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627 lines
22 KiB
C++
627 lines
22 KiB
C++
#include <Processors/Merges/SummingSortedTransform.h>
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#include <DataTypes/DataTypeArray.h>
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#include <DataTypes/NestedUtils.h>
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#include <Columns/ColumnAggregateFunction.h>
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#include <Columns/ColumnTuple.h>
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#include <Common/StringUtils/StringUtils.h>
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#include <Common/FieldVisitors.h>
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#include <Core/Row.h>
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#include <IO/WriteHelpers.h>
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namespace DB
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{
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namespace ErrorCodes
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{
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extern const int LOGICAL_ERROR;
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extern const int CORRUPTED_DATA;
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}
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namespace
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{
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bool isInPrimaryKey(const SortDescription & description, const std::string & name, const size_t number)
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{
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for (auto & desc : description)
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if (desc.column_name == name || (desc.column_name.empty() && desc.column_number == number))
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return true;
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return false;
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}
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/// Returns true if merge result is not empty
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bool mergeMap(const SummingSortedTransform::MapDescription & desc, Row & row, SortCursor & cursor)
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{
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/// Strongly non-optimal.
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Row & left = row;
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Row right(left.size());
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for (size_t col_num : desc.key_col_nums)
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right[col_num] = (*cursor->all_columns[col_num])[cursor->pos].template get<Array>();
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for (size_t col_num : desc.val_col_nums)
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right[col_num] = (*cursor->all_columns[col_num])[cursor->pos].template get<Array>();
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auto at_ith_column_jth_row = [&](const Row & matrix, size_t i, size_t j) -> const Field &
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{
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return matrix[i].get<Array>()[j];
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};
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auto tuple_of_nth_columns_at_jth_row = [&](const Row & matrix, const ColumnNumbers & col_nums, size_t j) -> Array
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{
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size_t size = col_nums.size();
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Array res(size);
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for (size_t col_num_index = 0; col_num_index < size; ++col_num_index)
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res[col_num_index] = at_ith_column_jth_row(matrix, col_nums[col_num_index], j);
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return res;
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};
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std::map<Array, Array> merged;
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auto accumulate = [](Array & dst, const Array & src)
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{
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bool has_non_zero = false;
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size_t size = dst.size();
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for (size_t i = 0; i < size; ++i)
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if (applyVisitor(FieldVisitorSum(src[i]), dst[i]))
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has_non_zero = true;
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return has_non_zero;
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};
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auto merge = [&](const Row & matrix)
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{
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size_t rows = matrix[desc.key_col_nums[0]].get<Array>().size();
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for (size_t j = 0; j < rows; ++j)
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{
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Array key = tuple_of_nth_columns_at_jth_row(matrix, desc.key_col_nums, j);
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Array value = tuple_of_nth_columns_at_jth_row(matrix, desc.val_col_nums, j);
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auto it = merged.find(key);
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if (merged.end() == it)
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merged.emplace(std::move(key), std::move(value));
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else
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{
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if (!accumulate(it->second, value))
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merged.erase(it);
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}
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}
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};
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merge(left);
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merge(right);
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for (size_t col_num : desc.key_col_nums)
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row[col_num] = Array(merged.size());
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for (size_t col_num : desc.val_col_nums)
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row[col_num] = Array(merged.size());
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size_t row_num = 0;
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for (const auto & key_value : merged)
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{
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for (size_t col_num_index = 0, size = desc.key_col_nums.size(); col_num_index < size; ++col_num_index)
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row[desc.key_col_nums[col_num_index]].get<Array>()[row_num] = key_value.first[col_num_index];
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for (size_t col_num_index = 0, size = desc.val_col_nums.size(); col_num_index < size; ++col_num_index)
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row[desc.val_col_nums[col_num_index]].get<Array>()[row_num] = key_value.second[col_num_index];
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++row_num;
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}
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return row_num != 0;
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}
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SummingSortedTransform::ColumnsDefinition defineColumns(
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const Block & header,
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const SortDescription & description,
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const Names & column_names_to_sum)
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{
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size_t num_columns = header.columns();
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SummingSortedTransform::ColumnsDefinition def;
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/// name of nested structure -> the column numbers that refer to it.
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std::unordered_map<std::string, std::vector<size_t>> discovered_maps;
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/** Fill in the column numbers, which must be summed.
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* This can only be numeric columns that are not part of the sort key.
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* If a non-empty column_names_to_sum is specified, then we only take these columns.
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* Some columns from column_names_to_sum may not be found. This is ignored.
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*/
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for (size_t i = 0; i < num_columns; ++i)
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{
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const ColumnWithTypeAndName & column = header.safeGetByPosition(i);
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/// Discover nested Maps and find columns for summation
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if (typeid_cast<const DataTypeArray *>(column.type.get()))
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{
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const auto map_name = Nested::extractTableName(column.name);
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/// if nested table name ends with `Map` it is a possible candidate for special handling
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if (map_name == column.name || !endsWith(map_name, "Map"))
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{
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def.column_numbers_not_to_aggregate.push_back(i);
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continue;
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}
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discovered_maps[map_name].emplace_back(i);
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}
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else
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{
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bool is_agg_func = WhichDataType(column.type).isAggregateFunction();
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/// There are special const columns for example after prewhere sections.
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if ((!column.type->isSummable() && !is_agg_func) || isColumnConst(*column.column))
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{
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def.column_numbers_not_to_aggregate.push_back(i);
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continue;
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}
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/// Are they inside the PK?
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if (isInPrimaryKey(description, column.name, i))
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{
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def.column_numbers_not_to_aggregate.push_back(i);
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continue;
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}
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if (column_names_to_sum.empty()
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|| column_names_to_sum.end() !=
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std::find(column_names_to_sum.begin(), column_names_to_sum.end(), column.name))
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{
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// Create aggregator to sum this column
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SummingSortedTransform::AggregateDescription desc;
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desc.is_agg_func_type = is_agg_func;
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desc.column_numbers = {i};
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if (!is_agg_func)
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{
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desc.init("sumWithOverflow", {column.type});
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}
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def.columns_to_aggregate.emplace_back(std::move(desc));
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}
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else
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{
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// Column is not going to be summed, use last value
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def.column_numbers_not_to_aggregate.push_back(i);
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}
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}
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}
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/// select actual nested Maps from list of candidates
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for (const auto & map : discovered_maps)
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{
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/// map should contain at least two elements (key -> value)
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if (map.second.size() < 2)
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{
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for (auto col : map.second)
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def.column_numbers_not_to_aggregate.push_back(col);
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continue;
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}
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/// no elements of map could be in primary key
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auto column_num_it = map.second.begin();
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for (; column_num_it != map.second.end(); ++column_num_it)
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if (isInPrimaryKey(description, header.safeGetByPosition(*column_num_it).name, *column_num_it))
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break;
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if (column_num_it != map.second.end())
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{
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for (auto col : map.second)
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def.column_numbers_not_to_aggregate.push_back(col);
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continue;
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}
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DataTypes argument_types;
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SummingSortedTransform::AggregateDescription desc;
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SummingSortedTransform::MapDescription map_desc;
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column_num_it = map.second.begin();
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for (; column_num_it != map.second.end(); ++column_num_it)
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{
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const ColumnWithTypeAndName & key_col = header.safeGetByPosition(*column_num_it);
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const String & name = key_col.name;
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const IDataType & nested_type = *assert_cast<const DataTypeArray &>(*key_col.type).getNestedType();
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if (column_num_it == map.second.begin()
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|| endsWith(name, "ID")
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|| endsWith(name, "Key")
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|| endsWith(name, "Type"))
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{
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if (!nested_type.isValueRepresentedByInteger() && !isStringOrFixedString(nested_type))
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break;
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map_desc.key_col_nums.push_back(*column_num_it);
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}
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else
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{
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if (!nested_type.isSummable())
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break;
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map_desc.val_col_nums.push_back(*column_num_it);
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}
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// Add column to function arguments
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desc.column_numbers.push_back(*column_num_it);
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argument_types.push_back(key_col.type);
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}
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if (column_num_it != map.second.end())
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{
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for (auto col : map.second)
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def.column_numbers_not_to_aggregate.push_back(col);
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continue;
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}
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if (map_desc.key_col_nums.size() == 1)
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{
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// Create summation for all value columns in the map
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desc.init("sumMapWithOverflow", argument_types);
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def.columns_to_aggregate.emplace_back(std::move(desc));
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}
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else
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{
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// Fall back to legacy mergeMaps for composite keys
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for (auto col : map.second)
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def.column_numbers_not_to_aggregate.push_back(col);
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def.maps_to_sum.emplace_back(std::move(map_desc));
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}
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}
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return def;
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}
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MutableColumns getMergedDataColumns(
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const Block & header,
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const SummingSortedTransform::ColumnsDefinition & columns_definition)
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{
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MutableColumns columns;
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columns.reserve(columns_definition.getNumColumns());
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for (auto & desc : columns_definition.columns_to_aggregate)
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{
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// Wrap aggregated columns in a tuple to match function signature
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if (!desc.is_agg_func_type && isTuple(desc.function->getReturnType()))
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{
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size_t tuple_size = desc.column_numbers.size();
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MutableColumns tuple_columns(tuple_size);
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for (size_t i = 0; i < tuple_size; ++i)
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tuple_columns[i] = header.safeGetByPosition(desc.column_numbers[i]).column->cloneEmpty();
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columns.emplace_back(ColumnTuple::create(std::move(tuple_columns)));
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}
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else
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columns.emplace_back(header.safeGetByPosition(desc.column_numbers[0]).column->cloneEmpty());
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}
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for (auto & column_number : columns_definition.column_numbers_not_to_aggregate)
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columns.emplace_back(header.safeGetByPosition(column_number).type->createColumn());
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return columns;
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}
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void finalizeChunk(
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Chunk & chunk, size_t num_result_columns,
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const SummingSortedTransform::ColumnsDefinition & columns_definition)
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{
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size_t num_rows = chunk.getNumRows();
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auto columns = chunk.detachColumns();
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Columns res_columns(num_result_columns);
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size_t next_column = 0;
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for (auto & desc : columns_definition.columns_to_aggregate)
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{
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auto column = std::move(columns[next_column]);
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++next_column;
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if (!desc.is_agg_func_type && isTuple(desc.function->getReturnType()))
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{
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/// Unpack tuple into block.
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size_t tuple_size = desc.column_numbers.size();
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for (size_t i = 0; i < tuple_size; ++i)
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res_columns[desc.column_numbers[i]] = assert_cast<const ColumnTuple &>(*column).getColumnPtr(i);
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}
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else
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res_columns[desc.column_numbers[0]] = std::move(column);
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}
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for (auto column_number : columns_definition.column_numbers_not_to_aggregate)
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{
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auto column = std::move(columns[next_column]);
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++next_column;
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res_columns[column_number] = std::move(column);
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}
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chunk.setColumns(std::move(res_columns), num_rows);
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}
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void setRow(Row & row, SortCursor & cursor, const Block & header)
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{
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size_t num_columns = row.size();
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for (size_t i = 0; i < num_columns; ++i)
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{
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try
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{
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cursor->all_columns[i]->get(cursor->pos, row[i]);
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}
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catch (...)
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{
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tryLogCurrentException(__PRETTY_FUNCTION__);
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/// Find out the name of the column and throw more informative exception.
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String column_name;
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if (i < header.columns())
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{
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column_name = header.safeGetByPosition(i).name;
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break;
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}
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throw Exception("MergingSortedBlockInputStream failed to read row " + toString(cursor->pos)
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+ " of column " + toString(i) + (column_name.empty() ? "" : " (" + column_name + ")"),
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ErrorCodes::CORRUPTED_DATA);
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}
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}
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}
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}
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SummingSortedTransform::SummingSortedTransform(
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const Block & header, size_t num_inputs,
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SortDescription description_,
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/// List of columns to be summed. If empty, all numeric columns that are not in the description are taken.
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const Names & column_names_to_sum,
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size_t max_block_size)
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: IMergingTransform(num_inputs, header, header, true)
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, columns_definition(defineColumns(header, description_, column_names_to_sum))
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, merged_data(getMergedDataColumns(header, columns_definition), false, max_block_size)
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, description(std::move(description_))
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, source_chunks(num_inputs)
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, cursors(num_inputs)
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{
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current_row.resize(header.columns());
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merged_data.initAggregateDescription(columns_definition.columns_to_aggregate);
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}
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void SummingSortedTransform::initializeInputs()
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{
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queue = SortingHeap<SortCursor>(cursors);
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is_queue_initialized = true;
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}
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void SummingSortedTransform::consume(Chunk chunk, size_t input_number)
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{
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updateCursor(std::move(chunk), input_number);
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if (is_queue_initialized)
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queue.push(cursors[input_number]);
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}
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void SummingSortedTransform::updateCursor(Chunk chunk, size_t source_num)
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{
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auto num_rows = chunk.getNumRows();
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auto columns = chunk.detachColumns();
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for (auto & column : columns)
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column = column->convertToFullColumnIfConst();
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chunk.setColumns(std::move(columns), num_rows);
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auto & source_chunk = source_chunks[source_num];
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if (source_chunk)
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{
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/// Extend lifetime of last chunk.
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last_chunk = std::move(source_chunk);
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last_chunk_sort_columns = std::move(cursors[source_num].sort_columns);
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source_chunk = std::move(chunk);
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cursors[source_num].reset(source_chunk.getColumns(), {});
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}
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else
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{
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if (cursors[source_num].has_collation)
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throw Exception("Logical error: " + getName() + " does not support collations", ErrorCodes::LOGICAL_ERROR);
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source_chunk = std::move(chunk);
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cursors[source_num] = SortCursorImpl(source_chunk.getColumns(), description, source_num);
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}
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}
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void SummingSortedTransform::work()
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{
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merge();
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prepareOutputChunk(merged_data);
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if (has_output_chunk)
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{
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finalizeChunk(output_chunk, getOutputs().back().getHeader().columns(), columns_definition);
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merged_data.initAggregateDescription(columns_definition.columns_to_aggregate);
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}
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}
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void SummingSortedTransform::insertCurrentRowIfNeeded()
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{
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/// We have nothing to aggregate. It means that it could be non-zero, because we have columns_not_to_aggregate.
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if (columns_definition.columns_to_aggregate.empty())
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current_row_is_zero = false;
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for (auto & desc : columns_definition.columns_to_aggregate)
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{
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// Do not insert if the aggregation state hasn't been created
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if (desc.created)
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{
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if (desc.is_agg_func_type)
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{
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current_row_is_zero = false;
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}
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else
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{
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try
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{
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desc.function->insertResultInto(desc.state.data(), *desc.merged_column);
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/// Update zero status of current row
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if (desc.column_numbers.size() == 1)
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{
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// Flag row as non-empty if at least one column number if non-zero
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current_row_is_zero = current_row_is_zero && desc.merged_column->isDefaultAt(desc.merged_column->size() - 1);
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}
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else
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{
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/// It is sumMapWithOverflow aggregate function.
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/// Assume that the row isn't empty in this case (just because it is compatible with previous version)
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current_row_is_zero = false;
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}
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}
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catch (...)
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{
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desc.destroyState();
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throw;
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}
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}
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desc.destroyState();
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}
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else
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desc.merged_column->insertDefault();
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}
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/// If it is "zero" row, then rollback the insertion
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/// (at this moment we need rollback only cols from columns_to_aggregate)
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if (current_row_is_zero)
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{
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for (auto & desc : columns_definition.columns_to_aggregate)
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desc.merged_column->popBack(1);
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return;
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}
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merged_data.insertRow(current_row, columns_definition.column_numbers_not_to_aggregate);
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}
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void SummingSortedTransform::addRow(SortCursor & cursor)
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{
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for (auto & desc : columns_definition.columns_to_aggregate)
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{
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if (!desc.created)
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throw Exception("Logical error in SummingSortedBlockInputStream, there are no description", ErrorCodes::LOGICAL_ERROR);
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if (desc.is_agg_func_type)
|
|
{
|
|
// desc.state is not used for AggregateFunction types
|
|
auto & col = cursor->all_columns[desc.column_numbers[0]];
|
|
assert_cast<ColumnAggregateFunction &>(*desc.merged_column).insertMergeFrom(*col, cursor->pos);
|
|
}
|
|
else
|
|
{
|
|
// Specialized case for unary functions
|
|
if (desc.column_numbers.size() == 1)
|
|
{
|
|
auto & col = cursor->all_columns[desc.column_numbers[0]];
|
|
desc.add_function(desc.function.get(), desc.state.data(), &col, cursor->pos, nullptr);
|
|
}
|
|
else
|
|
{
|
|
// Gather all source columns into a vector
|
|
ColumnRawPtrs columns(desc.column_numbers.size());
|
|
for (size_t i = 0; i < desc.column_numbers.size(); ++i)
|
|
columns[i] = cursor->all_columns[desc.column_numbers[i]];
|
|
|
|
desc.add_function(desc.function.get(), desc.state.data(), columns.data(), cursor->pos, nullptr);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void SummingSortedTransform::merge()
|
|
{
|
|
/// Take the rows in needed order and put them in `merged_columns` until rows no more than `max_block_size`
|
|
while (queue.isValid())
|
|
{
|
|
bool key_differs;
|
|
bool has_previous_group = !last_key.empty();
|
|
|
|
SortCursor current = queue.current();
|
|
|
|
{
|
|
detail::RowRef current_key;
|
|
current_key.set(current);
|
|
|
|
if (!has_previous_group) /// The first key encountered.
|
|
{
|
|
key_differs = true;
|
|
current_row_is_zero = true;
|
|
}
|
|
else
|
|
key_differs = !last_key.hasEqualSortColumnsWith(current_key);
|
|
|
|
last_key = current_key;
|
|
last_chunk_sort_columns.clear();
|
|
}
|
|
|
|
if (key_differs)
|
|
{
|
|
if (has_previous_group)
|
|
/// Write the data for the previous group.
|
|
insertCurrentRowIfNeeded();
|
|
|
|
if (merged_data.hasEnoughRows())
|
|
{
|
|
/// The block is now full and the last row is calculated completely.
|
|
last_key.reset();
|
|
return;
|
|
}
|
|
|
|
setRow(current_row, current, getInputs().front().getHeader());
|
|
|
|
/// Reset aggregation states for next row
|
|
for (auto & desc : columns_definition.columns_to_aggregate)
|
|
desc.createState();
|
|
|
|
// Start aggregations with current row
|
|
addRow(current);
|
|
|
|
if (columns_definition.maps_to_sum.empty())
|
|
{
|
|
/// We have only columns_to_aggregate. The status of current row will be determined
|
|
/// in 'insertCurrentRowIfNeeded' method on the values of aggregate functions.
|
|
current_row_is_zero = true; // NOLINT
|
|
}
|
|
else
|
|
{
|
|
/// We have complex maps that will be summed with 'mergeMap' method.
|
|
/// The single row is considered non zero, and the status after merging with other rows
|
|
/// will be determined in the branch below (when key_differs == false).
|
|
current_row_is_zero = false; // NOLINT
|
|
}
|
|
}
|
|
else
|
|
{
|
|
addRow(current);
|
|
|
|
// Merge maps only for same rows
|
|
for (const auto & desc : columns_definition.maps_to_sum)
|
|
if (mergeMap(desc, current_row, current))
|
|
current_row_is_zero = false;
|
|
}
|
|
|
|
if (!current->isLast())
|
|
{
|
|
queue.next();
|
|
}
|
|
else
|
|
{
|
|
/// We get the next block from the corresponding source, if there is one.
|
|
queue.removeTop();
|
|
requestDataForInput(current.impl->order);
|
|
return;
|
|
}
|
|
}
|
|
|
|
/// We will write the data for the last group, if it is non-zero.
|
|
/// If it is zero, and without it the output stream will be empty, we will write it anyway.
|
|
insertCurrentRowIfNeeded();
|
|
last_chunk_sort_columns.clear();
|
|
is_finished = true;
|
|
}
|
|
|
|
}
|