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Add SummingSortedTransform [part 2]
This commit is contained in:
Nikolai Kochetov
parent
5f5eb58abe
commit
f3743552ce
@ -25,7 +25,7 @@ CollapsingSortedTransform::CollapsingSortedTransform(
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WriteBuffer * out_row_sources_buf_,
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bool use_average_block_sizes)
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: IMergingTransform(num_inputs, header, header, true)
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, merged_data(header, use_average_block_sizes, max_block_size)
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, merged_data(header.cloneEmptyColumns(), use_average_block_sizes, max_block_size)
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, description(std::move(description_))
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, sign_column_number(header.getPositionByName(sign_column))
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, out_row_sources_buf(out_row_sources_buf_)
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@ -13,12 +13,9 @@ namespace ErrorCodes
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class MergedData
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{
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public:
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explicit MergedData(const Block & header, bool use_average_block_size_, UInt64 max_block_size_)
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: max_block_size(max_block_size_), use_average_block_size(use_average_block_size_)
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explicit MergedData(MutableColumns columns_, bool use_average_block_size_, UInt64 max_block_size_)
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: columns(std::move(columns_)), max_block_size(max_block_size_), use_average_block_size(use_average_block_size_)
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{
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columns.reserve(header.columns());
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for (const auto & column : header)
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columns.emplace_back(column.type->createColumn());
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}
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/// Pull will be called at next prepare call.
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@ -24,7 +24,7 @@ MergingSortedTransform::MergingSortedTransform(
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bool use_average_block_sizes,
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bool have_all_inputs_)
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: IMergingTransform(num_inputs, header, header, have_all_inputs_)
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, merged_data(header, use_average_block_sizes, max_block_size)
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, merged_data(header.cloneEmptyColumns(), use_average_block_sizes, max_block_size)
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, description(std::move(description_))
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, limit(limit_)
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, quiet(quiet_)
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@ -16,7 +16,7 @@ ReplacingSortedTransform::ReplacingSortedTransform(
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WriteBuffer * out_row_sources_buf_,
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bool use_average_block_sizes)
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: IMergingTransform(num_inputs, header, header, true)
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, merged_data(header, use_average_block_sizes, max_block_size)
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, merged_data(header.cloneEmptyColumns(), use_average_block_sizes, max_block_size)
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, description(std::move(description_))
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, out_row_sources_buf(out_row_sources_buf_)
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, chunk_allocator(num_inputs + max_row_refs)
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@ -4,261 +4,302 @@
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#include <Common/StringUtils/StringUtils.h>
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#include <Core/Row.h>
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#include <Common/FieldVisitors.h>
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#include <Columns/ColumnTuple.h>
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namespace DB
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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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bool isInPrimaryKey(const SortDescription & description, const std::string & name, const size_t number)
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{
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return matrix[i].get<Array>()[j];
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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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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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return false;
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}
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return row_num != 0;
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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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}
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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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}
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SummingSortedTransform::SummingSortedTransform(
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size_t num_inputs, const Block & header,
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SortDescription description,
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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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{
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size_t num_columns = header.columns();
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current_row.resize(num_columns);
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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;
|
||||
|
||||
/** Fill in the column numbers, which must be summed.
|
||||
* This can only be numeric columns that are not part of the sort key.
|
||||
* If a non-empty column_names_to_sum is specified, then we only take these columns.
|
||||
* Some columns from column_names_to_sum may not be found. This is ignored.
|
||||
*/
|
||||
for (size_t i = 0; i < num_columns; ++i)
|
||||
{
|
||||
const ColumnWithTypeAndName & column = header.safeGetByPosition(i);
|
||||
|
||||
/// Discover nested Maps and find columns for summation
|
||||
if (typeid_cast<const DataTypeArray *>(column.type.get()))
|
||||
{
|
||||
const auto map_name = Nested::extractTableName(column.name);
|
||||
/// if nested table name ends with `Map` it is a possible candidate for special handling
|
||||
if (map_name == column.name || !endsWith(map_name, "Map"))
|
||||
{
|
||||
column_numbers_not_to_aggregate.push_back(i);
|
||||
continue;
|
||||
}
|
||||
|
||||
discovered_maps[map_name].emplace_back(i);
|
||||
}
|
||||
else
|
||||
{
|
||||
bool is_agg_func = WhichDataType(column.type).isAggregateFunction();
|
||||
|
||||
/// There are special const columns for example after prewere sections.
|
||||
if ((!column.type->isSummable() && !is_agg_func) || isColumnConst(*column.column))
|
||||
{
|
||||
column_numbers_not_to_aggregate.push_back(i);
|
||||
continue;
|
||||
}
|
||||
|
||||
/// Are they inside the PK?
|
||||
if (isInPrimaryKey(description, column.name, i))
|
||||
{
|
||||
column_numbers_not_to_aggregate.push_back(i);
|
||||
continue;
|
||||
}
|
||||
|
||||
if (column_names_to_sum.empty()
|
||||
|| column_names_to_sum.end() !=
|
||||
std::find(column_names_to_sum.begin(), column_names_to_sum.end(), column.name))
|
||||
{
|
||||
// Create aggregator to sum this column
|
||||
AggregateDescription desc;
|
||||
desc.is_agg_func_type = is_agg_func;
|
||||
desc.column_numbers = {i};
|
||||
|
||||
if (!is_agg_func)
|
||||
{
|
||||
desc.init("sumWithOverflow", {column.type});
|
||||
}
|
||||
|
||||
columns_to_aggregate.emplace_back(std::move(desc));
|
||||
}
|
||||
else
|
||||
{
|
||||
// Column is not going to be summed, use last value
|
||||
column_numbers_not_to_aggregate.push_back(i);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// select actual nested Maps from list of candidates
|
||||
for (const auto & map : discovered_maps)
|
||||
{
|
||||
/// map should contain at least two elements (key -> value)
|
||||
if (map.second.size() < 2)
|
||||
{
|
||||
for (auto col : map.second)
|
||||
column_numbers_not_to_aggregate.push_back(col);
|
||||
continue;
|
||||
}
|
||||
|
||||
/// no elements of map could be in primary key
|
||||
auto column_num_it = map.second.begin();
|
||||
for (; column_num_it != map.second.end(); ++column_num_it)
|
||||
if (isInPrimaryKey(description, header.safeGetByPosition(*column_num_it).name, *column_num_it))
|
||||
break;
|
||||
if (column_num_it != map.second.end())
|
||||
{
|
||||
for (auto col : map.second)
|
||||
column_numbers_not_to_aggregate.push_back(col);
|
||||
continue;
|
||||
}
|
||||
|
||||
DataTypes argument_types;
|
||||
AggregateDescription desc;
|
||||
MapDescription map_desc;
|
||||
|
||||
column_num_it = map.second.begin();
|
||||
for (; column_num_it != map.second.end(); ++column_num_it)
|
||||
{
|
||||
const ColumnWithTypeAndName & key_col = header.safeGetByPosition(*column_num_it);
|
||||
const String & name = key_col.name;
|
||||
const IDataType & nested_type = *static_cast<const DataTypeArray *>(key_col.type.get())->getNestedType();
|
||||
|
||||
if (column_num_it == map.second.begin()
|
||||
|| endsWith(name, "ID")
|
||||
|| endsWith(name, "Key")
|
||||
|| endsWith(name, "Type"))
|
||||
{
|
||||
if (!nested_type.isValueRepresentedByInteger() && !isStringOrFixedString(nested_type))
|
||||
break;
|
||||
|
||||
map_desc.key_col_nums.push_back(*column_num_it);
|
||||
}
|
||||
else
|
||||
{
|
||||
if (!nested_type.isSummable())
|
||||
break;
|
||||
|
||||
map_desc.val_col_nums.push_back(*column_num_it);
|
||||
}
|
||||
|
||||
// Add column to function arguments
|
||||
desc.column_numbers.push_back(*column_num_it);
|
||||
argument_types.push_back(key_col.type);
|
||||
}
|
||||
|
||||
if (column_num_it != map.second.end())
|
||||
{
|
||||
for (auto col : map.second)
|
||||
column_numbers_not_to_aggregate.push_back(col);
|
||||
continue;
|
||||
}
|
||||
|
||||
if (map_desc.key_col_nums.size() == 1)
|
||||
{
|
||||
// Create summation for all value columns in the map
|
||||
desc.init("sumMapWithOverflow", argument_types);
|
||||
columns_to_aggregate.emplace_back(std::move(desc));
|
||||
}
|
||||
else
|
||||
{
|
||||
// Fall back to legacy mergeMaps for composite keys
|
||||
for (auto col : map.second)
|
||||
column_numbers_not_to_aggregate.push_back(col);
|
||||
maps_to_sum.emplace_back(std::move(map_desc));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
@ -8,6 +8,7 @@
|
||||
#include <Common/AlignedBuffer.h>
|
||||
#include <Core/SortDescription.h>
|
||||
#include <Core/SortCursor.h>
|
||||
#include <Core/Row.h>
|
||||
|
||||
namespace DB
|
||||
{
|
||||
@ -20,7 +21,7 @@ public:
|
||||
|
||||
SummingSortedTransform(
|
||||
size_t num_inputs, const Block & header,
|
||||
SortDescription description,
|
||||
SortDescription description_,
|
||||
/// List of columns to be summed. If empty, all numeric columns that are not in the description are taken.
|
||||
const Names & column_names_to_sum,
|
||||
size_t max_block_size);
|
||||
@ -80,7 +81,7 @@ public:
|
||||
struct SummingMergedData : public MergedData
|
||||
{
|
||||
public:
|
||||
|
||||
using MergedData::MergedData;
|
||||
};
|
||||
|
||||
/// Stores numbers of key-columns and value-columns.
|
||||
@ -90,12 +91,51 @@ public:
|
||||
std::vector<size_t> val_col_nums;
|
||||
};
|
||||
|
||||
private:
|
||||
/// Columns with which values should be summed.
|
||||
ColumnNumbers column_numbers_not_to_aggregate;
|
||||
struct ColumnsDefinition
|
||||
{
|
||||
/// Columns with which values should be summed.
|
||||
ColumnNumbers column_numbers_not_to_aggregate;
|
||||
/// Columns which should be aggregated.
|
||||
std::vector<AggregateDescription> columns_to_aggregate;
|
||||
/// Mapping for nested columns.
|
||||
std::vector<MapDescription> maps_to_sum;
|
||||
|
||||
std::vector<AggregateDescription> columns_to_aggregate;
|
||||
std::vector<MapDescription> maps_to_sum;
|
||||
size_t getNumColumns() const { return column_numbers_not_to_aggregate.size() + columns_to_aggregate.size(); }
|
||||
};
|
||||
|
||||
private:
|
||||
Row current_row;
|
||||
bool current_row_is_zero = true; /// Are all summed columns zero (or empty)? It is updated incrementally.
|
||||
|
||||
ColumnsDefinition columns_definition;
|
||||
SummingMergedData merged_data;
|
||||
|
||||
SortDescription description;
|
||||
|
||||
/// Chunks currently being merged.
|
||||
std::vector<Chunk> source_chunks;
|
||||
SortCursorImpls cursors;
|
||||
|
||||
/// In merging algorithm, we need to compare current sort key with the last one.
|
||||
/// So, sorting columns for last row needed to be stored.
|
||||
/// In order to do it, we extend lifetime of last chunk and it's sort columns (from corresponding sort cursor).
|
||||
Chunk last_chunk;
|
||||
ColumnRawPtrs last_chunk_sort_columns; /// Point to last_chunk if valid.
|
||||
|
||||
struct RowRef
|
||||
{
|
||||
ColumnRawPtrs * sort_columns = nullptr; /// Point to sort_columns from SortCursor or last_chunk_sort_columns.
|
||||
UInt64 row_number = 0;
|
||||
};
|
||||
|
||||
RowRef last_row;
|
||||
|
||||
SortingHeap<SortCursor> queue;
|
||||
bool is_queue_initialized = false;
|
||||
|
||||
void insertRow();
|
||||
void merge();
|
||||
void updateCursor(Chunk chunk, size_t source_num);
|
||||
};
|
||||
|
||||
}
|
||||
|
||||
@ -14,7 +14,7 @@ VersionedCollapsingTransform::VersionedCollapsingTransform(
|
||||
WriteBuffer * out_row_sources_buf_,
|
||||
bool use_average_block_sizes)
|
||||
: IMergingTransform(num_inputs, header, header, true)
|
||||
, merged_data(header, use_average_block_sizes, max_block_size)
|
||||
, merged_data(header.cloneEmptyColumns(), use_average_block_sizes, max_block_size)
|
||||
, description(std::move(description_))
|
||||
, out_row_sources_buf(out_row_sources_buf_)
|
||||
, max_rows_in_queue(MAX_ROWS_IN_MULTIVERSION_QUEUE - 1) /// -1 for +1 in FixedSizeDequeWithGaps's internal buffer
|
||||
|
||||
Loading…
Reference in New Issue
Block a user