Coverage Report

Created: 2026-04-15 12:22

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/PaloInternalService_types.h>
22
#include <gen_cpp/PlanNodes_types.h>
23
#include <pthread.h>
24
25
#include <algorithm>
26
#include <cstdlib>
27
// IWYU pragma: no_include <bits/chrono.h>
28
#include <fmt/format.h>
29
30
#include <chrono> // IWYU pragma: keep
31
#include <map>
32
#include <memory>
33
#include <ostream>
34
#include <utility>
35
36
#include "cloud/config.h"
37
#include "common/cast_set.h"
38
#include "common/config.h"
39
#include "common/exception.h"
40
#include "common/logging.h"
41
#include "common/status.h"
42
#include "exec/exchange/local_exchange_sink_operator.h"
43
#include "exec/exchange/local_exchange_source_operator.h"
44
#include "exec/exchange/local_exchanger.h"
45
#include "exec/exchange/vdata_stream_mgr.h"
46
#include "exec/operator/aggregation_sink_operator.h"
47
#include "exec/operator/aggregation_source_operator.h"
48
#include "exec/operator/analytic_sink_operator.h"
49
#include "exec/operator/analytic_source_operator.h"
50
#include "exec/operator/assert_num_rows_operator.h"
51
#include "exec/operator/blackhole_sink_operator.h"
52
#include "exec/operator/cache_sink_operator.h"
53
#include "exec/operator/cache_source_operator.h"
54
#include "exec/operator/datagen_operator.h"
55
#include "exec/operator/dict_sink_operator.h"
56
#include "exec/operator/distinct_streaming_aggregation_operator.h"
57
#include "exec/operator/empty_set_operator.h"
58
#include "exec/operator/es_scan_operator.h"
59
#include "exec/operator/exchange_sink_operator.h"
60
#include "exec/operator/exchange_source_operator.h"
61
#include "exec/operator/file_scan_operator.h"
62
#include "exec/operator/group_commit_block_sink_operator.h"
63
#include "exec/operator/group_commit_scan_operator.h"
64
#include "exec/operator/hashjoin_build_sink.h"
65
#include "exec/operator/hashjoin_probe_operator.h"
66
#include "exec/operator/hive_table_sink_operator.h"
67
#include "exec/operator/iceberg_delete_sink_operator.h"
68
#include "exec/operator/iceberg_merge_sink_operator.h"
69
#include "exec/operator/iceberg_table_sink_operator.h"
70
#include "exec/operator/jdbc_scan_operator.h"
71
#include "exec/operator/jdbc_table_sink_operator.h"
72
#include "exec/operator/local_merge_sort_source_operator.h"
73
#include "exec/operator/materialization_opertor.h"
74
#include "exec/operator/maxcompute_table_sink_operator.h"
75
#include "exec/operator/memory_scratch_sink_operator.h"
76
#include "exec/operator/meta_scan_operator.h"
77
#include "exec/operator/multi_cast_data_stream_sink.h"
78
#include "exec/operator/multi_cast_data_stream_source.h"
79
#include "exec/operator/nested_loop_join_build_operator.h"
80
#include "exec/operator/nested_loop_join_probe_operator.h"
81
#include "exec/operator/olap_scan_operator.h"
82
#include "exec/operator/olap_table_sink_operator.h"
83
#include "exec/operator/olap_table_sink_v2_operator.h"
84
#include "exec/operator/partition_sort_sink_operator.h"
85
#include "exec/operator/partition_sort_source_operator.h"
86
#include "exec/operator/partitioned_aggregation_sink_operator.h"
87
#include "exec/operator/partitioned_aggregation_source_operator.h"
88
#include "exec/operator/partitioned_hash_join_probe_operator.h"
89
#include "exec/operator/partitioned_hash_join_sink_operator.h"
90
#include "exec/operator/rec_cte_anchor_sink_operator.h"
91
#include "exec/operator/rec_cte_scan_operator.h"
92
#include "exec/operator/rec_cte_sink_operator.h"
93
#include "exec/operator/rec_cte_source_operator.h"
94
#include "exec/operator/repeat_operator.h"
95
#include "exec/operator/result_file_sink_operator.h"
96
#include "exec/operator/result_sink_operator.h"
97
#include "exec/operator/schema_scan_operator.h"
98
#include "exec/operator/select_operator.h"
99
#include "exec/operator/set_probe_sink_operator.h"
100
#include "exec/operator/set_sink_operator.h"
101
#include "exec/operator/set_source_operator.h"
102
#include "exec/operator/sort_sink_operator.h"
103
#include "exec/operator/sort_source_operator.h"
104
#include "exec/operator/spill_iceberg_table_sink_operator.h"
105
#include "exec/operator/spill_sort_sink_operator.h"
106
#include "exec/operator/spill_sort_source_operator.h"
107
#include "exec/operator/streaming_aggregation_operator.h"
108
#include "exec/operator/table_function_operator.h"
109
#include "exec/operator/tvf_table_sink_operator.h"
110
#include "exec/operator/union_sink_operator.h"
111
#include "exec/operator/union_source_operator.h"
112
#include "exec/pipeline/dependency.h"
113
#include "exec/pipeline/pipeline_task.h"
114
#include "exec/pipeline/task_scheduler.h"
115
#include "exec/runtime_filter/runtime_filter_mgr.h"
116
#include "exec/sort/topn_sorter.h"
117
#include "exec/spill/spill_file.h"
118
#include "io/fs/stream_load_pipe.h"
119
#include "load/stream_load/new_load_stream_mgr.h"
120
#include "runtime/exec_env.h"
121
#include "runtime/fragment_mgr.h"
122
#include "runtime/result_buffer_mgr.h"
123
#include "runtime/runtime_state.h"
124
#include "runtime/thread_context.h"
125
#include "util/countdown_latch.h"
126
#include "util/debug_util.h"
127
#include "util/uid_util.h"
128
129
namespace doris {
130
PipelineFragmentContext::PipelineFragmentContext(
131
        TUniqueId query_id, const TPipelineFragmentParams& request,
132
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
133
        const std::function<void(RuntimeState*, Status*)>& call_back,
134
        report_status_callback report_status_cb)
135
434k
        : _query_id(std::move(query_id)),
136
434k
          _fragment_id(request.fragment_id),
137
434k
          _exec_env(exec_env),
138
434k
          _query_ctx(std::move(query_ctx)),
139
434k
          _call_back(call_back),
140
434k
          _is_report_on_cancel(true),
141
434k
          _report_status_cb(std::move(report_status_cb)),
142
434k
          _params(request),
143
434k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
144
434k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
145
434k
                                                               : false) {
146
434k
    _fragment_watcher.start();
147
434k
}
148
149
435k
PipelineFragmentContext::~PipelineFragmentContext() {
150
435k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
151
435k
            .tag("query_id", print_id(_query_id))
152
435k
            .tag("fragment_id", _fragment_id);
153
435k
    _release_resource();
154
435k
    {
155
        // The memory released by the query end is recorded in the query mem tracker.
156
435k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
157
435k
        _runtime_state.reset();
158
435k
        _query_ctx.reset();
159
435k
    }
160
435k
}
161
162
276
bool PipelineFragmentContext::is_timeout(timespec now) const {
163
276
    if (_timeout <= 0) {
164
0
        return false;
165
0
    }
166
276
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
167
276
}
168
169
// notify_close() transitions the PFC from "waiting for external close notification" to
170
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
171
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
173
9.43k
bool PipelineFragmentContext::notify_close() {
174
9.43k
    bool all_closed = false;
175
9.43k
    bool need_remove = false;
176
9.43k
    {
177
9.43k
        std::lock_guard<std::mutex> l(_task_mutex);
178
9.43k
        if (_closed_tasks >= _total_tasks) {
179
3.52k
            if (_need_notify_close) {
180
                // Fragment was cancelled and waiting for notify to close.
181
                // Record that we need to remove from fragment mgr, but do it
182
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
184
                // first, then _task_mutex via debug_string()).
185
3.42k
                need_remove = true;
186
3.42k
            }
187
3.52k
            all_closed = true;
188
3.52k
        }
189
        // make fragment release by self after cancel
190
9.43k
        _need_notify_close = false;
191
9.43k
    }
192
9.43k
    if (need_remove) {
193
3.42k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
194
3.42k
    }
195
9.43k
    return all_closed;
196
9.43k
}
197
198
// Must not add lock in this method. Because it will call query ctx cancel. And
199
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
200
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
202
5.95k
void PipelineFragmentContext::cancel(const Status reason) {
203
5.95k
    LOG_INFO("PipelineFragmentContext::cancel")
204
5.95k
            .tag("query_id", print_id(_query_id))
205
5.95k
            .tag("fragment_id", _fragment_id)
206
5.95k
            .tag("reason", reason.to_string());
207
5.95k
    if (notify_close()) {
208
120
        return;
209
120
    }
210
    // Timeout is a special error code, we need print current stack to debug timeout issue.
211
5.83k
    if (reason.is<ErrorCode::TIMEOUT>()) {
212
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
213
1
                                   debug_string());
214
1
        LOG_LONG_STRING(WARNING, dbg_str);
215
1
    }
216
217
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
218
5.83k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
219
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
220
0
                    debug_string());
221
0
    }
222
223
5.83k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
224
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
225
0
    }
226
227
5.83k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
228
22
        _query_ctx->set_load_error_url(error_url);
229
22
    }
230
231
5.83k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
232
22
        _query_ctx->set_first_error_msg(first_error_msg);
233
22
    }
234
235
5.83k
    _query_ctx->cancel(reason, _fragment_id);
236
5.83k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
237
660
        _is_report_on_cancel = false;
238
5.17k
    } else {
239
20.3k
        for (auto& id : _fragment_instance_ids) {
240
20.3k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
241
20.3k
        }
242
5.17k
    }
243
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
244
    // For stream load the fragment's query_id == load id, it is set in FE.
245
5.83k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
246
5.83k
    if (stream_load_ctx != nullptr) {
247
30
        stream_load_ctx->pipe->cancel(reason.to_string());
248
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
249
        // We need to set the error URL at this point to ensure error information is properly
250
        // propagated to the client.
251
30
        stream_load_ctx->error_url = get_load_error_url();
252
30
        stream_load_ctx->first_error_msg = get_first_error_msg();
253
30
    }
254
255
22.1k
    for (auto& tasks : _tasks) {
256
47.2k
        for (auto& task : tasks) {
257
47.2k
            task.first->unblock_all_dependencies();
258
47.2k
        }
259
22.1k
    }
260
5.83k
}
261
262
676k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
263
676k
    PipelineId id = _next_pipeline_id++;
264
676k
    auto pipeline = std::make_shared<Pipeline>(
265
676k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
266
676k
            parent ? parent->num_tasks() : _num_instances);
267
676k
    if (idx >= 0) {
268
112k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
269
564k
    } else {
270
564k
        _pipelines.emplace_back(pipeline);
271
564k
    }
272
676k
    if (parent) {
273
237k
        parent->set_children(pipeline);
274
237k
    }
275
676k
    return pipeline;
276
676k
}
277
278
434k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
279
434k
    {
280
434k
        SCOPED_TIMER(_build_pipelines_timer);
281
        // 2. Build pipelines with operators in this fragment.
282
434k
        auto root_pipeline = add_pipeline();
283
434k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
284
434k
                                         &_root_op, root_pipeline));
285
286
        // 3. Create sink operator
287
434k
        if (!_params.fragment.__isset.output_sink) {
288
0
            return Status::InternalError("No output sink in this fragment!");
289
0
        }
290
434k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
291
434k
                                          _params.fragment.output_exprs, _params,
292
434k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
293
434k
                                          *_desc_tbl, root_pipeline->id()));
294
434k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
295
434k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
296
297
564k
        for (PipelinePtr& pipeline : _pipelines) {
298
18.4E
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
299
564k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
300
564k
        }
301
434k
    }
302
    // 4. Build local exchanger
303
434k
    if (_runtime_state->enable_local_shuffle()) {
304
432k
        SCOPED_TIMER(_plan_local_exchanger_timer);
305
432k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
306
432k
                                             _params.bucket_seq_to_instance_idx,
307
432k
                                             _params.shuffle_idx_to_instance_idx));
308
432k
    }
309
310
    // 5. Initialize global states in pipelines.
311
678k
    for (PipelinePtr& pipeline : _pipelines) {
312
678k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
313
678k
        pipeline->children().clear();
314
678k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
315
678k
    }
316
317
432k
    {
318
432k
        SCOPED_TIMER(_build_tasks_timer);
319
        // 6. Build pipeline tasks and initialize local state.
320
432k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
321
432k
    }
322
323
432k
    return Status::OK();
324
432k
}
325
326
434k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
327
434k
    if (_prepared) {
328
0
        return Status::InternalError("Already prepared");
329
0
    }
330
434k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
331
434k
        _timeout = _params.query_options.execution_timeout;
332
434k
    }
333
334
434k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
335
434k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
336
434k
    SCOPED_TIMER(_prepare_timer);
337
434k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
338
434k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
339
434k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
340
434k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
341
434k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
342
434k
    {
343
434k
        SCOPED_TIMER(_init_context_timer);
344
434k
        cast_set(_num_instances, _params.local_params.size());
345
434k
        _total_instances =
346
434k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
347
348
434k
        auto* fragment_context = this;
349
350
434k
        if (_params.query_options.__isset.is_report_success) {
351
432k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
352
432k
        }
353
354
        // 1. Set up the global runtime state.
355
434k
        _runtime_state = RuntimeState::create_unique(
356
434k
                _params.query_id, _params.fragment_id, _params.query_options,
357
434k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
358
434k
        _runtime_state->set_task_execution_context(shared_from_this());
359
434k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
360
434k
        if (_params.__isset.backend_id) {
361
431k
            _runtime_state->set_backend_id(_params.backend_id);
362
431k
        }
363
434k
        if (_params.__isset.import_label) {
364
241
            _runtime_state->set_import_label(_params.import_label);
365
241
        }
366
434k
        if (_params.__isset.db_name) {
367
193
            _runtime_state->set_db_name(_params.db_name);
368
193
        }
369
434k
        if (_params.__isset.load_job_id) {
370
0
            _runtime_state->set_load_job_id(_params.load_job_id);
371
0
        }
372
373
434k
        if (_params.is_simplified_param) {
374
147k
            _desc_tbl = _query_ctx->desc_tbl;
375
287k
        } else {
376
287k
            DCHECK(_params.__isset.desc_tbl);
377
287k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
378
287k
                                                  &_desc_tbl));
379
287k
        }
380
434k
        _runtime_state->set_desc_tbl(_desc_tbl);
381
434k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
382
434k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
383
434k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
384
434k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
385
386
        // init fragment_instance_ids
387
434k
        const auto target_size = _params.local_params.size();
388
434k
        _fragment_instance_ids.resize(target_size);
389
1.63M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
390
1.19M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
391
1.19M
            _fragment_instance_ids[i] = fragment_instance_id;
392
1.19M
        }
393
434k
    }
394
395
434k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
396
397
433k
    _init_next_report_time();
398
399
433k
    _prepared = true;
400
433k
    return Status::OK();
401
434k
}
402
403
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
404
        int instance_idx,
405
1.19M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
406
1.19M
    const auto& local_params = _params.local_params[instance_idx];
407
1.19M
    auto fragment_instance_id = local_params.fragment_instance_id;
408
1.19M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
409
1.19M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
410
1.19M
    auto get_shared_state = [&](PipelinePtr pipeline)
411
1.19M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
412
1.99M
                                       std::vector<std::shared_ptr<Dependency>>>> {
413
1.99M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
414
1.99M
                                std::vector<std::shared_ptr<Dependency>>>>
415
1.99M
                shared_state_map;
416
2.59M
        for (auto& op : pipeline->operators()) {
417
2.59M
            auto source_id = op->operator_id();
418
2.59M
            if (auto iter = _op_id_to_shared_state.find(source_id);
419
2.59M
                iter != _op_id_to_shared_state.end()) {
420
742k
                shared_state_map.insert({source_id, iter->second});
421
742k
            }
422
2.59M
        }
423
1.99M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
424
1.99M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
425
1.99M
                iter != _op_id_to_shared_state.end()) {
426
289k
                shared_state_map.insert({sink_to_source_id, iter->second});
427
289k
            }
428
1.99M
        }
429
1.99M
        return shared_state_map;
430
1.99M
    };
431
432
3.64M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
433
2.44M
        auto& pipeline = _pipelines[pip_idx];
434
2.44M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
435
1.98M
            auto task_runtime_state = RuntimeState::create_unique(
436
1.98M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
437
1.98M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
438
1.98M
            {
439
                // Initialize runtime state for this task
440
1.98M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
441
442
1.98M
                task_runtime_state->set_task_execution_context(shared_from_this());
443
1.98M
                task_runtime_state->set_be_number(local_params.backend_num);
444
445
1.99M
                if (_params.__isset.backend_id) {
446
1.99M
                    task_runtime_state->set_backend_id(_params.backend_id);
447
1.99M
                }
448
1.98M
                if (_params.__isset.import_label) {
449
242
                    task_runtime_state->set_import_label(_params.import_label);
450
242
                }
451
1.98M
                if (_params.__isset.db_name) {
452
194
                    task_runtime_state->set_db_name(_params.db_name);
453
194
                }
454
1.98M
                if (_params.__isset.load_job_id) {
455
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
456
0
                }
457
1.98M
                if (_params.__isset.wal_id) {
458
114
                    task_runtime_state->set_wal_id(_params.wal_id);
459
114
                }
460
1.98M
                if (_params.__isset.content_length) {
461
31
                    task_runtime_state->set_content_length(_params.content_length);
462
31
                }
463
464
1.98M
                task_runtime_state->set_desc_tbl(_desc_tbl);
465
1.98M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
466
1.98M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
467
1.98M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
468
1.98M
                task_runtime_state->set_max_operator_id(max_operator_id());
469
1.98M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
470
1.98M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
471
1.98M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
472
473
1.98M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
474
1.98M
            }
475
1.98M
            auto cur_task_id = _total_tasks++;
476
1.98M
            task_runtime_state->set_task_id(cur_task_id);
477
1.98M
            task_runtime_state->set_task_num(pipeline->num_tasks());
478
1.98M
            auto task = std::make_shared<PipelineTask>(
479
1.98M
                    pipeline, cur_task_id, task_runtime_state.get(),
480
1.98M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
481
1.98M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
482
1.98M
                    instance_idx);
483
1.98M
            pipeline->incr_created_tasks(instance_idx, task.get());
484
1.98M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
485
1.98M
            _tasks[instance_idx].emplace_back(
486
1.98M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
487
1.98M
                            std::move(task), std::move(task_runtime_state)});
488
1.98M
        }
489
2.44M
    }
490
491
    /**
492
         * Build DAG for pipeline tasks.
493
         * For example, we have
494
         *
495
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
496
         *            \                      /
497
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
498
         *                 \                          /
499
         *               JoinProbeOperator2 (Pipeline1)
500
         *
501
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
502
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
503
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
504
         *
505
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
506
         * and JoinProbeOperator2.
507
         */
508
2.44M
    for (auto& _pipeline : _pipelines) {
509
2.44M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
510
1.98M
            auto* task = pipeline_id_to_task[_pipeline->id()];
511
1.98M
            DCHECK(task != nullptr);
512
513
            // If this task has upstream dependency, then inject it into this task.
514
1.98M
            if (_dag.contains(_pipeline->id())) {
515
1.24M
                auto& deps = _dag[_pipeline->id()];
516
1.96M
                for (auto& dep : deps) {
517
1.96M
                    if (pipeline_id_to_task.contains(dep)) {
518
1.06M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
519
1.06M
                        if (ss) {
520
494k
                            task->inject_shared_state(ss);
521
569k
                        } else {
522
569k
                            pipeline_id_to_task[dep]->inject_shared_state(
523
569k
                                    task->get_source_shared_state());
524
569k
                        }
525
1.06M
                    }
526
1.96M
                }
527
1.24M
            }
528
1.98M
        }
529
2.44M
    }
530
3.64M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
531
2.44M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
532
1.98M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
533
1.98M
            DCHECK(pipeline_id_to_profile[pip_idx]);
534
1.98M
            std::vector<TScanRangeParams> scan_ranges;
535
1.98M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
536
1.98M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
537
351k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
538
351k
            }
539
1.98M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
540
1.98M
                                                             _params.fragment.output_sink));
541
1.98M
        }
542
2.44M
    }
543
1.20M
    {
544
1.20M
        std::lock_guard<std::mutex> l(_state_map_lock);
545
1.20M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
546
1.20M
    }
547
1.20M
    return Status::OK();
548
1.19M
}
549
550
433k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
551
433k
    _total_tasks = 0;
552
433k
    _closed_tasks = 0;
553
433k
    const auto target_size = _params.local_params.size();
554
433k
    _tasks.resize(target_size);
555
433k
    _runtime_filter_mgr_map.resize(target_size);
556
1.11M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
557
676k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
558
676k
    }
559
433k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
560
561
433k
    if (target_size > 1 &&
562
433k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
563
149k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
564
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
565
32.1k
        std::vector<Status> prepare_status(target_size);
566
32.1k
        int submitted_tasks = 0;
567
32.1k
        Status submit_status;
568
32.1k
        CountDownLatch latch((int)target_size);
569
318k
        for (int i = 0; i < target_size; i++) {
570
285k
            submit_status = thread_pool->submit_func([&, i]() {
571
285k
                SCOPED_ATTACH_TASK(_query_ctx.get());
572
285k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
573
285k
                latch.count_down();
574
285k
            });
575
285k
            if (LIKELY(submit_status.ok())) {
576
285k
                submitted_tasks++;
577
18.4E
            } else {
578
18.4E
                break;
579
18.4E
            }
580
285k
        }
581
32.1k
        latch.arrive_and_wait(target_size - submitted_tasks);
582
32.1k
        if (UNLIKELY(!submit_status.ok())) {
583
0
            return submit_status;
584
0
        }
585
318k
        for (int i = 0; i < submitted_tasks; i++) {
586
285k
            if (!prepare_status[i].ok()) {
587
0
                return prepare_status[i];
588
0
            }
589
285k
        }
590
401k
    } else {
591
1.31M
        for (int i = 0; i < target_size; i++) {
592
914k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
593
914k
        }
594
401k
    }
595
433k
    _pipeline_parent_map.clear();
596
433k
    _op_id_to_shared_state.clear();
597
598
433k
    return Status::OK();
599
433k
}
600
601
432k
void PipelineFragmentContext::_init_next_report_time() {
602
432k
    auto interval_s = config::pipeline_status_report_interval;
603
432k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
604
41.2k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
605
41.2k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
606
        // We don't want to wait longer than it takes to run the entire fragment.
607
41.2k
        _previous_report_time =
608
41.2k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
609
41.2k
        _disable_period_report = false;
610
41.2k
    }
611
432k
}
612
613
4.84k
void PipelineFragmentContext::refresh_next_report_time() {
614
4.84k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
615
4.84k
    DCHECK(disable == true);
616
4.84k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
617
4.84k
    _disable_period_report.compare_exchange_strong(disable, false);
618
4.84k
}
619
620
7.26M
void PipelineFragmentContext::trigger_report_if_necessary() {
621
7.26M
    if (!_is_report_success) {
622
6.75M
        return;
623
6.75M
    }
624
508k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
625
508k
    if (disable) {
626
8.14k
        return;
627
8.14k
    }
628
500k
    int32_t interval_s = config::pipeline_status_report_interval;
629
500k
    if (interval_s <= 0) {
630
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
631
0
                        "trigger "
632
0
                        "report.";
633
0
    }
634
500k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
635
500k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
636
500k
    if (MonotonicNanos() > next_report_time) {
637
4.84k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
638
4.84k
                                                            std::memory_order_acq_rel)) {
639
8
            return;
640
8
        }
641
4.84k
        if (VLOG_FILE_IS_ON) {
642
0
            VLOG_FILE << "Reporting "
643
0
                      << "profile for query_id " << print_id(_query_id)
644
0
                      << ", fragment id: " << _fragment_id;
645
646
0
            std::stringstream ss;
647
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
648
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
649
0
            if (_runtime_state->load_channel_profile()) {
650
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
651
0
            }
652
653
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
654
0
                      << " profile:\n"
655
0
                      << ss.str();
656
0
        }
657
4.84k
        auto st = send_report(false);
658
4.84k
        if (!st.ok()) {
659
0
            disable = true;
660
0
            _disable_period_report.compare_exchange_strong(disable, false,
661
0
                                                           std::memory_order_acq_rel);
662
0
        }
663
4.84k
    }
664
500k
}
665
666
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
667
431k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
668
431k
    if (_params.fragment.plan.nodes.empty()) {
669
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
670
0
    }
671
672
431k
    int node_idx = 0;
673
674
431k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
675
431k
                                        &node_idx, root, cur_pipe, 0, false, false));
676
677
431k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
678
0
        return Status::InternalError(
679
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
680
0
    }
681
431k
    return Status::OK();
682
431k
}
683
684
Status PipelineFragmentContext::_create_tree_helper(
685
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
686
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
687
669k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
688
    // propagate error case
689
669k
    if (*node_idx >= tnodes.size()) {
690
0
        return Status::InternalError(
691
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
692
0
                *node_idx, tnodes.size());
693
0
    }
694
669k
    const TPlanNode& tnode = tnodes[*node_idx];
695
696
669k
    int num_children = tnodes[*node_idx].num_children;
697
669k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
698
669k
    bool current_require_bucket_distribution = require_bucket_distribution;
699
    // TODO: Create CacheOperator is confused now
700
669k
    OperatorPtr op = nullptr;
701
669k
    OperatorPtr cache_op = nullptr;
702
669k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
703
669k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
704
669k
                                     followed_by_shuffled_operator,
705
669k
                                     current_require_bucket_distribution, cache_op));
706
    // Initialization must be done here. For example, group by expressions in agg will be used to
707
    // decide if a local shuffle should be planed, so it must be initialized here.
708
669k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
709
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
710
669k
    if (parent != nullptr) {
711
        // add to parent's child(s)
712
238k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
713
430k
    } else {
714
430k
        *root = op;
715
430k
    }
716
    /**
717
     * `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).
718
     *
719
     * For plan:
720
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
721
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
722
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
723
     *
724
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
725
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
726
     */
727
669k
    auto required_data_distribution =
728
669k
            cur_pipe->operators().empty()
729
669k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
730
669k
                    : op->required_data_distribution(_runtime_state.get());
731
669k
    current_followed_by_shuffled_operator =
732
669k
            ((followed_by_shuffled_operator ||
733
669k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
734
612k
                                             : op->is_shuffled_operator())) &&
735
669k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
736
669k
            (followed_by_shuffled_operator &&
737
560k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
738
739
669k
    current_require_bucket_distribution =
740
669k
            ((require_bucket_distribution ||
741
669k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
742
616k
                                             : op->is_colocated_operator())) &&
743
669k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
744
669k
            (require_bucket_distribution &&
745
566k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
746
747
669k
    if (num_children == 0) {
748
449k
        _use_serial_source = op->is_serial_operator();
749
449k
    }
750
    // rely on that tnodes is preorder of the plan
751
908k
    for (int i = 0; i < num_children; i++) {
752
238k
        ++*node_idx;
753
238k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
754
238k
                                            current_followed_by_shuffled_operator,
755
238k
                                            current_require_bucket_distribution));
756
757
        // we are expecting a child, but have used all nodes
758
        // this means we have been given a bad tree and must fail
759
238k
        if (*node_idx >= tnodes.size()) {
760
0
            return Status::InternalError(
761
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
762
0
                    "nodes: {}",
763
0
                    *node_idx, tnodes.size());
764
0
        }
765
238k
    }
766
767
669k
    return Status::OK();
768
669k
}
769
770
void PipelineFragmentContext::_inherit_pipeline_properties(
771
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
772
112k
        PipelinePtr pipe_with_sink) {
773
112k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
774
112k
    pipe_with_source->set_num_tasks(_num_instances);
775
112k
    pipe_with_source->set_data_distribution(data_distribution);
776
112k
}
777
778
Status PipelineFragmentContext::_add_local_exchange_impl(
779
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
780
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
781
        const std::map<int, int>& bucket_seq_to_instance_idx,
782
112k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
783
112k
    auto& operators = cur_pipe->operators();
784
112k
    const auto downstream_pipeline_id = cur_pipe->id();
785
112k
    auto local_exchange_id = next_operator_id();
786
    // 1. Create a new pipeline with local exchange sink.
787
112k
    DataSinkOperatorPtr sink;
788
112k
    auto sink_id = next_sink_operator_id();
789
790
    /**
791
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
792
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
793
     */
794
112k
    const bool followed_by_shuffled_operator =
795
112k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
796
112k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
797
112k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
798
112k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
799
112k
                                         followed_by_shuffled_operator && !_use_serial_source;
800
112k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
801
112k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
802
112k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
803
112k
    if (bucket_seq_to_instance_idx.empty() &&
804
112k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
805
37
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
806
37
    }
807
112k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
808
112k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
809
112k
                                          num_buckets, use_global_hash_shuffle,
810
112k
                                          shuffle_idx_to_instance_idx));
811
812
    // 2. Create and initialize LocalExchangeSharedState.
813
112k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
814
112k
            LocalExchangeSharedState::create_shared(_num_instances);
815
112k
    switch (data_distribution.distribution_type) {
816
9.16k
    case ExchangeType::HASH_SHUFFLE:
817
9.16k
        shared_state->exchanger = ShuffleExchanger::create_unique(
818
9.16k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
819
9.16k
                use_global_hash_shuffle ? _total_instances : _num_instances,
820
9.16k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
821
9.16k
                        ? cast_set<int>(
822
9.15k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
823
9.16k
                        : 0);
824
9.16k
        break;
825
542
    case ExchangeType::BUCKET_HASH_SHUFFLE:
826
542
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
827
542
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
828
542
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
829
542
                        ? cast_set<int>(
830
542
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
831
542
                        : 0);
832
542
        break;
833
98.6k
    case ExchangeType::PASSTHROUGH:
834
98.6k
        shared_state->exchanger = PassthroughExchanger::create_unique(
835
98.6k
                cur_pipe->num_tasks(), _num_instances,
836
98.6k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
837
98.6k
                        ? cast_set<int>(
838
98.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
839
98.6k
                        : 0);
840
98.6k
        break;
841
381
    case ExchangeType::BROADCAST:
842
381
        shared_state->exchanger = BroadcastExchanger::create_unique(
843
381
                cur_pipe->num_tasks(), _num_instances,
844
381
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
845
381
                        ? cast_set<int>(
846
381
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
847
381
                        : 0);
848
381
        break;
849
2.56k
    case ExchangeType::PASS_TO_ONE:
850
2.56k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
851
            // If shared hash table is enabled for BJ, hash table will be built by only one task
852
1.42k
            shared_state->exchanger = PassToOneExchanger::create_unique(
853
1.42k
                    cur_pipe->num_tasks(), _num_instances,
854
1.42k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
855
1.42k
                            ? cast_set<int>(_runtime_state->query_options()
856
1.42k
                                                    .local_exchange_free_blocks_limit)
857
1.42k
                            : 0);
858
1.42k
        } else {
859
1.13k
            shared_state->exchanger = BroadcastExchanger::create_unique(
860
1.13k
                    cur_pipe->num_tasks(), _num_instances,
861
1.13k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
862
1.13k
                            ? cast_set<int>(_runtime_state->query_options()
863
1.13k
                                                    .local_exchange_free_blocks_limit)
864
1.13k
                            : 0);
865
1.13k
        }
866
2.56k
        break;
867
902
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
868
902
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
869
902
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
870
902
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
902
                        ? cast_set<int>(
872
902
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
873
902
                        : 0);
874
902
        break;
875
0
    default:
876
0
        return Status::InternalError("Unsupported local exchange type : " +
877
0
                                     std::to_string((int)data_distribution.distribution_type));
878
112k
    }
879
112k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
880
112k
                                             "LOCAL_EXCHANGE_OPERATOR");
881
112k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
882
112k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
883
884
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
885
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
886
887
    // 3.1 Initialize new pipeline's operator list.
888
112k
    std::copy(operators.begin(), operators.begin() + idx,
889
112k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
890
891
    // 3.2 Erase unused operators in previous pipeline.
892
112k
    operators.erase(operators.begin(), operators.begin() + idx);
893
894
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
895
112k
    OperatorPtr source_op;
896
112k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
897
112k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
898
112k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
899
112k
    if (!operators.empty()) {
900
49.8k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
901
49.8k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
902
49.8k
    }
903
112k
    operators.insert(operators.begin(), source_op);
904
905
    // 5. Set children for two pipelines separately.
906
112k
    std::vector<std::shared_ptr<Pipeline>> new_children;
907
112k
    std::vector<PipelineId> edges_with_source;
908
130k
    for (auto child : cur_pipe->children()) {
909
130k
        bool found = false;
910
145k
        for (auto op : new_pip->operators()) {
911
145k
            if (child->sink()->node_id() == op->node_id()) {
912
12.8k
                new_pip->set_children(child);
913
12.8k
                found = true;
914
12.8k
            };
915
145k
        }
916
130k
        if (!found) {
917
117k
            new_children.push_back(child);
918
117k
            edges_with_source.push_back(child->id());
919
117k
        }
920
130k
    }
921
112k
    new_children.push_back(new_pip);
922
112k
    edges_with_source.push_back(new_pip->id());
923
924
    // 6. Set DAG for new pipelines.
925
112k
    if (!new_pip->children().empty()) {
926
7.46k
        std::vector<PipelineId> edges_with_sink;
927
12.8k
        for (auto child : new_pip->children()) {
928
12.8k
            edges_with_sink.push_back(child->id());
929
12.8k
        }
930
7.46k
        _dag.insert({new_pip->id(), edges_with_sink});
931
7.46k
    }
932
112k
    cur_pipe->set_children(new_children);
933
112k
    _dag[downstream_pipeline_id] = edges_with_source;
934
112k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
935
112k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
936
112k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
937
938
    // 7. Inherit properties from current pipeline.
939
112k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
940
112k
    return Status::OK();
941
112k
}
942
943
Status PipelineFragmentContext::_add_local_exchange(
944
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
945
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
946
        const std::map<int, int>& bucket_seq_to_instance_idx,
947
193k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
948
193k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
949
37.3k
        return Status::OK();
950
37.3k
    }
951
952
156k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
953
52.9k
        return Status::OK();
954
52.9k
    }
955
103k
    *do_local_exchange = true;
956
957
103k
    auto& operators = cur_pipe->operators();
958
103k
    auto total_op_num = operators.size();
959
103k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
960
103k
    RETURN_IF_ERROR(_add_local_exchange_impl(
961
103k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
962
103k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
963
964
103k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
965
482
            << "total_op_num: " << total_op_num
966
482
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
967
482
            << " new_pip->operators().size(): " << new_pip->operators().size();
968
969
    // There are some local shuffles with relatively heavy operations on the sink.
970
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
971
    // Therefore, local passthrough is used to increase the concurrency of the sink.
972
    // op -> local sink(1) -> local source (n)
973
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
974
103k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
975
103k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
976
9.61k
        RETURN_IF_ERROR(_add_local_exchange_impl(
977
9.61k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
978
9.61k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
979
9.61k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
980
9.61k
                shuffle_idx_to_instance_idx));
981
9.61k
    }
982
103k
    return Status::OK();
983
103k
}
984
985
Status PipelineFragmentContext::_plan_local_exchange(
986
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
987
430k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
988
993k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
989
562k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
990
        // Set property if child pipeline is not join operator's child.
991
562k
        if (!_pipelines[pip_idx]->children().empty()) {
992
125k
            for (auto& child : _pipelines[pip_idx]->children()) {
993
125k
                if (child->sink()->node_id() ==
994
125k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
995
110k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
996
110k
                }
997
125k
            }
998
120k
        }
999
1000
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1001
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1002
        // still keep colocate plan after local shuffle
1003
562k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1004
562k
                                             bucket_seq_to_instance_idx,
1005
562k
                                             shuffle_idx_to_instance_idx));
1006
562k
    }
1007
430k
    return Status::OK();
1008
430k
}
1009
1010
Status PipelineFragmentContext::_plan_local_exchange(
1011
        int num_buckets, int pip_idx, PipelinePtr pip,
1012
        const std::map<int, int>& bucket_seq_to_instance_idx,
1013
561k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1014
561k
    int idx = 1;
1015
561k
    bool do_local_exchange = false;
1016
612k
    do {
1017
612k
        auto& ops = pip->operators();
1018
612k
        do_local_exchange = false;
1019
        // Plan local exchange for each operator.
1020
676k
        for (; idx < ops.size();) {
1021
114k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1022
107k
                RETURN_IF_ERROR(_add_local_exchange(
1023
107k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1024
107k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1025
107k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1026
107k
                        shuffle_idx_to_instance_idx));
1027
107k
            }
1028
114k
            if (do_local_exchange) {
1029
                // If local exchange is needed for current operator, we will split this pipeline to
1030
                // two pipelines by local exchange sink/source. And then we need to process remaining
1031
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1032
                // is current operator was already processed) and continue to plan local exchange.
1033
50.0k
                idx = 2;
1034
50.0k
                break;
1035
50.0k
            }
1036
64.2k
            idx++;
1037
64.2k
        }
1038
612k
    } while (do_local_exchange);
1039
561k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1040
85.4k
        RETURN_IF_ERROR(_add_local_exchange(
1041
85.4k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1042
85.4k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1043
85.4k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1044
85.4k
    }
1045
561k
    return Status::OK();
1046
561k
}
1047
1048
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1049
                                                  const std::vector<TExpr>& output_exprs,
1050
                                                  const TPipelineFragmentParams& params,
1051
                                                  const RowDescriptor& row_desc,
1052
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1053
433k
                                                  PipelineId cur_pipeline_id) {
1054
433k
    switch (thrift_sink.type) {
1055
145k
    case TDataSinkType::DATA_STREAM_SINK: {
1056
145k
        if (!thrift_sink.__isset.stream_sink) {
1057
0
            return Status::InternalError("Missing data stream sink.");
1058
0
        }
1059
145k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1060
145k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1061
145k
                params.destinations, _fragment_instance_ids);
1062
145k
        break;
1063
145k
    }
1064
251k
    case TDataSinkType::RESULT_SINK: {
1065
251k
        if (!thrift_sink.__isset.result_sink) {
1066
0
            return Status::InternalError("Missing data buffer sink.");
1067
0
        }
1068
1069
251k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), row_desc,
1070
251k
                                                      output_exprs, thrift_sink.result_sink);
1071
251k
        break;
1072
251k
    }
1073
104
    case TDataSinkType::DICTIONARY_SINK: {
1074
104
        if (!thrift_sink.__isset.dictionary_sink) {
1075
0
            return Status::InternalError("Missing dict sink.");
1076
0
        }
1077
1078
104
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1079
104
                                                    thrift_sink.dictionary_sink);
1080
104
        break;
1081
104
    }
1082
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1083
31.1k
    case TDataSinkType::OLAP_TABLE_SINK: {
1084
31.1k
        if (state->query_options().enable_memtable_on_sink_node &&
1085
31.1k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1086
31.1k
            !config::is_cloud_mode()) {
1087
2.08k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(pool, next_sink_operator_id(),
1088
2.08k
                                                               row_desc, output_exprs);
1089
29.0k
        } else {
1090
29.0k
            _sink = std::make_shared<OlapTableSinkOperatorX>(pool, next_sink_operator_id(),
1091
29.0k
                                                             row_desc, output_exprs);
1092
29.0k
        }
1093
31.1k
        break;
1094
0
    }
1095
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1096
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1097
165
        DCHECK(state->get_query_ctx() != nullptr);
1098
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1099
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1100
165
                                                                output_exprs);
1101
165
        break;
1102
0
    }
1103
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1104
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1105
0
            return Status::InternalError("Missing hive table sink.");
1106
0
        }
1107
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1108
1.46k
                                                         output_exprs);
1109
1.46k
        break;
1110
1.46k
    }
1111
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1112
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1113
0
            return Status::InternalError("Missing iceberg table sink.");
1114
0
        }
1115
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1116
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1117
0
                                                                     row_desc, output_exprs);
1118
1.73k
        } else {
1119
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1120
1.73k
                                                                row_desc, output_exprs);
1121
1.73k
        }
1122
1.73k
        break;
1123
1.73k
    }
1124
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1125
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1126
0
            return Status::InternalError("Missing iceberg delete sink.");
1127
0
        }
1128
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1129
20
                                                             row_desc, output_exprs);
1130
20
        break;
1131
20
    }
1132
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1133
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1134
0
            return Status::InternalError("Missing iceberg merge sink.");
1135
0
        }
1136
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1137
80
                                                            output_exprs);
1138
80
        break;
1139
80
    }
1140
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1141
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1142
0
            return Status::InternalError("Missing max compute table sink.");
1143
0
        }
1144
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1145
0
                                                       output_exprs);
1146
0
        break;
1147
0
    }
1148
80
    case TDataSinkType::JDBC_TABLE_SINK: {
1149
80
        if (!thrift_sink.__isset.jdbc_table_sink) {
1150
0
            return Status::InternalError("Missing data jdbc sink.");
1151
0
        }
1152
80
        if (config::enable_java_support) {
1153
80
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1154
80
                                                             output_exprs);
1155
80
        } else {
1156
0
            return Status::InternalError(
1157
0
                    "Jdbc table sink is not enabled, you can change be config "
1158
0
                    "enable_java_support to true and restart be.");
1159
0
        }
1160
80
        break;
1161
80
    }
1162
80
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1163
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1164
0
            return Status::InternalError("Missing data buffer sink.");
1165
0
        }
1166
1167
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
3
                                                             output_exprs);
1169
3
        break;
1170
3
    }
1171
502
    case TDataSinkType::RESULT_FILE_SINK: {
1172
502
        if (!thrift_sink.__isset.result_file_sink) {
1173
0
            return Status::InternalError("Missing result file sink.");
1174
0
        }
1175
1176
        // Result file sink is not the top sink
1177
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1178
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1179
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1180
0
                    params.destinations, output_exprs, desc_tbl);
1181
502
        } else {
1182
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1183
502
                                                              output_exprs);
1184
502
        }
1185
502
        break;
1186
502
    }
1187
1.92k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1188
1.92k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1189
1.92k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1190
1.92k
        auto sink_id = next_sink_operator_id();
1191
1.92k
        const int multi_cast_node_id = sink_id;
1192
1.92k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1193
        // one sink has multiple sources.
1194
1.92k
        std::vector<int> sources;
1195
7.49k
        for (int i = 0; i < sender_size; ++i) {
1196
5.56k
            auto source_id = next_operator_id();
1197
5.56k
            sources.push_back(source_id);
1198
5.56k
        }
1199
1200
1.92k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1201
1.92k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1202
7.49k
        for (int i = 0; i < sender_size; ++i) {
1203
5.56k
            auto new_pipeline = add_pipeline();
1204
            // use to exchange sink
1205
5.56k
            RowDescriptor* exchange_row_desc = nullptr;
1206
5.56k
            {
1207
5.56k
                const auto& tmp_row_desc =
1208
5.56k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1209
5.56k
                                ? RowDescriptor(state->desc_tbl(),
1210
5.56k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1211
5.56k
                                                         .output_tuple_id})
1212
5.56k
                                : row_desc;
1213
5.56k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1214
5.56k
            }
1215
5.56k
            auto source_id = sources[i];
1216
5.56k
            OperatorPtr source_op;
1217
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1218
5.56k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1219
5.56k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1220
5.56k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1221
5.56k
                    /*operator_id=*/source_id);
1222
5.56k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1223
5.56k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1224
            // 2. create and set sink operator of data stream sender for new pipeline
1225
1226
5.56k
            DataSinkOperatorPtr sink_op;
1227
5.56k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1228
5.56k
                    state, *exchange_row_desc, next_sink_operator_id(),
1229
5.56k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1230
5.56k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1231
1232
5.56k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1233
5.56k
            {
1234
5.56k
                TDataSink* t = pool->add(new TDataSink());
1235
5.56k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1236
5.56k
                RETURN_IF_ERROR(sink_op->init(*t));
1237
5.56k
            }
1238
1239
            // 3. set dependency dag
1240
5.56k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1241
5.56k
        }
1242
1.92k
        if (sources.empty()) {
1243
0
            return Status::InternalError("size of sources must be greater than 0");
1244
0
        }
1245
1.92k
        break;
1246
1.92k
    }
1247
1.92k
    case TDataSinkType::BLACKHOLE_SINK: {
1248
13
        if (!thrift_sink.__isset.blackhole_sink) {
1249
0
            return Status::InternalError("Missing blackhole sink.");
1250
0
        }
1251
1252
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1253
13
        break;
1254
13
    }
1255
156
    case TDataSinkType::TVF_TABLE_SINK: {
1256
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1257
0
            return Status::InternalError("Missing TVF table sink.");
1258
0
        }
1259
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1260
156
                                                        output_exprs);
1261
156
        break;
1262
156
    }
1263
0
    default:
1264
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1265
433k
    }
1266
433k
    return Status::OK();
1267
433k
}
1268
1269
// NOLINTBEGIN(readability-function-size)
1270
// NOLINTBEGIN(readability-function-cognitive-complexity)
1271
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1272
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1273
                                                 PipelinePtr& cur_pipe, int parent_idx,
1274
                                                 int child_idx,
1275
                                                 const bool followed_by_shuffled_operator,
1276
                                                 const bool require_bucket_distribution,
1277
673k
                                                 OperatorPtr& cache_op) {
1278
673k
    std::vector<DataSinkOperatorPtr> sink_ops;
1279
673k
    Defer defer = Defer([&]() {
1280
672k
        if (op) {
1281
672k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1282
672k
        }
1283
672k
        for (auto& s : sink_ops) {
1284
125k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1285
125k
        }
1286
672k
    });
1287
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1288
    // Therefore, here we need to use a stack-like structure.
1289
673k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1290
673k
    std::stringstream error_msg;
1291
673k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1292
1293
673k
    bool fe_with_old_version = false;
1294
673k
    switch (tnode.node_type) {
1295
212k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1296
212k
        op = std::make_shared<OlapScanOperatorX>(
1297
212k
                pool, tnode, next_operator_id(), descs, _num_instances,
1298
212k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1299
212k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1300
212k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1301
212k
        break;
1302
212k
    }
1303
80
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1304
80
        DCHECK(_query_ctx != nullptr);
1305
80
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1306
80
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1307
80
                                                    _num_instances);
1308
80
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1309
80
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1310
80
        break;
1311
80
    }
1312
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1313
0
        if (config::enable_java_support) {
1314
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1315
0
                                                     _num_instances);
1316
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1317
0
        } else {
1318
0
            return Status::InternalError(
1319
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1320
0
                    "to true and restart be.");
1321
0
        }
1322
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1323
0
        break;
1324
0
    }
1325
23.0k
    case TPlanNodeType::FILE_SCAN_NODE: {
1326
23.0k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1327
23.0k
                                                 _num_instances);
1328
23.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1329
23.0k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1330
23.0k
        break;
1331
23.0k
    }
1332
0
    case TPlanNodeType::ES_SCAN_NODE:
1333
592
    case TPlanNodeType::ES_HTTP_SCAN_NODE: {
1334
592
        op = std::make_shared<EsScanOperatorX>(pool, tnode, next_operator_id(), descs,
1335
592
                                               _num_instances);
1336
592
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1337
592
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1338
592
        break;
1339
592
    }
1340
148k
    case TPlanNodeType::EXCHANGE_NODE: {
1341
148k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1342
148k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1343
18.4E
                                  : 0;
1344
148k
        DCHECK_GT(num_senders, 0);
1345
148k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1346
148k
                                                       num_senders);
1347
148k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1348
148k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1349
148k
        break;
1350
148k
    }
1351
157k
    case TPlanNodeType::AGGREGATION_NODE: {
1352
157k
        if (tnode.agg_node.grouping_exprs.empty() &&
1353
157k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1354
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1355
0
                                         ": group by and output is empty");
1356
0
        }
1357
157k
        bool need_create_cache_op =
1358
157k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1359
157k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1360
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1361
10
            auto cache_source_id = next_operator_id();
1362
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1363
10
                                                        _params.fragment.query_cache_param);
1364
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1365
1366
10
            const auto downstream_pipeline_id = cur_pipe->id();
1367
10
            if (!_dag.contains(downstream_pipeline_id)) {
1368
10
                _dag.insert({downstream_pipeline_id, {}});
1369
10
            }
1370
10
            new_pipe = add_pipeline(cur_pipe);
1371
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1372
1373
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1374
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1375
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1376
10
            return Status::OK();
1377
10
        };
1378
157k
        const bool group_by_limit_opt =
1379
157k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1380
1381
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1382
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1383
157k
        const bool enable_spill = _runtime_state->enable_spill() &&
1384
157k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1385
157k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1386
157k
                                      tnode.agg_node.use_streaming_preaggregation &&
1387
157k
                                      !tnode.agg_node.grouping_exprs.empty();
1388
        // TODO: distinct streaming agg does not support spill.
1389
157k
        const bool can_use_distinct_streaming_agg =
1390
157k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1391
157k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1392
157k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1393
157k
                _params.query_options.enable_distinct_streaming_aggregation;
1394
1395
157k
        if (can_use_distinct_streaming_agg) {
1396
91.4k
            if (need_create_cache_op) {
1397
8
                PipelinePtr new_pipe;
1398
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1399
1400
8
                cache_op = op;
1401
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1402
8
                                                                     tnode, descs);
1403
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1404
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1405
8
                cur_pipe = new_pipe;
1406
91.4k
            } else {
1407
91.4k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
91.4k
                                                                     tnode, descs);
1409
91.4k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1410
91.4k
            }
1411
91.4k
        } else if (is_streaming_agg) {
1412
3.26k
            if (need_create_cache_op) {
1413
0
                PipelinePtr new_pipe;
1414
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1415
0
                cache_op = op;
1416
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1417
0
                                                             descs);
1418
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1419
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1420
0
                cur_pipe = new_pipe;
1421
3.26k
            } else {
1422
3.26k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
3.26k
                                                             descs);
1424
3.26k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1425
3.26k
            }
1426
62.5k
        } else {
1427
            // create new pipeline to add query cache operator
1428
62.5k
            PipelinePtr new_pipe;
1429
62.5k
            if (need_create_cache_op) {
1430
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1431
2
                cache_op = op;
1432
2
            }
1433
1434
62.5k
            if (enable_spill) {
1435
136
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1436
136
                                                                     next_operator_id(), descs);
1437
62.3k
            } else {
1438
62.3k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1439
62.3k
            }
1440
62.5k
            if (need_create_cache_op) {
1441
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1442
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1443
2
                cur_pipe = new_pipe;
1444
62.5k
            } else {
1445
62.5k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1446
62.5k
            }
1447
1448
62.5k
            const auto downstream_pipeline_id = cur_pipe->id();
1449
62.5k
            if (!_dag.contains(downstream_pipeline_id)) {
1450
60.3k
                _dag.insert({downstream_pipeline_id, {}});
1451
60.3k
            }
1452
62.5k
            cur_pipe = add_pipeline(cur_pipe);
1453
62.5k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1454
1455
62.5k
            if (enable_spill) {
1456
136
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1457
136
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1458
62.3k
            } else {
1459
62.3k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1460
62.3k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1461
62.3k
            }
1462
62.5k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1463
62.5k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1464
62.5k
        }
1465
157k
        break;
1466
157k
    }
1467
157k
    case TPlanNodeType::HASH_JOIN_NODE: {
1468
9.83k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1469
9.83k
                                       tnode.hash_join_node.is_broadcast_join;
1470
9.83k
        const auto enable_spill = _runtime_state->enable_spill();
1471
9.83k
        if (enable_spill && !is_broadcast_join) {
1472
0
            auto tnode_ = tnode;
1473
0
            tnode_.runtime_filters.clear();
1474
0
            auto inner_probe_operator =
1475
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1476
1477
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1478
            // So here use `tnode_` which has no runtime filters.
1479
0
            auto probe_side_inner_sink_operator =
1480
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1481
1482
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1483
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1484
1485
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1486
0
                    pool, tnode_, next_operator_id(), descs);
1487
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1488
0
                                                inner_probe_operator);
1489
0
            op = std::move(probe_operator);
1490
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1491
1492
0
            const auto downstream_pipeline_id = cur_pipe->id();
1493
0
            if (!_dag.contains(downstream_pipeline_id)) {
1494
0
                _dag.insert({downstream_pipeline_id, {}});
1495
0
            }
1496
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1497
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1498
1499
0
            auto inner_sink_operator =
1500
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1501
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1502
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1503
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1504
1505
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1506
0
            sink_ops.push_back(std::move(sink_operator));
1507
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1508
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1509
1510
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1511
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1512
9.83k
        } else {
1513
9.83k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1514
9.83k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1515
1516
9.83k
            const auto downstream_pipeline_id = cur_pipe->id();
1517
9.83k
            if (!_dag.contains(downstream_pipeline_id)) {
1518
8.11k
                _dag.insert({downstream_pipeline_id, {}});
1519
8.11k
            }
1520
9.83k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1521
9.83k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1522
1523
9.83k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1524
9.83k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1525
9.83k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1526
9.83k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1527
1528
9.83k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1529
9.83k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1530
9.83k
        }
1531
9.83k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1532
3.07k
            std::shared_ptr<HashJoinSharedState> shared_state =
1533
3.07k
                    HashJoinSharedState::create_shared(_num_instances);
1534
21.3k
            for (int i = 0; i < _num_instances; i++) {
1535
18.2k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1536
18.2k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1537
18.2k
                sink_dep->set_shared_state(shared_state.get());
1538
18.2k
                shared_state->sink_deps.push_back(sink_dep);
1539
18.2k
            }
1540
3.07k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1541
3.07k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1542
3.07k
            _op_id_to_shared_state.insert(
1543
3.07k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1544
3.07k
        }
1545
9.83k
        break;
1546
9.83k
    }
1547
4.77k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1548
4.77k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1549
4.77k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1550
1551
4.77k
        const auto downstream_pipeline_id = cur_pipe->id();
1552
4.77k
        if (!_dag.contains(downstream_pipeline_id)) {
1553
4.54k
            _dag.insert({downstream_pipeline_id, {}});
1554
4.54k
        }
1555
4.77k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1556
4.77k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1557
1558
4.77k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1559
4.77k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1560
4.77k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
4.77k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1562
4.77k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1563
4.77k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1564
4.77k
        break;
1565
4.77k
    }
1566
53.3k
    case TPlanNodeType::UNION_NODE: {
1567
53.3k
        int child_count = tnode.num_children;
1568
53.3k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1569
53.3k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1570
1571
53.3k
        const auto downstream_pipeline_id = cur_pipe->id();
1572
53.3k
        if (!_dag.contains(downstream_pipeline_id)) {
1573
53.0k
            _dag.insert({downstream_pipeline_id, {}});
1574
53.0k
        }
1575
55.0k
        for (int i = 0; i < child_count; i++) {
1576
1.66k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1577
1.66k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1578
1.66k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1579
1.66k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1580
1.66k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1581
1.66k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1582
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1583
1.66k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1584
1.66k
        }
1585
53.3k
        break;
1586
53.3k
    }
1587
53.3k
    case TPlanNodeType::SORT_NODE: {
1588
44.2k
        const auto should_spill = _runtime_state->enable_spill() &&
1589
44.2k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1590
44.2k
        const bool use_local_merge =
1591
44.2k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1592
44.2k
        if (should_spill) {
1593
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1594
44.2k
        } else if (use_local_merge) {
1595
41.9k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1596
41.9k
                                                                 descs);
1597
41.9k
        } else {
1598
2.29k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1599
2.29k
        }
1600
44.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1601
1602
44.2k
        const auto downstream_pipeline_id = cur_pipe->id();
1603
44.2k
        if (!_dag.contains(downstream_pipeline_id)) {
1604
44.2k
            _dag.insert({downstream_pipeline_id, {}});
1605
44.2k
        }
1606
44.2k
        cur_pipe = add_pipeline(cur_pipe);
1607
44.2k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1608
1609
44.2k
        if (should_spill) {
1610
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1611
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1612
44.2k
        } else {
1613
44.2k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1614
44.2k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1615
44.2k
        }
1616
44.2k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1617
44.2k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1618
44.2k
        break;
1619
44.2k
    }
1620
44.2k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1621
63
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
63
        const auto downstream_pipeline_id = cur_pipe->id();
1625
63
        if (!_dag.contains(downstream_pipeline_id)) {
1626
63
            _dag.insert({downstream_pipeline_id, {}});
1627
63
        }
1628
63
        cur_pipe = add_pipeline(cur_pipe);
1629
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1630
1631
63
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1632
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1633
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1634
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1635
63
        break;
1636
63
    }
1637
1.61k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1638
1.61k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1639
1.61k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1640
1641
1.61k
        const auto downstream_pipeline_id = cur_pipe->id();
1642
1.61k
        if (!_dag.contains(downstream_pipeline_id)) {
1643
1.60k
            _dag.insert({downstream_pipeline_id, {}});
1644
1.60k
        }
1645
1.61k
        cur_pipe = add_pipeline(cur_pipe);
1646
1.61k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1647
1648
1.61k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1649
1.61k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1650
1.61k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1651
1.61k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1652
1.61k
        break;
1653
1.61k
    }
1654
1.61k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1655
1.61k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1656
1.61k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1657
1.61k
        break;
1658
1.61k
    }
1659
1.61k
    case TPlanNodeType::INTERSECT_NODE: {
1660
119
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1661
119
                                                                      cur_pipe, sink_ops));
1662
119
        break;
1663
119
    }
1664
128
    case TPlanNodeType::EXCEPT_NODE: {
1665
128
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1666
128
                                                                       cur_pipe, sink_ops));
1667
128
        break;
1668
128
    }
1669
312
    case TPlanNodeType::REPEAT_NODE: {
1670
312
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1671
312
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1672
312
        break;
1673
312
    }
1674
920
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1675
920
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1676
920
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1677
920
        break;
1678
920
    }
1679
920
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1680
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1681
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1682
218
        break;
1683
218
    }
1684
1.60k
    case TPlanNodeType::EMPTY_SET_NODE: {
1685
1.60k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1686
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1687
1.60k
        break;
1688
1.60k
    }
1689
1.60k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1690
459
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1691
459
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1692
459
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1693
459
        break;
1694
459
    }
1695
2.32k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1696
2.32k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1697
2.32k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1698
2.32k
        break;
1699
2.32k
    }
1700
6.56k
    case TPlanNodeType::META_SCAN_NODE: {
1701
6.56k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1702
6.56k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1703
6.56k
        break;
1704
6.56k
    }
1705
6.56k
    case TPlanNodeType::SELECT_NODE: {
1706
1.89k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1707
1.89k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1708
1.89k
        break;
1709
1.89k
    }
1710
1.89k
    case TPlanNodeType::REC_CTE_NODE: {
1711
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1712
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1713
1714
151
        const auto downstream_pipeline_id = cur_pipe->id();
1715
151
        if (!_dag.contains(downstream_pipeline_id)) {
1716
148
            _dag.insert({downstream_pipeline_id, {}});
1717
148
        }
1718
1719
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1720
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1721
1722
151
        DataSinkOperatorPtr anchor_sink;
1723
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1724
151
                                                                  op->operator_id(), tnode, descs);
1725
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1726
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1727
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1728
1729
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1730
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1731
1732
151
        DataSinkOperatorPtr rec_sink;
1733
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1734
151
                                                         tnode, descs);
1735
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1736
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1737
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1738
1739
151
        break;
1740
151
    }
1741
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1742
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1743
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1744
1.95k
        break;
1745
1.95k
    }
1746
1.95k
    default:
1747
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1748
0
                                     print_plan_node_type(tnode.node_type));
1749
673k
    }
1750
671k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1751
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1752
0
        op->set_serial_operator();
1753
0
    }
1754
1755
671k
    return Status::OK();
1756
673k
}
1757
// NOLINTEND(readability-function-cognitive-complexity)
1758
// NOLINTEND(readability-function-size)
1759
1760
template <bool is_intersect>
1761
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1762
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1763
247
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1764
247
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1765
247
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
247
    const auto downstream_pipeline_id = cur_pipe->id();
1768
247
    if (!_dag.contains(downstream_pipeline_id)) {
1769
230
        _dag.insert({downstream_pipeline_id, {}});
1770
230
    }
1771
1772
834
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1773
587
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1774
587
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1775
1776
587
        if (child_id == 0) {
1777
247
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1778
247
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1779
340
        } else {
1780
340
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1781
340
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1782
340
        }
1783
587
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1784
587
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1785
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1786
587
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1787
587
    }
1788
1789
247
    return Status::OK();
1790
247
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1763
119
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1764
119
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1765
119
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
119
    const auto downstream_pipeline_id = cur_pipe->id();
1768
119
    if (!_dag.contains(downstream_pipeline_id)) {
1769
110
        _dag.insert({downstream_pipeline_id, {}});
1770
110
    }
1771
1772
435
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1773
316
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1774
316
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1775
1776
316
        if (child_id == 0) {
1777
119
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1778
119
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1779
197
        } else {
1780
197
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1781
197
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1782
197
        }
1783
316
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1784
316
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1785
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1786
316
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1787
316
    }
1788
1789
119
    return Status::OK();
1790
119
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1763
128
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1764
128
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1765
128
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
128
    const auto downstream_pipeline_id = cur_pipe->id();
1768
128
    if (!_dag.contains(downstream_pipeline_id)) {
1769
120
        _dag.insert({downstream_pipeline_id, {}});
1770
120
    }
1771
1772
399
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1773
271
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1774
271
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1775
1776
271
        if (child_id == 0) {
1777
128
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1778
128
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1779
143
        } else {
1780
143
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1781
143
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1782
143
        }
1783
271
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1784
271
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1785
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1786
271
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1787
271
    }
1788
1789
128
    return Status::OK();
1790
128
}
1791
1792
431k
Status PipelineFragmentContext::submit() {
1793
431k
    if (_submitted) {
1794
0
        return Status::InternalError("submitted");
1795
0
    }
1796
431k
    _submitted = true;
1797
1798
431k
    int submit_tasks = 0;
1799
431k
    Status st;
1800
431k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1801
1.19M
    for (auto& task : _tasks) {
1802
1.99M
        for (auto& t : task) {
1803
1.99M
            st = scheduler->submit(t.first);
1804
1.99M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1805
1.99M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1806
1.99M
            if (!st) {
1807
0
                cancel(Status::InternalError("submit context to executor fail"));
1808
0
                std::lock_guard<std::mutex> l(_task_mutex);
1809
0
                _total_tasks = submit_tasks;
1810
0
                break;
1811
0
            }
1812
1.99M
            submit_tasks++;
1813
1.99M
        }
1814
1.19M
    }
1815
431k
    if (!st.ok()) {
1816
0
        bool need_remove = false;
1817
0
        {
1818
0
            std::lock_guard<std::mutex> l(_task_mutex);
1819
0
            if (_closed_tasks >= _total_tasks) {
1820
0
                need_remove = _close_fragment_instance();
1821
0
            }
1822
0
        }
1823
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1824
0
        if (need_remove) {
1825
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1826
0
        }
1827
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1828
0
                                     BackendOptions::get_localhost());
1829
431k
    } else {
1830
431k
        return st;
1831
431k
    }
1832
431k
}
1833
1834
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1835
0
    if (_runtime_state->enable_profile()) {
1836
0
        std::stringstream ss;
1837
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1838
0
            runtime_profile_ptr->pretty_print(&ss);
1839
0
        }
1840
1841
0
        if (_runtime_state->load_channel_profile()) {
1842
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1843
0
        }
1844
1845
0
        auto profile_str =
1846
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1847
0
                            this->_fragment_id, extra_info, ss.str());
1848
0
        LOG_LONG_STRING(INFO, profile_str);
1849
0
    }
1850
0
}
1851
// If all pipeline tasks binded to the fragment instance are finished, then we could
1852
// close the fragment instance.
1853
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1854
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1855
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1856
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1857
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1858
// (via debug_string()).
1859
433k
bool PipelineFragmentContext::_close_fragment_instance() {
1860
433k
    if (_is_fragment_instance_closed) {
1861
0
        return false;
1862
0
    }
1863
433k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1864
433k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1865
433k
    if (!_need_notify_close) {
1866
430k
        auto st = send_report(true);
1867
430k
        if (!st) {
1868
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1869
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1870
0
        }
1871
430k
    }
1872
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1873
    // Since stream load does not have someting like coordinator on FE, so
1874
    // backend can not report profile to FE, ant its profile can not be shown
1875
    // in the same way with other query. So we print the profile content to info log.
1876
1877
433k
    if (_runtime_state->enable_profile() &&
1878
433k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1879
2.23k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1880
2.23k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1881
0
        std::stringstream ss;
1882
        // Compute the _local_time_percent before pretty_print the runtime_profile
1883
        // Before add this operation, the print out like that:
1884
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1885
        // After add the operation, the print out like that:
1886
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1887
        // We can easily know the exec node execute time without child time consumed.
1888
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1889
0
            runtime_profile_ptr->pretty_print(&ss);
1890
0
        }
1891
1892
0
        if (_runtime_state->load_channel_profile()) {
1893
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1894
0
        }
1895
1896
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1897
0
    }
1898
1899
433k
    if (_query_ctx->enable_profile()) {
1900
2.23k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1901
2.23k
                                         collect_realtime_load_channel_profile());
1902
2.23k
    }
1903
1904
    // Return whether the caller needs to remove from the pipeline map.
1905
    // The caller must do this after releasing _task_mutex.
1906
433k
    return !_need_notify_close;
1907
433k
}
1908
1909
1.98M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1910
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1911
1.98M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1912
1.98M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1913
677k
        if (_dag.contains(pipeline_id)) {
1914
355k
            for (auto dep : _dag[pipeline_id]) {
1915
355k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1916
355k
            }
1917
285k
        }
1918
677k
    }
1919
1.98M
    bool need_remove = false;
1920
1.98M
    {
1921
1.98M
        std::lock_guard<std::mutex> l(_task_mutex);
1922
1.98M
        ++_closed_tasks;
1923
1.98M
        if (_closed_tasks >= _total_tasks) {
1924
433k
            need_remove = _close_fragment_instance();
1925
433k
        }
1926
1.98M
    }
1927
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1928
1.98M
    if (need_remove) {
1929
430k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1930
430k
    }
1931
1.98M
}
1932
1933
53.4k
std::string PipelineFragmentContext::get_load_error_url() {
1934
53.4k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1935
0
        return to_load_error_http_path(str);
1936
0
    }
1937
138k
    for (auto& tasks : _tasks) {
1938
215k
        for (auto& task : tasks) {
1939
215k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1940
160
                return to_load_error_http_path(str);
1941
160
            }
1942
215k
        }
1943
138k
    }
1944
53.2k
    return "";
1945
53.4k
}
1946
1947
53.4k
std::string PipelineFragmentContext::get_first_error_msg() {
1948
53.4k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
1949
0
        return str;
1950
0
    }
1951
138k
    for (auto& tasks : _tasks) {
1952
215k
        for (auto& task : tasks) {
1953
215k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
1954
160
                return str;
1955
160
            }
1956
215k
        }
1957
138k
    }
1958
53.2k
    return "";
1959
53.4k
}
1960
1961
435k
Status PipelineFragmentContext::send_report(bool done) {
1962
435k
    Status exec_status = _query_ctx->exec_status();
1963
    // If plan is done successfully, but _is_report_success is false,
1964
    // no need to send report.
1965
    // Load will set _is_report_success to true because load wants to know
1966
    // the process.
1967
435k
    if (!_is_report_success && done && exec_status.ok()) {
1968
387k
        return Status::OK();
1969
387k
    }
1970
1971
    // If both _is_report_success and _is_report_on_cancel are false,
1972
    // which means no matter query is success or failed, no report is needed.
1973
    // This may happen when the query limit reached and
1974
    // a internal cancellation being processed
1975
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
1976
    // be set to false, to avoid sending fault report to FE.
1977
48.0k
    if (!_is_report_success && !_is_report_on_cancel) {
1978
518
        if (done) {
1979
            // 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.
1980
518
            return Status::OK();
1981
518
        }
1982
0
        return Status::NeedSendAgain("");
1983
518
    }
1984
1985
47.5k
    std::vector<RuntimeState*> runtime_states;
1986
1987
116k
    for (auto& tasks : _tasks) {
1988
168k
        for (auto& task : tasks) {
1989
168k
            runtime_states.push_back(task.second.get());
1990
168k
        }
1991
116k
    }
1992
1993
47.5k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
1994
47.5k
                                        ? get_load_error_url()
1995
18.4E
                                        : _query_ctx->get_load_error_url();
1996
47.5k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
1997
47.5k
                                          ? get_first_error_msg()
1998
18.4E
                                          : _query_ctx->get_first_error_msg();
1999
2000
47.5k
    ReportStatusRequest req {.status = exec_status,
2001
47.5k
                             .runtime_states = runtime_states,
2002
47.5k
                             .done = done || !exec_status.ok(),
2003
47.5k
                             .coord_addr = _query_ctx->coord_addr,
2004
47.5k
                             .query_id = _query_id,
2005
47.5k
                             .fragment_id = _fragment_id,
2006
47.5k
                             .fragment_instance_id = TUniqueId(),
2007
47.5k
                             .backend_num = -1,
2008
47.5k
                             .runtime_state = _runtime_state.get(),
2009
47.5k
                             .load_error_url = load_eror_url,
2010
47.5k
                             .first_error_msg = first_error_msg,
2011
47.5k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2012
2013
47.5k
    return _report_status_cb(
2014
47.5k
            req, std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()));
2015
48.0k
}
2016
2017
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2018
0
    size_t res = 0;
2019
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2020
    // here to traverse the vector.
2021
0
    for (const auto& task_instances : _tasks) {
2022
0
        for (const auto& task : task_instances) {
2023
0
            if (task.first->is_running()) {
2024
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2025
0
                                      << " is running, task: " << (void*)task.first.get()
2026
0
                                      << ", is_running: " << task.first->is_running();
2027
0
                *has_running_task = true;
2028
0
                return 0;
2029
0
            }
2030
2031
0
            size_t revocable_size = task.first->get_revocable_size();
2032
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2033
0
                res += revocable_size;
2034
0
            }
2035
0
        }
2036
0
    }
2037
0
    return res;
2038
0
}
2039
2040
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2041
0
    std::vector<PipelineTask*> revocable_tasks;
2042
0
    for (const auto& task_instances : _tasks) {
2043
0
        for (const auto& task : task_instances) {
2044
0
            size_t revocable_size_ = task.first->get_revocable_size();
2045
2046
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2047
0
                revocable_tasks.emplace_back(task.first.get());
2048
0
            }
2049
0
        }
2050
0
    }
2051
0
    return revocable_tasks;
2052
0
}
2053
2054
277
std::string PipelineFragmentContext::debug_string() {
2055
277
    std::lock_guard<std::mutex> l(_task_mutex);
2056
277
    fmt::memory_buffer debug_string_buffer;
2057
277
    fmt::format_to(debug_string_buffer,
2058
277
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2059
277
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2060
277
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2061
1.24k
    for (size_t j = 0; j < _tasks.size(); j++) {
2062
968
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2063
2.46k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2064
1.49k
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2065
1.49k
                           _tasks[j][i].first->debug_string());
2066
1.49k
        }
2067
968
    }
2068
2069
277
    return fmt::to_string(debug_string_buffer);
2070
277
}
2071
2072
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2073
2.23k
PipelineFragmentContext::collect_realtime_profile() const {
2074
2.23k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2075
2076
    // we do not have mutex to protect pipeline_id_to_profile
2077
    // so we need to make sure this funciton is invoked after fragment context
2078
    // has already been prepared.
2079
2.23k
    if (!_prepared) {
2080
0
        std::string msg =
2081
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2082
0
        DCHECK(false) << msg;
2083
0
        LOG_ERROR(msg);
2084
0
        return res;
2085
0
    }
2086
2087
    // Make sure first profile is fragment level profile
2088
2.23k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2089
2.23k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2090
2.23k
    res.push_back(fragment_profile);
2091
2092
    // pipeline_id_to_profile is initialized in prepare stage
2093
3.89k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2094
3.89k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2095
3.89k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2096
3.89k
        res.push_back(profile_ptr);
2097
3.89k
    }
2098
2099
2.23k
    return res;
2100
2.23k
}
2101
2102
std::shared_ptr<TRuntimeProfileTree>
2103
2.23k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2104
    // we do not have mutex to protect pipeline_id_to_profile
2105
    // so we need to make sure this funciton is invoked after fragment context
2106
    // has already been prepared.
2107
2.23k
    if (!_prepared) {
2108
0
        std::string msg =
2109
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2110
0
        DCHECK(false) << msg;
2111
0
        LOG_ERROR(msg);
2112
0
        return nullptr;
2113
0
    }
2114
2115
4.51k
    for (const auto& tasks : _tasks) {
2116
8.75k
        for (const auto& task : tasks) {
2117
8.75k
            if (task.second->load_channel_profile() == nullptr) {
2118
0
                continue;
2119
0
            }
2120
2121
8.75k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2122
2123
8.75k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2124
8.75k
                                                           _runtime_state->profile_level());
2125
8.75k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2126
8.75k
        }
2127
4.51k
    }
2128
2129
2.23k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2130
2.23k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2131
2.23k
                                                      _runtime_state->profile_level());
2132
2.23k
    return load_channel_profile;
2133
2.23k
}
2134
2135
// Collect runtime filter IDs registered by all tasks in this PFC.
2136
// Used during recursive CTE stage transitions to know which filters to deregister
2137
// before creating the new PFC for the next recursion round.
2138
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2139
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2140
// the vector sizes do not change, and individual RuntimeState filter sets are
2141
// written only during open() which has completed by the time we reach rerun.
2142
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2143
3.28k
    std::set<int> result;
2144
7.63k
    for (const auto& _task : _tasks) {
2145
13.4k
        for (const auto& task : _task) {
2146
13.4k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2147
13.4k
            result.merge(set);
2148
13.4k
        }
2149
7.63k
    }
2150
3.28k
    if (_runtime_state) {
2151
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2152
3.28k
        result.merge(set);
2153
3.28k
    }
2154
3.28k
    return result;
2155
3.28k
}
2156
2157
435k
void PipelineFragmentContext::_release_resource() {
2158
435k
    std::lock_guard<std::mutex> l(_task_mutex);
2159
    // The memory released by the query end is recorded in the query mem tracker.
2160
435k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2161
435k
    auto st = _query_ctx->exec_status();
2162
1.20M
    for (auto& _task : _tasks) {
2163
1.20M
        if (!_task.empty()) {
2164
1.20M
            _call_back(_task.front().first->runtime_state(), &st);
2165
1.20M
        }
2166
1.20M
    }
2167
435k
    _tasks.clear();
2168
435k
    _dag.clear();
2169
435k
    _pip_id_to_pipeline.clear();
2170
435k
    _pipelines.clear();
2171
435k
    _sink.reset();
2172
435k
    _root_op.reset();
2173
435k
    _runtime_filter_mgr_map.clear();
2174
435k
    _op_id_to_shared_state.clear();
2175
435k
}
2176
2177
} // namespace doris