Coverage Report

Created: 2026-05-18 10:13

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
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"
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#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
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#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
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#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
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#include "util/client_cache.h"
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#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
325k
        : _query_id(std::move(query_id)),
144
325k
          _fragment_id(request.fragment_id),
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325k
          _exec_env(exec_env),
146
325k
          _query_ctx(std::move(query_ctx)),
147
325k
          _call_back(call_back),
148
325k
          _is_report_on_cancel(true),
149
325k
          _params(request),
150
325k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
325k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
325k
                                                               : false) {
153
325k
    _fragment_watcher.start();
154
325k
}
155
156
325k
PipelineFragmentContext::~PipelineFragmentContext() {
157
325k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
325k
            .tag("query_id", print_id(_query_id))
159
325k
            .tag("fragment_id", _fragment_id);
160
325k
    _release_resource();
161
325k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
325k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
325k
        _runtime_state.reset();
165
325k
        _query_ctx.reset();
166
325k
    }
167
325k
}
168
169
115
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
115
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
115
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
115
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
179
// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
9.25k
bool PipelineFragmentContext::notify_close() {
181
9.25k
    bool all_closed = false;
182
9.25k
    bool need_remove = false;
183
9.25k
    {
184
9.25k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.25k
        if (_closed_tasks >= _total_tasks) {
186
3.45k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
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3.43k
                need_remove = true;
193
3.43k
            }
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3.45k
            all_closed = true;
195
3.45k
        }
196
        // make fragment release by self after cancel
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9.25k
        _need_notify_close = false;
198
9.25k
    }
199
9.25k
    if (need_remove) {
200
3.43k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.43k
    }
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9.25k
    return all_closed;
203
9.25k
}
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// Must not add lock in this method. Because it will call query ctx cancel. And
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// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
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// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
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5.77k
void PipelineFragmentContext::cancel(const Status reason) {
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5.77k
    LOG_INFO("PipelineFragmentContext::cancel")
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5.77k
            .tag("query_id", print_id(_query_id))
212
5.77k
            .tag("fragment_id", _fragment_id)
213
5.77k
            .tag("reason", reason.to_string());
214
5.77k
    if (notify_close()) {
215
38
        return;
216
38
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
5.73k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
5.73k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
5.73k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
5.73k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
5.73k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
5.73k
    _query_ctx->cancel(reason, _fragment_id);
243
5.73k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
126
        _is_report_on_cancel = false;
245
5.61k
    } else {
246
33.5k
        for (auto& id : _fragment_instance_ids) {
247
33.5k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
33.5k
        }
249
5.61k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
5.73k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
5.73k
    if (stream_load_ctx != nullptr) {
254
31
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
31
        stream_load_ctx->error_url = get_load_error_url();
259
31
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
31
    }
261
262
34.2k
    for (auto& tasks : _tasks) {
263
72.5k
        for (auto& task : tasks) {
264
72.5k
            task.first->unblock_all_dependencies();
265
72.5k
        }
266
34.2k
    }
267
5.73k
}
268
269
509k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
509k
    PipelineId id = _next_pipeline_id++;
271
509k
    auto pipeline = std::make_shared<Pipeline>(
272
509k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
509k
            parent ? parent->num_tasks() : _num_instances);
274
509k
    if (idx >= 0) {
275
93.7k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
415k
    } else {
277
415k
        _pipelines.emplace_back(pipeline);
278
415k
    }
279
509k
    if (parent) {
280
182k
        parent->set_children(pipeline);
281
182k
    }
282
509k
    return pipeline;
283
509k
}
284
285
324k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
324k
    {
287
324k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
324k
        auto root_pipeline = add_pipeline();
290
324k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
324k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
324k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
324k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
324k
                                          _params.fragment.output_exprs, _params,
299
324k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
324k
                                          *_desc_tbl, root_pipeline->id()));
301
324k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
324k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
414k
        for (PipelinePtr& pipeline : _pipelines) {
305
414k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
414k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
414k
        }
308
324k
    }
309
    // 4. Build local exchanger
310
324k
    if (_runtime_state->enable_local_shuffle()) {
311
323k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
323k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
323k
                                             _params.bucket_seq_to_instance_idx,
314
323k
                                             _params.shuffle_idx_to_instance_idx));
315
323k
    }
316
317
    // 5. Initialize global states in pipelines.
318
509k
    for (PipelinePtr& pipeline : _pipelines) {
319
509k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
509k
        pipeline->children().clear();
321
509k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
509k
    }
323
324
323k
    {
325
323k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
323k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
323k
    }
329
330
323k
    return Status::OK();
331
323k
}
332
333
325k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
325k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
325k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
325k
        _timeout = _params.query_options.execution_timeout;
339
325k
    }
340
341
325k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
325k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
325k
    SCOPED_TIMER(_prepare_timer);
344
325k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
325k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
325k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
325k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
325k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
325k
    {
350
325k
        SCOPED_TIMER(_init_context_timer);
351
325k
        cast_set(_num_instances, _params.local_params.size());
352
325k
        _total_instances =
353
325k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
325k
        auto* fragment_context = this;
356
357
325k
        if (_params.query_options.__isset.is_report_success) {
358
323k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
323k
        }
360
361
        // 1. Set up the global runtime state.
362
325k
        _runtime_state = RuntimeState::create_unique(
363
325k
                _params.query_id, _params.fragment_id, _params.query_options,
364
325k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
325k
        _runtime_state->set_task_execution_context(shared_from_this());
366
325k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
325k
        if (_params.__isset.backend_id) {
368
322k
            _runtime_state->set_backend_id(_params.backend_id);
369
322k
        }
370
325k
        if (_params.__isset.import_label) {
371
237
            _runtime_state->set_import_label(_params.import_label);
372
237
        }
373
325k
        if (_params.__isset.db_name) {
374
189
            _runtime_state->set_db_name(_params.db_name);
375
189
        }
376
325k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
325k
        if (_params.is_simplified_param) {
381
114k
            _desc_tbl = _query_ctx->desc_tbl;
382
211k
        } else {
383
211k
            DCHECK(_params.__isset.desc_tbl);
384
211k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
211k
                                                  &_desc_tbl));
386
211k
        }
387
325k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
325k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
325k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
325k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
325k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
325k
        const auto target_size = _params.local_params.size();
395
325k
        _fragment_instance_ids.resize(target_size);
396
1.14M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
822k
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
822k
            _fragment_instance_ids[i] = fragment_instance_id;
399
822k
        }
400
325k
    }
401
402
325k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
324k
    _init_next_report_time();
405
406
324k
    _prepared = true;
407
324k
    return Status::OK();
408
325k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
821k
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
821k
    const auto& local_params = _params.local_params[instance_idx];
414
821k
    auto fragment_instance_id = local_params.fragment_instance_id;
415
821k
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
821k
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
821k
    auto get_shared_state = [&](PipelinePtr pipeline)
418
821k
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.37M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.37M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.37M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.37M
                shared_state_map;
423
1.79M
        for (auto& op : pipeline->operators()) {
424
1.79M
            auto source_id = op->operator_id();
425
1.79M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
1.79M
                iter != _op_id_to_shared_state.end()) {
427
549k
                shared_state_map.insert({source_id, iter->second});
428
549k
            }
429
1.79M
        }
430
1.37M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.37M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.37M
                iter != _op_id_to_shared_state.end()) {
433
229k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
229k
            }
435
1.37M
        }
436
1.37M
        return shared_state_map;
437
1.37M
    };
438
439
2.51M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
1.69M
        auto& pipeline = _pipelines[pip_idx];
441
1.69M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.37M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.37M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.37M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.37M
            {
446
                // Initialize runtime state for this task
447
1.37M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.37M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.37M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.37M
                if (_params.__isset.backend_id) {
453
1.37M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.37M
                }
455
1.37M
                if (_params.__isset.import_label) {
456
238
                    task_runtime_state->set_import_label(_params.import_label);
457
238
                }
458
1.37M
                if (_params.__isset.db_name) {
459
190
                    task_runtime_state->set_db_name(_params.db_name);
460
190
                }
461
1.37M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.37M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.37M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.37M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.37M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.37M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.37M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.37M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.37M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.37M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.37M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.37M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.37M
            }
482
1.37M
            auto cur_task_id = _total_tasks++;
483
1.37M
            task_runtime_state->set_task_id(cur_task_id);
484
1.37M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.37M
            auto task = std::make_shared<PipelineTask>(
486
1.37M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.37M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.37M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.37M
                    instance_idx);
490
1.37M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.37M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.37M
            _tasks[instance_idx].emplace_back(
493
1.37M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.37M
                            std::move(task), std::move(task_runtime_state)});
495
1.37M
        }
496
1.69M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
1.69M
    for (auto& _pipeline : _pipelines) {
516
1.69M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.37M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.37M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.37M
            if (_dag.contains(_pipeline->id())) {
522
878k
                auto& deps = _dag[_pipeline->id()];
523
1.40M
                for (auto& dep : deps) {
524
1.40M
                    if (pipeline_id_to_task.contains(dep)) {
525
768k
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
768k
                        if (ss) {
527
315k
                            task->inject_shared_state(ss);
528
452k
                        } else {
529
452k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
452k
                                    task->get_source_shared_state());
531
452k
                        }
532
768k
                    }
533
1.40M
                }
534
878k
            }
535
1.37M
        }
536
1.69M
    }
537
2.51M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
1.69M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.37M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.37M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.37M
            std::vector<TScanRangeParams> scan_ranges;
542
1.37M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.37M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
233k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
233k
            }
546
1.37M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.37M
                                                             _params.fragment.output_sink));
548
1.37M
        }
549
1.69M
    }
550
823k
    {
551
823k
        std::lock_guard<std::mutex> l(_state_map_lock);
552
823k
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
823k
    }
554
823k
    return Status::OK();
555
821k
}
556
557
324k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
324k
    _total_tasks = 0;
559
324k
    _closed_tasks = 0;
560
324k
    const auto target_size = _params.local_params.size();
561
324k
    _tasks.resize(target_size);
562
324k
    _runtime_filter_mgr_map.resize(target_size);
563
832k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
508k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
508k
    }
566
324k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
324k
    if (target_size > 1 &&
569
324k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
117k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
571
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
572
21.3k
        std::vector<Status> prepare_status(target_size);
573
21.3k
        int submitted_tasks = 0;
574
21.3k
        Status submit_status;
575
21.3k
        CountDownLatch latch((int)target_size);
576
200k
        for (int i = 0; i < target_size; i++) {
577
179k
            submit_status = thread_pool->submit_func([&, i]() {
578
179k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
179k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
179k
                latch.count_down();
581
179k
            });
582
179k
            if (LIKELY(submit_status.ok())) {
583
179k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
179k
        }
588
21.3k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
21.3k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
200k
        for (int i = 0; i < submitted_tasks; i++) {
593
179k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
179k
        }
597
302k
    } else {
598
945k
        for (int i = 0; i < target_size; i++) {
599
642k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
642k
        }
601
302k
    }
602
324k
    _pipeline_parent_map.clear();
603
324k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
324k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
324k
    return Status::OK();
608
324k
}
609
610
323k
void PipelineFragmentContext::_init_next_report_time() {
611
323k
    auto interval_s = config::pipeline_status_report_interval;
612
323k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
31.8k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
31.8k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
31.8k
        _previous_report_time =
617
31.8k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
31.8k
        _disable_period_report = false;
619
31.8k
    }
620
323k
}
621
622
3.57k
void PipelineFragmentContext::refresh_next_report_time() {
623
3.57k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
3.57k
    DCHECK(disable == true);
625
3.57k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
3.57k
    _disable_period_report.compare_exchange_strong(disable, false);
627
3.57k
}
628
629
5.02M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
5.02M
    if (!_is_report_success) {
631
4.67M
        return;
632
4.67M
    }
633
351k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
351k
    if (disable) {
635
6.21k
        return;
636
6.21k
    }
637
345k
    int32_t interval_s = config::pipeline_status_report_interval;
638
345k
    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
345k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
345k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
345k
    if (MonotonicNanos() > next_report_time) {
646
3.58k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
3.58k
                                                            std::memory_order_acq_rel)) {
648
9
            return;
649
9
        }
650
3.57k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
3.57k
        auto st = send_report(false);
667
3.57k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
3.57k
    }
673
345k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
323k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
323k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
323k
    int node_idx = 0;
682
683
323k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
323k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
323k
    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
323k
    return Status::OK();
691
323k
}
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
517k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
517k
    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
517k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
517k
    int num_children = tnodes[*node_idx].num_children;
706
517k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
517k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
517k
    OperatorPtr op = nullptr;
710
517k
    OperatorPtr cache_op = nullptr;
711
517k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
517k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
517k
                                     followed_by_shuffled_operator,
714
517k
                                     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
517k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
517k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
194k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
322k
    } else {
723
322k
        *root = op;
724
322k
    }
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
517k
    auto required_data_distribution =
737
517k
            cur_pipe->operators().empty()
738
517k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
517k
                    : op->required_data_distribution(_runtime_state.get());
740
517k
    current_followed_by_shuffled_operator =
741
517k
            ((followed_by_shuffled_operator ||
742
517k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
461k
                                             : op->is_shuffled_operator())) &&
744
517k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
517k
            (followed_by_shuffled_operator &&
746
411k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
517k
    current_require_bucket_distribution =
749
517k
            ((require_bucket_distribution ||
750
517k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
465k
                                             : op->is_colocated_operator())) &&
752
517k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
517k
            (require_bucket_distribution &&
754
417k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
517k
    if (num_children == 0) {
757
335k
        _use_serial_source = op->is_serial_operator();
758
335k
    }
759
    // rely on that tnodes is preorder of the plan
760
712k
    for (int i = 0; i < num_children; i++) {
761
195k
        ++*node_idx;
762
195k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
195k
                                            current_followed_by_shuffled_operator,
764
195k
                                            current_require_bucket_distribution));
765
766
        // we are expecting a child, but have used all nodes
767
        // this means we have been given a bad tree and must fail
768
195k
        if (*node_idx >= tnodes.size()) {
769
0
            return Status::InternalError(
770
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
771
0
                    "nodes: {}",
772
0
                    *node_idx, tnodes.size());
773
0
        }
774
195k
    }
775
776
517k
    return Status::OK();
777
517k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
93.7k
        PipelinePtr pipe_with_sink) {
782
93.7k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
93.7k
    pipe_with_source->set_num_tasks(_num_instances);
784
93.7k
    pipe_with_source->set_data_distribution(data_distribution);
785
93.7k
}
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
93.6k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
93.6k
    auto& operators = cur_pipe->operators();
793
93.6k
    const auto downstream_pipeline_id = cur_pipe->id();
794
93.6k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
93.6k
    DataSinkOperatorPtr sink;
797
93.6k
    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
93.6k
    const bool followed_by_shuffled_operator =
804
93.6k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
93.6k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
93.6k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
93.6k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
93.6k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
93.6k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
93.6k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
93.6k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
93.6k
    if (bucket_seq_to_instance_idx.empty() &&
813
93.6k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
7
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
7
    }
816
93.6k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
93.6k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
93.6k
                                          num_buckets, use_global_hash_shuffle,
819
93.6k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
93.6k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
93.6k
            LocalExchangeSharedState::create_shared(_num_instances);
824
93.6k
    switch (data_distribution.distribution_type) {
825
12.5k
    case ExchangeType::HASH_SHUFFLE:
826
12.5k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
12.5k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
12.5k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
12.5k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
12.5k
                        ? cast_set<int>(
831
12.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
12.5k
                        : 0);
833
12.5k
        break;
834
529
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
529
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
529
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
529
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
529
                        ? cast_set<int>(
839
529
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
529
                        : 0);
841
529
        break;
842
77.0k
    case ExchangeType::PASSTHROUGH:
843
77.0k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
77.0k
                cur_pipe->num_tasks(), _num_instances,
845
77.0k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
77.0k
                        ? cast_set<int>(
847
77.0k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
77.0k
                        : 0);
849
77.0k
        break;
850
415
    case ExchangeType::BROADCAST:
851
415
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
415
                cur_pipe->num_tasks(), _num_instances,
853
415
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
415
                        ? cast_set<int>(
855
415
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
415
                        : 0);
857
415
        break;
858
2.31k
    case ExchangeType::PASS_TO_ONE:
859
2.31k
        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
1.35k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.35k
                    cur_pipe->num_tasks(), _num_instances,
863
1.35k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.35k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.35k
                                                    .local_exchange_free_blocks_limit)
866
1.35k
                            : 0);
867
1.35k
        } else {
868
954
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
954
                    cur_pipe->num_tasks(), _num_instances,
870
954
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
954
                            ? cast_set<int>(_runtime_state->query_options()
872
954
                                                    .local_exchange_free_blocks_limit)
873
954
                            : 0);
874
954
        }
875
2.31k
        break;
876
809
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
809
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
809
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
809
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
809
                        ? cast_set<int>(
881
809
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
809
                        : 0);
883
809
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
93.6k
    }
888
93.7k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
93.7k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
93.7k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
93.7k
    _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
93.7k
    std::copy(operators.begin(), operators.begin() + idx,
898
93.7k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
93.7k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
93.7k
    OperatorPtr source_op;
905
93.7k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
93.7k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
93.7k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
93.7k
    if (!operators.empty()) {
909
40.1k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
40.1k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
40.1k
    }
912
93.7k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
93.7k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
93.7k
    std::vector<PipelineId> edges_with_source;
917
109k
    for (auto child : cur_pipe->children()) {
918
109k
        bool found = false;
919
123k
        for (auto op : new_pip->operators()) {
920
123k
            if (child->sink()->node_id() == op->node_id()) {
921
11.3k
                new_pip->set_children(child);
922
11.3k
                found = true;
923
11.3k
            };
924
123k
        }
925
109k
        if (!found) {
926
98.4k
            new_children.push_back(child);
927
98.4k
            edges_with_source.push_back(child->id());
928
98.4k
        }
929
109k
    }
930
93.7k
    new_children.push_back(new_pip);
931
93.7k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
93.7k
    if (!new_pip->children().empty()) {
935
6.46k
        std::vector<PipelineId> edges_with_sink;
936
11.3k
        for (auto child : new_pip->children()) {
937
11.3k
            edges_with_sink.push_back(child->id());
938
11.3k
        }
939
6.46k
        _dag.insert({new_pip->id(), edges_with_sink});
940
6.46k
    }
941
93.7k
    cur_pipe->set_children(new_children);
942
93.7k
    _dag[downstream_pipeline_id] = edges_with_source;
943
93.7k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
93.7k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
93.7k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
93.7k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
93.7k
    return Status::OK();
950
93.7k
}
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
156k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
156k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
32.0k
        return Status::OK();
959
32.0k
    }
960
961
124k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
44.0k
        return Status::OK();
963
44.0k
    }
964
80.4k
    *do_local_exchange = true;
965
966
80.4k
    auto& operators = cur_pipe->operators();
967
80.4k
    auto total_op_num = operators.size();
968
80.4k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
80.4k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
80.4k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
80.4k
            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
80.5k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
80.4k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
13.1k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
13.1k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
13.1k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
13.1k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
13.1k
                shuffle_idx_to_instance_idx));
990
13.1k
    }
991
80.4k
    return Status::OK();
992
80.4k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
321k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
734k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
412k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
412k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
89.0k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
89.0k
                if (child->sink()->node_id() ==
1003
89.0k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
78.0k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
78.0k
                }
1006
89.0k
            }
1007
85.4k
        }
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
412k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
412k
                                             bucket_seq_to_instance_idx,
1014
412k
                                             shuffle_idx_to_instance_idx));
1015
412k
    }
1016
321k
    return Status::OK();
1017
321k
}
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
411k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
411k
    int idx = 1;
1024
411k
    bool do_local_exchange = false;
1025
452k
    do {
1026
452k
        auto& ops = pip->operators();
1027
452k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
518k
        for (; idx < ops.size();) {
1030
106k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
95.0k
                RETURN_IF_ERROR(_add_local_exchange(
1032
95.0k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
95.0k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
95.0k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
95.0k
                        shuffle_idx_to_instance_idx));
1036
95.0k
            }
1037
106k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
40.2k
                idx = 2;
1043
40.2k
                break;
1044
40.2k
            }
1045
66.1k
            idx++;
1046
66.1k
        }
1047
452k
    } while (do_local_exchange);
1048
411k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
60.9k
        RETURN_IF_ERROR(_add_local_exchange(
1050
60.9k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
60.9k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
60.9k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
60.9k
    }
1054
411k
    return Status::OK();
1055
411k
}
1056
1057
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1058
                                                  const std::vector<TExpr>& output_exprs,
1059
                                                  const TPipelineFragmentParams& params,
1060
                                                  const RowDescriptor& row_desc,
1061
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1062
324k
                                                  PipelineId cur_pipeline_id) {
1063
324k
    switch (thrift_sink.type) {
1064
113k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
113k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
113k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
113k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
113k
                params.destinations, _fragment_instance_ids);
1071
113k
        break;
1072
113k
    }
1073
180k
    case TDataSinkType::RESULT_SINK: {
1074
180k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
180k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
180k
        int child_node_id = pipeline->operators().back()->node_id();
1080
180k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
180k
                                                      row_desc, output_exprs,
1082
180k
                                                      thrift_sink.result_sink);
1083
180k
        break;
1084
180k
    }
1085
103
    case TDataSinkType::DICTIONARY_SINK: {
1086
103
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
103
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
103
                                                    thrift_sink.dictionary_sink);
1092
103
        break;
1093
103
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
28.8k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
28.8k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
28.8k
        int child_node_id = pipeline->operators().back()->node_id();
1098
28.8k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
28.8k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
28.8k
            !config::is_cloud_mode()) {
1101
54
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
54
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
28.8k
        } else {
1104
28.8k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
28.8k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
28.8k
        }
1107
28.8k
        break;
1108
0
    }
1109
166
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
166
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
166
        DCHECK(state->get_query_ctx() != nullptr);
1112
166
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
166
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
166
                                                                output_exprs);
1115
166
        break;
1116
0
    }
1117
0
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
0
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
0
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
0
                                                         output_exprs);
1123
0
        break;
1124
0
    }
1125
0
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
0
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
0
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
0
        } else {
1133
0
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
0
                                                                row_desc, output_exprs);
1135
0
        }
1136
0
        break;
1137
0
    }
1138
0
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
0
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
0
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
0
                                                             row_desc, output_exprs);
1144
0
        break;
1145
0
    }
1146
0
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
0
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
0
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
0
                                                            output_exprs);
1152
0
        break;
1153
0
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
0
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
0
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
0
        if (config::enable_java_support) {
1167
0
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
0
                                                             output_exprs);
1169
0
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
0
        break;
1175
0
    }
1176
3
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
338
    case TDataSinkType::RESULT_FILE_SINK: {
1186
338
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
338
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
338
        } else {
1196
338
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
338
                                                              output_exprs);
1198
338
        }
1199
338
        break;
1200
338
    }
1201
613
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
613
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
613
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
613
        auto sink_id = next_sink_operator_id();
1205
613
        const int multi_cast_node_id = sink_id;
1206
613
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
613
        std::vector<int> sources;
1209
2.23k
        for (int i = 0; i < sender_size; ++i) {
1210
1.62k
            auto source_id = next_operator_id();
1211
1.62k
            sources.push_back(source_id);
1212
1.62k
        }
1213
1214
613
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
613
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
2.23k
        for (int i = 0; i < sender_size; ++i) {
1217
1.62k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
1.62k
            RowDescriptor* exchange_row_desc = nullptr;
1220
1.62k
            {
1221
1.62k
                const auto& tmp_row_desc =
1222
1.62k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
1.62k
                                ? RowDescriptor(state->desc_tbl(),
1224
1.62k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
1.62k
                                                         .output_tuple_id})
1226
1.62k
                                : row_desc;
1227
1.62k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
1.62k
            }
1229
1.62k
            auto source_id = sources[i];
1230
1.62k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
1.62k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
1.62k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
1.62k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
1.62k
                    /*operator_id=*/source_id);
1236
1.62k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
1.62k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1238
            // 2. create and set sink operator of data stream sender for new pipeline
1239
1240
1.62k
            DataSinkOperatorPtr sink_op;
1241
1.62k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
1.62k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
1.62k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
1.62k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
1.62k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
1.62k
            {
1248
1.62k
                TDataSink* t = pool->add(new TDataSink());
1249
1.62k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
1.62k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
1.62k
            }
1252
1253
            // 3. set dependency dag
1254
1.62k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
1.62k
        }
1256
613
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
613
        break;
1260
613
    }
1261
613
    case TDataSinkType::BLACKHOLE_SINK: {
1262
3
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
3
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
3
        break;
1268
3
    }
1269
0
    case TDataSinkType::TVF_TABLE_SINK: {
1270
0
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
0
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
0
                                                        output_exprs);
1275
0
        break;
1276
0
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
324k
    }
1280
323k
    return Status::OK();
1281
324k
}
1282
1283
// NOLINTBEGIN(readability-function-size)
1284
// NOLINTBEGIN(readability-function-cognitive-complexity)
1285
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1286
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1287
                                                 PipelinePtr& cur_pipe, int parent_idx,
1288
                                                 int child_idx,
1289
                                                 const bool followed_by_shuffled_operator,
1290
                                                 const bool require_bucket_distribution,
1291
519k
                                                 OperatorPtr& cache_op) {
1292
519k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
519k
    Defer defer = Defer([&]() {
1294
519k
        if (op) {
1295
519k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
519k
        }
1297
519k
        for (auto& s : sink_ops) {
1298
88.7k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
88.7k
        }
1300
519k
    });
1301
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1302
    // Therefore, here we need to use a stack-like structure.
1303
519k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
519k
    std::stringstream error_msg;
1305
519k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
519k
    bool fe_with_old_version = false;
1308
519k
    switch (tnode.node_type) {
1309
162k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
162k
        op = std::make_shared<OlapScanOperatorX>(
1311
162k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
162k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
162k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
162k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
162k
        break;
1316
162k
    }
1317
76
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
76
        DCHECK(_query_ctx != nullptr);
1319
76
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
76
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
76
                                                    _num_instances);
1322
76
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
76
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
76
        break;
1325
76
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
2.64k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
2.64k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
2.64k
                                                 _num_instances);
1342
2.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
2.64k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
2.64k
        break;
1345
2.64k
    }
1346
112k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
112k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
113k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
112k
        DCHECK_GT(num_senders, 0);
1351
112k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
112k
                                                       num_senders);
1353
112k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
112k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
112k
        break;
1356
112k
    }
1357
136k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
136k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
136k
            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
136k
        bool need_create_cache_op =
1364
136k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
136k
        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
136k
        const bool group_by_limit_opt =
1385
136k
                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
136k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
136k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
136k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
136k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
136k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
136k
        const bool can_use_distinct_streaming_agg =
1396
136k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
136k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
136k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
136k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
136k
        if (can_use_distinct_streaming_agg) {
1402
92.1k
            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
92.1k
            } else {
1413
92.1k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
92.1k
                                                                     tnode, descs);
1415
92.1k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
92.1k
            }
1417
92.1k
        } else if (is_streaming_agg) {
1418
1.25k
            if (need_create_cache_op) {
1419
0
                PipelinePtr new_pipe;
1420
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1421
0
                cache_op = op;
1422
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
0
                                                             descs);
1424
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1425
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1426
0
                cur_pipe = new_pipe;
1427
1.25k
            } else {
1428
1.25k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.25k
                                                             descs);
1430
1.25k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.25k
            }
1432
42.7k
        } else {
1433
            // create new pipeline to add query cache operator
1434
42.7k
            PipelinePtr new_pipe;
1435
42.7k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
42.7k
            if (enable_spill) {
1441
149
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
149
                                                                     next_operator_id(), descs);
1443
42.6k
            } else {
1444
42.6k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
42.6k
            }
1446
42.7k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
42.7k
            } else {
1451
42.7k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
42.7k
            }
1453
1454
42.7k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
42.7k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
41.9k
                _dag.insert({downstream_pipeline_id, {}});
1457
41.9k
            }
1458
42.7k
            cur_pipe = add_pipeline(cur_pipe);
1459
42.7k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
42.7k
            if (enable_spill) {
1462
149
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
149
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
42.6k
            } else {
1465
42.6k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
42.6k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
42.6k
            }
1468
42.7k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
42.7k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
42.7k
        }
1471
136k
        break;
1472
136k
    }
1473
136k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
67
        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
67
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
67
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
67
        const auto downstream_pipeline_id = cur_pipe->id();
1486
67
        if (!_dag.contains(downstream_pipeline_id)) {
1487
67
            _dag.insert({downstream_pipeline_id, {}});
1488
67
        }
1489
67
        cur_pipe = add_pipeline(cur_pipe);
1490
67
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
67
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
67
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
67
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
67
        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
67
        {
1503
67
            auto shared_state = BucketedAggSharedState::create_shared();
1504
67
            shared_state->id = op->operator_id();
1505
67
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
433
            for (int i = 0; i < _num_instances; i++) {
1508
366
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
366
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
366
                sink_dep->set_shared_state(shared_state.get());
1511
366
                shared_state->sink_deps.push_back(sink_dep);
1512
366
            }
1513
67
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
67
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
67
            _op_id_to_shared_state.insert(
1516
67
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
67
        }
1518
67
        break;
1519
67
    }
1520
8.82k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
8.82k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
8.82k
                                       tnode.hash_join_node.is_broadcast_join;
1523
8.82k
        const auto enable_spill = _runtime_state->enable_spill();
1524
8.82k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
8.82k
        } else {
1566
8.82k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
8.82k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
8.82k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
8.82k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.12k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.12k
            }
1573
8.82k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
8.82k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
8.82k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
8.82k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
8.82k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
8.82k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
8.82k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
8.82k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
8.82k
        }
1584
8.82k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
4.25k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
4.25k
                    HashJoinSharedState::create_shared(_num_instances);
1587
19.8k
            for (int i = 0; i < _num_instances; i++) {
1588
15.5k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
15.5k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
15.5k
                sink_dep->set_shared_state(shared_state.get());
1591
15.5k
                shared_state->sink_deps.push_back(sink_dep);
1592
15.5k
            }
1593
4.25k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
4.25k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
4.25k
            _op_id_to_shared_state.insert(
1596
4.25k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
4.25k
        }
1598
8.82k
        break;
1599
8.82k
    }
1600
2.08k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
2.08k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
2.08k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
2.08k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
2.08k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
1.84k
            _dag.insert({downstream_pipeline_id, {}});
1607
1.84k
        }
1608
2.08k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
2.08k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
2.08k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
2.08k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
2.08k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
2.08k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
2.08k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
2.08k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
2.08k
        break;
1618
2.08k
    }
1619
49.5k
    case TPlanNodeType::UNION_NODE: {
1620
49.5k
        int child_count = tnode.num_children;
1621
49.5k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
49.5k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
49.5k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
49.5k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
49.0k
            _dag.insert({downstream_pipeline_id, {}});
1627
49.0k
        }
1628
50.5k
        for (int i = 0; i < child_count; i++) {
1629
1.01k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.01k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.01k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.01k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.01k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.01k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.01k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.01k
        }
1638
49.5k
        break;
1639
49.5k
    }
1640
49.5k
    case TPlanNodeType::SORT_NODE: {
1641
31.9k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
31.9k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
31.9k
        const bool use_local_merge =
1644
31.9k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
31.9k
        if (should_spill) {
1646
7
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
31.9k
        } else if (use_local_merge) {
1648
30.0k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
30.0k
                                                                 descs);
1650
30.0k
        } else {
1651
1.84k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
1.84k
        }
1653
31.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
31.9k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
31.9k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
31.8k
            _dag.insert({downstream_pipeline_id, {}});
1658
31.8k
        }
1659
31.9k
        cur_pipe = add_pipeline(cur_pipe);
1660
31.9k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
31.9k
        if (should_spill) {
1663
7
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
7
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
31.9k
        } else {
1666
31.9k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
31.9k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
31.9k
        }
1669
31.9k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
31.9k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
31.9k
        break;
1672
31.9k
    }
1673
31.9k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.60k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.60k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.60k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.60k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.59k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.59k
        }
1698
1.60k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.60k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.60k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.60k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.60k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.60k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.60k
        break;
1706
1.60k
    }
1707
1.60k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
672
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
672
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
672
        break;
1711
672
    }
1712
672
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
297
    case TPlanNodeType::REPEAT_NODE: {
1723
297
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
297
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
297
        break;
1726
297
    }
1727
911
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
911
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
911
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
911
        break;
1731
911
    }
1732
911
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
18
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
18
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
18
        break;
1736
18
    }
1737
1.46k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.46k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.46k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.46k
        break;
1741
1.46k
    }
1742
1.46k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
265
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
265
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
265
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
265
        break;
1747
265
    }
1748
1.53k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.53k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.53k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.53k
        break;
1752
1.53k
    }
1753
4.22k
    case TPlanNodeType::META_SCAN_NODE: {
1754
4.22k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
4.22k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
4.22k
        break;
1757
4.22k
    }
1758
4.22k
    case TPlanNodeType::SELECT_NODE: {
1759
590
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
590
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
590
        break;
1762
590
    }
1763
590
    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
519k
    }
1803
519k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1804
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1805
0
        op->set_serial_operator();
1806
0
    }
1807
1808
519k
    return Status::OK();
1809
519k
}
1810
// NOLINTEND(readability-function-cognitive-complexity)
1811
// NOLINTEND(readability-function-size)
1812
1813
template <bool is_intersect>
1814
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1815
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1816
267
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
267
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
267
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
267
    const auto downstream_pipeline_id = cur_pipe->id();
1821
267
    if (!_dag.contains(downstream_pipeline_id)) {
1822
242
        _dag.insert({downstream_pipeline_id, {}});
1823
242
    }
1824
1825
895
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
628
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
628
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
628
        if (child_id == 0) {
1830
267
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
267
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
361
        } else {
1833
361
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
361
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
361
        }
1836
628
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
628
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
628
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
628
    }
1841
1842
267
    return Status::OK();
1843
267
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
134
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
134
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
134
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
134
    const auto downstream_pipeline_id = cur_pipe->id();
1821
134
    if (!_dag.contains(downstream_pipeline_id)) {
1822
118
        _dag.insert({downstream_pipeline_id, {}});
1823
118
    }
1824
1825
481
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
347
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
347
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
347
        if (child_id == 0) {
1830
134
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
134
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
213
        } else {
1833
213
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
213
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
213
        }
1836
347
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
347
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
347
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
347
    }
1841
1842
134
    return Status::OK();
1843
134
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
133
    const auto downstream_pipeline_id = cur_pipe->id();
1821
133
    if (!_dag.contains(downstream_pipeline_id)) {
1822
124
        _dag.insert({downstream_pipeline_id, {}});
1823
124
    }
1824
1825
414
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
281
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
281
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
281
        if (child_id == 0) {
1830
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
148
        } else {
1833
148
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
148
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
148
        }
1836
281
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
281
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
281
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
281
    }
1841
1842
133
    return Status::OK();
1843
133
}
1844
1845
323k
Status PipelineFragmentContext::submit() {
1846
323k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
323k
    _submitted = true;
1850
1851
323k
    int submit_tasks = 0;
1852
323k
    Status st;
1853
323k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
821k
    for (auto& task : _tasks) {
1855
1.37M
        for (auto& t : task) {
1856
1.37M
            st = scheduler->submit(t.first);
1857
1.37M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.37M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.37M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
1.37M
            submit_tasks++;
1866
1.37M
        }
1867
821k
    }
1868
323k
    if (!st.ok()) {
1869
0
        bool need_remove = false;
1870
0
        {
1871
0
            std::lock_guard<std::mutex> l(_task_mutex);
1872
0
            if (_closed_tasks >= _total_tasks) {
1873
0
                need_remove = _close_fragment_instance();
1874
0
            }
1875
0
        }
1876
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1877
0
        if (need_remove) {
1878
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1879
0
        }
1880
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1881
0
                                     BackendOptions::get_localhost());
1882
323k
    } else {
1883
323k
        return st;
1884
323k
    }
1885
323k
}
1886
1887
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1888
0
    if (_runtime_state->enable_profile()) {
1889
0
        std::stringstream ss;
1890
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1891
0
            runtime_profile_ptr->pretty_print(&ss);
1892
0
        }
1893
1894
0
        if (_runtime_state->load_channel_profile()) {
1895
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1896
0
        }
1897
1898
0
        auto profile_str =
1899
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1900
0
                            this->_fragment_id, extra_info, ss.str());
1901
0
        LOG_LONG_STRING(INFO, profile_str);
1902
0
    }
1903
0
}
1904
// If all pipeline tasks binded to the fragment instance are finished, then we could
1905
// close the fragment instance.
1906
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1907
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1908
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1909
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1910
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1911
// (via debug_string()).
1912
324k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
324k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
324k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
324k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
324k
    if (!_need_notify_close) {
1919
321k
        auto st = send_report(true);
1920
321k
        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
321k
    }
1925
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1926
    // Since stream load does not have someting like coordinator on FE, so
1927
    // backend can not report profile to FE, ant its profile can not be shown
1928
    // in the same way with other query. So we print the profile content to info log.
1929
1930
324k
    if (_runtime_state->enable_profile() &&
1931
324k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.40k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.40k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1934
0
        std::stringstream ss;
1935
        // Compute the _local_time_percent before pretty_print the runtime_profile
1936
        // Before add this operation, the print out like that:
1937
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1938
        // After add the operation, the print out like that:
1939
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1940
        // We can easily know the exec node execute time without child time consumed.
1941
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1942
0
            runtime_profile_ptr->pretty_print(&ss);
1943
0
        }
1944
1945
0
        if (_runtime_state->load_channel_profile()) {
1946
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1947
0
        }
1948
1949
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1950
0
    }
1951
1952
324k
    if (_query_ctx->enable_profile()) {
1953
2.40k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.40k
                                         collect_realtime_load_channel_profile());
1955
2.40k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
324k
    return !_need_notify_close;
1960
324k
}
1961
1962
1.37M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
1.37M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.37M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
508k
        if (_dag.contains(pipeline_id)) {
1967
278k
            for (auto dep : _dag[pipeline_id]) {
1968
278k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
278k
            }
1970
225k
        }
1971
508k
    }
1972
1.37M
    bool need_remove = false;
1973
1.37M
    {
1974
1.37M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.37M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.37M
        _query_ctx->inc_finished_task_num();
1978
1.37M
        if (_closed_tasks >= _total_tasks) {
1979
324k
            need_remove = _close_fragment_instance();
1980
324k
        }
1981
1.37M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.37M
    if (need_remove) {
1984
321k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
321k
    }
1986
1.37M
}
1987
1988
42.5k
std::string PipelineFragmentContext::get_load_error_url() {
1989
42.5k
    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
108k
    for (auto& tasks : _tasks) {
1993
185k
        for (auto& task : tasks) {
1994
185k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
160
                return to_load_error_http_path(str);
1996
160
            }
1997
185k
        }
1998
108k
    }
1999
42.3k
    return "";
2000
42.5k
}
2001
2002
42.5k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
42.5k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
108k
    for (auto& tasks : _tasks) {
2007
185k
        for (auto& task : tasks) {
2008
185k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
160
                return str;
2010
160
            }
2011
185k
        }
2012
108k
    }
2013
42.3k
    return "";
2014
42.5k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
36.8k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
36.8k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
36.8k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
36.8k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
36.8k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
36.8k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
36.8k
    });
2031
2032
36.8k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
36.8k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
36.8k
    int callback_retries = 10;
2038
36.8k
    const int sleep_ms = 1000;
2039
36.8k
    Status exec_status = req.status;
2040
36.8k
    Status coord_status;
2041
36.8k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
36.8k
    do {
2043
36.8k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
36.8k
                                                            req.coord_addr, &coord_status);
2045
36.8k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
36.8k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
36.8k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
36.8k
    TReportExecStatusParams params;
2059
36.8k
    params.protocol_version = FrontendServiceVersion::V1;
2060
36.8k
    params.__set_query_id(req.query_id);
2061
36.8k
    params.__set_backend_num(req.backend_num);
2062
36.8k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
36.8k
    params.__set_fragment_id(req.fragment_id);
2064
36.8k
    params.__set_status(exec_status.to_thrift());
2065
36.8k
    params.__set_done(req.done);
2066
36.8k
    params.__set_query_type(req.runtime_state->query_type());
2067
36.8k
    params.__isset.profile = false;
2068
2069
36.8k
    DCHECK(req.runtime_state != nullptr);
2070
2071
36.8k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
32.7k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
32.7k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
32.7k
    } else {
2075
4.02k
        DCHECK(!req.runtime_states.empty());
2076
4.02k
        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
4.02k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.02k
    }
2086
2087
36.8k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
36.8k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
36.8k
    static std::string s_unselected_rows = "unselected.rows";
2090
36.8k
    int64_t num_rows_load_success = 0;
2091
36.8k
    int64_t num_rows_load_filtered = 0;
2092
36.8k
    int64_t num_rows_load_unselected = 0;
2093
36.8k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
36.8k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
36.8k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
36.8k
    } else if (!req.runtime_states.empty()) {
2109
112k
        for (auto* rs : req.runtime_states) {
2110
112k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
112k
                rs->num_finished_range() > 0) {
2112
30.2k
                params.__isset.load_counters = true;
2113
30.2k
                num_rows_load_success += rs->num_rows_load_success();
2114
30.2k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
30.2k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
30.2k
                params.__isset.fragment_instance_reports = true;
2117
30.2k
                TFragmentInstanceReport t;
2118
30.2k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
30.2k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
30.2k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
30.2k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
30.2k
                params.fragment_instance_reports.push_back(t);
2123
30.2k
            }
2124
112k
        }
2125
36.8k
    }
2126
36.8k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
36.8k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
36.8k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
36.8k
    if (!req.load_error_url.empty()) {
2131
145
        params.__set_tracking_url(req.load_error_url);
2132
145
    }
2133
36.8k
    if (!req.first_error_msg.empty()) {
2134
145
        params.__set_first_error_msg(req.first_error_msg);
2135
145
    }
2136
112k
    for (auto* rs : req.runtime_states) {
2137
112k
        if (rs->wal_id() > 0) {
2138
107
            params.__set_txn_id(rs->wal_id());
2139
107
            params.__set_label(rs->import_label());
2140
107
        }
2141
112k
    }
2142
36.8k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
36.8k
    } else if (!req.runtime_states.empty()) {
2146
112k
        for (auto* rs : req.runtime_states) {
2147
112k
            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
112k
        }
2154
36.7k
    }
2155
36.8k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
36.8k
    } else if (!req.runtime_states.empty()) {
2159
112k
        for (auto* rs : req.runtime_states) {
2160
112k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
24.9k
                params.__isset.commitInfos = true;
2162
24.9k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
24.9k
            }
2164
112k
        }
2165
36.7k
    }
2166
36.8k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
36.8k
    } else if (!req.runtime_states.empty()) {
2170
112k
        for (auto* rs : req.runtime_states) {
2171
112k
            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
112k
        }
2177
36.7k
    }
2178
36.8k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
36.8k
    } else if (!req.runtime_states.empty()) {
2183
112k
        for (auto* rs : req.runtime_states) {
2184
112k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
0
                params.__isset.hive_partition_updates = true;
2186
0
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
0
                                                     rs_hpu.begin(), rs_hpu.end());
2188
0
            }
2189
112k
        }
2190
36.7k
    }
2191
36.8k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
36.8k
    } else if (!req.runtime_states.empty()) {
2196
112k
        for (auto* rs : req.runtime_states) {
2197
112k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
0
                params.__isset.iceberg_commit_datas = true;
2199
0
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
0
                                                   rs_icd.begin(), rs_icd.end());
2201
0
            }
2202
112k
        }
2203
36.8k
    }
2204
2205
36.8k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
36.8k
    } else if (!req.runtime_states.empty()) {
2209
112k
        for (auto* rs : req.runtime_states) {
2210
112k
            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
112k
        }
2216
36.8k
    }
2217
2218
36.8k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
36.8k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
36.8k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
36.7k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
36.7k
    }
2224
2225
36.8k
    TReportExecStatusResult res;
2226
36.8k
    Status rpc_status;
2227
2228
36.8k
    VLOG_DEBUG << "reportExecStatus params is "
2229
31
               << apache::thrift::ThriftDebugString(params).c_str();
2230
36.8k
    if (!exec_status.ok()) {
2231
1.52k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.52k
                     << " to coordinator: " << req.coord_addr
2233
1.52k
                     << ", query id: " << print_id(req.query_id);
2234
1.52k
    }
2235
36.8k
    try {
2236
36.8k
        try {
2237
36.8k
            (*coord)->reportExecStatus(res, params);
2238
36.8k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
36.8k
        rpc_status = Status::create<false>(res.status);
2254
36.8k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
36.7k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
36.7k
}
2265
2266
324k
Status PipelineFragmentContext::send_report(bool done) {
2267
324k
    Status exec_status = _query_ctx->exec_status();
2268
    // If plan is done successfully, but _is_report_success is false,
2269
    // no need to send report.
2270
    // Load will set _is_report_success to true because load wants to know
2271
    // the process.
2272
324k
    if (!_is_report_success && done && exec_status.ok()) {
2273
287k
        return Status::OK();
2274
287k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
36.8k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
74
        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
74
            return Status::OK();
2286
74
        }
2287
0
        return Status::NeedSendAgain("");
2288
74
    }
2289
2290
36.7k
    std::vector<RuntimeState*> runtime_states;
2291
2292
74.8k
    for (auto& tasks : _tasks) {
2293
112k
        for (auto& task : tasks) {
2294
112k
            runtime_states.push_back(task.second.get());
2295
112k
        }
2296
74.8k
    }
2297
2298
36.7k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
36.7k
                                        ? get_load_error_url()
2300
36.7k
                                        : _query_ctx->get_load_error_url();
2301
36.7k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
36.7k
                                          ? get_first_error_msg()
2303
36.7k
                                          : _query_ctx->get_first_error_msg();
2304
2305
36.7k
    ReportStatusRequest req {.status = exec_status,
2306
36.7k
                             .runtime_states = runtime_states,
2307
36.7k
                             .done = done || !exec_status.ok(),
2308
36.7k
                             .coord_addr = _query_ctx->coord_addr,
2309
36.7k
                             .query_id = _query_id,
2310
36.7k
                             .fragment_id = _fragment_id,
2311
36.7k
                             .fragment_instance_id = TUniqueId(),
2312
36.7k
                             .backend_num = -1,
2313
36.7k
                             .runtime_state = _runtime_state.get(),
2314
36.7k
                             .load_error_url = load_eror_url,
2315
36.7k
                             .first_error_msg = first_error_msg,
2316
36.7k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
36.7k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
36.8k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
36.8k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
36.8k
        _coordinator_callback(req);
2321
36.8k
        if (!req.done) {
2322
3.57k
            ctx->refresh_next_report_time();
2323
3.57k
        }
2324
36.8k
    });
2325
36.8k
}
2326
2327
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
0
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
0
    for (const auto& task_instances : _tasks) {
2332
0
        for (const auto& task : task_instances) {
2333
0
            if (task.first->is_running()) {
2334
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2335
0
                                      << " is running, task: " << (void*)task.first.get()
2336
0
                                      << ", is_running: " << task.first->is_running();
2337
0
                *has_running_task = true;
2338
0
                return 0;
2339
0
            }
2340
2341
0
            size_t revocable_size = task.first->get_revocable_size();
2342
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
0
                res += revocable_size;
2344
0
            }
2345
0
        }
2346
0
    }
2347
0
    return res;
2348
0
}
2349
2350
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
0
    std::vector<PipelineTask*> revocable_tasks;
2352
0
    for (const auto& task_instances : _tasks) {
2353
0
        for (const auto& task : task_instances) {
2354
0
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
0
                revocable_tasks.emplace_back(task.first.get());
2358
0
            }
2359
0
        }
2360
0
    }
2361
0
    return revocable_tasks;
2362
0
}
2363
2364
116
std::string PipelineFragmentContext::debug_string() {
2365
116
    std::lock_guard<std::mutex> l(_task_mutex);
2366
116
    fmt::memory_buffer debug_string_buffer;
2367
116
    fmt::format_to(debug_string_buffer,
2368
116
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
116
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
116
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
892
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
776
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
2.03k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
1.26k
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
1.26k
                           _tasks[j][i].first->debug_string());
2376
1.26k
        }
2377
776
    }
2378
2379
116
    return fmt::to_string(debug_string_buffer);
2380
116
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.40k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.40k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2385
2386
    // we do not have mutex to protect pipeline_id_to_profile
2387
    // so we need to make sure this funciton is invoked after fragment context
2388
    // has already been prepared.
2389
2.40k
    if (!_prepared) {
2390
0
        std::string msg =
2391
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2392
0
        DCHECK(false) << msg;
2393
0
        LOG_ERROR(msg);
2394
0
        return res;
2395
0
    }
2396
2397
    // Make sure first profile is fragment level profile
2398
2.40k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.40k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.40k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.69k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.69k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.69k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.69k
        res.push_back(profile_ptr);
2407
4.69k
    }
2408
2409
2.40k
    return res;
2410
2.40k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.40k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2414
    // we do not have mutex to protect pipeline_id_to_profile
2415
    // so we need to make sure this funciton is invoked after fragment context
2416
    // has already been prepared.
2417
2.40k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
10.2k
    for (const auto& tasks : _tasks) {
2426
20.7k
        for (const auto& task : tasks) {
2427
20.7k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
20.7k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
20.7k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
20.7k
                                                           _runtime_state->profile_level());
2435
20.7k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
20.7k
        }
2437
10.2k
    }
2438
2439
2.40k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.40k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.40k
                                                      _runtime_state->profile_level());
2442
2.40k
    return load_channel_profile;
2443
2.40k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
10.1k
    for (const auto& _task : _tasks) {
2455
18.2k
        for (const auto& task : _task) {
2456
18.2k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
18.2k
            result.merge(set);
2458
18.2k
        }
2459
10.1k
    }
2460
3.28k
    if (_runtime_state) {
2461
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.28k
        result.merge(set);
2463
3.28k
    }
2464
3.28k
    return result;
2465
3.28k
}
2466
2467
325k
void PipelineFragmentContext::_release_resource() {
2468
325k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
325k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
325k
    auto st = _query_ctx->exec_status();
2472
823k
    for (auto& _task : _tasks) {
2473
823k
        if (!_task.empty()) {
2474
823k
            _call_back(_task.front().first->runtime_state(), &st);
2475
823k
        }
2476
823k
    }
2477
325k
    _tasks.clear();
2478
325k
    _dag.clear();
2479
325k
    _pip_id_to_pipeline.clear();
2480
325k
    _pipelines.clear();
2481
325k
    _sink.reset();
2482
325k
    _root_op.reset();
2483
325k
    _runtime_filter_mgr_map.clear();
2484
325k
    _op_id_to_shared_state.clear();
2485
325k
}
2486
2487
} // namespace doris