Coverage Report

Created: 2026-04-03 05:40

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/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"
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#include "exec/operator/partitioned_hash_join_probe_operator.h"
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#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"
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#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
#include "common/compile_check_begin.h"
131
PipelineFragmentContext::PipelineFragmentContext(
132
        TUniqueId query_id, const TPipelineFragmentParams& request,
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        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
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        const std::function<void(RuntimeState*, Status*)>& call_back,
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        report_status_callback report_status_cb)
136
427k
        : _query_id(std::move(query_id)),
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427k
          _fragment_id(request.fragment_id),
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427k
          _exec_env(exec_env),
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427k
          _query_ctx(std::move(query_ctx)),
140
427k
          _call_back(call_back),
141
427k
          _is_report_on_cancel(true),
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427k
          _report_status_cb(std::move(report_status_cb)),
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427k
          _params(request),
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427k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
145
427k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
146
427k
                                                               : false) {
147
427k
    _fragment_watcher.start();
148
427k
}
149
150
427k
PipelineFragmentContext::~PipelineFragmentContext() {
151
427k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
152
427k
            .tag("query_id", print_id(_query_id))
153
427k
            .tag("fragment_id", _fragment_id);
154
427k
    _release_resource();
155
427k
    {
156
        // The memory released by the query end is recorded in the query mem tracker.
157
427k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
158
427k
        _runtime_state.reset();
159
427k
        _query_ctx.reset();
160
427k
    }
161
427k
}
162
163
70
bool PipelineFragmentContext::is_timeout(timespec now) const {
164
70
    if (_timeout <= 0) {
165
0
        return false;
166
0
    }
167
70
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
168
70
}
169
170
// notify_close() transitions the PFC from "waiting for external close notification" to
171
// "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).
174
9.57k
bool PipelineFragmentContext::notify_close() {
175
9.57k
    bool all_closed = false;
176
9.57k
    bool need_remove = false;
177
9.57k
    {
178
9.57k
        std::lock_guard<std::mutex> l(_task_mutex);
179
9.57k
        if (_closed_tasks >= _total_tasks) {
180
3.50k
            if (_need_notify_close) {
181
                // Fragment was cancelled and waiting for notify to close.
182
                // Record that we need to remove from fragment mgr, but do it
183
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
185
                // first, then _task_mutex via debug_string()).
186
3.40k
                need_remove = true;
187
3.40k
            }
188
3.50k
            all_closed = true;
189
3.50k
        }
190
        // make fragment release by self after cancel
191
9.57k
        _need_notify_close = false;
192
9.57k
    }
193
9.57k
    if (need_remove) {
194
3.40k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
195
3.40k
    }
196
9.57k
    return all_closed;
197
9.57k
}
198
199
// Must not add lock in this method. Because it will call query ctx cancel. And
200
// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
201
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
203
6.09k
void PipelineFragmentContext::cancel(const Status reason) {
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6.09k
    LOG_INFO("PipelineFragmentContext::cancel")
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6.09k
            .tag("query_id", print_id(_query_id))
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6.09k
            .tag("fragment_id", _fragment_id)
207
6.09k
            .tag("reason", reason.to_string());
208
6.09k
    if (notify_close()) {
209
116
        return;
210
116
    }
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    // Timeout is a special error code, we need print current stack to debug timeout issue.
212
5.98k
    if (reason.is<ErrorCode::TIMEOUT>()) {
213
8
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
214
8
                                   debug_string());
215
8
        LOG_LONG_STRING(WARNING, dbg_str);
216
8
    }
217
218
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
219
5.98k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
220
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
221
0
                    debug_string());
222
0
    }
223
224
5.98k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
225
12
        print_profile("cancel pipeline, reason: " + reason.to_string());
226
12
    }
227
228
5.98k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
229
24
        _query_ctx->set_load_error_url(error_url);
230
24
    }
231
232
5.98k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
233
24
        _query_ctx->set_first_error_msg(first_error_msg);
234
24
    }
235
236
5.98k
    _query_ctx->cancel(reason, _fragment_id);
237
5.98k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
238
468
        _is_report_on_cancel = false;
239
5.51k
    } else {
240
22.0k
        for (auto& id : _fragment_instance_ids) {
241
22.0k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
242
22.0k
        }
243
5.51k
    }
244
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
245
    // For stream load the fragment's query_id == load id, it is set in FE.
246
5.98k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
247
5.98k
    if (stream_load_ctx != nullptr) {
248
32
        stream_load_ctx->pipe->cancel(reason.to_string());
249
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
250
        // We need to set the error URL at this point to ensure error information is properly
251
        // propagated to the client.
252
32
        stream_load_ctx->error_url = get_load_error_url();
253
32
        stream_load_ctx->first_error_msg = get_first_error_msg();
254
32
    }
255
256
23.3k
    for (auto& tasks : _tasks) {
257
48.9k
        for (auto& task : tasks) {
258
48.9k
            task.first->unblock_all_dependencies();
259
48.9k
        }
260
23.3k
    }
261
5.98k
}
262
263
675k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
264
675k
    PipelineId id = _next_pipeline_id++;
265
675k
    auto pipeline = std::make_shared<Pipeline>(
266
675k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
267
675k
            parent ? parent->num_tasks() : _num_instances);
268
675k
    if (idx >= 0) {
269
123k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
270
552k
    } else {
271
552k
        _pipelines.emplace_back(pipeline);
272
552k
    }
273
675k
    if (parent) {
274
243k
        parent->set_children(pipeline);
275
243k
    }
276
675k
    return pipeline;
277
675k
}
278
279
426k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
280
426k
    {
281
426k
        SCOPED_TIMER(_build_pipelines_timer);
282
        // 2. Build pipelines with operators in this fragment.
283
426k
        auto root_pipeline = add_pipeline();
284
426k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
285
426k
                                         &_root_op, root_pipeline));
286
287
        // 3. Create sink operator
288
426k
        if (!_params.fragment.__isset.output_sink) {
289
0
            return Status::InternalError("No output sink in this fragment!");
290
0
        }
291
426k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
292
426k
                                          _params.fragment.output_exprs, _params,
293
426k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
294
426k
                                          *_desc_tbl, root_pipeline->id()));
295
426k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
296
426k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
297
298
551k
        for (PipelinePtr& pipeline : _pipelines) {
299
18.4E
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
300
551k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
301
551k
        }
302
426k
    }
303
    // 4. Build local exchanger
304
426k
    if (_runtime_state->enable_local_shuffle()) {
305
425k
        SCOPED_TIMER(_plan_local_exchanger_timer);
306
425k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
307
425k
                                             _params.bucket_seq_to_instance_idx,
308
425k
                                             _params.shuffle_idx_to_instance_idx));
309
425k
    }
310
311
    // 5. Initialize global states in pipelines.
312
677k
    for (PipelinePtr& pipeline : _pipelines) {
313
677k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
314
677k
        pipeline->children().clear();
315
677k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
316
677k
    }
317
318
425k
    {
319
425k
        SCOPED_TIMER(_build_tasks_timer);
320
        // 6. Build pipeline tasks and initialize local state.
321
425k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
322
425k
    }
323
324
425k
    return Status::OK();
325
425k
}
326
327
427k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
328
427k
    if (_prepared) {
329
0
        return Status::InternalError("Already prepared");
330
0
    }
331
427k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
332
427k
        _timeout = _params.query_options.execution_timeout;
333
427k
    }
334
335
427k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
336
427k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
337
427k
    SCOPED_TIMER(_prepare_timer);
338
427k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
339
427k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
340
427k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
341
427k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
342
427k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
343
427k
    {
344
427k
        SCOPED_TIMER(_init_context_timer);
345
427k
        cast_set(_num_instances, _params.local_params.size());
346
427k
        _total_instances =
347
427k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
348
349
427k
        auto* fragment_context = this;
350
351
427k
        if (_params.query_options.__isset.is_report_success) {
352
425k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
353
425k
        }
354
355
        // 1. Set up the global runtime state.
356
427k
        _runtime_state = RuntimeState::create_unique(
357
427k
                _params.query_id, _params.fragment_id, _params.query_options,
358
427k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
359
427k
        _runtime_state->set_task_execution_context(shared_from_this());
360
427k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
361
427k
        if (_params.__isset.backend_id) {
362
424k
            _runtime_state->set_backend_id(_params.backend_id);
363
424k
        }
364
427k
        if (_params.__isset.import_label) {
365
236
            _runtime_state->set_import_label(_params.import_label);
366
236
        }
367
427k
        if (_params.__isset.db_name) {
368
188
            _runtime_state->set_db_name(_params.db_name);
369
188
        }
370
427k
        if (_params.__isset.load_job_id) {
371
0
            _runtime_state->set_load_job_id(_params.load_job_id);
372
0
        }
373
374
427k
        if (_params.is_simplified_param) {
375
142k
            _desc_tbl = _query_ctx->desc_tbl;
376
284k
        } else {
377
284k
            DCHECK(_params.__isset.desc_tbl);
378
284k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
379
284k
                                                  &_desc_tbl));
380
284k
        }
381
427k
        _runtime_state->set_desc_tbl(_desc_tbl);
382
427k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
383
427k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
384
427k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
385
427k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
386
387
        // init fragment_instance_ids
388
427k
        const auto target_size = _params.local_params.size();
389
427k
        _fragment_instance_ids.resize(target_size);
390
1.57M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
391
1.14M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
392
1.14M
            _fragment_instance_ids[i] = fragment_instance_id;
393
1.14M
        }
394
427k
    }
395
396
427k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
397
398
426k
    _init_next_report_time();
399
400
426k
    _prepared = true;
401
426k
    return Status::OK();
402
427k
}
403
404
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
405
        int instance_idx,
406
1.14M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
407
1.14M
    const auto& local_params = _params.local_params[instance_idx];
408
1.14M
    auto fragment_instance_id = local_params.fragment_instance_id;
409
1.14M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
410
1.14M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
411
1.14M
    auto get_shared_state = [&](PipelinePtr pipeline)
412
1.14M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
413
2.03M
                                       std::vector<std::shared_ptr<Dependency>>>> {
414
2.03M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
415
2.03M
                                std::vector<std::shared_ptr<Dependency>>>>
416
2.03M
                shared_state_map;
417
2.57M
        for (auto& op : pipeline->operators()) {
418
2.57M
            auto source_id = op->operator_id();
419
2.57M
            if (auto iter = _op_id_to_shared_state.find(source_id);
420
2.57M
                iter != _op_id_to_shared_state.end()) {
421
827k
                shared_state_map.insert({source_id, iter->second});
422
827k
            }
423
2.57M
        }
424
2.04M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
425
2.04M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
426
2.04M
                iter != _op_id_to_shared_state.end()) {
427
381k
                shared_state_map.insert({sink_to_source_id, iter->second});
428
381k
            }
429
2.04M
        }
430
2.03M
        return shared_state_map;
431
2.03M
    };
432
433
3.62M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
434
2.47M
        auto& pipeline = _pipelines[pip_idx];
435
2.47M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
436
2.03M
            auto task_runtime_state = RuntimeState::create_unique(
437
2.03M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
438
2.03M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
439
2.03M
            {
440
                // Initialize runtime state for this task
441
2.03M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
442
443
2.03M
                task_runtime_state->set_task_execution_context(shared_from_this());
444
2.03M
                task_runtime_state->set_be_number(local_params.backend_num);
445
446
2.03M
                if (_params.__isset.backend_id) {
447
2.03M
                    task_runtime_state->set_backend_id(_params.backend_id);
448
2.03M
                }
449
2.03M
                if (_params.__isset.import_label) {
450
237
                    task_runtime_state->set_import_label(_params.import_label);
451
237
                }
452
2.03M
                if (_params.__isset.db_name) {
453
189
                    task_runtime_state->set_db_name(_params.db_name);
454
189
                }
455
2.03M
                if (_params.__isset.load_job_id) {
456
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
457
0
                }
458
2.03M
                if (_params.__isset.wal_id) {
459
112
                    task_runtime_state->set_wal_id(_params.wal_id);
460
112
                }
461
2.03M
                if (_params.__isset.content_length) {
462
31
                    task_runtime_state->set_content_length(_params.content_length);
463
31
                }
464
465
2.03M
                task_runtime_state->set_desc_tbl(_desc_tbl);
466
2.03M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
467
2.03M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
468
2.03M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
469
2.03M
                task_runtime_state->set_max_operator_id(max_operator_id());
470
2.03M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
471
2.03M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
472
2.03M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
473
474
2.03M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
475
2.03M
            }
476
2.03M
            auto cur_task_id = _total_tasks++;
477
2.03M
            task_runtime_state->set_task_id(cur_task_id);
478
2.03M
            task_runtime_state->set_task_num(pipeline->num_tasks());
479
2.03M
            auto task = std::make_shared<PipelineTask>(
480
2.03M
                    pipeline, cur_task_id, task_runtime_state.get(),
481
2.03M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
482
2.03M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
483
2.03M
                    instance_idx);
484
2.03M
            pipeline->incr_created_tasks(instance_idx, task.get());
485
2.03M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
486
2.03M
            _tasks[instance_idx].emplace_back(
487
2.03M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
488
2.03M
                            std::move(task), std::move(task_runtime_state)});
489
2.03M
        }
490
2.47M
    }
491
492
    /**
493
         * Build DAG for pipeline tasks.
494
         * For example, we have
495
         *
496
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
497
         *            \                      /
498
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
499
         *                 \                          /
500
         *               JoinProbeOperator2 (Pipeline1)
501
         *
502
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
503
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
504
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
505
         *
506
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
507
         * and JoinProbeOperator2.
508
         */
509
2.47M
    for (auto& _pipeline : _pipelines) {
510
2.47M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
511
2.03M
            auto* task = pipeline_id_to_task[_pipeline->id()];
512
2.03M
            DCHECK(task != nullptr);
513
514
            // If this task has upstream dependency, then inject it into this task.
515
2.03M
            if (_dag.contains(_pipeline->id())) {
516
1.33M
                auto& deps = _dag[_pipeline->id()];
517
2.14M
                for (auto& dep : deps) {
518
2.14M
                    if (pipeline_id_to_task.contains(dep)) {
519
1.25M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
520
1.25M
                        if (ss) {
521
499k
                            task->inject_shared_state(ss);
522
753k
                        } else {
523
753k
                            pipeline_id_to_task[dep]->inject_shared_state(
524
753k
                                    task->get_source_shared_state());
525
753k
                        }
526
1.25M
                    }
527
2.14M
                }
528
1.33M
            }
529
2.03M
        }
530
2.47M
    }
531
3.62M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
532
2.47M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
533
2.03M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
534
2.03M
            DCHECK(pipeline_id_to_profile[pip_idx]);
535
2.03M
            std::vector<TScanRangeParams> scan_ranges;
536
2.03M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
537
2.03M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
538
343k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
539
343k
            }
540
2.03M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
541
2.03M
                                                             _params.fragment.output_sink));
542
2.03M
        }
543
2.47M
    }
544
1.14M
    {
545
1.14M
        std::lock_guard<std::mutex> l(_state_map_lock);
546
1.14M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
547
1.14M
    }
548
1.14M
    return Status::OK();
549
1.14M
}
550
551
426k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
552
426k
    _total_tasks = 0;
553
426k
    _closed_tasks = 0;
554
426k
    const auto target_size = _params.local_params.size();
555
426k
    _tasks.resize(target_size);
556
426k
    _runtime_filter_mgr_map.resize(target_size);
557
1.10M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
558
675k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
559
675k
    }
560
426k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
561
562
426k
    if (target_size > 1 &&
563
426k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
564
139k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
565
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
566
16.5k
        std::vector<Status> prepare_status(target_size);
567
16.5k
        int submitted_tasks = 0;
568
16.5k
        Status submit_status;
569
16.5k
        CountDownLatch latch((int)target_size);
570
223k
        for (int i = 0; i < target_size; i++) {
571
207k
            submit_status = thread_pool->submit_func([&, i]() {
572
206k
                SCOPED_ATTACH_TASK(_query_ctx.get());
573
206k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
574
206k
                latch.count_down();
575
206k
            });
576
207k
            if (LIKELY(submit_status.ok())) {
577
207k
                submitted_tasks++;
578
18.4E
            } else {
579
18.4E
                break;
580
18.4E
            }
581
207k
        }
582
16.5k
        latch.arrive_and_wait(target_size - submitted_tasks);
583
16.5k
        if (UNLIKELY(!submit_status.ok())) {
584
0
            return submit_status;
585
0
        }
586
223k
        for (int i = 0; i < submitted_tasks; i++) {
587
207k
            if (!prepare_status[i].ok()) {
588
0
                return prepare_status[i];
589
0
            }
590
207k
        }
591
410k
    } else {
592
1.34M
        for (int i = 0; i < target_size; i++) {
593
939k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
594
939k
        }
595
410k
    }
596
426k
    _pipeline_parent_map.clear();
597
426k
    _op_id_to_shared_state.clear();
598
599
426k
    return Status::OK();
600
426k
}
601
602
424k
void PipelineFragmentContext::_init_next_report_time() {
603
424k
    auto interval_s = config::pipeline_status_report_interval;
604
424k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
605
40.4k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
606
40.4k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
607
        // We don't want to wait longer than it takes to run the entire fragment.
608
40.4k
        _previous_report_time =
609
40.4k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
610
40.4k
        _disable_period_report = false;
611
40.4k
    }
612
424k
}
613
614
4.81k
void PipelineFragmentContext::refresh_next_report_time() {
615
4.81k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
616
4.81k
    DCHECK(disable == true);
617
4.81k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
618
4.81k
    _disable_period_report.compare_exchange_strong(disable, false);
619
4.81k
}
620
621
7.41M
void PipelineFragmentContext::trigger_report_if_necessary() {
622
7.41M
    if (!_is_report_success) {
623
6.87M
        return;
624
6.87M
    }
625
540k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
626
540k
    if (disable) {
627
9.49k
        return;
628
9.49k
    }
629
530k
    int32_t interval_s = config::pipeline_status_report_interval;
630
530k
    if (interval_s <= 0) {
631
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
632
0
                        "trigger "
633
0
                        "report.";
634
0
    }
635
530k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
636
530k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
637
530k
    if (MonotonicNanos() > next_report_time) {
638
4.83k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
639
4.83k
                                                            std::memory_order_acq_rel)) {
640
17
            return;
641
17
        }
642
4.81k
        if (VLOG_FILE_IS_ON) {
643
0
            VLOG_FILE << "Reporting "
644
0
                      << "profile for query_id " << print_id(_query_id)
645
0
                      << ", fragment id: " << _fragment_id;
646
647
0
            std::stringstream ss;
648
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
649
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
650
0
            if (_runtime_state->load_channel_profile()) {
651
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
652
0
            }
653
654
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
655
0
                      << " profile:\n"
656
0
                      << ss.str();
657
0
        }
658
4.81k
        auto st = send_report(false);
659
4.81k
        if (!st.ok()) {
660
0
            disable = true;
661
0
            _disable_period_report.compare_exchange_strong(disable, false,
662
0
                                                           std::memory_order_acq_rel);
663
0
        }
664
4.81k
    }
665
530k
}
666
667
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
668
423k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
669
423k
    if (_params.fragment.plan.nodes.empty()) {
670
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
671
0
    }
672
673
423k
    int node_idx = 0;
674
675
423k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
676
423k
                                        &node_idx, root, cur_pipe, 0, false, false));
677
678
423k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
679
0
        return Status::InternalError(
680
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
681
0
    }
682
423k
    return Status::OK();
683
423k
}
684
685
Status PipelineFragmentContext::_create_tree_helper(
686
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
687
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
688
654k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
689
    // propagate error case
690
654k
    if (*node_idx >= tnodes.size()) {
691
0
        return Status::InternalError(
692
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
693
0
                *node_idx, tnodes.size());
694
0
    }
695
654k
    const TPlanNode& tnode = tnodes[*node_idx];
696
697
654k
    int num_children = tnodes[*node_idx].num_children;
698
654k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
699
654k
    bool current_require_bucket_distribution = require_bucket_distribution;
700
    // TODO: Create CacheOperator is confused now
701
654k
    OperatorPtr op = nullptr;
702
654k
    OperatorPtr cache_op = nullptr;
703
654k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
704
654k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
705
654k
                                     followed_by_shuffled_operator,
706
654k
                                     current_require_bucket_distribution, cache_op));
707
    // Initialization must be done here. For example, group by expressions in agg will be used to
708
    // decide if a local shuffle should be planed, so it must be initialized here.
709
654k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
710
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
711
654k
    if (parent != nullptr) {
712
        // add to parent's child(s)
713
230k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
714
423k
    } else {
715
423k
        *root = op;
716
423k
    }
717
    /**
718
     * `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).
719
     *
720
     * For plan:
721
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
722
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
723
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
724
     *
725
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
726
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
727
     */
728
654k
    auto required_data_distribution =
729
654k
            cur_pipe->operators().empty()
730
654k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
731
654k
                    : op->required_data_distribution(_runtime_state.get());
732
654k
    current_followed_by_shuffled_operator =
733
654k
            ((followed_by_shuffled_operator ||
734
654k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
735
598k
                                             : op->is_shuffled_operator())) &&
736
654k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
737
654k
            (followed_by_shuffled_operator &&
738
546k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
739
740
654k
    current_require_bucket_distribution =
741
654k
            ((require_bucket_distribution ||
742
654k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
743
602k
                                             : op->is_colocated_operator())) &&
744
654k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
654k
            (require_bucket_distribution &&
746
552k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
654k
    if (num_children == 0) {
749
439k
        _use_serial_source = op->is_serial_operator();
750
439k
    }
751
    // rely on that tnodes is preorder of the plan
752
885k
    for (int i = 0; i < num_children; i++) {
753
231k
        ++*node_idx;
754
231k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
755
231k
                                            current_followed_by_shuffled_operator,
756
231k
                                            current_require_bucket_distribution));
757
758
        // we are expecting a child, but have used all nodes
759
        // this means we have been given a bad tree and must fail
760
231k
        if (*node_idx >= tnodes.size()) {
761
0
            return Status::InternalError(
762
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
763
0
                    "nodes: {}",
764
0
                    *node_idx, tnodes.size());
765
0
        }
766
231k
    }
767
768
654k
    return Status::OK();
769
654k
}
770
771
void PipelineFragmentContext::_inherit_pipeline_properties(
772
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
773
123k
        PipelinePtr pipe_with_sink) {
774
123k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
775
123k
    pipe_with_source->set_num_tasks(_num_instances);
776
123k
    pipe_with_source->set_data_distribution(data_distribution);
777
123k
}
778
779
Status PipelineFragmentContext::_add_local_exchange_impl(
780
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
781
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
782
        const std::map<int, int>& bucket_seq_to_instance_idx,
783
122k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
784
122k
    auto& operators = cur_pipe->operators();
785
122k
    const auto downstream_pipeline_id = cur_pipe->id();
786
122k
    auto local_exchange_id = next_operator_id();
787
    // 1. Create a new pipeline with local exchange sink.
788
122k
    DataSinkOperatorPtr sink;
789
122k
    auto sink_id = next_sink_operator_id();
790
791
    /**
792
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
793
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
794
     */
795
122k
    const bool followed_by_shuffled_operator =
796
122k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
797
122k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
798
122k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
799
122k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
800
122k
                                         followed_by_shuffled_operator && !_use_serial_source;
801
122k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
802
122k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
803
122k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
804
122k
    if (bucket_seq_to_instance_idx.empty() &&
805
122k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
806
40
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
807
40
    }
808
122k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
809
122k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
810
122k
                                          num_buckets, use_global_hash_shuffle,
811
122k
                                          shuffle_idx_to_instance_idx));
812
813
    // 2. Create and initialize LocalExchangeSharedState.
814
122k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
815
122k
            LocalExchangeSharedState::create_shared(_num_instances);
816
122k
    switch (data_distribution.distribution_type) {
817
26.2k
    case ExchangeType::HASH_SHUFFLE:
818
26.2k
        shared_state->exchanger = ShuffleExchanger::create_unique(
819
26.2k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
820
26.2k
                use_global_hash_shuffle ? _total_instances : _num_instances,
821
26.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
822
26.2k
                        ? cast_set<int>(
823
26.2k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
824
26.2k
                        : 0);
825
26.2k
        break;
826
438
    case ExchangeType::BUCKET_HASH_SHUFFLE:
827
438
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
828
438
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
829
438
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
438
                        ? cast_set<int>(
831
438
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
438
                        : 0);
833
438
        break;
834
92.5k
    case ExchangeType::PASSTHROUGH:
835
92.5k
        shared_state->exchanger = PassthroughExchanger::create_unique(
836
92.5k
                cur_pipe->num_tasks(), _num_instances,
837
92.5k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
92.5k
                        ? cast_set<int>(
839
92.5k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
92.5k
                        : 0);
841
92.5k
        break;
842
354
    case ExchangeType::BROADCAST:
843
354
        shared_state->exchanger = BroadcastExchanger::create_unique(
844
354
                cur_pipe->num_tasks(), _num_instances,
845
354
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
354
                        ? cast_set<int>(
847
354
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
354
                        : 0);
849
354
        break;
850
2.56k
    case ExchangeType::PASS_TO_ONE:
851
2.56k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
852
            // If shared hash table is enabled for BJ, hash table will be built by only one task
853
1.58k
            shared_state->exchanger = PassToOneExchanger::create_unique(
854
1.58k
                    cur_pipe->num_tasks(), _num_instances,
855
1.58k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
856
1.58k
                            ? cast_set<int>(_runtime_state->query_options()
857
1.58k
                                                    .local_exchange_free_blocks_limit)
858
1.58k
                            : 0);
859
1.58k
        } else {
860
985
            shared_state->exchanger = BroadcastExchanger::create_unique(
861
985
                    cur_pipe->num_tasks(), _num_instances,
862
985
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
863
985
                            ? cast_set<int>(_runtime_state->query_options()
864
984
                                                    .local_exchange_free_blocks_limit)
865
985
                            : 0);
866
985
        }
867
2.56k
        break;
868
928
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
869
928
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
870
928
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
871
928
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
872
928
                        ? cast_set<int>(
873
928
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
874
928
                        : 0);
875
928
        break;
876
0
    default:
877
0
        return Status::InternalError("Unsupported local exchange type : " +
878
0
                                     std::to_string((int)data_distribution.distribution_type));
879
122k
    }
880
123k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
881
123k
                                             "LOCAL_EXCHANGE_OPERATOR");
882
123k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
883
123k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
884
885
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
886
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
887
888
    // 3.1 Initialize new pipeline's operator list.
889
123k
    std::copy(operators.begin(), operators.begin() + idx,
890
123k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
891
892
    // 3.2 Erase unused operators in previous pipeline.
893
123k
    operators.erase(operators.begin(), operators.begin() + idx);
894
895
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
896
123k
    OperatorPtr source_op;
897
123k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
898
123k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
899
123k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
900
123k
    if (!operators.empty()) {
901
44.9k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
902
44.9k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
903
44.9k
    }
904
123k
    operators.insert(operators.begin(), source_op);
905
906
    // 5. Set children for two pipelines separately.
907
123k
    std::vector<std::shared_ptr<Pipeline>> new_children;
908
123k
    std::vector<PipelineId> edges_with_source;
909
140k
    for (auto child : cur_pipe->children()) {
910
140k
        bool found = false;
911
155k
        for (auto op : new_pip->operators()) {
912
155k
            if (child->sink()->node_id() == op->node_id()) {
913
12.6k
                new_pip->set_children(child);
914
12.6k
                found = true;
915
12.6k
            };
916
155k
        }
917
140k
        if (!found) {
918
128k
            new_children.push_back(child);
919
128k
            edges_with_source.push_back(child->id());
920
128k
        }
921
140k
    }
922
123k
    new_children.push_back(new_pip);
923
123k
    edges_with_source.push_back(new_pip->id());
924
925
    // 6. Set DAG for new pipelines.
926
123k
    if (!new_pip->children().empty()) {
927
7.22k
        std::vector<PipelineId> edges_with_sink;
928
12.6k
        for (auto child : new_pip->children()) {
929
12.6k
            edges_with_sink.push_back(child->id());
930
12.6k
        }
931
7.22k
        _dag.insert({new_pip->id(), edges_with_sink});
932
7.22k
    }
933
123k
    cur_pipe->set_children(new_children);
934
123k
    _dag[downstream_pipeline_id] = edges_with_source;
935
123k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
936
123k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
937
123k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
938
939
    // 7. Inherit properties from current pipeline.
940
123k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
941
123k
    return Status::OK();
942
123k
}
943
944
Status PipelineFragmentContext::_add_local_exchange(
945
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
946
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
947
        const std::map<int, int>& bucket_seq_to_instance_idx,
948
188k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
949
188k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
950
43.4k
        return Status::OK();
951
43.4k
    }
952
953
145k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
954
48.2k
        return Status::OK();
955
48.2k
    }
956
96.9k
    *do_local_exchange = true;
957
958
96.9k
    auto& operators = cur_pipe->operators();
959
96.9k
    auto total_op_num = operators.size();
960
96.9k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
961
96.9k
    RETURN_IF_ERROR(_add_local_exchange_impl(
962
96.9k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
963
96.9k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
964
965
96.9k
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
966
122
            << "total_op_num: " << total_op_num
967
122
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
968
122
            << " new_pip->operators().size(): " << new_pip->operators().size();
969
970
    // There are some local shuffles with relatively heavy operations on the sink.
971
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
972
    // Therefore, local passthrough is used to increase the concurrency of the sink.
973
    // op -> local sink(1) -> local source (n)
974
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
975
96.9k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
976
96.9k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
977
26.2k
        RETURN_IF_ERROR(_add_local_exchange_impl(
978
26.2k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
979
26.2k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
980
26.2k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
981
26.2k
                shuffle_idx_to_instance_idx));
982
26.2k
    }
983
96.9k
    return Status::OK();
984
96.9k
}
985
986
Status PipelineFragmentContext::_plan_local_exchange(
987
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
988
423k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
989
973k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
990
549k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
991
        // Set property if child pipeline is not join operator's child.
992
549k
        if (!_pipelines[pip_idx]->children().empty()) {
993
120k
            for (auto& child : _pipelines[pip_idx]->children()) {
994
120k
                if (child->sink()->node_id() ==
995
120k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
996
108k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
997
108k
                }
998
120k
            }
999
116k
        }
1000
1001
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1002
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1003
        // still keep colocate plan after local shuffle
1004
549k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1005
549k
                                             bucket_seq_to_instance_idx,
1006
549k
                                             shuffle_idx_to_instance_idx));
1007
549k
    }
1008
423k
    return Status::OK();
1009
423k
}
1010
1011
Status PipelineFragmentContext::_plan_local_exchange(
1012
        int num_buckets, int pip_idx, PipelinePtr pip,
1013
        const std::map<int, int>& bucket_seq_to_instance_idx,
1014
549k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1015
549k
    int idx = 1;
1016
549k
    bool do_local_exchange = false;
1017
594k
    do {
1018
594k
        auto& ops = pip->operators();
1019
594k
        do_local_exchange = false;
1020
        // Plan local exchange for each operator.
1021
660k
        for (; idx < ops.size();) {
1022
111k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1023
103k
                RETURN_IF_ERROR(_add_local_exchange(
1024
103k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1025
103k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1026
103k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1027
103k
                        shuffle_idx_to_instance_idx));
1028
103k
            }
1029
111k
            if (do_local_exchange) {
1030
                // If local exchange is needed for current operator, we will split this pipeline to
1031
                // two pipelines by local exchange sink/source. And then we need to process remaining
1032
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1033
                // is current operator was already processed) and continue to plan local exchange.
1034
45.1k
                idx = 2;
1035
45.1k
                break;
1036
45.1k
            }
1037
66.1k
            idx++;
1038
66.1k
        }
1039
594k
    } while (do_local_exchange);
1040
549k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1041
84.9k
        RETURN_IF_ERROR(_add_local_exchange(
1042
84.9k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1043
84.9k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1044
84.9k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1045
84.9k
    }
1046
549k
    return Status::OK();
1047
549k
}
1048
1049
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1050
                                                  const std::vector<TExpr>& output_exprs,
1051
                                                  const TPipelineFragmentParams& params,
1052
                                                  const RowDescriptor& row_desc,
1053
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1054
426k
                                                  PipelineId cur_pipeline_id) {
1055
426k
    switch (thrift_sink.type) {
1056
141k
    case TDataSinkType::DATA_STREAM_SINK: {
1057
141k
        if (!thrift_sink.__isset.stream_sink) {
1058
0
            return Status::InternalError("Missing data stream sink.");
1059
0
        }
1060
141k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1061
141k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1062
141k
                params.destinations, _fragment_instance_ids);
1063
141k
        break;
1064
141k
    }
1065
249k
    case TDataSinkType::RESULT_SINK: {
1066
249k
        if (!thrift_sink.__isset.result_sink) {
1067
0
            return Status::InternalError("Missing data buffer sink.");
1068
0
        }
1069
1070
249k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), row_desc,
1071
249k
                                                      output_exprs, thrift_sink.result_sink);
1072
249k
        break;
1073
249k
    }
1074
105
    case TDataSinkType::DICTIONARY_SINK: {
1075
105
        if (!thrift_sink.__isset.dictionary_sink) {
1076
0
            return Status::InternalError("Missing dict sink.");
1077
0
        }
1078
1079
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1080
105
                                                    thrift_sink.dictionary_sink);
1081
105
        break;
1082
105
    }
1083
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1084
30.0k
    case TDataSinkType::OLAP_TABLE_SINK: {
1085
30.0k
        if (state->query_options().enable_memtable_on_sink_node &&
1086
30.0k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1087
30.0k
            !config::is_cloud_mode()) {
1088
2.07k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(pool, next_sink_operator_id(),
1089
2.07k
                                                               row_desc, output_exprs);
1090
27.9k
        } else {
1091
27.9k
            _sink = std::make_shared<OlapTableSinkOperatorX>(pool, next_sink_operator_id(),
1092
27.9k
                                                             row_desc, output_exprs);
1093
27.9k
        }
1094
30.0k
        break;
1095
0
    }
1096
164
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1097
164
        DCHECK(thrift_sink.__isset.olap_table_sink);
1098
164
        DCHECK(state->get_query_ctx() != nullptr);
1099
164
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1100
164
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1101
164
                                                                output_exprs);
1102
164
        break;
1103
0
    }
1104
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1105
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1106
0
            return Status::InternalError("Missing hive table sink.");
1107
0
        }
1108
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1109
1.46k
                                                         output_exprs);
1110
1.46k
        break;
1111
1.46k
    }
1112
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1113
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1114
0
            return Status::InternalError("Missing iceberg table sink.");
1115
0
        }
1116
1.73k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1117
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1118
0
                                                                     row_desc, output_exprs);
1119
1.73k
        } else {
1120
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1121
1.73k
                                                                row_desc, output_exprs);
1122
1.73k
        }
1123
1.73k
        break;
1124
1.73k
    }
1125
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1126
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1127
0
            return Status::InternalError("Missing iceberg delete sink.");
1128
0
        }
1129
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1130
20
                                                             row_desc, output_exprs);
1131
20
        break;
1132
20
    }
1133
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1134
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1135
0
            return Status::InternalError("Missing iceberg merge sink.");
1136
0
        }
1137
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1138
80
                                                            output_exprs);
1139
80
        break;
1140
80
    }
1141
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1142
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1143
0
            return Status::InternalError("Missing max compute table sink.");
1144
0
        }
1145
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1146
0
                                                       output_exprs);
1147
0
        break;
1148
0
    }
1149
80
    case TDataSinkType::JDBC_TABLE_SINK: {
1150
80
        if (!thrift_sink.__isset.jdbc_table_sink) {
1151
0
            return Status::InternalError("Missing data jdbc sink.");
1152
0
        }
1153
80
        if (config::enable_java_support) {
1154
80
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1155
80
                                                             output_exprs);
1156
80
        } else {
1157
0
            return Status::InternalError(
1158
0
                    "Jdbc table sink is not enabled, you can change be config "
1159
0
                    "enable_java_support to true and restart be.");
1160
0
        }
1161
80
        break;
1162
80
    }
1163
80
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1164
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1165
0
            return Status::InternalError("Missing data buffer sink.");
1166
0
        }
1167
1168
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1169
3
                                                             output_exprs);
1170
3
        break;
1171
3
    }
1172
502
    case TDataSinkType::RESULT_FILE_SINK: {
1173
502
        if (!thrift_sink.__isset.result_file_sink) {
1174
0
            return Status::InternalError("Missing result file sink.");
1175
0
        }
1176
1177
        // Result file sink is not the top sink
1178
502
        if (params.__isset.destinations && !params.destinations.empty()) {
1179
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1180
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1181
0
                    params.destinations, output_exprs, desc_tbl);
1182
502
        } else {
1183
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1184
502
                                                              output_exprs);
1185
502
        }
1186
502
        break;
1187
502
    }
1188
1.89k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1189
1.89k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1190
1.89k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1191
1.89k
        auto sink_id = next_sink_operator_id();
1192
1.89k
        const int multi_cast_node_id = sink_id;
1193
1.89k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1194
        // one sink has multiple sources.
1195
1.89k
        std::vector<int> sources;
1196
7.36k
        for (int i = 0; i < sender_size; ++i) {
1197
5.46k
            auto source_id = next_operator_id();
1198
5.46k
            sources.push_back(source_id);
1199
5.46k
        }
1200
1201
1.89k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1202
1.89k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1203
7.36k
        for (int i = 0; i < sender_size; ++i) {
1204
5.46k
            auto new_pipeline = add_pipeline();
1205
            // use to exchange sink
1206
5.46k
            RowDescriptor* exchange_row_desc = nullptr;
1207
5.46k
            {
1208
5.46k
                const auto& tmp_row_desc =
1209
5.46k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1210
5.46k
                                ? RowDescriptor(state->desc_tbl(),
1211
5.46k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1212
5.46k
                                                         .output_tuple_id})
1213
18.4E
                                : row_desc;
1214
5.46k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1215
5.46k
            }
1216
5.46k
            auto source_id = sources[i];
1217
5.46k
            OperatorPtr source_op;
1218
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1219
5.46k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1220
5.46k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1221
5.46k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1222
5.46k
                    /*operator_id=*/source_id);
1223
5.46k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1224
5.46k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1225
            // 2. create and set sink operator of data stream sender for new pipeline
1226
1227
5.46k
            DataSinkOperatorPtr sink_op;
1228
5.46k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1229
5.46k
                    state, *exchange_row_desc, next_sink_operator_id(),
1230
5.46k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1231
5.46k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1232
1233
5.46k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1234
5.46k
            {
1235
5.46k
                TDataSink* t = pool->add(new TDataSink());
1236
5.46k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1237
5.46k
                RETURN_IF_ERROR(sink_op->init(*t));
1238
5.46k
            }
1239
1240
            // 3. set dependency dag
1241
5.46k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1242
5.46k
        }
1243
1.89k
        if (sources.empty()) {
1244
0
            return Status::InternalError("size of sources must be greater than 0");
1245
0
        }
1246
1.89k
        break;
1247
1.89k
    }
1248
1.89k
    case TDataSinkType::BLACKHOLE_SINK: {
1249
13
        if (!thrift_sink.__isset.blackhole_sink) {
1250
0
            return Status::InternalError("Missing blackhole sink.");
1251
0
        }
1252
1253
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1254
13
        break;
1255
13
    }
1256
156
    case TDataSinkType::TVF_TABLE_SINK: {
1257
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1258
0
            return Status::InternalError("Missing TVF table sink.");
1259
0
        }
1260
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1261
156
                                                        output_exprs);
1262
156
        break;
1263
156
    }
1264
0
    default:
1265
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1266
426k
    }
1267
425k
    return Status::OK();
1268
426k
}
1269
1270
// NOLINTBEGIN(readability-function-size)
1271
// NOLINTBEGIN(readability-function-cognitive-complexity)
1272
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1273
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1274
                                                 PipelinePtr& cur_pipe, int parent_idx,
1275
                                                 int child_idx,
1276
                                                 const bool followed_by_shuffled_operator,
1277
                                                 const bool require_bucket_distribution,
1278
658k
                                                 OperatorPtr& cache_op) {
1279
658k
    std::vector<DataSinkOperatorPtr> sink_ops;
1280
658k
    Defer defer = Defer([&]() {
1281
657k
        if (op) {
1282
657k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1283
657k
        }
1284
656k
        for (auto& s : sink_ops) {
1285
120k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1286
120k
        }
1287
656k
    });
1288
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1289
    // Therefore, here we need to use a stack-like structure.
1290
658k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1291
658k
    std::stringstream error_msg;
1292
658k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1293
1294
658k
    bool fe_with_old_version = false;
1295
658k
    switch (tnode.node_type) {
1296
208k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1297
208k
        op = std::make_shared<OlapScanOperatorX>(
1298
208k
                pool, tnode, next_operator_id(), descs, _num_instances,
1299
208k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1300
208k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1301
208k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1302
208k
        break;
1303
208k
    }
1304
77
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1305
77
        DCHECK(_query_ctx != nullptr);
1306
77
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1307
77
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1308
77
                                                    _num_instances);
1309
77
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1310
77
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1311
77
        break;
1312
77
    }
1313
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1314
0
        if (config::enable_java_support) {
1315
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1316
0
                                                     _num_instances);
1317
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1318
0
        } else {
1319
0
            return Status::InternalError(
1320
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1321
0
                    "to true and restart be.");
1322
0
        }
1323
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
0
        break;
1325
0
    }
1326
23.0k
    case TPlanNodeType::FILE_SCAN_NODE: {
1327
23.0k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1328
23.0k
                                                 _num_instances);
1329
23.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1330
23.0k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1331
23.0k
        break;
1332
23.0k
    }
1333
0
    case TPlanNodeType::ES_SCAN_NODE:
1334
592
    case TPlanNodeType::ES_HTTP_SCAN_NODE: {
1335
592
        op = std::make_shared<EsScanOperatorX>(pool, tnode, next_operator_id(), descs,
1336
592
                                               _num_instances);
1337
592
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1338
592
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1339
592
        break;
1340
592
    }
1341
144k
    case TPlanNodeType::EXCHANGE_NODE: {
1342
144k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1343
144k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1344
144k
                                  : 0;
1345
144k
        DCHECK_GT(num_senders, 0);
1346
144k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1347
144k
                                                       num_senders);
1348
144k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1349
144k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1350
144k
        break;
1351
144k
    }
1352
154k
    case TPlanNodeType::AGGREGATION_NODE: {
1353
154k
        if (tnode.agg_node.grouping_exprs.empty() &&
1354
154k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1355
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1356
0
                                         ": group by and output is empty");
1357
0
        }
1358
154k
        bool need_create_cache_op =
1359
154k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1360
154k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1361
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1362
10
            auto cache_source_id = next_operator_id();
1363
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1364
10
                                                        _params.fragment.query_cache_param);
1365
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1366
1367
10
            const auto downstream_pipeline_id = cur_pipe->id();
1368
10
            if (!_dag.contains(downstream_pipeline_id)) {
1369
10
                _dag.insert({downstream_pipeline_id, {}});
1370
10
            }
1371
10
            new_pipe = add_pipeline(cur_pipe);
1372
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1373
1374
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1375
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1376
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1377
10
            return Status::OK();
1378
10
        };
1379
154k
        const bool group_by_limit_opt =
1380
154k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1381
1382
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1383
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1384
154k
        const bool enable_spill = _runtime_state->enable_spill() &&
1385
154k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1386
154k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1387
154k
                                      tnode.agg_node.use_streaming_preaggregation &&
1388
154k
                                      !tnode.agg_node.grouping_exprs.empty();
1389
        // TODO: distinct streaming agg does not support spill.
1390
154k
        const bool can_use_distinct_streaming_agg =
1391
154k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1392
154k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1393
154k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1394
154k
                _params.query_options.enable_distinct_streaming_aggregation;
1395
1396
154k
        if (can_use_distinct_streaming_agg) {
1397
90.9k
            if (need_create_cache_op) {
1398
8
                PipelinePtr new_pipe;
1399
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1400
1401
8
                cache_op = op;
1402
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1403
8
                                                                     tnode, descs);
1404
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1405
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1406
8
                cur_pipe = new_pipe;
1407
90.9k
            } else {
1408
90.9k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1409
90.9k
                                                                     tnode, descs);
1410
90.9k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1411
90.9k
            }
1412
90.9k
        } else if (is_streaming_agg) {
1413
3.42k
            if (need_create_cache_op) {
1414
0
                PipelinePtr new_pipe;
1415
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1416
0
                cache_op = op;
1417
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1418
0
                                                             descs);
1419
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1420
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1421
0
                cur_pipe = new_pipe;
1422
3.42k
            } else {
1423
3.42k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1424
3.42k
                                                             descs);
1425
3.42k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1426
3.42k
            }
1427
60.3k
        } else {
1428
            // create new pipeline to add query cache operator
1429
60.3k
            PipelinePtr new_pipe;
1430
60.3k
            if (need_create_cache_op) {
1431
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1432
2
                cache_op = op;
1433
2
            }
1434
1435
60.3k
            if (enable_spill) {
1436
73
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1437
73
                                                                     next_operator_id(), descs);
1438
60.2k
            } else {
1439
60.2k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1440
60.2k
            }
1441
60.3k
            if (need_create_cache_op) {
1442
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1443
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1444
2
                cur_pipe = new_pipe;
1445
60.3k
            } else {
1446
60.3k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1447
60.3k
            }
1448
1449
60.3k
            const auto downstream_pipeline_id = cur_pipe->id();
1450
60.3k
            if (!_dag.contains(downstream_pipeline_id)) {
1451
58.0k
                _dag.insert({downstream_pipeline_id, {}});
1452
58.0k
            }
1453
60.3k
            cur_pipe = add_pipeline(cur_pipe);
1454
60.3k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1455
1456
60.3k
            if (enable_spill) {
1457
73
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1458
73
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1459
60.2k
            } else {
1460
60.2k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1461
60.2k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1462
60.2k
            }
1463
60.3k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1464
60.3k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1465
60.3k
        }
1466
154k
        break;
1467
154k
    }
1468
154k
    case TPlanNodeType::HASH_JOIN_NODE: {
1469
7.72k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1470
7.72k
                                       tnode.hash_join_node.is_broadcast_join;
1471
7.72k
        const auto enable_spill = _runtime_state->enable_spill();
1472
7.72k
        if (enable_spill && !is_broadcast_join) {
1473
0
            auto tnode_ = tnode;
1474
0
            tnode_.runtime_filters.clear();
1475
0
            auto inner_probe_operator =
1476
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1477
1478
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1479
            // So here use `tnode_` which has no runtime filters.
1480
0
            auto probe_side_inner_sink_operator =
1481
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1482
1483
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1484
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1485
1486
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1487
0
                    pool, tnode_, next_operator_id(), descs);
1488
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1489
0
                                                inner_probe_operator);
1490
0
            op = std::move(probe_operator);
1491
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1492
1493
0
            const auto downstream_pipeline_id = cur_pipe->id();
1494
0
            if (!_dag.contains(downstream_pipeline_id)) {
1495
0
                _dag.insert({downstream_pipeline_id, {}});
1496
0
            }
1497
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1498
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1499
1500
0
            auto inner_sink_operator =
1501
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1502
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1503
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1504
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1505
1506
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1507
0
            sink_ops.push_back(std::move(sink_operator));
1508
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1509
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1510
1511
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1512
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1513
7.72k
        } else {
1514
7.72k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1515
7.72k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1516
1517
7.72k
            const auto downstream_pipeline_id = cur_pipe->id();
1518
7.72k
            if (!_dag.contains(downstream_pipeline_id)) {
1519
6.94k
                _dag.insert({downstream_pipeline_id, {}});
1520
6.94k
            }
1521
7.72k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1522
7.72k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1523
1524
7.72k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1525
7.72k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1526
7.72k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1527
7.72k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1528
1529
7.72k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1530
7.72k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1531
7.72k
        }
1532
7.72k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1533
2.86k
            std::shared_ptr<HashJoinSharedState> shared_state =
1534
2.86k
                    HashJoinSharedState::create_shared(_num_instances);
1535
19.3k
            for (int i = 0; i < _num_instances; i++) {
1536
16.4k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1537
16.4k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1538
16.4k
                sink_dep->set_shared_state(shared_state.get());
1539
16.4k
                shared_state->sink_deps.push_back(sink_dep);
1540
16.4k
            }
1541
2.86k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1542
2.86k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1543
2.86k
            _op_id_to_shared_state.insert(
1544
2.86k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1545
2.86k
        }
1546
7.72k
        break;
1547
7.72k
    }
1548
4.49k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1549
4.49k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1550
4.49k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1551
1552
4.49k
        const auto downstream_pipeline_id = cur_pipe->id();
1553
4.49k
        if (!_dag.contains(downstream_pipeline_id)) {
1554
4.27k
            _dag.insert({downstream_pipeline_id, {}});
1555
4.27k
        }
1556
4.49k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1557
4.49k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1558
1559
4.49k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1560
4.49k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1561
4.49k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1562
4.49k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1563
4.49k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
4.49k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
4.49k
        break;
1566
4.49k
    }
1567
52.0k
    case TPlanNodeType::UNION_NODE: {
1568
52.0k
        int child_count = tnode.num_children;
1569
52.0k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1570
52.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1571
1572
52.0k
        const auto downstream_pipeline_id = cur_pipe->id();
1573
52.0k
        if (!_dag.contains(downstream_pipeline_id)) {
1574
51.6k
            _dag.insert({downstream_pipeline_id, {}});
1575
51.6k
        }
1576
53.7k
        for (int i = 0; i < child_count; i++) {
1577
1.67k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1578
1.67k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1579
1.67k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1580
1.67k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1581
1.67k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1582
1.67k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1583
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1584
1.67k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1585
1.67k
        }
1586
52.0k
        break;
1587
52.0k
    }
1588
52.0k
    case TPlanNodeType::SORT_NODE: {
1589
43.9k
        const auto should_spill = _runtime_state->enable_spill() &&
1590
43.9k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1591
43.9k
        const bool use_local_merge =
1592
43.9k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1593
43.9k
        if (should_spill) {
1594
7
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1595
43.9k
        } else if (use_local_merge) {
1596
41.6k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1597
41.6k
                                                                 descs);
1598
41.6k
        } else {
1599
2.33k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1600
2.33k
        }
1601
43.9k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1602
1603
43.9k
        const auto downstream_pipeline_id = cur_pipe->id();
1604
43.9k
        if (!_dag.contains(downstream_pipeline_id)) {
1605
43.8k
            _dag.insert({downstream_pipeline_id, {}});
1606
43.8k
        }
1607
43.9k
        cur_pipe = add_pipeline(cur_pipe);
1608
43.9k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1609
1610
43.9k
        if (should_spill) {
1611
7
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1612
7
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
43.9k
        } else {
1614
43.9k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1615
43.9k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1616
43.9k
        }
1617
43.9k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1618
43.9k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1619
43.9k
        break;
1620
43.9k
    }
1621
43.9k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1622
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1623
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1624
1625
62
        const auto downstream_pipeline_id = cur_pipe->id();
1626
62
        if (!_dag.contains(downstream_pipeline_id)) {
1627
62
            _dag.insert({downstream_pipeline_id, {}});
1628
62
        }
1629
62
        cur_pipe = add_pipeline(cur_pipe);
1630
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1631
1632
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1633
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1634
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1635
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1636
62
        break;
1637
62
    }
1638
1.61k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1639
1.61k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1640
1.61k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1641
1642
1.61k
        const auto downstream_pipeline_id = cur_pipe->id();
1643
1.61k
        if (!_dag.contains(downstream_pipeline_id)) {
1644
1.59k
            _dag.insert({downstream_pipeline_id, {}});
1645
1.59k
        }
1646
1.61k
        cur_pipe = add_pipeline(cur_pipe);
1647
1.61k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1648
1649
1.61k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1650
1.61k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1651
1.61k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1652
1.61k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1653
1.61k
        break;
1654
1.61k
    }
1655
1.61k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1656
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1657
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1658
1.60k
        break;
1659
1.60k
    }
1660
1.60k
    case TPlanNodeType::INTERSECT_NODE: {
1661
113
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1662
113
                                                                      cur_pipe, sink_ops));
1663
113
        break;
1664
113
    }
1665
125
    case TPlanNodeType::EXCEPT_NODE: {
1666
125
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1667
125
                                                                       cur_pipe, sink_ops));
1668
125
        break;
1669
125
    }
1670
298
    case TPlanNodeType::REPEAT_NODE: {
1671
298
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1672
298
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1673
298
        break;
1674
298
    }
1675
921
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1676
921
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1677
921
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1678
921
        break;
1679
921
    }
1680
921
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1681
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1682
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1683
218
        break;
1684
218
    }
1685
1.57k
    case TPlanNodeType::EMPTY_SET_NODE: {
1686
1.57k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1687
1.57k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1688
1.57k
        break;
1689
1.57k
    }
1690
1.57k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1691
459
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
459
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
459
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1694
459
        break;
1695
459
    }
1696
2.31k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1697
2.31k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1698
2.31k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1699
2.31k
        break;
1700
2.31k
    }
1701
6.46k
    case TPlanNodeType::META_SCAN_NODE: {
1702
6.46k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1703
6.46k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1704
6.46k
        break;
1705
6.46k
    }
1706
6.46k
    case TPlanNodeType::SELECT_NODE: {
1707
1.65k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1708
1.65k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1709
1.65k
        break;
1710
1.65k
    }
1711
1.65k
    case TPlanNodeType::REC_CTE_NODE: {
1712
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1713
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1714
1715
151
        const auto downstream_pipeline_id = cur_pipe->id();
1716
151
        if (!_dag.contains(downstream_pipeline_id)) {
1717
149
            _dag.insert({downstream_pipeline_id, {}});
1718
149
        }
1719
1720
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1721
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1722
1723
151
        DataSinkOperatorPtr anchor_sink;
1724
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1725
151
                                                                  op->operator_id(), tnode, descs);
1726
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1727
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1728
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1729
1730
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1731
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1732
1733
151
        DataSinkOperatorPtr rec_sink;
1734
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1735
151
                                                         tnode, descs);
1736
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1737
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1738
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1739
1740
151
        break;
1741
151
    }
1742
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1743
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1744
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
1.95k
        break;
1746
1.95k
    }
1747
1.95k
    default:
1748
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1749
0
                                     print_plan_node_type(tnode.node_type));
1750
658k
    }
1751
656k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1752
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1753
0
        op->set_serial_operator();
1754
0
    }
1755
1756
656k
    return Status::OK();
1757
658k
}
1758
// NOLINTEND(readability-function-cognitive-complexity)
1759
// NOLINTEND(readability-function-size)
1760
1761
template <bool is_intersect>
1762
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1763
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1764
238
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1765
238
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1766
238
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1767
1768
238
    const auto downstream_pipeline_id = cur_pipe->id();
1769
238
    if (!_dag.contains(downstream_pipeline_id)) {
1770
222
        _dag.insert({downstream_pipeline_id, {}});
1771
222
    }
1772
1773
807
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1774
569
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1775
569
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1776
1777
569
        if (child_id == 0) {
1778
238
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1779
238
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1780
331
        } else {
1781
331
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1782
331
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1783
331
        }
1784
569
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1785
569
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1786
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1787
569
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1788
569
    }
1789
1790
238
    return Status::OK();
1791
238
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1764
113
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1765
113
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1766
113
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1767
1768
113
    const auto downstream_pipeline_id = cur_pipe->id();
1769
113
    if (!_dag.contains(downstream_pipeline_id)) {
1770
105
        _dag.insert({downstream_pipeline_id, {}});
1771
105
    }
1772
1773
417
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1774
304
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1775
304
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1776
1777
304
        if (child_id == 0) {
1778
113
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1779
113
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1780
191
        } else {
1781
191
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1782
191
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1783
191
        }
1784
304
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1785
304
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1786
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1787
304
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1788
304
    }
1789
1790
113
    return Status::OK();
1791
113
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1764
125
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1765
125
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1766
125
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1767
1768
125
    const auto downstream_pipeline_id = cur_pipe->id();
1769
125
    if (!_dag.contains(downstream_pipeline_id)) {
1770
117
        _dag.insert({downstream_pipeline_id, {}});
1771
117
    }
1772
1773
390
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1774
265
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1775
265
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1776
1777
265
        if (child_id == 0) {
1778
125
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1779
125
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1780
140
        } else {
1781
140
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1782
140
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1783
140
        }
1784
265
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1785
265
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1786
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1787
265
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1788
265
    }
1789
1790
125
    return Status::OK();
1791
125
}
1792
1793
423k
Status PipelineFragmentContext::submit() {
1794
423k
    if (_submitted) {
1795
0
        return Status::InternalError("submitted");
1796
0
    }
1797
423k
    _submitted = true;
1798
1799
423k
    int submit_tasks = 0;
1800
423k
    Status st;
1801
423k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1802
1.14M
    for (auto& task : _tasks) {
1803
2.03M
        for (auto& t : task) {
1804
2.03M
            st = scheduler->submit(t.first);
1805
2.03M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1806
2.03M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1807
2.03M
            if (!st) {
1808
0
                cancel(Status::InternalError("submit context to executor fail"));
1809
0
                std::lock_guard<std::mutex> l(_task_mutex);
1810
0
                _total_tasks = submit_tasks;
1811
0
                break;
1812
0
            }
1813
2.03M
            submit_tasks++;
1814
2.03M
        }
1815
1.14M
    }
1816
423k
    if (!st.ok()) {
1817
0
        bool need_remove = false;
1818
0
        {
1819
0
            std::lock_guard<std::mutex> l(_task_mutex);
1820
0
            if (_closed_tasks >= _total_tasks) {
1821
0
                need_remove = _close_fragment_instance();
1822
0
            }
1823
0
        }
1824
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1825
0
        if (need_remove) {
1826
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1827
0
        }
1828
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1829
0
                                     BackendOptions::get_localhost());
1830
423k
    } else {
1831
423k
        return st;
1832
423k
    }
1833
423k
}
1834
1835
12
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1836
12
    if (_runtime_state->enable_profile()) {
1837
0
        std::stringstream ss;
1838
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1839
0
            runtime_profile_ptr->pretty_print(&ss);
1840
0
        }
1841
1842
0
        if (_runtime_state->load_channel_profile()) {
1843
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1844
0
        }
1845
1846
0
        auto profile_str =
1847
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1848
0
                            this->_fragment_id, extra_info, ss.str());
1849
0
        LOG_LONG_STRING(INFO, profile_str);
1850
0
    }
1851
12
}
1852
// If all pipeline tasks binded to the fragment instance are finished, then we could
1853
// close the fragment instance.
1854
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1855
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1856
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1857
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1858
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1859
// (via debug_string()).
1860
426k
bool PipelineFragmentContext::_close_fragment_instance() {
1861
426k
    if (_is_fragment_instance_closed) {
1862
0
        return false;
1863
0
    }
1864
426k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1865
426k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1866
426k
    if (!_need_notify_close) {
1867
423k
        auto st = send_report(true);
1868
423k
        if (!st) {
1869
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1870
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1871
0
        }
1872
423k
    }
1873
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1874
    // Since stream load does not have someting like coordinator on FE, so
1875
    // backend can not report profile to FE, ant its profile can not be shown
1876
    // in the same way with other query. So we print the profile content to info log.
1877
1878
426k
    if (_runtime_state->enable_profile() &&
1879
426k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1880
2.53k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1881
2.53k
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1882
0
        std::stringstream ss;
1883
        // Compute the _local_time_percent before pretty_print the runtime_profile
1884
        // Before add this operation, the print out like that:
1885
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1886
        // After add the operation, the print out like that:
1887
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1888
        // We can easily know the exec node execute time without child time consumed.
1889
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1890
0
            runtime_profile_ptr->pretty_print(&ss);
1891
0
        }
1892
1893
0
        if (_runtime_state->load_channel_profile()) {
1894
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1895
0
        }
1896
1897
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1898
0
    }
1899
1900
426k
    if (_query_ctx->enable_profile()) {
1901
2.53k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1902
2.53k
                                         collect_realtime_load_channel_profile());
1903
2.53k
    }
1904
1905
    // Return whether the caller needs to remove from the pipeline map.
1906
    // The caller must do this after releasing _task_mutex.
1907
426k
    return !_need_notify_close;
1908
426k
}
1909
1910
2.02M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1911
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1912
2.02M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1913
2.02M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1914
676k
        if (_dag.contains(pipeline_id)) {
1915
372k
            for (auto dep : _dag[pipeline_id]) {
1916
372k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1917
372k
            }
1918
291k
        }
1919
676k
    }
1920
2.02M
    bool need_remove = false;
1921
2.02M
    {
1922
2.02M
        std::lock_guard<std::mutex> l(_task_mutex);
1923
2.02M
        ++_closed_tasks;
1924
2.02M
        if (_closed_tasks >= _total_tasks) {
1925
426k
            need_remove = _close_fragment_instance();
1926
426k
        }
1927
2.02M
    }
1928
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1929
2.02M
    if (need_remove) {
1930
423k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1931
423k
    }
1932
2.02M
}
1933
1934
52.7k
std::string PipelineFragmentContext::get_load_error_url() {
1935
52.7k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1936
0
        return to_load_error_http_path(str);
1937
0
    }
1938
144k
    for (auto& tasks : _tasks) {
1939
227k
        for (auto& task : tasks) {
1940
227k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1941
166
                return to_load_error_http_path(str);
1942
166
            }
1943
227k
        }
1944
144k
    }
1945
52.5k
    return "";
1946
52.7k
}
1947
1948
52.7k
std::string PipelineFragmentContext::get_first_error_msg() {
1949
52.7k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
1950
0
        return str;
1951
0
    }
1952
144k
    for (auto& tasks : _tasks) {
1953
228k
        for (auto& task : tasks) {
1954
228k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
1955
166
                return str;
1956
166
            }
1957
228k
        }
1958
144k
    }
1959
52.5k
    return "";
1960
52.7k
}
1961
1962
428k
Status PipelineFragmentContext::send_report(bool done) {
1963
428k
    Status exec_status = _query_ctx->exec_status();
1964
    // If plan is done successfully, but _is_report_success is false,
1965
    // no need to send report.
1966
    // Load will set _is_report_success to true because load wants to know
1967
    // the process.
1968
428k
    if (!_is_report_success && done && exec_status.ok()) {
1969
381k
        return Status::OK();
1970
381k
    }
1971
1972
    // If both _is_report_success and _is_report_on_cancel are false,
1973
    // which means no matter query is success or failed, no report is needed.
1974
    // This may happen when the query limit reached and
1975
    // a internal cancellation being processed
1976
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
1977
    // be set to false, to avoid sending fault report to FE.
1978
47.1k
    if (!_is_report_success && !_is_report_on_cancel) {
1979
377
        if (done) {
1980
            // 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.
1981
377
            return Status::OK();
1982
377
        }
1983
0
        return Status::NeedSendAgain("");
1984
377
    }
1985
1986
46.7k
    std::vector<RuntimeState*> runtime_states;
1987
1988
121k
    for (auto& tasks : _tasks) {
1989
179k
        for (auto& task : tasks) {
1990
179k
            runtime_states.push_back(task.second.get());
1991
179k
        }
1992
121k
    }
1993
1994
46.7k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
1995
46.7k
                                        ? get_load_error_url()
1996
46.7k
                                        : _query_ctx->get_load_error_url();
1997
46.7k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
1998
46.7k
                                          ? get_first_error_msg()
1999
46.7k
                                          : _query_ctx->get_first_error_msg();
2000
2001
46.7k
    ReportStatusRequest req {.status = exec_status,
2002
46.7k
                             .runtime_states = runtime_states,
2003
46.7k
                             .done = done || !exec_status.ok(),
2004
46.7k
                             .coord_addr = _query_ctx->coord_addr,
2005
46.7k
                             .query_id = _query_id,
2006
46.7k
                             .fragment_id = _fragment_id,
2007
46.7k
                             .fragment_instance_id = TUniqueId(),
2008
46.7k
                             .backend_num = -1,
2009
46.7k
                             .runtime_state = _runtime_state.get(),
2010
46.7k
                             .load_error_url = load_eror_url,
2011
46.7k
                             .first_error_msg = first_error_msg,
2012
46.7k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2013
2014
46.7k
    return _report_status_cb(
2015
46.7k
            req, std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()));
2016
47.1k
}
2017
2018
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2019
0
    size_t res = 0;
2020
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2021
    // here to traverse the vector.
2022
0
    for (const auto& task_instances : _tasks) {
2023
0
        for (const auto& task : task_instances) {
2024
0
            if (task.first->is_running()) {
2025
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2026
0
                                      << " is running, task: " << (void*)task.first.get()
2027
0
                                      << ", is_running: " << task.first->is_running();
2028
0
                *has_running_task = true;
2029
0
                return 0;
2030
0
            }
2031
2032
0
            size_t revocable_size = task.first->get_revocable_size();
2033
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2034
0
                res += revocable_size;
2035
0
            }
2036
0
        }
2037
0
    }
2038
0
    return res;
2039
0
}
2040
2041
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2042
0
    std::vector<PipelineTask*> revocable_tasks;
2043
0
    for (const auto& task_instances : _tasks) {
2044
0
        for (const auto& task : task_instances) {
2045
0
            size_t revocable_size_ = task.first->get_revocable_size();
2046
2047
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2048
0
                revocable_tasks.emplace_back(task.first.get());
2049
0
            }
2050
0
        }
2051
0
    }
2052
0
    return revocable_tasks;
2053
0
}
2054
2055
78
std::string PipelineFragmentContext::debug_string() {
2056
78
    std::lock_guard<std::mutex> l(_task_mutex);
2057
78
    fmt::memory_buffer debug_string_buffer;
2058
78
    fmt::format_to(debug_string_buffer,
2059
78
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2060
78
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2061
78
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2062
284
    for (size_t j = 0; j < _tasks.size(); j++) {
2063
206
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2064
712
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2065
506
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2066
506
                           _tasks[j][i].first->debug_string());
2067
506
        }
2068
206
    }
2069
2070
78
    return fmt::to_string(debug_string_buffer);
2071
78
}
2072
2073
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2074
2.53k
PipelineFragmentContext::collect_realtime_profile() const {
2075
2.53k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2076
2077
    // we do not have mutex to protect pipeline_id_to_profile
2078
    // so we need to make sure this funciton is invoked after fragment context
2079
    // has already been prepared.
2080
2.53k
    if (!_prepared) {
2081
0
        std::string msg =
2082
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2083
0
        DCHECK(false) << msg;
2084
0
        LOG_ERROR(msg);
2085
0
        return res;
2086
0
    }
2087
2088
    // Make sure first profile is fragment level profile
2089
2.53k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2090
2.53k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2091
2.53k
    res.push_back(fragment_profile);
2092
2093
    // pipeline_id_to_profile is initialized in prepare stage
2094
4.72k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2095
4.72k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2096
4.72k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2097
4.72k
        res.push_back(profile_ptr);
2098
4.72k
    }
2099
2100
2.53k
    return res;
2101
2.53k
}
2102
2103
std::shared_ptr<TRuntimeProfileTree>
2104
2.53k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2105
    // we do not have mutex to protect pipeline_id_to_profile
2106
    // so we need to make sure this funciton is invoked after fragment context
2107
    // has already been prepared.
2108
2.53k
    if (!_prepared) {
2109
0
        std::string msg =
2110
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2111
0
        DCHECK(false) << msg;
2112
0
        LOG_ERROR(msg);
2113
0
        return nullptr;
2114
0
    }
2115
2116
7.59k
    for (const auto& tasks : _tasks) {
2117
15.6k
        for (const auto& task : tasks) {
2118
15.6k
            if (task.second->load_channel_profile() == nullptr) {
2119
0
                continue;
2120
0
            }
2121
2122
15.6k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2123
2124
15.6k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2125
15.6k
                                                           _runtime_state->profile_level());
2126
15.6k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2127
15.6k
        }
2128
7.59k
    }
2129
2130
2.53k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2131
2.53k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2132
2.53k
                                                      _runtime_state->profile_level());
2133
2.53k
    return load_channel_profile;
2134
2.53k
}
2135
2136
// Collect runtime filter IDs registered by all tasks in this PFC.
2137
// Used during recursive CTE stage transitions to know which filters to deregister
2138
// before creating the new PFC for the next recursion round.
2139
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2140
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2141
// the vector sizes do not change, and individual RuntimeState filter sets are
2142
// written only during open() which has completed by the time we reach rerun.
2143
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2144
3.28k
    std::set<int> result;
2145
4.69k
    for (const auto& _task : _tasks) {
2146
7.56k
        for (const auto& task : _task) {
2147
7.56k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2148
7.56k
            result.merge(set);
2149
7.56k
        }
2150
4.69k
    }
2151
3.28k
    if (_runtime_state) {
2152
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2153
3.28k
        result.merge(set);
2154
3.28k
    }
2155
3.28k
    return result;
2156
3.28k
}
2157
2158
428k
void PipelineFragmentContext::_release_resource() {
2159
428k
    std::lock_guard<std::mutex> l(_task_mutex);
2160
    // The memory released by the query end is recorded in the query mem tracker.
2161
428k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2162
428k
    auto st = _query_ctx->exec_status();
2163
1.14M
    for (auto& _task : _tasks) {
2164
1.14M
        if (!_task.empty()) {
2165
1.14M
            _call_back(_task.front().first->runtime_state(), &st);
2166
1.14M
        }
2167
1.14M
    }
2168
428k
    _tasks.clear();
2169
428k
    _dag.clear();
2170
428k
    _pip_id_to_pipeline.clear();
2171
428k
    _pipelines.clear();
2172
428k
    _sink.reset();
2173
428k
    _root_op.reset();
2174
428k
    _runtime_filter_mgr_map.clear();
2175
428k
    _op_id_to_shared_state.clear();
2176
428k
}
2177
2178
#include "common/compile_check_end.h"
2179
} // namespace doris