Coverage Report

Created: 2026-05-15 08:39

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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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"
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#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"
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#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"
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#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
325k
        : _query_id(std::move(query_id)),
144
325k
          _fragment_id(request.fragment_id),
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325k
          _exec_env(exec_env),
146
325k
          _query_ctx(std::move(query_ctx)),
147
325k
          _call_back(call_back),
148
325k
          _is_report_on_cancel(true),
149
325k
          _params(request),
150
325k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
325k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
325k
                                                               : false) {
153
325k
    _fragment_watcher.start();
154
325k
}
155
156
325k
PipelineFragmentContext::~PipelineFragmentContext() {
157
325k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
325k
            .tag("query_id", print_id(_query_id))
159
325k
            .tag("fragment_id", _fragment_id);
160
325k
    _release_resource();
161
325k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
325k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
325k
        _runtime_state.reset();
165
325k
        _query_ctx.reset();
166
325k
    }
167
325k
}
168
169
237
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
237
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
237
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
237
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
179
// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
8.16k
bool PipelineFragmentContext::notify_close() {
181
8.16k
    bool all_closed = false;
182
8.16k
    bool need_remove = false;
183
8.16k
    {
184
8.16k
        std::lock_guard<std::mutex> l(_task_mutex);
185
8.16k
        if (_closed_tasks >= _total_tasks) {
186
3.50k
            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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3.42k
                need_remove = true;
193
3.42k
            }
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3.50k
            all_closed = true;
195
3.50k
        }
196
        // make fragment release by self after cancel
197
8.16k
        _need_notify_close = false;
198
8.16k
    }
199
8.16k
    if (need_remove) {
200
3.42k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.42k
    }
202
8.16k
    return all_closed;
203
8.16k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
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// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
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// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
4.68k
void PipelineFragmentContext::cancel(const Status reason) {
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4.68k
    LOG_INFO("PipelineFragmentContext::cancel")
211
4.68k
            .tag("query_id", print_id(_query_id))
212
4.68k
            .tag("fragment_id", _fragment_id)
213
4.68k
            .tag("reason", reason.to_string());
214
4.68k
    if (notify_close()) {
215
95
        return;
216
95
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
4.58k
    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
4.58k
    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
4.58k
    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
4.58k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
25
        _query_ctx->set_load_error_url(error_url);
236
25
    }
237
238
4.58k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
25
        _query_ctx->set_first_error_msg(first_error_msg);
240
25
    }
241
242
4.58k
    _query_ctx->cancel(reason, _fragment_id);
243
4.58k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
214
        _is_report_on_cancel = false;
245
4.37k
    } else {
246
14.1k
        for (auto& id : _fragment_instance_ids) {
247
14.1k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
14.1k
        }
249
4.37k
    }
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
4.58k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
4.58k
    if (stream_load_ctx != nullptr) {
254
30
        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
30
        stream_load_ctx->error_url = get_load_error_url();
259
30
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
30
    }
261
262
14.7k
    for (auto& tasks : _tasks) {
263
29.4k
        for (auto& task : tasks) {
264
29.4k
            task.first->unblock_all_dependencies();
265
29.4k
        }
266
14.7k
    }
267
4.58k
}
268
269
506k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
506k
    PipelineId id = _next_pipeline_id++;
271
506k
    auto pipeline = std::make_shared<Pipeline>(
272
506k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
506k
            parent ? parent->num_tasks() : _num_instances);
274
506k
    if (idx >= 0) {
275
91.0k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
415k
    } else {
277
415k
        _pipelines.emplace_back(pipeline);
278
415k
    }
279
506k
    if (parent) {
280
179k
        parent->set_children(pipeline);
281
179k
    }
282
506k
    return pipeline;
283
506k
}
284
285
325k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
325k
    {
287
325k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
325k
        auto root_pipeline = add_pipeline();
290
325k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
325k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
325k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
325k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
325k
                                          _params.fragment.output_exprs, _params,
299
325k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
325k
                                          *_desc_tbl, root_pipeline->id()));
301
325k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
325k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
414k
        for (PipelinePtr& pipeline : _pipelines) {
305
414k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
414k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
414k
        }
308
325k
    }
309
    // 4. Build local exchanger
310
325k
    if (_runtime_state->enable_local_shuffle()) {
311
322k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
322k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
322k
                                             _params.bucket_seq_to_instance_idx,
314
322k
                                             _params.shuffle_idx_to_instance_idx));
315
322k
    }
316
317
    // 5. Initialize global states in pipelines.
318
506k
    for (PipelinePtr& pipeline : _pipelines) {
319
506k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
506k
        pipeline->children().clear();
321
506k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
506k
    }
323
324
323k
    {
325
323k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
323k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
323k
    }
329
330
323k
    return Status::OK();
331
323k
}
332
333
325k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
325k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
325k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
325k
        _timeout = _params.query_options.execution_timeout;
339
325k
    }
340
341
325k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
325k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
325k
    SCOPED_TIMER(_prepare_timer);
344
325k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
325k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
325k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
325k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
325k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
325k
    {
350
325k
        SCOPED_TIMER(_init_context_timer);
351
325k
        cast_set(_num_instances, _params.local_params.size());
352
325k
        _total_instances =
353
325k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
325k
        auto* fragment_context = this;
356
357
325k
        if (_params.query_options.__isset.is_report_success) {
358
324k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
324k
        }
360
361
        // 1. Set up the global runtime state.
362
325k
        _runtime_state = RuntimeState::create_unique(
363
325k
                _params.query_id, _params.fragment_id, _params.query_options,
364
325k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
325k
        _runtime_state->set_task_execution_context(shared_from_this());
366
325k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
325k
        if (_params.__isset.backend_id) {
368
322k
            _runtime_state->set_backend_id(_params.backend_id);
369
322k
        }
370
325k
        if (_params.__isset.import_label) {
371
240
            _runtime_state->set_import_label(_params.import_label);
372
240
        }
373
325k
        if (_params.__isset.db_name) {
374
192
            _runtime_state->set_db_name(_params.db_name);
375
192
        }
376
325k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
325k
        if (_params.is_simplified_param) {
381
113k
            _desc_tbl = _query_ctx->desc_tbl;
382
211k
        } else {
383
211k
            DCHECK(_params.__isset.desc_tbl);
384
211k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
211k
                                                  &_desc_tbl));
386
211k
        }
387
325k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
325k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
325k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
325k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
325k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
325k
        const auto target_size = _params.local_params.size();
395
325k
        _fragment_instance_ids.resize(target_size);
396
1.20M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
882k
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
882k
            _fragment_instance_ids[i] = fragment_instance_id;
399
882k
        }
400
325k
    }
401
402
325k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
324k
    _init_next_report_time();
405
406
324k
    _prepared = true;
407
324k
    return Status::OK();
408
325k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
881k
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
881k
    const auto& local_params = _params.local_params[instance_idx];
414
881k
    auto fragment_instance_id = local_params.fragment_instance_id;
415
881k
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
881k
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
881k
    auto get_shared_state = [&](PipelinePtr pipeline)
418
881k
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.49M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.49M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.49M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.49M
                shared_state_map;
423
1.97M
        for (auto& op : pipeline->operators()) {
424
1.97M
            auto source_id = op->operator_id();
425
1.97M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
1.97M
                iter != _op_id_to_shared_state.end()) {
427
548k
                shared_state_map.insert({source_id, iter->second});
428
548k
            }
429
1.97M
        }
430
1.49M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.49M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.49M
                iter != _op_id_to_shared_state.end()) {
433
236k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
236k
            }
435
1.49M
        }
436
1.49M
        return shared_state_map;
437
1.49M
    };
438
439
2.68M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
1.79M
        auto& pipeline = _pipelines[pip_idx];
441
1.79M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.48M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.48M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.48M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.48M
            {
446
                // Initialize runtime state for this task
447
1.48M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.48M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.48M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.48M
                if (_params.__isset.backend_id) {
453
1.48M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.48M
                }
455
1.48M
                if (_params.__isset.import_label) {
456
241
                    task_runtime_state->set_import_label(_params.import_label);
457
241
                }
458
1.48M
                if (_params.__isset.db_name) {
459
193
                    task_runtime_state->set_db_name(_params.db_name);
460
193
                }
461
1.48M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.48M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.48M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.48M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.48M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.48M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.48M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.48M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.48M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.48M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.48M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.48M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.48M
            }
482
1.48M
            auto cur_task_id = _total_tasks++;
483
1.48M
            task_runtime_state->set_task_id(cur_task_id);
484
1.48M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.48M
            auto task = std::make_shared<PipelineTask>(
486
1.48M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.48M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.48M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.48M
                    instance_idx);
490
1.48M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.48M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.48M
            _tasks[instance_idx].emplace_back(
493
1.48M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.48M
                            std::move(task), std::move(task_runtime_state)});
495
1.48M
        }
496
1.79M
    }
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
1.79M
    for (auto& _pipeline : _pipelines) {
516
1.79M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.48M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.48M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.48M
            if (_dag.contains(_pipeline->id())) {
522
927k
                auto& deps = _dag[_pipeline->id()];
523
1.45M
                for (auto& dep : deps) {
524
1.45M
                    if (pipeline_id_to_task.contains(dep)) {
525
832k
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
832k
                        if (ss) {
527
361k
                            task->inject_shared_state(ss);
528
470k
                        } else {
529
470k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
470k
                                    task->get_source_shared_state());
531
470k
                        }
532
832k
                    }
533
1.45M
                }
534
927k
            }
535
1.48M
        }
536
1.79M
    }
537
2.67M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
1.79M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.48M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.48M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.48M
            std::vector<TScanRangeParams> scan_ranges;
542
1.48M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.48M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
255k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
255k
            }
546
1.48M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.48M
                                                             _params.fragment.output_sink));
548
1.48M
        }
549
1.79M
    }
550
880k
    {
551
880k
        std::lock_guard<std::mutex> l(_state_map_lock);
552
880k
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
880k
    }
554
880k
    return Status::OK();
555
881k
}
556
557
324k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
324k
    _total_tasks = 0;
559
324k
    _closed_tasks = 0;
560
324k
    const auto target_size = _params.local_params.size();
561
324k
    _tasks.resize(target_size);
562
324k
    _runtime_filter_mgr_map.resize(target_size);
563
829k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
505k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
505k
    }
566
324k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
324k
    if (target_size > 1 &&
569
324k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
117k
         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
13.3k
        std::vector<Status> prepare_status(target_size);
573
13.3k
        int submitted_tasks = 0;
574
13.3k
        Status submit_status;
575
13.3k
        CountDownLatch latch((int)target_size);
576
172k
        for (int i = 0; i < target_size; i++) {
577
158k
            submit_status = thread_pool->submit_func([&, i]() {
578
158k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
158k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
158k
                latch.count_down();
581
158k
            });
582
158k
            if (LIKELY(submit_status.ok())) {
583
158k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
158k
        }
588
13.3k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
13.3k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
172k
        for (int i = 0; i < submitted_tasks; i++) {
593
158k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
158k
        }
597
310k
    } else {
598
1.03M
        for (int i = 0; i < target_size; i++) {
599
723k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
723k
        }
601
310k
    }
602
324k
    _pipeline_parent_map.clear();
603
324k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
324k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
324k
    return Status::OK();
608
324k
}
609
610
323k
void PipelineFragmentContext::_init_next_report_time() {
611
323k
    auto interval_s = config::pipeline_status_report_interval;
612
323k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
31.8k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
31.8k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
31.8k
        _previous_report_time =
617
31.8k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
31.8k
        _disable_period_report = false;
619
31.8k
    }
620
323k
}
621
622
3.64k
void PipelineFragmentContext::refresh_next_report_time() {
623
3.64k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
3.64k
    DCHECK(disable == true);
625
3.64k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
3.64k
    _disable_period_report.compare_exchange_strong(disable, false);
627
3.64k
}
628
629
5.32M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
5.32M
    if (!_is_report_success) {
631
4.90M
        return;
632
4.90M
    }
633
418k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
418k
    if (disable) {
635
7.32k
        return;
636
7.32k
    }
637
411k
    int32_t interval_s = config::pipeline_status_report_interval;
638
411k
    if (interval_s <= 0) {
639
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
640
0
                        "trigger "
641
0
                        "report.";
642
0
    }
643
411k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
411k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
411k
    if (MonotonicNanos() > next_report_time) {
646
3.65k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
3.65k
                                                            std::memory_order_acq_rel)) {
648
6
            return;
649
6
        }
650
3.64k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
3.64k
        auto st = send_report(false);
667
3.64k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
3.64k
    }
673
411k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
324k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
324k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
324k
    int node_idx = 0;
682
683
324k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
324k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
324k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
687
0
        return Status::InternalError(
688
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
689
0
    }
690
324k
    return Status::OK();
691
324k
}
692
693
Status PipelineFragmentContext::_create_tree_helper(
694
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
695
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
696
519k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
519k
    if (*node_idx >= tnodes.size()) {
699
0
        return Status::InternalError(
700
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
701
0
                *node_idx, tnodes.size());
702
0
    }
703
519k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
519k
    int num_children = tnodes[*node_idx].num_children;
706
519k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
519k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
519k
    OperatorPtr op = nullptr;
710
519k
    OperatorPtr cache_op = nullptr;
711
519k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
519k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
519k
                                     followed_by_shuffled_operator,
714
519k
                                     current_require_bucket_distribution, cache_op));
715
    // Initialization must be done here. For example, group by expressions in agg will be used to
716
    // decide if a local shuffle should be planed, so it must be initialized here.
717
519k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
519k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
195k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
324k
    } else {
723
324k
        *root = op;
724
324k
    }
725
    /**
726
     * `ExchangeType::HASH_SHUFFLE` should be used if an operator is followed by a shuffled operator (shuffled hash join, union operator followed by co-located operators).
727
     *
728
     * For plan:
729
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
730
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
731
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
732
     *
733
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
734
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
735
     */
736
519k
    auto required_data_distribution =
737
519k
            cur_pipe->operators().empty()
738
519k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
519k
                    : op->required_data_distribution(_runtime_state.get());
740
519k
    current_followed_by_shuffled_operator =
741
519k
            ((followed_by_shuffled_operator ||
742
519k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
461k
                                             : op->is_shuffled_operator())) &&
744
519k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
519k
            (followed_by_shuffled_operator &&
746
410k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
519k
    current_require_bucket_distribution =
749
519k
            ((require_bucket_distribution ||
750
519k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
465k
                                             : op->is_colocated_operator())) &&
752
519k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
519k
            (require_bucket_distribution &&
754
416k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
519k
    if (num_children == 0) {
757
336k
        _use_serial_source = op->is_serial_operator();
758
336k
    }
759
    // rely on that tnodes is preorder of the plan
760
714k
    for (int i = 0; i < num_children; i++) {
761
195k
        ++*node_idx;
762
195k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
195k
                                            current_followed_by_shuffled_operator,
764
195k
                                            current_require_bucket_distribution));
765
766
        // we are expecting a child, but have used all nodes
767
        // this means we have been given a bad tree and must fail
768
195k
        if (*node_idx >= tnodes.size()) {
769
0
            return Status::InternalError(
770
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
771
0
                    "nodes: {}",
772
0
                    *node_idx, tnodes.size());
773
0
        }
774
195k
    }
775
776
519k
    return Status::OK();
777
519k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
91.0k
        PipelinePtr pipe_with_sink) {
782
91.0k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
91.0k
    pipe_with_source->set_num_tasks(_num_instances);
784
91.0k
    pipe_with_source->set_data_distribution(data_distribution);
785
91.0k
}
786
787
Status PipelineFragmentContext::_add_local_exchange_impl(
788
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
789
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
790
        const std::map<int, int>& bucket_seq_to_instance_idx,
791
91.0k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
91.0k
    auto& operators = cur_pipe->operators();
793
91.0k
    const auto downstream_pipeline_id = cur_pipe->id();
794
91.0k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
91.0k
    DataSinkOperatorPtr sink;
797
91.0k
    auto sink_id = next_sink_operator_id();
798
799
    /**
800
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
801
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
802
     */
803
91.0k
    const bool followed_by_shuffled_operator =
804
91.0k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
91.0k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
91.0k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
91.0k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
91.0k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
91.0k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
91.0k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
91.0k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
91.0k
    if (bucket_seq_to_instance_idx.empty() &&
813
91.0k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
8
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
8
    }
816
91.0k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
91.0k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
91.0k
                                          num_buckets, use_global_hash_shuffle,
819
91.0k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
91.0k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
91.0k
            LocalExchangeSharedState::create_shared(_num_instances);
824
91.0k
    switch (data_distribution.distribution_type) {
825
12.5k
    case ExchangeType::HASH_SHUFFLE:
826
12.5k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
12.5k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
12.5k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
12.5k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
12.5k
                        ? cast_set<int>(
831
12.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
12.5k
                        : 0);
833
12.5k
        break;
834
488
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
488
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
488
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
488
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
488
                        ? cast_set<int>(
839
488
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
488
                        : 0);
841
488
        break;
842
75.0k
    case ExchangeType::PASSTHROUGH:
843
75.0k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
75.0k
                cur_pipe->num_tasks(), _num_instances,
845
75.0k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
75.0k
                        ? cast_set<int>(
847
75.0k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
75.0k
                        : 0);
849
75.0k
        break;
850
307
    case ExchangeType::BROADCAST:
851
307
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
307
                cur_pipe->num_tasks(), _num_instances,
853
307
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
307
                        ? cast_set<int>(
855
307
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
307
                        : 0);
857
307
        break;
858
1.82k
    case ExchangeType::PASS_TO_ONE:
859
1.82k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
860
            // If shared hash table is enabled for BJ, hash table will be built by only one task
861
823
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
823
                    cur_pipe->num_tasks(), _num_instances,
863
823
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
823
                            ? cast_set<int>(_runtime_state->query_options()
865
823
                                                    .local_exchange_free_blocks_limit)
866
823
                            : 0);
867
997
        } else {
868
997
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
997
                    cur_pipe->num_tasks(), _num_instances,
870
997
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
997
                            ? cast_set<int>(_runtime_state->query_options()
872
997
                                                    .local_exchange_free_blocks_limit)
873
997
                            : 0);
874
997
        }
875
1.82k
        break;
876
829
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
829
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
829
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
829
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
829
                        ? cast_set<int>(
881
829
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
829
                        : 0);
883
829
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
91.0k
    }
888
91.0k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
91.0k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
91.0k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
91.0k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
892
893
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
894
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
895
896
    // 3.1 Initialize new pipeline's operator list.
897
91.0k
    std::copy(operators.begin(), operators.begin() + idx,
898
91.0k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
91.0k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
91.0k
    OperatorPtr source_op;
905
91.0k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
91.0k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
91.0k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
91.0k
    if (!operators.empty()) {
909
41.3k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
41.3k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
41.3k
    }
912
91.0k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
91.0k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
91.0k
    std::vector<PipelineId> edges_with_source;
917
107k
    for (auto child : cur_pipe->children()) {
918
107k
        bool found = false;
919
120k
        for (auto op : new_pip->operators()) {
920
120k
            if (child->sink()->node_id() == op->node_id()) {
921
11.5k
                new_pip->set_children(child);
922
11.5k
                found = true;
923
11.5k
            };
924
120k
        }
925
107k
        if (!found) {
926
95.6k
            new_children.push_back(child);
927
95.6k
            edges_with_source.push_back(child->id());
928
95.6k
        }
929
107k
    }
930
91.0k
    new_children.push_back(new_pip);
931
91.0k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
91.0k
    if (!new_pip->children().empty()) {
935
6.61k
        std::vector<PipelineId> edges_with_sink;
936
11.5k
        for (auto child : new_pip->children()) {
937
11.5k
            edges_with_sink.push_back(child->id());
938
11.5k
        }
939
6.61k
        _dag.insert({new_pip->id(), edges_with_sink});
940
6.61k
    }
941
91.0k
    cur_pipe->set_children(new_children);
942
91.0k
    _dag[downstream_pipeline_id] = edges_with_source;
943
91.0k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
91.0k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
91.0k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
91.0k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
91.0k
    return Status::OK();
950
91.0k
}
951
952
Status PipelineFragmentContext::_add_local_exchange(
953
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
954
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
955
        const std::map<int, int>& bucket_seq_to_instance_idx,
956
153k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
153k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
29.5k
        return Status::OK();
959
29.5k
    }
960
961
124k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
46.1k
        return Status::OK();
963
46.1k
    }
964
78.1k
    *do_local_exchange = true;
965
966
78.1k
    auto& operators = cur_pipe->operators();
967
78.1k
    auto total_op_num = operators.size();
968
78.1k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
78.1k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
78.1k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
78.1k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
18.4E
            << "total_op_num: " << total_op_num
975
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
78.1k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
78.1k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
12.8k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
12.8k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
12.8k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
12.8k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
12.8k
                shuffle_idx_to_instance_idx));
990
12.8k
    }
991
78.1k
    return Status::OK();
992
78.1k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
322k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
735k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
413k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
413k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
88.8k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
88.8k
                if (child->sink()->node_id() ==
1003
88.8k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
78.0k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
78.0k
                }
1006
88.8k
            }
1007
85.2k
        }
1008
1009
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1010
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1011
        // still keep colocate plan after local shuffle
1012
413k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
413k
                                             bucket_seq_to_instance_idx,
1014
413k
                                             shuffle_idx_to_instance_idx));
1015
413k
    }
1016
322k
    return Status::OK();
1017
322k
}
1018
1019
Status PipelineFragmentContext::_plan_local_exchange(
1020
        int num_buckets, int pip_idx, PipelinePtr pip,
1021
        const std::map<int, int>& bucket_seq_to_instance_idx,
1022
412k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
412k
    int idx = 1;
1024
412k
    bool do_local_exchange = false;
1025
454k
    do {
1026
454k
        auto& ops = pip->operators();
1027
454k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
519k
        for (; idx < ops.size();) {
1030
106k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
94.8k
                RETURN_IF_ERROR(_add_local_exchange(
1032
94.8k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
94.8k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
94.8k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
94.8k
                        shuffle_idx_to_instance_idx));
1036
94.8k
            }
1037
106k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
41.4k
                idx = 2;
1043
41.4k
                break;
1044
41.4k
            }
1045
65.1k
            idx++;
1046
65.1k
        }
1047
454k
    } while (do_local_exchange);
1048
412k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
58.8k
        RETURN_IF_ERROR(_add_local_exchange(
1050
58.8k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
58.8k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
58.8k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
58.8k
    }
1054
412k
    return Status::OK();
1055
412k
}
1056
1057
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1058
                                                  const std::vector<TExpr>& output_exprs,
1059
                                                  const TPipelineFragmentParams& params,
1060
                                                  const RowDescriptor& row_desc,
1061
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1062
324k
                                                  PipelineId cur_pipeline_id) {
1063
324k
    switch (thrift_sink.type) {
1064
113k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
113k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
113k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
113k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
113k
                params.destinations, _fragment_instance_ids);
1071
113k
        break;
1072
113k
    }
1073
181k
    case TDataSinkType::RESULT_SINK: {
1074
181k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
181k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
181k
        int child_node_id = pipeline->operators().back()->node_id();
1080
181k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
181k
                                                      row_desc, output_exprs,
1082
181k
                                                      thrift_sink.result_sink);
1083
181k
        break;
1084
181k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
28.8k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
28.8k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
28.8k
        int child_node_id = pipeline->operators().back()->node_id();
1098
28.8k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
28.8k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
28.8k
            !config::is_cloud_mode()) {
1101
36
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
36
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
28.8k
        } else {
1104
28.8k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
28.8k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
28.8k
        }
1107
28.8k
        break;
1108
0
    }
1109
166
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
166
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
166
        DCHECK(state->get_query_ctx() != nullptr);
1112
166
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
166
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
166
                                                                output_exprs);
1115
166
        break;
1116
0
    }
1117
0
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
0
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
0
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
0
                                                         output_exprs);
1123
0
        break;
1124
0
    }
1125
0
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
0
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
0
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
0
        } else {
1133
0
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
0
                                                                row_desc, output_exprs);
1135
0
        }
1136
0
        break;
1137
0
    }
1138
0
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
0
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
0
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
0
                                                             row_desc, output_exprs);
1144
0
        break;
1145
0
    }
1146
0
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
0
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
0
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
0
                                                            output_exprs);
1152
0
        break;
1153
0
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
0
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
0
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
0
        if (config::enable_java_support) {
1167
0
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
0
                                                             output_exprs);
1169
0
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
0
        break;
1175
0
    }
1176
3
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
338
    case TDataSinkType::RESULT_FILE_SINK: {
1186
338
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
338
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
338
        } else {
1196
338
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
338
                                                              output_exprs);
1198
338
        }
1199
338
        break;
1200
338
    }
1201
569
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
569
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
569
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
569
        auto sink_id = next_sink_operator_id();
1205
569
        const int multi_cast_node_id = sink_id;
1206
569
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
569
        std::vector<int> sources;
1209
2.05k
        for (int i = 0; i < sender_size; ++i) {
1210
1.48k
            auto source_id = next_operator_id();
1211
1.48k
            sources.push_back(source_id);
1212
1.48k
        }
1213
1214
569
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
569
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
2.05k
        for (int i = 0; i < sender_size; ++i) {
1217
1.48k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
1.48k
            RowDescriptor* exchange_row_desc = nullptr;
1220
1.48k
            {
1221
1.48k
                const auto& tmp_row_desc =
1222
1.48k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
1.48k
                                ? RowDescriptor(state->desc_tbl(),
1224
1.48k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
1.48k
                                                         .output_tuple_id})
1226
1.48k
                                : row_desc;
1227
1.48k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
1.48k
            }
1229
1.48k
            auto source_id = sources[i];
1230
1.48k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
1.48k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
1.48k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
1.48k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
1.48k
                    /*operator_id=*/source_id);
1236
1.48k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
1.48k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1238
            // 2. create and set sink operator of data stream sender for new pipeline
1239
1240
1.48k
            DataSinkOperatorPtr sink_op;
1241
1.48k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
1.48k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
1.48k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
1.48k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
1.48k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
1.48k
            {
1248
1.48k
                TDataSink* t = pool->add(new TDataSink());
1249
1.48k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
1.48k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
1.48k
            }
1252
1253
            // 3. set dependency dag
1254
1.48k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
1.48k
        }
1256
569
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
569
        break;
1260
569
    }
1261
569
    case TDataSinkType::BLACKHOLE_SINK: {
1262
3
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
3
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
3
        break;
1268
3
    }
1269
0
    case TDataSinkType::TVF_TABLE_SINK: {
1270
0
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
0
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
0
                                                        output_exprs);
1275
0
        break;
1276
0
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
324k
    }
1280
324k
    return Status::OK();
1281
324k
}
1282
1283
// NOLINTBEGIN(readability-function-size)
1284
// NOLINTBEGIN(readability-function-cognitive-complexity)
1285
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1286
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1287
                                                 PipelinePtr& cur_pipe, int parent_idx,
1288
                                                 int child_idx,
1289
                                                 const bool followed_by_shuffled_operator,
1290
                                                 const bool require_bucket_distribution,
1291
520k
                                                 OperatorPtr& cache_op) {
1292
520k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
520k
    Defer defer = Defer([&]() {
1294
520k
        if (op) {
1295
520k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
520k
        }
1297
519k
        for (auto& s : sink_ops) {
1298
88.5k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
88.5k
        }
1300
519k
    });
1301
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1302
    // Therefore, here we need to use a stack-like structure.
1303
520k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
520k
    std::stringstream error_msg;
1305
520k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
520k
    bool fe_with_old_version = false;
1308
520k
    switch (tnode.node_type) {
1309
162k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
162k
        op = std::make_shared<OlapScanOperatorX>(
1311
162k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
162k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
162k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
162k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
162k
        break;
1316
162k
    }
1317
79
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
79
        DCHECK(_query_ctx != nullptr);
1319
79
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
79
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
79
                                                    _num_instances);
1322
79
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
79
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
79
        break;
1325
79
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
2.66k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
2.66k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
2.66k
                                                 _num_instances);
1342
2.66k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
2.66k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
2.66k
        break;
1345
2.66k
    }
1346
112k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
112k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
112k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
112k
        DCHECK_GT(num_senders, 0);
1351
112k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
112k
                                                       num_senders);
1353
112k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
112k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
112k
        break;
1356
112k
    }
1357
135k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
135k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
135k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1360
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1361
0
                                         ": group by and output is empty");
1362
0
        }
1363
135k
        bool need_create_cache_op =
1364
135k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
135k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1366
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1367
10
            auto cache_source_id = next_operator_id();
1368
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1369
10
                                                        _params.fragment.query_cache_param);
1370
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1371
1372
10
            const auto downstream_pipeline_id = cur_pipe->id();
1373
10
            if (!_dag.contains(downstream_pipeline_id)) {
1374
10
                _dag.insert({downstream_pipeline_id, {}});
1375
10
            }
1376
10
            new_pipe = add_pipeline(cur_pipe);
1377
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1378
1379
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1380
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1381
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1382
10
            return Status::OK();
1383
10
        };
1384
135k
        const bool group_by_limit_opt =
1385
135k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1386
1387
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1388
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1389
135k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
135k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
135k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
135k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
135k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
135k
        const bool can_use_distinct_streaming_agg =
1396
135k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
135k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
135k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
135k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
135k
        if (can_use_distinct_streaming_agg) {
1402
92.4k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
92.4k
            } else {
1413
92.4k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
92.4k
                                                                     tnode, descs);
1415
92.4k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
92.4k
            }
1417
92.4k
        } else if (is_streaming_agg) {
1418
1.12k
            if (need_create_cache_op) {
1419
0
                PipelinePtr new_pipe;
1420
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1421
0
                cache_op = op;
1422
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
0
                                                             descs);
1424
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1425
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1426
0
                cur_pipe = new_pipe;
1427
1.12k
            } else {
1428
1.12k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.12k
                                                             descs);
1430
1.12k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.12k
            }
1432
42.2k
        } else {
1433
            // create new pipeline to add query cache operator
1434
42.2k
            PipelinePtr new_pipe;
1435
42.2k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
42.2k
            if (enable_spill) {
1441
91
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
91
                                                                     next_operator_id(), descs);
1443
42.1k
            } else {
1444
42.1k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
42.1k
            }
1446
42.2k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
42.2k
            } else {
1451
42.2k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
42.2k
            }
1453
1454
42.2k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
42.2k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
41.7k
                _dag.insert({downstream_pipeline_id, {}});
1457
41.7k
            }
1458
42.2k
            cur_pipe = add_pipeline(cur_pipe);
1459
42.2k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
42.2k
            if (enable_spill) {
1462
91
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
91
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
42.1k
            } else {
1465
42.1k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
42.1k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
42.1k
            }
1468
42.2k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
42.2k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
42.2k
        }
1471
135k
        break;
1472
135k
    }
1473
135k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
80
        if (tnode.bucketed_agg_node.grouping_exprs.empty()) {
1475
0
            return Status::InternalError(
1476
0
                    "Bucketed aggregation node {} should not be used without group by keys",
1477
0
                    tnode.node_id);
1478
0
        }
1479
1480
        // Create source operator (goes on the current / downstream pipeline).
1481
80
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
80
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
80
        const auto downstream_pipeline_id = cur_pipe->id();
1486
80
        if (!_dag.contains(downstream_pipeline_id)) {
1487
80
            _dag.insert({downstream_pipeline_id, {}});
1488
80
        }
1489
80
        cur_pipe = add_pipeline(cur_pipe);
1490
80
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
80
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
80
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
80
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
80
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1497
1498
        // Pre-register a single shared state for ALL instances so that every
1499
        // sink instance writes its per-instance hash table into the same
1500
        // BucketedAggSharedState and every source instance can merge across
1501
        // all of them.
1502
80
        {
1503
80
            auto shared_state = BucketedAggSharedState::create_shared();
1504
80
            shared_state->id = op->operator_id();
1505
80
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
552
            for (int i = 0; i < _num_instances; i++) {
1508
472
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
472
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
472
                sink_dep->set_shared_state(shared_state.get());
1511
472
                shared_state->sink_deps.push_back(sink_dep);
1512
472
            }
1513
80
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
80
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
80
            _op_id_to_shared_state.insert(
1516
80
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
80
        }
1518
80
        break;
1519
80
    }
1520
8.79k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
8.79k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
8.79k
                                       tnode.hash_join_node.is_broadcast_join;
1523
8.79k
        const auto enable_spill = _runtime_state->enable_spill();
1524
8.79k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
8.79k
        } else {
1566
8.79k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
8.79k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
8.79k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
8.79k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.09k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.09k
            }
1573
8.79k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
8.79k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
8.79k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
8.79k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
8.79k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
8.79k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
8.79k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
8.79k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
8.79k
        }
1584
8.79k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
3.95k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
3.95k
                    HashJoinSharedState::create_shared(_num_instances);
1587
16.5k
            for (int i = 0; i < _num_instances; i++) {
1588
12.5k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
12.5k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
12.5k
                sink_dep->set_shared_state(shared_state.get());
1591
12.5k
                shared_state->sink_deps.push_back(sink_dep);
1592
12.5k
            }
1593
3.95k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
3.95k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
3.95k
            _op_id_to_shared_state.insert(
1596
3.95k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
3.95k
        }
1598
8.79k
        break;
1599
8.79k
    }
1600
2.00k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
2.00k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
2.00k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
2.00k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
2.00k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
1.77k
            _dag.insert({downstream_pipeline_id, {}});
1607
1.77k
        }
1608
2.00k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
2.00k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
2.00k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
2.00k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
2.00k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
2.00k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
2.00k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
2.00k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
2.00k
        break;
1618
2.00k
    }
1619
49.6k
    case TPlanNodeType::UNION_NODE: {
1620
49.6k
        int child_count = tnode.num_children;
1621
49.6k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
49.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
49.6k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
49.6k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
49.4k
            _dag.insert({downstream_pipeline_id, {}});
1627
49.4k
        }
1628
50.6k
        for (int i = 0; i < child_count; i++) {
1629
1.01k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.01k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.01k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.01k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.01k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.01k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.01k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.01k
        }
1638
49.6k
        break;
1639
49.6k
    }
1640
49.6k
    case TPlanNodeType::SORT_NODE: {
1641
32.1k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
32.1k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
32.1k
        const bool use_local_merge =
1644
32.1k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
32.1k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
32.1k
        } else if (use_local_merge) {
1648
30.2k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
30.2k
                                                                 descs);
1650
30.2k
        } else {
1651
1.86k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
1.86k
        }
1653
32.1k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
32.1k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
32.1k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
32.1k
            _dag.insert({downstream_pipeline_id, {}});
1658
32.1k
        }
1659
32.1k
        cur_pipe = add_pipeline(cur_pipe);
1660
32.1k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
32.1k
        if (should_spill) {
1663
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
32.1k
        } else {
1666
32.1k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
32.1k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
32.1k
        }
1669
32.1k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
32.1k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
32.1k
        break;
1672
32.1k
    }
1673
32.1k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.60k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.60k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.60k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.60k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.59k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.59k
        }
1698
1.60k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.60k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.60k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.60k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.60k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.60k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.60k
        break;
1706
1.60k
    }
1707
1.60k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
672
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
672
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
672
        break;
1711
672
    }
1712
672
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
296
    case TPlanNodeType::REPEAT_NODE: {
1723
296
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
296
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
296
        break;
1726
296
    }
1727
909
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
909
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
909
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
909
        break;
1731
909
    }
1732
909
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
18
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
18
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
18
        break;
1736
18
    }
1737
1.47k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.47k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.47k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.47k
        break;
1741
1.47k
    }
1742
1.47k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
265
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
265
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
265
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
265
        break;
1747
265
    }
1748
1.53k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.53k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.53k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.53k
        break;
1752
1.53k
    }
1753
4.51k
    case TPlanNodeType::META_SCAN_NODE: {
1754
4.51k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
4.51k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
4.51k
        break;
1757
4.51k
    }
1758
4.51k
    case TPlanNodeType::SELECT_NODE: {
1759
551
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
551
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
551
        break;
1762
551
    }
1763
551
    case TPlanNodeType::REC_CTE_NODE: {
1764
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
151
        const auto downstream_pipeline_id = cur_pipe->id();
1768
151
        if (!_dag.contains(downstream_pipeline_id)) {
1769
148
            _dag.insert({downstream_pipeline_id, {}});
1770
148
        }
1771
1772
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
151
        DataSinkOperatorPtr anchor_sink;
1776
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
151
                                                                  op->operator_id(), tnode, descs);
1778
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
151
        DataSinkOperatorPtr rec_sink;
1786
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
151
                                                         tnode, descs);
1788
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
151
        break;
1793
151
    }
1794
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.95k
        break;
1798
1.95k
    }
1799
1.95k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
520k
    }
1803
519k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1804
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1805
0
        op->set_serial_operator();
1806
0
    }
1807
1808
519k
    return Status::OK();
1809
520k
}
1810
// NOLINTEND(readability-function-cognitive-complexity)
1811
// NOLINTEND(readability-function-size)
1812
1813
template <bool is_intersect>
1814
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1815
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1816
267
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
267
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
267
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
267
    const auto downstream_pipeline_id = cur_pipe->id();
1821
267
    if (!_dag.contains(downstream_pipeline_id)) {
1822
242
        _dag.insert({downstream_pipeline_id, {}});
1823
242
    }
1824
1825
895
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
628
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
628
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
628
        if (child_id == 0) {
1830
267
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
267
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
361
        } else {
1833
361
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
361
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
361
        }
1836
628
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
628
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
628
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
628
    }
1841
1842
267
    return Status::OK();
1843
267
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
134
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
134
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
134
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
134
    const auto downstream_pipeline_id = cur_pipe->id();
1821
134
    if (!_dag.contains(downstream_pipeline_id)) {
1822
118
        _dag.insert({downstream_pipeline_id, {}});
1823
118
    }
1824
1825
481
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
347
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
347
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
347
        if (child_id == 0) {
1830
134
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
134
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
213
        } else {
1833
213
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
213
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
213
        }
1836
347
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
347
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
347
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
347
    }
1841
1842
134
    return Status::OK();
1843
134
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
133
    const auto downstream_pipeline_id = cur_pipe->id();
1821
133
    if (!_dag.contains(downstream_pipeline_id)) {
1822
124
        _dag.insert({downstream_pipeline_id, {}});
1823
124
    }
1824
1825
414
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
281
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
281
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
281
        if (child_id == 0) {
1830
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
148
        } else {
1833
148
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
148
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
148
        }
1836
281
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
281
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
281
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
281
    }
1841
1842
133
    return Status::OK();
1843
133
}
1844
1845
323k
Status PipelineFragmentContext::submit() {
1846
323k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
323k
    _submitted = true;
1850
1851
323k
    int submit_tasks = 0;
1852
323k
    Status st;
1853
323k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
882k
    for (auto& task : _tasks) {
1855
1.49M
        for (auto& t : task) {
1856
1.49M
            st = scheduler->submit(t.first);
1857
1.49M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.49M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.49M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
1.49M
            submit_tasks++;
1866
1.49M
        }
1867
882k
    }
1868
323k
    if (!st.ok()) {
1869
0
        bool need_remove = false;
1870
0
        {
1871
0
            std::lock_guard<std::mutex> l(_task_mutex);
1872
0
            if (_closed_tasks >= _total_tasks) {
1873
0
                need_remove = _close_fragment_instance();
1874
0
            }
1875
0
        }
1876
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1877
0
        if (need_remove) {
1878
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1879
0
        }
1880
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1881
0
                                     BackendOptions::get_localhost());
1882
323k
    } else {
1883
323k
        return st;
1884
323k
    }
1885
323k
}
1886
1887
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1888
0
    if (_runtime_state->enable_profile()) {
1889
0
        std::stringstream ss;
1890
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1891
0
            runtime_profile_ptr->pretty_print(&ss);
1892
0
        }
1893
1894
0
        if (_runtime_state->load_channel_profile()) {
1895
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1896
0
        }
1897
1898
0
        auto profile_str =
1899
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1900
0
                            this->_fragment_id, extra_info, ss.str());
1901
0
        LOG_LONG_STRING(INFO, profile_str);
1902
0
    }
1903
0
}
1904
// If all pipeline tasks binded to the fragment instance are finished, then we could
1905
// close the fragment instance.
1906
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1907
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1908
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1909
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1910
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1911
// (via debug_string()).
1912
324k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
324k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
324k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
324k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
324k
    if (!_need_notify_close) {
1919
320k
        auto st = send_report(true);
1920
320k
        if (!st) {
1921
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1922
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1923
0
        }
1924
320k
    }
1925
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1926
    // Since stream load does not have someting like coordinator on FE, so
1927
    // backend can not report profile to FE, ant its profile can not be shown
1928
    // in the same way with other query. So we print the profile content to info log.
1929
1930
324k
    if (_runtime_state->enable_profile() &&
1931
324k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.40k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.40k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1934
0
        std::stringstream ss;
1935
        // Compute the _local_time_percent before pretty_print the runtime_profile
1936
        // Before add this operation, the print out like that:
1937
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1938
        // After add the operation, the print out like that:
1939
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1940
        // We can easily know the exec node execute time without child time consumed.
1941
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1942
0
            runtime_profile_ptr->pretty_print(&ss);
1943
0
        }
1944
1945
0
        if (_runtime_state->load_channel_profile()) {
1946
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1947
0
        }
1948
1949
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1950
0
    }
1951
1952
324k
    if (_query_ctx->enable_profile()) {
1953
2.40k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.40k
                                         collect_realtime_load_channel_profile());
1955
2.40k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
324k
    return !_need_notify_close;
1960
324k
}
1961
1962
1.48M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
1.48M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.48M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
505k
        if (_dag.contains(pipeline_id)) {
1967
272k
            for (auto dep : _dag[pipeline_id]) {
1968
272k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
272k
            }
1970
222k
        }
1971
505k
    }
1972
1.48M
    bool need_remove = false;
1973
1.48M
    {
1974
1.48M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.48M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.48M
        _query_ctx->inc_finished_task_num();
1978
1.48M
        if (_closed_tasks >= _total_tasks) {
1979
324k
            need_remove = _close_fragment_instance();
1980
324k
        }
1981
1.48M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.48M
    if (need_remove) {
1984
320k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
320k
    }
1986
1.48M
}
1987
1988
41.4k
std::string PipelineFragmentContext::get_load_error_url() {
1989
41.4k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1990
0
        return to_load_error_http_path(str);
1991
0
    }
1992
102k
    for (auto& tasks : _tasks) {
1993
169k
        for (auto& task : tasks) {
1994
169k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
163
                return to_load_error_http_path(str);
1996
163
            }
1997
169k
        }
1998
102k
    }
1999
41.3k
    return "";
2000
41.4k
}
2001
2002
41.4k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
41.4k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
102k
    for (auto& tasks : _tasks) {
2007
169k
        for (auto& task : tasks) {
2008
169k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
163
                return str;
2010
163
            }
2011
169k
        }
2012
102k
    }
2013
41.3k
    return "";
2014
41.4k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
36.8k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
36.8k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
36.8k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
36.8k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
36.8k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
36.8k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
36.8k
    });
2031
2032
36.8k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
36.8k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
36.8k
    int callback_retries = 10;
2038
36.8k
    const int sleep_ms = 1000;
2039
36.8k
    Status exec_status = req.status;
2040
36.8k
    Status coord_status;
2041
36.8k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
36.8k
    do {
2043
36.8k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
36.8k
                                                            req.coord_addr, &coord_status);
2045
36.8k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
36.8k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
36.8k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
36.8k
    TReportExecStatusParams params;
2059
36.8k
    params.protocol_version = FrontendServiceVersion::V1;
2060
36.8k
    params.__set_query_id(req.query_id);
2061
36.8k
    params.__set_backend_num(req.backend_num);
2062
36.8k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
36.8k
    params.__set_fragment_id(req.fragment_id);
2064
36.8k
    params.__set_status(exec_status.to_thrift());
2065
36.8k
    params.__set_done(req.done);
2066
36.8k
    params.__set_query_type(req.runtime_state->query_type());
2067
36.8k
    params.__isset.profile = false;
2068
2069
36.8k
    DCHECK(req.runtime_state != nullptr);
2070
2071
36.8k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
32.8k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
32.8k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
32.8k
    } else {
2075
4.03k
        DCHECK(!req.runtime_states.empty());
2076
4.03k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
4.03k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.03k
    }
2086
2087
36.8k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
36.8k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
36.8k
    static std::string s_unselected_rows = "unselected.rows";
2090
36.8k
    int64_t num_rows_load_success = 0;
2091
36.8k
    int64_t num_rows_load_filtered = 0;
2092
36.8k
    int64_t num_rows_load_unselected = 0;
2093
36.8k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
36.8k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
36.8k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
36.8k
    } else if (!req.runtime_states.empty()) {
2109
140k
        for (auto* rs : req.runtime_states) {
2110
140k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
140k
                rs->num_finished_range() > 0) {
2112
31.1k
                params.__isset.load_counters = true;
2113
31.1k
                num_rows_load_success += rs->num_rows_load_success();
2114
31.1k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
31.1k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
31.1k
                params.__isset.fragment_instance_reports = true;
2117
31.1k
                TFragmentInstanceReport t;
2118
31.1k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
31.1k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
31.1k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
31.1k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
31.1k
                params.fragment_instance_reports.push_back(t);
2123
31.1k
            }
2124
140k
        }
2125
36.8k
    }
2126
36.8k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
36.8k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
36.8k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
36.8k
    if (!req.load_error_url.empty()) {
2131
147
        params.__set_tracking_url(req.load_error_url);
2132
147
    }
2133
36.8k
    if (!req.first_error_msg.empty()) {
2134
147
        params.__set_first_error_msg(req.first_error_msg);
2135
147
    }
2136
140k
    for (auto* rs : req.runtime_states) {
2137
140k
        if (rs->wal_id() > 0) {
2138
106
            params.__set_txn_id(rs->wal_id());
2139
106
            params.__set_label(rs->import_label());
2140
106
        }
2141
140k
    }
2142
36.8k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
36.8k
    } else if (!req.runtime_states.empty()) {
2146
140k
        for (auto* rs : req.runtime_states) {
2147
140k
            if (!rs->export_output_files().empty()) {
2148
0
                params.__isset.export_files = true;
2149
0
                params.export_files.insert(params.export_files.end(),
2150
0
                                           rs->export_output_files().begin(),
2151
0
                                           rs->export_output_files().end());
2152
0
            }
2153
140k
        }
2154
36.8k
    }
2155
36.8k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
36.8k
    } else if (!req.runtime_states.empty()) {
2159
140k
        for (auto* rs : req.runtime_states) {
2160
140k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
24.9k
                params.__isset.commitInfos = true;
2162
24.9k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
24.9k
            }
2164
140k
        }
2165
36.8k
    }
2166
36.8k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
36.8k
    } else if (!req.runtime_states.empty()) {
2170
140k
        for (auto* rs : req.runtime_states) {
2171
140k
            if (auto rs_eti = rs->error_tablet_infos(); !rs_eti.empty()) {
2172
0
                params.__isset.errorTabletInfos = true;
2173
0
                params.errorTabletInfos.insert(params.errorTabletInfos.end(), rs_eti.begin(),
2174
0
                                               rs_eti.end());
2175
0
            }
2176
140k
        }
2177
36.8k
    }
2178
36.8k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
36.8k
    } else if (!req.runtime_states.empty()) {
2183
140k
        for (auto* rs : req.runtime_states) {
2184
140k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
0
                params.__isset.hive_partition_updates = true;
2186
0
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
0
                                                     rs_hpu.begin(), rs_hpu.end());
2188
0
            }
2189
140k
        }
2190
36.8k
    }
2191
36.8k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
36.8k
    } else if (!req.runtime_states.empty()) {
2196
140k
        for (auto* rs : req.runtime_states) {
2197
140k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
0
                params.__isset.iceberg_commit_datas = true;
2199
0
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
0
                                                   rs_icd.begin(), rs_icd.end());
2201
0
            }
2202
140k
        }
2203
36.8k
    }
2204
2205
36.8k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
36.8k
    } else if (!req.runtime_states.empty()) {
2209
140k
        for (auto* rs : req.runtime_states) {
2210
140k
            if (auto rs_mcd = rs->mc_commit_datas(); !rs_mcd.empty()) {
2211
0
                params.__isset.mc_commit_datas = true;
2212
0
                params.mc_commit_datas.insert(params.mc_commit_datas.end(), rs_mcd.begin(),
2213
0
                                              rs_mcd.end());
2214
0
            }
2215
140k
        }
2216
36.8k
    }
2217
2218
36.8k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
36.8k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
36.8k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
36.8k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
36.8k
    }
2224
2225
36.8k
    TReportExecStatusResult res;
2226
36.8k
    Status rpc_status;
2227
2228
36.8k
    VLOG_DEBUG << "reportExecStatus params is "
2229
9
               << apache::thrift::ThriftDebugString(params).c_str();
2230
36.8k
    if (!exec_status.ok()) {
2231
1.52k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.52k
                     << " to coordinator: " << req.coord_addr
2233
1.52k
                     << ", query id: " << print_id(req.query_id);
2234
1.52k
    }
2235
36.8k
    try {
2236
36.8k
        try {
2237
36.8k
            (*coord)->reportExecStatus(res, params);
2238
36.8k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
36.8k
        rpc_status = Status::create<false>(res.status);
2254
36.8k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
36.8k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
36.8k
}
2265
2266
324k
Status PipelineFragmentContext::send_report(bool done) {
2267
324k
    Status exec_status = _query_ctx->exec_status();
2268
    // If plan is done successfully, but _is_report_success is false,
2269
    // no need to send report.
2270
    // Load will set _is_report_success to true because load wants to know
2271
    // the process.
2272
324k
    if (!_is_report_success && done && exec_status.ok()) {
2273
287k
        return Status::OK();
2274
287k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
37.0k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
131
        if (done) {
2284
            // if done is true, which means the query is finished successfully, we can safely close the fragment instance without sending report to FE, and just return OK status here.
2285
131
            return Status::OK();
2286
131
        }
2287
0
        return Status::NeedSendAgain("");
2288
131
    }
2289
2290
36.8k
    std::vector<RuntimeState*> runtime_states;
2291
2292
88.2k
    for (auto& tasks : _tasks) {
2293
140k
        for (auto& task : tasks) {
2294
140k
            runtime_states.push_back(task.second.get());
2295
140k
        }
2296
88.2k
    }
2297
2298
36.8k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
36.8k
                                        ? get_load_error_url()
2300
36.8k
                                        : _query_ctx->get_load_error_url();
2301
36.8k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
36.8k
                                          ? get_first_error_msg()
2303
36.8k
                                          : _query_ctx->get_first_error_msg();
2304
2305
36.8k
    ReportStatusRequest req {.status = exec_status,
2306
36.8k
                             .runtime_states = runtime_states,
2307
36.8k
                             .done = done || !exec_status.ok(),
2308
36.8k
                             .coord_addr = _query_ctx->coord_addr,
2309
36.8k
                             .query_id = _query_id,
2310
36.8k
                             .fragment_id = _fragment_id,
2311
36.8k
                             .fragment_instance_id = TUniqueId(),
2312
36.8k
                             .backend_num = -1,
2313
36.8k
                             .runtime_state = _runtime_state.get(),
2314
36.8k
                             .load_error_url = load_eror_url,
2315
36.8k
                             .first_error_msg = first_error_msg,
2316
36.8k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
36.8k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
36.8k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
36.8k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
36.8k
        _coordinator_callback(req);
2321
36.8k
        if (!req.done) {
2322
3.64k
            ctx->refresh_next_report_time();
2323
3.64k
        }
2324
36.8k
    });
2325
37.0k
}
2326
2327
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
0
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
0
    for (const auto& task_instances : _tasks) {
2332
0
        for (const auto& task : task_instances) {
2333
0
            if (task.first->is_running()) {
2334
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2335
0
                                      << " is running, task: " << (void*)task.first.get()
2336
0
                                      << ", is_running: " << task.first->is_running();
2337
0
                *has_running_task = true;
2338
0
                return 0;
2339
0
            }
2340
2341
0
            size_t revocable_size = task.first->get_revocable_size();
2342
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
0
                res += revocable_size;
2344
0
            }
2345
0
        }
2346
0
    }
2347
0
    return res;
2348
0
}
2349
2350
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
0
    std::vector<PipelineTask*> revocable_tasks;
2352
0
    for (const auto& task_instances : _tasks) {
2353
0
        for (const auto& task : task_instances) {
2354
0
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
0
                revocable_tasks.emplace_back(task.first.get());
2358
0
            }
2359
0
        }
2360
0
    }
2361
0
    return revocable_tasks;
2362
0
}
2363
2364
238
std::string PipelineFragmentContext::debug_string() {
2365
238
    std::lock_guard<std::mutex> l(_task_mutex);
2366
238
    fmt::memory_buffer debug_string_buffer;
2367
238
    fmt::format_to(debug_string_buffer,
2368
238
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
238
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
238
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
990
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
752
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
1.98k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
1.23k
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
1.23k
                           _tasks[j][i].first->debug_string());
2376
1.23k
        }
2377
752
    }
2378
2379
238
    return fmt::to_string(debug_string_buffer);
2380
238
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.40k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.40k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2385
2386
    // we do not have mutex to protect pipeline_id_to_profile
2387
    // so we need to make sure this funciton is invoked after fragment context
2388
    // has already been prepared.
2389
2.40k
    if (!_prepared) {
2390
0
        std::string msg =
2391
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2392
0
        DCHECK(false) << msg;
2393
0
        LOG_ERROR(msg);
2394
0
        return res;
2395
0
    }
2396
2397
    // Make sure first profile is fragment level profile
2398
2.40k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.40k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.40k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.72k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.72k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.72k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.72k
        res.push_back(profile_ptr);
2407
4.72k
    }
2408
2409
2.40k
    return res;
2410
2.40k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.40k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2414
    // we do not have mutex to protect pipeline_id_to_profile
2415
    // so we need to make sure this funciton is invoked after fragment context
2416
    // has already been prepared.
2417
2.40k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
7.37k
    for (const auto& tasks : _tasks) {
2426
15.0k
        for (const auto& task : tasks) {
2427
15.0k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
15.0k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
15.0k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
15.0k
                                                           _runtime_state->profile_level());
2435
15.0k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
15.0k
        }
2437
7.37k
    }
2438
2439
2.40k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.40k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.40k
                                                      _runtime_state->profile_level());
2442
2.40k
    return load_channel_profile;
2443
2.40k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
4.62k
    for (const auto& _task : _tasks) {
2455
8.85k
        for (const auto& task : _task) {
2456
8.85k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
8.85k
            result.merge(set);
2458
8.85k
        }
2459
4.62k
    }
2460
3.28k
    if (_runtime_state) {
2461
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.28k
        result.merge(set);
2463
3.28k
    }
2464
3.28k
    return result;
2465
3.28k
}
2466
2467
325k
void PipelineFragmentContext::_release_resource() {
2468
325k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
325k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
325k
    auto st = _query_ctx->exec_status();
2472
882k
    for (auto& _task : _tasks) {
2473
882k
        if (!_task.empty()) {
2474
882k
            _call_back(_task.front().first->runtime_state(), &st);
2475
882k
        }
2476
882k
    }
2477
325k
    _tasks.clear();
2478
325k
    _dag.clear();
2479
325k
    _pip_id_to_pipeline.clear();
2480
325k
    _pipelines.clear();
2481
325k
    _sink.reset();
2482
325k
    _root_op.reset();
2483
325k
    _runtime_filter_mgr_map.clear();
2484
325k
    _op_id_to_shared_state.clear();
2485
325k
}
2486
2487
} // namespace doris