Coverage Report

Created: 2026-05-13 16:33

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
114
#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
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#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
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#include "util/client_cache.h"
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#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
325k
        : _query_id(std::move(query_id)),
144
325k
          _fragment_id(request.fragment_id),
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325k
          _exec_env(exec_env),
146
325k
          _query_ctx(std::move(query_ctx)),
147
325k
          _call_back(call_back),
148
325k
          _is_report_on_cancel(true),
149
325k
          _params(request),
150
325k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
325k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
325k
                                                               : false) {
153
325k
    _fragment_watcher.start();
154
325k
}
155
156
325k
PipelineFragmentContext::~PipelineFragmentContext() {
157
325k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
325k
            .tag("query_id", print_id(_query_id))
159
325k
            .tag("fragment_id", _fragment_id);
160
325k
    _release_resource();
161
325k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
325k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
325k
        _runtime_state.reset();
165
325k
        _query_ctx.reset();
166
325k
    }
167
325k
}
168
169
159
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
159
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
159
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
159
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
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// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
179
// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
9.62k
bool PipelineFragmentContext::notify_close() {
181
9.62k
    bool all_closed = false;
182
9.62k
    bool need_remove = false;
183
9.62k
    {
184
9.62k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.62k
        if (_closed_tasks >= _total_tasks) {
186
3.46k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
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3.40k
                need_remove = true;
193
3.40k
            }
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3.46k
            all_closed = true;
195
3.46k
        }
196
        // make fragment release by self after cancel
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9.62k
        _need_notify_close = false;
198
9.62k
    }
199
9.62k
    if (need_remove) {
200
3.40k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.40k
    }
202
9.62k
    return all_closed;
203
9.62k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
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// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
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// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
209
6.14k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.14k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.14k
            .tag("query_id", print_id(_query_id))
212
6.14k
            .tag("fragment_id", _fragment_id)
213
6.14k
            .tag("reason", reason.to_string());
214
6.14k
    if (notify_close()) {
215
70
        return;
216
70
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.07k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
6.07k
    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
6.07k
    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
6.07k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
6.07k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
6.07k
    _query_ctx->cancel(reason, _fragment_id);
243
6.07k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
246
        _is_report_on_cancel = false;
245
5.82k
    } else {
246
38.0k
        for (auto& id : _fragment_instance_ids) {
247
38.0k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
38.0k
        }
249
5.82k
    }
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
6.07k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.07k
    if (stream_load_ctx != nullptr) {
254
31
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
31
        stream_load_ctx->error_url = get_load_error_url();
259
31
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
31
    }
261
262
38.7k
    for (auto& tasks : _tasks) {
263
81.7k
        for (auto& task : tasks) {
264
81.7k
            task.first->unblock_all_dependencies();
265
81.7k
        }
266
38.7k
    }
267
6.07k
}
268
269
507k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
507k
    PipelineId id = _next_pipeline_id++;
271
507k
    auto pipeline = std::make_shared<Pipeline>(
272
507k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
507k
            parent ? parent->num_tasks() : _num_instances);
274
507k
    if (idx >= 0) {
275
91.5k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
416k
    } else {
277
416k
        _pipelines.emplace_back(pipeline);
278
416k
    }
279
507k
    if (parent) {
280
180k
        parent->set_children(pipeline);
281
180k
    }
282
507k
    return pipeline;
283
507k
}
284
285
325k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
325k
    {
287
325k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
325k
        auto root_pipeline = add_pipeline();
290
325k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
325k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
325k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
325k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
325k
                                          _params.fragment.output_exprs, _params,
299
325k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
325k
                                          *_desc_tbl, root_pipeline->id()));
301
325k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
325k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
415k
        for (PipelinePtr& pipeline : _pipelines) {
305
415k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
415k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
415k
        }
308
325k
    }
309
    // 4. Build local exchanger
310
325k
    if (_runtime_state->enable_local_shuffle()) {
311
323k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
323k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
323k
                                             _params.bucket_seq_to_instance_idx,
314
323k
                                             _params.shuffle_idx_to_instance_idx));
315
323k
    }
316
317
    // 5. Initialize global states in pipelines.
318
508k
    for (PipelinePtr& pipeline : _pipelines) {
319
508k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
508k
        pipeline->children().clear();
321
508k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
508k
    }
323
324
323k
    {
325
323k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
323k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
323k
    }
329
330
323k
    return Status::OK();
331
323k
}
332
333
325k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
325k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
325k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
325k
        _timeout = _params.query_options.execution_timeout;
339
325k
    }
340
341
325k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
325k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
325k
    SCOPED_TIMER(_prepare_timer);
344
325k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
325k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
325k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
325k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
325k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
325k
    {
350
325k
        SCOPED_TIMER(_init_context_timer);
351
325k
        cast_set(_num_instances, _params.local_params.size());
352
325k
        _total_instances =
353
325k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
325k
        auto* fragment_context = this;
356
357
325k
        if (_params.query_options.__isset.is_report_success) {
358
323k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
323k
        }
360
361
        // 1. Set up the global runtime state.
362
325k
        _runtime_state = RuntimeState::create_unique(
363
325k
                _params.query_id, _params.fragment_id, _params.query_options,
364
325k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
325k
        _runtime_state->set_task_execution_context(shared_from_this());
366
325k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
325k
        if (_params.__isset.backend_id) {
368
323k
            _runtime_state->set_backend_id(_params.backend_id);
369
323k
        }
370
325k
        if (_params.__isset.import_label) {
371
237
            _runtime_state->set_import_label(_params.import_label);
372
237
        }
373
325k
        if (_params.__isset.db_name) {
374
189
            _runtime_state->set_db_name(_params.db_name);
375
189
        }
376
325k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
325k
        if (_params.is_simplified_param) {
381
114k
            _desc_tbl = _query_ctx->desc_tbl;
382
211k
        } else {
383
211k
            DCHECK(_params.__isset.desc_tbl);
384
211k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
211k
                                                  &_desc_tbl));
386
211k
        }
387
325k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
325k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
325k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
325k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
325k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
325k
        const auto target_size = _params.local_params.size();
395
325k
        _fragment_instance_ids.resize(target_size);
396
1.20M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
876k
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
876k
            _fragment_instance_ids[i] = fragment_instance_id;
399
876k
        }
400
325k
    }
401
402
325k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
324k
    _init_next_report_time();
405
406
324k
    _prepared = true;
407
324k
    return Status::OK();
408
325k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
875k
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
875k
    const auto& local_params = _params.local_params[instance_idx];
414
875k
    auto fragment_instance_id = local_params.fragment_instance_id;
415
875k
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
875k
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
875k
    auto get_shared_state = [&](PipelinePtr pipeline)
418
875k
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.50M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.50M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.50M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.50M
                shared_state_map;
423
1.97M
        for (auto& op : pipeline->operators()) {
424
1.97M
            auto source_id = op->operator_id();
425
1.97M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
1.97M
                iter != _op_id_to_shared_state.end()) {
427
566k
                shared_state_map.insert({source_id, iter->second});
428
566k
            }
429
1.97M
        }
430
1.50M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.50M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.50M
                iter != _op_id_to_shared_state.end()) {
433
251k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
251k
            }
435
1.50M
        }
436
1.50M
        return shared_state_map;
437
1.50M
    };
438
439
2.68M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
1.81M
        auto& pipeline = _pipelines[pip_idx];
441
1.81M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.49M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.49M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.49M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.49M
            {
446
                // Initialize runtime state for this task
447
1.49M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.49M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.49M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.49M
                if (_params.__isset.backend_id) {
453
1.49M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.49M
                }
455
1.49M
                if (_params.__isset.import_label) {
456
238
                    task_runtime_state->set_import_label(_params.import_label);
457
238
                }
458
1.49M
                if (_params.__isset.db_name) {
459
190
                    task_runtime_state->set_db_name(_params.db_name);
460
190
                }
461
1.49M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.49M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.49M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.49M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.49M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.49M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.49M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.49M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.49M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.49M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.49M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.49M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.49M
            }
482
1.49M
            auto cur_task_id = _total_tasks++;
483
1.49M
            task_runtime_state->set_task_id(cur_task_id);
484
1.49M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.49M
            auto task = std::make_shared<PipelineTask>(
486
1.49M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.49M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.49M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.49M
                    instance_idx);
490
1.49M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.49M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.49M
            _tasks[instance_idx].emplace_back(
493
1.49M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.49M
                            std::move(task), std::move(task_runtime_state)});
495
1.49M
        }
496
1.81M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
1.81M
    for (auto& _pipeline : _pipelines) {
516
1.81M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.49M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.49M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.49M
            if (_dag.contains(_pipeline->id())) {
522
945k
                auto& deps = _dag[_pipeline->id()];
523
1.48M
                for (auto& dep : deps) {
524
1.48M
                    if (pipeline_id_to_task.contains(dep)) {
525
862k
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
862k
                        if (ss) {
527
360k
                            task->inject_shared_state(ss);
528
501k
                        } else {
529
501k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
501k
                                    task->get_source_shared_state());
531
501k
                        }
532
862k
                    }
533
1.48M
                }
534
945k
            }
535
1.49M
        }
536
1.81M
    }
537
2.68M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
1.81M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.49M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.49M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.49M
            std::vector<TScanRangeParams> scan_ranges;
542
1.49M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.49M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
262k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
262k
            }
546
1.49M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.49M
                                                             _params.fragment.output_sink));
548
1.49M
        }
549
1.81M
    }
550
877k
    {
551
877k
        std::lock_guard<std::mutex> l(_state_map_lock);
552
877k
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
877k
    }
554
877k
    return Status::OK();
555
875k
}
556
557
324k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
324k
    _total_tasks = 0;
559
324k
    _closed_tasks = 0;
560
324k
    const auto target_size = _params.local_params.size();
561
324k
    _tasks.resize(target_size);
562
324k
    _runtime_filter_mgr_map.resize(target_size);
563
831k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
506k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
506k
    }
566
324k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
324k
    if (target_size > 1 &&
569
324k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
116k
         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
19.5k
        std::vector<Status> prepare_status(target_size);
573
19.5k
        int submitted_tasks = 0;
574
19.5k
        Status submit_status;
575
19.5k
        CountDownLatch latch((int)target_size);
576
182k
        for (int i = 0; i < target_size; i++) {
577
162k
            submit_status = thread_pool->submit_func([&, i]() {
578
162k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
162k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
162k
                latch.count_down();
581
162k
            });
582
162k
            if (LIKELY(submit_status.ok())) {
583
162k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
162k
        }
588
19.5k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
19.5k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
182k
        for (int i = 0; i < submitted_tasks; i++) {
593
162k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
162k
        }
597
305k
    } else {
598
1.01M
        for (int i = 0; i < target_size; i++) {
599
714k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
714k
        }
601
305k
    }
602
324k
    _pipeline_parent_map.clear();
603
324k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
324k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
324k
    return Status::OK();
608
324k
}
609
610
323k
void PipelineFragmentContext::_init_next_report_time() {
611
323k
    auto interval_s = config::pipeline_status_report_interval;
612
323k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
31.4k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
31.4k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
31.4k
        _previous_report_time =
617
31.4k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
31.4k
        _disable_period_report = false;
619
31.4k
    }
620
323k
}
621
622
3.52k
void PipelineFragmentContext::refresh_next_report_time() {
623
3.52k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
3.52k
    DCHECK(disable == true);
625
3.52k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
3.52k
    _disable_period_report.compare_exchange_strong(disable, false);
627
3.52k
}
628
629
5.34M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
5.34M
    if (!_is_report_success) {
631
4.94M
        return;
632
4.94M
    }
633
403k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
403k
    if (disable) {
635
5.90k
        return;
636
5.90k
    }
637
397k
    int32_t interval_s = config::pipeline_status_report_interval;
638
397k
    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
397k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
397k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
397k
    if (MonotonicNanos() > next_report_time) {
646
3.53k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
3.53k
                                                            std::memory_order_acq_rel)) {
648
9
            return;
649
9
        }
650
3.52k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
3.52k
        auto st = send_report(false);
667
3.52k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
3.52k
    }
673
397k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
323k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
323k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
323k
    int node_idx = 0;
682
683
323k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
323k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
323k
    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
323k
    return Status::OK();
691
323k
}
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
518k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
518k
    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
518k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
518k
    int num_children = tnodes[*node_idx].num_children;
706
518k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
518k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
518k
    OperatorPtr op = nullptr;
710
518k
    OperatorPtr cache_op = nullptr;
711
518k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
518k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
518k
                                     followed_by_shuffled_operator,
714
518k
                                     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
518k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
518k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
194k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
323k
    } else {
723
323k
        *root = op;
724
323k
    }
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
518k
    auto required_data_distribution =
737
518k
            cur_pipe->operators().empty()
738
518k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
518k
                    : op->required_data_distribution(_runtime_state.get());
740
518k
    current_followed_by_shuffled_operator =
741
518k
            ((followed_by_shuffled_operator ||
742
518k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
461k
                                             : op->is_shuffled_operator())) &&
744
518k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
518k
            (followed_by_shuffled_operator &&
746
411k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
518k
    current_require_bucket_distribution =
749
518k
            ((require_bucket_distribution ||
750
518k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
465k
                                             : op->is_colocated_operator())) &&
752
518k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
518k
            (require_bucket_distribution &&
754
417k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
518k
    if (num_children == 0) {
757
336k
        _use_serial_source = op->is_serial_operator();
758
336k
    }
759
    // rely on that tnodes is preorder of the plan
760
713k
    for (int i = 0; i < num_children; i++) {
761
195k
        ++*node_idx;
762
195k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
195k
                                            current_followed_by_shuffled_operator,
764
195k
                                            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
195k
        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
195k
    }
775
776
518k
    return Status::OK();
777
518k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
91.5k
        PipelinePtr pipe_with_sink) {
782
91.5k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
91.5k
    pipe_with_source->set_num_tasks(_num_instances);
784
91.5k
    pipe_with_source->set_data_distribution(data_distribution);
785
91.5k
}
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
91.5k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
91.5k
    auto& operators = cur_pipe->operators();
793
91.5k
    const auto downstream_pipeline_id = cur_pipe->id();
794
91.5k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
91.5k
    DataSinkOperatorPtr sink;
797
91.5k
    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
91.5k
    const bool followed_by_shuffled_operator =
804
91.5k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
91.5k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
91.5k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
91.5k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
91.5k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
91.5k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
91.5k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
91.5k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
91.5k
    if (bucket_seq_to_instance_idx.empty() &&
813
91.5k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
6
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
6
    }
816
91.5k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
91.5k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
91.5k
                                          num_buckets, use_global_hash_shuffle,
819
91.5k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
91.5k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
91.5k
            LocalExchangeSharedState::create_shared(_num_instances);
824
91.5k
    switch (data_distribution.distribution_type) {
825
12.2k
    case ExchangeType::HASH_SHUFFLE:
826
12.2k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
12.2k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
12.2k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
12.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
12.2k
                        ? cast_set<int>(
831
12.2k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
12.2k
                        : 0);
833
12.2k
        break;
834
505
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
505
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
505
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
505
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
505
                        ? cast_set<int>(
839
505
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
505
                        : 0);
841
505
        break;
842
76.0k
    case ExchangeType::PASSTHROUGH:
843
76.0k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
76.0k
                cur_pipe->num_tasks(), _num_instances,
845
76.0k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
76.0k
                        ? cast_set<int>(
847
75.9k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
76.0k
                        : 0);
849
76.0k
        break;
850
252
    case ExchangeType::BROADCAST:
851
252
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
252
                cur_pipe->num_tasks(), _num_instances,
853
252
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
252
                        ? cast_set<int>(
855
252
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
252
                        : 0);
857
252
        break;
858
1.95k
    case ExchangeType::PASS_TO_ONE:
859
1.95k
        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
747
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
747
                    cur_pipe->num_tasks(), _num_instances,
863
747
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
747
                            ? cast_set<int>(_runtime_state->query_options()
865
747
                                                    .local_exchange_free_blocks_limit)
866
747
                            : 0);
867
1.20k
        } else {
868
1.20k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.20k
                    cur_pipe->num_tasks(), _num_instances,
870
1.20k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.20k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.20k
                                                    .local_exchange_free_blocks_limit)
873
1.20k
                            : 0);
874
1.20k
        }
875
1.95k
        break;
876
599
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
599
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
599
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
599
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
599
                        ? cast_set<int>(
881
599
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
599
                        : 0);
883
599
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
91.5k
    }
888
91.6k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
91.6k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
91.6k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
91.6k
    _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
91.6k
    std::copy(operators.begin(), operators.begin() + idx,
898
91.6k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
91.6k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
91.6k
    OperatorPtr source_op;
905
91.6k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
91.6k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
91.6k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
91.6k
    if (!operators.empty()) {
909
40.2k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
40.2k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
40.2k
    }
912
91.6k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
91.6k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
91.6k
    std::vector<PipelineId> edges_with_source;
917
105k
    for (auto child : cur_pipe->children()) {
918
105k
        bool found = false;
919
116k
        for (auto op : new_pip->operators()) {
920
116k
            if (child->sink()->node_id() == op->node_id()) {
921
9.79k
                new_pip->set_children(child);
922
9.79k
                found = true;
923
9.79k
            };
924
116k
        }
925
105k
        if (!found) {
926
95.6k
            new_children.push_back(child);
927
95.6k
            edges_with_source.push_back(child->id());
928
95.6k
        }
929
105k
    }
930
91.6k
    new_children.push_back(new_pip);
931
91.6k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
91.6k
    if (!new_pip->children().empty()) {
935
5.93k
        std::vector<PipelineId> edges_with_sink;
936
9.79k
        for (auto child : new_pip->children()) {
937
9.79k
            edges_with_sink.push_back(child->id());
938
9.79k
        }
939
5.93k
        _dag.insert({new_pip->id(), edges_with_sink});
940
5.93k
    }
941
91.6k
    cur_pipe->set_children(new_children);
942
91.6k
    _dag[downstream_pipeline_id] = edges_with_source;
943
91.6k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
91.6k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
91.6k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
91.6k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
91.6k
    return Status::OK();
950
91.6k
}
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
156k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
156k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
33.7k
        return Status::OK();
959
33.7k
    }
960
961
123k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
43.9k
        return Status::OK();
963
43.9k
    }
964
79.0k
    *do_local_exchange = true;
965
966
79.0k
    auto& operators = cur_pipe->operators();
967
79.0k
    auto total_op_num = operators.size();
968
79.0k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
79.0k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
79.0k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
79.0k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
79.0k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
91
            << "total_op_num: " << total_op_num
975
91
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
91
            << " 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
79.0k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
79.0k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
12.5k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
12.5k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
12.5k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
12.5k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
12.5k
                shuffle_idx_to_instance_idx));
990
12.5k
    }
991
79.0k
    return Status::OK();
992
79.0k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
322k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
736k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
413k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
413k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
89.2k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
89.2k
                if (child->sink()->node_id() ==
1003
89.2k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
78.3k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
78.3k
                }
1006
89.2k
            }
1007
85.6k
        }
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
413k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
413k
                                             bucket_seq_to_instance_idx,
1014
413k
                                             shuffle_idx_to_instance_idx));
1015
413k
    }
1016
322k
    return Status::OK();
1017
322k
}
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
413k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
413k
    int idx = 1;
1024
413k
    bool do_local_exchange = false;
1025
454k
    do {
1026
454k
        auto& ops = pip->operators();
1027
454k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
520k
        for (; idx < ops.size();) {
1030
106k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
97.6k
                RETURN_IF_ERROR(_add_local_exchange(
1032
97.6k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
97.6k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
97.6k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
97.6k
                        shuffle_idx_to_instance_idx));
1036
97.6k
            }
1037
106k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
40.3k
                idx = 2;
1043
40.3k
                break;
1044
40.3k
            }
1045
66.1k
            idx++;
1046
66.1k
        }
1047
454k
    } while (do_local_exchange);
1048
413k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
58.5k
        RETURN_IF_ERROR(_add_local_exchange(
1050
58.5k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
58.5k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
58.5k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
58.5k
    }
1054
413k
    return Status::OK();
1055
413k
}
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
324k
                                                  PipelineId cur_pipeline_id) {
1063
324k
    switch (thrift_sink.type) {
1064
113k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
113k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
113k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
113k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
113k
                params.destinations, _fragment_instance_ids);
1071
113k
        break;
1072
113k
    }
1073
181k
    case TDataSinkType::RESULT_SINK: {
1074
181k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
181k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
181k
        int child_node_id = pipeline->operators().back()->node_id();
1080
181k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
181k
                                                      row_desc, output_exprs,
1082
181k
                                                      thrift_sink.result_sink);
1083
181k
        break;
1084
181k
    }
1085
104
    case TDataSinkType::DICTIONARY_SINK: {
1086
104
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
104
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
104
                                                    thrift_sink.dictionary_sink);
1092
104
        break;
1093
104
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
28.8k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
28.8k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
28.8k
        int child_node_id = pipeline->operators().back()->node_id();
1098
28.8k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
28.8k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
28.8k
            !config::is_cloud_mode()) {
1101
58
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
58
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
28.7k
        } else {
1104
28.7k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
28.7k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
28.7k
        }
1107
28.8k
        break;
1108
0
    }
1109
166
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
166
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
166
        DCHECK(state->get_query_ctx() != nullptr);
1112
166
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
166
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
166
                                                                output_exprs);
1115
166
        break;
1116
0
    }
1117
0
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
0
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
0
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
0
                                                         output_exprs);
1123
0
        break;
1124
0
    }
1125
0
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
0
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
0
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
0
        } else {
1133
0
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
0
                                                                row_desc, output_exprs);
1135
0
        }
1136
0
        break;
1137
0
    }
1138
0
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
0
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
0
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
0
                                                             row_desc, output_exprs);
1144
0
        break;
1145
0
    }
1146
0
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
0
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
0
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
0
                                                            output_exprs);
1152
0
        break;
1153
0
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
0
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
0
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
0
        if (config::enable_java_support) {
1167
0
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
0
                                                             output_exprs);
1169
0
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
0
        break;
1175
0
    }
1176
3
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
338
    case TDataSinkType::RESULT_FILE_SINK: {
1186
338
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
338
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
338
        } else {
1196
338
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
338
                                                              output_exprs);
1198
338
        }
1199
338
        break;
1200
338
    }
1201
626
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
626
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
626
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
626
        auto sink_id = next_sink_operator_id();
1205
626
        const int multi_cast_node_id = sink_id;
1206
626
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
626
        std::vector<int> sources;
1209
2.28k
        for (int i = 0; i < sender_size; ++i) {
1210
1.66k
            auto source_id = next_operator_id();
1211
1.66k
            sources.push_back(source_id);
1212
1.66k
        }
1213
1214
626
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
626
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
2.28k
        for (int i = 0; i < sender_size; ++i) {
1217
1.66k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
1.66k
            RowDescriptor* exchange_row_desc = nullptr;
1220
1.66k
            {
1221
1.66k
                const auto& tmp_row_desc =
1222
1.66k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
1.66k
                                ? RowDescriptor(state->desc_tbl(),
1224
1.66k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
1.66k
                                                         .output_tuple_id})
1226
1.66k
                                : row_desc;
1227
1.66k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
1.66k
            }
1229
1.66k
            auto source_id = sources[i];
1230
1.66k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
1.66k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
1.66k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
1.66k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
1.66k
                    /*operator_id=*/source_id);
1236
1.66k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
1.66k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1238
            // 2. create and set sink operator of data stream sender for new pipeline
1239
1240
1.66k
            DataSinkOperatorPtr sink_op;
1241
1.66k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
1.66k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
1.66k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
1.66k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
1.66k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
1.66k
            {
1248
1.66k
                TDataSink* t = pool->add(new TDataSink());
1249
1.66k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
1.66k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
1.66k
            }
1252
1253
            // 3. set dependency dag
1254
1.66k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
1.66k
        }
1256
626
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
626
        break;
1260
626
    }
1261
626
    case TDataSinkType::BLACKHOLE_SINK: {
1262
3
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
3
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
3
        break;
1268
3
    }
1269
0
    case TDataSinkType::TVF_TABLE_SINK: {
1270
0
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
0
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
0
                                                        output_exprs);
1275
0
        break;
1276
0
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
324k
    }
1280
324k
    return Status::OK();
1281
324k
}
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
520k
                                                 OperatorPtr& cache_op) {
1292
520k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
520k
    Defer defer = Defer([&]() {
1294
519k
        if (op) {
1295
519k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
519k
        }
1297
519k
        for (auto& s : sink_ops) {
1298
88.8k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
88.8k
        }
1300
519k
    });
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
520k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
520k
    std::stringstream error_msg;
1305
520k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
520k
    bool fe_with_old_version = false;
1308
520k
    switch (tnode.node_type) {
1309
162k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
162k
        op = std::make_shared<OlapScanOperatorX>(
1311
162k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
162k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
162k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
162k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
162k
        break;
1316
162k
    }
1317
76
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
76
        DCHECK(_query_ctx != nullptr);
1319
76
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
76
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
76
                                                    _num_instances);
1322
76
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
76
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
76
        break;
1325
76
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
2.65k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
2.65k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
2.65k
                                                 _num_instances);
1342
2.65k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
2.65k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
2.65k
        break;
1345
2.65k
    }
1346
113k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
113k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
113k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
113k
        DCHECK_GT(num_senders, 0);
1351
113k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
113k
                                                       num_senders);
1353
113k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
113k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
113k
        break;
1356
113k
    }
1357
135k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
135k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
135k
            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
135k
        bool need_create_cache_op =
1364
135k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
135k
        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
135k
        const bool group_by_limit_opt =
1385
135k
                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
135k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
135k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
135k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
135k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
135k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
135k
        const bool can_use_distinct_streaming_agg =
1396
135k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
135k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
135k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
135k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
135k
        if (can_use_distinct_streaming_agg) {
1402
92.0k
            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
92.0k
            } else {
1413
92.0k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
92.0k
                                                                     tnode, descs);
1415
92.0k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
92.0k
            }
1417
92.0k
        } else if (is_streaming_agg) {
1418
1.06k
            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
1.06k
            } else {
1428
1.06k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
1.06k
                                                             descs);
1430
1.06k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
1.06k
            }
1432
42.8k
        } else {
1433
            // create new pipeline to add query cache operator
1434
42.8k
            PipelinePtr new_pipe;
1435
42.8k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
42.8k
            if (enable_spill) {
1441
170
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
170
                                                                     next_operator_id(), descs);
1443
42.6k
            } else {
1444
42.6k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
42.6k
            }
1446
42.8k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
42.8k
            } else {
1451
42.8k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
42.8k
            }
1453
1454
42.8k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
42.8k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
41.9k
                _dag.insert({downstream_pipeline_id, {}});
1457
41.9k
            }
1458
42.8k
            cur_pipe = add_pipeline(cur_pipe);
1459
42.8k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
42.8k
            if (enable_spill) {
1462
170
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
170
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
42.6k
            } else {
1465
42.6k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
42.6k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
42.6k
            }
1468
42.8k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
42.8k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
42.8k
        }
1471
135k
        break;
1472
135k
    }
1473
135k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
74
        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
74
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
74
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
74
        const auto downstream_pipeline_id = cur_pipe->id();
1486
74
        if (!_dag.contains(downstream_pipeline_id)) {
1487
74
            _dag.insert({downstream_pipeline_id, {}});
1488
74
        }
1489
74
        cur_pipe = add_pipeline(cur_pipe);
1490
74
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
74
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
74
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
74
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
74
        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
74
        {
1503
74
            auto shared_state = BucketedAggSharedState::create_shared();
1504
74
            shared_state->id = op->operator_id();
1505
74
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
469
            for (int i = 0; i < _num_instances; i++) {
1508
395
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
395
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
395
                sink_dep->set_shared_state(shared_state.get());
1511
395
                shared_state->sink_deps.push_back(sink_dep);
1512
395
            }
1513
74
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
74
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
74
            _op_id_to_shared_state.insert(
1516
74
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
74
        }
1518
74
        break;
1519
74
    }
1520
8.77k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
8.77k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
8.77k
                                       tnode.hash_join_node.is_broadcast_join;
1523
8.77k
        const auto enable_spill = _runtime_state->enable_spill();
1524
8.77k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
8.77k
        } else {
1566
8.77k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
8.77k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
8.77k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
8.77k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.07k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.07k
            }
1573
8.77k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
8.77k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
8.77k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
8.77k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
8.77k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
8.77k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
8.77k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
8.77k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
8.77k
        }
1584
8.77k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
3.66k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
3.66k
                    HashJoinSharedState::create_shared(_num_instances);
1587
16.3k
            for (int i = 0; i < _num_instances; i++) {
1588
12.6k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
12.6k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
12.6k
                sink_dep->set_shared_state(shared_state.get());
1591
12.6k
                shared_state->sink_deps.push_back(sink_dep);
1592
12.6k
            }
1593
3.66k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
3.66k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
3.66k
            _op_id_to_shared_state.insert(
1596
3.66k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
3.66k
        }
1598
8.77k
        break;
1599
8.77k
    }
1600
2.11k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
2.11k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
2.11k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
2.11k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
2.11k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
1.88k
            _dag.insert({downstream_pipeline_id, {}});
1607
1.88k
        }
1608
2.11k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
2.11k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
2.11k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
2.11k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
2.11k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
2.11k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
2.11k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
2.11k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
2.11k
        break;
1618
2.11k
    }
1619
49.4k
    case TPlanNodeType::UNION_NODE: {
1620
49.4k
        int child_count = tnode.num_children;
1621
49.4k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
49.4k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
49.4k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
49.4k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
49.1k
            _dag.insert({downstream_pipeline_id, {}});
1627
49.1k
        }
1628
50.5k
        for (int i = 0; i < child_count; i++) {
1629
1.02k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.02k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.02k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.02k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.02k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.02k
            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
1.02k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.02k
        }
1638
49.4k
        break;
1639
49.4k
    }
1640
49.4k
    case TPlanNodeType::SORT_NODE: {
1641
32.1k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
32.1k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
32.1k
        const bool use_local_merge =
1644
32.1k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
32.1k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
32.1k
        } else if (use_local_merge) {
1648
30.3k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
30.3k
                                                                 descs);
1650
30.3k
        } else {
1651
1.76k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
1.76k
        }
1653
32.1k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
32.1k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
32.1k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
32.1k
            _dag.insert({downstream_pipeline_id, {}});
1658
32.1k
        }
1659
32.1k
        cur_pipe = add_pipeline(cur_pipe);
1660
32.1k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
32.1k
        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
32.1k
        } else {
1666
32.1k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
32.1k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
32.1k
        }
1669
32.1k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
32.1k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
32.1k
        break;
1672
32.1k
    }
1673
32.1k
    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
1.52k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.52k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.52k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.52k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.52k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.50k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.50k
        }
1698
1.52k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.52k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.52k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.52k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.52k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.52k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.52k
        break;
1706
1.52k
    }
1707
1.52k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
673
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
673
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
673
        break;
1711
673
    }
1712
673
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
296
    case TPlanNodeType::REPEAT_NODE: {
1723
296
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
296
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
296
        break;
1726
296
    }
1727
908
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
908
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
908
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
908
        break;
1731
908
    }
1732
908
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
18
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
18
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
18
        break;
1736
18
    }
1737
1.43k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.43k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.43k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.43k
        break;
1741
1.43k
    }
1742
1.43k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
263
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
263
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
263
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
263
        break;
1747
263
    }
1748
1.53k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.53k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.53k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.53k
        break;
1752
1.53k
    }
1753
4.72k
    case TPlanNodeType::META_SCAN_NODE: {
1754
4.72k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
4.72k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
4.72k
        break;
1757
4.72k
    }
1758
4.72k
    case TPlanNodeType::SELECT_NODE: {
1759
603
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
603
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
603
        break;
1762
603
    }
1763
603
    case TPlanNodeType::REC_CTE_NODE: {
1764
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
151
        const auto downstream_pipeline_id = cur_pipe->id();
1768
151
        if (!_dag.contains(downstream_pipeline_id)) {
1769
149
            _dag.insert({downstream_pipeline_id, {}});
1770
149
        }
1771
1772
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
151
        DataSinkOperatorPtr anchor_sink;
1776
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
151
                                                                  op->operator_id(), tnode, descs);
1778
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
151
        DataSinkOperatorPtr rec_sink;
1786
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
151
                                                         tnode, descs);
1788
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
151
        break;
1793
151
    }
1794
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.95k
        break;
1798
1.95k
    }
1799
1.95k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
520k
    }
1803
518k
    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
518k
    return Status::OK();
1809
520k
}
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
323k
Status PipelineFragmentContext::submit() {
1846
323k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
323k
    _submitted = true;
1850
1851
323k
    int submit_tasks = 0;
1852
323k
    Status st;
1853
323k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
876k
    for (auto& task : _tasks) {
1855
1.50M
        for (auto& t : task) {
1856
1.50M
            st = scheduler->submit(t.first);
1857
1.50M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.50M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.50M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
1.50M
            submit_tasks++;
1866
1.50M
        }
1867
876k
    }
1868
323k
    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
323k
    } else {
1883
323k
        return st;
1884
323k
    }
1885
323k
}
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
324k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
324k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
324k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
324k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
324k
    if (!_need_notify_close) {
1919
321k
        auto st = send_report(true);
1920
321k
        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
321k
    }
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
324k
    if (_runtime_state->enable_profile() &&
1931
324k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.10k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.10k
         _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
324k
    if (_query_ctx->enable_profile()) {
1953
2.10k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.10k
                                         collect_realtime_load_channel_profile());
1955
2.10k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
324k
    return !_need_notify_close;
1960
324k
}
1961
1962
1.49M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
1.49M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.49M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
507k
        if (_dag.contains(pipeline_id)) {
1967
274k
            for (auto dep : _dag[pipeline_id]) {
1968
274k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
274k
            }
1970
223k
        }
1971
507k
    }
1972
1.49M
    bool need_remove = false;
1973
1.49M
    {
1974
1.49M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.49M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.49M
        _query_ctx->inc_finished_task_num();
1978
1.49M
        if (_closed_tasks >= _total_tasks) {
1979
324k
            need_remove = _close_fragment_instance();
1980
324k
        }
1981
1.49M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.49M
    if (need_remove) {
1984
321k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
321k
    }
1986
1.49M
}
1987
1988
42.4k
std::string PipelineFragmentContext::get_load_error_url() {
1989
42.4k
    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
122k
    for (auto& tasks : _tasks) {
1993
213k
        for (auto& task : tasks) {
1994
213k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
160
                return to_load_error_http_path(str);
1996
160
            }
1997
213k
        }
1998
122k
    }
1999
42.2k
    return "";
2000
42.4k
}
2001
2002
42.4k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
42.4k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
122k
    for (auto& tasks : _tasks) {
2007
213k
        for (auto& task : tasks) {
2008
213k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
160
                return str;
2010
160
            }
2011
213k
        }
2012
122k
    }
2013
42.2k
    return "";
2014
42.4k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
36.3k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
36.3k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
36.3k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
36.3k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
36.3k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
36.3k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
36.3k
    });
2031
2032
36.3k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
36.3k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
36.3k
    int callback_retries = 10;
2038
36.3k
    const int sleep_ms = 1000;
2039
36.3k
    Status exec_status = req.status;
2040
36.3k
    Status coord_status;
2041
36.3k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
36.3k
    do {
2043
36.3k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
36.3k
                                                            req.coord_addr, &coord_status);
2045
36.3k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
36.3k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
36.3k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
36.3k
    TReportExecStatusParams params;
2059
36.3k
    params.protocol_version = FrontendServiceVersion::V1;
2060
36.3k
    params.__set_query_id(req.query_id);
2061
36.3k
    params.__set_backend_num(req.backend_num);
2062
36.3k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
36.3k
    params.__set_fragment_id(req.fragment_id);
2064
36.3k
    params.__set_status(exec_status.to_thrift());
2065
36.3k
    params.__set_done(req.done);
2066
36.3k
    params.__set_query_type(req.runtime_state->query_type());
2067
36.3k
    params.__isset.profile = false;
2068
2069
36.3k
    DCHECK(req.runtime_state != nullptr);
2070
2071
36.3k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
32.6k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
32.6k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
32.6k
    } else {
2075
3.69k
        DCHECK(!req.runtime_states.empty());
2076
3.69k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
3.69k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
3.69k
    }
2086
2087
36.3k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
36.3k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
36.3k
    static std::string s_unselected_rows = "unselected.rows";
2090
36.3k
    int64_t num_rows_load_success = 0;
2091
36.3k
    int64_t num_rows_load_filtered = 0;
2092
36.3k
    int64_t num_rows_load_unselected = 0;
2093
36.3k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
36.3k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
36.3k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
36.3k
    } else if (!req.runtime_states.empty()) {
2109
131k
        for (auto* rs : req.runtime_states) {
2110
131k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
131k
                rs->num_finished_range() > 0) {
2112
30.0k
                params.__isset.load_counters = true;
2113
30.0k
                num_rows_load_success += rs->num_rows_load_success();
2114
30.0k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
30.0k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
30.0k
                params.__isset.fragment_instance_reports = true;
2117
30.0k
                TFragmentInstanceReport t;
2118
30.0k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
30.0k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
30.0k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
30.0k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
30.0k
                params.fragment_instance_reports.push_back(t);
2123
30.0k
            }
2124
131k
        }
2125
36.3k
    }
2126
36.3k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
36.3k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
36.3k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
36.3k
    if (!req.load_error_url.empty()) {
2131
145
        params.__set_tracking_url(req.load_error_url);
2132
145
    }
2133
36.3k
    if (!req.first_error_msg.empty()) {
2134
145
        params.__set_first_error_msg(req.first_error_msg);
2135
145
    }
2136
131k
    for (auto* rs : req.runtime_states) {
2137
131k
        if (rs->wal_id() > 0) {
2138
106
            params.__set_txn_id(rs->wal_id());
2139
106
            params.__set_label(rs->import_label());
2140
106
        }
2141
131k
    }
2142
36.3k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
36.3k
    } else if (!req.runtime_states.empty()) {
2146
131k
        for (auto* rs : req.runtime_states) {
2147
131k
            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
131k
        }
2154
36.3k
    }
2155
36.3k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
36.3k
    } else if (!req.runtime_states.empty()) {
2159
131k
        for (auto* rs : req.runtime_states) {
2160
131k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
24.8k
                params.__isset.commitInfos = true;
2162
24.8k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
24.8k
            }
2164
131k
        }
2165
36.3k
    }
2166
36.3k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
36.3k
    } else if (!req.runtime_states.empty()) {
2170
131k
        for (auto* rs : req.runtime_states) {
2171
131k
            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
131k
        }
2177
36.3k
    }
2178
36.3k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
36.3k
    } else if (!req.runtime_states.empty()) {
2183
131k
        for (auto* rs : req.runtime_states) {
2184
131k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
0
                params.__isset.hive_partition_updates = true;
2186
0
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
0
                                                     rs_hpu.begin(), rs_hpu.end());
2188
0
            }
2189
131k
        }
2190
36.3k
    }
2191
36.3k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
36.3k
    } else if (!req.runtime_states.empty()) {
2196
131k
        for (auto* rs : req.runtime_states) {
2197
131k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
0
                params.__isset.iceberg_commit_datas = true;
2199
0
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
0
                                                   rs_icd.begin(), rs_icd.end());
2201
0
            }
2202
131k
        }
2203
36.3k
    }
2204
2205
36.3k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
36.3k
    } else if (!req.runtime_states.empty()) {
2209
131k
        for (auto* rs : req.runtime_states) {
2210
131k
            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
131k
        }
2216
36.3k
    }
2217
2218
36.3k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
36.3k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
36.3k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
36.3k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
36.3k
    }
2224
2225
36.3k
    TReportExecStatusResult res;
2226
36.3k
    Status rpc_status;
2227
2228
36.3k
    VLOG_DEBUG << "reportExecStatus params is "
2229
24
               << apache::thrift::ThriftDebugString(params).c_str();
2230
36.3k
    if (!exec_status.ok()) {
2231
1.52k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.52k
                     << " to coordinator: " << req.coord_addr
2233
1.52k
                     << ", query id: " << print_id(req.query_id);
2234
1.52k
    }
2235
36.3k
    try {
2236
36.3k
        try {
2237
36.3k
            (*coord)->reportExecStatus(res, params);
2238
36.3k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
36.3k
        rpc_status = Status::create<false>(res.status);
2254
36.3k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
36.3k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
36.3k
}
2265
2266
325k
Status PipelineFragmentContext::send_report(bool done) {
2267
325k
    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
325k
    if (!_is_report_success && done && exec_status.ok()) {
2273
288k
        return Status::OK();
2274
288k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
36.4k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
146
        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
146
            return Status::OK();
2286
146
        }
2287
0
        return Status::NeedSendAgain("");
2288
146
    }
2289
2290
36.3k
    std::vector<RuntimeState*> runtime_states;
2291
2292
83.5k
    for (auto& tasks : _tasks) {
2293
131k
        for (auto& task : tasks) {
2294
131k
            runtime_states.push_back(task.second.get());
2295
131k
        }
2296
83.5k
    }
2297
2298
36.3k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
36.3k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
36.3k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
36.3k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
36.3k
    ReportStatusRequest req {.status = exec_status,
2306
36.3k
                             .runtime_states = runtime_states,
2307
36.3k
                             .done = done || !exec_status.ok(),
2308
36.3k
                             .coord_addr = _query_ctx->coord_addr,
2309
36.3k
                             .query_id = _query_id,
2310
36.3k
                             .fragment_id = _fragment_id,
2311
36.3k
                             .fragment_instance_id = TUniqueId(),
2312
36.3k
                             .backend_num = -1,
2313
36.3k
                             .runtime_state = _runtime_state.get(),
2314
36.3k
                             .load_error_url = load_eror_url,
2315
36.3k
                             .first_error_msg = first_error_msg,
2316
36.3k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
36.3k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
36.3k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
36.3k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
36.3k
        _coordinator_callback(req);
2321
36.3k
        if (!req.done) {
2322
3.52k
            ctx->refresh_next_report_time();
2323
3.52k
        }
2324
36.3k
    });
2325
36.4k
}
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
160
std::string PipelineFragmentContext::debug_string() {
2365
160
    std::lock_guard<std::mutex> l(_task_mutex);
2366
160
    fmt::memory_buffer debug_string_buffer;
2367
160
    fmt::format_to(debug_string_buffer,
2368
160
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
160
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
160
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
608
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
448
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
1.02k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
578
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
578
                           _tasks[j][i].first->debug_string());
2376
578
        }
2377
448
    }
2378
2379
160
    return fmt::to_string(debug_string_buffer);
2380
160
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.10k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.10k
    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
2.10k
    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
2.10k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.10k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.10k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.12k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.12k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.12k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.12k
        res.push_back(profile_ptr);
2407
4.12k
    }
2408
2409
2.10k
    return res;
2410
2.10k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.10k
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
2.10k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
6.53k
    for (const auto& tasks : _tasks) {
2426
13.5k
        for (const auto& task : tasks) {
2427
13.5k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
13.5k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
13.5k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
13.5k
                                                           _runtime_state->profile_level());
2435
13.5k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
13.5k
        }
2437
6.53k
    }
2438
2439
2.10k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.10k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.10k
                                                      _runtime_state->profile_level());
2442
2.10k
    return load_channel_profile;
2443
2.10k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
7.99k
    for (const auto& _task : _tasks) {
2455
16.9k
        for (const auto& task : _task) {
2456
16.9k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
16.9k
            result.merge(set);
2458
16.9k
        }
2459
7.99k
    }
2460
3.28k
    if (_runtime_state) {
2461
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.28k
        result.merge(set);
2463
3.28k
    }
2464
3.28k
    return result;
2465
3.28k
}
2466
2467
326k
void PipelineFragmentContext::_release_resource() {
2468
326k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
326k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
326k
    auto st = _query_ctx->exec_status();
2472
877k
    for (auto& _task : _tasks) {
2473
877k
        if (!_task.empty()) {
2474
877k
            _call_back(_task.front().first->runtime_state(), &st);
2475
877k
        }
2476
877k
    }
2477
326k
    _tasks.clear();
2478
326k
    _dag.clear();
2479
326k
    _pip_id_to_pipeline.clear();
2480
326k
    _pipelines.clear();
2481
326k
    _sink.reset();
2482
326k
    _root_op.reset();
2483
326k
    _runtime_filter_mgr_map.clear();
2484
326k
    _op_id_to_shared_state.clear();
2485
326k
}
2486
2487
} // namespace doris