Coverage Report

Created: 2026-04-06 14:28

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
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Source
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// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
14
// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
17
18
#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
#include "common/compile_check_begin.h"
131
PipelineFragmentContext::PipelineFragmentContext(
132
        TUniqueId query_id, const TPipelineFragmentParams& request,
133
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
134
        const std::function<void(RuntimeState*, Status*)>& call_back,
135
        report_status_callback report_status_cb)
136
320k
        : _query_id(std::move(query_id)),
137
320k
          _fragment_id(request.fragment_id),
138
320k
          _exec_env(exec_env),
139
320k
          _query_ctx(std::move(query_ctx)),
140
320k
          _call_back(call_back),
141
320k
          _is_report_on_cancel(true),
142
320k
          _report_status_cb(std::move(report_status_cb)),
143
320k
          _params(request),
144
320k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
145
320k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
146
320k
                                                               : false) {
147
320k
    _fragment_watcher.start();
148
320k
}
149
150
320k
PipelineFragmentContext::~PipelineFragmentContext() {
151
320k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
152
320k
            .tag("query_id", print_id(_query_id))
153
320k
            .tag("fragment_id", _fragment_id);
154
320k
    _release_resource();
155
320k
    {
156
        // The memory released by the query end is recorded in the query mem tracker.
157
320k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
158
320k
        _runtime_state.reset();
159
320k
        _query_ctx.reset();
160
320k
    }
161
320k
}
162
163
115
bool PipelineFragmentContext::is_timeout(timespec now) const {
164
115
    if (_timeout <= 0) {
165
0
        return false;
166
0
    }
167
115
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
168
115
}
169
170
// notify_close() transitions the PFC from "waiting for external close notification" to
171
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
172
// 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).
174
8.83k
bool PipelineFragmentContext::notify_close() {
175
8.83k
    bool all_closed = false;
176
8.83k
    bool need_remove = false;
177
8.83k
    {
178
8.83k
        std::lock_guard<std::mutex> l(_task_mutex);
179
8.83k
        if (_closed_tasks >= _total_tasks) {
180
3.43k
            if (_need_notify_close) {
181
                // Fragment was cancelled and waiting for notify to close.
182
                // Record that we need to remove from fragment mgr, but do it
183
                // after releasing _task_mutex to avoid ABBA deadlock with
184
                // dump_pipeline_tasks() (which acquires _pipeline_map lock
185
                // first, then _task_mutex via debug_string()).
186
3.38k
                need_remove = true;
187
3.38k
            }
188
3.43k
            all_closed = true;
189
3.43k
        }
190
        // make fragment release by self after cancel
191
8.83k
        _need_notify_close = false;
192
8.83k
    }
193
8.83k
    if (need_remove) {
194
3.38k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
195
3.38k
    }
196
8.83k
    return all_closed;
197
8.83k
}
198
199
// Must not add lock in this method. Because it will call query ctx cancel. And
200
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
201
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
203
5.36k
void PipelineFragmentContext::cancel(const Status reason) {
204
5.36k
    LOG_INFO("PipelineFragmentContext::cancel")
205
5.36k
            .tag("query_id", print_id(_query_id))
206
5.36k
            .tag("fragment_id", _fragment_id)
207
5.36k
            .tag("reason", reason.to_string());
208
5.36k
    if (notify_close()) {
209
61
        return;
210
61
    }
211
    // Timeout is a special error code, we need print current stack to debug timeout issue.
212
5.29k
    if (reason.is<ErrorCode::TIMEOUT>()) {
213
8
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
214
8
                                   debug_string());
215
8
        LOG_LONG_STRING(WARNING, dbg_str);
216
8
    }
217
218
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
219
5.29k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
220
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
221
0
                    debug_string());
222
0
    }
223
224
5.30k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
225
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
226
0
    }
227
228
5.29k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
229
24
        _query_ctx->set_load_error_url(error_url);
230
24
    }
231
232
5.29k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
233
24
        _query_ctx->set_first_error_msg(first_error_msg);
234
24
    }
235
236
5.29k
    _query_ctx->cancel(reason, _fragment_id);
237
5.29k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
238
298
        _is_report_on_cancel = false;
239
5.00k
    } else {
240
20.0k
        for (auto& id : _fragment_instance_ids) {
241
20.0k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
242
20.0k
        }
243
5.00k
    }
244
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
245
    // For stream load the fragment's query_id == load id, it is set in FE.
246
5.29k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
247
5.29k
    if (stream_load_ctx != nullptr) {
248
32
        stream_load_ctx->pipe->cancel(reason.to_string());
249
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
250
        // We need to set the error URL at this point to ensure error information is properly
251
        // propagated to the client.
252
32
        stream_load_ctx->error_url = get_load_error_url();
253
32
        stream_load_ctx->first_error_msg = get_first_error_msg();
254
32
    }
255
256
21.8k
    for (auto& tasks : _tasks) {
257
47.6k
        for (auto& task : tasks) {
258
47.6k
            task.first->unblock_all_dependencies();
259
47.6k
        }
260
21.8k
    }
261
5.29k
}
262
263
520k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
264
520k
    PipelineId id = _next_pipeline_id++;
265
520k
    auto pipeline = std::make_shared<Pipeline>(
266
520k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
267
520k
            parent ? parent->num_tasks() : _num_instances);
268
520k
    if (idx >= 0) {
269
113k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
270
406k
    } else {
271
406k
        _pipelines.emplace_back(pipeline);
272
406k
    }
273
520k
    if (parent) {
274
199k
        parent->set_children(pipeline);
275
199k
    }
276
520k
    return pipeline;
277
520k
}
278
279
319k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
280
319k
    {
281
319k
        SCOPED_TIMER(_build_pipelines_timer);
282
        // 2. Build pipelines with operators in this fragment.
283
319k
        auto root_pipeline = add_pipeline();
284
319k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
285
319k
                                         &_root_op, root_pipeline));
286
287
        // 3. Create sink operator
288
319k
        if (!_params.fragment.__isset.output_sink) {
289
0
            return Status::InternalError("No output sink in this fragment!");
290
0
        }
291
319k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
292
319k
                                          _params.fragment.output_exprs, _params,
293
319k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
294
319k
                                          *_desc_tbl, root_pipeline->id()));
295
319k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
296
319k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
297
298
405k
        for (PipelinePtr& pipeline : _pipelines) {
299
18.4E
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
300
405k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
301
405k
        }
302
319k
    }
303
    // 4. Build local exchanger
304
319k
    if (_runtime_state->enable_local_shuffle()) {
305
317k
        SCOPED_TIMER(_plan_local_exchanger_timer);
306
317k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
307
317k
                                             _params.bucket_seq_to_instance_idx,
308
317k
                                             _params.shuffle_idx_to_instance_idx));
309
317k
    }
310
311
    // 5. Initialize global states in pipelines.
312
521k
    for (PipelinePtr& pipeline : _pipelines) {
313
521k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
314
521k
        pipeline->children().clear();
315
521k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
316
521k
    }
317
318
318k
    {
319
318k
        SCOPED_TIMER(_build_tasks_timer);
320
        // 6. Build pipeline tasks and initialize local state.
321
318k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
322
318k
    }
323
324
318k
    return Status::OK();
325
318k
}
326
327
320k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
328
320k
    if (_prepared) {
329
0
        return Status::InternalError("Already prepared");
330
0
    }
331
320k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
332
319k
        _timeout = _params.query_options.execution_timeout;
333
319k
    }
334
335
320k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
336
320k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
337
320k
    SCOPED_TIMER(_prepare_timer);
338
320k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
339
320k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
340
320k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
341
320k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
342
320k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
343
320k
    {
344
320k
        SCOPED_TIMER(_init_context_timer);
345
320k
        cast_set(_num_instances, _params.local_params.size());
346
320k
        _total_instances =
347
320k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
348
349
320k
        auto* fragment_context = this;
350
351
320k
        if (_params.query_options.__isset.is_report_success) {
352
317k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
353
317k
        }
354
355
        // 1. Set up the global runtime state.
356
320k
        _runtime_state = RuntimeState::create_unique(
357
320k
                _params.query_id, _params.fragment_id, _params.query_options,
358
320k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
359
320k
        _runtime_state->set_task_execution_context(shared_from_this());
360
320k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
361
320k
        if (_params.__isset.backend_id) {
362
317k
            _runtime_state->set_backend_id(_params.backend_id);
363
317k
        }
364
320k
        if (_params.__isset.import_label) {
365
235
            _runtime_state->set_import_label(_params.import_label);
366
235
        }
367
320k
        if (_params.__isset.db_name) {
368
187
            _runtime_state->set_db_name(_params.db_name);
369
187
        }
370
320k
        if (_params.__isset.load_job_id) {
371
0
            _runtime_state->set_load_job_id(_params.load_job_id);
372
0
        }
373
374
320k
        if (_params.is_simplified_param) {
375
110k
            _desc_tbl = _query_ctx->desc_tbl;
376
209k
        } else {
377
209k
            DCHECK(_params.__isset.desc_tbl);
378
209k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
379
209k
                                                  &_desc_tbl));
380
209k
        }
381
320k
        _runtime_state->set_desc_tbl(_desc_tbl);
382
320k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
383
320k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
384
320k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
385
320k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
386
387
        // init fragment_instance_ids
388
320k
        const auto target_size = _params.local_params.size();
389
320k
        _fragment_instance_ids.resize(target_size);
390
1.27M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
391
952k
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
392
952k
            _fragment_instance_ids[i] = fragment_instance_id;
393
952k
        }
394
320k
    }
395
396
320k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
397
398
318k
    _init_next_report_time();
399
400
318k
    _prepared = true;
401
318k
    return Status::OK();
402
320k
}
403
404
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
405
        int instance_idx,
406
953k
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
407
953k
    const auto& local_params = _params.local_params[instance_idx];
408
953k
    auto fragment_instance_id = local_params.fragment_instance_id;
409
953k
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
410
953k
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
411
953k
    auto get_shared_state = [&](PipelinePtr pipeline)
412
953k
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
413
1.66M
                                       std::vector<std::shared_ptr<Dependency>>>> {
414
1.66M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
415
1.66M
                                std::vector<std::shared_ptr<Dependency>>>>
416
1.66M
                shared_state_map;
417
2.22M
        for (auto& op : pipeline->operators()) {
418
2.22M
            auto source_id = op->operator_id();
419
2.22M
            if (auto iter = _op_id_to_shared_state.find(source_id);
420
2.22M
                iter != _op_id_to_shared_state.end()) {
421
687k
                shared_state_map.insert({source_id, iter->second});
422
687k
            }
423
2.22M
        }
424
1.66M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
425
1.66M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
426
1.66M
                iter != _op_id_to_shared_state.end()) {
427
339k
                shared_state_map.insert({sink_to_source_id, iter->second});
428
339k
            }
429
1.66M
        }
430
1.66M
        return shared_state_map;
431
1.66M
    };
432
433
2.96M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
434
2.00M
        auto& pipeline = _pipelines[pip_idx];
435
2.00M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
436
1.66M
            auto task_runtime_state = RuntimeState::create_unique(
437
1.66M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
438
1.66M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
439
1.66M
            {
440
                // Initialize runtime state for this task
441
1.66M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
442
443
1.66M
                task_runtime_state->set_task_execution_context(shared_from_this());
444
1.66M
                task_runtime_state->set_be_number(local_params.backend_num);
445
446
1.66M
                if (_params.__isset.backend_id) {
447
1.66M
                    task_runtime_state->set_backend_id(_params.backend_id);
448
1.66M
                }
449
1.66M
                if (_params.__isset.import_label) {
450
236
                    task_runtime_state->set_import_label(_params.import_label);
451
236
                }
452
1.66M
                if (_params.__isset.db_name) {
453
188
                    task_runtime_state->set_db_name(_params.db_name);
454
188
                }
455
1.66M
                if (_params.__isset.load_job_id) {
456
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
457
0
                }
458
1.66M
                if (_params.__isset.wal_id) {
459
112
                    task_runtime_state->set_wal_id(_params.wal_id);
460
112
                }
461
1.66M
                if (_params.__isset.content_length) {
462
31
                    task_runtime_state->set_content_length(_params.content_length);
463
31
                }
464
465
1.66M
                task_runtime_state->set_desc_tbl(_desc_tbl);
466
1.66M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
467
1.66M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
468
1.66M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
469
1.66M
                task_runtime_state->set_max_operator_id(max_operator_id());
470
1.66M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
471
1.66M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
472
1.66M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
473
474
1.66M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
475
1.66M
            }
476
1.66M
            auto cur_task_id = _total_tasks++;
477
1.66M
            task_runtime_state->set_task_id(cur_task_id);
478
1.66M
            task_runtime_state->set_task_num(pipeline->num_tasks());
479
1.66M
            auto task = std::make_shared<PipelineTask>(
480
1.66M
                    pipeline, cur_task_id, task_runtime_state.get(),
481
1.66M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
482
1.66M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
483
1.66M
                    instance_idx);
484
1.66M
            pipeline->incr_created_tasks(instance_idx, task.get());
485
1.66M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
486
1.66M
            _tasks[instance_idx].emplace_back(
487
1.66M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
488
1.66M
                            std::move(task), std::move(task_runtime_state)});
489
1.66M
        }
490
2.00M
    }
491
492
    /**
493
         * Build DAG for pipeline tasks.
494
         * For example, we have
495
         *
496
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
497
         *            \                      /
498
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
499
         *                 \                          /
500
         *               JoinProbeOperator2 (Pipeline1)
501
         *
502
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
503
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
504
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
505
         *
506
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
507
         * and JoinProbeOperator2.
508
         */
509
2.01M
    for (auto& _pipeline : _pipelines) {
510
2.01M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
511
1.66M
            auto* task = pipeline_id_to_task[_pipeline->id()];
512
1.66M
            DCHECK(task != nullptr);
513
514
            // If this task has upstream dependency, then inject it into this task.
515
1.66M
            if (_dag.contains(_pipeline->id())) {
516
1.06M
                auto& deps = _dag[_pipeline->id()];
517
1.73M
                for (auto& dep : deps) {
518
1.73M
                    if (pipeline_id_to_task.contains(dep)) {
519
1.03M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
520
1.03M
                        if (ss) {
521
364k
                            task->inject_shared_state(ss);
522
672k
                        } else {
523
672k
                            pipeline_id_to_task[dep]->inject_shared_state(
524
672k
                                    task->get_source_shared_state());
525
672k
                        }
526
1.03M
                    }
527
1.73M
                }
528
1.06M
            }
529
1.66M
        }
530
2.01M
    }
531
2.96M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
532
2.01M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
533
1.66M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
534
1.66M
            DCHECK(pipeline_id_to_profile[pip_idx]);
535
1.66M
            std::vector<TScanRangeParams> scan_ranges;
536
1.66M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
537
1.66M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
538
264k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
539
264k
            }
540
1.66M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
541
1.66M
                                                             _params.fragment.output_sink));
542
1.66M
        }
543
2.01M
    }
544
955k
    {
545
955k
        std::lock_guard<std::mutex> l(_state_map_lock);
546
955k
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
547
955k
    }
548
955k
    return Status::OK();
549
953k
}
550
551
319k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
552
319k
    _total_tasks = 0;
553
319k
    _closed_tasks = 0;
554
319k
    const auto target_size = _params.local_params.size();
555
319k
    _tasks.resize(target_size);
556
319k
    _runtime_filter_mgr_map.resize(target_size);
557
838k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
558
519k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
559
519k
    }
560
319k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
561
562
319k
    if (target_size > 1 &&
563
319k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
564
133k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
565
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
566
17.5k
        std::vector<Status> prepare_status(target_size);
567
17.5k
        int submitted_tasks = 0;
568
17.5k
        Status submit_status;
569
17.5k
        CountDownLatch latch((int)target_size);
570
199k
        for (int i = 0; i < target_size; i++) {
571
181k
            submit_status = thread_pool->submit_func([&, i]() {
572
181k
                SCOPED_ATTACH_TASK(_query_ctx.get());
573
181k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
574
181k
                latch.count_down();
575
181k
            });
576
181k
            if (LIKELY(submit_status.ok())) {
577
181k
                submitted_tasks++;
578
18.4E
            } else {
579
18.4E
                break;
580
18.4E
            }
581
181k
        }
582
17.5k
        latch.arrive_and_wait(target_size - submitted_tasks);
583
17.5k
        if (UNLIKELY(!submit_status.ok())) {
584
0
            return submit_status;
585
0
        }
586
199k
        for (int i = 0; i < submitted_tasks; i++) {
587
181k
            if (!prepare_status[i].ok()) {
588
0
                return prepare_status[i];
589
0
            }
590
181k
        }
591
301k
    } else {
592
1.07M
        for (int i = 0; i < target_size; i++) {
593
773k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
594
773k
        }
595
301k
    }
596
319k
    _pipeline_parent_map.clear();
597
319k
    _op_id_to_shared_state.clear();
598
599
319k
    return Status::OK();
600
319k
}
601
602
318k
void PipelineFragmentContext::_init_next_report_time() {
603
318k
    auto interval_s = config::pipeline_status_report_interval;
604
318k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
605
30.3k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
606
30.3k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
607
        // We don't want to wait longer than it takes to run the entire fragment.
608
30.3k
        _previous_report_time =
609
30.3k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
610
30.3k
        _disable_period_report = false;
611
30.3k
    }
612
318k
}
613
614
3.44k
void PipelineFragmentContext::refresh_next_report_time() {
615
3.44k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
616
3.44k
    DCHECK(disable == true);
617
3.44k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
618
3.44k
    _disable_period_report.compare_exchange_strong(disable, false);
619
3.44k
}
620
621
5.90M
void PipelineFragmentContext::trigger_report_if_necessary() {
622
5.90M
    if (!_is_report_success) {
623
5.49M
        return;
624
5.49M
    }
625
410k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
626
410k
    if (disable) {
627
6.31k
        return;
628
6.31k
    }
629
404k
    int32_t interval_s = config::pipeline_status_report_interval;
630
404k
    if (interval_s <= 0) {
631
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
632
0
                        "trigger "
633
0
                        "report.";
634
0
    }
635
404k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
636
404k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
637
404k
    if (MonotonicNanos() > next_report_time) {
638
3.45k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
639
3.45k
                                                            std::memory_order_acq_rel)) {
640
7
            return;
641
7
        }
642
3.44k
        if (VLOG_FILE_IS_ON) {
643
0
            VLOG_FILE << "Reporting "
644
0
                      << "profile for query_id " << print_id(_query_id)
645
0
                      << ", fragment id: " << _fragment_id;
646
647
0
            std::stringstream ss;
648
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
649
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
650
0
            if (_runtime_state->load_channel_profile()) {
651
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
652
0
            }
653
654
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
655
0
                      << " profile:\n"
656
0
                      << ss.str();
657
0
        }
658
3.44k
        auto st = send_report(false);
659
3.44k
        if (!st.ok()) {
660
0
            disable = true;
661
0
            _disable_period_report.compare_exchange_strong(disable, false,
662
0
                                                           std::memory_order_acq_rel);
663
0
        }
664
3.44k
    }
665
404k
}
666
667
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
668
316k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
669
316k
    if (_params.fragment.plan.nodes.empty()) {
670
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
671
0
    }
672
673
316k
    int node_idx = 0;
674
675
316k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
676
316k
                                        &node_idx, root, cur_pipe, 0, false, false));
677
678
316k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
679
0
        return Status::InternalError(
680
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
681
0
    }
682
316k
    return Status::OK();
683
316k
}
684
685
Status PipelineFragmentContext::_create_tree_helper(
686
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
687
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
688
504k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
689
    // propagate error case
690
504k
    if (*node_idx >= tnodes.size()) {
691
0
        return Status::InternalError(
692
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
693
0
                *node_idx, tnodes.size());
694
0
    }
695
504k
    const TPlanNode& tnode = tnodes[*node_idx];
696
697
504k
    int num_children = tnodes[*node_idx].num_children;
698
504k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
699
504k
    bool current_require_bucket_distribution = require_bucket_distribution;
700
    // TODO: Create CacheOperator is confused now
701
504k
    OperatorPtr op = nullptr;
702
504k
    OperatorPtr cache_op = nullptr;
703
504k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
704
504k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
705
504k
                                     followed_by_shuffled_operator,
706
504k
                                     current_require_bucket_distribution, cache_op));
707
    // Initialization must be done here. For example, group by expressions in agg will be used to
708
    // decide if a local shuffle should be planed, so it must be initialized here.
709
504k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
710
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
711
504k
    if (parent != nullptr) {
712
        // add to parent's child(s)
713
187k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
714
316k
    } else {
715
316k
        *root = op;
716
316k
    }
717
    /**
718
     * `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).
719
     *
720
     * For plan:
721
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
722
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
723
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
724
     *
725
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
726
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
727
     */
728
504k
    auto required_data_distribution =
729
504k
            cur_pipe->operators().empty()
730
504k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
731
504k
                    : op->required_data_distribution(_runtime_state.get());
732
504k
    current_followed_by_shuffled_operator =
733
504k
            ((followed_by_shuffled_operator ||
734
504k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
735
449k
                                             : op->is_shuffled_operator())) &&
736
504k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
737
504k
            (followed_by_shuffled_operator &&
738
399k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
739
740
504k
    current_require_bucket_distribution =
741
504k
            ((require_bucket_distribution ||
742
504k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
743
453k
                                             : op->is_colocated_operator())) &&
744
504k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
504k
            (require_bucket_distribution &&
746
404k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
504k
    if (num_children == 0) {
749
328k
        _use_serial_source = op->is_serial_operator();
750
328k
    }
751
    // rely on that tnodes is preorder of the plan
752
692k
    for (int i = 0; i < num_children; i++) {
753
187k
        ++*node_idx;
754
187k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
755
187k
                                            current_followed_by_shuffled_operator,
756
187k
                                            current_require_bucket_distribution));
757
758
        // we are expecting a child, but have used all nodes
759
        // this means we have been given a bad tree and must fail
760
187k
        if (*node_idx >= tnodes.size()) {
761
0
            return Status::InternalError(
762
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
763
0
                    "nodes: {}",
764
0
                    *node_idx, tnodes.size());
765
0
        }
766
187k
    }
767
768
504k
    return Status::OK();
769
504k
}
770
771
void PipelineFragmentContext::_inherit_pipeline_properties(
772
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
773
114k
        PipelinePtr pipe_with_sink) {
774
114k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
775
114k
    pipe_with_source->set_num_tasks(_num_instances);
776
114k
    pipe_with_source->set_data_distribution(data_distribution);
777
114k
}
778
779
Status PipelineFragmentContext::_add_local_exchange_impl(
780
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
781
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
782
        const std::map<int, int>& bucket_seq_to_instance_idx,
783
113k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
784
113k
    auto& operators = cur_pipe->operators();
785
113k
    const auto downstream_pipeline_id = cur_pipe->id();
786
113k
    auto local_exchange_id = next_operator_id();
787
    // 1. Create a new pipeline with local exchange sink.
788
113k
    DataSinkOperatorPtr sink;
789
113k
    auto sink_id = next_sink_operator_id();
790
791
    /**
792
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
793
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
794
     */
795
113k
    const bool followed_by_shuffled_operator =
796
113k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
797
113k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
798
113k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
799
113k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
800
113k
                                         followed_by_shuffled_operator && !_use_serial_source;
801
113k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
802
113k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
803
113k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
804
113k
    if (bucket_seq_to_instance_idx.empty() &&
805
113k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
806
11
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
807
11
    }
808
113k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
809
113k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
810
113k
                                          num_buckets, use_global_hash_shuffle,
811
113k
                                          shuffle_idx_to_instance_idx));
812
813
    // 2. Create and initialize LocalExchangeSharedState.
814
113k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
815
113k
            LocalExchangeSharedState::create_shared(_num_instances);
816
113k
    switch (data_distribution.distribution_type) {
817
26.8k
    case ExchangeType::HASH_SHUFFLE:
818
26.8k
        shared_state->exchanger = ShuffleExchanger::create_unique(
819
26.8k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
820
26.8k
                use_global_hash_shuffle ? _total_instances : _num_instances,
821
26.8k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
822
26.8k
                        ? cast_set<int>(
823
26.8k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
824
26.8k
                        : 0);
825
26.8k
        break;
826
497
    case ExchangeType::BUCKET_HASH_SHUFFLE:
827
497
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
828
497
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
829
497
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
497
                        ? cast_set<int>(
831
497
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
497
                        : 0);
833
497
        break;
834
83.5k
    case ExchangeType::PASSTHROUGH:
835
83.5k
        shared_state->exchanger = PassthroughExchanger::create_unique(
836
83.5k
                cur_pipe->num_tasks(), _num_instances,
837
83.5k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
83.5k
                        ? cast_set<int>(
839
83.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
18.4E
                        : 0);
841
83.5k
        break;
842
307
    case ExchangeType::BROADCAST:
843
307
        shared_state->exchanger = BroadcastExchanger::create_unique(
844
307
                cur_pipe->num_tasks(), _num_instances,
845
307
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
307
                        ? cast_set<int>(
847
307
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
307
                        : 0);
849
307
        break;
850
1.90k
    case ExchangeType::PASS_TO_ONE:
851
1.90k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
852
            // If shared hash table is enabled for BJ, hash table will be built by only one task
853
910
            shared_state->exchanger = PassToOneExchanger::create_unique(
854
910
                    cur_pipe->num_tasks(), _num_instances,
855
910
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
856
910
                            ? cast_set<int>(_runtime_state->query_options()
857
910
                                                    .local_exchange_free_blocks_limit)
858
910
                            : 0);
859
994
        } else {
860
994
            shared_state->exchanger = BroadcastExchanger::create_unique(
861
994
                    cur_pipe->num_tasks(), _num_instances,
862
994
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
863
994
                            ? cast_set<int>(_runtime_state->query_options()
864
994
                                                    .local_exchange_free_blocks_limit)
865
994
                            : 0);
866
994
        }
867
1.90k
        break;
868
825
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
869
825
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
870
825
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
871
825
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
872
825
                        ? cast_set<int>(
873
825
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
874
825
                        : 0);
875
825
        break;
876
0
    default:
877
0
        return Status::InternalError("Unsupported local exchange type : " +
878
0
                                     std::to_string((int)data_distribution.distribution_type));
879
113k
    }
880
114k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
881
114k
                                             "LOCAL_EXCHANGE_OPERATOR");
882
114k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
883
114k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
884
885
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
886
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
887
888
    // 3.1 Initialize new pipeline's operator list.
889
114k
    std::copy(operators.begin(), operators.begin() + idx,
890
114k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
891
892
    // 3.2 Erase unused operators in previous pipeline.
893
114k
    operators.erase(operators.begin(), operators.begin() + idx);
894
895
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
896
114k
    OperatorPtr source_op;
897
114k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
898
114k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
899
114k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
900
114k
    if (!operators.empty()) {
901
49.2k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
902
49.2k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
903
49.2k
    }
904
114k
    operators.insert(operators.begin(), source_op);
905
906
    // 5. Set children for two pipelines separately.
907
114k
    std::vector<std::shared_ptr<Pipeline>> new_children;
908
114k
    std::vector<PipelineId> edges_with_source;
909
130k
    for (auto child : cur_pipe->children()) {
910
130k
        bool found = false;
911
144k
        for (auto op : new_pip->operators()) {
912
144k
            if (child->sink()->node_id() == op->node_id()) {
913
11.7k
                new_pip->set_children(child);
914
11.7k
                found = true;
915
11.7k
            };
916
144k
        }
917
130k
        if (!found) {
918
118k
            new_children.push_back(child);
919
118k
            edges_with_source.push_back(child->id());
920
118k
        }
921
130k
    }
922
114k
    new_children.push_back(new_pip);
923
114k
    edges_with_source.push_back(new_pip->id());
924
925
    // 6. Set DAG for new pipelines.
926
114k
    if (!new_pip->children().empty()) {
927
6.50k
        std::vector<PipelineId> edges_with_sink;
928
11.7k
        for (auto child : new_pip->children()) {
929
11.7k
            edges_with_sink.push_back(child->id());
930
11.7k
        }
931
6.50k
        _dag.insert({new_pip->id(), edges_with_sink});
932
6.50k
    }
933
114k
    cur_pipe->set_children(new_children);
934
114k
    _dag[downstream_pipeline_id] = edges_with_source;
935
114k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
936
114k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
937
114k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
938
939
    // 7. Inherit properties from current pipeline.
940
114k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
941
114k
    return Status::OK();
942
114k
}
943
944
Status PipelineFragmentContext::_add_local_exchange(
945
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
946
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
947
        const std::map<int, int>& bucket_seq_to_instance_idx,
948
159k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
949
159k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
950
18.3k
        return Status::OK();
951
18.3k
    }
952
953
141k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
954
53.3k
        return Status::OK();
955
53.3k
    }
956
87.7k
    *do_local_exchange = true;
957
958
87.7k
    auto& operators = cur_pipe->operators();
959
87.7k
    auto total_op_num = operators.size();
960
87.7k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
961
87.7k
    RETURN_IF_ERROR(_add_local_exchange_impl(
962
87.7k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
963
87.7k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
964
965
87.7k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
966
615
            << "total_op_num: " << total_op_num
967
615
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
968
615
            << " new_pip->operators().size(): " << new_pip->operators().size();
969
970
    // There are some local shuffles with relatively heavy operations on the sink.
971
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
972
    // Therefore, local passthrough is used to increase the concurrency of the sink.
973
    // op -> local sink(1) -> local source (n)
974
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
975
87.7k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
976
87.7k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
977
26.7k
        RETURN_IF_ERROR(_add_local_exchange_impl(
978
26.7k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
979
26.7k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
980
26.7k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
981
26.7k
                shuffle_idx_to_instance_idx));
982
26.7k
    }
983
87.7k
    return Status::OK();
984
87.7k
}
985
986
Status PipelineFragmentContext::_plan_local_exchange(
987
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
988
316k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
989
720k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
990
404k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
991
        // Set property if child pipeline is not join operator's child.
992
404k
        if (!_pipelines[pip_idx]->children().empty()) {
993
85.4k
            for (auto& child : _pipelines[pip_idx]->children()) {
994
85.4k
                if (child->sink()->node_id() ==
995
85.4k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
996
76.5k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
997
76.5k
                }
998
85.4k
            }
999
82.8k
        }
1000
1001
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1002
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1003
        // still keep colocate plan after local shuffle
1004
404k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1005
404k
                                             bucket_seq_to_instance_idx,
1006
404k
                                             shuffle_idx_to_instance_idx));
1007
404k
    }
1008
316k
    return Status::OK();
1009
316k
}
1010
1011
Status PipelineFragmentContext::_plan_local_exchange(
1012
        int num_buckets, int pip_idx, PipelinePtr pip,
1013
        const std::map<int, int>& bucket_seq_to_instance_idx,
1014
403k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1015
403k
    int idx = 1;
1016
403k
    bool do_local_exchange = false;
1017
452k
    do {
1018
452k
        auto& ops = pip->operators();
1019
452k
        do_local_exchange = false;
1020
        // Plan local exchange for each operator.
1021
506k
        for (; idx < ops.size();) {
1022
103k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1023
99.4k
                RETURN_IF_ERROR(_add_local_exchange(
1024
99.4k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1025
99.4k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1026
99.4k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1027
99.4k
                        shuffle_idx_to_instance_idx));
1028
99.4k
            }
1029
103k
            if (do_local_exchange) {
1030
                // If local exchange is needed for current operator, we will split this pipeline to
1031
                // two pipelines by local exchange sink/source. And then we need to process remaining
1032
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1033
                // is current operator was already processed) and continue to plan local exchange.
1034
49.4k
                idx = 2;
1035
49.4k
                break;
1036
49.4k
            }
1037
53.7k
            idx++;
1038
53.7k
        }
1039
452k
    } while (do_local_exchange);
1040
403k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1041
59.6k
        RETURN_IF_ERROR(_add_local_exchange(
1042
59.6k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1043
59.6k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1044
59.6k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1045
59.6k
    }
1046
403k
    return Status::OK();
1047
403k
}
1048
1049
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1050
                                                  const std::vector<TExpr>& output_exprs,
1051
                                                  const TPipelineFragmentParams& params,
1052
                                                  const RowDescriptor& row_desc,
1053
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1054
319k
                                                  PipelineId cur_pipeline_id) {
1055
319k
    switch (thrift_sink.type) {
1056
110k
    case TDataSinkType::DATA_STREAM_SINK: {
1057
110k
        if (!thrift_sink.__isset.stream_sink) {
1058
0
            return Status::InternalError("Missing data stream sink.");
1059
0
        }
1060
110k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1061
110k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1062
110k
                params.destinations, _fragment_instance_ids);
1063
110k
        break;
1064
110k
    }
1065
180k
    case TDataSinkType::RESULT_SINK: {
1066
180k
        if (!thrift_sink.__isset.result_sink) {
1067
0
            return Status::InternalError("Missing data buffer sink.");
1068
0
        }
1069
1070
180k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), row_desc,
1071
180k
                                                      output_exprs, thrift_sink.result_sink);
1072
180k
        break;
1073
180k
    }
1074
104
    case TDataSinkType::DICTIONARY_SINK: {
1075
104
        if (!thrift_sink.__isset.dictionary_sink) {
1076
0
            return Status::InternalError("Missing dict sink.");
1077
0
        }
1078
1079
104
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1080
104
                                                    thrift_sink.dictionary_sink);
1081
104
        break;
1082
104
    }
1083
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1084
27.6k
    case TDataSinkType::OLAP_TABLE_SINK: {
1085
27.6k
        if (state->query_options().enable_memtable_on_sink_node &&
1086
27.6k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1087
27.6k
            !config::is_cloud_mode()) {
1088
40
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(pool, next_sink_operator_id(),
1089
40
                                                               row_desc, output_exprs);
1090
27.6k
        } else {
1091
27.6k
            _sink = std::make_shared<OlapTableSinkOperatorX>(pool, next_sink_operator_id(),
1092
27.6k
                                                             row_desc, output_exprs);
1093
27.6k
        }
1094
27.6k
        break;
1095
0
    }
1096
164
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1097
164
        DCHECK(thrift_sink.__isset.olap_table_sink);
1098
164
        DCHECK(state->get_query_ctx() != nullptr);
1099
164
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1100
164
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1101
164
                                                                output_exprs);
1102
164
        break;
1103
0
    }
1104
0
    case TDataSinkType::HIVE_TABLE_SINK: {
1105
0
        if (!thrift_sink.__isset.hive_table_sink) {
1106
0
            return Status::InternalError("Missing hive table sink.");
1107
0
        }
1108
0
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1109
0
                                                         output_exprs);
1110
0
        break;
1111
0
    }
1112
0
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1113
0
        if (!thrift_sink.__isset.iceberg_table_sink) {
1114
0
            return Status::InternalError("Missing iceberg table sink.");
1115
0
        }
1116
0
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1117
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1118
0
                                                                     row_desc, output_exprs);
1119
0
        } else {
1120
0
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1121
0
                                                                row_desc, output_exprs);
1122
0
        }
1123
0
        break;
1124
0
    }
1125
0
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1126
0
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1127
0
            return Status::InternalError("Missing iceberg delete sink.");
1128
0
        }
1129
0
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1130
0
                                                             row_desc, output_exprs);
1131
0
        break;
1132
0
    }
1133
0
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1134
0
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1135
0
            return Status::InternalError("Missing iceberg merge sink.");
1136
0
        }
1137
0
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1138
0
                                                            output_exprs);
1139
0
        break;
1140
0
    }
1141
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1142
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1143
0
            return Status::InternalError("Missing max compute table sink.");
1144
0
        }
1145
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1146
0
                                                       output_exprs);
1147
0
        break;
1148
0
    }
1149
0
    case TDataSinkType::JDBC_TABLE_SINK: {
1150
0
        if (!thrift_sink.__isset.jdbc_table_sink) {
1151
0
            return Status::InternalError("Missing data jdbc sink.");
1152
0
        }
1153
0
        if (config::enable_java_support) {
1154
0
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1155
0
                                                             output_exprs);
1156
0
        } else {
1157
0
            return Status::InternalError(
1158
0
                    "Jdbc table sink is not enabled, you can change be config "
1159
0
                    "enable_java_support to true and restart be.");
1160
0
        }
1161
0
        break;
1162
0
    }
1163
3
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1164
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1165
0
            return Status::InternalError("Missing data buffer sink.");
1166
0
        }
1167
1168
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1169
3
                                                             output_exprs);
1170
3
        break;
1171
3
    }
1172
338
    case TDataSinkType::RESULT_FILE_SINK: {
1173
338
        if (!thrift_sink.__isset.result_file_sink) {
1174
0
            return Status::InternalError("Missing result file sink.");
1175
0
        }
1176
1177
        // Result file sink is not the top sink
1178
338
        if (params.__isset.destinations && !params.destinations.empty()) {
1179
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1180
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1181
0
                    params.destinations, output_exprs, desc_tbl);
1182
338
        } else {
1183
338
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1184
338
                                                              output_exprs);
1185
338
        }
1186
338
        break;
1187
338
    }
1188
578
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1189
578
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1190
578
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1191
578
        auto sink_id = next_sink_operator_id();
1192
578
        const int multi_cast_node_id = sink_id;
1193
578
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1194
        // one sink has multiple sources.
1195
578
        std::vector<int> sources;
1196
2.09k
        for (int i = 0; i < sender_size; ++i) {
1197
1.51k
            auto source_id = next_operator_id();
1198
1.51k
            sources.push_back(source_id);
1199
1.51k
        }
1200
1201
578
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1202
578
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1203
2.09k
        for (int i = 0; i < sender_size; ++i) {
1204
1.51k
            auto new_pipeline = add_pipeline();
1205
            // use to exchange sink
1206
1.51k
            RowDescriptor* exchange_row_desc = nullptr;
1207
1.51k
            {
1208
1.51k
                const auto& tmp_row_desc =
1209
1.51k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1210
1.51k
                                ? RowDescriptor(state->desc_tbl(),
1211
1.51k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1212
1.51k
                                                         .output_tuple_id})
1213
1.51k
                                : row_desc;
1214
1.51k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1215
1.51k
            }
1216
1.51k
            auto source_id = sources[i];
1217
1.51k
            OperatorPtr source_op;
1218
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1219
1.51k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1220
1.51k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1221
1.51k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1222
1.51k
                    /*operator_id=*/source_id);
1223
1.51k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1224
1.51k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1225
            // 2. create and set sink operator of data stream sender for new pipeline
1226
1227
1.51k
            DataSinkOperatorPtr sink_op;
1228
1.51k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1229
1.51k
                    state, *exchange_row_desc, next_sink_operator_id(),
1230
1.51k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1231
1.51k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1232
1233
1.51k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1234
1.51k
            {
1235
1.51k
                TDataSink* t = pool->add(new TDataSink());
1236
1.51k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1237
1.51k
                RETURN_IF_ERROR(sink_op->init(*t));
1238
1.51k
            }
1239
1240
            // 3. set dependency dag
1241
1.51k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1242
1.51k
        }
1243
578
        if (sources.empty()) {
1244
0
            return Status::InternalError("size of sources must be greater than 0");
1245
0
        }
1246
578
        break;
1247
578
    }
1248
578
    case TDataSinkType::BLACKHOLE_SINK: {
1249
3
        if (!thrift_sink.__isset.blackhole_sink) {
1250
0
            return Status::InternalError("Missing blackhole sink.");
1251
0
        }
1252
1253
3
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1254
3
        break;
1255
3
    }
1256
0
    case TDataSinkType::TVF_TABLE_SINK: {
1257
0
        if (!thrift_sink.__isset.tvf_table_sink) {
1258
0
            return Status::InternalError("Missing TVF table sink.");
1259
0
        }
1260
0
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1261
0
                                                        output_exprs);
1262
0
        break;
1263
0
    }
1264
0
    default:
1265
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1266
319k
    }
1267
318k
    return Status::OK();
1268
319k
}
1269
1270
// NOLINTBEGIN(readability-function-size)
1271
// NOLINTBEGIN(readability-function-cognitive-complexity)
1272
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1273
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1274
                                                 PipelinePtr& cur_pipe, int parent_idx,
1275
                                                 int child_idx,
1276
                                                 const bool followed_by_shuffled_operator,
1277
                                                 const bool require_bucket_distribution,
1278
507k
                                                 OperatorPtr& cache_op) {
1279
507k
    std::vector<DataSinkOperatorPtr> sink_ops;
1280
507k
    Defer defer = Defer([&]() {
1281
506k
        if (op) {
1282
506k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1283
506k
        }
1284
506k
        for (auto& s : sink_ops) {
1285
85.1k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1286
85.1k
        }
1287
506k
    });
1288
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1289
    // Therefore, here we need to use a stack-like structure.
1290
507k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1291
507k
    std::stringstream error_msg;
1292
507k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1293
1294
507k
    bool fe_with_old_version = false;
1295
507k
    switch (tnode.node_type) {
1296
159k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1297
159k
        op = std::make_shared<OlapScanOperatorX>(
1298
159k
                pool, tnode, next_operator_id(), descs, _num_instances,
1299
159k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1300
159k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1301
159k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1302
159k
        break;
1303
159k
    }
1304
76
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1305
76
        DCHECK(_query_ctx != nullptr);
1306
76
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1307
76
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1308
76
                                                    _num_instances);
1309
76
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1310
76
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1311
76
        break;
1312
76
    }
1313
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1314
0
        if (config::enable_java_support) {
1315
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1316
0
                                                     _num_instances);
1317
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1318
0
        } else {
1319
0
            return Status::InternalError(
1320
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1321
0
                    "to true and restart be.");
1322
0
        }
1323
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
0
        break;
1325
0
    }
1326
2.64k
    case TPlanNodeType::FILE_SCAN_NODE: {
1327
2.64k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1328
2.64k
                                                 _num_instances);
1329
2.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1330
2.64k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1331
2.64k
        break;
1332
2.64k
    }
1333
0
    case TPlanNodeType::ES_SCAN_NODE:
1334
0
    case TPlanNodeType::ES_HTTP_SCAN_NODE: {
1335
0
        op = std::make_shared<EsScanOperatorX>(pool, tnode, next_operator_id(), descs,
1336
0
                                               _num_instances);
1337
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1338
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1339
0
        break;
1340
0
    }
1341
109k
    case TPlanNodeType::EXCHANGE_NODE: {
1342
109k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1343
109k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1344
18.4E
                                  : 0;
1345
109k
        DCHECK_GT(num_senders, 0);
1346
109k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1347
109k
                                                       num_senders);
1348
109k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1349
109k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1350
109k
        break;
1351
109k
    }
1352
133k
    case TPlanNodeType::AGGREGATION_NODE: {
1353
133k
        if (tnode.agg_node.grouping_exprs.empty() &&
1354
133k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1355
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1356
0
                                         ": group by and output is empty");
1357
0
        }
1358
133k
        bool need_create_cache_op =
1359
133k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1360
133k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1361
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1362
10
            auto cache_source_id = next_operator_id();
1363
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1364
10
                                                        _params.fragment.query_cache_param);
1365
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1366
1367
10
            const auto downstream_pipeline_id = cur_pipe->id();
1368
10
            if (!_dag.contains(downstream_pipeline_id)) {
1369
10
                _dag.insert({downstream_pipeline_id, {}});
1370
10
            }
1371
10
            new_pipe = add_pipeline(cur_pipe);
1372
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1373
1374
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1375
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1376
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1377
10
            return Status::OK();
1378
10
        };
1379
133k
        const bool group_by_limit_opt =
1380
133k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1381
1382
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1383
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1384
133k
        const bool enable_spill = _runtime_state->enable_spill() &&
1385
133k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1386
133k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1387
133k
                                      tnode.agg_node.use_streaming_preaggregation &&
1388
133k
                                      !tnode.agg_node.grouping_exprs.empty();
1389
        // TODO: distinct streaming agg does not support spill.
1390
133k
        const bool can_use_distinct_streaming_agg =
1391
133k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1392
133k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1393
133k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1394
133k
                _params.query_options.enable_distinct_streaming_aggregation;
1395
1396
133k
        if (can_use_distinct_streaming_agg) {
1397
90.7k
            if (need_create_cache_op) {
1398
8
                PipelinePtr new_pipe;
1399
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1400
1401
8
                cache_op = op;
1402
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1403
8
                                                                     tnode, descs);
1404
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1405
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1406
8
                cur_pipe = new_pipe;
1407
90.7k
            } else {
1408
90.7k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1409
90.7k
                                                                     tnode, descs);
1410
90.7k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1411
90.7k
            }
1412
90.7k
        } else if (is_streaming_agg) {
1413
1.00k
            if (need_create_cache_op) {
1414
0
                PipelinePtr new_pipe;
1415
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1416
0
                cache_op = op;
1417
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1418
0
                                                             descs);
1419
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1420
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1421
0
                cur_pipe = new_pipe;
1422
1.00k
            } else {
1423
1.00k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1424
1.00k
                                                             descs);
1425
1.00k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1426
1.00k
            }
1427
41.4k
        } else {
1428
            // create new pipeline to add query cache operator
1429
41.4k
            PipelinePtr new_pipe;
1430
41.4k
            if (need_create_cache_op) {
1431
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1432
2
                cache_op = op;
1433
2
            }
1434
1435
41.4k
            if (enable_spill) {
1436
130
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1437
130
                                                                     next_operator_id(), descs);
1438
41.3k
            } else {
1439
41.3k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1440
41.3k
            }
1441
41.4k
            if (need_create_cache_op) {
1442
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1443
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1444
2
                cur_pipe = new_pipe;
1445
41.4k
            } else {
1446
41.4k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1447
41.4k
            }
1448
1449
41.4k
            const auto downstream_pipeline_id = cur_pipe->id();
1450
41.4k
            if (!_dag.contains(downstream_pipeline_id)) {
1451
40.2k
                _dag.insert({downstream_pipeline_id, {}});
1452
40.2k
            }
1453
41.4k
            cur_pipe = add_pipeline(cur_pipe);
1454
41.4k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1455
1456
41.4k
            if (enable_spill) {
1457
130
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1458
130
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1459
41.3k
            } else {
1460
41.3k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1461
41.3k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1462
41.3k
            }
1463
41.4k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1464
41.4k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1465
41.4k
        }
1466
133k
        break;
1467
133k
    }
1468
133k
    case TPlanNodeType::HASH_JOIN_NODE: {
1469
7.03k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1470
7.03k
                                       tnode.hash_join_node.is_broadcast_join;
1471
7.03k
        const auto enable_spill = _runtime_state->enable_spill();
1472
7.03k
        if (enable_spill && !is_broadcast_join) {
1473
0
            auto tnode_ = tnode;
1474
0
            tnode_.runtime_filters.clear();
1475
0
            auto inner_probe_operator =
1476
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1477
1478
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1479
            // So here use `tnode_` which has no runtime filters.
1480
0
            auto probe_side_inner_sink_operator =
1481
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1482
1483
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1484
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1485
1486
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1487
0
                    pool, tnode_, next_operator_id(), descs);
1488
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1489
0
                                                inner_probe_operator);
1490
0
            op = std::move(probe_operator);
1491
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1492
1493
0
            const auto downstream_pipeline_id = cur_pipe->id();
1494
0
            if (!_dag.contains(downstream_pipeline_id)) {
1495
0
                _dag.insert({downstream_pipeline_id, {}});
1496
0
            }
1497
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1498
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1499
1500
0
            auto inner_sink_operator =
1501
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1502
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1503
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1504
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1505
1506
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1507
0
            sink_ops.push_back(std::move(sink_operator));
1508
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1509
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1510
1511
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1512
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1513
7.03k
        } else {
1514
7.03k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1515
7.03k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1516
1517
7.03k
            const auto downstream_pipeline_id = cur_pipe->id();
1518
7.03k
            if (!_dag.contains(downstream_pipeline_id)) {
1519
6.23k
                _dag.insert({downstream_pipeline_id, {}});
1520
6.23k
            }
1521
7.03k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1522
7.03k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1523
1524
7.03k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1525
7.03k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1526
7.03k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1527
7.03k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1528
1529
7.03k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1530
7.03k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1531
7.03k
        }
1532
7.03k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1533
2.20k
            std::shared_ptr<HashJoinSharedState> shared_state =
1534
2.20k
                    HashJoinSharedState::create_shared(_num_instances);
1535
14.4k
            for (int i = 0; i < _num_instances; i++) {
1536
12.2k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1537
12.2k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1538
12.2k
                sink_dep->set_shared_state(shared_state.get());
1539
12.2k
                shared_state->sink_deps.push_back(sink_dep);
1540
12.2k
            }
1541
2.20k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1542
2.20k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1543
2.20k
            _op_id_to_shared_state.insert(
1544
2.20k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1545
2.20k
        }
1546
7.03k
        break;
1547
7.03k
    }
1548
1.83k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1549
1.83k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1550
1.83k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1551
1552
1.83k
        const auto downstream_pipeline_id = cur_pipe->id();
1553
1.83k
        if (!_dag.contains(downstream_pipeline_id)) {
1554
1.60k
            _dag.insert({downstream_pipeline_id, {}});
1555
1.60k
        }
1556
1.83k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1557
1.83k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1558
1559
1.83k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1560
1.83k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1561
1.83k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1562
1.83k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1563
1.83k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
1.83k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
1.83k
        break;
1566
1.83k
    }
1567
48.1k
    case TPlanNodeType::UNION_NODE: {
1568
48.1k
        int child_count = tnode.num_children;
1569
48.1k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1570
48.1k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1571
1572
48.1k
        const auto downstream_pipeline_id = cur_pipe->id();
1573
48.1k
        if (!_dag.contains(downstream_pipeline_id)) {
1574
47.7k
            _dag.insert({downstream_pipeline_id, {}});
1575
47.7k
        }
1576
49.1k
        for (int i = 0; i < child_count; i++) {
1577
1.01k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1578
1.01k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1579
1.01k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1580
1.01k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1581
1.01k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1582
1.01k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1583
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1584
1.01k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1585
1.01k
        }
1586
48.1k
        break;
1587
48.1k
    }
1588
48.1k
    case TPlanNodeType::SORT_NODE: {
1589
32.2k
        const auto should_spill = _runtime_state->enable_spill() &&
1590
32.2k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1591
32.2k
        const bool use_local_merge =
1592
32.2k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1593
32.2k
        if (should_spill) {
1594
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1595
32.2k
        } else if (use_local_merge) {
1596
30.4k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1597
30.4k
                                                                 descs);
1598
30.4k
        } else {
1599
1.81k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1600
1.81k
        }
1601
32.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1602
1603
32.2k
        const auto downstream_pipeline_id = cur_pipe->id();
1604
32.2k
        if (!_dag.contains(downstream_pipeline_id)) {
1605
32.2k
            _dag.insert({downstream_pipeline_id, {}});
1606
32.2k
        }
1607
32.2k
        cur_pipe = add_pipeline(cur_pipe);
1608
32.2k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1609
1610
32.2k
        if (should_spill) {
1611
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1612
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
32.2k
        } else {
1614
32.2k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1615
32.2k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1616
32.2k
        }
1617
32.2k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1618
32.2k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1619
32.2k
        break;
1620
32.2k
    }
1621
32.2k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1622
63
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1623
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1624
1625
63
        const auto downstream_pipeline_id = cur_pipe->id();
1626
63
        if (!_dag.contains(downstream_pipeline_id)) {
1627
63
            _dag.insert({downstream_pipeline_id, {}});
1628
63
        }
1629
63
        cur_pipe = add_pipeline(cur_pipe);
1630
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1631
1632
63
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1633
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1634
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1635
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1636
63
        break;
1637
63
    }
1638
1.51k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1639
1.51k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1640
1.51k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1641
1642
1.51k
        const auto downstream_pipeline_id = cur_pipe->id();
1643
1.51k
        if (!_dag.contains(downstream_pipeline_id)) {
1644
1.50k
            _dag.insert({downstream_pipeline_id, {}});
1645
1.50k
        }
1646
1.51k
        cur_pipe = add_pipeline(cur_pipe);
1647
1.51k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1648
1649
1.51k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1650
1.51k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1651
1.51k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1652
1.51k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1653
1.51k
        break;
1654
1.51k
    }
1655
1.51k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1656
670
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1657
670
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1658
670
        break;
1659
670
    }
1660
670
    case TPlanNodeType::INTERSECT_NODE: {
1661
114
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1662
114
                                                                      cur_pipe, sink_ops));
1663
114
        break;
1664
114
    }
1665
125
    case TPlanNodeType::EXCEPT_NODE: {
1666
125
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1667
125
                                                                       cur_pipe, sink_ops));
1668
125
        break;
1669
125
    }
1670
313
    case TPlanNodeType::REPEAT_NODE: {
1671
313
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1672
313
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1673
313
        break;
1674
313
    }
1675
917
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1676
917
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1677
917
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1678
917
        break;
1679
917
    }
1680
917
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1681
18
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1682
18
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1683
18
        break;
1684
18
    }
1685
1.43k
    case TPlanNodeType::EMPTY_SET_NODE: {
1686
1.43k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1687
1.43k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1688
1.43k
        break;
1689
1.43k
    }
1690
1.43k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1691
265
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
265
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
265
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1694
265
        break;
1695
265
    }
1696
1.52k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1697
1.52k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1698
1.52k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1699
1.52k
        break;
1700
1.52k
    }
1701
4.88k
    case TPlanNodeType::META_SCAN_NODE: {
1702
4.88k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1703
4.88k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1704
4.88k
        break;
1705
4.88k
    }
1706
4.88k
    case TPlanNodeType::SELECT_NODE: {
1707
338
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1708
338
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1709
338
        break;
1710
338
    }
1711
338
    case TPlanNodeType::REC_CTE_NODE: {
1712
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1713
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1714
1715
151
        const auto downstream_pipeline_id = cur_pipe->id();
1716
151
        if (!_dag.contains(downstream_pipeline_id)) {
1717
148
            _dag.insert({downstream_pipeline_id, {}});
1718
148
        }
1719
1720
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1721
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1722
1723
151
        DataSinkOperatorPtr anchor_sink;
1724
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1725
151
                                                                  op->operator_id(), tnode, descs);
1726
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1727
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1728
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1729
1730
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1731
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1732
1733
151
        DataSinkOperatorPtr rec_sink;
1734
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1735
151
                                                         tnode, descs);
1736
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1737
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1738
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1739
1740
151
        break;
1741
151
    }
1742
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1743
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1744
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
1.95k
        break;
1746
1.95k
    }
1747
1.95k
    default:
1748
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1749
0
                                     print_plan_node_type(tnode.node_type));
1750
507k
    }
1751
506k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1752
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1753
0
        op->set_serial_operator();
1754
0
    }
1755
1756
506k
    return Status::OK();
1757
507k
}
1758
// NOLINTEND(readability-function-cognitive-complexity)
1759
// NOLINTEND(readability-function-size)
1760
1761
template <bool is_intersect>
1762
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1763
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1764
239
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1765
239
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1766
239
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1767
1768
239
    const auto downstream_pipeline_id = cur_pipe->id();
1769
239
    if (!_dag.contains(downstream_pipeline_id)) {
1770
222
        _dag.insert({downstream_pipeline_id, {}});
1771
222
    }
1772
1773
810
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1774
571
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1775
571
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1776
1777
571
        if (child_id == 0) {
1778
239
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1779
239
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1780
332
        } else {
1781
332
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1782
332
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1783
332
        }
1784
571
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1785
571
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1786
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1787
571
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1788
571
    }
1789
1790
239
    return Status::OK();
1791
239
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1764
114
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1765
114
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1766
114
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1767
1768
114
    const auto downstream_pipeline_id = cur_pipe->id();
1769
114
    if (!_dag.contains(downstream_pipeline_id)) {
1770
105
        _dag.insert({downstream_pipeline_id, {}});
1771
105
    }
1772
1773
420
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1774
306
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1775
306
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1776
1777
306
        if (child_id == 0) {
1778
114
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1779
114
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1780
192
        } else {
1781
192
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1782
192
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1783
192
        }
1784
306
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1785
306
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1786
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1787
306
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1788
306
    }
1789
1790
114
    return Status::OK();
1791
114
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1764
125
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1765
125
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1766
125
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1767
1768
125
    const auto downstream_pipeline_id = cur_pipe->id();
1769
125
    if (!_dag.contains(downstream_pipeline_id)) {
1770
117
        _dag.insert({downstream_pipeline_id, {}});
1771
117
    }
1772
1773
390
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1774
265
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1775
265
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1776
1777
265
        if (child_id == 0) {
1778
125
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1779
125
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1780
140
        } else {
1781
140
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1782
140
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1783
140
        }
1784
265
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1785
265
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1786
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1787
265
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1788
265
    }
1789
1790
125
    return Status::OK();
1791
125
}
1792
1793
317k
Status PipelineFragmentContext::submit() {
1794
317k
    if (_submitted) {
1795
0
        return Status::InternalError("submitted");
1796
0
    }
1797
317k
    _submitted = true;
1798
1799
317k
    int submit_tasks = 0;
1800
317k
    Status st;
1801
317k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1802
954k
    for (auto& task : _tasks) {
1803
1.66M
        for (auto& t : task) {
1804
1.66M
            st = scheduler->submit(t.first);
1805
1.66M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1806
1.66M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1807
1.66M
            if (!st) {
1808
0
                cancel(Status::InternalError("submit context to executor fail"));
1809
0
                std::lock_guard<std::mutex> l(_task_mutex);
1810
0
                _total_tasks = submit_tasks;
1811
0
                break;
1812
0
            }
1813
1.66M
            submit_tasks++;
1814
1.66M
        }
1815
954k
    }
1816
317k
    if (!st.ok()) {
1817
0
        bool need_remove = false;
1818
0
        {
1819
0
            std::lock_guard<std::mutex> l(_task_mutex);
1820
0
            if (_closed_tasks >= _total_tasks) {
1821
0
                need_remove = _close_fragment_instance();
1822
0
            }
1823
0
        }
1824
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1825
0
        if (need_remove) {
1826
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1827
0
        }
1828
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1829
0
                                     BackendOptions::get_localhost());
1830
317k
    } else {
1831
317k
        return st;
1832
317k
    }
1833
317k
}
1834
1835
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1836
0
    if (_runtime_state->enable_profile()) {
1837
0
        std::stringstream ss;
1838
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1839
0
            runtime_profile_ptr->pretty_print(&ss);
1840
0
        }
1841
1842
0
        if (_runtime_state->load_channel_profile()) {
1843
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1844
0
        }
1845
1846
0
        auto profile_str =
1847
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1848
0
                            this->_fragment_id, extra_info, ss.str());
1849
0
        LOG_LONG_STRING(INFO, profile_str);
1850
0
    }
1851
0
}
1852
// If all pipeline tasks binded to the fragment instance are finished, then we could
1853
// close the fragment instance.
1854
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1855
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1856
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1857
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1858
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1859
// (via debug_string()).
1860
319k
bool PipelineFragmentContext::_close_fragment_instance() {
1861
319k
    if (_is_fragment_instance_closed) {
1862
0
        return false;
1863
0
    }
1864
319k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1865
319k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1866
319k
    if (!_need_notify_close) {
1867
315k
        auto st = send_report(true);
1868
315k
        if (!st) {
1869
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1870
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1871
0
        }
1872
315k
    }
1873
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1874
    // Since stream load does not have someting like coordinator on FE, so
1875
    // backend can not report profile to FE, ant its profile can not be shown
1876
    // in the same way with other query. So we print the profile content to info log.
1877
1878
319k
    if (_runtime_state->enable_profile() &&
1879
319k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1880
2.09k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1881
2.09k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1882
0
        std::stringstream ss;
1883
        // Compute the _local_time_percent before pretty_print the runtime_profile
1884
        // Before add this operation, the print out like that:
1885
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1886
        // After add the operation, the print out like that:
1887
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1888
        // We can easily know the exec node execute time without child time consumed.
1889
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1890
0
            runtime_profile_ptr->pretty_print(&ss);
1891
0
        }
1892
1893
0
        if (_runtime_state->load_channel_profile()) {
1894
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1895
0
        }
1896
1897
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1898
0
    }
1899
1900
319k
    if (_query_ctx->enable_profile()) {
1901
2.09k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1902
2.09k
                                         collect_realtime_load_channel_profile());
1903
2.09k
    }
1904
1905
    // Return whether the caller needs to remove from the pipeline map.
1906
    // The caller must do this after releasing _task_mutex.
1907
319k
    return !_need_notify_close;
1908
319k
}
1909
1910
1.66M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1911
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1912
1.66M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1913
1.66M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1914
520k
        if (_dag.contains(pipeline_id)) {
1915
315k
            for (auto dep : _dag[pipeline_id]) {
1916
315k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1917
315k
            }
1918
241k
        }
1919
520k
    }
1920
1.66M
    bool need_remove = false;
1921
1.66M
    {
1922
1.66M
        std::lock_guard<std::mutex> l(_task_mutex);
1923
1.66M
        ++_closed_tasks;
1924
1.66M
        if (_closed_tasks >= _total_tasks) {
1925
319k
            need_remove = _close_fragment_instance();
1926
319k
        }
1927
1.66M
    }
1928
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1929
1.66M
    if (need_remove) {
1930
315k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1931
315k
    }
1932
1.66M
}
1933
1934
40.5k
std::string PipelineFragmentContext::get_load_error_url() {
1935
40.5k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1936
0
        return to_load_error_http_path(str);
1937
0
    }
1938
106k
    for (auto& tasks : _tasks) {
1939
182k
        for (auto& task : tasks) {
1940
182k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1941
154
                return to_load_error_http_path(str);
1942
154
            }
1943
182k
        }
1944
106k
    }
1945
40.3k
    return "";
1946
40.5k
}
1947
1948
40.5k
std::string PipelineFragmentContext::get_first_error_msg() {
1949
40.5k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
1950
0
        return str;
1951
0
    }
1952
106k
    for (auto& tasks : _tasks) {
1953
182k
        for (auto& task : tasks) {
1954
182k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
1955
154
                return str;
1956
154
            }
1957
182k
        }
1958
106k
    }
1959
40.3k
    return "";
1960
40.5k
}
1961
1962
319k
Status PipelineFragmentContext::send_report(bool done) {
1963
319k
    Status exec_status = _query_ctx->exec_status();
1964
    // If plan is done successfully, but _is_report_success is false,
1965
    // no need to send report.
1966
    // Load will set _is_report_success to true because load wants to know
1967
    // the process.
1968
319k
    if (!_is_report_success && done && exec_status.ok()) {
1969
284k
        return Status::OK();
1970
284k
    }
1971
1972
    // If both _is_report_success and _is_report_on_cancel are false,
1973
    // which means no matter query is success or failed, no report is needed.
1974
    // This may happen when the query limit reached and
1975
    // a internal cancellation being processed
1976
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
1977
    // be set to false, to avoid sending fault report to FE.
1978
35.3k
    if (!_is_report_success && !_is_report_on_cancel) {
1979
143
        if (done) {
1980
            // 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.
1981
143
            return Status::OK();
1982
143
        }
1983
0
        return Status::NeedSendAgain("");
1984
143
    }
1985
1986
35.1k
    std::vector<RuntimeState*> runtime_states;
1987
1988
84.9k
    for (auto& tasks : _tasks) {
1989
135k
        for (auto& task : tasks) {
1990
135k
            runtime_states.push_back(task.second.get());
1991
135k
        }
1992
84.9k
    }
1993
1994
35.1k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
1995
35.1k
                                        ? get_load_error_url()
1996
35.1k
                                        : _query_ctx->get_load_error_url();
1997
35.1k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
1998
35.1k
                                          ? get_first_error_msg()
1999
35.1k
                                          : _query_ctx->get_first_error_msg();
2000
2001
35.1k
    ReportStatusRequest req {.status = exec_status,
2002
35.1k
                             .runtime_states = runtime_states,
2003
35.1k
                             .done = done || !exec_status.ok(),
2004
35.1k
                             .coord_addr = _query_ctx->coord_addr,
2005
35.1k
                             .query_id = _query_id,
2006
35.1k
                             .fragment_id = _fragment_id,
2007
35.1k
                             .fragment_instance_id = TUniqueId(),
2008
35.1k
                             .backend_num = -1,
2009
35.1k
                             .runtime_state = _runtime_state.get(),
2010
35.1k
                             .load_error_url = load_eror_url,
2011
35.1k
                             .first_error_msg = first_error_msg,
2012
35.1k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2013
2014
35.1k
    return _report_status_cb(
2015
35.1k
            req, std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()));
2016
35.3k
}
2017
2018
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2019
0
    size_t res = 0;
2020
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2021
    // here to traverse the vector.
2022
0
    for (const auto& task_instances : _tasks) {
2023
0
        for (const auto& task : task_instances) {
2024
0
            if (task.first->is_running()) {
2025
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2026
0
                                      << " is running, task: " << (void*)task.first.get()
2027
0
                                      << ", is_running: " << task.first->is_running();
2028
0
                *has_running_task = true;
2029
0
                return 0;
2030
0
            }
2031
2032
0
            size_t revocable_size = task.first->get_revocable_size();
2033
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2034
0
                res += revocable_size;
2035
0
            }
2036
0
        }
2037
0
    }
2038
0
    return res;
2039
0
}
2040
2041
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2042
0
    std::vector<PipelineTask*> revocable_tasks;
2043
0
    for (const auto& task_instances : _tasks) {
2044
0
        for (const auto& task : task_instances) {
2045
0
            size_t revocable_size_ = task.first->get_revocable_size();
2046
2047
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2048
0
                revocable_tasks.emplace_back(task.first.get());
2049
0
            }
2050
0
        }
2051
0
    }
2052
0
    return revocable_tasks;
2053
0
}
2054
2055
123
std::string PipelineFragmentContext::debug_string() {
2056
123
    std::lock_guard<std::mutex> l(_task_mutex);
2057
123
    fmt::memory_buffer debug_string_buffer;
2058
123
    fmt::format_to(debug_string_buffer,
2059
123
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2060
123
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2061
123
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2062
507
    for (size_t j = 0; j < _tasks.size(); j++) {
2063
384
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2064
927
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2065
543
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2066
543
                           _tasks[j][i].first->debug_string());
2067
543
        }
2068
384
    }
2069
2070
123
    return fmt::to_string(debug_string_buffer);
2071
123
}
2072
2073
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2074
2.09k
PipelineFragmentContext::collect_realtime_profile() const {
2075
2.09k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2076
2077
    // we do not have mutex to protect pipeline_id_to_profile
2078
    // so we need to make sure this funciton is invoked after fragment context
2079
    // has already been prepared.
2080
2.09k
    if (!_prepared) {
2081
0
        std::string msg =
2082
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2083
0
        DCHECK(false) << msg;
2084
0
        LOG_ERROR(msg);
2085
0
        return res;
2086
0
    }
2087
2088
    // Make sure first profile is fragment level profile
2089
2.09k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2090
2.09k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2091
2.09k
    res.push_back(fragment_profile);
2092
2093
    // pipeline_id_to_profile is initialized in prepare stage
2094
3.87k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2095
3.87k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2096
3.87k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2097
3.87k
        res.push_back(profile_ptr);
2098
3.87k
    }
2099
2100
2.09k
    return res;
2101
2.09k
}
2102
2103
std::shared_ptr<TRuntimeProfileTree>
2104
2.09k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2105
    // we do not have mutex to protect pipeline_id_to_profile
2106
    // so we need to make sure this funciton is invoked after fragment context
2107
    // has already been prepared.
2108
2.09k
    if (!_prepared) {
2109
0
        std::string msg =
2110
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2111
0
        DCHECK(false) << msg;
2112
0
        LOG_ERROR(msg);
2113
0
        return nullptr;
2114
0
    }
2115
2116
5.75k
    for (const auto& tasks : _tasks) {
2117
11.2k
        for (const auto& task : tasks) {
2118
11.2k
            if (task.second->load_channel_profile() == nullptr) {
2119
0
                continue;
2120
0
            }
2121
2122
11.2k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2123
2124
11.2k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2125
11.2k
                                                           _runtime_state->profile_level());
2126
11.2k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2127
11.2k
        }
2128
5.75k
    }
2129
2130
2.09k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2131
2.09k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2132
2.09k
                                                      _runtime_state->profile_level());
2133
2.09k
    return load_channel_profile;
2134
2.09k
}
2135
2136
// Collect runtime filter IDs registered by all tasks in this PFC.
2137
// Used during recursive CTE stage transitions to know which filters to deregister
2138
// before creating the new PFC for the next recursion round.
2139
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2140
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2141
// the vector sizes do not change, and individual RuntimeState filter sets are
2142
// written only during open() which has completed by the time we reach rerun.
2143
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2144
3.28k
    std::set<int> result;
2145
5.53k
    for (const auto& _task : _tasks) {
2146
9.45k
        for (const auto& task : _task) {
2147
9.45k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2148
9.45k
            result.merge(set);
2149
9.45k
        }
2150
5.53k
    }
2151
3.28k
    if (_runtime_state) {
2152
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2153
3.28k
        result.merge(set);
2154
3.28k
    }
2155
3.28k
    return result;
2156
3.28k
}
2157
2158
320k
void PipelineFragmentContext::_release_resource() {
2159
320k
    std::lock_guard<std::mutex> l(_task_mutex);
2160
    // The memory released by the query end is recorded in the query mem tracker.
2161
320k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2162
320k
    auto st = _query_ctx->exec_status();
2163
956k
    for (auto& _task : _tasks) {
2164
956k
        if (!_task.empty()) {
2165
956k
            _call_back(_task.front().first->runtime_state(), &st);
2166
956k
        }
2167
956k
    }
2168
320k
    _tasks.clear();
2169
320k
    _dag.clear();
2170
320k
    _pip_id_to_pipeline.clear();
2171
320k
    _pipelines.clear();
2172
320k
    _sink.reset();
2173
320k
    _root_op.reset();
2174
320k
    _runtime_filter_mgr_map.clear();
2175
320k
    _op_id_to_shared_state.clear();
2176
320k
}
2177
2178
#include "common/compile_check_end.h"
2179
} // namespace doris