dbms: Server: queries with several replicas: development [#METR-14410]

This commit is contained in:
Alexey Arno 2015-01-21 03:09:14 +03:00
parent e723ad675c
commit fbee36d6a8
4 changed files with 195 additions and 0 deletions

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@ -6,11 +6,14 @@
namespace DB
{
class PartsWithRangesSplitter;
/** Выполняет запросы SELECT на данных из merge-дерева.
*/
class MergeTreeDataSelectExecutor
{
friend class PartsWithRangesSplitter;
public:
MergeTreeDataSelectExecutor(MergeTreeData & data_);

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@ -0,0 +1,61 @@
#include <DB/Storages/MergeTree/MergeTreeDataSelectExecutor.h>
namespace DB
{
/// Разбиваем parts_with_ranges на n частей.
/// Следующие условия должны быть выполнены:
/// - 1 <= n <= settings.max_clusters_count;
/// - каждая из n частей имеет >= min_cluster_size записей.
/// 3 levels: cluster / part / range
class PartsWithRangesSplitter
{
public:
typedef MergeTreeDataSelectExecutor::RangesInDataParts Cluster;
public:
PartsWithRangesSplitter(const Cluster & input_cluster_,
size_t total_size_, size_t min_cluster_size_, size_t max_clusters_count_);
~PartsWithRangesSplitter() = default;
PartsWithRangesSplitter(const PartsWithRangesSplitter &) = delete;
PartsWithRangesSplitter & operator=(const PartsWithRangesSplitter &) = delete;
std::vector<Cluster> perform();
private:
void init();
bool emit();
bool updateCluster();
bool updateRange(bool add_part);
void addPart();
void initRangeInfo();
void initClusterInfo();
bool isRangeConsumed() const { return range_begin == range_end; }
bool isClusterConsumed() const { return cluster_begin == cluster_end; }
private:
// Input data.
const Cluster & input_cluster;
Cluster::const_iterator input_part;
std::vector<MarkRange>::const_iterator input_range;
// Output data.
std::vector<Cluster> output_clusters;
std::vector<Cluster>::iterator current_output_cluster;
MergeTreeDataSelectExecutor::RangesInDataPart * current_output_part;
size_t total_size;
size_t remaining_size;
size_t min_cluster_size;
size_t max_clusters_count;
size_t cluster_size;
size_t range_begin;
size_t range_end;
size_t cluster_begin;
size_t cluster_end;
};
}

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@ -1,5 +1,6 @@
#include <DB/Storages/MergeTree/MergeTreeDataSelectExecutor.h>
#include <DB/Storages/MergeTree/MergeTreeWhereOptimizer.h>
#include <DB/Storages/MergeTree/PartsWithRangesSplitter.h>
#include <DB/Interpreters/ExpressionAnalyzer.h>
#include <DB/Parsers/ASTIdentifier.h>
#include <DB/DataStreams/ExpressionBlockInputStream.h>
@ -226,6 +227,18 @@ BlockInputStreams MergeTreeDataSelectExecutor::read(
}
}
if (settings.parallel_replicas_count > 0)
{
PartsWithRangesSplitter splitter(parts_with_ranges, sum_marks, data.settings.min_rows_for_seek,
settings.parallel_replicas_count);
auto per_replica_parts_with_ranges = splitter.perform();
/// Для каждого элемента per_replica_parts_with_ranges[k], вычисляем хэш от RangesInDataParts
/// Сортируем per_replica_parts_with_ranges по хэшу
/// Выбираем per_replica_parts_with_ranges[settings.parallel_replica_offset]
/// Если settings.parallel_replica_offset > (n - 1), то ничего не делаем.
}
LOG_DEBUG(log, "Selected " << parts.size() << " parts by date, " << parts_with_ranges.size() << " parts by key, "
<< sum_marks << " marks to read from " << sum_ranges << " ranges");

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@ -0,0 +1,118 @@
#include <DB/Storages/MergeTree/PartsWithRangesSplitter.h>
namespace DB
{
PartsWithRangesSplitter::PartsWithRangesSplitter(const Cluster & input_cluster_,
size_t total_size_, size_t min_cluster_size_, size_t max_clusters_count_)
: input_cluster(input_cluster_),
total_size(total_size_),
remaining_size(total_size_),
min_cluster_size(min_cluster_size_),
max_clusters_count(max_clusters_count_)
{
}
std::vector<PartsWithRangesSplitter::Cluster> PartsWithRangesSplitter::perform()
{
init();
while (emit()) {}
return output_clusters;
}
void PartsWithRangesSplitter::init()
{
size_t clusters_count = max_clusters_count;
while ((clusters_count > 0) && (total_size < (min_cluster_size * clusters_count)))
--clusters_count;
cluster_size = total_size / clusters_count;
output_clusters.resize(clusters_count);
// Initialize range reader.
input_part = input_cluster.begin();
input_range = input_part->ranges.begin();
initRangeInfo();
// Initialize output writer.
current_output_cluster = output_clusters.begin();
addPart();
initClusterInfo();
}
bool PartsWithRangesSplitter::emit()
{
size_t new_size = std::min(range_end - range_begin, cluster_end - cluster_begin);
current_output_part->ranges.push_back(MarkRange(range_begin, range_begin + new_size));
range_begin += new_size;
cluster_begin += new_size;
if (isClusterConsumed())
return updateCluster();
else if (isRangeConsumed())
return updateRange(true);
else
return false;
}
bool PartsWithRangesSplitter::updateCluster()
{
++current_output_cluster;
if (current_output_cluster == output_clusters.end())
return false;
if (isRangeConsumed())
if (!updateRange(false))
return false;
addPart();
initClusterInfo();
return true;
}
bool PartsWithRangesSplitter::updateRange(bool add_part)
{
++input_range;
if (input_range == input_part->ranges.end())
{
++input_part;
if (input_part == input_cluster.end())
return false;
input_range = input_part->ranges.begin();
if (add_part)
addPart();
}
initRangeInfo();
return true;
}
void PartsWithRangesSplitter::addPart()
{
MergeTreeDataSelectExecutor::RangesInDataPart new_part;
new_part.data_part = input_part->data_part;
current_output_cluster->push_back(new_part);
current_output_part = &(current_output_cluster->back());
}
void PartsWithRangesSplitter::initRangeInfo()
{
range_begin = 0;
range_end = input_range->end - input_range->begin;
}
void PartsWithRangesSplitter::initClusterInfo()
{
cluster_begin = 0;
cluster_end = cluster_size;
remaining_size -= cluster_size;
if (remaining_size < cluster_size)
cluster_end += remaining_size;
}
}