Coverage Report

Created: 2026-06-05 15:14

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
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#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
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#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
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#include "runtime/exec_env.h"
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#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
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#include "util/client_cache.h"
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#include "util/countdown_latch.h"
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#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
449k
        : _query_id(std::move(query_id)),
144
449k
          _fragment_id(request.fragment_id),
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449k
          _exec_env(exec_env),
146
449k
          _query_ctx(std::move(query_ctx)),
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449k
          _call_back(call_back),
148
449k
          _is_report_on_cancel(true),
149
449k
          _params(request),
150
449k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
449k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
449k
                                                               : false) {
153
449k
    _fragment_watcher.start();
154
449k
}
155
156
449k
PipelineFragmentContext::~PipelineFragmentContext() {
157
449k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
449k
            .tag("query_id", print_id(_query_id))
159
449k
            .tag("fragment_id", _fragment_id);
160
449k
    _release_resource();
161
449k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
449k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
449k
        _runtime_state.reset();
165
449k
        _query_ctx.reset();
166
449k
    }
167
449k
}
168
169
190
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
190
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
190
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
190
}
175
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// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
10.3k
bool PipelineFragmentContext::notify_close() {
181
10.3k
    bool all_closed = false;
182
10.3k
    bool need_remove = false;
183
10.3k
    {
184
10.3k
        std::lock_guard<std::mutex> l(_task_mutex);
185
10.3k
        if (_closed_tasks >= _total_tasks) {
186
3.38k
            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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3.32k
                need_remove = true;
193
3.32k
            }
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3.38k
            all_closed = true;
195
3.38k
        }
196
        // make fragment release by self after cancel
197
10.3k
        _need_notify_close = false;
198
10.3k
    }
199
10.3k
    if (need_remove) {
200
3.32k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.32k
    }
202
10.3k
    return all_closed;
203
10.3k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
7.02k
void PipelineFragmentContext::cancel(const Status reason) {
210
7.02k
    LOG_INFO("PipelineFragmentContext::cancel")
211
7.02k
            .tag("query_id", print_id(_query_id))
212
7.02k
            .tag("fragment_id", _fragment_id)
213
7.02k
            .tag("reason", reason.to_string());
214
7.02k
    if (notify_close()) {
215
78
        return;
216
78
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.94k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
12
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
12
                                   debug_string());
221
12
        LOG_LONG_STRING(WARNING, dbg_str);
222
12
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
6.94k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
6.95k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
6.94k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
26
        _query_ctx->set_load_error_url(error_url);
236
26
    }
237
238
6.94k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
26
        _query_ctx->set_first_error_msg(first_error_msg);
240
26
    }
241
242
6.94k
    _query_ctx->cancel(reason, _fragment_id);
243
6.94k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
416
        _is_report_on_cancel = false;
245
6.53k
    } else {
246
39.7k
        for (auto& id : _fragment_instance_ids) {
247
39.7k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
39.7k
        }
249
6.53k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
6.94k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.94k
    if (stream_load_ctx != nullptr) {
254
32
        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
32
        stream_load_ctx->error_url = get_load_error_url();
259
32
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
32
    }
261
262
41.8k
    for (auto& tasks : _tasks) {
263
91.9k
        for (auto& task : tasks) {
264
91.9k
            task.first->unblock_all_dependencies();
265
91.9k
        }
266
41.8k
    }
267
6.94k
}
268
269
707k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
707k
    PipelineId id = _next_pipeline_id++;
271
707k
    auto pipeline = std::make_shared<Pipeline>(
272
707k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
707k
            parent ? parent->num_tasks() : _num_instances);
274
707k
    if (idx >= 0) {
275
131k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
576k
    } else {
277
576k
        _pipelines.emplace_back(pipeline);
278
576k
    }
279
707k
    if (parent) {
280
250k
        parent->set_children(pipeline);
281
250k
    }
282
707k
    return pipeline;
283
707k
}
284
285
448k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
448k
    {
287
448k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
448k
        auto root_pipeline = add_pipeline();
290
448k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
448k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
448k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
448k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
448k
                                          _params.fragment.output_exprs, _params,
299
448k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
448k
                                          *_desc_tbl, root_pipeline->id()));
301
448k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
448k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
575k
        for (PipelinePtr& pipeline : _pipelines) {
305
575k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
575k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
575k
        }
308
448k
    }
309
    // 4. Build local exchanger
310
448k
    if (_runtime_state->enable_local_shuffle()) {
311
444k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
444k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
444k
                                             _params.bucket_seq_to_instance_idx,
314
444k
                                             _params.shuffle_idx_to_instance_idx));
315
444k
    }
316
317
    // 5. Initialize global states in pipelines.
318
707k
    for (PipelinePtr& pipeline : _pipelines) {
319
707k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
707k
        pipeline->children().clear();
321
707k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
707k
    }
323
324
447k
    {
325
447k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
447k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
447k
    }
329
330
447k
    return Status::OK();
331
447k
}
332
333
448k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
448k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
448k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
448k
        _timeout = _params.query_options.execution_timeout;
339
448k
    }
340
341
448k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
448k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
448k
    SCOPED_TIMER(_prepare_timer);
344
448k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
448k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
448k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
448k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
448k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
448k
    {
350
448k
        SCOPED_TIMER(_init_context_timer);
351
448k
        cast_set(_num_instances, _params.local_params.size());
352
448k
        _total_instances =
353
448k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
448k
        auto* fragment_context = this;
356
357
448k
        if (_params.query_options.__isset.is_report_success) {
358
448k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
448k
        }
360
361
        // 1. Set up the global runtime state.
362
448k
        _runtime_state = RuntimeState::create_unique(
363
448k
                _params.query_id, _params.fragment_id, _params.query_options,
364
448k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
448k
        _runtime_state->set_task_execution_context(shared_from_this());
366
448k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
448k
        if (_params.__isset.backend_id) {
368
444k
            _runtime_state->set_backend_id(_params.backend_id);
369
444k
        }
370
448k
        if (_params.__isset.import_label) {
371
237
            _runtime_state->set_import_label(_params.import_label);
372
237
        }
373
448k
        if (_params.__isset.db_name) {
374
189
            _runtime_state->set_db_name(_params.db_name);
375
189
        }
376
448k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
448k
        if (_params.is_simplified_param) {
381
149k
            _desc_tbl = _query_ctx->desc_tbl;
382
298k
        } else {
383
298k
            DCHECK(_params.__isset.desc_tbl);
384
298k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
298k
                                                  &_desc_tbl));
386
298k
        }
387
448k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
448k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
448k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
448k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
448k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
448k
        const auto target_size = _params.local_params.size();
395
448k
        _fragment_instance_ids.resize(target_size);
396
1.70M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.25M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.25M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.25M
        }
400
448k
    }
401
402
448k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
447k
    _init_next_report_time();
405
406
447k
    _prepared = true;
407
447k
    return Status::OK();
408
448k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.25M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.25M
    const auto& local_params = _params.local_params[instance_idx];
414
1.25M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.25M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.25M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.25M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.25M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
2.11M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
2.11M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
2.11M
                                std::vector<std::shared_ptr<Dependency>>>>
422
2.11M
                shared_state_map;
423
2.68M
        for (auto& op : pipeline->operators()) {
424
2.68M
            auto source_id = op->operator_id();
425
2.68M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.68M
                iter != _op_id_to_shared_state.end()) {
427
876k
                shared_state_map.insert({source_id, iter->second});
428
876k
            }
429
2.68M
        }
430
2.11M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
2.11M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
2.11M
                iter != _op_id_to_shared_state.end()) {
433
360k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
360k
            }
435
2.11M
        }
436
2.11M
        return shared_state_map;
437
2.11M
    };
438
439
3.87M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.62M
        auto& pipeline = _pipelines[pip_idx];
441
2.62M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
2.11M
            auto task_runtime_state = RuntimeState::create_unique(
443
2.11M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
2.11M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
2.11M
            {
446
                // Initialize runtime state for this task
447
2.11M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
2.11M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
2.11M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
2.11M
                if (_params.__isset.backend_id) {
453
2.10M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
2.10M
                }
455
2.11M
                if (_params.__isset.import_label) {
456
238
                    task_runtime_state->set_import_label(_params.import_label);
457
238
                }
458
2.11M
                if (_params.__isset.db_name) {
459
190
                    task_runtime_state->set_db_name(_params.db_name);
460
190
                }
461
2.11M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
2.11M
                if (_params.__isset.wal_id) {
465
112
                    task_runtime_state->set_wal_id(_params.wal_id);
466
112
                }
467
2.11M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
2.11M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
2.11M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
2.11M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
2.11M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
2.11M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
2.11M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
2.11M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
2.11M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
2.11M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
2.11M
            }
482
2.11M
            auto cur_task_id = _total_tasks++;
483
2.11M
            task_runtime_state->set_task_id(cur_task_id);
484
2.11M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
2.11M
            auto task = std::make_shared<PipelineTask>(
486
2.11M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
2.11M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
2.11M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
2.11M
                    instance_idx);
490
2.11M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
2.11M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
2.11M
            _tasks[instance_idx].emplace_back(
493
2.11M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
2.11M
                            std::move(task), std::move(task_runtime_state)});
495
2.11M
        }
496
2.62M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
2.62M
    for (auto& _pipeline : _pipelines) {
516
2.62M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
2.11M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
2.11M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
2.11M
            if (_dag.contains(_pipeline->id())) {
522
1.37M
                auto& deps = _dag[_pipeline->id()];
523
2.23M
                for (auto& dep : deps) {
524
2.23M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.20M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.20M
                        if (ss) {
527
486k
                            task->inject_shared_state(ss);
528
716k
                        } else {
529
716k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
716k
                                    task->get_source_shared_state());
531
716k
                        }
532
1.20M
                    }
533
2.23M
                }
534
1.37M
            }
535
2.11M
        }
536
2.62M
    }
537
3.87M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.62M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
2.11M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
2.11M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
2.11M
            std::vector<TScanRangeParams> scan_ranges;
542
2.11M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
2.11M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
336k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
336k
            }
546
2.11M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
2.11M
                                                             _params.fragment.output_sink));
548
2.11M
        }
549
2.62M
    }
550
1.25M
    {
551
1.25M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.25M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.25M
    }
554
1.25M
    return Status::OK();
555
1.25M
}
556
557
447k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
447k
    _total_tasks = 0;
559
447k
    _closed_tasks = 0;
560
447k
    const auto target_size = _params.local_params.size();
561
447k
    _tasks.resize(target_size);
562
447k
    _runtime_filter_mgr_map.resize(target_size);
563
1.15M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
706k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
706k
    }
566
447k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
447k
    if (target_size > 1 &&
569
447k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
151k
         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
15.5k
        std::vector<Status> prepare_status(target_size);
573
15.5k
        int submitted_tasks = 0;
574
15.5k
        Status submit_status;
575
15.5k
        CountDownLatch latch((int)target_size);
576
165k
        for (int i = 0; i < target_size; i++) {
577
150k
            submit_status = thread_pool->submit_func([&, i]() {
578
150k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
150k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
150k
                latch.count_down();
581
150k
            });
582
150k
            if (LIKELY(submit_status.ok())) {
583
150k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
150k
        }
588
15.5k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
15.5k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
165k
        for (int i = 0; i < submitted_tasks; i++) {
593
150k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
150k
        }
597
432k
    } else {
598
1.53M
        for (int i = 0; i < target_size; i++) {
599
1.10M
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
1.10M
        }
601
432k
    }
602
447k
    _pipeline_parent_map.clear();
603
447k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
447k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
447k
    return Status::OK();
608
447k
}
609
610
447k
void PipelineFragmentContext::_init_next_report_time() {
611
447k
    auto interval_s = config::pipeline_status_report_interval;
612
447k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
42.9k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
42.9k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
42.9k
        _previous_report_time =
617
42.9k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
42.9k
        _disable_period_report = false;
619
42.9k
    }
620
447k
}
621
622
4.92k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.92k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.92k
    DCHECK(disable == true);
625
4.92k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.92k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.92k
}
628
629
7.70M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.70M
    if (!_is_report_success) {
631
7.21M
        return;
632
7.21M
    }
633
490k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
490k
    if (disable) {
635
9.07k
        return;
636
9.07k
    }
637
481k
    int32_t interval_s = config::pipeline_status_report_interval;
638
481k
    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
481k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
481k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
481k
    if (MonotonicNanos() > next_report_time) {
646
4.92k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.92k
                                                            std::memory_order_acq_rel)) {
648
6
            return;
649
6
        }
650
4.92k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
4.92k
        auto st = send_report(false);
667
4.92k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
4.92k
    }
673
481k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
447k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
447k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
447k
    int node_idx = 0;
682
683
447k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
447k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
447k
    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
447k
    return Status::OK();
691
447k
}
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
679k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
679k
    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
679k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
679k
    int num_children = tnodes[*node_idx].num_children;
706
679k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
679k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
679k
    OperatorPtr op = nullptr;
710
679k
    OperatorPtr cache_op = nullptr;
711
679k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
679k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
679k
                                     followed_by_shuffled_operator,
714
679k
                                     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
679k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
679k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
231k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
448k
    } else {
723
448k
        *root = op;
724
448k
    }
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
679k
    auto required_data_distribution =
737
679k
            cur_pipe->operators().empty()
738
679k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
679k
                    : op->required_data_distribution(_runtime_state.get());
740
679k
    current_followed_by_shuffled_operator =
741
679k
            ((followed_by_shuffled_operator ||
742
679k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
617k
                                             : op->is_shuffled_operator())) &&
744
679k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
679k
            (followed_by_shuffled_operator &&
746
564k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
679k
    current_require_bucket_distribution =
749
679k
            ((require_bucket_distribution ||
750
679k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
622k
                                             : op->is_colocated_operator())) &&
752
679k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
679k
            (require_bucket_distribution &&
754
570k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
679k
    if (num_children == 0) {
757
465k
        _use_serial_source = op->is_serial_operator();
758
465k
    }
759
    // rely on that tnodes is preorder of the plan
760
910k
    for (int i = 0; i < num_children; i++) {
761
231k
        ++*node_idx;
762
231k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
231k
                                            current_followed_by_shuffled_operator,
764
231k
                                            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
231k
        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
231k
    }
775
776
679k
    return Status::OK();
777
679k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
131k
        PipelinePtr pipe_with_sink) {
782
131k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
131k
    pipe_with_source->set_num_tasks(_num_instances);
784
131k
    pipe_with_source->set_data_distribution(data_distribution);
785
131k
}
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
131k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
131k
    auto& operators = cur_pipe->operators();
793
131k
    const auto downstream_pipeline_id = cur_pipe->id();
794
131k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
131k
    DataSinkOperatorPtr sink;
797
131k
    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
131k
    const bool followed_by_shuffled_operator =
804
131k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
131k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
131k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
131k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
131k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
131k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
131k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
131k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
131k
    if (bucket_seq_to_instance_idx.empty() &&
813
131k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
4
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
4
    }
816
131k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
131k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
131k
                                          num_buckets, use_global_hash_shuffle,
819
131k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
131k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
131k
            LocalExchangeSharedState::create_shared(_num_instances);
824
131k
    switch (data_distribution.distribution_type) {
825
25.3k
    case ExchangeType::HASH_SHUFFLE:
826
25.3k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
25.3k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
25.3k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
25.3k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
25.3k
                        ? cast_set<int>(
831
25.3k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
25.3k
                        : 0);
833
25.3k
        break;
834
725
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
725
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
725
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
725
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
725
                        ? cast_set<int>(
839
725
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
725
                        : 0);
841
725
        break;
842
100k
    case ExchangeType::PASSTHROUGH:
843
100k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
100k
                cur_pipe->num_tasks(), _num_instances,
845
100k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
100k
                        ? cast_set<int>(
847
100k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
100k
                        : 0);
849
100k
        break;
850
555
    case ExchangeType::BROADCAST:
851
555
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
555
                cur_pipe->num_tasks(), _num_instances,
853
555
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
555
                        ? cast_set<int>(
855
555
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
555
                        : 0);
857
555
        break;
858
2.89k
    case ExchangeType::PASS_TO_ONE:
859
2.89k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
860
            // If shared hash table is enabled for BJ, hash table will be built by only one task
861
1.44k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.44k
                    cur_pipe->num_tasks(), _num_instances,
863
1.44k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.44k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.44k
                                                    .local_exchange_free_blocks_limit)
866
1.44k
                            : 0);
867
1.45k
        } else {
868
1.45k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.45k
                    cur_pipe->num_tasks(), _num_instances,
870
1.45k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.45k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.45k
                                                    .local_exchange_free_blocks_limit)
873
1.45k
                            : 0);
874
1.45k
        }
875
2.89k
        break;
876
1.00k
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
1.00k
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
1.00k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
1.00k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
1.00k
                        ? cast_set<int>(
881
1.00k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
1.00k
                        : 0);
883
1.00k
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
131k
    }
888
131k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
131k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
131k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
131k
    _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
131k
    std::copy(operators.begin(), operators.begin() + idx,
898
131k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
131k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
131k
    OperatorPtr source_op;
905
131k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
131k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
131k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
131k
    if (!operators.empty()) {
909
47.7k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
47.7k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
47.7k
    }
912
131k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
131k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
131k
    std::vector<PipelineId> edges_with_source;
917
150k
    for (auto child : cur_pipe->children()) {
918
150k
        bool found = false;
919
165k
        for (auto op : new_pip->operators()) {
920
165k
            if (child->sink()->node_id() == op->node_id()) {
921
13.5k
                new_pip->set_children(child);
922
13.5k
                found = true;
923
13.5k
            };
924
165k
        }
925
150k
        if (!found) {
926
136k
            new_children.push_back(child);
927
136k
            edges_with_source.push_back(child->id());
928
136k
        }
929
150k
    }
930
131k
    new_children.push_back(new_pip);
931
131k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
131k
    if (!new_pip->children().empty()) {
935
7.75k
        std::vector<PipelineId> edges_with_sink;
936
13.5k
        for (auto child : new_pip->children()) {
937
13.5k
            edges_with_sink.push_back(child->id());
938
13.5k
        }
939
7.75k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.75k
    }
941
131k
    cur_pipe->set_children(new_children);
942
131k
    _dag[downstream_pipeline_id] = edges_with_source;
943
131k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
131k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
131k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
131k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
131k
    return Status::OK();
950
131k
}
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
197k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
197k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
40.6k
        return Status::OK();
959
40.6k
    }
960
961
156k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
51.6k
        return Status::OK();
963
51.6k
    }
964
104k
    *do_local_exchange = true;
965
966
104k
    auto& operators = cur_pipe->operators();
967
104k
    auto total_op_num = operators.size();
968
104k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
104k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
104k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
104k
            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
105k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
104k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
26.0k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
26.0k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
26.0k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
26.0k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
26.0k
                shuffle_idx_to_instance_idx));
990
26.0k
    }
991
104k
    return Status::OK();
992
104k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
443k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.01M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
571k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
571k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
119k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
119k
                if (child->sink()->node_id() ==
1003
119k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
104k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
104k
                }
1006
119k
            }
1007
114k
        }
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
571k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
571k
                                             bucket_seq_to_instance_idx,
1014
571k
                                             shuffle_idx_to_instance_idx));
1015
571k
    }
1016
443k
    return Status::OK();
1017
443k
}
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
570k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
570k
    int idx = 1;
1024
570k
    bool do_local_exchange = false;
1025
618k
    do {
1026
618k
        auto& ops = pip->operators();
1027
618k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
682k
        for (; idx < ops.size();) {
1030
111k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
103k
                RETURN_IF_ERROR(_add_local_exchange(
1032
103k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
103k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
103k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
103k
                        shuffle_idx_to_instance_idx));
1036
103k
            }
1037
111k
            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
47.8k
                idx = 2;
1043
47.8k
                break;
1044
47.8k
            }
1045
64.0k
            idx++;
1046
64.0k
        }
1047
618k
    } while (do_local_exchange);
1048
570k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
94.0k
        RETURN_IF_ERROR(_add_local_exchange(
1050
94.0k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
94.0k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
94.0k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
94.0k
    }
1054
570k
    return Status::OK();
1055
570k
}
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
448k
                                                  PipelineId cur_pipeline_id) {
1063
448k
    switch (thrift_sink.type) {
1064
147k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
147k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
147k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
147k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
147k
                params.destinations, _fragment_instance_ids);
1071
147k
        break;
1072
147k
    }
1073
259k
    case TDataSinkType::RESULT_SINK: {
1074
259k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
259k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
259k
        int child_node_id = pipeline->operators().back()->node_id();
1080
259k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
259k
                                                      row_desc, output_exprs,
1082
259k
                                                      thrift_sink.result_sink);
1083
259k
        break;
1084
259k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
34.4k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
34.4k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
34.4k
        int child_node_id = pipeline->operators().back()->node_id();
1098
34.4k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
34.4k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
34.4k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.89k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.89k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
31.5k
        } else {
1104
31.5k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
31.5k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
31.5k
        }
1107
34.4k
        break;
1108
0
    }
1109
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
165
        DCHECK(state->get_query_ctx() != nullptr);
1112
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
165
                                                                output_exprs);
1115
165
        break;
1116
0
    }
1117
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.46k
                                                         output_exprs);
1123
1.46k
        break;
1124
1.46k
    }
1125
1.72k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.72k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.72k
        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
1.72k
        } else {
1133
1.72k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.72k
                                                                row_desc, output_exprs);
1135
1.72k
        }
1136
1.72k
        break;
1137
1.72k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
502
    case TDataSinkType::RESULT_FILE_SINK: {
1186
502
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
502
        } else {
1196
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
502
                                                              output_exprs);
1198
502
        }
1199
502
        break;
1200
502
    }
1201
2.58k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.58k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.58k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.58k
        auto sink_id = next_sink_operator_id();
1205
2.58k
        const int multi_cast_node_id = sink_id;
1206
2.58k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.58k
        std::vector<int> sources;
1209
10.1k
        for (int i = 0; i < sender_size; ++i) {
1210
7.57k
            auto source_id = next_operator_id();
1211
7.57k
            sources.push_back(source_id);
1212
7.57k
        }
1213
1214
2.58k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.58k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
10.1k
        for (int i = 0; i < sender_size; ++i) {
1217
7.57k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
7.57k
            RowDescriptor* exchange_row_desc = nullptr;
1220
7.57k
            {
1221
7.57k
                const auto& tmp_row_desc =
1222
7.57k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
7.57k
                                ? RowDescriptor(state->desc_tbl(),
1224
7.57k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
7.57k
                                                         .output_tuple_id})
1226
7.57k
                                : row_desc;
1227
7.57k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
7.57k
            }
1229
7.57k
            auto source_id = sources[i];
1230
7.57k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
7.57k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
7.57k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
7.57k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
7.57k
                    /*operator_id=*/source_id);
1236
7.57k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
7.57k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1238
            // 2. create and set sink operator of data stream sender for new pipeline
1239
1240
7.57k
            DataSinkOperatorPtr sink_op;
1241
7.57k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
7.57k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
7.57k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
7.57k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
7.57k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
7.57k
            {
1248
7.57k
                TDataSink* t = pool->add(new TDataSink());
1249
7.57k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
7.57k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
7.57k
            }
1252
1253
            // 3. set dependency dag
1254
7.57k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
7.57k
        }
1256
2.58k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.58k
        break;
1260
2.58k
    }
1261
2.58k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
13
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
13
        break;
1268
13
    }
1269
156
    case TDataSinkType::TVF_TABLE_SINK: {
1270
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
156
                                                        output_exprs);
1275
156
        break;
1276
156
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
448k
    }
1280
448k
    return Status::OK();
1281
448k
}
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
680k
                                                 OperatorPtr& cache_op) {
1292
680k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
680k
    Defer defer = Defer([&]() {
1294
680k
        if (op) {
1295
680k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
680k
        }
1297
679k
        for (auto& s : sink_ops) {
1298
119k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
119k
        }
1300
679k
    });
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
680k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
680k
    std::stringstream error_msg;
1305
680k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
680k
    bool fe_with_old_version = false;
1308
680k
    switch (tnode.node_type) {
1309
220k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
220k
        op = std::make_shared<OlapScanOperatorX>(
1311
220k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
220k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
220k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
220k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
220k
        break;
1316
220k
    }
1317
78
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
78
        DCHECK(_query_ctx != nullptr);
1319
78
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
78
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
78
                                                    _num_instances);
1322
78
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
78
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
78
        break;
1325
78
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
25.8k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
25.8k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
25.8k
                                                 _num_instances);
1342
25.8k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
25.8k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
25.8k
        break;
1345
25.8k
    }
1346
152k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
152k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
153k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
152k
        DCHECK_GT(num_senders, 0);
1351
152k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
152k
                                                       num_senders);
1353
152k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
152k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
152k
        break;
1356
152k
    }
1357
145k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
145k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
145k
            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
145k
        bool need_create_cache_op =
1364
145k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
145k
        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
145k
        const bool group_by_limit_opt =
1385
145k
                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
145k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
145k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
145k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
145k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
145k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
145k
        const bool can_use_distinct_streaming_agg =
1396
145k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
145k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
145k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
145k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
145k
        if (can_use_distinct_streaming_agg) {
1402
89.0k
            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
89.0k
            } else {
1413
89.0k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
89.0k
                                                                     tnode, descs);
1415
89.0k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
89.0k
            }
1417
89.0k
        } else if (is_streaming_agg) {
1418
1.60k
            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
1.60k
            } else {
1428
1.60k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.60k
                                                             descs);
1430
1.60k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.60k
            }
1432
54.9k
        } else {
1433
            // create new pipeline to add query cache operator
1434
54.9k
            PipelinePtr new_pipe;
1435
54.9k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
54.9k
            if (enable_spill) {
1441
95
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
95
                                                                     next_operator_id(), descs);
1443
54.8k
            } else {
1444
54.8k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
54.8k
            }
1446
54.9k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
54.9k
            } else {
1451
54.9k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
54.9k
            }
1453
1454
54.9k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
54.9k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
52.3k
                _dag.insert({downstream_pipeline_id, {}});
1457
52.3k
            }
1458
54.9k
            cur_pipe = add_pipeline(cur_pipe);
1459
54.9k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
54.9k
            if (enable_spill) {
1462
95
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
95
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
54.8k
            } else {
1465
54.8k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
54.8k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
54.8k
            }
1468
54.9k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
54.9k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
54.9k
        }
1471
145k
        break;
1472
145k
    }
1473
145k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
64
        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
64
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
64
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
64
        const auto downstream_pipeline_id = cur_pipe->id();
1486
64
        if (!_dag.contains(downstream_pipeline_id)) {
1487
64
            _dag.insert({downstream_pipeline_id, {}});
1488
64
        }
1489
64
        cur_pipe = add_pipeline(cur_pipe);
1490
64
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
64
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
64
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
64
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
64
        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
64
        {
1503
64
            auto shared_state = BucketedAggSharedState::create_shared();
1504
64
            shared_state->id = op->operator_id();
1505
64
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
400
            for (int i = 0; i < _num_instances; i++) {
1508
336
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
336
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
336
                sink_dep->set_shared_state(shared_state.get());
1511
336
                shared_state->sink_deps.push_back(sink_dep);
1512
336
            }
1513
64
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
64
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
64
            _op_id_to_shared_state.insert(
1516
64
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
64
        }
1518
64
        break;
1519
64
    }
1520
9.60k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.60k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.60k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.60k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.60k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
9.60k
        } else {
1566
9.60k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.60k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.60k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.60k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.93k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.93k
            }
1573
9.60k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.60k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.60k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.60k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.60k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.60k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.60k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.60k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.60k
        }
1584
9.60k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.86k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.86k
                    HashJoinSharedState::create_shared(_num_instances);
1587
18.7k
            for (int i = 0; i < _num_instances; i++) {
1588
15.9k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
15.9k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
15.9k
                sink_dep->set_shared_state(shared_state.get());
1591
15.9k
                shared_state->sink_deps.push_back(sink_dep);
1592
15.9k
            }
1593
2.86k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.86k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.86k
            _op_id_to_shared_state.insert(
1596
2.86k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.86k
        }
1598
9.60k
        break;
1599
9.60k
    }
1600
6.12k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
6.12k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
6.12k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
6.12k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
6.12k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
5.89k
            _dag.insert({downstream_pipeline_id, {}});
1607
5.89k
        }
1608
6.12k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
6.12k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
6.12k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
6.12k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
6.12k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
6.12k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
6.12k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
6.12k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
6.12k
        break;
1618
6.12k
    }
1619
54.2k
    case TPlanNodeType::UNION_NODE: {
1620
54.2k
        int child_count = tnode.num_children;
1621
54.2k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
54.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
54.2k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
54.2k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
53.9k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.9k
        }
1628
55.6k
        for (int i = 0; i < child_count; i++) {
1629
1.39k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.39k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.39k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.39k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.39k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.39k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.39k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.39k
        }
1638
54.2k
        break;
1639
54.2k
    }
1640
54.2k
    case TPlanNodeType::SORT_NODE: {
1641
45.1k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
45.1k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
45.1k
        const bool use_local_merge =
1644
45.1k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
45.1k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
45.1k
        } else if (use_local_merge) {
1648
42.8k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
42.8k
                                                                 descs);
1650
42.8k
        } else {
1651
2.33k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.33k
        }
1653
45.1k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
45.1k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
45.1k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
45.1k
            _dag.insert({downstream_pipeline_id, {}});
1658
45.1k
        }
1659
45.1k
        cur_pipe = add_pipeline(cur_pipe);
1660
45.1k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
45.1k
        if (should_spill) {
1663
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
45.1k
        } else {
1666
45.1k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
45.1k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
45.1k
        }
1669
45.1k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
45.1k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
45.1k
        break;
1672
45.1k
    }
1673
45.1k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.63k
        }
1698
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.64k
        break;
1706
1.64k
    }
1707
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.59k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.59k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.59k
        break;
1711
1.59k
    }
1712
1.59k
    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
300
    case TPlanNodeType::REPEAT_NODE: {
1723
300
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
300
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
300
        break;
1726
300
    }
1727
914
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
914
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
914
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
914
        break;
1731
914
    }
1732
914
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
218
        break;
1736
218
    }
1737
1.69k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.69k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.69k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.69k
        break;
1741
1.69k
    }
1742
1.69k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
466
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
466
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
466
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
466
        break;
1747
466
    }
1748
2.15k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.15k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.15k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.15k
        break;
1752
2.15k
    }
1753
6.81k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.81k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.81k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.81k
        break;
1757
6.81k
    }
1758
6.81k
    case TPlanNodeType::SELECT_NODE: {
1759
2.58k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.58k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.58k
        break;
1762
2.58k
    }
1763
2.58k
    case TPlanNodeType::REC_CTE_NODE: {
1764
134
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
134
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
134
        const auto downstream_pipeline_id = cur_pipe->id();
1768
134
        if (!_dag.contains(downstream_pipeline_id)) {
1769
133
            _dag.insert({downstream_pipeline_id, {}});
1770
133
        }
1771
1772
134
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
134
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
134
        DataSinkOperatorPtr anchor_sink;
1776
134
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
134
                                                                  op->operator_id(), tnode, descs);
1778
134
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
134
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
134
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
134
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
134
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
134
        DataSinkOperatorPtr rec_sink;
1786
134
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
134
                                                         tnode, descs);
1788
134
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
134
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
134
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
134
        break;
1793
134
    }
1794
1.85k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.85k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.85k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.85k
        break;
1798
1.85k
    }
1799
1.85k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
680k
    }
1803
679k
    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
679k
    return Status::OK();
1809
680k
}
1810
// NOLINTEND(readability-function-cognitive-complexity)
1811
// NOLINTEND(readability-function-size)
1812
1813
template <bool is_intersect>
1814
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1815
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1816
267
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
267
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
267
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
267
    const auto downstream_pipeline_id = cur_pipe->id();
1821
267
    if (!_dag.contains(downstream_pipeline_id)) {
1822
242
        _dag.insert({downstream_pipeline_id, {}});
1823
242
    }
1824
1825
895
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
628
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
628
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
628
        if (child_id == 0) {
1830
267
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
267
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
361
        } else {
1833
361
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
361
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
361
        }
1836
628
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
628
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
628
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
628
    }
1841
1842
267
    return Status::OK();
1843
267
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
134
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
134
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
134
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
134
    const auto downstream_pipeline_id = cur_pipe->id();
1821
134
    if (!_dag.contains(downstream_pipeline_id)) {
1822
118
        _dag.insert({downstream_pipeline_id, {}});
1823
118
    }
1824
1825
481
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
347
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
347
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
347
        if (child_id == 0) {
1830
134
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
134
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
213
        } else {
1833
213
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
213
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
213
        }
1836
347
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
347
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
347
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
347
    }
1841
1842
134
    return Status::OK();
1843
134
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
133
    const auto downstream_pipeline_id = cur_pipe->id();
1821
133
    if (!_dag.contains(downstream_pipeline_id)) {
1822
124
        _dag.insert({downstream_pipeline_id, {}});
1823
124
    }
1824
1825
414
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
281
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
281
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
281
        if (child_id == 0) {
1830
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
148
        } else {
1833
148
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
148
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
148
        }
1836
281
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
281
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
281
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
281
    }
1841
1842
133
    return Status::OK();
1843
133
}
1844
1845
446k
Status PipelineFragmentContext::submit() {
1846
446k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
446k
    _submitted = true;
1850
1851
446k
    int submit_tasks = 0;
1852
446k
    Status st;
1853
446k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.25M
    for (auto& task : _tasks) {
1855
2.11M
        for (auto& t : task) {
1856
2.11M
            st = scheduler->submit(t.first);
1857
2.11M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
2.11M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
2.11M
            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
2.11M
            submit_tasks++;
1866
2.11M
        }
1867
1.25M
    }
1868
446k
    if (!st.ok()) {
1869
0
        bool need_remove = false;
1870
0
        {
1871
0
            std::lock_guard<std::mutex> l(_task_mutex);
1872
0
            if (_closed_tasks >= _total_tasks) {
1873
0
                need_remove = _close_fragment_instance();
1874
0
            }
1875
0
        }
1876
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1877
0
        if (need_remove) {
1878
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1879
0
        }
1880
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1881
0
                                     BackendOptions::get_localhost());
1882
446k
    } else {
1883
446k
        return st;
1884
446k
    }
1885
446k
}
1886
1887
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1888
0
    if (_runtime_state->enable_profile()) {
1889
0
        std::stringstream ss;
1890
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1891
0
            runtime_profile_ptr->pretty_print(&ss);
1892
0
        }
1893
1894
0
        if (_runtime_state->load_channel_profile()) {
1895
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1896
0
        }
1897
1898
0
        auto profile_str =
1899
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1900
0
                            this->_fragment_id, extra_info, ss.str());
1901
0
        LOG_LONG_STRING(INFO, profile_str);
1902
0
    }
1903
0
}
1904
// If all pipeline tasks binded to the fragment instance are finished, then we could
1905
// close the fragment instance.
1906
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1907
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1908
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1909
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1910
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1911
// (via debug_string()).
1912
447k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
447k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
447k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
447k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
447k
    if (!_need_notify_close) {
1919
444k
        auto st = send_report(true);
1920
444k
        if (!st) {
1921
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1922
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1923
0
        }
1924
444k
    }
1925
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1926
    // Since stream load does not have someting like coordinator on FE, so
1927
    // backend can not report profile to FE, ant its profile can not be shown
1928
    // in the same way with other query. So we print the profile content to info log.
1929
1930
447k
    if (_runtime_state->enable_profile() &&
1931
447k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.81k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.81k
         _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
447k
    if (_query_ctx->enable_profile()) {
1953
2.81k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.81k
                                         collect_realtime_load_channel_profile());
1955
2.81k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
447k
    return !_need_notify_close;
1960
447k
}
1961
1962
2.10M
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
2.10M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
2.10M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
706k
        if (_dag.contains(pipeline_id)) {
1967
389k
            for (auto dep : _dag[pipeline_id]) {
1968
389k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
389k
            }
1970
300k
        }
1971
706k
    }
1972
2.10M
    bool need_remove = false;
1973
2.10M
    {
1974
2.10M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
2.10M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
2.10M
        _query_ctx->inc_finished_task_num();
1978
2.10M
        if (_closed_tasks >= _total_tasks) {
1979
447k
            need_remove = _close_fragment_instance();
1980
447k
        }
1981
2.10M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
2.10M
    if (need_remove) {
1984
444k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
444k
    }
1986
2.10M
}
1987
1988
56.3k
std::string PipelineFragmentContext::get_load_error_url() {
1989
56.3k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1990
0
        return to_load_error_http_path(str);
1991
0
    }
1992
157k
    for (auto& tasks : _tasks) {
1993
251k
        for (auto& task : tasks) {
1994
251k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
179
                return to_load_error_http_path(str);
1996
179
            }
1997
251k
        }
1998
157k
    }
1999
56.1k
    return "";
2000
56.3k
}
2001
2002
56.3k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
56.3k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
157k
    for (auto& tasks : _tasks) {
2007
251k
        for (auto& task : tasks) {
2008
251k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
179
                return str;
2010
179
            }
2011
251k
        }
2012
157k
    }
2013
56.1k
    return "";
2014
56.3k
}
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
49.4k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
49.4k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
49.4k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
49.4k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
49.4k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
49.4k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
49.4k
    });
2031
2032
49.4k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
49.4k
    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
49.4k
    int callback_retries = 10;
2038
49.4k
    const int sleep_ms = 1000;
2039
49.4k
    Status exec_status = req.status;
2040
49.4k
    Status coord_status;
2041
49.4k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
49.4k
    do {
2043
49.4k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
49.4k
                                                            req.coord_addr, &coord_status);
2045
49.4k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
49.4k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
49.4k
    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
49.4k
    TReportExecStatusParams params;
2059
49.4k
    params.protocol_version = FrontendServiceVersion::V1;
2060
49.4k
    params.__set_query_id(req.query_id);
2061
49.4k
    params.__set_backend_num(req.backend_num);
2062
49.4k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
49.4k
    params.__set_fragment_id(req.fragment_id);
2064
49.4k
    params.__set_status(exec_status.to_thrift());
2065
49.4k
    params.__set_done(req.done);
2066
49.4k
    params.__set_query_type(req.runtime_state->query_type());
2067
49.4k
    params.__isset.profile = false;
2068
2069
49.4k
    DCHECK(req.runtime_state != nullptr);
2070
2071
49.4k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
44.4k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
44.4k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
44.4k
    } else {
2075
4.96k
        DCHECK(!req.runtime_states.empty());
2076
4.96k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
4.96k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.96k
    }
2086
2087
49.4k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
49.4k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
49.4k
    static std::string s_unselected_rows = "unselected.rows";
2090
49.4k
    int64_t num_rows_load_success = 0;
2091
49.4k
    int64_t num_rows_load_filtered = 0;
2092
49.4k
    int64_t num_rows_load_unselected = 0;
2093
49.4k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
49.4k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
49.4k
        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
49.4k
    } else if (!req.runtime_states.empty()) {
2109
159k
        for (auto* rs : req.runtime_states) {
2110
159k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
159k
                rs->num_finished_range() > 0) {
2112
37.6k
                params.__isset.load_counters = true;
2113
37.6k
                num_rows_load_success += rs->num_rows_load_success();
2114
37.6k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
37.6k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
37.6k
                params.__isset.fragment_instance_reports = true;
2117
37.6k
                TFragmentInstanceReport t;
2118
37.6k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
37.6k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
37.6k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
37.6k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
37.6k
                params.fragment_instance_reports.push_back(t);
2123
37.6k
            }
2124
159k
        }
2125
49.4k
    }
2126
49.4k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
49.4k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
49.4k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
49.4k
    if (!req.load_error_url.empty()) {
2131
161
        params.__set_tracking_url(req.load_error_url);
2132
161
    }
2133
49.4k
    if (!req.first_error_msg.empty()) {
2134
161
        params.__set_first_error_msg(req.first_error_msg);
2135
161
    }
2136
159k
    for (auto* rs : req.runtime_states) {
2137
159k
        if (rs->wal_id() > 0) {
2138
109
            params.__set_txn_id(rs->wal_id());
2139
109
            params.__set_label(rs->import_label());
2140
109
        }
2141
159k
    }
2142
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2146
159k
        for (auto* rs : req.runtime_states) {
2147
159k
            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
159k
        }
2154
49.3k
    }
2155
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2159
159k
        for (auto* rs : req.runtime_states) {
2160
159k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
28.0k
                params.__isset.commitInfos = true;
2162
28.0k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
28.0k
            }
2164
159k
        }
2165
49.4k
    }
2166
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2170
159k
        for (auto* rs : req.runtime_states) {
2171
159k
            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
159k
        }
2177
49.4k
    }
2178
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2183
159k
        for (auto* rs : req.runtime_states) {
2184
159k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.14k
                params.__isset.hive_partition_updates = true;
2186
2.14k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.14k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.14k
            }
2189
159k
        }
2190
49.4k
    }
2191
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2196
159k
        for (auto* rs : req.runtime_states) {
2197
159k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.06k
                params.__isset.iceberg_commit_datas = true;
2199
2.06k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.06k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.06k
            }
2202
159k
        }
2203
49.3k
    }
2204
2205
49.4k
    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
49.4k
    } else if (!req.runtime_states.empty()) {
2209
159k
        for (auto* rs : req.runtime_states) {
2210
159k
            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
159k
        }
2216
49.4k
    }
2217
2218
49.4k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
49.4k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
49.4k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
49.3k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
49.3k
    }
2224
2225
49.4k
    TReportExecStatusResult res;
2226
49.4k
    Status rpc_status;
2227
2228
49.4k
    VLOG_DEBUG << "reportExecStatus params is "
2229
26
               << apache::thrift::ThriftDebugString(params).c_str();
2230
49.4k
    if (!exec_status.ok()) {
2231
1.67k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.67k
                     << " to coordinator: " << req.coord_addr
2233
1.67k
                     << ", query id: " << print_id(req.query_id);
2234
1.67k
    }
2235
49.4k
    try {
2236
49.4k
        try {
2237
49.4k
            (*coord)->reportExecStatus(res, params);
2238
49.4k
        } 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
49.4k
        rpc_status = Status::create<false>(res.status);
2254
49.4k
    } 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
49.4k
    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
49.4k
}
2265
2266
449k
Status PipelineFragmentContext::send_report(bool done) {
2267
449k
    Status exec_status = _query_ctx->exec_status();
2268
    // If plan is done successfully, but _is_report_success is false,
2269
    // no need to send report.
2270
    // Load will set _is_report_success to true because load wants to know
2271
    // the process.
2272
449k
    if (!_is_report_success && done && exec_status.ok()) {
2273
400k
        return Status::OK();
2274
400k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
49.7k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
298
        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
298
            return Status::OK();
2286
298
        }
2287
0
        return Status::NeedSendAgain("");
2288
298
    }
2289
2290
49.4k
    std::vector<RuntimeState*> runtime_states;
2291
2292
115k
    for (auto& tasks : _tasks) {
2293
159k
        for (auto& task : tasks) {
2294
159k
            runtime_states.push_back(task.second.get());
2295
159k
        }
2296
115k
    }
2297
2298
49.4k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
49.4k
                                        ? get_load_error_url()
2300
49.4k
                                        : _query_ctx->get_load_error_url();
2301
49.4k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
49.4k
                                          ? get_first_error_msg()
2303
49.4k
                                          : _query_ctx->get_first_error_msg();
2304
2305
49.4k
    ReportStatusRequest req {.status = exec_status,
2306
49.4k
                             .runtime_states = runtime_states,
2307
49.4k
                             .done = done || !exec_status.ok(),
2308
49.4k
                             .coord_addr = _query_ctx->coord_addr,
2309
49.4k
                             .query_id = _query_id,
2310
49.4k
                             .fragment_id = _fragment_id,
2311
49.4k
                             .fragment_instance_id = TUniqueId(),
2312
49.4k
                             .backend_num = -1,
2313
49.4k
                             .runtime_state = _runtime_state.get(),
2314
49.4k
                             .load_error_url = load_eror_url,
2315
49.4k
                             .first_error_msg = first_error_msg,
2316
49.4k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
49.4k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
49.4k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
49.4k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
49.4k
        _coordinator_callback(req);
2321
49.4k
        if (!req.done) {
2322
4.92k
            ctx->refresh_next_report_time();
2323
4.92k
        }
2324
49.4k
    });
2325
49.7k
}
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
202
std::string PipelineFragmentContext::debug_string() {
2365
202
    std::lock_guard<std::mutex> l(_task_mutex);
2366
202
    fmt::memory_buffer debug_string_buffer;
2367
202
    fmt::format_to(debug_string_buffer,
2368
202
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
202
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
202
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
1.10k
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
905
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
2.84k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
1.94k
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
1.94k
                           _tasks[j][i].first->debug_string());
2376
1.94k
        }
2377
905
    }
2378
2379
202
    return fmt::to_string(debug_string_buffer);
2380
202
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.81k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.81k
    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
2.81k
    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
2.81k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.81k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.81k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
5.28k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
5.28k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
5.28k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
5.28k
        res.push_back(profile_ptr);
2407
5.28k
    }
2408
2409
2.81k
    return res;
2410
2.81k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.81k
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
2.81k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
10.1k
    for (const auto& tasks : _tasks) {
2426
20.6k
        for (const auto& task : tasks) {
2427
20.6k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
20.6k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
20.6k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
20.6k
                                                           _runtime_state->profile_level());
2435
20.6k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
20.6k
        }
2437
10.1k
    }
2438
2439
2.81k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.81k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.81k
                                                      _runtime_state->profile_level());
2442
2.81k
    return load_channel_profile;
2443
2.81k
}
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
3.18k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.18k
    std::set<int> result;
2454
6.74k
    for (const auto& _task : _tasks) {
2455
14.2k
        for (const auto& task : _task) {
2456
14.2k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
14.2k
            result.merge(set);
2458
14.2k
        }
2459
6.74k
    }
2460
3.18k
    if (_runtime_state) {
2461
3.18k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.18k
        result.merge(set);
2463
3.18k
    }
2464
3.18k
    return result;
2465
3.18k
}
2466
2467
449k
void PipelineFragmentContext::_release_resource() {
2468
449k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
449k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
449k
    auto st = _query_ctx->exec_status();
2472
1.25M
    for (auto& _task : _tasks) {
2473
1.25M
        if (!_task.empty()) {
2474
1.25M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.25M
        }
2476
1.25M
    }
2477
449k
    _tasks.clear();
2478
449k
    _dag.clear();
2479
449k
    _pip_id_to_pipeline.clear();
2480
449k
    _pipelines.clear();
2481
449k
    _sink.reset();
2482
449k
    _root_op.reset();
2483
449k
    _runtime_filter_mgr_map.clear();
2484
449k
    _op_id_to_shared_state.clear();
2485
449k
}
2486
2487
} // namespace doris