Coverage Report

Created: 2026-05-09 06:58

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
114
#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
132
#include "util/client_cache.h"
133
#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
327k
        : _query_id(std::move(query_id)),
144
327k
          _fragment_id(request.fragment_id),
145
327k
          _exec_env(exec_env),
146
327k
          _query_ctx(std::move(query_ctx)),
147
327k
          _call_back(call_back),
148
327k
          _is_report_on_cancel(true),
149
327k
          _params(request),
150
327k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
327k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
327k
                                                               : false) {
153
327k
    _fragment_watcher.start();
154
327k
}
155
156
328k
PipelineFragmentContext::~PipelineFragmentContext() {
157
328k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
328k
            .tag("query_id", print_id(_query_id))
159
328k
            .tag("fragment_id", _fragment_id);
160
328k
    _release_resource();
161
328k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
328k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
328k
        _runtime_state.reset();
165
328k
        _query_ctx.reset();
166
328k
    }
167
328k
}
168
169
100
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
100
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
100
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
100
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
8.81k
bool PipelineFragmentContext::notify_close() {
181
8.81k
    bool all_closed = false;
182
8.81k
    bool need_remove = false;
183
8.81k
    {
184
8.81k
        std::lock_guard<std::mutex> l(_task_mutex);
185
8.81k
        if (_closed_tasks >= _total_tasks) {
186
3.45k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
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3.38k
                need_remove = true;
193
3.38k
            }
194
3.45k
            all_closed = true;
195
3.45k
        }
196
        // make fragment release by self after cancel
197
8.81k
        _need_notify_close = false;
198
8.81k
    }
199
8.81k
    if (need_remove) {
200
3.38k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.38k
    }
202
8.81k
    return all_closed;
203
8.81k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
5.33k
void PipelineFragmentContext::cancel(const Status reason) {
210
5.33k
    LOG_INFO("PipelineFragmentContext::cancel")
211
5.33k
            .tag("query_id", print_id(_query_id))
212
5.33k
            .tag("fragment_id", _fragment_id)
213
5.33k
            .tag("reason", reason.to_string());
214
5.33k
    if (notify_close()) {
215
94
        return;
216
94
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
5.23k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
5.23k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
5.23k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
5.23k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
5.23k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
5.23k
    _query_ctx->cancel(reason, _fragment_id);
243
5.23k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
276
        _is_report_on_cancel = false;
245
4.96k
    } else {
246
22.2k
        for (auto& id : _fragment_instance_ids) {
247
22.2k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
22.2k
        }
249
4.96k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
5.23k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
5.23k
    if (stream_load_ctx != nullptr) {
254
31
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
31
        stream_load_ctx->error_url = get_load_error_url();
259
31
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
31
    }
261
262
23.5k
    for (auto& tasks : _tasks) {
263
49.2k
        for (auto& task : tasks) {
264
49.2k
            task.first->unblock_all_dependencies();
265
49.2k
        }
266
23.5k
    }
267
5.23k
}
268
269
509k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
509k
    PipelineId id = _next_pipeline_id++;
271
509k
    auto pipeline = std::make_shared<Pipeline>(
272
509k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
509k
            parent ? parent->num_tasks() : _num_instances);
274
509k
    if (idx >= 0) {
275
90.6k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
418k
    } else {
277
418k
        _pipelines.emplace_back(pipeline);
278
418k
    }
279
509k
    if (parent) {
280
180k
        parent->set_children(pipeline);
281
180k
    }
282
509k
    return pipeline;
283
509k
}
284
285
327k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
327k
    {
287
327k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
327k
        auto root_pipeline = add_pipeline();
290
327k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
327k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
327k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
327k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
327k
                                          _params.fragment.output_exprs, _params,
299
327k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
327k
                                          *_desc_tbl, root_pipeline->id()));
301
327k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
327k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
417k
        for (PipelinePtr& pipeline : _pipelines) {
305
417k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
417k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
417k
        }
308
327k
    }
309
    // 4. Build local exchanger
310
327k
    if (_runtime_state->enable_local_shuffle()) {
311
325k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
325k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
325k
                                             _params.bucket_seq_to_instance_idx,
314
325k
                                             _params.shuffle_idx_to_instance_idx));
315
325k
    }
316
317
    // 5. Initialize global states in pipelines.
318
510k
    for (PipelinePtr& pipeline : _pipelines) {
319
510k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
510k
        pipeline->children().clear();
321
510k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
510k
    }
323
324
325k
    {
325
325k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
325k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
325k
    }
329
330
325k
    return Status::OK();
331
325k
}
332
333
327k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
327k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
327k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
327k
        _timeout = _params.query_options.execution_timeout;
339
327k
    }
340
341
327k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
327k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
327k
    SCOPED_TIMER(_prepare_timer);
344
327k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
327k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
327k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
327k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
327k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
327k
    {
350
327k
        SCOPED_TIMER(_init_context_timer);
351
327k
        cast_set(_num_instances, _params.local_params.size());
352
327k
        _total_instances =
353
327k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
327k
        auto* fragment_context = this;
356
357
327k
        if (_params.query_options.__isset.is_report_success) {
358
325k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
325k
        }
360
361
        // 1. Set up the global runtime state.
362
327k
        _runtime_state = RuntimeState::create_unique(
363
327k
                _params.query_id, _params.fragment_id, _params.query_options,
364
327k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
327k
        _runtime_state->set_task_execution_context(shared_from_this());
366
327k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
327k
        if (_params.__isset.backend_id) {
368
324k
            _runtime_state->set_backend_id(_params.backend_id);
369
324k
        }
370
327k
        if (_params.__isset.import_label) {
371
239
            _runtime_state->set_import_label(_params.import_label);
372
239
        }
373
327k
        if (_params.__isset.db_name) {
374
191
            _runtime_state->set_db_name(_params.db_name);
375
191
        }
376
327k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
327k
        if (_params.is_simplified_param) {
381
115k
            _desc_tbl = _query_ctx->desc_tbl;
382
212k
        } else {
383
212k
            DCHECK(_params.__isset.desc_tbl);
384
212k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
212k
                                                  &_desc_tbl));
386
212k
        }
387
327k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
327k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
327k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
327k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
327k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
327k
        const auto target_size = _params.local_params.size();
395
327k
        _fragment_instance_ids.resize(target_size);
396
1.36M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.03M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.03M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.03M
        }
400
327k
    }
401
402
327k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
326k
    _init_next_report_time();
405
406
326k
    _prepared = true;
407
326k
    return Status::OK();
408
327k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.03M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.03M
    const auto& local_params = _params.local_params[instance_idx];
414
1.03M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.03M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.03M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.03M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.03M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.69M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.69M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.69M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.69M
                shared_state_map;
423
2.30M
        for (auto& op : pipeline->operators()) {
424
2.30M
            auto source_id = op->operator_id();
425
2.30M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.30M
                iter != _op_id_to_shared_state.end()) {
427
656k
                shared_state_map.insert({source_id, iter->second});
428
656k
            }
429
2.30M
        }
430
1.69M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.69M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.69M
                iter != _op_id_to_shared_state.end()) {
433
253k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
253k
            }
435
1.69M
        }
436
1.69M
        return shared_state_map;
437
1.69M
    };
438
439
3.12M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.08M
        auto& pipeline = _pipelines[pip_idx];
441
2.08M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.68M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.68M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.68M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.68M
            {
446
                // Initialize runtime state for this task
447
1.68M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.68M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.68M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.69M
                if (_params.__isset.backend_id) {
453
1.69M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.69M
                }
455
1.68M
                if (_params.__isset.import_label) {
456
240
                    task_runtime_state->set_import_label(_params.import_label);
457
240
                }
458
1.68M
                if (_params.__isset.db_name) {
459
192
                    task_runtime_state->set_db_name(_params.db_name);
460
192
                }
461
1.68M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.68M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.68M
                if (_params.__isset.content_length) {
468
31
                    task_runtime_state->set_content_length(_params.content_length);
469
31
                }
470
471
1.68M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.68M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.68M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.68M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.68M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.68M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.68M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.68M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.68M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.68M
            }
482
1.68M
            auto cur_task_id = _total_tasks++;
483
1.68M
            task_runtime_state->set_task_id(cur_task_id);
484
1.68M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.68M
            auto task = std::make_shared<PipelineTask>(
486
1.68M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.68M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.68M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.68M
                    instance_idx);
490
1.68M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.68M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.68M
            _tasks[instance_idx].emplace_back(
493
1.68M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.68M
                            std::move(task), std::move(task_runtime_state)});
495
1.68M
        }
496
2.08M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
2.08M
    for (auto& _pipeline : _pipelines) {
516
2.08M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.68M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.68M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.68M
            if (_dag.contains(_pipeline->id())) {
522
1.06M
                auto& deps = _dag[_pipeline->id()];
523
1.69M
                for (auto& dep : deps) {
524
1.69M
                    if (pipeline_id_to_task.contains(dep)) {
525
898k
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
898k
                        if (ss) {
527
393k
                            task->inject_shared_state(ss);
528
505k
                        } else {
529
505k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
505k
                                    task->get_source_shared_state());
531
505k
                        }
532
898k
                    }
533
1.69M
                }
534
1.06M
            }
535
1.68M
        }
536
2.08M
    }
537
3.13M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.08M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.68M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.68M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.68M
            std::vector<TScanRangeParams> scan_ranges;
542
1.68M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.68M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
265k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
265k
            }
546
1.68M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.68M
                                                             _params.fragment.output_sink));
548
1.68M
        }
549
2.08M
    }
550
1.04M
    {
551
1.04M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.04M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.04M
    }
554
1.04M
    return Status::OK();
555
1.03M
}
556
557
326k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
326k
    _total_tasks = 0;
559
326k
    _closed_tasks = 0;
560
326k
    const auto target_size = _params.local_params.size();
561
326k
    _tasks.resize(target_size);
562
326k
    _runtime_filter_mgr_map.resize(target_size);
563
835k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
508k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
508k
    }
566
326k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
326k
    if (target_size > 1 &&
569
326k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
120k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
571
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
572
18.8k
        std::vector<Status> prepare_status(target_size);
573
18.8k
        int submitted_tasks = 0;
574
18.8k
        Status submit_status;
575
18.8k
        CountDownLatch latch((int)target_size);
576
279k
        for (int i = 0; i < target_size; i++) {
577
260k
            submit_status = thread_pool->submit_func([&, i]() {
578
260k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
260k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
260k
                latch.count_down();
581
260k
            });
582
260k
            if (LIKELY(submit_status.ok())) {
583
260k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
260k
        }
588
18.8k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
18.8k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
279k
        for (int i = 0; i < submitted_tasks; i++) {
593
260k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
260k
        }
597
308k
    } else {
598
1.08M
        for (int i = 0; i < target_size; i++) {
599
777k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
777k
        }
601
308k
    }
602
326k
    _pipeline_parent_map.clear();
603
326k
    _op_id_to_shared_state.clear();
604
605
326k
    return Status::OK();
606
326k
}
607
608
325k
void PipelineFragmentContext::_init_next_report_time() {
609
325k
    auto interval_s = config::pipeline_status_report_interval;
610
325k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
611
31.7k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
612
31.7k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
613
        // We don't want to wait longer than it takes to run the entire fragment.
614
31.7k
        _previous_report_time =
615
31.7k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
616
31.7k
        _disable_period_report = false;
617
31.7k
    }
618
325k
}
619
620
3.62k
void PipelineFragmentContext::refresh_next_report_time() {
621
3.62k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
622
3.62k
    DCHECK(disable == true);
623
3.62k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
624
3.62k
    _disable_period_report.compare_exchange_strong(disable, false);
625
3.62k
}
626
627
6.01M
void PipelineFragmentContext::trigger_report_if_necessary() {
628
6.01M
    if (!_is_report_success) {
629
5.59M
        return;
630
5.59M
    }
631
424k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
632
424k
    if (disable) {
633
5.90k
        return;
634
5.90k
    }
635
418k
    int32_t interval_s = config::pipeline_status_report_interval;
636
418k
    if (interval_s <= 0) {
637
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
638
0
                        "trigger "
639
0
                        "report.";
640
0
    }
641
418k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
642
418k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
643
418k
    if (MonotonicNanos() > next_report_time) {
644
3.62k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
645
3.62k
                                                            std::memory_order_acq_rel)) {
646
3
            return;
647
3
        }
648
3.62k
        if (VLOG_FILE_IS_ON) {
649
0
            VLOG_FILE << "Reporting "
650
0
                      << "profile for query_id " << print_id(_query_id)
651
0
                      << ", fragment id: " << _fragment_id;
652
653
0
            std::stringstream ss;
654
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
655
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
656
0
            if (_runtime_state->load_channel_profile()) {
657
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
658
0
            }
659
660
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
661
0
                      << " profile:\n"
662
0
                      << ss.str();
663
0
        }
664
3.62k
        auto st = send_report(false);
665
3.62k
        if (!st.ok()) {
666
0
            disable = true;
667
0
            _disable_period_report.compare_exchange_strong(disable, false,
668
0
                                                           std::memory_order_acq_rel);
669
0
        }
670
3.62k
    }
671
418k
}
672
673
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
674
324k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
675
324k
    if (_params.fragment.plan.nodes.empty()) {
676
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
677
0
    }
678
679
324k
    int node_idx = 0;
680
681
324k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
682
324k
                                        &node_idx, root, cur_pipe, 0, false, false));
683
684
324k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
685
0
        return Status::InternalError(
686
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
687
0
    }
688
324k
    return Status::OK();
689
324k
}
690
691
Status PipelineFragmentContext::_create_tree_helper(
692
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
693
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
694
519k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
695
    // propagate error case
696
519k
    if (*node_idx >= tnodes.size()) {
697
0
        return Status::InternalError(
698
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
699
0
                *node_idx, tnodes.size());
700
0
    }
701
519k
    const TPlanNode& tnode = tnodes[*node_idx];
702
703
519k
    int num_children = tnodes[*node_idx].num_children;
704
519k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
705
519k
    bool current_require_bucket_distribution = require_bucket_distribution;
706
    // TODO: Create CacheOperator is confused now
707
519k
    OperatorPtr op = nullptr;
708
519k
    OperatorPtr cache_op = nullptr;
709
519k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
710
519k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
711
519k
                                     followed_by_shuffled_operator,
712
519k
                                     current_require_bucket_distribution, cache_op));
713
    // Initialization must be done here. For example, group by expressions in agg will be used to
714
    // decide if a local shuffle should be planed, so it must be initialized here.
715
519k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
716
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
717
519k
    if (parent != nullptr) {
718
        // add to parent's child(s)
719
195k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
720
324k
    } else {
721
324k
        *root = op;
722
324k
    }
723
    /**
724
     * `ExchangeType::HASH_SHUFFLE` should be used if an operator is followed by a shuffled operator (shuffled hash join, union operator followed by co-located operators).
725
     *
726
     * For plan:
727
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
728
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
729
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
730
     *
731
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
732
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
733
     */
734
519k
    auto required_data_distribution =
735
519k
            cur_pipe->operators().empty()
736
519k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
737
519k
                    : op->required_data_distribution(_runtime_state.get());
738
519k
    current_followed_by_shuffled_operator =
739
519k
            ((followed_by_shuffled_operator ||
740
519k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
741
464k
                                             : op->is_shuffled_operator())) &&
742
519k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
743
519k
            (followed_by_shuffled_operator &&
744
413k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
745
746
519k
    current_require_bucket_distribution =
747
519k
            ((require_bucket_distribution ||
748
519k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
749
468k
                                             : op->is_colocated_operator())) &&
750
519k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
751
519k
            (require_bucket_distribution &&
752
419k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
753
754
519k
    if (num_children == 0) {
755
338k
        _use_serial_source = op->is_serial_operator();
756
338k
    }
757
    // rely on that tnodes is preorder of the plan
758
715k
    for (int i = 0; i < num_children; i++) {
759
195k
        ++*node_idx;
760
195k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
761
195k
                                            current_followed_by_shuffled_operator,
762
195k
                                            current_require_bucket_distribution));
763
764
        // we are expecting a child, but have used all nodes
765
        // this means we have been given a bad tree and must fail
766
195k
        if (*node_idx >= tnodes.size()) {
767
0
            return Status::InternalError(
768
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
769
0
                    "nodes: {}",
770
0
                    *node_idx, tnodes.size());
771
0
        }
772
195k
    }
773
774
519k
    return Status::OK();
775
519k
}
776
777
void PipelineFragmentContext::_inherit_pipeline_properties(
778
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
779
90.6k
        PipelinePtr pipe_with_sink) {
780
90.6k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
781
90.6k
    pipe_with_source->set_num_tasks(_num_instances);
782
90.6k
    pipe_with_source->set_data_distribution(data_distribution);
783
90.6k
}
784
785
Status PipelineFragmentContext::_add_local_exchange_impl(
786
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
787
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
788
        const std::map<int, int>& bucket_seq_to_instance_idx,
789
90.5k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
790
90.5k
    auto& operators = cur_pipe->operators();
791
90.5k
    const auto downstream_pipeline_id = cur_pipe->id();
792
90.5k
    auto local_exchange_id = next_operator_id();
793
    // 1. Create a new pipeline with local exchange sink.
794
90.5k
    DataSinkOperatorPtr sink;
795
90.5k
    auto sink_id = next_sink_operator_id();
796
797
    /**
798
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
799
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
800
     */
801
90.5k
    const bool followed_by_shuffled_operator =
802
90.5k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
803
90.5k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
804
90.5k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
805
90.5k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
806
90.5k
                                         followed_by_shuffled_operator && !_use_serial_source;
807
90.5k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
808
90.5k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
809
90.5k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
810
90.5k
    if (bucket_seq_to_instance_idx.empty() &&
811
90.5k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
812
7
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
813
7
    }
814
90.5k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
815
90.5k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
816
90.5k
                                          num_buckets, use_global_hash_shuffle,
817
90.5k
                                          shuffle_idx_to_instance_idx));
818
819
    // 2. Create and initialize LocalExchangeSharedState.
820
90.5k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
821
90.5k
            LocalExchangeSharedState::create_shared(_num_instances);
822
90.5k
    switch (data_distribution.distribution_type) {
823
10.3k
    case ExchangeType::HASH_SHUFFLE:
824
10.3k
        shared_state->exchanger = ShuffleExchanger::create_unique(
825
10.3k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
826
10.3k
                use_global_hash_shuffle ? _total_instances : _num_instances,
827
10.3k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
828
10.3k
                        ? cast_set<int>(
829
10.3k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
830
10.3k
                        : 0);
831
10.3k
        break;
832
423
    case ExchangeType::BUCKET_HASH_SHUFFLE:
833
423
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
834
423
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
835
423
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
836
423
                        ? cast_set<int>(
837
423
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
838
423
                        : 0);
839
423
        break;
840
76.7k
    case ExchangeType::PASSTHROUGH:
841
76.7k
        shared_state->exchanger = PassthroughExchanger::create_unique(
842
76.7k
                cur_pipe->num_tasks(), _num_instances,
843
76.7k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
844
76.7k
                        ? cast_set<int>(
845
76.6k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
846
76.7k
                        : 0);
847
76.7k
        break;
848
299
    case ExchangeType::BROADCAST:
849
299
        shared_state->exchanger = BroadcastExchanger::create_unique(
850
299
                cur_pipe->num_tasks(), _num_instances,
851
299
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
852
299
                        ? cast_set<int>(
853
299
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
854
299
                        : 0);
855
299
        break;
856
1.98k
    case ExchangeType::PASS_TO_ONE:
857
1.98k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
858
            // If shared hash table is enabled for BJ, hash table will be built by only one task
859
708
            shared_state->exchanger = PassToOneExchanger::create_unique(
860
708
                    cur_pipe->num_tasks(), _num_instances,
861
708
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
862
708
                            ? cast_set<int>(_runtime_state->query_options()
863
708
                                                    .local_exchange_free_blocks_limit)
864
708
                            : 0);
865
1.27k
        } else {
866
1.27k
            shared_state->exchanger = BroadcastExchanger::create_unique(
867
1.27k
                    cur_pipe->num_tasks(), _num_instances,
868
1.27k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
869
1.27k
                            ? cast_set<int>(_runtime_state->query_options()
870
1.27k
                                                    .local_exchange_free_blocks_limit)
871
1.27k
                            : 0);
872
1.27k
        }
873
1.98k
        break;
874
863
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
875
863
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
876
863
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
877
863
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
878
863
                        ? cast_set<int>(
879
863
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
880
863
                        : 0);
881
863
        break;
882
0
    default:
883
0
        return Status::InternalError("Unsupported local exchange type : " +
884
0
                                     std::to_string((int)data_distribution.distribution_type));
885
90.5k
    }
886
90.7k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
887
90.7k
                                             "LOCAL_EXCHANGE_OPERATOR");
888
90.7k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
889
90.7k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
890
891
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
892
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
893
894
    // 3.1 Initialize new pipeline's operator list.
895
90.7k
    std::copy(operators.begin(), operators.begin() + idx,
896
90.7k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
897
898
    // 3.2 Erase unused operators in previous pipeline.
899
90.7k
    operators.erase(operators.begin(), operators.begin() + idx);
900
901
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
902
90.7k
    OperatorPtr source_op;
903
90.7k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
904
90.7k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
905
90.7k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
906
90.7k
    if (!operators.empty()) {
907
40.8k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
908
40.8k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
909
40.8k
    }
910
90.7k
    operators.insert(operators.begin(), source_op);
911
912
    // 5. Set children for two pipelines separately.
913
90.7k
    std::vector<std::shared_ptr<Pipeline>> new_children;
914
90.7k
    std::vector<PipelineId> edges_with_source;
915
106k
    for (auto child : cur_pipe->children()) {
916
106k
        bool found = false;
917
119k
        for (auto op : new_pip->operators()) {
918
119k
            if (child->sink()->node_id() == op->node_id()) {
919
11.1k
                new_pip->set_children(child);
920
11.1k
                found = true;
921
11.1k
            };
922
119k
        }
923
106k
        if (!found) {
924
94.9k
            new_children.push_back(child);
925
94.9k
            edges_with_source.push_back(child->id());
926
94.9k
        }
927
106k
    }
928
90.7k
    new_children.push_back(new_pip);
929
90.7k
    edges_with_source.push_back(new_pip->id());
930
931
    // 6. Set DAG for new pipelines.
932
90.7k
    if (!new_pip->children().empty()) {
933
6.58k
        std::vector<PipelineId> edges_with_sink;
934
11.1k
        for (auto child : new_pip->children()) {
935
11.1k
            edges_with_sink.push_back(child->id());
936
11.1k
        }
937
6.58k
        _dag.insert({new_pip->id(), edges_with_sink});
938
6.58k
    }
939
90.7k
    cur_pipe->set_children(new_children);
940
90.7k
    _dag[downstream_pipeline_id] = edges_with_source;
941
90.7k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
942
90.7k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
943
90.7k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
944
945
    // 7. Inherit properties from current pipeline.
946
90.7k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
947
90.7k
    return Status::OK();
948
90.7k
}
949
950
Status PipelineFragmentContext::_add_local_exchange(
951
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
952
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
953
        const std::map<int, int>& bucket_seq_to_instance_idx,
954
156k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
955
156k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
956
31.3k
        return Status::OK();
957
31.3k
    }
958
959
125k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
960
45.0k
        return Status::OK();
961
45.0k
    }
962
80.1k
    *do_local_exchange = true;
963
964
80.1k
    auto& operators = cur_pipe->operators();
965
80.1k
    auto total_op_num = operators.size();
966
80.1k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
967
80.1k
    RETURN_IF_ERROR(_add_local_exchange_impl(
968
80.1k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
969
80.1k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
970
971
80.1k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
972
77
            << "total_op_num: " << total_op_num
973
77
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
974
77
            << " new_pip->operators().size(): " << new_pip->operators().size();
975
976
    // There are some local shuffles with relatively heavy operations on the sink.
977
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
978
    // Therefore, local passthrough is used to increase the concurrency of the sink.
979
    // op -> local sink(1) -> local source (n)
980
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
981
80.1k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
982
80.1k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
983
10.5k
        RETURN_IF_ERROR(_add_local_exchange_impl(
984
10.5k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
985
10.5k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
986
10.5k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
987
10.5k
                shuffle_idx_to_instance_idx));
988
10.5k
    }
989
80.1k
    return Status::OK();
990
80.1k
}
991
992
Status PipelineFragmentContext::_plan_local_exchange(
993
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
994
324k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
995
740k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
996
416k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
997
        // Set property if child pipeline is not join operator's child.
998
416k
        if (!_pipelines[pip_idx]->children().empty()) {
999
90.0k
            for (auto& child : _pipelines[pip_idx]->children()) {
1000
90.0k
                if (child->sink()->node_id() ==
1001
90.0k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1002
78.8k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1003
78.8k
                }
1004
90.0k
            }
1005
86.3k
        }
1006
1007
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1008
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1009
        // still keep colocate plan after local shuffle
1010
416k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1011
416k
                                             bucket_seq_to_instance_idx,
1012
416k
                                             shuffle_idx_to_instance_idx));
1013
416k
    }
1014
324k
    return Status::OK();
1015
324k
}
1016
1017
Status PipelineFragmentContext::_plan_local_exchange(
1018
        int num_buckets, int pip_idx, PipelinePtr pip,
1019
        const std::map<int, int>& bucket_seq_to_instance_idx,
1020
416k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1021
416k
    int idx = 1;
1022
416k
    bool do_local_exchange = false;
1023
457k
    do {
1024
457k
        auto& ops = pip->operators();
1025
457k
        do_local_exchange = false;
1026
        // Plan local exchange for each operator.
1027
522k
        for (; idx < ops.size();) {
1028
106k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1029
97.8k
                RETURN_IF_ERROR(_add_local_exchange(
1030
97.8k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1031
97.8k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1032
97.8k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1033
97.8k
                        shuffle_idx_to_instance_idx));
1034
97.8k
            }
1035
106k
            if (do_local_exchange) {
1036
                // If local exchange is needed for current operator, we will split this pipeline to
1037
                // two pipelines by local exchange sink/source. And then we need to process remaining
1038
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1039
                // is current operator was already processed) and continue to plan local exchange.
1040
41.0k
                idx = 2;
1041
41.0k
                break;
1042
41.0k
            }
1043
65.4k
            idx++;
1044
65.4k
        }
1045
457k
    } while (do_local_exchange);
1046
416k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1047
58.4k
        RETURN_IF_ERROR(_add_local_exchange(
1048
58.4k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1049
58.4k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1050
58.4k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1051
58.4k
    }
1052
416k
    return Status::OK();
1053
416k
}
1054
1055
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1056
                                                  const std::vector<TExpr>& output_exprs,
1057
                                                  const TPipelineFragmentParams& params,
1058
                                                  const RowDescriptor& row_desc,
1059
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1060
326k
                                                  PipelineId cur_pipeline_id) {
1061
326k
    switch (thrift_sink.type) {
1062
114k
    case TDataSinkType::DATA_STREAM_SINK: {
1063
114k
        if (!thrift_sink.__isset.stream_sink) {
1064
0
            return Status::InternalError("Missing data stream sink.");
1065
0
        }
1066
114k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1067
114k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1068
114k
                params.destinations, _fragment_instance_ids);
1069
114k
        break;
1070
114k
    }
1071
182k
    case TDataSinkType::RESULT_SINK: {
1072
182k
        if (!thrift_sink.__isset.result_sink) {
1073
0
            return Status::InternalError("Missing data buffer sink.");
1074
0
        }
1075
1076
182k
        auto& pipeline = _pipelines[cur_pipeline_id];
1077
182k
        int child_node_id = pipeline->operators().back()->node_id();
1078
182k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1079
182k
                                                      row_desc, output_exprs,
1080
182k
                                                      thrift_sink.result_sink);
1081
182k
        break;
1082
182k
    }
1083
105
    case TDataSinkType::DICTIONARY_SINK: {
1084
105
        if (!thrift_sink.__isset.dictionary_sink) {
1085
0
            return Status::InternalError("Missing dict sink.");
1086
0
        }
1087
1088
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1089
105
                                                    thrift_sink.dictionary_sink);
1090
105
        break;
1091
105
    }
1092
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1093
28.8k
    case TDataSinkType::OLAP_TABLE_SINK: {
1094
28.8k
        auto& pipeline = _pipelines[cur_pipeline_id];
1095
28.8k
        int child_node_id = pipeline->operators().back()->node_id();
1096
28.8k
        if (state->query_options().enable_memtable_on_sink_node &&
1097
28.8k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1098
28.8k
            !config::is_cloud_mode()) {
1099
64
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1100
64
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1101
28.7k
        } else {
1102
28.7k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1103
28.7k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1104
28.7k
        }
1105
28.8k
        break;
1106
0
    }
1107
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1108
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1109
165
        DCHECK(state->get_query_ctx() != nullptr);
1110
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1111
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1112
165
                                                                output_exprs);
1113
165
        break;
1114
0
    }
1115
0
    case TDataSinkType::HIVE_TABLE_SINK: {
1116
0
        if (!thrift_sink.__isset.hive_table_sink) {
1117
0
            return Status::InternalError("Missing hive table sink.");
1118
0
        }
1119
0
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1120
0
                                                         output_exprs);
1121
0
        break;
1122
0
    }
1123
0
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1124
0
        if (!thrift_sink.__isset.iceberg_table_sink) {
1125
0
            return Status::InternalError("Missing iceberg table sink.");
1126
0
        }
1127
0
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1128
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1129
0
                                                                     row_desc, output_exprs);
1130
0
        } else {
1131
0
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1132
0
                                                                row_desc, output_exprs);
1133
0
        }
1134
0
        break;
1135
0
    }
1136
0
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1137
0
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1138
0
            return Status::InternalError("Missing iceberg delete sink.");
1139
0
        }
1140
0
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1141
0
                                                             row_desc, output_exprs);
1142
0
        break;
1143
0
    }
1144
0
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1145
0
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1146
0
            return Status::InternalError("Missing iceberg merge sink.");
1147
0
        }
1148
0
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1149
0
                                                            output_exprs);
1150
0
        break;
1151
0
    }
1152
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1153
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1154
0
            return Status::InternalError("Missing max compute table sink.");
1155
0
        }
1156
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1157
0
                                                       output_exprs);
1158
0
        break;
1159
0
    }
1160
0
    case TDataSinkType::JDBC_TABLE_SINK: {
1161
0
        if (!thrift_sink.__isset.jdbc_table_sink) {
1162
0
            return Status::InternalError("Missing data jdbc sink.");
1163
0
        }
1164
0
        if (config::enable_java_support) {
1165
0
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1166
0
                                                             output_exprs);
1167
0
        } else {
1168
0
            return Status::InternalError(
1169
0
                    "Jdbc table sink is not enabled, you can change be config "
1170
0
                    "enable_java_support to true and restart be.");
1171
0
        }
1172
0
        break;
1173
0
    }
1174
3
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1175
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1176
0
            return Status::InternalError("Missing data buffer sink.");
1177
0
        }
1178
1179
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1180
3
                                                             output_exprs);
1181
3
        break;
1182
3
    }
1183
338
    case TDataSinkType::RESULT_FILE_SINK: {
1184
338
        if (!thrift_sink.__isset.result_file_sink) {
1185
0
            return Status::InternalError("Missing result file sink.");
1186
0
        }
1187
1188
        // Result file sink is not the top sink
1189
338
        if (params.__isset.destinations && !params.destinations.empty()) {
1190
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1191
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1192
0
                    params.destinations, output_exprs, desc_tbl);
1193
338
        } else {
1194
338
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1195
338
                                                              output_exprs);
1196
338
        }
1197
338
        break;
1198
338
    }
1199
640
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1200
640
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1201
640
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1202
640
        auto sink_id = next_sink_operator_id();
1203
640
        const int multi_cast_node_id = sink_id;
1204
640
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1205
        // one sink has multiple sources.
1206
640
        std::vector<int> sources;
1207
2.34k
        for (int i = 0; i < sender_size; ++i) {
1208
1.70k
            auto source_id = next_operator_id();
1209
1.70k
            sources.push_back(source_id);
1210
1.70k
        }
1211
1212
640
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1213
640
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1214
2.34k
        for (int i = 0; i < sender_size; ++i) {
1215
1.70k
            auto new_pipeline = add_pipeline();
1216
            // use to exchange sink
1217
1.70k
            RowDescriptor* exchange_row_desc = nullptr;
1218
1.70k
            {
1219
1.70k
                const auto& tmp_row_desc =
1220
1.70k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1221
1.70k
                                ? RowDescriptor(state->desc_tbl(),
1222
1.70k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1223
1.70k
                                                         .output_tuple_id})
1224
1.70k
                                : row_desc;
1225
1.70k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1226
1.70k
            }
1227
1.70k
            auto source_id = sources[i];
1228
1.70k
            OperatorPtr source_op;
1229
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1230
1.70k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1231
1.70k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1232
1.70k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1233
1.70k
                    /*operator_id=*/source_id);
1234
1.70k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1235
1.70k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1236
            // 2. create and set sink operator of data stream sender for new pipeline
1237
1238
1.70k
            DataSinkOperatorPtr sink_op;
1239
1.70k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1240
1.70k
                    state, *exchange_row_desc, next_sink_operator_id(),
1241
1.70k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1242
1.70k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1243
1244
1.70k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1245
1.70k
            {
1246
1.70k
                TDataSink* t = pool->add(new TDataSink());
1247
1.70k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1248
1.70k
                RETURN_IF_ERROR(sink_op->init(*t));
1249
1.70k
            }
1250
1251
            // 3. set dependency dag
1252
1.70k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1253
1.70k
        }
1254
640
        if (sources.empty()) {
1255
0
            return Status::InternalError("size of sources must be greater than 0");
1256
0
        }
1257
640
        break;
1258
640
    }
1259
640
    case TDataSinkType::BLACKHOLE_SINK: {
1260
3
        if (!thrift_sink.__isset.blackhole_sink) {
1261
0
            return Status::InternalError("Missing blackhole sink.");
1262
0
        }
1263
1264
3
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1265
3
        break;
1266
3
    }
1267
0
    case TDataSinkType::TVF_TABLE_SINK: {
1268
0
        if (!thrift_sink.__isset.tvf_table_sink) {
1269
0
            return Status::InternalError("Missing TVF table sink.");
1270
0
        }
1271
0
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1272
0
                                                        output_exprs);
1273
0
        break;
1274
0
    }
1275
0
    default:
1276
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1277
326k
    }
1278
326k
    return Status::OK();
1279
326k
}
1280
1281
// NOLINTBEGIN(readability-function-size)
1282
// NOLINTBEGIN(readability-function-cognitive-complexity)
1283
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1284
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1285
                                                 PipelinePtr& cur_pipe, int parent_idx,
1286
                                                 int child_idx,
1287
                                                 const bool followed_by_shuffled_operator,
1288
                                                 const bool require_bucket_distribution,
1289
521k
                                                 OperatorPtr& cache_op) {
1290
521k
    std::vector<DataSinkOperatorPtr> sink_ops;
1291
521k
    Defer defer = Defer([&]() {
1292
521k
        if (op) {
1293
521k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1294
521k
        }
1295
521k
        for (auto& s : sink_ops) {
1296
89.6k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1297
89.6k
        }
1298
521k
    });
1299
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1300
    // Therefore, here we need to use a stack-like structure.
1301
521k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1302
521k
    std::stringstream error_msg;
1303
521k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1304
1305
521k
    bool fe_with_old_version = false;
1306
521k
    switch (tnode.node_type) {
1307
163k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1308
163k
        op = std::make_shared<OlapScanOperatorX>(
1309
163k
                pool, tnode, next_operator_id(), descs, _num_instances,
1310
163k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1311
163k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1312
163k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1313
163k
        break;
1314
163k
    }
1315
78
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1316
78
        DCHECK(_query_ctx != nullptr);
1317
78
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1318
78
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1319
78
                                                    _num_instances);
1320
78
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1321
78
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1322
78
        break;
1323
78
    }
1324
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1325
0
        if (config::enable_java_support) {
1326
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1327
0
                                                     _num_instances);
1328
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1329
0
        } else {
1330
0
            return Status::InternalError(
1331
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1332
0
                    "to true and restart be.");
1333
0
        }
1334
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1335
0
        break;
1336
0
    }
1337
2.65k
    case TPlanNodeType::FILE_SCAN_NODE: {
1338
2.65k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1339
2.65k
                                                 _num_instances);
1340
2.65k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1341
2.65k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1342
2.65k
        break;
1343
2.65k
    }
1344
113k
    case TPlanNodeType::EXCHANGE_NODE: {
1345
113k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1346
113k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1347
18.4E
                                  : 0;
1348
113k
        DCHECK_GT(num_senders, 0);
1349
113k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1350
113k
                                                       num_senders);
1351
113k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1352
113k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1353
113k
        break;
1354
113k
    }
1355
135k
    case TPlanNodeType::AGGREGATION_NODE: {
1356
135k
        if (tnode.agg_node.grouping_exprs.empty() &&
1357
135k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1358
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1359
0
                                         ": group by and output is empty");
1360
0
        }
1361
135k
        bool need_create_cache_op =
1362
135k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1363
135k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1364
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1365
10
            auto cache_source_id = next_operator_id();
1366
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1367
10
                                                        _params.fragment.query_cache_param);
1368
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1369
1370
10
            const auto downstream_pipeline_id = cur_pipe->id();
1371
10
            if (!_dag.contains(downstream_pipeline_id)) {
1372
10
                _dag.insert({downstream_pipeline_id, {}});
1373
10
            }
1374
10
            new_pipe = add_pipeline(cur_pipe);
1375
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1376
1377
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1378
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1379
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1380
10
            return Status::OK();
1381
10
        };
1382
135k
        const bool group_by_limit_opt =
1383
135k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1384
1385
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1386
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1387
135k
        const bool enable_spill = _runtime_state->enable_spill() &&
1388
135k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1389
135k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1390
135k
                                      tnode.agg_node.use_streaming_preaggregation &&
1391
135k
                                      !tnode.agg_node.grouping_exprs.empty();
1392
        // TODO: distinct streaming agg does not support spill.
1393
135k
        const bool can_use_distinct_streaming_agg =
1394
135k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1395
135k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1396
135k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1397
135k
                _params.query_options.enable_distinct_streaming_aggregation;
1398
1399
135k
        if (can_use_distinct_streaming_agg) {
1400
91.4k
            if (need_create_cache_op) {
1401
8
                PipelinePtr new_pipe;
1402
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1403
1404
8
                cache_op = op;
1405
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1406
8
                                                                     tnode, descs);
1407
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1408
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1409
8
                cur_pipe = new_pipe;
1410
91.4k
            } else {
1411
91.4k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1412
91.4k
                                                                     tnode, descs);
1413
91.4k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1414
91.4k
            }
1415
91.4k
        } else if (is_streaming_agg) {
1416
1.26k
            if (need_create_cache_op) {
1417
0
                PipelinePtr new_pipe;
1418
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1419
0
                cache_op = op;
1420
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1421
0
                                                             descs);
1422
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1423
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1424
0
                cur_pipe = new_pipe;
1425
1.26k
            } else {
1426
1.26k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1427
1.26k
                                                             descs);
1428
1.26k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1429
1.26k
            }
1430
43.0k
        } else {
1431
            // create new pipeline to add query cache operator
1432
43.0k
            PipelinePtr new_pipe;
1433
43.0k
            if (need_create_cache_op) {
1434
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1435
2
                cache_op = op;
1436
2
            }
1437
1438
43.0k
            if (enable_spill) {
1439
190
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1440
190
                                                                     next_operator_id(), descs);
1441
42.9k
            } else {
1442
42.9k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1443
42.9k
            }
1444
43.0k
            if (need_create_cache_op) {
1445
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1446
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1447
2
                cur_pipe = new_pipe;
1448
43.0k
            } else {
1449
43.0k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1450
43.0k
            }
1451
1452
43.0k
            const auto downstream_pipeline_id = cur_pipe->id();
1453
43.0k
            if (!_dag.contains(downstream_pipeline_id)) {
1454
41.8k
                _dag.insert({downstream_pipeline_id, {}});
1455
41.8k
            }
1456
43.0k
            cur_pipe = add_pipeline(cur_pipe);
1457
43.0k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1458
1459
43.0k
            if (enable_spill) {
1460
190
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1461
190
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1462
42.9k
            } else {
1463
42.9k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1464
42.9k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1465
42.9k
            }
1466
43.0k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1467
43.0k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1468
43.0k
        }
1469
135k
        break;
1470
135k
    }
1471
135k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1472
76
        if (tnode.bucketed_agg_node.grouping_exprs.empty()) {
1473
0
            return Status::InternalError(
1474
0
                    "Bucketed aggregation node {} should not be used without group by keys",
1475
0
                    tnode.node_id);
1476
0
        }
1477
1478
        // Create source operator (goes on the current / downstream pipeline).
1479
76
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1480
76
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1481
1482
        // Create a new pipeline for the sink side.
1483
76
        const auto downstream_pipeline_id = cur_pipe->id();
1484
76
        if (!_dag.contains(downstream_pipeline_id)) {
1485
76
            _dag.insert({downstream_pipeline_id, {}});
1486
76
        }
1487
76
        cur_pipe = add_pipeline(cur_pipe);
1488
76
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1489
1490
        // Create sink operator.
1491
76
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1492
76
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1493
76
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1494
76
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1495
1496
        // Pre-register a single shared state for ALL instances so that every
1497
        // sink instance writes its per-instance hash table into the same
1498
        // BucketedAggSharedState and every source instance can merge across
1499
        // all of them.
1500
76
        {
1501
76
            auto shared_state = BucketedAggSharedState::create_shared();
1502
76
            shared_state->id = op->operator_id();
1503
76
            shared_state->related_op_ids.insert(op->operator_id());
1504
1505
639
            for (int i = 0; i < _num_instances; i++) {
1506
563
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1507
563
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1508
563
                sink_dep->set_shared_state(shared_state.get());
1509
563
                shared_state->sink_deps.push_back(sink_dep);
1510
563
            }
1511
76
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1512
76
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1513
76
            _op_id_to_shared_state.insert(
1514
76
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1515
76
        }
1516
76
        break;
1517
76
    }
1518
8.95k
    case TPlanNodeType::HASH_JOIN_NODE: {
1519
8.95k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1520
8.95k
                                       tnode.hash_join_node.is_broadcast_join;
1521
8.95k
        const auto enable_spill = _runtime_state->enable_spill();
1522
8.95k
        if (enable_spill && !is_broadcast_join) {
1523
0
            auto tnode_ = tnode;
1524
0
            tnode_.runtime_filters.clear();
1525
0
            auto inner_probe_operator =
1526
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1527
1528
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1529
            // So here use `tnode_` which has no runtime filters.
1530
0
            auto probe_side_inner_sink_operator =
1531
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1532
1533
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1534
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1535
1536
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1537
0
                    pool, tnode_, next_operator_id(), descs);
1538
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1539
0
                                                inner_probe_operator);
1540
0
            op = std::move(probe_operator);
1541
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1542
1543
0
            const auto downstream_pipeline_id = cur_pipe->id();
1544
0
            if (!_dag.contains(downstream_pipeline_id)) {
1545
0
                _dag.insert({downstream_pipeline_id, {}});
1546
0
            }
1547
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1548
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1549
1550
0
            auto inner_sink_operator =
1551
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1552
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1553
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1554
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1555
1556
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1557
0
            sink_ops.push_back(std::move(sink_operator));
1558
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1559
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1560
1561
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1562
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1563
8.95k
        } else {
1564
8.95k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1565
8.95k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1566
1567
8.95k
            const auto downstream_pipeline_id = cur_pipe->id();
1568
8.95k
            if (!_dag.contains(downstream_pipeline_id)) {
1569
7.22k
                _dag.insert({downstream_pipeline_id, {}});
1570
7.22k
            }
1571
8.95k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1572
8.95k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1573
1574
8.95k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1575
8.95k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1576
8.95k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1577
8.95k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1578
1579
8.95k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1580
8.95k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1581
8.95k
        }
1582
8.95k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1583
1.78k
            std::shared_ptr<HashJoinSharedState> shared_state =
1584
1.78k
                    HashJoinSharedState::create_shared(_num_instances);
1585
12.3k
            for (int i = 0; i < _num_instances; i++) {
1586
10.5k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1587
10.5k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1588
10.5k
                sink_dep->set_shared_state(shared_state.get());
1589
10.5k
                shared_state->sink_deps.push_back(sink_dep);
1590
10.5k
            }
1591
1.78k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1592
1.78k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1593
1.78k
            _op_id_to_shared_state.insert(
1594
1.78k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1595
1.78k
        }
1596
8.95k
        break;
1597
8.95k
    }
1598
2.14k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1599
2.14k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1600
2.14k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1601
1602
2.14k
        const auto downstream_pipeline_id = cur_pipe->id();
1603
2.14k
        if (!_dag.contains(downstream_pipeline_id)) {
1604
1.91k
            _dag.insert({downstream_pipeline_id, {}});
1605
1.91k
        }
1606
2.14k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1607
2.14k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1608
1609
2.14k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1610
2.14k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1611
2.14k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1612
2.14k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1613
2.14k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1614
2.14k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1615
2.14k
        break;
1616
2.14k
    }
1617
49.3k
    case TPlanNodeType::UNION_NODE: {
1618
49.3k
        int child_count = tnode.num_children;
1619
49.3k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1620
49.3k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1621
1622
49.3k
        const auto downstream_pipeline_id = cur_pipe->id();
1623
49.3k
        if (!_dag.contains(downstream_pipeline_id)) {
1624
48.8k
            _dag.insert({downstream_pipeline_id, {}});
1625
48.8k
        }
1626
50.3k
        for (int i = 0; i < child_count; i++) {
1627
996
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1628
996
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1629
996
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1630
996
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1631
996
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1632
996
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1633
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1634
996
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1635
996
        }
1636
49.3k
        break;
1637
49.3k
    }
1638
49.3k
    case TPlanNodeType::SORT_NODE: {
1639
32.8k
        const auto should_spill = _runtime_state->enable_spill() &&
1640
32.8k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1641
32.8k
        const bool use_local_merge =
1642
32.8k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1643
32.8k
        if (should_spill) {
1644
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1645
32.8k
        } else if (use_local_merge) {
1646
31.1k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1647
31.1k
                                                                 descs);
1648
31.1k
        } else {
1649
1.74k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1650
1.74k
        }
1651
32.8k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1652
1653
32.8k
        const auto downstream_pipeline_id = cur_pipe->id();
1654
32.8k
        if (!_dag.contains(downstream_pipeline_id)) {
1655
32.8k
            _dag.insert({downstream_pipeline_id, {}});
1656
32.8k
        }
1657
32.8k
        cur_pipe = add_pipeline(cur_pipe);
1658
32.8k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1659
1660
32.8k
        if (should_spill) {
1661
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1662
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1663
32.8k
        } else {
1664
32.8k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1665
32.8k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1666
32.8k
        }
1667
32.8k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1668
32.8k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1669
32.8k
        break;
1670
32.8k
    }
1671
32.8k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1672
63
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1673
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1674
1675
63
        const auto downstream_pipeline_id = cur_pipe->id();
1676
63
        if (!_dag.contains(downstream_pipeline_id)) {
1677
63
            _dag.insert({downstream_pipeline_id, {}});
1678
63
        }
1679
63
        cur_pipe = add_pipeline(cur_pipe);
1680
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1681
1682
63
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1683
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1684
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1685
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1686
63
        break;
1687
63
    }
1688
1.47k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1689
1.47k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1690
1.47k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1691
1692
1.47k
        const auto downstream_pipeline_id = cur_pipe->id();
1693
1.47k
        if (!_dag.contains(downstream_pipeline_id)) {
1694
1.46k
            _dag.insert({downstream_pipeline_id, {}});
1695
1.46k
        }
1696
1.47k
        cur_pipe = add_pipeline(cur_pipe);
1697
1.47k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1698
1699
1.47k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1700
1.47k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1701
1.47k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1702
1.47k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1703
1.47k
        break;
1704
1.47k
    }
1705
1.47k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1706
667
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1707
667
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1708
667
        break;
1709
667
    }
1710
667
    case TPlanNodeType::INTERSECT_NODE: {
1711
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1712
133
                                                                      cur_pipe, sink_ops));
1713
133
        break;
1714
133
    }
1715
133
    case TPlanNodeType::EXCEPT_NODE: {
1716
131
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1717
131
                                                                       cur_pipe, sink_ops));
1718
131
        break;
1719
131
    }
1720
314
    case TPlanNodeType::REPEAT_NODE: {
1721
314
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1722
314
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1723
314
        break;
1724
314
    }
1725
908
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1726
908
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1727
908
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1728
908
        break;
1729
908
    }
1730
908
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1731
18
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1732
18
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1733
18
        break;
1734
18
    }
1735
1.43k
    case TPlanNodeType::EMPTY_SET_NODE: {
1736
1.43k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1737
1.43k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1738
1.43k
        break;
1739
1.43k
    }
1740
1.43k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1741
263
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1742
263
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1743
263
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1744
263
        break;
1745
263
    }
1746
1.53k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1747
1.53k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1748
1.53k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1749
1.53k
        break;
1750
1.53k
    }
1751
5.12k
    case TPlanNodeType::META_SCAN_NODE: {
1752
5.12k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1753
5.12k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1754
5.12k
        break;
1755
5.12k
    }
1756
5.12k
    case TPlanNodeType::SELECT_NODE: {
1757
601
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1758
601
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1759
601
        break;
1760
601
    }
1761
601
    case TPlanNodeType::REC_CTE_NODE: {
1762
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1763
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1764
1765
151
        const auto downstream_pipeline_id = cur_pipe->id();
1766
151
        if (!_dag.contains(downstream_pipeline_id)) {
1767
148
            _dag.insert({downstream_pipeline_id, {}});
1768
148
        }
1769
1770
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1771
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1772
1773
151
        DataSinkOperatorPtr anchor_sink;
1774
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1775
151
                                                                  op->operator_id(), tnode, descs);
1776
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1777
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1778
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1779
1780
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1781
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1782
1783
151
        DataSinkOperatorPtr rec_sink;
1784
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1785
151
                                                         tnode, descs);
1786
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1787
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1788
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1789
1790
151
        break;
1791
151
    }
1792
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1793
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1794
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1795
1.95k
        break;
1796
1.95k
    }
1797
1.95k
    default:
1798
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1799
0
                                     print_plan_node_type(tnode.node_type));
1800
521k
    }
1801
520k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1802
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1803
0
        op->set_serial_operator();
1804
0
    }
1805
1806
520k
    return Status::OK();
1807
521k
}
1808
// NOLINTEND(readability-function-cognitive-complexity)
1809
// NOLINTEND(readability-function-size)
1810
1811
template <bool is_intersect>
1812
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1813
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1814
264
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1815
264
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1816
264
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1817
1818
264
    const auto downstream_pipeline_id = cur_pipe->id();
1819
264
    if (!_dag.contains(downstream_pipeline_id)) {
1820
240
        _dag.insert({downstream_pipeline_id, {}});
1821
240
    }
1822
1823
886
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1824
622
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1825
622
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1826
1827
622
        if (child_id == 0) {
1828
264
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1829
264
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1830
358
        } else {
1831
358
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1832
358
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1833
358
        }
1834
622
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1835
622
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1836
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1837
622
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1838
622
    }
1839
1840
264
    return Status::OK();
1841
264
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1814
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1815
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1816
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1817
1818
133
    const auto downstream_pipeline_id = cur_pipe->id();
1819
133
    if (!_dag.contains(downstream_pipeline_id)) {
1820
118
        _dag.insert({downstream_pipeline_id, {}});
1821
118
    }
1822
1823
478
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1824
345
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1825
345
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1826
1827
345
        if (child_id == 0) {
1828
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1829
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1830
212
        } else {
1831
212
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1832
212
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1833
212
        }
1834
345
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1835
345
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1836
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1837
345
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1838
345
    }
1839
1840
133
    return Status::OK();
1841
133
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1814
131
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1815
131
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1816
131
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1817
1818
131
    const auto downstream_pipeline_id = cur_pipe->id();
1819
131
    if (!_dag.contains(downstream_pipeline_id)) {
1820
122
        _dag.insert({downstream_pipeline_id, {}});
1821
122
    }
1822
1823
408
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1824
277
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1825
277
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1826
1827
277
        if (child_id == 0) {
1828
131
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1829
131
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1830
146
        } else {
1831
146
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1832
146
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1833
146
        }
1834
277
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1835
277
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1836
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1837
277
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1838
277
    }
1839
1840
131
    return Status::OK();
1841
131
}
1842
1843
323k
Status PipelineFragmentContext::submit() {
1844
323k
    if (_submitted) {
1845
0
        return Status::InternalError("submitted");
1846
0
    }
1847
323k
    _submitted = true;
1848
1849
323k
    int submit_tasks = 0;
1850
323k
    Status st;
1851
323k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1852
1.03M
    for (auto& task : _tasks) {
1853
1.69M
        for (auto& t : task) {
1854
1.69M
            st = scheduler->submit(t.first);
1855
1.69M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1856
1.69M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1857
1.69M
            if (!st) {
1858
0
                cancel(Status::InternalError("submit context to executor fail"));
1859
0
                std::lock_guard<std::mutex> l(_task_mutex);
1860
0
                _total_tasks = submit_tasks;
1861
0
                break;
1862
0
            }
1863
1.69M
            submit_tasks++;
1864
1.69M
        }
1865
1.03M
    }
1866
323k
    if (!st.ok()) {
1867
0
        bool need_remove = false;
1868
0
        {
1869
0
            std::lock_guard<std::mutex> l(_task_mutex);
1870
0
            if (_closed_tasks >= _total_tasks) {
1871
0
                need_remove = _close_fragment_instance();
1872
0
            }
1873
0
        }
1874
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1875
0
        if (need_remove) {
1876
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1877
0
        }
1878
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1879
0
                                     BackendOptions::get_localhost());
1880
323k
    } else {
1881
323k
        return st;
1882
323k
    }
1883
323k
}
1884
1885
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1886
0
    if (_runtime_state->enable_profile()) {
1887
0
        std::stringstream ss;
1888
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1889
0
            runtime_profile_ptr->pretty_print(&ss);
1890
0
        }
1891
1892
0
        if (_runtime_state->load_channel_profile()) {
1893
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1894
0
        }
1895
1896
0
        auto profile_str =
1897
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1898
0
                            this->_fragment_id, extra_info, ss.str());
1899
0
        LOG_LONG_STRING(INFO, profile_str);
1900
0
    }
1901
0
}
1902
// If all pipeline tasks binded to the fragment instance are finished, then we could
1903
// close the fragment instance.
1904
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1905
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1906
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1907
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1908
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1909
// (via debug_string()).
1910
326k
bool PipelineFragmentContext::_close_fragment_instance() {
1911
326k
    if (_is_fragment_instance_closed) {
1912
0
        return false;
1913
0
    }
1914
326k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1915
326k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1916
326k
    if (!_need_notify_close) {
1917
323k
        auto st = send_report(true);
1918
323k
        if (!st) {
1919
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1920
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1921
0
        }
1922
323k
    }
1923
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1924
    // Since stream load does not have someting like coordinator on FE, so
1925
    // backend can not report profile to FE, ant its profile can not be shown
1926
    // in the same way with other query. So we print the profile content to info log.
1927
1928
326k
    if (_runtime_state->enable_profile() &&
1929
326k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1930
2.40k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1931
2.40k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1932
0
        std::stringstream ss;
1933
        // Compute the _local_time_percent before pretty_print the runtime_profile
1934
        // Before add this operation, the print out like that:
1935
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1936
        // After add the operation, the print out like that:
1937
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1938
        // We can easily know the exec node execute time without child time consumed.
1939
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1940
0
            runtime_profile_ptr->pretty_print(&ss);
1941
0
        }
1942
1943
0
        if (_runtime_state->load_channel_profile()) {
1944
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1945
0
        }
1946
1947
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1948
0
    }
1949
1950
326k
    if (_query_ctx->enable_profile()) {
1951
2.40k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1952
2.40k
                                         collect_realtime_load_channel_profile());
1953
2.40k
    }
1954
1955
    // Return whether the caller needs to remove from the pipeline map.
1956
    // The caller must do this after releasing _task_mutex.
1957
326k
    return !_need_notify_close;
1958
326k
}
1959
1960
1.68M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1961
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1962
1.68M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1963
1.68M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1964
509k
        if (_dag.contains(pipeline_id)) {
1965
273k
            for (auto dep : _dag[pipeline_id]) {
1966
273k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1967
273k
            }
1968
223k
        }
1969
509k
    }
1970
1.68M
    bool need_remove = false;
1971
1.68M
    {
1972
1.68M
        std::lock_guard<std::mutex> l(_task_mutex);
1973
1.68M
        ++_closed_tasks;
1974
1.68M
        if (_closed_tasks >= _total_tasks) {
1975
326k
            need_remove = _close_fragment_instance();
1976
326k
        }
1977
1.68M
    }
1978
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1979
1.68M
    if (need_remove) {
1980
323k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1981
323k
    }
1982
1.68M
}
1983
1984
41.9k
std::string PipelineFragmentContext::get_load_error_url() {
1985
41.9k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1986
0
        return to_load_error_http_path(str);
1987
0
    }
1988
111k
    for (auto& tasks : _tasks) {
1989
188k
        for (auto& task : tasks) {
1990
188k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1991
160
                return to_load_error_http_path(str);
1992
160
            }
1993
188k
        }
1994
111k
    }
1995
41.8k
    return "";
1996
41.9k
}
1997
1998
41.9k
std::string PipelineFragmentContext::get_first_error_msg() {
1999
41.9k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2000
0
        return str;
2001
0
    }
2002
111k
    for (auto& tasks : _tasks) {
2003
188k
        for (auto& task : tasks) {
2004
188k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2005
160
                return str;
2006
160
            }
2007
188k
        }
2008
111k
    }
2009
41.8k
    return "";
2010
41.9k
}
2011
2012
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2013
0
    std::stringstream url;
2014
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2015
0
        << "/api/_download_load?"
2016
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2017
0
    return url.str();
2018
0
}
2019
2020
36.7k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2021
36.7k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2022
36.7k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2023
36.7k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2024
36.7k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2025
36.7k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2026
36.7k
    });
2027
2028
36.7k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2029
36.7k
    if (req.coord_addr.hostname == "external") {
2030
        // External query (flink/spark read tablets) not need to report to FE.
2031
0
        return;
2032
0
    }
2033
36.7k
    int callback_retries = 10;
2034
36.7k
    const int sleep_ms = 1000;
2035
36.7k
    Status exec_status = req.status;
2036
36.7k
    Status coord_status;
2037
36.7k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2038
36.7k
    do {
2039
36.7k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2040
36.7k
                                                            req.coord_addr, &coord_status);
2041
36.7k
        if (!coord_status.ok()) {
2042
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2043
0
        }
2044
36.7k
    } while (!coord_status.ok() && callback_retries-- > 0);
2045
2046
36.7k
    if (!coord_status.ok()) {
2047
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2048
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2049
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2050
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2051
0
        return;
2052
0
    }
2053
2054
36.7k
    TReportExecStatusParams params;
2055
36.7k
    params.protocol_version = FrontendServiceVersion::V1;
2056
36.7k
    params.__set_query_id(req.query_id);
2057
36.7k
    params.__set_backend_num(req.backend_num);
2058
36.7k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2059
36.7k
    params.__set_fragment_id(req.fragment_id);
2060
36.7k
    params.__set_status(exec_status.to_thrift());
2061
36.7k
    params.__set_done(req.done);
2062
36.7k
    params.__set_query_type(req.runtime_state->query_type());
2063
36.7k
    params.__isset.profile = false;
2064
2065
36.7k
    DCHECK(req.runtime_state != nullptr);
2066
2067
36.7k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2068
32.7k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2069
32.7k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2070
32.7k
    } else {
2071
3.99k
        DCHECK(!req.runtime_states.empty());
2072
3.99k
        if (!req.runtime_state->output_files().empty()) {
2073
0
            params.__isset.delta_urls = true;
2074
0
            for (auto& it : req.runtime_state->output_files()) {
2075
0
                params.delta_urls.push_back(_to_http_path(it));
2076
0
            }
2077
0
        }
2078
3.99k
        if (!params.delta_urls.empty()) {
2079
0
            params.__isset.delta_urls = true;
2080
0
        }
2081
3.99k
    }
2082
2083
36.7k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2084
36.7k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2085
36.7k
    static std::string s_unselected_rows = "unselected.rows";
2086
36.7k
    int64_t num_rows_load_success = 0;
2087
36.7k
    int64_t num_rows_load_filtered = 0;
2088
36.7k
    int64_t num_rows_load_unselected = 0;
2089
36.7k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2090
36.7k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2091
36.7k
        req.runtime_state->num_finished_range() > 0) {
2092
0
        params.__isset.load_counters = true;
2093
2094
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2095
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2096
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2097
0
        params.__isset.fragment_instance_reports = true;
2098
0
        TFragmentInstanceReport t;
2099
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2100
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2101
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2102
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2103
0
        params.fragment_instance_reports.push_back(t);
2104
36.7k
    } else if (!req.runtime_states.empty()) {
2105
139k
        for (auto* rs : req.runtime_states) {
2106
139k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2107
139k
                rs->num_finished_range() > 0) {
2108
30.2k
                params.__isset.load_counters = true;
2109
30.2k
                num_rows_load_success += rs->num_rows_load_success();
2110
30.2k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2111
30.2k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2112
30.2k
                params.__isset.fragment_instance_reports = true;
2113
30.2k
                TFragmentInstanceReport t;
2114
30.2k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2115
30.2k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2116
30.2k
                t.__set_loaded_rows(rs->num_rows_load_total());
2117
30.2k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2118
30.2k
                params.fragment_instance_reports.push_back(t);
2119
30.2k
            }
2120
139k
        }
2121
36.7k
    }
2122
36.7k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2123
36.7k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2124
36.7k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2125
2126
36.7k
    if (!req.load_error_url.empty()) {
2127
145
        params.__set_tracking_url(req.load_error_url);
2128
145
    }
2129
36.7k
    if (!req.first_error_msg.empty()) {
2130
145
        params.__set_first_error_msg(req.first_error_msg);
2131
145
    }
2132
139k
    for (auto* rs : req.runtime_states) {
2133
139k
        if (rs->wal_id() > 0) {
2134
109
            params.__set_txn_id(rs->wal_id());
2135
109
            params.__set_label(rs->import_label());
2136
109
        }
2137
139k
    }
2138
36.7k
    if (!req.runtime_state->export_output_files().empty()) {
2139
0
        params.__isset.export_files = true;
2140
0
        params.export_files = req.runtime_state->export_output_files();
2141
36.7k
    } else if (!req.runtime_states.empty()) {
2142
139k
        for (auto* rs : req.runtime_states) {
2143
139k
            if (!rs->export_output_files().empty()) {
2144
0
                params.__isset.export_files = true;
2145
0
                params.export_files.insert(params.export_files.end(),
2146
0
                                           rs->export_output_files().begin(),
2147
0
                                           rs->export_output_files().end());
2148
0
            }
2149
139k
        }
2150
36.7k
    }
2151
36.7k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2152
0
        params.__isset.commitInfos = true;
2153
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2154
36.7k
    } else if (!req.runtime_states.empty()) {
2155
139k
        for (auto* rs : req.runtime_states) {
2156
139k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2157
24.9k
                params.__isset.commitInfos = true;
2158
24.9k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2159
24.9k
            }
2160
139k
        }
2161
36.7k
    }
2162
36.7k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2163
0
        params.__isset.errorTabletInfos = true;
2164
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2165
36.7k
    } else if (!req.runtime_states.empty()) {
2166
139k
        for (auto* rs : req.runtime_states) {
2167
139k
            if (auto rs_eti = rs->error_tablet_infos(); !rs_eti.empty()) {
2168
0
                params.__isset.errorTabletInfos = true;
2169
0
                params.errorTabletInfos.insert(params.errorTabletInfos.end(), rs_eti.begin(),
2170
0
                                               rs_eti.end());
2171
0
            }
2172
139k
        }
2173
36.7k
    }
2174
36.7k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2175
0
        params.__isset.hive_partition_updates = true;
2176
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2177
0
                                             hpu.end());
2178
36.7k
    } else if (!req.runtime_states.empty()) {
2179
139k
        for (auto* rs : req.runtime_states) {
2180
139k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2181
0
                params.__isset.hive_partition_updates = true;
2182
0
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2183
0
                                                     rs_hpu.begin(), rs_hpu.end());
2184
0
            }
2185
139k
        }
2186
36.7k
    }
2187
36.7k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2188
0
        params.__isset.iceberg_commit_datas = true;
2189
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2190
0
                                           icd.end());
2191
36.7k
    } else if (!req.runtime_states.empty()) {
2192
139k
        for (auto* rs : req.runtime_states) {
2193
139k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2194
0
                params.__isset.iceberg_commit_datas = true;
2195
0
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2196
0
                                                   rs_icd.begin(), rs_icd.end());
2197
0
            }
2198
139k
        }
2199
36.7k
    }
2200
2201
36.7k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2202
0
        params.__isset.mc_commit_datas = true;
2203
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2204
36.7k
    } else if (!req.runtime_states.empty()) {
2205
139k
        for (auto* rs : req.runtime_states) {
2206
139k
            if (auto rs_mcd = rs->mc_commit_datas(); !rs_mcd.empty()) {
2207
0
                params.__isset.mc_commit_datas = true;
2208
0
                params.mc_commit_datas.insert(params.mc_commit_datas.end(), rs_mcd.begin(),
2209
0
                                              rs_mcd.end());
2210
0
            }
2211
139k
        }
2212
36.7k
    }
2213
2214
36.7k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2215
36.7k
    params.__isset.error_log = (!params.error_log.empty());
2216
2217
36.7k
    if (_exec_env->cluster_info()->backend_id != 0) {
2218
36.7k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2219
36.7k
    }
2220
2221
36.7k
    TReportExecStatusResult res;
2222
36.7k
    Status rpc_status;
2223
2224
36.7k
    VLOG_DEBUG << "reportExecStatus params is "
2225
15
               << apache::thrift::ThriftDebugString(params).c_str();
2226
36.7k
    if (!exec_status.ok()) {
2227
1.51k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2228
1.51k
                     << " to coordinator: " << req.coord_addr
2229
1.51k
                     << ", query id: " << print_id(req.query_id);
2230
1.51k
    }
2231
36.7k
    try {
2232
36.7k
        try {
2233
36.7k
            (*coord)->reportExecStatus(res, params);
2234
36.7k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2235
#ifndef ADDRESS_SANITIZER
2236
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2237
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2238
                         << req.coord_addr << ", err: " << e.what();
2239
#endif
2240
0
            rpc_status = coord->reopen();
2241
2242
0
            if (!rpc_status.ok()) {
2243
0
                req.cancel_fn(rpc_status);
2244
0
                return;
2245
0
            }
2246
0
            (*coord)->reportExecStatus(res, params);
2247
0
        }
2248
2249
36.7k
        rpc_status = Status::create<false>(res.status);
2250
36.7k
    } catch (apache::thrift::TException& e) {
2251
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2252
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2253
0
    }
2254
2255
36.7k
    if (!rpc_status.ok()) {
2256
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2257
0
                 print_id(req.query_id), rpc_status.to_string());
2258
0
        req.cancel_fn(rpc_status);
2259
0
    }
2260
36.7k
}
2261
2262
327k
Status PipelineFragmentContext::send_report(bool done) {
2263
327k
    Status exec_status = _query_ctx->exec_status();
2264
    // If plan is done successfully, but _is_report_success is false,
2265
    // no need to send report.
2266
    // Load will set _is_report_success to true because load wants to know
2267
    // the process.
2268
327k
    if (!_is_report_success && done && exec_status.ok()) {
2269
290k
        return Status::OK();
2270
290k
    }
2271
2272
    // If both _is_report_success and _is_report_on_cancel are false,
2273
    // which means no matter query is success or failed, no report is needed.
2274
    // This may happen when the query limit reached and
2275
    // a internal cancellation being processed
2276
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2277
    // be set to false, to avoid sending fault report to FE.
2278
36.9k
    if (!_is_report_success && !_is_report_on_cancel) {
2279
162
        if (done) {
2280
            // if done is true, which means the query is finished successfully, we can safely close the fragment instance without sending report to FE, and just return OK status here.
2281
162
            return Status::OK();
2282
162
        }
2283
0
        return Status::NeedSendAgain("");
2284
162
    }
2285
2286
36.7k
    std::vector<RuntimeState*> runtime_states;
2287
2288
87.7k
    for (auto& tasks : _tasks) {
2289
139k
        for (auto& task : tasks) {
2290
139k
            runtime_states.push_back(task.second.get());
2291
139k
        }
2292
87.7k
    }
2293
2294
36.7k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2295
36.7k
                                        ? get_load_error_url()
2296
36.7k
                                        : _query_ctx->get_load_error_url();
2297
36.7k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2298
36.7k
                                          ? get_first_error_msg()
2299
36.7k
                                          : _query_ctx->get_first_error_msg();
2300
2301
36.7k
    ReportStatusRequest req {.status = exec_status,
2302
36.7k
                             .runtime_states = runtime_states,
2303
36.7k
                             .done = done || !exec_status.ok(),
2304
36.7k
                             .coord_addr = _query_ctx->coord_addr,
2305
36.7k
                             .query_id = _query_id,
2306
36.7k
                             .fragment_id = _fragment_id,
2307
36.7k
                             .fragment_instance_id = TUniqueId(),
2308
36.7k
                             .backend_num = -1,
2309
36.7k
                             .runtime_state = _runtime_state.get(),
2310
36.7k
                             .load_error_url = load_eror_url,
2311
36.7k
                             .first_error_msg = first_error_msg,
2312
36.7k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2313
36.7k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2314
36.7k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2315
36.7k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2316
36.7k
        _coordinator_callback(req);
2317
36.7k
        if (!req.done) {
2318
3.62k
            ctx->refresh_next_report_time();
2319
3.62k
        }
2320
36.7k
    });
2321
36.9k
}
2322
2323
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2324
0
    size_t res = 0;
2325
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2326
    // here to traverse the vector.
2327
0
    for (const auto& task_instances : _tasks) {
2328
0
        for (const auto& task : task_instances) {
2329
0
            if (task.first->is_running()) {
2330
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2331
0
                                      << " is running, task: " << (void*)task.first.get()
2332
0
                                      << ", is_running: " << task.first->is_running();
2333
0
                *has_running_task = true;
2334
0
                return 0;
2335
0
            }
2336
2337
0
            size_t revocable_size = task.first->get_revocable_size();
2338
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2339
0
                res += revocable_size;
2340
0
            }
2341
0
        }
2342
0
    }
2343
0
    return res;
2344
0
}
2345
2346
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2347
0
    std::vector<PipelineTask*> revocable_tasks;
2348
0
    for (const auto& task_instances : _tasks) {
2349
0
        for (const auto& task : task_instances) {
2350
0
            size_t revocable_size_ = task.first->get_revocable_size();
2351
2352
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2353
0
                revocable_tasks.emplace_back(task.first.get());
2354
0
            }
2355
0
        }
2356
0
    }
2357
0
    return revocable_tasks;
2358
0
}
2359
2360
101
std::string PipelineFragmentContext::debug_string() {
2361
101
    std::lock_guard<std::mutex> l(_task_mutex);
2362
101
    fmt::memory_buffer debug_string_buffer;
2363
101
    fmt::format_to(debug_string_buffer,
2364
101
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2365
101
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2366
101
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2367
630
    for (size_t j = 0; j < _tasks.size(); j++) {
2368
529
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2369
1.14k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2370
612
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2371
612
                           _tasks[j][i].first->debug_string());
2372
612
        }
2373
529
    }
2374
2375
101
    return fmt::to_string(debug_string_buffer);
2376
101
}
2377
2378
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2379
2.40k
PipelineFragmentContext::collect_realtime_profile() const {
2380
2.40k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2381
2382
    // we do not have mutex to protect pipeline_id_to_profile
2383
    // so we need to make sure this funciton is invoked after fragment context
2384
    // has already been prepared.
2385
2.40k
    if (!_prepared) {
2386
0
        std::string msg =
2387
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2388
0
        DCHECK(false) << msg;
2389
0
        LOG_ERROR(msg);
2390
0
        return res;
2391
0
    }
2392
2393
    // Make sure first profile is fragment level profile
2394
2.40k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2395
2.40k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2396
2.40k
    res.push_back(fragment_profile);
2397
2398
    // pipeline_id_to_profile is initialized in prepare stage
2399
4.73k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2400
4.73k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2401
4.73k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2402
4.73k
        res.push_back(profile_ptr);
2403
4.73k
    }
2404
2405
2.40k
    return res;
2406
2.40k
}
2407
2408
std::shared_ptr<TRuntimeProfileTree>
2409
2.40k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2410
    // we do not have mutex to protect pipeline_id_to_profile
2411
    // so we need to make sure this funciton is invoked after fragment context
2412
    // has already been prepared.
2413
2.40k
    if (!_prepared) {
2414
0
        std::string msg =
2415
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2416
0
        DCHECK(false) << msg;
2417
0
        LOG_ERROR(msg);
2418
0
        return nullptr;
2419
0
    }
2420
2421
9.26k
    for (const auto& tasks : _tasks) {
2422
18.9k
        for (const auto& task : tasks) {
2423
18.9k
            if (task.second->load_channel_profile() == nullptr) {
2424
0
                continue;
2425
0
            }
2426
2427
18.9k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2428
2429
18.9k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2430
18.9k
                                                           _runtime_state->profile_level());
2431
18.9k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2432
18.9k
        }
2433
9.26k
    }
2434
2435
2.40k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2436
2.40k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2437
2.40k
                                                      _runtime_state->profile_level());
2438
2.40k
    return load_channel_profile;
2439
2.40k
}
2440
2441
// Collect runtime filter IDs registered by all tasks in this PFC.
2442
// Used during recursive CTE stage transitions to know which filters to deregister
2443
// before creating the new PFC for the next recursion round.
2444
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2445
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2446
// the vector sizes do not change, and individual RuntimeState filter sets are
2447
// written only during open() which has completed by the time we reach rerun.
2448
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2449
3.28k
    std::set<int> result;
2450
8.55k
    for (const auto& _task : _tasks) {
2451
15.0k
        for (const auto& task : _task) {
2452
15.0k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2453
15.0k
            result.merge(set);
2454
15.0k
        }
2455
8.55k
    }
2456
3.28k
    if (_runtime_state) {
2457
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2458
3.28k
        result.merge(set);
2459
3.28k
    }
2460
3.28k
    return result;
2461
3.28k
}
2462
2463
328k
void PipelineFragmentContext::_release_resource() {
2464
328k
    std::lock_guard<std::mutex> l(_task_mutex);
2465
    // The memory released by the query end is recorded in the query mem tracker.
2466
328k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2467
328k
    auto st = _query_ctx->exec_status();
2468
1.04M
    for (auto& _task : _tasks) {
2469
1.04M
        if (!_task.empty()) {
2470
1.04M
            _call_back(_task.front().first->runtime_state(), &st);
2471
1.04M
        }
2472
1.04M
    }
2473
328k
    _tasks.clear();
2474
328k
    _dag.clear();
2475
328k
    _pip_id_to_pipeline.clear();
2476
328k
    _pipelines.clear();
2477
328k
    _sink.reset();
2478
328k
    _root_op.reset();
2479
328k
    _runtime_filter_mgr_map.clear();
2480
328k
    _op_id_to_shared_state.clear();
2481
328k
}
2482
2483
} // namespace doris