Coverage Report

Created: 2026-06-17 17:30

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
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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"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
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#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
388k
        : _query_id(std::move(query_id)),
144
388k
          _fragment_id(request.fragment_id),
145
388k
          _exec_env(exec_env),
146
388k
          _query_ctx(std::move(query_ctx)),
147
388k
          _call_back(call_back),
148
388k
          _is_report_on_cancel(true),
149
388k
          _params(request),
150
388k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
388k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
388k
                                                               : false) {
153
388k
    _fragment_watcher.start();
154
388k
}
155
156
388k
PipelineFragmentContext::~PipelineFragmentContext() {
157
388k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
388k
            .tag("query_id", print_id(_query_id))
159
388k
            .tag("fragment_id", _fragment_id);
160
388k
    _release_resource();
161
388k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
388k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
388k
        _runtime_state.reset();
165
388k
        _query_ctx.reset();
166
388k
    }
167
388k
}
168
169
33
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
33
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
33
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
33
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
9.54k
bool PipelineFragmentContext::notify_close() {
181
9.54k
    bool all_closed = false;
182
9.54k
    bool need_remove = false;
183
9.54k
    {
184
9.54k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.54k
        if (_closed_tasks >= _total_tasks) {
186
3.42k
            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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3.37k
                need_remove = true;
193
3.37k
            }
194
3.42k
            all_closed = true;
195
3.42k
        }
196
        // make fragment release by self after cancel
197
9.54k
        _need_notify_close = false;
198
9.54k
    }
199
9.54k
    if (need_remove) {
200
3.37k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.37k
    }
202
9.54k
    return all_closed;
203
9.54k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
6.06k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.06k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.06k
            .tag("query_id", print_id(_query_id))
212
6.06k
            .tag("fragment_id", _fragment_id)
213
6.06k
            .tag("reason", reason.to_string());
214
6.06k
    if (notify_close()) {
215
72
        return;
216
72
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
5.99k
    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
5.99k
    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
5.99k
    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
5.99k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
22
        _query_ctx->set_load_error_url(error_url);
236
22
    }
237
238
5.99k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
22
        _query_ctx->set_first_error_msg(first_error_msg);
240
22
    }
241
242
5.99k
    _query_ctx->cancel(reason, _fragment_id);
243
5.99k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
306
        _is_report_on_cancel = false;
245
5.68k
    } else {
246
27.8k
        for (auto& id : _fragment_instance_ids) {
247
27.8k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
27.8k
        }
249
5.68k
    }
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
5.99k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
5.99k
    if (stream_load_ctx != nullptr) {
254
30
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
30
        stream_load_ctx->error_url = get_load_error_url();
259
30
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
30
    }
261
262
28.7k
    for (auto& tasks : _tasks) {
263
71.8k
        for (auto& task : tasks) {
264
71.8k
            task.first->unblock_all_dependencies();
265
71.8k
        }
266
28.7k
    }
267
5.99k
}
268
269
600k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
600k
    PipelineId id = _next_pipeline_id++;
271
600k
    auto pipeline = std::make_shared<Pipeline>(
272
600k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
600k
            parent ? parent->num_tasks() : _num_instances);
274
600k
    if (idx >= 0) {
275
110k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
490k
    } else {
277
490k
        _pipelines.emplace_back(pipeline);
278
490k
    }
279
600k
    if (parent) {
280
208k
        parent->set_children(pipeline);
281
208k
    }
282
600k
    return pipeline;
283
600k
}
284
285
387k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
387k
    {
287
387k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
387k
        auto root_pipeline = add_pipeline();
290
387k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
387k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
387k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
387k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
387k
                                          _params.fragment.output_exprs, _params,
299
387k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
387k
                                          *_desc_tbl, root_pipeline->id()));
301
387k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
387k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
488k
        for (PipelinePtr& pipeline : _pipelines) {
305
488k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
488k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
488k
        }
308
387k
    }
309
    // 4. Build local exchanger
310
387k
    if (_runtime_state->enable_local_shuffle()) {
311
384k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
384k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
384k
                                             _params.bucket_seq_to_instance_idx,
314
384k
                                             _params.shuffle_idx_to_instance_idx));
315
384k
    }
316
317
    // 5. Initialize global states in pipelines.
318
602k
    for (PipelinePtr& pipeline : _pipelines) {
319
602k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
602k
        pipeline->children().clear();
321
602k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
602k
    }
323
324
386k
    {
325
386k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
386k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
386k
    }
329
330
386k
    return Status::OK();
331
386k
}
332
333
388k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
388k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
388k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
388k
        _timeout = _params.query_options.execution_timeout;
339
388k
    }
340
341
388k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
388k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
388k
    SCOPED_TIMER(_prepare_timer);
344
388k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
388k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
388k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
388k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
388k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
388k
    {
350
388k
        SCOPED_TIMER(_init_context_timer);
351
388k
        cast_set(_num_instances, _params.local_params.size());
352
388k
        _total_instances =
353
388k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
388k
        auto* fragment_context = this;
356
357
388k
        if (_params.query_options.__isset.is_report_success) {
358
385k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
385k
        }
360
361
        // 1. Set up the global runtime state.
362
388k
        _runtime_state = RuntimeState::create_unique(
363
388k
                _params.query_id, _params.fragment_id, _params.query_options,
364
388k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
388k
        _runtime_state->set_task_execution_context(shared_from_this());
366
388k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
388k
        if (_params.__isset.backend_id) {
368
384k
            _runtime_state->set_backend_id(_params.backend_id);
369
384k
        }
370
388k
        if (_params.__isset.import_label) {
371
238
            _runtime_state->set_import_label(_params.import_label);
372
238
        }
373
388k
        if (_params.__isset.db_name) {
374
190
            _runtime_state->set_db_name(_params.db_name);
375
190
        }
376
388k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
388k
        if (_params.is_simplified_param) {
381
132k
            _desc_tbl = _query_ctx->desc_tbl;
382
256k
        } else {
383
256k
            DCHECK(_params.__isset.desc_tbl);
384
256k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
256k
                                                  &_desc_tbl));
386
256k
        }
387
388k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
388k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
388k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
388k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
388k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
388k
        const auto target_size = _params.local_params.size();
395
388k
        _fragment_instance_ids.resize(target_size);
396
1.43M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.04M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.04M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.04M
        }
400
388k
    }
401
402
388k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
387k
    _init_next_report_time();
405
406
387k
    _prepared = true;
407
387k
    return Status::OK();
408
388k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.04M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.04M
    const auto& local_params = _params.local_params[instance_idx];
414
1.04M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.04M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.04M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.04M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.04M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.75M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.75M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.75M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.75M
                shared_state_map;
423
2.26M
        for (auto& op : pipeline->operators()) {
424
2.26M
            auto source_id = op->operator_id();
425
2.26M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.26M
                iter != _op_id_to_shared_state.end()) {
427
720k
                shared_state_map.insert({source_id, iter->second});
428
720k
            }
429
2.26M
        }
430
1.75M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.75M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.75M
                iter != _op_id_to_shared_state.end()) {
433
328k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
328k
            }
435
1.75M
        }
436
1.75M
        return shared_state_map;
437
1.75M
    };
438
439
3.18M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.13M
        auto& pipeline = _pipelines[pip_idx];
441
2.13M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.74M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.74M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.74M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.74M
            {
446
                // Initialize runtime state for this task
447
1.74M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.74M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.74M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.75M
                if (_params.__isset.backend_id) {
453
1.75M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.75M
                }
455
1.74M
                if (_params.__isset.import_label) {
456
239
                    task_runtime_state->set_import_label(_params.import_label);
457
239
                }
458
1.74M
                if (_params.__isset.db_name) {
459
191
                    task_runtime_state->set_db_name(_params.db_name);
460
191
                }
461
1.74M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.74M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.74M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.74M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.74M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.74M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.74M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.74M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.74M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.74M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.74M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.74M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.74M
            }
482
1.74M
            auto cur_task_id = _total_tasks++;
483
1.74M
            task_runtime_state->set_task_id(cur_task_id);
484
1.74M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.74M
            auto task = std::make_shared<PipelineTask>(
486
1.74M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.74M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.74M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.74M
                    instance_idx);
490
1.74M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.74M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.74M
            _tasks[instance_idx].emplace_back(
493
1.74M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.74M
                            std::move(task), std::move(task_runtime_state)});
495
1.74M
        }
496
2.13M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
2.13M
    for (auto& _pipeline : _pipelines) {
516
2.13M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.74M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.74M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.74M
            if (_dag.contains(_pipeline->id())) {
522
1.11M
                auto& deps = _dag[_pipeline->id()];
523
1.80M
                for (auto& dep : deps) {
524
1.80M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.02M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.02M
                        if (ss) {
527
372k
                            task->inject_shared_state(ss);
528
650k
                        } else {
529
650k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
650k
                                    task->get_source_shared_state());
531
650k
                        }
532
1.02M
                    }
533
1.80M
                }
534
1.11M
            }
535
1.74M
        }
536
2.13M
    }
537
3.18M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.13M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.74M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.74M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.74M
            std::vector<TScanRangeParams> scan_ranges;
542
1.74M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.74M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
290k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
290k
            }
546
1.74M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.74M
                                                             _params.fragment.output_sink));
548
1.74M
        }
549
2.13M
    }
550
1.05M
    {
551
1.05M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.05M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.05M
    }
554
1.05M
    return Status::OK();
555
1.04M
}
556
557
387k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
387k
    _total_tasks = 0;
559
387k
    _closed_tasks = 0;
560
387k
    const auto target_size = _params.local_params.size();
561
387k
    _tasks.resize(target_size);
562
387k
    _runtime_filter_mgr_map.resize(target_size);
563
988k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
600k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
600k
    }
566
387k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
387k
    if (target_size > 1 &&
569
387k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
129k
         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
21.7k
        std::vector<Status> prepare_status(target_size);
573
21.7k
        int submitted_tasks = 0;
574
21.7k
        Status submit_status;
575
21.7k
        CountDownLatch latch((int)target_size);
576
262k
        for (int i = 0; i < target_size; i++) {
577
240k
            submit_status = thread_pool->submit_func([&, i]() {
578
240k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
240k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
240k
                latch.count_down();
581
240k
            });
582
240k
            if (LIKELY(submit_status.ok())) {
583
240k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
240k
        }
588
21.7k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
21.7k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
262k
        for (int i = 0; i < submitted_tasks; i++) {
593
240k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
240k
        }
597
365k
    } else {
598
1.17M
        for (int i = 0; i < target_size; i++) {
599
806k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
806k
        }
601
365k
    }
602
387k
    _pipeline_parent_map.clear();
603
387k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
387k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
387k
    return Status::OK();
608
387k
}
609
610
385k
void PipelineFragmentContext::_init_next_report_time() {
611
385k
    auto interval_s = config::pipeline_status_report_interval;
612
385k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
37.5k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
37.5k
        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
37.5k
        _previous_report_time =
617
37.5k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
37.5k
        _disable_period_report = false;
619
37.5k
    }
620
385k
}
621
622
4.31k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.31k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.31k
    DCHECK(disable == true);
625
4.31k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.31k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.31k
}
628
629
6.36M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
6.36M
    if (!_is_report_success) {
631
5.96M
        return;
632
5.96M
    }
633
396k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
396k
    if (disable) {
635
7.50k
        return;
636
7.50k
    }
637
389k
    int32_t interval_s = config::pipeline_status_report_interval;
638
389k
    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
389k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
389k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
389k
    if (MonotonicNanos() > next_report_time) {
646
4.32k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.32k
                                                            std::memory_order_acq_rel)) {
648
12
            return;
649
12
        }
650
4.31k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
4.31k
        auto st = send_report(false);
667
4.31k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
4.31k
    }
673
389k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
384k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
384k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
384k
    int node_idx = 0;
682
683
384k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
384k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
384k
    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
384k
    return Status::OK();
691
384k
}
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
584k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
584k
    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
584k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
584k
    int num_children = tnodes[*node_idx].num_children;
706
584k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
584k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
584k
    OperatorPtr op = nullptr;
710
584k
    OperatorPtr cache_op = nullptr;
711
584k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
584k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
584k
                                     followed_by_shuffled_operator,
714
584k
                                     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
584k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
584k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
198k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
385k
    } else {
723
385k
        *root = op;
724
385k
    }
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
584k
    auto required_data_distribution =
737
584k
            cur_pipe->operators().empty()
738
584k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
584k
                    : op->required_data_distribution(_runtime_state.get());
740
584k
    current_followed_by_shuffled_operator =
741
584k
            ((followed_by_shuffled_operator ||
742
584k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
527k
                                             : op->is_shuffled_operator())) &&
744
584k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
584k
            (followed_by_shuffled_operator &&
746
473k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
584k
    current_require_bucket_distribution =
749
584k
            ((require_bucket_distribution ||
750
584k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
531k
                                             : op->is_colocated_operator())) &&
752
584k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
584k
            (require_bucket_distribution &&
754
480k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
584k
    if (num_children == 0) {
757
401k
        _use_serial_source = op->is_serial_operator();
758
401k
    }
759
    // rely on that tnodes is preorder of the plan
760
783k
    for (int i = 0; i < num_children; i++) {
761
199k
        ++*node_idx;
762
199k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
199k
                                            current_followed_by_shuffled_operator,
764
199k
                                            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
199k
        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
199k
    }
775
776
584k
    return Status::OK();
777
584k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
110k
        PipelinePtr pipe_with_sink) {
782
110k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
110k
    pipe_with_source->set_num_tasks(_num_instances);
784
110k
    pipe_with_source->set_data_distribution(data_distribution);
785
110k
}
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
110k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
110k
    auto& operators = cur_pipe->operators();
793
110k
    const auto downstream_pipeline_id = cur_pipe->id();
794
110k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
110k
    DataSinkOperatorPtr sink;
797
110k
    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
110k
    const bool followed_by_shuffled_operator =
804
110k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
110k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
110k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
110k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
110k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
110k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
110k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
110k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
110k
    if (bucket_seq_to_instance_idx.empty() &&
813
110k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
5
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
5
    }
816
110k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
110k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
110k
                                          num_buckets, use_global_hash_shuffle,
819
110k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
110k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
110k
            LocalExchangeSharedState::create_shared(_num_instances);
824
110k
    switch (data_distribution.distribution_type) {
825
22.7k
    case ExchangeType::HASH_SHUFFLE:
826
22.7k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
22.7k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
22.7k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
22.7k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
22.7k
                        ? cast_set<int>(
831
22.6k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
22.7k
                        : 0);
833
22.7k
        break;
834
505
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
505
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
505
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
505
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
505
                        ? cast_set<int>(
839
505
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
505
                        : 0);
841
505
        break;
842
84.2k
    case ExchangeType::PASSTHROUGH:
843
84.2k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
84.2k
                cur_pipe->num_tasks(), _num_instances,
845
84.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
84.2k
                        ? cast_set<int>(
847
84.2k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
84.2k
                        : 0);
849
84.2k
        break;
850
331
    case ExchangeType::BROADCAST:
851
331
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
331
                cur_pipe->num_tasks(), _num_instances,
853
331
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
331
                        ? cast_set<int>(
855
331
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
331
                        : 0);
857
331
        break;
858
2.25k
    case ExchangeType::PASS_TO_ONE:
859
2.25k
        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
1.25k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.25k
                    cur_pipe->num_tasks(), _num_instances,
863
1.25k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.25k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.25k
                                                    .local_exchange_free_blocks_limit)
866
1.25k
                            : 0);
867
1.25k
        } else {
868
1.00k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.00k
                    cur_pipe->num_tasks(), _num_instances,
870
1.00k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.00k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.00k
                                                    .local_exchange_free_blocks_limit)
873
1.00k
                            : 0);
874
1.00k
        }
875
2.25k
        break;
876
787
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
787
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
787
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
787
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
787
                        ? cast_set<int>(
881
786
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
787
                        : 0);
883
787
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
110k
    }
888
111k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
111k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
111k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
111k
    _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
111k
    std::copy(operators.begin(), operators.begin() + idx,
898
111k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
111k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
111k
    OperatorPtr source_op;
905
111k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
111k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
111k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
111k
    if (!operators.empty()) {
909
41.0k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
41.0k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
41.0k
    }
912
111k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
111k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
111k
    std::vector<PipelineId> edges_with_source;
917
127k
    for (auto child : cur_pipe->children()) {
918
127k
        bool found = false;
919
142k
        for (auto op : new_pip->operators()) {
920
142k
            if (child->sink()->node_id() == op->node_id()) {
921
12.2k
                new_pip->set_children(child);
922
12.2k
                found = true;
923
12.2k
            };
924
142k
        }
925
127k
        if (!found) {
926
115k
            new_children.push_back(child);
927
115k
            edges_with_source.push_back(child->id());
928
115k
        }
929
127k
    }
930
111k
    new_children.push_back(new_pip);
931
111k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
111k
    if (!new_pip->children().empty()) {
935
6.97k
        std::vector<PipelineId> edges_with_sink;
936
12.2k
        for (auto child : new_pip->children()) {
937
12.2k
            edges_with_sink.push_back(child->id());
938
12.2k
        }
939
6.97k
        _dag.insert({new_pip->id(), edges_with_sink});
940
6.97k
    }
941
111k
    cur_pipe->set_children(new_children);
942
111k
    _dag[downstream_pipeline_id] = edges_with_source;
943
111k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
111k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
111k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
111k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
111k
    return Status::OK();
950
111k
}
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
173k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
173k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
39.2k
        return Status::OK();
959
39.2k
    }
960
961
133k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
45.8k
        return Status::OK();
963
45.8k
    }
964
88.0k
    *do_local_exchange = true;
965
966
88.0k
    auto& operators = cur_pipe->operators();
967
88.0k
    auto total_op_num = operators.size();
968
88.0k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
88.0k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
88.0k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
88.0k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
88.0k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
98
            << "total_op_num: " << total_op_num
975
98
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
98
            << " 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
88.0k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
88.0k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
22.9k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
22.9k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
22.9k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
22.9k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
22.9k
                shuffle_idx_to_instance_idx));
990
22.9k
    }
991
88.0k
    return Status::OK();
992
88.0k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
383k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
869k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
486k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
486k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
98.1k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
98.1k
                if (child->sink()->node_id() ==
1003
98.1k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
84.7k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
84.7k
                }
1006
98.1k
            }
1007
93.4k
        }
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
486k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
486k
                                             bucket_seq_to_instance_idx,
1014
486k
                                             shuffle_idx_to_instance_idx));
1015
486k
    }
1016
383k
    return Status::OK();
1017
383k
}
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
485k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
485k
    int idx = 1;
1024
485k
    bool do_local_exchange = false;
1025
527k
    do {
1026
527k
        auto& ops = pip->operators();
1027
527k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
587k
        for (; idx < ops.size();) {
1030
101k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
95.9k
                RETURN_IF_ERROR(_add_local_exchange(
1032
95.9k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
95.9k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
95.9k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
95.9k
                        shuffle_idx_to_instance_idx));
1036
95.9k
            }
1037
101k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
41.2k
                idx = 2;
1043
41.2k
                break;
1044
41.2k
            }
1045
60.5k
            idx++;
1046
60.5k
        }
1047
527k
    } while (do_local_exchange);
1048
485k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
76.7k
        RETURN_IF_ERROR(_add_local_exchange(
1050
76.7k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
76.7k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
76.7k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
76.7k
    }
1054
485k
    return Status::OK();
1055
485k
}
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
387k
                                                  PipelineId cur_pipeline_id) {
1063
387k
    switch (thrift_sink.type) {
1064
130k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
130k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
130k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
130k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
130k
                params.destinations, _fragment_instance_ids);
1071
130k
        break;
1072
130k
    }
1073
221k
    case TDataSinkType::RESULT_SINK: {
1074
221k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
221k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
221k
        int child_node_id = pipeline->operators().back()->node_id();
1080
221k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
221k
                                                      row_desc, output_exprs,
1082
221k
                                                      thrift_sink.result_sink);
1083
221k
        break;
1084
221k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
31.7k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
31.7k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
31.7k
        int child_node_id = pipeline->operators().back()->node_id();
1098
31.7k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
31.7k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
31.7k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
1.44k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
1.44k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
30.3k
        } else {
1104
30.3k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
30.3k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
30.3k
        }
1107
31.7k
        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
742
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
742
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
742
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
742
                                                         output_exprs);
1123
742
        break;
1124
742
    }
1125
868
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
868
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
868
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
2
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
2
                                                                     row_desc, output_exprs);
1132
866
        } else {
1133
866
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
866
                                                                row_desc, output_exprs);
1135
866
        }
1136
868
        break;
1137
868
    }
1138
10
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
10
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
10
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
10
                                                             row_desc, output_exprs);
1144
10
        break;
1145
10
    }
1146
40
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
40
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
40
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
40
                                                            output_exprs);
1152
40
        break;
1153
40
    }
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
44
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
44
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
44
        if (config::enable_java_support) {
1167
44
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
44
                                                             output_exprs);
1169
44
        } 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
44
        break;
1175
44
    }
1176
44
    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
420
    case TDataSinkType::RESULT_FILE_SINK: {
1186
420
        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
420
        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
420
        } else {
1196
420
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
420
                                                              output_exprs);
1198
420
        }
1199
420
        break;
1200
420
    }
1201
1.51k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
1.51k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
1.51k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
1.51k
        auto sink_id = next_sink_operator_id();
1205
1.51k
        const int multi_cast_node_id = sink_id;
1206
1.51k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
1.51k
        std::vector<int> sources;
1209
5.86k
        for (int i = 0; i < sender_size; ++i) {
1210
4.34k
            auto source_id = next_operator_id();
1211
4.34k
            sources.push_back(source_id);
1212
4.34k
        }
1213
1214
1.51k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
1.51k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
5.86k
        for (int i = 0; i < sender_size; ++i) {
1217
4.34k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
4.34k
            RowDescriptor* exchange_row_desc = nullptr;
1220
4.34k
            {
1221
4.34k
                const auto& tmp_row_desc =
1222
4.34k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
4.34k
                                ? RowDescriptor(state->desc_tbl(),
1224
4.34k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
4.34k
                                                         .output_tuple_id})
1226
4.34k
                                : row_desc;
1227
4.34k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
4.34k
            }
1229
4.34k
            auto source_id = sources[i];
1230
4.34k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
4.34k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
4.34k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
4.34k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
4.34k
                    /*operator_id=*/source_id);
1236
4.34k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
4.34k
                    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
4.34k
            DataSinkOperatorPtr sink_op;
1241
4.34k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
4.34k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
4.34k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
4.34k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
4.34k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
4.34k
            {
1248
4.34k
                TDataSink* t = pool->add(new TDataSink());
1249
4.34k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
4.34k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
4.34k
            }
1252
1253
            // 3. set dependency dag
1254
4.34k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
4.34k
        }
1256
1.51k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
1.51k
        break;
1260
1.51k
    }
1261
1.51k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
8
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
8
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
8
        break;
1268
8
    }
1269
78
    case TDataSinkType::TVF_TABLE_SINK: {
1270
78
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
78
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
78
                                                        output_exprs);
1275
78
        break;
1276
78
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
387k
    }
1280
386k
    return Status::OK();
1281
387k
}
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
587k
                                                 OperatorPtr& cache_op) {
1292
587k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
587k
    Defer defer = Defer([&]() {
1294
585k
        if (op) {
1295
585k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
585k
        }
1297
585k
        for (auto& s : sink_ops) {
1298
97.7k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
97.7k
        }
1300
585k
    });
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
587k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
587k
    std::stringstream error_msg;
1305
587k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
587k
    bool fe_with_old_version = false;
1308
587k
    switch (tnode.node_type) {
1309
191k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
191k
        op = std::make_shared<OlapScanOperatorX>(
1311
191k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
191k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
191k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
191k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
191k
        break;
1316
191k
    }
1317
77
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
77
        DCHECK(_query_ctx != nullptr);
1319
77
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
77
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
77
                                                    _num_instances);
1322
77
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
77
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
77
        break;
1325
77
    }
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
14.3k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
14.3k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
14.3k
                                                 _num_instances);
1342
14.3k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
14.3k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
14.3k
        break;
1345
14.3k
    }
1346
132k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
132k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
132k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
132k
        DCHECK_GT(num_senders, 0);
1351
132k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
132k
                                                       num_senders);
1353
132k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
132k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
132k
        break;
1356
132k
    }
1357
126k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
126k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
126k
            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
126k
        bool need_create_cache_op =
1364
126k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
126k
        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
126k
        const bool group_by_limit_opt =
1385
126k
                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
126k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
126k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
126k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
126k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
126k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
126k
        const bool can_use_distinct_streaming_agg =
1396
126k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
126k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
126k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
126k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
126k
        if (can_use_distinct_streaming_agg) {
1402
82.9k
            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
82.9k
            } else {
1413
82.9k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
82.9k
                                                                     tnode, descs);
1415
82.9k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
82.9k
            }
1417
82.9k
        } else if (is_streaming_agg) {
1418
1.49k
            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
1.49k
            } else {
1428
1.49k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.49k
                                                             descs);
1430
1.49k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.49k
            }
1432
42.2k
        } else {
1433
            // create new pipeline to add query cache operator
1434
42.2k
            PipelinePtr new_pipe;
1435
42.2k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
42.2k
            if (enable_spill) {
1441
61
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
61
                                                                     next_operator_id(), descs);
1443
42.1k
            } else {
1444
42.1k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
42.1k
            }
1446
42.2k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
42.2k
            } else {
1451
42.2k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
42.2k
            }
1453
1454
42.2k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
42.2k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
40.1k
                _dag.insert({downstream_pipeline_id, {}});
1457
40.1k
            }
1458
42.2k
            cur_pipe = add_pipeline(cur_pipe);
1459
42.2k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
42.2k
            if (enable_spill) {
1462
61
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
61
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
42.1k
            } else {
1465
42.1k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
42.1k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
42.1k
            }
1468
42.2k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
42.2k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
42.2k
        }
1471
126k
        break;
1472
126k
    }
1473
126k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
77
        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
77
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
77
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
77
        const auto downstream_pipeline_id = cur_pipe->id();
1486
77
        if (!_dag.contains(downstream_pipeline_id)) {
1487
77
            _dag.insert({downstream_pipeline_id, {}});
1488
77
        }
1489
77
        cur_pipe = add_pipeline(cur_pipe);
1490
77
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
77
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
77
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
77
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
77
        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
77
        {
1503
77
            auto shared_state = BucketedAggSharedState::create_shared();
1504
77
            shared_state->id = op->operator_id();
1505
77
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
534
            for (int i = 0; i < _num_instances; i++) {
1508
457
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
457
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
457
                sink_dep->set_shared_state(shared_state.get());
1511
457
                shared_state->sink_deps.push_back(sink_dep);
1512
457
            }
1513
77
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
77
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
77
            _op_id_to_shared_state.insert(
1516
77
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
77
        }
1518
77
        break;
1519
77
    }
1520
9.37k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.37k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.37k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.37k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.37k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
9.37k
        } else {
1566
9.37k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.37k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.37k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.37k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.68k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.68k
            }
1573
9.37k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.37k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.37k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.37k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.37k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.37k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.37k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.37k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.37k
        }
1584
9.37k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.55k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.55k
                    HashJoinSharedState::create_shared(_num_instances);
1587
15.9k
            for (int i = 0; i < _num_instances; i++) {
1588
13.3k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
13.3k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
13.3k
                sink_dep->set_shared_state(shared_state.get());
1591
13.3k
                shared_state->sink_deps.push_back(sink_dep);
1592
13.3k
            }
1593
2.55k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.55k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.55k
            _op_id_to_shared_state.insert(
1596
2.55k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.55k
        }
1598
9.37k
        break;
1599
9.37k
    }
1600
3.97k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
3.97k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
3.97k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
3.97k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
3.97k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
3.74k
            _dag.insert({downstream_pipeline_id, {}});
1607
3.74k
        }
1608
3.97k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
3.97k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
3.97k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
3.97k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
3.97k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
3.97k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
3.97k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
3.97k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
3.97k
        break;
1618
3.97k
    }
1619
52.0k
    case TPlanNodeType::UNION_NODE: {
1620
52.0k
        int child_count = tnode.num_children;
1621
52.0k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
52.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
52.0k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
52.0k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
51.6k
            _dag.insert({downstream_pipeline_id, {}});
1627
51.6k
        }
1628
53.3k
        for (int i = 0; i < child_count; i++) {
1629
1.21k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.21k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.21k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.21k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.21k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.21k
            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
1.21k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.21k
        }
1638
52.0k
        break;
1639
52.0k
    }
1640
52.0k
    case TPlanNodeType::SORT_NODE: {
1641
39.2k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
39.2k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
39.2k
        const bool use_local_merge =
1644
39.2k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
39.2k
        if (should_spill) {
1646
7
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
39.2k
        } else if (use_local_merge) {
1648
37.1k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
37.1k
                                                                 descs);
1650
37.1k
        } else {
1651
2.10k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.10k
        }
1653
39.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
39.2k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
39.2k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
39.1k
            _dag.insert({downstream_pipeline_id, {}});
1658
39.1k
        }
1659
39.2k
        cur_pipe = add_pipeline(cur_pipe);
1660
39.2k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
39.2k
        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
39.2k
        } else {
1666
39.2k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
39.2k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
39.2k
        }
1669
39.2k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
39.2k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
39.2k
        break;
1672
39.2k
    }
1673
39.2k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
63
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
63
        const auto downstream_pipeline_id = cur_pipe->id();
1678
63
        if (!_dag.contains(downstream_pipeline_id)) {
1679
63
            _dag.insert({downstream_pipeline_id, {}});
1680
63
        }
1681
63
        cur_pipe = add_pipeline(cur_pipe);
1682
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
63
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
63
        break;
1689
63
    }
1690
1.62k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.62k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.62k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.62k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.62k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.61k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.61k
        }
1698
1.62k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.62k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.62k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.62k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.62k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.62k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.62k
        break;
1706
1.62k
    }
1707
1.62k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.18k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.18k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.18k
        break;
1711
1.18k
    }
1712
1.18k
    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
314
    case TPlanNodeType::REPEAT_NODE: {
1723
314
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
314
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
314
        break;
1726
314
    }
1727
912
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
912
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
912
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
912
        break;
1731
912
    }
1732
912
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
118
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
118
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
118
        break;
1736
118
    }
1737
1.58k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.58k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.58k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.58k
        break;
1741
1.58k
    }
1742
1.58k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
371
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
371
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
371
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
371
        break;
1747
371
    }
1748
1.81k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.81k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.81k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.81k
        break;
1752
1.81k
    }
1753
6.00k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.00k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.00k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.00k
        break;
1757
6.00k
    }
1758
6.00k
    case TPlanNodeType::SELECT_NODE: {
1759
1.52k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
1.52k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
1.52k
        break;
1762
1.52k
    }
1763
1.52k
    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
587k
    }
1803
584k
    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
584k
    return Status::OK();
1809
587k
}
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
384k
Status PipelineFragmentContext::submit() {
1846
384k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
384k
    _submitted = true;
1850
1851
384k
    int submit_tasks = 0;
1852
384k
    Status st;
1853
384k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.04M
    for (auto& task : _tasks) {
1855
1.75M
        for (auto& t : task) {
1856
1.75M
            st = scheduler->submit(t.first);
1857
1.75M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.75M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.75M
            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
1.75M
            submit_tasks++;
1866
1.75M
        }
1867
1.04M
    }
1868
384k
    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
384k
    } else {
1883
384k
        return st;
1884
384k
    }
1885
384k
}
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
387k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
387k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
387k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
387k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
387k
    if (!_need_notify_close) {
1919
384k
        auto st = send_report(true);
1920
384k
        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
384k
    }
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
387k
    if (_runtime_state->enable_profile() &&
1931
387k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.58k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.58k
         _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
387k
    if (_query_ctx->enable_profile()) {
1953
2.58k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.58k
                                         collect_realtime_load_channel_profile());
1955
2.58k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
387k
    return !_need_notify_close;
1960
387k
}
1961
1962
1.74M
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
1.74M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.74M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
601k
        if (_dag.contains(pipeline_id)) {
1967
324k
            for (auto dep : _dag[pipeline_id]) {
1968
324k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
324k
            }
1970
255k
        }
1971
601k
    }
1972
1.74M
    bool need_remove = false;
1973
1.74M
    {
1974
1.74M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.74M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.74M
        _query_ctx->inc_finished_task_num();
1978
1.74M
        if (_closed_tasks >= _total_tasks) {
1979
387k
            need_remove = _close_fragment_instance();
1980
387k
        }
1981
1.74M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.74M
    if (need_remove) {
1984
384k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
384k
    }
1986
1.74M
}
1987
1988
49.3k
std::string PipelineFragmentContext::get_load_error_url() {
1989
49.3k
    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
119k
    for (auto& tasks : _tasks) {
1993
201k
        for (auto& task : tasks) {
1994
201k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
186
                return to_load_error_http_path(str);
1996
186
            }
1997
201k
        }
1998
119k
    }
1999
49.1k
    return "";
2000
49.3k
}
2001
2002
49.2k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
49.2k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
119k
    for (auto& tasks : _tasks) {
2007
200k
        for (auto& task : tasks) {
2008
200k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
186
                return str;
2010
186
            }
2011
200k
        }
2012
119k
    }
2013
49.1k
    return "";
2014
49.2k
}
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
43.2k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
43.2k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
43.2k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
43.2k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
43.2k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
43.2k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
43.2k
    });
2031
2032
43.2k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
43.2k
    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
43.2k
    int callback_retries = 10;
2038
43.2k
    const int sleep_ms = 1000;
2039
43.2k
    Status exec_status = req.status;
2040
43.2k
    Status coord_status;
2041
43.2k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
43.2k
    do {
2043
43.2k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
43.2k
                                                            req.coord_addr, &coord_status);
2045
43.2k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
43.2k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
43.2k
    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
43.2k
    TReportExecStatusParams params;
2059
43.2k
    params.protocol_version = FrontendServiceVersion::V1;
2060
43.2k
    params.__set_query_id(req.query_id);
2061
43.2k
    params.__set_backend_num(req.backend_num);
2062
43.2k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
43.2k
    params.__set_fragment_id(req.fragment_id);
2064
43.2k
    params.__set_status(exec_status.to_thrift());
2065
43.2k
    params.__set_done(req.done);
2066
43.2k
    params.__set_query_type(req.runtime_state->query_type());
2067
43.2k
    params.__isset.profile = false;
2068
2069
43.2k
    DCHECK(req.runtime_state != nullptr);
2070
2071
43.2k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
38.8k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
38.8k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
38.8k
    } else {
2075
4.46k
        DCHECK(!req.runtime_states.empty());
2076
4.46k
        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
4.46k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.46k
    }
2086
2087
43.2k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
43.2k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
43.2k
    static std::string s_unselected_rows = "unselected.rows";
2090
43.2k
    int64_t num_rows_load_success = 0;
2091
43.2k
    int64_t num_rows_load_filtered = 0;
2092
43.2k
    int64_t num_rows_load_unselected = 0;
2093
43.2k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
43.2k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
43.3k
        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
43.2k
    } else if (!req.runtime_states.empty()) {
2109
129k
        for (auto* rs : req.runtime_states) {
2110
129k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
129k
                rs->num_finished_range() > 0) {
2112
34.1k
                params.__isset.load_counters = true;
2113
34.1k
                num_rows_load_success += rs->num_rows_load_success();
2114
34.1k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
34.1k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
34.1k
                params.__isset.fragment_instance_reports = true;
2117
34.1k
                TFragmentInstanceReport t;
2118
34.1k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
34.1k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
34.1k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
34.1k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
34.1k
                params.fragment_instance_reports.push_back(t);
2123
34.1k
            }
2124
129k
        }
2125
43.2k
    }
2126
43.2k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
43.2k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
43.2k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
43.2k
    if (!req.load_error_url.empty()) {
2131
173
        params.__set_tracking_url(req.load_error_url);
2132
173
    }
2133
43.2k
    if (!req.first_error_msg.empty()) {
2134
173
        params.__set_first_error_msg(req.first_error_msg);
2135
173
    }
2136
129k
    for (auto* rs : req.runtime_states) {
2137
129k
        if (rs->wal_id() > 0) {
2138
108
            params.__set_txn_id(rs->wal_id());
2139
108
            params.__set_label(rs->import_label());
2140
108
        }
2141
129k
    }
2142
43.2k
    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
43.2k
    } else if (!req.runtime_states.empty()) {
2146
129k
        for (auto* rs : req.runtime_states) {
2147
129k
            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
129k
        }
2154
43.2k
    }
2155
43.2k
    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
43.2k
    } else if (!req.runtime_states.empty()) {
2159
129k
        for (auto* rs : req.runtime_states) {
2160
129k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
26.5k
                params.__isset.commitInfos = true;
2162
26.5k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
26.5k
            }
2164
129k
        }
2165
43.2k
    }
2166
43.2k
    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
43.2k
    } else if (!req.runtime_states.empty()) {
2170
129k
        for (auto* rs : req.runtime_states) {
2171
129k
            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
129k
        }
2177
43.2k
    }
2178
43.2k
    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
43.2k
    } else if (!req.runtime_states.empty()) {
2183
129k
        for (auto* rs : req.runtime_states) {
2184
129k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
1.07k
                params.__isset.hive_partition_updates = true;
2186
1.07k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
1.07k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
1.07k
            }
2189
129k
        }
2190
43.2k
    }
2191
43.2k
    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
43.2k
    } else if (!req.runtime_states.empty()) {
2196
129k
        for (auto* rs : req.runtime_states) {
2197
129k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
1.03k
                params.__isset.iceberg_commit_datas = true;
2199
1.03k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
1.03k
                                                   rs_icd.begin(), rs_icd.end());
2201
1.03k
            }
2202
129k
        }
2203
43.2k
    }
2204
2205
43.2k
    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
43.2k
    } else if (!req.runtime_states.empty()) {
2209
129k
        for (auto* rs : req.runtime_states) {
2210
129k
            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
129k
        }
2216
43.2k
    }
2217
2218
43.2k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
43.2k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
43.2k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
43.2k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
43.2k
    }
2224
2225
43.2k
    TReportExecStatusResult res;
2226
43.2k
    Status rpc_status;
2227
2228
43.2k
    VLOG_DEBUG << "reportExecStatus params is "
2229
24
               << apache::thrift::ThriftDebugString(params).c_str();
2230
43.2k
    if (!exec_status.ok()) {
2231
1.61k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.61k
                     << " to coordinator: " << req.coord_addr
2233
1.61k
                     << ", query id: " << print_id(req.query_id);
2234
1.61k
    }
2235
43.2k
    try {
2236
43.2k
        try {
2237
43.2k
            (*coord)->reportExecStatus(res, params);
2238
43.2k
        } 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
43.2k
        rpc_status = Status::create<false>(res.status);
2254
43.2k
    } 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
43.2k
    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
43.2k
}
2265
2266
388k
Status PipelineFragmentContext::send_report(bool done) {
2267
388k
    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
388k
    if (!_is_report_success && done && exec_status.ok()) {
2273
345k
        return Status::OK();
2274
345k
    }
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
43.5k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
231
        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
231
            return Status::OK();
2286
231
        }
2287
0
        return Status::NeedSendAgain("");
2288
231
    }
2289
2290
43.2k
    std::vector<RuntimeState*> runtime_states;
2291
2292
91.6k
    for (auto& tasks : _tasks) {
2293
129k
        for (auto& task : tasks) {
2294
129k
            runtime_states.push_back(task.second.get());
2295
129k
        }
2296
91.6k
    }
2297
2298
43.2k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
43.2k
                                        ? get_load_error_url()
2300
43.2k
                                        : _query_ctx->get_load_error_url();
2301
43.2k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
43.2k
                                          ? get_first_error_msg()
2303
43.2k
                                          : _query_ctx->get_first_error_msg();
2304
2305
43.2k
    ReportStatusRequest req {.status = exec_status,
2306
43.2k
                             .runtime_states = runtime_states,
2307
43.2k
                             .done = done || !exec_status.ok(),
2308
43.2k
                             .coord_addr = _query_ctx->coord_addr,
2309
43.2k
                             .query_id = _query_id,
2310
43.2k
                             .fragment_id = _fragment_id,
2311
43.2k
                             .fragment_instance_id = TUniqueId(),
2312
43.2k
                             .backend_num = -1,
2313
43.2k
                             .runtime_state = _runtime_state.get(),
2314
43.2k
                             .load_error_url = load_eror_url,
2315
43.2k
                             .first_error_msg = first_error_msg,
2316
43.2k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
43.2k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
43.3k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
43.3k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
43.3k
        _coordinator_callback(req);
2321
43.3k
        if (!req.done) {
2322
4.31k
            ctx->refresh_next_report_time();
2323
4.31k
        }
2324
43.3k
    });
2325
43.5k
}
2326
2327
8
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
8
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
8
    for (const auto& task_instances : _tasks) {
2332
12
        for (const auto& task : task_instances) {
2333
12
            if (task.first->is_running()) {
2334
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2335
0
                                      << " is running, task: " << (void*)task.first.get()
2336
0
                                      << ", is_running: " << task.first->is_running();
2337
0
                *has_running_task = true;
2338
0
                return 0;
2339
0
            }
2340
2341
12
            size_t revocable_size = task.first->get_revocable_size();
2342
12
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
4
                res += revocable_size;
2344
4
            }
2345
12
        }
2346
8
    }
2347
8
    return res;
2348
8
}
2349
2350
16
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
16
    std::vector<PipelineTask*> revocable_tasks;
2352
16
    for (const auto& task_instances : _tasks) {
2353
24
        for (const auto& task : task_instances) {
2354
24
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
24
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
8
                revocable_tasks.emplace_back(task.first.get());
2358
8
            }
2359
24
        }
2360
16
    }
2361
16
    return revocable_tasks;
2362
16
}
2363
2364
34
std::string PipelineFragmentContext::debug_string() {
2365
34
    std::lock_guard<std::mutex> l(_task_mutex);
2366
34
    fmt::memory_buffer debug_string_buffer;
2367
34
    fmt::format_to(debug_string_buffer,
2368
34
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
34
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
34
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
142
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
108
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
364
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
256
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
256
                           _tasks[j][i].first->debug_string());
2376
256
        }
2377
108
    }
2378
2379
34
    return fmt::to_string(debug_string_buffer);
2380
34
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.58k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.58k
    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
2.58k
    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
2.58k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.58k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.58k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.81k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.81k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.81k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.81k
        res.push_back(profile_ptr);
2407
4.81k
    }
2408
2409
2.58k
    return res;
2410
2.58k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.58k
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
2.58k
    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
6.51k
    for (const auto& tasks : _tasks) {
2426
13.0k
        for (const auto& task : tasks) {
2427
13.0k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
13.0k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
13.0k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
13.0k
                                                           _runtime_state->profile_level());
2435
13.0k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
13.0k
        }
2437
6.51k
    }
2438
2439
2.58k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.58k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.58k
                                                      _runtime_state->profile_level());
2442
2.58k
    return load_channel_profile;
2443
2.58k
}
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
5.80k
    for (const auto& _task : _tasks) {
2455
9.79k
        for (const auto& task : _task) {
2456
9.79k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
9.79k
            result.merge(set);
2458
9.79k
        }
2459
5.80k
    }
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
388k
void PipelineFragmentContext::_release_resource() {
2468
388k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
388k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
388k
    auto st = _query_ctx->exec_status();
2472
1.04M
    for (auto& _task : _tasks) {
2473
1.04M
        if (!_task.empty()) {
2474
1.04M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.04M
        }
2476
1.04M
    }
2477
388k
    _tasks.clear();
2478
388k
    _dag.clear();
2479
388k
    _pip_id_to_pipeline.clear();
2480
388k
    _pipelines.clear();
2481
388k
    _sink.reset();
2482
388k
    _root_op.reset();
2483
388k
    _runtime_filter_mgr_map.clear();
2484
388k
    _op_id_to_shared_state.clear();
2485
388k
}
2486
2487
} // namespace doris