Coverage Report

Created: 2026-05-14 04:14

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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Count
Source
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
11
// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
19
20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/FrontendService.h>
22
#include <gen_cpp/FrontendService_types.h>
23
#include <gen_cpp/PaloInternalService_types.h>
24
#include <gen_cpp/PlanNodes_types.h>
25
#include <pthread.h>
26
27
#include <algorithm>
28
#include <cstdlib>
29
// IWYU pragma: no_include <bits/chrono.h>
30
#include <fmt/format.h>
31
#include <thrift/Thrift.h>
32
#include <thrift/protocol/TDebugProtocol.h>
33
#include <thrift/transport/TTransportException.h>
34
35
#include <chrono> // IWYU pragma: keep
36
#include <map>
37
#include <memory>
38
#include <ostream>
39
#include <utility>
40
41
#include "cloud/config.h"
42
#include "common/cast_set.h"
43
#include "common/config.h"
44
#include "common/exception.h"
45
#include "common/logging.h"
46
#include "common/status.h"
47
#include "exec/exchange/local_exchange_sink_operator.h"
48
#include "exec/exchange/local_exchange_source_operator.h"
49
#include "exec/exchange/local_exchanger.h"
50
#include "exec/exchange/vdata_stream_mgr.h"
51
#include "exec/operator/aggregation_sink_operator.h"
52
#include "exec/operator/aggregation_source_operator.h"
53
#include "exec/operator/analytic_sink_operator.h"
54
#include "exec/operator/analytic_source_operator.h"
55
#include "exec/operator/assert_num_rows_operator.h"
56
#include "exec/operator/blackhole_sink_operator.h"
57
#include "exec/operator/bucketed_aggregation_sink_operator.h"
58
#include "exec/operator/bucketed_aggregation_source_operator.h"
59
#include "exec/operator/cache_sink_operator.h"
60
#include "exec/operator/cache_source_operator.h"
61
#include "exec/operator/datagen_operator.h"
62
#include "exec/operator/dict_sink_operator.h"
63
#include "exec/operator/distinct_streaming_aggregation_operator.h"
64
#include "exec/operator/empty_set_operator.h"
65
#include "exec/operator/exchange_sink_operator.h"
66
#include "exec/operator/exchange_source_operator.h"
67
#include "exec/operator/file_scan_operator.h"
68
#include "exec/operator/group_commit_block_sink_operator.h"
69
#include "exec/operator/group_commit_scan_operator.h"
70
#include "exec/operator/hashjoin_build_sink.h"
71
#include "exec/operator/hashjoin_probe_operator.h"
72
#include "exec/operator/hive_table_sink_operator.h"
73
#include "exec/operator/iceberg_delete_sink_operator.h"
74
#include "exec/operator/iceberg_merge_sink_operator.h"
75
#include "exec/operator/iceberg_table_sink_operator.h"
76
#include "exec/operator/jdbc_scan_operator.h"
77
#include "exec/operator/jdbc_table_sink_operator.h"
78
#include "exec/operator/local_merge_sort_source_operator.h"
79
#include "exec/operator/materialization_opertor.h"
80
#include "exec/operator/maxcompute_table_sink_operator.h"
81
#include "exec/operator/memory_scratch_sink_operator.h"
82
#include "exec/operator/meta_scan_operator.h"
83
#include "exec/operator/multi_cast_data_stream_sink.h"
84
#include "exec/operator/multi_cast_data_stream_source.h"
85
#include "exec/operator/nested_loop_join_build_operator.h"
86
#include "exec/operator/nested_loop_join_probe_operator.h"
87
#include "exec/operator/olap_scan_operator.h"
88
#include "exec/operator/olap_table_sink_operator.h"
89
#include "exec/operator/olap_table_sink_v2_operator.h"
90
#include "exec/operator/partition_sort_sink_operator.h"
91
#include "exec/operator/partition_sort_source_operator.h"
92
#include "exec/operator/partitioned_aggregation_sink_operator.h"
93
#include "exec/operator/partitioned_aggregation_source_operator.h"
94
#include "exec/operator/partitioned_hash_join_probe_operator.h"
95
#include "exec/operator/partitioned_hash_join_sink_operator.h"
96
#include "exec/operator/rec_cte_anchor_sink_operator.h"
97
#include "exec/operator/rec_cte_scan_operator.h"
98
#include "exec/operator/rec_cte_sink_operator.h"
99
#include "exec/operator/rec_cte_source_operator.h"
100
#include "exec/operator/repeat_operator.h"
101
#include "exec/operator/result_file_sink_operator.h"
102
#include "exec/operator/result_sink_operator.h"
103
#include "exec/operator/schema_scan_operator.h"
104
#include "exec/operator/select_operator.h"
105
#include "exec/operator/set_probe_sink_operator.h"
106
#include "exec/operator/set_sink_operator.h"
107
#include "exec/operator/set_source_operator.h"
108
#include "exec/operator/sort_sink_operator.h"
109
#include "exec/operator/sort_source_operator.h"
110
#include "exec/operator/spill_iceberg_table_sink_operator.h"
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#include "exec/operator/spill_sort_sink_operator.h"
112
#include "exec/operator/spill_sort_source_operator.h"
113
#include "exec/operator/streaming_aggregation_operator.h"
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#include "exec/operator/table_function_operator.h"
115
#include "exec/operator/tvf_table_sink_operator.h"
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#include "exec/operator/union_sink_operator.h"
117
#include "exec/operator/union_source_operator.h"
118
#include "exec/pipeline/dependency.h"
119
#include "exec/pipeline/pipeline_task.h"
120
#include "exec/pipeline/task_scheduler.h"
121
#include "exec/runtime_filter/runtime_filter_mgr.h"
122
#include "exec/sort/topn_sorter.h"
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#include "exec/spill/spill_file.h"
124
#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"
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138
namespace doris {
139
PipelineFragmentContext::PipelineFragmentContext(
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        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
436k
        : _query_id(std::move(query_id)),
144
436k
          _fragment_id(request.fragment_id),
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436k
          _exec_env(exec_env),
146
436k
          _query_ctx(std::move(query_ctx)),
147
436k
          _call_back(call_back),
148
436k
          _is_report_on_cancel(true),
149
436k
          _params(request),
150
436k
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
151
436k
          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
152
436k
                                                               : false) {
153
436k
    _fragment_watcher.start();
154
436k
}
155
156
436k
PipelineFragmentContext::~PipelineFragmentContext() {
157
436k
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
158
436k
            .tag("query_id", print_id(_query_id))
159
436k
            .tag("fragment_id", _fragment_id);
160
436k
    _release_resource();
161
436k
    {
162
        // The memory released by the query end is recorded in the query mem tracker.
163
436k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
164
436k
        _runtime_state.reset();
165
436k
        _query_ctx.reset();
166
436k
    }
167
436k
}
168
169
48
bool PipelineFragmentContext::is_timeout(timespec now) const {
170
48
    if (_timeout <= 0) {
171
0
        return false;
172
0
    }
173
48
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
174
48
}
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
9.97k
bool PipelineFragmentContext::notify_close() {
181
9.97k
    bool all_closed = false;
182
9.97k
    bool need_remove = false;
183
9.97k
    {
184
9.97k
        std::lock_guard<std::mutex> l(_task_mutex);
185
9.97k
        if (_closed_tasks >= _total_tasks) {
186
3.52k
            if (_need_notify_close) {
187
                // Fragment was cancelled and waiting for notify to close.
188
                // Record that we need to remove from fragment mgr, but do it
189
                // after releasing _task_mutex to avoid ABBA deadlock with
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                // dump_pipeline_tasks() (which acquires _pipeline_map lock
191
                // first, then _task_mutex via debug_string()).
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3.40k
                need_remove = true;
193
3.40k
            }
194
3.52k
            all_closed = true;
195
3.52k
        }
196
        // make fragment release by self after cancel
197
9.97k
        _need_notify_close = false;
198
9.97k
    }
199
9.97k
    if (need_remove) {
200
3.40k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
201
3.40k
    }
202
9.97k
    return all_closed;
203
9.97k
}
204
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// Must not add lock in this method. Because it will call query ctx cancel. And
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// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
207
// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
209
6.49k
void PipelineFragmentContext::cancel(const Status reason) {
210
6.49k
    LOG_INFO("PipelineFragmentContext::cancel")
211
6.49k
            .tag("query_id", print_id(_query_id))
212
6.49k
            .tag("fragment_id", _fragment_id)
213
6.49k
            .tag("reason", reason.to_string());
214
6.49k
    if (notify_close()) {
215
141
        return;
216
141
    }
217
    // Timeout is a special error code, we need print current stack to debug timeout issue.
218
6.35k
    if (reason.is<ErrorCode::TIMEOUT>()) {
219
1
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
220
1
                                   debug_string());
221
1
        LOG_LONG_STRING(WARNING, dbg_str);
222
1
    }
223
224
    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
225
6.35k
    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
6.35k
    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
6.35k
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
235
23
        _query_ctx->set_load_error_url(error_url);
236
23
    }
237
238
6.35k
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
239
23
        _query_ctx->set_first_error_msg(first_error_msg);
240
23
    }
241
242
6.35k
    _query_ctx->cancel(reason, _fragment_id);
243
6.35k
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
244
402
        _is_report_on_cancel = false;
245
5.95k
    } else {
246
27.2k
        for (auto& id : _fragment_instance_ids) {
247
27.2k
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
248
27.2k
        }
249
5.95k
    }
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
6.35k
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
253
6.35k
    if (stream_load_ctx != nullptr) {
254
41
        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
41
        stream_load_ctx->error_url = get_load_error_url();
259
41
        stream_load_ctx->first_error_msg = get_first_error_msg();
260
41
    }
261
262
28.4k
    for (auto& tasks : _tasks) {
263
67.4k
        for (auto& task : tasks) {
264
67.4k
            task.first->unblock_all_dependencies();
265
67.4k
        }
266
28.4k
    }
267
6.35k
}
268
269
693k
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
270
693k
    PipelineId id = _next_pipeline_id++;
271
693k
    auto pipeline = std::make_shared<Pipeline>(
272
693k
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
273
693k
            parent ? parent->num_tasks() : _num_instances);
274
693k
    if (idx >= 0) {
275
123k
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
276
569k
    } else {
277
569k
        _pipelines.emplace_back(pipeline);
278
569k
    }
279
693k
    if (parent) {
280
250k
        parent->set_children(pipeline);
281
250k
    }
282
693k
    return pipeline;
283
693k
}
284
285
436k
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
286
436k
    {
287
436k
        SCOPED_TIMER(_build_pipelines_timer);
288
        // 2. Build pipelines with operators in this fragment.
289
436k
        auto root_pipeline = add_pipeline();
290
436k
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
291
436k
                                         &_root_op, root_pipeline));
292
293
        // 3. Create sink operator
294
436k
        if (!_params.fragment.__isset.output_sink) {
295
0
            return Status::InternalError("No output sink in this fragment!");
296
0
        }
297
436k
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
298
436k
                                          _params.fragment.output_exprs, _params,
299
436k
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
300
436k
                                          *_desc_tbl, root_pipeline->id()));
301
436k
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
302
436k
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
303
304
569k
        for (PipelinePtr& pipeline : _pipelines) {
305
569k
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
306
569k
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
307
569k
        }
308
436k
    }
309
    // 4. Build local exchanger
310
436k
    if (_runtime_state->enable_local_shuffle()) {
311
433k
        SCOPED_TIMER(_plan_local_exchanger_timer);
312
433k
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
313
433k
                                             _params.bucket_seq_to_instance_idx,
314
433k
                                             _params.shuffle_idx_to_instance_idx));
315
433k
    }
316
317
    // 5. Initialize global states in pipelines.
318
693k
    for (PipelinePtr& pipeline : _pipelines) {
319
693k
        SCOPED_TIMER(_prepare_all_pipelines_timer);
320
693k
        pipeline->children().clear();
321
693k
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
322
693k
    }
323
324
435k
    {
325
435k
        SCOPED_TIMER(_build_tasks_timer);
326
        // 6. Build pipeline tasks and initialize local state.
327
435k
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
328
435k
    }
329
330
435k
    return Status::OK();
331
435k
}
332
333
436k
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
334
436k
    if (_prepared) {
335
0
        return Status::InternalError("Already prepared");
336
0
    }
337
436k
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
338
436k
        _timeout = _params.query_options.execution_timeout;
339
436k
    }
340
341
436k
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
342
436k
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
343
436k
    SCOPED_TIMER(_prepare_timer);
344
436k
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
345
436k
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
346
436k
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
347
436k
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
348
436k
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
349
436k
    {
350
436k
        SCOPED_TIMER(_init_context_timer);
351
436k
        cast_set(_num_instances, _params.local_params.size());
352
436k
        _total_instances =
353
436k
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
354
355
436k
        auto* fragment_context = this;
356
357
436k
        if (_params.query_options.__isset.is_report_success) {
358
435k
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
359
435k
        }
360
361
        // 1. Set up the global runtime state.
362
436k
        _runtime_state = RuntimeState::create_unique(
363
436k
                _params.query_id, _params.fragment_id, _params.query_options,
364
436k
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
365
436k
        _runtime_state->set_task_execution_context(shared_from_this());
366
436k
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
367
436k
        if (_params.__isset.backend_id) {
368
433k
            _runtime_state->set_backend_id(_params.backend_id);
369
433k
        }
370
436k
        if (_params.__isset.import_label) {
371
242
            _runtime_state->set_import_label(_params.import_label);
372
242
        }
373
436k
        if (_params.__isset.db_name) {
374
194
            _runtime_state->set_db_name(_params.db_name);
375
194
        }
376
436k
        if (_params.__isset.load_job_id) {
377
0
            _runtime_state->set_load_job_id(_params.load_job_id);
378
0
        }
379
380
436k
        if (_params.is_simplified_param) {
381
149k
            _desc_tbl = _query_ctx->desc_tbl;
382
287k
        } else {
383
287k
            DCHECK(_params.__isset.desc_tbl);
384
287k
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
385
287k
                                                  &_desc_tbl));
386
287k
        }
387
436k
        _runtime_state->set_desc_tbl(_desc_tbl);
388
436k
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
389
436k
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
390
436k
        _runtime_state->set_total_load_streams(_params.total_load_streams);
391
436k
        _runtime_state->set_num_local_sink(_params.num_local_sink);
392
393
        // init fragment_instance_ids
394
436k
        const auto target_size = _params.local_params.size();
395
436k
        _fragment_instance_ids.resize(target_size);
396
1.56M
        for (size_t i = 0; i < _params.local_params.size(); i++) {
397
1.12M
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
398
1.12M
            _fragment_instance_ids[i] = fragment_instance_id;
399
1.12M
        }
400
436k
    }
401
402
436k
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
403
404
435k
    _init_next_report_time();
405
406
435k
    _prepared = true;
407
435k
    return Status::OK();
408
436k
}
409
410
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
411
        int instance_idx,
412
1.12M
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
413
1.12M
    const auto& local_params = _params.local_params[instance_idx];
414
1.12M
    auto fragment_instance_id = local_params.fragment_instance_id;
415
1.12M
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
416
1.12M
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
417
1.12M
    auto get_shared_state = [&](PipelinePtr pipeline)
418
1.12M
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
419
1.97M
                                       std::vector<std::shared_ptr<Dependency>>>> {
420
1.97M
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
421
1.97M
                                std::vector<std::shared_ptr<Dependency>>>>
422
1.97M
                shared_state_map;
423
2.49M
        for (auto& op : pipeline->operators()) {
424
2.49M
            auto source_id = op->operator_id();
425
2.49M
            if (auto iter = _op_id_to_shared_state.find(source_id);
426
2.49M
                iter != _op_id_to_shared_state.end()) {
427
756k
                shared_state_map.insert({source_id, iter->second});
428
756k
            }
429
2.49M
        }
430
1.98M
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
431
1.98M
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
432
1.98M
                iter != _op_id_to_shared_state.end()) {
433
333k
                shared_state_map.insert({sink_to_source_id, iter->second});
434
333k
            }
435
1.98M
        }
436
1.97M
        return shared_state_map;
437
1.97M
    };
438
439
3.52M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
440
2.39M
        auto& pipeline = _pipelines[pip_idx];
441
2.39M
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
442
1.97M
            auto task_runtime_state = RuntimeState::create_unique(
443
1.97M
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
444
1.97M
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
445
1.97M
            {
446
                // Initialize runtime state for this task
447
1.97M
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
448
449
1.97M
                task_runtime_state->set_task_execution_context(shared_from_this());
450
1.97M
                task_runtime_state->set_be_number(local_params.backend_num);
451
452
1.97M
                if (_params.__isset.backend_id) {
453
1.97M
                    task_runtime_state->set_backend_id(_params.backend_id);
454
1.97M
                }
455
1.97M
                if (_params.__isset.import_label) {
456
243
                    task_runtime_state->set_import_label(_params.import_label);
457
243
                }
458
1.97M
                if (_params.__isset.db_name) {
459
195
                    task_runtime_state->set_db_name(_params.db_name);
460
195
                }
461
1.97M
                if (_params.__isset.load_job_id) {
462
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
463
0
                }
464
1.97M
                if (_params.__isset.wal_id) {
465
114
                    task_runtime_state->set_wal_id(_params.wal_id);
466
114
                }
467
1.97M
                if (_params.__isset.content_length) {
468
32
                    task_runtime_state->set_content_length(_params.content_length);
469
32
                }
470
471
1.97M
                task_runtime_state->set_desc_tbl(_desc_tbl);
472
1.97M
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
473
1.97M
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
474
1.97M
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
475
1.97M
                task_runtime_state->set_max_operator_id(max_operator_id());
476
1.97M
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
477
1.97M
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
478
1.97M
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
479
480
1.97M
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
481
1.97M
            }
482
1.97M
            auto cur_task_id = _total_tasks++;
483
1.97M
            task_runtime_state->set_task_id(cur_task_id);
484
1.97M
            task_runtime_state->set_task_num(pipeline->num_tasks());
485
1.97M
            auto task = std::make_shared<PipelineTask>(
486
1.97M
                    pipeline, cur_task_id, task_runtime_state.get(),
487
1.97M
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
488
1.97M
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
489
1.97M
                    instance_idx);
490
1.97M
            pipeline->incr_created_tasks(instance_idx, task.get());
491
1.97M
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
492
1.97M
            _tasks[instance_idx].emplace_back(
493
1.97M
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
494
1.97M
                            std::move(task), std::move(task_runtime_state)});
495
1.97M
        }
496
2.39M
    }
497
498
    /**
499
         * Build DAG for pipeline tasks.
500
         * For example, we have
501
         *
502
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
503
         *            \                      /
504
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
505
         *                 \                          /
506
         *               JoinProbeOperator2 (Pipeline1)
507
         *
508
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
509
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
510
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
511
         *
512
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
513
         * and JoinProbeOperator2.
514
         */
515
2.39M
    for (auto& _pipeline : _pipelines) {
516
2.39M
        if (pipeline_id_to_task.contains(_pipeline->id())) {
517
1.97M
            auto* task = pipeline_id_to_task[_pipeline->id()];
518
1.97M
            DCHECK(task != nullptr);
519
520
            // If this task has upstream dependency, then inject it into this task.
521
1.97M
            if (_dag.contains(_pipeline->id())) {
522
1.27M
                auto& deps = _dag[_pipeline->id()];
523
2.00M
                for (auto& dep : deps) {
524
2.00M
                    if (pipeline_id_to_task.contains(dep)) {
525
1.16M
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
526
1.16M
                        if (ss) {
527
506k
                            task->inject_shared_state(ss);
528
657k
                        } else {
529
657k
                            pipeline_id_to_task[dep]->inject_shared_state(
530
657k
                                    task->get_source_shared_state());
531
657k
                        }
532
1.16M
                    }
533
2.00M
                }
534
1.27M
            }
535
1.97M
        }
536
2.39M
    }
537
3.52M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
538
2.39M
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
539
1.97M
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
540
1.97M
            DCHECK(pipeline_id_to_profile[pip_idx]);
541
1.97M
            std::vector<TScanRangeParams> scan_ranges;
542
1.97M
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
543
1.97M
            if (local_params.per_node_scan_ranges.contains(node_id)) {
544
358k
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
545
358k
            }
546
1.97M
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
547
1.97M
                                                             _params.fragment.output_sink));
548
1.97M
        }
549
2.39M
    }
550
1.12M
    {
551
1.12M
        std::lock_guard<std::mutex> l(_state_map_lock);
552
1.12M
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
553
1.12M
    }
554
1.12M
    return Status::OK();
555
1.12M
}
556
557
435k
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
558
435k
    _total_tasks = 0;
559
435k
    _closed_tasks = 0;
560
435k
    const auto target_size = _params.local_params.size();
561
435k
    _tasks.resize(target_size);
562
435k
    _runtime_filter_mgr_map.resize(target_size);
563
1.12M
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
564
692k
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
565
692k
    }
566
435k
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
567
568
435k
    if (target_size > 1 &&
569
435k
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
570
148k
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
571
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
572
14.6k
        std::vector<Status> prepare_status(target_size);
573
14.6k
        int submitted_tasks = 0;
574
14.6k
        Status submit_status;
575
14.6k
        CountDownLatch latch((int)target_size);
576
179k
        for (int i = 0; i < target_size; i++) {
577
164k
            submit_status = thread_pool->submit_func([&, i]() {
578
164k
                SCOPED_ATTACH_TASK(_query_ctx.get());
579
164k
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
580
164k
                latch.count_down();
581
164k
            });
582
164k
            if (LIKELY(submit_status.ok())) {
583
164k
                submitted_tasks++;
584
164k
            } else {
585
0
                break;
586
0
            }
587
164k
        }
588
14.6k
        latch.arrive_and_wait(target_size - submitted_tasks);
589
14.6k
        if (UNLIKELY(!submit_status.ok())) {
590
0
            return submit_status;
591
0
        }
592
179k
        for (int i = 0; i < submitted_tasks; i++) {
593
164k
            if (!prepare_status[i].ok()) {
594
0
                return prepare_status[i];
595
0
            }
596
164k
        }
597
421k
    } else {
598
1.38M
        for (int i = 0; i < target_size; i++) {
599
963k
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
600
963k
        }
601
421k
    }
602
435k
    _pipeline_parent_map.clear();
603
435k
    _op_id_to_shared_state.clear();
604
    // Record task cardinality once when this fragment context finishes task initialization.
605
435k
    _query_ctx->add_total_task_num(_total_tasks.load(std::memory_order_relaxed));
606
607
435k
    return Status::OK();
608
435k
}
609
610
434k
void PipelineFragmentContext::_init_next_report_time() {
611
434k
    auto interval_s = config::pipeline_status_report_interval;
612
434k
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
613
41.6k
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
614
41.6k
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
615
        // We don't want to wait longer than it takes to run the entire fragment.
616
41.6k
        _previous_report_time =
617
41.6k
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
618
41.6k
        _disable_period_report = false;
619
41.6k
    }
620
434k
}
621
622
4.92k
void PipelineFragmentContext::refresh_next_report_time() {
623
4.92k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
624
4.92k
    DCHECK(disable == true);
625
4.92k
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
626
4.92k
    _disable_period_report.compare_exchange_strong(disable, false);
627
4.92k
}
628
629
7.21M
void PipelineFragmentContext::trigger_report_if_necessary() {
630
7.21M
    if (!_is_report_success) {
631
6.67M
        return;
632
6.67M
    }
633
534k
    auto disable = _disable_period_report.load(std::memory_order_acquire);
634
534k
    if (disable) {
635
9.90k
        return;
636
9.90k
    }
637
524k
    int32_t interval_s = config::pipeline_status_report_interval;
638
524k
    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
524k
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
644
524k
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
645
524k
    if (MonotonicNanos() > next_report_time) {
646
4.93k
        if (!_disable_period_report.compare_exchange_strong(disable, true,
647
4.93k
                                                            std::memory_order_acq_rel)) {
648
11
            return;
649
11
        }
650
4.92k
        if (VLOG_FILE_IS_ON) {
651
0
            VLOG_FILE << "Reporting "
652
0
                      << "profile for query_id " << print_id(_query_id)
653
0
                      << ", fragment id: " << _fragment_id;
654
655
0
            std::stringstream ss;
656
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
657
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
658
0
            if (_runtime_state->load_channel_profile()) {
659
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
660
0
            }
661
662
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
663
0
                      << " profile:\n"
664
0
                      << ss.str();
665
0
        }
666
4.92k
        auto st = send_report(false);
667
4.92k
        if (!st.ok()) {
668
0
            disable = true;
669
0
            _disable_period_report.compare_exchange_strong(disable, false,
670
0
                                                           std::memory_order_acq_rel);
671
0
        }
672
4.92k
    }
673
524k
}
674
675
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
676
434k
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
677
434k
    if (_params.fragment.plan.nodes.empty()) {
678
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
679
0
    }
680
681
434k
    int node_idx = 0;
682
683
434k
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
684
434k
                                        &node_idx, root, cur_pipe, 0, false, false));
685
686
434k
    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
434k
    return Status::OK();
691
434k
}
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
677k
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
697
    // propagate error case
698
677k
    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
677k
    const TPlanNode& tnode = tnodes[*node_idx];
704
705
677k
    int num_children = tnodes[*node_idx].num_children;
706
677k
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
707
677k
    bool current_require_bucket_distribution = require_bucket_distribution;
708
    // TODO: Create CacheOperator is confused now
709
677k
    OperatorPtr op = nullptr;
710
677k
    OperatorPtr cache_op = nullptr;
711
677k
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
712
677k
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
713
677k
                                     followed_by_shuffled_operator,
714
677k
                                     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
677k
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
718
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
719
677k
    if (parent != nullptr) {
720
        // add to parent's child(s)
721
242k
        RETURN_IF_ERROR(parent->set_child(cache_op ? cache_op : op));
722
435k
    } else {
723
435k
        *root = op;
724
435k
    }
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
677k
    auto required_data_distribution =
737
677k
            cur_pipe->operators().empty()
738
677k
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
739
677k
                    : op->required_data_distribution(_runtime_state.get());
740
677k
    current_followed_by_shuffled_operator =
741
677k
            ((followed_by_shuffled_operator ||
742
677k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
743
617k
                                             : op->is_shuffled_operator())) &&
744
677k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
745
677k
            (followed_by_shuffled_operator &&
746
564k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
747
748
677k
    current_require_bucket_distribution =
749
677k
            ((require_bucket_distribution ||
750
677k
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
751
622k
                                             : op->is_colocated_operator())) &&
752
677k
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
753
677k
            (require_bucket_distribution &&
754
570k
             required_data_distribution.distribution_type == ExchangeType::NOOP);
755
756
677k
    if (num_children == 0) {
757
451k
        _use_serial_source = op->is_serial_operator();
758
451k
    }
759
    // rely on that tnodes is preorder of the plan
760
920k
    for (int i = 0; i < num_children; i++) {
761
242k
        ++*node_idx;
762
242k
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
763
242k
                                            current_followed_by_shuffled_operator,
764
242k
                                            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
242k
        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
242k
    }
775
776
677k
    return Status::OK();
777
677k
}
778
779
void PipelineFragmentContext::_inherit_pipeline_properties(
780
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
781
123k
        PipelinePtr pipe_with_sink) {
782
123k
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
783
123k
    pipe_with_source->set_num_tasks(_num_instances);
784
123k
    pipe_with_source->set_data_distribution(data_distribution);
785
123k
}
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
123k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
792
123k
    auto& operators = cur_pipe->operators();
793
123k
    const auto downstream_pipeline_id = cur_pipe->id();
794
123k
    auto local_exchange_id = next_operator_id();
795
    // 1. Create a new pipeline with local exchange sink.
796
123k
    DataSinkOperatorPtr sink;
797
123k
    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
123k
    const bool followed_by_shuffled_operator =
804
123k
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
805
123k
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
806
123k
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
807
123k
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
808
123k
                                         followed_by_shuffled_operator && !_use_serial_source;
809
123k
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
810
123k
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
811
123k
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
812
123k
    if (bucket_seq_to_instance_idx.empty() &&
813
123k
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
814
7
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
815
7
    }
816
123k
    RETURN_IF_ERROR(new_pip->set_sink(sink));
817
123k
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
818
123k
                                          num_buckets, use_global_hash_shuffle,
819
123k
                                          shuffle_idx_to_instance_idx));
820
821
    // 2. Create and initialize LocalExchangeSharedState.
822
123k
    std::shared_ptr<LocalExchangeSharedState> shared_state =
823
123k
            LocalExchangeSharedState::create_shared(_num_instances);
824
123k
    switch (data_distribution.distribution_type) {
825
20.9k
    case ExchangeType::HASH_SHUFFLE:
826
20.9k
        shared_state->exchanger = ShuffleExchanger::create_unique(
827
20.9k
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
828
20.9k
                use_global_hash_shuffle ? _total_instances : _num_instances,
829
20.9k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
830
20.9k
                        ? cast_set<int>(
831
20.9k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
832
20.9k
                        : 0);
833
20.9k
        break;
834
547
    case ExchangeType::BUCKET_HASH_SHUFFLE:
835
547
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
836
547
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
837
547
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
547
                        ? cast_set<int>(
839
547
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
840
547
                        : 0);
841
547
        break;
842
98.2k
    case ExchangeType::PASSTHROUGH:
843
98.2k
        shared_state->exchanger = PassthroughExchanger::create_unique(
844
98.2k
                cur_pipe->num_tasks(), _num_instances,
845
98.2k
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
846
98.2k
                        ? cast_set<int>(
847
98.1k
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
848
98.2k
                        : 0);
849
98.2k
        break;
850
308
    case ExchangeType::BROADCAST:
851
308
        shared_state->exchanger = BroadcastExchanger::create_unique(
852
308
                cur_pipe->num_tasks(), _num_instances,
853
308
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
854
308
                        ? cast_set<int>(
855
308
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
856
308
                        : 0);
857
308
        break;
858
2.76k
    case ExchangeType::PASS_TO_ONE:
859
2.76k
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
860
            // If shared hash table is enabled for BJ, hash table will be built by only one task
861
1.59k
            shared_state->exchanger = PassToOneExchanger::create_unique(
862
1.59k
                    cur_pipe->num_tasks(), _num_instances,
863
1.59k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
864
1.59k
                            ? cast_set<int>(_runtime_state->query_options()
865
1.59k
                                                    .local_exchange_free_blocks_limit)
866
1.59k
                            : 0);
867
1.59k
        } else {
868
1.16k
            shared_state->exchanger = BroadcastExchanger::create_unique(
869
1.16k
                    cur_pipe->num_tasks(), _num_instances,
870
1.16k
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
871
1.16k
                            ? cast_set<int>(_runtime_state->query_options()
872
1.16k
                                                    .local_exchange_free_blocks_limit)
873
1.16k
                            : 0);
874
1.16k
        }
875
2.76k
        break;
876
912
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
877
912
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
878
912
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
879
912
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
880
912
                        ? cast_set<int>(
881
912
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
882
912
                        : 0);
883
912
        break;
884
0
    default:
885
0
        return Status::InternalError("Unsupported local exchange type : " +
886
0
                                     std::to_string((int)data_distribution.distribution_type));
887
123k
    }
888
123k
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
889
123k
                                             "LOCAL_EXCHANGE_OPERATOR");
890
123k
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
891
123k
    _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
123k
    std::copy(operators.begin(), operators.begin() + idx,
898
123k
              std::inserter(new_pip->operators(), new_pip->operators().end()));
899
900
    // 3.2 Erase unused operators in previous pipeline.
901
123k
    operators.erase(operators.begin(), operators.begin() + idx);
902
903
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
904
123k
    OperatorPtr source_op;
905
123k
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
906
123k
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
907
123k
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
908
123k
    if (!operators.empty()) {
909
48.1k
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
910
48.1k
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
911
48.1k
    }
912
123k
    operators.insert(operators.begin(), source_op);
913
914
    // 5. Set children for two pipelines separately.
915
123k
    std::vector<std::shared_ptr<Pipeline>> new_children;
916
123k
    std::vector<PipelineId> edges_with_source;
917
141k
    for (auto child : cur_pipe->children()) {
918
141k
        bool found = false;
919
155k
        for (auto op : new_pip->operators()) {
920
155k
            if (child->sink()->node_id() == op->node_id()) {
921
12.4k
                new_pip->set_children(child);
922
12.4k
                found = true;
923
12.4k
            };
924
155k
        }
925
141k
        if (!found) {
926
128k
            new_children.push_back(child);
927
128k
            edges_with_source.push_back(child->id());
928
128k
        }
929
141k
    }
930
123k
    new_children.push_back(new_pip);
931
123k
    edges_with_source.push_back(new_pip->id());
932
933
    // 6. Set DAG for new pipelines.
934
123k
    if (!new_pip->children().empty()) {
935
7.37k
        std::vector<PipelineId> edges_with_sink;
936
12.4k
        for (auto child : new_pip->children()) {
937
12.4k
            edges_with_sink.push_back(child->id());
938
12.4k
        }
939
7.37k
        _dag.insert({new_pip->id(), edges_with_sink});
940
7.37k
    }
941
123k
    cur_pipe->set_children(new_children);
942
123k
    _dag[downstream_pipeline_id] = edges_with_source;
943
123k
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
944
123k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
945
123k
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
946
947
    // 7. Inherit properties from current pipeline.
948
123k
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
949
123k
    return Status::OK();
950
123k
}
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
192k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
957
192k
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
958
37.4k
        return Status::OK();
959
37.4k
    }
960
961
154k
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
962
52.6k
        return Status::OK();
963
52.6k
    }
964
102k
    *do_local_exchange = true;
965
966
102k
    auto& operators = cur_pipe->operators();
967
102k
    auto total_op_num = operators.size();
968
102k
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
969
102k
    RETURN_IF_ERROR(_add_local_exchange_impl(
970
102k
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
971
102k
            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
102k
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
984
102k
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
985
21.3k
        RETURN_IF_ERROR(_add_local_exchange_impl(
986
21.3k
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
987
21.3k
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
988
21.3k
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
989
21.3k
                shuffle_idx_to_instance_idx));
990
21.3k
    }
991
102k
    return Status::OK();
992
102k
}
993
994
Status PipelineFragmentContext::_plan_local_exchange(
995
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
996
433k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
997
1.00M
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
998
567k
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
999
        // Set property if child pipeline is not join operator's child.
1000
567k
        if (!_pipelines[pip_idx]->children().empty()) {
1001
127k
            for (auto& child : _pipelines[pip_idx]->children()) {
1002
127k
                if (child->sink()->node_id() ==
1003
127k
                    _pipelines[pip_idx]->operators().front()->node_id()) {
1004
112k
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
1005
112k
                }
1006
127k
            }
1007
121k
        }
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
567k
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
1013
567k
                                             bucket_seq_to_instance_idx,
1014
567k
                                             shuffle_idx_to_instance_idx));
1015
567k
    }
1016
433k
    return Status::OK();
1017
433k
}
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
566k
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
1023
566k
    int idx = 1;
1024
566k
    bool do_local_exchange = false;
1025
615k
    do {
1026
615k
        auto& ops = pip->operators();
1027
615k
        do_local_exchange = false;
1028
        // Plan local exchange for each operator.
1029
682k
        for (; idx < ops.size();) {
1030
115k
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1031
104k
                RETURN_IF_ERROR(_add_local_exchange(
1032
104k
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1033
104k
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1034
104k
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1035
104k
                        shuffle_idx_to_instance_idx));
1036
104k
            }
1037
115k
            if (do_local_exchange) {
1038
                // If local exchange is needed for current operator, we will split this pipeline to
1039
                // two pipelines by local exchange sink/source. And then we need to process remaining
1040
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1041
                // is current operator was already processed) and continue to plan local exchange.
1042
48.2k
                idx = 2;
1043
48.2k
                break;
1044
48.2k
            }
1045
67.4k
            idx++;
1046
67.4k
        }
1047
615k
    } while (do_local_exchange);
1048
566k
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1049
87.4k
        RETURN_IF_ERROR(_add_local_exchange(
1050
87.4k
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1051
87.4k
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1052
87.4k
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1053
87.4k
    }
1054
566k
    return Status::OK();
1055
566k
}
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
436k
                                                  PipelineId cur_pipeline_id) {
1063
436k
    switch (thrift_sink.type) {
1064
146k
    case TDataSinkType::DATA_STREAM_SINK: {
1065
146k
        if (!thrift_sink.__isset.stream_sink) {
1066
0
            return Status::InternalError("Missing data stream sink.");
1067
0
        }
1068
146k
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1069
146k
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1070
146k
                params.destinations, _fragment_instance_ids);
1071
146k
        break;
1072
146k
    }
1073
251k
    case TDataSinkType::RESULT_SINK: {
1074
251k
        if (!thrift_sink.__isset.result_sink) {
1075
0
            return Status::InternalError("Missing data buffer sink.");
1076
0
        }
1077
1078
251k
        auto& pipeline = _pipelines[cur_pipeline_id];
1079
251k
        int child_node_id = pipeline->operators().back()->node_id();
1080
251k
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), child_node_id + 1,
1081
251k
                                                      row_desc, output_exprs,
1082
251k
                                                      thrift_sink.result_sink);
1083
251k
        break;
1084
251k
    }
1085
105
    case TDataSinkType::DICTIONARY_SINK: {
1086
105
        if (!thrift_sink.__isset.dictionary_sink) {
1087
0
            return Status::InternalError("Missing dict sink.");
1088
0
        }
1089
1090
105
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1091
105
                                                    thrift_sink.dictionary_sink);
1092
105
        break;
1093
105
    }
1094
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1095
31.3k
    case TDataSinkType::OLAP_TABLE_SINK: {
1096
31.3k
        auto& pipeline = _pipelines[cur_pipeline_id];
1097
31.3k
        int child_node_id = pipeline->operators().back()->node_id();
1098
31.3k
        if (state->query_options().enable_memtable_on_sink_node &&
1099
31.3k
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1100
31.3k
            !config::is_cloud_mode()) {
1101
2.16k
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(
1102
2.16k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1103
29.2k
        } else {
1104
29.2k
            _sink = std::make_shared<OlapTableSinkOperatorX>(
1105
29.2k
                    pool, next_sink_operator_id(), child_node_id + 1, row_desc, output_exprs);
1106
29.2k
        }
1107
31.3k
        break;
1108
0
    }
1109
166
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1110
166
        DCHECK(thrift_sink.__isset.olap_table_sink);
1111
166
        DCHECK(state->get_query_ctx() != nullptr);
1112
166
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1113
166
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1114
166
                                                                output_exprs);
1115
166
        break;
1116
0
    }
1117
1.46k
    case TDataSinkType::HIVE_TABLE_SINK: {
1118
1.46k
        if (!thrift_sink.__isset.hive_table_sink) {
1119
0
            return Status::InternalError("Missing hive table sink.");
1120
0
        }
1121
1.46k
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1122
1.46k
                                                         output_exprs);
1123
1.46k
        break;
1124
1.46k
    }
1125
1.73k
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1126
1.73k
        if (!thrift_sink.__isset.iceberg_table_sink) {
1127
0
            return Status::InternalError("Missing iceberg table sink.");
1128
0
        }
1129
1.73k
        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
1.73k
        } else {
1133
1.73k
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1134
1.73k
                                                                row_desc, output_exprs);
1135
1.73k
        }
1136
1.73k
        break;
1137
1.73k
    }
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
3
        if (!thrift_sink.__isset.memory_scratch_sink) {
1178
0
            return Status::InternalError("Missing data buffer sink.");
1179
0
        }
1180
1181
3
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1182
3
                                                             output_exprs);
1183
3
        break;
1184
3
    }
1185
502
    case TDataSinkType::RESULT_FILE_SINK: {
1186
502
        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
502
        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
502
        } else {
1196
502
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1197
502
                                                              output_exprs);
1198
502
        }
1199
502
        break;
1200
502
    }
1201
2.15k
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1202
2.15k
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1203
2.15k
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1204
2.15k
        auto sink_id = next_sink_operator_id();
1205
2.15k
        const int multi_cast_node_id = sink_id;
1206
2.15k
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1207
        // one sink has multiple sources.
1208
2.15k
        std::vector<int> sources;
1209
8.40k
        for (int i = 0; i < sender_size; ++i) {
1210
6.24k
            auto source_id = next_operator_id();
1211
6.24k
            sources.push_back(source_id);
1212
6.24k
        }
1213
1214
2.15k
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1215
2.15k
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1216
8.40k
        for (int i = 0; i < sender_size; ++i) {
1217
6.24k
            auto new_pipeline = add_pipeline();
1218
            // use to exchange sink
1219
6.24k
            RowDescriptor* exchange_row_desc = nullptr;
1220
6.24k
            {
1221
6.24k
                const auto& tmp_row_desc =
1222
6.24k
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1223
6.24k
                                ? RowDescriptor(state->desc_tbl(),
1224
6.24k
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1225
6.24k
                                                         .output_tuple_id})
1226
6.24k
                                : row_desc;
1227
6.24k
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1228
6.24k
            }
1229
6.24k
            auto source_id = sources[i];
1230
6.24k
            OperatorPtr source_op;
1231
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1232
6.24k
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1233
6.24k
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1234
6.24k
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1235
6.24k
                    /*operator_id=*/source_id);
1236
6.24k
            RETURN_IF_ERROR(new_pipeline->add_operator(
1237
6.24k
                    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
6.24k
            DataSinkOperatorPtr sink_op;
1241
6.24k
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1242
6.24k
                    state, *exchange_row_desc, next_sink_operator_id(),
1243
6.24k
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1244
6.24k
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1245
1246
6.24k
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1247
6.24k
            {
1248
6.24k
                TDataSink* t = pool->add(new TDataSink());
1249
6.24k
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1250
6.24k
                RETURN_IF_ERROR(sink_op->init(*t));
1251
6.24k
            }
1252
1253
            // 3. set dependency dag
1254
6.24k
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1255
6.24k
        }
1256
2.15k
        if (sources.empty()) {
1257
0
            return Status::InternalError("size of sources must be greater than 0");
1258
0
        }
1259
2.15k
        break;
1260
2.15k
    }
1261
2.15k
    case TDataSinkType::BLACKHOLE_SINK: {
1262
13
        if (!thrift_sink.__isset.blackhole_sink) {
1263
0
            return Status::InternalError("Missing blackhole sink.");
1264
0
        }
1265
1266
13
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1267
13
        break;
1268
13
    }
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
436k
    }
1280
435k
    return Status::OK();
1281
436k
}
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
679k
                                                 OperatorPtr& cache_op) {
1292
679k
    std::vector<DataSinkOperatorPtr> sink_ops;
1293
679k
    Defer defer = Defer([&]() {
1294
678k
        if (op) {
1295
678k
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1296
678k
        }
1297
678k
        for (auto& s : sink_ops) {
1298
126k
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1299
126k
        }
1300
678k
    });
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
679k
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1304
679k
    std::stringstream error_msg;
1305
679k
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1306
1307
679k
    bool fe_with_old_version = false;
1308
679k
    switch (tnode.node_type) {
1309
212k
    case TPlanNodeType::OLAP_SCAN_NODE: {
1310
212k
        op = std::make_shared<OlapScanOperatorX>(
1311
212k
                pool, tnode, next_operator_id(), descs, _num_instances,
1312
212k
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1313
212k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1314
212k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1315
212k
        break;
1316
212k
    }
1317
81
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1318
81
        DCHECK(_query_ctx != nullptr);
1319
81
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1320
81
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1321
81
                                                    _num_instances);
1322
81
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1323
81
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1324
81
        break;
1325
81
    }
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
23.3k
    case TPlanNodeType::FILE_SCAN_NODE: {
1340
23.3k
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1341
23.3k
                                                 _num_instances);
1342
23.3k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1343
23.3k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1344
23.3k
        break;
1345
23.3k
    }
1346
151k
    case TPlanNodeType::EXCHANGE_NODE: {
1347
151k
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1348
151k
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1349
18.4E
                                  : 0;
1350
151k
        DCHECK_GT(num_senders, 0);
1351
151k
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1352
151k
                                                       num_senders);
1353
151k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1354
151k
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1355
151k
        break;
1356
151k
    }
1357
159k
    case TPlanNodeType::AGGREGATION_NODE: {
1358
159k
        if (tnode.agg_node.grouping_exprs.empty() &&
1359
159k
            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
159k
        bool need_create_cache_op =
1364
159k
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1365
159k
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1366
10
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1367
10
            auto cache_source_id = next_operator_id();
1368
10
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1369
10
                                                        _params.fragment.query_cache_param);
1370
10
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1371
1372
10
            const auto downstream_pipeline_id = cur_pipe->id();
1373
10
            if (!_dag.contains(downstream_pipeline_id)) {
1374
10
                _dag.insert({downstream_pipeline_id, {}});
1375
10
            }
1376
10
            new_pipe = add_pipeline(cur_pipe);
1377
10
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1378
1379
10
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1380
10
                    next_sink_operator_id(), op->node_id(), op->operator_id()));
1381
10
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1382
10
            return Status::OK();
1383
10
        };
1384
159k
        const bool group_by_limit_opt =
1385
159k
                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
159k
        const bool enable_spill = _runtime_state->enable_spill() &&
1390
159k
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1391
159k
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1392
159k
                                      tnode.agg_node.use_streaming_preaggregation &&
1393
159k
                                      !tnode.agg_node.grouping_exprs.empty();
1394
        // TODO: distinct streaming agg does not support spill.
1395
159k
        const bool can_use_distinct_streaming_agg =
1396
159k
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1397
159k
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1398
159k
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1399
159k
                _params.query_options.enable_distinct_streaming_aggregation;
1400
1401
159k
        if (can_use_distinct_streaming_agg) {
1402
92.1k
            if (need_create_cache_op) {
1403
8
                PipelinePtr new_pipe;
1404
8
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1405
1406
8
                cache_op = op;
1407
8
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1408
8
                                                                     tnode, descs);
1409
8
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1410
8
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1411
8
                cur_pipe = new_pipe;
1412
92.1k
            } else {
1413
92.1k
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1414
92.1k
                                                                     tnode, descs);
1415
92.1k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1416
92.1k
            }
1417
92.1k
        } else if (is_streaming_agg) {
1418
3.45k
            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
3.45k
            } else {
1428
3.45k
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1429
3.45k
                                                             descs);
1430
3.45k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1431
3.45k
            }
1432
64.0k
        } else {
1433
            // create new pipeline to add query cache operator
1434
64.0k
            PipelinePtr new_pipe;
1435
64.0k
            if (need_create_cache_op) {
1436
2
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1437
2
                cache_op = op;
1438
2
            }
1439
1440
64.0k
            if (enable_spill) {
1441
118
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1442
118
                                                                     next_operator_id(), descs);
1443
63.8k
            } else {
1444
63.8k
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1445
63.8k
            }
1446
64.0k
            if (need_create_cache_op) {
1447
2
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1448
2
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1449
2
                cur_pipe = new_pipe;
1450
64.0k
            } else {
1451
64.0k
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1452
64.0k
            }
1453
1454
64.0k
            const auto downstream_pipeline_id = cur_pipe->id();
1455
64.0k
            if (!_dag.contains(downstream_pipeline_id)) {
1456
61.6k
                _dag.insert({downstream_pipeline_id, {}});
1457
61.6k
            }
1458
64.0k
            cur_pipe = add_pipeline(cur_pipe);
1459
64.0k
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1460
1461
64.0k
            if (enable_spill) {
1462
118
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1463
118
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1464
63.8k
            } else {
1465
63.8k
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1466
63.8k
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1467
63.8k
            }
1468
64.0k
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1469
64.0k
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1470
64.0k
        }
1471
159k
        break;
1472
159k
    }
1473
159k
    case TPlanNodeType::BUCKETED_AGGREGATION_NODE: {
1474
83
        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
83
        op = std::make_shared<BucketedAggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1482
83
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1483
1484
        // Create a new pipeline for the sink side.
1485
83
        const auto downstream_pipeline_id = cur_pipe->id();
1486
83
        if (!_dag.contains(downstream_pipeline_id)) {
1487
83
            _dag.insert({downstream_pipeline_id, {}});
1488
83
        }
1489
83
        cur_pipe = add_pipeline(cur_pipe);
1490
83
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1491
1492
        // Create sink operator.
1493
83
        sink_ops.push_back(std::make_shared<BucketedAggSinkOperatorX>(
1494
83
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1495
83
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1496
83
        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
83
        {
1503
83
            auto shared_state = BucketedAggSharedState::create_shared();
1504
83
            shared_state->id = op->operator_id();
1505
83
            shared_state->related_op_ids.insert(op->operator_id());
1506
1507
568
            for (int i = 0; i < _num_instances; i++) {
1508
485
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1509
485
                                                             "BUCKETED_AGG_SINK_DEPENDENCY");
1510
485
                sink_dep->set_shared_state(shared_state.get());
1511
485
                shared_state->sink_deps.push_back(sink_dep);
1512
485
            }
1513
83
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1514
83
                                                     op->node_id(), "BUCKETED_AGG_SOURCE");
1515
83
            _op_id_to_shared_state.insert(
1516
83
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1517
83
        }
1518
83
        break;
1519
83
    }
1520
9.63k
    case TPlanNodeType::HASH_JOIN_NODE: {
1521
9.63k
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1522
9.63k
                                       tnode.hash_join_node.is_broadcast_join;
1523
9.63k
        const auto enable_spill = _runtime_state->enable_spill();
1524
9.63k
        if (enable_spill && !is_broadcast_join) {
1525
0
            auto tnode_ = tnode;
1526
0
            tnode_.runtime_filters.clear();
1527
0
            auto inner_probe_operator =
1528
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1529
1530
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1531
            // So here use `tnode_` which has no runtime filters.
1532
0
            auto probe_side_inner_sink_operator =
1533
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1534
1535
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1536
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1537
1538
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1539
0
                    pool, tnode_, next_operator_id(), descs);
1540
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1541
0
                                                inner_probe_operator);
1542
0
            op = std::move(probe_operator);
1543
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1544
1545
0
            const auto downstream_pipeline_id = cur_pipe->id();
1546
0
            if (!_dag.contains(downstream_pipeline_id)) {
1547
0
                _dag.insert({downstream_pipeline_id, {}});
1548
0
            }
1549
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1550
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1551
1552
0
            auto inner_sink_operator =
1553
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1554
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1555
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1556
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1557
1558
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1559
0
            sink_ops.push_back(std::move(sink_operator));
1560
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1561
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1562
1563
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1564
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1565
9.63k
        } else {
1566
9.63k
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1567
9.63k
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1568
1569
9.63k
            const auto downstream_pipeline_id = cur_pipe->id();
1570
9.63k
            if (!_dag.contains(downstream_pipeline_id)) {
1571
7.92k
                _dag.insert({downstream_pipeline_id, {}});
1572
7.92k
            }
1573
9.63k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1574
9.63k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1575
1576
9.63k
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1577
9.63k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1578
9.63k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1579
9.63k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1580
1581
9.63k
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1582
9.63k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1583
9.63k
        }
1584
9.63k
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1585
4.70k
            std::shared_ptr<HashJoinSharedState> shared_state =
1586
4.70k
                    HashJoinSharedState::create_shared(_num_instances);
1587
24.2k
            for (int i = 0; i < _num_instances; i++) {
1588
19.5k
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1589
19.5k
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1590
19.5k
                sink_dep->set_shared_state(shared_state.get());
1591
19.5k
                shared_state->sink_deps.push_back(sink_dep);
1592
19.5k
            }
1593
4.70k
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1594
4.70k
                                                     op->node_id(), "HASH_JOIN_PROBE");
1595
4.70k
            _op_id_to_shared_state.insert(
1596
4.70k
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1597
4.70k
        }
1598
9.63k
        break;
1599
9.63k
    }
1600
5.23k
    case TPlanNodeType::CROSS_JOIN_NODE: {
1601
5.23k
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1602
5.23k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1603
1604
5.23k
        const auto downstream_pipeline_id = cur_pipe->id();
1605
5.23k
        if (!_dag.contains(downstream_pipeline_id)) {
1606
5.00k
            _dag.insert({downstream_pipeline_id, {}});
1607
5.00k
        }
1608
5.23k
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1609
5.23k
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1610
1611
5.23k
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1612
5.23k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1613
5.23k
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1614
5.23k
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1615
5.23k
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1616
5.23k
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1617
5.23k
        break;
1618
5.23k
    }
1619
53.5k
    case TPlanNodeType::UNION_NODE: {
1620
53.5k
        int child_count = tnode.num_children;
1621
53.5k
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1622
53.5k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1623
1624
53.5k
        const auto downstream_pipeline_id = cur_pipe->id();
1625
53.5k
        if (!_dag.contains(downstream_pipeline_id)) {
1626
53.3k
            _dag.insert({downstream_pipeline_id, {}});
1627
53.3k
        }
1628
54.9k
        for (int i = 0; i < child_count; i++) {
1629
1.42k
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1630
1.42k
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1631
1.42k
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1632
1.42k
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1633
1.42k
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1634
1.42k
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1635
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1636
1.42k
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1637
1.42k
        }
1638
53.5k
        break;
1639
53.5k
    }
1640
53.5k
    case TPlanNodeType::SORT_NODE: {
1641
44.6k
        const auto should_spill = _runtime_state->enable_spill() &&
1642
44.6k
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1643
44.6k
        const bool use_local_merge =
1644
44.6k
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1645
44.6k
        if (should_spill) {
1646
9
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1647
44.6k
        } else if (use_local_merge) {
1648
42.4k
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1649
42.4k
                                                                 descs);
1650
42.4k
        } else {
1651
2.18k
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1652
2.18k
        }
1653
44.6k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1654
1655
44.6k
        const auto downstream_pipeline_id = cur_pipe->id();
1656
44.6k
        if (!_dag.contains(downstream_pipeline_id)) {
1657
44.6k
            _dag.insert({downstream_pipeline_id, {}});
1658
44.6k
        }
1659
44.6k
        cur_pipe = add_pipeline(cur_pipe);
1660
44.6k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1661
1662
44.6k
        if (should_spill) {
1663
9
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1664
9
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1665
44.6k
        } else {
1666
44.6k
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1667
44.6k
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1668
44.6k
        }
1669
44.6k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1670
44.6k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1671
44.6k
        break;
1672
44.6k
    }
1673
44.6k
    case TPlanNodeType::PARTITION_SORT_NODE: {
1674
62
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1675
62
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1676
1677
62
        const auto downstream_pipeline_id = cur_pipe->id();
1678
62
        if (!_dag.contains(downstream_pipeline_id)) {
1679
62
            _dag.insert({downstream_pipeline_id, {}});
1680
62
        }
1681
62
        cur_pipe = add_pipeline(cur_pipe);
1682
62
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1683
1684
62
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1685
62
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1686
62
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1687
62
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1688
62
        break;
1689
62
    }
1690
1.51k
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1691
1.51k
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1692
1.51k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1693
1694
1.51k
        const auto downstream_pipeline_id = cur_pipe->id();
1695
1.51k
        if (!_dag.contains(downstream_pipeline_id)) {
1696
1.50k
            _dag.insert({downstream_pipeline_id, {}});
1697
1.50k
        }
1698
1.51k
        cur_pipe = add_pipeline(cur_pipe);
1699
1.51k
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1700
1701
1.51k
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1702
1.51k
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1703
1.51k
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1704
1.51k
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1705
1.51k
        break;
1706
1.51k
    }
1707
1.60k
    case TPlanNodeType::MATERIALIZATION_NODE: {
1708
1.60k
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1709
1.60k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1710
1.60k
        break;
1711
1.60k
    }
1712
1.60k
    case TPlanNodeType::INTERSECT_NODE: {
1713
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1714
133
                                                                      cur_pipe, sink_ops));
1715
133
        break;
1716
133
    }
1717
133
    case TPlanNodeType::EXCEPT_NODE: {
1718
133
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1719
133
                                                                       cur_pipe, sink_ops));
1720
133
        break;
1721
133
    }
1722
299
    case TPlanNodeType::REPEAT_NODE: {
1723
299
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1724
299
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1725
299
        break;
1726
299
    }
1727
914
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1728
914
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1729
914
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1730
914
        break;
1731
914
    }
1732
914
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1733
218
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1734
218
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1735
218
        break;
1736
218
    }
1737
1.52k
    case TPlanNodeType::EMPTY_SET_NODE: {
1738
1.52k
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1739
1.52k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1740
1.52k
        break;
1741
1.52k
    }
1742
1.52k
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1743
458
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1744
458
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1745
458
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1746
458
        break;
1747
458
    }
1748
2.04k
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1749
2.04k
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1750
2.04k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1751
2.04k
        break;
1752
2.04k
    }
1753
7.03k
    case TPlanNodeType::META_SCAN_NODE: {
1754
7.03k
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1755
7.03k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1756
7.03k
        break;
1757
7.03k
    }
1758
7.03k
    case TPlanNodeType::SELECT_NODE: {
1759
2.13k
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1760
2.13k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1761
2.13k
        break;
1762
2.13k
    }
1763
2.13k
    case TPlanNodeType::REC_CTE_NODE: {
1764
151
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1765
151
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1766
1767
151
        const auto downstream_pipeline_id = cur_pipe->id();
1768
151
        if (!_dag.contains(downstream_pipeline_id)) {
1769
148
            _dag.insert({downstream_pipeline_id, {}});
1770
148
        }
1771
1772
151
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1773
151
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1774
1775
151
        DataSinkOperatorPtr anchor_sink;
1776
151
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1777
151
                                                                  op->operator_id(), tnode, descs);
1778
151
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1779
151
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1780
151
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1781
1782
151
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1783
151
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1784
1785
151
        DataSinkOperatorPtr rec_sink;
1786
151
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1787
151
                                                         tnode, descs);
1788
151
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1789
151
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1790
151
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1791
1792
151
        break;
1793
151
    }
1794
1.95k
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1795
1.95k
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1796
1.95k
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1797
1.95k
        break;
1798
1.95k
    }
1799
1.95k
    default:
1800
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1801
0
                                     print_plan_node_type(tnode.node_type));
1802
679k
    }
1803
677k
    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
677k
    return Status::OK();
1809
679k
}
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
266
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
266
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
266
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
266
    const auto downstream_pipeline_id = cur_pipe->id();
1821
266
    if (!_dag.contains(downstream_pipeline_id)) {
1822
242
        _dag.insert({downstream_pipeline_id, {}});
1823
242
    }
1824
1825
892
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
626
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
626
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
626
        if (child_id == 0) {
1830
266
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
266
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
360
        } else {
1833
360
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
360
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
360
        }
1836
626
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
626
        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
626
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
626
    }
1841
1842
266
    return Status::OK();
1843
266
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
133
    const auto downstream_pipeline_id = cur_pipe->id();
1821
133
    if (!_dag.contains(downstream_pipeline_id)) {
1822
118
        _dag.insert({downstream_pipeline_id, {}});
1823
118
    }
1824
1825
478
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
345
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
345
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
345
        if (child_id == 0) {
1830
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
212
        } else {
1833
212
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
212
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
212
        }
1836
345
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
345
        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
345
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
345
    }
1841
1842
133
    return Status::OK();
1843
133
}
_ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Line
Count
Source
1816
133
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1817
133
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1818
133
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1819
1820
133
    const auto downstream_pipeline_id = cur_pipe->id();
1821
133
    if (!_dag.contains(downstream_pipeline_id)) {
1822
124
        _dag.insert({downstream_pipeline_id, {}});
1823
124
    }
1824
1825
414
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1826
281
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1827
281
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1828
1829
281
        if (child_id == 0) {
1830
133
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1831
133
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1832
148
        } else {
1833
148
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1834
148
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1835
148
        }
1836
281
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1837
281
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1838
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1839
281
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1840
281
    }
1841
1842
133
    return Status::OK();
1843
133
}
1844
1845
434k
Status PipelineFragmentContext::submit() {
1846
434k
    if (_submitted) {
1847
0
        return Status::InternalError("submitted");
1848
0
    }
1849
434k
    _submitted = true;
1850
1851
434k
    int submit_tasks = 0;
1852
434k
    Status st;
1853
434k
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1854
1.12M
    for (auto& task : _tasks) {
1855
1.97M
        for (auto& t : task) {
1856
1.97M
            st = scheduler->submit(t.first);
1857
1.97M
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1858
1.97M
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1859
1.97M
            if (!st) {
1860
0
                cancel(Status::InternalError("submit context to executor fail"));
1861
0
                std::lock_guard<std::mutex> l(_task_mutex);
1862
0
                _total_tasks = submit_tasks;
1863
0
                break;
1864
0
            }
1865
1.97M
            submit_tasks++;
1866
1.97M
        }
1867
1.12M
    }
1868
434k
    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
434k
    } else {
1883
434k
        return st;
1884
434k
    }
1885
434k
}
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
435k
bool PipelineFragmentContext::_close_fragment_instance() {
1913
435k
    if (_is_fragment_instance_closed) {
1914
0
        return false;
1915
0
    }
1916
435k
    Defer defer_op {[&]() { _is_fragment_instance_closed = true; }};
1917
435k
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1918
435k
    if (!_need_notify_close) {
1919
432k
        auto st = send_report(true);
1920
432k
        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
432k
    }
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
435k
    if (_runtime_state->enable_profile() &&
1931
435k
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1932
2.54k
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1933
2.54k
         _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
435k
    if (_query_ctx->enable_profile()) {
1953
2.54k
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1954
2.54k
                                         collect_realtime_load_channel_profile());
1955
2.54k
    }
1956
1957
    // Return whether the caller needs to remove from the pipeline map.
1958
    // The caller must do this after releasing _task_mutex.
1959
435k
    return !_need_notify_close;
1960
435k
}
1961
1962
1.97M
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1963
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1964
1.97M
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1965
1.97M
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1966
693k
        if (_dag.contains(pipeline_id)) {
1967
381k
            for (auto dep : _dag[pipeline_id]) {
1968
381k
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1969
381k
            }
1970
299k
        }
1971
693k
    }
1972
1.97M
    bool need_remove = false;
1973
1.97M
    {
1974
1.97M
        std::lock_guard<std::mutex> l(_task_mutex);
1975
1.97M
        ++_closed_tasks;
1976
        // Update query-level finished task progress in real time.
1977
1.97M
        _query_ctx->inc_finished_task_num();
1978
1.97M
        if (_closed_tasks >= _total_tasks) {
1979
435k
            need_remove = _close_fragment_instance();
1980
435k
        }
1981
1.97M
    }
1982
    // Call remove_pipeline_context() outside _task_mutex to avoid ABBA deadlock.
1983
1.97M
    if (need_remove) {
1984
432k
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1985
432k
    }
1986
1.97M
}
1987
1988
54.4k
std::string PipelineFragmentContext::get_load_error_url() {
1989
54.4k
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1990
0
        return to_load_error_http_path(str);
1991
0
    }
1992
150k
    for (auto& tasks : _tasks) {
1993
245k
        for (auto& task : tasks) {
1994
245k
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1995
174
                return to_load_error_http_path(str);
1996
174
            }
1997
245k
        }
1998
150k
    }
1999
54.2k
    return "";
2000
54.4k
}
2001
2002
54.4k
std::string PipelineFragmentContext::get_first_error_msg() {
2003
54.4k
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
2004
0
        return str;
2005
0
    }
2006
150k
    for (auto& tasks : _tasks) {
2007
245k
        for (auto& task : tasks) {
2008
245k
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
2009
174
                return str;
2010
174
            }
2011
245k
        }
2012
150k
    }
2013
54.2k
    return "";
2014
54.4k
}
2015
2016
0
std::string PipelineFragmentContext::_to_http_path(const std::string& file_name) const {
2017
0
    std::stringstream url;
2018
0
    url << "http://" << BackendOptions::get_localhost() << ":" << config::webserver_port
2019
0
        << "/api/_download_load?"
2020
0
        << "token=" << _exec_env->token() << "&file=" << file_name;
2021
0
    return url.str();
2022
0
}
2023
2024
48.0k
void PipelineFragmentContext::_coordinator_callback(const ReportStatusRequest& req) {
2025
48.0k
    DBUG_EXECUTE_IF("FragmentMgr::coordinator_callback.report_delay", {
2026
48.0k
        int random_seconds = req.status.is<ErrorCode::DATA_QUALITY_ERROR>() ? 8 : 2;
2027
48.0k
        LOG_INFO("sleep : ").tag("time", random_seconds).tag("query_id", print_id(req.query_id));
2028
48.0k
        std::this_thread::sleep_for(std::chrono::seconds(random_seconds));
2029
48.0k
        LOG_INFO("sleep done").tag("query_id", print_id(req.query_id));
2030
48.0k
    });
2031
2032
48.0k
    DCHECK(req.status.ok() || req.done); // if !status.ok() => done
2033
48.0k
    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
48.0k
    int callback_retries = 10;
2038
48.0k
    const int sleep_ms = 1000;
2039
48.0k
    Status exec_status = req.status;
2040
48.0k
    Status coord_status;
2041
48.0k
    std::unique_ptr<FrontendServiceConnection> coord = nullptr;
2042
48.0k
    do {
2043
48.0k
        coord = std::make_unique<FrontendServiceConnection>(_exec_env->frontend_client_cache(),
2044
48.0k
                                                            req.coord_addr, &coord_status);
2045
48.0k
        if (!coord_status.ok()) {
2046
0
            std::this_thread::sleep_for(std::chrono::milliseconds(sleep_ms));
2047
0
        }
2048
48.0k
    } while (!coord_status.ok() && callback_retries-- > 0);
2049
2050
48.0k
    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
48.0k
    TReportExecStatusParams params;
2059
48.0k
    params.protocol_version = FrontendServiceVersion::V1;
2060
48.0k
    params.__set_query_id(req.query_id);
2061
48.0k
    params.__set_backend_num(req.backend_num);
2062
48.0k
    params.__set_fragment_instance_id(req.fragment_instance_id);
2063
48.0k
    params.__set_fragment_id(req.fragment_id);
2064
48.0k
    params.__set_status(exec_status.to_thrift());
2065
48.0k
    params.__set_done(req.done);
2066
48.0k
    params.__set_query_type(req.runtime_state->query_type());
2067
48.0k
    params.__isset.profile = false;
2068
2069
48.0k
    DCHECK(req.runtime_state != nullptr);
2070
2071
48.0k
    if (req.runtime_state->query_type() == TQueryType::LOAD) {
2072
43.4k
        params.__set_loaded_rows(req.runtime_state->num_rows_load_total());
2073
43.4k
        params.__set_loaded_bytes(req.runtime_state->num_bytes_load_total());
2074
43.4k
    } else {
2075
4.67k
        DCHECK(!req.runtime_states.empty());
2076
4.67k
        if (!req.runtime_state->output_files().empty()) {
2077
0
            params.__isset.delta_urls = true;
2078
0
            for (auto& it : req.runtime_state->output_files()) {
2079
0
                params.delta_urls.push_back(_to_http_path(it));
2080
0
            }
2081
0
        }
2082
4.67k
        if (!params.delta_urls.empty()) {
2083
0
            params.__isset.delta_urls = true;
2084
0
        }
2085
4.67k
    }
2086
2087
48.0k
    static std::string s_dpp_normal_all = "dpp.norm.ALL";
2088
48.0k
    static std::string s_dpp_abnormal_all = "dpp.abnorm.ALL";
2089
48.0k
    static std::string s_unselected_rows = "unselected.rows";
2090
48.0k
    int64_t num_rows_load_success = 0;
2091
48.0k
    int64_t num_rows_load_filtered = 0;
2092
48.0k
    int64_t num_rows_load_unselected = 0;
2093
48.0k
    if (req.runtime_state->num_rows_load_total() > 0 ||
2094
48.0k
        req.runtime_state->num_rows_load_filtered() > 0 ||
2095
48.0k
        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
48.0k
    } else if (!req.runtime_states.empty()) {
2109
178k
        for (auto* rs : req.runtime_states) {
2110
178k
            if (rs->num_rows_load_total() > 0 || rs->num_rows_load_filtered() > 0 ||
2111
178k
                rs->num_finished_range() > 0) {
2112
35.8k
                params.__isset.load_counters = true;
2113
35.8k
                num_rows_load_success += rs->num_rows_load_success();
2114
35.8k
                num_rows_load_filtered += rs->num_rows_load_filtered();
2115
35.8k
                num_rows_load_unselected += rs->num_rows_load_unselected();
2116
35.8k
                params.__isset.fragment_instance_reports = true;
2117
35.8k
                TFragmentInstanceReport t;
2118
35.8k
                t.__set_fragment_instance_id(rs->fragment_instance_id());
2119
35.8k
                t.__set_num_finished_range(cast_set<int>(rs->num_finished_range()));
2120
35.8k
                t.__set_loaded_rows(rs->num_rows_load_total());
2121
35.8k
                t.__set_loaded_bytes(rs->num_bytes_load_total());
2122
35.8k
                params.fragment_instance_reports.push_back(t);
2123
35.8k
            }
2124
178k
        }
2125
48.0k
    }
2126
48.0k
    params.load_counters.emplace(s_dpp_normal_all, std::to_string(num_rows_load_success));
2127
48.0k
    params.load_counters.emplace(s_dpp_abnormal_all, std::to_string(num_rows_load_filtered));
2128
48.0k
    params.load_counters.emplace(s_unselected_rows, std::to_string(num_rows_load_unselected));
2129
2130
48.0k
    if (!req.load_error_url.empty()) {
2131
159
        params.__set_tracking_url(req.load_error_url);
2132
159
    }
2133
48.0k
    if (!req.first_error_msg.empty()) {
2134
159
        params.__set_first_error_msg(req.first_error_msg);
2135
159
    }
2136
178k
    for (auto* rs : req.runtime_states) {
2137
178k
        if (rs->wal_id() > 0) {
2138
108
            params.__set_txn_id(rs->wal_id());
2139
108
            params.__set_label(rs->import_label());
2140
108
        }
2141
178k
    }
2142
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2146
178k
        for (auto* rs : req.runtime_states) {
2147
178k
            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
178k
        }
2154
48.0k
    }
2155
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2159
178k
        for (auto* rs : req.runtime_states) {
2160
178k
            if (auto rs_tci = rs->tablet_commit_infos(); !rs_tci.empty()) {
2161
27.0k
                params.__isset.commitInfos = true;
2162
27.0k
                params.commitInfos.insert(params.commitInfos.end(), rs_tci.begin(), rs_tci.end());
2163
27.0k
            }
2164
178k
        }
2165
48.0k
    }
2166
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2170
178k
        for (auto* rs : req.runtime_states) {
2171
178k
            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
178k
        }
2177
48.0k
    }
2178
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2183
178k
        for (auto* rs : req.runtime_states) {
2184
178k
            if (auto rs_hpu = rs->hive_partition_updates(); !rs_hpu.empty()) {
2185
2.16k
                params.__isset.hive_partition_updates = true;
2186
2.16k
                params.hive_partition_updates.insert(params.hive_partition_updates.end(),
2187
2.16k
                                                     rs_hpu.begin(), rs_hpu.end());
2188
2.16k
            }
2189
178k
        }
2190
48.0k
    }
2191
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2196
178k
        for (auto* rs : req.runtime_states) {
2197
178k
            if (auto rs_icd = rs->iceberg_commit_datas(); !rs_icd.empty()) {
2198
2.08k
                params.__isset.iceberg_commit_datas = true;
2199
2.08k
                params.iceberg_commit_datas.insert(params.iceberg_commit_datas.end(),
2200
2.08k
                                                   rs_icd.begin(), rs_icd.end());
2201
2.08k
            }
2202
178k
        }
2203
48.0k
    }
2204
2205
48.0k
    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
48.0k
    } else if (!req.runtime_states.empty()) {
2209
178k
        for (auto* rs : req.runtime_states) {
2210
178k
            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
178k
        }
2216
48.0k
    }
2217
2218
48.0k
    req.runtime_state->get_unreported_errors(&(params.error_log));
2219
48.0k
    params.__isset.error_log = (!params.error_log.empty());
2220
2221
48.0k
    if (_exec_env->cluster_info()->backend_id != 0) {
2222
48.0k
        params.__set_backend_id(_exec_env->cluster_info()->backend_id);
2223
48.0k
    }
2224
2225
48.0k
    TReportExecStatusResult res;
2226
48.0k
    Status rpc_status;
2227
2228
48.0k
    VLOG_DEBUG << "reportExecStatus params is "
2229
6
               << apache::thrift::ThriftDebugString(params).c_str();
2230
48.0k
    if (!exec_status.ok()) {
2231
1.69k
        LOG(WARNING) << "report error status: " << exec_status.msg()
2232
1.69k
                     << " to coordinator: " << req.coord_addr
2233
1.69k
                     << ", query id: " << print_id(req.query_id);
2234
1.69k
    }
2235
48.0k
    try {
2236
48.0k
        try {
2237
48.0k
            (*coord)->reportExecStatus(res, params);
2238
48.0k
        } 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
48.0k
        rpc_status = Status::create<false>(res.status);
2254
48.0k
    } 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
48.0k
    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
48.0k
}
2265
2266
437k
Status PipelineFragmentContext::send_report(bool done) {
2267
437k
    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
437k
    if (!_is_report_success && done && exec_status.ok()) {
2273
389k
        return Status::OK();
2274
389k
    }
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
48.4k
    if (!_is_report_success && !_is_report_on_cancel) {
2283
325
        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
325
            return Status::OK();
2286
325
        }
2287
0
        return Status::NeedSendAgain("");
2288
325
    }
2289
2290
48.1k
    std::vector<RuntimeState*> runtime_states;
2291
2292
122k
    for (auto& tasks : _tasks) {
2293
178k
        for (auto& task : tasks) {
2294
178k
            runtime_states.push_back(task.second.get());
2295
178k
        }
2296
122k
    }
2297
2298
48.1k
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
2299
48.1k
                                        ? get_load_error_url()
2300
48.1k
                                        : _query_ctx->get_load_error_url();
2301
48.1k
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
2302
48.1k
                                          ? get_first_error_msg()
2303
48.1k
                                          : _query_ctx->get_first_error_msg();
2304
2305
48.1k
    ReportStatusRequest req {.status = exec_status,
2306
48.1k
                             .runtime_states = runtime_states,
2307
48.1k
                             .done = done || !exec_status.ok(),
2308
48.1k
                             .coord_addr = _query_ctx->coord_addr,
2309
48.1k
                             .query_id = _query_id,
2310
48.1k
                             .fragment_id = _fragment_id,
2311
48.1k
                             .fragment_instance_id = TUniqueId(),
2312
48.1k
                             .backend_num = -1,
2313
48.1k
                             .runtime_state = _runtime_state.get(),
2314
48.1k
                             .load_error_url = load_eror_url,
2315
48.1k
                             .first_error_msg = first_error_msg,
2316
48.1k
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
2317
48.1k
    auto ctx = std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this());
2318
48.1k
    return _exec_env->fragment_mgr()->get_thread_pool()->submit_func([this, req, ctx]() {
2319
48.0k
        SCOPED_ATTACH_TASK(ctx->get_query_ctx()->query_mem_tracker());
2320
48.0k
        _coordinator_callback(req);
2321
48.0k
        if (!req.done) {
2322
4.92k
            ctx->refresh_next_report_time();
2323
4.92k
        }
2324
48.0k
    });
2325
48.4k
}
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
49
std::string PipelineFragmentContext::debug_string() {
2365
49
    std::lock_guard<std::mutex> l(_task_mutex);
2366
49
    fmt::memory_buffer debug_string_buffer;
2367
49
    fmt::format_to(debug_string_buffer,
2368
49
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
2369
49
                   "need_notify_close={}, fragment_id={}, _rec_cte_stage={}\n",
2370
49
                   _closed_tasks, _total_tasks, _need_notify_close, _fragment_id, _rec_cte_stage);
2371
338
    for (size_t j = 0; j < _tasks.size(); j++) {
2372
289
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2373
638
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2374
349
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2375
349
                           _tasks[j][i].first->debug_string());
2376
349
        }
2377
289
    }
2378
2379
49
    return fmt::to_string(debug_string_buffer);
2380
49
}
2381
2382
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2383
2.54k
PipelineFragmentContext::collect_realtime_profile() const {
2384
2.54k
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2385
2386
    // we do not have mutex to protect pipeline_id_to_profile
2387
    // so we need to make sure this funciton is invoked after fragment context
2388
    // has already been prepared.
2389
2.54k
    if (!_prepared) {
2390
0
        std::string msg =
2391
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2392
0
        DCHECK(false) << msg;
2393
0
        LOG_ERROR(msg);
2394
0
        return res;
2395
0
    }
2396
2397
    // Make sure first profile is fragment level profile
2398
2.54k
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2399
2.54k
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2400
2.54k
    res.push_back(fragment_profile);
2401
2402
    // pipeline_id_to_profile is initialized in prepare stage
2403
4.73k
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2404
4.73k
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2405
4.73k
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2406
4.73k
        res.push_back(profile_ptr);
2407
4.73k
    }
2408
2409
2.54k
    return res;
2410
2.54k
}
2411
2412
std::shared_ptr<TRuntimeProfileTree>
2413
2.54k
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2414
    // we do not have mutex to protect pipeline_id_to_profile
2415
    // so we need to make sure this funciton is invoked after fragment context
2416
    // has already been prepared.
2417
2.54k
    if (!_prepared) {
2418
0
        std::string msg =
2419
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2420
0
        DCHECK(false) << msg;
2421
0
        LOG_ERROR(msg);
2422
0
        return nullptr;
2423
0
    }
2424
2425
6.32k
    for (const auto& tasks : _tasks) {
2426
12.7k
        for (const auto& task : tasks) {
2427
12.7k
            if (task.second->load_channel_profile() == nullptr) {
2428
0
                continue;
2429
0
            }
2430
2431
12.7k
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2432
2433
12.7k
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2434
12.7k
                                                           _runtime_state->profile_level());
2435
12.7k
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2436
12.7k
        }
2437
6.32k
    }
2438
2439
2.54k
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2440
2.54k
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2441
2.54k
                                                      _runtime_state->profile_level());
2442
2.54k
    return load_channel_profile;
2443
2.54k
}
2444
2445
// Collect runtime filter IDs registered by all tasks in this PFC.
2446
// Used during recursive CTE stage transitions to know which filters to deregister
2447
// before creating the new PFC for the next recursion round.
2448
// Called from rerun_fragment(wait_for_destroy) while tasks are still closing.
2449
// Thread safety: safe because _tasks is structurally immutable after prepare() —
2450
// the vector sizes do not change, and individual RuntimeState filter sets are
2451
// written only during open() which has completed by the time we reach rerun.
2452
3.28k
std::set<int> PipelineFragmentContext::get_deregister_runtime_filter() const {
2453
3.28k
    std::set<int> result;
2454
8.28k
    for (const auto& _task : _tasks) {
2455
14.3k
        for (const auto& task : _task) {
2456
14.3k
            auto set = task.first->runtime_state()->get_deregister_runtime_filter();
2457
14.3k
            result.merge(set);
2458
14.3k
        }
2459
8.28k
    }
2460
3.28k
    if (_runtime_state) {
2461
3.28k
        auto set = _runtime_state->get_deregister_runtime_filter();
2462
3.28k
        result.merge(set);
2463
3.28k
    }
2464
3.28k
    return result;
2465
3.28k
}
2466
2467
437k
void PipelineFragmentContext::_release_resource() {
2468
437k
    std::lock_guard<std::mutex> l(_task_mutex);
2469
    // The memory released by the query end is recorded in the query mem tracker.
2470
437k
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2471
437k
    auto st = _query_ctx->exec_status();
2472
1.12M
    for (auto& _task : _tasks) {
2473
1.12M
        if (!_task.empty()) {
2474
1.12M
            _call_back(_task.front().first->runtime_state(), &st);
2475
1.12M
        }
2476
1.12M
    }
2477
437k
    _tasks.clear();
2478
437k
    _dag.clear();
2479
437k
    _pip_id_to_pipeline.clear();
2480
437k
    _pipelines.clear();
2481
437k
    _sink.reset();
2482
437k
    _root_op.reset();
2483
437k
    _runtime_filter_mgr_map.clear();
2484
437k
    _op_id_to_shared_state.clear();
2485
437k
}
2486
2487
} // namespace doris