ClickHouse/src/DataStreams/TTLAggregationAlgorithm.cpp

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2020-12-25 14:52:46 +00:00
#include <DataStreams/TTLAggregationAlgorithm.h>
namespace DB
{
TTLAggregationAlgorithm::TTLAggregationAlgorithm(
const TTLDescription & description_,
const TTLInfo & old_ttl_info_,
time_t current_time_,
bool force_,
const Block & header_,
const MergeTreeData & storage_)
: ITTLAlgorithm(description_, old_ttl_info_, current_time_, force_)
, header(header_)
{
current_key_value.resize(description.group_by_keys.size());
ColumnNumbers keys;
for (const auto & key : description.group_by_keys)
keys.push_back(header.getPositionByName(key));
key_columns.resize(description.group_by_keys.size());
AggregateDescriptions aggregates = description.aggregate_descriptions;
for (auto & descr : aggregates)
if (descr.arguments.empty())
for (const auto & name : descr.argument_names)
descr.arguments.push_back(header.getPositionByName(name));
columns_for_aggregator.resize(description.aggregate_descriptions.size());
const Settings & settings = storage_.global_context.getSettingsRef();
Aggregator::Params params(header, keys, aggregates,
false, settings.max_rows_to_group_by, settings.group_by_overflow_mode, 0, 0,
settings.max_bytes_before_external_group_by, settings.empty_result_for_aggregation_by_empty_set,
storage_.global_context.getTemporaryVolume(), settings.max_threads, settings.min_free_disk_space_for_temporary_data);
aggregator = std::make_unique<Aggregator>(params);
}
void TTLAggregationAlgorithm::execute(Block & block)
{
if (!block)
{
if (!aggregation_result.empty())
{
MutableColumns result_columns = header.cloneEmptyColumns();
finalizeAggregates(result_columns);
block = header.cloneWithColumns(std::move(result_columns));
}
return;
}
const auto & column_names = header.getNames();
MutableColumns result_columns = header.cloneEmptyColumns();
MutableColumns aggregate_columns = header.cloneEmptyColumns();
auto ttl_column = extractRequieredColumn(description.expression, block, description.result_column);
auto where_column = extractRequieredColumn(description.where_expression, block, description.where_result_column);
size_t rows_aggregated = 0;
size_t current_key_start = 0;
size_t rows_with_current_key = 0;
for (size_t i = 0; i < block.rows(); ++i)
{
UInt32 cur_ttl = getTimestampByIndex(ttl_column.get(), i);
bool where_filter_passed = !where_column || where_column->getBool(i);
bool ttl_expired = isTTLExpired(cur_ttl) && where_filter_passed;
bool same_as_current = true;
for (size_t j = 0; j < description.group_by_keys.size(); ++j)
{
const String & key_column = description.group_by_keys[j];
const IColumn * values_column = block.getByName(key_column).column.get();
if (!same_as_current || (*values_column)[i] != current_key_value[j])
{
values_column->get(i, current_key_value[j]);
same_as_current = false;
}
}
if (!same_as_current)
{
if (rows_with_current_key)
calculateAggregates(aggregate_columns, current_key_start, rows_with_current_key);
finalizeAggregates(result_columns);
current_key_start = rows_aggregated;
rows_with_current_key = 0;
}
if (ttl_expired)
{
++rows_with_current_key;
++rows_aggregated;
for (const auto & name : column_names)
{
const IColumn * values_column = block.getByName(name).column.get();
auto & column = aggregate_columns[header.getPositionByName(name)];
column->insertFrom(*values_column, i);
}
}
else
{
new_ttl_info.update(cur_ttl);
for (const auto & name : column_names)
{
const IColumn * values_column = block.getByName(name).column.get();
auto & column = result_columns[header.getPositionByName(name)];
column->insertFrom(*values_column, i);
}
}
}
if (rows_with_current_key)
calculateAggregates(aggregate_columns, current_key_start, rows_with_current_key);
block = header.cloneWithColumns(std::move(result_columns));
}
void TTLAggregationAlgorithm::calculateAggregates(const MutableColumns & aggregate_columns, size_t start_pos, size_t length)
{
Columns aggregate_chunk;
aggregate_chunk.reserve(aggregate_columns.size());
for (const auto & name : header.getNames())
{
const auto & column = aggregate_columns[header.getPositionByName(name)];
ColumnPtr chunk_column = column->cut(start_pos, length);
aggregate_chunk.emplace_back(std::move(chunk_column));
}
aggregator->executeOnBlock(aggregate_chunk, length, aggregation_result, key_columns,
columns_for_aggregator, no_more_keys);
}
void TTLAggregationAlgorithm::finalizeAggregates(MutableColumns & result_columns)
{
if (!aggregation_result.empty())
{
auto aggregated_res = aggregator->convertToBlocks(aggregation_result, true, 1);
for (auto & agg_block : aggregated_res)
{
for (const auto & it : description.set_parts)
it.expression->execute(agg_block);
for (const auto & name : description.group_by_keys)
{
const IColumn * values_column = agg_block.getByName(name).column.get();
auto & result_column = result_columns[header.getPositionByName(name)];
result_column->insertRangeFrom(*values_column, 0, agg_block.rows());
}
for (const auto & it : description.set_parts)
{
const IColumn * values_column = agg_block.getByName(it.expression_result_column_name).column.get();
auto & result_column = result_columns[header.getPositionByName(it.column_name)];
result_column->insertRangeFrom(*values_column, 0, agg_block.rows());
}
}
}
aggregation_result.invalidate();
}
void TTLAggregationAlgorithm::finalize(const MutableDataPartPtr & data_part) const
{
data_part->ttl_infos.group_by_ttl[description.result_column] = new_ttl_info;
data_part->ttl_infos.updatePartMinMaxTTL(new_ttl_info.min, new_ttl_info.max);
}
}