Coverage Report

Created: 2026-04-14 10:14

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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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
PipelineFragmentContext::PipelineFragmentContext(
131
        TUniqueId query_id, const TPipelineFragmentParams& request,
132
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
133
        const std::function<void(RuntimeState*, Status*)>& call_back,
134
        report_status_callback report_status_cb)
135
431k
        : _query_id(std::move(query_id)),
136
431k
          _fragment_id(request.fragment_id),
137
431k
          _exec_env(exec_env),
138
431k
          _query_ctx(std::move(query_ctx)),
139
431k
          _call_back(call_back),
140
431k
          _is_report_on_cancel(true),
141
431k
          _report_status_cb(std::move(report_status_cb)),
142
431k
          _params(request),
143
431k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
144
431k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
145
431k
                                                               : false) {
146
431k
    _fragment_watcher.start();
147
431k
}
148
149
431k
PipelineFragmentContext::~PipelineFragmentContext() {
150
431k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
151
431k
            .tag("query_id", print_id(_query_id))
152
431k
            .tag("fragment_id", _fragment_id);
153
431k
    _release_resource();
154
431k
    {
155
        // The memory released by the query end is recorded in the query mem tracker.
156
431k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
157
431k
        _runtime_state.reset();
158
431k
        _query_ctx.reset();
159
431k
    }
160
431k
}
161
162
135
bool PipelineFragmentContext::is_timeout(timespec now) const {
163
135
    if (_timeout <= 0) {
164
0
        return false;
165
0
    }
166
135
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
167
135
}
168
169
// notify_close() transitions the PFC from "waiting for external close notification" to
170
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
171
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
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9.80k
bool PipelineFragmentContext::notify_close() {
174
9.80k
    bool all_closed = false;
175
9.80k
    bool need_remove = false;
176
9.80k
    {
177
9.80k
        std::lock_guard<std::mutex> l(_task_mutex);
178
9.80k
        if (_closed_tasks >= _total_tasks) {
179
3.44k
            if (_need_notify_close) {
180
                // Fragment was cancelled and waiting for notify to close.
181
                // Record that we need to remove from fragment mgr, but do it
182
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
184
                // first, then _task_mutex via debug_string()).
185
3.38k
                need_remove = true;
186
3.38k
            }
187
3.44k
            all_closed = true;
188
3.44k
        }
189
        // make fragment release by self after cancel
190
9.80k
        _need_notify_close = false;
191
9.80k
    }
192
9.80k
    if (need_remove) {
193
3.38k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
194
3.38k
    }
195
9.80k
    return all_closed;
196
9.80k
}
197
198
// Must not add lock in this method. Because it will call query ctx cancel. And
199
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
200
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
202
6.32k
void PipelineFragmentContext::cancel(const Status reason) {
203
6.32k
    LOG_INFO("PipelineFragmentContext::cancel")
204
6.32k
            .tag("query_id", print_id(_query_id))
205
6.32k
            .tag("fragment_id", _fragment_id)
206
6.32k
            .tag("reason", reason.to_string());
207
6.32k
    if (notify_close()) {
208
82
        return;
209
82
    }
210
    // Timeout is a special error code, we need print current stack to debug timeout issue.
211
6.23k
    if (reason.is<ErrorCode::TIMEOUT>()) {
212
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
213
1
                                   debug_string());
214
1
        LOG_LONG_STRING(WARNING, dbg_str);
215
1
    }
216
217
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
218
6.23k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
219
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
220
0
                    debug_string());
221
0
    }
222
223
6.23k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
224
12
        print_profile("cancel pipeline, reason: " + reason.to_string());
225
12
    }
226
227
6.23k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
228
23
        _query_ctx->set_load_error_url(error_url);
229
23
    }
230
231
6.23k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
232
23
        _query_ctx->set_first_error_msg(first_error_msg);
233
23
    }
234
235
6.23k
    _query_ctx->cancel(reason, _fragment_id);
236
6.23k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
237
454
        _is_report_on_cancel = false;
238
5.78k
    } else {
239
31.4k
        for (auto& id : _fragment_instance_ids) {
240
31.4k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
241
31.4k
        }
242
5.78k
    }
243
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
244
    // For stream load the fragment's query_id == load id, it is set in FE.
245
6.23k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
246
6.23k
    if (stream_load_ctx != nullptr) {
247
31
        stream_load_ctx->pipe->cancel(reason.to_string());
248
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
249
        // We need to set the error URL at this point to ensure error information is properly
250
        // propagated to the client.
251
31
        stream_load_ctx->error_url = get_load_error_url();
252
31
        stream_load_ctx->first_error_msg = get_first_error_msg();
253
31
    }
254
255
32.4k
    for (auto& tasks : _tasks) {
256
78.5k
        for (auto& task : tasks) {
257
78.5k
            task.first->unblock_all_dependencies();
258
78.5k
        }
259
32.4k
    }
260
6.23k
}
261
262
672k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
263
672k
    PipelineId id = _next_pipeline_id++;
264
672k
    auto pipeline = std::make_shared<Pipeline>(
265
672k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
266
672k
            parent ? parent->num_tasks() : _num_instances);
267
672k
    if (idx >= 0) {
268
112k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
269
559k
    } else {
270
559k
        _pipelines.emplace_back(pipeline);
271
559k
    }
272
672k
    if (parent) {
273
236k
        parent->set_children(pipeline);
274
236k
    }
275
672k
    return pipeline;
276
672k
}
277
278
430k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
279
430k
    {
280
430k
        SCOPED_TIMER(_build_pipelines_timer);
281
        // 2. Build pipelines with operators in this fragment.
282
430k
        auto root_pipeline = add_pipeline();
283
430k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
284
430k
                                         &_root_op, root_pipeline));
285
286
        // 3. Create sink operator
287
430k
        if (!_params.fragment.__isset.output_sink) {
288
0
            return Status::InternalError("No output sink in this fragment!");
289
0
        }
290
430k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
291
430k
                                          _params.fragment.output_exprs, _params,
292
430k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
293
430k
                                          *_desc_tbl, root_pipeline->id()));
294
430k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
295
430k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
296
297
559k
        for (PipelinePtr& pipeline : _pipelines) {
298
18.4E
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
299
559k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
300
559k
        }
301
430k
    }
302
    // 4. Build local exchanger
303
430k
    if (_runtime_state->enable_local_shuffle()) {
304
428k
        SCOPED_TIMER(_plan_local_exchanger_timer);
305
428k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
306
428k
                                             _params.bucket_seq_to_instance_idx,
307
428k
                                             _params.shuffle_idx_to_instance_idx));
308
428k
    }
309
310
    // 5. Initialize global states in pipelines.
311
673k
    for (PipelinePtr& pipeline : _pipelines) {
312
673k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
313
673k
        pipeline->children().clear();
314
673k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
315
673k
    }
316
317
429k
    {
318
429k
        SCOPED_TIMER(_build_tasks_timer);
319
        // 6. Build pipeline tasks and initialize local state.
320
429k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
321
429k
    }
322
323
429k
    return Status::OK();
324
429k
}
325
326
431k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
327
431k
    if (_prepared) {
328
0
        return Status::InternalError("Already prepared");
329
0
    }
330
431k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
331
431k
        _timeout = _params.query_options.execution_timeout;
332
431k
    }
333
334
431k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
335
431k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
336
431k
    SCOPED_TIMER(_prepare_timer);
337
431k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
338
431k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
339
431k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
340
431k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
341
431k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
342
431k
    {
343
431k
        SCOPED_TIMER(_init_context_timer);
344
431k
        cast_set(_num_instances, _params.local_params.size());
345
431k
        _total_instances =
346
431k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
347
348
431k
        auto* fragment_context = this;
349
350
431k
        if (_params.query_options.__isset.is_report_success) {
351
429k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
352
429k
        }
353
354
        // 1. Set up the global runtime state.
355
431k
        _runtime_state = RuntimeState::create_unique(
356
431k
                _params.query_id, _params.fragment_id, _params.query_options,
357
431k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
358
431k
        _runtime_state->set_task_execution_context(shared_from_this());
359
431k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
360
431k
        if (_params.__isset.backend_id) {
361
428k
            _runtime_state->set_backend_id(_params.backend_id);
362
428k
        }
363
431k
        if (_params.__isset.import_label) {
364
239
            _runtime_state->set_import_label(_params.import_label);
365
239
        }
366
431k
        if (_params.__isset.db_name) {
367
191
            _runtime_state->set_db_name(_params.db_name);
368
191
        }
369
431k
        if (_params.__isset.load_job_id) {
370
0
            _runtime_state->set_load_job_id(_params.load_job_id);
371
0
        }
372
373
431k
        if (_params.is_simplified_param) {
374
145k
            _desc_tbl = _query_ctx->desc_tbl;
375
285k
        } else {
376
285k
            DCHECK(_params.__isset.desc_tbl);
377
285k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
378
285k
                                                  &_desc_tbl));
379
285k
        }
380
431k
        _runtime_state->set_desc_tbl(_desc_tbl);
381
431k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
382
431k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
383
431k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
384
431k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
385
386
        // init fragment_instance_ids
387
431k
        const auto target_size = _params.local_params.size();
388
431k
        _fragment_instance_ids.resize(target_size);
389
1.68M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
390
1.25M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
391
1.25M
            _fragment_instance_ids[i] = fragment_instance_id;
392
1.25M
        }
393
431k
    }
394
395
431k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
396
397
430k
    _init_next_report_time();
398
399
430k
    _prepared = true;
400
430k
    return Status::OK();
401
431k
}
402
403
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
404
        int instance_idx,
405
1.25M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
406
1.25M
    const auto& local_params = _params.local_params[instance_idx];
407
1.25M
    auto fragment_instance_id = local_params.fragment_instance_id;
408
1.25M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
409
1.25M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
410
1.25M
    auto get_shared_state = [&](PipelinePtr pipeline)
411
1.25M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
412
2.04M
                                       std::vector<std::shared_ptr<Dependency>>>> {
413
2.04M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
414
2.04M
                                std::vector<std::shared_ptr<Dependency>>>>
415
2.04M
                shared_state_map;
416
2.72M
        for (auto& op : pipeline->operators()) {
417
2.72M
            auto source_id = op->operator_id();
418
2.72M
            if (auto iter = _op_id_to_shared_state.find(source_id);
419
2.72M
                iter != _op_id_to_shared_state.end()) {
420
803k
                shared_state_map.insert({source_id, iter->second});
421
803k
            }
422
2.72M
        }
423
2.04M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
424
2.04M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
425
2.04M
                iter != _op_id_to_shared_state.end()) {
426
313k
                shared_state_map.insert({sink_to_source_id, iter->second});
427
313k
            }
428
2.04M
        }
429
2.04M
        return shared_state_map;
430
2.04M
    };
431
432
3.79M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
433
2.53M
        auto& pipeline = _pipelines[pip_idx];
434
2.53M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
435
2.04M
            auto task_runtime_state = RuntimeState::create_unique(
436
2.04M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
437
2.04M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
438
2.04M
            {
439
                // Initialize runtime state for this task
440
2.04M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
441
442
2.04M
                task_runtime_state->set_task_execution_context(shared_from_this());
443
2.04M
                task_runtime_state->set_be_number(local_params.backend_num);
444
445
2.04M
                if (_params.__isset.backend_id) {
446
2.04M
                    task_runtime_state->set_backend_id(_params.backend_id);
447
2.04M
                }
448
2.04M
                if (_params.__isset.import_label) {
449
240
                    task_runtime_state->set_import_label(_params.import_label);
450
240
                }
451
2.04M
                if (_params.__isset.db_name) {
452
192
                    task_runtime_state->set_db_name(_params.db_name);
453
192
                }
454
2.04M
                if (_params.__isset.load_job_id) {
455
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
456
0
                }
457
2.04M
                if (_params.__isset.wal_id) {
458
114
                    task_runtime_state->set_wal_id(_params.wal_id);
459
114
                }
460
2.04M
                if (_params.__isset.content_length) {
461
31
                    task_runtime_state->set_content_length(_params.content_length);
462
31
                }
463
464
2.04M
                task_runtime_state->set_desc_tbl(_desc_tbl);
465
2.04M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
466
2.04M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
467
2.04M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
468
2.04M
                task_runtime_state->set_max_operator_id(max_operator_id());
469
2.04M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
470
2.04M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
471
2.04M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
472
473
2.04M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
474
2.04M
            }
475
2.04M
            auto cur_task_id = _total_tasks++;
476
2.04M
            task_runtime_state->set_task_id(cur_task_id);
477
2.04M
            task_runtime_state->set_task_num(pipeline->num_tasks());
478
2.04M
            auto task = std::make_shared<PipelineTask>(
479
2.04M
                    pipeline, cur_task_id, task_runtime_state.get(),
480
2.04M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
481
2.04M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
482
2.04M
                    instance_idx);
483
2.04M
            pipeline->incr_created_tasks(instance_idx, task.get());
484
2.04M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
485
2.04M
            _tasks[instance_idx].emplace_back(
486
2.04M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
487
2.04M
                            std::move(task), std::move(task_runtime_state)});
488
2.04M
        }
489
2.53M
    }
490
491
    /**
492
         * Build DAG for pipeline tasks.
493
         * For example, we have
494
         *
495
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
496
         *            \                      /
497
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
498
         *                 \                          /
499
         *               JoinProbeOperator2 (Pipeline1)
500
         *
501
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
502
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
503
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
504
         *
505
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
506
         * and JoinProbeOperator2.
507
         */
508
2.53M
    for (auto& _pipeline : _pipelines) {
509
2.53M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
510
2.04M
            auto* task = pipeline_id_to_task[_pipeline->id()];
511
2.04M
            DCHECK(task != nullptr);
512
513
            // If this task has upstream dependency, then inject it into this task.
514
2.04M
            if (_dag.contains(_pipeline->id())) {
515
1.28M
                auto& deps = _dag[_pipeline->id()];
516
2.05M
                for (auto& dep : deps) {
517
2.05M
                    if (pipeline_id_to_task.contains(dep)) {
518
1.08M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
519
1.08M
                        if (ss) {
520
466k
                            task->inject_shared_state(ss);
521
614k
                        } else {
522
614k
                            pipeline_id_to_task[dep]->inject_shared_state(
523
614k
                                    task->get_source_shared_state());
524
614k
                        }
525
1.08M
                    }
526
2.05M
                }
527
1.28M
            }
528
2.04M
        }
529
2.53M
    }
530
3.79M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
531
2.53M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
532
2.04M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
533
2.04M
            DCHECK(pipeline_id_to_profile[pip_idx]);
534
2.04M
            std::vector<TScanRangeParams> scan_ranges;
535
2.04M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
536
2.04M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
537
345k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
538
345k
            }
539
2.04M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
540
2.04M
                                                             _params.fragment.output_sink));
541
2.04M
        }
542
2.53M
    }
543
1.26M
    {
544
1.26M
        std::lock_guard<std::mutex> l(_state_map_lock);
545
1.26M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
546
1.26M
    }
547
1.26M
    return Status::OK();
548
1.25M
}
549
550
430k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
551
430k
    _total_tasks = 0;
552
430k
    _closed_tasks = 0;
553
430k
    const auto target_size = _params.local_params.size();
554
430k
    _tasks.resize(target_size);
555
430k
    _runtime_filter_mgr_map.resize(target_size);
556
1.10M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
557
672k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
558
672k
    }
559
430k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
560
561
430k
    if (target_size > 1 &&
562
430k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
563
144k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
564
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
565
17.4k
        std::vector<Status> prepare_status(target_size);
566
17.4k
        int submitted_tasks = 0;
567
17.4k
        Status submit_status;
568
17.4k
        CountDownLatch latch((int)target_size);
569
303k
        for (int i = 0; i < target_size; i++) {
570
285k
            submit_status = thread_pool->submit_func([&, i]() {
571
285k
                SCOPED_ATTACH_TASK(_query_ctx.get());
572
285k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
573
285k
                latch.count_down();
574
285k
            });
575
285k
            if (LIKELY(submit_status.ok())) {
576
285k
                submitted_tasks++;
577
18.4E
            } else {
578
18.4E
                break;
579
18.4E
            }
580
285k
        }
581
17.4k
        latch.arrive_and_wait(target_size - submitted_tasks);
582
17.4k
        if (UNLIKELY(!submit_status.ok())) {
583
0
            return submit_status;
584
0
        }
585
303k
        for (int i = 0; i < submitted_tasks; i++) {
586
285k
            if (!prepare_status[i].ok()) {
587
0
                return prepare_status[i];
588
0
            }
589
285k
        }
590
413k
    } else {
591
1.38M
        for (int i = 0; i < target_size; i++) {
592
973k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
593
973k
        }
594
413k
    }
595
430k
    _pipeline_parent_map.clear();
596
430k
    _op_id_to_shared_state.clear();
597
598
430k
    return Status::OK();
599
430k
}
600
601
428k
void PipelineFragmentContext::_init_next_report_time() {
602
428k
    auto interval_s = config::pipeline_status_report_interval;
603
428k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
604
41.2k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
605
41.2k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
606
        // We don't want to wait longer than it takes to run the entire fragment.
607
41.2k
        _previous_report_time =
608
41.2k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
609
41.2k
        _disable_period_report = false;
610
41.2k
    }
611
428k
}
612
613
4.75k
void PipelineFragmentContext::refresh_next_report_time() {
614
4.75k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
615
4.75k
    DCHECK(disable == true);
616
4.75k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
617
4.75k
    _disable_period_report.compare_exchange_strong(disable, false);
618
4.75k
}
619
620
7.44M
void PipelineFragmentContext::trigger_report_if_necessary() {
621
7.44M
    if (!_is_report_success) {
622
6.92M
        return;
623
6.92M
    }
624
520k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
625
520k
    if (disable) {
626
8.38k
        return;
627
8.38k
    }
628
511k
    int32_t interval_s = config::pipeline_status_report_interval;
629
511k
    if (interval_s <= 0) {
630
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
631
0
                        "trigger "
632
0
                        "report.";
633
0
    }
634
511k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
635
511k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
636
511k
    if (MonotonicNanos() > next_report_time) {
637
4.77k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
638
4.77k
                                                            std::memory_order_acq_rel)) {
639
18
            return;
640
18
        }
641
4.75k
        if (VLOG_FILE_IS_ON) {
642
0
            VLOG_FILE << "Reporting "
643
0
                      << "profile for query_id " << print_id(_query_id)
644
0
                      << ", fragment id: " << _fragment_id;
645
646
0
            std::stringstream ss;
647
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
648
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
649
0
            if (_runtime_state->load_channel_profile()) {
650
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
651
0
            }
652
653
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
654
0
                      << " profile:\n"
655
0
                      << ss.str();
656
0
        }
657
4.75k
        auto st = send_report(false);
658
4.75k
        if (!st.ok()) {
659
0
            disable = true;
660
0
            _disable_period_report.compare_exchange_strong(disable, false,
661
0
                                                           std::memory_order_acq_rel);
662
0
        }
663
4.75k
    }
664
511k
}
665
666
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
667
428k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
668
428k
    if (_params.fragment.plan.nodes.empty()) {
669
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
670
0
    }
671
672
428k
    int node_idx = 0;
673
674
428k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
675
428k
                                        &node_idx, root, cur_pipe, 0, false, false));
676
677
428k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
678
0
        return Status::InternalError(
679
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
680
0
    }
681
428k
    return Status::OK();
682
428k
}
683
684
Status PipelineFragmentContext::_create_tree_helper(
685
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
686
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
687
665k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
688
    // propagate error case
689
665k
    if (*node_idx >= tnodes.size()) {
690
0
        return Status::InternalError(
691
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
692
0
                *node_idx, tnodes.size());
693
0
    }
694
665k
    const TPlanNode& tnode = tnodes[*node_idx];
695
696
665k
    int num_children = tnodes[*node_idx].num_children;
697
665k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
698
665k
    bool current_require_bucket_distribution = require_bucket_distribution;
699
    // TODO: Create CacheOperator is confused now
700
665k
    OperatorPtr op = nullptr;
701
665k
    OperatorPtr cache_op = nullptr;
702
665k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
703
665k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
704
665k
                                     followed_by_shuffled_operator,
705
665k
                                     current_require_bucket_distribution, cache_op));
706
    // Initialization must be done here. For example, group by expressions in agg will be used to
707
    // decide if a local shuffle should be planed, so it must be initialized here.
708
665k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
709
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
710
665k
    if (parent != nullptr) {
711
        // add to parent's child(s)
712
236k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
713
428k
    } else {
714
428k
        *root = op;
715
428k
    }
716
    /**
717
     * `ExchangeType::HASH_SHUFFLE` should be used if an operator is followed by a shuffled operator (shuffled hash join, union operator followed by co-located operators).
718
     *
719
     * For plan:
720
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
721
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
722
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
723
     *
724
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
725
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
726
     */
727
665k
    auto required_data_distribution =
728
665k
            cur_pipe->operators().empty()
729
665k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
730
665k
                    : op->required_data_distribution(_runtime_state.get());
731
665k
    current_followed_by_shuffled_operator =
732
665k
            ((followed_by_shuffled_operator ||
733
665k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
734
607k
                                             : op->is_shuffled_operator())) &&
735
665k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
736
665k
            (followed_by_shuffled_operator &&
737
554k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
738
739
665k
    current_require_bucket_distribution =
740
665k
            ((require_bucket_distribution ||
741
665k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
742
612k
                                             : op->is_colocated_operator())) &&
743
665k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
744
665k
            (require_bucket_distribution &&
745
561k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
746
747
665k
    if (num_children == 0) {
748
446k
        _use_serial_source = op->is_serial_operator();
749
446k
    }
750
    // rely on that tnodes is preorder of the plan
751
901k
    for (int i = 0; i < num_children; i++) {
752
236k
        ++*node_idx;
753
236k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
754
236k
                                            current_followed_by_shuffled_operator,
755
236k
                                            current_require_bucket_distribution));
756
757
        // we are expecting a child, but have used all nodes
758
        // this means we have been given a bad tree and must fail
759
236k
        if (*node_idx >= tnodes.size()) {
760
0
            return Status::InternalError(
761
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
762
0
                    "nodes: {}",
763
0
                    *node_idx, tnodes.size());
764
0
        }
765
236k
    }
766
767
665k
    return Status::OK();
768
665k
}
769
770
void PipelineFragmentContext::_inherit_pipeline_properties(
771
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
772
113k
        PipelinePtr pipe_with_sink) {
773
113k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
774
113k
    pipe_with_source->set_num_tasks(_num_instances);
775
113k
    pipe_with_source->set_data_distribution(data_distribution);
776
113k
}
777
778
Status PipelineFragmentContext::_add_local_exchange_impl(
779
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
780
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
781
        const std::map<int, int>& bucket_seq_to_instance_idx,
782
112k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
783
112k
    auto& operators = cur_pipe->operators();
784
112k
    const auto downstream_pipeline_id = cur_pipe->id();
785
112k
    auto local_exchange_id = next_operator_id();
786
    // 1. Create a new pipeline with local exchange sink.
787
112k
    DataSinkOperatorPtr sink;
788
112k
    auto sink_id = next_sink_operator_id();
789
790
    /**
791
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
792
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
793
     */
794
112k
    const bool followed_by_shuffled_operator =
795
112k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
796
112k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
797
112k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
798
112k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
799
112k
                                         followed_by_shuffled_operator && !_use_serial_source;
800
112k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
801
112k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
802
112k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
803
112k
    if (bucket_seq_to_instance_idx.empty() &&
804
112k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
805
7
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
806
7
    }
807
112k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
808
112k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
809
112k
                                          num_buckets, use_global_hash_shuffle,
810
112k
                                          shuffle_idx_to_instance_idx));
811
812
    // 2. Create and initialize LocalExchangeSharedState.
813
112k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
814
112k
            LocalExchangeSharedState::create_shared(_num_instances);
815
112k
    switch (data_distribution.distribution_type) {
816
13.9k
    case ExchangeType::HASH_SHUFFLE:
817
13.9k
        shared_state->exchanger = ShuffleExchanger::create_unique(
818
13.9k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
819
13.9k
                use_global_hash_shuffle ? _total_instances : _num_instances,
820
13.9k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
821
13.9k
                        ? cast_set<int>(
822
13.9k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
823
13.9k
                        : 0);
824
13.9k
        break;
825
513
    case ExchangeType::BUCKET_HASH_SHUFFLE:
826
513
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
827
513
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
828
513
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
829
513
                        ? cast_set<int>(
830
513
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
831
513
                        : 0);
832
513
        break;
833
94.6k
    case ExchangeType::PASSTHROUGH:
834
94.6k
        shared_state->exchanger = PassthroughExchanger::create_unique(
835
94.6k
                cur_pipe->num_tasks(), _num_instances,
836
94.6k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
837
94.6k
                        ? cast_set<int>(
838
94.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
839
94.6k
                        : 0);
840
94.6k
        break;
841
352
    case ExchangeType::BROADCAST:
842
352
        shared_state->exchanger = BroadcastExchanger::create_unique(
843
352
                cur_pipe->num_tasks(), _num_instances,
844
352
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
845
352
                        ? cast_set<int>(
846
352
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
847
352
                        : 0);
848
352
        break;
849
2.68k
    case ExchangeType::PASS_TO_ONE:
850
2.68k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
851
            // If shared hash table is enabled for BJ, hash table will be built by only one task
852
1.69k
            shared_state->exchanger = PassToOneExchanger::create_unique(
853
1.69k
                    cur_pipe->num_tasks(), _num_instances,
854
1.69k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
855
1.69k
                            ? cast_set<int>(_runtime_state->query_options()
856
1.69k
                                                    .local_exchange_free_blocks_limit)
857
1.69k
                            : 0);
858
1.69k
        } else {
859
986
            shared_state->exchanger = BroadcastExchanger::create_unique(
860
986
                    cur_pipe->num_tasks(), _num_instances,
861
986
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
862
986
                            ? cast_set<int>(_runtime_state->query_options()
863
986
                                                    .local_exchange_free_blocks_limit)
864
986
                            : 0);
865
986
        }
866
2.68k
        break;
867
877
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
868
877
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
869
877
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
870
877
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
877
                        ? cast_set<int>(
872
877
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
873
877
                        : 0);
874
877
        break;
875
0
    default:
876
0
        return Status::InternalError("Unsupported local exchange type : " +
877
0
                                     std::to_string((int)data_distribution.distribution_type));
878
112k
    }
879
113k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
880
113k
                                             "LOCAL_EXCHANGE_OPERATOR");
881
113k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
882
113k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
883
884
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
885
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
886
887
    // 3.1 Initialize new pipeline's operator list.
888
113k
    std::copy(operators.begin(), operators.begin() + idx,
889
113k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
890
891
    // 3.2 Erase unused operators in previous pipeline.
892
113k
    operators.erase(operators.begin(), operators.begin() + idx);
893
894
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
895
113k
    OperatorPtr source_op;
896
113k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
897
113k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
898
113k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
899
113k
    if (!operators.empty()) {
900
47.9k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
901
47.9k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
902
47.9k
    }
903
113k
    operators.insert(operators.begin(), source_op);
904
905
    // 5. Set children for two pipelines separately.
906
113k
    std::vector<std::shared_ptr<Pipeline>> new_children;
907
113k
    std::vector<PipelineId> edges_with_source;
908
130k
    for (auto child : cur_pipe->children()) {
909
130k
        bool found = false;
910
143k
        for (auto op : new_pip->operators()) {
911
143k
            if (child->sink()->node_id() == op->node_id()) {
912
12.1k
                new_pip->set_children(child);
913
12.1k
                found = true;
914
12.1k
            };
915
143k
        }
916
130k
        if (!found) {
917
118k
            new_children.push_back(child);
918
118k
            edges_with_source.push_back(child->id());
919
118k
        }
920
130k
    }
921
113k
    new_children.push_back(new_pip);
922
113k
    edges_with_source.push_back(new_pip->id());
923
924
    // 6. Set DAG for new pipelines.
925
113k
    if (!new_pip->children().empty()) {
926
7.36k
        std::vector<PipelineId> edges_with_sink;
927
12.1k
        for (auto child : new_pip->children()) {
928
12.1k
            edges_with_sink.push_back(child->id());
929
12.1k
        }
930
7.36k
        _dag.insert({new_pip->id(), edges_with_sink});
931
7.36k
    }
932
113k
    cur_pipe->set_children(new_children);
933
113k
    _dag[downstream_pipeline_id] = edges_with_source;
934
113k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
935
113k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
936
113k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
937
938
    // 7. Inherit properties from current pipeline.
939
113k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
940
113k
    return Status::OK();
941
113k
}
942
943
Status PipelineFragmentContext::_add_local_exchange(
944
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
945
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
946
        const std::map<int, int>& bucket_seq_to_instance_idx,
947
189k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
948
189k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
949
39.8k
        return Status::OK();
950
39.8k
    }
951
952
150k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
953
50.8k
        return Status::OK();
954
50.8k
    }
955
99.3k
    *do_local_exchange = true;
956
957
99.3k
    auto& operators = cur_pipe->operators();
958
99.3k
    auto total_op_num = operators.size();
959
99.3k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
960
99.3k
    RETURN_IF_ERROR(_add_local_exchange_impl(
961
99.3k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
962
99.3k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
963
964
99.3k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
965
796
            << "total_op_num: " << total_op_num
966
796
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
967
796
            << " new_pip->operators().size(): " << new_pip->operators().size();
968
969
    // There are some local shuffles with relatively heavy operations on the sink.
970
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
971
    // Therefore, local passthrough is used to increase the concurrency of the sink.
972
    // op -> local sink(1) -> local source (n)
973
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
974
99.3k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
975
99.3k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
976
14.4k
        RETURN_IF_ERROR(_add_local_exchange_impl(
977
14.4k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
978
14.4k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
979
14.4k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
980
14.4k
                shuffle_idx_to_instance_idx));
981
14.4k
    }
982
99.3k
    return Status::OK();
983
99.3k
}
984
985
Status PipelineFragmentContext::_plan_local_exchange(
986
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
987
427k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
988
984k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
989
557k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
990
        // Set property if child pipeline is not join operator's child.
991
557k
        if (!_pipelines[pip_idx]->children().empty()) {
992
123k
            for (auto& child : _pipelines[pip_idx]->children()) {
993
123k
                if (child->sink()->node_id() ==
994
123k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
995
109k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
996
109k
                }
997
123k
            }
998
118k
        }
999
1000
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1001
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1002
        // still keep colocate plan after local shuffle
1003
557k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1004
557k
                                             bucket_seq_to_instance_idx,
1005
557k
                                             shuffle_idx_to_instance_idx));
1006
557k
    }
1007
427k
    return Status::OK();
1008
427k
}
1009
1010
Status PipelineFragmentContext::_plan_local_exchange(
1011
        int num_buckets, int pip_idx, PipelinePtr pip,
1012
        const std::map<int, int>& bucket_seq_to_instance_idx,
1013
556k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1014
556k
    int idx = 1;
1015
556k
    bool do_local_exchange = false;
1016
604k
    do {
1017
604k
        auto& ops = pip->operators();
1018
604k
        do_local_exchange = false;
1019
        // Plan local exchange for each operator.
1020
670k
        for (; idx < ops.size();) {
1021
113k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1022
104k
                RETURN_IF_ERROR(_add_local_exchange(
1023
104k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1024
104k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1025
104k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1026
104k
                        shuffle_idx_to_instance_idx));
1027
104k
            }
1028
113k
            if (do_local_exchange) {
1029
                // If local exchange is needed for current operator, we will split this pipeline to
1030
                // two pipelines by local exchange sink/source. And then we need to process remaining
1031
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1032
                // is current operator was already processed) and continue to plan local exchange.
1033
48.1k
                idx = 2;
1034
48.1k
                break;
1035
48.1k
            }
1036
65.5k
            idx++;
1037
65.5k
        }
1038
604k
    } while (do_local_exchange);
1039
556k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1040
84.4k
        RETURN_IF_ERROR(_add_local_exchange(
1041
84.4k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1042
84.4k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1043
84.4k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1044
84.4k
    }
1045
556k
    return Status::OK();
1046
556k
}
1047
1048
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1049
                                                  const std::vector<TExpr>& output_exprs,
1050
                                                  const TPipelineFragmentParams& params,
1051
                                                  const RowDescriptor& row_desc,
1052
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1053
430k
                                                  PipelineId cur_pipeline_id) {
1054
430k
    switch (thrift_sink.type) {
1055
143k
    case TDataSinkType::DATA_STREAM_SINK: {
1056
143k
        if (!thrift_sink.__isset.stream_sink) {
1057
0
            return Status::InternalError("Missing data stream sink.");
1058
0
        }
1059
143k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1060
143k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1061
143k
                params.destinations, _fragment_instance_ids);
1062
143k
        break;
1063
143k
    }
1064
249k
    case TDataSinkType::RESULT_SINK: {
1065
249k
        if (!thrift_sink.__isset.result_sink) {
1066
0
            return Status::InternalError("Missing data buffer sink.");
1067
0
        }
1068
1069
249k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), row_desc,
1070
249k
                                                      output_exprs, thrift_sink.result_sink);
1071
249k
        break;
1072
249k
    }
1073
102
    case TDataSinkType::DICTIONARY_SINK: {
1074
102
        if (!thrift_sink.__isset.dictionary_sink) {
1075
0
            return Status::InternalError("Missing dict sink.");
1076
0
        }
1077
1078
102
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1079
102
                                                    thrift_sink.dictionary_sink);
1080
102
        break;
1081
102
    }
1082
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1083
31.0k
    case TDataSinkType::OLAP_TABLE_SINK: {
1084
31.0k
        if (state->query_options().enable_memtable_on_sink_node &&
1085
31.0k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1086
31.0k
            !config::is_cloud_mode()) {
1087
2.05k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(pool, next_sink_operator_id(),
1088
2.05k
                                                               row_desc, output_exprs);
1089
29.0k
        } else {
1090
29.0k
            _sink = std::make_shared<OlapTableSinkOperatorX>(pool, next_sink_operator_id(),
1091
29.0k
                                                             row_desc, output_exprs);
1092
29.0k
        }
1093
31.0k
        break;
1094
0
    }
1095
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1096
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1097
165
        DCHECK(state->get_query_ctx() != nullptr);
1098
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1099
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1100
165
                                                                output_exprs);
1101
165
        break;
1102
0
    }
1103
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1104
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1105
0
            return Status::InternalError("Missing hive table sink.");
1106
0
        }
1107
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1108
1.46k
                                                         output_exprs);
1109
1.46k
        break;
1110
1.46k
    }
1111
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1112
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1113
0
            return Status::InternalError("Missing iceberg table sink.");
1114
0
        }
1115
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1116
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1117
0
                                                                     row_desc, output_exprs);
1118
1.73k
        } else {
1119
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1120
1.73k
                                                                row_desc, output_exprs);
1121
1.73k
        }
1122
1.73k
        break;
1123
1.73k
    }
1124
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1125
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1126
0
            return Status::InternalError("Missing iceberg delete sink.");
1127
0
        }
1128
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1129
20
                                                             row_desc, output_exprs);
1130
20
        break;
1131
20
    }
1132
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1133
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1134
0
            return Status::InternalError("Missing iceberg merge sink.");
1135
0
        }
1136
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1137
80
                                                            output_exprs);
1138
80
        break;
1139
80
    }
1140
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1141
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1142
0
            return Status::InternalError("Missing max compute table sink.");
1143
0
        }
1144
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1145
0
                                                       output_exprs);
1146
0
        break;
1147
0
    }
1148
80
    case TDataSinkType::JDBC_TABLE_SINK: {
1149
80
        if (!thrift_sink.__isset.jdbc_table_sink) {
1150
0
            return Status::InternalError("Missing data jdbc sink.");
1151
0
        }
1152
80
        if (config::enable_java_support) {
1153
80
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1154
80
                                                             output_exprs);
1155
80
        } else {
1156
0
            return Status::InternalError(
1157
0
                    "Jdbc table sink is not enabled, you can change be config "
1158
0
                    "enable_java_support to true and restart be.");
1159
0
        }
1160
80
        break;
1161
80
    }
1162
80
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1163
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1164
0
            return Status::InternalError("Missing data buffer sink.");
1165
0
        }
1166
1167
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
3
                                                             output_exprs);
1169
3
        break;
1170
3
    }
1171
502
    case TDataSinkType::RESULT_FILE_SINK: {
1172
502
        if (!thrift_sink.__isset.result_file_sink) {
1173
0
            return Status::InternalError("Missing result file sink.");
1174
0
        }
1175
1176
        // Result file sink is not the top sink
1177
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1178
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1179
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1180
0
                    params.destinations, output_exprs, desc_tbl);
1181
502
        } else {
1182
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1183
502
                                                              output_exprs);
1184
502
        }
1185
502
        break;
1186
502
    }
1187
1.85k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1188
1.85k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1189
1.85k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1190
1.85k
        auto sink_id = next_sink_operator_id();
1191
1.85k
        const int multi_cast_node_id = sink_id;
1192
1.85k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1193
        // one sink has multiple sources.
1194
1.85k
        std::vector<int> sources;
1195
7.21k
        for (int i = 0; i < sender_size; ++i) {
1196
5.35k
            auto source_id = next_operator_id();
1197
5.35k
            sources.push_back(source_id);
1198
5.35k
        }
1199
1200
1.85k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1201
1.85k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1202
7.21k
        for (int i = 0; i < sender_size; ++i) {
1203
5.35k
            auto new_pipeline = add_pipeline();
1204
            // use to exchange sink
1205
5.35k
            RowDescriptor* exchange_row_desc = nullptr;
1206
5.35k
            {
1207
5.35k
                const auto& tmp_row_desc =
1208
5.35k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1209
5.35k
                                ? RowDescriptor(state->desc_tbl(),
1210
5.35k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1211
5.35k
                                                         .output_tuple_id})
1212
5.35k
                                : row_desc;
1213
5.35k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1214
5.35k
            }
1215
5.35k
            auto source_id = sources[i];
1216
5.35k
            OperatorPtr source_op;
1217
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1218
5.35k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1219
5.35k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1220
5.35k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1221
5.35k
                    /*operator_id=*/source_id);
1222
5.35k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1223
5.35k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1224
            // 2. create and set sink operator of data stream sender for new pipeline
1225
1226
5.35k
            DataSinkOperatorPtr sink_op;
1227
5.35k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1228
5.35k
                    state, *exchange_row_desc, next_sink_operator_id(),
1229
5.35k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1230
5.35k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1231
1232
5.35k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1233
5.35k
            {
1234
5.35k
                TDataSink* t = pool->add(new TDataSink());
1235
5.35k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1236
5.35k
                RETURN_IF_ERROR(sink_op->init(*t));
1237
5.35k
            }
1238
1239
            // 3. set dependency dag
1240
5.35k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1241
5.35k
        }
1242
1.85k
        if (sources.empty()) {
1243
0
            return Status::InternalError("size of sources must be greater than 0");
1244
0
        }
1245
1.85k
        break;
1246
1.85k
    }
1247
1.85k
    case TDataSinkType::BLACKHOLE_SINK: {
1248
13
        if (!thrift_sink.__isset.blackhole_sink) {
1249
0
            return Status::InternalError("Missing blackhole sink.");
1250
0
        }
1251
1252
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1253
13
        break;
1254
13
    }
1255
156
    case TDataSinkType::TVF_TABLE_SINK: {
1256
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1257
0
            return Status::InternalError("Missing TVF table sink.");
1258
0
        }
1259
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1260
156
                                                        output_exprs);
1261
156
        break;
1262
156
    }
1263
0
    default:
1264
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1265
430k
    }
1266
430k
    return Status::OK();
1267
430k
}
1268
1269
// NOLINTBEGIN(readability-function-size)
1270
// NOLINTBEGIN(readability-function-cognitive-complexity)
1271
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1272
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1273
                                                 PipelinePtr& cur_pipe, int parent_idx,
1274
                                                 int child_idx,
1275
                                                 const bool followed_by_shuffled_operator,
1276
                                                 const bool require_bucket_distribution,
1277
668k
                                                 OperatorPtr& cache_op) {
1278
668k
    std::vector<DataSinkOperatorPtr> sink_ops;
1279
668k
    Defer defer = Defer([&]() {
1280
666k
        if (op) {
1281
666k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1282
666k
        }
1283
666k
        for (auto& s : sink_ops) {
1284
123k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1285
123k
        }
1286
666k
    });
1287
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1288
    // Therefore, here we need to use a stack-like structure.
1289
668k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1290
668k
    std::stringstream error_msg;
1291
668k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1292
1293
668k
    bool fe_with_old_version = false;
1294
668k
    switch (tnode.node_type) {
1295
211k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1296
211k
        op = std::make_shared<OlapScanOperatorX>(
1297
211k
                pool, tnode, next_operator_id(), descs, _num_instances,
1298
211k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1299
211k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1300
211k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1301
211k
        break;
1302
211k
    }
1303
78
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1304
78
        DCHECK(_query_ctx != nullptr);
1305
78
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1306
78
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1307
78
                                                    _num_instances);
1308
78
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1309
78
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1310
78
        break;
1311
78
    }
1312
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1313
0
        if (config::enable_java_support) {
1314
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1315
0
                                                     _num_instances);
1316
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1317
0
        } else {
1318
0
            return Status::InternalError(
1319
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1320
0
                    "to true and restart be.");
1321
0
        }
1322
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1323
0
        break;
1324
0
    }
1325
22.9k
    case TPlanNodeType::FILE_SCAN_NODE: {
1326
22.9k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1327
22.9k
                                                 _num_instances);
1328
22.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1329
22.9k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1330
22.9k
        break;
1331
22.9k
    }
1332
0
    case TPlanNodeType::ES_SCAN_NODE:
1333
592
    case TPlanNodeType::ES_HTTP_SCAN_NODE: {
1334
592
        op = std::make_shared<EsScanOperatorX>(pool, tnode, next_operator_id(), descs,
1335
592
                                               _num_instances);
1336
592
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1337
592
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1338
592
        break;
1339
592
    }
1340
146k
    case TPlanNodeType::EXCHANGE_NODE: {
1341
146k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1342
146k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1343
18.4E
                                  : 0;
1344
146k
        DCHECK_GT(num_senders, 0);
1345
146k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1346
146k
                                                       num_senders);
1347
146k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1348
146k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1349
146k
        break;
1350
146k
    }
1351
156k
    case TPlanNodeType::AGGREGATION_NODE: {
1352
156k
        if (tnode.agg_node.grouping_exprs.empty() &&
1353
156k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1354
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1355
0
                                         ": group by and output is empty");
1356
0
        }
1357
156k
        bool need_create_cache_op =
1358
156k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1359
156k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1360
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1361
10
            auto cache_source_id = next_operator_id();
1362
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1363
10
                                                        _params.fragment.query_cache_param);
1364
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1365
1366
10
            const auto downstream_pipeline_id = cur_pipe->id();
1367
10
            if (!_dag.contains(downstream_pipeline_id)) {
1368
10
                _dag.insert({downstream_pipeline_id, {}});
1369
10
            }
1370
10
            new_pipe = add_pipeline(cur_pipe);
1371
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1372
1373
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1374
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1375
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1376
10
            return Status::OK();
1377
10
        };
1378
156k
        const bool group_by_limit_opt =
1379
156k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1380
1381
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1382
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1383
156k
        const bool enable_spill = _runtime_state->enable_spill() &&
1384
156k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1385
156k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1386
156k
                                      tnode.agg_node.use_streaming_preaggregation &&
1387
156k
                                      !tnode.agg_node.grouping_exprs.empty();
1388
        // TODO: distinct streaming agg does not support spill.
1389
156k
        const bool can_use_distinct_streaming_agg =
1390
156k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1391
156k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1392
156k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1393
156k
                _params.query_options.enable_distinct_streaming_aggregation;
1394
1395
156k
        if (can_use_distinct_streaming_agg) {
1396
91.3k
            if (need_create_cache_op) {
1397
8
                PipelinePtr new_pipe;
1398
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1399
1400
8
                cache_op = op;
1401
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1402
8
                                                                     tnode, descs);
1403
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1404
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1405
8
                cur_pipe = new_pipe;
1406
91.2k
            } else {
1407
91.2k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
91.2k
                                                                     tnode, descs);
1409
91.2k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1410
91.2k
            }
1411
91.3k
        } else if (is_streaming_agg) {
1412
3.17k
            if (need_create_cache_op) {
1413
0
                PipelinePtr new_pipe;
1414
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1415
0
                cache_op = op;
1416
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1417
0
                                                             descs);
1418
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1419
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1420
0
                cur_pipe = new_pipe;
1421
3.17k
            } else {
1422
3.17k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
3.17k
                                                             descs);
1424
3.17k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1425
3.17k
            }
1426
61.9k
        } else {
1427
            // create new pipeline to add query cache operator
1428
61.9k
            PipelinePtr new_pipe;
1429
61.9k
            if (need_create_cache_op) {
1430
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1431
2
                cache_op = op;
1432
2
            }
1433
1434
61.9k
            if (enable_spill) {
1435
5
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1436
5
                                                                     next_operator_id(), descs);
1437
61.9k
            } else {
1438
61.9k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1439
61.9k
            }
1440
61.9k
            if (need_create_cache_op) {
1441
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1442
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1443
2
                cur_pipe = new_pipe;
1444
61.9k
            } else {
1445
61.9k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1446
61.9k
            }
1447
1448
61.9k
            const auto downstream_pipeline_id = cur_pipe->id();
1449
61.9k
            if (!_dag.contains(downstream_pipeline_id)) {
1450
59.8k
                _dag.insert({downstream_pipeline_id, {}});
1451
59.8k
            }
1452
61.9k
            cur_pipe = add_pipeline(cur_pipe);
1453
61.9k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1454
1455
61.9k
            if (enable_spill) {
1456
5
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1457
5
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1458
61.9k
            } else {
1459
61.9k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1460
61.9k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1461
61.9k
            }
1462
61.9k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1463
61.9k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1464
61.9k
        }
1465
156k
        break;
1466
156k
    }
1467
156k
    case TPlanNodeType::HASH_JOIN_NODE: {
1468
9.73k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1469
9.73k
                                       tnode.hash_join_node.is_broadcast_join;
1470
9.73k
        const auto enable_spill = _runtime_state->enable_spill();
1471
9.73k
        if (enable_spill && !is_broadcast_join) {
1472
0
            auto tnode_ = tnode;
1473
0
            tnode_.runtime_filters.clear();
1474
0
            auto inner_probe_operator =
1475
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1476
1477
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1478
            // So here use `tnode_` which has no runtime filters.
1479
0
            auto probe_side_inner_sink_operator =
1480
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1481
1482
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1483
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1484
1485
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1486
0
                    pool, tnode_, next_operator_id(), descs);
1487
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1488
0
                                                inner_probe_operator);
1489
0
            op = std::move(probe_operator);
1490
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1491
1492
0
            const auto downstream_pipeline_id = cur_pipe->id();
1493
0
            if (!_dag.contains(downstream_pipeline_id)) {
1494
0
                _dag.insert({downstream_pipeline_id, {}});
1495
0
            }
1496
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1497
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1498
1499
0
            auto inner_sink_operator =
1500
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1501
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1502
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1503
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1504
1505
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1506
0
            sink_ops.push_back(std::move(sink_operator));
1507
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1508
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1509
1510
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1511
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1512
9.73k
        } else {
1513
9.73k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1514
9.73k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1515
1516
9.73k
            const auto downstream_pipeline_id = cur_pipe->id();
1517
9.73k
            if (!_dag.contains(downstream_pipeline_id)) {
1518
8.04k
                _dag.insert({downstream_pipeline_id, {}});
1519
8.04k
            }
1520
9.73k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1521
9.73k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1522
1523
9.73k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1524
9.73k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1525
9.73k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1526
9.73k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1527
1528
9.73k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1529
9.73k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1530
9.73k
        }
1531
9.73k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1532
4.74k
            std::shared_ptr<HashJoinSharedState> shared_state =
1533
4.74k
                    HashJoinSharedState::create_shared(_num_instances);
1534
24.1k
            for (int i = 0; i < _num_instances; i++) {
1535
19.4k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1536
19.4k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1537
19.4k
                sink_dep->set_shared_state(shared_state.get());
1538
19.4k
                shared_state->sink_deps.push_back(sink_dep);
1539
19.4k
            }
1540
4.74k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1541
4.74k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1542
4.74k
            _op_id_to_shared_state.insert(
1543
4.74k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1544
4.74k
        }
1545
9.73k
        break;
1546
9.73k
    }
1547
4.61k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1548
4.61k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1549
4.61k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1550
1551
4.61k
        const auto downstream_pipeline_id = cur_pipe->id();
1552
4.61k
        if (!_dag.contains(downstream_pipeline_id)) {
1553
4.38k
            _dag.insert({downstream_pipeline_id, {}});
1554
4.38k
        }
1555
4.61k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1556
4.61k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1557
1558
4.61k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1559
4.61k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1560
4.61k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
4.61k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1562
4.61k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1563
4.61k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1564
4.61k
        break;
1565
4.61k
    }
1566
53.2k
    case TPlanNodeType::UNION_NODE: {
1567
53.2k
        int child_count = tnode.num_children;
1568
53.2k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1569
53.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1570
1571
53.2k
        const auto downstream_pipeline_id = cur_pipe->id();
1572
53.2k
        if (!_dag.contains(downstream_pipeline_id)) {
1573
52.9k
            _dag.insert({downstream_pipeline_id, {}});
1574
52.9k
        }
1575
54.9k
        for (int i = 0; i < child_count; i++) {
1576
1.66k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1577
1.66k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1578
1.66k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1579
1.66k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1580
1.66k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1581
1.66k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1582
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1583
1.66k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1584
1.66k
        }
1585
53.2k
        break;
1586
53.2k
    }
1587
53.2k
    case TPlanNodeType::SORT_NODE: {
1588
43.2k
        const auto should_spill = _runtime_state->enable_spill() &&
1589
43.2k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1590
43.2k
        const bool use_local_merge =
1591
43.2k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1592
43.2k
        if (should_spill) {
1593
7
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1594
43.2k
        } else if (use_local_merge) {
1595
40.9k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1596
40.9k
                                                                 descs);
1597
40.9k
        } else {
1598
2.33k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1599
2.33k
        }
1600
43.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1601
1602
43.2k
        const auto downstream_pipeline_id = cur_pipe->id();
1603
43.2k
        if (!_dag.contains(downstream_pipeline_id)) {
1604
43.2k
            _dag.insert({downstream_pipeline_id, {}});
1605
43.2k
        }
1606
43.2k
        cur_pipe = add_pipeline(cur_pipe);
1607
43.2k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1608
1609
43.2k
        if (should_spill) {
1610
7
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1611
7
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1612
43.2k
        } else {
1613
43.2k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1614
43.2k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1615
43.2k
        }
1616
43.2k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1617
43.2k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1618
43.2k
        break;
1619
43.2k
    }
1620
43.2k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1621
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
62
        const auto downstream_pipeline_id = cur_pipe->id();
1625
62
        if (!_dag.contains(downstream_pipeline_id)) {
1626
62
            _dag.insert({downstream_pipeline_id, {}});
1627
62
        }
1628
62
        cur_pipe = add_pipeline(cur_pipe);
1629
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1630
1631
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1632
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1633
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1634
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1635
62
        break;
1636
62
    }
1637
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1638
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1639
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1640
1641
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1642
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1643
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1644
1.63k
        }
1645
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1646
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1647
1648
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1649
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1650
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1651
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1652
1.64k
        break;
1653
1.64k
    }
1654
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1655
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1656
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1657
1.60k
        break;
1658
1.60k
    }
1659
1.60k
    case TPlanNodeType::INTERSECT_NODE: {
1660
119
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1661
119
                                                                      cur_pipe, sink_ops));
1662
119
        break;
1663
119
    }
1664
128
    case TPlanNodeType::EXCEPT_NODE: {
1665
128
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1666
128
                                                                       cur_pipe, sink_ops));
1667
128
        break;
1668
128
    }
1669
303
    case TPlanNodeType::REPEAT_NODE: {
1670
303
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1671
303
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1672
303
        break;
1673
303
    }
1674
914
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1675
914
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1676
914
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1677
914
        break;
1678
914
    }
1679
914
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1680
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1681
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1682
218
        break;
1683
218
    }
1684
1.59k
    case TPlanNodeType::EMPTY_SET_NODE: {
1685
1.59k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1686
1.59k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1687
1.59k
        break;
1688
1.59k
    }
1689
1.59k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1690
459
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1691
459
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1692
459
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1693
459
        break;
1694
459
    }
1695
2.32k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1696
2.32k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1697
2.32k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1698
2.32k
        break;
1699
2.32k
    }
1700
6.01k
    case TPlanNodeType::META_SCAN_NODE: {
1701
6.01k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1702
6.01k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1703
6.01k
        break;
1704
6.01k
    }
1705
6.01k
    case TPlanNodeType::SELECT_NODE: {
1706
1.84k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1707
1.84k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1708
1.84k
        break;
1709
1.84k
    }
1710
1.84k
    case TPlanNodeType::REC_CTE_NODE: {
1711
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1712
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1713
1714
151
        const auto downstream_pipeline_id = cur_pipe->id();
1715
151
        if (!_dag.contains(downstream_pipeline_id)) {
1716
148
            _dag.insert({downstream_pipeline_id, {}});
1717
148
        }
1718
1719
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1720
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1721
1722
151
        DataSinkOperatorPtr anchor_sink;
1723
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1724
151
                                                                  op->operator_id(), tnode, descs);
1725
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1726
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1727
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1728
1729
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1730
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1731
1732
151
        DataSinkOperatorPtr rec_sink;
1733
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1734
151
                                                         tnode, descs);
1735
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1736
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1737
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1738
1739
151
        break;
1740
151
    }
1741
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1742
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1743
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1744
1.95k
        break;
1745
1.95k
    }
1746
1.95k
    default:
1747
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1748
0
                                     print_plan_node_type(tnode.node_type));
1749
668k
    }
1750
665k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1751
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1752
0
        op->set_serial_operator();
1753
0
    }
1754
1755
665k
    return Status::OK();
1756
668k
}
1757
// NOLINTEND(readability-function-cognitive-complexity)
1758
// NOLINTEND(readability-function-size)
1759
1760
template <bool is_intersect>
1761
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1762
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1763
247
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1764
247
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1765
247
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
247
    const auto downstream_pipeline_id = cur_pipe->id();
1768
247
    if (!_dag.contains(downstream_pipeline_id)) {
1769
230
        _dag.insert({downstream_pipeline_id, {}});
1770
230
    }
1771
1772
834
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1773
587
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1774
587
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1775
1776
587
        if (child_id == 0) {
1777
247
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1778
247
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1779
340
        } else {
1780
340
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1781
340
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1782
340
        }
1783
587
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1784
587
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1785
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1786
587
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1787
587
    }
1788
1789
247
    return Status::OK();
1790
247
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1763
119
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1764
119
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1765
119
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
119
    const auto downstream_pipeline_id = cur_pipe->id();
1768
119
    if (!_dag.contains(downstream_pipeline_id)) {
1769
110
        _dag.insert({downstream_pipeline_id, {}});
1770
110
    }
1771
1772
435
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1773
316
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1774
316
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1775
1776
316
        if (child_id == 0) {
1777
119
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1778
119
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1779
197
        } else {
1780
197
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1781
197
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1782
197
        }
1783
316
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1784
316
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1785
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1786
316
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1787
316
    }
1788
1789
119
    return Status::OK();
1790
119
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1763
128
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1764
128
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1765
128
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
128
    const auto downstream_pipeline_id = cur_pipe->id();
1768
128
    if (!_dag.contains(downstream_pipeline_id)) {
1769
120
        _dag.insert({downstream_pipeline_id, {}});
1770
120
    }
1771
1772
399
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1773
271
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1774
271
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1775
1776
271
        if (child_id == 0) {
1777
128
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1778
128
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1779
143
        } else {
1780
143
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1781
143
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1782
143
        }
1783
271
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1784
271
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1785
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1786
271
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1787
271
    }
1788
1789
128
    return Status::OK();
1790
128
}
1791
1792
428k
Status PipelineFragmentContext::submit() {
1793
428k
    if (_submitted) {
1794
0
        return Status::InternalError("submitted");
1795
0
    }
1796
428k
    _submitted = true;
1797
1798
428k
    int submit_tasks = 0;
1799
428k
    Status st;
1800
428k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1801
1.25M
    for (auto& task : _tasks) {
1802
2.04M
        for (auto& t : task) {
1803
2.04M
            st = scheduler->submit(t.first);
1804
2.04M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1805
2.04M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1806
2.04M
            if (!st) {
1807
0
                cancel(Status::InternalError("submit context to executor fail"));
1808
0
                std::lock_guard<std::mutex> l(_task_mutex);
1809
0
                _total_tasks = submit_tasks;
1810
0
                break;
1811
0
            }
1812
2.04M
            submit_tasks++;
1813
2.04M
        }
1814
1.25M
    }
1815
428k
    if (!st.ok()) {
1816
0
        bool need_remove = false;
1817
0
        {
1818
0
            std::lock_guard<std::mutex> l(_task_mutex);
1819
0
            if (_closed_tasks >= _total_tasks) {
1820
0
                need_remove = _close_fragment_instance();
1821
0
            }
1822
0
        }
1823
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1824
0
        if (need_remove) {
1825
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1826
0
        }
1827
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1828
0
                                     BackendOptions::get_localhost());
1829
428k
    } else {
1830
428k
        return st;
1831
428k
    }
1832
428k
}
1833
1834
12
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1835
12
    if (_runtime_state->enable_profile()) {
1836
0
        std::stringstream ss;
1837
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1838
0
            runtime_profile_ptr->pretty_print(&ss);
1839
0
        }
1840
1841
0
        if (_runtime_state->load_channel_profile()) {
1842
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1843
0
        }
1844
1845
0
        auto profile_str =
1846
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1847
0
                            this->_fragment_id, extra_info, ss.str());
1848
0
        LOG_LONG_STRING(INFO, profile_str);
1849
0
    }
1850
12
}
1851
// If all pipeline tasks binded to the fragment instance are finished, then we could
1852
// close the fragment instance.
1853
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1854
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1855
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1856
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1857
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1858
// (via debug_string()).
1859
430k
bool PipelineFragmentContext::_close_fragment_instance() {
1860
430k
    if (_is_fragment_instance_closed) {
1861
0
        return false;
1862
0
    }
1863
430k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1864
430k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1865
430k
    if (!_need_notify_close) {
1866
427k
        auto st = send_report(true);
1867
427k
        if (!st) {
1868
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1869
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1870
0
        }
1871
427k
    }
1872
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1873
    // Since stream load does not have someting like coordinator on FE, so
1874
    // backend can not report profile to FE, ant its profile can not be shown
1875
    // in the same way with other query. So we print the profile content to info log.
1876
1877
430k
    if (_runtime_state->enable_profile() &&
1878
430k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1879
2.23k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1880
2.23k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1881
0
        std::stringstream ss;
1882
        // Compute the _local_time_percent before pretty_print the runtime_profile
1883
        // Before add this operation, the print out like that:
1884
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1885
        // After add the operation, the print out like that:
1886
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1887
        // We can easily know the exec node execute time without child time consumed.
1888
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1889
0
            runtime_profile_ptr->pretty_print(&ss);
1890
0
        }
1891
1892
0
        if (_runtime_state->load_channel_profile()) {
1893
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1894
0
        }
1895
1896
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1897
0
    }
1898
1899
430k
    if (_query_ctx->enable_profile()) {
1900
2.23k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1901
2.23k
                                         collect_realtime_load_channel_profile());
1902
2.23k
    }
1903
1904
    // Return whether the caller needs to remove from the pipeline map.
1905
    // The caller must do this after releasing _task_mutex.
1906
430k
    return !_need_notify_close;
1907
430k
}
1908
1909
2.04M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1910
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1911
2.04M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1912
2.04M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1913
672k
        if (_dag.contains(pipeline_id)) {
1914
355k
            for (auto dep : _dag[pipeline_id]) {
1915
355k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1916
355k
            }
1917
284k
        }
1918
672k
    }
1919
2.04M
    bool need_remove = false;
1920
2.04M
    {
1921
2.04M
        std::lock_guard<std::mutex> l(_task_mutex);
1922
2.04M
        ++_closed_tasks;
1923
2.04M
        if (_closed_tasks >= _total_tasks) {
1924
430k
            need_remove = _close_fragment_instance();
1925
430k
        }
1926
2.04M
    }
1927
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1928
2.04M
    if (need_remove) {
1929
427k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1930
427k
    }
1931
2.04M
}
1932
1933
53.7k
std::string PipelineFragmentContext::get_load_error_url() {
1934
53.7k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1935
0
        return to_load_error_http_path(str);
1936
0
    }
1937
150k
    for (auto& tasks : _tasks) {
1938
248k
        for (auto& task : tasks) {
1939
248k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1940
162
                return to_load_error_http_path(str);
1941
162
            }
1942
248k
        }
1943
150k
    }
1944
53.5k
    return "";
1945
53.7k
}
1946
1947
53.7k
std::string PipelineFragmentContext::get_first_error_msg() {
1948
53.7k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
1949
0
        return str;
1950
0
    }
1951
150k
    for (auto& tasks : _tasks) {
1952
248k
        for (auto& task : tasks) {
1953
248k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
1954
162
                return str;
1955
162
            }
1956
248k
        }
1957
150k
    }
1958
53.5k
    return "";
1959
53.7k
}
1960
1961
432k
Status PipelineFragmentContext::send_report(bool done) {
1962
432k
    Status exec_status = _query_ctx->exec_status();
1963
    // If plan is done successfully, but _is_report_success is false,
1964
    // no need to send report.
1965
    // Load will set _is_report_success to true because load wants to know
1966
    // the process.
1967
432k
    if (!_is_report_success && done && exec_status.ok()) {
1968
384k
        return Status::OK();
1969
384k
    }
1970
1971
    // If both _is_report_success and _is_report_on_cancel are false,
1972
    // which means no matter query is success or failed, no report is needed.
1973
    // This may happen when the query limit reached and
1974
    // a internal cancellation being processed
1975
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
1976
    // be set to false, to avoid sending fault report to FE.
1977
47.7k
    if (!_is_report_success && !_is_report_on_cancel) {
1978
365
        if (done) {
1979
            // if done is true, which means the query is finished successfully, we can safely close the fragment instance without sending report to FE, and just return OK status here.
1980
365
            return Status::OK();
1981
365
        }
1982
0
        return Status::NeedSendAgain("");
1983
365
    }
1984
1985
47.3k
    std::vector<RuntimeState*> runtime_states;
1986
1987
118k
    for (auto& tasks : _tasks) {
1988
170k
        for (auto& task : tasks) {
1989
170k
            runtime_states.push_back(task.second.get());
1990
170k
        }
1991
118k
    }
1992
1993
47.3k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
1994
47.4k
                                        ? get_load_error_url()
1995
18.4E
                                        : _query_ctx->get_load_error_url();
1996
47.3k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
1997
47.4k
                                          ? get_first_error_msg()
1998
18.4E
                                          : _query_ctx->get_first_error_msg();
1999
2000
47.3k
    ReportStatusRequest req {.status = exec_status,
2001
47.3k
                             .runtime_states = runtime_states,
2002
47.3k
                             .done = done || !exec_status.ok(),
2003
47.3k
                             .coord_addr = _query_ctx->coord_addr,
2004
47.3k
                             .query_id = _query_id,
2005
47.3k
                             .fragment_id = _fragment_id,
2006
47.3k
                             .fragment_instance_id = TUniqueId(),
2007
47.3k
                             .backend_num = -1,
2008
47.3k
                             .runtime_state = _runtime_state.get(),
2009
47.3k
                             .load_error_url = load_eror_url,
2010
47.3k
                             .first_error_msg = first_error_msg,
2011
47.3k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2012
2013
47.3k
    return _report_status_cb(
2014
47.3k
            req, std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()));
2015
47.7k
}
2016
2017
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2018
0
    size_t res = 0;
2019
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2020
    // here to traverse the vector.
2021
0
    for (const auto& task_instances : _tasks) {
2022
0
        for (const auto& task : task_instances) {
2023
0
            if (task.first->is_running()) {
2024
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2025
0
                                      << " is running, task: " << (void*)task.first.get()
2026
0
                                      << ", is_running: " << task.first->is_running();
2027
0
                *has_running_task = true;
2028
0
                return 0;
2029
0
            }
2030
2031
0
            size_t revocable_size = task.first->get_revocable_size();
2032
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2033
0
                res += revocable_size;
2034
0
            }
2035
0
        }
2036
0
    }
2037
0
    return res;
2038
0
}
2039
2040
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2041
0
    std::vector<PipelineTask*> revocable_tasks;
2042
0
    for (const auto& task_instances : _tasks) {
2043
0
        for (const auto& task : task_instances) {
2044
0
            size_t revocable_size_ = task.first->get_revocable_size();
2045
2046
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2047
0
                revocable_tasks.emplace_back(task.first.get());
2048
0
            }
2049
0
        }
2050
0
    }
2051
0
    return revocable_tasks;
2052
0
}
2053
2054
136
std::string PipelineFragmentContext::debug_string() {
2055
136
    std::lock_guard<std::mutex> l(_task_mutex);
2056
136
    fmt::memory_buffer debug_string_buffer;
2057
136
    fmt::format_to(debug_string_buffer,
2058
136
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2059
136
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2060
136
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2061
715
    for (size_t j = 0; j < _tasks.size(); j++) {
2062
579
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2063
1.29k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2064
715
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2065
715
                           _tasks[j][i].first->debug_string());
2066
715
        }
2067
579
    }
2068
2069
136
    return fmt::to_string(debug_string_buffer);
2070
136
}
2071
2072
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2073
2.23k
PipelineFragmentContext::collect_realtime_profile() const {
2074
2.23k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2075
2076
    // we do not have mutex to protect pipeline_id_to_profile
2077
    // so we need to make sure this funciton is invoked after fragment context
2078
    // has already been prepared.
2079
2.23k
    if (!_prepared) {
2080
0
        std::string msg =
2081
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2082
0
        DCHECK(false) << msg;
2083
0
        LOG_ERROR(msg);
2084
0
        return res;
2085
0
    }
2086
2087
    // Make sure first profile is fragment level profile
2088
2.23k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2089
2.23k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2090
2.23k
    res.push_back(fragment_profile);
2091
2092
    // pipeline_id_to_profile is initialized in prepare stage
2093
4.09k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2094
4.09k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2095
4.09k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2096
4.09k
        res.push_back(profile_ptr);
2097
4.09k
    }
2098
2099
2.23k
    return res;
2100
2.23k
}
2101
2102
std::shared_ptr<TRuntimeProfileTree>
2103
2.23k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2104
    // we do not have mutex to protect pipeline_id_to_profile
2105
    // so we need to make sure this funciton is invoked after fragment context
2106
    // has already been prepared.
2107
2.23k
    if (!_prepared) {
2108
0
        std::string msg =
2109
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2110
0
        DCHECK(false) << msg;
2111
0
        LOG_ERROR(msg);
2112
0
        return nullptr;
2113
0
    }
2114
2115
4.40k
    for (const auto& tasks : _tasks) {
2116
8.96k
        for (const auto& task : tasks) {
2117
8.96k
            if (task.second->load_channel_profile() == nullptr) {
2118
0
                continue;
2119
0
            }
2120
2121
8.96k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2122
2123
8.96k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2124
8.96k
                                                           _runtime_state->profile_level());
2125
8.96k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2126
8.96k
        }
2127
4.40k
    }
2128
2129
2.23k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2130
2.23k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2131
2.23k
                                                      _runtime_state->profile_level());
2132
2.23k
    return load_channel_profile;
2133
2.23k
}
2134
2135
// Collect runtime filter IDs registered by all tasks in this PFC.
2136
// Used during recursive CTE stage transitions to know which filters to deregister
2137
// before creating the new PFC for the next recursion round.
2138
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2139
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2140
// the vector sizes do not change, and individual RuntimeState filter sets are
2141
// written only during open() which has completed by the time we reach rerun.
2142
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2143
3.28k
    std::set<int> result;
2144
8.43k
    for (const auto& _task : _tasks) {
2145
14.3k
        for (const auto& task : _task) {
2146
14.3k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2147
14.3k
            result.merge(set);
2148
14.3k
        }
2149
8.43k
    }
2150
3.28k
    if (_runtime_state) {
2151
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2152
3.28k
        result.merge(set);
2153
3.28k
    }
2154
3.28k
    return result;
2155
3.28k
}
2156
2157
431k
void PipelineFragmentContext::_release_resource() {
2158
431k
    std::lock_guard<std::mutex> l(_task_mutex);
2159
    // The memory released by the query end is recorded in the query mem tracker.
2160
431k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2161
431k
    auto st = _query_ctx->exec_status();
2162
1.26M
    for (auto& _task : _tasks) {
2163
1.26M
        if (!_task.empty()) {
2164
1.26M
            _call_back(_task.front().first->runtime_state(), &st);
2165
1.26M
        }
2166
1.26M
    }
2167
431k
    _tasks.clear();
2168
431k
    _dag.clear();
2169
431k
    _pip_id_to_pipeline.clear();
2170
431k
    _pipelines.clear();
2171
431k
    _sink.reset();
2172
431k
    _root_op.reset();
2173
431k
    _runtime_filter_mgr_map.clear();
2174
431k
    _op_id_to_shared_state.clear();
2175
431k
}
2176
2177
} // namespace doris