Coverage Report

Created: 2026-05-22 05:25

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
2
// 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
//
11
// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
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#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
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#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
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#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
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#include "exec/spill/spill_file.h"
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#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
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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"
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#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"
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#include "util/network_util.h"
136
#include "util/uid_util.h"
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138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
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        TUniqueId query_id, const TPipelineFragmentParams& request,
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        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
441k
        : _query_id(std::move(query_id)),
144
441k
          _fragment_id(request.fragment_id),
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441k
          _exec_env(exec_env),
146
441k
          _query_ctx(std::move(query_ctx)),
147
441k
          _call_back(call_back),
148
441k
          _is_report_on_cancel(true),
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441k
          _params(request),
150
441k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
441k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
441k
                                                               : false) {
153
441k
    _fragment_watcher.start();
154
441k
}
155
156
442k
PipelineFragmentContext::~PipelineFragmentContext() {
157
442k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
442k
            .tag("query_id", print_id(_query_id))
159
442k
            .tag("fragment_id", _fragment_id);
160
442k
    _release_resource();
161
442k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
442k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
442k
        _runtime_state.reset();
165
442k
        _query_ctx.reset();
166
442k
    }
167
442k
}
168
169
120
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
120
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
120
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
120
}
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
8.66k
bool PipelineFragmentContext::notify_close() {
181
8.66k
    bool all_closed = false;
182
8.66k
    bool need_remove = false;
183
8.66k
    {
184
8.66k
        std::lock_guard<std::mutex> l(_task_mutex);
185
8.66k
        if (_closed_tasks >= _total_tasks) {
186
3.43k
            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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3.38k
                need_remove = true;
193
3.38k
            }
194
3.43k
            all_closed = true;
195
3.43k
        }
196
        // make fragment release by self after cancel
197
8.66k
        _need_notify_close = false;
198
8.66k
    }
199
8.66k
    if (need_remove) {
200
3.38k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.38k
    }
202
8.66k
    return all_closed;
203
8.66k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
206
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
5.18k
void PipelineFragmentContext::cancel(const Status reason) {
210
5.18k
    LOG_INFO("PipelineFragmentContext::cancel")
211
5.18k
            .tag("query_id", print_id(_query_id))
212
5.18k
            .tag("fragment_id", _fragment_id)
213
5.18k
            .tag("reason", reason.to_string());
214
5.18k
    if (notify_close()) {
215
74
        return;
216
74
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
5.11k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
5.11k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
5.11k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
5.11k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
5.11k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
5.11k
    _query_ctx->cancel(reason, _fragment_id);
243
5.11k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
236
        _is_report_on_cancel = false;
245
4.87k
    } else {
246
16.6k
        for (auto& id : _fragment_instance_ids) {
247
16.6k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
16.6k
        }
249
4.87k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
5.11k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
5.11k
    if (stream_load_ctx != nullptr) {
254
31
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
31
        stream_load_ctx->error_url = get_load_error_url();
259
31
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
31
    }
261
262
17.1k
    for (auto& tasks : _tasks) {
263
36.7k
        for (auto& task : tasks) {
264
36.7k
            task.first->unblock_all_dependencies();
265
36.7k
        }
266
17.1k
    }
267
5.11k
}
268
269
763k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
763k
    PipelineId id = _next_pipeline_id++;
271
763k
    auto pipeline = std::make_shared<Pipeline>(
272
763k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
763k
            parent ? parent->num_tasks() : _num_instances);
274
763k
    if (idx >= 0) {
275
102k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
661k
    } else {
277
661k
        _pipelines.emplace_back(pipeline);
278
661k
    }
279
763k
    if (parent) {
280
286k
        parent->set_children(pipeline);
281
286k
    }
282
763k
    return pipeline;
283
763k
}
284
285
441k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
441k
    {
287
441k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
441k
        auto root_pipeline = add_pipeline();
290
441k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
441k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
441k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
441k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
441k
                                          _params.fragment.output_exprs, _params,
299
441k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
441k
                                          *_desc_tbl, root_pipeline->id()));
301
441k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
441k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
660k
        for (PipelinePtr& pipeline : _pipelines) {
305
660k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
660k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
660k
        }
308
441k
    }
309
    // 4. Build local exchanger
310
441k
    if (_runtime_state->enable_local_shuffle()) {
311
439k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
439k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
439k
                                             _params.bucket_seq_to_instance_idx,
314
439k
                                             _params.shuffle_idx_to_instance_idx));
315
439k
    }
316
317
    // 5. Initialize global states in pipelines.
318
764k
    for (PipelinePtr& pipeline : _pipelines) {
319
764k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
764k
        pipeline->children().clear();
321
764k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
764k
    }
323
324
439k
    {
325
439k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
439k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
439k
    }
329
330
439k
    return Status::OK();
331
439k
}
332
333
441k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
441k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
441k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
441k
        _timeout = _params.query_options.execution_timeout;
339
441k
    }
340
341
441k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
441k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
441k
    SCOPED_TIMER(_prepare_timer);
344
441k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
441k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
441k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
441k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
441k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
441k
    {
350
441k
        SCOPED_TIMER(_init_context_timer);
351
441k
        cast_set(_num_instances, _params.local_params.size());
352
441k
        _total_instances =
353
441k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
441k
        auto* fragment_context = this;
356
357
441k
        if (_params.query_options.__isset.is_report_success) {
358
439k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
439k
        }
360
361
        // 1. Set up the global runtime state.
362
441k
        _runtime_state = RuntimeState::create_unique(
363
441k
                _params.query_id, _params.fragment_id, _params.query_options,
364
441k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
441k
        _runtime_state->set_task_execution_context(shared_from_this());
366
441k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
441k
        if (_params.__isset.backend_id) {
368
438k
            _runtime_state->set_backend_id(_params.backend_id);
369
438k
        }
370
441k
        if (_params.__isset.import_label) {
371
239
            _runtime_state->set_import_label(_params.import_label);
372
239
        }
373
441k
        if (_params.__isset.db_name) {
374
191
            _runtime_state->set_db_name(_params.db_name);
375
191
        }
376
441k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
441k
        if (_params.is_simplified_param) {
381
190k
            _desc_tbl = _query_ctx->desc_tbl;
382
251k
        } else {
383
251k
            DCHECK(_params.__isset.desc_tbl);
384
251k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
251k
                                                  &_desc_tbl));
386
251k
        }
387
441k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
441k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
441k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
441k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
441k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
441k
        const auto target_size = _params.local_params.size();
395
441k
        _fragment_instance_ids.resize(target_size);
396
1.56M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.12M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.12M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.12M
        }
400
441k
    }
401
402
441k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
440k
    _init_next_report_time();
405
406
440k
    _prepared = true;
407
440k
    return Status::OK();
408
441k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.12M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.12M
    const auto& local_params = _params.local_params[instance_idx];
414
1.12M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.12M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.12M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.12M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.12M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.85M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.85M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.85M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.85M
                shared_state_map;
423
2.45M
        for (auto& op : pipeline->operators()) {
424
2.45M
            auto source_id = op->operator_id();
425
2.45M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.45M
                iter != _op_id_to_shared_state.end()) {
427
643k
                shared_state_map.insert({source_id, iter->second});
428
643k
            }
429
2.45M
        }
430
1.87M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.87M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.87M
                iter != _op_id_to_shared_state.end()) {
433
232k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
232k
            }
435
1.87M
        }
436
1.85M
        return shared_state_map;
437
1.85M
    };
438
439
3.39M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.26M
        auto& pipeline = _pipelines[pip_idx];
441
2.26M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.85M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.85M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.85M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.85M
            {
446
                // Initialize runtime state for this task
447
1.85M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.85M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.85M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.85M
                if (_params.__isset.backend_id) {
453
1.85M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.85M
                }
455
1.85M
                if (_params.__isset.import_label) {
456
240
                    task_runtime_state->set_import_label(_params.import_label);
457
240
                }
458
1.85M
                if (_params.__isset.db_name) {
459
192
                    task_runtime_state->set_db_name(_params.db_name);
460
192
                }
461
1.85M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.85M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.85M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.85M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.85M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.85M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.85M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.85M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.85M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.85M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.85M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.85M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.85M
            }
482
1.85M
            auto cur_task_id = _total_tasks++;
483
1.85M
            task_runtime_state->set_task_id(cur_task_id);
484
1.85M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.85M
            auto task = std::make_shared<PipelineTask>(
486
1.85M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.85M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.85M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.85M
                    instance_idx);
490
1.85M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.85M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.85M
            _tasks[instance_idx].emplace_back(
493
1.85M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.85M
                            std::move(task), std::move(task_runtime_state)});
495
1.85M
        }
496
2.26M
    }
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
2.26M
    for (auto& _pipeline : _pipelines) {
516
2.26M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.84M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.84M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.84M
            if (_dag.contains(_pipeline->id())) {
522
1.13M
                auto& deps = _dag[_pipeline->id()];
523
1.76M
                for (auto& dep : deps) {
524
1.76M
                    if (pipeline_id_to_task.contains(dep)) {
525
947k
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
947k
                        if (ss) {
527
483k
                            task->inject_shared_state(ss);
528
483k
                        } else {
529
463k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
463k
                                    task->get_source_shared_state());
531
463k
                        }
532
947k
                    }
533
1.76M
                }
534
1.13M
            }
535
1.84M
        }
536
2.26M
    }
537
3.39M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.26M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.85M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.85M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.85M
            std::vector<TScanRangeParams> scan_ranges;
542
1.85M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.85M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
279k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
279k
            }
546
1.85M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.85M
                                                             _params.fragment.output_sink));
548
1.85M
        }
549
2.26M
    }
550
1.13M
    {
551
1.13M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.13M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.13M
    }
554
1.13M
    return Status::OK();
555
1.12M
}
556
557
441k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
441k
    _total_tasks = 0;
559
441k
    _closed_tasks = 0;
560
441k
    const auto target_size = _params.local_params.size();
561
441k
    _tasks.resize(target_size);
562
441k
    _runtime_filter_mgr_map.resize(target_size);
563
1.20M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
763k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
763k
    }
566
441k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
441k
    if (target_size > 1 &&
569
441k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
136k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
571
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
572
17.6k
        std::vector<Status> prepare_status(target_size);
573
17.6k
        int submitted_tasks = 0;
574
17.6k
        Status submit_status;
575
17.6k
        CountDownLatch latch((int)target_size);
576
219k
        for (int i = 0; i < target_size; i++) {
577
202k
            submit_status = thread_pool->submit_func([&, i]() {
578
202k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
202k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
202k
                latch.count_down();
581
202k
            });
582
202k
            if (LIKELY(submit_status.ok())) {
583
202k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
202k
        }
588
17.6k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
17.6k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
219k
        for (int i = 0; i < submitted_tasks; i++) {
593
202k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
202k
        }
597
423k
    } else {
598
1.35M
        for (int i = 0; i < target_size; i++) {
599
928k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
928k
        }
601
423k
    }
602
441k
    _pipeline_parent_map.clear();
603
441k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
441k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
441k
    return Status::OK();
608
441k
}
609
610
439k
void PipelineFragmentContext::_init_next_report_time() {
611
439k
    auto interval_s = config::pipeline_status_report_interval;
612
439k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
37.1k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
37.1k
        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
37.1k
        _previous_report_time =
617
37.1k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
37.1k
        _disable_period_report = false;
619
37.1k
    }
620
439k
}
621
622
4.09k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.09k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.09k
    DCHECK(disable == true);
625
4.09k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.09k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.09k
}
628
629
6.82M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
6.82M
    if (!_is_report_success) {
631
6.43M
        return;
632
6.43M
    }
633
387k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
387k
    if (disable) {
635
6.43k
        return;
636
6.43k
    }
637
380k
    int32_t interval_s = config::pipeline_status_report_interval;
638
380k
    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
380k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
380k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
380k
    if (MonotonicNanos() > next_report_time) {
646
4.10k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.10k
                                                            std::memory_order_acq_rel)) {
648
12
            return;
649
12
        }
650
4.09k
        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
4.09k
        auto st = send_report(false);
667
4.09k
        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
4.09k
    }
673
380k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
436k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
436k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
436k
    int node_idx = 0;
682
683
436k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
436k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
436k
    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
436k
    return Status::OK();
691
436k
}
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
766k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
766k
    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
766k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
766k
    int num_children = tnodes[*node_idx].num_children;
706
766k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
766k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
766k
    OperatorPtr op = nullptr;
710
766k
    OperatorPtr cache_op = nullptr;
711
766k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
766k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
766k
                                     followed_by_shuffled_operator,
714
766k
                                     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
766k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
766k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
329k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
437k
    } else {
723
437k
        *root = op;
724
437k
    }
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
766k
    auto required_data_distribution =
737
766k
            cur_pipe->operators().empty()
738
766k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
766k
                    : op->required_data_distribution(_runtime_state.get());
740
766k
    current_followed_by_shuffled_operator =
741
766k
            ((followed_by_shuffled_operator ||
742
766k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
702k
                                             : op->is_shuffled_operator())) &&
744
766k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
766k
            (followed_by_shuffled_operator &&
746
642k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
766k
    current_require_bucket_distribution =
749
766k
            ((require_bucket_distribution ||
750
766k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
705k
                                             : op->is_colocated_operator())) &&
752
766k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
766k
            (require_bucket_distribution &&
754
648k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
766k
    if (num_children == 0) {
757
475k
        _use_serial_source = op->is_serial_operator();
758
475k
    }
759
    // rely on that tnodes is preorder of the plan
760
1.09M
    for (int i = 0; i < num_children; i++) {
761
329k
        ++*node_idx;
762
329k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
329k
                                            current_followed_by_shuffled_operator,
764
329k
                                            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
329k
        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
329k
    }
775
776
766k
    return Status::OK();
777
766k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
102k
        PipelinePtr pipe_with_sink) {
782
102k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
102k
    pipe_with_source->set_num_tasks(_num_instances);
784
102k
    pipe_with_source->set_data_distribution(data_distribution);
785
102k
}
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
102k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
102k
    auto& operators = cur_pipe->operators();
793
102k
    const auto downstream_pipeline_id = cur_pipe->id();
794
102k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
102k
    DataSinkOperatorPtr sink;
797
102k
    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
102k
    const bool followed_by_shuffled_operator =
804
102k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
102k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
102k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
102k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
102k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
102k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
102k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
102k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
102k
    if (bucket_seq_to_instance_idx.empty() &&
813
102k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
15
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
15
    }
816
102k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
102k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
102k
                                          num_buckets, use_global_hash_shuffle,
819
102k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
102k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
102k
            LocalExchangeSharedState::create_shared(_num_instances);
824
102k
    switch (data_distribution.distribution_type) {
825
10.2k
    case ExchangeType::HASH_SHUFFLE:
826
10.2k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
10.2k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
10.2k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
10.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
10.2k
                        ? cast_set<int>(
831
10.2k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
10.2k
                        : 0);
833
10.2k
        break;
834
458
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
458
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
458
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
458
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
458
                        ? cast_set<int>(
839
458
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
458
                        : 0);
841
458
        break;
842
87.8k
    case ExchangeType::PASSTHROUGH:
843
87.8k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
87.8k
                cur_pipe->num_tasks(), _num_instances,
845
87.8k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
87.8k
                        ? cast_set<int>(
847
87.7k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
87.8k
                        : 0);
849
87.8k
        break;
850
297
    case ExchangeType::BROADCAST:
851
297
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
297
                cur_pipe->num_tasks(), _num_instances,
853
297
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
297
                        ? cast_set<int>(
855
297
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
297
                        : 0);
857
297
        break;
858
2.36k
    case ExchangeType::PASS_TO_ONE:
859
2.36k
        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
1.12k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.12k
                    cur_pipe->num_tasks(), _num_instances,
863
1.12k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.12k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.12k
                                                    .local_exchange_free_blocks_limit)
866
1.12k
                            : 0);
867
1.24k
        } else {
868
1.24k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.24k
                    cur_pipe->num_tasks(), _num_instances,
870
1.24k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.24k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.24k
                                                    .local_exchange_free_blocks_limit)
873
1.24k
                            : 0);
874
1.24k
        }
875
2.36k
        break;
876
905
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
905
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
905
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
905
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
905
                        ? cast_set<int>(
881
905
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
905
                        : 0);
883
905
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
102k
    }
888
102k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
102k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
102k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
102k
    _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
102k
    std::copy(operators.begin(), operators.begin() + idx,
898
102k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
102k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
102k
    OperatorPtr source_op;
905
102k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
102k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
102k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
102k
    if (!operators.empty()) {
909
48.3k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
48.3k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
48.3k
    }
912
102k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
102k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
102k
    std::vector<PipelineId> edges_with_source;
917
120k
    for (auto child : cur_pipe->children()) {
918
120k
        bool found = false;
919
135k
        for (auto op : new_pip->operators()) {
920
135k
            if (child->sink()->node_id() == op->node_id()) {
921
12.8k
                new_pip->set_children(child);
922
12.8k
                found = true;
923
12.8k
            };
924
135k
        }
925
120k
        if (!found) {
926
107k
            new_children.push_back(child);
927
107k
            edges_with_source.push_back(child->id());
928
107k
        }
929
120k
    }
930
102k
    new_children.push_back(new_pip);
931
102k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
102k
    if (!new_pip->children().empty()) {
935
7.03k
        std::vector<PipelineId> edges_with_sink;
936
12.8k
        for (auto child : new_pip->children()) {
937
12.8k
            edges_with_sink.push_back(child->id());
938
12.8k
        }
939
7.03k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.03k
    }
941
102k
    cur_pipe->set_children(new_children);
942
102k
    _dag[downstream_pipeline_id] = edges_with_source;
943
102k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
102k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
102k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
102k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
102k
    return Status::OK();
950
102k
}
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
227k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
227k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
86.1k
        return Status::OK();
959
86.1k
    }
960
961
141k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
49.1k
        return Status::OK();
963
49.1k
    }
964
91.9k
    *do_local_exchange = true;
965
966
91.9k
    auto& operators = cur_pipe->operators();
967
91.9k
    auto total_op_num = operators.size();
968
91.9k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
91.9k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
91.9k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
91.9k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
91.9k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
321
            << "total_op_num: " << total_op_num
975
321
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
321
            << " 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
91.9k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
91.9k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
10.4k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
10.4k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
10.4k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
10.4k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
10.4k
                shuffle_idx_to_instance_idx));
990
10.4k
    }
991
91.9k
    return Status::OK();
992
91.9k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
437k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.09M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
658k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
658k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
185k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
185k
                if (child->sink()->node_id() ==
1003
185k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
151k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
151k
                }
1006
185k
            }
1007
170k
        }
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
658k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
658k
                                             bucket_seq_to_instance_idx,
1014
658k
                                             shuffle_idx_to_instance_idx));
1015
658k
    }
1016
437k
    return Status::OK();
1017
437k
}
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
656k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
656k
    int idx = 1;
1024
656k
    bool do_local_exchange = false;
1025
705k
    do {
1026
705k
        auto& ops = pip->operators();
1027
705k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
802k
        for (; idx < ops.size();) {
1030
145k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
126k
                RETURN_IF_ERROR(_add_local_exchange(
1032
126k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
126k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
126k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
126k
                        shuffle_idx_to_instance_idx));
1036
126k
            }
1037
145k
            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
48.6k
                idx = 2;
1043
48.6k
                break;
1044
48.6k
            }
1045
96.4k
            idx++;
1046
96.4k
        }
1047
705k
    } while (do_local_exchange);
1048
656k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
100k
        RETURN_IF_ERROR(_add_local_exchange(
1050
100k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
100k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
100k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
100k
    }
1054
656k
    return Status::OK();
1055
656k
}
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
440k
                                                  PipelineId cur_pipeline_id) {
1063
440k
    switch (thrift_sink.type) {
1064
178k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
178k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
178k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
178k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
178k
                params.destinations, _fragment_instance_ids);
1071
178k
        break;
1072
178k
    }
1073
217k
    case TDataSinkType::RESULT_SINK: {
1074
217k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
217k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
217k
        int child_node_id = pipeline->operators().back()->node_id();
1080
217k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
217k
                                                      row_desc, output_exprs,
1082
217k
                                                      thrift_sink.result_sink);
1083
217k
        break;
1084
217k
    }
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
30.8k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
30.8k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
30.8k
        int child_node_id = pipeline->operators().back()->node_id();
1098
30.8k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
30.8k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
30.8k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
1.35k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
1.35k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
29.5k
        } else {
1104
29.5k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
29.5k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
29.5k
        }
1107
30.8k
        break;
1108
0
    }
1109
166
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
166
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
166
        DCHECK(state->get_query_ctx() != nullptr);
1112
166
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
166
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
166
                                                                output_exprs);
1115
166
        break;
1116
0
    }
1117
734
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
734
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
734
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
734
                                                         output_exprs);
1123
734
        break;
1124
734
    }
1125
866
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
866
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
866
        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
866
        } else {
1133
866
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
866
                                                                row_desc, output_exprs);
1135
866
        }
1136
866
        break;
1137
866
    }
1138
10
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
10
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
10
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
10
                                                             row_desc, output_exprs);
1144
10
        break;
1145
10
    }
1146
40
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
40
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
40
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
40
                                                            output_exprs);
1152
40
        break;
1153
40
    }
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
44
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
44
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
44
        if (config::enable_java_support) {
1167
44
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
44
                                                             output_exprs);
1169
44
        } 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
44
        break;
1175
44
    }
1176
44
    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
420
    case TDataSinkType::RESULT_FILE_SINK: {
1186
420
        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
420
        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
420
        } else {
1196
420
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
420
                                                              output_exprs);
1198
420
        }
1199
420
        break;
1200
420
    }
1201
11.7k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
11.7k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
11.7k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
11.7k
        auto sink_id = next_sink_operator_id();
1205
11.7k
        const int multi_cast_node_id = sink_id;
1206
11.7k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
11.7k
        std::vector<int> sources;
1209
46.8k
        for (int i = 0; i < sender_size; ++i) {
1210
35.0k
            auto source_id = next_operator_id();
1211
35.0k
            sources.push_back(source_id);
1212
35.0k
        }
1213
1214
11.7k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
11.7k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
46.8k
        for (int i = 0; i < sender_size; ++i) {
1217
35.0k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
35.0k
            RowDescriptor* exchange_row_desc = nullptr;
1220
35.0k
            {
1221
35.0k
                const auto& tmp_row_desc =
1222
35.0k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
35.0k
                                ? RowDescriptor(state->desc_tbl(),
1224
35.0k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
35.0k
                                                         .output_tuple_id})
1226
18.4E
                                : row_desc;
1227
35.0k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
35.0k
            }
1229
35.0k
            auto source_id = sources[i];
1230
35.0k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
35.0k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
35.0k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
35.0k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
35.0k
                    /*operator_id=*/source_id);
1236
35.0k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
35.0k
                    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
35.0k
            DataSinkOperatorPtr sink_op;
1241
35.0k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
35.0k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
35.0k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
35.0k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
35.0k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
35.0k
            {
1248
35.0k
                TDataSink* t = pool->add(new TDataSink());
1249
35.0k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
35.0k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
35.0k
            }
1252
1253
            // 3. set dependency dag
1254
35.0k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
35.0k
        }
1256
11.7k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
11.7k
        break;
1260
11.7k
    }
1261
11.7k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
8
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
8
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
8
        break;
1268
8
    }
1269
78
    case TDataSinkType::TVF_TABLE_SINK: {
1270
78
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
78
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
78
                                                        output_exprs);
1275
78
        break;
1276
78
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
440k
    }
1280
439k
    return Status::OK();
1281
440k
}
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
771k
                                                 OperatorPtr& cache_op) {
1292
771k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
771k
    Defer defer = Defer([&]() {
1294
769k
        if (op) {
1295
769k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
769k
        }
1297
769k
        for (auto& s : sink_ops) {
1298
184k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
184k
        }
1300
769k
    });
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
771k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
771k
    std::stringstream error_msg;
1305
771k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
771k
    bool fe_with_old_version = false;
1308
771k
    switch (tnode.node_type) {
1309
188k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
188k
        op = std::make_shared<OlapScanOperatorX>(
1311
188k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
188k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
188k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
188k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
188k
        break;
1316
188k
    }
1317
78
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
78
        DCHECK(_query_ctx != nullptr);
1319
78
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
78
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
78
                                                    _num_instances);
1322
78
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
78
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
78
        break;
1325
78
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
13.6k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
13.6k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
13.6k
                                                 _num_instances);
1342
13.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
13.6k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
13.6k
        break;
1345
13.6k
    }
1346
211k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
211k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
211k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
211k
        DCHECK_GT(num_senders, 0);
1351
211k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
211k
                                                       num_senders);
1353
211k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
211k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
211k
        break;
1356
211k
    }
1357
196k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
196k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
196k
            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
196k
        bool need_create_cache_op =
1364
196k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
196k
        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
196k
        const bool group_by_limit_opt =
1385
196k
                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
196k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
196k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
196k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
196k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
196k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
196k
        const bool can_use_distinct_streaming_agg =
1396
196k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
196k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
196k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
196k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
196k
        if (can_use_distinct_streaming_agg) {
1402
91.6k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
91.6k
            } else {
1413
91.6k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
91.6k
                                                                     tnode, descs);
1415
91.6k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
91.6k
            }
1417
105k
        } else if (is_streaming_agg) {
1418
5.67k
            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
5.67k
            } else {
1428
5.67k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
5.67k
                                                             descs);
1430
5.67k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
5.67k
            }
1432
99.5k
        } else {
1433
            // create new pipeline to add query cache operator
1434
99.5k
            PipelinePtr new_pipe;
1435
99.5k
            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
99.5k
            if (enable_spill) {
1441
145
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
145
                                                                     next_operator_id(), descs);
1443
99.4k
            } else {
1444
99.4k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
99.4k
            }
1446
99.5k
            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
99.5k
            } else {
1451
99.5k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
99.5k
            }
1453
1454
99.5k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
99.5k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
86.8k
                _dag.insert({downstream_pipeline_id, {}});
1457
86.8k
            }
1458
99.5k
            cur_pipe = add_pipeline(cur_pipe);
1459
99.5k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
99.5k
            if (enable_spill) {
1462
145
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
145
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
99.4k
            } else {
1465
99.4k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
99.4k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
99.4k
            }
1468
99.5k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
99.5k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
99.5k
        }
1471
196k
        break;
1472
196k
    }
1473
196k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
81
        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
81
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
81
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
81
        const auto downstream_pipeline_id = cur_pipe->id();
1486
81
        if (!_dag.contains(downstream_pipeline_id)) {
1487
81
            _dag.insert({downstream_pipeline_id, {}});
1488
81
        }
1489
81
        cur_pipe = add_pipeline(cur_pipe);
1490
81
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
81
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
81
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
81
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
81
        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
81
        {
1503
81
            auto shared_state = BucketedAggSharedState::create_shared();
1504
81
            shared_state->id = op->operator_id();
1505
81
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
403
            for (int i = 0; i < _num_instances; i++) {
1508
322
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
322
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
322
                sink_dep->set_shared_state(shared_state.get());
1511
322
                shared_state->sink_deps.push_back(sink_dep);
1512
322
            }
1513
81
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
81
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
81
            _op_id_to_shared_state.insert(
1516
81
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
81
        }
1518
81
        break;
1519
81
    }
1520
9.17k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.17k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.17k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.17k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.17k
        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
9.17k
        } else {
1566
9.17k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.17k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.17k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.17k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.41k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.41k
            }
1573
9.17k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.17k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.17k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.17k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.17k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.17k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.17k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.17k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.17k
        }
1584
9.17k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.39k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.39k
                    HashJoinSharedState::create_shared(_num_instances);
1587
14.1k
            for (int i = 0; i < _num_instances; i++) {
1588
11.7k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
11.7k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
11.7k
                sink_dep->set_shared_state(shared_state.get());
1591
11.7k
                shared_state->sink_deps.push_back(sink_dep);
1592
11.7k
            }
1593
2.39k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.39k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.39k
            _op_id_to_shared_state.insert(
1596
2.39k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.39k
        }
1598
9.17k
        break;
1599
9.17k
    }
1600
24.7k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
24.7k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
24.7k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
24.7k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
24.7k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
24.4k
            _dag.insert({downstream_pipeline_id, {}});
1607
24.4k
        }
1608
24.7k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
24.7k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
24.7k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
24.7k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
24.7k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
24.7k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
24.7k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
24.7k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
24.7k
        break;
1618
24.7k
    }
1619
51.4k
    case TPlanNodeType::UNION_NODE: {
1620
51.4k
        int child_count = tnode.num_children;
1621
51.4k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
51.4k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
51.4k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
51.4k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
50.9k
            _dag.insert({downstream_pipeline_id, {}});
1627
50.9k
        }
1628
52.6k
        for (int i = 0; i < child_count; i++) {
1629
1.21k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.21k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.21k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.21k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.21k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.21k
            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
1.21k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.21k
        }
1638
51.4k
        break;
1639
51.4k
    }
1640
51.4k
    case TPlanNodeType::SORT_NODE: {
1641
48.6k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
48.6k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
48.6k
        const bool use_local_merge =
1644
48.6k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
48.6k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
48.6k
        } else if (use_local_merge) {
1648
46.6k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
46.6k
                                                                 descs);
1650
46.6k
        } else {
1651
1.99k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
1.99k
        }
1653
48.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
48.6k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
48.6k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
48.5k
            _dag.insert({downstream_pipeline_id, {}});
1658
48.5k
        }
1659
48.6k
        cur_pipe = add_pipeline(cur_pipe);
1660
48.6k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
48.6k
        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
48.6k
        } else {
1666
48.6k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
48.6k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
48.6k
        }
1669
48.6k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
48.6k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
48.6k
        break;
1672
48.6k
    }
1673
48.6k
    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
1.49k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.49k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.49k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.49k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.49k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.47k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.47k
        }
1698
1.49k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.49k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.49k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.49k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.49k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.49k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.49k
        break;
1706
1.49k
    }
1707
1.49k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.13k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.13k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.13k
        break;
1711
1.13k
    }
1712
1.13k
    case TPlanNodeType::INTERSECT_NODE: {
1713
134
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
134
                                                                      cur_pipe, sink_ops));
1715
134
        break;
1716
134
    }
1717
134
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
296
    case TPlanNodeType::REPEAT_NODE: {
1723
296
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
296
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
296
        break;
1726
296
    }
1727
912
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
912
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
912
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
912
        break;
1731
912
    }
1732
912
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
118
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
118
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
118
        break;
1736
118
    }
1737
1.81k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.81k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.81k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.81k
        break;
1741
1.81k
    }
1742
1.81k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
366
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
366
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
366
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
366
        break;
1747
366
    }
1748
1.79k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.79k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.79k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.79k
        break;
1752
1.79k
    }
1753
5.76k
    case TPlanNodeType::META_SCAN_NODE: {
1754
5.76k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
5.76k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
5.76k
        break;
1757
5.76k
    }
1758
11.6k
    case TPlanNodeType::SELECT_NODE: {
1759
11.6k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
11.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
11.6k
        break;
1762
11.6k
    }
1763
11.6k
    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
771k
    }
1803
769k
    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
769k
    return Status::OK();
1809
771k
}
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
438k
Status PipelineFragmentContext::submit() {
1846
438k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
438k
    _submitted = true;
1850
1851
438k
    int submit_tasks = 0;
1852
438k
    Status st;
1853
438k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.13M
    for (auto& task : _tasks) {
1855
1.85M
        for (auto& t : task) {
1856
1.85M
            st = scheduler->submit(t.first);
1857
1.85M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.85M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.85M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
1.85M
            submit_tasks++;
1866
1.85M
        }
1867
1.13M
    }
1868
438k
    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
438k
    } else {
1883
438k
        return st;
1884
438k
    }
1885
438k
}
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
441k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
441k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
441k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
441k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
441k
    if (!_need_notify_close) {
1919
437k
        auto st = send_report(true);
1920
437k
        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
437k
    }
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
441k
    if (_runtime_state->enable_profile() &&
1931
441k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.63k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.63k
         _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
441k
    if (_query_ctx->enable_profile()) {
1953
2.63k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.63k
                                         collect_realtime_load_channel_profile());
1955
2.63k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
441k
    return !_need_notify_close;
1960
441k
}
1961
1962
1.85M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
1.85M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.85M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
764k
        if (_dag.contains(pipeline_id)) {
1967
424k
            for (auto dep : _dag[pipeline_id]) {
1968
424k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
424k
            }
1970
353k
        }
1971
764k
    }
1972
1.85M
    bool need_remove = false;
1973
1.85M
    {
1974
1.85M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.85M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.85M
        _query_ctx->inc_finished_task_num();
1978
1.85M
        if (_closed_tasks >= _total_tasks) {
1979
441k
            need_remove = _close_fragment_instance();
1980
441k
        }
1981
1.85M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.85M
    if (need_remove) {
1984
438k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
438k
    }
1986
1.85M
}
1987
1988
47.8k
std::string PipelineFragmentContext::get_load_error_url() {
1989
47.8k
    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
105k
    for (auto& tasks : _tasks) {
1993
160k
        for (auto& task : tasks) {
1994
160k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
169
                return to_load_error_http_path(str);
1996
169
            }
1997
160k
        }
1998
105k
    }
1999
47.6k
    return "";
2000
47.8k
}
2001
2002
47.8k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
47.8k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
105k
    for (auto& tasks : _tasks) {
2007
160k
        for (auto& task : tasks) {
2008
160k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
169
                return str;
2010
169
            }
2011
160k
        }
2012
105k
    }
2013
47.6k
    return "";
2014
47.8k
}
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
42.7k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
42.7k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
42.7k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
42.7k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
42.7k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
42.7k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
42.7k
    });
2031
2032
42.7k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
42.7k
    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
42.7k
    int callback_retries = 10;
2038
42.7k
    const int sleep_ms = 1000;
2039
42.7k
    Status exec_status = req.status;
2040
42.7k
    Status coord_status;
2041
42.7k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
42.7k
    do {
2043
42.7k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
42.7k
                                                            req.coord_addr, &coord_status);
2045
42.7k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
42.7k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
42.7k
    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
42.7k
    TReportExecStatusParams params;
2059
42.7k
    params.protocol_version = FrontendServiceVersion::V1;
2060
42.7k
    params.__set_query_id(req.query_id);
2061
42.7k
    params.__set_backend_num(req.backend_num);
2062
42.7k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
42.7k
    params.__set_fragment_id(req.fragment_id);
2064
42.7k
    params.__set_status(exec_status.to_thrift());
2065
42.7k
    params.__set_done(req.done);
2066
42.7k
    params.__set_query_type(req.runtime_state->query_type());
2067
42.7k
    params.__isset.profile = false;
2068
2069
42.7k
    DCHECK(req.runtime_state != nullptr);
2070
2071
42.7k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
38.2k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
38.2k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
38.2k
    } else {
2075
4.48k
        DCHECK(!req.runtime_states.empty());
2076
4.48k
        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
4.48k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.48k
    }
2086
2087
42.7k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
42.7k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
42.7k
    static std::string s_unselected_rows = "unselected.rows";
2090
42.7k
    int64_t num_rows_load_success = 0;
2091
42.7k
    int64_t num_rows_load_filtered = 0;
2092
42.7k
    int64_t num_rows_load_unselected = 0;
2093
42.7k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
42.7k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
42.7k
        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
42.7k
    } else if (!req.runtime_states.empty()) {
2109
123k
        for (auto* rs : req.runtime_states) {
2110
123k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
123k
                rs->num_finished_range() > 0) {
2112
33.5k
                params.__isset.load_counters = true;
2113
33.5k
                num_rows_load_success += rs->num_rows_load_success();
2114
33.5k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
33.5k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
33.5k
                params.__isset.fragment_instance_reports = true;
2117
33.5k
                TFragmentInstanceReport t;
2118
33.5k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
33.5k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
33.5k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
33.5k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
33.5k
                params.fragment_instance_reports.push_back(t);
2123
33.5k
            }
2124
123k
        }
2125
42.7k
    }
2126
42.7k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
42.7k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
42.7k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
42.7k
    if (!req.load_error_url.empty()) {
2131
154
        params.__set_tracking_url(req.load_error_url);
2132
154
    }
2133
42.7k
    if (!req.first_error_msg.empty()) {
2134
154
        params.__set_first_error_msg(req.first_error_msg);
2135
154
    }
2136
123k
    for (auto* rs : req.runtime_states) {
2137
123k
        if (rs->wal_id() > 0) {
2138
114
            params.__set_txn_id(rs->wal_id());
2139
114
            params.__set_label(rs->import_label());
2140
114
        }
2141
123k
    }
2142
42.7k
    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
42.7k
    } else if (!req.runtime_states.empty()) {
2146
123k
        for (auto* rs : req.runtime_states) {
2147
123k
            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
123k
        }
2154
42.7k
    }
2155
42.7k
    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
42.7k
    } else if (!req.runtime_states.empty()) {
2159
123k
        for (auto* rs : req.runtime_states) {
2160
123k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
26.2k
                params.__isset.commitInfos = true;
2162
26.2k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
26.2k
            }
2164
123k
        }
2165
42.7k
    }
2166
42.7k
    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
42.7k
    } else if (!req.runtime_states.empty()) {
2170
123k
        for (auto* rs : req.runtime_states) {
2171
123k
            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
123k
        }
2177
42.7k
    }
2178
42.7k
    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
42.7k
    } else if (!req.runtime_states.empty()) {
2183
123k
        for (auto* rs : req.runtime_states) {
2184
123k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
1.05k
                params.__isset.hive_partition_updates = true;
2186
1.05k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
1.05k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
1.05k
            }
2189
123k
        }
2190
42.7k
    }
2191
42.7k
    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
42.7k
    } else if (!req.runtime_states.empty()) {
2196
123k
        for (auto* rs : req.runtime_states) {
2197
123k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
1.04k
                params.__isset.iceberg_commit_datas = true;
2199
1.04k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
1.04k
                                                   rs_icd.begin(), rs_icd.end());
2201
1.04k
            }
2202
123k
        }
2203
42.7k
    }
2204
2205
42.7k
    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
42.7k
    } else if (!req.runtime_states.empty()) {
2209
123k
        for (auto* rs : req.runtime_states) {
2210
123k
            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
123k
        }
2216
42.7k
    }
2217
2218
42.7k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
42.7k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
42.7k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
42.7k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
42.7k
    }
2224
2225
42.7k
    TReportExecStatusResult res;
2226
42.7k
    Status rpc_status;
2227
2228
42.7k
    VLOG_DEBUG << "reportExecStatus params is "
2229
4
               << apache::thrift::ThriftDebugString(params).c_str();
2230
42.7k
    if (!exec_status.ok()) {
2231
1.61k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.61k
                     << " to coordinator: " << req.coord_addr
2233
1.61k
                     << ", query id: " << print_id(req.query_id);
2234
1.61k
    }
2235
42.7k
    try {
2236
42.7k
        try {
2237
42.7k
            (*coord)->reportExecStatus(res, params);
2238
42.7k
        } 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
42.7k
        rpc_status = Status::create<false>(res.status);
2254
42.7k
    } 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
42.7k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
42.7k
}
2265
2266
442k
Status PipelineFragmentContext::send_report(bool done) {
2267
442k
    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
442k
    if (!_is_report_success && done && exec_status.ok()) {
2273
399k
        return Status::OK();
2274
399k
    }
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
42.8k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
192
        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
192
            return Status::OK();
2286
192
        }
2287
0
        return Status::NeedSendAgain("");
2288
192
    }
2289
2290
42.6k
    std::vector<RuntimeState*> runtime_states;
2291
2292
88.1k
    for (auto& tasks : _tasks) {
2293
123k
        for (auto& task : tasks) {
2294
123k
            runtime_states.push_back(task.second.get());
2295
123k
        }
2296
88.1k
    }
2297
2298
42.6k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
42.6k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
42.6k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
42.6k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
42.6k
    ReportStatusRequest req {.status = exec_status,
2306
42.6k
                             .runtime_states = runtime_states,
2307
42.6k
                             .done = done || !exec_status.ok(),
2308
42.6k
                             .coord_addr = _query_ctx->coord_addr,
2309
42.6k
                             .query_id = _query_id,
2310
42.6k
                             .fragment_id = _fragment_id,
2311
42.6k
                             .fragment_instance_id = TUniqueId(),
2312
42.6k
                             .backend_num = -1,
2313
42.6k
                             .runtime_state = _runtime_state.get(),
2314
42.6k
                             .load_error_url = load_eror_url,
2315
42.6k
                             .first_error_msg = first_error_msg,
2316
42.6k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
42.6k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
42.7k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
42.7k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
42.7k
        _coordinator_callback(req);
2321
42.7k
        if (!req.done) {
2322
4.09k
            ctx->refresh_next_report_time();
2323
4.09k
        }
2324
42.7k
    });
2325
42.8k
}
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
121
std::string PipelineFragmentContext::debug_string() {
2365
121
    std::lock_guard<std::mutex> l(_task_mutex);
2366
121
    fmt::memory_buffer debug_string_buffer;
2367
121
    fmt::format_to(debug_string_buffer,
2368
121
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
121
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
121
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
747
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
626
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
1.49k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
871
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
871
                           _tasks[j][i].first->debug_string());
2376
871
        }
2377
626
    }
2378
2379
121
    return fmt::to_string(debug_string_buffer);
2380
121
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.63k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.63k
    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
2.63k
    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
2.63k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.63k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.63k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.86k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.86k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.86k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.86k
        res.push_back(profile_ptr);
2407
4.86k
    }
2408
2409
2.63k
    return res;
2410
2.63k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.63k
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
2.63k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
6.63k
    for (const auto& tasks : _tasks) {
2426
13.5k
        for (const auto& task : tasks) {
2427
13.5k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
13.5k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
13.5k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
13.5k
                                                           _runtime_state->profile_level());
2435
13.5k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
13.5k
        }
2437
6.63k
    }
2438
2439
2.63k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.63k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.63k
                                                      _runtime_state->profile_level());
2442
2.63k
    return load_channel_profile;
2443
2.63k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
8.22k
    for (const auto& _task : _tasks) {
2455
13.9k
        for (const auto& task : _task) {
2456
13.9k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
13.9k
            result.merge(set);
2458
13.9k
        }
2459
8.22k
    }
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
442k
void PipelineFragmentContext::_release_resource() {
2468
442k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
442k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
442k
    auto st = _query_ctx->exec_status();
2472
1.13M
    for (auto& _task : _tasks) {
2473
1.13M
        if (!_task.empty()) {
2474
1.13M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.13M
        }
2476
1.13M
    }
2477
442k
    _tasks.clear();
2478
442k
    _dag.clear();
2479
442k
    _pip_id_to_pipeline.clear();
2480
442k
    _pipelines.clear();
2481
442k
    _sink.reset();
2482
442k
    _root_op.reset();
2483
442k
    _runtime_filter_mgr_map.clear();
2484
442k
    _op_id_to_shared_state.clear();
2485
442k
}
2486
2487
} // namespace doris