Coverage Report

Created: 2026-05-14 10:10

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
Line
Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
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#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
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#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
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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"
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#include "runtime/exec_env.h"
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#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
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#include "util/client_cache.h"
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#include "util/countdown_latch.h"
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#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
432k
        : _query_id(std::move(query_id)),
144
432k
          _fragment_id(request.fragment_id),
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432k
          _exec_env(exec_env),
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432k
          _query_ctx(std::move(query_ctx)),
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432k
          _call_back(call_back),
148
432k
          _is_report_on_cancel(true),
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432k
          _params(request),
150
432k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
432k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
432k
                                                               : false) {
153
432k
    _fragment_watcher.start();
154
432k
}
155
156
432k
PipelineFragmentContext::~PipelineFragmentContext() {
157
432k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
432k
            .tag("query_id", print_id(_query_id))
159
432k
            .tag("fragment_id", _fragment_id);
160
432k
    _release_resource();
161
432k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
432k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
432k
        _runtime_state.reset();
165
432k
        _query_ctx.reset();
166
432k
    }
167
432k
}
168
169
132
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
132
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
132
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
132
}
175
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// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
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// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
9.94k
bool PipelineFragmentContext::notify_close() {
181
9.94k
    bool all_closed = false;
182
9.94k
    bool need_remove = false;
183
9.94k
    {
184
9.94k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.94k
        if (_closed_tasks >= _total_tasks) {
186
3.50k
            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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3.42k
                need_remove = true;
193
3.42k
            }
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3.50k
            all_closed = true;
195
3.50k
        }
196
        // make fragment release by self after cancel
197
9.94k
        _need_notify_close = false;
198
9.94k
    }
199
9.94k
    if (need_remove) {
200
3.42k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.42k
    }
202
9.94k
    return all_closed;
203
9.94k
}
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// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
209
6.46k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.46k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.46k
            .tag("query_id", print_id(_query_id))
212
6.46k
            .tag("fragment_id", _fragment_id)
213
6.46k
            .tag("reason", reason.to_string());
214
6.46k
    if (notify_close()) {
215
104
        return;
216
104
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.36k
    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
6.36k
    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
6.36k
    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
6.36k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
24
        _query_ctx->set_load_error_url(error_url);
236
24
    }
237
238
6.36k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
24
        _query_ctx->set_first_error_msg(first_error_msg);
240
24
    }
241
242
6.36k
    _query_ctx->cancel(reason, _fragment_id);
243
6.36k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
395
        _is_report_on_cancel = false;
245
5.96k
    } else {
246
26.3k
        for (auto& id : _fragment_instance_ids) {
247
26.3k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
26.3k
        }
249
5.96k
    }
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
6.36k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.36k
    if (stream_load_ctx != nullptr) {
254
32
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
32
        stream_load_ctx->error_url = get_load_error_url();
259
32
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
32
    }
261
262
27.6k
    for (auto& tasks : _tasks) {
263
61.4k
        for (auto& task : tasks) {
264
61.4k
            task.first->unblock_all_dependencies();
265
61.4k
        }
266
27.6k
    }
267
6.36k
}
268
269
677k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
677k
    PipelineId id = _next_pipeline_id++;
271
677k
    auto pipeline = std::make_shared<Pipeline>(
272
677k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
677k
            parent ? parent->num_tasks() : _num_instances);
274
677k
    if (idx >= 0) {
275
116k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
561k
    } else {
277
561k
        _pipelines.emplace_back(pipeline);
278
561k
    }
279
677k
    if (parent) {
280
239k
        parent->set_children(pipeline);
281
239k
    }
282
677k
    return pipeline;
283
677k
}
284
285
432k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
432k
    {
287
432k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
432k
        auto root_pipeline = add_pipeline();
290
432k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
432k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
432k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
432k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
432k
                                          _params.fragment.output_exprs, _params,
299
432k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
432k
                                          *_desc_tbl, root_pipeline->id()));
301
432k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
432k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
560k
        for (PipelinePtr& pipeline : _pipelines) {
305
560k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
560k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
560k
        }
308
432k
    }
309
    // 4. Build local exchanger
310
432k
    if (_runtime_state->enable_local_shuffle()) {
311
429k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
429k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
429k
                                             _params.bucket_seq_to_instance_idx,
314
429k
                                             _params.shuffle_idx_to_instance_idx));
315
429k
    }
316
317
    // 5. Initialize global states in pipelines.
318
678k
    for (PipelinePtr& pipeline : _pipelines) {
319
678k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
678k
        pipeline->children().clear();
321
678k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
678k
    }
323
324
431k
    {
325
431k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
431k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
431k
    }
329
330
431k
    return Status::OK();
331
431k
}
332
333
432k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
432k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
432k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
432k
        _timeout = _params.query_options.execution_timeout;
339
432k
    }
340
341
432k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
432k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
432k
    SCOPED_TIMER(_prepare_timer);
344
432k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
432k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
432k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
432k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
432k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
432k
    {
350
432k
        SCOPED_TIMER(_init_context_timer);
351
432k
        cast_set(_num_instances, _params.local_params.size());
352
432k
        _total_instances =
353
432k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
432k
        auto* fragment_context = this;
356
357
432k
        if (_params.query_options.__isset.is_report_success) {
358
430k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
430k
        }
360
361
        // 1. Set up the global runtime state.
362
432k
        _runtime_state = RuntimeState::create_unique(
363
432k
                _params.query_id, _params.fragment_id, _params.query_options,
364
432k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
432k
        _runtime_state->set_task_execution_context(shared_from_this());
366
432k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
432k
        if (_params.__isset.backend_id) {
368
429k
            _runtime_state->set_backend_id(_params.backend_id);
369
429k
        }
370
432k
        if (_params.__isset.import_label) {
371
238
            _runtime_state->set_import_label(_params.import_label);
372
238
        }
373
432k
        if (_params.__isset.db_name) {
374
190
            _runtime_state->set_db_name(_params.db_name);
375
190
        }
376
432k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
432k
        if (_params.is_simplified_param) {
381
146k
            _desc_tbl = _query_ctx->desc_tbl;
382
286k
        } else {
383
286k
            DCHECK(_params.__isset.desc_tbl);
384
286k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
286k
                                                  &_desc_tbl));
386
286k
        }
387
432k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
432k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
432k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
432k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
432k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
432k
        const auto target_size = _params.local_params.size();
395
432k
        _fragment_instance_ids.resize(target_size);
396
1.65M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.22M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.22M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.22M
        }
400
432k
    }
401
402
432k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
431k
    _init_next_report_time();
405
406
431k
    _prepared = true;
407
431k
    return Status::OK();
408
432k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.22M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.22M
    const auto& local_params = _params.local_params[instance_idx];
414
1.22M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.22M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.22M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.22M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.22M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
2.02M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
2.02M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
2.02M
                                std::vector<std::shared_ptr<Dependency>>>>
422
2.02M
                shared_state_map;
423
2.64M
        for (auto& op : pipeline->operators()) {
424
2.64M
            auto source_id = op->operator_id();
425
2.64M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.64M
                iter != _op_id_to_shared_state.end()) {
427
769k
                shared_state_map.insert({source_id, iter->second});
428
769k
            }
429
2.64M
        }
430
2.02M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
2.02M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
2.02M
                iter != _op_id_to_shared_state.end()) {
433
297k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
297k
            }
435
2.02M
        }
436
2.02M
        return shared_state_map;
437
2.02M
    };
438
439
3.71M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.49M
        auto& pipeline = _pipelines[pip_idx];
441
2.49M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
2.02M
            auto task_runtime_state = RuntimeState::create_unique(
443
2.02M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
2.02M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
2.02M
            {
446
                // Initialize runtime state for this task
447
2.02M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
2.02M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
2.02M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
2.02M
                if (_params.__isset.backend_id) {
453
2.02M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
2.02M
                }
455
2.02M
                if (_params.__isset.import_label) {
456
239
                    task_runtime_state->set_import_label(_params.import_label);
457
239
                }
458
2.02M
                if (_params.__isset.db_name) {
459
191
                    task_runtime_state->set_db_name(_params.db_name);
460
191
                }
461
2.02M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
2.02M
                if (_params.__isset.wal_id) {
465
112
                    task_runtime_state->set_wal_id(_params.wal_id);
466
112
                }
467
2.02M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
2.02M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
2.02M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
2.02M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
2.02M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
2.02M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
2.02M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
2.02M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
2.02M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
2.02M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
2.02M
            }
482
2.02M
            auto cur_task_id = _total_tasks++;
483
2.02M
            task_runtime_state->set_task_id(cur_task_id);
484
2.02M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
2.02M
            auto task = std::make_shared<PipelineTask>(
486
2.02M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
2.02M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
2.02M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
2.02M
                    instance_idx);
490
2.02M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
2.02M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
2.02M
            _tasks[instance_idx].emplace_back(
493
2.02M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
2.02M
                            std::move(task), std::move(task_runtime_state)});
495
2.02M
        }
496
2.49M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
2.49M
    for (auto& _pipeline : _pipelines) {
516
2.49M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
2.01M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
2.01M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
2.01M
            if (_dag.contains(_pipeline->id())) {
522
1.27M
                auto& deps = _dag[_pipeline->id()];
523
2.02M
                for (auto& dep : deps) {
524
2.02M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.08M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.08M
                        if (ss) {
527
493k
                            task->inject_shared_state(ss);
528
587k
                        } else {
529
587k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
587k
                                    task->get_source_shared_state());
531
587k
                        }
532
1.08M
                    }
533
2.02M
                }
534
1.27M
            }
535
2.01M
        }
536
2.49M
    }
537
3.71M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.49M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
2.01M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
2.01M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
2.01M
            std::vector<TScanRangeParams> scan_ranges;
542
2.01M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
2.01M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
346k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
346k
            }
546
2.01M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
2.01M
                                                             _params.fragment.output_sink));
548
2.01M
        }
549
2.49M
    }
550
1.22M
    {
551
1.22M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.22M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.22M
    }
554
1.22M
    return Status::OK();
555
1.22M
}
556
557
431k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
431k
    _total_tasks = 0;
559
431k
    _closed_tasks = 0;
560
431k
    const auto target_size = _params.local_params.size();
561
431k
    _tasks.resize(target_size);
562
431k
    _runtime_filter_mgr_map.resize(target_size);
563
1.10M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
676k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
676k
    }
566
431k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
431k
    if (target_size > 1 &&
569
431k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
147k
         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
29.2k
        std::vector<Status> prepare_status(target_size);
573
29.2k
        int submitted_tasks = 0;
574
29.2k
        Status submit_status;
575
29.2k
        CountDownLatch latch((int)target_size);
576
274k
        for (int i = 0; i < target_size; i++) {
577
245k
            submit_status = thread_pool->submit_func([&, i]() {
578
245k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
245k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
245k
                latch.count_down();
581
245k
            });
582
245k
            if (LIKELY(submit_status.ok())) {
583
245k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
245k
        }
588
29.2k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
29.2k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
274k
        for (int i = 0; i < submitted_tasks; i++) {
593
245k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
245k
        }
597
402k
    } else {
598
1.38M
        for (int i = 0; i < target_size; i++) {
599
978k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
978k
        }
601
402k
    }
602
431k
    _pipeline_parent_map.clear();
603
431k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
431k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
431k
    return Status::OK();
608
431k
}
609
610
430k
void PipelineFragmentContext::_init_next_report_time() {
611
430k
    auto interval_s = config::pipeline_status_report_interval;
612
430k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
41.7k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
41.7k
        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
41.7k
        _previous_report_time =
617
41.7k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
41.7k
        _disable_period_report = false;
619
41.7k
    }
620
430k
}
621
622
4.96k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.96k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.96k
    DCHECK(disable == true);
625
4.96k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.96k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.96k
}
628
629
7.28M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.28M
    if (!_is_report_success) {
631
6.75M
        return;
632
6.75M
    }
633
537k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
537k
    if (disable) {
635
9.43k
        return;
636
9.43k
    }
637
528k
    int32_t interval_s = config::pipeline_status_report_interval;
638
528k
    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
528k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
528k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
528k
    if (MonotonicNanos() > next_report_time) {
646
4.97k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.97k
                                                            std::memory_order_acq_rel)) {
648
11
            return;
649
11
        }
650
4.96k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
4.96k
        auto st = send_report(false);
667
4.96k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
4.96k
    }
673
528k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
429k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
429k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
429k
    int node_idx = 0;
682
683
429k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
429k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
429k
    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
429k
    return Status::OK();
691
429k
}
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
665k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
665k
    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
665k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
665k
    int num_children = tnodes[*node_idx].num_children;
706
665k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
665k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
665k
    OperatorPtr op = nullptr;
710
665k
    OperatorPtr cache_op = nullptr;
711
665k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
665k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
665k
                                     followed_by_shuffled_operator,
714
665k
                                     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
665k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
665k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
237k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
427k
    } else {
723
427k
        *root = op;
724
427k
    }
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
665k
    auto required_data_distribution =
737
665k
            cur_pipe->operators().empty()
738
665k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
665k
                    : op->required_data_distribution(_runtime_state.get());
740
665k
    current_followed_by_shuffled_operator =
741
665k
            ((followed_by_shuffled_operator ||
742
665k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
608k
                                             : op->is_shuffled_operator())) &&
744
665k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
665k
            (followed_by_shuffled_operator &&
746
556k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
665k
    current_require_bucket_distribution =
749
665k
            ((require_bucket_distribution ||
750
665k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
613k
                                             : op->is_colocated_operator())) &&
752
665k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
665k
            (require_bucket_distribution &&
754
562k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
665k
    if (num_children == 0) {
757
446k
        _use_serial_source = op->is_serial_operator();
758
446k
    }
759
    // rely on that tnodes is preorder of the plan
760
902k
    for (int i = 0; i < num_children; i++) {
761
237k
        ++*node_idx;
762
237k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
237k
                                            current_followed_by_shuffled_operator,
764
237k
                                            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
237k
        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
237k
    }
775
776
665k
    return Status::OK();
777
665k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
116k
        PipelinePtr pipe_with_sink) {
782
116k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
116k
    pipe_with_source->set_num_tasks(_num_instances);
784
116k
    pipe_with_source->set_data_distribution(data_distribution);
785
116k
}
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
116k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
116k
    auto& operators = cur_pipe->operators();
793
116k
    const auto downstream_pipeline_id = cur_pipe->id();
794
116k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
116k
    DataSinkOperatorPtr sink;
797
116k
    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
116k
    const bool followed_by_shuffled_operator =
804
116k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
116k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
116k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
116k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
116k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
116k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
116k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
116k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
116k
    if (bucket_seq_to_instance_idx.empty() &&
813
116k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
5
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
5
    }
816
116k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
116k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
116k
                                          num_buckets, use_global_hash_shuffle,
819
116k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
116k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
116k
            LocalExchangeSharedState::create_shared(_num_instances);
824
116k
    switch (data_distribution.distribution_type) {
825
14.4k
    case ExchangeType::HASH_SHUFFLE:
826
14.4k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
14.4k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
14.4k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
14.4k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
14.4k
                        ? cast_set<int>(
831
14.4k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
14.4k
                        : 0);
833
14.4k
        break;
834
490
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
490
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
490
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
490
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
490
                        ? cast_set<int>(
839
490
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
490
                        : 0);
841
490
        break;
842
97.2k
    case ExchangeType::PASSTHROUGH:
843
97.2k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
97.2k
                cur_pipe->num_tasks(), _num_instances,
845
97.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
97.2k
                        ? cast_set<int>(
847
97.1k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
97.2k
                        : 0);
849
97.2k
        break;
850
370
    case ExchangeType::BROADCAST:
851
370
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
370
                cur_pipe->num_tasks(), _num_instances,
853
370
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
370
                        ? cast_set<int>(
855
370
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
370
                        : 0);
857
370
        break;
858
2.71k
    case ExchangeType::PASS_TO_ONE:
859
2.71k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
860
            // If shared hash table is enabled for BJ, hash table will be built by only one task
861
1.52k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.52k
                    cur_pipe->num_tasks(), _num_instances,
863
1.52k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.52k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.52k
                                                    .local_exchange_free_blocks_limit)
866
1.52k
                            : 0);
867
1.52k
        } else {
868
1.18k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.18k
                    cur_pipe->num_tasks(), _num_instances,
870
1.18k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.18k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.18k
                                                    .local_exchange_free_blocks_limit)
873
1.18k
                            : 0);
874
1.18k
        }
875
2.71k
        break;
876
907
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
907
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
907
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
907
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
907
                        ? cast_set<int>(
881
907
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
907
                        : 0);
883
907
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
116k
    }
888
116k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
116k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
116k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
116k
    _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
116k
    std::copy(operators.begin(), operators.begin() + idx,
898
116k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
116k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
116k
    OperatorPtr source_op;
905
116k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
116k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
116k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
116k
    if (!operators.empty()) {
909
48.6k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
48.6k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
48.6k
    }
912
116k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
116k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
116k
    std::vector<PipelineId> edges_with_source;
917
134k
    for (auto child : cur_pipe->children()) {
918
134k
        bool found = false;
919
149k
        for (auto op : new_pip->operators()) {
920
149k
            if (child->sink()->node_id() == op->node_id()) {
921
13.0k
                new_pip->set_children(child);
922
13.0k
                found = true;
923
13.0k
            };
924
149k
        }
925
134k
        if (!found) {
926
121k
            new_children.push_back(child);
927
121k
            edges_with_source.push_back(child->id());
928
121k
        }
929
134k
    }
930
116k
    new_children.push_back(new_pip);
931
116k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
116k
    if (!new_pip->children().empty()) {
935
7.41k
        std::vector<PipelineId> edges_with_sink;
936
13.0k
        for (auto child : new_pip->children()) {
937
13.0k
            edges_with_sink.push_back(child->id());
938
13.0k
        }
939
7.41k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.41k
    }
941
116k
    cur_pipe->set_children(new_children);
942
116k
    _dag[downstream_pipeline_id] = edges_with_source;
943
116k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
116k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
116k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
116k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
116k
    return Status::OK();
950
116k
}
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
191k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
191k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
37.7k
        return Status::OK();
959
37.7k
    }
960
961
153k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
51.5k
        return Status::OK();
963
51.5k
    }
964
101k
    *do_local_exchange = true;
965
966
101k
    auto& operators = cur_pipe->operators();
967
101k
    auto total_op_num = operators.size();
968
101k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
101k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
101k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
101k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
101k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
324
            << "total_op_num: " << total_op_num
975
324
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
324
            << " 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
101k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
101k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
14.6k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
14.6k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
14.6k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
14.6k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
14.6k
                shuffle_idx_to_instance_idx));
990
14.6k
    }
991
101k
    return Status::OK();
992
101k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
428k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
987k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
558k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
558k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
124k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
124k
                if (child->sink()->node_id() ==
1003
124k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
109k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
109k
                }
1006
124k
            }
1007
119k
        }
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
558k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
558k
                                             bucket_seq_to_instance_idx,
1014
558k
                                             shuffle_idx_to_instance_idx));
1015
558k
    }
1016
428k
    return Status::OK();
1017
428k
}
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
557k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
557k
    int idx = 1;
1024
557k
    bool do_local_exchange = false;
1025
606k
    do {
1026
606k
        auto& ops = pip->operators();
1027
606k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
671k
        for (; idx < ops.size();) {
1030
113k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
105k
                RETURN_IF_ERROR(_add_local_exchange(
1032
105k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
105k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
105k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
105k
                        shuffle_idx_to_instance_idx));
1036
105k
            }
1037
113k
            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
48.7k
                idx = 2;
1043
48.7k
                break;
1044
48.7k
            }
1045
64.9k
            idx++;
1046
64.9k
        }
1047
606k
    } while (do_local_exchange);
1048
557k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
85.6k
        RETURN_IF_ERROR(_add_local_exchange(
1050
85.6k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
85.6k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
85.6k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
85.6k
    }
1054
557k
    return Status::OK();
1055
557k
}
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
431k
                                                  PipelineId cur_pipeline_id) {
1063
431k
    switch (thrift_sink.type) {
1064
144k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
144k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
144k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
144k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
144k
                params.destinations, _fragment_instance_ids);
1071
144k
        break;
1072
144k
    }
1073
250k
    case TDataSinkType::RESULT_SINK: {
1074
250k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
250k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
250k
        int child_node_id = pipeline->operators().back()->node_id();
1080
250k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
250k
                                                      row_desc, output_exprs,
1082
250k
                                                      thrift_sink.result_sink);
1083
250k
        break;
1084
250k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
31.3k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
31.3k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
31.3k
        int child_node_id = pipeline->operators().back()->node_id();
1098
31.3k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
31.3k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
31.3k
            !config::is_cloud_mode()) {
1101
2.15k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.15k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
29.1k
        } else {
1104
29.1k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
29.1k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
29.1k
        }
1107
31.3k
        break;
1108
0
    }
1109
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
165
        DCHECK(state->get_query_ctx() != nullptr);
1112
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
165
                                                                output_exprs);
1115
165
        break;
1116
0
    }
1117
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.46k
                                                         output_exprs);
1123
1.46k
        break;
1124
1.46k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
1.73k
        } else {
1133
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.73k
                                                                row_desc, output_exprs);
1135
1.73k
        }
1136
1.73k
        break;
1137
1.73k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
501
    case TDataSinkType::RESULT_FILE_SINK: {
1186
501
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
501
        } else {
1196
501
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
501
                                                              output_exprs);
1198
501
        }
1199
501
        break;
1200
501
    }
1201
1.86k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
1.86k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
1.86k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
1.86k
        auto sink_id = next_sink_operator_id();
1205
1.86k
        const int multi_cast_node_id = sink_id;
1206
1.86k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
1.86k
        std::vector<int> sources;
1209
7.23k
        for (int i = 0; i < sender_size; ++i) {
1210
5.37k
            auto source_id = next_operator_id();
1211
5.37k
            sources.push_back(source_id);
1212
5.37k
        }
1213
1214
1.86k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
1.86k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
7.23k
        for (int i = 0; i < sender_size; ++i) {
1217
5.37k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
5.37k
            RowDescriptor* exchange_row_desc = nullptr;
1220
5.37k
            {
1221
5.37k
                const auto& tmp_row_desc =
1222
5.37k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
5.37k
                                ? RowDescriptor(state->desc_tbl(),
1224
5.37k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
5.37k
                                                         .output_tuple_id})
1226
5.37k
                                : row_desc;
1227
5.37k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
5.37k
            }
1229
5.37k
            auto source_id = sources[i];
1230
5.37k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
5.37k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
5.37k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
5.37k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
5.37k
                    /*operator_id=*/source_id);
1236
5.37k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
5.37k
                    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
5.37k
            DataSinkOperatorPtr sink_op;
1241
5.37k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
5.37k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
5.37k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
5.37k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
5.37k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
5.37k
            {
1248
5.37k
                TDataSink* t = pool->add(new TDataSink());
1249
5.37k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
5.37k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
5.37k
            }
1252
1253
            // 3. set dependency dag
1254
5.37k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
5.37k
        }
1256
1.86k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
1.86k
        break;
1260
1.86k
    }
1261
1.86k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
13
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
13
        break;
1268
13
    }
1269
156
    case TDataSinkType::TVF_TABLE_SINK: {
1270
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
156
                                                        output_exprs);
1275
156
        break;
1276
156
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
431k
    }
1280
431k
    return Status::OK();
1281
431k
}
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
670k
                                                 OperatorPtr& cache_op) {
1292
670k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
670k
    Defer defer = Defer([&]() {
1294
668k
        if (op) {
1295
668k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
668k
        }
1297
668k
        for (auto& s : sink_ops) {
1298
123k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
123k
        }
1300
668k
    });
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
670k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
670k
    std::stringstream error_msg;
1305
670k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
670k
    bool fe_with_old_version = false;
1308
670k
    switch (tnode.node_type) {
1309
211k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
211k
        op = std::make_shared<OlapScanOperatorX>(
1311
211k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
211k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
211k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
211k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
211k
        break;
1316
211k
    }
1317
79
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
79
        DCHECK(_query_ctx != nullptr);
1319
79
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
79
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
79
                                                    _num_instances);
1322
79
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
79
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
79
        break;
1325
79
    }
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
23.2k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
23.2k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
23.2k
                                                 _num_instances);
1342
23.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
23.2k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
23.2k
        break;
1345
23.2k
    }
1346
147k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
147k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
147k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
147k
        DCHECK_GT(num_senders, 0);
1351
147k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
147k
                                                       num_senders);
1353
147k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
147k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
147k
        break;
1356
147k
    }
1357
156k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
156k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
156k
            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
156k
        bool need_create_cache_op =
1364
156k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
156k
        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
156k
        const bool group_by_limit_opt =
1385
156k
                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
156k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
156k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
156k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
156k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
156k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
156k
        const bool can_use_distinct_streaming_agg =
1396
156k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
156k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
156k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
156k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
156k
        if (can_use_distinct_streaming_agg) {
1402
91.5k
            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
91.5k
            } else {
1413
91.5k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
91.5k
                                                                     tnode, descs);
1415
91.5k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
91.5k
            }
1417
91.5k
        } else if (is_streaming_agg) {
1418
2.79k
            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
2.79k
            } else {
1428
2.79k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
2.79k
                                                             descs);
1430
2.79k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
2.79k
            }
1432
62.3k
        } else {
1433
            // create new pipeline to add query cache operator
1434
62.3k
            PipelinePtr new_pipe;
1435
62.3k
            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
62.3k
            if (enable_spill) {
1441
178
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
178
                                                                     next_operator_id(), descs);
1443
62.2k
            } else {
1444
62.2k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
62.2k
            }
1446
62.3k
            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
62.3k
            } else {
1451
62.3k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
62.3k
            }
1453
1454
62.3k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
62.3k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
59.8k
                _dag.insert({downstream_pipeline_id, {}});
1457
59.8k
            }
1458
62.3k
            cur_pipe = add_pipeline(cur_pipe);
1459
62.3k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
62.3k
            if (enable_spill) {
1462
178
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
178
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
62.2k
            } else {
1465
62.2k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
62.2k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
62.2k
            }
1468
62.3k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
62.3k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
62.3k
        }
1471
156k
        break;
1472
156k
    }
1473
156k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
65
        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
65
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
65
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
65
        const auto downstream_pipeline_id = cur_pipe->id();
1486
65
        if (!_dag.contains(downstream_pipeline_id)) {
1487
65
            _dag.insert({downstream_pipeline_id, {}});
1488
65
        }
1489
65
        cur_pipe = add_pipeline(cur_pipe);
1490
65
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
65
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
65
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
65
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
65
        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
65
        {
1503
65
            auto shared_state = BucketedAggSharedState::create_shared();
1504
65
            shared_state->id = op->operator_id();
1505
65
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
444
            for (int i = 0; i < _num_instances; i++) {
1508
379
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
379
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
379
                sink_dep->set_shared_state(shared_state.get());
1511
379
                shared_state->sink_deps.push_back(sink_dep);
1512
379
            }
1513
65
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
65
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
65
            _op_id_to_shared_state.insert(
1516
65
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
65
        }
1518
65
        break;
1519
65
    }
1520
9.70k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.70k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.70k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.70k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.70k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
9.70k
        } else {
1566
9.70k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.70k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.70k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.70k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
8.00k
                _dag.insert({downstream_pipeline_id, {}});
1572
8.00k
            }
1573
9.70k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.70k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.70k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.70k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.70k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.70k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.70k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.70k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.70k
        }
1584
9.70k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
4.38k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
4.38k
                    HashJoinSharedState::create_shared(_num_instances);
1587
21.2k
            for (int i = 0; i < _num_instances; i++) {
1588
16.8k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
16.8k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
16.8k
                sink_dep->set_shared_state(shared_state.get());
1591
16.8k
                shared_state->sink_deps.push_back(sink_dep);
1592
16.8k
            }
1593
4.38k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
4.38k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
4.38k
            _op_id_to_shared_state.insert(
1596
4.38k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
4.38k
        }
1598
9.70k
        break;
1599
9.70k
    }
1600
4.63k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
4.63k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
4.63k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
4.63k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
4.63k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
4.40k
            _dag.insert({downstream_pipeline_id, {}});
1607
4.40k
        }
1608
4.63k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
4.63k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
4.63k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
4.63k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
4.63k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
4.63k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
4.63k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
4.63k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
4.63k
        break;
1618
4.63k
    }
1619
53.3k
    case TPlanNodeType::UNION_NODE: {
1620
53.3k
        int child_count = tnode.num_children;
1621
53.3k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
53.3k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
53.3k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
53.3k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
52.6k
            _dag.insert({downstream_pipeline_id, {}});
1627
52.6k
        }
1628
54.7k
        for (int i = 0; i < child_count; i++) {
1629
1.40k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.40k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.40k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.40k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.40k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.40k
            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
1.40k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.40k
        }
1638
53.3k
        break;
1639
53.3k
    }
1640
53.3k
    case TPlanNodeType::SORT_NODE: {
1641
43.9k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
43.9k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
43.9k
        const bool use_local_merge =
1644
43.9k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
43.9k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
43.9k
        } else if (use_local_merge) {
1648
41.6k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
41.6k
                                                                 descs);
1650
41.6k
        } else {
1651
2.31k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.31k
        }
1653
43.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
43.9k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
43.9k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
43.8k
            _dag.insert({downstream_pipeline_id, {}});
1658
43.8k
        }
1659
43.9k
        cur_pipe = add_pipeline(cur_pipe);
1660
43.9k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
43.9k
        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
43.9k
        } else {
1666
43.9k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
43.9k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
43.9k
        }
1669
43.9k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
43.9k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
43.9k
        break;
1672
43.9k
    }
1673
43.9k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.63k
        }
1698
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.64k
        break;
1706
1.64k
    }
1707
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.60k
        break;
1711
1.60k
    }
1712
1.60k
    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
298
    case TPlanNodeType::REPEAT_NODE: {
1723
298
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
298
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
298
        break;
1726
298
    }
1727
914
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
914
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
914
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
914
        break;
1731
914
    }
1732
914
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
218
        break;
1736
218
    }
1737
1.56k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.56k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.56k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.56k
        break;
1741
1.56k
    }
1742
1.56k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
459
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
459
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
459
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
459
        break;
1747
459
    }
1748
2.02k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.02k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.02k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.02k
        break;
1752
2.02k
    }
1753
6.40k
    case TPlanNodeType::META_SCAN_NODE: {
1754
6.40k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
6.40k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
6.40k
        break;
1757
6.40k
    }
1758
6.40k
    case TPlanNodeType::SELECT_NODE: {
1759
1.85k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
1.85k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
1.85k
        break;
1762
1.85k
    }
1763
1.85k
    case TPlanNodeType::REC_CTE_NODE: {
1764
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
151
        const auto downstream_pipeline_id = cur_pipe->id();
1768
151
        if (!_dag.contains(downstream_pipeline_id)) {
1769
148
            _dag.insert({downstream_pipeline_id, {}});
1770
148
        }
1771
1772
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
151
        DataSinkOperatorPtr anchor_sink;
1776
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
151
                                                                  op->operator_id(), tnode, descs);
1778
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
151
        DataSinkOperatorPtr rec_sink;
1786
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
151
                                                         tnode, descs);
1788
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
151
        break;
1793
151
    }
1794
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.95k
        break;
1798
1.95k
    }
1799
1.95k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
670k
    }
1803
668k
    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
668k
    return Status::OK();
1809
670k
}
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
429k
Status PipelineFragmentContext::submit() {
1846
429k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
429k
    _submitted = true;
1850
1851
429k
    int submit_tasks = 0;
1852
429k
    Status st;
1853
429k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.22M
    for (auto& task : _tasks) {
1855
2.02M
        for (auto& t : task) {
1856
2.02M
            st = scheduler->submit(t.first);
1857
2.02M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
2.02M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
2.02M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
2.02M
            submit_tasks++;
1866
2.02M
        }
1867
1.22M
    }
1868
429k
    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
429k
    } else {
1883
429k
        return st;
1884
429k
    }
1885
429k
}
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
431k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
431k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
431k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
431k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
431k
    if (!_need_notify_close) {
1919
428k
        auto st = send_report(true);
1920
428k
        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
428k
    }
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
431k
    if (_runtime_state->enable_profile() &&
1931
431k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.54k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.54k
         _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
431k
    if (_query_ctx->enable_profile()) {
1953
2.54k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.54k
                                         collect_realtime_load_channel_profile());
1955
2.54k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
431k
    return !_need_notify_close;
1960
431k
}
1961
1962
2.01M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
2.01M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
2.01M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
677k
        if (_dag.contains(pipeline_id)) {
1967
362k
            for (auto dep : _dag[pipeline_id]) {
1968
362k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
362k
            }
1970
288k
        }
1971
677k
    }
1972
2.01M
    bool need_remove = false;
1973
2.01M
    {
1974
2.01M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
2.01M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
2.01M
        _query_ctx->inc_finished_task_num();
1978
2.01M
        if (_closed_tasks >= _total_tasks) {
1979
431k
            need_remove = _close_fragment_instance();
1980
431k
        }
1981
2.01M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
2.01M
    if (need_remove) {
1984
428k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
428k
    }
1986
2.01M
}
1987
1988
54.5k
std::string PipelineFragmentContext::get_load_error_url() {
1989
54.5k
    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
150k
    for (auto& tasks : _tasks) {
1993
240k
        for (auto& task : tasks) {
1994
240k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
177
                return to_load_error_http_path(str);
1996
177
            }
1997
240k
        }
1998
150k
    }
1999
54.3k
    return "";
2000
54.5k
}
2001
2002
54.5k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
54.5k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
149k
    for (auto& tasks : _tasks) {
2007
240k
        for (auto& task : tasks) {
2008
240k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
177
                return str;
2010
177
            }
2011
240k
        }
2012
149k
    }
2013
54.3k
    return "";
2014
54.5k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
48.1k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
48.1k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
48.1k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
48.1k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
48.1k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
48.1k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
48.1k
    });
2031
2032
48.1k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
48.1k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
48.1k
    int callback_retries = 10;
2038
48.1k
    const int sleep_ms = 1000;
2039
48.1k
    Status exec_status = req.status;
2040
48.1k
    Status coord_status;
2041
48.1k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
48.1k
    do {
2043
48.1k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
48.1k
                                                            req.coord_addr, &coord_status);
2045
48.1k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
48.1k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
48.1k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
48.1k
    TReportExecStatusParams params;
2059
48.1k
    params.protocol_version = FrontendServiceVersion::V1;
2060
48.1k
    params.__set_query_id(req.query_id);
2061
48.1k
    params.__set_backend_num(req.backend_num);
2062
48.1k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
48.1k
    params.__set_fragment_id(req.fragment_id);
2064
48.1k
    params.__set_status(exec_status.to_thrift());
2065
48.1k
    params.__set_done(req.done);
2066
48.1k
    params.__set_query_type(req.runtime_state->query_type());
2067
48.1k
    params.__isset.profile = false;
2068
2069
48.1k
    DCHECK(req.runtime_state != nullptr);
2070
2071
48.1k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
43.5k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
43.5k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
43.5k
    } else {
2075
4.65k
        DCHECK(!req.runtime_states.empty());
2076
4.65k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
4.65k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.65k
    }
2086
2087
48.1k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
48.1k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
48.1k
    static std::string s_unselected_rows = "unselected.rows";
2090
48.1k
    int64_t num_rows_load_success = 0;
2091
48.1k
    int64_t num_rows_load_filtered = 0;
2092
48.1k
    int64_t num_rows_load_unselected = 0;
2093
48.1k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
48.1k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
48.1k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
48.1k
    } else if (!req.runtime_states.empty()) {
2109
179k
        for (auto* rs : req.runtime_states) {
2110
179k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
179k
                rs->num_finished_range() > 0) {
2112
35.9k
                params.__isset.load_counters = true;
2113
35.9k
                num_rows_load_success += rs->num_rows_load_success();
2114
35.9k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
35.9k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
35.9k
                params.__isset.fragment_instance_reports = true;
2117
35.9k
                TFragmentInstanceReport t;
2118
35.9k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
35.9k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
35.9k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
35.9k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
35.9k
                params.fragment_instance_reports.push_back(t);
2123
35.9k
            }
2124
179k
        }
2125
48.1k
    }
2126
48.1k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
48.1k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
48.1k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
48.1k
    if (!req.load_error_url.empty()) {
2131
161
        params.__set_tracking_url(req.load_error_url);
2132
161
    }
2133
48.1k
    if (!req.first_error_msg.empty()) {
2134
161
        params.__set_first_error_msg(req.first_error_msg);
2135
161
    }
2136
179k
    for (auto* rs : req.runtime_states) {
2137
179k
        if (rs->wal_id() > 0) {
2138
108
            params.__set_txn_id(rs->wal_id());
2139
108
            params.__set_label(rs->import_label());
2140
108
        }
2141
179k
    }
2142
48.1k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
48.1k
    } else if (!req.runtime_states.empty()) {
2146
179k
        for (auto* rs : req.runtime_states) {
2147
179k
            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
179k
        }
2154
48.1k
    }
2155
48.1k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
48.1k
    } else if (!req.runtime_states.empty()) {
2159
179k
        for (auto* rs : req.runtime_states) {
2160
179k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
27.0k
                params.__isset.commitInfos = true;
2162
27.0k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
27.0k
            }
2164
179k
        }
2165
48.1k
    }
2166
48.1k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
48.1k
    } else if (!req.runtime_states.empty()) {
2170
179k
        for (auto* rs : req.runtime_states) {
2171
179k
            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
179k
        }
2177
48.1k
    }
2178
48.1k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
48.1k
    } else if (!req.runtime_states.empty()) {
2183
179k
        for (auto* rs : req.runtime_states) {
2184
179k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.13k
                params.__isset.hive_partition_updates = true;
2186
2.13k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.13k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.13k
            }
2189
179k
        }
2190
48.1k
    }
2191
48.1k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
48.1k
    } else if (!req.runtime_states.empty()) {
2196
179k
        for (auto* rs : req.runtime_states) {
2197
179k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.08k
                params.__isset.iceberg_commit_datas = true;
2199
2.08k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.08k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.08k
            }
2202
179k
        }
2203
48.1k
    }
2204
2205
48.1k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
48.1k
    } else if (!req.runtime_states.empty()) {
2209
179k
        for (auto* rs : req.runtime_states) {
2210
179k
            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
179k
        }
2216
48.1k
    }
2217
2218
48.1k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
48.1k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
48.1k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
48.1k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
48.1k
    }
2224
2225
48.1k
    TReportExecStatusResult res;
2226
48.1k
    Status rpc_status;
2227
2228
48.1k
    VLOG_DEBUG << "reportExecStatus params is "
2229
9
               << apache::thrift::ThriftDebugString(params).c_str();
2230
48.1k
    if (!exec_status.ok()) {
2231
1.67k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.67k
                     << " to coordinator: " << req.coord_addr
2233
1.67k
                     << ", query id: " << print_id(req.query_id);
2234
1.67k
    }
2235
48.1k
    try {
2236
48.1k
        try {
2237
48.1k
            (*coord)->reportExecStatus(res, params);
2238
48.1k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
48.1k
        rpc_status = Status::create<false>(res.status);
2254
48.1k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
48.1k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
48.1k
}
2265
2266
433k
Status PipelineFragmentContext::send_report(bool done) {
2267
433k
    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
433k
    if (!_is_report_success && done && exec_status.ok()) {
2273
385k
        return Status::OK();
2274
385k
    }
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
48.4k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
304
        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
304
            return Status::OK();
2286
304
        }
2287
0
        return Status::NeedSendAgain("");
2288
304
    }
2289
2290
48.1k
    std::vector<RuntimeState*> runtime_states;
2291
2292
122k
    for (auto& tasks : _tasks) {
2293
179k
        for (auto& task : tasks) {
2294
179k
            runtime_states.push_back(task.second.get());
2295
179k
        }
2296
122k
    }
2297
2298
48.1k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
48.1k
                                        ? get_load_error_url()
2300
48.1k
                                        : _query_ctx->get_load_error_url();
2301
48.1k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
48.1k
                                          ? get_first_error_msg()
2303
48.1k
                                          : _query_ctx->get_first_error_msg();
2304
2305
48.1k
    ReportStatusRequest req {.status = exec_status,
2306
48.1k
                             .runtime_states = runtime_states,
2307
48.1k
                             .done = done || !exec_status.ok(),
2308
48.1k
                             .coord_addr = _query_ctx->coord_addr,
2309
48.1k
                             .query_id = _query_id,
2310
48.1k
                             .fragment_id = _fragment_id,
2311
48.1k
                             .fragment_instance_id = TUniqueId(),
2312
48.1k
                             .backend_num = -1,
2313
48.1k
                             .runtime_state = _runtime_state.get(),
2314
48.1k
                             .load_error_url = load_eror_url,
2315
48.1k
                             .first_error_msg = first_error_msg,
2316
48.1k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
48.1k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
48.1k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
48.1k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
48.1k
        _coordinator_callback(req);
2321
48.1k
        if (!req.done) {
2322
4.96k
            ctx->refresh_next_report_time();
2323
4.96k
        }
2324
48.1k
    });
2325
48.4k
}
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
133
std::string PipelineFragmentContext::debug_string() {
2365
133
    std::lock_guard<std::mutex> l(_task_mutex);
2366
133
    fmt::memory_buffer debug_string_buffer;
2367
133
    fmt::format_to(debug_string_buffer,
2368
133
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
133
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
133
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
466
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
333
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
816
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
483
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
483
                           _tasks[j][i].first->debug_string());
2376
483
        }
2377
333
    }
2378
2379
133
    return fmt::to_string(debug_string_buffer);
2380
133
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.54k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.54k
    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
2.54k
    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
2.54k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.54k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.54k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.76k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.76k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.76k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.76k
        res.push_back(profile_ptr);
2407
4.76k
    }
2408
2409
2.54k
    return res;
2410
2.54k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.54k
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
2.54k
    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
8.09k
    for (const auto& tasks : _tasks) {
2426
16.4k
        for (const auto& task : tasks) {
2427
16.4k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
16.4k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
16.4k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
16.4k
                                                           _runtime_state->profile_level());
2435
16.4k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
16.4k
        }
2437
8.09k
    }
2438
2439
2.54k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.54k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.54k
                                                      _runtime_state->profile_level());
2442
2.54k
    return load_channel_profile;
2443
2.54k
}
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
7.41k
    for (const auto& _task : _tasks) {
2455
12.9k
        for (const auto& task : _task) {
2456
12.9k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
12.9k
            result.merge(set);
2458
12.9k
        }
2459
7.41k
    }
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
433k
void PipelineFragmentContext::_release_resource() {
2468
433k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
433k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
433k
    auto st = _query_ctx->exec_status();
2472
1.22M
    for (auto& _task : _tasks) {
2473
1.22M
        if (!_task.empty()) {
2474
1.22M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.22M
        }
2476
1.22M
    }
2477
433k
    _tasks.clear();
2478
433k
    _dag.clear();
2479
433k
    _pip_id_to_pipeline.clear();
2480
433k
    _pipelines.clear();
2481
433k
    _sink.reset();
2482
433k
    _root_op.reset();
2483
433k
    _runtime_filter_mgr_map.clear();
2484
433k
    _op_id_to_shared_state.clear();
2485
433k
}
2486
2487
} // namespace doris