Coverage Report

Created: 2026-05-28 05:51

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
9
//   http://www.apache.org/licenses/LICENSE-2.0
10
//
11
// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
13
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
17
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
114
#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
132
#include "util/client_cache.h"
133
#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
451k
        : _query_id(std::move(query_id)),
144
451k
          _fragment_id(request.fragment_id),
145
451k
          _exec_env(exec_env),
146
451k
          _query_ctx(std::move(query_ctx)),
147
451k
          _call_back(call_back),
148
451k
          _is_report_on_cancel(true),
149
451k
          _params(request),
150
451k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
451k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
451k
                                                               : false) {
153
451k
    _fragment_watcher.start();
154
451k
}
155
156
451k
PipelineFragmentContext::~PipelineFragmentContext() {
157
451k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
451k
            .tag("query_id", print_id(_query_id))
159
451k
            .tag("fragment_id", _fragment_id);
160
451k
    _release_resource();
161
451k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
451k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
451k
        _runtime_state.reset();
165
451k
        _query_ctx.reset();
166
451k
    }
167
451k
}
168
169
76
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
76
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
76
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
76
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
179
// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
10.1k
bool PipelineFragmentContext::notify_close() {
181
10.1k
    bool all_closed = false;
182
10.1k
    bool need_remove = false;
183
10.1k
    {
184
10.1k
        std::lock_guard<std::mutex> l(_task_mutex);
185
10.1k
        if (_closed_tasks >= _total_tasks) {
186
3.31k
            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
3.26k
                need_remove = true;
193
3.26k
            }
194
3.31k
            all_closed = true;
195
3.31k
        }
196
        // make fragment release by self after cancel
197
10.1k
        _need_notify_close = false;
198
10.1k
    }
199
10.1k
    if (need_remove) {
200
3.26k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.26k
    }
202
10.1k
    return all_closed;
203
10.1k
}
204
205
// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
6.77k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.77k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.77k
            .tag("query_id", print_id(_query_id))
212
6.77k
            .tag("fragment_id", _fragment_id)
213
6.77k
            .tag("reason", reason.to_string());
214
6.77k
    if (notify_close()) {
215
77
        return;
216
77
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.70k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
14
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
14
                                   debug_string());
221
14
        LOG_LONG_STRING(WARNING, dbg_str);
222
14
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
6.70k
    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
6.70k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
6.70k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
41
        _query_ctx->set_load_error_url(error_url);
236
41
    }
237
238
6.70k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
41
        _query_ctx->set_first_error_msg(first_error_msg);
240
41
    }
241
242
6.70k
    _query_ctx->cancel(reason, _fragment_id);
243
6.70k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
475
        _is_report_on_cancel = false;
245
6.22k
    } else {
246
32.9k
        for (auto& id : _fragment_instance_ids) {
247
32.9k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
32.9k
        }
249
6.22k
    }
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
6.70k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.70k
    if (stream_load_ctx != nullptr) {
254
33
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
33
        stream_load_ctx->error_url = get_load_error_url();
259
33
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
33
    }
261
262
34.6k
    for (auto& tasks : _tasks) {
263
72.1k
        for (auto& task : tasks) {
264
72.1k
            task.first->unblock_all_dependencies();
265
72.1k
        }
266
34.6k
    }
267
6.70k
}
268
269
706k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
706k
    PipelineId id = _next_pipeline_id++;
271
706k
    auto pipeline = std::make_shared<Pipeline>(
272
706k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
706k
            parent ? parent->num_tasks() : _num_instances);
274
706k
    if (idx >= 0) {
275
111k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
595k
    } else {
277
595k
        _pipelines.emplace_back(pipeline);
278
595k
    }
279
706k
    if (parent) {
280
248k
        parent->set_children(pipeline);
281
248k
    }
282
706k
    return pipeline;
283
706k
}
284
285
450k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
450k
    {
287
450k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
450k
        auto root_pipeline = add_pipeline();
290
450k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
450k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
450k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
450k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
450k
                                          _params.fragment.output_exprs, _params,
299
450k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
450k
                                          *_desc_tbl, root_pipeline->id()));
301
450k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
450k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
594k
        for (PipelinePtr& pipeline : _pipelines) {
305
594k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
594k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
594k
        }
308
450k
    }
309
    // 4. Build local exchanger
310
450k
    if (_runtime_state->enable_local_shuffle()) {
311
446k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
446k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
446k
                                             _params.bucket_seq_to_instance_idx,
314
446k
                                             _params.shuffle_idx_to_instance_idx));
315
446k
    }
316
317
    // 5. Initialize global states in pipelines.
318
707k
    for (PipelinePtr& pipeline : _pipelines) {
319
707k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
707k
        pipeline->children().clear();
321
707k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
707k
    }
323
324
449k
    {
325
449k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
449k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
449k
    }
329
330
449k
    return Status::OK();
331
449k
}
332
333
451k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
451k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
451k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
450k
        _timeout = _params.query_options.execution_timeout;
339
450k
    }
340
341
451k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
451k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
451k
    SCOPED_TIMER(_prepare_timer);
344
451k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
451k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
451k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
451k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
451k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
451k
    {
350
451k
        SCOPED_TIMER(_init_context_timer);
351
451k
        cast_set(_num_instances, _params.local_params.size());
352
451k
        _total_instances =
353
451k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
451k
        auto* fragment_context = this;
356
357
451k
        if (_params.query_options.__isset.is_report_success) {
358
449k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
449k
        }
360
361
        // 1. Set up the global runtime state.
362
451k
        _runtime_state = RuntimeState::create_unique(
363
451k
                _params.query_id, _params.fragment_id, _params.query_options,
364
451k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
451k
        _runtime_state->set_task_execution_context(shared_from_this());
366
451k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
451k
        if (_params.__isset.backend_id) {
368
446k
            _runtime_state->set_backend_id(_params.backend_id);
369
446k
        }
370
451k
        if (_params.__isset.import_label) {
371
235
            _runtime_state->set_import_label(_params.import_label);
372
235
        }
373
451k
        if (_params.__isset.db_name) {
374
187
            _runtime_state->set_db_name(_params.db_name);
375
187
        }
376
451k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
451k
        if (_params.is_simplified_param) {
381
154k
            _desc_tbl = _query_ctx->desc_tbl;
382
296k
        } else {
383
296k
            DCHECK(_params.__isset.desc_tbl);
384
296k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
296k
                                                  &_desc_tbl));
386
296k
        }
387
451k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
451k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
451k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
451k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
451k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
451k
        const auto target_size = _params.local_params.size();
395
451k
        _fragment_instance_ids.resize(target_size);
396
1.68M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.23M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.23M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.23M
        }
400
451k
    }
401
402
451k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
449k
    _init_next_report_time();
405
406
449k
    _prepared = true;
407
449k
    return Status::OK();
408
451k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.22M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.22M
    const auto& local_params = _params.local_params[instance_idx];
414
1.22M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.22M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.22M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.22M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.22M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
2.03M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
2.03M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
2.03M
                                std::vector<std::shared_ptr<Dependency>>>>
422
2.03M
                shared_state_map;
423
2.61M
        for (auto& op : pipeline->operators()) {
424
2.61M
            auto source_id = op->operator_id();
425
2.61M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.61M
                iter != _op_id_to_shared_state.end()) {
427
805k
                shared_state_map.insert({source_id, iter->second});
428
805k
            }
429
2.61M
        }
430
2.03M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
2.03M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
2.03M
                iter != _op_id_to_shared_state.end()) {
433
316k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
316k
            }
435
2.03M
        }
436
2.03M
        return shared_state_map;
437
2.03M
    };
438
439
3.74M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.51M
        auto& pipeline = _pipelines[pip_idx];
441
2.51M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
2.02M
            auto task_runtime_state = RuntimeState::create_unique(
443
2.02M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
2.02M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
2.02M
            {
446
                // Initialize runtime state for this task
447
2.02M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
2.02M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
2.02M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
2.02M
                if (_params.__isset.backend_id) {
453
2.02M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
2.02M
                }
455
2.02M
                if (_params.__isset.import_label) {
456
236
                    task_runtime_state->set_import_label(_params.import_label);
457
236
                }
458
2.02M
                if (_params.__isset.db_name) {
459
188
                    task_runtime_state->set_db_name(_params.db_name);
460
188
                }
461
2.02M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
2.02M
                if (_params.__isset.wal_id) {
465
112
                    task_runtime_state->set_wal_id(_params.wal_id);
466
112
                }
467
2.02M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
2.02M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
2.02M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
2.02M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
2.02M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
2.02M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
2.02M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
2.02M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
2.02M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
2.02M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
2.02M
            }
482
2.02M
            auto cur_task_id = _total_tasks++;
483
2.02M
            task_runtime_state->set_task_id(cur_task_id);
484
2.02M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
2.02M
            auto task = std::make_shared<PipelineTask>(
486
2.02M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
2.02M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
2.02M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
2.02M
                    instance_idx);
490
2.02M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
2.02M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
2.02M
            _tasks[instance_idx].emplace_back(
493
2.02M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
2.02M
                            std::move(task), std::move(task_runtime_state)});
495
2.02M
        }
496
2.51M
    }
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
2.51M
    for (auto& _pipeline : _pipelines) {
516
2.51M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
2.02M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
2.02M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
2.02M
            if (_dag.contains(_pipeline->id())) {
522
1.28M
                auto& deps = _dag[_pipeline->id()];
523
2.06M
                for (auto& dep : deps) {
524
2.06M
                    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
468k
                            task->inject_shared_state(ss);
528
625k
                        } else {
529
625k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
625k
                                    task->get_source_shared_state());
531
625k
                        }
532
1.09M
                    }
533
2.06M
                }
534
1.28M
            }
535
2.02M
        }
536
2.51M
    }
537
3.74M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.51M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
2.02M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
2.02M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
2.02M
            std::vector<TScanRangeParams> scan_ranges;
542
2.02M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
2.02M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
336k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
336k
            }
546
2.02M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
2.02M
                                                             _params.fragment.output_sink));
548
2.02M
        }
549
2.51M
    }
550
1.23M
    {
551
1.23M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.23M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.23M
    }
554
1.23M
    return Status::OK();
555
1.22M
}
556
557
450k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
450k
    _total_tasks = 0;
559
450k
    _closed_tasks = 0;
560
450k
    const auto target_size = _params.local_params.size();
561
450k
    _tasks.resize(target_size);
562
450k
    _runtime_filter_mgr_map.resize(target_size);
563
1.15M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
706k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
706k
    }
566
450k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
450k
    if (target_size > 1 &&
569
450k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
136k
         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
12.3k
        std::vector<Status> prepare_status(target_size);
573
12.3k
        int submitted_tasks = 0;
574
12.3k
        Status submit_status;
575
12.3k
        CountDownLatch latch((int)target_size);
576
187k
        for (int i = 0; i < target_size; i++) {
577
175k
            submit_status = thread_pool->submit_func([&, i]() {
578
175k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
175k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
175k
                latch.count_down();
581
175k
            });
582
175k
            if (LIKELY(submit_status.ok())) {
583
175k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
175k
        }
588
12.3k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
12.3k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
187k
        for (int i = 0; i < submitted_tasks; i++) {
593
175k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
175k
        }
597
437k
    } else {
598
1.49M
        for (int i = 0; i < target_size; i++) {
599
1.05M
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
1.05M
        }
601
437k
    }
602
450k
    _pipeline_parent_map.clear();
603
450k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
450k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
450k
    return Status::OK();
608
450k
}
609
610
448k
void PipelineFragmentContext::_init_next_report_time() {
611
448k
    auto interval_s = config::pipeline_status_report_interval;
612
448k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
42.8k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.8k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
42.8k
        _previous_report_time =
617
42.8k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.8k
        _disable_period_report = false;
619
42.8k
    }
620
448k
}
621
622
4.89k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.89k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.89k
    DCHECK(disable == true);
625
4.89k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.89k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.89k
}
628
629
7.39M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.39M
    if (!_is_report_success) {
631
6.93M
        return;
632
6.93M
    }
633
454k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
454k
    if (disable) {
635
8.49k
        return;
636
8.49k
    }
637
445k
    int32_t interval_s = config::pipeline_status_report_interval;
638
445k
    if (interval_s <= 0) {
639
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
640
0
                        "trigger "
641
0
                        "report.";
642
0
    }
643
445k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
445k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
445k
    if (MonotonicNanos() > next_report_time) {
646
4.90k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.90k
                                                            std::memory_order_acq_rel)) {
648
6
            return;
649
6
        }
650
4.89k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
4.89k
        auto st = send_report(false);
667
4.89k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
4.89k
    }
673
445k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
447k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
447k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
447k
    int node_idx = 0;
682
683
447k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
447k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
447k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
687
0
        return Status::InternalError(
688
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
689
0
    }
690
447k
    return Status::OK();
691
447k
}
692
693
Status PipelineFragmentContext::_create_tree_helper(
694
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
695
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
696
700k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
700k
    if (*node_idx >= tnodes.size()) {
699
0
        return Status::InternalError(
700
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
701
0
                *node_idx, tnodes.size());
702
0
    }
703
700k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
700k
    int num_children = tnodes[*node_idx].num_children;
706
700k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
700k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
700k
    OperatorPtr op = nullptr;
710
700k
    OperatorPtr cache_op = nullptr;
711
700k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
700k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
700k
                                     followed_by_shuffled_operator,
714
700k
                                     current_require_bucket_distribution, cache_op));
715
    // Initialization must be done here. For example, group by expressions in agg will be used to
716
    // decide if a local shuffle should be planed, so it must be initialized here.
717
700k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
700k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
253k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
447k
    } else {
723
447k
        *root = op;
724
447k
    }
725
    /**
726
     * `ExchangeType::HASH_SHUFFLE` should be used if an operator is followed by a shuffled operator (shuffled hash join, union operator followed by co-located operators).
727
     *
728
     * For plan:
729
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
730
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
731
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
732
     *
733
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
734
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
735
     */
736
700k
    auto required_data_distribution =
737
700k
            cur_pipe->operators().empty()
738
700k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
700k
                    : op->required_data_distribution(_runtime_state.get());
740
700k
    current_followed_by_shuffled_operator =
741
700k
            ((followed_by_shuffled_operator ||
742
700k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
642k
                                             : op->is_shuffled_operator())) &&
744
700k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
700k
            (followed_by_shuffled_operator &&
746
588k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
700k
    current_require_bucket_distribution =
749
700k
            ((require_bucket_distribution ||
750
700k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
647k
                                             : op->is_colocated_operator())) &&
752
700k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
700k
            (require_bucket_distribution &&
754
595k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
700k
    if (num_children == 0) {
757
466k
        _use_serial_source = op->is_serial_operator();
758
466k
    }
759
    // rely on that tnodes is preorder of the plan
760
954k
    for (int i = 0; i < num_children; i++) {
761
253k
        ++*node_idx;
762
253k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
253k
                                            current_followed_by_shuffled_operator,
764
253k
                                            current_require_bucket_distribution));
765
766
        // we are expecting a child, but have used all nodes
767
        // this means we have been given a bad tree and must fail
768
253k
        if (*node_idx >= tnodes.size()) {
769
0
            return Status::InternalError(
770
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
771
0
                    "nodes: {}",
772
0
                    *node_idx, tnodes.size());
773
0
        }
774
253k
    }
775
776
700k
    return Status::OK();
777
700k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
111k
        PipelinePtr pipe_with_sink) {
782
111k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
111k
    pipe_with_source->set_num_tasks(_num_instances);
784
111k
    pipe_with_source->set_data_distribution(data_distribution);
785
111k
}
786
787
Status PipelineFragmentContext::_add_local_exchange_impl(
788
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
789
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
790
        const std::map<int, int>& bucket_seq_to_instance_idx,
791
111k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
111k
    auto& operators = cur_pipe->operators();
793
111k
    const auto downstream_pipeline_id = cur_pipe->id();
794
111k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
111k
    DataSinkOperatorPtr sink;
797
111k
    auto sink_id = next_sink_operator_id();
798
799
    /**
800
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
801
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
802
     */
803
111k
    const bool followed_by_shuffled_operator =
804
111k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
111k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
111k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
111k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
111k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
111k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
111k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
111k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
111k
    if (bucket_seq_to_instance_idx.empty() &&
813
111k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
9
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
9
    }
816
111k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
111k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
111k
                                          num_buckets, use_global_hash_shuffle,
819
111k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
111k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
111k
            LocalExchangeSharedState::create_shared(_num_instances);
824
111k
    switch (data_distribution.distribution_type) {
825
14.4k
    case ExchangeType::HASH_SHUFFLE:
826
14.4k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
14.4k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
14.4k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
14.4k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
14.4k
                        ? cast_set<int>(
831
14.4k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
14.4k
                        : 0);
833
14.4k
        break;
834
538
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
538
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
538
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
538
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
538
                        ? cast_set<int>(
839
538
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
538
                        : 0);
841
538
        break;
842
92.7k
    case ExchangeType::PASSTHROUGH:
843
92.7k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
92.7k
                cur_pipe->num_tasks(), _num_instances,
845
92.7k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
92.7k
                        ? cast_set<int>(
847
92.6k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
92.7k
                        : 0);
849
92.7k
        break;
850
402
    case ExchangeType::BROADCAST:
851
402
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
402
                cur_pipe->num_tasks(), _num_instances,
853
402
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
402
                        ? cast_set<int>(
855
402
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
402
                        : 0);
857
402
        break;
858
2.77k
    case ExchangeType::PASS_TO_ONE:
859
2.77k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
860
            // If shared hash table is enabled for BJ, hash table will be built by only one task
861
1.79k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.79k
                    cur_pipe->num_tasks(), _num_instances,
863
1.79k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.79k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.79k
                                                    .local_exchange_free_blocks_limit)
866
1.79k
                            : 0);
867
1.79k
        } else {
868
983
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
983
                    cur_pipe->num_tasks(), _num_instances,
870
983
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
983
                            ? cast_set<int>(_runtime_state->query_options()
872
983
                                                    .local_exchange_free_blocks_limit)
873
983
                            : 0);
874
983
        }
875
2.77k
        break;
876
918
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
918
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
918
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
918
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
918
                        ? cast_set<int>(
881
918
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
918
                        : 0);
883
918
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
111k
    }
888
111k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
111k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
111k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
111k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
892
893
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
894
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
895
896
    // 3.1 Initialize new pipeline's operator list.
897
111k
    std::copy(operators.begin(), operators.begin() + idx,
898
111k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
111k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
111k
    OperatorPtr source_op;
905
111k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
111k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
111k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
111k
    if (!operators.empty()) {
909
41.6k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
41.6k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
41.6k
    }
912
111k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
111k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
111k
    std::vector<PipelineId> edges_with_source;
917
130k
    for (auto child : cur_pipe->children()) {
918
130k
        bool found = false;
919
144k
        for (auto op : new_pip->operators()) {
920
144k
            if (child->sink()->node_id() == op->node_id()) {
921
12.9k
                new_pip->set_children(child);
922
12.9k
                found = true;
923
12.9k
            };
924
144k
        }
925
130k
        if (!found) {
926
117k
            new_children.push_back(child);
927
117k
            edges_with_source.push_back(child->id());
928
117k
        }
929
130k
    }
930
111k
    new_children.push_back(new_pip);
931
111k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
111k
    if (!new_pip->children().empty()) {
935
7.35k
        std::vector<PipelineId> edges_with_sink;
936
12.9k
        for (auto child : new_pip->children()) {
937
12.9k
            edges_with_sink.push_back(child->id());
938
12.9k
        }
939
7.35k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.35k
    }
941
111k
    cur_pipe->set_children(new_children);
942
111k
    _dag[downstream_pipeline_id] = edges_with_source;
943
111k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
111k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
111k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
111k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
111k
    return Status::OK();
950
111k
}
951
952
Status PipelineFragmentContext::_add_local_exchange(
953
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
954
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
955
        const std::map<int, int>& bucket_seq_to_instance_idx,
956
195k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
195k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
54.4k
        return Status::OK();
959
54.4k
    }
960
961
140k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
44.0k
        return Status::OK();
963
44.0k
    }
964
96.7k
    *do_local_exchange = true;
965
966
96.7k
    auto& operators = cur_pipe->operators();
967
96.7k
    auto total_op_num = operators.size();
968
96.7k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
96.7k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
96.7k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
96.7k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
18.4E
            << "total_op_num: " << total_op_num
975
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
96.8k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
96.7k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
14.9k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
14.9k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
14.9k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
14.9k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
14.9k
                shuffle_idx_to_instance_idx));
990
14.9k
    }
991
96.7k
    return Status::OK();
992
96.7k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
446k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.03M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
590k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
590k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
137k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
137k
                if (child->sink()->node_id() ==
1003
137k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
121k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
121k
                }
1006
137k
            }
1007
131k
        }
1008
1009
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1010
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1011
        // still keep colocate plan after local shuffle
1012
590k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
590k
                                             bucket_seq_to_instance_idx,
1014
590k
                                             shuffle_idx_to_instance_idx));
1015
590k
    }
1016
446k
    return Status::OK();
1017
446k
}
1018
1019
Status PipelineFragmentContext::_plan_local_exchange(
1020
        int num_buckets, int pip_idx, PipelinePtr pip,
1021
        const std::map<int, int>& bucket_seq_to_instance_idx,
1022
589k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
589k
    int idx = 1;
1024
589k
    bool do_local_exchange = false;
1025
631k
    do {
1026
631k
        auto& ops = pip->operators();
1027
631k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
706k
        for (; idx < ops.size();) {
1030
117k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
102k
                RETURN_IF_ERROR(_add_local_exchange(
1032
102k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
102k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
102k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
102k
                        shuffle_idx_to_instance_idx));
1036
102k
            }
1037
117k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
41.7k
                idx = 2;
1043
41.7k
                break;
1044
41.7k
            }
1045
75.2k
            idx++;
1046
75.2k
        }
1047
631k
    } while (do_local_exchange);
1048
589k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
92.2k
        RETURN_IF_ERROR(_add_local_exchange(
1050
92.2k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
92.2k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
92.2k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
92.2k
    }
1054
589k
    return Status::OK();
1055
589k
}
1056
1057
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1058
                                                  const std::vector<TExpr>& output_exprs,
1059
                                                  const TPipelineFragmentParams& params,
1060
                                                  const RowDescriptor& row_desc,
1061
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1062
450k
                                                  PipelineId cur_pipeline_id) {
1063
450k
    switch (thrift_sink.type) {
1064
152k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
152k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
152k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
152k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
152k
                params.destinations, _fragment_instance_ids);
1071
152k
        break;
1072
152k
    }
1073
257k
    case TDataSinkType::RESULT_SINK: {
1074
257k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
257k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
257k
        int child_node_id = pipeline->operators().back()->node_id();
1080
257k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
257k
                                                      row_desc, output_exprs,
1082
257k
                                                      thrift_sink.result_sink);
1083
257k
        break;
1084
257k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
33.6k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
33.6k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
33.6k
        int child_node_id = pipeline->operators().back()->node_id();
1098
33.6k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
33.6k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
33.6k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.79k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.79k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
30.8k
        } else {
1104
30.8k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
30.8k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
30.8k
        }
1107
33.6k
        break;
1108
0
    }
1109
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
165
        DCHECK(state->get_query_ctx() != nullptr);
1112
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
165
                                                                output_exprs);
1115
165
        break;
1116
0
    }
1117
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.46k
                                                         output_exprs);
1123
1.46k
        break;
1124
1.46k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
1.73k
        } else {
1133
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.73k
                                                                row_desc, output_exprs);
1135
1.73k
        }
1136
1.73k
        break;
1137
1.73k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
501
    case TDataSinkType::RESULT_FILE_SINK: {
1186
501
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
501
        } else {
1196
501
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
501
                                                              output_exprs);
1198
501
        }
1199
501
        break;
1200
501
    }
1201
2.47k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.47k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.47k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.47k
        auto sink_id = next_sink_operator_id();
1205
2.47k
        const int multi_cast_node_id = sink_id;
1206
2.47k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.47k
        std::vector<int> sources;
1209
9.71k
        for (int i = 0; i < sender_size; ++i) {
1210
7.23k
            auto source_id = next_operator_id();
1211
7.23k
            sources.push_back(source_id);
1212
7.23k
        }
1213
1214
2.47k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.47k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
9.71k
        for (int i = 0; i < sender_size; ++i) {
1217
7.23k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
7.23k
            RowDescriptor* exchange_row_desc = nullptr;
1220
7.23k
            {
1221
7.23k
                const auto& tmp_row_desc =
1222
7.23k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
7.23k
                                ? RowDescriptor(state->desc_tbl(),
1224
7.23k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
7.23k
                                                         .output_tuple_id})
1226
7.23k
                                : row_desc;
1227
7.23k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
7.23k
            }
1229
7.23k
            auto source_id = sources[i];
1230
7.23k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
7.23k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
7.23k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
7.23k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
7.23k
                    /*operator_id=*/source_id);
1236
7.23k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
7.23k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1238
            // 2. create and set sink operator of data stream sender for new pipeline
1239
1240
7.23k
            DataSinkOperatorPtr sink_op;
1241
7.23k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
7.23k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
7.23k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
7.23k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
7.23k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
7.23k
            {
1248
7.23k
                TDataSink* t = pool->add(new TDataSink());
1249
7.23k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
7.23k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
7.23k
            }
1252
1253
            // 3. set dependency dag
1254
7.23k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
7.23k
        }
1256
2.47k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.47k
        break;
1260
2.47k
    }
1261
2.47k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
13
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
13
        break;
1268
13
    }
1269
156
    case TDataSinkType::TVF_TABLE_SINK: {
1270
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
156
                                                        output_exprs);
1275
156
        break;
1276
156
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
450k
    }
1280
449k
    return Status::OK();
1281
450k
}
1282
1283
// NOLINTBEGIN(readability-function-size)
1284
// NOLINTBEGIN(readability-function-cognitive-complexity)
1285
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1286
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1287
                                                 PipelinePtr& cur_pipe, int parent_idx,
1288
                                                 int child_idx,
1289
                                                 const bool followed_by_shuffled_operator,
1290
                                                 const bool require_bucket_distribution,
1291
704k
                                                 OperatorPtr& cache_op) {
1292
704k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
704k
    Defer defer = Defer([&]() {
1294
703k
        if (op) {
1295
703k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
703k
        }
1297
703k
        for (auto& s : sink_ops) {
1298
136k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
136k
        }
1300
703k
    });
1301
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1302
    // Therefore, here we need to use a stack-like structure.
1303
704k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
704k
    std::stringstream error_msg;
1305
704k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
704k
    bool fe_with_old_version = false;
1308
704k
    switch (tnode.node_type) {
1309
218k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
218k
        op = std::make_shared<OlapScanOperatorX>(
1311
218k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
218k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
218k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
218k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
218k
        break;
1316
218k
    }
1317
76
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
76
        DCHECK(_query_ctx != nullptr);
1319
76
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
76
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
76
                                                    _num_instances);
1322
76
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
76
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
76
        break;
1325
76
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
25.2k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
25.2k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
25.2k
                                                 _num_instances);
1342
25.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
25.2k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
25.2k
        break;
1345
25.2k
    }
1346
157k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
157k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
157k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
157k
        DCHECK_GT(num_senders, 0);
1351
157k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
157k
                                                       num_senders);
1353
157k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
157k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
157k
        break;
1356
157k
    }
1357
168k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
168k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
168k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1360
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1361
0
                                         ": group by and output is empty");
1362
0
        }
1363
168k
        bool need_create_cache_op =
1364
168k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
168k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1366
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1367
10
            auto cache_source_id = next_operator_id();
1368
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1369
10
                                                        _params.fragment.query_cache_param);
1370
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1371
1372
10
            const auto downstream_pipeline_id = cur_pipe->id();
1373
10
            if (!_dag.contains(downstream_pipeline_id)) {
1374
10
                _dag.insert({downstream_pipeline_id, {}});
1375
10
            }
1376
10
            new_pipe = add_pipeline(cur_pipe);
1377
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1378
1379
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1380
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1381
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1382
10
            return Status::OK();
1383
10
        };
1384
168k
        const bool group_by_limit_opt =
1385
168k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1386
1387
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1388
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1389
168k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
168k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
168k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
168k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
168k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
168k
        const bool can_use_distinct_streaming_agg =
1396
168k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
168k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
168k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
168k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
168k
        if (can_use_distinct_streaming_agg) {
1402
91.9k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
91.9k
            } else {
1413
91.9k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
91.9k
                                                                     tnode, descs);
1415
91.9k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
91.9k
            }
1417
91.9k
        } else if (is_streaming_agg) {
1418
3.77k
            if (need_create_cache_op) {
1419
0
                PipelinePtr new_pipe;
1420
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1421
0
                cache_op = op;
1422
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
0
                                                             descs);
1424
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1425
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1426
0
                cur_pipe = new_pipe;
1427
3.77k
            } else {
1428
3.77k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
3.77k
                                                             descs);
1430
3.77k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
3.77k
            }
1432
72.7k
        } else {
1433
            // create new pipeline to add query cache operator
1434
72.7k
            PipelinePtr new_pipe;
1435
72.7k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
72.7k
            if (enable_spill) {
1441
270
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
270
                                                                     next_operator_id(), descs);
1443
72.4k
            } else {
1444
72.4k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
72.4k
            }
1446
72.7k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
72.7k
            } else {
1451
72.7k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
72.7k
            }
1453
1454
72.7k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
72.7k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
69.7k
                _dag.insert({downstream_pipeline_id, {}});
1457
69.7k
            }
1458
72.7k
            cur_pipe = add_pipeline(cur_pipe);
1459
72.7k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
72.7k
            if (enable_spill) {
1462
270
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
270
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
72.4k
            } else {
1465
72.4k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
72.4k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
72.4k
            }
1468
72.7k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
72.7k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
72.7k
        }
1471
168k
        break;
1472
168k
    }
1473
168k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
62
        if (tnode.bucketed_agg_node.grouping_exprs.empty()) {
1475
0
            return Status::InternalError(
1476
0
                    "Bucketed aggregation node {} should not be used without group by keys",
1477
0
                    tnode.node_id);
1478
0
        }
1479
1480
        // Create source operator (goes on the current / downstream pipeline).
1481
62
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
62
        const auto downstream_pipeline_id = cur_pipe->id();
1486
62
        if (!_dag.contains(downstream_pipeline_id)) {
1487
62
            _dag.insert({downstream_pipeline_id, {}});
1488
62
        }
1489
62
        cur_pipe = add_pipeline(cur_pipe);
1490
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
62
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1497
1498
        // Pre-register a single shared state for ALL instances so that every
1499
        // sink instance writes its per-instance hash table into the same
1500
        // BucketedAggSharedState and every source instance can merge across
1501
        // all of them.
1502
62
        {
1503
62
            auto shared_state = BucketedAggSharedState::create_shared();
1504
62
            shared_state->id = op->operator_id();
1505
62
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
423
            for (int i = 0; i < _num_instances; i++) {
1508
361
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
361
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
361
                sink_dep->set_shared_state(shared_state.get());
1511
361
                shared_state->sink_deps.push_back(sink_dep);
1512
361
            }
1513
62
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
62
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
62
            _op_id_to_shared_state.insert(
1516
62
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
62
        }
1518
62
        break;
1519
62
    }
1520
9.77k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.77k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.77k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.77k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.77k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
9.77k
        } else {
1566
9.77k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.77k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.77k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.77k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
8.08k
                _dag.insert({downstream_pipeline_id, {}});
1572
8.08k
            }
1573
9.77k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.77k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.77k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.77k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.77k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.77k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.77k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.77k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.77k
        }
1584
9.77k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
4.77k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
4.77k
                    HashJoinSharedState::create_shared(_num_instances);
1587
23.6k
            for (int i = 0; i < _num_instances; i++) {
1588
18.8k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
18.8k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
18.8k
                sink_dep->set_shared_state(shared_state.get());
1591
18.8k
                shared_state->sink_deps.push_back(sink_dep);
1592
18.8k
            }
1593
4.77k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
4.77k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
4.77k
            _op_id_to_shared_state.insert(
1596
4.77k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
4.77k
        }
1598
9.77k
        break;
1599
9.77k
    }
1600
5.91k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
5.91k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
5.91k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
5.91k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
5.91k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
5.68k
            _dag.insert({downstream_pipeline_id, {}});
1607
5.68k
        }
1608
5.91k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
5.91k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
5.91k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
5.91k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
5.91k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
5.91k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
5.91k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
5.91k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
5.91k
        break;
1618
5.91k
    }
1619
53.7k
    case TPlanNodeType::UNION_NODE: {
1620
53.7k
        int child_count = tnode.num_children;
1621
53.7k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
53.7k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
53.7k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
53.7k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
53.2k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.2k
        }
1628
55.1k
        for (int i = 0; i < child_count; i++) {
1629
1.40k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.40k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.40k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.40k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.40k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.40k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.40k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.40k
        }
1638
53.7k
        break;
1639
53.7k
    }
1640
53.7k
    case TPlanNodeType::SORT_NODE: {
1641
45.2k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
45.2k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
45.2k
        const bool use_local_merge =
1644
45.2k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
45.2k
        if (should_spill) {
1646
7
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
45.2k
        } else if (use_local_merge) {
1648
42.8k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
42.8k
                                                                 descs);
1650
42.8k
        } else {
1651
2.33k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.33k
        }
1653
45.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
45.2k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
45.2k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
45.1k
            _dag.insert({downstream_pipeline_id, {}});
1658
45.1k
        }
1659
45.2k
        cur_pipe = add_pipeline(cur_pipe);
1660
45.2k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
45.2k
        if (should_spill) {
1663
7
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
7
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
45.2k
        } else {
1666
45.2k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
45.2k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
45.2k
        }
1669
45.2k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
45.2k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
45.2k
        break;
1672
45.2k
    }
1673
45.2k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
63
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
63
        const auto downstream_pipeline_id = cur_pipe->id();
1678
63
        if (!_dag.contains(downstream_pipeline_id)) {
1679
63
            _dag.insert({downstream_pipeline_id, {}});
1680
63
        }
1681
63
        cur_pipe = add_pipeline(cur_pipe);
1682
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
63
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
63
        break;
1689
63
    }
1690
1.61k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.61k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.61k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.61k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.61k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.60k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.60k
        }
1698
1.61k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.61k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.61k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.61k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.61k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.61k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.61k
        break;
1706
1.61k
    }
1707
1.61k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.60k
        break;
1711
1.60k
    }
1712
1.60k
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
313
    case TPlanNodeType::REPEAT_NODE: {
1723
313
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
313
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
313
        break;
1726
313
    }
1727
914
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
914
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
914
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
914
        break;
1731
914
    }
1732
914
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
218
        break;
1736
218
    }
1737
1.67k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.67k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.67k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.67k
        break;
1741
1.67k
    }
1742
1.67k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
464
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
464
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
464
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
464
        break;
1747
464
    }
1748
2.06k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.06k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.06k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.06k
        break;
1752
2.06k
    }
1753
6.94k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.94k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.94k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.94k
        break;
1757
6.94k
    }
1758
6.94k
    case TPlanNodeType::SELECT_NODE: {
1759
2.47k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.47k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.47k
        break;
1762
2.47k
    }
1763
2.47k
    case TPlanNodeType::REC_CTE_NODE: {
1764
134
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
134
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
134
        const auto downstream_pipeline_id = cur_pipe->id();
1768
134
        if (!_dag.contains(downstream_pipeline_id)) {
1769
133
            _dag.insert({downstream_pipeline_id, {}});
1770
133
        }
1771
1772
134
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
134
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
134
        DataSinkOperatorPtr anchor_sink;
1776
134
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
134
                                                                  op->operator_id(), tnode, descs);
1778
134
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
134
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
134
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
134
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
134
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
134
        DataSinkOperatorPtr rec_sink;
1786
134
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
134
                                                         tnode, descs);
1788
134
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
134
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
134
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
134
        break;
1793
134
    }
1794
1.85k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.85k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.85k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.85k
        break;
1798
1.85k
    }
1799
1.85k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
704k
    }
1803
702k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1804
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1805
0
        op->set_serial_operator();
1806
0
    }
1807
1808
702k
    return Status::OK();
1809
704k
}
1810
// NOLINTEND(readability-function-cognitive-complexity)
1811
// NOLINTEND(readability-function-size)
1812
1813
template <bool is_intersect>
1814
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1815
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1816
267
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
267
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
267
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
267
    const auto downstream_pipeline_id = cur_pipe->id();
1821
267
    if (!_dag.contains(downstream_pipeline_id)) {
1822
242
        _dag.insert({downstream_pipeline_id, {}});
1823
242
    }
1824
1825
895
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
628
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
628
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
628
        if (child_id == 0) {
1830
267
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
267
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
361
        } else {
1833
361
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
361
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
361
        }
1836
628
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
628
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
628
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
628
    }
1841
1842
267
    return Status::OK();
1843
267
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
134
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
134
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
134
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
134
    const auto downstream_pipeline_id = cur_pipe->id();
1821
134
    if (!_dag.contains(downstream_pipeline_id)) {
1822
118
        _dag.insert({downstream_pipeline_id, {}});
1823
118
    }
1824
1825
481
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
347
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
347
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
347
        if (child_id == 0) {
1830
134
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
134
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
213
        } else {
1833
213
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
213
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
213
        }
1836
347
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
347
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
347
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
347
    }
1841
1842
134
    return Status::OK();
1843
134
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
133
    const auto downstream_pipeline_id = cur_pipe->id();
1821
133
    if (!_dag.contains(downstream_pipeline_id)) {
1822
124
        _dag.insert({downstream_pipeline_id, {}});
1823
124
    }
1824
1825
414
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
281
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
281
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
281
        if (child_id == 0) {
1830
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
148
        } else {
1833
148
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
148
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
148
        }
1836
281
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
281
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
281
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
281
    }
1841
1842
133
    return Status::OK();
1843
133
}
1844
1845
448k
Status PipelineFragmentContext::submit() {
1846
448k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
448k
    _submitted = true;
1850
1851
448k
    int submit_tasks = 0;
1852
448k
    Status st;
1853
448k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.23M
    for (auto& task : _tasks) {
1855
2.03M
        for (auto& t : task) {
1856
2.03M
            st = scheduler->submit(t.first);
1857
2.03M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
2.03M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
2.03M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
2.03M
            submit_tasks++;
1866
2.03M
        }
1867
1.23M
    }
1868
448k
    if (!st.ok()) {
1869
0
        bool need_remove = false;
1870
0
        {
1871
0
            std::lock_guard<std::mutex> l(_task_mutex);
1872
0
            if (_closed_tasks >= _total_tasks) {
1873
0
                need_remove = _close_fragment_instance();
1874
0
            }
1875
0
        }
1876
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1877
0
        if (need_remove) {
1878
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1879
0
        }
1880
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1881
0
                                     BackendOptions::get_localhost());
1882
448k
    } else {
1883
448k
        return st;
1884
448k
    }
1885
448k
}
1886
1887
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1888
0
    if (_runtime_state->enable_profile()) {
1889
0
        std::stringstream ss;
1890
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1891
0
            runtime_profile_ptr->pretty_print(&ss);
1892
0
        }
1893
1894
0
        if (_runtime_state->load_channel_profile()) {
1895
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1896
0
        }
1897
1898
0
        auto profile_str =
1899
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1900
0
                            this->_fragment_id, extra_info, ss.str());
1901
0
        LOG_LONG_STRING(INFO, profile_str);
1902
0
    }
1903
0
}
1904
// If all pipeline tasks binded to the fragment instance are finished, then we could
1905
// close the fragment instance.
1906
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1907
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1908
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1909
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1910
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1911
// (via debug_string()).
1912
450k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
450k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
450k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
450k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
450k
    if (!_need_notify_close) {
1919
447k
        auto st = send_report(true);
1920
447k
        if (!st) {
1921
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1922
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1923
0
        }
1924
447k
    }
1925
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1926
    // Since stream load does not have someting like coordinator on FE, so
1927
    // backend can not report profile to FE, ant its profile can not be shown
1928
    // in the same way with other query. So we print the profile content to info log.
1929
1930
450k
    if (_runtime_state->enable_profile() &&
1931
450k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.86k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.86k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1934
0
        std::stringstream ss;
1935
        // Compute the _local_time_percent before pretty_print the runtime_profile
1936
        // Before add this operation, the print out like that:
1937
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1938
        // After add the operation, the print out like that:
1939
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1940
        // We can easily know the exec node execute time without child time consumed.
1941
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1942
0
            runtime_profile_ptr->pretty_print(&ss);
1943
0
        }
1944
1945
0
        if (_runtime_state->load_channel_profile()) {
1946
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1947
0
        }
1948
1949
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1950
0
    }
1951
1952
450k
    if (_query_ctx->enable_profile()) {
1953
2.86k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.86k
                                         collect_realtime_load_channel_profile());
1955
2.86k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
450k
    return !_need_notify_close;
1960
450k
}
1961
1962
2.02M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
2.02M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
2.02M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
706k
        if (_dag.contains(pipeline_id)) {
1967
368k
            for (auto dep : _dag[pipeline_id]) {
1968
368k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
368k
            }
1970
298k
        }
1971
706k
    }
1972
2.02M
    bool need_remove = false;
1973
2.02M
    {
1974
2.02M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
2.02M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
2.02M
        _query_ctx->inc_finished_task_num();
1978
2.02M
        if (_closed_tasks >= _total_tasks) {
1979
450k
            need_remove = _close_fragment_instance();
1980
450k
        }
1981
2.02M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
2.02M
    if (need_remove) {
1984
447k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
447k
    }
1986
2.02M
}
1987
1988
55.9k
std::string PipelineFragmentContext::get_load_error_url() {
1989
55.9k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1990
0
        return to_load_error_http_path(str);
1991
0
    }
1992
144k
    for (auto& tasks : _tasks) {
1993
221k
        for (auto& task : tasks) {
1994
221k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
195
                return to_load_error_http_path(str);
1996
195
            }
1997
221k
        }
1998
144k
    }
1999
55.7k
    return "";
2000
55.9k
}
2001
2002
55.9k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
55.9k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
143k
    for (auto& tasks : _tasks) {
2007
221k
        for (auto& task : tasks) {
2008
221k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
195
                return str;
2010
195
            }
2011
221k
        }
2012
143k
    }
2013
55.7k
    return "";
2014
55.9k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
49.2k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
49.2k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
49.2k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
49.2k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
49.2k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
49.2k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
49.2k
    });
2031
2032
49.2k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
49.2k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
49.2k
    int callback_retries = 10;
2038
49.2k
    const int sleep_ms = 1000;
2039
49.2k
    Status exec_status = req.status;
2040
49.2k
    Status coord_status;
2041
49.2k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
49.2k
    do {
2043
49.2k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
49.2k
                                                            req.coord_addr, &coord_status);
2045
49.2k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
49.2k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
49.2k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
49.2k
    TReportExecStatusParams params;
2059
49.2k
    params.protocol_version = FrontendServiceVersion::V1;
2060
49.2k
    params.__set_query_id(req.query_id);
2061
49.2k
    params.__set_backend_num(req.backend_num);
2062
49.2k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
49.2k
    params.__set_fragment_id(req.fragment_id);
2064
49.2k
    params.__set_status(exec_status.to_thrift());
2065
49.2k
    params.__set_done(req.done);
2066
49.2k
    params.__set_query_type(req.runtime_state->query_type());
2067
49.2k
    params.__isset.profile = false;
2068
2069
49.2k
    DCHECK(req.runtime_state != nullptr);
2070
2071
49.2k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
44.2k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
44.2k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
44.2k
    } else {
2075
5.02k
        DCHECK(!req.runtime_states.empty());
2076
5.02k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
5.02k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
5.02k
    }
2086
2087
49.2k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
49.2k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
49.2k
    static std::string s_unselected_rows = "unselected.rows";
2090
49.2k
    int64_t num_rows_load_success = 0;
2091
49.2k
    int64_t num_rows_load_filtered = 0;
2092
49.2k
    int64_t num_rows_load_unselected = 0;
2093
49.2k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
49.2k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
49.2k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
49.2k
    } else if (!req.runtime_states.empty()) {
2109
149k
        for (auto* rs : req.runtime_states) {
2110
149k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
149k
                rs->num_finished_range() > 0) {
2112
37.0k
                params.__isset.load_counters = true;
2113
37.0k
                num_rows_load_success += rs->num_rows_load_success();
2114
37.0k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
37.0k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
37.0k
                params.__isset.fragment_instance_reports = true;
2117
37.0k
                TFragmentInstanceReport t;
2118
37.0k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
37.0k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
37.0k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
37.0k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
37.0k
                params.fragment_instance_reports.push_back(t);
2123
37.0k
            }
2124
149k
        }
2125
49.2k
    }
2126
49.2k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
49.2k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
49.2k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
49.2k
    if (!req.load_error_url.empty()) {
2131
161
        params.__set_tracking_url(req.load_error_url);
2132
161
    }
2133
49.2k
    if (!req.first_error_msg.empty()) {
2134
161
        params.__set_first_error_msg(req.first_error_msg);
2135
161
    }
2136
149k
    for (auto* rs : req.runtime_states) {
2137
149k
        if (rs->wal_id() > 0) {
2138
110
            params.__set_txn_id(rs->wal_id());
2139
110
            params.__set_label(rs->import_label());
2140
110
        }
2141
149k
    }
2142
49.2k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
49.2k
    } else if (!req.runtime_states.empty()) {
2146
149k
        for (auto* rs : req.runtime_states) {
2147
149k
            if (!rs->export_output_files().empty()) {
2148
0
                params.__isset.export_files = true;
2149
0
                params.export_files.insert(params.export_files.end(),
2150
0
                                           rs->export_output_files().begin(),
2151
0
                                           rs->export_output_files().end());
2152
0
            }
2153
149k
        }
2154
49.2k
    }
2155
49.2k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
49.2k
    } else if (!req.runtime_states.empty()) {
2159
149k
        for (auto* rs : req.runtime_states) {
2160
149k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
27.7k
                params.__isset.commitInfos = true;
2162
27.7k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
27.7k
            }
2164
149k
        }
2165
49.2k
    }
2166
49.2k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
49.2k
    } else if (!req.runtime_states.empty()) {
2170
149k
        for (auto* rs : req.runtime_states) {
2171
149k
            if (auto rs_eti = rs->error_tablet_infos(); !rs_eti.empty()) {
2172
0
                params.__isset.errorTabletInfos = true;
2173
0
                params.errorTabletInfos.insert(params.errorTabletInfos.end(), rs_eti.begin(),
2174
0
                                               rs_eti.end());
2175
0
            }
2176
149k
        }
2177
49.2k
    }
2178
49.2k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
49.2k
    } else if (!req.runtime_states.empty()) {
2183
149k
        for (auto* rs : req.runtime_states) {
2184
149k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.12k
                params.__isset.hive_partition_updates = true;
2186
2.12k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.12k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.12k
            }
2189
149k
        }
2190
49.2k
    }
2191
49.2k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
49.2k
    } else if (!req.runtime_states.empty()) {
2196
149k
        for (auto* rs : req.runtime_states) {
2197
149k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.07k
                params.__isset.iceberg_commit_datas = true;
2199
2.07k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.07k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.07k
            }
2202
149k
        }
2203
49.2k
    }
2204
2205
49.2k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
49.2k
    } else if (!req.runtime_states.empty()) {
2209
149k
        for (auto* rs : req.runtime_states) {
2210
149k
            if (auto rs_mcd = rs->mc_commit_datas(); !rs_mcd.empty()) {
2211
0
                params.__isset.mc_commit_datas = true;
2212
0
                params.mc_commit_datas.insert(params.mc_commit_datas.end(), rs_mcd.begin(),
2213
0
                                              rs_mcd.end());
2214
0
            }
2215
149k
        }
2216
49.2k
    }
2217
2218
49.2k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
49.2k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
49.2k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
49.2k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
49.2k
    }
2224
2225
49.2k
    TReportExecStatusResult res;
2226
49.2k
    Status rpc_status;
2227
2228
49.2k
    VLOG_DEBUG << "reportExecStatus params is "
2229
7
               << apache::thrift::ThriftDebugString(params).c_str();
2230
49.2k
    if (!exec_status.ok()) {
2231
1.70k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.70k
                     << " to coordinator: " << req.coord_addr
2233
1.70k
                     << ", query id: " << print_id(req.query_id);
2234
1.70k
    }
2235
49.2k
    try {
2236
49.2k
        try {
2237
49.2k
            (*coord)->reportExecStatus(res, params);
2238
49.2k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
49.2k
        rpc_status = Status::create<false>(res.status);
2254
49.2k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
49.2k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
49.2k
}
2265
2266
452k
Status PipelineFragmentContext::send_report(bool done) {
2267
452k
    Status exec_status = _query_ctx->exec_status();
2268
    // If plan is done successfully, but _is_report_success is false,
2269
    // no need to send report.
2270
    // Load will set _is_report_success to true because load wants to know
2271
    // the process.
2272
452k
    if (!_is_report_success && done && exec_status.ok()) {
2273
402k
        return Status::OK();
2274
402k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
49.5k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
378
        if (done) {
2284
            // if done is true, which means the query is finished successfully, we can safely close the fragment instance without sending report to FE, and just return OK status here.
2285
378
            return Status::OK();
2286
378
        }
2287
0
        return Status::NeedSendAgain("");
2288
378
    }
2289
2290
49.2k
    std::vector<RuntimeState*> runtime_states;
2291
2292
109k
    for (auto& tasks : _tasks) {
2293
149k
        for (auto& task : tasks) {
2294
149k
            runtime_states.push_back(task.second.get());
2295
149k
        }
2296
109k
    }
2297
2298
49.2k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
49.2k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
49.2k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
49.2k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
49.2k
    ReportStatusRequest req {.status = exec_status,
2306
49.2k
                             .runtime_states = runtime_states,
2307
49.2k
                             .done = done || !exec_status.ok(),
2308
49.2k
                             .coord_addr = _query_ctx->coord_addr,
2309
49.2k
                             .query_id = _query_id,
2310
49.2k
                             .fragment_id = _fragment_id,
2311
49.2k
                             .fragment_instance_id = TUniqueId(),
2312
49.2k
                             .backend_num = -1,
2313
49.2k
                             .runtime_state = _runtime_state.get(),
2314
49.2k
                             .load_error_url = load_eror_url,
2315
49.2k
                             .first_error_msg = first_error_msg,
2316
49.2k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
49.2k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
49.2k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
49.2k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
49.2k
        _coordinator_callback(req);
2321
49.2k
        if (!req.done) {
2322
4.89k
            ctx->refresh_next_report_time();
2323
4.89k
        }
2324
49.2k
    });
2325
49.5k
}
2326
2327
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
0
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
0
    for (const auto& task_instances : _tasks) {
2332
0
        for (const auto& task : task_instances) {
2333
0
            if (task.first->is_running()) {
2334
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2335
0
                                      << " is running, task: " << (void*)task.first.get()
2336
0
                                      << ", is_running: " << task.first->is_running();
2337
0
                *has_running_task = true;
2338
0
                return 0;
2339
0
            }
2340
2341
0
            size_t revocable_size = task.first->get_revocable_size();
2342
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
0
                res += revocable_size;
2344
0
            }
2345
0
        }
2346
0
    }
2347
0
    return res;
2348
0
}
2349
2350
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
0
    std::vector<PipelineTask*> revocable_tasks;
2352
0
    for (const auto& task_instances : _tasks) {
2353
0
        for (const auto& task : task_instances) {
2354
0
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
0
                revocable_tasks.emplace_back(task.first.get());
2358
0
            }
2359
0
        }
2360
0
    }
2361
0
    return revocable_tasks;
2362
0
}
2363
2364
90
std::string PipelineFragmentContext::debug_string() {
2365
90
    std::lock_guard<std::mutex> l(_task_mutex);
2366
90
    fmt::memory_buffer debug_string_buffer;
2367
90
    fmt::format_to(debug_string_buffer,
2368
90
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
90
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
90
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
529
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
439
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
1.25k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
813
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
813
                           _tasks[j][i].first->debug_string());
2376
813
        }
2377
439
    }
2378
2379
90
    return fmt::to_string(debug_string_buffer);
2380
90
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.86k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.86k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2385
2386
    // we do not have mutex to protect pipeline_id_to_profile
2387
    // so we need to make sure this funciton is invoked after fragment context
2388
    // has already been prepared.
2389
2.86k
    if (!_prepared) {
2390
0
        std::string msg =
2391
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2392
0
        DCHECK(false) << msg;
2393
0
        LOG_ERROR(msg);
2394
0
        return res;
2395
0
    }
2396
2397
    // Make sure first profile is fragment level profile
2398
2.86k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.86k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.86k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
5.21k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
5.21k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
5.21k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
5.21k
        res.push_back(profile_ptr);
2407
5.21k
    }
2408
2409
2.86k
    return res;
2410
2.86k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.86k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2414
    // we do not have mutex to protect pipeline_id_to_profile
2415
    // so we need to make sure this funciton is invoked after fragment context
2416
    // has already been prepared.
2417
2.86k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
7.70k
    for (const auto& tasks : _tasks) {
2426
15.2k
        for (const auto& task : tasks) {
2427
15.2k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
15.2k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
15.2k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
15.2k
                                                           _runtime_state->profile_level());
2435
15.2k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
15.2k
        }
2437
7.70k
    }
2438
2439
2.86k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.86k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.86k
                                                      _runtime_state->profile_level());
2442
2.86k
    return load_channel_profile;
2443
2.86k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.18k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.18k
    std::set<int> result;
2454
8.64k
    for (const auto& _task : _tasks) {
2455
14.8k
        for (const auto& task : _task) {
2456
14.8k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
14.8k
            result.merge(set);
2458
14.8k
        }
2459
8.64k
    }
2460
3.18k
    if (_runtime_state) {
2461
3.18k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.18k
        result.merge(set);
2463
3.18k
    }
2464
3.18k
    return result;
2465
3.18k
}
2466
2467
451k
void PipelineFragmentContext::_release_resource() {
2468
451k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
451k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
451k
    auto st = _query_ctx->exec_status();
2472
1.23M
    for (auto& _task : _tasks) {
2473
1.23M
        if (!_task.empty()) {
2474
1.23M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.23M
        }
2476
1.23M
    }
2477
451k
    _tasks.clear();
2478
451k
    _dag.clear();
2479
451k
    _pip_id_to_pipeline.clear();
2480
451k
    _pipelines.clear();
2481
451k
    _sink.reset();
2482
451k
    _root_op.reset();
2483
451k
    _runtime_filter_mgr_map.clear();
2484
451k
    _op_id_to_shared_state.clear();
2485
451k
}
2486
2487
} // namespace doris