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https://github.com/ClickHouse/ClickHouse.git
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178 lines
4.6 KiB
C++
178 lines
4.6 KiB
C++
#include <QueryPipeline/printPipeline.h>
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#include <Processors/QueryPlan/IQueryPlanStep.h>
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#include <set>
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#include <map>
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namespace DB
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{
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void printPipelineCompact(const Processors & processors, WriteBuffer & out, bool with_header)
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{
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struct Node;
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/// Group by processors name, QueryPlanStep and group in this step.
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struct Key
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{
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size_t group;
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IQueryPlanStep * step;
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std::string name;
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auto getTuple() const { return std::forward_as_tuple(group, step, name); }
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bool operator<(const Key & other) const
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{
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return getTuple() < other.getTuple();
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}
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};
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/// Group ports by header.
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struct EdgeData
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{
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Block header;
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size_t count;
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};
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using Edge = std::vector<EdgeData>;
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struct Node
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{
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size_t id = 0;
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std::map<Node *, Edge> edges = {};
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std::vector<const IProcessor *> agents = {};
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};
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std::map<Key, Node> graph;
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auto get_key = [](const IProcessor & processor)
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{
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return Key{processor.getQueryPlanStepGroup(), processor.getQueryPlanStep(), processor.getName()};
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};
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/// Fill nodes.
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for (const auto & processor : processors)
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{
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auto res = graph.emplace(get_key(*processor), Node());
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auto & node = res.first->second;
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node.agents.emplace_back(processor.get());
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if (res.second)
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node.id = graph.size();
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}
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Block empty_header;
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/// Fill edges.
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for (const auto & processor : processors)
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{
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auto & from = graph[get_key(*processor)];
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for (auto & port : processor->getOutputs())
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{
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if (!port.isConnected())
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continue;
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auto & to = graph[get_key(port.getInputPort().getProcessor())];
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auto & edge = from.edges[&to];
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/// Use empty header for each edge if with_header is false.
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const auto & header = with_header ? port.getHeader()
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: empty_header;
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/// Group by header.
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bool found = false;
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for (auto & item : edge)
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{
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if (blocksHaveEqualStructure(header, item.header))
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{
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found = true;
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++item.count;
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break;
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}
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}
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if (!found)
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edge.emplace_back(EdgeData{header, 1});
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}
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}
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/// Group processors by it's QueryPlanStep.
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std::map<IQueryPlanStep *, std::vector<const Node *>> steps_map;
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for (const auto & item : graph)
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steps_map[item.first.step].emplace_back(&item.second);
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out << "digraph\n{\n";
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out << " rankdir=\"LR\";\n";
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out << " { node [shape = rect]\n";
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/// Nodes // TODO quoting and escaping
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size_t next_step = 0;
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for (const auto & item : steps_map)
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{
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/// Use separate clusters for each step.
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if (item.first != nullptr)
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{
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out << " subgraph cluster_" << next_step << " {\n";
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out << " label =\"" << item.first->getName() << "\";\n";
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out << " style=filled;\n";
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out << " color=lightgrey;\n";
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out << " node [style=filled,color=white];\n";
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out << " { rank = same;\n";
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++next_step;
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}
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for (const auto & node : item.second)
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{
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const auto & processor = node->agents.front();
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out << " n" << node->id << " [label=\"" << processor->getName();
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if (node->agents.size() > 1)
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out << " × " << node->agents.size();
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const auto & description = processor->getDescription();
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if (!description.empty())
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out << ' ' << description;
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out << "\"];\n";
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}
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if (item.first != nullptr)
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{
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out << " }\n";
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out << " }\n";
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}
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}
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out << " }\n";
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/// Edges
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for (const auto & item : graph)
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{
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for (const auto & edge : item.second.edges)
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{
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for (const auto & data : edge.second)
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{
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out << " n" << item.second.id << " -> " << "n" << edge.first->id << " [label=\"";
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if (data.count > 1)
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out << "× " << data.count;
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if (with_header)
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{
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for (const auto & elem : data.header)
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{
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out << "\n";
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elem.dumpStructure(out);
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}
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}
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out << "\"];\n";
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}
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}
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}
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out << "}\n";
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}
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}
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