Coverage Report

Created: 2026-04-02 10:16

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
17
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/PaloInternalService_types.h>
22
#include <gen_cpp/PlanNodes_types.h>
23
#include <pthread.h>
24
25
#include <algorithm>
26
#include <cstdlib>
27
// IWYU pragma: no_include <bits/chrono.h>
28
#include <fmt/format.h>
29
30
#include <chrono> // IWYU pragma: keep
31
#include <map>
32
#include <memory>
33
#include <ostream>
34
#include <utility>
35
36
#include "cloud/config.h"
37
#include "common/cast_set.h"
38
#include "common/config.h"
39
#include "common/exception.h"
40
#include "common/logging.h"
41
#include "common/status.h"
42
#include "exec/exchange/local_exchange_sink_operator.h"
43
#include "exec/exchange/local_exchange_source_operator.h"
44
#include "exec/exchange/local_exchanger.h"
45
#include "exec/exchange/vdata_stream_mgr.h"
46
#include "exec/operator/aggregation_sink_operator.h"
47
#include "exec/operator/aggregation_source_operator.h"
48
#include "exec/operator/analytic_sink_operator.h"
49
#include "exec/operator/analytic_source_operator.h"
50
#include "exec/operator/assert_num_rows_operator.h"
51
#include "exec/operator/blackhole_sink_operator.h"
52
#include "exec/operator/cache_sink_operator.h"
53
#include "exec/operator/cache_source_operator.h"
54
#include "exec/operator/datagen_operator.h"
55
#include "exec/operator/dict_sink_operator.h"
56
#include "exec/operator/distinct_streaming_aggregation_operator.h"
57
#include "exec/operator/empty_set_operator.h"
58
#include "exec/operator/es_scan_operator.h"
59
#include "exec/operator/exchange_sink_operator.h"
60
#include "exec/operator/exchange_source_operator.h"
61
#include "exec/operator/file_scan_operator.h"
62
#include "exec/operator/group_commit_block_sink_operator.h"
63
#include "exec/operator/group_commit_scan_operator.h"
64
#include "exec/operator/hashjoin_build_sink.h"
65
#include "exec/operator/hashjoin_probe_operator.h"
66
#include "exec/operator/hive_table_sink_operator.h"
67
#include "exec/operator/iceberg_delete_sink_operator.h"
68
#include "exec/operator/iceberg_merge_sink_operator.h"
69
#include "exec/operator/iceberg_table_sink_operator.h"
70
#include "exec/operator/jdbc_scan_operator.h"
71
#include "exec/operator/jdbc_table_sink_operator.h"
72
#include "exec/operator/local_merge_sort_source_operator.h"
73
#include "exec/operator/materialization_opertor.h"
74
#include "exec/operator/maxcompute_table_sink_operator.h"
75
#include "exec/operator/memory_scratch_sink_operator.h"
76
#include "exec/operator/meta_scan_operator.h"
77
#include "exec/operator/multi_cast_data_stream_sink.h"
78
#include "exec/operator/multi_cast_data_stream_source.h"
79
#include "exec/operator/nested_loop_join_build_operator.h"
80
#include "exec/operator/nested_loop_join_probe_operator.h"
81
#include "exec/operator/olap_scan_operator.h"
82
#include "exec/operator/olap_table_sink_operator.h"
83
#include "exec/operator/olap_table_sink_v2_operator.h"
84
#include "exec/operator/partition_sort_sink_operator.h"
85
#include "exec/operator/partition_sort_source_operator.h"
86
#include "exec/operator/partitioned_aggregation_sink_operator.h"
87
#include "exec/operator/partitioned_aggregation_source_operator.h"
88
#include "exec/operator/partitioned_hash_join_probe_operator.h"
89
#include "exec/operator/partitioned_hash_join_sink_operator.h"
90
#include "exec/operator/rec_cte_anchor_sink_operator.h"
91
#include "exec/operator/rec_cte_scan_operator.h"
92
#include "exec/operator/rec_cte_sink_operator.h"
93
#include "exec/operator/rec_cte_source_operator.h"
94
#include "exec/operator/repeat_operator.h"
95
#include "exec/operator/result_file_sink_operator.h"
96
#include "exec/operator/result_sink_operator.h"
97
#include "exec/operator/schema_scan_operator.h"
98
#include "exec/operator/select_operator.h"
99
#include "exec/operator/set_probe_sink_operator.h"
100
#include "exec/operator/set_sink_operator.h"
101
#include "exec/operator/set_source_operator.h"
102
#include "exec/operator/sort_sink_operator.h"
103
#include "exec/operator/sort_source_operator.h"
104
#include "exec/operator/spill_iceberg_table_sink_operator.h"
105
#include "exec/operator/spill_sort_sink_operator.h"
106
#include "exec/operator/spill_sort_source_operator.h"
107
#include "exec/operator/streaming_aggregation_operator.h"
108
#include "exec/operator/table_function_operator.h"
109
#include "exec/operator/tvf_table_sink_operator.h"
110
#include "exec/operator/union_sink_operator.h"
111
#include "exec/operator/union_source_operator.h"
112
#include "exec/pipeline/dependency.h"
113
#include "exec/pipeline/pipeline_task.h"
114
#include "exec/pipeline/task_scheduler.h"
115
#include "exec/runtime_filter/runtime_filter_mgr.h"
116
#include "exec/sort/topn_sorter.h"
117
#include "exec/spill/spill_file.h"
118
#include "io/fs/stream_load_pipe.h"
119
#include "load/stream_load/new_load_stream_mgr.h"
120
#include "runtime/exec_env.h"
121
#include "runtime/fragment_mgr.h"
122
#include "runtime/result_buffer_mgr.h"
123
#include "runtime/runtime_state.h"
124
#include "runtime/thread_context.h"
125
#include "util/countdown_latch.h"
126
#include "util/debug_util.h"
127
#include "util/uid_util.h"
128
129
namespace doris {
130
#include "common/compile_check_begin.h"
131
PipelineFragmentContext::PipelineFragmentContext(
132
        TUniqueId query_id, const TPipelineFragmentParams& request,
133
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
134
        const std::function<void(RuntimeState*, Status*)>& call_back,
135
        report_status_callback report_status_cb)
136
319k
        : _query_id(std::move(query_id)),
137
319k
          _fragment_id(request.fragment_id),
138
319k
          _exec_env(exec_env),
139
319k
          _query_ctx(std::move(query_ctx)),
140
319k
          _call_back(call_back),
141
319k
          _is_report_on_cancel(true),
142
319k
          _report_status_cb(std::move(report_status_cb)),
143
319k
          _params(request),
144
319k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
145
319k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
146
319k
                                                               : false) {
147
319k
    _fragment_watcher.start();
148
319k
}
149
150
319k
PipelineFragmentContext::~PipelineFragmentContext() {
151
319k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
152
319k
            .tag("query_id", print_id(_query_id))
153
319k
            .tag("fragment_id", _fragment_id);
154
319k
    _release_resource();
155
319k
    {
156
        // The memory released by the query end is recorded in the query mem tracker.
157
319k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
158
319k
        _runtime_state.reset();
159
319k
        _query_ctx.reset();
160
319k
    }
161
319k
}
162
163
118
bool PipelineFragmentContext::is_timeout(timespec now) const {
164
118
    if (_timeout <= 0) {
165
0
        return false;
166
0
    }
167
118
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
168
118
}
169
170
// notify_close() transitions the PFC from "waiting for external close notification" to
171
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
172
// 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).
174
9.20k
bool PipelineFragmentContext::notify_close() {
175
9.20k
    bool all_closed = false;
176
9.20k
    bool need_remove = false;
177
9.20k
    {
178
9.20k
        std::lock_guard<std::mutex> l(_task_mutex);
179
9.20k
        if (_closed_tasks >= _total_tasks) {
180
3.44k
            if (_need_notify_close) {
181
                // Fragment was cancelled and waiting for notify to close.
182
                // Record that we need to remove from fragment mgr, but do it
183
                // after releasing _task_mutex to avoid ABBA deadlock with
184
                // dump_pipeline_tasks() (which acquires _pipeline_map lock
185
                // first, then _task_mutex via debug_string()).
186
3.37k
                need_remove = true;
187
3.37k
            }
188
3.44k
            all_closed = true;
189
3.44k
        }
190
        // make fragment release by self after cancel
191
9.20k
        _need_notify_close = false;
192
9.20k
    }
193
9.20k
    if (need_remove) {
194
3.37k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
195
3.37k
    }
196
9.20k
    return all_closed;
197
9.20k
}
198
199
// Must not add lock in this method. Because it will call query ctx cancel. And
200
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
201
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
203
5.72k
void PipelineFragmentContext::cancel(const Status reason) {
204
5.72k
    LOG_INFO("PipelineFragmentContext::cancel")
205
5.72k
            .tag("query_id", print_id(_query_id))
206
5.72k
            .tag("fragment_id", _fragment_id)
207
5.72k
            .tag("reason", reason.to_string());
208
5.72k
    if (notify_close()) {
209
82
        return;
210
82
    }
211
    // Timeout is a special error code, we need print current stack to debug timeout issue.
212
5.64k
    if (reason.is<ErrorCode::TIMEOUT>()) {
213
8
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
214
8
                                   debug_string());
215
8
        LOG_LONG_STRING(WARNING, dbg_str);
216
8
    }
217
218
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
219
5.64k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
220
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
221
0
                    debug_string());
222
0
    }
223
224
5.64k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
225
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
226
0
    }
227
228
5.64k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
229
22
        _query_ctx->set_load_error_url(error_url);
230
22
    }
231
232
5.64k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
233
22
        _query_ctx->set_first_error_msg(first_error_msg);
234
22
    }
235
236
5.64k
    _query_ctx->cancel(reason, _fragment_id);
237
5.64k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
238
223
        _is_report_on_cancel = false;
239
5.41k
    } else {
240
29.6k
        for (auto& id : _fragment_instance_ids) {
241
29.6k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
242
29.6k
        }
243
5.41k
    }
244
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
245
    // For stream load the fragment's query_id == load id, it is set in FE.
246
5.64k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
247
5.64k
    if (stream_load_ctx != nullptr) {
248
30
        stream_load_ctx->pipe->cancel(reason.to_string());
249
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
250
        // We need to set the error URL at this point to ensure error information is properly
251
        // propagated to the client.
252
30
        stream_load_ctx->error_url = get_load_error_url();
253
30
        stream_load_ctx->first_error_msg = get_first_error_msg();
254
30
    }
255
256
30.7k
    for (auto& tasks : _tasks) {
257
65.1k
        for (auto& task : tasks) {
258
65.1k
            task.first->unblock_all_dependencies();
259
65.1k
        }
260
30.7k
    }
261
5.64k
}
262
263
503k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
264
503k
    PipelineId id = _next_pipeline_id++;
265
503k
    auto pipeline = std::make_shared<Pipeline>(
266
503k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
267
503k
            parent ? parent->num_tasks() : _num_instances);
268
503k
    if (idx >= 0) {
269
99.3k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
270
404k
    } else {
271
404k
        _pipelines.emplace_back(pipeline);
272
404k
    }
273
503k
    if (parent) {
274
184k
        parent->set_children(pipeline);
275
184k
    }
276
503k
    return pipeline;
277
503k
}
278
279
319k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
280
319k
    {
281
319k
        SCOPED_TIMER(_build_pipelines_timer);
282
        // 2. Build pipelines with operators in this fragment.
283
319k
        auto root_pipeline = add_pipeline();
284
319k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
285
319k
                                         &_root_op, root_pipeline));
286
287
        // 3. Create sink operator
288
319k
        if (!_params.fragment.__isset.output_sink) {
289
0
            return Status::InternalError("No output sink in this fragment!");
290
0
        }
291
319k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
292
319k
                                          _params.fragment.output_exprs, _params,
293
319k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
294
319k
                                          *_desc_tbl, root_pipeline->id()));
295
319k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
296
319k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
297
298
404k
        for (PipelinePtr& pipeline : _pipelines) {
299
18.4E
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
300
404k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
301
404k
        }
302
319k
    }
303
    // 4. Build local exchanger
304
319k
    if (_runtime_state->enable_local_shuffle()) {
305
316k
        SCOPED_TIMER(_plan_local_exchanger_timer);
306
316k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
307
316k
                                             _params.bucket_seq_to_instance_idx,
308
316k
                                             _params.shuffle_idx_to_instance_idx));
309
316k
    }
310
311
    // 5. Initialize global states in pipelines.
312
505k
    for (PipelinePtr& pipeline : _pipelines) {
313
505k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
314
505k
        pipeline->children().clear();
315
505k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
316
505k
    }
317
318
317k
    {
319
317k
        SCOPED_TIMER(_build_tasks_timer);
320
        // 6. Build pipeline tasks and initialize local state.
321
317k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
322
317k
    }
323
324
317k
    return Status::OK();
325
317k
}
326
327
319k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
328
319k
    if (_prepared) {
329
0
        return Status::InternalError("Already prepared");
330
0
    }
331
319k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
332
319k
        _timeout = _params.query_options.execution_timeout;
333
319k
    }
334
335
319k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
336
319k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
337
319k
    SCOPED_TIMER(_prepare_timer);
338
319k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
339
319k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
340
319k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
341
319k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
342
319k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
343
319k
    {
344
319k
        SCOPED_TIMER(_init_context_timer);
345
319k
        cast_set(_num_instances, _params.local_params.size());
346
319k
        _total_instances =
347
319k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
348
349
319k
        auto* fragment_context = this;
350
351
319k
        if (_params.query_options.__isset.is_report_success) {
352
317k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
353
317k
        }
354
355
        // 1. Set up the global runtime state.
356
319k
        _runtime_state = RuntimeState::create_unique(
357
319k
                _params.query_id, _params.fragment_id, _params.query_options,
358
319k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
359
319k
        _runtime_state->set_task_execution_context(shared_from_this());
360
319k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
361
319k
        if (_params.__isset.backend_id) {
362
316k
            _runtime_state->set_backend_id(_params.backend_id);
363
316k
        }
364
319k
        if (_params.__isset.import_label) {
365
238
            _runtime_state->set_import_label(_params.import_label);
366
238
        }
367
319k
        if (_params.__isset.db_name) {
368
190
            _runtime_state->set_db_name(_params.db_name);
369
190
        }
370
319k
        if (_params.__isset.load_job_id) {
371
0
            _runtime_state->set_load_job_id(_params.load_job_id);
372
0
        }
373
374
319k
        if (_params.is_simplified_param) {
375
110k
            _desc_tbl = _query_ctx->desc_tbl;
376
209k
        } else {
377
209k
            DCHECK(_params.__isset.desc_tbl);
378
209k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
379
209k
                                                  &_desc_tbl));
380
209k
        }
381
319k
        _runtime_state->set_desc_tbl(_desc_tbl);
382
319k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
383
319k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
384
319k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
385
319k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
386
387
        // init fragment_instance_ids
388
319k
        const auto target_size = _params.local_params.size();
389
319k
        _fragment_instance_ids.resize(target_size);
390
1.25M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
391
937k
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
392
937k
            _fragment_instance_ids[i] = fragment_instance_id;
393
937k
        }
394
319k
    }
395
396
319k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
397
398
318k
    _init_next_report_time();
399
400
318k
    _prepared = true;
401
318k
    return Status::OK();
402
319k
}
403
404
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
405
        int instance_idx,
406
937k
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
407
937k
    const auto& local_params = _params.local_params[instance_idx];
408
937k
    auto fragment_instance_id = local_params.fragment_instance_id;
409
937k
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
410
937k
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
411
937k
    auto get_shared_state = [&](PipelinePtr pipeline)
412
937k
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
413
1.65M
                                       std::vector<std::shared_ptr<Dependency>>>> {
414
1.65M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
415
1.65M
                                std::vector<std::shared_ptr<Dependency>>>>
416
1.65M
                shared_state_map;
417
2.15M
        for (auto& op : pipeline->operators()) {
418
2.15M
            auto source_id = op->operator_id();
419
2.15M
            if (auto iter = _op_id_to_shared_state.find(source_id);
420
2.15M
                iter != _op_id_to_shared_state.end()) {
421
668k
                shared_state_map.insert({source_id, iter->second});
422
668k
            }
423
2.15M
        }
424
1.65M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
425
1.65M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
426
1.65M
                iter != _op_id_to_shared_state.end()) {
427
300k
                shared_state_map.insert({sink_to_source_id, iter->second});
428
300k
            }
429
1.65M
        }
430
1.65M
        return shared_state_map;
431
1.65M
    };
432
433
2.94M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
434
2.01M
        auto& pipeline = _pipelines[pip_idx];
435
2.01M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
436
1.64M
            auto task_runtime_state = RuntimeState::create_unique(
437
1.64M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
438
1.64M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
439
1.64M
            {
440
                // Initialize runtime state for this task
441
1.64M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
442
443
1.64M
                task_runtime_state->set_task_execution_context(shared_from_this());
444
1.64M
                task_runtime_state->set_be_number(local_params.backend_num);
445
446
1.65M
                if (_params.__isset.backend_id) {
447
1.65M
                    task_runtime_state->set_backend_id(_params.backend_id);
448
1.65M
                }
449
1.64M
                if (_params.__isset.import_label) {
450
239
                    task_runtime_state->set_import_label(_params.import_label);
451
239
                }
452
1.64M
                if (_params.__isset.db_name) {
453
191
                    task_runtime_state->set_db_name(_params.db_name);
454
191
                }
455
1.64M
                if (_params.__isset.load_job_id) {
456
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
457
0
                }
458
1.64M
                if (_params.__isset.wal_id) {
459
114
                    task_runtime_state->set_wal_id(_params.wal_id);
460
114
                }
461
1.64M
                if (_params.__isset.content_length) {
462
31
                    task_runtime_state->set_content_length(_params.content_length);
463
31
                }
464
465
1.64M
                task_runtime_state->set_desc_tbl(_desc_tbl);
466
1.64M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
467
1.64M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
468
1.64M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
469
1.64M
                task_runtime_state->set_max_operator_id(max_operator_id());
470
1.64M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
471
1.64M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
472
1.64M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
473
474
1.64M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
475
1.64M
            }
476
1.64M
            auto cur_task_id = _total_tasks++;
477
1.64M
            task_runtime_state->set_task_id(cur_task_id);
478
1.64M
            task_runtime_state->set_task_num(pipeline->num_tasks());
479
1.64M
            auto task = std::make_shared<PipelineTask>(
480
1.64M
                    pipeline, cur_task_id, task_runtime_state.get(),
481
1.64M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
482
1.64M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
483
1.64M
                    instance_idx);
484
1.64M
            pipeline->incr_created_tasks(instance_idx, task.get());
485
1.64M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
486
1.64M
            _tasks[instance_idx].emplace_back(
487
1.64M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
488
1.64M
                            std::move(task), std::move(task_runtime_state)});
489
1.64M
        }
490
2.01M
    }
491
492
    /**
493
         * Build DAG for pipeline tasks.
494
         * For example, we have
495
         *
496
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
497
         *            \                      /
498
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
499
         *                 \                          /
500
         *               JoinProbeOperator2 (Pipeline1)
501
         *
502
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
503
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
504
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
505
         *
506
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
507
         * and JoinProbeOperator2.
508
         */
509
2.01M
    for (auto& _pipeline : _pipelines) {
510
2.01M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
511
1.64M
            auto* task = pipeline_id_to_task[_pipeline->id()];
512
1.64M
            DCHECK(task != nullptr);
513
514
            // If this task has upstream dependency, then inject it into this task.
515
1.64M
            if (_dag.contains(_pipeline->id())) {
516
1.07M
                auto& deps = _dag[_pipeline->id()];
517
1.73M
                for (auto& dep : deps) {
518
1.73M
                    if (pipeline_id_to_task.contains(dep)) {
519
999k
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
520
999k
                        if (ss) {
521
402k
                            task->inject_shared_state(ss);
522
597k
                        } else {
523
597k
                            pipeline_id_to_task[dep]->inject_shared_state(
524
597k
                                    task->get_source_shared_state());
525
597k
                        }
526
999k
                    }
527
1.73M
                }
528
1.07M
            }
529
1.64M
        }
530
2.01M
    }
531
2.95M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
532
2.01M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
533
1.64M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
534
1.64M
            DCHECK(pipeline_id_to_profile[pip_idx]);
535
1.64M
            std::vector<TScanRangeParams> scan_ranges;
536
1.64M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
537
1.64M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
538
259k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
539
259k
            }
540
1.64M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
541
1.64M
                                                             _params.fragment.output_sink));
542
1.64M
        }
543
2.01M
    }
544
939k
    {
545
939k
        std::lock_guard<std::mutex> l(_state_map_lock);
546
939k
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
547
939k
    }
548
939k
    return Status::OK();
549
937k
}
550
551
318k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
552
318k
    _total_tasks = 0;
553
318k
    _closed_tasks = 0;
554
318k
    const auto target_size = _params.local_params.size();
555
318k
    _tasks.resize(target_size);
556
318k
    _runtime_filter_mgr_map.resize(target_size);
557
822k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
558
503k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
559
503k
    }
560
318k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
561
562
318k
    if (target_size > 1 &&
563
318k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
564
114k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
565
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
566
17.3k
        std::vector<Status> prepare_status(target_size);
567
17.3k
        int submitted_tasks = 0;
568
17.3k
        Status submit_status;
569
17.3k
        CountDownLatch latch((int)target_size);
570
273k
        for (int i = 0; i < target_size; i++) {
571
256k
            submit_status = thread_pool->submit_func([&, i]() {
572
256k
                SCOPED_ATTACH_TASK(_query_ctx.get());
573
256k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
574
256k
                latch.count_down();
575
256k
            });
576
256k
            if (LIKELY(submit_status.ok())) {
577
256k
                submitted_tasks++;
578
18.4E
            } else {
579
18.4E
                break;
580
18.4E
            }
581
256k
        }
582
17.3k
        latch.arrive_and_wait(target_size - submitted_tasks);
583
17.3k
        if (UNLIKELY(!submit_status.ok())) {
584
0
            return submit_status;
585
0
        }
586
273k
        for (int i = 0; i < submitted_tasks; i++) {
587
256k
            if (!prepare_status[i].ok()) {
588
0
                return prepare_status[i];
589
0
            }
590
256k
        }
591
301k
    } else {
592
983k
        for (int i = 0; i < target_size; i++) {
593
682k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
594
682k
        }
595
301k
    }
596
318k
    _pipeline_parent_map.clear();
597
318k
    _op_id_to_shared_state.clear();
598
599
318k
    return Status::OK();
600
318k
}
601
602
317k
void PipelineFragmentContext::_init_next_report_time() {
603
317k
    auto interval_s = config::pipeline_status_report_interval;
604
317k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
605
30.7k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
606
30.7k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
607
        // We don't want to wait longer than it takes to run the entire fragment.
608
30.7k
        _previous_report_time =
609
30.7k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
610
30.7k
        _disable_period_report = false;
611
30.7k
    }
612
317k
}
613
614
3.64k
void PipelineFragmentContext::refresh_next_report_time() {
615
3.64k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
616
3.64k
    DCHECK(disable == true);
617
3.64k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
618
3.64k
    _disable_period_report.compare_exchange_strong(disable, false);
619
3.64k
}
620
621
5.85M
void PipelineFragmentContext::trigger_report_if_necessary() {
622
5.85M
    if (!_is_report_success) {
623
5.42M
        return;
624
5.42M
    }
625
420k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
626
420k
    if (disable) {
627
7.23k
        return;
628
7.23k
    }
629
413k
    int32_t interval_s = config::pipeline_status_report_interval;
630
413k
    if (interval_s <= 0) {
631
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
632
0
                        "trigger "
633
0
                        "report.";
634
0
    }
635
413k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
636
413k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
637
413k
    if (MonotonicNanos() > next_report_time) {
638
3.65k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
639
3.65k
                                                            std::memory_order_acq_rel)) {
640
11
            return;
641
11
        }
642
3.64k
        if (VLOG_FILE_IS_ON) {
643
0
            VLOG_FILE << "Reporting "
644
0
                      << "profile for query_id " << print_id(_query_id)
645
0
                      << ", fragment id: " << _fragment_id;
646
647
0
            std::stringstream ss;
648
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
649
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
650
0
            if (_runtime_state->load_channel_profile()) {
651
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
652
0
            }
653
654
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
655
0
                      << " profile:\n"
656
0
                      << ss.str();
657
0
        }
658
3.64k
        auto st = send_report(false);
659
3.64k
        if (!st.ok()) {
660
0
            disable = true;
661
0
            _disable_period_report.compare_exchange_strong(disable, false,
662
0
                                                           std::memory_order_acq_rel);
663
0
        }
664
3.64k
    }
665
413k
}
666
667
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
668
317k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
669
317k
    if (_params.fragment.plan.nodes.empty()) {
670
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
671
0
    }
672
673
317k
    int node_idx = 0;
674
675
317k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
676
317k
                                        &node_idx, root, cur_pipe, 0, false, false));
677
678
317k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
679
0
        return Status::InternalError(
680
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
681
0
    }
682
317k
    return Status::OK();
683
317k
}
684
685
Status PipelineFragmentContext::_create_tree_helper(
686
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
687
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
688
504k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
689
    // propagate error case
690
504k
    if (*node_idx >= tnodes.size()) {
691
0
        return Status::InternalError(
692
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
693
0
                *node_idx, tnodes.size());
694
0
    }
695
504k
    const TPlanNode& tnode = tnodes[*node_idx];
696
697
504k
    int num_children = tnodes[*node_idx].num_children;
698
504k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
699
504k
    bool current_require_bucket_distribution = require_bucket_distribution;
700
    // TODO: Create CacheOperator is confused now
701
504k
    OperatorPtr op = nullptr;
702
504k
    OperatorPtr cache_op = nullptr;
703
504k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
704
504k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
705
504k
                                     followed_by_shuffled_operator,
706
504k
                                     current_require_bucket_distribution, cache_op));
707
    // Initialization must be done here. For example, group by expressions in agg will be used to
708
    // decide if a local shuffle should be planed, so it must be initialized here.
709
504k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
710
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
711
504k
    if (parent != nullptr) {
712
        // add to parent's child(s)
713
187k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
714
317k
    } else {
715
317k
        *root = op;
716
317k
    }
717
    /**
718
     * `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).
719
     *
720
     * For plan:
721
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
722
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
723
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
724
     *
725
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
726
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
727
     */
728
504k
    auto required_data_distribution =
729
504k
            cur_pipe->operators().empty()
730
504k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
731
504k
                    : op->required_data_distribution(_runtime_state.get());
732
504k
    current_followed_by_shuffled_operator =
733
504k
            ((followed_by_shuffled_operator ||
734
504k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
735
448k
                                             : op->is_shuffled_operator())) &&
736
504k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
737
504k
            (followed_by_shuffled_operator &&
738
398k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
739
740
504k
    current_require_bucket_distribution =
741
504k
            ((require_bucket_distribution ||
742
504k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
743
452k
                                             : op->is_colocated_operator())) &&
744
504k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
504k
            (require_bucket_distribution &&
746
404k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
504k
    if (num_children == 0) {
749
327k
        _use_serial_source = op->is_serial_operator();
750
327k
    }
751
    // rely on that tnodes is preorder of the plan
752
692k
    for (int i = 0; i < num_children; i++) {
753
187k
        ++*node_idx;
754
187k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
755
187k
                                            current_followed_by_shuffled_operator,
756
187k
                                            current_require_bucket_distribution));
757
758
        // we are expecting a child, but have used all nodes
759
        // this means we have been given a bad tree and must fail
760
187k
        if (*node_idx >= tnodes.size()) {
761
0
            return Status::InternalError(
762
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
763
0
                    "nodes: {}",
764
0
                    *node_idx, tnodes.size());
765
0
        }
766
187k
    }
767
768
504k
    return Status::OK();
769
504k
}
770
771
void PipelineFragmentContext::_inherit_pipeline_properties(
772
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
773
99.3k
        PipelinePtr pipe_with_sink) {
774
99.3k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
775
99.3k
    pipe_with_source->set_num_tasks(_num_instances);
776
99.3k
    pipe_with_source->set_data_distribution(data_distribution);
777
99.3k
}
778
779
Status PipelineFragmentContext::_add_local_exchange_impl(
780
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
781
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
782
        const std::map<int, int>& bucket_seq_to_instance_idx,
783
99.2k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
784
99.2k
    auto& operators = cur_pipe->operators();
785
99.2k
    const auto downstream_pipeline_id = cur_pipe->id();
786
99.2k
    auto local_exchange_id = next_operator_id();
787
    // 1. Create a new pipeline with local exchange sink.
788
99.2k
    DataSinkOperatorPtr sink;
789
99.2k
    auto sink_id = next_sink_operator_id();
790
791
    /**
792
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
793
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
794
     */
795
99.2k
    const bool followed_by_shuffled_operator =
796
99.2k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
797
99.2k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
798
99.2k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
799
99.2k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
800
99.2k
                                         followed_by_shuffled_operator && !_use_serial_source;
801
99.2k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
802
99.2k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
803
99.2k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
804
99.2k
    if (bucket_seq_to_instance_idx.empty() &&
805
99.2k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
806
7
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
807
7
    }
808
99.2k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
809
99.2k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
810
99.2k
                                          num_buckets, use_global_hash_shuffle,
811
99.2k
                                          shuffle_idx_to_instance_idx));
812
813
    // 2. Create and initialize LocalExchangeSharedState.
814
99.2k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
815
99.2k
            LocalExchangeSharedState::create_shared(_num_instances);
816
99.2k
    switch (data_distribution.distribution_type) {
817
19.7k
    case ExchangeType::HASH_SHUFFLE:
818
19.7k
        shared_state->exchanger = ShuffleExchanger::create_unique(
819
19.7k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
820
19.7k
                use_global_hash_shuffle ? _total_instances : _num_instances,
821
19.7k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
822
19.7k
                        ? cast_set<int>(
823
19.7k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
824
19.7k
                        : 0);
825
19.7k
        break;
826
691
    case ExchangeType::BUCKET_HASH_SHUFFLE:
827
691
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
828
691
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
829
691
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
691
                        ? cast_set<int>(
831
691
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
691
                        : 0);
833
691
        break;
834
75.1k
    case ExchangeType::PASSTHROUGH:
835
75.1k
        shared_state->exchanger = PassthroughExchanger::create_unique(
836
75.1k
                cur_pipe->num_tasks(), _num_instances,
837
75.1k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
75.1k
                        ? cast_set<int>(
839
75.0k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
75.1k
                        : 0);
841
75.1k
        break;
842
486
    case ExchangeType::BROADCAST:
843
486
        shared_state->exchanger = BroadcastExchanger::create_unique(
844
486
                cur_pipe->num_tasks(), _num_instances,
845
486
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
486
                        ? cast_set<int>(
847
486
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
486
                        : 0);
849
486
        break;
850
2.39k
    case ExchangeType::PASS_TO_ONE:
851
2.39k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
852
            // If shared hash table is enabled for BJ, hash table will be built by only one task
853
1.13k
            shared_state->exchanger = PassToOneExchanger::create_unique(
854
1.13k
                    cur_pipe->num_tasks(), _num_instances,
855
1.13k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
856
1.13k
                            ? cast_set<int>(_runtime_state->query_options()
857
1.13k
                                                    .local_exchange_free_blocks_limit)
858
1.13k
                            : 0);
859
1.26k
        } else {
860
1.26k
            shared_state->exchanger = BroadcastExchanger::create_unique(
861
1.26k
                    cur_pipe->num_tasks(), _num_instances,
862
1.26k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
863
1.26k
                            ? cast_set<int>(_runtime_state->query_options()
864
1.26k
                                                    .local_exchange_free_blocks_limit)
865
1.26k
                            : 0);
866
1.26k
        }
867
2.39k
        break;
868
895
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
869
895
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
870
895
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
871
895
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
872
895
                        ? cast_set<int>(
873
895
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
874
895
                        : 0);
875
895
        break;
876
0
    default:
877
0
        return Status::InternalError("Unsupported local exchange type : " +
878
0
                                     std::to_string((int)data_distribution.distribution_type));
879
99.2k
    }
880
99.3k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
881
99.3k
                                             "LOCAL_EXCHANGE_OPERATOR");
882
99.3k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
883
99.3k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
884
885
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
886
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
887
888
    // 3.1 Initialize new pipeline's operator list.
889
99.3k
    std::copy(operators.begin(), operators.begin() + idx,
890
99.3k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
891
892
    // 3.2 Erase unused operators in previous pipeline.
893
99.3k
    operators.erase(operators.begin(), operators.begin() + idx);
894
895
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
896
99.3k
    OperatorPtr source_op;
897
99.3k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
898
99.3k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
899
99.3k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
900
99.3k
    if (!operators.empty()) {
901
39.7k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
902
39.7k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
903
39.7k
    }
904
99.3k
    operators.insert(operators.begin(), source_op);
905
906
    // 5. Set children for two pipelines separately.
907
99.3k
    std::vector<std::shared_ptr<Pipeline>> new_children;
908
99.3k
    std::vector<PipelineId> edges_with_source;
909
116k
    for (auto child : cur_pipe->children()) {
910
116k
        bool found = false;
911
131k
        for (auto op : new_pip->operators()) {
912
131k
            if (child->sink()->node_id() == op->node_id()) {
913
12.5k
                new_pip->set_children(child);
914
12.5k
                found = true;
915
12.5k
            };
916
131k
        }
917
116k
        if (!found) {
918
104k
            new_children.push_back(child);
919
104k
            edges_with_source.push_back(child->id());
920
104k
        }
921
116k
    }
922
99.3k
    new_children.push_back(new_pip);
923
99.3k
    edges_with_source.push_back(new_pip->id());
924
925
    // 6. Set DAG for new pipelines.
926
99.3k
    if (!new_pip->children().empty()) {
927
6.73k
        std::vector<PipelineId> edges_with_sink;
928
12.5k
        for (auto child : new_pip->children()) {
929
12.5k
            edges_with_sink.push_back(child->id());
930
12.5k
        }
931
6.73k
        _dag.insert({new_pip->id(), edges_with_sink});
932
6.73k
    }
933
99.3k
    cur_pipe->set_children(new_children);
934
99.3k
    _dag[downstream_pipeline_id] = edges_with_source;
935
99.3k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
936
99.3k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
937
99.3k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
938
939
    // 7. Inherit properties from current pipeline.
940
99.3k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
941
99.3k
    return Status::OK();
942
99.3k
}
943
944
Status PipelineFragmentContext::_add_local_exchange(
945
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
946
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
947
        const std::map<int, int>& bucket_seq_to_instance_idx,
948
154k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
949
154k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
950
31.3k
        return Status::OK();
951
31.3k
    }
952
953
123k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
954
44.2k
        return Status::OK();
955
44.2k
    }
956
79.1k
    *do_local_exchange = true;
957
958
79.1k
    auto& operators = cur_pipe->operators();
959
79.1k
    auto total_op_num = operators.size();
960
79.1k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
961
79.1k
    RETURN_IF_ERROR(_add_local_exchange_impl(
962
79.1k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
963
79.1k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
964
965
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
966
18.4E
            << "total_op_num: " << total_op_num
967
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
968
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
969
970
    // There are some local shuffles with relatively heavy operations on the sink.
971
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
972
    // Therefore, local passthrough is used to increase the concurrency of the sink.
973
    // op -> local sink(1) -> local source (n)
974
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
975
79.2k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
976
79.1k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
977
20.0k
        RETURN_IF_ERROR(_add_local_exchange_impl(
978
20.0k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
979
20.0k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
980
20.0k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
981
20.0k
                shuffle_idx_to_instance_idx));
982
20.0k
    }
983
79.1k
    return Status::OK();
984
79.1k
}
985
986
Status PipelineFragmentContext::_plan_local_exchange(
987
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
988
316k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
989
719k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
990
403k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
991
        // Set property if child pipeline is not join operator's child.
992
403k
        if (!_pipelines[pip_idx]->children().empty()) {
993
85.0k
            for (auto& child : _pipelines[pip_idx]->children()) {
994
85.0k
                if (child->sink()->node_id() ==
995
85.0k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
996
76.2k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
997
76.2k
                }
998
85.0k
            }
999
82.4k
        }
1000
1001
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1002
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1003
        // still keep colocate plan after local shuffle
1004
403k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1005
403k
                                             bucket_seq_to_instance_idx,
1006
403k
                                             shuffle_idx_to_instance_idx));
1007
403k
    }
1008
316k
    return Status::OK();
1009
316k
}
1010
1011
Status PipelineFragmentContext::_plan_local_exchange(
1012
        int num_buckets, int pip_idx, PipelinePtr pip,
1013
        const std::map<int, int>& bucket_seq_to_instance_idx,
1014
402k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1015
402k
    int idx = 1;
1016
402k
    bool do_local_exchange = false;
1017
442k
    do {
1018
442k
        auto& ops = pip->operators();
1019
442k
        do_local_exchange = false;
1020
        // Plan local exchange for each operator.
1021
505k
        for (; idx < ops.size();) {
1022
103k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1023
93.6k
                RETURN_IF_ERROR(_add_local_exchange(
1024
93.6k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1025
93.6k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1026
93.6k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1027
93.6k
                        shuffle_idx_to_instance_idx));
1028
93.6k
            }
1029
103k
            if (do_local_exchange) {
1030
                // If local exchange is needed for current operator, we will split this pipeline to
1031
                // two pipelines by local exchange sink/source. And then we need to process remaining
1032
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1033
                // is current operator was already processed) and continue to plan local exchange.
1034
39.9k
                idx = 2;
1035
39.9k
                break;
1036
39.9k
            }
1037
63.2k
            idx++;
1038
63.2k
        }
1039
442k
    } while (do_local_exchange);
1040
402k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1041
60.8k
        RETURN_IF_ERROR(_add_local_exchange(
1042
60.8k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1043
60.8k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1044
60.8k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1045
60.8k
    }
1046
402k
    return Status::OK();
1047
402k
}
1048
1049
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1050
                                                  const std::vector<TExpr>& output_exprs,
1051
                                                  const TPipelineFragmentParams& params,
1052
                                                  const RowDescriptor& row_desc,
1053
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1054
318k
                                                  PipelineId cur_pipeline_id) {
1055
318k
    switch (thrift_sink.type) {
1056
109k
    case TDataSinkType::DATA_STREAM_SINK: {
1057
109k
        if (!thrift_sink.__isset.stream_sink) {
1058
0
            return Status::InternalError("Missing data stream sink.");
1059
0
        }
1060
109k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1061
109k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1062
109k
                params.destinations, _fragment_instance_ids);
1063
109k
        break;
1064
109k
    }
1065
180k
    case TDataSinkType::RESULT_SINK: {
1066
180k
        if (!thrift_sink.__isset.result_sink) {
1067
0
            return Status::InternalError("Missing data buffer sink.");
1068
0
        }
1069
1070
180k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), row_desc,
1071
180k
                                                      output_exprs, thrift_sink.result_sink);
1072
180k
        break;
1073
180k
    }
1074
105
    case TDataSinkType::DICTIONARY_SINK: {
1075
105
        if (!thrift_sink.__isset.dictionary_sink) {
1076
0
            return Status::InternalError("Missing dict sink.");
1077
0
        }
1078
1079
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1080
105
                                                    thrift_sink.dictionary_sink);
1081
105
        break;
1082
105
    }
1083
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1084
27.6k
    case TDataSinkType::OLAP_TABLE_SINK: {
1085
27.6k
        if (state->query_options().enable_memtable_on_sink_node &&
1086
27.6k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1087
27.6k
            !config::is_cloud_mode()) {
1088
34
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(pool, next_sink_operator_id(),
1089
34
                                                               row_desc, output_exprs);
1090
27.6k
        } else {
1091
27.6k
            _sink = std::make_shared<OlapTableSinkOperatorX>(pool, next_sink_operator_id(),
1092
27.6k
                                                             row_desc, output_exprs);
1093
27.6k
        }
1094
27.6k
        break;
1095
0
    }
1096
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1097
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1098
165
        DCHECK(state->get_query_ctx() != nullptr);
1099
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1100
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1101
165
                                                                output_exprs);
1102
165
        break;
1103
0
    }
1104
0
    case TDataSinkType::HIVE_TABLE_SINK: {
1105
0
        if (!thrift_sink.__isset.hive_table_sink) {
1106
0
            return Status::InternalError("Missing hive table sink.");
1107
0
        }
1108
0
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1109
0
                                                         output_exprs);
1110
0
        break;
1111
0
    }
1112
0
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1113
0
        if (!thrift_sink.__isset.iceberg_table_sink) {
1114
0
            return Status::InternalError("Missing iceberg table sink.");
1115
0
        }
1116
0
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1117
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1118
0
                                                                     row_desc, output_exprs);
1119
0
        } else {
1120
0
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1121
0
                                                                row_desc, output_exprs);
1122
0
        }
1123
0
        break;
1124
0
    }
1125
0
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1126
0
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1127
0
            return Status::InternalError("Missing iceberg delete sink.");
1128
0
        }
1129
0
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1130
0
                                                             row_desc, output_exprs);
1131
0
        break;
1132
0
    }
1133
0
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1134
0
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1135
0
            return Status::InternalError("Missing iceberg merge sink.");
1136
0
        }
1137
0
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1138
0
                                                            output_exprs);
1139
0
        break;
1140
0
    }
1141
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1142
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1143
0
            return Status::InternalError("Missing max compute table sink.");
1144
0
        }
1145
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1146
0
                                                       output_exprs);
1147
0
        break;
1148
0
    }
1149
0
    case TDataSinkType::JDBC_TABLE_SINK: {
1150
0
        if (!thrift_sink.__isset.jdbc_table_sink) {
1151
0
            return Status::InternalError("Missing data jdbc sink.");
1152
0
        }
1153
0
        if (config::enable_java_support) {
1154
0
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1155
0
                                                             output_exprs);
1156
0
        } else {
1157
0
            return Status::InternalError(
1158
0
                    "Jdbc table sink is not enabled, you can change be config "
1159
0
                    "enable_java_support to true and restart be.");
1160
0
        }
1161
0
        break;
1162
0
    }
1163
3
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1164
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1165
0
            return Status::InternalError("Missing data buffer sink.");
1166
0
        }
1167
1168
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1169
3
                                                             output_exprs);
1170
3
        break;
1171
3
    }
1172
338
    case TDataSinkType::RESULT_FILE_SINK: {
1173
338
        if (!thrift_sink.__isset.result_file_sink) {
1174
0
            return Status::InternalError("Missing result file sink.");
1175
0
        }
1176
1177
        // Result file sink is not the top sink
1178
338
        if (params.__isset.destinations && !params.destinations.empty()) {
1179
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1180
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1181
0
                    params.destinations, output_exprs, desc_tbl);
1182
338
        } else {
1183
338
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1184
338
                                                              output_exprs);
1185
338
        }
1186
338
        break;
1187
338
    }
1188
566
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1189
566
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1190
566
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1191
566
        auto sink_id = next_sink_operator_id();
1192
566
        const int multi_cast_node_id = sink_id;
1193
566
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1194
        // one sink has multiple sources.
1195
566
        std::vector<int> sources;
1196
2.04k
        for (int i = 0; i < sender_size; ++i) {
1197
1.47k
            auto source_id = next_operator_id();
1198
1.47k
            sources.push_back(source_id);
1199
1.47k
        }
1200
1201
566
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1202
566
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1203
2.04k
        for (int i = 0; i < sender_size; ++i) {
1204
1.47k
            auto new_pipeline = add_pipeline();
1205
            // use to exchange sink
1206
1.47k
            RowDescriptor* exchange_row_desc = nullptr;
1207
1.47k
            {
1208
1.47k
                const auto& tmp_row_desc =
1209
1.47k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1210
1.47k
                                ? RowDescriptor(state->desc_tbl(),
1211
1.47k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1212
1.47k
                                                         .output_tuple_id})
1213
1.47k
                                : row_desc;
1214
1.47k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1215
1.47k
            }
1216
1.47k
            auto source_id = sources[i];
1217
1.47k
            OperatorPtr source_op;
1218
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1219
1.47k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1220
1.47k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1221
1.47k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1222
1.47k
                    /*operator_id=*/source_id);
1223
1.47k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1224
1.47k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1225
            // 2. create and set sink operator of data stream sender for new pipeline
1226
1227
1.47k
            DataSinkOperatorPtr sink_op;
1228
1.47k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1229
1.47k
                    state, *exchange_row_desc, next_sink_operator_id(),
1230
1.47k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1231
1.47k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1232
1233
1.47k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1234
1.47k
            {
1235
1.47k
                TDataSink* t = pool->add(new TDataSink());
1236
1.47k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1237
1.47k
                RETURN_IF_ERROR(sink_op->init(*t));
1238
1.47k
            }
1239
1240
            // 3. set dependency dag
1241
1.47k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1242
1.47k
        }
1243
566
        if (sources.empty()) {
1244
0
            return Status::InternalError("size of sources must be greater than 0");
1245
0
        }
1246
566
        break;
1247
566
    }
1248
566
    case TDataSinkType::BLACKHOLE_SINK: {
1249
3
        if (!thrift_sink.__isset.blackhole_sink) {
1250
0
            return Status::InternalError("Missing blackhole sink.");
1251
0
        }
1252
1253
3
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1254
3
        break;
1255
3
    }
1256
0
    case TDataSinkType::TVF_TABLE_SINK: {
1257
0
        if (!thrift_sink.__isset.tvf_table_sink) {
1258
0
            return Status::InternalError("Missing TVF table sink.");
1259
0
        }
1260
0
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1261
0
                                                        output_exprs);
1262
0
        break;
1263
0
    }
1264
0
    default:
1265
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1266
318k
    }
1267
317k
    return Status::OK();
1268
318k
}
1269
1270
// NOLINTBEGIN(readability-function-size)
1271
// NOLINTBEGIN(readability-function-cognitive-complexity)
1272
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1273
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1274
                                                 PipelinePtr& cur_pipe, int parent_idx,
1275
                                                 int child_idx,
1276
                                                 const bool followed_by_shuffled_operator,
1277
                                                 const bool require_bucket_distribution,
1278
507k
                                                 OperatorPtr& cache_op) {
1279
507k
    std::vector<DataSinkOperatorPtr> sink_ops;
1280
507k
    Defer defer = Defer([&]() {
1281
505k
        if (op) {
1282
505k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1283
505k
        }
1284
505k
        for (auto& s : sink_ops) {
1285
84.6k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1286
84.6k
        }
1287
505k
    });
1288
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1289
    // Therefore, here we need to use a stack-like structure.
1290
507k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1291
507k
    std::stringstream error_msg;
1292
507k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1293
1294
507k
    bool fe_with_old_version = false;
1295
507k
    switch (tnode.node_type) {
1296
159k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1297
159k
        op = std::make_shared<OlapScanOperatorX>(
1298
159k
                pool, tnode, next_operator_id(), descs, _num_instances,
1299
159k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1300
159k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1301
159k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1302
159k
        break;
1303
159k
    }
1304
77
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1305
77
        DCHECK(_query_ctx != nullptr);
1306
77
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1307
77
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1308
77
                                                    _num_instances);
1309
77
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1310
77
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1311
77
        break;
1312
77
    }
1313
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1314
0
        if (config::enable_java_support) {
1315
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1316
0
                                                     _num_instances);
1317
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1318
0
        } else {
1319
0
            return Status::InternalError(
1320
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1321
0
                    "to true and restart be.");
1322
0
        }
1323
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
0
        break;
1325
0
    }
1326
2.64k
    case TPlanNodeType::FILE_SCAN_NODE: {
1327
2.64k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1328
2.64k
                                                 _num_instances);
1329
2.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1330
2.64k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1331
2.64k
        break;
1332
2.64k
    }
1333
0
    case TPlanNodeType::ES_SCAN_NODE:
1334
0
    case TPlanNodeType::ES_HTTP_SCAN_NODE: {
1335
0
        op = std::make_shared<EsScanOperatorX>(pool, tnode, next_operator_id(), descs,
1336
0
                                               _num_instances);
1337
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1338
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1339
0
        break;
1340
0
    }
1341
109k
    case TPlanNodeType::EXCHANGE_NODE: {
1342
109k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1343
109k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1344
18.4E
                                  : 0;
1345
109k
        DCHECK_GT(num_senders, 0);
1346
109k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1347
109k
                                                       num_senders);
1348
109k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1349
109k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1350
109k
        break;
1351
109k
    }
1352
133k
    case TPlanNodeType::AGGREGATION_NODE: {
1353
133k
        if (tnode.agg_node.grouping_exprs.empty() &&
1354
133k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1355
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1356
0
                                         ": group by and output is empty");
1357
0
        }
1358
133k
        bool need_create_cache_op =
1359
133k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1360
133k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1361
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1362
10
            auto cache_source_id = next_operator_id();
1363
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1364
10
                                                        _params.fragment.query_cache_param);
1365
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1366
1367
10
            const auto downstream_pipeline_id = cur_pipe->id();
1368
10
            if (!_dag.contains(downstream_pipeline_id)) {
1369
10
                _dag.insert({downstream_pipeline_id, {}});
1370
10
            }
1371
10
            new_pipe = add_pipeline(cur_pipe);
1372
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1373
1374
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1375
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1376
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1377
10
            return Status::OK();
1378
10
        };
1379
133k
        const bool group_by_limit_opt =
1380
133k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1381
1382
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1383
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1384
133k
        const bool enable_spill = _runtime_state->enable_spill() &&
1385
133k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1386
133k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1387
133k
                                      tnode.agg_node.use_streaming_preaggregation &&
1388
133k
                                      !tnode.agg_node.grouping_exprs.empty();
1389
        // TODO: distinct streaming agg does not support spill.
1390
133k
        const bool can_use_distinct_streaming_agg =
1391
133k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1392
133k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1393
133k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1394
133k
                _params.query_options.enable_distinct_streaming_aggregation;
1395
1396
133k
        if (can_use_distinct_streaming_agg) {
1397
90.8k
            if (need_create_cache_op) {
1398
8
                PipelinePtr new_pipe;
1399
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1400
1401
8
                cache_op = op;
1402
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1403
8
                                                                     tnode, descs);
1404
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1405
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1406
8
                cur_pipe = new_pipe;
1407
90.7k
            } else {
1408
90.7k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1409
90.7k
                                                                     tnode, descs);
1410
90.7k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1411
90.7k
            }
1412
90.8k
        } else if (is_streaming_agg) {
1413
1.23k
            if (need_create_cache_op) {
1414
0
                PipelinePtr new_pipe;
1415
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1416
0
                cache_op = op;
1417
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1418
0
                                                             descs);
1419
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1420
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1421
0
                cur_pipe = new_pipe;
1422
1.23k
            } else {
1423
1.23k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1424
1.23k
                                                             descs);
1425
1.23k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1426
1.23k
            }
1427
41.1k
        } else {
1428
            // create new pipeline to add query cache operator
1429
41.1k
            PipelinePtr new_pipe;
1430
41.1k
            if (need_create_cache_op) {
1431
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1432
2
                cache_op = op;
1433
2
            }
1434
1435
41.1k
            if (enable_spill) {
1436
86
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1437
86
                                                                     next_operator_id(), descs);
1438
41.1k
            } else {
1439
41.1k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1440
41.1k
            }
1441
41.1k
            if (need_create_cache_op) {
1442
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1443
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1444
2
                cur_pipe = new_pipe;
1445
41.1k
            } else {
1446
41.1k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1447
41.1k
            }
1448
1449
41.1k
            const auto downstream_pipeline_id = cur_pipe->id();
1450
41.1k
            if (!_dag.contains(downstream_pipeline_id)) {
1451
40.0k
                _dag.insert({downstream_pipeline_id, {}});
1452
40.0k
            }
1453
41.1k
            cur_pipe = add_pipeline(cur_pipe);
1454
41.1k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1455
1456
41.1k
            if (enable_spill) {
1457
86
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1458
86
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1459
41.1k
            } else {
1460
41.1k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1461
41.1k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1462
41.1k
            }
1463
41.1k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1464
41.1k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1465
41.1k
        }
1466
133k
        break;
1467
133k
    }
1468
133k
    case TPlanNodeType::HASH_JOIN_NODE: {
1469
7.02k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1470
7.02k
                                       tnode.hash_join_node.is_broadcast_join;
1471
7.02k
        const auto enable_spill = _runtime_state->enable_spill();
1472
7.02k
        if (enable_spill && !is_broadcast_join) {
1473
0
            auto tnode_ = tnode;
1474
0
            tnode_.runtime_filters.clear();
1475
0
            auto inner_probe_operator =
1476
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1477
1478
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1479
            // So here use `tnode_` which has no runtime filters.
1480
0
            auto probe_side_inner_sink_operator =
1481
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1482
1483
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1484
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1485
1486
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1487
0
                    pool, tnode_, next_operator_id(), descs);
1488
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1489
0
                                                inner_probe_operator);
1490
0
            op = std::move(probe_operator);
1491
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1492
1493
0
            const auto downstream_pipeline_id = cur_pipe->id();
1494
0
            if (!_dag.contains(downstream_pipeline_id)) {
1495
0
                _dag.insert({downstream_pipeline_id, {}});
1496
0
            }
1497
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1498
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1499
1500
0
            auto inner_sink_operator =
1501
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1502
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1503
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1504
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1505
1506
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1507
0
            sink_ops.push_back(std::move(sink_operator));
1508
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1509
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1510
1511
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1512
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1513
7.02k
        } else {
1514
7.02k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1515
7.02k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1516
1517
7.02k
            const auto downstream_pipeline_id = cur_pipe->id();
1518
7.02k
            if (!_dag.contains(downstream_pipeline_id)) {
1519
6.24k
                _dag.insert({downstream_pipeline_id, {}});
1520
6.24k
            }
1521
7.02k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1522
7.02k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1523
1524
7.02k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1525
7.02k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1526
7.02k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1527
7.02k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1528
1529
7.02k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1530
7.02k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1531
7.02k
        }
1532
7.02k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1533
2.05k
            std::shared_ptr<HashJoinSharedState> shared_state =
1534
2.05k
                    HashJoinSharedState::create_shared(_num_instances);
1535
14.6k
            for (int i = 0; i < _num_instances; i++) {
1536
12.6k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1537
12.6k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1538
12.6k
                sink_dep->set_shared_state(shared_state.get());
1539
12.6k
                shared_state->sink_deps.push_back(sink_dep);
1540
12.6k
            }
1541
2.05k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1542
2.05k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1543
2.05k
            _op_id_to_shared_state.insert(
1544
2.05k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1545
2.05k
        }
1546
7.02k
        break;
1547
7.02k
    }
1548
1.77k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1549
1.77k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1550
1.77k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1551
1552
1.77k
        const auto downstream_pipeline_id = cur_pipe->id();
1553
1.77k
        if (!_dag.contains(downstream_pipeline_id)) {
1554
1.54k
            _dag.insert({downstream_pipeline_id, {}});
1555
1.54k
        }
1556
1.77k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1557
1.77k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1558
1559
1.77k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1560
1.77k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1561
1.77k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1562
1.77k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1563
1.77k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
1.77k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
1.77k
        break;
1566
1.77k
    }
1567
48.2k
    case TPlanNodeType::UNION_NODE: {
1568
48.2k
        int child_count = tnode.num_children;
1569
48.2k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1570
48.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1571
1572
48.2k
        const auto downstream_pipeline_id = cur_pipe->id();
1573
48.2k
        if (!_dag.contains(downstream_pipeline_id)) {
1574
47.7k
            _dag.insert({downstream_pipeline_id, {}});
1575
47.7k
        }
1576
49.2k
        for (int i = 0; i < child_count; i++) {
1577
1.01k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1578
1.01k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1579
1.01k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1580
1.01k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1581
1.01k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1582
1.01k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1583
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1584
1.01k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1585
1.01k
        }
1586
48.2k
        break;
1587
48.2k
    }
1588
48.2k
    case TPlanNodeType::SORT_NODE: {
1589
32.0k
        const auto should_spill = _runtime_state->enable_spill() &&
1590
32.0k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1591
32.0k
        const bool use_local_merge =
1592
32.0k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1593
32.0k
        if (should_spill) {
1594
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1595
32.0k
        } else if (use_local_merge) {
1596
30.2k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1597
30.2k
                                                                 descs);
1598
30.2k
        } else {
1599
1.87k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1600
1.87k
        }
1601
32.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1602
1603
32.0k
        const auto downstream_pipeline_id = cur_pipe->id();
1604
32.0k
        if (!_dag.contains(downstream_pipeline_id)) {
1605
32.0k
            _dag.insert({downstream_pipeline_id, {}});
1606
32.0k
        }
1607
32.0k
        cur_pipe = add_pipeline(cur_pipe);
1608
32.0k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1609
1610
32.0k
        if (should_spill) {
1611
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1612
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
32.0k
        } else {
1614
32.0k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1615
32.0k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1616
32.0k
        }
1617
32.0k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1618
32.0k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1619
32.0k
        break;
1620
32.0k
    }
1621
32.0k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1622
63
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1623
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1624
1625
63
        const auto downstream_pipeline_id = cur_pipe->id();
1626
63
        if (!_dag.contains(downstream_pipeline_id)) {
1627
63
            _dag.insert({downstream_pipeline_id, {}});
1628
63
        }
1629
63
        cur_pipe = add_pipeline(cur_pipe);
1630
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1631
1632
63
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1633
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1634
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1635
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1636
63
        break;
1637
63
    }
1638
1.60k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1639
1.60k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1640
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1641
1642
1.60k
        const auto downstream_pipeline_id = cur_pipe->id();
1643
1.60k
        if (!_dag.contains(downstream_pipeline_id)) {
1644
1.58k
            _dag.insert({downstream_pipeline_id, {}});
1645
1.58k
        }
1646
1.60k
        cur_pipe = add_pipeline(cur_pipe);
1647
1.60k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1648
1649
1.60k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1650
1.60k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1651
1.60k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1652
1.60k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1653
1.60k
        break;
1654
1.60k
    }
1655
1.60k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1656
671
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1657
671
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1658
671
        break;
1659
671
    }
1660
671
    case TPlanNodeType::INTERSECT_NODE: {
1661
114
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1662
114
                                                                      cur_pipe, sink_ops));
1663
114
        break;
1664
114
    }
1665
125
    case TPlanNodeType::EXCEPT_NODE: {
1666
125
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1667
125
                                                                       cur_pipe, sink_ops));
1668
125
        break;
1669
125
    }
1670
314
    case TPlanNodeType::REPEAT_NODE: {
1671
314
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1672
314
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1673
314
        break;
1674
314
    }
1675
917
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1676
917
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1677
917
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1678
917
        break;
1679
917
    }
1680
917
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1681
18
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1682
18
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1683
18
        break;
1684
18
    }
1685
1.45k
    case TPlanNodeType::EMPTY_SET_NODE: {
1686
1.45k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1687
1.45k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1688
1.45k
        break;
1689
1.45k
    }
1690
1.45k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1691
265
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
265
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
265
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1694
265
        break;
1695
265
    }
1696
1.52k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1697
1.52k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1698
1.52k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1699
1.52k
        break;
1700
1.52k
    }
1701
4.44k
    case TPlanNodeType::META_SCAN_NODE: {
1702
4.44k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1703
4.44k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1704
4.44k
        break;
1705
4.44k
    }
1706
4.44k
    case TPlanNodeType::SELECT_NODE: {
1707
331
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1708
331
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1709
331
        break;
1710
331
    }
1711
331
    case TPlanNodeType::REC_CTE_NODE: {
1712
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1713
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1714
1715
151
        const auto downstream_pipeline_id = cur_pipe->id();
1716
151
        if (!_dag.contains(downstream_pipeline_id)) {
1717
148
            _dag.insert({downstream_pipeline_id, {}});
1718
148
        }
1719
1720
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1721
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1722
1723
151
        DataSinkOperatorPtr anchor_sink;
1724
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1725
151
                                                                  op->operator_id(), tnode, descs);
1726
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1727
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1728
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1729
1730
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1731
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1732
1733
151
        DataSinkOperatorPtr rec_sink;
1734
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1735
151
                                                         tnode, descs);
1736
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1737
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1738
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1739
1740
151
        break;
1741
151
    }
1742
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1743
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1744
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
1.95k
        break;
1746
1.95k
    }
1747
1.95k
    default:
1748
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1749
0
                                     print_plan_node_type(tnode.node_type));
1750
507k
    }
1751
505k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1752
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1753
0
        op->set_serial_operator();
1754
0
    }
1755
1756
505k
    return Status::OK();
1757
507k
}
1758
// NOLINTEND(readability-function-cognitive-complexity)
1759
// NOLINTEND(readability-function-size)
1760
1761
template <bool is_intersect>
1762
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1763
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1764
239
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1765
239
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1766
239
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1767
1768
239
    const auto downstream_pipeline_id = cur_pipe->id();
1769
239
    if (!_dag.contains(downstream_pipeline_id)) {
1770
222
        _dag.insert({downstream_pipeline_id, {}});
1771
222
    }
1772
1773
810
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1774
571
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1775
571
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1776
1777
571
        if (child_id == 0) {
1778
239
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1779
239
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1780
332
        } else {
1781
332
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1782
332
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1783
332
        }
1784
571
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1785
571
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1786
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1787
571
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1788
571
    }
1789
1790
239
    return Status::OK();
1791
239
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1764
114
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1765
114
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1766
114
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1767
1768
114
    const auto downstream_pipeline_id = cur_pipe->id();
1769
114
    if (!_dag.contains(downstream_pipeline_id)) {
1770
105
        _dag.insert({downstream_pipeline_id, {}});
1771
105
    }
1772
1773
420
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1774
306
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1775
306
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1776
1777
306
        if (child_id == 0) {
1778
114
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1779
114
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1780
192
        } else {
1781
192
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1782
192
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1783
192
        }
1784
306
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1785
306
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1786
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1787
306
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1788
306
    }
1789
1790
114
    return Status::OK();
1791
114
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1764
125
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1765
125
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1766
125
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1767
1768
125
    const auto downstream_pipeline_id = cur_pipe->id();
1769
125
    if (!_dag.contains(downstream_pipeline_id)) {
1770
117
        _dag.insert({downstream_pipeline_id, {}});
1771
117
    }
1772
1773
390
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1774
265
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1775
265
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1776
1777
265
        if (child_id == 0) {
1778
125
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1779
125
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1780
140
        } else {
1781
140
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1782
140
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1783
140
        }
1784
265
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1785
265
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1786
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1787
265
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1788
265
    }
1789
1790
125
    return Status::OK();
1791
125
}
1792
1793
316k
Status PipelineFragmentContext::submit() {
1794
316k
    if (_submitted) {
1795
0
        return Status::InternalError("submitted");
1796
0
    }
1797
316k
    _submitted = true;
1798
1799
316k
    int submit_tasks = 0;
1800
316k
    Status st;
1801
316k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1802
939k
    for (auto& task : _tasks) {
1803
1.65M
        for (auto& t : task) {
1804
1.65M
            st = scheduler->submit(t.first);
1805
1.65M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1806
1.65M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1807
1.65M
            if (!st) {
1808
0
                cancel(Status::InternalError("submit context to executor fail"));
1809
0
                std::lock_guard<std::mutex> l(_task_mutex);
1810
0
                _total_tasks = submit_tasks;
1811
0
                break;
1812
0
            }
1813
1.65M
            submit_tasks++;
1814
1.65M
        }
1815
939k
    }
1816
316k
    if (!st.ok()) {
1817
0
        bool need_remove = false;
1818
0
        {
1819
0
            std::lock_guard<std::mutex> l(_task_mutex);
1820
0
            if (_closed_tasks >= _total_tasks) {
1821
0
                need_remove = _close_fragment_instance();
1822
0
            }
1823
0
        }
1824
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1825
0
        if (need_remove) {
1826
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1827
0
        }
1828
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1829
0
                                     BackendOptions::get_localhost());
1830
316k
    } else {
1831
316k
        return st;
1832
316k
    }
1833
316k
}
1834
1835
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1836
0
    if (_runtime_state->enable_profile()) {
1837
0
        std::stringstream ss;
1838
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1839
0
            runtime_profile_ptr->pretty_print(&ss);
1840
0
        }
1841
1842
0
        if (_runtime_state->load_channel_profile()) {
1843
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1844
0
        }
1845
1846
0
        auto profile_str =
1847
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1848
0
                            this->_fragment_id, extra_info, ss.str());
1849
0
        LOG_LONG_STRING(INFO, profile_str);
1850
0
    }
1851
0
}
1852
// If all pipeline tasks binded to the fragment instance are finished, then we could
1853
// close the fragment instance.
1854
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1855
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1856
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1857
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1858
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1859
// (via debug_string()).
1860
318k
bool PipelineFragmentContext::_close_fragment_instance() {
1861
318k
    if (_is_fragment_instance_closed) {
1862
0
        return false;
1863
0
    }
1864
318k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1865
318k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1866
318k
    if (!_need_notify_close) {
1867
315k
        auto st = send_report(true);
1868
315k
        if (!st) {
1869
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1870
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1871
0
        }
1872
315k
    }
1873
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1874
    // Since stream load does not have someting like coordinator on FE, so
1875
    // backend can not report profile to FE, ant its profile can not be shown
1876
    // in the same way with other query. So we print the profile content to info log.
1877
1878
318k
    if (_runtime_state->enable_profile() &&
1879
318k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1880
2.40k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1881
2.40k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1882
0
        std::stringstream ss;
1883
        // Compute the _local_time_percent before pretty_print the runtime_profile
1884
        // Before add this operation, the print out like that:
1885
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1886
        // After add the operation, the print out like that:
1887
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1888
        // We can easily know the exec node execute time without child time consumed.
1889
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1890
0
            runtime_profile_ptr->pretty_print(&ss);
1891
0
        }
1892
1893
0
        if (_runtime_state->load_channel_profile()) {
1894
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1895
0
        }
1896
1897
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1898
0
    }
1899
1900
318k
    if (_query_ctx->enable_profile()) {
1901
2.40k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1902
2.40k
                                         collect_realtime_load_channel_profile());
1903
2.40k
    }
1904
1905
    // Return whether the caller needs to remove from the pipeline map.
1906
    // The caller must do this after releasing _task_mutex.
1907
318k
    return !_need_notify_close;
1908
318k
}
1909
1910
1.64M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1911
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1912
1.64M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1913
1.64M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1914
504k
        if (_dag.contains(pipeline_id)) {
1915
285k
            for (auto dep : _dag[pipeline_id]) {
1916
285k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1917
285k
            }
1918
226k
        }
1919
504k
    }
1920
1.64M
    bool need_remove = false;
1921
1.64M
    {
1922
1.64M
        std::lock_guard<std::mutex> l(_task_mutex);
1923
1.64M
        ++_closed_tasks;
1924
1.64M
        if (_closed_tasks >= _total_tasks) {
1925
318k
            need_remove = _close_fragment_instance();
1926
318k
        }
1927
1.64M
    }
1928
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1929
1.64M
    if (need_remove) {
1930
315k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1931
315k
    }
1932
1.64M
}
1933
1934
41.4k
std::string PipelineFragmentContext::get_load_error_url() {
1935
41.4k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1936
0
        return to_load_error_http_path(str);
1937
0
    }
1938
118k
    for (auto& tasks : _tasks) {
1939
204k
        for (auto& task : tasks) {
1940
204k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1941
148
                return to_load_error_http_path(str);
1942
148
            }
1943
204k
        }
1944
118k
    }
1945
41.2k
    return "";
1946
41.4k
}
1947
1948
41.4k
std::string PipelineFragmentContext::get_first_error_msg() {
1949
41.4k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
1950
0
        return str;
1951
0
    }
1952
118k
    for (auto& tasks : _tasks) {
1953
204k
        for (auto& task : tasks) {
1954
204k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
1955
148
                return str;
1956
148
            }
1957
204k
        }
1958
118k
    }
1959
41.2k
    return "";
1960
41.4k
}
1961
1962
318k
Status PipelineFragmentContext::send_report(bool done) {
1963
318k
    Status exec_status = _query_ctx->exec_status();
1964
    // If plan is done successfully, but _is_report_success is false,
1965
    // no need to send report.
1966
    // Load will set _is_report_success to true because load wants to know
1967
    // the process.
1968
318k
    if (!_is_report_success && done && exec_status.ok()) {
1969
283k
        return Status::OK();
1970
283k
    }
1971
1972
    // If both _is_report_success and _is_report_on_cancel are false,
1973
    // which means no matter query is success or failed, no report is needed.
1974
    // This may happen when the query limit reached and
1975
    // a internal cancellation being processed
1976
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
1977
    // be set to false, to avoid sending fault report to FE.
1978
35.9k
    if (!_is_report_success && !_is_report_on_cancel) {
1979
129
        if (done) {
1980
            // 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.
1981
129
            return Status::OK();
1982
129
        }
1983
0
        return Status::NeedSendAgain("");
1984
129
    }
1985
1986
35.7k
    std::vector<RuntimeState*> runtime_states;
1987
1988
87.9k
    for (auto& tasks : _tasks) {
1989
139k
        for (auto& task : tasks) {
1990
139k
            runtime_states.push_back(task.second.get());
1991
139k
        }
1992
87.9k
    }
1993
1994
35.7k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
1995
35.7k
                                        ? get_load_error_url()
1996
35.7k
                                        : _query_ctx->get_load_error_url();
1997
35.7k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
1998
35.7k
                                          ? get_first_error_msg()
1999
35.7k
                                          : _query_ctx->get_first_error_msg();
2000
2001
35.7k
    ReportStatusRequest req {.status = exec_status,
2002
35.7k
                             .runtime_states = runtime_states,
2003
35.7k
                             .done = done || !exec_status.ok(),
2004
35.7k
                             .coord_addr = _query_ctx->coord_addr,
2005
35.7k
                             .query_id = _query_id,
2006
35.7k
                             .fragment_id = _fragment_id,
2007
35.7k
                             .fragment_instance_id = TUniqueId(),
2008
35.7k
                             .backend_num = -1,
2009
35.7k
                             .runtime_state = _runtime_state.get(),
2010
35.7k
                             .load_error_url = load_eror_url,
2011
35.7k
                             .first_error_msg = first_error_msg,
2012
35.7k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2013
2014
35.7k
    return _report_status_cb(
2015
35.7k
            req, std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()));
2016
35.9k
}
2017
2018
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2019
0
    size_t res = 0;
2020
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2021
    // here to traverse the vector.
2022
0
    for (const auto& task_instances : _tasks) {
2023
0
        for (const auto& task : task_instances) {
2024
0
            if (task.first->is_running()) {
2025
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2026
0
                                      << " is running, task: " << (void*)task.first.get()
2027
0
                                      << ", is_running: " << task.first->is_running();
2028
0
                *has_running_task = true;
2029
0
                return 0;
2030
0
            }
2031
2032
0
            size_t revocable_size = task.first->get_revocable_size();
2033
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2034
0
                res += revocable_size;
2035
0
            }
2036
0
        }
2037
0
    }
2038
0
    return res;
2039
0
}
2040
2041
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2042
0
    std::vector<PipelineTask*> revocable_tasks;
2043
0
    for (const auto& task_instances : _tasks) {
2044
0
        for (const auto& task : task_instances) {
2045
0
            size_t revocable_size_ = task.first->get_revocable_size();
2046
2047
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2048
0
                revocable_tasks.emplace_back(task.first.get());
2049
0
            }
2050
0
        }
2051
0
    }
2052
0
    return revocable_tasks;
2053
0
}
2054
2055
126
std::string PipelineFragmentContext::debug_string() {
2056
126
    std::lock_guard<std::mutex> l(_task_mutex);
2057
126
    fmt::memory_buffer debug_string_buffer;
2058
126
    fmt::format_to(debug_string_buffer,
2059
126
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2060
126
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2061
126
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2062
342
    for (size_t j = 0; j < _tasks.size(); j++) {
2063
216
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2064
592
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2065
376
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2066
376
                           _tasks[j][i].first->debug_string());
2067
376
        }
2068
216
    }
2069
2070
126
    return fmt::to_string(debug_string_buffer);
2071
126
}
2072
2073
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2074
2.40k
PipelineFragmentContext::collect_realtime_profile() const {
2075
2.40k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2076
2077
    // we do not have mutex to protect pipeline_id_to_profile
2078
    // so we need to make sure this funciton is invoked after fragment context
2079
    // has already been prepared.
2080
2.40k
    if (!_prepared) {
2081
0
        std::string msg =
2082
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2083
0
        DCHECK(false) << msg;
2084
0
        LOG_ERROR(msg);
2085
0
        return res;
2086
0
    }
2087
2088
    // Make sure first profile is fragment level profile
2089
2.40k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2090
2.40k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2091
2.40k
    res.push_back(fragment_profile);
2092
2093
    // pipeline_id_to_profile is initialized in prepare stage
2094
4.62k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2095
4.62k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2096
4.62k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2097
4.62k
        res.push_back(profile_ptr);
2098
4.62k
    }
2099
2100
2.40k
    return res;
2101
2.40k
}
2102
2103
std::shared_ptr<TRuntimeProfileTree>
2104
2.40k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2105
    // we do not have mutex to protect pipeline_id_to_profile
2106
    // so we need to make sure this funciton is invoked after fragment context
2107
    // has already been prepared.
2108
2.40k
    if (!_prepared) {
2109
0
        std::string msg =
2110
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2111
0
        DCHECK(false) << msg;
2112
0
        LOG_ERROR(msg);
2113
0
        return nullptr;
2114
0
    }
2115
2116
6.95k
    for (const auto& tasks : _tasks) {
2117
14.2k
        for (const auto& task : tasks) {
2118
14.2k
            if (task.second->load_channel_profile() == nullptr) {
2119
0
                continue;
2120
0
            }
2121
2122
14.2k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2123
2124
14.2k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2125
14.2k
                                                           _runtime_state->profile_level());
2126
14.2k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2127
14.2k
        }
2128
6.95k
    }
2129
2130
2.40k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2131
2.40k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2132
2.40k
                                                      _runtime_state->profile_level());
2133
2.40k
    return load_channel_profile;
2134
2.40k
}
2135
2136
// Collect runtime filter IDs registered by all tasks in this PFC.
2137
// Used during recursive CTE stage transitions to know which filters to deregister
2138
// before creating the new PFC for the next recursion round.
2139
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2140
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2141
// the vector sizes do not change, and individual RuntimeState filter sets are
2142
// written only during open() which has completed by the time we reach rerun.
2143
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2144
3.28k
    std::set<int> result;
2145
6.05k
    for (const auto& _task : _tasks) {
2146
10.5k
        for (const auto& task : _task) {
2147
10.5k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2148
10.5k
            result.merge(set);
2149
10.5k
        }
2150
6.05k
    }
2151
3.28k
    if (_runtime_state) {
2152
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2153
3.28k
        result.merge(set);
2154
3.28k
    }
2155
3.28k
    return result;
2156
3.28k
}
2157
2158
319k
void PipelineFragmentContext::_release_resource() {
2159
319k
    std::lock_guard<std::mutex> l(_task_mutex);
2160
    // The memory released by the query end is recorded in the query mem tracker.
2161
319k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2162
319k
    auto st = _query_ctx->exec_status();
2163
939k
    for (auto& _task : _tasks) {
2164
939k
        if (!_task.empty()) {
2165
939k
            _call_back(_task.front().first->runtime_state(), &st);
2166
939k
        }
2167
939k
    }
2168
319k
    _tasks.clear();
2169
319k
    _dag.clear();
2170
319k
    _pip_id_to_pipeline.clear();
2171
319k
    _pipelines.clear();
2172
319k
    _sink.reset();
2173
319k
    _root_op.reset();
2174
319k
    _runtime_filter_mgr_map.clear();
2175
319k
    _op_id_to_shared_state.clear();
2176
319k
}
2177
2178
#include "common/compile_check_end.h"
2179
} // namespace doris