Coverage Report

Created: 2026-03-19 18:17

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/exec/pipeline/pipeline_fragment_context.cpp
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements.  See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership.  The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
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// "License"); you may not use this file except in compliance
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include "exec/pipeline/pipeline_fragment_context.h"
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20
#include <gen_cpp/DataSinks_types.h>
21
#include <gen_cpp/PaloInternalService_types.h>
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#include <gen_cpp/PlanNodes_types.h>
23
#include <pthread.h>
24
25
#include <algorithm>
26
#include <cstdlib>
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// IWYU pragma: no_include <bits/chrono.h>
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#include <fmt/format.h>
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#include <chrono> // IWYU pragma: keep
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#include <map>
32
#include <memory>
33
#include <ostream>
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#include <utility>
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#include "cloud/config.h"
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#include "common/cast_set.h"
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#include "common/config.h"
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#include "common/exception.h"
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#include "common/logging.h"
41
#include "common/status.h"
42
#include "exec/exchange/local_exchange_sink_operator.h"
43
#include "exec/exchange/local_exchange_source_operator.h"
44
#include "exec/exchange/local_exchanger.h"
45
#include "exec/exchange/vdata_stream_mgr.h"
46
#include "exec/operator/aggregation_sink_operator.h"
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#include "exec/operator/aggregation_source_operator.h"
48
#include "exec/operator/analytic_sink_operator.h"
49
#include "exec/operator/analytic_source_operator.h"
50
#include "exec/operator/assert_num_rows_operator.h"
51
#include "exec/operator/blackhole_sink_operator.h"
52
#include "exec/operator/cache_sink_operator.h"
53
#include "exec/operator/cache_source_operator.h"
54
#include "exec/operator/datagen_operator.h"
55
#include "exec/operator/dict_sink_operator.h"
56
#include "exec/operator/distinct_streaming_aggregation_operator.h"
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#include "exec/operator/empty_set_operator.h"
58
#include "exec/operator/es_scan_operator.h"
59
#include "exec/operator/exchange_sink_operator.h"
60
#include "exec/operator/exchange_source_operator.h"
61
#include "exec/operator/file_scan_operator.h"
62
#include "exec/operator/group_commit_block_sink_operator.h"
63
#include "exec/operator/group_commit_scan_operator.h"
64
#include "exec/operator/hashjoin_build_sink.h"
65
#include "exec/operator/hashjoin_probe_operator.h"
66
#include "exec/operator/hive_table_sink_operator.h"
67
#include "exec/operator/iceberg_table_sink_operator.h"
68
#include "exec/operator/jdbc_scan_operator.h"
69
#include "exec/operator/jdbc_table_sink_operator.h"
70
#include "exec/operator/local_merge_sort_source_operator.h"
71
#include "exec/operator/materialization_opertor.h"
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#include "exec/operator/maxcompute_table_sink_operator.h"
73
#include "exec/operator/memory_scratch_sink_operator.h"
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#include "exec/operator/meta_scan_operator.h"
75
#include "exec/operator/multi_cast_data_stream_sink.h"
76
#include "exec/operator/multi_cast_data_stream_source.h"
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#include "exec/operator/nested_loop_join_build_operator.h"
78
#include "exec/operator/nested_loop_join_probe_operator.h"
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#include "exec/operator/olap_scan_operator.h"
80
#include "exec/operator/olap_table_sink_operator.h"
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#include "exec/operator/olap_table_sink_v2_operator.h"
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#include "exec/operator/partition_sort_sink_operator.h"
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#include "exec/operator/partition_sort_source_operator.h"
84
#include "exec/operator/partitioned_aggregation_sink_operator.h"
85
#include "exec/operator/partitioned_aggregation_source_operator.h"
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#include "exec/operator/partitioned_hash_join_probe_operator.h"
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#include "exec/operator/partitioned_hash_join_sink_operator.h"
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#include "exec/operator/rec_cte_anchor_sink_operator.h"
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#include "exec/operator/rec_cte_scan_operator.h"
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#include "exec/operator/rec_cte_sink_operator.h"
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#include "exec/operator/rec_cte_source_operator.h"
92
#include "exec/operator/repeat_operator.h"
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#include "exec/operator/result_file_sink_operator.h"
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#include "exec/operator/result_sink_operator.h"
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#include "exec/operator/schema_scan_operator.h"
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#include "exec/operator/select_operator.h"
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#include "exec/operator/set_probe_sink_operator.h"
98
#include "exec/operator/set_sink_operator.h"
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#include "exec/operator/set_source_operator.h"
100
#include "exec/operator/sort_sink_operator.h"
101
#include "exec/operator/sort_source_operator.h"
102
#include "exec/operator/spill_iceberg_table_sink_operator.h"
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#include "exec/operator/spill_sort_sink_operator.h"
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#include "exec/operator/spill_sort_source_operator.h"
105
#include "exec/operator/streaming_aggregation_operator.h"
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#include "exec/operator/table_function_operator.h"
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#include "exec/operator/tvf_table_sink_operator.h"
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#include "exec/operator/union_sink_operator.h"
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#include "exec/operator/union_source_operator.h"
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#include "exec/pipeline/dependency.h"
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#include "exec/pipeline/pipeline_task.h"
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#include "exec/pipeline/task_scheduler.h"
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#include "exec/runtime_filter/runtime_filter_mgr.h"
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#include "exec/sort/topn_sorter.h"
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#include "exec/spill/spill_file.h"
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#include "io/fs/stream_load_pipe.h"
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#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"
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#include "runtime/result_buffer_mgr.h"
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#include "runtime/runtime_state.h"
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#include "runtime/thread_context.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/uid_util.h"
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namespace doris {
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#include "common/compile_check_begin.h"
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PipelineFragmentContext::PipelineFragmentContext(
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        TUniqueId query_id, const TPipelineFragmentParams& request,
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        std::shared_ptr<QueryContext> query_ctx, ExecEnv* exec_env,
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        const std::function<void(RuntimeState*, Status*)>& call_back,
133
        report_status_callback report_status_cb)
134
25
        : _query_id(std::move(query_id)),
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25
          _fragment_id(request.fragment_id),
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          _exec_env(exec_env),
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          _query_ctx(std::move(query_ctx)),
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          _call_back(call_back),
139
25
          _is_report_on_cancel(true),
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          _report_status_cb(std::move(report_status_cb)),
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          _params(request),
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25
          _parallel_instances(_params.__isset.parallel_instances ? _params.parallel_instances : 0),
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          _need_notify_close(request.__isset.need_notify_close ? request.need_notify_close
144
25
                                                               : false) {
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    _fragment_watcher.start();
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25
}
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PipelineFragmentContext::~PipelineFragmentContext() {
149
25
    LOG_INFO("PipelineFragmentContext::~PipelineFragmentContext")
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25
            .tag("query_id", print_id(_query_id))
151
25
            .tag("fragment_id", _fragment_id);
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25
    _release_resource();
153
25
    {
154
        // The memory released by the query end is recorded in the query mem tracker.
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        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
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        _runtime_state.reset();
157
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        _query_ctx.reset();
158
25
    }
159
25
}
160
161
0
bool PipelineFragmentContext::is_timeout(timespec now) const {
162
0
    if (_timeout <= 0) {
163
0
        return false;
164
0
    }
165
0
    return _fragment_watcher.elapsed_time_seconds(now) > _timeout;
166
0
}
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// Must not add lock in this method. Because it will call query ctx cancel. And
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// QueryCtx cancel will call fragment ctx cancel. And Also Fragment ctx's running
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// Method like exchange sink buffer will call query ctx cancel. If we add lock here
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// There maybe dead lock.
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0
void PipelineFragmentContext::cancel(const Status reason) {
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0
    LOG_INFO("PipelineFragmentContext::cancel")
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0
            .tag("query_id", print_id(_query_id))
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0
            .tag("fragment_id", _fragment_id)
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0
            .tag("reason", reason.to_string());
177
0
    {
178
0
        std::lock_guard<std::mutex> l(_task_mutex);
179
0
        if (_closed_tasks >= _total_tasks) {
180
            // All tasks in this PipelineXFragmentContext already closed.
181
0
            return;
182
0
        }
183
0
    }
184
    // Timeout is a special error code, we need print current stack to debug timeout issue.
185
0
    if (reason.is<ErrorCode::TIMEOUT>()) {
186
0
        auto dbg_str = fmt::format("PipelineFragmentContext is cancelled due to timeout:\n{}",
187
0
                                   debug_string());
188
0
        LOG_LONG_STRING(WARNING, dbg_str);
189
0
    }
190
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    // `ILLEGAL_STATE` means queries this fragment belongs to was not found in FE (maybe finished)
192
0
    if (reason.is<ErrorCode::ILLEGAL_STATE>()) {
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0
        LOG_WARNING("PipelineFragmentContext is cancelled due to illegal state : {}",
194
0
                    debug_string());
195
0
    }
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197
0
    if (reason.is<ErrorCode::MEM_LIMIT_EXCEEDED>() || reason.is<ErrorCode::MEM_ALLOC_FAILED>()) {
198
0
        print_profile("cancel pipeline, reason: " + reason.to_string());
199
0
    }
200
201
0
    if (auto error_url = get_load_error_url(); !error_url.empty()) {
202
0
        _query_ctx->set_load_error_url(error_url);
203
0
    }
204
205
0
    if (auto first_error_msg = get_first_error_msg(); !first_error_msg.empty()) {
206
0
        _query_ctx->set_first_error_msg(first_error_msg);
207
0
    }
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209
0
    _query_ctx->cancel(reason, _fragment_id);
210
0
    if (reason.is<ErrorCode::LIMIT_REACH>()) {
211
0
        _is_report_on_cancel = false;
212
0
    } else {
213
0
        for (auto& id : _fragment_instance_ids) {
214
0
            LOG(WARNING) << "PipelineFragmentContext cancel instance: " << print_id(id);
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0
        }
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0
    }
217
    // Get pipe from new load stream manager and send cancel to it or the fragment may hang to wait read from pipe
218
    // For stream load the fragment's query_id == load id, it is set in FE.
219
0
    auto stream_load_ctx = _exec_env->new_load_stream_mgr()->get(_query_id);
220
0
    if (stream_load_ctx != nullptr) {
221
0
        stream_load_ctx->pipe->cancel(reason.to_string());
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        // Set error URL here because after pipe is cancelled, stream load execution may return early.
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        // We need to set the error URL at this point to ensure error information is properly
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        // propagated to the client.
225
0
        stream_load_ctx->error_url = get_load_error_url();
226
0
        stream_load_ctx->first_error_msg = get_first_error_msg();
227
0
    }
228
229
0
    for (auto& tasks : _tasks) {
230
0
        for (auto& task : tasks) {
231
0
            task.first->terminate();
232
0
        }
233
0
    }
234
0
}
235
236
0
PipelinePtr PipelineFragmentContext::add_pipeline(PipelinePtr parent, int idx) {
237
0
    PipelineId id = _next_pipeline_id++;
238
0
    auto pipeline = std::make_shared<Pipeline>(
239
0
            id, parent ? std::min(parent->num_tasks(), _num_instances) : _num_instances,
240
0
            parent ? parent->num_tasks() : _num_instances);
241
0
    if (idx >= 0) {
242
0
        _pipelines.insert(_pipelines.begin() + idx, pipeline);
243
0
    } else {
244
0
        _pipelines.emplace_back(pipeline);
245
0
    }
246
0
    if (parent) {
247
0
        parent->set_children(pipeline);
248
0
    }
249
0
    return pipeline;
250
0
}
251
252
0
Status PipelineFragmentContext::_build_and_prepare_full_pipeline(ThreadPool* thread_pool) {
253
0
    {
254
0
        SCOPED_TIMER(_build_pipelines_timer);
255
        // 2. Build pipelines with operators in this fragment.
256
0
        auto root_pipeline = add_pipeline();
257
0
        RETURN_IF_ERROR(_build_pipelines(_runtime_state->obj_pool(), *_query_ctx->desc_tbl,
258
0
                                         &_root_op, root_pipeline));
259
260
        // 3. Create sink operator
261
0
        if (!_params.fragment.__isset.output_sink) {
262
0
            return Status::InternalError("No output sink in this fragment!");
263
0
        }
264
0
        RETURN_IF_ERROR(_create_data_sink(_runtime_state->obj_pool(), _params.fragment.output_sink,
265
0
                                          _params.fragment.output_exprs, _params,
266
0
                                          root_pipeline->output_row_desc(), _runtime_state.get(),
267
0
                                          *_desc_tbl, root_pipeline->id()));
268
0
        RETURN_IF_ERROR(_sink->init(_params.fragment.output_sink));
269
0
        RETURN_IF_ERROR(root_pipeline->set_sink(_sink));
270
271
0
        for (PipelinePtr& pipeline : _pipelines) {
272
0
            DCHECK(pipeline->sink() != nullptr) << pipeline->operators().size();
273
0
            RETURN_IF_ERROR(pipeline->sink()->set_child(pipeline->operators().back()));
274
0
        }
275
0
    }
276
    // 4. Build local exchanger
277
0
    if (_runtime_state->enable_local_shuffle()) {
278
0
        SCOPED_TIMER(_plan_local_exchanger_timer);
279
0
        RETURN_IF_ERROR(_plan_local_exchange(_params.num_buckets,
280
0
                                             _params.bucket_seq_to_instance_idx,
281
0
                                             _params.shuffle_idx_to_instance_idx));
282
0
    }
283
284
    // 5. Initialize global states in pipelines.
285
0
    for (PipelinePtr& pipeline : _pipelines) {
286
0
        SCOPED_TIMER(_prepare_all_pipelines_timer);
287
0
        pipeline->children().clear();
288
0
        RETURN_IF_ERROR(pipeline->prepare(_runtime_state.get()));
289
0
    }
290
291
0
    {
292
0
        SCOPED_TIMER(_build_tasks_timer);
293
        // 6. Build pipeline tasks and initialize local state.
294
0
        RETURN_IF_ERROR(_build_pipeline_tasks(thread_pool));
295
0
    }
296
297
0
    return Status::OK();
298
0
}
299
300
0
Status PipelineFragmentContext::prepare(ThreadPool* thread_pool) {
301
0
    if (_prepared) {
302
0
        return Status::InternalError("Already prepared");
303
0
    }
304
0
    if (_params.__isset.query_options && _params.query_options.__isset.execution_timeout) {
305
0
        _timeout = _params.query_options.execution_timeout;
306
0
    }
307
308
0
    _fragment_level_profile = std::make_unique<RuntimeProfile>("PipelineContext");
309
0
    _prepare_timer = ADD_TIMER(_fragment_level_profile, "PrepareTime");
310
0
    SCOPED_TIMER(_prepare_timer);
311
0
    _build_pipelines_timer = ADD_TIMER(_fragment_level_profile, "BuildPipelinesTime");
312
0
    _init_context_timer = ADD_TIMER(_fragment_level_profile, "InitContextTime");
313
0
    _plan_local_exchanger_timer = ADD_TIMER(_fragment_level_profile, "PlanLocalLocalExchangerTime");
314
0
    _build_tasks_timer = ADD_TIMER(_fragment_level_profile, "BuildTasksTime");
315
0
    _prepare_all_pipelines_timer = ADD_TIMER(_fragment_level_profile, "PrepareAllPipelinesTime");
316
0
    {
317
0
        SCOPED_TIMER(_init_context_timer);
318
0
        cast_set(_num_instances, _params.local_params.size());
319
0
        _total_instances =
320
0
                _params.__isset.total_instances ? _params.total_instances : _num_instances;
321
322
0
        auto* fragment_context = this;
323
324
0
        if (_params.query_options.__isset.is_report_success) {
325
0
            fragment_context->set_is_report_success(_params.query_options.is_report_success);
326
0
        }
327
328
        // 1. Set up the global runtime state.
329
0
        _runtime_state = RuntimeState::create_unique(
330
0
                _params.query_id, _params.fragment_id, _params.query_options,
331
0
                _query_ctx->query_globals, _exec_env, _query_ctx.get());
332
0
        _runtime_state->set_task_execution_context(shared_from_this());
333
0
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_runtime_state->query_mem_tracker());
334
0
        if (_params.__isset.backend_id) {
335
0
            _runtime_state->set_backend_id(_params.backend_id);
336
0
        }
337
0
        if (_params.__isset.import_label) {
338
0
            _runtime_state->set_import_label(_params.import_label);
339
0
        }
340
0
        if (_params.__isset.db_name) {
341
0
            _runtime_state->set_db_name(_params.db_name);
342
0
        }
343
0
        if (_params.__isset.load_job_id) {
344
0
            _runtime_state->set_load_job_id(_params.load_job_id);
345
0
        }
346
347
0
        if (_params.is_simplified_param) {
348
0
            _desc_tbl = _query_ctx->desc_tbl;
349
0
        } else {
350
0
            DCHECK(_params.__isset.desc_tbl);
351
0
            RETURN_IF_ERROR(DescriptorTbl::create(_runtime_state->obj_pool(), _params.desc_tbl,
352
0
                                                  &_desc_tbl));
353
0
        }
354
0
        _runtime_state->set_desc_tbl(_desc_tbl);
355
0
        _runtime_state->set_num_per_fragment_instances(_params.num_senders);
356
0
        _runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
357
0
        _runtime_state->set_total_load_streams(_params.total_load_streams);
358
0
        _runtime_state->set_num_local_sink(_params.num_local_sink);
359
360
        // init fragment_instance_ids
361
0
        const auto target_size = _params.local_params.size();
362
0
        _fragment_instance_ids.resize(target_size);
363
0
        for (size_t i = 0; i < _params.local_params.size(); i++) {
364
0
            auto fragment_instance_id = _params.local_params[i].fragment_instance_id;
365
0
            _fragment_instance_ids[i] = fragment_instance_id;
366
0
        }
367
0
    }
368
369
0
    RETURN_IF_ERROR(_build_and_prepare_full_pipeline(thread_pool));
370
371
0
    _init_next_report_time();
372
373
0
    _prepared = true;
374
0
    return Status::OK();
375
0
}
376
377
Status PipelineFragmentContext::_build_pipeline_tasks_for_instance(
378
        int instance_idx,
379
0
        const std::vector<std::shared_ptr<RuntimeProfile>>& pipeline_id_to_profile) {
380
0
    const auto& local_params = _params.local_params[instance_idx];
381
0
    auto fragment_instance_id = local_params.fragment_instance_id;
382
0
    auto runtime_filter_mgr = std::make_unique<RuntimeFilterMgr>(false);
383
0
    std::map<PipelineId, PipelineTask*> pipeline_id_to_task;
384
0
    auto get_shared_state = [&](PipelinePtr pipeline)
385
0
            -> std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
386
0
                                       std::vector<std::shared_ptr<Dependency>>>> {
387
0
        std::map<int, std::pair<std::shared_ptr<BasicSharedState>,
388
0
                                std::vector<std::shared_ptr<Dependency>>>>
389
0
                shared_state_map;
390
0
        for (auto& op : pipeline->operators()) {
391
0
            auto source_id = op->operator_id();
392
0
            if (auto iter = _op_id_to_shared_state.find(source_id);
393
0
                iter != _op_id_to_shared_state.end()) {
394
0
                shared_state_map.insert({source_id, iter->second});
395
0
            }
396
0
        }
397
0
        for (auto sink_to_source_id : pipeline->sink()->dests_id()) {
398
0
            if (auto iter = _op_id_to_shared_state.find(sink_to_source_id);
399
0
                iter != _op_id_to_shared_state.end()) {
400
0
                shared_state_map.insert({sink_to_source_id, iter->second});
401
0
            }
402
0
        }
403
0
        return shared_state_map;
404
0
    };
405
406
0
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
407
0
        auto& pipeline = _pipelines[pip_idx];
408
0
        if (pipeline->num_tasks() > 1 || instance_idx == 0) {
409
0
            auto task_runtime_state = RuntimeState::create_unique(
410
0
                    local_params.fragment_instance_id, _params.query_id, _params.fragment_id,
411
0
                    _params.query_options, _query_ctx->query_globals, _exec_env, _query_ctx.get());
412
0
            {
413
                // Initialize runtime state for this task
414
0
                task_runtime_state->set_query_mem_tracker(_query_ctx->query_mem_tracker());
415
416
0
                task_runtime_state->set_task_execution_context(shared_from_this());
417
0
                task_runtime_state->set_be_number(local_params.backend_num);
418
0
                if (_need_notify_close) {
419
                    // rec cte require child rf to wait infinitely to make sure all rpc done
420
0
                    task_runtime_state->set_force_make_rf_wait_infinite();
421
0
                }
422
423
0
                if (_params.__isset.backend_id) {
424
0
                    task_runtime_state->set_backend_id(_params.backend_id);
425
0
                }
426
0
                if (_params.__isset.import_label) {
427
0
                    task_runtime_state->set_import_label(_params.import_label);
428
0
                }
429
0
                if (_params.__isset.db_name) {
430
0
                    task_runtime_state->set_db_name(_params.db_name);
431
0
                }
432
0
                if (_params.__isset.load_job_id) {
433
0
                    task_runtime_state->set_load_job_id(_params.load_job_id);
434
0
                }
435
0
                if (_params.__isset.wal_id) {
436
0
                    task_runtime_state->set_wal_id(_params.wal_id);
437
0
                }
438
0
                if (_params.__isset.content_length) {
439
0
                    task_runtime_state->set_content_length(_params.content_length);
440
0
                }
441
442
0
                task_runtime_state->set_desc_tbl(_desc_tbl);
443
0
                task_runtime_state->set_per_fragment_instance_idx(local_params.sender_id);
444
0
                task_runtime_state->set_num_per_fragment_instances(_params.num_senders);
445
0
                task_runtime_state->resize_op_id_to_local_state(max_operator_id());
446
0
                task_runtime_state->set_max_operator_id(max_operator_id());
447
0
                task_runtime_state->set_load_stream_per_node(_params.load_stream_per_node);
448
0
                task_runtime_state->set_total_load_streams(_params.total_load_streams);
449
0
                task_runtime_state->set_num_local_sink(_params.num_local_sink);
450
451
0
                task_runtime_state->set_runtime_filter_mgr(runtime_filter_mgr.get());
452
0
            }
453
0
            auto cur_task_id = _total_tasks++;
454
0
            task_runtime_state->set_task_id(cur_task_id);
455
0
            task_runtime_state->set_task_num(pipeline->num_tasks());
456
0
            auto task = std::make_shared<PipelineTask>(
457
0
                    pipeline, cur_task_id, task_runtime_state.get(),
458
0
                    std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()),
459
0
                    pipeline_id_to_profile[pip_idx].get(), get_shared_state(pipeline),
460
0
                    instance_idx);
461
0
            pipeline->incr_created_tasks(instance_idx, task.get());
462
0
            pipeline_id_to_task.insert({pipeline->id(), task.get()});
463
0
            _tasks[instance_idx].emplace_back(
464
0
                    std::pair<std::shared_ptr<PipelineTask>, std::unique_ptr<RuntimeState>> {
465
0
                            std::move(task), std::move(task_runtime_state)});
466
0
        }
467
0
    }
468
469
    /**
470
         * Build DAG for pipeline tasks.
471
         * For example, we have
472
         *
473
         *   ExchangeSink (Pipeline1)     JoinBuildSink (Pipeline2)
474
         *            \                      /
475
         *          JoinProbeOperator1 (Pipeline1)    JoinBuildSink (Pipeline3)
476
         *                 \                          /
477
         *               JoinProbeOperator2 (Pipeline1)
478
         *
479
         * In this fragment, we have three pipelines and pipeline 1 depends on pipeline 2 and pipeline 3.
480
         * To build this DAG, `_dag` manage dependencies between pipelines by pipeline ID and
481
         * `pipeline_id_to_task` is used to find the task by a unique pipeline ID.
482
         *
483
         * Finally, we have two upstream dependencies in Pipeline1 corresponding to JoinProbeOperator1
484
         * and JoinProbeOperator2.
485
         */
486
0
    for (auto& _pipeline : _pipelines) {
487
0
        if (pipeline_id_to_task.contains(_pipeline->id())) {
488
0
            auto* task = pipeline_id_to_task[_pipeline->id()];
489
0
            DCHECK(task != nullptr);
490
491
            // If this task has upstream dependency, then inject it into this task.
492
0
            if (_dag.contains(_pipeline->id())) {
493
0
                auto& deps = _dag[_pipeline->id()];
494
0
                for (auto& dep : deps) {
495
0
                    if (pipeline_id_to_task.contains(dep)) {
496
0
                        auto ss = pipeline_id_to_task[dep]->get_sink_shared_state();
497
0
                        if (ss) {
498
0
                            task->inject_shared_state(ss);
499
0
                        } else {
500
0
                            pipeline_id_to_task[dep]->inject_shared_state(
501
0
                                    task->get_source_shared_state());
502
0
                        }
503
0
                    }
504
0
                }
505
0
            }
506
0
        }
507
0
    }
508
0
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
509
0
        if (pipeline_id_to_task.contains(_pipelines[pip_idx]->id())) {
510
0
            auto* task = pipeline_id_to_task[_pipelines[pip_idx]->id()];
511
0
            DCHECK(pipeline_id_to_profile[pip_idx]);
512
0
            std::vector<TScanRangeParams> scan_ranges;
513
0
            auto node_id = _pipelines[pip_idx]->operators().front()->node_id();
514
0
            if (local_params.per_node_scan_ranges.contains(node_id)) {
515
0
                scan_ranges = local_params.per_node_scan_ranges.find(node_id)->second;
516
0
            }
517
0
            RETURN_IF_ERROR_OR_CATCH_EXCEPTION(task->prepare(scan_ranges, local_params.sender_id,
518
0
                                                             _params.fragment.output_sink));
519
0
        }
520
0
    }
521
0
    {
522
0
        std::lock_guard<std::mutex> l(_state_map_lock);
523
0
        _runtime_filter_mgr_map[instance_idx] = std::move(runtime_filter_mgr);
524
0
    }
525
0
    return Status::OK();
526
0
}
527
528
0
Status PipelineFragmentContext::_build_pipeline_tasks(ThreadPool* thread_pool) {
529
0
    _total_tasks = 0;
530
0
    _closed_tasks = 0;
531
0
    const auto target_size = _params.local_params.size();
532
0
    _tasks.resize(target_size);
533
0
    _runtime_filter_mgr_map.resize(target_size);
534
0
    for (size_t pip_idx = 0; pip_idx < _pipelines.size(); pip_idx++) {
535
0
        _pip_id_to_pipeline[_pipelines[pip_idx]->id()] = _pipelines[pip_idx].get();
536
0
    }
537
0
    auto pipeline_id_to_profile = _runtime_state->build_pipeline_profile(_pipelines.size());
538
539
0
    if (target_size > 1 &&
540
0
        (_runtime_state->query_options().__isset.parallel_prepare_threshold &&
541
0
         target_size > _runtime_state->query_options().parallel_prepare_threshold)) {
542
        // If instances parallelism is big enough ( > parallel_prepare_threshold), we will prepare all tasks by multi-threads
543
0
        std::vector<Status> prepare_status(target_size);
544
0
        int submitted_tasks = 0;
545
0
        Status submit_status;
546
0
        CountDownLatch latch((int)target_size);
547
0
        for (int i = 0; i < target_size; i++) {
548
0
            submit_status = thread_pool->submit_func([&, i]() {
549
0
                SCOPED_ATTACH_TASK(_query_ctx.get());
550
0
                prepare_status[i] = _build_pipeline_tasks_for_instance(i, pipeline_id_to_profile);
551
0
                latch.count_down();
552
0
            });
553
0
            if (LIKELY(submit_status.ok())) {
554
0
                submitted_tasks++;
555
0
            } else {
556
0
                break;
557
0
            }
558
0
        }
559
0
        latch.arrive_and_wait(target_size - submitted_tasks);
560
0
        if (UNLIKELY(!submit_status.ok())) {
561
0
            return submit_status;
562
0
        }
563
0
        for (int i = 0; i < submitted_tasks; i++) {
564
0
            if (!prepare_status[i].ok()) {
565
0
                return prepare_status[i];
566
0
            }
567
0
        }
568
0
    } else {
569
0
        for (int i = 0; i < target_size; i++) {
570
0
            RETURN_IF_ERROR(_build_pipeline_tasks_for_instance(i, pipeline_id_to_profile));
571
0
        }
572
0
    }
573
0
    _pipeline_parent_map.clear();
574
0
    _op_id_to_shared_state.clear();
575
576
0
    return Status::OK();
577
0
}
578
579
0
void PipelineFragmentContext::_init_next_report_time() {
580
0
    auto interval_s = config::pipeline_status_report_interval;
581
0
    if (_is_report_success && interval_s > 0 && _timeout > interval_s) {
582
0
        VLOG_FILE << "enable period report: fragment id=" << _fragment_id;
583
0
        uint64_t report_fragment_offset = (uint64_t)(rand() % interval_s) * NANOS_PER_SEC;
584
        // We don't want to wait longer than it takes to run the entire fragment.
585
0
        _previous_report_time =
586
0
                MonotonicNanos() + report_fragment_offset - (uint64_t)(interval_s)*NANOS_PER_SEC;
587
0
        _disable_period_report = false;
588
0
    }
589
0
}
590
591
0
void PipelineFragmentContext::refresh_next_report_time() {
592
0
    auto disable = _disable_period_report.load(std::memory_order_acquire);
593
0
    DCHECK(disable == true);
594
0
    _previous_report_time.store(MonotonicNanos(), std::memory_order_release);
595
0
    _disable_period_report.compare_exchange_strong(disable, false);
596
0
}
597
598
0
void PipelineFragmentContext::trigger_report_if_necessary() {
599
0
    if (!_is_report_success) {
600
0
        return;
601
0
    }
602
0
    auto disable = _disable_period_report.load(std::memory_order_acquire);
603
0
    if (disable) {
604
0
        return;
605
0
    }
606
0
    int32_t interval_s = config::pipeline_status_report_interval;
607
0
    if (interval_s <= 0) {
608
0
        LOG(WARNING) << "config::status_report_interval is equal to or less than zero, do not "
609
0
                        "trigger "
610
0
                        "report.";
611
0
    }
612
0
    uint64_t next_report_time = _previous_report_time.load(std::memory_order_acquire) +
613
0
                                (uint64_t)(interval_s)*NANOS_PER_SEC;
614
0
    if (MonotonicNanos() > next_report_time) {
615
0
        if (!_disable_period_report.compare_exchange_strong(disable, true,
616
0
                                                            std::memory_order_acq_rel)) {
617
0
            return;
618
0
        }
619
0
        if (VLOG_FILE_IS_ON) {
620
0
            VLOG_FILE << "Reporting "
621
0
                      << "profile for query_id " << print_id(_query_id)
622
0
                      << ", fragment id: " << _fragment_id;
623
624
0
            std::stringstream ss;
625
0
            _runtime_state->runtime_profile()->compute_time_in_profile();
626
0
            _runtime_state->runtime_profile()->pretty_print(&ss);
627
0
            if (_runtime_state->load_channel_profile()) {
628
0
                _runtime_state->load_channel_profile()->pretty_print(&ss);
629
0
            }
630
631
0
            VLOG_FILE << "Query " << print_id(get_query_id()) << " fragment " << get_fragment_id()
632
0
                      << " profile:\n"
633
0
                      << ss.str();
634
0
        }
635
0
        auto st = send_report(false);
636
0
        if (!st.ok()) {
637
0
            disable = true;
638
0
            _disable_period_report.compare_exchange_strong(disable, false,
639
0
                                                           std::memory_order_acq_rel);
640
0
        }
641
0
    }
642
0
}
643
644
Status PipelineFragmentContext::_build_pipelines(ObjectPool* pool, const DescriptorTbl& descs,
645
0
                                                 OperatorPtr* root, PipelinePtr cur_pipe) {
646
0
    if (_params.fragment.plan.nodes.empty()) {
647
0
        throw Exception(ErrorCode::INTERNAL_ERROR, "Invalid plan which has no plan node!");
648
0
    }
649
650
0
    int node_idx = 0;
651
652
0
    RETURN_IF_ERROR(_create_tree_helper(pool, _params.fragment.plan.nodes, descs, nullptr,
653
0
                                        &node_idx, root, cur_pipe, 0, false, false));
654
655
0
    if (node_idx + 1 != _params.fragment.plan.nodes.size()) {
656
0
        return Status::InternalError(
657
0
                "Plan tree only partially reconstructed. Not all thrift nodes were used.");
658
0
    }
659
0
    return Status::OK();
660
0
}
661
662
Status PipelineFragmentContext::_create_tree_helper(
663
        ObjectPool* pool, const std::vector<TPlanNode>& tnodes, const DescriptorTbl& descs,
664
        OperatorPtr parent, int* node_idx, OperatorPtr* root, PipelinePtr& cur_pipe, int child_idx,
665
0
        const bool followed_by_shuffled_operator, const bool require_bucket_distribution) {
666
    // propagate error case
667
0
    if (*node_idx >= tnodes.size()) {
668
0
        return Status::InternalError(
669
0
                "Failed to reconstruct plan tree from thrift. Node id: {}, number of nodes: {}",
670
0
                *node_idx, tnodes.size());
671
0
    }
672
0
    const TPlanNode& tnode = tnodes[*node_idx];
673
674
0
    int num_children = tnodes[*node_idx].num_children;
675
0
    bool current_followed_by_shuffled_operator = followed_by_shuffled_operator;
676
0
    bool current_require_bucket_distribution = require_bucket_distribution;
677
0
    OperatorPtr op = nullptr;
678
0
    RETURN_IF_ERROR(_create_operator(pool, tnodes[*node_idx], descs, op, cur_pipe,
679
0
                                     parent == nullptr ? -1 : parent->node_id(), child_idx,
680
0
                                     followed_by_shuffled_operator,
681
0
                                     current_require_bucket_distribution));
682
    // Initialization must be done here. For example, group by expressions in agg will be used to
683
    // decide if a local shuffle should be planed, so it must be initialized here.
684
0
    RETURN_IF_ERROR(op->init(tnode, _runtime_state.get()));
685
    // assert(parent != nullptr || (node_idx == 0 && root_expr != nullptr));
686
0
    if (parent != nullptr) {
687
        // add to parent's child(s)
688
0
        RETURN_IF_ERROR(parent->set_child(op));
689
0
    } else {
690
0
        *root = op;
691
0
    }
692
    /**
693
     * `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).
694
     *
695
     * For plan:
696
     * LocalExchange(id=0) -> Aggregation(id=1) -> ShuffledHashJoin(id=2)
697
     *                           Exchange(id=3) -> ShuffledHashJoinBuild(id=2)
698
     * We must ensure data distribution of `LocalExchange(id=0)` is same as Exchange(id=3).
699
     *
700
     * If an operator's is followed by a local exchange without shuffle (e.g. passthrough), a
701
     * shuffled local exchanger will be used before join so it is not followed by shuffle join.
702
     */
703
0
    auto required_data_distribution =
704
0
            cur_pipe->operators().empty()
705
0
                    ? cur_pipe->sink()->required_data_distribution(_runtime_state.get())
706
0
                    : op->required_data_distribution(_runtime_state.get());
707
0
    current_followed_by_shuffled_operator =
708
0
            ((followed_by_shuffled_operator ||
709
0
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_shuffled_operator()
710
0
                                             : op->is_shuffled_operator())) &&
711
0
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
712
0
            (followed_by_shuffled_operator &&
713
0
             required_data_distribution.distribution_type == ExchangeType::NOOP);
714
715
0
    current_require_bucket_distribution =
716
0
            ((require_bucket_distribution ||
717
0
              (cur_pipe->operators().empty() ? cur_pipe->sink()->is_colocated_operator()
718
0
                                             : op->is_colocated_operator())) &&
719
0
             Pipeline::is_hash_exchange(required_data_distribution.distribution_type)) ||
720
0
            (require_bucket_distribution &&
721
0
             required_data_distribution.distribution_type == ExchangeType::NOOP);
722
723
0
    if (num_children == 0) {
724
0
        _use_serial_source = op->is_serial_operator();
725
0
    }
726
    // rely on that tnodes is preorder of the plan
727
0
    for (int i = 0; i < num_children; i++) {
728
0
        ++*node_idx;
729
0
        RETURN_IF_ERROR(_create_tree_helper(pool, tnodes, descs, op, node_idx, nullptr, cur_pipe, i,
730
0
                                            current_followed_by_shuffled_operator,
731
0
                                            current_require_bucket_distribution));
732
733
        // we are expecting a child, but have used all nodes
734
        // this means we have been given a bad tree and must fail
735
0
        if (*node_idx >= tnodes.size()) {
736
0
            return Status::InternalError(
737
0
                    "Failed to reconstruct plan tree from thrift. Node id: {}, number of "
738
0
                    "nodes: {}",
739
0
                    *node_idx, tnodes.size());
740
0
        }
741
0
    }
742
743
0
    return Status::OK();
744
0
}
745
746
void PipelineFragmentContext::_inherit_pipeline_properties(
747
        const DataDistribution& data_distribution, PipelinePtr pipe_with_source,
748
0
        PipelinePtr pipe_with_sink) {
749
0
    pipe_with_sink->set_num_tasks(pipe_with_source->num_tasks());
750
0
    pipe_with_source->set_num_tasks(_num_instances);
751
0
    pipe_with_source->set_data_distribution(data_distribution);
752
0
}
753
754
Status PipelineFragmentContext::_add_local_exchange_impl(
755
        int idx, ObjectPool* pool, PipelinePtr cur_pipe, PipelinePtr new_pip,
756
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
757
        const std::map<int, int>& bucket_seq_to_instance_idx,
758
0
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
759
0
    auto& operators = cur_pipe->operators();
760
0
    const auto downstream_pipeline_id = cur_pipe->id();
761
0
    auto local_exchange_id = next_operator_id();
762
    // 1. Create a new pipeline with local exchange sink.
763
0
    DataSinkOperatorPtr sink;
764
0
    auto sink_id = next_sink_operator_id();
765
766
    /**
767
     * `bucket_seq_to_instance_idx` is empty if no scan operator is contained in this fragment.
768
     * So co-located operators(e.g. Agg, Analytic) should use `HASH_SHUFFLE` instead of `BUCKET_HASH_SHUFFLE`.
769
     */
770
0
    const bool followed_by_shuffled_operator =
771
0
            operators.size() > idx ? operators[idx]->followed_by_shuffled_operator()
772
0
                                   : cur_pipe->sink()->followed_by_shuffled_operator();
773
0
    const bool use_global_hash_shuffle = bucket_seq_to_instance_idx.empty() &&
774
0
                                         !shuffle_idx_to_instance_idx.contains(-1) &&
775
0
                                         followed_by_shuffled_operator && !_use_serial_source;
776
0
    sink = std::make_shared<LocalExchangeSinkOperatorX>(
777
0
            sink_id, local_exchange_id, use_global_hash_shuffle ? _total_instances : _num_instances,
778
0
            data_distribution.partition_exprs, bucket_seq_to_instance_idx);
779
0
    if (bucket_seq_to_instance_idx.empty() &&
780
0
        data_distribution.distribution_type == ExchangeType::BUCKET_HASH_SHUFFLE) {
781
0
        data_distribution.distribution_type = ExchangeType::HASH_SHUFFLE;
782
0
    }
783
0
    RETURN_IF_ERROR(new_pip->set_sink(sink));
784
0
    RETURN_IF_ERROR(new_pip->sink()->init(_runtime_state.get(), data_distribution.distribution_type,
785
0
                                          num_buckets, use_global_hash_shuffle,
786
0
                                          shuffle_idx_to_instance_idx));
787
788
    // 2. Create and initialize LocalExchangeSharedState.
789
0
    std::shared_ptr<LocalExchangeSharedState> shared_state =
790
0
            LocalExchangeSharedState::create_shared(_num_instances);
791
0
    switch (data_distribution.distribution_type) {
792
0
    case ExchangeType::HASH_SHUFFLE:
793
0
        shared_state->exchanger = ShuffleExchanger::create_unique(
794
0
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
795
0
                use_global_hash_shuffle ? _total_instances : _num_instances,
796
0
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
797
0
                        ? cast_set<int>(
798
0
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
799
0
                        : 0);
800
0
        break;
801
0
    case ExchangeType::BUCKET_HASH_SHUFFLE:
802
0
        shared_state->exchanger = BucketShuffleExchanger::create_unique(
803
0
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances, num_buckets,
804
0
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
805
0
                        ? cast_set<int>(
806
0
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
807
0
                        : 0);
808
0
        break;
809
0
    case ExchangeType::PASSTHROUGH:
810
0
        shared_state->exchanger = PassthroughExchanger::create_unique(
811
0
                cur_pipe->num_tasks(), _num_instances,
812
0
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
813
0
                        ? cast_set<int>(
814
0
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
815
0
                        : 0);
816
0
        break;
817
0
    case ExchangeType::BROADCAST:
818
0
        shared_state->exchanger = BroadcastExchanger::create_unique(
819
0
                cur_pipe->num_tasks(), _num_instances,
820
0
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
821
0
                        ? cast_set<int>(
822
0
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
823
0
                        : 0);
824
0
        break;
825
0
    case ExchangeType::PASS_TO_ONE:
826
0
        if (_runtime_state->enable_share_hash_table_for_broadcast_join()) {
827
            // If shared hash table is enabled for BJ, hash table will be built by only one task
828
0
            shared_state->exchanger = PassToOneExchanger::create_unique(
829
0
                    cur_pipe->num_tasks(), _num_instances,
830
0
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
831
0
                            ? cast_set<int>(_runtime_state->query_options()
832
0
                                                    .local_exchange_free_blocks_limit)
833
0
                            : 0);
834
0
        } else {
835
0
            shared_state->exchanger = BroadcastExchanger::create_unique(
836
0
                    cur_pipe->num_tasks(), _num_instances,
837
0
                    _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
838
0
                            ? cast_set<int>(_runtime_state->query_options()
839
0
                                                    .local_exchange_free_blocks_limit)
840
0
                            : 0);
841
0
        }
842
0
        break;
843
0
    case ExchangeType::ADAPTIVE_PASSTHROUGH:
844
0
        shared_state->exchanger = AdaptivePassthroughExchanger::create_unique(
845
0
                std::max(cur_pipe->num_tasks(), _num_instances), _num_instances,
846
0
                _runtime_state->query_options().__isset.local_exchange_free_blocks_limit
847
0
                        ? cast_set<int>(
848
0
                                  _runtime_state->query_options().local_exchange_free_blocks_limit)
849
0
                        : 0);
850
0
        break;
851
0
    default:
852
0
        return Status::InternalError("Unsupported local exchange type : " +
853
0
                                     std::to_string((int)data_distribution.distribution_type));
854
0
    }
855
0
    shared_state->create_source_dependencies(_num_instances, local_exchange_id, local_exchange_id,
856
0
                                             "LOCAL_EXCHANGE_OPERATOR");
857
0
    shared_state->create_sink_dependency(sink_id, local_exchange_id, "LOCAL_EXCHANGE_SINK");
858
0
    _op_id_to_shared_state.insert({local_exchange_id, {shared_state, shared_state->sink_deps}});
859
860
    // 3. Set two pipelines' operator list. For example, split pipeline [Scan - AggSink] to
861
    // pipeline1 [Scan - LocalExchangeSink] and pipeline2 [LocalExchangeSource - AggSink].
862
863
    // 3.1 Initialize new pipeline's operator list.
864
0
    std::copy(operators.begin(), operators.begin() + idx,
865
0
              std::inserter(new_pip->operators(), new_pip->operators().end()));
866
867
    // 3.2 Erase unused operators in previous pipeline.
868
0
    operators.erase(operators.begin(), operators.begin() + idx);
869
870
    // 4. Initialize LocalExchangeSource and insert it into this pipeline.
871
0
    OperatorPtr source_op;
872
0
    source_op = std::make_shared<LocalExchangeSourceOperatorX>(pool, local_exchange_id);
873
0
    RETURN_IF_ERROR(source_op->set_child(new_pip->operators().back()));
874
0
    RETURN_IF_ERROR(source_op->init(data_distribution.distribution_type));
875
0
    if (!operators.empty()) {
876
0
        RETURN_IF_ERROR(operators.front()->set_child(nullptr));
877
0
        RETURN_IF_ERROR(operators.front()->set_child(source_op));
878
0
    }
879
0
    operators.insert(operators.begin(), source_op);
880
881
    // 5. Set children for two pipelines separately.
882
0
    std::vector<std::shared_ptr<Pipeline>> new_children;
883
0
    std::vector<PipelineId> edges_with_source;
884
0
    for (auto child : cur_pipe->children()) {
885
0
        bool found = false;
886
0
        for (auto op : new_pip->operators()) {
887
0
            if (child->sink()->node_id() == op->node_id()) {
888
0
                new_pip->set_children(child);
889
0
                found = true;
890
0
            };
891
0
        }
892
0
        if (!found) {
893
0
            new_children.push_back(child);
894
0
            edges_with_source.push_back(child->id());
895
0
        }
896
0
    }
897
0
    new_children.push_back(new_pip);
898
0
    edges_with_source.push_back(new_pip->id());
899
900
    // 6. Set DAG for new pipelines.
901
0
    if (!new_pip->children().empty()) {
902
0
        std::vector<PipelineId> edges_with_sink;
903
0
        for (auto child : new_pip->children()) {
904
0
            edges_with_sink.push_back(child->id());
905
0
        }
906
0
        _dag.insert({new_pip->id(), edges_with_sink});
907
0
    }
908
0
    cur_pipe->set_children(new_children);
909
0
    _dag[downstream_pipeline_id] = edges_with_source;
910
0
    RETURN_IF_ERROR(new_pip->sink()->set_child(new_pip->operators().back()));
911
0
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(nullptr));
912
0
    RETURN_IF_ERROR(cur_pipe->sink()->set_child(cur_pipe->operators().back()));
913
914
    // 7. Inherit properties from current pipeline.
915
0
    _inherit_pipeline_properties(data_distribution, cur_pipe, new_pip);
916
0
    return Status::OK();
917
0
}
918
919
Status PipelineFragmentContext::_add_local_exchange(
920
        int pip_idx, int idx, int node_id, ObjectPool* pool, PipelinePtr cur_pipe,
921
        DataDistribution data_distribution, bool* do_local_exchange, int num_buckets,
922
        const std::map<int, int>& bucket_seq_to_instance_idx,
923
0
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
924
0
    if (_num_instances <= 1 || cur_pipe->num_tasks_of_parent() <= 1) {
925
0
        return Status::OK();
926
0
    }
927
928
0
    if (!cur_pipe->need_to_local_exchange(data_distribution, idx)) {
929
0
        return Status::OK();
930
0
    }
931
0
    *do_local_exchange = true;
932
933
0
    auto& operators = cur_pipe->operators();
934
0
    auto total_op_num = operators.size();
935
0
    auto new_pip = add_pipeline(cur_pipe, pip_idx + 1);
936
0
    RETURN_IF_ERROR(_add_local_exchange_impl(
937
0
            idx, pool, cur_pipe, new_pip, data_distribution, do_local_exchange, num_buckets,
938
0
            bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
939
940
0
    CHECK(total_op_num + 1 == cur_pipe->operators().size() + new_pip->operators().size())
941
0
            << "total_op_num: " << total_op_num
942
0
            << " cur_pipe->operators().size(): " << cur_pipe->operators().size()
943
0
            << " new_pip->operators().size(): " << new_pip->operators().size();
944
945
    // There are some local shuffles with relatively heavy operations on the sink.
946
    // If the local sink concurrency is 1 and the local source concurrency is n, the sink becomes a bottleneck.
947
    // Therefore, local passthrough is used to increase the concurrency of the sink.
948
    // op -> local sink(1) -> local source (n)
949
    // op -> local passthrough(1) -> local passthrough(n) ->  local sink(n) -> local source (n)
950
0
    if (cur_pipe->num_tasks() > 1 && new_pip->num_tasks() == 1 &&
951
0
        Pipeline::heavy_operations_on_the_sink(data_distribution.distribution_type)) {
952
0
        RETURN_IF_ERROR(_add_local_exchange_impl(
953
0
                cast_set<int>(new_pip->operators().size()), pool, new_pip,
954
0
                add_pipeline(new_pip, pip_idx + 2), DataDistribution(ExchangeType::PASSTHROUGH),
955
0
                do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
956
0
                shuffle_idx_to_instance_idx));
957
0
    }
958
0
    return Status::OK();
959
0
}
960
961
Status PipelineFragmentContext::_plan_local_exchange(
962
        int num_buckets, const std::map<int, int>& bucket_seq_to_instance_idx,
963
0
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
964
0
    for (int pip_idx = cast_set<int>(_pipelines.size()) - 1; pip_idx >= 0; pip_idx--) {
965
0
        _pipelines[pip_idx]->init_data_distribution(_runtime_state.get());
966
        // Set property if child pipeline is not join operator's child.
967
0
        if (!_pipelines[pip_idx]->children().empty()) {
968
0
            for (auto& child : _pipelines[pip_idx]->children()) {
969
0
                if (child->sink()->node_id() ==
970
0
                    _pipelines[pip_idx]->operators().front()->node_id()) {
971
0
                    _pipelines[pip_idx]->set_data_distribution(child->data_distribution());
972
0
                }
973
0
            }
974
0
        }
975
976
        // if 'num_buckets == 0' means the fragment is colocated by exchange node not the
977
        // scan node. so here use `_num_instance` to replace the `num_buckets` to prevent dividing 0
978
        // still keep colocate plan after local shuffle
979
0
        RETURN_IF_ERROR(_plan_local_exchange(num_buckets, pip_idx, _pipelines[pip_idx],
980
0
                                             bucket_seq_to_instance_idx,
981
0
                                             shuffle_idx_to_instance_idx));
982
0
    }
983
0
    return Status::OK();
984
0
}
985
986
Status PipelineFragmentContext::_plan_local_exchange(
987
        int num_buckets, int pip_idx, PipelinePtr pip,
988
        const std::map<int, int>& bucket_seq_to_instance_idx,
989
0
        const std::map<int, int>& shuffle_idx_to_instance_idx) {
990
0
    int idx = 1;
991
0
    bool do_local_exchange = false;
992
0
    do {
993
0
        auto& ops = pip->operators();
994
0
        do_local_exchange = false;
995
        // Plan local exchange for each operator.
996
0
        for (; idx < ops.size();) {
997
0
            if (ops[idx]->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
998
0
                RETURN_IF_ERROR(_add_local_exchange(
999
0
                        pip_idx, idx, ops[idx]->node_id(), _runtime_state->obj_pool(), pip,
1000
0
                        ops[idx]->required_data_distribution(_runtime_state.get()),
1001
0
                        &do_local_exchange, num_buckets, bucket_seq_to_instance_idx,
1002
0
                        shuffle_idx_to_instance_idx));
1003
0
            }
1004
0
            if (do_local_exchange) {
1005
                // If local exchange is needed for current operator, we will split this pipeline to
1006
                // two pipelines by local exchange sink/source. And then we need to process remaining
1007
                // operators in this pipeline so we set idx to 2 (0 is local exchange source and 1
1008
                // is current operator was already processed) and continue to plan local exchange.
1009
0
                idx = 2;
1010
0
                break;
1011
0
            }
1012
0
            idx++;
1013
0
        }
1014
0
    } while (do_local_exchange);
1015
0
    if (pip->sink()->required_data_distribution(_runtime_state.get()).need_local_exchange()) {
1016
0
        RETURN_IF_ERROR(_add_local_exchange(
1017
0
                pip_idx, idx, pip->sink()->node_id(), _runtime_state->obj_pool(), pip,
1018
0
                pip->sink()->required_data_distribution(_runtime_state.get()), &do_local_exchange,
1019
0
                num_buckets, bucket_seq_to_instance_idx, shuffle_idx_to_instance_idx));
1020
0
    }
1021
0
    return Status::OK();
1022
0
}
1023
1024
Status PipelineFragmentContext::_create_data_sink(ObjectPool* pool, const TDataSink& thrift_sink,
1025
                                                  const std::vector<TExpr>& output_exprs,
1026
                                                  const TPipelineFragmentParams& params,
1027
                                                  const RowDescriptor& row_desc,
1028
                                                  RuntimeState* state, DescriptorTbl& desc_tbl,
1029
0
                                                  PipelineId cur_pipeline_id) {
1030
0
    switch (thrift_sink.type) {
1031
0
    case TDataSinkType::DATA_STREAM_SINK: {
1032
0
        if (!thrift_sink.__isset.stream_sink) {
1033
0
            return Status::InternalError("Missing data stream sink.");
1034
0
        }
1035
0
        _sink = std::make_shared<ExchangeSinkOperatorX>(
1036
0
                state, row_desc, next_sink_operator_id(), thrift_sink.stream_sink,
1037
0
                params.destinations, _fragment_instance_ids);
1038
0
        break;
1039
0
    }
1040
0
    case TDataSinkType::RESULT_SINK: {
1041
0
        if (!thrift_sink.__isset.result_sink) {
1042
0
            return Status::InternalError("Missing data buffer sink.");
1043
0
        }
1044
1045
0
        _sink = std::make_shared<ResultSinkOperatorX>(next_sink_operator_id(), row_desc,
1046
0
                                                      output_exprs, thrift_sink.result_sink);
1047
0
        break;
1048
0
    }
1049
0
    case TDataSinkType::DICTIONARY_SINK: {
1050
0
        if (!thrift_sink.__isset.dictionary_sink) {
1051
0
            return Status::InternalError("Missing dict sink.");
1052
0
        }
1053
1054
0
        _sink = std::make_shared<DictSinkOperatorX>(next_sink_operator_id(), row_desc, output_exprs,
1055
0
                                                    thrift_sink.dictionary_sink);
1056
0
        break;
1057
0
    }
1058
0
    case TDataSinkType::GROUP_COMMIT_OLAP_TABLE_SINK:
1059
0
    case TDataSinkType::OLAP_TABLE_SINK: {
1060
0
        if (state->query_options().enable_memtable_on_sink_node &&
1061
0
            !_has_inverted_index_v1_or_partial_update(thrift_sink.olap_table_sink) &&
1062
0
            !config::is_cloud_mode()) {
1063
0
            _sink = std::make_shared<OlapTableSinkV2OperatorX>(pool, next_sink_operator_id(),
1064
0
                                                               row_desc, output_exprs);
1065
0
        } else {
1066
0
            _sink = std::make_shared<OlapTableSinkOperatorX>(pool, next_sink_operator_id(),
1067
0
                                                             row_desc, output_exprs);
1068
0
        }
1069
0
        break;
1070
0
    }
1071
0
    case TDataSinkType::GROUP_COMMIT_BLOCK_SINK: {
1072
0
        DCHECK(thrift_sink.__isset.olap_table_sink);
1073
0
        DCHECK(state->get_query_ctx() != nullptr);
1074
0
        state->get_query_ctx()->query_mem_tracker()->is_group_commit_load = true;
1075
0
        _sink = std::make_shared<GroupCommitBlockSinkOperatorX>(next_sink_operator_id(), row_desc,
1076
0
                                                                output_exprs);
1077
0
        break;
1078
0
    }
1079
0
    case TDataSinkType::HIVE_TABLE_SINK: {
1080
0
        if (!thrift_sink.__isset.hive_table_sink) {
1081
0
            return Status::InternalError("Missing hive table sink.");
1082
0
        }
1083
0
        _sink = std::make_shared<HiveTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1084
0
                                                         output_exprs);
1085
0
        break;
1086
0
    }
1087
0
    case TDataSinkType::ICEBERG_TABLE_SINK: {
1088
0
        if (!thrift_sink.__isset.iceberg_table_sink) {
1089
0
            return Status::InternalError("Missing iceberg table sink.");
1090
0
        }
1091
0
        if (thrift_sink.iceberg_table_sink.__isset.sort_info) {
1092
0
            _sink = std::make_shared<SpillIcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1093
0
                                                                     row_desc, output_exprs);
1094
0
        } else {
1095
0
            _sink = std::make_shared<IcebergTableSinkOperatorX>(pool, next_sink_operator_id(),
1096
0
                                                                row_desc, output_exprs);
1097
0
        }
1098
0
        break;
1099
0
    }
1100
0
    case TDataSinkType::MAXCOMPUTE_TABLE_SINK: {
1101
0
        if (!thrift_sink.__isset.max_compute_table_sink) {
1102
0
            return Status::InternalError("Missing max compute table sink.");
1103
0
        }
1104
0
        _sink = std::make_shared<MCTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1105
0
                                                       output_exprs);
1106
0
        break;
1107
0
    }
1108
0
    case TDataSinkType::JDBC_TABLE_SINK: {
1109
0
        if (!thrift_sink.__isset.jdbc_table_sink) {
1110
0
            return Status::InternalError("Missing data jdbc sink.");
1111
0
        }
1112
0
        if (config::enable_java_support) {
1113
0
            _sink = std::make_shared<JdbcTableSinkOperatorX>(row_desc, next_sink_operator_id(),
1114
0
                                                             output_exprs);
1115
0
        } else {
1116
0
            return Status::InternalError(
1117
0
                    "Jdbc table sink is not enabled, you can change be config "
1118
0
                    "enable_java_support to true and restart be.");
1119
0
        }
1120
0
        break;
1121
0
    }
1122
0
    case TDataSinkType::MEMORY_SCRATCH_SINK: {
1123
0
        if (!thrift_sink.__isset.memory_scratch_sink) {
1124
0
            return Status::InternalError("Missing data buffer sink.");
1125
0
        }
1126
1127
0
        _sink = std::make_shared<MemoryScratchSinkOperatorX>(row_desc, next_sink_operator_id(),
1128
0
                                                             output_exprs);
1129
0
        break;
1130
0
    }
1131
0
    case TDataSinkType::RESULT_FILE_SINK: {
1132
0
        if (!thrift_sink.__isset.result_file_sink) {
1133
0
            return Status::InternalError("Missing result file sink.");
1134
0
        }
1135
1136
        // Result file sink is not the top sink
1137
0
        if (params.__isset.destinations && !params.destinations.empty()) {
1138
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(
1139
0
                    next_sink_operator_id(), row_desc, thrift_sink.result_file_sink,
1140
0
                    params.destinations, output_exprs, desc_tbl);
1141
0
        } else {
1142
0
            _sink = std::make_shared<ResultFileSinkOperatorX>(next_sink_operator_id(), row_desc,
1143
0
                                                              output_exprs);
1144
0
        }
1145
0
        break;
1146
0
    }
1147
0
    case TDataSinkType::MULTI_CAST_DATA_STREAM_SINK: {
1148
0
        DCHECK(thrift_sink.__isset.multi_cast_stream_sink);
1149
0
        DCHECK_GT(thrift_sink.multi_cast_stream_sink.sinks.size(), 0);
1150
0
        auto sink_id = next_sink_operator_id();
1151
0
        const int multi_cast_node_id = sink_id;
1152
0
        auto sender_size = thrift_sink.multi_cast_stream_sink.sinks.size();
1153
        // one sink has multiple sources.
1154
0
        std::vector<int> sources;
1155
0
        for (int i = 0; i < sender_size; ++i) {
1156
0
            auto source_id = next_operator_id();
1157
0
            sources.push_back(source_id);
1158
0
        }
1159
1160
0
        _sink = std::make_shared<MultiCastDataStreamSinkOperatorX>(
1161
0
                sink_id, multi_cast_node_id, sources, pool, thrift_sink.multi_cast_stream_sink);
1162
0
        for (int i = 0; i < sender_size; ++i) {
1163
0
            auto new_pipeline = add_pipeline();
1164
            // use to exchange sink
1165
0
            RowDescriptor* exchange_row_desc = nullptr;
1166
0
            {
1167
0
                const auto& tmp_row_desc =
1168
0
                        !thrift_sink.multi_cast_stream_sink.sinks[i].output_exprs.empty()
1169
0
                                ? RowDescriptor(state->desc_tbl(),
1170
0
                                                {thrift_sink.multi_cast_stream_sink.sinks[i]
1171
0
                                                         .output_tuple_id})
1172
0
                                : row_desc;
1173
0
                exchange_row_desc = pool->add(new RowDescriptor(tmp_row_desc));
1174
0
            }
1175
0
            auto source_id = sources[i];
1176
0
            OperatorPtr source_op;
1177
            // 1. create and set the source operator of multi_cast_data_stream_source for new pipeline
1178
0
            source_op = std::make_shared<MultiCastDataStreamerSourceOperatorX>(
1179
0
                    /*node_id*/ source_id, /*consumer_id*/ i, pool,
1180
0
                    thrift_sink.multi_cast_stream_sink.sinks[i], row_desc,
1181
0
                    /*operator_id=*/source_id);
1182
0
            RETURN_IF_ERROR(new_pipeline->add_operator(
1183
0
                    source_op, params.__isset.parallel_instances ? params.parallel_instances : 0));
1184
            // 2. create and set sink operator of data stream sender for new pipeline
1185
1186
0
            DataSinkOperatorPtr sink_op;
1187
0
            sink_op = std::make_shared<ExchangeSinkOperatorX>(
1188
0
                    state, *exchange_row_desc, next_sink_operator_id(),
1189
0
                    thrift_sink.multi_cast_stream_sink.sinks[i],
1190
0
                    thrift_sink.multi_cast_stream_sink.destinations[i], _fragment_instance_ids);
1191
1192
0
            RETURN_IF_ERROR(new_pipeline->set_sink(sink_op));
1193
0
            {
1194
0
                TDataSink* t = pool->add(new TDataSink());
1195
0
                t->stream_sink = thrift_sink.multi_cast_stream_sink.sinks[i];
1196
0
                RETURN_IF_ERROR(sink_op->init(*t));
1197
0
            }
1198
1199
            // 3. set dependency dag
1200
0
            _dag[new_pipeline->id()].push_back(cur_pipeline_id);
1201
0
        }
1202
0
        if (sources.empty()) {
1203
0
            return Status::InternalError("size of sources must be greater than 0");
1204
0
        }
1205
0
        break;
1206
0
    }
1207
0
    case TDataSinkType::BLACKHOLE_SINK: {
1208
0
        if (!thrift_sink.__isset.blackhole_sink) {
1209
0
            return Status::InternalError("Missing blackhole sink.");
1210
0
        }
1211
1212
0
        _sink.reset(new BlackholeSinkOperatorX(next_sink_operator_id()));
1213
0
        break;
1214
0
    }
1215
0
    case TDataSinkType::TVF_TABLE_SINK: {
1216
0
        if (!thrift_sink.__isset.tvf_table_sink) {
1217
0
            return Status::InternalError("Missing TVF table sink.");
1218
0
        }
1219
0
        _sink = std::make_shared<TVFTableSinkOperatorX>(pool, next_sink_operator_id(), row_desc,
1220
0
                                                        output_exprs);
1221
0
        break;
1222
0
    }
1223
0
    default:
1224
0
        return Status::InternalError("Unsuported sink type in pipeline: {}", thrift_sink.type);
1225
0
    }
1226
0
    return Status::OK();
1227
0
}
1228
1229
// NOLINTBEGIN(readability-function-size)
1230
// NOLINTBEGIN(readability-function-cognitive-complexity)
1231
Status PipelineFragmentContext::_create_operator(ObjectPool* pool, const TPlanNode& tnode,
1232
                                                 const DescriptorTbl& descs, OperatorPtr& op,
1233
                                                 PipelinePtr& cur_pipe, int parent_idx,
1234
                                                 int child_idx,
1235
                                                 const bool followed_by_shuffled_operator,
1236
0
                                                 const bool require_bucket_distribution) {
1237
0
    std::vector<DataSinkOperatorPtr> sink_ops;
1238
0
    Defer defer = Defer([&]() {
1239
0
        if (op) {
1240
0
            op->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1241
0
        }
1242
0
        for (auto& s : sink_ops) {
1243
0
            s->update_operator(tnode, followed_by_shuffled_operator, require_bucket_distribution);
1244
0
        }
1245
0
    });
1246
    // We directly construct the operator from Thrift because the given array is in the order of preorder traversal.
1247
    // Therefore, here we need to use a stack-like structure.
1248
0
    _pipeline_parent_map.pop(cur_pipe, parent_idx, child_idx);
1249
0
    std::stringstream error_msg;
1250
0
    bool enable_query_cache = _params.fragment.__isset.query_cache_param;
1251
1252
0
    bool fe_with_old_version = false;
1253
0
    switch (tnode.node_type) {
1254
0
    case TPlanNodeType::OLAP_SCAN_NODE: {
1255
0
        op = std::make_shared<OlapScanOperatorX>(
1256
0
                pool, tnode, next_operator_id(), descs, _num_instances,
1257
0
                enable_query_cache ? _params.fragment.query_cache_param : TQueryCacheParam {});
1258
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1259
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1260
0
        break;
1261
0
    }
1262
0
    case TPlanNodeType::GROUP_COMMIT_SCAN_NODE: {
1263
0
        DCHECK(_query_ctx != nullptr);
1264
0
        _query_ctx->query_mem_tracker()->is_group_commit_load = true;
1265
0
        op = std::make_shared<GroupCommitOperatorX>(pool, tnode, next_operator_id(), descs,
1266
0
                                                    _num_instances);
1267
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1268
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1269
0
        break;
1270
0
    }
1271
0
    case TPlanNodeType::JDBC_SCAN_NODE: {
1272
0
        if (config::enable_java_support) {
1273
0
            op = std::make_shared<JDBCScanOperatorX>(pool, tnode, next_operator_id(), descs,
1274
0
                                                     _num_instances);
1275
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1276
0
        } else {
1277
0
            return Status::InternalError(
1278
0
                    "Jdbc scan node is disabled, you can change be config enable_java_support "
1279
0
                    "to true and restart be.");
1280
0
        }
1281
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1282
0
        break;
1283
0
    }
1284
0
    case TPlanNodeType::FILE_SCAN_NODE: {
1285
0
        op = std::make_shared<FileScanOperatorX>(pool, tnode, next_operator_id(), descs,
1286
0
                                                 _num_instances);
1287
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1288
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1289
0
        break;
1290
0
    }
1291
0
    case TPlanNodeType::ES_SCAN_NODE:
1292
0
    case TPlanNodeType::ES_HTTP_SCAN_NODE: {
1293
0
        op = std::make_shared<EsScanOperatorX>(pool, tnode, next_operator_id(), descs,
1294
0
                                               _num_instances);
1295
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1296
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1297
0
        break;
1298
0
    }
1299
0
    case TPlanNodeType::EXCHANGE_NODE: {
1300
0
        int num_senders = _params.per_exch_num_senders.contains(tnode.node_id)
1301
0
                                  ? _params.per_exch_num_senders.find(tnode.node_id)->second
1302
0
                                  : 0;
1303
0
        DCHECK_GT(num_senders, 0);
1304
0
        op = std::make_shared<ExchangeSourceOperatorX>(pool, tnode, next_operator_id(), descs,
1305
0
                                                       num_senders);
1306
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1307
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1308
0
        break;
1309
0
    }
1310
0
    case TPlanNodeType::AGGREGATION_NODE: {
1311
0
        if (tnode.agg_node.grouping_exprs.empty() &&
1312
0
            descs.get_tuple_descriptor(tnode.agg_node.output_tuple_id)->slots().empty()) {
1313
0
            return Status::InternalError("Illegal aggregate node " + std::to_string(tnode.node_id) +
1314
0
                                         ": group by and output is empty");
1315
0
        }
1316
0
        bool need_create_cache_op =
1317
0
                enable_query_cache && tnode.node_id == _params.fragment.query_cache_param.node_id;
1318
0
        auto create_query_cache_operator = [&](PipelinePtr& new_pipe) {
1319
0
            auto cache_node_id = _params.local_params[0].per_node_scan_ranges.begin()->first;
1320
0
            auto cache_source_id = next_operator_id();
1321
0
            op = std::make_shared<CacheSourceOperatorX>(pool, cache_node_id, cache_source_id,
1322
0
                                                        _params.fragment.query_cache_param);
1323
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1324
1325
0
            const auto downstream_pipeline_id = cur_pipe->id();
1326
0
            if (!_dag.contains(downstream_pipeline_id)) {
1327
0
                _dag.insert({downstream_pipeline_id, {}});
1328
0
            }
1329
0
            new_pipe = add_pipeline(cur_pipe);
1330
0
            _dag[downstream_pipeline_id].push_back(new_pipe->id());
1331
1332
0
            DataSinkOperatorPtr cache_sink(new CacheSinkOperatorX(
1333
0
                    next_sink_operator_id(), cache_source_id, op->operator_id()));
1334
0
            RETURN_IF_ERROR(new_pipe->set_sink(cache_sink));
1335
0
            return Status::OK();
1336
0
        };
1337
0
        const bool group_by_limit_opt =
1338
0
                tnode.agg_node.__isset.agg_sort_info_by_group_key && tnode.limit > 0;
1339
1340
        /// PartitionedAggSourceOperatorX does not support "group by limit opt(#29641)" yet.
1341
        /// If `group_by_limit_opt` is true, then it might not need to spill at all.
1342
0
        const bool enable_spill = _runtime_state->enable_spill() &&
1343
0
                                  !tnode.agg_node.grouping_exprs.empty() && !group_by_limit_opt;
1344
0
        const bool is_streaming_agg = tnode.agg_node.__isset.use_streaming_preaggregation &&
1345
0
                                      tnode.agg_node.use_streaming_preaggregation &&
1346
0
                                      !tnode.agg_node.grouping_exprs.empty();
1347
        // TODO: distinct streaming agg does not support spill.
1348
0
        const bool can_use_distinct_streaming_agg =
1349
0
                (!enable_spill || is_streaming_agg) && tnode.agg_node.aggregate_functions.empty() &&
1350
0
                !tnode.agg_node.__isset.agg_sort_info_by_group_key &&
1351
0
                _params.query_options.__isset.enable_distinct_streaming_aggregation &&
1352
0
                _params.query_options.enable_distinct_streaming_aggregation;
1353
1354
0
        if (can_use_distinct_streaming_agg) {
1355
0
            if (need_create_cache_op) {
1356
0
                PipelinePtr new_pipe;
1357
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1358
1359
0
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1360
0
                                                                     tnode, descs);
1361
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1362
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1363
0
                cur_pipe = new_pipe;
1364
0
            } else {
1365
0
                op = std::make_shared<DistinctStreamingAggOperatorX>(pool, next_operator_id(),
1366
0
                                                                     tnode, descs);
1367
0
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1368
0
            }
1369
0
        } else if (is_streaming_agg) {
1370
0
            if (need_create_cache_op) {
1371
0
                PipelinePtr new_pipe;
1372
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1373
1374
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1375
0
                                                             descs);
1376
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1377
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1378
0
                cur_pipe = new_pipe;
1379
0
            } else {
1380
0
                op = std::make_shared<StreamingAggOperatorX>(pool, next_operator_id(), tnode,
1381
0
                                                             descs);
1382
0
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1383
0
            }
1384
0
        } else {
1385
            // create new pipeline to add query cache operator
1386
0
            PipelinePtr new_pipe;
1387
0
            if (need_create_cache_op) {
1388
0
                RETURN_IF_ERROR(create_query_cache_operator(new_pipe));
1389
0
            }
1390
1391
0
            if (enable_spill) {
1392
0
                op = std::make_shared<PartitionedAggSourceOperatorX>(pool, tnode,
1393
0
                                                                     next_operator_id(), descs);
1394
0
            } else {
1395
0
                op = std::make_shared<AggSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1396
0
            }
1397
0
            if (need_create_cache_op) {
1398
0
                RETURN_IF_ERROR(cur_pipe->operators().front()->set_child(op));
1399
0
                RETURN_IF_ERROR(new_pipe->add_operator(op, _parallel_instances));
1400
0
                cur_pipe = new_pipe;
1401
0
            } else {
1402
0
                RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1403
0
            }
1404
1405
0
            const auto downstream_pipeline_id = cur_pipe->id();
1406
0
            if (!_dag.contains(downstream_pipeline_id)) {
1407
0
                _dag.insert({downstream_pipeline_id, {}});
1408
0
            }
1409
0
            cur_pipe = add_pipeline(cur_pipe);
1410
0
            _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1411
1412
0
            if (enable_spill) {
1413
0
                sink_ops.push_back(std::make_shared<PartitionedAggSinkOperatorX>(
1414
0
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1415
0
            } else {
1416
0
                sink_ops.push_back(std::make_shared<AggSinkOperatorX>(
1417
0
                        pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1418
0
            }
1419
0
            RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1420
0
            RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1421
0
        }
1422
0
        break;
1423
0
    }
1424
0
    case TPlanNodeType::HASH_JOIN_NODE: {
1425
0
        const auto is_broadcast_join = tnode.hash_join_node.__isset.is_broadcast_join &&
1426
0
                                       tnode.hash_join_node.is_broadcast_join;
1427
0
        const auto enable_spill = _runtime_state->enable_spill();
1428
0
        if (enable_spill && !is_broadcast_join) {
1429
0
            auto tnode_ = tnode;
1430
0
            tnode_.runtime_filters.clear();
1431
0
            auto inner_probe_operator =
1432
0
                    std::make_shared<HashJoinProbeOperatorX>(pool, tnode_, 0, descs);
1433
1434
            // probe side inner sink operator is used to build hash table on probe side when data is spilled.
1435
            // So here use `tnode_` which has no runtime filters.
1436
0
            auto probe_side_inner_sink_operator =
1437
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode_, descs);
1438
1439
0
            RETURN_IF_ERROR(inner_probe_operator->init(tnode_, _runtime_state.get()));
1440
0
            RETURN_IF_ERROR(probe_side_inner_sink_operator->init(tnode_, _runtime_state.get()));
1441
1442
0
            auto probe_operator = std::make_shared<PartitionedHashJoinProbeOperatorX>(
1443
0
                    pool, tnode_, next_operator_id(), descs);
1444
0
            probe_operator->set_inner_operators(probe_side_inner_sink_operator,
1445
0
                                                inner_probe_operator);
1446
0
            op = std::move(probe_operator);
1447
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1448
1449
0
            const auto downstream_pipeline_id = cur_pipe->id();
1450
0
            if (!_dag.contains(downstream_pipeline_id)) {
1451
0
                _dag.insert({downstream_pipeline_id, {}});
1452
0
            }
1453
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1454
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1455
1456
0
            auto inner_sink_operator =
1457
0
                    std::make_shared<HashJoinBuildSinkOperatorX>(pool, 0, 0, tnode, descs);
1458
0
            auto sink_operator = std::make_shared<PartitionedHashJoinSinkOperatorX>(
1459
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode_, descs);
1460
0
            RETURN_IF_ERROR(inner_sink_operator->init(tnode, _runtime_state.get()));
1461
1462
0
            sink_operator->set_inner_operators(inner_sink_operator, inner_probe_operator);
1463
0
            sink_ops.push_back(std::move(sink_operator));
1464
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1465
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode_, _runtime_state.get()));
1466
1467
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1468
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1469
0
        } else {
1470
0
            op = std::make_shared<HashJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1471
0
            RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1472
1473
0
            const auto downstream_pipeline_id = cur_pipe->id();
1474
0
            if (!_dag.contains(downstream_pipeline_id)) {
1475
0
                _dag.insert({downstream_pipeline_id, {}});
1476
0
            }
1477
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1478
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1479
1480
0
            sink_ops.push_back(std::make_shared<HashJoinBuildSinkOperatorX>(
1481
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1482
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1483
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1484
1485
0
            _pipeline_parent_map.push(op->node_id(), cur_pipe);
1486
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1487
0
        }
1488
0
        if (is_broadcast_join && _runtime_state->enable_share_hash_table_for_broadcast_join()) {
1489
0
            std::shared_ptr<HashJoinSharedState> shared_state =
1490
0
                    HashJoinSharedState::create_shared(_num_instances);
1491
0
            for (int i = 0; i < _num_instances; i++) {
1492
0
                auto sink_dep = std::make_shared<Dependency>(op->operator_id(), op->node_id(),
1493
0
                                                             "HASH_JOIN_BUILD_DEPENDENCY");
1494
0
                sink_dep->set_shared_state(shared_state.get());
1495
0
                shared_state->sink_deps.push_back(sink_dep);
1496
0
            }
1497
0
            shared_state->create_source_dependencies(_num_instances, op->operator_id(),
1498
0
                                                     op->node_id(), "HASH_JOIN_PROBE");
1499
0
            _op_id_to_shared_state.insert(
1500
0
                    {op->operator_id(), {shared_state, shared_state->sink_deps}});
1501
0
        }
1502
0
        break;
1503
0
    }
1504
0
    case TPlanNodeType::CROSS_JOIN_NODE: {
1505
0
        op = std::make_shared<NestedLoopJoinProbeOperatorX>(pool, tnode, next_operator_id(), descs);
1506
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1507
1508
0
        const auto downstream_pipeline_id = cur_pipe->id();
1509
0
        if (!_dag.contains(downstream_pipeline_id)) {
1510
0
            _dag.insert({downstream_pipeline_id, {}});
1511
0
        }
1512
0
        PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1513
0
        _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1514
1515
0
        sink_ops.push_back(std::make_shared<NestedLoopJoinBuildSinkOperatorX>(
1516
0
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1517
0
        RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1518
0
        RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1519
0
        _pipeline_parent_map.push(op->node_id(), cur_pipe);
1520
0
        _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1521
0
        break;
1522
0
    }
1523
0
    case TPlanNodeType::UNION_NODE: {
1524
0
        int child_count = tnode.num_children;
1525
0
        op = std::make_shared<UnionSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1526
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1527
1528
0
        const auto downstream_pipeline_id = cur_pipe->id();
1529
0
        if (!_dag.contains(downstream_pipeline_id)) {
1530
0
            _dag.insert({downstream_pipeline_id, {}});
1531
0
        }
1532
0
        for (int i = 0; i < child_count; i++) {
1533
0
            PipelinePtr build_side_pipe = add_pipeline(cur_pipe);
1534
0
            _dag[downstream_pipeline_id].push_back(build_side_pipe->id());
1535
0
            sink_ops.push_back(std::make_shared<UnionSinkOperatorX>(
1536
0
                    i, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1537
0
            RETURN_IF_ERROR(build_side_pipe->set_sink(sink_ops.back()));
1538
0
            RETURN_IF_ERROR(build_side_pipe->sink()->init(tnode, _runtime_state.get()));
1539
            // preset children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1540
0
            _pipeline_parent_map.push(op->node_id(), build_side_pipe);
1541
0
        }
1542
0
        break;
1543
0
    }
1544
0
    case TPlanNodeType::SORT_NODE: {
1545
0
        const auto should_spill = _runtime_state->enable_spill() &&
1546
0
                                  tnode.sort_node.algorithm == TSortAlgorithm::FULL_SORT;
1547
0
        const bool use_local_merge =
1548
0
                tnode.sort_node.__isset.use_local_merge && tnode.sort_node.use_local_merge;
1549
0
        if (should_spill) {
1550
0
            op = std::make_shared<SpillSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1551
0
        } else if (use_local_merge) {
1552
0
            op = std::make_shared<LocalMergeSortSourceOperatorX>(pool, tnode, next_operator_id(),
1553
0
                                                                 descs);
1554
0
        } else {
1555
0
            op = std::make_shared<SortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1556
0
        }
1557
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1558
1559
0
        const auto downstream_pipeline_id = cur_pipe->id();
1560
0
        if (!_dag.contains(downstream_pipeline_id)) {
1561
0
            _dag.insert({downstream_pipeline_id, {}});
1562
0
        }
1563
0
        cur_pipe = add_pipeline(cur_pipe);
1564
0
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1565
1566
0
        if (should_spill) {
1567
0
            sink_ops.push_back(std::make_shared<SpillSortSinkOperatorX>(
1568
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1569
0
        } else {
1570
0
            sink_ops.push_back(std::make_shared<SortSinkOperatorX>(
1571
0
                    pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1572
0
        }
1573
0
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1574
0
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1575
0
        break;
1576
0
    }
1577
0
    case TPlanNodeType::PARTITION_SORT_NODE: {
1578
0
        op = std::make_shared<PartitionSortSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1579
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1580
1581
0
        const auto downstream_pipeline_id = cur_pipe->id();
1582
0
        if (!_dag.contains(downstream_pipeline_id)) {
1583
0
            _dag.insert({downstream_pipeline_id, {}});
1584
0
        }
1585
0
        cur_pipe = add_pipeline(cur_pipe);
1586
0
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1587
1588
0
        sink_ops.push_back(std::make_shared<PartitionSortSinkOperatorX>(
1589
0
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1590
0
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1591
0
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1592
0
        break;
1593
0
    }
1594
0
    case TPlanNodeType::ANALYTIC_EVAL_NODE: {
1595
0
        op = std::make_shared<AnalyticSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1596
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1597
1598
0
        const auto downstream_pipeline_id = cur_pipe->id();
1599
0
        if (!_dag.contains(downstream_pipeline_id)) {
1600
0
            _dag.insert({downstream_pipeline_id, {}});
1601
0
        }
1602
0
        cur_pipe = add_pipeline(cur_pipe);
1603
0
        _dag[downstream_pipeline_id].push_back(cur_pipe->id());
1604
1605
0
        sink_ops.push_back(std::make_shared<AnalyticSinkOperatorX>(
1606
0
                pool, next_sink_operator_id(), op->operator_id(), tnode, descs));
1607
0
        RETURN_IF_ERROR(cur_pipe->set_sink(sink_ops.back()));
1608
0
        RETURN_IF_ERROR(cur_pipe->sink()->init(tnode, _runtime_state.get()));
1609
0
        break;
1610
0
    }
1611
0
    case TPlanNodeType::MATERIALIZATION_NODE: {
1612
0
        op = std::make_shared<MaterializationOperator>(pool, tnode, next_operator_id(), descs);
1613
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1614
0
        break;
1615
0
    }
1616
0
    case TPlanNodeType::INTERSECT_NODE: {
1617
0
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<true>(pool, tnode, descs, op,
1618
0
                                                                      cur_pipe, sink_ops));
1619
0
        break;
1620
0
    }
1621
0
    case TPlanNodeType::EXCEPT_NODE: {
1622
0
        RETURN_IF_ERROR(_build_operators_for_set_operation_node<false>(pool, tnode, descs, op,
1623
0
                                                                       cur_pipe, sink_ops));
1624
0
        break;
1625
0
    }
1626
0
    case TPlanNodeType::REPEAT_NODE: {
1627
0
        op = std::make_shared<RepeatOperatorX>(pool, tnode, next_operator_id(), descs);
1628
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1629
0
        break;
1630
0
    }
1631
0
    case TPlanNodeType::TABLE_FUNCTION_NODE: {
1632
0
        op = std::make_shared<TableFunctionOperatorX>(pool, tnode, next_operator_id(), descs);
1633
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1634
0
        break;
1635
0
    }
1636
0
    case TPlanNodeType::ASSERT_NUM_ROWS_NODE: {
1637
0
        op = std::make_shared<AssertNumRowsOperatorX>(pool, tnode, next_operator_id(), descs);
1638
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1639
0
        break;
1640
0
    }
1641
0
    case TPlanNodeType::EMPTY_SET_NODE: {
1642
0
        op = std::make_shared<EmptySetSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1643
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1644
0
        break;
1645
0
    }
1646
0
    case TPlanNodeType::DATA_GEN_SCAN_NODE: {
1647
0
        op = std::make_shared<DataGenSourceOperatorX>(pool, tnode, next_operator_id(), descs);
1648
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1649
0
        fe_with_old_version = !tnode.__isset.is_serial_operator;
1650
0
        break;
1651
0
    }
1652
0
    case TPlanNodeType::SCHEMA_SCAN_NODE: {
1653
0
        op = std::make_shared<SchemaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1654
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1655
0
        break;
1656
0
    }
1657
0
    case TPlanNodeType::META_SCAN_NODE: {
1658
0
        op = std::make_shared<MetaScanOperatorX>(pool, tnode, next_operator_id(), descs);
1659
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1660
0
        break;
1661
0
    }
1662
0
    case TPlanNodeType::SELECT_NODE: {
1663
0
        op = std::make_shared<SelectOperatorX>(pool, tnode, next_operator_id(), descs);
1664
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1665
0
        break;
1666
0
    }
1667
0
    case TPlanNodeType::REC_CTE_NODE: {
1668
0
        op = std::make_shared<RecCTESourceOperatorX>(pool, tnode, next_operator_id(), descs);
1669
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1670
1671
0
        const auto downstream_pipeline_id = cur_pipe->id();
1672
0
        if (!_dag.contains(downstream_pipeline_id)) {
1673
0
            _dag.insert({downstream_pipeline_id, {}});
1674
0
        }
1675
1676
0
        PipelinePtr anchor_side_pipe = add_pipeline(cur_pipe);
1677
0
        _dag[downstream_pipeline_id].push_back(anchor_side_pipe->id());
1678
1679
0
        DataSinkOperatorPtr anchor_sink;
1680
0
        anchor_sink = std::make_shared<RecCTEAnchorSinkOperatorX>(next_sink_operator_id(),
1681
0
                                                                  op->operator_id(), tnode, descs);
1682
0
        RETURN_IF_ERROR(anchor_side_pipe->set_sink(anchor_sink));
1683
0
        RETURN_IF_ERROR(anchor_side_pipe->sink()->init(tnode, _runtime_state.get()));
1684
0
        _pipeline_parent_map.push(op->node_id(), anchor_side_pipe);
1685
1686
0
        PipelinePtr rec_side_pipe = add_pipeline(cur_pipe);
1687
0
        _dag[downstream_pipeline_id].push_back(rec_side_pipe->id());
1688
1689
0
        DataSinkOperatorPtr rec_sink;
1690
0
        rec_sink = std::make_shared<RecCTESinkOperatorX>(next_sink_operator_id(), op->operator_id(),
1691
0
                                                         tnode, descs);
1692
0
        RETURN_IF_ERROR(rec_side_pipe->set_sink(rec_sink));
1693
0
        RETURN_IF_ERROR(rec_side_pipe->sink()->init(tnode, _runtime_state.get()));
1694
0
        _pipeline_parent_map.push(op->node_id(), rec_side_pipe);
1695
1696
0
        break;
1697
0
    }
1698
0
    case TPlanNodeType::REC_CTE_SCAN_NODE: {
1699
0
        op = std::make_shared<RecCTEScanOperatorX>(pool, tnode, next_operator_id(), descs);
1700
0
        RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1701
0
        break;
1702
0
    }
1703
0
    default:
1704
0
        return Status::InternalError("Unsupported exec type in pipeline: {}",
1705
0
                                     print_plan_node_type(tnode.node_type));
1706
0
    }
1707
0
    if (_params.__isset.parallel_instances && fe_with_old_version) {
1708
0
        cur_pipe->set_num_tasks(_params.parallel_instances);
1709
0
        op->set_serial_operator();
1710
0
    }
1711
1712
0
    return Status::OK();
1713
0
}
1714
// NOLINTEND(readability-function-cognitive-complexity)
1715
// NOLINTEND(readability-function-size)
1716
1717
template <bool is_intersect>
1718
Status PipelineFragmentContext::_build_operators_for_set_operation_node(
1719
        ObjectPool* pool, const TPlanNode& tnode, const DescriptorTbl& descs, OperatorPtr& op,
1720
0
        PipelinePtr& cur_pipe, std::vector<DataSinkOperatorPtr>& sink_ops) {
1721
0
    op.reset(new SetSourceOperatorX<is_intersect>(pool, tnode, next_operator_id(), descs));
1722
0
    RETURN_IF_ERROR(cur_pipe->add_operator(op, _parallel_instances));
1723
1724
0
    const auto downstream_pipeline_id = cur_pipe->id();
1725
0
    if (!_dag.contains(downstream_pipeline_id)) {
1726
0
        _dag.insert({downstream_pipeline_id, {}});
1727
0
    }
1728
1729
0
    for (int child_id = 0; child_id < tnode.num_children; child_id++) {
1730
0
        PipelinePtr probe_side_pipe = add_pipeline(cur_pipe);
1731
0
        _dag[downstream_pipeline_id].push_back(probe_side_pipe->id());
1732
1733
0
        if (child_id == 0) {
1734
0
            sink_ops.push_back(std::make_shared<SetSinkOperatorX<is_intersect>>(
1735
0
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1736
0
        } else {
1737
0
            sink_ops.push_back(std::make_shared<SetProbeSinkOperatorX<is_intersect>>(
1738
0
                    child_id, next_sink_operator_id(), op->operator_id(), pool, tnode, descs));
1739
0
        }
1740
0
        RETURN_IF_ERROR(probe_side_pipe->set_sink(sink_ops.back()));
1741
0
        RETURN_IF_ERROR(probe_side_pipe->sink()->init(tnode, _runtime_state.get()));
1742
        // prepare children pipelines. if any pipeline found this as its father, will use the prepared pipeline to build.
1743
0
        _pipeline_parent_map.push(op->node_id(), probe_side_pipe);
1744
0
    }
1745
1746
0
    return Status::OK();
1747
0
}
Unexecuted instantiation: _ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb1EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
Unexecuted instantiation: _ZN5doris23PipelineFragmentContext39_build_operators_for_set_operation_nodeILb0EEENS_6StatusEPNS_10ObjectPoolERKNS_9TPlanNodeERKNS_13DescriptorTblERSt10shared_ptrINS_13OperatorXBaseEERSB_INS_8PipelineEERSt6vectorISB_INS_21DataSinkOperatorXBaseEESaISK_EE
1748
1749
0
Status PipelineFragmentContext::submit() {
1750
0
    if (_submitted) {
1751
0
        return Status::InternalError("submitted");
1752
0
    }
1753
0
    _submitted = true;
1754
1755
0
    int submit_tasks = 0;
1756
0
    Status st;
1757
0
    auto* scheduler = _query_ctx->get_pipe_exec_scheduler();
1758
0
    for (auto& task : _tasks) {
1759
0
        for (auto& t : task) {
1760
0
            st = scheduler->submit(t.first);
1761
0
            DBUG_EXECUTE_IF("PipelineFragmentContext.submit.failed",
1762
0
                            { st = Status::Aborted("PipelineFragmentContext.submit.failed"); });
1763
0
            if (!st) {
1764
0
                cancel(Status::InternalError("submit context to executor fail"));
1765
0
                std::lock_guard<std::mutex> l(_task_mutex);
1766
0
                _total_tasks = submit_tasks;
1767
0
                break;
1768
0
            }
1769
0
            submit_tasks++;
1770
0
        }
1771
0
    }
1772
0
    if (!st.ok()) {
1773
0
        std::lock_guard<std::mutex> l(_task_mutex);
1774
0
        if (_closed_tasks >= _total_tasks) {
1775
0
            _close_fragment_instance();
1776
0
        }
1777
0
        return Status::InternalError("Submit pipeline failed. err = {}, BE: {}", st.to_string(),
1778
0
                                     BackendOptions::get_localhost());
1779
0
    } else {
1780
0
        return st;
1781
0
    }
1782
0
}
1783
1784
0
void PipelineFragmentContext::print_profile(const std::string& extra_info) {
1785
0
    if (_runtime_state->enable_profile()) {
1786
0
        std::stringstream ss;
1787
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1788
0
            runtime_profile_ptr->pretty_print(&ss);
1789
0
        }
1790
1791
0
        if (_runtime_state->load_channel_profile()) {
1792
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1793
0
        }
1794
1795
0
        auto profile_str =
1796
0
                fmt::format("Query {} fragment {} {}, profile, {}", print_id(this->_query_id),
1797
0
                            this->_fragment_id, extra_info, ss.str());
1798
0
        LOG_LONG_STRING(INFO, profile_str);
1799
0
    }
1800
0
}
1801
// If all pipeline tasks binded to the fragment instance are finished, then we could
1802
// close the fragment instance.
1803
0
void PipelineFragmentContext::_close_fragment_instance() {
1804
0
    if (_is_fragment_instance_closed) {
1805
0
        return;
1806
0
    }
1807
0
    Defer defer_op {[&]() {
1808
0
        _is_fragment_instance_closed = true;
1809
0
        _notify_cv.notify_all();
1810
0
    }};
1811
0
    _fragment_level_profile->total_time_counter()->update(_fragment_watcher.elapsed_time());
1812
0
    if (!_need_notify_close) {
1813
0
        auto st = send_report(true);
1814
0
        if (!st) {
1815
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
1816
0
                                        print_id(_query_id), _fragment_id, st.to_string());
1817
0
        }
1818
0
    }
1819
    // Print profile content in info log is a tempoeray solution for stream load and external_connector.
1820
    // Since stream load does not have someting like coordinator on FE, so
1821
    // backend can not report profile to FE, ant its profile can not be shown
1822
    // in the same way with other query. So we print the profile content to info log.
1823
1824
0
    if (_runtime_state->enable_profile() &&
1825
0
        (_query_ctx->get_query_source() == QuerySource::STREAM_LOAD ||
1826
0
         _query_ctx->get_query_source() == QuerySource::EXTERNAL_CONNECTOR ||
1827
0
         _query_ctx->get_query_source() == QuerySource::GROUP_COMMIT_LOAD)) {
1828
0
        std::stringstream ss;
1829
        // Compute the _local_time_percent before pretty_print the runtime_profile
1830
        // Before add this operation, the print out like that:
1831
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 00.00%)
1832
        // After add the operation, the print out like that:
1833
        // UNION_NODE (id=0):(Active: 56.720us, non-child: 82.53%)
1834
        // We can easily know the exec node execute time without child time consumed.
1835
0
        for (auto runtime_profile_ptr : _runtime_state->pipeline_id_to_profile()) {
1836
0
            runtime_profile_ptr->pretty_print(&ss);
1837
0
        }
1838
1839
0
        if (_runtime_state->load_channel_profile()) {
1840
0
            _runtime_state->load_channel_profile()->pretty_print(&ss);
1841
0
        }
1842
1843
0
        LOG_INFO("Query {} fragment {} profile:\n {}", print_id(_query_id), _fragment_id, ss.str());
1844
0
    }
1845
1846
0
    if (_query_ctx->enable_profile()) {
1847
0
        _query_ctx->add_fragment_profile(_fragment_id, collect_realtime_profile(),
1848
0
                                         collect_realtime_load_channel_profile());
1849
0
    }
1850
1851
0
    if (!_need_notify_close) {
1852
        // all submitted tasks done
1853
0
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
1854
0
    }
1855
0
}
1856
1857
0
void PipelineFragmentContext::decrement_running_task(PipelineId pipeline_id) {
1858
    // If all tasks of this pipeline has been closed, upstream tasks is never needed, and we just make those runnable here
1859
0
    DCHECK(_pip_id_to_pipeline.contains(pipeline_id));
1860
0
    if (_pip_id_to_pipeline[pipeline_id]->close_task()) {
1861
0
        if (_dag.contains(pipeline_id)) {
1862
0
            for (auto dep : _dag[pipeline_id]) {
1863
0
                _pip_id_to_pipeline[dep]->make_all_runnable(pipeline_id);
1864
0
            }
1865
0
        }
1866
0
    }
1867
0
    std::lock_guard<std::mutex> l(_task_mutex);
1868
0
    ++_closed_tasks;
1869
0
    if (_closed_tasks >= _total_tasks) {
1870
0
        _close_fragment_instance();
1871
0
    }
1872
0
}
1873
1874
0
std::string PipelineFragmentContext::get_load_error_url() {
1875
0
    if (const auto& str = _runtime_state->get_error_log_file_path(); !str.empty()) {
1876
0
        return to_load_error_http_path(str);
1877
0
    }
1878
0
    for (auto& tasks : _tasks) {
1879
0
        for (auto& task : tasks) {
1880
0
            if (const auto& str = task.second->get_error_log_file_path(); !str.empty()) {
1881
0
                return to_load_error_http_path(str);
1882
0
            }
1883
0
        }
1884
0
    }
1885
0
    return "";
1886
0
}
1887
1888
0
std::string PipelineFragmentContext::get_first_error_msg() {
1889
0
    if (const auto& str = _runtime_state->get_first_error_msg(); !str.empty()) {
1890
0
        return str;
1891
0
    }
1892
0
    for (auto& tasks : _tasks) {
1893
0
        for (auto& task : tasks) {
1894
0
            if (const auto& str = task.second->get_first_error_msg(); !str.empty()) {
1895
0
                return str;
1896
0
            }
1897
0
        }
1898
0
    }
1899
0
    return "";
1900
0
}
1901
1902
0
Status PipelineFragmentContext::send_report(bool done) {
1903
0
    Status exec_status = _query_ctx->exec_status();
1904
    // If plan is done successfully, but _is_report_success is false,
1905
    // no need to send report.
1906
    // Load will set _is_report_success to true because load wants to know
1907
    // the process.
1908
0
    if (!_is_report_success && done && exec_status.ok()) {
1909
0
        return Status::NeedSendAgain("");
1910
0
    }
1911
1912
    // If both _is_report_success and _is_report_on_cancel are false,
1913
    // which means no matter query is success or failed, no report is needed.
1914
    // This may happen when the query limit reached and
1915
    // a internal cancellation being processed
1916
    // When limit is reached the fragment is also cancelled, but _is_report_on_cancel will
1917
    // be set to false, to avoid sending fault report to FE.
1918
0
    if (!_is_report_success && !_is_report_on_cancel) {
1919
0
        return Status::NeedSendAgain("");
1920
0
    }
1921
1922
0
    std::vector<RuntimeState*> runtime_states;
1923
1924
0
    for (auto& tasks : _tasks) {
1925
0
        for (auto& task : tasks) {
1926
0
            runtime_states.push_back(task.second.get());
1927
0
        }
1928
0
    }
1929
1930
0
    std::string load_eror_url = _query_ctx->get_load_error_url().empty()
1931
0
                                        ? get_load_error_url()
1932
0
                                        : _query_ctx->get_load_error_url();
1933
0
    std::string first_error_msg = _query_ctx->get_first_error_msg().empty()
1934
0
                                          ? get_first_error_msg()
1935
0
                                          : _query_ctx->get_first_error_msg();
1936
1937
0
    ReportStatusRequest req {.status = exec_status,
1938
0
                             .runtime_states = runtime_states,
1939
0
                             .done = done || !exec_status.ok(),
1940
0
                             .coord_addr = _query_ctx->coord_addr,
1941
0
                             .query_id = _query_id,
1942
0
                             .fragment_id = _fragment_id,
1943
0
                             .fragment_instance_id = TUniqueId(),
1944
0
                             .backend_num = -1,
1945
0
                             .runtime_state = _runtime_state.get(),
1946
0
                             .load_error_url = load_eror_url,
1947
0
                             .first_error_msg = first_error_msg,
1948
0
                             .cancel_fn = [this](const Status& reason) { cancel(reason); }};
1949
1950
0
    return _report_status_cb(
1951
0
            req, std::dynamic_pointer_cast<PipelineFragmentContext>(shared_from_this()));
1952
0
}
1953
1954
0
size_t PipelineFragmentContext::get_revocable_size(bool* has_running_task) const {
1955
0
    size_t res = 0;
1956
    // _tasks will be cleared during ~PipelineFragmentContext, so that it's safe
1957
    // here to traverse the vector.
1958
0
    for (const auto& task_instances : _tasks) {
1959
0
        for (const auto& task : task_instances) {
1960
0
            if (task.first->is_running()) {
1961
0
                LOG_EVERY_N(INFO, 50) << "Query: " << print_id(_query_id)
1962
0
                                      << " is running, task: " << (void*)task.first.get()
1963
0
                                      << ", is_running: " << task.first->is_running();
1964
0
                *has_running_task = true;
1965
0
                return 0;
1966
0
            }
1967
1968
0
            size_t revocable_size = task.first->get_revocable_size();
1969
0
            if (revocable_size >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
1970
0
                res += revocable_size;
1971
0
            }
1972
0
        }
1973
0
    }
1974
0
    return res;
1975
0
}
1976
1977
0
std::vector<PipelineTask*> PipelineFragmentContext::get_revocable_tasks() const {
1978
0
    std::vector<PipelineTask*> revocable_tasks;
1979
0
    for (const auto& task_instances : _tasks) {
1980
0
        for (const auto& task : task_instances) {
1981
0
            size_t revocable_size_ = task.first->get_revocable_size();
1982
1983
0
            if (revocable_size_ >= SpillFile::MIN_SPILL_WRITE_BATCH_MEM) {
1984
0
                revocable_tasks.emplace_back(task.first.get());
1985
0
            }
1986
0
        }
1987
0
    }
1988
0
    return revocable_tasks;
1989
0
}
1990
1991
0
std::string PipelineFragmentContext::debug_string() {
1992
0
    std::lock_guard<std::mutex> l(_task_mutex);
1993
0
    fmt::memory_buffer debug_string_buffer;
1994
0
    fmt::format_to(debug_string_buffer,
1995
0
                   "PipelineFragmentContext Info: _closed_tasks={}, _total_tasks={}, "
1996
0
                   "need_notify_close={}, has_task_execution_ctx_ref_count={}\n",
1997
0
                   _closed_tasks, _total_tasks, _need_notify_close,
1998
0
                   _has_task_execution_ctx_ref_count);
1999
0
    for (size_t j = 0; j < _tasks.size(); j++) {
2000
0
        fmt::format_to(debug_string_buffer, "Tasks in instance {}:\n", j);
2001
0
        for (size_t i = 0; i < _tasks[j].size(); i++) {
2002
0
            fmt::format_to(debug_string_buffer, "Task {}: {}\n", i,
2003
0
                           _tasks[j][i].first->debug_string());
2004
0
        }
2005
0
    }
2006
2007
0
    return fmt::to_string(debug_string_buffer);
2008
0
}
2009
2010
std::vector<std::shared_ptr<TRuntimeProfileTree>>
2011
0
PipelineFragmentContext::collect_realtime_profile() const {
2012
0
    std::vector<std::shared_ptr<TRuntimeProfileTree>> res;
2013
2014
    // we do not have mutex to protect pipeline_id_to_profile
2015
    // so we need to make sure this funciton is invoked after fragment context
2016
    // has already been prepared.
2017
0
    if (!_prepared) {
2018
0
        std::string msg =
2019
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2020
0
        DCHECK(false) << msg;
2021
0
        LOG_ERROR(msg);
2022
0
        return res;
2023
0
    }
2024
2025
    // Make sure first profile is fragment level profile
2026
0
    auto fragment_profile = std::make_shared<TRuntimeProfileTree>();
2027
0
    _fragment_level_profile->to_thrift(fragment_profile.get(), _runtime_state->profile_level());
2028
0
    res.push_back(fragment_profile);
2029
2030
    // pipeline_id_to_profile is initialized in prepare stage
2031
0
    for (auto pipeline_profile : _runtime_state->pipeline_id_to_profile()) {
2032
0
        auto profile_ptr = std::make_shared<TRuntimeProfileTree>();
2033
0
        pipeline_profile->to_thrift(profile_ptr.get(), _runtime_state->profile_level());
2034
0
        res.push_back(profile_ptr);
2035
0
    }
2036
2037
0
    return res;
2038
0
}
2039
2040
std::shared_ptr<TRuntimeProfileTree>
2041
0
PipelineFragmentContext::collect_realtime_load_channel_profile() const {
2042
    // we do not have mutex to protect pipeline_id_to_profile
2043
    // so we need to make sure this funciton is invoked after fragment context
2044
    // has already been prepared.
2045
0
    if (!_prepared) {
2046
0
        std::string msg =
2047
0
                "Query " + print_id(_query_id) + " collecting profile, but its not prepared";
2048
0
        DCHECK(false) << msg;
2049
0
        LOG_ERROR(msg);
2050
0
        return nullptr;
2051
0
    }
2052
2053
0
    for (const auto& tasks : _tasks) {
2054
0
        for (const auto& task : tasks) {
2055
0
            if (task.second->load_channel_profile() == nullptr) {
2056
0
                continue;
2057
0
            }
2058
2059
0
            auto tmp_load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2060
2061
0
            task.second->load_channel_profile()->to_thrift(tmp_load_channel_profile.get(),
2062
0
                                                           _runtime_state->profile_level());
2063
0
            _runtime_state->load_channel_profile()->update(*tmp_load_channel_profile);
2064
0
        }
2065
0
    }
2066
2067
0
    auto load_channel_profile = std::make_shared<TRuntimeProfileTree>();
2068
0
    _runtime_state->load_channel_profile()->to_thrift(load_channel_profile.get(),
2069
0
                                                      _runtime_state->profile_level());
2070
0
    return load_channel_profile;
2071
0
}
2072
2073
0
Status PipelineFragmentContext::wait_close(bool close) {
2074
0
    if (_exec_env->new_load_stream_mgr()->get(_query_id) != nullptr) {
2075
0
        return Status::InternalError("stream load do not support reset");
2076
0
    }
2077
0
    if (!_need_notify_close) {
2078
0
        return Status::InternalError("_need_notify_close is false, do not support reset");
2079
0
    }
2080
2081
0
    {
2082
0
        std::unique_lock<std::mutex> lock(_task_mutex);
2083
0
        while (!(_is_fragment_instance_closed.load() && !_has_task_execution_ctx_ref_count)) {
2084
0
            if (_query_ctx->is_cancelled()) {
2085
0
                return Status::Cancelled("Query has been cancelled");
2086
0
            }
2087
0
            _notify_cv.wait_for(lock, std::chrono::seconds(1));
2088
0
        }
2089
0
    }
2090
2091
0
    if (close) {
2092
0
        auto st = send_report(true);
2093
0
        if (!st) {
2094
0
            LOG(WARNING) << fmt::format("Failed to send report for query {}, fragment {}: {}",
2095
0
                                        print_id(_query_id), _fragment_id, st.to_string());
2096
0
        }
2097
0
        _exec_env->fragment_mgr()->remove_pipeline_context({_query_id, _fragment_id});
2098
0
    }
2099
0
    return Status::OK();
2100
0
}
2101
2102
0
Status PipelineFragmentContext::set_to_rerun() {
2103
0
    {
2104
0
        std::lock_guard<std::mutex> l(_task_mutex);
2105
0
        SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2106
0
        for (auto& tasks : _tasks) {
2107
0
            for (const auto& task : tasks) {
2108
0
                task.first->runtime_state()->reset_to_rerun();
2109
0
            }
2110
0
        }
2111
0
    }
2112
0
    _release_resource();
2113
0
    _runtime_state->reset_to_rerun();
2114
0
    return Status::OK();
2115
0
}
2116
2117
0
Status PipelineFragmentContext::rebuild(ThreadPool* thread_pool) {
2118
0
    _submitted = false;
2119
0
    _is_fragment_instance_closed = false;
2120
0
    return _build_and_prepare_full_pipeline(thread_pool);
2121
0
}
2122
2123
25
void PipelineFragmentContext::_release_resource() {
2124
25
    std::lock_guard<std::mutex> l(_task_mutex);
2125
    // The memory released by the query end is recorded in the query mem tracker.
2126
25
    SCOPED_SWITCH_THREAD_MEM_TRACKER_LIMITER(_query_ctx->query_mem_tracker());
2127
25
    auto st = _query_ctx->exec_status();
2128
25
    for (auto& _task : _tasks) {
2129
0
        if (!_task.empty()) {
2130
0
            _call_back(_task.front().first->runtime_state(), &st);
2131
0
        }
2132
0
    }
2133
25
    _tasks.clear();
2134
25
    _dag.clear();
2135
25
    _pip_id_to_pipeline.clear();
2136
25
    _pipelines.clear();
2137
25
    _sink.reset();
2138
25
    _root_op.reset();
2139
25
    _runtime_filter_mgr_map.clear();
2140
25
    _op_id_to_shared_state.clear();
2141
25
}
2142
2143
#include "common/compile_check_end.h"
2144
} // namespace doris