Coverage Report

Created: 2026-06-03 21:01

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
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// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
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#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"
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#include "exec/spill/spill_file.h"
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#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
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#include "util/client_cache.h"
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#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
324k
        : _query_id(std::move(query_id)),
144
324k
          _fragment_id(request.fragment_id),
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324k
          _exec_env(exec_env),
146
324k
          _query_ctx(std::move(query_ctx)),
147
324k
          _call_back(call_back),
148
324k
          _is_report_on_cancel(true),
149
324k
          _params(request),
150
324k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
324k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
324k
                                                               : false) {
153
324k
    _fragment_watcher.start();
154
324k
}
155
156
324k
PipelineFragmentContext::~PipelineFragmentContext() {
157
324k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
324k
            .tag("query_id", print_id(_query_id))
159
324k
            .tag("fragment_id", _fragment_id);
160
324k
    _release_resource();
161
324k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
324k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
324k
        _runtime_state.reset();
165
324k
        _query_ctx.reset();
166
324k
    }
167
324k
}
168
169
129
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
129
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
129
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
129
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
179
// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
8.87k
bool PipelineFragmentContext::notify_close() {
181
8.87k
    bool all_closed = false;
182
8.87k
    bool need_remove = false;
183
8.87k
    {
184
8.87k
        std::lock_guard<std::mutex> l(_task_mutex);
185
8.87k
        if (_closed_tasks >= _total_tasks) {
186
3.48k
            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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3.44k
                need_remove = true;
193
3.44k
            }
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3.48k
            all_closed = true;
195
3.48k
        }
196
        // make fragment release by self after cancel
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8.87k
        _need_notify_close = false;
198
8.87k
    }
199
8.87k
    if (need_remove) {
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3.44k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
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3.44k
    }
202
8.87k
    return all_closed;
203
8.87k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
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// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
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5.39k
void PipelineFragmentContext::cancel(const Status reason) {
210
5.39k
    LOG_INFO("PipelineFragmentContext::cancel")
211
5.39k
            .tag("query_id", print_id(_query_id))
212
5.39k
            .tag("fragment_id", _fragment_id)
213
5.39k
            .tag("reason", reason.to_string());
214
5.39k
    if (notify_close()) {
215
51
        return;
216
51
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
5.34k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
5.34k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
5.34k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
5.34k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
5.34k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
5.34k
    _query_ctx->cancel(reason, _fragment_id);
243
5.34k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
166
        _is_report_on_cancel = false;
245
5.17k
    } else {
246
23.5k
        for (auto& id : _fragment_instance_ids) {
247
23.5k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
23.5k
        }
249
5.17k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
5.34k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
5.34k
    if (stream_load_ctx != nullptr) {
254
31
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
31
        stream_load_ctx->error_url = get_load_error_url();
259
31
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
31
    }
261
262
24.2k
    for (auto& tasks : _tasks) {
263
51.3k
        for (auto& task : tasks) {
264
51.3k
            task.first->unblock_all_dependencies();
265
51.3k
        }
266
24.2k
    }
267
5.34k
}
268
269
505k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
505k
    PipelineId id = _next_pipeline_id++;
271
505k
    auto pipeline = std::make_shared<Pipeline>(
272
505k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
505k
            parent ? parent->num_tasks() : _num_instances);
274
505k
    if (idx >= 0) {
275
104k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
401k
    } else {
277
401k
        _pipelines.emplace_back(pipeline);
278
401k
    }
279
505k
    if (parent) {
280
180k
        parent->set_children(pipeline);
281
180k
    }
282
505k
    return pipeline;
283
505k
}
284
285
324k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
324k
    {
287
324k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
324k
        auto root_pipeline = add_pipeline();
290
324k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
324k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
324k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
324k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
324k
                                          _params.fragment.output_exprs, _params,
299
324k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
324k
                                          *_desc_tbl, root_pipeline->id()));
301
324k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
324k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
400k
        for (PipelinePtr& pipeline : _pipelines) {
305
400k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
400k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
400k
        }
308
324k
    }
309
    // 4. Build local exchanger
310
324k
    if (_runtime_state->enable_local_shuffle()) {
311
322k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
322k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
322k
                                             _params.bucket_seq_to_instance_idx,
314
322k
                                             _params.shuffle_idx_to_instance_idx));
315
322k
    }
316
317
    // 5. Initialize global states in pipelines.
318
506k
    for (PipelinePtr& pipeline : _pipelines) {
319
506k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
506k
        pipeline->children().clear();
321
506k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
506k
    }
323
324
322k
    {
325
322k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
322k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
322k
    }
329
330
322k
    return Status::OK();
331
322k
}
332
333
324k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
324k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
324k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
324k
        _timeout = _params.query_options.execution_timeout;
339
324k
    }
340
341
324k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
324k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
324k
    SCOPED_TIMER(_prepare_timer);
344
324k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
324k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
324k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
324k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
324k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
324k
    {
350
324k
        SCOPED_TIMER(_init_context_timer);
351
324k
        cast_set(_num_instances, _params.local_params.size());
352
324k
        _total_instances =
353
324k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
324k
        auto* fragment_context = this;
356
357
324k
        if (_params.query_options.__isset.is_report_success) {
358
322k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
322k
        }
360
361
        // 1. Set up the global runtime state.
362
324k
        _runtime_state = RuntimeState::create_unique(
363
324k
                _params.query_id, _params.fragment_id, _params.query_options,
364
324k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
324k
        _runtime_state->set_task_execution_context(shared_from_this());
366
324k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
324k
        if (_params.__isset.backend_id) {
368
321k
            _runtime_state->set_backend_id(_params.backend_id);
369
321k
        }
370
324k
        if (_params.__isset.import_label) {
371
238
            _runtime_state->set_import_label(_params.import_label);
372
238
        }
373
324k
        if (_params.__isset.db_name) {
374
190
            _runtime_state->set_db_name(_params.db_name);
375
190
        }
376
324k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
324k
        if (_params.is_simplified_param) {
381
113k
            _desc_tbl = _query_ctx->desc_tbl;
382
211k
        } else {
383
211k
            DCHECK(_params.__isset.desc_tbl);
384
211k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
211k
                                                  &_desc_tbl));
386
211k
        }
387
324k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
324k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
324k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
324k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
324k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
324k
        const auto target_size = _params.local_params.size();
395
324k
        _fragment_instance_ids.resize(target_size);
396
1.19M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
871k
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
871k
            _fragment_instance_ids[i] = fragment_instance_id;
399
871k
        }
400
324k
    }
401
402
324k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
323k
    _init_next_report_time();
405
406
323k
    _prepared = true;
407
323k
    return Status::OK();
408
324k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
872k
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
872k
    const auto& local_params = _params.local_params[instance_idx];
414
872k
    auto fragment_instance_id = local_params.fragment_instance_id;
415
872k
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
872k
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
872k
    auto get_shared_state = [&](PipelinePtr pipeline)
418
872k
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.49M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.49M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.49M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.49M
                shared_state_map;
423
1.93M
        for (auto& op : pipeline->operators()) {
424
1.93M
            auto source_id = op->operator_id();
425
1.93M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
1.93M
                iter != _op_id_to_shared_state.end()) {
427
629k
                shared_state_map.insert({source_id, iter->second});
428
629k
            }
429
1.93M
        }
430
1.49M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.49M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.49M
                iter != _op_id_to_shared_state.end()) {
433
290k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
290k
            }
435
1.49M
        }
436
1.49M
        return shared_state_map;
437
1.49M
    };
438
439
2.69M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
1.82M
        auto& pipeline = _pipelines[pip_idx];
441
1.82M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.48M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.48M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.48M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.48M
            {
446
                // Initialize runtime state for this task
447
1.48M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.48M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.48M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.49M
                if (_params.__isset.backend_id) {
453
1.49M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.49M
                }
455
1.48M
                if (_params.__isset.import_label) {
456
239
                    task_runtime_state->set_import_label(_params.import_label);
457
239
                }
458
1.48M
                if (_params.__isset.db_name) {
459
191
                    task_runtime_state->set_db_name(_params.db_name);
460
191
                }
461
1.48M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.48M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.48M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.48M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.48M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.48M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.48M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.48M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.48M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.48M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.48M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.48M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.48M
            }
482
1.48M
            auto cur_task_id = _total_tasks++;
483
1.48M
            task_runtime_state->set_task_id(cur_task_id);
484
1.48M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.48M
            auto task = std::make_shared<PipelineTask>(
486
1.48M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.48M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.48M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.48M
                    instance_idx);
490
1.48M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.48M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.48M
            _tasks[instance_idx].emplace_back(
493
1.48M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.48M
                            std::move(task), std::move(task_runtime_state)});
495
1.48M
        }
496
1.82M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
1.82M
    for (auto& _pipeline : _pipelines) {
516
1.82M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.48M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.48M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.48M
            if (_dag.contains(_pipeline->id())) {
522
969k
                auto& deps = _dag[_pipeline->id()];
523
1.57M
                for (auto& dep : deps) {
524
1.57M
                    if (pipeline_id_to_task.contains(dep)) {
525
900k
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
900k
                        if (ss) {
527
323k
                            task->inject_shared_state(ss);
528
577k
                        } else {
529
577k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
577k
                                    task->get_source_shared_state());
531
577k
                        }
532
900k
                    }
533
1.57M
                }
534
969k
            }
535
1.48M
        }
536
1.82M
    }
537
2.70M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
1.82M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.48M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.48M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.48M
            std::vector<TScanRangeParams> scan_ranges;
542
1.48M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.48M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
228k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
228k
            }
546
1.48M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.48M
                                                             _params.fragment.output_sink));
548
1.48M
        }
549
1.82M
    }
550
876k
    {
551
876k
        std::lock_guard<std::mutex> l(_state_map_lock);
552
876k
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
876k
    }
554
876k
    return Status::OK();
555
872k
}
556
557
323k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
323k
    _total_tasks = 0;
559
323k
    _closed_tasks = 0;
560
323k
    const auto target_size = _params.local_params.size();
561
323k
    _tasks.resize(target_size);
562
323k
    _runtime_filter_mgr_map.resize(target_size);
563
829k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
505k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
505k
    }
566
323k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
323k
    if (target_size > 1 &&
569
323k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
117k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
571
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
572
20.7k
        std::vector<Status> prepare_status(target_size);
573
20.7k
        int submitted_tasks = 0;
574
20.7k
        Status submit_status;
575
20.7k
        CountDownLatch latch((int)target_size);
576
228k
        for (int i = 0; i < target_size; i++) {
577
207k
            submit_status = thread_pool->submit_func([&, i]() {
578
207k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
207k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
207k
                latch.count_down();
581
207k
            });
582
207k
            if (LIKELY(submit_status.ok())) {
583
207k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
207k
        }
588
20.7k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
20.7k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
228k
        for (int i = 0; i < submitted_tasks; i++) {
593
207k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
207k
        }
597
302k
    } else {
598
969k
        for (int i = 0; i < target_size; i++) {
599
666k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
666k
        }
601
302k
    }
602
323k
    _pipeline_parent_map.clear();
603
323k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
323k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
323k
    return Status::OK();
608
323k
}
609
610
321k
void PipelineFragmentContext::_init_next_report_time() {
611
321k
    auto interval_s = config::pipeline_status_report_interval;
612
321k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
31.4k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
31.4k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
31.4k
        _previous_report_time =
617
31.4k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
31.4k
        _disable_period_report = false;
619
31.4k
    }
620
321k
}
621
622
3.59k
void PipelineFragmentContext::refresh_next_report_time() {
623
3.59k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
3.59k
    DCHECK(disable == true);
625
3.59k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
3.59k
    _disable_period_report.compare_exchange_strong(disable, false);
627
3.59k
}
628
629
5.43M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
5.43M
    if (!_is_report_success) {
631
5.09M
        return;
632
5.09M
    }
633
338k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
338k
    if (disable) {
635
4.80k
        return;
636
4.80k
    }
637
334k
    int32_t interval_s = config::pipeline_status_report_interval;
638
334k
    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
334k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
334k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
334k
    if (MonotonicNanos() > next_report_time) {
646
3.60k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
3.60k
                                                            std::memory_order_acq_rel)) {
648
13
            return;
649
13
        }
650
3.59k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
3.59k
        auto st = send_report(false);
667
3.59k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
3.59k
    }
673
334k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
320k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
320k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
320k
    int node_idx = 0;
682
683
320k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
320k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
320k
    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
320k
    return Status::OK();
691
320k
}
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
492k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
492k
    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
492k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
492k
    int num_children = tnodes[*node_idx].num_children;
706
492k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
492k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
492k
    OperatorPtr op = nullptr;
710
492k
    OperatorPtr cache_op = nullptr;
711
492k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
492k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
492k
                                     followed_by_shuffled_operator,
714
492k
                                     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
492k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
492k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
172k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
320k
    } else {
723
320k
        *root = op;
724
320k
    }
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
492k
    auto required_data_distribution =
737
492k
            cur_pipe->operators().empty()
738
492k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
492k
                    : op->required_data_distribution(_runtime_state.get());
740
492k
    current_followed_by_shuffled_operator =
741
492k
            ((followed_by_shuffled_operator ||
742
492k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
437k
                                             : op->is_shuffled_operator())) &&
744
492k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
492k
            (followed_by_shuffled_operator &&
746
388k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
492k
    current_require_bucket_distribution =
749
492k
            ((require_bucket_distribution ||
750
492k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
442k
                                             : op->is_colocated_operator())) &&
752
492k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
492k
            (require_bucket_distribution &&
754
394k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
492k
    if (num_children == 0) {
757
334k
        _use_serial_source = op->is_serial_operator();
758
334k
    }
759
    // rely on that tnodes is preorder of the plan
760
665k
    for (int i = 0; i < num_children; i++) {
761
172k
        ++*node_idx;
762
172k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
172k
                                            current_followed_by_shuffled_operator,
764
172k
                                            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
172k
        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
172k
    }
775
776
492k
    return Status::OK();
777
492k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
104k
        PipelinePtr pipe_with_sink) {
782
104k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
104k
    pipe_with_source->set_num_tasks(_num_instances);
784
104k
    pipe_with_source->set_data_distribution(data_distribution);
785
104k
}
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
103k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
103k
    auto& operators = cur_pipe->operators();
793
103k
    const auto downstream_pipeline_id = cur_pipe->id();
794
103k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
103k
    DataSinkOperatorPtr sink;
797
103k
    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
103k
    const bool followed_by_shuffled_operator =
804
103k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
103k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
103k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
103k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
103k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
103k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
103k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
103k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
103k
    if (bucket_seq_to_instance_idx.empty() &&
813
103k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
35
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
35
    }
816
103k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
103k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
103k
                                          num_buckets, use_global_hash_shuffle,
819
103k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
103k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
103k
            LocalExchangeSharedState::create_shared(_num_instances);
824
103k
    switch (data_distribution.distribution_type) {
825
22.5k
    case ExchangeType::HASH_SHUFFLE:
826
22.5k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
22.5k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
22.5k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
22.5k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
22.5k
                        ? cast_set<int>(
831
22.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
22.5k
                        : 0);
833
22.5k
        break;
834
574
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
574
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
574
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
574
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
574
                        ? cast_set<int>(
839
574
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
574
                        : 0);
841
574
        break;
842
77.2k
    case ExchangeType::PASSTHROUGH:
843
77.2k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
77.2k
                cur_pipe->num_tasks(), _num_instances,
845
77.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
77.2k
                        ? cast_set<int>(
847
77.2k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
77.2k
                        : 0);
849
77.2k
        break;
850
495
    case ExchangeType::BROADCAST:
851
495
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
495
                cur_pipe->num_tasks(), _num_instances,
853
495
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
495
                        ? cast_set<int>(
855
495
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
495
                        : 0);
857
495
        break;
858
2.12k
    case ExchangeType::PASS_TO_ONE:
859
2.12k
        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
924
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
924
                    cur_pipe->num_tasks(), _num_instances,
863
924
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
924
                            ? cast_set<int>(_runtime_state->query_options()
865
924
                                                    .local_exchange_free_blocks_limit)
866
924
                            : 0);
867
1.19k
        } else {
868
1.19k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.19k
                    cur_pipe->num_tasks(), _num_instances,
870
1.19k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.19k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.19k
                                                    .local_exchange_free_blocks_limit)
873
1.19k
                            : 0);
874
1.19k
        }
875
2.12k
        break;
876
948
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
948
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
948
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
948
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
948
                        ? cast_set<int>(
881
948
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
948
                        : 0);
883
948
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
103k
    }
888
104k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
104k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
104k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
104k
    _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
104k
    std::copy(operators.begin(), operators.begin() + idx,
898
104k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
104k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
104k
    OperatorPtr source_op;
905
104k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
104k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
104k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
104k
    if (!operators.empty()) {
909
41.0k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
41.0k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
41.0k
    }
912
104k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
104k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
104k
    std::vector<PipelineId> edges_with_source;
917
121k
    for (auto child : cur_pipe->children()) {
918
121k
        bool found = false;
919
135k
        for (auto op : new_pip->operators()) {
920
135k
            if (child->sink()->node_id() == op->node_id()) {
921
12.1k
                new_pip->set_children(child);
922
12.1k
                found = true;
923
12.1k
            };
924
135k
        }
925
121k
        if (!found) {
926
109k
            new_children.push_back(child);
927
109k
            edges_with_source.push_back(child->id());
928
109k
        }
929
121k
    }
930
104k
    new_children.push_back(new_pip);
931
104k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
104k
    if (!new_pip->children().empty()) {
935
6.78k
        std::vector<PipelineId> edges_with_sink;
936
12.1k
        for (auto child : new_pip->children()) {
937
12.1k
            edges_with_sink.push_back(child->id());
938
12.1k
        }
939
6.78k
        _dag.insert({new_pip->id(), edges_with_sink});
940
6.78k
    }
941
104k
    cur_pipe->set_children(new_children);
942
104k
    _dag[downstream_pipeline_id] = edges_with_source;
943
104k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
104k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
104k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
104k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
104k
    return Status::OK();
950
104k
}
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
151k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
151k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
27.2k
        return Status::OK();
959
27.2k
    }
960
961
123k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
43.3k
        return Status::OK();
963
43.3k
    }
964
80.5k
    *do_local_exchange = true;
965
966
80.5k
    auto& operators = cur_pipe->operators();
967
80.5k
    auto total_op_num = operators.size();
968
80.5k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
80.5k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
80.5k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
80.5k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
18.4E
            << "total_op_num: " << total_op_num
975
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
80.9k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
80.5k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
23.0k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
23.0k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
23.0k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
23.0k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
23.0k
                shuffle_idx_to_instance_idx));
990
23.0k
    }
991
80.5k
    return Status::OK();
992
80.5k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
321k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
720k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
399k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
399k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
76.3k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
76.3k
                if (child->sink()->node_id() ==
1003
76.3k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
65.4k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
65.4k
                }
1006
76.3k
            }
1007
72.7k
        }
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
399k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
399k
                                             bucket_seq_to_instance_idx,
1014
399k
                                             shuffle_idx_to_instance_idx));
1015
399k
    }
1016
321k
    return Status::OK();
1017
321k
}
1018
1019
Status PipelineFragmentContext::_plan_local_exchange(
1020
        int num_buckets, int pip_idx, PipelinePtr pip,
1021
        const std::map<int, int>& bucket_seq_to_instance_idx,
1022
399k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
399k
    int idx = 1;
1024
399k
    bool do_local_exchange = false;
1025
440k
    do {
1026
440k
        auto& ops = pip->operators();
1027
440k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
495k
        for (; idx < ops.size();) {
1030
96.7k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
91.0k
                RETURN_IF_ERROR(_add_local_exchange(
1032
91.0k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
91.0k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
91.0k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
91.0k
                        shuffle_idx_to_instance_idx));
1036
91.0k
            }
1037
96.7k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
41.2k
                idx = 2;
1043
41.2k
                break;
1044
41.2k
            }
1045
55.4k
            idx++;
1046
55.4k
        }
1047
440k
    } while (do_local_exchange);
1048
399k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
59.8k
        RETURN_IF_ERROR(_add_local_exchange(
1050
59.8k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
59.8k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
59.8k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
59.8k
    }
1054
399k
    return Status::OK();
1055
399k
}
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
323k
                                                  PipelineId cur_pipeline_id) {
1063
323k
    switch (thrift_sink.type) {
1064
112k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
112k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
112k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
112k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
112k
                params.destinations, _fragment_instance_ids);
1071
112k
        break;
1072
112k
    }
1073
181k
    case TDataSinkType::RESULT_SINK: {
1074
181k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
181k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
181k
        int child_node_id = pipeline->operators().back()->node_id();
1080
181k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
181k
                                                      row_desc, output_exprs,
1082
181k
                                                      thrift_sink.result_sink);
1083
181k
        break;
1084
181k
    }
1085
78
    case TDataSinkType::DICTIONARY_SINK: {
1086
78
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
78
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
78
                                                    thrift_sink.dictionary_sink);
1092
78
        break;
1093
78
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
28.8k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
28.8k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
28.8k
        int child_node_id = pipeline->operators().back()->node_id();
1098
28.8k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
28.8k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
28.8k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
31
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
31
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
28.8k
        } else {
1104
28.8k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
28.8k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
28.8k
        }
1107
28.8k
        break;
1108
0
    }
1109
166
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
166
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
166
        DCHECK(state->get_query_ctx() != nullptr);
1112
166
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
166
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
166
                                                                output_exprs);
1115
166
        break;
1116
0
    }
1117
0
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
0
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
0
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
0
                                                         output_exprs);
1123
0
        break;
1124
0
    }
1125
0
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
0
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
0
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
0
        } else {
1133
0
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
0
                                                                row_desc, output_exprs);
1135
0
        }
1136
0
        break;
1137
0
    }
1138
0
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
0
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
0
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
0
                                                             row_desc, output_exprs);
1144
0
        break;
1145
0
    }
1146
0
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
0
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
0
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
0
                                                            output_exprs);
1152
0
        break;
1153
0
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
0
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
0
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
0
        if (config::enable_java_support) {
1167
0
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
0
                                                             output_exprs);
1169
0
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
0
        break;
1175
0
    }
1176
3
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
338
    case TDataSinkType::RESULT_FILE_SINK: {
1186
338
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
338
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
338
        } else {
1196
338
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
338
                                                              output_exprs);
1198
338
        }
1199
338
        break;
1200
338
    }
1201
565
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
565
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
565
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
565
        auto sink_id = next_sink_operator_id();
1205
565
        const int multi_cast_node_id = sink_id;
1206
565
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
565
        std::vector<int> sources;
1209
2.06k
        for (int i = 0; i < sender_size; ++i) {
1210
1.50k
            auto source_id = next_operator_id();
1211
1.50k
            sources.push_back(source_id);
1212
1.50k
        }
1213
1214
565
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
565
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
2.06k
        for (int i = 0; i < sender_size; ++i) {
1217
1.50k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
1.50k
            RowDescriptor* exchange_row_desc = nullptr;
1220
1.50k
            {
1221
1.50k
                const auto& tmp_row_desc =
1222
1.50k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
1.50k
                                ? RowDescriptor(state->desc_tbl(),
1224
1.50k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
1.50k
                                                         .output_tuple_id})
1226
1.50k
                                : row_desc;
1227
1.50k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
1.50k
            }
1229
1.50k
            auto source_id = sources[i];
1230
1.50k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
1.50k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
1.50k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
1.50k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
1.50k
                    /*operator_id=*/source_id);
1236
1.50k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
1.50k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1238
            // 2. create and set sink operator of data stream sender for new pipeline
1239
1240
1.50k
            DataSinkOperatorPtr sink_op;
1241
1.50k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
1.50k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
1.50k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
1.50k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
1.50k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
1.50k
            {
1248
1.50k
                TDataSink* t = pool->add(new TDataSink());
1249
1.50k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
1.50k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
1.50k
            }
1252
1253
            // 3. set dependency dag
1254
1.50k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
1.50k
        }
1256
565
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
565
        break;
1260
565
    }
1261
565
    case TDataSinkType::BLACKHOLE_SINK: {
1262
3
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
3
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
3
        break;
1268
3
    }
1269
0
    case TDataSinkType::TVF_TABLE_SINK: {
1270
0
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
0
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
0
                                                        output_exprs);
1275
0
        break;
1276
0
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
323k
    }
1280
322k
    return Status::OK();
1281
323k
}
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
497k
                                                 OperatorPtr& cache_op) {
1292
497k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
497k
    Defer defer = Defer([&]() {
1294
495k
        if (op) {
1295
495k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
495k
        }
1297
494k
        for (auto& s : sink_ops) {
1298
75.9k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
75.9k
        }
1300
494k
    });
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
497k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
497k
    std::stringstream error_msg;
1305
497k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
497k
    bool fe_with_old_version = false;
1308
497k
    switch (tnode.node_type) {
1309
162k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
162k
        op = std::make_shared<OlapScanOperatorX>(
1311
162k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
162k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
162k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
162k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
162k
        break;
1316
162k
    }
1317
77
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
77
        DCHECK(_query_ctx != nullptr);
1319
77
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
77
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
77
                                                    _num_instances);
1322
77
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
77
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
77
        break;
1325
77
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
2.65k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
2.65k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
2.65k
                                                 _num_instances);
1342
2.65k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
2.65k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
2.65k
        break;
1345
2.65k
    }
1346
111k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
111k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
112k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
111k
        DCHECK_GT(num_senders, 0);
1351
111k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
111k
                                                       num_senders);
1353
111k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
111k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
111k
        break;
1356
111k
    }
1357
113k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
113k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
113k
            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
113k
        bool need_create_cache_op =
1364
113k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
113k
        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
113k
        const bool group_by_limit_opt =
1385
113k
                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
113k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
113k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
113k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
113k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
113k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
113k
        const bool can_use_distinct_streaming_agg =
1396
113k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
113k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
113k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
113k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
113k
        if (can_use_distinct_streaming_agg) {
1402
82.1k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
82.1k
            } else {
1413
82.1k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
82.1k
                                                                     tnode, descs);
1415
82.1k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
82.1k
            }
1417
82.1k
        } else if (is_streaming_agg) {
1418
1.04k
            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
1.04k
            } else {
1428
1.04k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.04k
                                                             descs);
1430
1.04k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.04k
            }
1432
30.7k
        } else {
1433
            // create new pipeline to add query cache operator
1434
30.7k
            PipelinePtr new_pipe;
1435
30.7k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
30.7k
            if (enable_spill) {
1441
57
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
57
                                                                     next_operator_id(), descs);
1443
30.6k
            } else {
1444
30.6k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
30.6k
            }
1446
30.7k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
30.7k
            } else {
1451
30.7k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
30.7k
            }
1453
1454
30.7k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
30.7k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
29.2k
                _dag.insert({downstream_pipeline_id, {}});
1457
29.2k
            }
1458
30.7k
            cur_pipe = add_pipeline(cur_pipe);
1459
30.7k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
30.7k
            if (enable_spill) {
1462
57
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
57
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
30.6k
            } else {
1465
30.6k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
30.6k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
30.6k
            }
1468
30.7k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
30.7k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
30.7k
        }
1471
113k
        break;
1472
113k
    }
1473
113k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
72
        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
72
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
72
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
72
        const auto downstream_pipeline_id = cur_pipe->id();
1486
72
        if (!_dag.contains(downstream_pipeline_id)) {
1487
72
            _dag.insert({downstream_pipeline_id, {}});
1488
72
        }
1489
72
        cur_pipe = add_pipeline(cur_pipe);
1490
72
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
72
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
72
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
72
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
72
        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
72
        {
1503
72
            auto shared_state = BucketedAggSharedState::create_shared();
1504
72
            shared_state->id = op->operator_id();
1505
72
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
473
            for (int i = 0; i < _num_instances; i++) {
1508
401
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
401
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
401
                sink_dep->set_shared_state(shared_state.get());
1511
401
                shared_state->sink_deps.push_back(sink_dep);
1512
401
            }
1513
72
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
72
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
72
            _op_id_to_shared_state.insert(
1516
72
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
72
        }
1518
72
        break;
1519
72
    }
1520
8.82k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
8.82k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
8.82k
                                       tnode.hash_join_node.is_broadcast_join;
1523
8.82k
        const auto enable_spill = _runtime_state->enable_spill();
1524
8.82k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
8.82k
        } else {
1566
8.82k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
8.82k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
8.82k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
8.82k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.14k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.14k
            }
1573
8.82k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
8.82k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
8.82k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
8.82k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
8.82k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
8.82k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
8.82k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
8.82k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
8.82k
        }
1584
8.82k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
3.96k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
3.96k
                    HashJoinSharedState::create_shared(_num_instances);
1587
15.7k
            for (int i = 0; i < _num_instances; i++) {
1588
11.7k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
11.7k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
11.7k
                sink_dep->set_shared_state(shared_state.get());
1591
11.7k
                shared_state->sink_deps.push_back(sink_dep);
1592
11.7k
            }
1593
3.96k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
3.96k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
3.96k
            _op_id_to_shared_state.insert(
1596
3.96k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
3.96k
        }
1598
8.82k
        break;
1599
8.82k
    }
1600
2.02k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
2.02k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
2.02k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
2.02k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
2.02k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
1.80k
            _dag.insert({downstream_pipeline_id, {}});
1607
1.80k
        }
1608
2.02k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
2.02k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
2.02k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
2.02k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
2.02k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
2.02k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
2.02k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
2.02k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
2.02k
        break;
1618
2.02k
    }
1619
49.5k
    case TPlanNodeType::UNION_NODE: {
1620
49.5k
        int child_count = tnode.num_children;
1621
49.5k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
49.5k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
49.5k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
49.5k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
49.1k
            _dag.insert({downstream_pipeline_id, {}});
1627
49.1k
        }
1628
50.5k
        for (int i = 0; i < child_count; i++) {
1629
989
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
989
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
989
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
989
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
989
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
989
            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
989
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
989
        }
1638
49.5k
        break;
1639
49.5k
    }
1640
49.5k
    case TPlanNodeType::SORT_NODE: {
1641
31.9k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
31.9k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
31.9k
        const bool use_local_merge =
1644
31.9k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
31.9k
        if (should_spill) {
1646
7
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
31.9k
        } else if (use_local_merge) {
1648
30.0k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
30.0k
                                                                 descs);
1650
30.0k
        } else {
1651
1.91k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
1.91k
        }
1653
31.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
31.9k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
31.9k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
31.8k
            _dag.insert({downstream_pipeline_id, {}});
1658
31.8k
        }
1659
31.9k
        cur_pipe = add_pipeline(cur_pipe);
1660
31.9k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
31.9k
        if (should_spill) {
1663
7
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
7
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
31.9k
        } else {
1666
31.9k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
31.9k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
31.9k
        }
1669
31.9k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
31.9k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
31.9k
        break;
1672
31.9k
    }
1673
31.9k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.60k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.60k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.60k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.60k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.59k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.59k
        }
1698
1.60k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.60k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.60k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.60k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.60k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.60k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.60k
        break;
1706
1.60k
    }
1707
1.60k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
656
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
656
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
656
        break;
1711
656
    }
1712
656
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
297
    case TPlanNodeType::REPEAT_NODE: {
1723
297
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
297
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
297
        break;
1726
297
    }
1727
910
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
910
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
910
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
910
        break;
1731
910
    }
1732
910
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
18
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
18
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
18
        break;
1736
18
    }
1737
1.46k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.46k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.46k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.46k
        break;
1741
1.46k
    }
1742
1.46k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
272
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
272
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
272
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
272
        break;
1747
272
    }
1748
1.54k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.54k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.54k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.54k
        break;
1752
1.54k
    }
1753
4.28k
    case TPlanNodeType::META_SCAN_NODE: {
1754
4.28k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
4.28k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
4.28k
        break;
1757
4.28k
    }
1758
4.28k
    case TPlanNodeType::SELECT_NODE: {
1759
565
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
565
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
565
        break;
1762
565
    }
1763
565
    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
497k
    }
1803
493k
    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
493k
    return Status::OK();
1809
497k
}
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
320k
Status PipelineFragmentContext::submit() {
1846
320k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
320k
    _submitted = true;
1850
1851
320k
    int submit_tasks = 0;
1852
320k
    Status st;
1853
320k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
873k
    for (auto& task : _tasks) {
1855
1.49M
        for (auto& t : task) {
1856
1.49M
            st = scheduler->submit(t.first);
1857
1.49M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.49M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.49M
            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
1.49M
            submit_tasks++;
1866
1.49M
        }
1867
873k
    }
1868
320k
    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
320k
    } else {
1883
320k
        return st;
1884
320k
    }
1885
320k
}
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
323k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
323k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
323k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
323k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
323k
    if (!_need_notify_close) {
1919
320k
        auto st = send_report(true);
1920
320k
        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
320k
    }
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
323k
    if (_runtime_state->enable_profile() &&
1931
323k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.04k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.04k
         _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
323k
    if (_query_ctx->enable_profile()) {
1953
2.04k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.04k
                                         collect_realtime_load_channel_profile());
1955
2.04k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
323k
    return !_need_notify_close;
1960
323k
}
1961
1962
1.48M
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
1.48M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.48M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
505k
        if (_dag.contains(pipeline_id)) {
1967
286k
            for (auto dep : _dag[pipeline_id]) {
1968
286k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
286k
            }
1970
222k
        }
1971
505k
    }
1972
1.48M
    bool need_remove = false;
1973
1.48M
    {
1974
1.48M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.48M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.48M
        _query_ctx->inc_finished_task_num();
1978
1.48M
        if (_closed_tasks >= _total_tasks) {
1979
323k
            need_remove = _close_fragment_instance();
1980
323k
        }
1981
1.48M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.48M
    if (need_remove) {
1984
320k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
320k
    }
1986
1.48M
}
1987
1988
41.7k
std::string PipelineFragmentContext::get_load_error_url() {
1989
41.7k
    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
94.4k
    for (auto& tasks : _tasks) {
1993
156k
        for (auto& task : tasks) {
1994
156k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
162
                return to_load_error_http_path(str);
1996
162
            }
1997
156k
        }
1998
94.4k
    }
1999
41.5k
    return "";
2000
41.7k
}
2001
2002
41.7k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
41.7k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
94.3k
    for (auto& tasks : _tasks) {
2007
155k
        for (auto& task : tasks) {
2008
155k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
162
                return str;
2010
162
            }
2011
155k
        }
2012
94.3k
    }
2013
41.5k
    return "";
2014
41.7k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
36.4k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
36.4k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
36.4k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
36.4k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
36.4k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
36.4k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
36.4k
    });
2031
2032
36.4k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
36.4k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
36.4k
    int callback_retries = 10;
2038
36.4k
    const int sleep_ms = 1000;
2039
36.4k
    Status exec_status = req.status;
2040
36.4k
    Status coord_status;
2041
36.4k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
36.4k
    do {
2043
36.4k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
36.4k
                                                            req.coord_addr, &coord_status);
2045
36.4k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
36.4k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
36.4k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
36.4k
    TReportExecStatusParams params;
2059
36.4k
    params.protocol_version = FrontendServiceVersion::V1;
2060
36.4k
    params.__set_query_id(req.query_id);
2061
36.4k
    params.__set_backend_num(req.backend_num);
2062
36.4k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
36.4k
    params.__set_fragment_id(req.fragment_id);
2064
36.4k
    params.__set_status(exec_status.to_thrift());
2065
36.4k
    params.__set_done(req.done);
2066
36.4k
    params.__set_query_type(req.runtime_state->query_type());
2067
36.4k
    params.__isset.profile = false;
2068
2069
36.4k
    DCHECK(req.runtime_state != nullptr);
2070
2071
36.4k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
32.7k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
32.7k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
32.7k
    } else {
2075
3.62k
        DCHECK(!req.runtime_states.empty());
2076
3.62k
        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
3.62k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
3.62k
    }
2086
2087
36.4k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
36.4k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
36.4k
    static std::string s_unselected_rows = "unselected.rows";
2090
36.4k
    int64_t num_rows_load_success = 0;
2091
36.4k
    int64_t num_rows_load_filtered = 0;
2092
36.4k
    int64_t num_rows_load_unselected = 0;
2093
36.4k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
36.4k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
36.4k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
36.4k
    } else if (!req.runtime_states.empty()) {
2109
105k
        for (auto* rs : req.runtime_states) {
2110
105k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
105k
                rs->num_finished_range() > 0) {
2112
30.3k
                params.__isset.load_counters = true;
2113
30.3k
                num_rows_load_success += rs->num_rows_load_success();
2114
30.3k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
30.3k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
30.3k
                params.__isset.fragment_instance_reports = true;
2117
30.3k
                TFragmentInstanceReport t;
2118
30.3k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
30.3k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
30.3k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
30.3k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
30.3k
                params.fragment_instance_reports.push_back(t);
2123
30.3k
            }
2124
105k
        }
2125
36.4k
    }
2126
36.4k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
36.4k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
36.4k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
36.4k
    if (!req.load_error_url.empty()) {
2131
147
        params.__set_tracking_url(req.load_error_url);
2132
147
    }
2133
36.4k
    if (!req.first_error_msg.empty()) {
2134
147
        params.__set_first_error_msg(req.first_error_msg);
2135
147
    }
2136
105k
    for (auto* rs : req.runtime_states) {
2137
105k
        if (rs->wal_id() > 0) {
2138
112
            params.__set_txn_id(rs->wal_id());
2139
112
            params.__set_label(rs->import_label());
2140
112
        }
2141
105k
    }
2142
36.4k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
36.4k
    } else if (!req.runtime_states.empty()) {
2146
105k
        for (auto* rs : req.runtime_states) {
2147
105k
            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
105k
        }
2154
36.4k
    }
2155
36.4k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
36.4k
    } else if (!req.runtime_states.empty()) {
2159
105k
        for (auto* rs : req.runtime_states) {
2160
105k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
24.9k
                params.__isset.commitInfos = true;
2162
24.9k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
24.9k
            }
2164
105k
        }
2165
36.4k
    }
2166
36.4k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
36.4k
    } else if (!req.runtime_states.empty()) {
2170
105k
        for (auto* rs : req.runtime_states) {
2171
105k
            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
105k
        }
2177
36.4k
    }
2178
36.4k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
36.4k
    } else if (!req.runtime_states.empty()) {
2183
105k
        for (auto* rs : req.runtime_states) {
2184
105k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
0
                params.__isset.hive_partition_updates = true;
2186
0
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
0
                                                     rs_hpu.begin(), rs_hpu.end());
2188
0
            }
2189
105k
        }
2190
36.4k
    }
2191
36.4k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
36.4k
    } else if (!req.runtime_states.empty()) {
2196
105k
        for (auto* rs : req.runtime_states) {
2197
105k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
0
                params.__isset.iceberg_commit_datas = true;
2199
0
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
0
                                                   rs_icd.begin(), rs_icd.end());
2201
0
            }
2202
105k
        }
2203
36.4k
    }
2204
2205
36.4k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
36.4k
    } else if (!req.runtime_states.empty()) {
2209
105k
        for (auto* rs : req.runtime_states) {
2210
105k
            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
105k
        }
2216
36.4k
    }
2217
2218
36.4k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
36.4k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
36.4k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
36.4k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
36.4k
    }
2224
2225
36.4k
    TReportExecStatusResult res;
2226
36.4k
    Status rpc_status;
2227
2228
36.4k
    VLOG_DEBUG << "reportExecStatus params is "
2229
6
               << apache::thrift::ThriftDebugString(params).c_str();
2230
36.4k
    if (!exec_status.ok()) {
2231
1.54k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.54k
                     << " to coordinator: " << req.coord_addr
2233
1.54k
                     << ", query id: " << print_id(req.query_id);
2234
1.54k
    }
2235
36.4k
    try {
2236
36.4k
        try {
2237
36.4k
            (*coord)->reportExecStatus(res, params);
2238
36.4k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
36.4k
        rpc_status = Status::create<false>(res.status);
2254
36.4k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
36.4k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
36.4k
}
2265
2266
324k
Status PipelineFragmentContext::send_report(bool done) {
2267
324k
    Status exec_status = _query_ctx->exec_status();
2268
    // If plan is done successfully, but _is_report_success is false,
2269
    // no need to send report.
2270
    // Load will set _is_report_success to true because load wants to know
2271
    // the process.
2272
324k
    if (!_is_report_success && done && exec_status.ok()) {
2273
287k
        return Status::OK();
2274
287k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
36.5k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
102
        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
102
            return Status::OK();
2286
102
        }
2287
0
        return Status::NeedSendAgain("");
2288
102
    }
2289
2290
36.4k
    std::vector<RuntimeState*> runtime_states;
2291
2292
70.5k
    for (auto& tasks : _tasks) {
2293
105k
        for (auto& task : tasks) {
2294
105k
            runtime_states.push_back(task.second.get());
2295
105k
        }
2296
70.5k
    }
2297
2298
36.4k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
36.4k
                                        ? get_load_error_url()
2300
36.4k
                                        : _query_ctx->get_load_error_url();
2301
36.4k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
36.4k
                                          ? get_first_error_msg()
2303
36.4k
                                          : _query_ctx->get_first_error_msg();
2304
2305
36.4k
    ReportStatusRequest req {.status = exec_status,
2306
36.4k
                             .runtime_states = runtime_states,
2307
36.4k
                             .done = done || !exec_status.ok(),
2308
36.4k
                             .coord_addr = _query_ctx->coord_addr,
2309
36.4k
                             .query_id = _query_id,
2310
36.4k
                             .fragment_id = _fragment_id,
2311
36.4k
                             .fragment_instance_id = TUniqueId(),
2312
36.4k
                             .backend_num = -1,
2313
36.4k
                             .runtime_state = _runtime_state.get(),
2314
36.4k
                             .load_error_url = load_eror_url,
2315
36.4k
                             .first_error_msg = first_error_msg,
2316
36.4k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
36.4k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
36.4k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
36.4k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
36.4k
        _coordinator_callback(req);
2321
36.4k
        if (!req.done) {
2322
3.59k
            ctx->refresh_next_report_time();
2323
3.59k
        }
2324
36.4k
    });
2325
36.5k
}
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
130
std::string PipelineFragmentContext::debug_string() {
2365
130
    std::lock_guard<std::mutex> l(_task_mutex);
2366
130
    fmt::memory_buffer debug_string_buffer;
2367
130
    fmt::format_to(debug_string_buffer,
2368
130
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
130
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
130
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
447
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
317
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
742
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
425
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
425
                           _tasks[j][i].first->debug_string());
2376
425
        }
2377
317
    }
2378
2379
130
    return fmt::to_string(debug_string_buffer);
2380
130
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.04k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.04k
    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
2.04k
    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
2.04k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.04k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.04k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.03k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.03k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.03k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.03k
        res.push_back(profile_ptr);
2407
4.03k
    }
2408
2409
2.04k
    return res;
2410
2.04k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.04k
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
2.04k
    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
7.26k
    for (const auto& tasks : _tasks) {
2426
14.7k
        for (const auto& task : tasks) {
2427
14.7k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
14.7k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
14.7k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
14.7k
                                                           _runtime_state->profile_level());
2435
14.7k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
14.7k
        }
2437
7.26k
    }
2438
2439
2.04k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.04k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.04k
                                                      _runtime_state->profile_level());
2442
2.04k
    return load_channel_profile;
2443
2.04k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
5.25k
    for (const auto& _task : _tasks) {
2455
10.6k
        for (const auto& task : _task) {
2456
10.6k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
10.6k
            result.merge(set);
2458
10.6k
        }
2459
5.25k
    }
2460
3.28k
    if (_runtime_state) {
2461
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.28k
        result.merge(set);
2463
3.28k
    }
2464
3.28k
    return result;
2465
3.28k
}
2466
2467
325k
void PipelineFragmentContext::_release_resource() {
2468
325k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
325k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
325k
    auto st = _query_ctx->exec_status();
2472
875k
    for (auto& _task : _tasks) {
2473
875k
        if (!_task.empty()) {
2474
875k
            _call_back(_task.front().first->runtime_state(), &st);
2475
875k
        }
2476
875k
    }
2477
325k
    _tasks.clear();
2478
325k
    _dag.clear();
2479
325k
    _pip_id_to_pipeline.clear();
2480
325k
    _pipelines.clear();
2481
325k
    _sink.reset();
2482
325k
    _root_op.reset();
2483
325k
    _runtime_filter_mgr_map.clear();
2484
325k
    _op_id_to_shared_state.clear();
2485
325k
}
2486
2487
} // namespace doris