Coverage Report

Created: 2026-05-24 16:45

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
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
114
#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
132
#include "util/client_cache.h"
133
#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
501k
        : _query_id(std::move(query_id)),
144
501k
          _fragment_id(request.fragment_id),
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501k
          _exec_env(exec_env),
146
501k
          _query_ctx(std::move(query_ctx)),
147
501k
          _call_back(call_back),
148
501k
          _is_report_on_cancel(true),
149
501k
          _params(request),
150
501k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
501k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
501k
                                                               : false) {
153
501k
    _fragment_watcher.start();
154
501k
}
155
156
501k
PipelineFragmentContext::~PipelineFragmentContext() {
157
501k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
501k
            .tag("query_id", print_id(_query_id))
159
501k
            .tag("fragment_id", _fragment_id);
160
501k
    _release_resource();
161
501k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
501k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
501k
        _runtime_state.reset();
165
501k
        _query_ctx.reset();
166
501k
    }
167
501k
}
168
169
109
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
109
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
109
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
109
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
9.43k
bool PipelineFragmentContext::notify_close() {
181
9.43k
    bool all_closed = false;
182
9.43k
    bool need_remove = false;
183
9.43k
    {
184
9.43k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.43k
        if (_closed_tasks >= _total_tasks) {
186
3.26k
            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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3.22k
                need_remove = true;
193
3.22k
            }
194
3.26k
            all_closed = true;
195
3.26k
        }
196
        // make fragment release by self after cancel
197
9.43k
        _need_notify_close = false;
198
9.43k
    }
199
9.43k
    if (need_remove) {
200
3.22k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.22k
    }
202
9.43k
    return all_closed;
203
9.43k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
6.15k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.15k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.15k
            .tag("query_id", print_id(_query_id))
212
6.15k
            .tag("fragment_id", _fragment_id)
213
6.15k
            .tag("reason", reason.to_string());
214
6.15k
    if (notify_close()) {
215
62
        return;
216
62
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.09k
    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
6.09k
    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
6.09k
    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
6.09k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
22
        _query_ctx->set_load_error_url(error_url);
236
22
    }
237
238
6.09k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
22
        _query_ctx->set_first_error_msg(first_error_msg);
240
22
    }
241
242
6.09k
    _query_ctx->cancel(reason, _fragment_id);
243
6.09k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
338
        _is_report_on_cancel = false;
245
5.75k
    } else {
246
29.8k
        for (auto& id : _fragment_instance_ids) {
247
29.8k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
29.8k
        }
249
5.75k
    }
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
6.09k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.09k
    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
30.9k
    for (auto& tasks : _tasks) {
263
74.6k
        for (auto& task : tasks) {
264
74.6k
            task.first->unblock_all_dependencies();
265
74.6k
        }
266
30.9k
    }
267
6.09k
}
268
269
851k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
851k
    PipelineId id = _next_pipeline_id++;
271
851k
    auto pipeline = std::make_shared<Pipeline>(
272
851k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
851k
            parent ? parent->num_tasks() : _num_instances);
274
851k
    if (idx >= 0) {
275
105k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
745k
    } else {
277
745k
        _pipelines.emplace_back(pipeline);
278
745k
    }
279
851k
    if (parent) {
280
312k
        parent->set_children(pipeline);
281
312k
    }
282
851k
    return pipeline;
283
851k
}
284
285
500k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
500k
    {
287
500k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
500k
        auto root_pipeline = add_pipeline();
290
500k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
500k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
500k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
500k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
500k
                                          _params.fragment.output_exprs, _params,
299
500k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
500k
                                          *_desc_tbl, root_pipeline->id()));
301
500k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
500k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
745k
        for (PipelinePtr& pipeline : _pipelines) {
305
745k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
745k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
745k
        }
308
500k
    }
309
    // 4. Build local exchanger
310
500k
    if (_runtime_state->enable_local_shuffle()) {
311
497k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
497k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
497k
                                             _params.bucket_seq_to_instance_idx,
314
497k
                                             _params.shuffle_idx_to_instance_idx));
315
497k
    }
316
317
    // 5. Initialize global states in pipelines.
318
851k
    for (PipelinePtr& pipeline : _pipelines) {
319
851k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
851k
        pipeline->children().clear();
321
851k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
851k
    }
323
324
499k
    {
325
499k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
499k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
499k
    }
329
330
499k
    return Status::OK();
331
499k
}
332
333
501k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
501k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
501k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
501k
        _timeout = _params.query_options.execution_timeout;
339
501k
    }
340
341
501k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
501k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
501k
    SCOPED_TIMER(_prepare_timer);
344
501k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
501k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
501k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
501k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
501k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
501k
    {
350
501k
        SCOPED_TIMER(_init_context_timer);
351
501k
        cast_set(_num_instances, _params.local_params.size());
352
501k
        _total_instances =
353
501k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
501k
        auto* fragment_context = this;
356
357
501k
        if (_params.query_options.__isset.is_report_success) {
358
500k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
500k
        }
360
361
        // 1. Set up the global runtime state.
362
501k
        _runtime_state = RuntimeState::create_unique(
363
501k
                _params.query_id, _params.fragment_id, _params.query_options,
364
501k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
501k
        _runtime_state->set_task_execution_context(shared_from_this());
366
501k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
501k
        if (_params.__isset.backend_id) {
368
497k
            _runtime_state->set_backend_id(_params.backend_id);
369
497k
        }
370
501k
        if (_params.__isset.import_label) {
371
243
            _runtime_state->set_import_label(_params.import_label);
372
243
        }
373
501k
        if (_params.__isset.db_name) {
374
195
            _runtime_state->set_db_name(_params.db_name);
375
195
        }
376
501k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
501k
        if (_params.is_simplified_param) {
381
209k
            _desc_tbl = _query_ctx->desc_tbl;
382
291k
        } else {
383
291k
            DCHECK(_params.__isset.desc_tbl);
384
291k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
291k
                                                  &_desc_tbl));
386
291k
        }
387
501k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
501k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
501k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
501k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
501k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
501k
        const auto target_size = _params.local_params.size();
395
501k
        _fragment_instance_ids.resize(target_size);
396
1.76M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.26M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.26M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.26M
        }
400
501k
    }
401
402
501k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
499k
    _init_next_report_time();
405
406
499k
    _prepared = true;
407
499k
    return Status::OK();
408
501k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.26M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.26M
    const auto& local_params = _params.local_params[instance_idx];
414
1.26M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.26M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.26M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.26M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.26M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
2.09M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
2.09M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
2.09M
                                std::vector<std::shared_ptr<Dependency>>>>
422
2.09M
                shared_state_map;
423
2.70M
        for (auto& op : pipeline->operators()) {
424
2.70M
            auto source_id = op->operator_id();
425
2.70M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.70M
                iter != _op_id_to_shared_state.end()) {
427
735k
                shared_state_map.insert({source_id, iter->second});
428
735k
            }
429
2.70M
        }
430
2.11M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
2.11M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
2.11M
                iter != _op_id_to_shared_state.end()) {
433
260k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
260k
            }
435
2.11M
        }
436
2.09M
        return shared_state_map;
437
2.09M
    };
438
439
3.82M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.56M
        auto& pipeline = _pipelines[pip_idx];
441
2.56M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
2.08M
            auto task_runtime_state = RuntimeState::create_unique(
443
2.08M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
2.08M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
2.08M
            {
446
                // Initialize runtime state for this task
447
2.08M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
2.08M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
2.08M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
2.08M
                if (_params.__isset.backend_id) {
453
2.08M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
2.08M
                }
455
2.08M
                if (_params.__isset.import_label) {
456
244
                    task_runtime_state->set_import_label(_params.import_label);
457
244
                }
458
2.08M
                if (_params.__isset.db_name) {
459
196
                    task_runtime_state->set_db_name(_params.db_name);
460
196
                }
461
2.08M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
2.08M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
2.08M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
2.08M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
2.08M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
2.08M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
2.08M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
2.08M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
2.08M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
2.08M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
2.08M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
2.08M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
2.08M
            }
482
2.08M
            auto cur_task_id = _total_tasks++;
483
2.08M
            task_runtime_state->set_task_id(cur_task_id);
484
2.08M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
2.08M
            auto task = std::make_shared<PipelineTask>(
486
2.08M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
2.08M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
2.08M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
2.08M
                    instance_idx);
490
2.08M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
2.08M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
2.08M
            _tasks[instance_idx].emplace_back(
493
2.08M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
2.08M
                            std::move(task), std::move(task_runtime_state)});
495
2.08M
        }
496
2.56M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
2.56M
    for (auto& _pipeline : _pipelines) {
516
2.56M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
2.08M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
2.08M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
2.08M
            if (_dag.contains(_pipeline->id())) {
522
1.29M
                auto& deps = _dag[_pipeline->id()];
523
2.01M
                for (auto& dep : deps) {
524
2.01M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.07M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.07M
                        if (ss) {
527
559k
                            task->inject_shared_state(ss);
528
559k
                        } else {
529
512k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
512k
                                    task->get_source_shared_state());
531
512k
                        }
532
1.07M
                    }
533
2.01M
                }
534
1.29M
            }
535
2.08M
        }
536
2.56M
    }
537
3.82M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.56M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
2.08M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
2.08M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
2.08M
            std::vector<TScanRangeParams> scan_ranges;
542
2.08M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
2.08M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
324k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
324k
            }
546
2.08M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
2.08M
                                                             _params.fragment.output_sink));
548
2.08M
        }
549
2.56M
    }
550
1.26M
    {
551
1.26M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.26M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.26M
    }
554
1.26M
    return Status::OK();
555
1.26M
}
556
557
500k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
500k
    _total_tasks = 0;
559
500k
    _closed_tasks = 0;
560
500k
    const auto target_size = _params.local_params.size();
561
500k
    _tasks.resize(target_size);
562
500k
    _runtime_filter_mgr_map.resize(target_size);
563
1.35M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
850k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
850k
    }
566
500k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
500k
    if (target_size > 1 &&
569
500k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
134k
         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
23.4k
        std::vector<Status> prepare_status(target_size);
573
23.4k
        int submitted_tasks = 0;
574
23.4k
        Status submit_status;
575
23.4k
        CountDownLatch latch((int)target_size);
576
274k
        for (int i = 0; i < target_size; i++) {
577
251k
            submit_status = thread_pool->submit_func([&, i]() {
578
250k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
250k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
250k
                latch.count_down();
581
250k
            });
582
251k
            if (LIKELY(submit_status.ok())) {
583
251k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
251k
        }
588
23.4k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
23.4k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
274k
        for (int i = 0; i < submitted_tasks; i++) {
593
251k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
251k
        }
597
476k
    } else {
598
1.48M
        for (int i = 0; i < target_size; i++) {
599
1.01M
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
1.01M
        }
601
476k
    }
602
500k
    _pipeline_parent_map.clear();
603
500k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
500k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
500k
    return Status::OK();
608
500k
}
609
610
499k
void PipelineFragmentContext::_init_next_report_time() {
611
499k
    auto interval_s = config::pipeline_status_report_interval;
612
499k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
18.4E
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.1k
        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
42.1k
        _previous_report_time =
617
42.1k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.1k
        _disable_period_report = false;
619
42.1k
    }
620
499k
}
621
622
4.79k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.79k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.79k
    DCHECK(disable == true);
625
4.79k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.79k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.79k
}
628
629
7.66M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.66M
    if (!_is_report_success) {
631
7.20M
        return;
632
7.20M
    }
633
455k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
455k
    if (disable) {
635
8.42k
        return;
636
8.42k
    }
637
447k
    int32_t interval_s = config::pipeline_status_report_interval;
638
447k
    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
447k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
447k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
447k
    if (MonotonicNanos() > next_report_time) {
646
4.80k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.80k
                                                            std::memory_order_acq_rel)) {
648
8
            return;
649
8
        }
650
4.79k
        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
4.79k
        auto st = send_report(false);
667
4.79k
        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
4.79k
    }
673
447k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
500k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
500k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
500k
    int node_idx = 0;
682
683
500k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
500k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
500k
    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
500k
    return Status::OK();
691
500k
}
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
858k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
858k
    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
858k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
858k
    int num_children = tnodes[*node_idx].num_children;
706
858k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
858k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
858k
    OperatorPtr op = nullptr;
710
858k
    OperatorPtr cache_op = nullptr;
711
858k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
858k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
858k
                                     followed_by_shuffled_operator,
714
858k
                                     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
858k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
858k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
358k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
499k
    } else {
723
499k
        *root = op;
724
499k
    }
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
858k
    auto required_data_distribution =
737
858k
            cur_pipe->operators().empty()
738
858k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
858k
                    : op->required_data_distribution(_runtime_state.get());
740
858k
    current_followed_by_shuffled_operator =
741
858k
            ((followed_by_shuffled_operator ||
742
858k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
787k
                                             : op->is_shuffled_operator())) &&
744
858k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
858k
            (followed_by_shuffled_operator &&
746
725k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
858k
    current_require_bucket_distribution =
749
858k
            ((require_bucket_distribution ||
750
858k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
791k
                                             : op->is_colocated_operator())) &&
752
858k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
858k
            (require_bucket_distribution &&
754
731k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
858k
    if (num_children == 0) {
757
538k
        _use_serial_source = op->is_serial_operator();
758
538k
    }
759
    // rely on that tnodes is preorder of the plan
760
1.21M
    for (int i = 0; i < num_children; i++) {
761
358k
        ++*node_idx;
762
358k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
358k
                                            current_followed_by_shuffled_operator,
764
358k
                                            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
358k
        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
358k
    }
775
776
858k
    return Status::OK();
777
858k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
105k
        PipelinePtr pipe_with_sink) {
782
105k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
105k
    pipe_with_source->set_num_tasks(_num_instances);
784
105k
    pipe_with_source->set_data_distribution(data_distribution);
785
105k
}
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
105k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
105k
    auto& operators = cur_pipe->operators();
793
105k
    const auto downstream_pipeline_id = cur_pipe->id();
794
105k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
105k
    DataSinkOperatorPtr sink;
797
105k
    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
105k
    const bool followed_by_shuffled_operator =
804
105k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
105k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
105k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
105k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
105k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
105k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
105k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
105k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
105k
    if (bucket_seq_to_instance_idx.empty() &&
813
105k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
5
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
5
    }
816
105k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
105k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
105k
                                          num_buckets, use_global_hash_shuffle,
819
105k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
105k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
105k
            LocalExchangeSharedState::create_shared(_num_instances);
824
105k
    switch (data_distribution.distribution_type) {
825
10.4k
    case ExchangeType::HASH_SHUFFLE:
826
10.4k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
10.4k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
10.4k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
10.4k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
10.4k
                        ? cast_set<int>(
831
10.4k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
10.4k
                        : 0);
833
10.4k
        break;
834
438
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
438
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
438
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
438
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
438
                        ? cast_set<int>(
839
438
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
438
                        : 0);
841
438
        break;
842
90.6k
    case ExchangeType::PASSTHROUGH:
843
90.6k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
90.6k
                cur_pipe->num_tasks(), _num_instances,
845
90.6k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
90.6k
                        ? cast_set<int>(
847
90.6k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
90.6k
                        : 0);
849
90.6k
        break;
850
329
    case ExchangeType::BROADCAST:
851
329
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
329
                cur_pipe->num_tasks(), _num_instances,
853
329
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
329
                        ? cast_set<int>(
855
329
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
329
                        : 0);
857
329
        break;
858
2.75k
    case ExchangeType::PASS_TO_ONE:
859
2.75k
        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
1.59k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.59k
                    cur_pipe->num_tasks(), _num_instances,
863
1.59k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.59k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.59k
                                                    .local_exchange_free_blocks_limit)
866
1.59k
                            : 0);
867
1.59k
        } else {
868
1.15k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.15k
                    cur_pipe->num_tasks(), _num_instances,
870
1.15k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.15k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.15k
                                                    .local_exchange_free_blocks_limit)
873
1.15k
                            : 0);
874
1.15k
        }
875
2.75k
        break;
876
834
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
834
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
834
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
834
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
834
                        ? cast_set<int>(
881
834
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
834
                        : 0);
883
834
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
105k
    }
888
105k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
105k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
105k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
105k
    _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
105k
    std::copy(operators.begin(), operators.begin() + idx,
898
105k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
105k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
105k
    OperatorPtr source_op;
905
105k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
105k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
105k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
105k
    if (!operators.empty()) {
909
42.8k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
42.8k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
42.8k
    }
912
105k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
105k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
105k
    std::vector<PipelineId> edges_with_source;
917
123k
    for (auto child : cur_pipe->children()) {
918
123k
        bool found = false;
919
137k
        for (auto op : new_pip->operators()) {
920
137k
            if (child->sink()->node_id() == op->node_id()) {
921
12.6k
                new_pip->set_children(child);
922
12.6k
                found = true;
923
12.6k
            };
924
137k
        }
925
123k
        if (!found) {
926
110k
            new_children.push_back(child);
927
110k
            edges_with_source.push_back(child->id());
928
110k
        }
929
123k
    }
930
105k
    new_children.push_back(new_pip);
931
105k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
105k
    if (!new_pip->children().empty()) {
935
7.07k
        std::vector<PipelineId> edges_with_sink;
936
12.6k
        for (auto child : new_pip->children()) {
937
12.6k
            edges_with_sink.push_back(child->id());
938
12.6k
        }
939
7.07k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.07k
    }
941
105k
    cur_pipe->set_children(new_children);
942
105k
    _dag[downstream_pipeline_id] = edges_with_source;
943
105k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
105k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
105k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
105k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
105k
    return Status::OK();
950
105k
}
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
244k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
244k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
104k
        return Status::OK();
959
104k
    }
960
961
140k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
45.4k
        return Status::OK();
963
45.4k
    }
964
94.6k
    *do_local_exchange = true;
965
966
94.6k
    auto& operators = cur_pipe->operators();
967
94.6k
    auto total_op_num = operators.size();
968
94.6k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
94.6k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
94.6k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
94.6k
            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
94.6k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
94.6k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
10.7k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
10.7k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
10.7k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
10.7k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
10.7k
                shuffle_idx_to_instance_idx));
990
10.7k
    }
991
94.6k
    return Status::OK();
992
94.6k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
497k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.23M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
742k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
742k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
206k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
206k
                if (child->sink()->node_id() ==
1003
206k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
170k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
170k
                }
1006
206k
            }
1007
190k
        }
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
742k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
742k
                                             bucket_seq_to_instance_idx,
1014
742k
                                             shuffle_idx_to_instance_idx));
1015
742k
    }
1016
497k
    return Status::OK();
1017
497k
}
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
741k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
741k
    int idx = 1;
1024
741k
    bool do_local_exchange = false;
1025
784k
    do {
1026
784k
        auto& ops = pip->operators();
1027
784k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
894k
        for (; idx < ops.size();) {
1030
152k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
128k
                RETURN_IF_ERROR(_add_local_exchange(
1032
128k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
128k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
128k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
128k
                        shuffle_idx_to_instance_idx));
1036
128k
            }
1037
152k
            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
42.8k
                idx = 2;
1043
42.8k
                break;
1044
42.8k
            }
1045
109k
            idx++;
1046
109k
        }
1047
784k
    } while (do_local_exchange);
1048
741k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
116k
        RETURN_IF_ERROR(_add_local_exchange(
1050
116k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
116k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
116k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
116k
    }
1054
741k
    return Status::OK();
1055
741k
}
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
500k
                                                  PipelineId cur_pipeline_id) {
1063
500k
    switch (thrift_sink.type) {
1064
197k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
197k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
197k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
197k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
197k
                params.destinations, _fragment_instance_ids);
1071
197k
        break;
1072
197k
    }
1073
253k
    case TDataSinkType::RESULT_SINK: {
1074
253k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
253k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
253k
        int child_node_id = pipeline->operators().back()->node_id();
1080
253k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
253k
                                                      row_desc, output_exprs,
1082
253k
                                                      thrift_sink.result_sink);
1083
253k
        break;
1084
253k
    }
1085
104
    case TDataSinkType::DICTIONARY_SINK: {
1086
104
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
104
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
104
                                                    thrift_sink.dictionary_sink);
1092
104
        break;
1093
104
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
32.8k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
32.8k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
32.8k
        int child_node_id = pipeline->operators().back()->node_id();
1098
32.8k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
32.8k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
32.8k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.61k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.61k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
30.2k
        } else {
1104
30.2k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
30.2k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
30.2k
        }
1107
32.8k
        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
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.46k
                                                         output_exprs);
1123
1.46k
        break;
1124
1.46k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        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
1.73k
        } else {
1133
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.73k
                                                                row_desc, output_exprs);
1135
1.73k
        }
1136
1.73k
        break;
1137
1.73k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
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
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } 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
88
        break;
1175
88
    }
1176
88
    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
502
    case TDataSinkType::RESULT_FILE_SINK: {
1186
502
        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
502
        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
502
        } else {
1196
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
502
                                                              output_exprs);
1198
502
        }
1199
502
        break;
1200
502
    }
1201
12.8k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
12.8k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
12.8k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
12.8k
        auto sink_id = next_sink_operator_id();
1205
12.8k
        const int multi_cast_node_id = sink_id;
1206
12.8k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
12.8k
        std::vector<int> sources;
1209
51.0k
        for (int i = 0; i < sender_size; ++i) {
1210
38.2k
            auto source_id = next_operator_id();
1211
38.2k
            sources.push_back(source_id);
1212
38.2k
        }
1213
1214
12.8k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
12.8k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
51.0k
        for (int i = 0; i < sender_size; ++i) {
1217
38.2k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
38.2k
            RowDescriptor* exchange_row_desc = nullptr;
1220
38.2k
            {
1221
38.2k
                const auto& tmp_row_desc =
1222
38.2k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
38.2k
                                ? RowDescriptor(state->desc_tbl(),
1224
38.2k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
38.2k
                                                         .output_tuple_id})
1226
38.2k
                                : row_desc;
1227
38.2k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
38.2k
            }
1229
38.2k
            auto source_id = sources[i];
1230
38.2k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
38.2k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
38.2k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
38.2k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
38.2k
                    /*operator_id=*/source_id);
1236
38.2k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
38.2k
                    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
38.2k
            DataSinkOperatorPtr sink_op;
1241
38.2k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
38.2k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
38.2k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
38.2k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
38.2k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
38.2k
            {
1248
38.2k
                TDataSink* t = pool->add(new TDataSink());
1249
38.2k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
38.2k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
38.2k
            }
1252
1253
            // 3. set dependency dag
1254
38.2k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
38.2k
        }
1256
12.8k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
12.8k
        break;
1260
12.8k
    }
1261
12.8k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
13
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
13
        break;
1268
13
    }
1269
156
    case TDataSinkType::TVF_TABLE_SINK: {
1270
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
156
                                                        output_exprs);
1275
156
        break;
1276
156
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
500k
    }
1280
500k
    return Status::OK();
1281
500k
}
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
859k
                                                 OperatorPtr& cache_op) {
1292
859k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
859k
    Defer defer = Defer([&]() {
1294
859k
        if (op) {
1295
859k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
859k
        }
1297
859k
        for (auto& s : sink_ops) {
1298
206k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
206k
        }
1300
859k
    });
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
859k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
859k
    std::stringstream error_msg;
1305
859k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
859k
    bool fe_with_old_version = false;
1308
859k
    switch (tnode.node_type) {
1309
213k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
213k
        op = std::make_shared<OlapScanOperatorX>(
1311
213k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
213k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
213k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
213k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
213k
        break;
1316
213k
    }
1317
82
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
82
        DCHECK(_query_ctx != nullptr);
1319
82
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
82
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
82
                                                    _num_instances);
1322
82
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
82
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
82
        break;
1325
82
    }
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
24.6k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
24.6k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
24.6k
                                                 _num_instances);
1342
24.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
24.6k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
24.6k
        break;
1345
24.6k
    }
1346
233k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
233k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
233k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
233k
        DCHECK_GT(num_senders, 0);
1351
233k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
233k
                                                       num_senders);
1353
233k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
233k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
233k
        break;
1356
233k
    }
1357
211k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
211k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
211k
            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
211k
        bool need_create_cache_op =
1364
211k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
211k
        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
211k
        const bool group_by_limit_opt =
1385
211k
                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
211k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
211k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
211k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
211k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
211k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
211k
        const bool can_use_distinct_streaming_agg =
1396
211k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
211k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
211k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
211k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
211k
        if (can_use_distinct_streaming_agg) {
1402
92.7k
            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
92.7k
            } else {
1413
92.7k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
92.7k
                                                                     tnode, descs);
1415
92.7k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
92.7k
            }
1417
118k
        } else if (is_streaming_agg) {
1418
7.28k
            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
7.28k
            } else {
1428
7.28k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
7.28k
                                                             descs);
1430
7.28k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
7.28k
            }
1432
110k
        } else {
1433
            // create new pipeline to add query cache operator
1434
110k
            PipelinePtr new_pipe;
1435
110k
            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
110k
            if (enable_spill) {
1441
56
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
56
                                                                     next_operator_id(), descs);
1443
110k
            } else {
1444
110k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
110k
            }
1446
110k
            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
110k
            } else {
1451
110k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
110k
            }
1453
1454
110k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
110k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
97.7k
                _dag.insert({downstream_pipeline_id, {}});
1457
97.7k
            }
1458
110k
            cur_pipe = add_pipeline(cur_pipe);
1459
110k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
110k
            if (enable_spill) {
1462
56
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
56
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
110k
            } else {
1465
110k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
110k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
110k
            }
1468
110k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
110k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
110k
        }
1471
211k
        break;
1472
211k
    }
1473
211k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
92
        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
92
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
92
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
92
        const auto downstream_pipeline_id = cur_pipe->id();
1486
92
        if (!_dag.contains(downstream_pipeline_id)) {
1487
92
            _dag.insert({downstream_pipeline_id, {}});
1488
92
        }
1489
92
        cur_pipe = add_pipeline(cur_pipe);
1490
92
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
92
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
92
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
92
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
92
        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
92
        {
1503
92
            auto shared_state = BucketedAggSharedState::create_shared();
1504
92
            shared_state->id = op->operator_id();
1505
92
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
576
            for (int i = 0; i < _num_instances; i++) {
1508
484
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
484
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
484
                sink_dep->set_shared_state(shared_state.get());
1511
484
                shared_state->sink_deps.push_back(sink_dep);
1512
484
            }
1513
92
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
92
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
92
            _op_id_to_shared_state.insert(
1516
92
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
92
        }
1518
92
        break;
1519
92
    }
1520
9.68k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.68k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.68k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.68k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.68k
        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
9.68k
        } else {
1566
9.68k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.68k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.68k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.68k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.91k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.91k
            }
1573
9.68k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.68k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.68k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.68k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.68k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.68k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.68k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.68k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.68k
        }
1584
9.68k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
4.72k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
4.72k
                    HashJoinSharedState::create_shared(_num_instances);
1587
22.5k
            for (int i = 0; i < _num_instances; i++) {
1588
17.8k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
17.8k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
17.8k
                sink_dep->set_shared_state(shared_state.get());
1591
17.8k
                shared_state->sink_deps.push_back(sink_dep);
1592
17.8k
            }
1593
4.72k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
4.72k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
4.72k
            _op_id_to_shared_state.insert(
1596
4.72k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
4.72k
        }
1598
9.68k
        break;
1599
9.68k
    }
1600
26.9k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
26.9k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
26.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
26.9k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
26.9k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
26.6k
            _dag.insert({downstream_pipeline_id, {}});
1607
26.6k
        }
1608
26.9k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
26.9k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
26.9k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
26.9k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
26.9k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
26.9k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
26.9k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
26.9k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
26.9k
        break;
1618
26.9k
    }
1619
53.7k
    case TPlanNodeType::UNION_NODE: {
1620
53.7k
        int child_count = tnode.num_children;
1621
53.7k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
53.7k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
53.7k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
53.7k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
53.5k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.5k
        }
1628
55.1k
        for (int i = 0; i < child_count; i++) {
1629
1.42k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.42k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.42k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.42k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.42k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.42k
            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
1.42k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.42k
        }
1638
53.7k
        break;
1639
53.7k
    }
1640
55.1k
    case TPlanNodeType::SORT_NODE: {
1641
55.1k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
55.1k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
55.1k
        const bool use_local_merge =
1644
55.1k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
55.1k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
55.1k
        } else if (use_local_merge) {
1648
52.9k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
52.9k
                                                                 descs);
1650
52.9k
        } else {
1651
2.18k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.18k
        }
1653
55.1k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
55.1k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
55.1k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
55.1k
            _dag.insert({downstream_pipeline_id, {}});
1658
55.1k
        }
1659
55.1k
        cur_pipe = add_pipeline(cur_pipe);
1660
55.1k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
55.1k
        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
55.1k
        } else {
1666
55.1k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
55.1k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
55.1k
        }
1669
55.1k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
55.1k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
55.1k
        break;
1672
55.1k
    }
1673
55.1k
    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
1.51k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.51k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.51k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.51k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.51k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.50k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.50k
        }
1698
1.51k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.51k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.51k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.51k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.51k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.51k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.51k
        break;
1706
1.51k
    }
1707
1.60k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.60k
        break;
1711
1.60k
    }
1712
1.60k
    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
914
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
914
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
914
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
914
        break;
1731
914
    }
1732
914
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
218
        break;
1736
218
    }
1737
1.89k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.89k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.89k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.89k
        break;
1741
1.89k
    }
1742
1.89k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
463
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
463
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
463
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
463
        break;
1747
463
    }
1748
2.02k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.02k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.02k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.02k
        break;
1752
2.02k
    }
1753
7.05k
    case TPlanNodeType::META_SCAN_NODE: {
1754
7.05k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
7.05k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
7.05k
        break;
1757
7.05k
    }
1758
12.7k
    case TPlanNodeType::SELECT_NODE: {
1759
12.7k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
12.7k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
12.7k
        break;
1762
12.7k
    }
1763
12.7k
    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
859k
    }
1803
858k
    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
858k
    return Status::OK();
1809
859k
}
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
498k
Status PipelineFragmentContext::submit() {
1846
498k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
498k
    _submitted = true;
1850
1851
498k
    int submit_tasks = 0;
1852
498k
    Status st;
1853
498k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.26M
    for (auto& task : _tasks) {
1855
2.09M
        for (auto& t : task) {
1856
2.09M
            st = scheduler->submit(t.first);
1857
2.09M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
2.09M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
2.09M
            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
2.09M
            submit_tasks++;
1866
2.09M
        }
1867
1.26M
    }
1868
498k
    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
498k
    } else {
1883
498k
        return st;
1884
498k
    }
1885
498k
}
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
500k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
500k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
500k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
500k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
500k
    if (!_need_notify_close) {
1919
496k
        auto st = send_report(true);
1920
496k
        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
496k
    }
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
500k
    if (_runtime_state->enable_profile() &&
1931
500k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.55k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.55k
         _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
500k
    if (_query_ctx->enable_profile()) {
1953
2.55k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.55k
                                         collect_realtime_load_channel_profile());
1955
2.55k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
500k
    return !_need_notify_close;
1960
500k
}
1961
1962
2.08M
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
2.08M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
2.08M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
850k
        if (_dag.contains(pipeline_id)) {
1967
455k
            for (auto dep : _dag[pipeline_id]) {
1968
455k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
455k
            }
1970
381k
        }
1971
850k
    }
1972
2.08M
    bool need_remove = false;
1973
2.08M
    {
1974
2.08M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
2.08M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
2.08M
        _query_ctx->inc_finished_task_num();
1978
2.08M
        if (_closed_tasks >= _total_tasks) {
1979
500k
            need_remove = _close_fragment_instance();
1980
500k
        }
1981
2.08M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
2.08M
    if (need_remove) {
1984
496k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
496k
    }
1986
2.08M
}
1987
1988
54.6k
std::string PipelineFragmentContext::get_load_error_url() {
1989
54.6k
    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
139k
    for (auto& tasks : _tasks) {
1993
222k
        for (auto& task : tasks) {
1994
222k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
172
                return to_load_error_http_path(str);
1996
172
            }
1997
222k
        }
1998
139k
    }
1999
54.4k
    return "";
2000
54.6k
}
2001
2002
54.6k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
54.6k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
139k
    for (auto& tasks : _tasks) {
2007
222k
        for (auto& task : tasks) {
2008
222k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
172
                return str;
2010
172
            }
2011
222k
        }
2012
139k
    }
2013
54.4k
    return "";
2014
54.6k
}
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
48.5k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
48.5k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
48.5k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
48.5k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
48.5k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
48.5k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
48.5k
    });
2031
2032
48.5k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
48.5k
    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
48.5k
    int callback_retries = 10;
2038
48.5k
    const int sleep_ms = 1000;
2039
48.5k
    Status exec_status = req.status;
2040
48.5k
    Status coord_status;
2041
48.5k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
48.5k
    do {
2043
48.5k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
48.5k
                                                            req.coord_addr, &coord_status);
2045
48.5k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
48.5k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
48.5k
    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
48.5k
    TReportExecStatusParams params;
2059
48.5k
    params.protocol_version = FrontendServiceVersion::V1;
2060
48.5k
    params.__set_query_id(req.query_id);
2061
48.5k
    params.__set_backend_num(req.backend_num);
2062
48.5k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
48.5k
    params.__set_fragment_id(req.fragment_id);
2064
48.5k
    params.__set_status(exec_status.to_thrift());
2065
48.5k
    params.__set_done(req.done);
2066
48.5k
    params.__set_query_type(req.runtime_state->query_type());
2067
48.5k
    params.__isset.profile = false;
2068
2069
48.5k
    DCHECK(req.runtime_state != nullptr);
2070
2071
48.5k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
43.8k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
43.8k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
43.8k
    } else {
2075
4.66k
        DCHECK(!req.runtime_states.empty());
2076
4.66k
        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
4.66k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.66k
    }
2086
2087
48.5k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
48.5k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
48.5k
    static std::string s_unselected_rows = "unselected.rows";
2090
48.5k
    int64_t num_rows_load_success = 0;
2091
48.5k
    int64_t num_rows_load_filtered = 0;
2092
48.5k
    int64_t num_rows_load_unselected = 0;
2093
48.5k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
48.5k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
48.5k
        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
48.5k
    } else if (!req.runtime_states.empty()) {
2109
148k
        for (auto* rs : req.runtime_states) {
2110
148k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
148k
                rs->num_finished_range() > 0) {
2112
36.3k
                params.__isset.load_counters = true;
2113
36.3k
                num_rows_load_success += rs->num_rows_load_success();
2114
36.3k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
36.3k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
36.3k
                params.__isset.fragment_instance_reports = true;
2117
36.3k
                TFragmentInstanceReport t;
2118
36.3k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
36.3k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
36.3k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
36.3k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
36.3k
                params.fragment_instance_reports.push_back(t);
2123
36.3k
            }
2124
148k
        }
2125
48.5k
    }
2126
48.5k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
48.5k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
48.5k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
48.5k
    if (!req.load_error_url.empty()) {
2131
159
        params.__set_tracking_url(req.load_error_url);
2132
159
    }
2133
48.5k
    if (!req.first_error_msg.empty()) {
2134
159
        params.__set_first_error_msg(req.first_error_msg);
2135
159
    }
2136
148k
    for (auto* rs : req.runtime_states) {
2137
148k
        if (rs->wal_id() > 0) {
2138
105
            params.__set_txn_id(rs->wal_id());
2139
105
            params.__set_label(rs->import_label());
2140
105
        }
2141
148k
    }
2142
48.5k
    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
48.5k
    } else if (!req.runtime_states.empty()) {
2146
148k
        for (auto* rs : req.runtime_states) {
2147
148k
            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
148k
        }
2154
48.4k
    }
2155
48.5k
    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
48.5k
    } else if (!req.runtime_states.empty()) {
2159
148k
        for (auto* rs : req.runtime_states) {
2160
148k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
27.5k
                params.__isset.commitInfos = true;
2162
27.5k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
27.5k
            }
2164
148k
        }
2165
48.5k
    }
2166
48.5k
    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
48.5k
    } else if (!req.runtime_states.empty()) {
2170
148k
        for (auto* rs : req.runtime_states) {
2171
148k
            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
148k
        }
2177
48.5k
    }
2178
48.5k
    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
48.5k
    } else if (!req.runtime_states.empty()) {
2183
148k
        for (auto* rs : req.runtime_states) {
2184
148k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.09k
                params.__isset.hive_partition_updates = true;
2186
2.09k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.09k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.09k
            }
2189
148k
        }
2190
48.5k
    }
2191
48.5k
    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
48.5k
    } else if (!req.runtime_states.empty()) {
2196
148k
        for (auto* rs : req.runtime_states) {
2197
148k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.05k
                params.__isset.iceberg_commit_datas = true;
2199
2.05k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.05k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.05k
            }
2202
148k
        }
2203
48.5k
    }
2204
2205
48.5k
    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
48.5k
    } else if (!req.runtime_states.empty()) {
2209
148k
        for (auto* rs : req.runtime_states) {
2210
148k
            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
148k
        }
2216
48.5k
    }
2217
2218
48.5k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
48.5k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
48.5k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
48.4k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
48.4k
    }
2224
2225
48.5k
    TReportExecStatusResult res;
2226
48.5k
    Status rpc_status;
2227
2228
48.5k
    VLOG_DEBUG << "reportExecStatus params is "
2229
21
               << apache::thrift::ThriftDebugString(params).c_str();
2230
48.5k
    if (!exec_status.ok()) {
2231
1.68k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.68k
                     << " to coordinator: " << req.coord_addr
2233
1.68k
                     << ", query id: " << print_id(req.query_id);
2234
1.68k
    }
2235
48.5k
    try {
2236
48.5k
        try {
2237
48.5k
            (*coord)->reportExecStatus(res, params);
2238
48.5k
        } 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
48.5k
        rpc_status = Status::create<false>(res.status);
2254
48.5k
    } 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
48.5k
    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
48.5k
}
2265
2266
501k
Status PipelineFragmentContext::send_report(bool done) {
2267
501k
    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
501k
    if (!_is_report_success && done && exec_status.ok()) {
2273
453k
        return Status::OK();
2274
453k
    }
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
48.7k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
267
        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
267
            return Status::OK();
2286
267
        }
2287
0
        return Status::NeedSendAgain("");
2288
267
    }
2289
2290
48.5k
    std::vector<RuntimeState*> runtime_states;
2291
2292
108k
    for (auto& tasks : _tasks) {
2293
148k
        for (auto& task : tasks) {
2294
148k
            runtime_states.push_back(task.second.get());
2295
148k
        }
2296
108k
    }
2297
2298
48.5k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
48.5k
                                        ? get_load_error_url()
2300
48.5k
                                        : _query_ctx->get_load_error_url();
2301
48.5k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
48.5k
                                          ? get_first_error_msg()
2303
48.5k
                                          : _query_ctx->get_first_error_msg();
2304
2305
48.5k
    ReportStatusRequest req {.status = exec_status,
2306
48.5k
                             .runtime_states = runtime_states,
2307
48.5k
                             .done = done || !exec_status.ok(),
2308
48.5k
                             .coord_addr = _query_ctx->coord_addr,
2309
48.5k
                             .query_id = _query_id,
2310
48.5k
                             .fragment_id = _fragment_id,
2311
48.5k
                             .fragment_instance_id = TUniqueId(),
2312
48.5k
                             .backend_num = -1,
2313
48.5k
                             .runtime_state = _runtime_state.get(),
2314
48.5k
                             .load_error_url = load_eror_url,
2315
48.5k
                             .first_error_msg = first_error_msg,
2316
48.5k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
48.5k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
48.5k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
48.5k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
48.5k
        _coordinator_callback(req);
2321
48.5k
        if (!req.done) {
2322
4.79k
            ctx->refresh_next_report_time();
2323
4.79k
        }
2324
48.5k
    });
2325
48.7k
}
2326
2327
8
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
8
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
8
    for (const auto& task_instances : _tasks) {
2332
12
        for (const auto& task : task_instances) {
2333
12
            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
12
            size_t revocable_size = task.first->get_revocable_size();
2342
12
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
4
                res += revocable_size;
2344
4
            }
2345
12
        }
2346
8
    }
2347
8
    return res;
2348
8
}
2349
2350
16
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
16
    std::vector<PipelineTask*> revocable_tasks;
2352
16
    for (const auto& task_instances : _tasks) {
2353
24
        for (const auto& task : task_instances) {
2354
24
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
24
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
8
                revocable_tasks.emplace_back(task.first.get());
2358
8
            }
2359
24
        }
2360
16
    }
2361
16
    return revocable_tasks;
2362
16
}
2363
2364
110
std::string PipelineFragmentContext::debug_string() {
2365
110
    std::lock_guard<std::mutex> l(_task_mutex);
2366
110
    fmt::memory_buffer debug_string_buffer;
2367
110
    fmt::format_to(debug_string_buffer,
2368
110
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
110
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
110
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
646
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
536
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
1.79k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
1.25k
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
1.25k
                           _tasks[j][i].first->debug_string());
2376
1.25k
        }
2377
536
    }
2378
2379
110
    return fmt::to_string(debug_string_buffer);
2380
110
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.55k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.55k
    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
2.55k
    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
2.55k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.55k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.55k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.51k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.51k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.51k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.51k
        res.push_back(profile_ptr);
2407
4.51k
    }
2408
2409
2.55k
    return res;
2410
2.55k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.55k
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
2.55k
    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
8.05k
    for (const auto& tasks : _tasks) {
2426
15.6k
        for (const auto& task : tasks) {
2427
15.6k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
15.6k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
15.6k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
15.6k
                                                           _runtime_state->profile_level());
2435
15.6k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
15.6k
        }
2437
8.05k
    }
2438
2439
2.55k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.55k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.55k
                                                      _runtime_state->profile_level());
2442
2.55k
    return load_channel_profile;
2443
2.55k
}
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
3.08k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.08k
    std::set<int> result;
2454
7.46k
    for (const auto& _task : _tasks) {
2455
13.4k
        for (const auto& task : _task) {
2456
13.4k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
13.4k
            result.merge(set);
2458
13.4k
        }
2459
7.46k
    }
2460
3.08k
    if (_runtime_state) {
2461
3.08k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.08k
        result.merge(set);
2463
3.08k
    }
2464
3.08k
    return result;
2465
3.08k
}
2466
2467
501k
void PipelineFragmentContext::_release_resource() {
2468
501k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
501k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
501k
    auto st = _query_ctx->exec_status();
2472
1.26M
    for (auto& _task : _tasks) {
2473
1.26M
        if (!_task.empty()) {
2474
1.26M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.26M
        }
2476
1.26M
    }
2477
501k
    _tasks.clear();
2478
501k
    _dag.clear();
2479
501k
    _pip_id_to_pipeline.clear();
2480
501k
    _pipelines.clear();
2481
501k
    _sink.reset();
2482
501k
    _root_op.reset();
2483
501k
    _runtime_filter_mgr_map.clear();
2484
501k
    _op_id_to_shared_state.clear();
2485
501k
}
2486
2487
} // namespace doris