Coverage Report

Created: 2026-05-22 10:36

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
111
#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
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#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
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#include "exec/spill/spill_file.h"
124
#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
126
#include "runtime/exec_env.h"
127
#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
131
#include "service/backend_options.h"
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#include "util/client_cache.h"
133
#include "util/countdown_latch.h"
134
#include "util/debug_util.h"
135
#include "util/network_util.h"
136
#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
382k
        : _query_id(std::move(query_id)),
144
382k
          _fragment_id(request.fragment_id),
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382k
          _exec_env(exec_env),
146
382k
          _query_ctx(std::move(query_ctx)),
147
382k
          _call_back(call_back),
148
382k
          _is_report_on_cancel(true),
149
382k
          _params(request),
150
382k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
382k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
382k
                                                               : false) {
153
382k
    _fragment_watcher.start();
154
382k
}
155
156
383k
PipelineFragmentContext::~PipelineFragmentContext() {
157
383k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
383k
            .tag("query_id", print_id(_query_id))
159
383k
            .tag("fragment_id", _fragment_id);
160
383k
    _release_resource();
161
383k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
383k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
383k
        _runtime_state.reset();
165
383k
        _query_ctx.reset();
166
383k
    }
167
383k
}
168
169
64
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
64
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
64
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
64
}
175
176
// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
178
// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
179
// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
8.37k
bool PipelineFragmentContext::notify_close() {
181
8.37k
    bool all_closed = false;
182
8.37k
    bool need_remove = false;
183
8.37k
    {
184
8.37k
        std::lock_guard<std::mutex> l(_task_mutex);
185
8.37k
        if (_closed_tasks >= _total_tasks) {
186
3.44k
            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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3.39k
                need_remove = true;
193
3.39k
            }
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3.44k
            all_closed = true;
195
3.44k
        }
196
        // make fragment release by self after cancel
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8.37k
        _need_notify_close = false;
198
8.37k
    }
199
8.37k
    if (need_remove) {
200
3.39k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.39k
    }
202
8.37k
    return all_closed;
203
8.37k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
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// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
208
// There maybe dead lock.
209
4.89k
void PipelineFragmentContext::cancel(const Status reason) {
210
4.89k
    LOG_INFO("PipelineFragmentContext::cancel")
211
4.89k
            .tag("query_id", print_id(_query_id))
212
4.89k
            .tag("fragment_id", _fragment_id)
213
4.89k
            .tag("reason", reason.to_string());
214
4.89k
    if (notify_close()) {
215
68
        return;
216
68
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
4.82k
    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
4.82k
    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
4.82k
    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
4.82k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
24
        _query_ctx->set_load_error_url(error_url);
236
24
    }
237
238
4.82k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
24
        _query_ctx->set_first_error_msg(first_error_msg);
240
24
    }
241
242
4.82k
    _query_ctx->cancel(reason, _fragment_id);
243
4.82k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
138
        _is_report_on_cancel = false;
245
4.68k
    } else {
246
18.3k
        for (auto& id : _fragment_instance_ids) {
247
18.3k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
18.3k
        }
249
4.68k
    }
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
4.82k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
4.82k
    if (stream_load_ctx != nullptr) {
254
32
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
32
        stream_load_ctx->error_url = get_load_error_url();
259
32
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
32
    }
261
262
18.8k
    for (auto& tasks : _tasks) {
263
47.4k
        for (auto& task : tasks) {
264
47.4k
            task.first->unblock_all_dependencies();
265
47.4k
        }
266
18.8k
    }
267
4.82k
}
268
269
667k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
667k
    PipelineId id = _next_pipeline_id++;
271
667k
    auto pipeline = std::make_shared<Pipeline>(
272
667k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
667k
            parent ? parent->num_tasks() : _num_instances);
274
667k
    if (idx >= 0) {
275
91.5k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
576k
    } else {
277
576k
        _pipelines.emplace_back(pipeline);
278
576k
    }
279
667k
    if (parent) {
280
253k
        parent->set_children(pipeline);
281
253k
    }
282
667k
    return pipeline;
283
667k
}
284
285
382k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
382k
    {
287
382k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
382k
        auto root_pipeline = add_pipeline();
290
382k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
382k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
382k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
382k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
382k
                                          _params.fragment.output_exprs, _params,
299
382k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
382k
                                          *_desc_tbl, root_pipeline->id()));
301
382k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
382k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
575k
        for (PipelinePtr& pipeline : _pipelines) {
305
575k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
575k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
575k
        }
308
382k
    }
309
    // 4. Build local exchanger
310
382k
    if (_runtime_state->enable_local_shuffle()) {
311
380k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
380k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
380k
                                             _params.bucket_seq_to_instance_idx,
314
380k
                                             _params.shuffle_idx_to_instance_idx));
315
380k
    }
316
317
    // 5. Initialize global states in pipelines.
318
668k
    for (PipelinePtr& pipeline : _pipelines) {
319
668k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
668k
        pipeline->children().clear();
321
668k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
668k
    }
323
324
381k
    {
325
381k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
381k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
381k
    }
329
330
381k
    return Status::OK();
331
381k
}
332
333
382k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
382k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
382k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
382k
        _timeout = _params.query_options.execution_timeout;
339
382k
    }
340
341
382k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
382k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
382k
    SCOPED_TIMER(_prepare_timer);
344
382k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
382k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
382k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
382k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
382k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
382k
    {
350
382k
        SCOPED_TIMER(_init_context_timer);
351
382k
        cast_set(_num_instances, _params.local_params.size());
352
382k
        _total_instances =
353
382k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
382k
        auto* fragment_context = this;
356
357
382k
        if (_params.query_options.__isset.is_report_success) {
358
380k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
380k
        }
360
361
        // 1. Set up the global runtime state.
362
382k
        _runtime_state = RuntimeState::create_unique(
363
382k
                _params.query_id, _params.fragment_id, _params.query_options,
364
382k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
382k
        _runtime_state->set_task_execution_context(shared_from_this());
366
382k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
382k
        if (_params.__isset.backend_id) {
368
380k
            _runtime_state->set_backend_id(_params.backend_id);
369
380k
        }
370
382k
        if (_params.__isset.import_label) {
371
234
            _runtime_state->set_import_label(_params.import_label);
372
234
        }
373
382k
        if (_params.__isset.db_name) {
374
186
            _runtime_state->set_db_name(_params.db_name);
375
186
        }
376
382k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
382k
        if (_params.is_simplified_param) {
381
170k
            _desc_tbl = _query_ctx->desc_tbl;
382
212k
        } else {
383
212k
            DCHECK(_params.__isset.desc_tbl);
384
212k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
212k
                                                  &_desc_tbl));
386
212k
        }
387
382k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
382k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
382k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
382k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
382k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
382k
        const auto target_size = _params.local_params.size();
395
382k
        _fragment_instance_ids.resize(target_size);
396
1.33M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
954k
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
954k
            _fragment_instance_ids[i] = fragment_instance_id;
399
954k
        }
400
382k
    }
401
402
382k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
381k
    _init_next_report_time();
405
406
381k
    _prepared = true;
407
381k
    return Status::OK();
408
382k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
953k
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
953k
    const auto& local_params = _params.local_params[instance_idx];
414
953k
    auto fragment_instance_id = local_params.fragment_instance_id;
415
953k
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
953k
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
953k
    auto get_shared_state = [&](PipelinePtr pipeline)
418
953k
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.61M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.61M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.61M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.61M
                shared_state_map;
423
2.13M
        for (auto& op : pipeline->operators()) {
424
2.13M
            auto source_id = op->operator_id();
425
2.13M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.13M
                iter != _op_id_to_shared_state.end()) {
427
561k
                shared_state_map.insert({source_id, iter->second});
428
561k
            }
429
2.13M
        }
430
1.63M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.63M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.63M
                iter != _op_id_to_shared_state.end()) {
433
216k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
216k
            }
435
1.63M
        }
436
1.61M
        return shared_state_map;
437
1.61M
    };
438
439
2.90M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
1.95M
        auto& pipeline = _pipelines[pip_idx];
441
1.95M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.61M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.61M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.61M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.61M
            {
446
                // Initialize runtime state for this task
447
1.61M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.61M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.61M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.61M
                if (_params.__isset.backend_id) {
453
1.61M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.61M
                }
455
1.61M
                if (_params.__isset.import_label) {
456
235
                    task_runtime_state->set_import_label(_params.import_label);
457
235
                }
458
1.61M
                if (_params.__isset.db_name) {
459
187
                    task_runtime_state->set_db_name(_params.db_name);
460
187
                }
461
1.61M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.61M
                if (_params.__isset.wal_id) {
465
112
                    task_runtime_state->set_wal_id(_params.wal_id);
466
112
                }
467
1.61M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.61M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.61M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.61M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.61M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.61M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.61M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.61M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.61M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.61M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.61M
            }
482
1.61M
            auto cur_task_id = _total_tasks++;
483
1.61M
            task_runtime_state->set_task_id(cur_task_id);
484
1.61M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.61M
            auto task = std::make_shared<PipelineTask>(
486
1.61M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.61M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.61M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.61M
                    instance_idx);
490
1.61M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.61M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.61M
            _tasks[instance_idx].emplace_back(
493
1.61M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.61M
                            std::move(task), std::move(task_runtime_state)});
495
1.61M
        }
496
1.95M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
1.95M
    for (auto& _pipeline : _pipelines) {
516
1.95M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.61M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.61M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.61M
            if (_dag.contains(_pipeline->id())) {
522
1.00M
                auto& deps = _dag[_pipeline->id()];
523
1.55M
                for (auto& dep : deps) {
524
1.55M
                    if (pipeline_id_to_task.contains(dep)) {
525
862k
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
862k
                        if (ss) {
527
433k
                            task->inject_shared_state(ss);
528
433k
                        } else {
529
429k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
429k
                                    task->get_source_shared_state());
531
429k
                        }
532
862k
                    }
533
1.55M
                }
534
1.00M
            }
535
1.61M
        }
536
1.95M
    }
537
2.91M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
1.95M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.61M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.61M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.61M
            std::vector<TScanRangeParams> scan_ranges;
542
1.61M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.61M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
229k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
229k
            }
546
1.61M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.61M
                                                             _params.fragment.output_sink));
548
1.61M
        }
549
1.95M
    }
550
956k
    {
551
956k
        std::lock_guard<std::mutex> l(_state_map_lock);
552
956k
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
956k
    }
554
956k
    return Status::OK();
555
953k
}
556
557
381k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
381k
    _total_tasks = 0;
559
381k
    _closed_tasks = 0;
560
381k
    const auto target_size = _params.local_params.size();
561
381k
    _tasks.resize(target_size);
562
381k
    _runtime_filter_mgr_map.resize(target_size);
563
1.04M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
667k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
667k
    }
566
381k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
381k
    if (target_size > 1 &&
569
381k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
120k
         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
14.2k
        std::vector<Status> prepare_status(target_size);
573
14.2k
        int submitted_tasks = 0;
574
14.2k
        Status submit_status;
575
14.2k
        CountDownLatch latch((int)target_size);
576
161k
        for (int i = 0; i < target_size; i++) {
577
147k
            submit_status = thread_pool->submit_func([&, i]() {
578
146k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
146k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
146k
                latch.count_down();
581
146k
            });
582
147k
            if (LIKELY(submit_status.ok())) {
583
147k
                submitted_tasks++;
584
18.4E
            } else {
585
18.4E
                break;
586
18.4E
            }
587
147k
        }
588
14.2k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
14.2k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
161k
        for (int i = 0; i < submitted_tasks; i++) {
593
147k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
147k
        }
597
367k
    } else {
598
1.17M
        for (int i = 0; i < target_size; i++) {
599
808k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
808k
        }
601
367k
    }
602
381k
    _pipeline_parent_map.clear();
603
381k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
381k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
381k
    return Status::OK();
608
381k
}
609
610
380k
void PipelineFragmentContext::_init_next_report_time() {
611
380k
    auto interval_s = config::pipeline_status_report_interval;
612
380k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
31.6k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
31.6k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
31.6k
        _previous_report_time =
617
31.6k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
31.6k
        _disable_period_report = false;
619
31.6k
    }
620
380k
}
621
622
3.60k
void PipelineFragmentContext::refresh_next_report_time() {
623
3.60k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
3.60k
    DCHECK(disable == true);
625
3.60k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
3.60k
    _disable_period_report.compare_exchange_strong(disable, false);
627
3.60k
}
628
629
5.86M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
5.86M
    if (!_is_report_success) {
631
5.54M
        return;
632
5.54M
    }
633
321k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
321k
    if (disable) {
635
4.97k
        return;
636
4.97k
    }
637
316k
    int32_t interval_s = config::pipeline_status_report_interval;
638
316k
    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
316k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
316k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
316k
    if (MonotonicNanos() > next_report_time) {
646
3.61k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
3.61k
                                                            std::memory_order_acq_rel)) {
648
8
            return;
649
8
        }
650
3.60k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
3.60k
        auto st = send_report(false);
667
3.60k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
3.60k
    }
673
316k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
379k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
379k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
379k
    int node_idx = 0;
682
683
379k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
379k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
379k
    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
379k
    return Status::OK();
691
379k
}
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
681k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
681k
    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
681k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
681k
    int num_children = tnodes[*node_idx].num_children;
706
681k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
681k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
681k
    OperatorPtr op = nullptr;
710
681k
    OperatorPtr cache_op = nullptr;
711
681k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
681k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
681k
                                     followed_by_shuffled_operator,
714
681k
                                     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
681k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
681k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
301k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
379k
    } else {
723
379k
        *root = op;
724
379k
    }
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
681k
    auto required_data_distribution =
737
681k
            cur_pipe->operators().empty()
738
681k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
681k
                    : op->required_data_distribution(_runtime_state.get());
740
681k
    current_followed_by_shuffled_operator =
741
681k
            ((followed_by_shuffled_operator ||
742
681k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
615k
                                             : op->is_shuffled_operator())) &&
744
681k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
681k
            (followed_by_shuffled_operator &&
746
557k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
681k
    current_require_bucket_distribution =
749
681k
            ((require_bucket_distribution ||
750
681k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
620k
                                             : op->is_colocated_operator())) &&
752
681k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
681k
            (require_bucket_distribution &&
754
565k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
681k
    if (num_children == 0) {
757
413k
        _use_serial_source = op->is_serial_operator();
758
413k
    }
759
    // rely on that tnodes is preorder of the plan
760
983k
    for (int i = 0; i < num_children; i++) {
761
301k
        ++*node_idx;
762
301k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
301k
                                            current_followed_by_shuffled_operator,
764
301k
                                            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
301k
        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
301k
    }
775
776
681k
    return Status::OK();
777
681k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
91.5k
        PipelinePtr pipe_with_sink) {
782
91.5k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
91.5k
    pipe_with_source->set_num_tasks(_num_instances);
784
91.5k
    pipe_with_source->set_data_distribution(data_distribution);
785
91.5k
}
786
787
Status PipelineFragmentContext::_add_local_exchange_impl(
788
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
789
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
790
        const std::map<int, int>& bucket_seq_to_instance_idx,
791
91.4k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
91.4k
    auto& operators = cur_pipe->operators();
793
91.4k
    const auto downstream_pipeline_id = cur_pipe->id();
794
91.4k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
91.4k
    DataSinkOperatorPtr sink;
797
91.4k
    auto sink_id = next_sink_operator_id();
798
799
    /**
800
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
801
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
802
     */
803
91.4k
    const bool followed_by_shuffled_operator =
804
91.4k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
91.4k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
91.4k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
91.4k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
91.4k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
91.4k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
91.4k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
91.4k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
91.4k
    if (bucket_seq_to_instance_idx.empty() &&
813
91.4k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
9
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
9
    }
816
91.4k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
91.4k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
91.4k
                                          num_buckets, use_global_hash_shuffle,
819
91.4k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
91.4k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
91.4k
            LocalExchangeSharedState::create_shared(_num_instances);
824
91.4k
    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
18.4E
                        : 0);
833
10.2k
        break;
834
435
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
435
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
435
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
435
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
435
                        ? cast_set<int>(
839
435
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
435
                        : 0);
841
435
        break;
842
77.3k
    case ExchangeType::PASSTHROUGH:
843
77.3k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
77.3k
                cur_pipe->num_tasks(), _num_instances,
845
77.3k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
77.3k
                        ? cast_set<int>(
847
77.2k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
77.3k
                        : 0);
849
77.3k
        break;
850
420
    case ExchangeType::BROADCAST:
851
420
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
420
                cur_pipe->num_tasks(), _num_instances,
853
420
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
420
                        ? cast_set<int>(
855
420
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
420
                        : 0);
857
420
        break;
858
2.19k
    case ExchangeType::PASS_TO_ONE:
859
2.19k
        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
848
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
848
                    cur_pipe->num_tasks(), _num_instances,
863
848
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
848
                            ? cast_set<int>(_runtime_state->query_options()
865
848
                                                    .local_exchange_free_blocks_limit)
866
848
                            : 0);
867
1.34k
        } else {
868
1.34k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.34k
                    cur_pipe->num_tasks(), _num_instances,
870
1.34k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.34k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.34k
                                                    .local_exchange_free_blocks_limit)
873
1.34k
                            : 0);
874
1.34k
        }
875
2.19k
        break;
876
860
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
860
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
860
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
860
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
860
                        ? cast_set<int>(
881
860
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
860
                        : 0);
883
860
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
91.4k
    }
888
91.5k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
91.5k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
91.5k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
91.5k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
892
893
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
894
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
895
896
    // 3.1 Initialize new pipeline's operator list.
897
91.5k
    std::copy(operators.begin(), operators.begin() + idx,
898
91.5k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
91.5k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
91.5k
    OperatorPtr source_op;
905
91.5k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
91.5k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
91.5k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
91.5k
    if (!operators.empty()) {
909
44.0k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
44.0k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
44.0k
    }
912
91.5k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
91.5k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
91.5k
    std::vector<PipelineId> edges_with_source;
917
108k
    for (auto child : cur_pipe->children()) {
918
108k
        bool found = false;
919
122k
        for (auto op : new_pip->operators()) {
920
122k
            if (child->sink()->node_id() == op->node_id()) {
921
12.0k
                new_pip->set_children(child);
922
12.0k
                found = true;
923
12.0k
            };
924
122k
        }
925
108k
        if (!found) {
926
96.4k
            new_children.push_back(child);
927
96.4k
            edges_with_source.push_back(child->id());
928
96.4k
        }
929
108k
    }
930
91.5k
    new_children.push_back(new_pip);
931
91.5k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
91.5k
    if (!new_pip->children().empty()) {
935
6.65k
        std::vector<PipelineId> edges_with_sink;
936
12.0k
        for (auto child : new_pip->children()) {
937
12.0k
            edges_with_sink.push_back(child->id());
938
12.0k
        }
939
6.65k
        _dag.insert({new_pip->id(), edges_with_sink});
940
6.65k
    }
941
91.5k
    cur_pipe->set_children(new_children);
942
91.5k
    _dag[downstream_pipeline_id] = edges_with_source;
943
91.5k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
91.5k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
91.5k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
91.5k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
91.5k
    return Status::OK();
950
91.5k
}
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
209k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
209k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
82.3k
        return Status::OK();
959
82.3k
    }
960
961
127k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
46.3k
        return Status::OK();
963
46.3k
    }
964
81.0k
    *do_local_exchange = true;
965
966
81.0k
    auto& operators = cur_pipe->operators();
967
81.0k
    auto total_op_num = operators.size();
968
81.0k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
81.0k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
81.0k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
81.0k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
81.0k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
177
            << "total_op_num: " << total_op_num
975
177
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
177
            << " 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
81.0k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
81.0k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
10.6k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
10.6k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
10.6k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
10.6k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
10.6k
                shuffle_idx_to_instance_idx));
990
10.6k
    }
991
81.0k
    return Status::OK();
992
81.0k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
379k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
953k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
574k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
574k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
162k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
162k
                if (child->sink()->node_id() ==
1003
162k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
131k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
131k
                }
1006
162k
            }
1007
148k
        }
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
574k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
574k
                                             bucket_seq_to_instance_idx,
1014
574k
                                             shuffle_idx_to_instance_idx));
1015
574k
    }
1016
379k
    return Status::OK();
1017
379k
}
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
572k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
572k
    int idx = 1;
1024
572k
    bool do_local_exchange = false;
1025
616k
    do {
1026
616k
        auto& ops = pip->operators();
1027
616k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
712k
        for (; idx < ops.size();) {
1030
139k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
122k
                RETURN_IF_ERROR(_add_local_exchange(
1032
122k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
122k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
122k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
122k
                        shuffle_idx_to_instance_idx));
1036
122k
            }
1037
139k
            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
44.1k
                idx = 2;
1043
44.1k
                break;
1044
44.1k
            }
1045
95.4k
            idx++;
1046
95.4k
        }
1047
616k
    } while (do_local_exchange);
1048
572k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
86.7k
        RETURN_IF_ERROR(_add_local_exchange(
1050
86.7k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
86.7k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
86.7k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
86.7k
    }
1054
572k
    return Status::OK();
1055
572k
}
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
382k
                                                  PipelineId cur_pipeline_id) {
1063
382k
    switch (thrift_sink.type) {
1064
160k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
160k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
160k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
160k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
160k
                params.destinations, _fragment_instance_ids);
1071
160k
        break;
1072
160k
    }
1073
181k
    case TDataSinkType::RESULT_SINK: {
1074
181k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
181k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
181k
        int child_node_id = pipeline->operators().back()->node_id();
1080
181k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
181k
                                                      row_desc, output_exprs,
1082
181k
                                                      thrift_sink.result_sink);
1083
181k
        break;
1084
181k
    }
1085
106
    case TDataSinkType::DICTIONARY_SINK: {
1086
106
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
106
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
106
                                                    thrift_sink.dictionary_sink);
1092
106
        break;
1093
106
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
28.9k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
28.9k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
28.9k
        int child_node_id = pipeline->operators().back()->node_id();
1098
28.9k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
28.9k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
28.9k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
70
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
70
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
28.8k
        } else {
1104
28.8k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
28.8k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
28.8k
        }
1107
28.9k
        break;
1108
0
    }
1109
165
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
165
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
165
        DCHECK(state->get_query_ctx() != nullptr);
1112
165
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
165
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
165
                                                                output_exprs);
1115
165
        break;
1116
0
    }
1117
0
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
0
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
0
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
0
                                                         output_exprs);
1123
0
        break;
1124
0
    }
1125
0
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
0
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
0
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
0
        } else {
1133
0
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
0
                                                                row_desc, output_exprs);
1135
0
        }
1136
0
        break;
1137
0
    }
1138
0
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
0
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
0
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
0
                                                             row_desc, output_exprs);
1144
0
        break;
1145
0
    }
1146
0
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
0
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
0
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
0
                                                            output_exprs);
1152
0
        break;
1153
0
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
0
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
0
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
0
        if (config::enable_java_support) {
1167
0
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
0
                                                             output_exprs);
1169
0
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
0
        break;
1175
0
    }
1176
3
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
338
    case TDataSinkType::RESULT_FILE_SINK: {
1186
338
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
338
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
338
        } else {
1196
338
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
338
                                                              output_exprs);
1198
338
        }
1199
338
        break;
1200
338
    }
1201
10.5k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
10.5k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
10.5k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
10.5k
        auto sink_id = next_sink_operator_id();
1205
10.5k
        const int multi_cast_node_id = sink_id;
1206
10.5k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
10.5k
        std::vector<int> sources;
1209
41.8k
        for (int i = 0; i < sender_size; ++i) {
1210
31.3k
            auto source_id = next_operator_id();
1211
31.3k
            sources.push_back(source_id);
1212
31.3k
        }
1213
1214
10.5k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
10.5k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
41.8k
        for (int i = 0; i < sender_size; ++i) {
1217
31.3k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
31.3k
            RowDescriptor* exchange_row_desc = nullptr;
1220
31.3k
            {
1221
31.3k
                const auto& tmp_row_desc =
1222
31.3k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
31.3k
                                ? RowDescriptor(state->desc_tbl(),
1224
31.3k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
31.3k
                                                         .output_tuple_id})
1226
31.3k
                                : row_desc;
1227
31.3k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
31.3k
            }
1229
31.3k
            auto source_id = sources[i];
1230
31.3k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
31.3k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
31.3k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
31.3k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
31.3k
                    /*operator_id=*/source_id);
1236
31.3k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
31.3k
                    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
31.3k
            DataSinkOperatorPtr sink_op;
1241
31.3k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
31.3k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
31.3k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
31.3k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
31.3k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
31.3k
            {
1248
31.3k
                TDataSink* t = pool->add(new TDataSink());
1249
31.3k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
31.3k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
31.3k
            }
1252
1253
            // 3. set dependency dag
1254
31.3k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
31.3k
        }
1256
10.5k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
10.5k
        break;
1260
10.5k
    }
1261
10.5k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
3
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
3
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
3
        break;
1268
3
    }
1269
0
    case TDataSinkType::TVF_TABLE_SINK: {
1270
0
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
0
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
0
                                                        output_exprs);
1275
0
        break;
1276
0
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
382k
    }
1280
381k
    return Status::OK();
1281
382k
}
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
683k
                                                 OperatorPtr& cache_op) {
1292
683k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
683k
    Defer defer = Defer([&]() {
1294
683k
        if (op) {
1295
683k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
683k
        }
1297
683k
        for (auto& s : sink_ops) {
1298
162k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
162k
        }
1300
683k
    });
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
683k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
683k
    std::stringstream error_msg;
1305
683k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
683k
    bool fe_with_old_version = false;
1308
683k
    switch (tnode.node_type) {
1309
163k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
163k
        op = std::make_shared<OlapScanOperatorX>(
1311
163k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
163k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
163k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
163k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
163k
        break;
1316
163k
    }
1317
75
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
75
        DCHECK(_query_ctx != nullptr);
1319
75
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
75
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
75
                                                    _num_instances);
1322
75
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
75
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
75
        break;
1325
75
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
2.65k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
2.65k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
2.65k
                                                 _num_instances);
1342
2.65k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
2.65k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
2.65k
        break;
1345
2.65k
    }
1346
189k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
189k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
189k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
189k
        DCHECK_GT(num_senders, 0);
1351
189k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
189k
                                                       num_senders);
1353
189k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
189k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
189k
        break;
1356
189k
    }
1357
181k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
181k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
181k
            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
181k
        bool need_create_cache_op =
1364
181k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
181k
        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
181k
        const bool group_by_limit_opt =
1385
181k
                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
181k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
181k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
181k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
181k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
181k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
181k
        const bool can_use_distinct_streaming_agg =
1396
181k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
181k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
181k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
181k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
181k
        if (can_use_distinct_streaming_agg) {
1402
92.1k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
92.0k
            } else {
1413
92.0k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
92.0k
                                                                     tnode, descs);
1415
92.0k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
92.0k
            }
1417
92.1k
        } else if (is_streaming_agg) {
1418
4.26k
            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
4.26k
            } else {
1428
4.26k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
4.26k
                                                             descs);
1430
4.26k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
4.26k
            }
1432
85.6k
        } else {
1433
            // create new pipeline to add query cache operator
1434
85.6k
            PipelinePtr new_pipe;
1435
85.6k
            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
85.6k
            if (enable_spill) {
1441
212
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
212
                                                                     next_operator_id(), descs);
1443
85.3k
            } else {
1444
85.3k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
85.3k
            }
1446
85.6k
            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
85.6k
            } else {
1451
85.6k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
85.6k
            }
1453
1454
85.6k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
85.6k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
74.5k
                _dag.insert({downstream_pipeline_id, {}});
1457
74.5k
            }
1458
85.6k
            cur_pipe = add_pipeline(cur_pipe);
1459
85.6k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
85.6k
            if (enable_spill) {
1462
212
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
212
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
85.3k
            } else {
1465
85.3k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
85.3k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
85.3k
            }
1468
85.6k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
85.6k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
85.6k
        }
1471
181k
        break;
1472
181k
    }
1473
181k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
74
        if (tnode.bucketed_agg_node.grouping_exprs.empty()) {
1475
0
            return Status::InternalError(
1476
0
                    "Bucketed aggregation node {} should not be used without group by keys",
1477
0
                    tnode.node_id);
1478
0
        }
1479
1480
        // Create source operator (goes on the current / downstream pipeline).
1481
74
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
74
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
74
        const auto downstream_pipeline_id = cur_pipe->id();
1486
74
        if (!_dag.contains(downstream_pipeline_id)) {
1487
74
            _dag.insert({downstream_pipeline_id, {}});
1488
74
        }
1489
74
        cur_pipe = add_pipeline(cur_pipe);
1490
74
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
74
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
74
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
74
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
74
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1497
1498
        // Pre-register a single shared state for ALL instances so that every
1499
        // sink instance writes its per-instance hash table into the same
1500
        // BucketedAggSharedState and every source instance can merge across
1501
        // all of them.
1502
74
        {
1503
74
            auto shared_state = BucketedAggSharedState::create_shared();
1504
74
            shared_state->id = op->operator_id();
1505
74
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
395
            for (int i = 0; i < _num_instances; i++) {
1508
321
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
321
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
321
                sink_dep->set_shared_state(shared_state.get());
1511
321
                shared_state->sink_deps.push_back(sink_dep);
1512
321
            }
1513
74
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
74
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
74
            _op_id_to_shared_state.insert(
1516
74
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
74
        }
1518
74
        break;
1519
74
    }
1520
9.04k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.04k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.04k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.04k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.04k
        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
9.04k
        } else {
1566
9.04k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.04k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.04k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.04k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.24k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.24k
            }
1573
9.04k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.04k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.04k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.04k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.04k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.04k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.04k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.04k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.04k
        }
1584
9.04k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.32k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.32k
                    HashJoinSharedState::create_shared(_num_instances);
1587
13.5k
            for (int i = 0; i < _num_instances; i++) {
1588
11.1k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
11.1k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
11.1k
                sink_dep->set_shared_state(shared_state.get());
1591
11.1k
                shared_state->sink_deps.push_back(sink_dep);
1592
11.1k
            }
1593
2.32k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.32k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.32k
            _op_id_to_shared_state.insert(
1596
2.32k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.32k
        }
1598
9.04k
        break;
1599
9.04k
    }
1600
22.2k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
22.2k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
22.2k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
22.2k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
22.2k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
22.0k
            _dag.insert({downstream_pipeline_id, {}});
1607
22.0k
        }
1608
22.2k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
22.2k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
22.2k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
22.2k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
22.2k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
22.2k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
22.2k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
22.2k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
22.2k
        break;
1618
22.2k
    }
1619
49.6k
    case TPlanNodeType::UNION_NODE: {
1620
49.6k
        int child_count = tnode.num_children;
1621
49.6k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
49.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
49.6k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
49.6k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
49.3k
            _dag.insert({downstream_pipeline_id, {}});
1627
49.3k
        }
1628
50.6k
        for (int i = 0; i < child_count; i++) {
1629
1.02k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.02k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.02k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.02k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.02k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.02k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.02k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.02k
        }
1638
49.6k
        break;
1639
49.6k
    }
1640
49.6k
    case TPlanNodeType::SORT_NODE: {
1641
42.4k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
42.4k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
42.4k
        const bool use_local_merge =
1644
42.4k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
42.4k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
42.3k
        } else if (use_local_merge) {
1648
40.6k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
40.6k
                                                                 descs);
1650
40.6k
        } else {
1651
1.78k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
1.78k
        }
1653
42.4k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
42.4k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
42.4k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
42.3k
            _dag.insert({downstream_pipeline_id, {}});
1658
42.3k
        }
1659
42.4k
        cur_pipe = add_pipeline(cur_pipe);
1660
42.4k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
42.4k
        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
42.3k
        } else {
1666
42.3k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
42.3k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
42.3k
        }
1669
42.4k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
42.4k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
42.4k
        break;
1672
42.4k
    }
1673
42.4k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
63
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
63
        const auto downstream_pipeline_id = cur_pipe->id();
1678
63
        if (!_dag.contains(downstream_pipeline_id)) {
1679
63
            _dag.insert({downstream_pipeline_id, {}});
1680
63
        }
1681
63
        cur_pipe = add_pipeline(cur_pipe);
1682
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
63
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
63
        break;
1689
63
    }
1690
1.52k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.52k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.52k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.52k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.52k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.50k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.50k
        }
1698
1.52k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.52k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.52k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.52k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.52k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.52k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.52k
        break;
1706
1.52k
    }
1707
1.52k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
675
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
675
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
675
        break;
1711
675
    }
1712
675
    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
314
    case TPlanNodeType::REPEAT_NODE: {
1723
314
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
314
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
314
        break;
1726
314
    }
1727
910
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
910
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
910
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
910
        break;
1731
910
    }
1732
910
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
18
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
18
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
18
        break;
1736
18
    }
1737
1.74k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.74k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.74k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.74k
        break;
1741
1.74k
    }
1742
1.74k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
269
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
269
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
269
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
269
        break;
1747
269
    }
1748
1.53k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.53k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.53k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.53k
        break;
1752
1.53k
    }
1753
4.74k
    case TPlanNodeType::META_SCAN_NODE: {
1754
4.74k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
4.74k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
4.74k
        break;
1757
4.74k
    }
1758
10.4k
    case TPlanNodeType::SELECT_NODE: {
1759
10.4k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
10.4k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
10.4k
        break;
1762
10.4k
    }
1763
10.4k
    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
683k
    }
1803
682k
    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
682k
    return Status::OK();
1809
683k
}
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
379k
Status PipelineFragmentContext::submit() {
1846
379k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
379k
    _submitted = true;
1850
1851
379k
    int submit_tasks = 0;
1852
379k
    Status st;
1853
379k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
955k
    for (auto& task : _tasks) {
1855
1.61M
        for (auto& t : task) {
1856
1.61M
            st = scheduler->submit(t.first);
1857
1.61M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.61M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.61M
            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
1.61M
            submit_tasks++;
1866
1.61M
        }
1867
955k
    }
1868
379k
    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
379k
    } else {
1883
379k
        return st;
1884
379k
    }
1885
379k
}
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
382k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
382k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
382k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
382k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
382k
    if (!_need_notify_close) {
1919
378k
        auto st = send_report(true);
1920
378k
        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
378k
    }
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
382k
    if (_runtime_state->enable_profile() &&
1931
382k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.10k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.10k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1934
0
        std::stringstream ss;
1935
        // Compute the _local_time_percent before pretty_print the runtime_profile
1936
        // Before add this operation, the print out like that:
1937
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1938
        // After add the operation, the print out like that:
1939
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1940
        // We can easily know the exec node execute time without child time consumed.
1941
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1942
0
            runtime_profile_ptr->pretty_print(&ss);
1943
0
        }
1944
1945
0
        if (_runtime_state->load_channel_profile()) {
1946
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1947
0
        }
1948
1949
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1950
0
    }
1951
1952
382k
    if (_query_ctx->enable_profile()) {
1953
2.10k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.10k
                                         collect_realtime_load_channel_profile());
1955
2.10k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
382k
    return !_need_notify_close;
1960
382k
}
1961
1962
1.61M
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
1.61M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.61M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
667k
        if (_dag.contains(pipeline_id)) {
1967
377k
            for (auto dep : _dag[pipeline_id]) {
1968
377k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
377k
            }
1970
316k
        }
1971
667k
    }
1972
1.61M
    bool need_remove = false;
1973
1.61M
    {
1974
1.61M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.61M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.61M
        _query_ctx->inc_finished_task_num();
1978
1.61M
        if (_closed_tasks >= _total_tasks) {
1979
382k
            need_remove = _close_fragment_instance();
1980
382k
        }
1981
1.61M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.61M
    if (need_remove) {
1984
378k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
378k
    }
1986
1.61M
}
1987
1988
41.4k
std::string PipelineFragmentContext::get_load_error_url() {
1989
41.4k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1990
0
        return to_load_error_http_path(str);
1991
0
    }
1992
87.8k
    for (auto& tasks : _tasks) {
1993
148k
        for (auto& task : tasks) {
1994
148k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
164
                return to_load_error_http_path(str);
1996
164
            }
1997
148k
        }
1998
87.8k
    }
1999
41.2k
    return "";
2000
41.4k
}
2001
2002
41.4k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
41.4k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
87.8k
    for (auto& tasks : _tasks) {
2007
148k
        for (auto& task : tasks) {
2008
148k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
164
                return str;
2010
164
            }
2011
148k
        }
2012
87.8k
    }
2013
41.2k
    return "";
2014
41.4k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
36.6k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
36.6k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
36.6k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
36.6k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
36.6k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
36.6k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
36.6k
    });
2031
2032
36.6k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
36.6k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
36.6k
    int callback_retries = 10;
2038
36.6k
    const int sleep_ms = 1000;
2039
36.6k
    Status exec_status = req.status;
2040
36.6k
    Status coord_status;
2041
36.6k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
36.6k
    do {
2043
36.6k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
36.6k
                                                            req.coord_addr, &coord_status);
2045
36.6k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
36.6k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
36.6k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
36.6k
    TReportExecStatusParams params;
2059
36.6k
    params.protocol_version = FrontendServiceVersion::V1;
2060
36.6k
    params.__set_query_id(req.query_id);
2061
36.6k
    params.__set_backend_num(req.backend_num);
2062
36.6k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
36.6k
    params.__set_fragment_id(req.fragment_id);
2064
36.6k
    params.__set_status(exec_status.to_thrift());
2065
36.6k
    params.__set_done(req.done);
2066
36.6k
    params.__set_query_type(req.runtime_state->query_type());
2067
36.6k
    params.__isset.profile = false;
2068
2069
36.6k
    DCHECK(req.runtime_state != nullptr);
2070
2071
36.6k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
32.9k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
32.9k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
32.9k
    } else {
2075
3.67k
        DCHECK(!req.runtime_states.empty());
2076
3.67k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
3.67k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
3.67k
    }
2086
2087
36.6k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
36.6k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
36.6k
    static std::string s_unselected_rows = "unselected.rows";
2090
36.6k
    int64_t num_rows_load_success = 0;
2091
36.6k
    int64_t num_rows_load_filtered = 0;
2092
36.6k
    int64_t num_rows_load_unselected = 0;
2093
36.6k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
36.6k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
36.6k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
36.6k
    } else if (!req.runtime_states.empty()) {
2109
100k
        for (auto* rs : req.runtime_states) {
2110
100k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
100k
                rs->num_finished_range() > 0) {
2112
30.2k
                params.__isset.load_counters = true;
2113
30.2k
                num_rows_load_success += rs->num_rows_load_success();
2114
30.2k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
30.2k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
30.2k
                params.__isset.fragment_instance_reports = true;
2117
30.2k
                TFragmentInstanceReport t;
2118
30.2k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
30.2k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
30.2k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
30.2k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
30.2k
                params.fragment_instance_reports.push_back(t);
2123
30.2k
            }
2124
100k
        }
2125
36.5k
    }
2126
36.6k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
36.6k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
36.6k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
36.6k
    if (!req.load_error_url.empty()) {
2131
148
        params.__set_tracking_url(req.load_error_url);
2132
148
    }
2133
36.6k
    if (!req.first_error_msg.empty()) {
2134
148
        params.__set_first_error_msg(req.first_error_msg);
2135
148
    }
2136
100k
    for (auto* rs : req.runtime_states) {
2137
100k
        if (rs->wal_id() > 0) {
2138
112
            params.__set_txn_id(rs->wal_id());
2139
112
            params.__set_label(rs->import_label());
2140
112
        }
2141
100k
    }
2142
36.6k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
36.6k
    } else if (!req.runtime_states.empty()) {
2146
100k
        for (auto* rs : req.runtime_states) {
2147
100k
            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
100k
        }
2154
36.5k
    }
2155
36.6k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
36.6k
    } else if (!req.runtime_states.empty()) {
2159
100k
        for (auto* rs : req.runtime_states) {
2160
100k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
25.0k
                params.__isset.commitInfos = true;
2162
25.0k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
25.0k
            }
2164
100k
        }
2165
36.5k
    }
2166
36.6k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
36.6k
    } else if (!req.runtime_states.empty()) {
2170
100k
        for (auto* rs : req.runtime_states) {
2171
100k
            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
100k
        }
2177
36.5k
    }
2178
36.6k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
36.6k
    } else if (!req.runtime_states.empty()) {
2183
100k
        for (auto* rs : req.runtime_states) {
2184
100k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
0
                params.__isset.hive_partition_updates = true;
2186
0
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
0
                                                     rs_hpu.begin(), rs_hpu.end());
2188
0
            }
2189
100k
        }
2190
36.5k
    }
2191
36.6k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
36.6k
    } else if (!req.runtime_states.empty()) {
2196
100k
        for (auto* rs : req.runtime_states) {
2197
100k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
0
                params.__isset.iceberg_commit_datas = true;
2199
0
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
0
                                                   rs_icd.begin(), rs_icd.end());
2201
0
            }
2202
100k
        }
2203
36.5k
    }
2204
2205
36.6k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
36.6k
    } else if (!req.runtime_states.empty()) {
2209
100k
        for (auto* rs : req.runtime_states) {
2210
100k
            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
100k
        }
2216
36.5k
    }
2217
2218
36.6k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
36.6k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
36.6k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
36.5k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
36.5k
    }
2224
2225
36.6k
    TReportExecStatusResult res;
2226
36.6k
    Status rpc_status;
2227
2228
36.6k
    VLOG_DEBUG << "reportExecStatus params is "
2229
10
               << apache::thrift::ThriftDebugString(params).c_str();
2230
36.6k
    if (!exec_status.ok()) {
2231
1.52k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.52k
                     << " to coordinator: " << req.coord_addr
2233
1.52k
                     << ", query id: " << print_id(req.query_id);
2234
1.52k
    }
2235
36.6k
    try {
2236
36.6k
        try {
2237
36.6k
            (*coord)->reportExecStatus(res, params);
2238
36.6k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
36.5k
        rpc_status = Status::create<false>(res.status);
2254
36.5k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
36.5k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
36.5k
}
2265
2266
382k
Status PipelineFragmentContext::send_report(bool done) {
2267
382k
    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
382k
    if (!_is_report_success && done && exec_status.ok()) {
2273
345k
        return Status::OK();
2274
345k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
36.6k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
79
        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
79
            return Status::OK();
2286
79
        }
2287
0
        return Status::NeedSendAgain("");
2288
79
    }
2289
2290
36.5k
    std::vector<RuntimeState*> runtime_states;
2291
2292
69.1k
    for (auto& tasks : _tasks) {
2293
100k
        for (auto& task : tasks) {
2294
100k
            runtime_states.push_back(task.second.get());
2295
100k
        }
2296
69.1k
    }
2297
2298
36.5k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
36.5k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
36.5k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
36.5k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
36.5k
    ReportStatusRequest req {.status = exec_status,
2306
36.5k
                             .runtime_states = runtime_states,
2307
36.5k
                             .done = done || !exec_status.ok(),
2308
36.5k
                             .coord_addr = _query_ctx->coord_addr,
2309
36.5k
                             .query_id = _query_id,
2310
36.5k
                             .fragment_id = _fragment_id,
2311
36.5k
                             .fragment_instance_id = TUniqueId(),
2312
36.5k
                             .backend_num = -1,
2313
36.5k
                             .runtime_state = _runtime_state.get(),
2314
36.5k
                             .load_error_url = load_eror_url,
2315
36.5k
                             .first_error_msg = first_error_msg,
2316
36.5k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
36.5k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
36.6k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
36.6k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
36.6k
        _coordinator_callback(req);
2321
36.6k
        if (!req.done) {
2322
3.60k
            ctx->refresh_next_report_time();
2323
3.60k
        }
2324
36.6k
    });
2325
36.6k
}
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
65
std::string PipelineFragmentContext::debug_string() {
2365
65
    std::lock_guard<std::mutex> l(_task_mutex);
2366
65
    fmt::memory_buffer debug_string_buffer;
2367
65
    fmt::format_to(debug_string_buffer,
2368
65
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
65
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
65
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
424
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
359
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
1.23k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
874
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
874
                           _tasks[j][i].first->debug_string());
2376
874
        }
2377
359
    }
2378
2379
65
    return fmt::to_string(debug_string_buffer);
2380
65
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.10k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.10k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2385
2386
    // we do not have mutex to protect pipeline_id_to_profile
2387
    // so we need to make sure this funciton is invoked after fragment context
2388
    // has already been prepared.
2389
2.10k
    if (!_prepared) {
2390
0
        std::string msg =
2391
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2392
0
        DCHECK(false) << msg;
2393
0
        LOG_ERROR(msg);
2394
0
        return res;
2395
0
    }
2396
2397
    // Make sure first profile is fragment level profile
2398
2.10k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.10k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.10k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
3.92k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
3.92k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
3.92k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
3.92k
        res.push_back(profile_ptr);
2407
3.92k
    }
2408
2409
2.10k
    return res;
2410
2.10k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.10k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2414
    // we do not have mutex to protect pipeline_id_to_profile
2415
    // so we need to make sure this funciton is invoked after fragment context
2416
    // has already been prepared.
2417
2.10k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
5.15k
    for (const auto& tasks : _tasks) {
2426
10.4k
        for (const auto& task : tasks) {
2427
10.4k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
10.4k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
10.4k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
10.4k
                                                           _runtime_state->profile_level());
2435
10.4k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
10.4k
        }
2437
5.15k
    }
2438
2439
2.10k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.10k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.10k
                                                      _runtime_state->profile_level());
2442
2.10k
    return load_channel_profile;
2443
2.10k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
6.74k
    for (const auto& _task : _tasks) {
2455
11.6k
        for (const auto& task : _task) {
2456
11.6k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
11.6k
            result.merge(set);
2458
11.6k
        }
2459
6.74k
    }
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
383k
void PipelineFragmentContext::_release_resource() {
2468
383k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
383k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
383k
    auto st = _query_ctx->exec_status();
2472
957k
    for (auto& _task : _tasks) {
2473
957k
        if (!_task.empty()) {
2474
957k
            _call_back(_task.front().first->runtime_state(), &st);
2475
957k
        }
2476
957k
    }
2477
383k
    _tasks.clear();
2478
383k
    _dag.clear();
2479
383k
    _pip_id_to_pipeline.clear();
2480
383k
    _pipelines.clear();
2481
383k
    _sink.reset();
2482
383k
    _root_op.reset();
2483
383k
    _runtime_filter_mgr_map.clear();
2484
383k
    _op_id_to_shared_state.clear();
2485
383k
}
2486
2487
} // namespace doris