Coverage Report

Created: 2026-06-12 06:44

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
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#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
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#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
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#include "runtime/exec_env.h"
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#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
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#include "util/client_cache.h"
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#include "util/countdown_latch.h"
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#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
448k
        : _query_id(std::move(query_id)),
144
448k
          _fragment_id(request.fragment_id),
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448k
          _exec_env(exec_env),
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448k
          _query_ctx(std::move(query_ctx)),
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448k
          _call_back(call_back),
148
448k
          _is_report_on_cancel(true),
149
448k
          _params(request),
150
448k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
448k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
448k
                                                               : false) {
153
448k
    _fragment_watcher.start();
154
448k
}
155
156
449k
PipelineFragmentContext::~PipelineFragmentContext() {
157
449k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
449k
            .tag("query_id", print_id(_query_id))
159
449k
            .tag("fragment_id", _fragment_id);
160
449k
    _release_resource();
161
449k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
449k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
449k
        _runtime_state.reset();
165
449k
        _query_ctx.reset();
166
449k
    }
167
449k
}
168
169
72
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
72
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
72
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
72
}
175
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// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
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// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
9.95k
bool PipelineFragmentContext::notify_close() {
181
9.95k
    bool all_closed = false;
182
9.95k
    bool need_remove = false;
183
9.95k
    {
184
9.95k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.95k
        if (_closed_tasks >= _total_tasks) {
186
3.46k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
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3.40k
                need_remove = true;
193
3.40k
            }
194
3.46k
            all_closed = true;
195
3.46k
        }
196
        // make fragment release by self after cancel
197
9.95k
        _need_notify_close = false;
198
9.95k
    }
199
9.95k
    if (need_remove) {
200
3.40k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.40k
    }
202
9.95k
    return all_closed;
203
9.95k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
209
6.47k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.47k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.47k
            .tag("query_id", print_id(_query_id))
212
6.47k
            .tag("fragment_id", _fragment_id)
213
6.47k
            .tag("reason", reason.to_string());
214
6.47k
    if (notify_close()) {
215
78
        return;
216
78
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.39k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
6.39k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
6.39k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
6.39k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
20
        _query_ctx->set_load_error_url(error_url);
236
20
    }
237
238
6.39k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
20
        _query_ctx->set_first_error_msg(first_error_msg);
240
20
    }
241
242
6.39k
    _query_ctx->cancel(reason, _fragment_id);
243
6.39k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
390
        _is_report_on_cancel = false;
245
6.00k
    } else {
246
30.0k
        for (auto& id : _fragment_instance_ids) {
247
30.0k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
30.0k
        }
249
6.00k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
6.39k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.39k
    if (stream_load_ctx != nullptr) {
254
28
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
28
        stream_load_ctx->error_url = get_load_error_url();
259
28
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
28
    }
261
262
31.3k
    for (auto& tasks : _tasks) {
263
74.2k
        for (auto& task : tasks) {
264
74.2k
            task.first->unblock_all_dependencies();
265
74.2k
        }
266
31.3k
    }
267
6.39k
}
268
269
689k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
689k
    PipelineId id = _next_pipeline_id++;
271
689k
    auto pipeline = std::make_shared<Pipeline>(
272
689k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
689k
            parent ? parent->num_tasks() : _num_instances);
274
689k
    if (idx >= 0) {
275
114k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
575k
    } else {
277
575k
        _pipelines.emplace_back(pipeline);
278
575k
    }
279
689k
    if (parent) {
280
233k
        parent->set_children(pipeline);
281
233k
    }
282
689k
    return pipeline;
283
689k
}
284
285
448k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
448k
    {
287
448k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
448k
        auto root_pipeline = add_pipeline();
290
448k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
448k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
448k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
448k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
448k
                                          _params.fragment.output_exprs, _params,
299
448k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
448k
                                          *_desc_tbl, root_pipeline->id()));
301
448k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
448k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
574k
        for (PipelinePtr& pipeline : _pipelines) {
305
574k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
574k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
574k
        }
308
448k
    }
309
    // 4. Build local exchanger
310
448k
    if (_runtime_state->enable_local_shuffle()) {
311
444k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
444k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
444k
                                             _params.bucket_seq_to_instance_idx,
314
444k
                                             _params.shuffle_idx_to_instance_idx));
315
444k
    }
316
317
    // 5. Initialize global states in pipelines.
318
690k
    for (PipelinePtr& pipeline : _pipelines) {
319
690k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
690k
        pipeline->children().clear();
321
690k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
690k
    }
323
324
447k
    {
325
447k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
447k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
447k
    }
329
330
447k
    return Status::OK();
331
447k
}
332
333
448k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
448k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
448k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
448k
        _timeout = _params.query_options.execution_timeout;
339
448k
    }
340
341
448k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
448k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
448k
    SCOPED_TIMER(_prepare_timer);
344
448k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
448k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
448k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
448k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
448k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
448k
    {
350
448k
        SCOPED_TIMER(_init_context_timer);
351
448k
        cast_set(_num_instances, _params.local_params.size());
352
448k
        _total_instances =
353
448k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
448k
        auto* fragment_context = this;
356
357
448k
        if (_params.query_options.__isset.is_report_success) {
358
446k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
446k
        }
360
361
        // 1. Set up the global runtime state.
362
448k
        _runtime_state = RuntimeState::create_unique(
363
448k
                _params.query_id, _params.fragment_id, _params.query_options,
364
448k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
448k
        _runtime_state->set_task_execution_context(shared_from_this());
366
448k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
448k
        if (_params.__isset.backend_id) {
368
443k
            _runtime_state->set_backend_id(_params.backend_id);
369
443k
        }
370
448k
        if (_params.__isset.import_label) {
371
231
            _runtime_state->set_import_label(_params.import_label);
372
231
        }
373
448k
        if (_params.__isset.db_name) {
374
183
            _runtime_state->set_db_name(_params.db_name);
375
183
        }
376
448k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
448k
        if (_params.is_simplified_param) {
381
149k
            _desc_tbl = _query_ctx->desc_tbl;
382
298k
        } else {
383
298k
            DCHECK(_params.__isset.desc_tbl);
384
298k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
298k
                                                  &_desc_tbl));
386
298k
        }
387
448k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
448k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
448k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
448k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
448k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
448k
        const auto target_size = _params.local_params.size();
395
448k
        _fragment_instance_ids.resize(target_size);
396
1.55M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.10M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.10M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.10M
        }
400
448k
    }
401
402
448k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
447k
    _init_next_report_time();
405
406
447k
    _prepared = true;
407
447k
    return Status::OK();
408
448k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.10M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.10M
    const auto& local_params = _params.local_params[instance_idx];
414
1.10M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.10M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.10M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.10M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.10M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.88M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.88M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.88M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.88M
                shared_state_map;
423
2.32M
        for (auto& op : pipeline->operators()) {
424
2.32M
            auto source_id = op->operator_id();
425
2.32M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.32M
                iter != _op_id_to_shared_state.end()) {
427
725k
                shared_state_map.insert({source_id, iter->second});
428
725k
            }
429
2.32M
        }
430
1.88M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.88M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.88M
                iter != _op_id_to_shared_state.end()) {
433
297k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
297k
            }
435
1.88M
        }
436
1.88M
        return shared_state_map;
437
1.88M
    };
438
439
3.41M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.30M
        auto& pipeline = _pipelines[pip_idx];
441
2.30M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.87M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.87M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.87M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.87M
            {
446
                // Initialize runtime state for this task
447
1.87M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.87M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.87M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.88M
                if (_params.__isset.backend_id) {
453
1.88M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.88M
                }
455
1.87M
                if (_params.__isset.import_label) {
456
232
                    task_runtime_state->set_import_label(_params.import_label);
457
232
                }
458
1.87M
                if (_params.__isset.db_name) {
459
184
                    task_runtime_state->set_db_name(_params.db_name);
460
184
                }
461
1.87M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.87M
                if (_params.__isset.wal_id) {
465
112
                    task_runtime_state->set_wal_id(_params.wal_id);
466
112
                }
467
1.87M
                if (_params.__isset.content_length) {
468
31
                    task_runtime_state->set_content_length(_params.content_length);
469
31
                }
470
471
1.87M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.87M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.87M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.87M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.87M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.87M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.87M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.87M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.87M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.87M
            }
482
1.87M
            auto cur_task_id = _total_tasks++;
483
1.87M
            task_runtime_state->set_task_id(cur_task_id);
484
1.87M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.87M
            auto task = std::make_shared<PipelineTask>(
486
1.87M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.87M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.87M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.87M
                    instance_idx);
490
1.87M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.87M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.87M
            _tasks[instance_idx].emplace_back(
493
1.87M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.87M
                            std::move(task), std::move(task_runtime_state)});
495
1.87M
        }
496
2.30M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
2.30M
    for (auto& _pipeline : _pipelines) {
516
2.30M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.87M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.87M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.87M
            if (_dag.contains(_pipeline->id())) {
522
1.20M
                auto& deps = _dag[_pipeline->id()];
523
1.90M
                for (auto& dep : deps) {
524
1.90M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.05M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.05M
                        if (ss) {
527
470k
                            task->inject_shared_state(ss);
528
585k
                        } else {
529
585k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
585k
                                    task->get_source_shared_state());
531
585k
                        }
532
1.05M
                    }
533
1.90M
                }
534
1.20M
            }
535
1.87M
        }
536
2.30M
    }
537
3.41M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.30M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.87M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.87M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.87M
            std::vector<TScanRangeParams> scan_ranges;
542
1.87M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.87M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
342k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
342k
            }
546
1.87M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.87M
                                                             _params.fragment.output_sink));
548
1.87M
        }
549
2.30M
    }
550
1.10M
    {
551
1.10M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.10M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.10M
    }
554
1.10M
    return Status::OK();
555
1.10M
}
556
557
448k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
448k
    _total_tasks = 0;
559
448k
    _closed_tasks = 0;
560
448k
    const auto target_size = _params.local_params.size();
561
448k
    _tasks.resize(target_size);
562
448k
    _runtime_filter_mgr_map.resize(target_size);
563
1.13M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
689k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
689k
    }
566
448k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
448k
    if (target_size > 1 &&
569
448k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
136k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
571
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
572
27.1k
        std::vector<Status> prepare_status(target_size);
573
27.1k
        int submitted_tasks = 0;
574
27.1k
        Status submit_status;
575
27.1k
        CountDownLatch latch((int)target_size);
576
244k
        for (int i = 0; i < target_size; i++) {
577
217k
            submit_status = thread_pool->submit_func([&, i]() {
578
217k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
217k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
217k
                latch.count_down();
581
217k
            });
582
217k
            if (LIKELY(submit_status.ok())) {
583
217k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
217k
        }
588
27.1k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
27.1k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
244k
        for (int i = 0; i < submitted_tasks; i++) {
593
217k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
217k
        }
597
420k
    } else {
598
1.31M
        for (int i = 0; i < target_size; i++) {
599
889k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
889k
        }
601
420k
    }
602
448k
    _pipeline_parent_map.clear();
603
448k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
448k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
448k
    return Status::OK();
608
448k
}
609
610
446k
void PipelineFragmentContext::_init_next_report_time() {
611
446k
    auto interval_s = config::pipeline_status_report_interval;
612
446k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
42.5k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.5k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
42.5k
        _previous_report_time =
617
42.5k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.5k
        _disable_period_report = false;
619
42.5k
    }
620
446k
}
621
622
4.78k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.78k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.78k
    DCHECK(disable == true);
625
4.78k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.78k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.78k
}
628
629
6.98M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
6.98M
    if (!_is_report_success) {
631
6.52M
        return;
632
6.52M
    }
633
458k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
458k
    if (disable) {
635
8.54k
        return;
636
8.54k
    }
637
450k
    int32_t interval_s = config::pipeline_status_report_interval;
638
450k
    if (interval_s <= 0) {
639
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
640
0
                        "trigger "
641
0
                        "report.";
642
0
    }
643
450k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
450k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
450k
    if (MonotonicNanos() > next_report_time) {
646
4.78k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.78k
                                                            std::memory_order_acq_rel)) {
648
12
            return;
649
12
        }
650
4.77k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
4.77k
        auto st = send_report(false);
667
4.77k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
4.77k
    }
673
450k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
445k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
445k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
445k
    int node_idx = 0;
682
683
445k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
445k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
445k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
687
0
        return Status::InternalError(
688
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
689
0
    }
690
445k
    return Status::OK();
691
445k
}
692
693
Status PipelineFragmentContext::_create_tree_helper(
694
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
695
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
696
668k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
668k
    if (*node_idx >= tnodes.size()) {
699
0
        return Status::InternalError(
700
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
701
0
                *node_idx, tnodes.size());
702
0
    }
703
668k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
668k
    int num_children = tnodes[*node_idx].num_children;
706
668k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
668k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
668k
    OperatorPtr op = nullptr;
710
668k
    OperatorPtr cache_op = nullptr;
711
668k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
668k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
668k
                                     followed_by_shuffled_operator,
714
668k
                                     current_require_bucket_distribution, cache_op));
715
    // Initialization must be done here. For example, group by expressions in agg will be used to
716
    // decide if a local shuffle should be planed, so it must be initialized here.
717
668k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
668k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
223k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
445k
    } else {
723
445k
        *root = op;
724
445k
    }
725
    /**
726
     * `ExchangeType::HASH_SHUFFLE` should be used if an operator is followed by a shuffled operator (shuffled hash join, union operator followed by co-located operators).
727
     *
728
     * For plan:
729
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
730
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
731
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
732
     *
733
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
734
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
735
     */
736
668k
    auto required_data_distribution =
737
668k
            cur_pipe->operators().empty()
738
668k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
668k
                    : op->required_data_distribution(_runtime_state.get());
740
668k
    current_followed_by_shuffled_operator =
741
668k
            ((followed_by_shuffled_operator ||
742
668k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
609k
                                             : op->is_shuffled_operator())) &&
744
668k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
668k
            (followed_by_shuffled_operator &&
746
556k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
668k
    current_require_bucket_distribution =
749
668k
            ((require_bucket_distribution ||
750
668k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
614k
                                             : op->is_colocated_operator())) &&
752
668k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
668k
            (require_bucket_distribution &&
754
563k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
668k
    if (num_children == 0) {
757
464k
        _use_serial_source = op->is_serial_operator();
758
464k
    }
759
    // rely on that tnodes is preorder of the plan
760
892k
    for (int i = 0; i < num_children; i++) {
761
223k
        ++*node_idx;
762
223k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
223k
                                            current_followed_by_shuffled_operator,
764
223k
                                            current_require_bucket_distribution));
765
766
        // we are expecting a child, but have used all nodes
767
        // this means we have been given a bad tree and must fail
768
223k
        if (*node_idx >= tnodes.size()) {
769
0
            return Status::InternalError(
770
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
771
0
                    "nodes: {}",
772
0
                    *node_idx, tnodes.size());
773
0
        }
774
223k
    }
775
776
668k
    return Status::OK();
777
668k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
114k
        PipelinePtr pipe_with_sink) {
782
114k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
114k
    pipe_with_source->set_num_tasks(_num_instances);
784
114k
    pipe_with_source->set_data_distribution(data_distribution);
785
114k
}
786
787
Status PipelineFragmentContext::_add_local_exchange_impl(
788
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
789
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
790
        const std::map<int, int>& bucket_seq_to_instance_idx,
791
114k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
114k
    auto& operators = cur_pipe->operators();
793
114k
    const auto downstream_pipeline_id = cur_pipe->id();
794
114k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
114k
    DataSinkOperatorPtr sink;
797
114k
    auto sink_id = next_sink_operator_id();
798
799
    /**
800
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
801
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
802
     */
803
114k
    const bool followed_by_shuffled_operator =
804
114k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
114k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
114k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
114k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
114k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
114k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
114k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
114k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
114k
    if (bucket_seq_to_instance_idx.empty() &&
813
114k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
10
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
10
    }
816
114k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
114k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
114k
                                          num_buckets, use_global_hash_shuffle,
819
114k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
114k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
114k
            LocalExchangeSharedState::create_shared(_num_instances);
824
114k
    switch (data_distribution.distribution_type) {
825
18.0k
    case ExchangeType::HASH_SHUFFLE:
826
18.0k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
18.0k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
18.0k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
18.0k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
18.1k
                        ? cast_set<int>(
831
18.1k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
18.4E
                        : 0);
833
18.0k
        break;
834
479
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
479
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
479
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
479
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
479
                        ? cast_set<int>(
839
479
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
479
                        : 0);
841
479
        break;
842
91.5k
    case ExchangeType::PASSTHROUGH:
843
91.5k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
91.5k
                cur_pipe->num_tasks(), _num_instances,
845
91.5k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
91.5k
                        ? cast_set<int>(
847
91.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
91.5k
                        : 0);
849
91.5k
        break;
850
357
    case ExchangeType::BROADCAST:
851
357
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
357
                cur_pipe->num_tasks(), _num_instances,
853
357
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
357
                        ? cast_set<int>(
855
357
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
357
                        : 0);
857
357
        break;
858
2.77k
    case ExchangeType::PASS_TO_ONE:
859
2.77k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
860
            // If shared hash table is enabled for BJ, hash table will be built by only one task
861
1.69k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.69k
                    cur_pipe->num_tasks(), _num_instances,
863
1.69k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.69k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.69k
                                                    .local_exchange_free_blocks_limit)
866
1.69k
                            : 0);
867
1.69k
        } else {
868
1.07k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.07k
                    cur_pipe->num_tasks(), _num_instances,
870
1.07k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.07k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.07k
                                                    .local_exchange_free_blocks_limit)
873
1.07k
                            : 0);
874
1.07k
        }
875
2.77k
        break;
876
1.02k
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
1.02k
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
1.02k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
1.02k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
1.02k
                        ? cast_set<int>(
881
1.02k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
1.02k
                        : 0);
883
1.02k
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
114k
    }
888
114k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
114k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
114k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
114k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
892
893
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
894
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
895
896
    // 3.1 Initialize new pipeline's operator list.
897
114k
    std::copy(operators.begin(), operators.begin() + idx,
898
114k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
114k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
114k
    OperatorPtr source_op;
905
114k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
114k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
114k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
114k
    if (!operators.empty()) {
909
40.6k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
40.6k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
40.6k
    }
912
114k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
114k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
114k
    std::vector<PipelineId> edges_with_source;
917
132k
    for (auto child : cur_pipe->children()) {
918
132k
        bool found = false;
919
147k
        for (auto op : new_pip->operators()) {
920
147k
            if (child->sink()->node_id() == op->node_id()) {
921
13.1k
                new_pip->set_children(child);
922
13.1k
                found = true;
923
13.1k
            };
924
147k
        }
925
132k
        if (!found) {
926
119k
            new_children.push_back(child);
927
119k
            edges_with_source.push_back(child->id());
928
119k
        }
929
132k
    }
930
114k
    new_children.push_back(new_pip);
931
114k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
114k
    if (!new_pip->children().empty()) {
935
7.59k
        std::vector<PipelineId> edges_with_sink;
936
13.1k
        for (auto child : new_pip->children()) {
937
13.1k
            edges_with_sink.push_back(child->id());
938
13.1k
        }
939
7.59k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.59k
    }
941
114k
    cur_pipe->set_children(new_children);
942
114k
    _dag[downstream_pipeline_id] = edges_with_source;
943
114k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
114k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
114k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
114k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
114k
    return Status::OK();
950
114k
}
951
952
Status PipelineFragmentContext::_add_local_exchange(
953
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
954
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
955
        const std::map<int, int>& bucket_seq_to_instance_idx,
956
189k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
189k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
50.0k
        return Status::OK();
959
50.0k
    }
960
961
139k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
43.8k
        return Status::OK();
963
43.8k
    }
964
95.9k
    *do_local_exchange = true;
965
966
95.9k
    auto& operators = cur_pipe->operators();
967
95.9k
    auto total_op_num = operators.size();
968
95.9k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
95.9k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
95.9k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
95.9k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
95.9k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
137
            << "total_op_num: " << total_op_num
975
137
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
137
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
95.9k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
95.9k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
18.4k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
18.4k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
18.4k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
18.4k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
18.4k
                shuffle_idx_to_instance_idx));
990
18.4k
    }
991
95.9k
    return Status::OK();
992
95.9k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
442k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.01M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
570k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
570k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
119k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
119k
                if (child->sink()->node_id() ==
1003
119k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
103k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
103k
                }
1006
119k
            }
1007
113k
        }
1008
1009
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1010
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1011
        // still keep colocate plan after local shuffle
1012
570k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
570k
                                             bucket_seq_to_instance_idx,
1014
570k
                                             shuffle_idx_to_instance_idx));
1015
570k
    }
1016
442k
    return Status::OK();
1017
442k
}
1018
1019
Status PipelineFragmentContext::_plan_local_exchange(
1020
        int num_buckets, int pip_idx, PipelinePtr pip,
1021
        const std::map<int, int>& bucket_seq_to_instance_idx,
1022
569k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
569k
    int idx = 1;
1024
569k
    bool do_local_exchange = false;
1025
610k
    do {
1026
610k
        auto& ops = pip->operators();
1027
610k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
673k
        for (; idx < ops.size();) {
1030
104k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
97.1k
                RETURN_IF_ERROR(_add_local_exchange(
1032
97.1k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
97.1k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
97.1k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
97.1k
                        shuffle_idx_to_instance_idx));
1036
97.1k
            }
1037
104k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
40.7k
                idx = 2;
1043
40.7k
                break;
1044
40.7k
            }
1045
63.7k
            idx++;
1046
63.7k
        }
1047
610k
    } while (do_local_exchange);
1048
569k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
92.2k
        RETURN_IF_ERROR(_add_local_exchange(
1050
92.2k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
92.2k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
92.2k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
92.2k
    }
1054
569k
    return Status::OK();
1055
569k
}
1056
1057
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1058
                                                  const std::vector<TExpr>& output_exprs,
1059
                                                  const TPipelineFragmentParams& params,
1060
                                                  const RowDescriptor& row_desc,
1061
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1062
447k
                                                  PipelineId cur_pipeline_id) {
1063
447k
    switch (thrift_sink.type) {
1064
147k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
147k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
147k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
147k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
147k
                params.destinations, _fragment_instance_ids);
1071
147k
        break;
1072
147k
    }
1073
259k
    case TDataSinkType::RESULT_SINK: {
1074
259k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
259k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
259k
        int child_node_id = pipeline->operators().back()->node_id();
1080
259k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
259k
                                                      row_desc, output_exprs,
1082
259k
                                                      thrift_sink.result_sink);
1083
259k
        break;
1084
259k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
34.5k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
34.5k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
34.5k
        int child_node_id = pipeline->operators().back()->node_id();
1098
34.5k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
34.5k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
34.5k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.93k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.93k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
31.5k
        } else {
1104
31.5k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
31.5k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
31.5k
        }
1107
34.5k
        break;
1108
0
    }
1109
161
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
161
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
161
        DCHECK(state->get_query_ctx() != nullptr);
1112
161
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
161
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
161
                                                                output_exprs);
1115
161
        break;
1116
0
    }
1117
1.48k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.48k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.48k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.48k
                                                         output_exprs);
1123
1.48k
        break;
1124
1.48k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
4
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
4
                                                                     row_desc, output_exprs);
1132
1.73k
        } else {
1133
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.73k
                                                                row_desc, output_exprs);
1135
1.73k
        }
1136
1.73k
        break;
1137
1.73k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
502
    case TDataSinkType::RESULT_FILE_SINK: {
1186
502
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
502
        } else {
1196
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
502
                                                              output_exprs);
1198
502
        }
1199
502
        break;
1200
502
    }
1201
2.58k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.58k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.58k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.58k
        auto sink_id = next_sink_operator_id();
1205
2.58k
        const int multi_cast_node_id = sink_id;
1206
2.58k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.58k
        std::vector<int> sources;
1209
10.1k
        for (int i = 0; i < sender_size; ++i) {
1210
7.55k
            auto source_id = next_operator_id();
1211
7.55k
            sources.push_back(source_id);
1212
7.55k
        }
1213
1214
2.58k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.58k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
10.1k
        for (int i = 0; i < sender_size; ++i) {
1217
7.55k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
7.55k
            RowDescriptor* exchange_row_desc = nullptr;
1220
7.55k
            {
1221
7.55k
                const auto& tmp_row_desc =
1222
7.55k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
7.55k
                                ? RowDescriptor(state->desc_tbl(),
1224
7.55k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
7.55k
                                                         .output_tuple_id})
1226
18.4E
                                : row_desc;
1227
7.55k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
7.55k
            }
1229
7.55k
            auto source_id = sources[i];
1230
7.55k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
7.55k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
7.55k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
7.55k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
7.55k
                    /*operator_id=*/source_id);
1236
7.55k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
7.55k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1238
            // 2. create and set sink operator of data stream sender for new pipeline
1239
1240
7.55k
            DataSinkOperatorPtr sink_op;
1241
7.55k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
7.55k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
7.55k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
7.55k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
7.55k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
7.55k
            {
1248
7.55k
                TDataSink* t = pool->add(new TDataSink());
1249
7.55k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
7.55k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
7.55k
            }
1252
1253
            // 3. set dependency dag
1254
7.55k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
7.55k
        }
1256
2.58k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.58k
        break;
1260
2.58k
    }
1261
2.58k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
13
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
13
        break;
1268
13
    }
1269
156
    case TDataSinkType::TVF_TABLE_SINK: {
1270
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
156
                                                        output_exprs);
1275
156
        break;
1276
156
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
447k
    }
1280
447k
    return Status::OK();
1281
447k
}
1282
1283
// NOLINTBEGIN(readability-function-size)
1284
// NOLINTBEGIN(readability-function-cognitive-complexity)
1285
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1286
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1287
                                                 PipelinePtr& cur_pipe, int parent_idx,
1288
                                                 int child_idx,
1289
                                                 const bool followed_by_shuffled_operator,
1290
                                                 const bool require_bucket_distribution,
1291
672k
                                                 OperatorPtr& cache_op) {
1292
672k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
672k
    Defer defer = Defer([&]() {
1294
670k
        if (op) {
1295
670k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
670k
        }
1297
670k
        for (auto& s : sink_ops) {
1298
119k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
119k
        }
1300
670k
    });
1301
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1302
    // Therefore, here we need to use a stack-like structure.
1303
672k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
672k
    std::stringstream error_msg;
1305
672k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
672k
    bool fe_with_old_version = false;
1308
672k
    switch (tnode.node_type) {
1309
219k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
219k
        op = std::make_shared<OlapScanOperatorX>(
1311
219k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
219k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
219k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
219k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
219k
        break;
1316
219k
    }
1317
72
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
72
        DCHECK(_query_ctx != nullptr);
1319
72
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
72
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
72
                                                    _num_instances);
1322
72
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
72
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
72
        break;
1325
72
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
25.9k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
25.9k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
25.9k
                                                 _num_instances);
1342
25.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
25.9k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
25.9k
        break;
1345
25.9k
    }
1346
152k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
152k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
152k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
152k
        DCHECK_GT(num_senders, 0);
1351
152k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
152k
                                                       num_senders);
1353
152k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
152k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
152k
        break;
1356
152k
    }
1357
138k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
138k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
138k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1360
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1361
0
                                         ": group by and output is empty");
1362
0
        }
1363
138k
        bool need_create_cache_op =
1364
138k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
138k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1366
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1367
10
            auto cache_source_id = next_operator_id();
1368
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1369
10
                                                        _params.fragment.query_cache_param);
1370
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1371
1372
10
            const auto downstream_pipeline_id = cur_pipe->id();
1373
10
            if (!_dag.contains(downstream_pipeline_id)) {
1374
10
                _dag.insert({downstream_pipeline_id, {}});
1375
10
            }
1376
10
            new_pipe = add_pipeline(cur_pipe);
1377
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1378
1379
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1380
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1381
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1382
10
            return Status::OK();
1383
10
        };
1384
138k
        const bool group_by_limit_opt =
1385
138k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1386
1387
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1388
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1389
138k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
138k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
138k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
138k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
138k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
138k
        const bool can_use_distinct_streaming_agg =
1396
138k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
138k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
138k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
138k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
138k
        if (can_use_distinct_streaming_agg) {
1402
81.6k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
81.6k
            } else {
1413
81.6k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
81.6k
                                                                     tnode, descs);
1415
81.6k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
81.6k
            }
1417
81.6k
        } else if (is_streaming_agg) {
1418
1.89k
            if (need_create_cache_op) {
1419
0
                PipelinePtr new_pipe;
1420
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1421
0
                cache_op = op;
1422
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
0
                                                             descs);
1424
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1425
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1426
0
                cur_pipe = new_pipe;
1427
1.89k
            } else {
1428
1.89k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.89k
                                                             descs);
1430
1.89k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.89k
            }
1432
54.8k
        } else {
1433
            // create new pipeline to add query cache operator
1434
54.8k
            PipelinePtr new_pipe;
1435
54.8k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
54.8k
            if (enable_spill) {
1441
228
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
228
                                                                     next_operator_id(), descs);
1443
54.5k
            } else {
1444
54.5k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
54.5k
            }
1446
54.8k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
54.8k
            } else {
1451
54.8k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
54.8k
            }
1453
1454
54.8k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
54.8k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
52.0k
                _dag.insert({downstream_pipeline_id, {}});
1457
52.0k
            }
1458
54.8k
            cur_pipe = add_pipeline(cur_pipe);
1459
54.8k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
54.8k
            if (enable_spill) {
1462
228
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
228
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
54.5k
            } else {
1465
54.5k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
54.5k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
54.5k
            }
1468
54.8k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
54.8k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
54.8k
        }
1471
138k
        break;
1472
138k
    }
1473
138k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
63
        if (tnode.bucketed_agg_node.grouping_exprs.empty()) {
1475
0
            return Status::InternalError(
1476
0
                    "Bucketed aggregation node {} should not be used without group by keys",
1477
0
                    tnode.node_id);
1478
0
        }
1479
1480
        // Create source operator (goes on the current / downstream pipeline).
1481
63
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
63
        const auto downstream_pipeline_id = cur_pipe->id();
1486
63
        if (!_dag.contains(downstream_pipeline_id)) {
1487
63
            _dag.insert({downstream_pipeline_id, {}});
1488
63
        }
1489
63
        cur_pipe = add_pipeline(cur_pipe);
1490
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
63
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1497
1498
        // Pre-register a single shared state for ALL instances so that every
1499
        // sink instance writes its per-instance hash table into the same
1500
        // BucketedAggSharedState and every source instance can merge across
1501
        // all of them.
1502
63
        {
1503
63
            auto shared_state = BucketedAggSharedState::create_shared();
1504
63
            shared_state->id = op->operator_id();
1505
63
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
379
            for (int i = 0; i < _num_instances; i++) {
1508
316
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
316
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
316
                sink_dep->set_shared_state(shared_state.get());
1511
316
                shared_state->sink_deps.push_back(sink_dep);
1512
316
            }
1513
63
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
63
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
63
            _op_id_to_shared_state.insert(
1516
63
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
63
        }
1518
63
        break;
1519
63
    }
1520
9.61k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.61k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.61k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.61k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.61k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
9.61k
        } else {
1566
9.61k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.61k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.61k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.61k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.94k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.94k
            }
1573
9.61k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.61k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.61k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.61k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.61k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.61k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.61k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.61k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.61k
        }
1584
9.61k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
3.11k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
3.11k
                    HashJoinSharedState::create_shared(_num_instances);
1587
21.2k
            for (int i = 0; i < _num_instances; i++) {
1588
18.1k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
18.1k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
18.1k
                sink_dep->set_shared_state(shared_state.get());
1591
18.1k
                shared_state->sink_deps.push_back(sink_dep);
1592
18.1k
            }
1593
3.11k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
3.11k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
3.11k
            _op_id_to_shared_state.insert(
1596
3.11k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
3.11k
        }
1598
9.61k
        break;
1599
9.61k
    }
1600
6.13k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
6.13k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
6.13k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
6.13k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
6.13k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
5.89k
            _dag.insert({downstream_pipeline_id, {}});
1607
5.89k
        }
1608
6.13k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
6.13k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
6.13k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
6.13k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
6.13k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
6.13k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
6.13k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
6.13k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
6.13k
        break;
1618
6.13k
    }
1619
54.0k
    case TPlanNodeType::UNION_NODE: {
1620
54.0k
        int child_count = tnode.num_children;
1621
54.0k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
54.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
54.0k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
54.0k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
53.7k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.7k
        }
1628
55.4k
        for (int i = 0; i < child_count; i++) {
1629
1.41k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.41k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.41k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.41k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.41k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.41k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.41k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.41k
        }
1638
54.0k
        break;
1639
54.0k
    }
1640
54.0k
    case TPlanNodeType::SORT_NODE: {
1641
45.0k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
45.0k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
45.0k
        const bool use_local_merge =
1644
45.0k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
45.0k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
45.0k
        } else if (use_local_merge) {
1648
42.7k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
42.7k
                                                                 descs);
1650
42.7k
        } else {
1651
2.34k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.34k
        }
1653
45.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
45.0k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
45.0k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
45.0k
            _dag.insert({downstream_pipeline_id, {}});
1658
45.0k
        }
1659
45.0k
        cur_pipe = add_pipeline(cur_pipe);
1660
45.0k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
45.0k
        if (should_spill) {
1663
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
45.0k
        } else {
1666
45.0k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
45.0k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
45.0k
        }
1669
45.0k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
45.0k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
45.0k
        break;
1672
45.0k
    }
1673
45.0k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.63k
        }
1698
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.64k
        break;
1706
1.64k
    }
1707
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.64k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.64k
        break;
1711
1.64k
    }
1712
1.64k
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
296
    case TPlanNodeType::REPEAT_NODE: {
1723
296
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
296
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
296
        break;
1726
296
    }
1727
914
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
914
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
914
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
914
        break;
1731
914
    }
1732
914
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
218
        break;
1736
218
    }
1737
1.70k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.70k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.70k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.70k
        break;
1741
1.70k
    }
1742
1.70k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
470
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
470
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
470
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
470
        break;
1747
470
    }
1748
2.08k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.08k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.08k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.08k
        break;
1752
2.08k
    }
1753
6.89k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.89k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.89k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.89k
        break;
1757
6.89k
    }
1758
6.89k
    case TPlanNodeType::SELECT_NODE: {
1759
2.58k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.58k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.58k
        break;
1762
2.58k
    }
1763
2.58k
    case TPlanNodeType::REC_CTE_NODE: {
1764
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
151
        const auto downstream_pipeline_id = cur_pipe->id();
1768
151
        if (!_dag.contains(downstream_pipeline_id)) {
1769
148
            _dag.insert({downstream_pipeline_id, {}});
1770
148
        }
1771
1772
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
151
        DataSinkOperatorPtr anchor_sink;
1776
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
151
                                                                  op->operator_id(), tnode, descs);
1778
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
151
        DataSinkOperatorPtr rec_sink;
1786
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
151
                                                         tnode, descs);
1788
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
151
        break;
1793
151
    }
1794
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.95k
        break;
1798
1.95k
    }
1799
1.95k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
672k
    }
1803
670k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1804
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1805
0
        op->set_serial_operator();
1806
0
    }
1807
1808
670k
    return Status::OK();
1809
672k
}
1810
// NOLINTEND(readability-function-cognitive-complexity)
1811
// NOLINTEND(readability-function-size)
1812
1813
template <bool is_intersect>
1814
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1815
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1816
267
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
267
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
267
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
267
    const auto downstream_pipeline_id = cur_pipe->id();
1821
267
    if (!_dag.contains(downstream_pipeline_id)) {
1822
242
        _dag.insert({downstream_pipeline_id, {}});
1823
242
    }
1824
1825
895
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
628
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
628
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
628
        if (child_id == 0) {
1830
267
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
267
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
361
        } else {
1833
361
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
361
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
361
        }
1836
628
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
628
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
628
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
628
    }
1841
1842
267
    return Status::OK();
1843
267
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
134
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
134
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
134
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
134
    const auto downstream_pipeline_id = cur_pipe->id();
1821
134
    if (!_dag.contains(downstream_pipeline_id)) {
1822
118
        _dag.insert({downstream_pipeline_id, {}});
1823
118
    }
1824
1825
481
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
347
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
347
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
347
        if (child_id == 0) {
1830
134
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
134
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
213
        } else {
1833
213
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
213
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
213
        }
1836
347
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
347
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
347
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
347
    }
1841
1842
134
    return Status::OK();
1843
134
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
133
    const auto downstream_pipeline_id = cur_pipe->id();
1821
133
    if (!_dag.contains(downstream_pipeline_id)) {
1822
124
        _dag.insert({downstream_pipeline_id, {}});
1823
124
    }
1824
1825
414
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
281
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
281
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
281
        if (child_id == 0) {
1830
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
148
        } else {
1833
148
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
148
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
148
        }
1836
281
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
281
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
281
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
281
    }
1841
1842
133
    return Status::OK();
1843
133
}
1844
1845
446k
Status PipelineFragmentContext::submit() {
1846
446k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
446k
    _submitted = true;
1850
1851
446k
    int submit_tasks = 0;
1852
446k
    Status st;
1853
446k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.10M
    for (auto& task : _tasks) {
1855
1.88M
        for (auto& t : task) {
1856
1.88M
            st = scheduler->submit(t.first);
1857
1.88M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.88M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.88M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
1.88M
            submit_tasks++;
1866
1.88M
        }
1867
1.10M
    }
1868
446k
    if (!st.ok()) {
1869
0
        bool need_remove = false;
1870
0
        {
1871
0
            std::lock_guard<std::mutex> l(_task_mutex);
1872
0
            if (_closed_tasks >= _total_tasks) {
1873
0
                need_remove = _close_fragment_instance();
1874
0
            }
1875
0
        }
1876
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1877
0
        if (need_remove) {
1878
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1879
0
        }
1880
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1881
0
                                     BackendOptions::get_localhost());
1882
446k
    } else {
1883
446k
        return st;
1884
446k
    }
1885
446k
}
1886
1887
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1888
0
    if (_runtime_state->enable_profile()) {
1889
0
        std::stringstream ss;
1890
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1891
0
            runtime_profile_ptr->pretty_print(&ss);
1892
0
        }
1893
1894
0
        if (_runtime_state->load_channel_profile()) {
1895
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1896
0
        }
1897
1898
0
        auto profile_str =
1899
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1900
0
                            this->_fragment_id, extra_info, ss.str());
1901
0
        LOG_LONG_STRING(INFO, profile_str);
1902
0
    }
1903
0
}
1904
// If all pipeline tasks binded to the fragment instance are finished, then we could
1905
// close the fragment instance.
1906
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1907
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1908
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1909
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1910
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1911
// (via debug_string()).
1912
448k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
448k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
448k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
448k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
448k
    if (!_need_notify_close) {
1919
444k
        auto st = send_report(true);
1920
444k
        if (!st) {
1921
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1922
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1923
0
        }
1924
444k
    }
1925
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1926
    // Since stream load does not have someting like coordinator on FE, so
1927
    // backend can not report profile to FE, ant its profile can not be shown
1928
    // in the same way with other query. So we print the profile content to info log.
1929
1930
448k
    if (_runtime_state->enable_profile() &&
1931
448k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.18k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.18k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1934
0
        std::stringstream ss;
1935
        // Compute the _local_time_percent before pretty_print the runtime_profile
1936
        // Before add this operation, the print out like that:
1937
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1938
        // After add the operation, the print out like that:
1939
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1940
        // We can easily know the exec node execute time without child time consumed.
1941
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1942
0
            runtime_profile_ptr->pretty_print(&ss);
1943
0
        }
1944
1945
0
        if (_runtime_state->load_channel_profile()) {
1946
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1947
0
        }
1948
1949
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1950
0
    }
1951
1952
448k
    if (_query_ctx->enable_profile()) {
1953
2.18k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.18k
                                         collect_realtime_load_channel_profile());
1955
2.18k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
448k
    return !_need_notify_close;
1960
448k
}
1961
1962
1.87M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
1.87M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.87M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
689k
        if (_dag.contains(pipeline_id)) {
1967
356k
            for (auto dep : _dag[pipeline_id]) {
1968
356k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
356k
            }
1970
283k
        }
1971
689k
    }
1972
1.87M
    bool need_remove = false;
1973
1.87M
    {
1974
1.87M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.87M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.87M
        _query_ctx->inc_finished_task_num();
1978
1.87M
        if (_closed_tasks >= _total_tasks) {
1979
448k
            need_remove = _close_fragment_instance();
1980
448k
        }
1981
1.87M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.87M
    if (need_remove) {
1984
444k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
444k
    }
1986
1.87M
}
1987
1988
55.2k
std::string PipelineFragmentContext::get_load_error_url() {
1989
55.2k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1990
0
        return to_load_error_http_path(str);
1991
0
    }
1992
142k
    for (auto& tasks : _tasks) {
1993
225k
        for (auto& task : tasks) {
1994
225k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
182
                return to_load_error_http_path(str);
1996
182
            }
1997
225k
        }
1998
142k
    }
1999
55.0k
    return "";
2000
55.2k
}
2001
2002
55.2k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
55.2k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
142k
    for (auto& tasks : _tasks) {
2007
225k
        for (auto& task : tasks) {
2008
225k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
182
                return str;
2010
182
            }
2011
225k
        }
2012
142k
    }
2013
55.0k
    return "";
2014
55.2k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
48.8k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
48.8k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
48.8k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
48.8k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
48.8k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
48.8k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
48.8k
    });
2031
2032
48.8k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
48.8k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
48.8k
    int callback_retries = 10;
2038
48.8k
    const int sleep_ms = 1000;
2039
48.8k
    Status exec_status = req.status;
2040
48.8k
    Status coord_status;
2041
48.8k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
48.8k
    do {
2043
48.8k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
48.8k
                                                            req.coord_addr, &coord_status);
2045
48.8k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
48.8k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
48.8k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
48.8k
    TReportExecStatusParams params;
2059
48.8k
    params.protocol_version = FrontendServiceVersion::V1;
2060
48.8k
    params.__set_query_id(req.query_id);
2061
48.8k
    params.__set_backend_num(req.backend_num);
2062
48.8k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
48.8k
    params.__set_fragment_id(req.fragment_id);
2064
48.8k
    params.__set_status(exec_status.to_thrift());
2065
48.8k
    params.__set_done(req.done);
2066
48.8k
    params.__set_query_type(req.runtime_state->query_type());
2067
48.8k
    params.__isset.profile = false;
2068
2069
48.8k
    DCHECK(req.runtime_state != nullptr);
2070
2071
48.8k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
44.5k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
44.5k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
44.5k
    } else {
2075
4.25k
        DCHECK(!req.runtime_states.empty());
2076
4.25k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
4.25k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.25k
    }
2086
2087
48.8k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
48.8k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
48.8k
    static std::string s_unselected_rows = "unselected.rows";
2090
48.8k
    int64_t num_rows_load_success = 0;
2091
48.8k
    int64_t num_rows_load_filtered = 0;
2092
48.8k
    int64_t num_rows_load_unselected = 0;
2093
48.8k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
48.8k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
48.8k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
48.8k
    } else if (!req.runtime_states.empty()) {
2109
150k
        for (auto* rs : req.runtime_states) {
2110
150k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
150k
                rs->num_finished_range() > 0) {
2112
37.6k
                params.__isset.load_counters = true;
2113
37.6k
                num_rows_load_success += rs->num_rows_load_success();
2114
37.6k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
37.6k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
37.6k
                params.__isset.fragment_instance_reports = true;
2117
37.6k
                TFragmentInstanceReport t;
2118
37.6k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
37.6k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
37.6k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
37.6k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
37.6k
                params.fragment_instance_reports.push_back(t);
2123
37.6k
            }
2124
150k
        }
2125
48.8k
    }
2126
48.8k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
48.8k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
48.8k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
48.8k
    if (!req.load_error_url.empty()) {
2131
172
        params.__set_tracking_url(req.load_error_url);
2132
172
    }
2133
48.8k
    if (!req.first_error_msg.empty()) {
2134
172
        params.__set_first_error_msg(req.first_error_msg);
2135
172
    }
2136
150k
    for (auto* rs : req.runtime_states) {
2137
150k
        if (rs->wal_id() > 0) {
2138
104
            params.__set_txn_id(rs->wal_id());
2139
104
            params.__set_label(rs->import_label());
2140
104
        }
2141
150k
    }
2142
48.8k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
48.8k
    } else if (!req.runtime_states.empty()) {
2146
150k
        for (auto* rs : req.runtime_states) {
2147
150k
            if (!rs->export_output_files().empty()) {
2148
0
                params.__isset.export_files = true;
2149
0
                params.export_files.insert(params.export_files.end(),
2150
0
                                           rs->export_output_files().begin(),
2151
0
                                           rs->export_output_files().end());
2152
0
            }
2153
150k
        }
2154
48.7k
    }
2155
48.8k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
48.8k
    } else if (!req.runtime_states.empty()) {
2159
151k
        for (auto* rs : req.runtime_states) {
2160
151k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
28.0k
                params.__isset.commitInfos = true;
2162
28.0k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
28.0k
            }
2164
151k
        }
2165
48.8k
    }
2166
48.8k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
48.8k
    } else if (!req.runtime_states.empty()) {
2170
150k
        for (auto* rs : req.runtime_states) {
2171
150k
            if (auto rs_eti = rs->error_tablet_infos(); !rs_eti.empty()) {
2172
0
                params.__isset.errorTabletInfos = true;
2173
0
                params.errorTabletInfos.insert(params.errorTabletInfos.end(), rs_eti.begin(),
2174
0
                                               rs_eti.end());
2175
0
            }
2176
150k
        }
2177
48.7k
    }
2178
48.8k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
48.8k
    } else if (!req.runtime_states.empty()) {
2183
150k
        for (auto* rs : req.runtime_states) {
2184
150k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.16k
                params.__isset.hive_partition_updates = true;
2186
2.16k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.16k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.16k
            }
2189
150k
        }
2190
48.7k
    }
2191
48.8k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
48.8k
    } else if (!req.runtime_states.empty()) {
2196
150k
        for (auto* rs : req.runtime_states) {
2197
150k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.08k
                params.__isset.iceberg_commit_datas = true;
2199
2.08k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.08k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.08k
            }
2202
150k
        }
2203
48.7k
    }
2204
2205
48.8k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
48.8k
    } else if (!req.runtime_states.empty()) {
2209
151k
        for (auto* rs : req.runtime_states) {
2210
151k
            if (auto rs_mcd = rs->mc_commit_datas(); !rs_mcd.empty()) {
2211
0
                params.__isset.mc_commit_datas = true;
2212
0
                params.mc_commit_datas.insert(params.mc_commit_datas.end(), rs_mcd.begin(),
2213
0
                                              rs_mcd.end());
2214
0
            }
2215
151k
        }
2216
48.8k
    }
2217
2218
48.8k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
48.8k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
48.8k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
48.7k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
48.7k
    }
2224
2225
48.8k
    TReportExecStatusResult res;
2226
48.8k
    Status rpc_status;
2227
2228
48.8k
    VLOG_DEBUG << "reportExecStatus params is "
2229
61
               << apache::thrift::ThriftDebugString(params).c_str();
2230
48.8k
    if (!exec_status.ok()) {
2231
1.66k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.66k
                     << " to coordinator: " << req.coord_addr
2233
1.66k
                     << ", query id: " << print_id(req.query_id);
2234
1.66k
    }
2235
48.8k
    try {
2236
48.8k
        try {
2237
48.8k
            (*coord)->reportExecStatus(res, params);
2238
48.8k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
48.8k
        rpc_status = Status::create<false>(res.status);
2254
48.8k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
48.7k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
48.7k
}
2265
2266
449k
Status PipelineFragmentContext::send_report(bool done) {
2267
449k
    Status exec_status = _query_ctx->exec_status();
2268
    // If plan is done successfully, but _is_report_success is false,
2269
    // no need to send report.
2270
    // Load will set _is_report_success to true because load wants to know
2271
    // the process.
2272
449k
    if (!_is_report_success && done && exec_status.ok()) {
2273
400k
        return Status::OK();
2274
400k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
49.0k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
313
        if (done) {
2284
            // if done is true, which means the query is finished successfully, we can safely close the fragment instance without sending report to FE, and just return OK status here.
2285
313
            return Status::OK();
2286
313
        }
2287
0
        return Status::NeedSendAgain("");
2288
313
    }
2289
2290
48.7k
    std::vector<RuntimeState*> runtime_states;
2291
2292
111k
    for (auto& tasks : _tasks) {
2293
151k
        for (auto& task : tasks) {
2294
151k
            runtime_states.push_back(task.second.get());
2295
151k
        }
2296
111k
    }
2297
2298
48.7k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
48.8k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
48.7k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
48.7k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
48.7k
    ReportStatusRequest req {.status = exec_status,
2306
48.7k
                             .runtime_states = runtime_states,
2307
48.7k
                             .done = done || !exec_status.ok(),
2308
48.7k
                             .coord_addr = _query_ctx->coord_addr,
2309
48.7k
                             .query_id = _query_id,
2310
48.7k
                             .fragment_id = _fragment_id,
2311
48.7k
                             .fragment_instance_id = TUniqueId(),
2312
48.7k
                             .backend_num = -1,
2313
48.7k
                             .runtime_state = _runtime_state.get(),
2314
48.7k
                             .load_error_url = load_eror_url,
2315
48.7k
                             .first_error_msg = first_error_msg,
2316
48.7k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
48.7k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
48.8k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
48.8k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
48.8k
        _coordinator_callback(req);
2321
48.8k
        if (!req.done) {
2322
4.78k
            ctx->refresh_next_report_time();
2323
4.78k
        }
2324
48.8k
    });
2325
49.0k
}
2326
2327
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
0
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
0
    for (const auto& task_instances : _tasks) {
2332
0
        for (const auto& task : task_instances) {
2333
0
            if (task.first->is_running()) {
2334
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2335
0
                                      << " is running, task: " << (void*)task.first.get()
2336
0
                                      << ", is_running: " << task.first->is_running();
2337
0
                *has_running_task = true;
2338
0
                return 0;
2339
0
            }
2340
2341
0
            size_t revocable_size = task.first->get_revocable_size();
2342
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
0
                res += revocable_size;
2344
0
            }
2345
0
        }
2346
0
    }
2347
0
    return res;
2348
0
}
2349
2350
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
0
    std::vector<PipelineTask*> revocable_tasks;
2352
0
    for (const auto& task_instances : _tasks) {
2353
0
        for (const auto& task : task_instances) {
2354
0
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
0
                revocable_tasks.emplace_back(task.first.get());
2358
0
            }
2359
0
        }
2360
0
    }
2361
0
    return revocable_tasks;
2362
0
}
2363
2364
73
std::string PipelineFragmentContext::debug_string() {
2365
73
    std::lock_guard<std::mutex> l(_task_mutex);
2366
73
    fmt::memory_buffer debug_string_buffer;
2367
73
    fmt::format_to(debug_string_buffer,
2368
73
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
73
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
73
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
226
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
153
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
598
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
445
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
445
                           _tasks[j][i].first->debug_string());
2376
445
        }
2377
153
    }
2378
2379
73
    return fmt::to_string(debug_string_buffer);
2380
73
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.18k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.18k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2385
2386
    // we do not have mutex to protect pipeline_id_to_profile
2387
    // so we need to make sure this funciton is invoked after fragment context
2388
    // has already been prepared.
2389
2.18k
    if (!_prepared) {
2390
0
        std::string msg =
2391
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2392
0
        DCHECK(false) << msg;
2393
0
        LOG_ERROR(msg);
2394
0
        return res;
2395
0
    }
2396
2397
    // Make sure first profile is fragment level profile
2398
2.18k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.18k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.18k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
3.87k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
3.87k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
3.87k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
3.87k
        res.push_back(profile_ptr);
2407
3.87k
    }
2408
2409
2.18k
    return res;
2410
2.18k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.18k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2414
    // we do not have mutex to protect pipeline_id_to_profile
2415
    // so we need to make sure this funciton is invoked after fragment context
2416
    // has already been prepared.
2417
2.18k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
5.50k
    for (const auto& tasks : _tasks) {
2426
11.3k
        for (const auto& task : tasks) {
2427
11.3k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
11.3k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
11.3k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
11.3k
                                                           _runtime_state->profile_level());
2435
11.3k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
11.3k
        }
2437
5.50k
    }
2438
2439
2.18k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.18k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.18k
                                                      _runtime_state->profile_level());
2442
2.18k
    return load_channel_profile;
2443
2.18k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
8.66k
    for (const auto& _task : _tasks) {
2455
16.0k
        for (const auto& task : _task) {
2456
16.0k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
16.0k
            result.merge(set);
2458
16.0k
        }
2459
8.66k
    }
2460
3.28k
    if (_runtime_state) {
2461
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.28k
        result.merge(set);
2463
3.28k
    }
2464
3.28k
    return result;
2465
3.28k
}
2466
2467
449k
void PipelineFragmentContext::_release_resource() {
2468
449k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
449k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
449k
    auto st = _query_ctx->exec_status();
2472
1.10M
    for (auto& _task : _tasks) {
2473
1.10M
        if (!_task.empty()) {
2474
1.10M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.10M
        }
2476
1.10M
    }
2477
449k
    _tasks.clear();
2478
449k
    _dag.clear();
2479
449k
    _pip_id_to_pipeline.clear();
2480
449k
    _pipelines.clear();
2481
449k
    _sink.reset();
2482
449k
    _root_op.reset();
2483
449k
    _runtime_filter_mgr_map.clear();
2484
449k
    _op_id_to_shared_state.clear();
2485
449k
}
2486
2487
} // namespace doris