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
661
0
                      << " profile:\n"
662
0
                      << ss.str();
663
0
        }
664
5.00k
        auto st = send_report(false);
665
5.00k
        if (!st.ok()) {
666
0
            disable = true;
667
0
            _disable_period_report.compare_exchange_strong(disable, false,
668
0
                                                           std::memory_order_acq_rel);
669
0
        }
670
5.00k
    }
671
542k
}
672
673
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
674
431k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
675
431k
    if (_params.fragment.plan.nodes.empty()) {
676
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
677
0
    }
678
679
431k
    int node_idx = 0;
680
681
431k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
682
431k
                                        &node_idx, root, cur_pipe, 0, false, false));
683
684
431k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
685
0
        return Status::InternalError(
686
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
687
0
    }
688
431k
    return Status::OK();
689
431k
}
690
691
Status PipelineFragmentContext::_create_tree_helper(
692
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
693
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
694
670k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
695
    // propagate error case
696
670k
    if (*node_idx >= tnodes.size()) {
697
0
        return Status::InternalError(
698
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
699
0
                *node_idx, tnodes.size());
700
0
    }
701
670k
    const TPlanNode& tnode = tnodes[*node_idx];
702
703
670k
    int num_children = tnodes[*node_idx].num_children;
704
670k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
705
670k
    bool current_require_bucket_distribution = require_bucket_distribution;
706
    // TODO: Create CacheOperator is confused now
707
670k
    OperatorPtr op = nullptr;
708
670k
    OperatorPtr cache_op = nullptr;
709
670k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
710
670k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
711
670k
                                     followed_by_shuffled_operator,
712
670k
                                     current_require_bucket_distribution, cache_op));
713
    // Initialization must be done here. For example, group by expressions in agg will be used to
714
    // decide if a local shuffle should be planed, so it must be initialized here.
715
670k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
716
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
717
670k
    if (parent != nullptr) {
718
        // add to parent's child(s)
719
239k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
720
431k
    } else {
721
431k
        *root = op;
722
431k
    }
723
    /**
724
     * `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).
725
     *
726
     * For plan:
727
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
728
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
729
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
730
     *
731
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
732
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
733
     */
734
670k
    auto required_data_distribution =
735
670k
            cur_pipe->operators().empty()
736
670k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
737
670k
                    : op->required_data_distribution(_runtime_state.get());
738
670k
    current_followed_by_shuffled_operator =
739
670k
            ((followed_by_shuffled_operator ||
740
670k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
741
610k
                                             : op->is_shuffled_operator())) &&
742
670k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
743
670k
            (followed_by_shuffled_operator &&
744
557k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
745
746
670k
    current_require_bucket_distribution =
747
670k
            ((require_bucket_distribution ||
748
670k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
749
614k
                                             : op->is_colocated_operator())) &&
750
670k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
751
670k
            (require_bucket_distribution &&
752
564k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
753
754
670k
    if (num_children == 0) {
755
448k
        _use_serial_source = op->is_serial_operator();
756
448k
    }
757
    // rely on that tnodes is preorder of the plan
758
909k
    for (int i = 0; i < num_children; i++) {
759
239k
        ++*node_idx;
760
239k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
761
239k
                                            current_followed_by_shuffled_operator,
762
239k
                                            current_require_bucket_distribution));
763
764
        // we are expecting a child, but have used all nodes
765
        // this means we have been given a bad tree and must fail
766
239k
        if (*node_idx >= tnodes.size()) {
767
0
            return Status::InternalError(
768
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
769
0
                    "nodes: {}",
770
0
                    *node_idx, tnodes.size());
771
0
        }
772
239k
    }
773
774
670k
    return Status::OK();
775
670k
}
776
777
void PipelineFragmentContext::_inherit_pipeline_properties(
778
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
779
109k
        PipelinePtr pipe_with_sink) {
780
109k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
781
109k
    pipe_with_source->set_num_tasks(_num_instances);
782
109k
    pipe_with_source->set_data_distribution(data_distribution);
783
109k
}
784
785
Status PipelineFragmentContext::_add_local_exchange_impl(
786
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
787
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
788
        const std::map<int, int>& bucket_seq_to_instance_idx,
789
109k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
790
109k
    auto& operators = cur_pipe->operators();
791
109k
    const auto downstream_pipeline_id = cur_pipe->id();
792
109k
    auto local_exchange_id = next_operator_id();
793
    // 1. Create a new pipeline with local exchange sink.
794
109k
    DataSinkOperatorPtr sink;
795
109k
    auto sink_id = next_sink_operator_id();
796
797
    /**
798
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
799
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
800
     */
801
109k
    const bool followed_by_shuffled_operator =
802
109k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
803
109k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
804
109k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
805
109k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
806
109k
                                         followed_by_shuffled_operator && !_use_serial_source;
807
109k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
808
109k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
809
109k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
810
109k
    if (bucket_seq_to_instance_idx.empty() &&
811
109k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
812
7
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
813
7
    }
814
109k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
815
109k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
816
109k
                                          num_buckets, use_global_hash_shuffle,
817
109k
                                          shuffle_idx_to_instance_idx));
818
819
    // 2. Create and initialize LocalExchangeSharedState.
820
109k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
821
109k
            LocalExchangeSharedState::create_shared(_num_instances);
822
109k
    switch (data_distribution.distribution_type) {
823
14.5k
    case ExchangeType::HASH_SHUFFLE:
824
14.5k
        shared_state->exchanger = ShuffleExchanger::create_unique(
825
14.5k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
826
14.5k
                use_global_hash_shuffle ? _total_instances : _num_instances,
827
14.5k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
828
14.5k
                        ? cast_set<int>(
829
14.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
830
14.5k
                        : 0);
831
14.5k
        break;
832
535
    case ExchangeType::BUCKET_HASH_SHUFFLE:
833
535
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
834
535
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
835
535
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
836
535
                        ? cast_set<int>(
837
535
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
838
535
                        : 0);
839
535
        break;
840
90.0k
    case ExchangeType::PASSTHROUGH:
841
90.0k
        shared_state->exchanger = PassthroughExchanger::create_unique(
842
90.0k
                cur_pipe->num_tasks(), _num_instances,
843
90.0k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
844
90.0k
                        ? cast_set<int>(
845
90.0k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
846
90.0k
                        : 0);
847
90.0k
        break;
848
532
    case ExchangeType::BROADCAST:
849
532
        shared_state->exchanger = BroadcastExchanger::create_unique(
850
532
                cur_pipe->num_tasks(), _num_instances,
851
532
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
852
532
                        ? cast_set<int>(
853
532
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
854
532
                        : 0);
855
532
        break;
856
2.74k
    case ExchangeType::PASS_TO_ONE:
857
2.74k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
858
            // If shared hash table is enabled for BJ, hash table will be built by only one task
859
1.40k
            shared_state->exchanger = PassToOneExchanger::create_unique(
860
1.40k
                    cur_pipe->num_tasks(), _num_instances,
861
1.40k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
862
1.40k
                            ? cast_set<int>(_runtime_state->query_options()
863
1.40k
                                                    .local_exchange_free_blocks_limit)
864
1.40k
                            : 0);
865
1.40k
        } else {
866
1.34k
            shared_state->exchanger = BroadcastExchanger::create_unique(
867
1.34k
                    cur_pipe->num_tasks(), _num_instances,
868
1.34k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
869
1.34k
                            ? cast_set<int>(_runtime_state->query_options()
870
1.34k
                                                    .local_exchange_free_blocks_limit)
871
1.34k
                            : 0);
872
1.34k
        }
873
2.74k
        break;
874
955
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
875
955
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
876
955
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
877
955
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
878
955
                        ? cast_set<int>(
879
955
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
880
955
                        : 0);
881
955
        break;
882
0
    default:
883
0
        return Status::InternalError("Unsupported local exchange type : " +
884
0
                                     std::to_string((int)data_distribution.distribution_type));
885
109k
    }
886
109k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
887
109k
                                             "LOCAL_EXCHANGE_OPERATOR");
888
109k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
889
109k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
890
891
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
892
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
893
894
    // 3.1 Initialize new pipeline's operator list.
895
109k
    std::copy(operators.begin(), operators.begin() + idx,
896
109k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
897
898
    // 3.2 Erase unused operators in previous pipeline.
899
109k
    operators.erase(operators.begin(), operators.begin() + idx);
900
901
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
902
109k
    OperatorPtr source_op;
903
109k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
904
109k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
905
109k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
906
109k
    if (!operators.empty()) {
907
40.8k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
908
40.8k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
909
40.8k
    }
910
109k
    operators.insert(operators.begin(), source_op);
911
912
    // 5. Set children for two pipelines separately.
913
109k
    std::vector<std::shared_ptr<Pipeline>> new_children;
914
109k
    std::vector<PipelineId> edges_with_source;
915
127k
    for (auto child : cur_pipe->children()) {
916
127k
        bool found = false;
917
141k
        for (auto op : new_pip->operators()) {
918
141k
            if (child->sink()->node_id() == op->node_id()) {
919
12.8k
                new_pip->set_children(child);
920
12.8k
                found = true;
921
12.8k
            };
922
141k
        }
923
127k
        if (!found) {
924
114k
            new_children.push_back(child);
925
114k
            edges_with_source.push_back(child->id());
926
114k
        }
927
127k
    }
928
109k
    new_children.push_back(new_pip);
929
109k
    edges_with_source.push_back(new_pip->id());
930
931
    // 6. Set DAG for new pipelines.
932
109k
    if (!new_pip->children().empty()) {
933
7.41k
        std::vector<PipelineId> edges_with_sink;
934
12.8k
        for (auto child : new_pip->children()) {
935
12.8k
            edges_with_sink.push_back(child->id());
936
12.8k
        }
937
7.41k
        _dag.insert({new_pip->id(), edges_with_sink});
938
7.41k
    }
939
109k
    cur_pipe->set_children(new_children);
940
109k
    _dag[downstream_pipeline_id] = edges_with_source;
941
109k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
942
109k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
943
109k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
944
945
    // 7. Inherit properties from current pipeline.
946
109k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
947
109k
    return Status::OK();
948
109k
}
949
950
Status PipelineFragmentContext::_add_local_exchange(
951
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
952
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
953
        const std::map<int, int>& bucket_seq_to_instance_idx,
954
184k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
955
184k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
956
45.9k
        return Status::OK();
957
45.9k
    }
958
959
138k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
960
44.5k
        return Status::OK();
961
44.5k
    }
962
94.1k
    *do_local_exchange = true;
963
964
94.1k
    auto& operators = cur_pipe->operators();
965
94.1k
    auto total_op_num = operators.size();
966
94.1k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
967
94.1k
    RETURN_IF_ERROR(_add_local_exchange_impl(
968
94.1k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
969
94.1k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
970
971
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
972
18.4E
            << "total_op_num: " << total_op_num
973
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
974
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
975
976
    // There are some local shuffles with relatively heavy operations on the sink.
977
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
978
    // Therefore, local passthrough is used to increase the concurrency of the sink.
979
    // op -> local sink(1) -> local source (n)
980
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
981
94.1k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
982
94.1k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
983
15.1k
        RETURN_IF_ERROR(_add_local_exchange_impl(
984
15.1k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
985
15.1k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
986
15.1k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
987
15.1k
                shuffle_idx_to_instance_idx));
988
15.1k
    }
989
94.1k
    return Status::OK();
990
94.1k
}
991
992
Status PipelineFragmentContext::_plan_local_exchange(
993
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
994
429k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
995
989k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
996
560k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
997
        // Set property if child pipeline is not join operator's child.
998
560k
        if (!_pipelines[pip_idx]->children().empty()) {
999
124k
            for (auto& child : _pipelines[pip_idx]->children()) {
1000
124k
                if (child->sink()->node_id() ==
1001
124k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1002
110k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1003
110k
                }
1004
124k
            }
1005
119k
        }
1006
1007
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1008
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1009
        // still keep colocate plan after local shuffle
1010
560k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1011
560k
                                             bucket_seq_to_instance_idx,
1012
560k
                                             shuffle_idx_to_instance_idx));
1013
560k
    }
1014
429k
    return Status::OK();
1015
429k
}
1016
1017
Status PipelineFragmentContext::_plan_local_exchange(
1018
        int num_buckets, int pip_idx, PipelinePtr pip,
1019
        const std::map<int, int>& bucket_seq_to_instance_idx,
1020
560k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1021
560k
    int idx = 1;
1022
560k
    bool do_local_exchange = false;
1023
601k
    do {
1024
601k
        auto& ops = pip->operators();
1025
601k
        do_local_exchange = false;
1026
        // Plan local exchange for each operator.
1027
674k
        for (; idx < ops.size();) {
1028
114k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1029
98.7k
                RETURN_IF_ERROR(_add_local_exchange(
1030
98.7k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1031
98.7k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1032
98.7k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1033
98.7k
                        shuffle_idx_to_instance_idx));
1034
98.7k
            }
1035
114k
            if (do_local_exchange) {
1036
                // If local exchange is needed for current operator, we will split this pipeline to
1037
                // two pipelines by local exchange sink/source. And then we need to process remaining
1038
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1039
                // is current operator was already processed) and continue to plan local exchange.
1040
40.9k
                idx = 2;
1041
40.9k
                break;
1042
40.9k
            }
1043
73.8k
            idx++;
1044
73.8k
        }
1045
601k
    } while (do_local_exchange);
1046
560k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1047
85.8k
        RETURN_IF_ERROR(_add_local_exchange(
1048
85.8k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1049
85.8k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1050
85.8k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1051
85.8k
    }
1052
560k
    return Status::OK();
1053
560k
}
1054
1055
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1056
                                                  const std::vector<TExpr>& output_exprs,
1057
                                                  const TPipelineFragmentParams& params,
1058
                                                  const RowDescriptor& row_desc,
1059
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1060
432k
                                                  PipelineId cur_pipeline_id) {
1061
432k
    switch (thrift_sink.type) {
1062
144k
    case TDataSinkType::DATA_STREAM_SINK: {
1063
144k
        if (!thrift_sink.__isset.stream_sink) {
1064
0
            return Status::InternalError("Missing data stream sink.");
1065
0
        }
1066
144k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1067
144k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1068
144k
                params.destinations, _fragment_instance_ids);
1069
144k
        break;
1070
144k
    }
1071
250k
    case TDataSinkType::RESULT_SINK: {
1072
250k
        if (!thrift_sink.__isset.result_sink) {
1073
0
            return Status::InternalError("Missing data buffer sink.");
1074
0
        }
1075
1076
250k
        auto& pipeline = _pipelines[cur_pipeline_id];
1077
250k
        int child_node_id = pipeline->operators().back()->node_id();
1078
250k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1079
250k
                                                      row_desc, output_exprs,
1080
250k
                                                      thrift_sink.result_sink);
1081
250k
        break;
1082
250k
    }
1083
107
    case TDataSinkType::DICTIONARY_SINK: {
1084
107
        if (!thrift_sink.__isset.dictionary_sink) {
1085
0
            return Status::InternalError("Missing dict sink.");
1086
0
        }
1087
1088
107
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1089
107
                                                    thrift_sink.dictionary_sink);
1090
107
        break;
1091
107
    }
1092
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1093
31.4k
    case TDataSinkType::OLAP_TABLE_SINK: {
1094
31.4k
        auto& pipeline = _pipelines[cur_pipeline_id];
1095
31.4k
        int child_node_id = pipeline->operators().back()->node_id();
1096
31.4k
        if (state->query_options().enable_memtable_on_sink_node &&
1097
31.4k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1098
31.4k
            !config::is_cloud_mode()) {
1099
2.15k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1100
2.15k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1101
29.2k
        } else {
1102
29.2k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1103
29.2k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1104
29.2k
        }
1105
31.4k
        break;
1106
0
    }
1107
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1108
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1109
165
        DCHECK(state->get_query_ctx() != nullptr);
1110
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1111
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1112
165
                                                                output_exprs);
1113
165
        break;
1114
0
    }
1115
1.40k
    case TDataSinkType::HIVE_TABLE_SINK: {
1116
1.40k
        if (!thrift_sink.__isset.hive_table_sink) {
1117
0
            return Status::InternalError("Missing hive table sink.");
1118
0
        }
1119
1.40k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1120
1.40k
                                                         output_exprs);
1121
1.40k
        break;
1122
1.40k
    }
1123
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1124
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1125
0
            return Status::InternalError("Missing iceberg table sink.");
1126
0
        }
1127
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1128
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1129
0
                                                                     row_desc, output_exprs);
1130
1.73k
        } else {
1131
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1132
1.73k
                                                                row_desc, output_exprs);
1133
1.73k
        }
1134
1.73k
        break;
1135
1.73k
    }
1136
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1137
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1138
0
            return Status::InternalError("Missing iceberg delete sink.");
1139
0
        }
1140
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1141
20
                                                             row_desc, output_exprs);
1142
20
        break;
1143
20
    }
1144
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1145
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1146
0
            return Status::InternalError("Missing iceberg merge sink.");
1147
0
        }
1148
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1149
80
                                                            output_exprs);
1150
80
        break;
1151
80
    }
1152
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1153
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1154
0
            return Status::InternalError("Missing max compute table sink.");
1155
0
        }
1156
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1157
0
                                                       output_exprs);
1158
0
        break;
1159
0
    }
1160
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1161
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1162
0
            return Status::InternalError("Missing data jdbc sink.");
1163
0
        }
1164
88
        if (config::enable_java_support) {
1165
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1166
88
                                                             output_exprs);
1167
88
        } else {
1168
0
            return Status::InternalError(
1169
0
                    "Jdbc table sink is not enabled, you can change be config "
1170
0
                    "enable_java_support to true and restart be.");
1171
0
        }
1172
88
        break;
1173
88
    }
1174
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1175
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1176
0
            return Status::InternalError("Missing data buffer sink.");
1177
0
        }
1178
1179
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1180
3
                                                             output_exprs);
1181
3
        break;
1182
3
    }
1183
502
    case TDataSinkType::RESULT_FILE_SINK: {
1184
502
        if (!thrift_sink.__isset.result_file_sink) {
1185
0
            return Status::InternalError("Missing result file sink.");
1186
0
        }
1187
1188
        // Result file sink is not the top sink
1189
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1190
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1191
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1192
0
                    params.destinations, output_exprs, desc_tbl);
1193
502
        } else {
1194
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1195
502
                                                              output_exprs);
1196
502
        }
1197
502
        break;
1198
502
    }
1199
1.95k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1200
1.95k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1201
1.95k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1202
1.95k
        auto sink_id = next_sink_operator_id();
1203
1.95k
        const int multi_cast_node_id = sink_id;
1204
1.95k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1205
        // one sink has multiple sources.
1206
1.95k
        std::vector<int> sources;
1207
7.60k
        for (int i = 0; i < sender_size; ++i) {
1208
5.64k
            auto source_id = next_operator_id();
1209
5.64k
            sources.push_back(source_id);
1210
5.64k
        }
1211
1212
1.95k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1213
1.95k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1214
7.60k
        for (int i = 0; i < sender_size; ++i) {
1215
5.64k
            auto new_pipeline = add_pipeline();
1216
            // use to exchange sink
1217
5.64k
            RowDescriptor* exchange_row_desc = nullptr;
1218
5.64k
            {
1219
5.64k
                const auto& tmp_row_desc =
1220
5.64k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1221
5.64k
                                ? RowDescriptor(state->desc_tbl(),
1222
5.64k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1223
5.64k
                                                         .output_tuple_id})
1224
5.64k
                                : row_desc;
1225
5.64k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1226
5.64k
            }
1227
5.64k
            auto source_id = sources[i];
1228
5.64k
            OperatorPtr source_op;
1229
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1230
5.64k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1231
5.64k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1232
5.64k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1233
5.64k
                    /*operator_id=*/source_id);
1234
5.64k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1235
5.64k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1236
            // 2. create and set sink operator of data stream sender for new pipeline
1237
1238
5.64k
            DataSinkOperatorPtr sink_op;
1239
5.64k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1240
5.64k
                    state, *exchange_row_desc, next_sink_operator_id(),
1241
5.64k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1242
5.64k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1243
1244
5.64k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1245
5.64k
            {
1246
5.64k
                TDataSink* t = pool->add(new TDataSink());
1247
5.64k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1248
5.64k
                RETURN_IF_ERROR(sink_op->init(*t));
1249
5.64k
            }
1250
1251
            // 3. set dependency dag
1252
5.64k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1253
5.64k
        }
1254
1.95k
        if (sources.empty()) {
1255
0
            return Status::InternalError("size of sources must be greater than 0");
1256
0
        }
1257
1.95k
        break;
1258
1.95k
    }
1259
1.95k
    case TDataSinkType::BLACKHOLE_SINK: {
1260
13
        if (!thrift_sink.__isset.blackhole_sink) {
1261
0
            return Status::InternalError("Missing blackhole sink.");
1262
0
        }
1263
1264
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1265
13
        break;
1266
13
    }
1267
156
    case TDataSinkType::TVF_TABLE_SINK: {
1268
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1269
0
            return Status::InternalError("Missing TVF table sink.");
1270
0
        }
1271
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1272
156
                                                        output_exprs);
1273
156
        break;
1274
156
    }
1275
0
    default:
1276
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1277
432k
    }
1278
432k
    return Status::OK();
1279
432k
}
1280
1281
// NOLINTBEGIN(readability-function-size)
1282
// NOLINTBEGIN(readability-function-cognitive-complexity)
1283
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1284
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1285
                                                 PipelinePtr& cur_pipe, int parent_idx,
1286
                                                 int child_idx,
1287
                                                 const bool followed_by_shuffled_operator,
1288
                                                 const bool require_bucket_distribution,
1289
672k
                                                 OperatorPtr& cache_op) {
1290
672k
    std::vector<DataSinkOperatorPtr> sink_ops;
1291
672k
    Defer defer = Defer([&]() {
1292
671k
        if (op) {
1293
671k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1294
671k
        }
1295
671k
        for (auto& s : sink_ops) {
1296
124k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1297
124k
        }
1298
671k
    });
1299
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1300
    // Therefore, here we need to use a stack-like structure.
1301
672k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1302
672k
    std::stringstream error_msg;
1303
672k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1304
1305
672k
    bool fe_with_old_version = false;
1306
672k
    switch (tnode.node_type) {
1307
211k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1308
211k
        op = std::make_shared<OlapScanOperatorX>(
1309
211k
                pool, tnode, next_operator_id(), descs, _num_instances,
1310
211k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1311
211k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1312
211k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1313
211k
        break;
1314
211k
    }
1315
79
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1316
79
        DCHECK(_query_ctx != nullptr);
1317
79
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1318
79
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1319
79
                                                    _num_instances);
1320
79
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1321
79
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1322
79
        break;
1323
79
    }
1324
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1325
0
        if (config::enable_java_support) {
1326
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1327
0
                                                     _num_instances);
1328
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1329
0
        } else {
1330
0
            return Status::InternalError(
1331
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1332
0
                    "to true and restart be.");
1333
0
        }
1334
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1335
0
        break;
1336
0
    }
1337
23.1k
    case TPlanNodeType::FILE_SCAN_NODE: {
1338
23.1k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1339
23.1k
                                                 _num_instances);
1340
23.1k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1341
23.1k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1342
23.1k
        break;
1343
23.1k
    }
1344
148k
    case TPlanNodeType::EXCHANGE_NODE: {
1345
148k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1346
148k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1347
18.4E
                                  : 0;
1348
148k
        DCHECK_GT(num_senders, 0);
1349
148k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1350
148k
                                                       num_senders);
1351
148k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1352
148k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1353
148k
        break;
1354
148k
    }
1355
157k
    case TPlanNodeType::AGGREGATION_NODE: {
1356
157k
        if (tnode.agg_node.grouping_exprs.empty() &&
1357
157k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1358
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1359
0
                                         ": group by and output is empty");
1360
0
        }
1361
157k
        bool need_create_cache_op =
1362
157k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1363
157k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1364
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1365
10
            auto cache_source_id = next_operator_id();
1366
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1367
10
                                                        _params.fragment.query_cache_param);
1368
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1369
1370
10
            const auto downstream_pipeline_id = cur_pipe->id();
1371
10
            if (!_dag.contains(downstream_pipeline_id)) {
1372
10
                _dag.insert({downstream_pipeline_id, {}});
1373
10
            }
1374
10
            new_pipe = add_pipeline(cur_pipe);
1375
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1376
1377
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1378
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1379
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1380
10
            return Status::OK();
1381
10
        };
1382
157k
        const bool group_by_limit_opt =
1383
157k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1384
1385
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1386
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1387
157k
        const bool enable_spill = _runtime_state->enable_spill() &&
1388
157k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1389
157k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1390
157k
                                      tnode.agg_node.use_streaming_preaggregation &&
1391
157k
                                      !tnode.agg_node.grouping_exprs.empty();
1392
        // TODO: distinct streaming agg does not support spill.
1393
157k
        const bool can_use_distinct_streaming_agg =
1394
157k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1395
157k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1396
157k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1397
157k
                _params.query_options.enable_distinct_streaming_aggregation;
1398
1399
157k
        if (can_use_distinct_streaming_agg) {
1400
91.7k
            if (need_create_cache_op) {
1401
8
                PipelinePtr new_pipe;
1402
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1403
1404
8
                cache_op = op;
1405
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1406
8
                                                                     tnode, descs);
1407
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1408
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1409
8
                cur_pipe = new_pipe;
1410
91.7k
            } else {
1411
91.7k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1412
91.7k
                                                                     tnode, descs);
1413
91.7k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1414
91.7k
            }
1415
91.7k
        } else if (is_streaming_agg) {
1416
3.42k
            if (need_create_cache_op) {
1417
0
                PipelinePtr new_pipe;
1418
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1419
0
                cache_op = op;
1420
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1421
0
                                                             descs);
1422
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1423
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1424
0
                cur_pipe = new_pipe;
1425
3.42k
            } else {
1426
3.42k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1427
3.42k
                                                             descs);
1428
3.42k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1429
3.42k
            }
1430
62.6k
        } else {
1431
            // create new pipeline to add query cache operator
1432
62.6k
            PipelinePtr new_pipe;
1433
62.6k
            if (need_create_cache_op) {
1434
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1435
2
                cache_op = op;
1436
2
            }
1437
1438
62.6k
            if (enable_spill) {
1439
139
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1440
139
                                                                     next_operator_id(), descs);
1441
62.5k
            } else {
1442
62.5k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1443
62.5k
            }
1444
62.6k
            if (need_create_cache_op) {
1445
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1446
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1447
2
                cur_pipe = new_pipe;
1448
62.6k
            } else {
1449
62.6k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1450
62.6k
            }
1451
1452
62.6k
            const auto downstream_pipeline_id = cur_pipe->id();
1453
62.6k
            if (!_dag.contains(downstream_pipeline_id)) {
1454
60.3k
                _dag.insert({downstream_pipeline_id, {}});
1455
60.3k
            }
1456
62.6k
            cur_pipe = add_pipeline(cur_pipe);
1457
62.6k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1458
1459
62.6k
            if (enable_spill) {
1460
139
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1461
139
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1462
62.5k
            } else {
1463
62.5k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1464
62.5k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1465
62.5k
            }
1466
62.6k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1467
62.6k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1468
62.6k
        }
1469
157k
        break;
1470
157k
    }
1471
157k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1472
75
        if (tnode.bucketed_agg_node.grouping_exprs.empty()) {
1473
0
            return Status::InternalError(
1474
0
                    "Bucketed aggregation node {} should not be used without group by keys",
1475
0
                    tnode.node_id);
1476
0
        }
1477
1478
        // Create source operator (goes on the current / downstream pipeline).
1479
75
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1480
75
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1481
1482
        // Create a new pipeline for the sink side.
1483
75
        const auto downstream_pipeline_id = cur_pipe->id();
1484
75
        if (!_dag.contains(downstream_pipeline_id)) {
1485
75
            _dag.insert({downstream_pipeline_id, {}});
1486
75
        }
1487
75
        cur_pipe = add_pipeline(cur_pipe);
1488
75
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1489
1490
        // Create sink operator.
1491
75
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1492
75
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1493
75
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1494
75
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1495
1496
        // Pre-register a single shared state for ALL instances so that every
1497
        // sink instance writes its per-instance hash table into the same
1498
        // BucketedAggSharedState and every source instance can merge across
1499
        // all of them.
1500
75
        {
1501
75
            auto shared_state = BucketedAggSharedState::create_shared();
1502
75
            shared_state->id = op->operator_id();
1503
75
            shared_state->related_op_ids.insert(op->operator_id());
1504
1505
515
            for (int i = 0; i < _num_instances; i++) {
1506
440
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1507
440
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1508
440
                sink_dep->set_shared_state(shared_state.get());
1509
440
                shared_state->sink_deps.push_back(sink_dep);
1510
440
            }
1511
75
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1512
75
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1513
75
            _op_id_to_shared_state.insert(
1514
75
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1515
75
        }
1516
75
        break;
1517
75
    }
1518
9.66k
    case TPlanNodeType::HASH_JOIN_NODE: {
1519
9.66k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1520
9.66k
                                       tnode.hash_join_node.is_broadcast_join;
1521
9.66k
        const auto enable_spill = _runtime_state->enable_spill();
1522
9.66k
        if (enable_spill && !is_broadcast_join) {
1523
0
            auto tnode_ = tnode;
1524
0
            tnode_.runtime_filters.clear();
1525
0
            auto inner_probe_operator =
1526
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1527
1528
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1529
            // So here use `tnode_` which has no runtime filters.
1530
0
            auto probe_side_inner_sink_operator =
1531
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1532
1533
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1534
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1535
1536
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1537
0
                    pool, tnode_, next_operator_id(), descs);
1538
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1539
0
                                                inner_probe_operator);
1540
0
            op = std::move(probe_operator);
1541
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1542
1543
0
            const auto downstream_pipeline_id = cur_pipe->id();
1544
0
            if (!_dag.contains(downstream_pipeline_id)) {
1545
0
                _dag.insert({downstream_pipeline_id, {}});
1546
0
            }
1547
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1548
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1549
1550
0
            auto inner_sink_operator =
1551
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1552
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1553
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1554
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1555
1556
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1557
0
            sink_ops.push_back(std::move(sink_operator));
1558
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1559
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1560
1561
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1562
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1563
9.66k
        } else {
1564
9.66k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1565
9.66k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1566
1567
9.66k
            const auto downstream_pipeline_id = cur_pipe->id();
1568
9.66k
            if (!_dag.contains(downstream_pipeline_id)) {
1569
7.94k
                _dag.insert({downstream_pipeline_id, {}});
1570
7.94k
            }
1571
9.66k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1572
9.66k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1573
1574
9.66k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1575
9.66k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1576
9.66k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1577
9.66k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1578
1579
9.66k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1580
9.66k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1581
9.66k
        }
1582
9.66k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1583
2.70k
            std::shared_ptr<HashJoinSharedState> shared_state =
1584
2.70k
                    HashJoinSharedState::create_shared(_num_instances);
1585
17.6k
            for (int i = 0; i < _num_instances; i++) {
1586
14.9k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1587
14.9k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1588
14.9k
                sink_dep->set_shared_state(shared_state.get());
1589
14.9k
                shared_state->sink_deps.push_back(sink_dep);
1590
14.9k
            }
1591
2.70k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1592
2.70k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1593
2.70k
            _op_id_to_shared_state.insert(
1594
2.70k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1595
2.70k
        }
1596
9.66k
        break;
1597
9.66k
    }
1598
4.82k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1599
4.82k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1600
4.82k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1601
1602
4.82k
        const auto downstream_pipeline_id = cur_pipe->id();
1603
4.82k
        if (!_dag.contains(downstream_pipeline_id)) {
1604
4.59k
            _dag.insert({downstream_pipeline_id, {}});
1605
4.59k
        }
1606
4.82k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1607
4.82k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1608
1609
4.82k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1610
4.82k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1611
4.82k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1612
4.82k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1613
4.82k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1614
4.82k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1615
4.82k
        break;
1616
4.82k
    }
1617
53.5k
    case TPlanNodeType::UNION_NODE: {
1618
53.5k
        int child_count = tnode.num_children;
1619
53.5k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1620
53.5k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1621
1622
53.5k
        const auto downstream_pipeline_id = cur_pipe->id();
1623
53.5k
        if (!_dag.contains(downstream_pipeline_id)) {
1624
53.3k
            _dag.insert({downstream_pipeline_id, {}});
1625
53.3k
        }
1626
54.9k
        for (int i = 0; i < child_count; i++) {
1627
1.41k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1628
1.41k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1629
1.41k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1630
1.41k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1631
1.41k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1632
1.41k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1633
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1634
1.41k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1635
1.41k
        }
1636
53.5k
        break;
1637
53.5k
    }
1638
53.5k
    case TPlanNodeType::SORT_NODE: {
1639
43.9k
        const auto should_spill = _runtime_state->enable_spill() &&
1640
43.9k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1641
43.9k
        const bool use_local_merge =
1642
43.9k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1643
43.9k
        if (should_spill) {
1644
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1645
43.9k
        } else if (use_local_merge) {
1646
41.5k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1647
41.5k
                                                                 descs);
1648
41.5k
        } else {
1649
2.33k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1650
2.33k
        }
1651
43.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1652
1653
43.9k
        const auto downstream_pipeline_id = cur_pipe->id();
1654
43.9k
        if (!_dag.contains(downstream_pipeline_id)) {
1655
43.9k
            _dag.insert({downstream_pipeline_id, {}});
1656
43.9k
        }
1657
43.9k
        cur_pipe = add_pipeline(cur_pipe);
1658
43.9k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1659
1660
43.9k
        if (should_spill) {
1661
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1662
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1663
43.9k
        } else {
1664
43.9k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1665
43.9k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1666
43.9k
        }
1667
43.9k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1668
43.9k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1669
43.9k
        break;
1670
43.9k
    }
1671
43.9k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1672
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1673
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1674
1675
62
        const auto downstream_pipeline_id = cur_pipe->id();
1676
62
        if (!_dag.contains(downstream_pipeline_id)) {
1677
62
            _dag.insert({downstream_pipeline_id, {}});
1678
62
        }
1679
62
        cur_pipe = add_pipeline(cur_pipe);
1680
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1681
1682
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1683
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1684
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1685
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1686
62
        break;
1687
62
    }
1688
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1689
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1690
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1691
1692
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1693
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1694
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1695
1.63k
        }
1696
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1697
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1698
1699
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1700
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1701
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1702
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1703
1.64k
        break;
1704
1.64k
    }
1705
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1706
1.61k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1707
1.61k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1708
1.61k
        break;
1709
1.61k
    }
1710
1.61k
    case TPlanNodeType::INTERSECT_NODE: {
1711
125
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1712
125
                                                                      cur_pipe, sink_ops));
1713
125
        break;
1714
125
    }
1715
129
    case TPlanNodeType::EXCEPT_NODE: {
1716
129
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1717
129
                                                                       cur_pipe, sink_ops));
1718
129
        break;
1719
129
    }
1720
296
    case TPlanNodeType::REPEAT_NODE: {
1721
296
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1722
296
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1723
296
        break;
1724
296
    }
1725
921
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1726
921
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1727
921
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1728
921
        break;
1729
921
    }
1730
921
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1731
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1732
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1733
218
        break;
1734
218
    }
1735
1.60k
    case TPlanNodeType::EMPTY_SET_NODE: {
1736
1.60k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1737
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1738
1.60k
        break;
1739
1.60k
    }
1740
1.60k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1741
461
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1742
461
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1743
461
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1744
461
        break;
1745
461
    }
1746
2.04k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1747
2.04k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1748
2.04k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1749
2.04k
        break;
1750
2.04k
    }
1751
6.06k
    case TPlanNodeType::META_SCAN_NODE: {
1752
6.06k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1753
6.06k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1754
6.06k
        break;
1755
6.06k
    }
1756
6.06k
    case TPlanNodeType::SELECT_NODE: {
1757
1.92k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1758
1.92k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1759
1.92k
        break;
1760
1.92k
    }
1761
1.92k
    case TPlanNodeType::REC_CTE_NODE: {
1762
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1763
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1764
1765
151
        const auto downstream_pipeline_id = cur_pipe->id();
1766
151
        if (!_dag.contains(downstream_pipeline_id)) {
1767
148
            _dag.insert({downstream_pipeline_id, {}});
1768
148
        }
1769
1770
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1771
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1772
1773
151
        DataSinkOperatorPtr anchor_sink;
1774
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1775
151
                                                                  op->operator_id(), tnode, descs);
1776
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1777
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1778
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1779
1780
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1781
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1782
1783
151
        DataSinkOperatorPtr rec_sink;
1784
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1785
151
                                                         tnode, descs);
1786
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1787
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1788
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1789
1790
151
        break;
1791
151
    }
1792
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1793
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1794
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1795
1.95k
        break;
1796
1.95k
    }
1797
1.95k
    default:
1798
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1799
0
                                     print_plan_node_type(tnode.node_type));
1800
672k
    }
1801
671k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1802
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1803
0
        op->set_serial_operator();
1804
0
    }
1805
1806
671k
    return Status::OK();
1807
672k
}
1808
// NOLINTEND(readability-function-cognitive-complexity)
1809
// NOLINTEND(readability-function-size)
1810
1811
template <bool is_intersect>
1812
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1813
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1814
254
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1815
254
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1816
254
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1817
1818
254
    const auto downstream_pipeline_id = cur_pipe->id();
1819
254
    if (!_dag.contains(downstream_pipeline_id)) {
1820
230
        _dag.insert({downstream_pipeline_id, {}});
1821
230
    }
1822
1823
855
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1824
601
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1825
601
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1826
1827
601
        if (child_id == 0) {
1828
254
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1829
254
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1830
347
        } else {
1831
347
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1832
347
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1833
347
        }
1834
601
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1835
601
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1836
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1837
601
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1838
601
    }
1839
1840
254
    return Status::OK();
1841
254
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1814
125
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1815
125
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1816
125
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1817
1818
125
    const auto downstream_pipeline_id = cur_pipe->id();
1819
125
    if (!_dag.contains(downstream_pipeline_id)) {
1820
110
        _dag.insert({downstream_pipeline_id, {}});
1821
110
    }
1822
1823
453
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1824
328
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1825
328
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1826
1827
328
        if (child_id == 0) {
1828
125
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1829
125
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1830
203
        } else {
1831
203
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1832
203
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1833
203
        }
1834
328
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1835
328
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1836
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1837
328
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1838
328
    }
1839
1840
125
    return Status::OK();
1841
125
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1814
129
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1815
129
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1816
129
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1817
1818
129
    const auto downstream_pipeline_id = cur_pipe->id();
1819
129
    if (!_dag.contains(downstream_pipeline_id)) {
1820
120
        _dag.insert({downstream_pipeline_id, {}});
1821
120
    }
1822
1823
402
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1824
273
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1825
273
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1826
1827
273
        if (child_id == 0) {
1828
129
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1829
129
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1830
144
        } else {
1831
144
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1832
144
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1833
144
        }
1834
273
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1835
273
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1836
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1837
273
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1838
273
    }
1839
1840
129
    return Status::OK();
1841
129
}
1842
1843
430k
Status PipelineFragmentContext::submit() {
1844
430k
    if (_submitted) {
1845
0
        return Status::InternalError("submitted");
1846
0
    }
1847
430k
    _submitted = true;
1848
1849
430k
    int submit_tasks = 0;
1850
430k
    Status st;
1851
430k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1852
1.16M
    for (auto& task : _tasks) {
1853
1.97M
        for (auto& t : task) {
1854
1.97M
            st = scheduler->submit(t.first);
1855
1.97M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1856
1.97M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1857
1.97M
            if (!st) {
1858
0
                cancel(Status::InternalError("submit context to executor fail"));
1859
0
                std::lock_guard<std::mutex> l(_task_mutex);
1860
0
                _total_tasks = submit_tasks;
1861
0
                break;
1862
0
            }
1863
1.97M
            submit_tasks++;
1864
1.97M
        }
1865
1.16M
    }
1866
430k
    if (!st.ok()) {
1867
0
        bool need_remove = false;
1868
0
        {
1869
0
            std::lock_guard<std::mutex> l(_task_mutex);
1870
0
            if (_closed_tasks >= _total_tasks) {
1871
0
                need_remove = _close_fragment_instance();
1872
0
            }
1873
0
        }
1874
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1875
0
        if (need_remove) {
1876
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1877
0
        }
1878
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1879
0
                                     BackendOptions::get_localhost());
1880
430k
    } else {
1881
430k
        return st;
1882
430k
    }
1883
430k
}
1884
1885
54
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1886
54
    if (_runtime_state->enable_profile()) {
1887
0
        std::stringstream ss;
1888
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1889
0
            runtime_profile_ptr->pretty_print(&ss);
1890
0
        }
1891
1892
0
        if (_runtime_state->load_channel_profile()) {
1893
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1894
0
        }
1895
1896
0
        auto profile_str =
1897
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1898
0
                            this->_fragment_id, extra_info, ss.str());
1899
0
        LOG_LONG_STRING(INFO, profile_str);
1900
0
    }
1901
54
}
1902
// If all pipeline tasks binded to the fragment instance are finished, then we could
1903
// close the fragment instance.
1904
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1905
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1906
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1907
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1908
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1909
// (via debug_string()).
1910
432k
bool PipelineFragmentContext::_close_fragment_instance() {
1911
432k
    if (_is_fragment_instance_closed) {
1912
0
        return false;
1913
0
    }
1914
432k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1915
432k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1916
432k
    if (!_need_notify_close) {
1917
429k
        auto st = send_report(true);
1918
429k
        if (!st) {
1919
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1920
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1921
0
        }
1922
429k
    }
1923
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1924
    // Since stream load does not have someting like coordinator on FE, so
1925
    // backend can not report profile to FE, ant its profile can not be shown
1926
    // in the same way with other query. So we print the profile content to info log.
1927
1928
432k
    if (_runtime_state->enable_profile() &&
1929
432k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1930
2.84k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1931
2.84k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1932
0
        std::stringstream ss;
1933
        // Compute the _local_time_percent before pretty_print the runtime_profile
1934
        // Before add this operation, the print out like that:
1935
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1936
        // After add the operation, the print out like that:
1937
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1938
        // We can easily know the exec node execute time without child time consumed.
1939
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1940
0
            runtime_profile_ptr->pretty_print(&ss);
1941
0
        }
1942
1943
0
        if (_runtime_state->load_channel_profile()) {
1944
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1945
0
        }
1946
1947
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1948
0
    }
1949
1950
432k
    if (_query_ctx->enable_profile()) {
1951
2.84k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1952
2.84k
                                         collect_realtime_load_channel_profile());
1953
2.84k
    }
1954
1955
    // Return whether the caller needs to remove from the pipeline map.
1956
    // The caller must do this after releasing _task_mutex.
1957
432k
    return !_need_notify_close;
1958
432k
}
1959
1960
1.96M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1961
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1962
1.96M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1963
1.96M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1964
672k
        if (_dag.contains(pipeline_id)) {
1965
349k
            for (auto dep : _dag[pipeline_id]) {
1966
349k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1967
349k
            }
1968
282k
        }
1969
672k
    }
1970
1.96M
    bool need_remove = false;
1971
1.96M
    {
1972
1.96M
        std::lock_guard<std::mutex> l(_task_mutex);
1973
1.96M
        ++_closed_tasks;
1974
1.96M
        if (_closed_tasks >= _total_tasks) {
1975
432k
            need_remove = _close_fragment_instance();
1976
432k
        }
1977
1.96M
    }
1978
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1979
1.96M
    if (need_remove) {
1980
429k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1981
429k
    }
1982
1.96M
}
1983
1984
54.6k
std::string PipelineFragmentContext::get_load_error_url() {
1985
54.6k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1986
0
        return to_load_error_http_path(str);
1987
0
    }
1988
151k
    for (auto& tasks : _tasks) {
1989
247k
        for (auto& task : tasks) {
1990
247k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1991
174
                return to_load_error_http_path(str);
1992
174
            }
1993
247k
        }
1994
151k
    }
1995
54.4k
    return "";
1996
54.6k
}
1997
1998
54.6k
std::string PipelineFragmentContext::get_first_error_msg() {
1999
54.6k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2000
0
        return str;
2001
0
    }
2002
151k
    for (auto& tasks : _tasks) {
2003
247k
        for (auto& task : tasks) {
2004
247k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2005
174
                return str;
2006
174
            }
2007
247k
        }
2008
151k
    }
2009
54.4k
    return "";
2010
54.6k
}
2011
2012
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2013
0
    std::stringstream url;
2014
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2015
0
        << "/api/_download_load?"
2016
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2017
0
    return url.str();
2018
0
}
2019
2020
48.5k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2021
48.5k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2022
48.5k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2023
48.5k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2024
48.5k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2025
48.5k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2026
48.5k
    });
2027
2028
48.5k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2029
48.5k
    if (req.coord_addr.hostname == "external") {
2030
        // External query (flink/spark read tablets) not need to report to FE.
2031
0
        return;
2032
0
    }
2033
48.5k
    int callback_retries = 10;
2034
48.5k
    const int sleep_ms = 1000;
2035
48.5k
    Status exec_status = req.status;
2036
48.5k
    Status coord_status;
2037
48.5k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2038
48.5k
    do {
2039
48.5k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2040
48.5k
                                                            req.coord_addr, &coord_status);
2041
48.5k
        if (!coord_status.ok()) {
2042
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2043
0
        }
2044
48.5k
    } while (!coord_status.ok() && callback_retries-- > 0);
2045
2046
48.5k
    if (!coord_status.ok()) {
2047
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2048
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2049
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2050
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2051
0
        return;
2052
0
    }
2053
2054
48.5k
    TReportExecStatusParams params;
2055
48.5k
    params.protocol_version = FrontendServiceVersion::V1;
2056
48.5k
    params.__set_query_id(req.query_id);
2057
48.5k
    params.__set_backend_num(req.backend_num);
2058
48.5k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2059
48.5k
    params.__set_fragment_id(req.fragment_id);
2060
48.5k
    params.__set_status(exec_status.to_thrift());
2061
48.5k
    params.__set_done(req.done);
2062
48.5k
    params.__set_query_type(req.runtime_state->query_type());
2063
48.5k
    params.__isset.profile = false;
2064
2065
48.5k
    DCHECK(req.runtime_state != nullptr);
2066
2067
48.5k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2068
43.5k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2069
43.5k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2070
43.5k
    } else {
2071
5.01k
        DCHECK(!req.runtime_states.empty());
2072
5.01k
        if (!req.runtime_state->output_files().empty()) {
2073
0
            params.__isset.delta_urls = true;
2074
0
            for (auto& it : req.runtime_state->output_files()) {
2075
0
                params.delta_urls.push_back(_to_http_path(it));
2076
0
            }
2077
0
        }
2078
5.01k
        if (!params.delta_urls.empty()) {
2079
0
            params.__isset.delta_urls = true;
2080
0
        }
2081
5.01k
    }
2082
2083
48.5k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2084
48.5k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2085
48.5k
    static std::string s_unselected_rows = "unselected.rows";
2086
48.5k
    int64_t num_rows_load_success = 0;
2087
48.5k
    int64_t num_rows_load_filtered = 0;
2088
48.5k
    int64_t num_rows_load_unselected = 0;
2089
48.5k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2090
48.5k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2091
48.5k
        req.runtime_state->num_finished_range() > 0) {
2092
0
        params.__isset.load_counters = true;
2093
2094
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2095
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2096
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2097
0
        params.__isset.fragment_instance_reports = true;
2098
0
        TFragmentInstanceReport t;
2099
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2100
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2101
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2102
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2103
0
        params.fragment_instance_reports.push_back(t);
2104
48.5k
    } else if (!req.runtime_states.empty()) {
2105
181k
        for (auto* rs : req.runtime_states) {
2106
181k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2107
181k
                rs->num_finished_range() > 0) {
2108
36.0k
                params.__isset.load_counters = true;
2109
36.0k
                num_rows_load_success += rs->num_rows_load_success();
2110
36.0k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2111
36.0k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2112
36.0k
                params.__isset.fragment_instance_reports = true;
2113
36.0k
                TFragmentInstanceReport t;
2114
36.0k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2115
36.0k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2116
36.0k
                t.__set_loaded_rows(rs->num_rows_load_total());
2117
36.0k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2118
36.0k
                params.fragment_instance_reports.push_back(t);
2119
36.0k
            }
2120
181k
        }
2121
48.5k
    }
2122
48.5k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2123
48.5k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2124
48.5k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2125
2126
48.5k
    if (!req.load_error_url.empty()) {
2127
158
        params.__set_tracking_url(req.load_error_url);
2128
158
    }
2129
48.5k
    if (!req.first_error_msg.empty()) {
2130
158
        params.__set_first_error_msg(req.first_error_msg);
2131
158
    }
2132
181k
    for (auto* rs : req.runtime_states) {
2133
181k
        if (rs->wal_id() > 0) {
2134
112
            params.__set_txn_id(rs->wal_id());
2135
112
            params.__set_label(rs->import_label());
2136
112
        }
2137
181k
    }
2138
48.5k
    if (!req.runtime_state->export_output_files().empty()) {
2139
0
        params.__isset.export_files = true;
2140
0
        params.export_files = req.runtime_state->export_output_files();
2141
48.5k
    } else if (!req.runtime_states.empty()) {
2142
181k
        for (auto* rs : req.runtime_states) {
2143
181k
            if (!rs->export_output_files().empty()) {
2144
0
                params.__isset.export_files = true;
2145
0
                params.export_files.insert(params.export_files.end(),
2146
0
                                           rs->export_output_files().begin(),
2147
0
                                           rs->export_output_files().end());
2148
0
            }
2149
181k
        }
2150
48.5k
    }
2151
48.5k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2152
0
        params.__isset.commitInfos = true;
2153
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2154
48.5k
    } else if (!req.runtime_states.empty()) {
2155
181k
        for (auto* rs : req.runtime_states) {
2156
181k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2157
27.1k
                params.__isset.commitInfos = true;
2158
27.1k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2159
27.1k
            }
2160
181k
        }
2161
48.5k
    }
2162
48.5k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2163
0
        params.__isset.errorTabletInfos = true;
2164
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2165
48.5k
    } else if (!req.runtime_states.empty()) {
2166
181k
        for (auto* rs : req.runtime_states) {
2167
181k
            if (auto rs_eti = rs->error_tablet_infos(); !rs_eti.empty()) {
2168
0
                params.__isset.errorTabletInfos = true;
2169
0
                params.errorTabletInfos.insert(params.errorTabletInfos.end(), rs_eti.begin(),
2170
0
                                               rs_eti.end());
2171
0
            }
2172
181k
        }
2173
48.5k
    }
2174
48.5k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2175
0
        params.__isset.hive_partition_updates = true;
2176
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2177
0
                                             hpu.end());
2178
48.5k
    } else if (!req.runtime_states.empty()) {
2179
181k
        for (auto* rs : req.runtime_states) {
2180
181k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2181
2.02k
                params.__isset.hive_partition_updates = true;
2182
2.02k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2183
2.02k
                                                     rs_hpu.begin(), rs_hpu.end());
2184
2.02k
            }
2185
181k
        }
2186
48.5k
    }
2187
48.5k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2188
0
        params.__isset.iceberg_commit_datas = true;
2189
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2190
0
                                           icd.end());
2191
48.5k
    } else if (!req.runtime_states.empty()) {
2192
181k
        for (auto* rs : req.runtime_states) {
2193
181k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2194
2.07k
                params.__isset.iceberg_commit_datas = true;
2195
2.07k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2196
2.07k
                                                   rs_icd.begin(), rs_icd.end());
2197
2.07k
            }
2198
181k
        }
2199
48.5k
    }
2200
2201
48.5k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2202
0
        params.__isset.mc_commit_datas = true;
2203
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2204
48.5k
    } else if (!req.runtime_states.empty()) {
2205
181k
        for (auto* rs : req.runtime_states) {
2206
181k
            if (auto rs_mcd = rs->mc_commit_datas(); !rs_mcd.empty()) {
2207
0
                params.__isset.mc_commit_datas = true;
2208
0
                params.mc_commit_datas.insert(params.mc_commit_datas.end(), rs_mcd.begin(),
2209
0
                                              rs_mcd.end());
2210
0
            }
2211
181k
        }
2212
48.5k
    }
2213
2214
48.5k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2215
48.5k
    params.__isset.error_log = (!params.error_log.empty());
2216
2217
48.5k
    if (_exec_env->cluster_info()->backend_id != 0) {
2218
48.5k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2219
48.5k
    }
2220
2221
48.5k
    TReportExecStatusResult res;
2222
48.5k
    Status rpc_status;
2223
2224
48.5k
    VLOG_DEBUG << "reportExecStatus params is "
2225
21
               << apache::thrift::ThriftDebugString(params).c_str();
2226
48.5k
    if (!exec_status.ok()) {
2227
1.66k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2228
1.66k
                     << " to coordinator: " << req.coord_addr
2229
1.66k
                     << ", query id: " << print_id(req.query_id);
2230
1.66k
    }
2231
48.5k
    try {
2232
48.5k
        try {
2233
48.5k
            (*coord)->reportExecStatus(res, params);
2234
48.5k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2235
#ifndef ADDRESS_SANITIZER
2236
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2237
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2238
                         << req.coord_addr << ", err: " << e.what();
2239
#endif
2240
0
            rpc_status = coord->reopen();
2241
2242
0
            if (!rpc_status.ok()) {
2243
0
                req.cancel_fn(rpc_status);
2244
0
                return;
2245
0
            }
2246
0
            (*coord)->reportExecStatus(res, params);
2247
0
        }
2248
2249
48.5k
        rpc_status = Status::create<false>(res.status);
2250
48.5k
    } catch (apache::thrift::TException& e) {
2251
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2252
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2253
0
    }
2254
2255
48.5k
    if (!rpc_status.ok()) {
2256
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2257
0
                 print_id(req.query_id), rpc_status.to_string());
2258
0
        req.cancel_fn(rpc_status);
2259
0
    }
2260
48.5k
}
2261
2262
434k
Status PipelineFragmentContext::send_report(bool done) {
2263
434k
    Status exec_status = _query_ctx->exec_status();
2264
    // If plan is done successfully, but _is_report_success is false,
2265
    // no need to send report.
2266
    // Load will set _is_report_success to true because load wants to know
2267
    // the process.
2268
434k
    if (!_is_report_success && done && exec_status.ok()) {
2269
385k
        return Status::OK();
2270
385k
    }
2271
2272
    // If both _is_report_success and _is_report_on_cancel are false,
2273
    // which means no matter query is success or failed, no report is needed.
2274
    // This may happen when the query limit reached and
2275
    // a internal cancellation being processed
2276
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2277
    // be set to false, to avoid sending fault report to FE.
2278
48.8k
    if (!_is_report_success && !_is_report_on_cancel) {
2279
337
        if (done) {
2280
            // 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.
2281
337
            return Status::OK();
2282
337
        }
2283
0
        return Status::NeedSendAgain("");
2284
337
    }
2285
2286
48.5k
    std::vector<RuntimeState*> runtime_states;
2287
2288
123k
    for (auto& tasks : _tasks) {
2289
181k
        for (auto& task : tasks) {
2290
181k
            runtime_states.push_back(task.second.get());
2291
181k
        }
2292
123k
    }
2293
2294
48.5k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2295
48.5k
                                        ? get_load_error_url()
2296
48.5k
                                        : _query_ctx->get_load_error_url();
2297
48.5k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2298
48.5k
                                          ? get_first_error_msg()
2299
48.5k
                                          : _query_ctx->get_first_error_msg();
2300
2301
48.5k
    ReportStatusRequest req {.status = exec_status,
2302
48.5k
                             .runtime_states = runtime_states,
2303
48.5k
                             .done = done || !exec_status.ok(),
2304
48.5k
                             .coord_addr = _query_ctx->coord_addr,
2305
48.5k
                             .query_id = _query_id,
2306
48.5k
                             .fragment_id = _fragment_id,
2307
48.5k
                             .fragment_instance_id = TUniqueId(),
2308
48.5k
                             .backend_num = -1,
2309
48.5k
                             .runtime_state = _runtime_state.get(),
2310
48.5k
                             .load_error_url = load_eror_url,
2311
48.5k
                             .first_error_msg = first_error_msg,
2312
48.5k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2313
48.5k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2314
48.5k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2315
48.5k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2316
48.5k
        _coordinator_callback(req);
2317
48.5k
        if (!req.done) {
2318
5.00k
            ctx->refresh_next_report_time();
2319
5.00k
        }
2320
48.5k
    });
2321
48.8k
}
2322
2323
8
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2324
8
    size_t res = 0;
2325
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2326
    // here to traverse the vector.
2327
8
    for (const auto& task_instances : _tasks) {
2328
12
        for (const auto& task : task_instances) {
2329
12
            if (task.first->is_running()) {
2330
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2331
0
                                      << " is running, task: " << (void*)task.first.get()
2332
0
                                      << ", is_running: " << task.first->is_running();
2333
0
                *has_running_task = true;
2334
0
                return 0;
2335
0
            }
2336
2337
12
            size_t revocable_size = task.first->get_revocable_size();
2338
12
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2339
4
                res += revocable_size;
2340
4
            }
2341
12
        }
2342
8
    }
2343
8
    return res;
2344
8
}
2345
2346
16
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2347
16
    std::vector<PipelineTask*> revocable_tasks;
2348
16
    for (const auto& task_instances : _tasks) {
2349
24
        for (const auto& task : task_instances) {
2350
24
            size_t revocable_size_ = task.first->get_revocable_size();
2351
2352
24
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2353
8
                revocable_tasks.emplace_back(task.first.get());
2354
8
            }
2355
24
        }
2356
16
    }
2357
16
    return revocable_tasks;
2358
16
}
2359
2360
84
std::string PipelineFragmentContext::debug_string() {
2361
84
    std::lock_guard<std::mutex> l(_task_mutex);
2362
84
    fmt::memory_buffer debug_string_buffer;
2363
84
    fmt::format_to(debug_string_buffer,
2364
84
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2365
84
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2366
84
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2367
443
    for (size_t j = 0; j < _tasks.size(); j++) {
2368
359
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2369
1.42k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2370
1.06k
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2371
1.06k
                           _tasks[j][i].first->debug_string());
2372
1.06k
        }
2373
359
    }
2374
2375
84
    return fmt::to_string(debug_string_buffer);
2376
84
}
2377
2378
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2379
2.84k
PipelineFragmentContext::collect_realtime_profile() const {
2380
2.84k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2381
2382
    // we do not have mutex to protect pipeline_id_to_profile
2383
    // so we need to make sure this funciton is invoked after fragment context
2384
    // has already been prepared.
2385
2.84k
    if (!_prepared) {
2386
0
        std::string msg =
2387
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2388
0
        DCHECK(false) << msg;
2389
0
        LOG_ERROR(msg);
2390
0
        return res;
2391
0
    }
2392
2393
    // Make sure first profile is fragment level profile
2394
2.84k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2395
2.84k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2396
2.84k
    res.push_back(fragment_profile);
2397
2398
    // pipeline_id_to_profile is initialized in prepare stage
2399
5.18k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2400
5.18k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2401
5.18k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2402
5.18k
        res.push_back(profile_ptr);
2403
5.18k
    }
2404
2405
2.84k
    return res;
2406
2.84k
}
2407
2408
std::shared_ptr<TRuntimeProfileTree>
2409
2.84k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2410
    // we do not have mutex to protect pipeline_id_to_profile
2411
    // so we need to make sure this funciton is invoked after fragment context
2412
    // has already been prepared.
2413
2.84k
    if (!_prepared) {
2414
0
        std::string msg =
2415
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2416
0
        DCHECK(false) << msg;
2417
0
        LOG_ERROR(msg);
2418
0
        return nullptr;
2419
0
    }
2420
2421
8.82k
    for (const auto& tasks : _tasks) {
2422
17.5k
        for (const auto& task : tasks) {
2423
17.5k
            if (task.second->load_channel_profile() == nullptr) {
2424
0
                continue;
2425
0
            }
2426
2427
17.5k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2428
2429
17.5k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2430
17.5k
                                                           _runtime_state->profile_level());
2431
17.5k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2432
17.5k
        }
2433
8.82k
    }
2434
2435
2.84k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2436
2.84k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2437
2.84k
                                                      _runtime_state->profile_level());
2438
2.84k
    return load_channel_profile;
2439
2.84k
}
2440
2441
// Collect runtime filter IDs registered by all tasks in this PFC.
2442
// Used during recursive CTE stage transitions to know which filters to deregister
2443
// before creating the new PFC for the next recursion round.
2444
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2445
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2446
// the vector sizes do not change, and individual RuntimeState filter sets are
2447
// written only during open() which has completed by the time we reach rerun.
2448
3.08k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2449
3.08k
    std::set<int> result;
2450
6.28k
    for (const auto& _task : _tasks) {
2451
10.4k
        for (const auto& task : _task) {
2452
10.4k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2453
10.4k
            result.merge(set);
2454
10.4k
        }
2455
6.28k
    }
2456
3.08k
    if (_runtime_state) {
2457
3.08k
        auto set = _runtime_state->get_deregister_runtime_filter();
2458
3.08k
        result.merge(set);
2459
3.08k
    }
2460
3.08k
    return result;
2461
3.08k
}
2462
2463
433k
void PipelineFragmentContext::_release_resource() {
2464
433k
    std::lock_guard<std::mutex> l(_task_mutex);
2465
    // The memory released by the query end is recorded in the query mem tracker.
2466
433k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2467
433k
    auto st = _query_ctx->exec_status();
2468
1.16M
    for (auto& _task : _tasks) {
2469
1.16M
        if (!_task.empty()) {
2470
1.16M
            _call_back(_task.front().first->runtime_state(), &st);
2471
1.16M
        }
2472
1.16M
    }
2473
433k
    _tasks.clear();
2474
433k
    _dag.clear();
2475
433k
    _pip_id_to_pipeline.clear();
2476
433k
    _pipelines.clear();
2477
433k
    _sink.reset();
2478
433k
    _root_op.reset();
2479
433k
    _runtime_filter_mgr_map.clear();
2480
433k
    _op_id_to_shared_state.clear();
2481
433k
}
2482
2483
} // namespace doris