Coverage Report

Created: 2026-04-16 08:03

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
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//
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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/PaloInternalService_types.h>
22
#include <gen_cpp/PlanNodes_types.h>
23
#include <pthread.h>
24
25
#include <algorithm>
26
#include <cstdlib>
27
// IWYU pragma: no_include <bits/chrono.h>
28
#include <fmt/format.h>
29
30
#include <chrono> // IWYU pragma: keep
31
#include <map>
32
#include <memory>
33
#include <ostream>
34
#include <utility>
35
36
#include "cloud/config.h"
37
#include "common/cast_set.h"
38
#include "common/config.h"
39
#include "common/exception.h"
40
#include "common/logging.h"
41
#include "common/status.h"
42
#include "exec/exchange/local_exchange_sink_operator.h"
43
#include "exec/exchange/local_exchange_source_operator.h"
44
#include "exec/exchange/local_exchanger.h"
45
#include "exec/exchange/vdata_stream_mgr.h"
46
#include "exec/operator/aggregation_sink_operator.h"
47
#include "exec/operator/aggregation_source_operator.h"
48
#include "exec/operator/analytic_sink_operator.h"
49
#include "exec/operator/analytic_source_operator.h"
50
#include "exec/operator/assert_num_rows_operator.h"
51
#include "exec/operator/blackhole_sink_operator.h"
52
#include "exec/operator/cache_sink_operator.h"
53
#include "exec/operator/cache_source_operator.h"
54
#include "exec/operator/datagen_operator.h"
55
#include "exec/operator/dict_sink_operator.h"
56
#include "exec/operator/distinct_streaming_aggregation_operator.h"
57
#include "exec/operator/empty_set_operator.h"
58
#include "exec/operator/es_scan_operator.h"
59
#include "exec/operator/exchange_sink_operator.h"
60
#include "exec/operator/exchange_source_operator.h"
61
#include "exec/operator/file_scan_operator.h"
62
#include "exec/operator/group_commit_block_sink_operator.h"
63
#include "exec/operator/group_commit_scan_operator.h"
64
#include "exec/operator/hashjoin_build_sink.h"
65
#include "exec/operator/hashjoin_probe_operator.h"
66
#include "exec/operator/hive_table_sink_operator.h"
67
#include "exec/operator/iceberg_delete_sink_operator.h"
68
#include "exec/operator/iceberg_merge_sink_operator.h"
69
#include "exec/operator/iceberg_table_sink_operator.h"
70
#include "exec/operator/jdbc_scan_operator.h"
71
#include "exec/operator/jdbc_table_sink_operator.h"
72
#include "exec/operator/local_merge_sort_source_operator.h"
73
#include "exec/operator/materialization_opertor.h"
74
#include "exec/operator/maxcompute_table_sink_operator.h"
75
#include "exec/operator/memory_scratch_sink_operator.h"
76
#include "exec/operator/meta_scan_operator.h"
77
#include "exec/operator/multi_cast_data_stream_sink.h"
78
#include "exec/operator/multi_cast_data_stream_source.h"
79
#include "exec/operator/nested_loop_join_build_operator.h"
80
#include "exec/operator/nested_loop_join_probe_operator.h"
81
#include "exec/operator/olap_scan_operator.h"
82
#include "exec/operator/olap_table_sink_operator.h"
83
#include "exec/operator/olap_table_sink_v2_operator.h"
84
#include "exec/operator/partition_sort_sink_operator.h"
85
#include "exec/operator/partition_sort_source_operator.h"
86
#include "exec/operator/partitioned_aggregation_sink_operator.h"
87
#include "exec/operator/partitioned_aggregation_source_operator.h"
88
#include "exec/operator/partitioned_hash_join_probe_operator.h"
89
#include "exec/operator/partitioned_hash_join_sink_operator.h"
90
#include "exec/operator/rec_cte_anchor_sink_operator.h"
91
#include "exec/operator/rec_cte_scan_operator.h"
92
#include "exec/operator/rec_cte_sink_operator.h"
93
#include "exec/operator/rec_cte_source_operator.h"
94
#include "exec/operator/repeat_operator.h"
95
#include "exec/operator/result_file_sink_operator.h"
96
#include "exec/operator/result_sink_operator.h"
97
#include "exec/operator/schema_scan_operator.h"
98
#include "exec/operator/select_operator.h"
99
#include "exec/operator/set_probe_sink_operator.h"
100
#include "exec/operator/set_sink_operator.h"
101
#include "exec/operator/set_source_operator.h"
102
#include "exec/operator/sort_sink_operator.h"
103
#include "exec/operator/sort_source_operator.h"
104
#include "exec/operator/spill_iceberg_table_sink_operator.h"
105
#include "exec/operator/spill_sort_sink_operator.h"
106
#include "exec/operator/spill_sort_source_operator.h"
107
#include "exec/operator/streaming_aggregation_operator.h"
108
#include "exec/operator/table_function_operator.h"
109
#include "exec/operator/tvf_table_sink_operator.h"
110
#include "exec/operator/union_sink_operator.h"
111
#include "exec/operator/union_source_operator.h"
112
#include "exec/pipeline/dependency.h"
113
#include "exec/pipeline/pipeline_task.h"
114
#include "exec/pipeline/task_scheduler.h"
115
#include "exec/runtime_filter/runtime_filter_mgr.h"
116
#include "exec/sort/topn_sorter.h"
117
#include "exec/spill/spill_file.h"
118
#include "io/fs/stream_load_pipe.h"
119
#include "load/stream_load/new_load_stream_mgr.h"
120
#include "runtime/exec_env.h"
121
#include "runtime/fragment_mgr.h"
122
#include "runtime/result_buffer_mgr.h"
123
#include "runtime/runtime_state.h"
124
#include "runtime/thread_context.h"
125
#include "util/countdown_latch.h"
126
#include "util/debug_util.h"
127
#include "util/uid_util.h"
128
129
namespace doris {
130
PipelineFragmentContext::PipelineFragmentContext(
131
        TUniqueId query_id, const TPipelineFragmentParams& request,
132
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
133
        const std::function<void(RuntimeState*, Status*)>& call_back,
134
        report_status_callback report_status_cb)
135
435k
        : _query_id(std::move(query_id)),
136
435k
          _fragment_id(request.fragment_id),
137
435k
          _exec_env(exec_env),
138
435k
          _query_ctx(std::move(query_ctx)),
139
435k
          _call_back(call_back),
140
435k
          _is_report_on_cancel(true),
141
435k
          _report_status_cb(std::move(report_status_cb)),
142
435k
          _params(request),
143
435k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
144
435k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
145
435k
                                                               : false) {
146
435k
    _fragment_watcher.start();
147
435k
}
148
149
435k
PipelineFragmentContext::~PipelineFragmentContext() {
150
435k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
151
435k
            .tag("query_id", print_id(_query_id))
152
435k
            .tag("fragment_id", _fragment_id);
153
435k
    _release_resource();
154
435k
    {
155
        // The memory released by the query end is recorded in the query mem tracker.
156
435k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
157
435k
        _runtime_state.reset();
158
435k
        _query_ctx.reset();
159
435k
    }
160
435k
}
161
162
71
bool PipelineFragmentContext::is_timeout(timespec now) const {
163
71
    if (_timeout <= 0) {
164
0
        return false;
165
0
    }
166
71
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
167
71
}
168
169
// notify_close() transitions the PFC from "waiting for external close notification" to
170
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
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// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
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9.38k
bool PipelineFragmentContext::notify_close() {
174
9.38k
    bool all_closed = false;
175
9.38k
    bool need_remove = false;
176
9.38k
    {
177
9.38k
        std::lock_guard<std::mutex> l(_task_mutex);
178
9.38k
        if (_closed_tasks >= _total_tasks) {
179
3.34k
            if (_need_notify_close) {
180
                // Fragment was cancelled and waiting for notify to close.
181
                // Record that we need to remove from fragment mgr, but do it
182
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
184
                // first, then _task_mutex via debug_string()).
185
3.26k
                need_remove = true;
186
3.26k
            }
187
3.34k
            all_closed = true;
188
3.34k
        }
189
        // make fragment release by self after cancel
190
9.38k
        _need_notify_close = false;
191
9.38k
    }
192
9.38k
    if (need_remove) {
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3.26k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
194
3.26k
    }
195
9.38k
    return all_closed;
196
9.38k
}
197
198
// Must not add lock in this method. Because it will call query ctx cancel. And
199
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
200
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
202
6.03k
void PipelineFragmentContext::cancel(const Status reason) {
203
6.03k
    LOG_INFO("PipelineFragmentContext::cancel")
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6.03k
            .tag("query_id", print_id(_query_id))
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6.03k
            .tag("fragment_id", _fragment_id)
206
6.03k
            .tag("reason", reason.to_string());
207
6.03k
    if (notify_close()) {
208
102
        return;
209
102
    }
210
    // Timeout is a special error code, we need print current stack to debug timeout issue.
211
5.93k
    if (reason.is<ErrorCode::TIMEOUT>()) {
212
17
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
213
17
                                   debug_string());
214
17
        LOG_LONG_STRING(WARNING, dbg_str);
215
17
    }
216
217
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
218
5.93k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
219
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
220
0
                    debug_string());
221
0
    }
222
223
5.93k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
224
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
225
0
    }
226
227
5.93k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
228
24
        _query_ctx->set_load_error_url(error_url);
229
24
    }
230
231
5.93k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
232
24
        _query_ctx->set_first_error_msg(first_error_msg);
233
24
    }
234
235
5.93k
    _query_ctx->cancel(reason, _fragment_id);
236
5.93k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
237
618
        _is_report_on_cancel = false;
238
5.31k
    } else {
239
20.7k
        for (auto& id : _fragment_instance_ids) {
240
20.7k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
241
20.7k
        }
242
5.31k
    }
243
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
244
    // For stream load the fragment's query_id == load id, it is set in FE.
245
5.93k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
246
5.93k
    if (stream_load_ctx != nullptr) {
247
32
        stream_load_ctx->pipe->cancel(reason.to_string());
248
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
249
        // We need to set the error URL at this point to ensure error information is properly
250
        // propagated to the client.
251
32
        stream_load_ctx->error_url = get_load_error_url();
252
32
        stream_load_ctx->first_error_msg = get_first_error_msg();
253
32
    }
254
255
22.2k
    for (auto& tasks : _tasks) {
256
51.4k
        for (auto& task : tasks) {
257
51.4k
            task.first->unblock_all_dependencies();
258
51.4k
        }
259
22.2k
    }
260
5.93k
}
261
262
677k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
263
677k
    PipelineId id = _next_pipeline_id++;
264
677k
    auto pipeline = std::make_shared<Pipeline>(
265
677k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
266
677k
            parent ? parent->num_tasks() : _num_instances);
267
677k
    if (idx >= 0) {
268
110k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
269
567k
    } else {
270
567k
        _pipelines.emplace_back(pipeline);
271
567k
    }
272
677k
    if (parent) {
273
236k
        parent->set_children(pipeline);
274
236k
    }
275
677k
    return pipeline;
276
677k
}
277
278
435k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
279
435k
    {
280
435k
        SCOPED_TIMER(_build_pipelines_timer);
281
        // 2. Build pipelines with operators in this fragment.
282
435k
        auto root_pipeline = add_pipeline();
283
435k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
284
435k
                                         &_root_op, root_pipeline));
285
286
        // 3. Create sink operator
287
435k
        if (!_params.fragment.__isset.output_sink) {
288
0
            return Status::InternalError("No output sink in this fragment!");
289
0
        }
290
435k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
291
435k
                                          _params.fragment.output_exprs, _params,
292
435k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
293
435k
                                          *_desc_tbl, root_pipeline->id()));
294
435k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
295
435k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
296
297
566k
        for (PipelinePtr& pipeline : _pipelines) {
298
18.4E
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
299
566k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
300
566k
        }
301
435k
    }
302
    // 4. Build local exchanger
303
435k
    if (_runtime_state->enable_local_shuffle()) {
304
432k
        SCOPED_TIMER(_plan_local_exchanger_timer);
305
432k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
306
432k
                                             _params.bucket_seq_to_instance_idx,
307
432k
                                             _params.shuffle_idx_to_instance_idx));
308
432k
    }
309
310
    // 5. Initialize global states in pipelines.
311
678k
    for (PipelinePtr& pipeline : _pipelines) {
312
678k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
313
678k
        pipeline->children().clear();
314
678k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
315
678k
    }
316
317
433k
    {
318
433k
        SCOPED_TIMER(_build_tasks_timer);
319
        // 6. Build pipeline tasks and initialize local state.
320
433k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
321
433k
    }
322
323
433k
    return Status::OK();
324
433k
}
325
326
435k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
327
435k
    if (_prepared) {
328
0
        return Status::InternalError("Already prepared");
329
0
    }
330
435k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
331
435k
        _timeout = _params.query_options.execution_timeout;
332
435k
    }
333
334
435k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
335
435k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
336
435k
    SCOPED_TIMER(_prepare_timer);
337
435k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
338
435k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
339
435k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
340
435k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
341
435k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
342
435k
    {
343
435k
        SCOPED_TIMER(_init_context_timer);
344
435k
        cast_set(_num_instances, _params.local_params.size());
345
435k
        _total_instances =
346
435k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
347
348
435k
        auto* fragment_context = this;
349
350
435k
        if (_params.query_options.__isset.is_report_success) {
351
434k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
352
434k
        }
353
354
        // 1. Set up the global runtime state.
355
435k
        _runtime_state = RuntimeState::create_unique(
356
435k
                _params.query_id, _params.fragment_id, _params.query_options,
357
435k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
358
435k
        _runtime_state->set_task_execution_context(shared_from_this());
359
435k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
360
435k
        if (_params.__isset.backend_id) {
361
432k
            _runtime_state->set_backend_id(_params.backend_id);
362
432k
        }
363
435k
        if (_params.__isset.import_label) {
364
236
            _runtime_state->set_import_label(_params.import_label);
365
236
        }
366
435k
        if (_params.__isset.db_name) {
367
188
            _runtime_state->set_db_name(_params.db_name);
368
188
        }
369
435k
        if (_params.__isset.load_job_id) {
370
0
            _runtime_state->set_load_job_id(_params.load_job_id);
371
0
        }
372
373
435k
        if (_params.is_simplified_param) {
374
147k
            _desc_tbl = _query_ctx->desc_tbl;
375
287k
        } else {
376
287k
            DCHECK(_params.__isset.desc_tbl);
377
287k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
378
287k
                                                  &_desc_tbl));
379
287k
        }
380
435k
        _runtime_state->set_desc_tbl(_desc_tbl);
381
435k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
382
435k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
383
435k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
384
435k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
385
386
        // init fragment_instance_ids
387
435k
        const auto target_size = _params.local_params.size();
388
435k
        _fragment_instance_ids.resize(target_size);
389
1.65M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
390
1.22M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
391
1.22M
            _fragment_instance_ids[i] = fragment_instance_id;
392
1.22M
        }
393
435k
    }
394
395
435k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
396
397
434k
    _init_next_report_time();
398
399
434k
    _prepared = true;
400
434k
    return Status::OK();
401
435k
}
402
403
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
404
        int instance_idx,
405
1.21M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
406
1.21M
    const auto& local_params = _params.local_params[instance_idx];
407
1.21M
    auto fragment_instance_id = local_params.fragment_instance_id;
408
1.21M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
409
1.21M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
410
1.21M
    auto get_shared_state = [&](PipelinePtr pipeline)
411
1.21M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
412
2.06M
                                       std::vector<std::shared_ptr<Dependency>>>> {
413
2.06M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
414
2.06M
                                std::vector<std::shared_ptr<Dependency>>>>
415
2.06M
                shared_state_map;
416
2.64M
        for (auto& op : pipeline->operators()) {
417
2.64M
            auto source_id = op->operator_id();
418
2.64M
            if (auto iter = _op_id_to_shared_state.find(source_id);
419
2.64M
                iter != _op_id_to_shared_state.end()) {
420
787k
                shared_state_map.insert({source_id, iter->second});
421
787k
            }
422
2.64M
        }
423
2.06M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
424
2.06M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
425
2.06M
                iter != _op_id_to_shared_state.end()) {
426
303k
                shared_state_map.insert({sink_to_source_id, iter->second});
427
303k
            }
428
2.06M
        }
429
2.06M
        return shared_state_map;
430
2.06M
    };
431
432
3.75M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
433
2.54M
        auto& pipeline = _pipelines[pip_idx];
434
2.54M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
435
2.05M
            auto task_runtime_state = RuntimeState::create_unique(
436
2.05M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
437
2.05M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
438
2.05M
            {
439
                // Initialize runtime state for this task
440
2.05M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
441
442
2.05M
                task_runtime_state->set_task_execution_context(shared_from_this());
443
2.05M
                task_runtime_state->set_be_number(local_params.backend_num);
444
445
2.05M
                if (_params.__isset.backend_id) {
446
2.05M
                    task_runtime_state->set_backend_id(_params.backend_id);
447
2.05M
                }
448
2.05M
                if (_params.__isset.import_label) {
449
237
                    task_runtime_state->set_import_label(_params.import_label);
450
237
                }
451
2.05M
                if (_params.__isset.db_name) {
452
189
                    task_runtime_state->set_db_name(_params.db_name);
453
189
                }
454
2.05M
                if (_params.__isset.load_job_id) {
455
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
456
0
                }
457
2.05M
                if (_params.__isset.wal_id) {
458
112
                    task_runtime_state->set_wal_id(_params.wal_id);
459
112
                }
460
2.05M
                if (_params.__isset.content_length) {
461
31
                    task_runtime_state->set_content_length(_params.content_length);
462
31
                }
463
464
2.05M
                task_runtime_state->set_desc_tbl(_desc_tbl);
465
2.05M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
466
2.05M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
467
2.05M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
468
2.05M
                task_runtime_state->set_max_operator_id(max_operator_id());
469
2.05M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
470
2.05M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
471
2.05M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
472
473
2.05M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
474
2.05M
            }
475
2.05M
            auto cur_task_id = _total_tasks++;
476
2.05M
            task_runtime_state->set_task_id(cur_task_id);
477
2.05M
            task_runtime_state->set_task_num(pipeline->num_tasks());
478
2.05M
            auto task = std::make_shared<PipelineTask>(
479
2.05M
                    pipeline, cur_task_id, task_runtime_state.get(),
480
2.05M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
481
2.05M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
482
2.05M
                    instance_idx);
483
2.05M
            pipeline->incr_created_tasks(instance_idx, task.get());
484
2.05M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
485
2.05M
            _tasks[instance_idx].emplace_back(
486
2.05M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
487
2.05M
                            std::move(task), std::move(task_runtime_state)});
488
2.05M
        }
489
2.54M
    }
490
491
    /**
492
         * Build DAG for pipeline tasks.
493
         * For example, we have
494
         *
495
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
496
         *            \                      /
497
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
498
         *                 \                          /
499
         *               JoinProbeOperator2 (Pipeline1)
500
         *
501
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
502
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
503
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
504
         *
505
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
506
         * and JoinProbeOperator2.
507
         */
508
2.54M
    for (auto& _pipeline : _pipelines) {
509
2.54M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
510
2.05M
            auto* task = pipeline_id_to_task[_pipeline->id()];
511
2.05M
            DCHECK(task != nullptr);
512
513
            // If this task has upstream dependency, then inject it into this task.
514
2.05M
            if (_dag.contains(_pipeline->id())) {
515
1.32M
                auto& deps = _dag[_pipeline->id()];
516
2.08M
                for (auto& dep : deps) {
517
2.08M
                    if (pipeline_id_to_task.contains(dep)) {
518
1.11M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
519
1.11M
                        if (ss) {
520
526k
                            task->inject_shared_state(ss);
521
593k
                        } else {
522
593k
                            pipeline_id_to_task[dep]->inject_shared_state(
523
593k
                                    task->get_source_shared_state());
524
593k
                        }
525
1.11M
                    }
526
2.08M
                }
527
1.32M
            }
528
2.05M
        }
529
2.54M
    }
530
3.75M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
531
2.53M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
532
2.05M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
533
2.05M
            DCHECK(pipeline_id_to_profile[pip_idx]);
534
2.05M
            std::vector<TScanRangeParams> scan_ranges;
535
2.05M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
536
2.05M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
537
348k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
538
348k
            }
539
2.05M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
540
2.05M
                                                             _params.fragment.output_sink));
541
2.05M
        }
542
2.53M
    }
543
1.21M
    {
544
1.21M
        std::lock_guard<std::mutex> l(_state_map_lock);
545
1.21M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
546
1.21M
    }
547
1.21M
    return Status::OK();
548
1.21M
}
549
550
434k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
551
434k
    _total_tasks = 0;
552
434k
    _closed_tasks = 0;
553
434k
    const auto target_size = _params.local_params.size();
554
434k
    _tasks.resize(target_size);
555
434k
    _runtime_filter_mgr_map.resize(target_size);
556
1.11M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
557
677k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
558
677k
    }
559
434k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
560
561
434k
    if (target_size > 1 &&
562
434k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
563
140k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
564
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
565
25.1k
        std::vector<Status> prepare_status(target_size);
566
25.1k
        int submitted_tasks = 0;
567
25.1k
        Status submit_status;
568
25.1k
        CountDownLatch latch((int)target_size);
569
280k
        for (int i = 0; i < target_size; i++) {
570
255k
            submit_status = thread_pool->submit_func([&, i]() {
571
255k
                SCOPED_ATTACH_TASK(_query_ctx.get());
572
255k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
573
255k
                latch.count_down();
574
255k
            });
575
255k
            if (LIKELY(submit_status.ok())) {
576
255k
                submitted_tasks++;
577
18.4E
            } else {
578
18.4E
                break;
579
18.4E
            }
580
255k
        }
581
25.1k
        latch.arrive_and_wait(target_size - submitted_tasks);
582
25.1k
        if (UNLIKELY(!submit_status.ok())) {
583
0
            return submit_status;
584
0
        }
585
280k
        for (int i = 0; i < submitted_tasks; i++) {
586
255k
            if (!prepare_status[i].ok()) {
587
0
                return prepare_status[i];
588
0
            }
589
255k
        }
590
409k
    } else {
591
1.37M
        for (int i = 0; i < target_size; i++) {
592
964k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
593
964k
        }
594
409k
    }
595
434k
    _pipeline_parent_map.clear();
596
434k
    _op_id_to_shared_state.clear();
597
598
434k
    return Status::OK();
599
434k
}
600
601
433k
void PipelineFragmentContext::_init_next_report_time() {
602
433k
    auto interval_s = config::pipeline_status_report_interval;
603
433k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
604
41.6k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
605
41.6k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
606
        // We don't want to wait longer than it takes to run the entire fragment.
607
41.6k
        _previous_report_time =
608
41.6k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
609
41.6k
        _disable_period_report = false;
610
41.6k
    }
611
433k
}
612
613
4.85k
void PipelineFragmentContext::refresh_next_report_time() {
614
4.85k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
615
4.85k
    DCHECK(disable == true);
616
4.85k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
617
4.85k
    _disable_period_report.compare_exchange_strong(disable, false);
618
4.85k
}
619
620
7.44M
void PipelineFragmentContext::trigger_report_if_necessary() {
621
7.44M
    if (!_is_report_success) {
622
6.88M
        return;
623
6.88M
    }
624
560k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
625
560k
    if (disable) {
626
10.0k
        return;
627
10.0k
    }
628
550k
    int32_t interval_s = config::pipeline_status_report_interval;
629
550k
    if (interval_s <= 0) {
630
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
631
0
                        "trigger "
632
0
                        "report.";
633
0
    }
634
550k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
635
550k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
636
550k
    if (MonotonicNanos() > next_report_time) {
637
4.86k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
638
4.86k
                                                            std::memory_order_acq_rel)) {
639
3
            return;
640
3
        }
641
4.85k
        if (VLOG_FILE_IS_ON) {
642
0
            VLOG_FILE << "Reporting "
643
0
                      << "profile for query_id " << print_id(_query_id)
644
0
                      << ", fragment id: " << _fragment_id;
645
646
0
            std::stringstream ss;
647
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
648
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
649
0
            if (_runtime_state->load_channel_profile()) {
650
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
651
0
            }
652
653
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
654
0
                      << " profile:\n"
655
0
                      << ss.str();
656
0
        }
657
4.85k
        auto st = send_report(false);
658
4.85k
        if (!st.ok()) {
659
0
            disable = true;
660
0
            _disable_period_report.compare_exchange_strong(disable, false,
661
0
                                                           std::memory_order_acq_rel);
662
0
        }
663
4.85k
    }
664
550k
}
665
666
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
667
434k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
668
434k
    if (_params.fragment.plan.nodes.empty()) {
669
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
670
0
    }
671
672
434k
    int node_idx = 0;
673
674
434k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
675
434k
                                        &node_idx, root, cur_pipe, 0, false, false));
676
677
434k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
678
0
        return Status::InternalError(
679
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
680
0
    }
681
434k
    return Status::OK();
682
434k
}
683
684
Status PipelineFragmentContext::_create_tree_helper(
685
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
686
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
687
675k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
688
    // propagate error case
689
675k
    if (*node_idx >= tnodes.size()) {
690
0
        return Status::InternalError(
691
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
692
0
                *node_idx, tnodes.size());
693
0
    }
694
675k
    const TPlanNode& tnode = tnodes[*node_idx];
695
696
675k
    int num_children = tnodes[*node_idx].num_children;
697
675k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
698
675k
    bool current_require_bucket_distribution = require_bucket_distribution;
699
    // TODO: Create CacheOperator is confused now
700
675k
    OperatorPtr op = nullptr;
701
675k
    OperatorPtr cache_op = nullptr;
702
675k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
703
675k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
704
675k
                                     followed_by_shuffled_operator,
705
675k
                                     current_require_bucket_distribution, cache_op));
706
    // Initialization must be done here. For example, group by expressions in agg will be used to
707
    // decide if a local shuffle should be planed, so it must be initialized here.
708
675k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
709
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
710
675k
    if (parent != nullptr) {
711
        // add to parent's child(s)
712
240k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
713
434k
    } else {
714
434k
        *root = op;
715
434k
    }
716
    /**
717
     * `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).
718
     *
719
     * For plan:
720
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
721
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
722
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
723
     *
724
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
725
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
726
     */
727
675k
    auto required_data_distribution =
728
675k
            cur_pipe->operators().empty()
729
675k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
730
675k
                    : op->required_data_distribution(_runtime_state.get());
731
675k
    current_followed_by_shuffled_operator =
732
675k
            ((followed_by_shuffled_operator ||
733
675k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
734
614k
                                             : op->is_shuffled_operator())) &&
735
675k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
736
675k
            (followed_by_shuffled_operator &&
737
561k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
738
739
675k
    current_require_bucket_distribution =
740
675k
            ((require_bucket_distribution ||
741
675k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
742
619k
                                             : op->is_colocated_operator())) &&
743
675k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
744
675k
            (require_bucket_distribution &&
745
567k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
746
747
675k
    if (num_children == 0) {
748
450k
        _use_serial_source = op->is_serial_operator();
749
450k
    }
750
    // rely on that tnodes is preorder of the plan
751
916k
    for (int i = 0; i < num_children; i++) {
752
241k
        ++*node_idx;
753
241k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
754
241k
                                            current_followed_by_shuffled_operator,
755
241k
                                            current_require_bucket_distribution));
756
757
        // we are expecting a child, but have used all nodes
758
        // this means we have been given a bad tree and must fail
759
241k
        if (*node_idx >= tnodes.size()) {
760
0
            return Status::InternalError(
761
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
762
0
                    "nodes: {}",
763
0
                    *node_idx, tnodes.size());
764
0
        }
765
241k
    }
766
767
675k
    return Status::OK();
768
675k
}
769
770
void PipelineFragmentContext::_inherit_pipeline_properties(
771
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
772
110k
        PipelinePtr pipe_with_sink) {
773
110k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
774
110k
    pipe_with_source->set_num_tasks(_num_instances);
775
110k
    pipe_with_source->set_data_distribution(data_distribution);
776
110k
}
777
778
Status PipelineFragmentContext::_add_local_exchange_impl(
779
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
780
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
781
        const std::map<int, int>& bucket_seq_to_instance_idx,
782
110k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
783
110k
    auto& operators = cur_pipe->operators();
784
110k
    const auto downstream_pipeline_id = cur_pipe->id();
785
110k
    auto local_exchange_id = next_operator_id();
786
    // 1. Create a new pipeline with local exchange sink.
787
110k
    DataSinkOperatorPtr sink;
788
110k
    auto sink_id = next_sink_operator_id();
789
790
    /**
791
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
792
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
793
     */
794
110k
    const bool followed_by_shuffled_operator =
795
110k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
796
110k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
797
110k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
798
110k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
799
110k
                                         followed_by_shuffled_operator && !_use_serial_source;
800
110k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
801
110k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
802
110k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
803
110k
    if (bucket_seq_to_instance_idx.empty() &&
804
110k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
805
3
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
806
3
    }
807
110k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
808
110k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
809
110k
                                          num_buckets, use_global_hash_shuffle,
810
110k
                                          shuffle_idx_to_instance_idx));
811
812
    // 2. Create and initialize LocalExchangeSharedState.
813
110k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
814
110k
            LocalExchangeSharedState::create_shared(_num_instances);
815
110k
    switch (data_distribution.distribution_type) {
816
12.7k
    case ExchangeType::HASH_SHUFFLE:
817
12.7k
        shared_state->exchanger = ShuffleExchanger::create_unique(
818
12.7k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
819
12.7k
                use_global_hash_shuffle ? _total_instances : _num_instances,
820
12.7k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
821
12.8k
                        ? cast_set<int>(
822
12.8k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
823
18.4E
                        : 0);
824
12.7k
        break;
825
499
    case ExchangeType::BUCKET_HASH_SHUFFLE:
826
499
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
827
499
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
828
499
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
829
499
                        ? cast_set<int>(
830
499
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
831
499
                        : 0);
832
499
        break;
833
93.3k
    case ExchangeType::PASSTHROUGH:
834
93.3k
        shared_state->exchanger = PassthroughExchanger::create_unique(
835
93.3k
                cur_pipe->num_tasks(), _num_instances,
836
93.3k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
837
93.3k
                        ? cast_set<int>(
838
93.3k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
839
93.3k
                        : 0);
840
93.3k
        break;
841
375
    case ExchangeType::BROADCAST:
842
375
        shared_state->exchanger = BroadcastExchanger::create_unique(
843
375
                cur_pipe->num_tasks(), _num_instances,
844
375
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
845
375
                        ? cast_set<int>(
846
375
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
847
375
                        : 0);
848
375
        break;
849
2.89k
    case ExchangeType::PASS_TO_ONE:
850
2.89k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
851
            // If shared hash table is enabled for BJ, hash table will be built by only one task
852
1.95k
            shared_state->exchanger = PassToOneExchanger::create_unique(
853
1.95k
                    cur_pipe->num_tasks(), _num_instances,
854
1.95k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
855
1.95k
                            ? cast_set<int>(_runtime_state->query_options()
856
1.95k
                                                    .local_exchange_free_blocks_limit)
857
1.95k
                            : 0);
858
1.95k
        } else {
859
939
            shared_state->exchanger = BroadcastExchanger::create_unique(
860
939
                    cur_pipe->num_tasks(), _num_instances,
861
939
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
862
939
                            ? cast_set<int>(_runtime_state->query_options()
863
939
                                                    .local_exchange_free_blocks_limit)
864
939
                            : 0);
865
939
        }
866
2.89k
        break;
867
923
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
868
923
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
869
923
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
870
923
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
923
                        ? cast_set<int>(
872
923
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
873
923
                        : 0);
874
923
        break;
875
0
    default:
876
0
        return Status::InternalError("Unsupported local exchange type : " +
877
0
                                     std::to_string((int)data_distribution.distribution_type));
878
110k
    }
879
110k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
880
110k
                                             "LOCAL_EXCHANGE_OPERATOR");
881
110k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
882
110k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
883
884
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
885
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
886
887
    // 3.1 Initialize new pipeline's operator list.
888
110k
    std::copy(operators.begin(), operators.begin() + idx,
889
110k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
890
891
    // 3.2 Erase unused operators in previous pipeline.
892
110k
    operators.erase(operators.begin(), operators.begin() + idx);
893
894
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
895
110k
    OperatorPtr source_op;
896
110k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
897
110k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
898
110k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
899
110k
    if (!operators.empty()) {
900
44.9k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
901
44.9k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
902
44.9k
    }
903
110k
    operators.insert(operators.begin(), source_op);
904
905
    // 5. Set children for two pipelines separately.
906
110k
    std::vector<std::shared_ptr<Pipeline>> new_children;
907
110k
    std::vector<PipelineId> edges_with_source;
908
130k
    for (auto child : cur_pipe->children()) {
909
130k
        bool found = false;
910
144k
        for (auto op : new_pip->operators()) {
911
144k
            if (child->sink()->node_id() == op->node_id()) {
912
13.1k
                new_pip->set_children(child);
913
13.1k
                found = true;
914
13.1k
            };
915
144k
        }
916
130k
        if (!found) {
917
116k
            new_children.push_back(child);
918
116k
            edges_with_source.push_back(child->id());
919
116k
        }
920
130k
    }
921
110k
    new_children.push_back(new_pip);
922
110k
    edges_with_source.push_back(new_pip->id());
923
924
    // 6. Set DAG for new pipelines.
925
110k
    if (!new_pip->children().empty()) {
926
7.40k
        std::vector<PipelineId> edges_with_sink;
927
13.1k
        for (auto child : new_pip->children()) {
928
13.1k
            edges_with_sink.push_back(child->id());
929
13.1k
        }
930
7.40k
        _dag.insert({new_pip->id(), edges_with_sink});
931
7.40k
    }
932
110k
    cur_pipe->set_children(new_children);
933
110k
    _dag[downstream_pipeline_id] = edges_with_source;
934
110k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
935
110k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
936
110k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
937
938
    // 7. Inherit properties from current pipeline.
939
110k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
940
110k
    return Status::OK();
941
110k
}
942
943
Status PipelineFragmentContext::_add_local_exchange(
944
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
945
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
946
        const std::map<int, int>& bucket_seq_to_instance_idx,
947
189k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
948
189k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
949
42.9k
        return Status::OK();
950
42.9k
    }
951
952
146k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
953
49.2k
        return Status::OK();
954
49.2k
    }
955
97.7k
    *do_local_exchange = true;
956
957
97.7k
    auto& operators = cur_pipe->operators();
958
97.7k
    auto total_op_num = operators.size();
959
97.7k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
960
97.7k
    RETURN_IF_ERROR(_add_local_exchange_impl(
961
97.7k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
962
97.7k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
963
964
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
965
18.4E
            << "total_op_num: " << total_op_num
966
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
967
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
968
969
    // There are some local shuffles with relatively heavy operations on the sink.
970
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
971
    // Therefore, local passthrough is used to increase the concurrency of the sink.
972
    // op -> local sink(1) -> local source (n)
973
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
974
97.7k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
975
97.7k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
976
13.1k
        RETURN_IF_ERROR(_add_local_exchange_impl(
977
13.1k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
978
13.1k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
979
13.1k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
980
13.1k
                shuffle_idx_to_instance_idx));
981
13.1k
    }
982
97.7k
    return Status::OK();
983
97.7k
}
984
985
Status PipelineFragmentContext::_plan_local_exchange(
986
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
987
432k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
988
996k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
989
564k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
990
        // Set property if child pipeline is not join operator's child.
991
564k
        if (!_pipelines[pip_idx]->children().empty()) {
992
126k
            for (auto& child : _pipelines[pip_idx]->children()) {
993
126k
                if (child->sink()->node_id() ==
994
126k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
995
111k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
996
111k
                }
997
126k
            }
998
120k
        }
999
1000
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1001
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1002
        // still keep colocate plan after local shuffle
1003
564k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1004
564k
                                             bucket_seq_to_instance_idx,
1005
564k
                                             shuffle_idx_to_instance_idx));
1006
564k
    }
1007
432k
    return Status::OK();
1008
432k
}
1009
1010
Status PipelineFragmentContext::_plan_local_exchange(
1011
        int num_buckets, int pip_idx, PipelinePtr pip,
1012
        const std::map<int, int>& bucket_seq_to_instance_idx,
1013
563k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1014
563k
    int idx = 1;
1015
563k
    bool do_local_exchange = false;
1016
608k
    do {
1017
608k
        auto& ops = pip->operators();
1018
608k
        do_local_exchange = false;
1019
        // Plan local exchange for each operator.
1020
678k
        for (; idx < ops.size();) {
1021
114k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1022
102k
                RETURN_IF_ERROR(_add_local_exchange(
1023
102k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1024
102k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1025
102k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1026
102k
                        shuffle_idx_to_instance_idx));
1027
102k
            }
1028
114k
            if (do_local_exchange) {
1029
                // If local exchange is needed for current operator, we will split this pipeline to
1030
                // two pipelines by local exchange sink/source. And then we need to process remaining
1031
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1032
                // is current operator was already processed) and continue to plan local exchange.
1033
45.0k
                idx = 2;
1034
45.0k
                break;
1035
45.0k
            }
1036
69.9k
            idx++;
1037
69.9k
        }
1038
608k
    } while (do_local_exchange);
1039
563k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1040
87.0k
        RETURN_IF_ERROR(_add_local_exchange(
1041
87.0k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1042
87.0k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1043
87.0k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1044
87.0k
    }
1045
563k
    return Status::OK();
1046
563k
}
1047
1048
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1049
                                                  const std::vector<TExpr>& output_exprs,
1050
                                                  const TPipelineFragmentParams& params,
1051
                                                  const RowDescriptor& row_desc,
1052
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1053
435k
                                                  PipelineId cur_pipeline_id) {
1054
435k
    switch (thrift_sink.type) {
1055
145k
    case TDataSinkType::DATA_STREAM_SINK: {
1056
145k
        if (!thrift_sink.__isset.stream_sink) {
1057
0
            return Status::InternalError("Missing data stream sink.");
1058
0
        }
1059
145k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1060
145k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1061
145k
                params.destinations, _fragment_instance_ids);
1062
145k
        break;
1063
145k
    }
1064
251k
    case TDataSinkType::RESULT_SINK: {
1065
251k
        if (!thrift_sink.__isset.result_sink) {
1066
0
            return Status::InternalError("Missing data buffer sink.");
1067
0
        }
1068
1069
251k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), row_desc,
1070
251k
                                                      output_exprs, thrift_sink.result_sink);
1071
251k
        break;
1072
251k
    }
1073
105
    case TDataSinkType::DICTIONARY_SINK: {
1074
105
        if (!thrift_sink.__isset.dictionary_sink) {
1075
0
            return Status::InternalError("Missing dict sink.");
1076
0
        }
1077
1078
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1079
105
                                                    thrift_sink.dictionary_sink);
1080
105
        break;
1081
105
    }
1082
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1083
31.2k
    case TDataSinkType::OLAP_TABLE_SINK: {
1084
31.2k
        if (state->query_options().enable_memtable_on_sink_node &&
1085
31.2k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1086
31.2k
            !config::is_cloud_mode()) {
1087
2.10k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(pool, next_sink_operator_id(),
1088
2.10k
                                                               row_desc, output_exprs);
1089
29.1k
        } else {
1090
29.1k
            _sink = std::make_shared<OlapTableSinkOperatorX>(pool, next_sink_operator_id(),
1091
29.1k
                                                             row_desc, output_exprs);
1092
29.1k
        }
1093
31.2k
        break;
1094
0
    }
1095
164
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1096
164
        DCHECK(thrift_sink.__isset.olap_table_sink);
1097
164
        DCHECK(state->get_query_ctx() != nullptr);
1098
164
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1099
164
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1100
164
                                                                output_exprs);
1101
164
        break;
1102
0
    }
1103
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1104
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1105
0
            return Status::InternalError("Missing hive table sink.");
1106
0
        }
1107
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1108
1.46k
                                                         output_exprs);
1109
1.46k
        break;
1110
1.46k
    }
1111
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1112
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1113
0
            return Status::InternalError("Missing iceberg table sink.");
1114
0
        }
1115
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1116
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1117
0
                                                                     row_desc, output_exprs);
1118
1.73k
        } else {
1119
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1120
1.73k
                                                                row_desc, output_exprs);
1121
1.73k
        }
1122
1.73k
        break;
1123
1.73k
    }
1124
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1125
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1126
0
            return Status::InternalError("Missing iceberg delete sink.");
1127
0
        }
1128
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1129
20
                                                             row_desc, output_exprs);
1130
20
        break;
1131
20
    }
1132
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1133
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1134
0
            return Status::InternalError("Missing iceberg merge sink.");
1135
0
        }
1136
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1137
80
                                                            output_exprs);
1138
80
        break;
1139
80
    }
1140
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1141
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1142
0
            return Status::InternalError("Missing max compute table sink.");
1143
0
        }
1144
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1145
0
                                                       output_exprs);
1146
0
        break;
1147
0
    }
1148
80
    case TDataSinkType::JDBC_TABLE_SINK: {
1149
80
        if (!thrift_sink.__isset.jdbc_table_sink) {
1150
0
            return Status::InternalError("Missing data jdbc sink.");
1151
0
        }
1152
80
        if (config::enable_java_support) {
1153
80
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1154
80
                                                             output_exprs);
1155
80
        } else {
1156
0
            return Status::InternalError(
1157
0
                    "Jdbc table sink is not enabled, you can change be config "
1158
0
                    "enable_java_support to true and restart be.");
1159
0
        }
1160
80
        break;
1161
80
    }
1162
80
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1163
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1164
0
            return Status::InternalError("Missing data buffer sink.");
1165
0
        }
1166
1167
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
3
                                                             output_exprs);
1169
3
        break;
1170
3
    }
1171
502
    case TDataSinkType::RESULT_FILE_SINK: {
1172
502
        if (!thrift_sink.__isset.result_file_sink) {
1173
0
            return Status::InternalError("Missing result file sink.");
1174
0
        }
1175
1176
        // Result file sink is not the top sink
1177
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1178
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1179
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1180
0
                    params.destinations, output_exprs, desc_tbl);
1181
502
        } else {
1182
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1183
502
                                                              output_exprs);
1184
502
        }
1185
502
        break;
1186
502
    }
1187
1.99k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1188
1.99k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1189
1.99k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1190
1.99k
        auto sink_id = next_sink_operator_id();
1191
1.99k
        const int multi_cast_node_id = sink_id;
1192
1.99k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1193
        // one sink has multiple sources.
1194
1.99k
        std::vector<int> sources;
1195
7.77k
        for (int i = 0; i < sender_size; ++i) {
1196
5.77k
            auto source_id = next_operator_id();
1197
5.77k
            sources.push_back(source_id);
1198
5.77k
        }
1199
1200
1.99k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1201
1.99k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1202
7.77k
        for (int i = 0; i < sender_size; ++i) {
1203
5.77k
            auto new_pipeline = add_pipeline();
1204
            // use to exchange sink
1205
5.77k
            RowDescriptor* exchange_row_desc = nullptr;
1206
5.77k
            {
1207
5.77k
                const auto& tmp_row_desc =
1208
5.77k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1209
5.77k
                                ? RowDescriptor(state->desc_tbl(),
1210
5.77k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1211
5.77k
                                                         .output_tuple_id})
1212
5.77k
                                : row_desc;
1213
5.77k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1214
5.77k
            }
1215
5.77k
            auto source_id = sources[i];
1216
5.77k
            OperatorPtr source_op;
1217
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1218
5.77k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1219
5.77k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1220
5.77k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1221
5.77k
                    /*operator_id=*/source_id);
1222
5.77k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1223
5.77k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1224
            // 2. create and set sink operator of data stream sender for new pipeline
1225
1226
5.77k
            DataSinkOperatorPtr sink_op;
1227
5.77k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1228
5.77k
                    state, *exchange_row_desc, next_sink_operator_id(),
1229
5.77k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1230
5.77k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1231
1232
5.77k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1233
5.77k
            {
1234
5.77k
                TDataSink* t = pool->add(new TDataSink());
1235
5.77k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1236
5.77k
                RETURN_IF_ERROR(sink_op->init(*t));
1237
5.77k
            }
1238
1239
            // 3. set dependency dag
1240
5.77k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1241
5.77k
        }
1242
1.99k
        if (sources.empty()) {
1243
0
            return Status::InternalError("size of sources must be greater than 0");
1244
0
        }
1245
1.99k
        break;
1246
1.99k
    }
1247
1.99k
    case TDataSinkType::BLACKHOLE_SINK: {
1248
13
        if (!thrift_sink.__isset.blackhole_sink) {
1249
0
            return Status::InternalError("Missing blackhole sink.");
1250
0
        }
1251
1252
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1253
13
        break;
1254
13
    }
1255
156
    case TDataSinkType::TVF_TABLE_SINK: {
1256
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1257
0
            return Status::InternalError("Missing TVF table sink.");
1258
0
        }
1259
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1260
156
                                                        output_exprs);
1261
156
        break;
1262
156
    }
1263
0
    default:
1264
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1265
435k
    }
1266
434k
    return Status::OK();
1267
435k
}
1268
1269
// NOLINTBEGIN(readability-function-size)
1270
// NOLINTBEGIN(readability-function-cognitive-complexity)
1271
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1272
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1273
                                                 PipelinePtr& cur_pipe, int parent_idx,
1274
                                                 int child_idx,
1275
                                                 const bool followed_by_shuffled_operator,
1276
                                                 const bool require_bucket_distribution,
1277
676k
                                                 OperatorPtr& cache_op) {
1278
676k
    std::vector<DataSinkOperatorPtr> sink_ops;
1279
676k
    Defer defer = Defer([&]() {
1280
675k
        if (op) {
1281
675k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1282
675k
        }
1283
675k
        for (auto& s : sink_ops) {
1284
125k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1285
125k
        }
1286
675k
    });
1287
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1288
    // Therefore, here we need to use a stack-like structure.
1289
676k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1290
676k
    std::stringstream error_msg;
1291
676k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1292
1293
676k
    bool fe_with_old_version = false;
1294
676k
    switch (tnode.node_type) {
1295
212k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1296
212k
        op = std::make_shared<OlapScanOperatorX>(
1297
212k
                pool, tnode, next_operator_id(), descs, _num_instances,
1298
212k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1299
212k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1300
212k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1301
212k
        break;
1302
212k
    }
1303
77
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1304
77
        DCHECK(_query_ctx != nullptr);
1305
77
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1306
77
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1307
77
                                                    _num_instances);
1308
77
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1309
77
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1310
77
        break;
1311
77
    }
1312
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1313
0
        if (config::enable_java_support) {
1314
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1315
0
                                                     _num_instances);
1316
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1317
0
        } else {
1318
0
            return Status::InternalError(
1319
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1320
0
                    "to true and restart be.");
1321
0
        }
1322
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1323
0
        break;
1324
0
    }
1325
23.0k
    case TPlanNodeType::FILE_SCAN_NODE: {
1326
23.0k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1327
23.0k
                                                 _num_instances);
1328
23.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1329
23.0k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1330
23.0k
        break;
1331
23.0k
    }
1332
0
    case TPlanNodeType::ES_SCAN_NODE:
1333
592
    case TPlanNodeType::ES_HTTP_SCAN_NODE: {
1334
592
        op = std::make_shared<EsScanOperatorX>(pool, tnode, next_operator_id(), descs,
1335
592
                                               _num_instances);
1336
592
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1337
592
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1338
592
        break;
1339
592
    }
1340
149k
    case TPlanNodeType::EXCHANGE_NODE: {
1341
149k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1342
149k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1343
18.4E
                                  : 0;
1344
149k
        DCHECK_GT(num_senders, 0);
1345
149k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1346
149k
                                                       num_senders);
1347
149k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1348
149k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1349
149k
        break;
1350
149k
    }
1351
158k
    case TPlanNodeType::AGGREGATION_NODE: {
1352
158k
        if (tnode.agg_node.grouping_exprs.empty() &&
1353
158k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1354
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1355
0
                                         ": group by and output is empty");
1356
0
        }
1357
158k
        bool need_create_cache_op =
1358
158k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1359
158k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1360
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1361
10
            auto cache_source_id = next_operator_id();
1362
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1363
10
                                                        _params.fragment.query_cache_param);
1364
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1365
1366
10
            const auto downstream_pipeline_id = cur_pipe->id();
1367
10
            if (!_dag.contains(downstream_pipeline_id)) {
1368
10
                _dag.insert({downstream_pipeline_id, {}});
1369
10
            }
1370
10
            new_pipe = add_pipeline(cur_pipe);
1371
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1372
1373
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1374
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1375
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1376
10
            return Status::OK();
1377
10
        };
1378
158k
        const bool group_by_limit_opt =
1379
158k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1380
1381
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1382
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1383
158k
        const bool enable_spill = _runtime_state->enable_spill() &&
1384
158k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1385
158k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1386
158k
                                      tnode.agg_node.use_streaming_preaggregation &&
1387
158k
                                      !tnode.agg_node.grouping_exprs.empty();
1388
        // TODO: distinct streaming agg does not support spill.
1389
158k
        const bool can_use_distinct_streaming_agg =
1390
158k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1391
158k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1392
158k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1393
158k
                _params.query_options.enable_distinct_streaming_aggregation;
1394
1395
158k
        if (can_use_distinct_streaming_agg) {
1396
92.0k
            if (need_create_cache_op) {
1397
8
                PipelinePtr new_pipe;
1398
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1399
1400
8
                cache_op = op;
1401
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1402
8
                                                                     tnode, descs);
1403
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1404
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1405
8
                cur_pipe = new_pipe;
1406
91.9k
            } else {
1407
91.9k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
91.9k
                                                                     tnode, descs);
1409
91.9k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1410
91.9k
            }
1411
92.0k
        } else if (is_streaming_agg) {
1412
3.38k
            if (need_create_cache_op) {
1413
0
                PipelinePtr new_pipe;
1414
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1415
0
                cache_op = op;
1416
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1417
0
                                                             descs);
1418
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1419
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1420
0
                cur_pipe = new_pipe;
1421
3.38k
            } else {
1422
3.38k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
3.38k
                                                             descs);
1424
3.38k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1425
3.38k
            }
1426
63.0k
        } else {
1427
            // create new pipeline to add query cache operator
1428
63.0k
            PipelinePtr new_pipe;
1429
63.0k
            if (need_create_cache_op) {
1430
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1431
2
                cache_op = op;
1432
2
            }
1433
1434
63.0k
            if (enable_spill) {
1435
112
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1436
112
                                                                     next_operator_id(), descs);
1437
62.9k
            } else {
1438
62.9k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1439
62.9k
            }
1440
63.0k
            if (need_create_cache_op) {
1441
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1442
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1443
2
                cur_pipe = new_pipe;
1444
63.0k
            } else {
1445
63.0k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1446
63.0k
            }
1447
1448
63.0k
            const auto downstream_pipeline_id = cur_pipe->id();
1449
63.0k
            if (!_dag.contains(downstream_pipeline_id)) {
1450
60.9k
                _dag.insert({downstream_pipeline_id, {}});
1451
60.9k
            }
1452
63.0k
            cur_pipe = add_pipeline(cur_pipe);
1453
63.0k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1454
1455
63.0k
            if (enable_spill) {
1456
112
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1457
112
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1458
62.9k
            } else {
1459
62.9k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1460
62.9k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1461
62.9k
            }
1462
63.0k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1463
63.0k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1464
63.0k
        }
1465
158k
        break;
1466
158k
    }
1467
158k
    case TPlanNodeType::HASH_JOIN_NODE: {
1468
9.84k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1469
9.84k
                                       tnode.hash_join_node.is_broadcast_join;
1470
9.84k
        const auto enable_spill = _runtime_state->enable_spill();
1471
9.84k
        if (enable_spill && !is_broadcast_join) {
1472
0
            auto tnode_ = tnode;
1473
0
            tnode_.runtime_filters.clear();
1474
0
            auto inner_probe_operator =
1475
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1476
1477
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1478
            // So here use `tnode_` which has no runtime filters.
1479
0
            auto probe_side_inner_sink_operator =
1480
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1481
1482
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1483
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1484
1485
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1486
0
                    pool, tnode_, next_operator_id(), descs);
1487
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1488
0
                                                inner_probe_operator);
1489
0
            op = std::move(probe_operator);
1490
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1491
1492
0
            const auto downstream_pipeline_id = cur_pipe->id();
1493
0
            if (!_dag.contains(downstream_pipeline_id)) {
1494
0
                _dag.insert({downstream_pipeline_id, {}});
1495
0
            }
1496
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1497
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1498
1499
0
            auto inner_sink_operator =
1500
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1501
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1502
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1503
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1504
1505
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1506
0
            sink_ops.push_back(std::move(sink_operator));
1507
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1508
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1509
1510
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1511
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1512
9.84k
        } else {
1513
9.84k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1514
9.84k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1515
1516
9.84k
            const auto downstream_pipeline_id = cur_pipe->id();
1517
9.84k
            if (!_dag.contains(downstream_pipeline_id)) {
1518
8.14k
                _dag.insert({downstream_pipeline_id, {}});
1519
8.14k
            }
1520
9.84k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1521
9.84k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1522
1523
9.84k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1524
9.84k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1525
9.84k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1526
9.84k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1527
1528
9.84k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1529
9.84k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1530
9.84k
        }
1531
9.84k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1532
5.06k
            std::shared_ptr<HashJoinSharedState> shared_state =
1533
5.06k
                    HashJoinSharedState::create_shared(_num_instances);
1534
25.8k
            for (int i = 0; i < _num_instances; i++) {
1535
20.8k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1536
20.8k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1537
20.8k
                sink_dep->set_shared_state(shared_state.get());
1538
20.8k
                shared_state->sink_deps.push_back(sink_dep);
1539
20.8k
            }
1540
5.06k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1541
5.06k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1542
5.06k
            _op_id_to_shared_state.insert(
1543
5.06k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1544
5.06k
        }
1545
9.84k
        break;
1546
9.84k
    }
1547
4.92k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1548
4.92k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1549
4.92k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1550
1551
4.92k
        const auto downstream_pipeline_id = cur_pipe->id();
1552
4.92k
        if (!_dag.contains(downstream_pipeline_id)) {
1553
4.69k
            _dag.insert({downstream_pipeline_id, {}});
1554
4.69k
        }
1555
4.92k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1556
4.92k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1557
1558
4.92k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1559
4.92k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1560
4.92k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
4.92k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1562
4.92k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1563
4.92k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1564
4.92k
        break;
1565
4.92k
    }
1566
53.5k
    case TPlanNodeType::UNION_NODE: {
1567
53.5k
        int child_count = tnode.num_children;
1568
53.5k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1569
53.5k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1570
1571
53.5k
        const auto downstream_pipeline_id = cur_pipe->id();
1572
53.5k
        if (!_dag.contains(downstream_pipeline_id)) {
1573
53.3k
            _dag.insert({downstream_pipeline_id, {}});
1574
53.3k
        }
1575
55.2k
        for (int i = 0; i < child_count; i++) {
1576
1.67k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1577
1.67k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1578
1.67k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1579
1.67k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1580
1.67k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1581
1.67k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1582
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1583
1.67k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1584
1.67k
        }
1585
53.5k
        break;
1586
53.5k
    }
1587
53.5k
    case TPlanNodeType::SORT_NODE: {
1588
44.1k
        const auto should_spill = _runtime_state->enable_spill() &&
1589
44.1k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1590
44.1k
        const bool use_local_merge =
1591
44.1k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1592
44.1k
        if (should_spill) {
1593
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1594
44.1k
        } else if (use_local_merge) {
1595
41.8k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1596
41.8k
                                                                 descs);
1597
41.8k
        } else {
1598
2.33k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1599
2.33k
        }
1600
44.1k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1601
1602
44.1k
        const auto downstream_pipeline_id = cur_pipe->id();
1603
44.1k
        if (!_dag.contains(downstream_pipeline_id)) {
1604
44.1k
            _dag.insert({downstream_pipeline_id, {}});
1605
44.1k
        }
1606
44.1k
        cur_pipe = add_pipeline(cur_pipe);
1607
44.1k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1608
1609
44.1k
        if (should_spill) {
1610
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1611
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1612
44.1k
        } else {
1613
44.1k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1614
44.1k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1615
44.1k
        }
1616
44.1k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1617
44.1k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1618
44.1k
        break;
1619
44.1k
    }
1620
44.1k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1621
63
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
63
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
63
        const auto downstream_pipeline_id = cur_pipe->id();
1625
63
        if (!_dag.contains(downstream_pipeline_id)) {
1626
63
            _dag.insert({downstream_pipeline_id, {}});
1627
63
        }
1628
63
        cur_pipe = add_pipeline(cur_pipe);
1629
63
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1630
1631
63
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1632
63
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1633
63
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1634
63
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1635
63
        break;
1636
63
    }
1637
1.64k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1638
1.64k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1639
1.64k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1640
1641
1.64k
        const auto downstream_pipeline_id = cur_pipe->id();
1642
1.64k
        if (!_dag.contains(downstream_pipeline_id)) {
1643
1.63k
            _dag.insert({downstream_pipeline_id, {}});
1644
1.63k
        }
1645
1.64k
        cur_pipe = add_pipeline(cur_pipe);
1646
1.64k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1647
1648
1.64k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1649
1.64k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1650
1.64k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1651
1.64k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1652
1.64k
        break;
1653
1.64k
    }
1654
1.64k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1655
1.62k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1656
1.62k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1657
1.62k
        break;
1658
1.62k
    }
1659
1.62k
    case TPlanNodeType::INTERSECT_NODE: {
1660
126
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1661
126
                                                                      cur_pipe, sink_ops));
1662
126
        break;
1663
126
    }
1664
129
    case TPlanNodeType::EXCEPT_NODE: {
1665
129
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1666
129
                                                                       cur_pipe, sink_ops));
1667
129
        break;
1668
129
    }
1669
313
    case TPlanNodeType::REPEAT_NODE: {
1670
313
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1671
313
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1672
313
        break;
1673
313
    }
1674
921
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1675
921
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1676
921
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1677
921
        break;
1678
921
    }
1679
921
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1680
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1681
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1682
218
        break;
1683
218
    }
1684
1.60k
    case TPlanNodeType::EMPTY_SET_NODE: {
1685
1.60k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1686
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1687
1.60k
        break;
1688
1.60k
    }
1689
1.60k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1690
459
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1691
459
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1692
459
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1693
459
        break;
1694
459
    }
1695
2.32k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1696
2.32k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1697
2.32k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1698
2.32k
        break;
1699
2.32k
    }
1700
6.27k
    case TPlanNodeType::META_SCAN_NODE: {
1701
6.27k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1702
6.27k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1703
6.27k
        break;
1704
6.27k
    }
1705
6.27k
    case TPlanNodeType::SELECT_NODE: {
1706
1.97k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1707
1.97k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1708
1.97k
        break;
1709
1.97k
    }
1710
1.97k
    case TPlanNodeType::REC_CTE_NODE: {
1711
134
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1712
134
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1713
1714
134
        const auto downstream_pipeline_id = cur_pipe->id();
1715
134
        if (!_dag.contains(downstream_pipeline_id)) {
1716
133
            _dag.insert({downstream_pipeline_id, {}});
1717
133
        }
1718
1719
134
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1720
134
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1721
1722
134
        DataSinkOperatorPtr anchor_sink;
1723
134
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1724
134
                                                                  op->operator_id(), tnode, descs);
1725
134
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1726
134
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1727
134
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1728
1729
134
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1730
134
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1731
1732
134
        DataSinkOperatorPtr rec_sink;
1733
134
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1734
134
                                                         tnode, descs);
1735
134
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1736
134
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1737
134
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1738
1739
134
        break;
1740
134
    }
1741
1.85k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1742
1.85k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1743
1.85k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1744
1.85k
        break;
1745
1.85k
    }
1746
1.85k
    default:
1747
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1748
0
                                     print_plan_node_type(tnode.node_type));
1749
676k
    }
1750
675k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1751
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1752
0
        op->set_serial_operator();
1753
0
    }
1754
1755
675k
    return Status::OK();
1756
676k
}
1757
// NOLINTEND(readability-function-cognitive-complexity)
1758
// NOLINTEND(readability-function-size)
1759
1760
template <bool is_intersect>
1761
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1762
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1763
255
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1764
255
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1765
255
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
255
    const auto downstream_pipeline_id = cur_pipe->id();
1768
255
    if (!_dag.contains(downstream_pipeline_id)) {
1769
230
        _dag.insert({downstream_pipeline_id, {}});
1770
230
    }
1771
1772
858
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1773
603
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1774
603
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1775
1776
603
        if (child_id == 0) {
1777
255
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1778
255
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1779
348
        } else {
1780
348
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1781
348
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1782
348
        }
1783
603
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1784
603
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1785
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1786
603
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1787
603
    }
1788
1789
255
    return Status::OK();
1790
255
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1763
126
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1764
126
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1765
126
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
126
    const auto downstream_pipeline_id = cur_pipe->id();
1768
126
    if (!_dag.contains(downstream_pipeline_id)) {
1769
110
        _dag.insert({downstream_pipeline_id, {}});
1770
110
    }
1771
1772
456
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1773
330
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1774
330
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1775
1776
330
        if (child_id == 0) {
1777
126
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1778
126
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1779
204
        } else {
1780
204
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1781
204
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1782
204
        }
1783
330
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1784
330
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1785
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1786
330
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1787
330
    }
1788
1789
126
    return Status::OK();
1790
126
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1763
129
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1764
129
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1765
129
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
129
    const auto downstream_pipeline_id = cur_pipe->id();
1768
129
    if (!_dag.contains(downstream_pipeline_id)) {
1769
120
        _dag.insert({downstream_pipeline_id, {}});
1770
120
    }
1771
1772
402
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1773
273
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1774
273
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1775
1776
273
        if (child_id == 0) {
1777
129
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1778
129
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1779
144
        } else {
1780
144
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1781
144
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1782
144
        }
1783
273
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1784
273
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1785
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1786
273
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1787
273
    }
1788
1789
129
    return Status::OK();
1790
129
}
1791
1792
433k
Status PipelineFragmentContext::submit() {
1793
433k
    if (_submitted) {
1794
0
        return Status::InternalError("submitted");
1795
0
    }
1796
433k
    _submitted = true;
1797
1798
433k
    int submit_tasks = 0;
1799
433k
    Status st;
1800
433k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1801
1.21M
    for (auto& task : _tasks) {
1802
2.06M
        for (auto& t : task) {
1803
2.06M
            st = scheduler->submit(t.first);
1804
2.06M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1805
2.06M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1806
2.06M
            if (!st) {
1807
0
                cancel(Status::InternalError("submit context to executor fail"));
1808
0
                std::lock_guard<std::mutex> l(_task_mutex);
1809
0
                _total_tasks = submit_tasks;
1810
0
                break;
1811
0
            }
1812
2.06M
            submit_tasks++;
1813
2.06M
        }
1814
1.21M
    }
1815
433k
    if (!st.ok()) {
1816
0
        bool need_remove = false;
1817
0
        {
1818
0
            std::lock_guard<std::mutex> l(_task_mutex);
1819
0
            if (_closed_tasks >= _total_tasks) {
1820
0
                need_remove = _close_fragment_instance();
1821
0
            }
1822
0
        }
1823
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1824
0
        if (need_remove) {
1825
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1826
0
        }
1827
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1828
0
                                     BackendOptions::get_localhost());
1829
433k
    } else {
1830
433k
        return st;
1831
433k
    }
1832
433k
}
1833
1834
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1835
0
    if (_runtime_state->enable_profile()) {
1836
0
        std::stringstream ss;
1837
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1838
0
            runtime_profile_ptr->pretty_print(&ss);
1839
0
        }
1840
1841
0
        if (_runtime_state->load_channel_profile()) {
1842
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1843
0
        }
1844
1845
0
        auto profile_str =
1846
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1847
0
                            this->_fragment_id, extra_info, ss.str());
1848
0
        LOG_LONG_STRING(INFO, profile_str);
1849
0
    }
1850
0
}
1851
// If all pipeline tasks binded to the fragment instance are finished, then we could
1852
// close the fragment instance.
1853
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1854
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1855
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1856
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1857
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1858
// (via debug_string()).
1859
434k
bool PipelineFragmentContext::_close_fragment_instance() {
1860
434k
    if (_is_fragment_instance_closed) {
1861
0
        return false;
1862
0
    }
1863
434k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1864
434k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1865
434k
    if (!_need_notify_close) {
1866
431k
        auto st = send_report(true);
1867
431k
        if (!st) {
1868
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1869
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1870
0
        }
1871
431k
    }
1872
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1873
    // Since stream load does not have someting like coordinator on FE, so
1874
    // backend can not report profile to FE, ant its profile can not be shown
1875
    // in the same way with other query. So we print the profile content to info log.
1876
1877
434k
    if (_runtime_state->enable_profile() &&
1878
434k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1879
2.53k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1880
2.53k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1881
0
        std::stringstream ss;
1882
        // Compute the _local_time_percent before pretty_print the runtime_profile
1883
        // Before add this operation, the print out like that:
1884
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1885
        // After add the operation, the print out like that:
1886
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1887
        // We can easily know the exec node execute time without child time consumed.
1888
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1889
0
            runtime_profile_ptr->pretty_print(&ss);
1890
0
        }
1891
1892
0
        if (_runtime_state->load_channel_profile()) {
1893
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1894
0
        }
1895
1896
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1897
0
    }
1898
1899
434k
    if (_query_ctx->enable_profile()) {
1900
2.53k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1901
2.53k
                                         collect_realtime_load_channel_profile());
1902
2.53k
    }
1903
1904
    // Return whether the caller needs to remove from the pipeline map.
1905
    // The caller must do this after releasing _task_mutex.
1906
434k
    return !_need_notify_close;
1907
434k
}
1908
1909
2.05M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1910
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1911
2.05M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1912
2.05M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1913
677k
        if (_dag.contains(pipeline_id)) {
1914
353k
            for (auto dep : _dag[pipeline_id]) {
1915
353k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1916
353k
            }
1917
284k
        }
1918
677k
    }
1919
2.05M
    bool need_remove = false;
1920
2.05M
    {
1921
2.05M
        std::lock_guard<std::mutex> l(_task_mutex);
1922
2.05M
        ++_closed_tasks;
1923
2.05M
        if (_closed_tasks >= _total_tasks) {
1924
434k
            need_remove = _close_fragment_instance();
1925
434k
        }
1926
2.05M
    }
1927
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1928
2.05M
    if (need_remove) {
1929
431k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1930
431k
    }
1931
2.05M
}
1932
1933
53.9k
std::string PipelineFragmentContext::get_load_error_url() {
1934
53.9k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1935
0
        return to_load_error_http_path(str);
1936
0
    }
1937
147k
    for (auto& tasks : _tasks) {
1938
237k
        for (auto& task : tasks) {
1939
237k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1940
175
                return to_load_error_http_path(str);
1941
175
            }
1942
237k
        }
1943
147k
    }
1944
53.7k
    return "";
1945
53.9k
}
1946
1947
53.9k
std::string PipelineFragmentContext::get_first_error_msg() {
1948
53.9k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
1949
0
        return str;
1950
0
    }
1951
147k
    for (auto& tasks : _tasks) {
1952
237k
        for (auto& task : tasks) {
1953
237k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
1954
175
                return str;
1955
175
            }
1956
237k
        }
1957
147k
    }
1958
53.7k
    return "";
1959
53.9k
}
1960
1961
436k
Status PipelineFragmentContext::send_report(bool done) {
1962
436k
    Status exec_status = _query_ctx->exec_status();
1963
    // If plan is done successfully, but _is_report_success is false,
1964
    // no need to send report.
1965
    // Load will set _is_report_success to true because load wants to know
1966
    // the process.
1967
436k
    if (!_is_report_success && done && exec_status.ok()) {
1968
387k
        return Status::OK();
1969
387k
    }
1970
1971
    // If both _is_report_success and _is_report_on_cancel are false,
1972
    // which means no matter query is success or failed, no report is needed.
1973
    // This may happen when the query limit reached and
1974
    // a internal cancellation being processed
1975
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
1976
    // be set to false, to avoid sending fault report to FE.
1977
48.4k
    if (!_is_report_success && !_is_report_on_cancel) {
1978
506
        if (done) {
1979
            // 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.
1980
506
            return Status::OK();
1981
506
        }
1982
0
        return Status::NeedSendAgain("");
1983
506
    }
1984
1985
47.9k
    std::vector<RuntimeState*> runtime_states;
1986
1987
125k
    for (auto& tasks : _tasks) {
1988
186k
        for (auto& task : tasks) {
1989
186k
            runtime_states.push_back(task.second.get());
1990
186k
        }
1991
125k
    }
1992
1993
47.9k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
1994
47.9k
                                        ? get_load_error_url()
1995
18.4E
                                        : _query_ctx->get_load_error_url();
1996
47.9k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
1997
47.9k
                                          ? get_first_error_msg()
1998
18.4E
                                          : _query_ctx->get_first_error_msg();
1999
2000
47.9k
    ReportStatusRequest req {.status = exec_status,
2001
47.9k
                             .runtime_states = runtime_states,
2002
47.9k
                             .done = done || !exec_status.ok(),
2003
47.9k
                             .coord_addr = _query_ctx->coord_addr,
2004
47.9k
                             .query_id = _query_id,
2005
47.9k
                             .fragment_id = _fragment_id,
2006
47.9k
                             .fragment_instance_id = TUniqueId(),
2007
47.9k
                             .backend_num = -1,
2008
47.9k
                             .runtime_state = _runtime_state.get(),
2009
47.9k
                             .load_error_url = load_eror_url,
2010
47.9k
                             .first_error_msg = first_error_msg,
2011
47.9k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2012
2013
47.9k
    return _report_status_cb(
2014
47.9k
            req, std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()));
2015
48.4k
}
2016
2017
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2018
0
    size_t res = 0;
2019
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2020
    // here to traverse the vector.
2021
0
    for (const auto& task_instances : _tasks) {
2022
0
        for (const auto& task : task_instances) {
2023
0
            if (task.first->is_running()) {
2024
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2025
0
                                      << " is running, task: " << (void*)task.first.get()
2026
0
                                      << ", is_running: " << task.first->is_running();
2027
0
                *has_running_task = true;
2028
0
                return 0;
2029
0
            }
2030
2031
0
            size_t revocable_size = task.first->get_revocable_size();
2032
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2033
0
                res += revocable_size;
2034
0
            }
2035
0
        }
2036
0
    }
2037
0
    return res;
2038
0
}
2039
2040
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2041
0
    std::vector<PipelineTask*> revocable_tasks;
2042
0
    for (const auto& task_instances : _tasks) {
2043
0
        for (const auto& task : task_instances) {
2044
0
            size_t revocable_size_ = task.first->get_revocable_size();
2045
2046
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2047
0
                revocable_tasks.emplace_back(task.first.get());
2048
0
            }
2049
0
        }
2050
0
    }
2051
0
    return revocable_tasks;
2052
0
}
2053
2054
88
std::string PipelineFragmentContext::debug_string() {
2055
88
    std::lock_guard<std::mutex> l(_task_mutex);
2056
88
    fmt::memory_buffer debug_string_buffer;
2057
88
    fmt::format_to(debug_string_buffer,
2058
88
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2059
88
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2060
88
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2061
388
    for (size_t j = 0; j < _tasks.size(); j++) {
2062
300
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2063
1.11k
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2064
819
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2065
819
                           _tasks[j][i].first->debug_string());
2066
819
        }
2067
300
    }
2068
2069
88
    return fmt::to_string(debug_string_buffer);
2070
88
}
2071
2072
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2073
2.53k
PipelineFragmentContext::collect_realtime_profile() const {
2074
2.53k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2075
2076
    // we do not have mutex to protect pipeline_id_to_profile
2077
    // so we need to make sure this funciton is invoked after fragment context
2078
    // has already been prepared.
2079
2.53k
    if (!_prepared) {
2080
0
        std::string msg =
2081
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2082
0
        DCHECK(false) << msg;
2083
0
        LOG_ERROR(msg);
2084
0
        return res;
2085
0
    }
2086
2087
    // Make sure first profile is fragment level profile
2088
2.53k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2089
2.53k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2090
2.53k
    res.push_back(fragment_profile);
2091
2092
    // pipeline_id_to_profile is initialized in prepare stage
2093
4.71k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2094
4.71k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2095
4.71k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2096
4.71k
        res.push_back(profile_ptr);
2097
4.71k
    }
2098
2099
2.53k
    return res;
2100
2.53k
}
2101
2102
std::shared_ptr<TRuntimeProfileTree>
2103
2.53k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2104
    // we do not have mutex to protect pipeline_id_to_profile
2105
    // so we need to make sure this funciton is invoked after fragment context
2106
    // has already been prepared.
2107
2.53k
    if (!_prepared) {
2108
0
        std::string msg =
2109
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2110
0
        DCHECK(false) << msg;
2111
0
        LOG_ERROR(msg);
2112
0
        return nullptr;
2113
0
    }
2114
2115
10.8k
    for (const auto& tasks : _tasks) {
2116
21.6k
        for (const auto& task : tasks) {
2117
21.6k
            if (task.second->load_channel_profile() == nullptr) {
2118
0
                continue;
2119
0
            }
2120
2121
21.6k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2122
2123
21.6k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2124
21.6k
                                                           _runtime_state->profile_level());
2125
21.6k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2126
21.6k
        }
2127
10.8k
    }
2128
2129
2.53k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2130
2.53k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2131
2.53k
                                                      _runtime_state->profile_level());
2132
2.53k
    return load_channel_profile;
2133
2.53k
}
2134
2135
// Collect runtime filter IDs registered by all tasks in this PFC.
2136
// Used during recursive CTE stage transitions to know which filters to deregister
2137
// before creating the new PFC for the next recursion round.
2138
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2139
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2140
// the vector sizes do not change, and individual RuntimeState filter sets are
2141
// written only during open() which has completed by the time we reach rerun.
2142
3.18k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2143
3.18k
    std::set<int> result;
2144
7.16k
    for (const auto& _task : _tasks) {
2145
14.9k
        for (const auto& task : _task) {
2146
14.9k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2147
14.9k
            result.merge(set);
2148
14.9k
        }
2149
7.16k
    }
2150
3.18k
    if (_runtime_state) {
2151
3.18k
        auto set = _runtime_state->get_deregister_runtime_filter();
2152
3.18k
        result.merge(set);
2153
3.18k
    }
2154
3.18k
    return result;
2155
3.18k
}
2156
2157
435k
void PipelineFragmentContext::_release_resource() {
2158
435k
    std::lock_guard<std::mutex> l(_task_mutex);
2159
    // The memory released by the query end is recorded in the query mem tracker.
2160
435k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2161
435k
    auto st = _query_ctx->exec_status();
2162
1.22M
    for (auto& _task : _tasks) {
2163
1.22M
        if (!_task.empty()) {
2164
1.22M
            _call_back(_task.front().first->runtime_state(), &st);
2165
1.22M
        }
2166
1.22M
    }
2167
435k
    _tasks.clear();
2168
435k
    _dag.clear();
2169
435k
    _pip_id_to_pipeline.clear();
2170
435k
    _pipelines.clear();
2171
435k
    _sink.reset();
2172
435k
    _root_op.reset();
2173
435k
    _runtime_filter_mgr_map.clear();
2174
435k
    _op_id_to_shared_state.clear();
2175
435k
}
2176
2177
} // namespace doris