Coverage Report

Created: 2026-06-02 13:54

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
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// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
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#include "exec/operator/set_source_operator.h"
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#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
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#include "exec/operator/spill_sort_sink_operator.h"
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#include "exec/operator/spill_sort_source_operator.h"
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#include "exec/operator/streaming_aggregation_operator.h"
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#include "exec/operator/table_function_operator.h"
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#include "exec/operator/tvf_table_sink_operator.h"
116
#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
123
#include "exec/spill/spill_file.h"
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#include "io/fs/stream_load_pipe.h"
125
#include "load/stream_load/new_load_stream_mgr.h"
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#include "runtime/exec_env.h"
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#include "runtime/fragment_mgr.h"
128
#include "runtime/result_buffer_mgr.h"
129
#include "runtime/runtime_state.h"
130
#include "runtime/thread_context.h"
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#include "service/backend_options.h"
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#include "util/client_cache.h"
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#include "util/countdown_latch.h"
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#include "util/debug_util.h"
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#include "util/network_util.h"
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#include "util/uid_util.h"
137
138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
140
        TUniqueId query_id, const TPipelineFragmentParams& request,
141
        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
142
        const std::function<void(RuntimeState*, Status*)>& call_back)
143
173k
        : _query_id(std::move(query_id)),
144
173k
          _fragment_id(request.fragment_id),
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173k
          _exec_env(exec_env),
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173k
          _query_ctx(std::move(query_ctx)),
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173k
          _call_back(call_back),
148
173k
          _is_report_on_cancel(true),
149
173k
          _params(request),
150
173k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
173k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
173k
                                                               : false) {
153
173k
    _fragment_watcher.start();
154
173k
}
155
156
173k
PipelineFragmentContext::~PipelineFragmentContext() {
157
173k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
173k
            .tag("query_id", print_id(_query_id))
159
173k
            .tag("fragment_id", _fragment_id);
160
173k
    _release_resource();
161
173k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
173k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
173k
        _runtime_state.reset();
165
173k
        _query_ctx.reset();
166
173k
    }
167
173k
}
168
169
24
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
24
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
24
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
24
}
175
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// notify_close() transitions the PFC from "waiting for external close notification" to
177
// "self-managed close". For recursive CTE fragments, the old PFC is kept alive until
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// the rerun_fragment(wait_for_destroy) RPC calls this to trigger shutdown.
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// Returns true if all tasks have already closed (i.e., the PFC can be safely destroyed).
180
2.57k
bool PipelineFragmentContext::notify_close() {
181
2.57k
    bool all_closed = false;
182
2.57k
    bool need_remove = false;
183
2.57k
    {
184
2.57k
        std::lock_guard<std::mutex> l(_task_mutex);
185
2.57k
        if (_closed_tasks >= _total_tasks) {
186
28
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
192
0
                need_remove = true;
193
0
            }
194
28
            all_closed = true;
195
28
        }
196
        // make fragment release by self after cancel
197
2.57k
        _need_notify_close = false;
198
2.57k
    }
199
2.57k
    if (need_remove) {
200
0
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
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0
    }
202
2.57k
    return all_closed;
203
2.57k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
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// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
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// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
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2.57k
void PipelineFragmentContext::cancel(const Status reason) {
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2.57k
    LOG_INFO("PipelineFragmentContext::cancel")
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2.57k
            .tag("query_id", print_id(_query_id))
212
2.57k
            .tag("fragment_id", _fragment_id)
213
2.57k
            .tag("reason", reason.to_string());
214
2.57k
    if (notify_close()) {
215
28
        return;
216
28
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
2.54k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
0
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
0
                                   debug_string());
221
0
        LOG_LONG_STRING(WARNING, dbg_str);
222
0
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
2.54k
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
226
0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
227
0
                    debug_string());
228
0
    }
229
230
2.54k
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
231
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
232
0
    }
233
234
2.54k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
1
        _query_ctx->set_load_error_url(error_url);
236
1
    }
237
238
2.54k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
1
        _query_ctx->set_first_error_msg(first_error_msg);
240
1
    }
241
242
2.54k
    _query_ctx->cancel(reason, _fragment_id);
243
2.54k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
212
        _is_report_on_cancel = false;
245
2.33k
    } else {
246
17.8k
        for (auto& id : _fragment_instance_ids) {
247
17.8k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
17.8k
        }
249
2.33k
    }
250
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
251
    // For stream load the fragment's query_id == load id, it is set in FE.
252
2.54k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
2.54k
    if (stream_load_ctx != nullptr) {
254
15
        stream_load_ctx->pipe->cancel(reason.to_string());
255
        // Set error URL here because after pipe is cancelled, stream load execution may return early.
256
        // We need to set the error URL at this point to ensure error information is properly
257
        // propagated to the client.
258
15
        stream_load_ctx->error_url = get_load_error_url();
259
15
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
15
    }
261
262
18.1k
    for (auto& tasks : _tasks) {
263
47.3k
        for (auto& task : tasks) {
264
47.3k
            task.first->unblock_all_dependencies();
265
47.3k
        }
266
18.1k
    }
267
2.54k
}
268
269
260k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
260k
    PipelineId id = _next_pipeline_id++;
271
260k
    auto pipeline = std::make_shared<Pipeline>(
272
260k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
260k
            parent ? parent->num_tasks() : _num_instances);
274
260k
    if (idx >= 0) {
275
26.0k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
234k
    } else {
277
234k
        _pipelines.emplace_back(pipeline);
278
234k
    }
279
260k
    if (parent) {
280
81.0k
        parent->set_children(pipeline);
281
81.0k
    }
282
260k
    return pipeline;
283
260k
}
284
285
173k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
173k
    {
287
173k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
173k
        auto root_pipeline = add_pipeline();
290
173k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
173k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
173k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
173k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
173k
                                          _params.fragment.output_exprs, _params,
299
173k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
173k
                                          *_desc_tbl, root_pipeline->id()));
301
173k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
173k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
234k
        for (PipelinePtr& pipeline : _pipelines) {
305
234k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
234k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
234k
        }
308
173k
    }
309
    // 4. Build local exchanger
310
173k
    if (_runtime_state->enable_local_shuffle()) {
311
170k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
170k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
170k
                                             _params.bucket_seq_to_instance_idx,
314
170k
                                             _params.shuffle_idx_to_instance_idx));
315
170k
    }
316
317
    // 5. Initialize global states in pipelines.
318
260k
    for (PipelinePtr& pipeline : _pipelines) {
319
260k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
260k
        pipeline->children().clear();
321
260k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
260k
    }
323
324
172k
    {
325
172k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
172k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
172k
    }
329
330
172k
    return Status::OK();
331
172k
}
332
333
173k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
173k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
173k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
173k
        _timeout = _params.query_options.execution_timeout;
339
173k
    }
340
341
173k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
173k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
173k
    SCOPED_TIMER(_prepare_timer);
344
173k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
173k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
173k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
173k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
173k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
173k
    {
350
173k
        SCOPED_TIMER(_init_context_timer);
351
173k
        cast_set(_num_instances, _params.local_params.size());
352
173k
        _total_instances =
353
173k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
173k
        auto* fragment_context = this;
356
357
173k
        if (_params.query_options.__isset.is_report_success) {
358
172k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
172k
        }
360
361
        // 1. Set up the global runtime state.
362
173k
        _runtime_state = RuntimeState::create_unique(
363
173k
                _params.query_id, _params.fragment_id, _params.query_options,
364
173k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
173k
        _runtime_state->set_task_execution_context(shared_from_this());
366
173k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
173k
        if (_params.__isset.backend_id) {
368
170k
            _runtime_state->set_backend_id(_params.backend_id);
369
170k
        }
370
173k
        if (_params.__isset.import_label) {
371
13
            _runtime_state->set_import_label(_params.import_label);
372
13
        }
373
173k
        if (_params.__isset.db_name) {
374
0
            _runtime_state->set_db_name(_params.db_name);
375
0
        }
376
173k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
173k
        if (_params.is_simplified_param) {
381
46.8k
            _desc_tbl = _query_ctx->desc_tbl;
382
126k
        } else {
383
126k
            DCHECK(_params.__isset.desc_tbl);
384
126k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
126k
                                                  &_desc_tbl));
386
126k
        }
387
173k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
173k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
173k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
173k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
173k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
173k
        const auto target_size = _params.local_params.size();
395
173k
        _fragment_instance_ids.resize(target_size);
396
519k
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
346k
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
346k
            _fragment_instance_ids[i] = fragment_instance_id;
399
346k
        }
400
173k
    }
401
402
173k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
172k
    _init_next_report_time();
405
406
172k
    _prepared = true;
407
172k
    return Status::OK();
408
173k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
346k
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
346k
    const auto& local_params = _params.local_params[instance_idx];
414
346k
    auto fragment_instance_id = local_params.fragment_instance_id;
415
346k
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
346k
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
346k
    auto get_shared_state = [&](PipelinePtr pipeline)
418
346k
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
626k
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
626k
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
626k
                                std::vector<std::shared_ptr<Dependency>>>>
422
626k
                shared_state_map;
423
660k
        for (auto& op : pipeline->operators()) {
424
660k
            auto source_id = op->operator_id();
425
660k
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
660k
                iter != _op_id_to_shared_state.end()) {
427
213k
                shared_state_map.insert({source_id, iter->second});
428
213k
            }
429
660k
        }
430
630k
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
630k
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
630k
                iter != _op_id_to_shared_state.end()) {
433
70.4k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
70.4k
            }
435
630k
        }
436
626k
        return shared_state_map;
437
626k
    };
438
439
1.11M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
768k
        auto& pipeline = _pipelines[pip_idx];
441
768k
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
626k
            auto task_runtime_state = RuntimeState::create_unique(
443
626k
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
626k
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
626k
            {
446
                // Initialize runtime state for this task
447
626k
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
626k
                task_runtime_state->set_task_execution_context(shared_from_this());
450
626k
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
626k
                if (_params.__isset.backend_id) {
453
623k
                    task_runtime_state->set_backend_id(_params.backend_id);
454
623k
                }
455
626k
                if (_params.__isset.import_label) {
456
13
                    task_runtime_state->set_import_label(_params.import_label);
457
13
                }
458
626k
                if (_params.__isset.db_name) {
459
0
                    task_runtime_state->set_db_name(_params.db_name);
460
0
                }
461
626k
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
626k
                if (_params.__isset.wal_id) {
465
0
                    task_runtime_state->set_wal_id(_params.wal_id);
466
0
                }
467
626k
                if (_params.__isset.content_length) {
468
0
                    task_runtime_state->set_content_length(_params.content_length);
469
0
                }
470
471
626k
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
626k
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
626k
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
626k
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
626k
                task_runtime_state->set_max_operator_id(max_operator_id());
476
626k
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
626k
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
626k
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
626k
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
626k
            }
482
626k
            auto cur_task_id = _total_tasks++;
483
626k
            task_runtime_state->set_task_id(cur_task_id);
484
626k
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
626k
            auto task = std::make_shared<PipelineTask>(
486
626k
                    pipeline, cur_task_id, task_runtime_state.get(),
487
626k
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
626k
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
626k
                    instance_idx);
490
626k
            pipeline->incr_created_tasks(instance_idx, task.get());
491
626k
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
626k
            _tasks[instance_idx].emplace_back(
493
626k
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
626k
                            std::move(task), std::move(task_runtime_state)});
495
626k
        }
496
768k
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
768k
    for (auto& _pipeline : _pipelines) {
516
768k
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
626k
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
626k
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
626k
            if (_dag.contains(_pipeline->id())) {
522
423k
                auto& deps = _dag[_pipeline->id()];
523
625k
                for (auto& dep : deps) {
524
625k
                    if (pipeline_id_to_task.contains(dep)) {
525
339k
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
339k
                        if (ss) {
527
207k
                            task->inject_shared_state(ss);
528
207k
                        } else {
529
132k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
132k
                                    task->get_source_shared_state());
531
132k
                        }
532
339k
                    }
533
625k
                }
534
423k
            }
535
626k
        }
536
768k
    }
537
1.11M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
768k
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
626k
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
626k
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
626k
            std::vector<TScanRangeParams> scan_ranges;
542
626k
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
626k
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
139k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
139k
            }
546
626k
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
626k
                                                             _params.fragment.output_sink));
548
626k
        }
549
768k
    }
550
346k
    {
551
346k
        std::lock_guard<std::mutex> l(_state_map_lock);
552
346k
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
346k
    }
554
346k
    return Status::OK();
555
346k
}
556
557
173k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
173k
    _total_tasks = 0;
559
173k
    _closed_tasks = 0;
560
173k
    const auto target_size = _params.local_params.size();
561
173k
    _tasks.resize(target_size);
562
173k
    _runtime_filter_mgr_map.resize(target_size);
563
433k
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
260k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
260k
    }
566
173k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
173k
    if (target_size > 1 &&
569
173k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
26.5k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
571
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
572
1.19k
        std::vector<Status> prepare_status(target_size);
573
1.19k
        int submitted_tasks = 0;
574
1.19k
        Status submit_status;
575
1.19k
        CountDownLatch latch((int)target_size);
576
14.3k
        for (int i = 0; i < target_size; i++) {
577
13.1k
            submit_status = thread_pool->submit_func([&, i]() {
578
13.1k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
13.1k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
13.1k
                latch.count_down();
581
13.1k
            });
582
13.1k
            if (LIKELY(submit_status.ok())) {
583
13.1k
                submitted_tasks++;
584
13.1k
            } else {
585
0
                break;
586
0
            }
587
13.1k
        }
588
1.19k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
1.19k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
14.3k
        for (int i = 0; i < submitted_tasks; i++) {
593
13.1k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
13.1k
        }
597
171k
    } else {
598
505k
        for (int i = 0; i < target_size; i++) {
599
333k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
333k
        }
601
171k
    }
602
173k
    _pipeline_parent_map.clear();
603
173k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
173k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
173k
    return Status::OK();
608
173k
}
609
610
172k
void PipelineFragmentContext::_init_next_report_time() {
611
172k
    auto interval_s = config::pipeline_status_report_interval;
612
172k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
20.4k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
20.4k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
20.4k
        _previous_report_time =
617
20.4k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
20.4k
        _disable_period_report = false;
619
20.4k
    }
620
172k
}
621
622
2.30k
void PipelineFragmentContext::refresh_next_report_time() {
623
2.30k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
2.30k
    DCHECK(disable == true);
625
2.30k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
2.30k
    _disable_period_report.compare_exchange_strong(disable, false);
627
2.30k
}
628
629
2.48M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
2.48M
    if (!_is_report_success) {
631
2.33M
        return;
632
2.33M
    }
633
145k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
145k
    if (disable) {
635
2.68k
        return;
636
2.68k
    }
637
143k
    int32_t interval_s = config::pipeline_status_report_interval;
638
143k
    if (interval_s <= 0) {
639
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
640
0
                        "trigger "
641
0
                        "report.";
642
0
    }
643
143k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
143k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
143k
    if (MonotonicNanos() > next_report_time) {
646
2.30k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
2.30k
                                                            std::memory_order_acq_rel)) {
648
1
            return;
649
1
        }
650
2.30k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
2.30k
        auto st = send_report(false);
667
2.30k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
2.30k
    }
673
143k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
172k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
172k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
172k
    int node_idx = 0;
682
683
172k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
172k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
172k
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
687
0
        return Status::InternalError(
688
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
689
0
    }
690
172k
    return Status::OK();
691
172k
}
692
693
Status PipelineFragmentContext::_create_tree_helper(
694
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
695
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
696
241k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
241k
    if (*node_idx >= tnodes.size()) {
699
0
        return Status::InternalError(
700
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
701
0
                *node_idx, tnodes.size());
702
0
    }
703
241k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
241k
    int num_children = tnodes[*node_idx].num_children;
706
241k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
241k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
241k
    OperatorPtr op = nullptr;
710
241k
    OperatorPtr cache_op = nullptr;
711
241k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
241k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
241k
                                     followed_by_shuffled_operator,
714
241k
                                     current_require_bucket_distribution, cache_op));
715
    // Initialization must be done here. For example, group by expressions in agg will be used to
716
    // decide if a local shuffle should be planed, so it must be initialized here.
717
241k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
241k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
68.4k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
172k
    } else {
723
172k
        *root = op;
724
172k
    }
725
    /**
726
     * `ExchangeType::HASH_SHUFFLE` should be used if an operator is followed by a shuffled operator (shuffled hash join, union operator followed by co-located operators).
727
     *
728
     * For plan:
729
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
730
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
731
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
732
     *
733
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
734
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
735
     */
736
241k
    auto required_data_distribution =
737
241k
            cur_pipe->operators().empty()
738
241k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
241k
                    : op->required_data_distribution(_runtime_state.get());
740
241k
    current_followed_by_shuffled_operator =
741
241k
            ((followed_by_shuffled_operator ||
742
241k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
236k
                                             : op->is_shuffled_operator())) &&
744
241k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
241k
            (followed_by_shuffled_operator &&
746
233k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
241k
    current_require_bucket_distribution =
749
241k
            ((require_bucket_distribution ||
750
241k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
237k
                                             : op->is_colocated_operator())) &&
752
241k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
241k
            (require_bucket_distribution &&
754
234k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
241k
    if (num_children == 0) {
757
181k
        _use_serial_source = op->is_serial_operator();
758
181k
    }
759
    // rely on that tnodes is preorder of the plan
760
309k
    for (int i = 0; i < num_children; i++) {
761
68.4k
        ++*node_idx;
762
68.4k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
68.4k
                                            current_followed_by_shuffled_operator,
764
68.4k
                                            current_require_bucket_distribution));
765
766
        // we are expecting a child, but have used all nodes
767
        // this means we have been given a bad tree and must fail
768
68.4k
        if (*node_idx >= tnodes.size()) {
769
0
            return Status::InternalError(
770
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
771
0
                    "nodes: {}",
772
0
                    *node_idx, tnodes.size());
773
0
        }
774
68.4k
    }
775
776
241k
    return Status::OK();
777
241k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
26.0k
        PipelinePtr pipe_with_sink) {
782
26.0k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
26.0k
    pipe_with_source->set_num_tasks(_num_instances);
784
26.0k
    pipe_with_source->set_data_distribution(data_distribution);
785
26.0k
}
786
787
Status PipelineFragmentContext::_add_local_exchange_impl(
788
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
789
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
790
        const std::map<int, int>& bucket_seq_to_instance_idx,
791
26.0k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
26.0k
    auto& operators = cur_pipe->operators();
793
26.0k
    const auto downstream_pipeline_id = cur_pipe->id();
794
26.0k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
26.0k
    DataSinkOperatorPtr sink;
797
26.0k
    auto sink_id = next_sink_operator_id();
798
799
    /**
800
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
801
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
802
     */
803
26.0k
    const bool followed_by_shuffled_operator =
804
26.0k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
26.0k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
26.0k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
26.0k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
26.0k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
26.0k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
26.0k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
26.0k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
26.0k
    if (bucket_seq_to_instance_idx.empty() &&
813
26.0k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
0
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
0
    }
816
26.0k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
26.0k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
26.0k
                                          num_buckets, use_global_hash_shuffle,
819
26.0k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
26.0k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
26.0k
            LocalExchangeSharedState::create_shared(_num_instances);
824
26.0k
    switch (data_distribution.distribution_type) {
825
1.16k
    case ExchangeType::HASH_SHUFFLE:
826
1.16k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
1.16k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
1.16k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
1.16k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
1.16k
                        ? cast_set<int>(
831
1.16k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
1.16k
                        : 0);
833
1.16k
        break;
834
54
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
54
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
54
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
54
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
54
                        ? cast_set<int>(
839
54
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
54
                        : 0);
841
54
        break;
842
23.3k
    case ExchangeType::PASSTHROUGH:
843
23.3k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
23.3k
                cur_pipe->num_tasks(), _num_instances,
845
23.3k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
23.3k
                        ? cast_set<int>(
847
23.3k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
18.4E
                        : 0);
849
23.3k
        break;
850
132
    case ExchangeType::BROADCAST:
851
132
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
132
                cur_pipe->num_tasks(), _num_instances,
853
132
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
132
                        ? cast_set<int>(
855
132
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
132
                        : 0);
857
132
        break;
858
1.05k
    case ExchangeType::PASS_TO_ONE:
859
1.05k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
860
            // If shared hash table is enabled for BJ, hash table will be built by only one task
861
876
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
876
                    cur_pipe->num_tasks(), _num_instances,
863
876
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
876
                            ? cast_set<int>(_runtime_state->query_options()
865
876
                                                    .local_exchange_free_blocks_limit)
866
876
                            : 0);
867
876
        } else {
868
181
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
181
                    cur_pipe->num_tasks(), _num_instances,
870
181
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
181
                            ? cast_set<int>(_runtime_state->query_options()
872
181
                                                    .local_exchange_free_blocks_limit)
873
181
                            : 0);
874
181
        }
875
1.05k
        break;
876
237
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
237
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
237
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
237
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
237
                        ? cast_set<int>(
881
237
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
237
                        : 0);
883
237
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
26.0k
    }
888
26.0k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
26.0k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
26.0k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
26.0k
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
892
893
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
894
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
895
896
    // 3.1 Initialize new pipeline's operator list.
897
26.0k
    std::copy(operators.begin(), operators.begin() + idx,
898
26.0k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
26.0k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
26.0k
    OperatorPtr source_op;
905
26.0k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
26.0k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
26.0k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
26.0k
    if (!operators.empty()) {
909
2.45k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
2.45k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
2.45k
    }
912
26.0k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
26.0k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
26.0k
    std::vector<PipelineId> edges_with_source;
917
31.1k
    for (auto child : cur_pipe->children()) {
918
31.1k
        bool found = false;
919
34.7k
        for (auto op : new_pip->operators()) {
920
34.7k
            if (child->sink()->node_id() == op->node_id()) {
921
3.33k
                new_pip->set_children(child);
922
3.33k
                found = true;
923
3.33k
            };
924
34.7k
        }
925
31.1k
        if (!found) {
926
27.8k
            new_children.push_back(child);
927
27.8k
            edges_with_source.push_back(child->id());
928
27.8k
        }
929
31.1k
    }
930
26.0k
    new_children.push_back(new_pip);
931
26.0k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
26.0k
    if (!new_pip->children().empty()) {
935
1.87k
        std::vector<PipelineId> edges_with_sink;
936
3.32k
        for (auto child : new_pip->children()) {
937
3.32k
            edges_with_sink.push_back(child->id());
938
3.32k
        }
939
1.87k
        _dag.insert({new_pip->id(), edges_with_sink});
940
1.87k
    }
941
26.0k
    cur_pipe->set_children(new_children);
942
26.0k
    _dag[downstream_pipeline_id] = edges_with_source;
943
26.0k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
26.0k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
26.0k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
26.0k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
26.0k
    return Status::OK();
950
26.0k
}
951
952
Status PipelineFragmentContext::_add_local_exchange(
953
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
954
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
955
        const std::map<int, int>& bucket_seq_to_instance_idx,
956
50.3k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
50.3k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
23.7k
        return Status::OK();
959
23.7k
    }
960
961
26.5k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
1.80k
        return Status::OK();
963
1.80k
    }
964
24.7k
    *do_local_exchange = true;
965
966
24.7k
    auto& operators = cur_pipe->operators();
967
24.7k
    auto total_op_num = operators.size();
968
24.7k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
24.7k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
24.7k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
24.7k
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
972
973
18.4E
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
974
18.4E
            << "total_op_num: " << total_op_num
975
18.4E
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
976
18.4E
            << " new_pip->operators().size(): " << new_pip->operators().size();
977
978
    // There are some local shuffles with relatively heavy operations on the sink.
979
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
980
    // Therefore, local passthrough is used to increase the concurrency of the sink.
981
    // op -> local sink(1) -> local source (n)
982
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
983
24.7k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
24.7k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
1.26k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
1.26k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
1.26k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
1.26k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
1.26k
                shuffle_idx_to_instance_idx));
990
1.26k
    }
991
24.7k
    return Status::OK();
992
24.7k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
170k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
401k
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
231k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
231k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
55.0k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
55.0k
                if (child->sink()->node_id() ==
1003
55.0k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
46.7k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
46.7k
                }
1006
55.0k
            }
1007
51.3k
        }
1008
1009
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
1010
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
1011
        // still keep colocate plan after local shuffle
1012
231k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
231k
                                             bucket_seq_to_instance_idx,
1014
231k
                                             shuffle_idx_to_instance_idx));
1015
231k
    }
1016
170k
    return Status::OK();
1017
170k
}
1018
1019
Status PipelineFragmentContext::_plan_local_exchange(
1020
        int num_buckets, int pip_idx, PipelinePtr pip,
1021
        const std::map<int, int>& bucket_seq_to_instance_idx,
1022
231k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
231k
    int idx = 1;
1024
231k
    bool do_local_exchange = false;
1025
233k
    do {
1026
233k
        auto& ops = pip->operators();
1027
233k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
244k
        for (; idx < ops.size();) {
1030
13.3k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
9.40k
                RETURN_IF_ERROR(_add_local_exchange(
1032
9.40k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
9.40k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
9.40k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
9.40k
                        shuffle_idx_to_instance_idx));
1036
9.40k
            }
1037
13.3k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
2.45k
                idx = 2;
1043
2.45k
                break;
1044
2.45k
            }
1045
10.9k
            idx++;
1046
10.9k
        }
1047
233k
    } while (do_local_exchange);
1048
231k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
40.9k
        RETURN_IF_ERROR(_add_local_exchange(
1050
40.9k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
40.9k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
40.9k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
40.9k
    }
1054
231k
    return Status::OK();
1055
231k
}
1056
1057
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1058
                                                  const std::vector<TExpr>& output_exprs,
1059
                                                  const TPipelineFragmentParams& params,
1060
                                                  const RowDescriptor& row_desc,
1061
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1062
173k
                                                  PipelineId cur_pipeline_id) {
1063
173k
    switch (thrift_sink.type) {
1064
44.8k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
44.8k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
44.8k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
44.8k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
44.8k
                params.destinations, _fragment_instance_ids);
1071
44.8k
        break;
1072
44.8k
    }
1073
106k
    case TDataSinkType::RESULT_SINK: {
1074
106k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
106k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
106k
        int child_node_id = pipeline->operators().back()->node_id();
1080
106k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
106k
                                                      row_desc, output_exprs,
1082
106k
                                                      thrift_sink.result_sink);
1083
106k
        break;
1084
106k
    }
1085
58
    case TDataSinkType::DICTIONARY_SINK: {
1086
58
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
58
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
58
                                                    thrift_sink.dictionary_sink);
1092
58
        break;
1093
58
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
16.4k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
16.4k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
16.4k
        int child_node_id = pipeline->operators().back()->node_id();
1098
16.4k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
16.4k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
16.4k
            !_has_row_binlog(thrift_sink.olap_table_sink) && !config::is_cloud_mode()) {
1101
2.78k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.78k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
13.6k
        } else {
1104
13.6k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
13.6k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
13.6k
        }
1107
16.4k
        break;
1108
0
    }
1109
0
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
0
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
0
        DCHECK(state->get_query_ctx() != nullptr);
1112
0
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
0
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
0
                                                                output_exprs);
1115
0
        break;
1116
0
    }
1117
904
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
904
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
904
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
904
                                                         output_exprs);
1123
904
        break;
1124
904
    }
1125
1.48k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.48k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.48k
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1130
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1131
0
                                                                     row_desc, output_exprs);
1132
1.48k
        } else {
1133
1.48k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.48k
                                                                row_desc, output_exprs);
1135
1.48k
        }
1136
1.48k
        break;
1137
1.48k
    }
1138
20
    case TDataSinkType::ICEBERG_DELETE_SINK: {
1139
20
        if (!thrift_sink.__isset.iceberg_delete_sink) {
1140
0
            return Status::InternalError("Missing iceberg delete sink.");
1141
0
        }
1142
20
        _sink = std::make_shared<IcebergDeleteSinkOperatorX>(pool, next_sink_operator_id(),
1143
20
                                                             row_desc, output_exprs);
1144
20
        break;
1145
20
    }
1146
80
    case TDataSinkType::ICEBERG_MERGE_SINK: {
1147
80
        if (!thrift_sink.__isset.iceberg_merge_sink) {
1148
0
            return Status::InternalError("Missing iceberg merge sink.");
1149
0
        }
1150
80
        _sink = std::make_shared<IcebergMergeSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1151
80
                                                            output_exprs);
1152
80
        break;
1153
80
    }
1154
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1155
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1156
0
            return Status::InternalError("Missing max compute table sink.");
1157
0
        }
1158
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1159
0
                                                       output_exprs);
1160
0
        break;
1161
0
    }
1162
88
    case TDataSinkType::JDBC_TABLE_SINK: {
1163
88
        if (!thrift_sink.__isset.jdbc_table_sink) {
1164
0
            return Status::InternalError("Missing data jdbc sink.");
1165
0
        }
1166
88
        if (config::enable_java_support) {
1167
88
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1168
88
                                                             output_exprs);
1169
88
        } else {
1170
0
            return Status::InternalError(
1171
0
                    "Jdbc table sink is not enabled, you can change be config "
1172
0
                    "enable_java_support to true and restart be.");
1173
0
        }
1174
88
        break;
1175
88
    }
1176
88
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1177
0
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
0
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
0
                                                             output_exprs);
1183
0
        break;
1184
0
    }
1185
173
    case TDataSinkType::RESULT_FILE_SINK: {
1186
173
        if (!thrift_sink.__isset.result_file_sink) {
1187
0
            return Status::InternalError("Missing result file sink.");
1188
0
        }
1189
1190
        // Result file sink is not the top sink
1191
173
        if (params.__isset.destinations && !params.destinations.empty()) {
1192
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1193
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1194
0
                    params.destinations, output_exprs, desc_tbl);
1195
173
        } else {
1196
173
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
173
                                                              output_exprs);
1198
173
        }
1199
173
        break;
1200
173
    }
1201
2.06k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.06k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.06k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.06k
        auto sink_id = next_sink_operator_id();
1205
2.06k
        const int multi_cast_node_id = sink_id;
1206
2.06k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.06k
        std::vector<int> sources;
1209
8.25k
        for (int i = 0; i < sender_size; ++i) {
1210
6.18k
            auto source_id = next_operator_id();
1211
6.18k
            sources.push_back(source_id);
1212
6.18k
        }
1213
1214
2.06k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.06k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
8.25k
        for (int i = 0; i < sender_size; ++i) {
1217
6.18k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
6.18k
            RowDescriptor* exchange_row_desc = nullptr;
1220
6.18k
            {
1221
6.18k
                const auto& tmp_row_desc =
1222
6.18k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
6.18k
                                ? RowDescriptor(state->desc_tbl(),
1224
6.18k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
6.18k
                                                         .output_tuple_id})
1226
6.18k
                                : row_desc;
1227
6.18k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
6.18k
            }
1229
6.18k
            auto source_id = sources[i];
1230
6.18k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
6.18k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
6.18k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
6.18k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
6.18k
                    /*operator_id=*/source_id);
1236
6.18k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
6.18k
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1238
            // 2. create and set sink operator of data stream sender for new pipeline
1239
1240
6.18k
            DataSinkOperatorPtr sink_op;
1241
6.18k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
6.18k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
6.18k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
6.18k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
6.18k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
6.18k
            {
1248
6.18k
                TDataSink* t = pool->add(new TDataSink());
1249
6.18k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
6.18k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
6.18k
            }
1252
1253
            // 3. set dependency dag
1254
6.18k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
6.18k
        }
1256
2.06k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.06k
        break;
1260
2.06k
    }
1261
2.06k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
10
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
10
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
10
        break;
1268
10
    }
1269
156
    case TDataSinkType::TVF_TABLE_SINK: {
1270
156
        if (!thrift_sink.__isset.tvf_table_sink) {
1271
0
            return Status::InternalError("Missing TVF table sink.");
1272
0
        }
1273
156
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1274
156
                                                        output_exprs);
1275
156
        break;
1276
156
    }
1277
0
    default:
1278
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1279
173k
    }
1280
173k
    return Status::OK();
1281
173k
}
1282
1283
// NOLINTBEGIN(readability-function-size)
1284
// NOLINTBEGIN(readability-function-cognitive-complexity)
1285
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1286
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1287
                                                 PipelinePtr& cur_pipe, int parent_idx,
1288
                                                 int child_idx,
1289
                                                 const bool followed_by_shuffled_operator,
1290
                                                 const bool require_bucket_distribution,
1291
241k
                                                 OperatorPtr& cache_op) {
1292
241k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
241k
    Defer defer = Defer([&]() {
1294
241k
        if (op) {
1295
241k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
241k
        }
1297
241k
        for (auto& s : sink_ops) {
1298
55.0k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
55.0k
        }
1300
241k
    });
1301
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1302
    // Therefore, here we need to use a stack-like structure.
1303
241k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
241k
    std::stringstream error_msg;
1305
241k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
241k
    bool fe_with_old_version = false;
1308
241k
    switch (tnode.node_type) {
1309
86.0k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
86.0k
        op = std::make_shared<OlapScanOperatorX>(
1311
86.0k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
86.0k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
86.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
86.0k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
86.0k
        break;
1316
86.0k
    }
1317
0
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
0
        DCHECK(_query_ctx != nullptr);
1319
0
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
0
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
0
                                                    _num_instances);
1322
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
0
        break;
1325
0
    }
1326
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1327
0
        if (config::enable_java_support) {
1328
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1329
0
                                                     _num_instances);
1330
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1331
0
        } else {
1332
0
            return Status::InternalError(
1333
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1334
0
                    "to true and restart be.");
1335
0
        }
1336
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1337
0
        break;
1338
0
    }
1339
21.7k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
21.7k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
21.7k
                                                 _num_instances);
1342
21.7k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
21.7k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
21.7k
        break;
1345
21.7k
    }
1346
51.0k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
51.0k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
51.0k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
51.0k
        DCHECK_GT(num_senders, 0);
1351
51.0k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
51.0k
                                                       num_senders);
1353
51.0k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
51.0k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
51.0k
        break;
1356
51.0k
    }
1357
29.3k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
29.3k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
29.3k
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1360
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1361
0
                                         ": group by and output is empty");
1362
0
        }
1363
29.3k
        bool need_create_cache_op =
1364
29.3k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
29.3k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1366
0
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1367
0
            auto cache_source_id = next_operator_id();
1368
0
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1369
0
                                                        _params.fragment.query_cache_param);
1370
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1371
1372
0
            const auto downstream_pipeline_id = cur_pipe->id();
1373
0
            if (!_dag.contains(downstream_pipeline_id)) {
1374
0
                _dag.insert({downstream_pipeline_id, {}});
1375
0
            }
1376
0
            new_pipe = add_pipeline(cur_pipe);
1377
0
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1378
1379
0
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1380
0
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1381
0
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1382
0
            return Status::OK();
1383
0
        };
1384
29.3k
        const bool group_by_limit_opt =
1385
29.3k
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1386
1387
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1388
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1389
29.3k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
29.3k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
29.3k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
29.3k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
29.3k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
29.3k
        const bool can_use_distinct_streaming_agg =
1396
29.3k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
29.3k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
29.3k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
29.3k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
29.3k
        if (can_use_distinct_streaming_agg) {
1402
463
            if (need_create_cache_op) {
1403
0
                PipelinePtr new_pipe;
1404
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
0
                cache_op = op;
1407
0
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
0
                                                                     tnode, descs);
1409
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
0
                cur_pipe = new_pipe;
1412
463
            } else {
1413
463
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
463
                                                                     tnode, descs);
1415
463
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
463
            }
1417
28.8k
        } else if (is_streaming_agg) {
1418
790
            if (need_create_cache_op) {
1419
0
                PipelinePtr new_pipe;
1420
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1421
0
                cache_op = op;
1422
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1423
0
                                                             descs);
1424
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1425
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1426
0
                cur_pipe = new_pipe;
1427
790
            } else {
1428
790
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
790
                                                             descs);
1430
790
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
790
            }
1432
28.0k
        } else {
1433
            // create new pipeline to add query cache operator
1434
28.0k
            PipelinePtr new_pipe;
1435
28.0k
            if (need_create_cache_op) {
1436
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
0
                cache_op = op;
1438
0
            }
1439
1440
28.0k
            if (enable_spill) {
1441
120
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
120
                                                                     next_operator_id(), descs);
1443
27.9k
            } else {
1444
27.9k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
27.9k
            }
1446
28.0k
            if (need_create_cache_op) {
1447
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
0
                cur_pipe = new_pipe;
1450
28.0k
            } else {
1451
28.0k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
28.0k
            }
1453
1454
28.0k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
28.0k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
25.9k
                _dag.insert({downstream_pipeline_id, {}});
1457
25.9k
            }
1458
28.0k
            cur_pipe = add_pipeline(cur_pipe);
1459
28.0k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
28.0k
            if (enable_spill) {
1462
120
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
120
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
27.9k
            } else {
1465
27.9k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
27.9k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
27.9k
            }
1468
28.0k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
28.0k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
28.0k
        }
1471
29.3k
        break;
1472
29.3k
    }
1473
29.3k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
7
        if (tnode.bucketed_agg_node.grouping_exprs.empty()) {
1475
0
            return Status::InternalError(
1476
0
                    "Bucketed aggregation node {} should not be used without group by keys",
1477
0
                    tnode.node_id);
1478
0
        }
1479
1480
        // Create source operator (goes on the current / downstream pipeline).
1481
7
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
7
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
7
        const auto downstream_pipeline_id = cur_pipe->id();
1486
7
        if (!_dag.contains(downstream_pipeline_id)) {
1487
7
            _dag.insert({downstream_pipeline_id, {}});
1488
7
        }
1489
7
        cur_pipe = add_pipeline(cur_pipe);
1490
7
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
7
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
7
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
7
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
7
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1497
1498
        // Pre-register a single shared state for ALL instances so that every
1499
        // sink instance writes its per-instance hash table into the same
1500
        // BucketedAggSharedState and every source instance can merge across
1501
        // all of them.
1502
7
        {
1503
7
            auto shared_state = BucketedAggSharedState::create_shared();
1504
7
            shared_state->id = op->operator_id();
1505
7
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
33
            for (int i = 0; i < _num_instances; i++) {
1508
26
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
26
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
26
                sink_dep->set_shared_state(shared_state.get());
1511
26
                shared_state->sink_deps.push_back(sink_dep);
1512
26
            }
1513
7
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
7
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
7
            _op_id_to_shared_state.insert(
1516
7
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
7
        }
1518
7
        break;
1519
7
    }
1520
3.69k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
3.69k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
3.69k
                                       tnode.hash_join_node.is_broadcast_join;
1523
3.69k
        const auto enable_spill = _runtime_state->enable_spill();
1524
3.69k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
3.69k
        } else {
1566
3.69k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
3.69k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
3.69k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
3.69k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
2.51k
                _dag.insert({downstream_pipeline_id, {}});
1572
2.51k
            }
1573
3.69k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
3.69k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
3.69k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
3.69k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
3.69k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
3.69k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
3.69k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
3.69k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
3.69k
        }
1584
3.69k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
2.91k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
2.91k
                    HashJoinSharedState::create_shared(_num_instances);
1587
13.0k
            for (int i = 0; i < _num_instances; i++) {
1588
10.1k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
10.1k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
10.1k
                sink_dep->set_shared_state(shared_state.get());
1591
10.1k
                shared_state->sink_deps.push_back(sink_dep);
1592
10.1k
            }
1593
2.91k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
2.91k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
2.91k
            _op_id_to_shared_state.insert(
1596
2.91k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
2.91k
        }
1598
3.69k
        break;
1599
3.69k
    }
1600
4.63k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
4.63k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
4.63k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
4.63k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
4.63k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
4.57k
            _dag.insert({downstream_pipeline_id, {}});
1607
4.57k
        }
1608
4.63k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
4.63k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
4.63k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
4.63k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
4.63k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
4.63k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
4.63k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
4.63k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
4.63k
        break;
1618
4.63k
    }
1619
18.6k
    case TPlanNodeType::UNION_NODE: {
1620
18.6k
        int child_count = tnode.num_children;
1621
18.6k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
18.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
18.6k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
18.6k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
18.6k
            _dag.insert({downstream_pipeline_id, {}});
1627
18.6k
        }
1628
19.3k
        for (int i = 0; i < child_count; i++) {
1629
612
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
612
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
612
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
612
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
612
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
612
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
612
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
612
        }
1638
18.6k
        break;
1639
18.6k
    }
1640
18.6k
    case TPlanNodeType::SORT_NODE: {
1641
17.6k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
17.6k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
17.6k
        const bool use_local_merge =
1644
17.6k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
17.6k
        if (should_spill) {
1646
4
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
17.6k
        } else if (use_local_merge) {
1648
17.0k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
17.0k
                                                                 descs);
1650
17.0k
        } else {
1651
629
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
629
        }
1653
17.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
17.6k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
17.6k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
17.6k
            _dag.insert({downstream_pipeline_id, {}});
1658
17.6k
        }
1659
17.6k
        cur_pipe = add_pipeline(cur_pipe);
1660
17.6k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
17.6k
        if (should_spill) {
1663
4
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
4
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
17.6k
        } else {
1666
17.6k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
17.6k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
17.6k
        }
1669
17.6k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
17.6k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
17.6k
        break;
1672
17.6k
    }
1673
17.6k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
7
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
7
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
7
        const auto downstream_pipeline_id = cur_pipe->id();
1678
7
        if (!_dag.contains(downstream_pipeline_id)) {
1679
7
            _dag.insert({downstream_pipeline_id, {}});
1680
7
        }
1681
7
        cur_pipe = add_pipeline(cur_pipe);
1682
7
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
7
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
7
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
7
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
7
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
7
        break;
1689
7
    }
1690
233
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
233
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
233
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
233
        const auto downstream_pipeline_id = cur_pipe->id();
1695
233
        if (!_dag.contains(downstream_pipeline_id)) {
1696
230
            _dag.insert({downstream_pipeline_id, {}});
1697
230
        }
1698
233
        cur_pipe = add_pipeline(cur_pipe);
1699
233
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
233
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
233
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
233
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
233
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
233
        break;
1706
233
    }
1707
1.23k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.23k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.23k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.23k
        break;
1711
1.23k
    }
1712
1.23k
    case TPlanNodeType::INTERSECT_NODE: {
1713
32
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
32
                                                                      cur_pipe, sink_ops));
1715
32
        break;
1716
32
    }
1717
35
    case TPlanNodeType::EXCEPT_NODE: {
1718
35
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
35
                                                                       cur_pipe, sink_ops));
1720
35
        break;
1721
35
    }
1722
35
    case TPlanNodeType::REPEAT_NODE: {
1723
7
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
7
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
7
        break;
1726
7
    }
1727
69
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
69
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
69
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
69
        break;
1731
69
    }
1732
183
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
183
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
183
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
183
        break;
1736
183
    }
1737
611
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
611
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
611
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
611
        break;
1741
611
    }
1742
611
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
297
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
297
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
297
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
297
        break;
1747
297
    }
1748
1.28k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
1.28k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
1.28k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
1.28k
        break;
1752
1.28k
    }
1753
2.22k
    case TPlanNodeType::META_SCAN_NODE: {
1754
2.22k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
2.22k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
2.22k
        break;
1757
2.22k
    }
1758
2.30k
    case TPlanNodeType::SELECT_NODE: {
1759
2.30k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.30k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.30k
        break;
1762
2.30k
    }
1763
2.30k
    case TPlanNodeType::REC_CTE_NODE: {
1764
0
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
0
        const auto downstream_pipeline_id = cur_pipe->id();
1768
0
        if (!_dag.contains(downstream_pipeline_id)) {
1769
0
            _dag.insert({downstream_pipeline_id, {}});
1770
0
        }
1771
1772
0
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
0
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
0
        DataSinkOperatorPtr anchor_sink;
1776
0
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
0
                                                                  op->operator_id(), tnode, descs);
1778
0
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
0
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
0
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
0
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
0
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
0
        DataSinkOperatorPtr rec_sink;
1786
0
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
0
                                                         tnode, descs);
1788
0
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
0
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
0
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
0
        break;
1793
0
    }
1794
0
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
0
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
0
        break;
1798
0
    }
1799
0
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
241k
    }
1803
241k
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1804
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1805
0
        op->set_serial_operator();
1806
0
    }
1807
1808
241k
    return Status::OK();
1809
241k
}
1810
// NOLINTEND(readability-function-cognitive-complexity)
1811
// NOLINTEND(readability-function-size)
1812
1813
template <bool is_intersect>
1814
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1815
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1816
67
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
67
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
67
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
67
    const auto downstream_pipeline_id = cur_pipe->id();
1821
67
    if (!_dag.contains(downstream_pipeline_id)) {
1822
67
        _dag.insert({downstream_pipeline_id, {}});
1823
67
    }
1824
1825
229
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
162
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
162
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
162
        if (child_id == 0) {
1830
67
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
67
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
95
        } else {
1833
95
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
95
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
95
        }
1836
162
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
162
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
162
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
162
    }
1841
1842
67
    return Status::OK();
1843
67
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
32
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
32
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
32
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
32
    const auto downstream_pipeline_id = cur_pipe->id();
1821
32
    if (!_dag.contains(downstream_pipeline_id)) {
1822
32
        _dag.insert({downstream_pipeline_id, {}});
1823
32
    }
1824
1825
110
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
78
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
78
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
78
        if (child_id == 0) {
1830
32
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
32
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
46
        } else {
1833
46
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
46
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
46
        }
1836
78
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
78
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
78
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
78
    }
1841
1842
32
    return Status::OK();
1843
32
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
35
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
35
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
35
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
35
    const auto downstream_pipeline_id = cur_pipe->id();
1821
35
    if (!_dag.contains(downstream_pipeline_id)) {
1822
35
        _dag.insert({downstream_pipeline_id, {}});
1823
35
    }
1824
1825
119
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
84
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
84
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
84
        if (child_id == 0) {
1830
35
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
35
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
49
        } else {
1833
49
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
49
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
49
        }
1836
84
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
84
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
84
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
84
    }
1841
1842
35
    return Status::OK();
1843
35
}
1844
1845
172k
Status PipelineFragmentContext::submit() {
1846
172k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
172k
    _submitted = true;
1850
1851
172k
    int submit_tasks = 0;
1852
172k
    Status st;
1853
172k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
346k
    for (auto& task : _tasks) {
1855
626k
        for (auto& t : task) {
1856
626k
            st = scheduler->submit(t.first);
1857
626k
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
626k
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
626k
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
626k
            submit_tasks++;
1866
626k
        }
1867
346k
    }
1868
172k
    if (!st.ok()) {
1869
0
        bool need_remove = false;
1870
0
        {
1871
0
            std::lock_guard<std::mutex> l(_task_mutex);
1872
0
            if (_closed_tasks >= _total_tasks) {
1873
0
                need_remove = _close_fragment_instance();
1874
0
            }
1875
0
        }
1876
        // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1877
0
        if (need_remove) {
1878
0
            _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1879
0
        }
1880
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1881
0
                                     BackendOptions::get_localhost());
1882
172k
    } else {
1883
172k
        return st;
1884
172k
    }
1885
172k
}
1886
1887
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1888
0
    if (_runtime_state->enable_profile()) {
1889
0
        std::stringstream ss;
1890
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1891
0
            runtime_profile_ptr->pretty_print(&ss);
1892
0
        }
1893
1894
0
        if (_runtime_state->load_channel_profile()) {
1895
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1896
0
        }
1897
1898
0
        auto profile_str =
1899
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1900
0
                            this->_fragment_id, extra_info, ss.str());
1901
0
        LOG_LONG_STRING(INFO, profile_str);
1902
0
    }
1903
0
}
1904
// If all pipeline tasks binded to the fragment instance are finished, then we could
1905
// close the fragment instance.
1906
// Returns true if the caller should call remove_pipeline_context() **after** releasing
1907
// _task_mutex. We must not call remove_pipeline_context() here because it acquires
1908
// _pipeline_map's shard lock, and this function is called while _task_mutex is held.
1909
// Acquiring _pipeline_map while holding _task_mutex creates an ABBA deadlock with
1910
// dump_pipeline_tasks(), which acquires _pipeline_map first and then _task_mutex
1911
// (via debug_string()).
1912
173k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
173k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
173k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
173k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
173k
    if (!_need_notify_close) {
1919
173k
        auto st = send_report(true);
1920
173k
        if (!st) {
1921
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1922
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1923
0
        }
1924
173k
    }
1925
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1926
    // Since stream load does not have someting like coordinator on FE, so
1927
    // backend can not report profile to FE, ant its profile can not be shown
1928
    // in the same way with other query. So we print the profile content to info log.
1929
1930
173k
    if (_runtime_state->enable_profile() &&
1931
173k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
534
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
534
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1934
0
        std::stringstream ss;
1935
        // Compute the _local_time_percent before pretty_print the runtime_profile
1936
        // Before add this operation, the print out like that:
1937
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1938
        // After add the operation, the print out like that:
1939
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1940
        // We can easily know the exec node execute time without child time consumed.
1941
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1942
0
            runtime_profile_ptr->pretty_print(&ss);
1943
0
        }
1944
1945
0
        if (_runtime_state->load_channel_profile()) {
1946
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1947
0
        }
1948
1949
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1950
0
    }
1951
1952
173k
    if (_query_ctx->enable_profile()) {
1953
534
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
534
                                         collect_realtime_load_channel_profile());
1955
534
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
173k
    return !_need_notify_close;
1960
173k
}
1961
1962
624k
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
624k
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
624k
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
260k
        if (_dag.contains(pipeline_id)) {
1967
113k
            for (auto dep : _dag[pipeline_id]) {
1968
113k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
113k
            }
1970
100k
        }
1971
260k
    }
1972
624k
    bool need_remove = false;
1973
624k
    {
1974
624k
        std::lock_guard<std::mutex> l(_task_mutex);
1975
624k
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
624k
        _query_ctx->inc_finished_task_num();
1978
624k
        if (_closed_tasks >= _total_tasks) {
1979
173k
            need_remove = _close_fragment_instance();
1980
173k
        }
1981
624k
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
624k
    if (need_remove) {
1984
173k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
173k
    }
1986
624k
}
1987
1988
25.6k
std::string PipelineFragmentContext::get_load_error_url() {
1989
25.6k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1990
0
        return to_load_error_http_path(str);
1991
0
    }
1992
63.1k
    for (auto& tasks : _tasks) {
1993
100k
        for (auto& task : tasks) {
1994
100k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
21
                return to_load_error_http_path(str);
1996
21
            }
1997
100k
        }
1998
63.1k
    }
1999
25.6k
    return "";
2000
25.6k
}
2001
2002
25.6k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
25.6k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
63.1k
    for (auto& tasks : _tasks) {
2007
100k
        for (auto& task : tasks) {
2008
100k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
21
                return str;
2010
21
            }
2011
100k
        }
2012
63.1k
    }
2013
25.5k
    return "";
2014
25.6k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
23.0k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
23.0k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
23.0k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
23.0k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
23.0k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
23.0k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
23.0k
    });
2031
2032
23.0k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
23.0k
    if (req.coord_addr.hostname == "external") {
2034
        // External query (flink/spark read tablets) not need to report to FE.
2035
0
        return;
2036
0
    }
2037
23.0k
    int callback_retries = 10;
2038
23.0k
    const int sleep_ms = 1000;
2039
23.0k
    Status exec_status = req.status;
2040
23.0k
    Status coord_status;
2041
23.0k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
23.0k
    do {
2043
23.0k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
23.0k
                                                            req.coord_addr, &coord_status);
2045
23.0k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
23.0k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
23.0k
    if (!coord_status.ok()) {
2051
0
        UniqueId uid(req.query_id.hi, req.query_id.lo);
2052
0
        static_cast<void>(req.cancel_fn(Status::InternalError(
2053
0
                "query_id: {}, couldn't get a client for {}, reason is {}", uid.to_string(),
2054
0
                PrintThriftNetworkAddress(req.coord_addr), coord_status.to_string())));
2055
0
        return;
2056
0
    }
2057
2058
23.0k
    TReportExecStatusParams params;
2059
23.0k
    params.protocol_version = FrontendServiceVersion::V1;
2060
23.0k
    params.__set_query_id(req.query_id);
2061
23.0k
    params.__set_backend_num(req.backend_num);
2062
23.0k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
23.0k
    params.__set_fragment_id(req.fragment_id);
2064
23.0k
    params.__set_status(exec_status.to_thrift());
2065
23.0k
    params.__set_done(req.done);
2066
23.0k
    params.__set_query_type(req.runtime_state->query_type());
2067
23.0k
    params.__isset.profile = false;
2068
2069
23.0k
    DCHECK(req.runtime_state != nullptr);
2070
2071
23.0k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
21.8k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
21.8k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
21.8k
    } else {
2075
1.24k
        DCHECK(!req.runtime_states.empty());
2076
1.24k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
1.24k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
1.24k
    }
2086
2087
23.0k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
23.0k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
23.0k
    static std::string s_unselected_rows = "unselected.rows";
2090
23.0k
    int64_t num_rows_load_success = 0;
2091
23.0k
    int64_t num_rows_load_filtered = 0;
2092
23.0k
    int64_t num_rows_load_unselected = 0;
2093
23.0k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
23.0k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
23.0k
        req.runtime_state->num_finished_range() > 0) {
2096
0
        params.__isset.load_counters = true;
2097
2098
0
        num_rows_load_success = req.runtime_state->num_rows_load_success();
2099
0
        num_rows_load_filtered = req.runtime_state->num_rows_load_filtered();
2100
0
        num_rows_load_unselected = req.runtime_state->num_rows_load_unselected();
2101
0
        params.__isset.fragment_instance_reports = true;
2102
0
        TFragmentInstanceReport t;
2103
0
        t.__set_fragment_instance_id(req.runtime_state->fragment_instance_id());
2104
0
        t.__set_num_finished_range(cast_set<int>(req.runtime_state->num_finished_range()));
2105
0
        t.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2106
0
        t.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2107
0
        params.fragment_instance_reports.push_back(t);
2108
23.0k
    } else if (!req.runtime_states.empty()) {
2109
53.0k
        for (auto* rs : req.runtime_states) {
2110
53.0k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
53.0k
                rs->num_finished_range() > 0) {
2112
16.4k
                params.__isset.load_counters = true;
2113
16.4k
                num_rows_load_success += rs->num_rows_load_success();
2114
16.4k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
16.4k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
16.4k
                params.__isset.fragment_instance_reports = true;
2117
16.4k
                TFragmentInstanceReport t;
2118
16.4k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
16.4k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
16.4k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
16.4k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
16.4k
                params.fragment_instance_reports.push_back(t);
2123
16.4k
            }
2124
53.0k
        }
2125
23.0k
    }
2126
23.0k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
23.0k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
23.0k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
23.0k
    if (!req.load_error_url.empty()) {
2131
20
        params.__set_tracking_url(req.load_error_url);
2132
20
    }
2133
23.0k
    if (!req.first_error_msg.empty()) {
2134
20
        params.__set_first_error_msg(req.first_error_msg);
2135
20
    }
2136
52.9k
    for (auto* rs : req.runtime_states) {
2137
52.9k
        if (rs->wal_id() > 0) {
2138
0
            params.__set_txn_id(rs->wal_id());
2139
0
            params.__set_label(rs->import_label());
2140
0
        }
2141
52.9k
    }
2142
23.0k
    if (!req.runtime_state->export_output_files().empty()) {
2143
0
        params.__isset.export_files = true;
2144
0
        params.export_files = req.runtime_state->export_output_files();
2145
23.0k
    } else if (!req.runtime_states.empty()) {
2146
52.9k
        for (auto* rs : req.runtime_states) {
2147
52.9k
            if (!rs->export_output_files().empty()) {
2148
0
                params.__isset.export_files = true;
2149
0
                params.export_files.insert(params.export_files.end(),
2150
0
                                           rs->export_output_files().begin(),
2151
0
                                           rs->export_output_files().end());
2152
0
            }
2153
52.9k
        }
2154
23.0k
    }
2155
23.0k
    if (auto tci = req.runtime_state->tablet_commit_infos(); !tci.empty()) {
2156
0
        params.__isset.commitInfos = true;
2157
0
        params.commitInfos.insert(params.commitInfos.end(), tci.begin(), tci.end());
2158
23.0k
    } else if (!req.runtime_states.empty()) {
2159
53.0k
        for (auto* rs : req.runtime_states) {
2160
53.0k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
12.6k
                params.__isset.commitInfos = true;
2162
12.6k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
12.6k
            }
2164
53.0k
        }
2165
23.0k
    }
2166
23.0k
    if (auto eti = req.runtime_state->error_tablet_infos(); !eti.empty()) {
2167
0
        params.__isset.errorTabletInfos = true;
2168
0
        params.errorTabletInfos.insert(params.errorTabletInfos.end(), eti.begin(), eti.end());
2169
23.0k
    } else if (!req.runtime_states.empty()) {
2170
53.0k
        for (auto* rs : req.runtime_states) {
2171
53.0k
            if (auto rs_eti = rs->error_tablet_infos(); !rs_eti.empty()) {
2172
0
                params.__isset.errorTabletInfos = true;
2173
0
                params.errorTabletInfos.insert(params.errorTabletInfos.end(), rs_eti.begin(),
2174
0
                                               rs_eti.end());
2175
0
            }
2176
53.0k
        }
2177
23.0k
    }
2178
23.0k
    if (auto hpu = req.runtime_state->hive_partition_updates(); !hpu.empty()) {
2179
0
        params.__isset.hive_partition_updates = true;
2180
0
        params.hive_partition_updates.insert(params.hive_partition_updates.end(), hpu.begin(),
2181
0
                                             hpu.end());
2182
23.0k
    } else if (!req.runtime_states.empty()) {
2183
53.0k
        for (auto* rs : req.runtime_states) {
2184
53.0k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
938
                params.__isset.hive_partition_updates = true;
2186
938
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
938
                                                     rs_hpu.begin(), rs_hpu.end());
2188
938
            }
2189
53.0k
        }
2190
23.0k
    }
2191
23.0k
    if (auto icd = req.runtime_state->iceberg_commit_datas(); !icd.empty()) {
2192
0
        params.__isset.iceberg_commit_datas = true;
2193
0
        params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(), icd.begin(),
2194
0
                                           icd.end());
2195
23.0k
    } else if (!req.runtime_states.empty()) {
2196
53.0k
        for (auto* rs : req.runtime_states) {
2197
53.0k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
1.80k
                params.__isset.iceberg_commit_datas = true;
2199
1.80k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
1.80k
                                                   rs_icd.begin(), rs_icd.end());
2201
1.80k
            }
2202
53.0k
        }
2203
23.0k
    }
2204
2205
23.0k
    if (auto mcd = req.runtime_state->mc_commit_datas(); !mcd.empty()) {
2206
0
        params.__isset.mc_commit_datas = true;
2207
0
        params.mc_commit_datas.insert(params.mc_commit_datas.end(), mcd.begin(), mcd.end());
2208
23.0k
    } else if (!req.runtime_states.empty()) {
2209
53.0k
        for (auto* rs : req.runtime_states) {
2210
53.0k
            if (auto rs_mcd = rs->mc_commit_datas(); !rs_mcd.empty()) {
2211
0
                params.__isset.mc_commit_datas = true;
2212
0
                params.mc_commit_datas.insert(params.mc_commit_datas.end(), rs_mcd.begin(),
2213
0
                                              rs_mcd.end());
2214
0
            }
2215
53.0k
        }
2216
23.0k
    }
2217
2218
23.0k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
23.0k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
23.0k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
23.0k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
23.0k
    }
2224
2225
23.0k
    TReportExecStatusResult res;
2226
23.0k
    Status rpc_status;
2227
2228
23.0k
    VLOG_DEBUG << "reportExecStatus params is "
2229
3
               << apache::thrift::ThriftDebugString(params).c_str();
2230
23.0k
    if (!exec_status.ok()) {
2231
354
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
354
                     << " to coordinator: " << req.coord_addr
2233
354
                     << ", query id: " << print_id(req.query_id);
2234
354
    }
2235
23.0k
    try {
2236
23.0k
        try {
2237
23.0k
            (*coord)->reportExecStatus(res, params);
2238
23.0k
        } catch ([[maybe_unused]] apache::thrift::transport::TTransportException& e) {
2239
#ifndef ADDRESS_SANITIZER
2240
            LOG(WARNING) << "Retrying ReportExecStatus. query id: " << print_id(req.query_id)
2241
                         << ", instance id: " << print_id(req.fragment_instance_id) << " to "
2242
                         << req.coord_addr << ", err: " << e.what();
2243
#endif
2244
0
            rpc_status = coord->reopen();
2245
2246
0
            if (!rpc_status.ok()) {
2247
0
                req.cancel_fn(rpc_status);
2248
0
                return;
2249
0
            }
2250
0
            (*coord)->reportExecStatus(res, params);
2251
0
        }
2252
2253
23.0k
        rpc_status = Status::create<false>(res.status);
2254
23.0k
    } catch (apache::thrift::TException& e) {
2255
0
        rpc_status = Status::InternalError("ReportExecStatus() to {} failed: {}",
2256
0
                                           PrintThriftNetworkAddress(req.coord_addr), e.what());
2257
0
    }
2258
2259
23.0k
    if (!rpc_status.ok()) {
2260
0
        LOG_INFO("Going to cancel query {} since report exec status got rpc failed: {}",
2261
0
                 print_id(req.query_id), rpc_status.to_string());
2262
0
        req.cancel_fn(rpc_status);
2263
0
    }
2264
23.0k
}
2265
2266
175k
Status PipelineFragmentContext::send_report(bool done) {
2267
175k
    Status exec_status = _query_ctx->exec_status();
2268
    // If plan is done successfully, but _is_report_success is false,
2269
    // no need to send report.
2270
    // Load will set _is_report_success to true because load wants to know
2271
    // the process.
2272
175k
    if (!_is_report_success && done && exec_status.ok()) {
2273
152k
        return Status::OK();
2274
152k
    }
2275
2276
    // If both _is_report_success and _is_report_on_cancel are false,
2277
    // which means no matter query is success or failed, no report is needed.
2278
    // This may happen when the query limit reached and
2279
    // a internal cancellation being processed
2280
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
2281
    // be set to false, to avoid sending fault report to FE.
2282
23.2k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
203
        if (done) {
2284
            // if done is true, which means the query is finished successfully, we can safely close the fragment instance without sending report to FE, and just return OK status here.
2285
203
            return Status::OK();
2286
203
        }
2287
0
        return Status::NeedSendAgain("");
2288
203
    }
2289
2290
23.0k
    std::vector<RuntimeState*> runtime_states;
2291
2292
45.0k
    for (auto& tasks : _tasks) {
2293
53.0k
        for (auto& task : tasks) {
2294
53.0k
            runtime_states.push_back(task.second.get());
2295
53.0k
        }
2296
45.0k
    }
2297
2298
23.0k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
23.0k
                                        ? get_load_error_url()
2300
18.4E
                                        : _query_ctx->get_load_error_url();
2301
23.0k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
23.0k
                                          ? get_first_error_msg()
2303
18.4E
                                          : _query_ctx->get_first_error_msg();
2304
2305
23.0k
    ReportStatusRequest req {.status = exec_status,
2306
23.0k
                             .runtime_states = runtime_states,
2307
23.0k
                             .done = done || !exec_status.ok(),
2308
23.0k
                             .coord_addr = _query_ctx->coord_addr,
2309
23.0k
                             .query_id = _query_id,
2310
23.0k
                             .fragment_id = _fragment_id,
2311
23.0k
                             .fragment_instance_id = TUniqueId(),
2312
23.0k
                             .backend_num = -1,
2313
23.0k
                             .runtime_state = _runtime_state.get(),
2314
23.0k
                             .load_error_url = load_eror_url,
2315
23.0k
                             .first_error_msg = first_error_msg,
2316
23.0k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
23.0k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
23.0k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
23.0k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
23.0k
        _coordinator_callback(req);
2321
23.0k
        if (!req.done) {
2322
2.30k
            ctx->refresh_next_report_time();
2323
2.30k
        }
2324
23.0k
    });
2325
23.2k
}
2326
2327
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
2328
0
    size_t res = 0;
2329
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
2330
    // here to traverse the vector.
2331
0
    for (const auto& task_instances : _tasks) {
2332
0
        for (const auto& task : task_instances) {
2333
0
            if (task.first->is_running()) {
2334
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
2335
0
                                      << " is running, task: " << (void*)task.first.get()
2336
0
                                      << ", is_running: " << task.first->is_running();
2337
0
                *has_running_task = true;
2338
0
                return 0;
2339
0
            }
2340
2341
0
            size_t revocable_size = task.first->get_revocable_size();
2342
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2343
0
                res += revocable_size;
2344
0
            }
2345
0
        }
2346
0
    }
2347
0
    return res;
2348
0
}
2349
2350
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
2351
0
    std::vector<PipelineTask*> revocable_tasks;
2352
0
    for (const auto& task_instances : _tasks) {
2353
0
        for (const auto& task : task_instances) {
2354
0
            size_t revocable_size_ = task.first->get_revocable_size();
2355
2356
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
2357
0
                revocable_tasks.emplace_back(task.first.get());
2358
0
            }
2359
0
        }
2360
0
    }
2361
0
    return revocable_tasks;
2362
0
}
2363
2364
24
std::string PipelineFragmentContext::debug_string() {
2365
24
    std::lock_guard<std::mutex> l(_task_mutex);
2366
24
    fmt::memory_buffer debug_string_buffer;
2367
24
    fmt::format_to(debug_string_buffer,
2368
24
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
24
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
24
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
112
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
88
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
464
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
376
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
376
                           _tasks[j][i].first->debug_string());
2376
376
        }
2377
88
    }
2378
2379
24
    return fmt::to_string(debug_string_buffer);
2380
24
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
534
PipelineFragmentContext::collect_realtime_profile() const {
2384
534
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2385
2386
    // we do not have mutex to protect pipeline_id_to_profile
2387
    // so we need to make sure this funciton is invoked after fragment context
2388
    // has already been prepared.
2389
534
    if (!_prepared) {
2390
0
        std::string msg =
2391
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2392
0
        DCHECK(false) << msg;
2393
0
        LOG_ERROR(msg);
2394
0
        return res;
2395
0
    }
2396
2397
    // Make sure first profile is fragment level profile
2398
534
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
534
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
534
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
754
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
754
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
754
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
754
        res.push_back(profile_ptr);
2407
754
    }
2408
2409
534
    return res;
2410
534
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
534
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2414
    // we do not have mutex to protect pipeline_id_to_profile
2415
    // so we need to make sure this funciton is invoked after fragment context
2416
    // has already been prepared.
2417
534
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
714
    for (const auto& tasks : _tasks) {
2426
1.19k
        for (const auto& task : tasks) {
2427
1.19k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
1.19k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
1.19k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
1.19k
                                                           _runtime_state->profile_level());
2435
1.19k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
1.19k
        }
2437
714
    }
2438
2439
534
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
534
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
534
                                                      _runtime_state->profile_level());
2442
534
    return load_channel_profile;
2443
534
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
0
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
0
    std::set<int> result;
2454
0
    for (const auto& _task : _tasks) {
2455
0
        for (const auto& task : _task) {
2456
0
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
0
            result.merge(set);
2458
0
        }
2459
0
    }
2460
0
    if (_runtime_state) {
2461
0
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
0
        result.merge(set);
2463
0
    }
2464
0
    return result;
2465
0
}
2466
2467
173k
void PipelineFragmentContext::_release_resource() {
2468
173k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
173k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
173k
    auto st = _query_ctx->exec_status();
2472
346k
    for (auto& _task : _tasks) {
2473
346k
        if (!_task.empty()) {
2474
346k
            _call_back(_task.front().first->runtime_state(), &st);
2475
346k
        }
2476
346k
    }
2477
173k
    _tasks.clear();
2478
173k
    _dag.clear();
2479
173k
    _pip_id_to_pipeline.clear();
2480
173k
    _pipelines.clear();
2481
173k
    _sink.reset();
2482
173k
    _root_op.reset();
2483
173k
    _runtime_filter_mgr_map.clear();
2484
173k
    _op_id_to_shared_state.clear();
2485
173k
}
2486
2487
} // namespace doris