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ClickHouse/src/Storages/MergeTree/MergeTreeDataSelectExecutor.cpp

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#include <boost/rational.hpp> /// For calculations related to sampling coefficients.
#include <optional>
#include <Poco/File.h>
#include <Common/FieldVisitors.h>
#include <Storages/MergeTree/MergeTreeDataSelectExecutor.h>
#include <Storages/MergeTree/MergeTreeSelectProcessor.h>
#include <Storages/MergeTree/MergeTreeReverseSelectProcessor.h>
#include <Storages/MergeTree/MergeTreeReadPool.h>
#include <Storages/MergeTree/MergeTreeThreadSelectBlockInputProcessor.h>
#include <Storages/MergeTree/MergeTreeIndices.h>
#include <Storages/MergeTree/MergeTreeIndexReader.h>
#include <Storages/MergeTree/KeyCondition.h>
#include <Storages/ReadInOrderOptimizer.h>
#include <Parsers/ASTIdentifier.h>
#include <Parsers/ASTLiteral.h>
#include <Parsers/ASTFunction.h>
#include <Parsers/ASTSampleRatio.h>
#include <Interpreters/ExpressionAnalyzer.h>
/// Allow to use __uint128_t as a template parameter for boost::rational.
// https://stackoverflow.com/questions/41198673/uint128-t-not-working-with-clang-and-libstdc
#if !defined(__GLIBCXX_BITSIZE_INT_N_0) && defined(__SIZEOF_INT128__)
namespace std
{
template <>
struct numeric_limits<__uint128_t>
{
static constexpr bool is_specialized = true;
static constexpr bool is_signed = false;
static constexpr bool is_integer = true;
static constexpr int radix = 2;
static constexpr int digits = 128;
static constexpr __uint128_t min () { return 0; } // used in boost 1.65.1+
static constexpr __uint128_t max () { return __uint128_t(0) - 1; } // used in boost 1.68.0+
};
}
#endif
#include <DataStreams/CollapsingFinalBlockInputStream.h>
#include <DataStreams/CreatingSetsBlockInputStream.h>
#include <DataStreams/ReverseBlockInputStream.h>
#include <DataTypes/DataTypeDate.h>
#include <DataTypes/DataTypeEnum.h>
#include <DataTypes/DataTypesNumber.h>
#include <Processors/ConcatProcessor.h>
#include <Processors/Executors/TreeExecutorBlockInputStream.h>
#include <Processors/Merges/AggregatingSortedTransform.h>
#include <Processors/Merges/CollapsingSortedTransform.h>
#include <Processors/Merges/MergingSortedTransform.h>
#include <Processors/Merges/ReplacingSortedTransform.h>
#include <Processors/Merges/SummingSortedTransform.h>
#include <Processors/Merges/VersionedCollapsingTransform.h>
#include <Processors/Sources/SourceFromInputStream.h>
#include <Processors/Transforms/AddingConstColumnTransform.h>
#include <Processors/Transforms/AddingSelectorTransform.h>
#include <Processors/Transforms/CopyTransform.h>
#include <Processors/Transforms/ExpressionTransform.h>
#include <Processors/Transforms/FilterTransform.h>
#include <Processors/Transforms/ReverseTransform.h>
#include <Storages/VirtualColumnUtils.h>
namespace ProfileEvents
{
extern const Event SelectedParts;
extern const Event SelectedRanges;
extern const Event SelectedMarks;
}
namespace DB
{
namespace ErrorCodes
{
extern const int LOGICAL_ERROR;
extern const int INDEX_NOT_USED;
extern const int ILLEGAL_TYPE_OF_COLUMN_FOR_FILTER;
extern const int ILLEGAL_COLUMN;
extern const int ARGUMENT_OUT_OF_BOUND;
}
MergeTreeDataSelectExecutor::MergeTreeDataSelectExecutor(const MergeTreeData & data_)
: data(data_), log(&Logger::get(data.getLogName() + " (SelectExecutor)"))
{
}
/// Construct a block consisting only of possible values of virtual columns
static Block getBlockWithPartColumn(const MergeTreeData::DataPartsVector & parts)
{
auto column = ColumnString::create();
for (const auto & part : parts)
column->insert(part->name);
return Block{ColumnWithTypeAndName(std::move(column), std::make_shared<DataTypeString>(), "_part")};
}
size_t MergeTreeDataSelectExecutor::getApproximateTotalRowsToRead(
const MergeTreeData::DataPartsVector & parts, const KeyCondition & key_condition, const Settings & settings) const
{
size_t rows_count = 0;
/// We will find out how many rows we would have read without sampling.
LOG_DEBUG(log, "Preliminary index scan with condition: " << key_condition.toString());
for (const auto & part : parts)
{
MarkRanges ranges = markRangesFromPKRange(part, key_condition, settings);
/** In order to get a lower bound on the number of rows that match the condition on PK,
* consider only guaranteed full marks.
* That is, do not take into account the first and last marks, which may be incomplete.
*/
for (const auto & range : ranges)
if (range.end - range.begin > 2)
rows_count += part->index_granularity.getRowsCountInRange({range.begin + 1, range.end - 1});
}
return rows_count;
}
using RelativeSize = boost::rational<ASTSampleRatio::BigNum>;
static std::string toString(const RelativeSize & x)
{
return ASTSampleRatio::toString(x.numerator()) + "/" + ASTSampleRatio::toString(x.denominator());
}
/// Converts sample size to an approximate number of rows (ex. `SAMPLE 1000000`) to relative value (ex. `SAMPLE 0.1`).
static RelativeSize convertAbsoluteSampleSizeToRelative(const ASTPtr & node, size_t approx_total_rows)
{
if (approx_total_rows == 0)
return 1;
const auto & node_sample = node->as<ASTSampleRatio &>();
auto absolute_sample_size = node_sample.ratio.numerator / node_sample.ratio.denominator;
return std::min(RelativeSize(1), RelativeSize(absolute_sample_size) / RelativeSize(approx_total_rows));
}
Pipes MergeTreeDataSelectExecutor::read(
const Names & column_names_to_return,
const SelectQueryInfo & query_info,
const Context & context,
const UInt64 max_block_size,
const unsigned num_streams,
const PartitionIdToMaxBlock * max_block_numbers_to_read) const
{
return readFromParts(
data.getDataPartsVector(), column_names_to_return, query_info, context,
max_block_size, num_streams, max_block_numbers_to_read);
}
Pipes MergeTreeDataSelectExecutor::readFromParts(
MergeTreeData::DataPartsVector parts,
const Names & column_names_to_return,
const SelectQueryInfo & query_info,
const Context & context,
const UInt64 max_block_size,
const unsigned num_streams,
const PartitionIdToMaxBlock * max_block_numbers_to_read) const
{
size_t part_index = 0;
/// If query contains restrictions on the virtual column `_part` or `_part_index`, select only parts suitable for it.
/// The virtual column `_sample_factor` (which is equal to 1 / used sample rate) can be requested in the query.
Names virt_column_names;
Names real_column_names;
bool part_column_queried = false;
bool sample_factor_column_queried = false;
Float64 used_sample_factor = 1;
for (const String & name : column_names_to_return)
{
if (name == "_part")
{
part_column_queried = true;
virt_column_names.push_back(name);
}
else if (name == "_part_index")
{
virt_column_names.push_back(name);
}
else if (name == "_partition_id")
{
virt_column_names.push_back(name);
}
else if (name == "_sample_factor")
{
sample_factor_column_queried = true;
virt_column_names.push_back(name);
}
else
{
real_column_names.push_back(name);
}
}
NamesAndTypesList available_real_columns = data.getColumns().getAllPhysical();
/// If there are only virtual columns in the query, you must request at least one non-virtual one.
if (real_column_names.empty())
real_column_names.push_back(ExpressionActions::getSmallestColumn(available_real_columns));
/// If `_part` virtual column is requested, we try to use it as an index.
Block virtual_columns_block = getBlockWithPartColumn(parts);
if (part_column_queried)
VirtualColumnUtils::filterBlockWithQuery(query_info.query, virtual_columns_block, context);
std::multiset<String> part_values = VirtualColumnUtils::extractSingleValueFromBlock<String>(virtual_columns_block, "_part");
data.check(real_column_names);
const Settings & settings = context.getSettingsRef();
Names primary_key_columns = data.primary_key_columns;
KeyCondition key_condition(query_info, context, primary_key_columns, data.primary_key_expr);
if (settings.force_primary_key && key_condition.alwaysUnknownOrTrue())
{
std::stringstream exception_message;
exception_message << "Primary key (";
for (size_t i = 0, size = primary_key_columns.size(); i < size; ++i)
exception_message << (i == 0 ? "" : ", ") << primary_key_columns[i];
exception_message << ") is not used and setting 'force_primary_key' is set.";
throw Exception(exception_message.str(), ErrorCodes::INDEX_NOT_USED);
}
std::optional<KeyCondition> minmax_idx_condition;
if (data.minmax_idx_expr)
{
minmax_idx_condition.emplace(query_info, context, data.minmax_idx_columns, data.minmax_idx_expr);
if (settings.force_index_by_date && minmax_idx_condition->alwaysUnknownOrTrue())
{
String msg = "MinMax index by columns (";
bool first = true;
for (const String & col : data.minmax_idx_columns)
{
if (first)
first = false;
else
msg += ", ";
msg += col;
}
msg += ") is not used and setting 'force_index_by_date' is set";
throw Exception(msg, ErrorCodes::INDEX_NOT_USED);
}
}
/// Select the parts in which there can be data that satisfy `minmax_idx_condition` and that match the condition on `_part`,
/// as well as `max_block_number_to_read`.
{
auto prev_parts = parts;
parts.clear();
for (const auto & part : prev_parts)
{
if (part_values.find(part->name) == part_values.end())
continue;
if (part->isEmpty())
continue;
if (minmax_idx_condition && !minmax_idx_condition->checkInHyperrectangle(
part->minmax_idx.hyperrectangle, data.minmax_idx_column_types).can_be_true)
continue;
if (max_block_numbers_to_read)
{
auto blocks_iterator = max_block_numbers_to_read->find(part->info.partition_id);
if (blocks_iterator == max_block_numbers_to_read->end() || part->info.max_block > blocks_iterator->second)
continue;
}
parts.push_back(part);
}
}
/// Sampling.
Names column_names_to_read = real_column_names;
std::shared_ptr<ASTFunction> filter_function;
ExpressionActionsPtr filter_expression;
RelativeSize relative_sample_size = 0;
RelativeSize relative_sample_offset = 0;
const auto & select = query_info.query->as<ASTSelectQuery &>();
auto select_sample_size = select.sampleSize();
auto select_sample_offset = select.sampleOffset();
if (select_sample_size)
{
relative_sample_size.assign(
select_sample_size->as<ASTSampleRatio &>().ratio.numerator,
select_sample_size->as<ASTSampleRatio &>().ratio.denominator);
if (relative_sample_size < 0)
throw Exception("Negative sample size", ErrorCodes::ARGUMENT_OUT_OF_BOUND);
relative_sample_offset = 0;
if (select_sample_offset)
relative_sample_offset.assign(
select_sample_offset->as<ASTSampleRatio &>().ratio.numerator,
select_sample_offset->as<ASTSampleRatio &>().ratio.denominator);
if (relative_sample_offset < 0)
throw Exception("Negative sample offset", ErrorCodes::ARGUMENT_OUT_OF_BOUND);
/// Convert absolute value of the sampling (in form `SAMPLE 1000000` - how many rows to read) into the relative `SAMPLE 0.1` (how much data to read).
size_t approx_total_rows = 0;
if (relative_sample_size > 1 || relative_sample_offset > 1)
approx_total_rows = getApproximateTotalRowsToRead(parts, key_condition, settings);
if (relative_sample_size > 1)
{
relative_sample_size = convertAbsoluteSampleSizeToRelative(select_sample_size, approx_total_rows);
LOG_DEBUG(log, "Selected relative sample size: " << toString(relative_sample_size));
}
/// SAMPLE 1 is the same as the absence of SAMPLE.
if (relative_sample_size == RelativeSize(1))
relative_sample_size = 0;
if (relative_sample_offset > 0 && RelativeSize(0) == relative_sample_size)
throw Exception("Sampling offset is incorrect because no sampling", ErrorCodes::ARGUMENT_OUT_OF_BOUND);
if (relative_sample_offset > 1)
{
relative_sample_offset = convertAbsoluteSampleSizeToRelative(select_sample_offset, approx_total_rows);
LOG_DEBUG(log, "Selected relative sample offset: " << toString(relative_sample_offset));
}
}
/** Which range of sampling key values do I need to read?
* First, in the whole range ("universe") we select the interval
* of relative `relative_sample_size` size, offset from the beginning by `relative_sample_offset`.
*
* Example: SAMPLE 0.4 OFFSET 0.3
*
* [------********------]
* ^ - offset
* <------> - size
*
* If the interval passes through the end of the universe, then cut its right side.
*
* Example: SAMPLE 0.4 OFFSET 0.8
*
* [----------------****]
* ^ - offset
* <------> - size
*
* Next, if the `parallel_replicas_count`, `parallel_replica_offset` settings are set,
* then it is necessary to break the received interval into pieces of the number `parallel_replicas_count`,
* and select a piece with the number `parallel_replica_offset` (from zero).
*
* Example: SAMPLE 0.4 OFFSET 0.3, parallel_replicas_count = 2, parallel_replica_offset = 1
*
* [----------****------]
* ^ - offset
* <------> - size
* <--><--> - pieces for different `parallel_replica_offset`, select the second one.
*
* It is very important that the intervals for different `parallel_replica_offset` cover the entire range without gaps and overlaps.
* It is also important that the entire universe can be covered using SAMPLE 0.1 OFFSET 0, ... OFFSET 0.9 and similar decimals.
*/
bool use_sampling = relative_sample_size > 0 || (settings.parallel_replicas_count > 1 && data.supportsSampling());
bool no_data = false; /// There is nothing left after sampling.
if (use_sampling)
{
if (sample_factor_column_queried && relative_sample_size != RelativeSize(0))
used_sample_factor = 1.0 / boost::rational_cast<Float64>(relative_sample_size);
RelativeSize size_of_universum = 0;
DataTypePtr sampling_column_type = data.primary_key_sample.getByName(data.sampling_expr_column_name).type;
if (typeid_cast<const DataTypeUInt64 *>(sampling_column_type.get()))
size_of_universum = RelativeSize(std::numeric_limits<UInt64>::max()) + RelativeSize(1);
else if (typeid_cast<const DataTypeUInt32 *>(sampling_column_type.get()))
size_of_universum = RelativeSize(std::numeric_limits<UInt32>::max()) + RelativeSize(1);
else if (typeid_cast<const DataTypeUInt16 *>(sampling_column_type.get()))
size_of_universum = RelativeSize(std::numeric_limits<UInt16>::max()) + RelativeSize(1);
else if (typeid_cast<const DataTypeUInt8 *>(sampling_column_type.get()))
size_of_universum = RelativeSize(std::numeric_limits<UInt8>::max()) + RelativeSize(1);
else
throw Exception("Invalid sampling column type in storage parameters: " + sampling_column_type->getName() + ". Must be unsigned integer type.",
ErrorCodes::ILLEGAL_TYPE_OF_COLUMN_FOR_FILTER);
if (settings.parallel_replicas_count > 1)
{
if (relative_sample_size == RelativeSize(0))
relative_sample_size = 1;
relative_sample_size /= settings.parallel_replicas_count.value;
relative_sample_offset += relative_sample_size * RelativeSize(settings.parallel_replica_offset.value);
}
if (relative_sample_offset >= RelativeSize(1))
no_data = true;
/// Calculate the half-interval of `[lower, upper)` column values.
bool has_lower_limit = false;
bool has_upper_limit = false;
RelativeSize lower_limit_rational = relative_sample_offset * size_of_universum;
RelativeSize upper_limit_rational = (relative_sample_offset + relative_sample_size) * size_of_universum;
UInt64 lower = boost::rational_cast<ASTSampleRatio::BigNum>(lower_limit_rational);
UInt64 upper = boost::rational_cast<ASTSampleRatio::BigNum>(upper_limit_rational);
if (lower > 0)
has_lower_limit = true;
if (upper_limit_rational < size_of_universum)
has_upper_limit = true;
/*std::cerr << std::fixed << std::setprecision(100)
<< "relative_sample_size: " << relative_sample_size << "\n"
<< "relative_sample_offset: " << relative_sample_offset << "\n"
<< "lower_limit_float: " << lower_limit_rational << "\n"
<< "upper_limit_float: " << upper_limit_rational << "\n"
<< "lower: " << lower << "\n"
<< "upper: " << upper << "\n";*/
if ((has_upper_limit && upper == 0)
|| (has_lower_limit && has_upper_limit && lower == upper))
no_data = true;
if (no_data || (!has_lower_limit && !has_upper_limit))
{
use_sampling = false;
}
else
{
/// Let's add the conditions to cut off something else when the index is scanned again and when the request is processed.
std::shared_ptr<ASTFunction> lower_function;
std::shared_ptr<ASTFunction> upper_function;
/// If sample and final are used together no need to calculate sampling expression twice.
/// The first time it was calculated for final, because sample key is a part of the PK.
/// So, assume that we already have calculated column.
ASTPtr sampling_key_ast = data.getSamplingKeyAST();
if (select.final())
{
sampling_key_ast = std::make_shared<ASTIdentifier>(data.sampling_expr_column_name);
/// We do spoil available_real_columns here, but it is not used later.
available_real_columns.emplace_back(data.sampling_expr_column_name, std::move(sampling_column_type));
}
if (has_lower_limit)
{
if (!key_condition.addCondition(data.sampling_expr_column_name, Range::createLeftBounded(lower, true)))
throw Exception("Sampling column not in primary key", ErrorCodes::ILLEGAL_COLUMN);
ASTPtr args = std::make_shared<ASTExpressionList>();
args->children.push_back(sampling_key_ast);
args->children.push_back(std::make_shared<ASTLiteral>(lower));
lower_function = std::make_shared<ASTFunction>();
lower_function->name = "greaterOrEquals";
lower_function->arguments = args;
lower_function->children.push_back(lower_function->arguments);
filter_function = lower_function;
}
if (has_upper_limit)
{
if (!key_condition.addCondition(data.sampling_expr_column_name, Range::createRightBounded(upper, false)))
throw Exception("Sampling column not in primary key", ErrorCodes::ILLEGAL_COLUMN);
ASTPtr args = std::make_shared<ASTExpressionList>();
args->children.push_back(sampling_key_ast);
args->children.push_back(std::make_shared<ASTLiteral>(upper));
upper_function = std::make_shared<ASTFunction>();
upper_function->name = "less";
upper_function->arguments = args;
upper_function->children.push_back(upper_function->arguments);
filter_function = upper_function;
}
if (has_lower_limit && has_upper_limit)
{
ASTPtr args = std::make_shared<ASTExpressionList>();
args->children.push_back(lower_function);
args->children.push_back(upper_function);
filter_function = std::make_shared<ASTFunction>();
filter_function->name = "and";
filter_function->arguments = args;
filter_function->children.push_back(filter_function->arguments);
}
ASTPtr query = filter_function;
auto syntax_result = SyntaxAnalyzer(context).analyze(query, available_real_columns);
filter_expression = ExpressionAnalyzer(filter_function, syntax_result, context).getActions(false);
if (!select.final())
{
/// Add columns needed for `sample_by_ast` to `column_names_to_read`.
/// Skip this if final was used, because such columns were already added from PK.
std::vector<String> add_columns = filter_expression->getRequiredColumns();
column_names_to_read.insert(column_names_to_read.end(), add_columns.begin(), add_columns.end());
std::sort(column_names_to_read.begin(), column_names_to_read.end());
column_names_to_read.erase(std::unique(column_names_to_read.begin(), column_names_to_read.end()),
column_names_to_read.end());
}
}
}
if (no_data)
{
LOG_DEBUG(log, "Sampling yields no data.");
return {};
}
LOG_DEBUG(log, "Key condition: " << key_condition.toString());
if (minmax_idx_condition)
LOG_DEBUG(log, "MinMax index condition: " << minmax_idx_condition->toString());
/// PREWHERE
String prewhere_column;
if (select.prewhere())
prewhere_column = select.prewhere()->getColumnName();
RangesInDataParts parts_with_ranges;
std::vector<std::pair<MergeTreeIndexPtr, MergeTreeIndexConditionPtr>> useful_indices;
for (const auto & index : data.skip_indices)
{
auto condition = index->createIndexCondition(query_info, context);
if (!condition->alwaysUnknownOrTrue())
useful_indices.emplace_back(index, condition);
}
/// Let's find what range to read from each part.
size_t sum_marks = 0;
size_t sum_ranges = 0;
for (auto & part : parts)
{
RangesInDataPart ranges(part, part_index++);
if (data.hasPrimaryKey())
ranges.ranges = markRangesFromPKRange(part, key_condition, settings);
else
{
size_t total_marks_count = part->getMarksCount();
if (total_marks_count)
{
if (part->index_granularity.hasFinalMark())
--total_marks_count;
ranges.ranges = MarkRanges{MarkRange{0, total_marks_count}};
}
}
for (const auto & index_and_condition : useful_indices)
ranges.ranges = filterMarksUsingIndex(
index_and_condition.first, index_and_condition.second, part, ranges.ranges, settings);
if (!ranges.ranges.empty())
{
parts_with_ranges.push_back(ranges);
sum_ranges += ranges.ranges.size();
sum_marks += ranges.getMarksCount();
}
}
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");
if (parts_with_ranges.empty())
return {};
ProfileEvents::increment(ProfileEvents::SelectedParts, parts_with_ranges.size());
ProfileEvents::increment(ProfileEvents::SelectedRanges, sum_ranges);
ProfileEvents::increment(ProfileEvents::SelectedMarks, sum_marks);
Pipes res;
MergeTreeReaderSettings reader_settings =
{
.min_bytes_to_use_direct_io = settings.min_bytes_to_use_direct_io,
.max_read_buffer_size = settings.max_read_buffer_size,
.save_marks_in_cache = true
};
/// Projection, that needed to drop columns, which have appeared by execution
/// of some extra expressions, and to allow execute the same expressions later.
/// NOTE: It may lead to double computation of expressions.
ExpressionActionsPtr result_projection;
if (select.final())
{
/// Add columns needed to calculate the sorting expression and the sign.
std::vector<String> add_columns = data.sorting_key_expr->getRequiredColumns();
column_names_to_read.insert(column_names_to_read.end(), add_columns.begin(), add_columns.end());
if (!data.merging_params.sign_column.empty())
column_names_to_read.push_back(data.merging_params.sign_column);
if (!data.merging_params.version_column.empty())
column_names_to_read.push_back(data.merging_params.version_column);
std::sort(column_names_to_read.begin(), column_names_to_read.end());
column_names_to_read.erase(std::unique(column_names_to_read.begin(), column_names_to_read.end()), column_names_to_read.end());
res = spreadMarkRangesAmongStreamsFinal(
std::move(parts_with_ranges),
num_streams,
column_names_to_read,
max_block_size,
settings.use_uncompressed_cache,
query_info,
virt_column_names,
settings,
reader_settings,
result_projection);
}
else if (settings.optimize_read_in_order && query_info.input_sorting_info)
{
size_t prefix_size = query_info.input_sorting_info->order_key_prefix_descr.size();
auto order_key_prefix_ast = data.sorting_key_expr_ast->clone();
order_key_prefix_ast->children.resize(prefix_size);
auto syntax_result = SyntaxAnalyzer(context).analyze(order_key_prefix_ast, data.getColumns().getAllPhysical());
auto sorting_key_prefix_expr = ExpressionAnalyzer(order_key_prefix_ast, syntax_result, context).getActions(false);
res = spreadMarkRangesAmongStreamsWithOrder(
std::move(parts_with_ranges),
num_streams,
column_names_to_read,
max_block_size,
settings.use_uncompressed_cache,
query_info,
sorting_key_prefix_expr,
virt_column_names,
settings,
reader_settings,
result_projection);
}
else
{
res = spreadMarkRangesAmongStreams(
std::move(parts_with_ranges),
num_streams,
column_names_to_read,
max_block_size,
settings.use_uncompressed_cache,
query_info,
virt_column_names,
settings,
reader_settings);
}
if (use_sampling)
{
for (auto & pipe : res)
pipe.addSimpleTransform(std::make_shared<FilterTransform>(
pipe.getHeader(), filter_expression, filter_function->getColumnName(), false));
}
if (result_projection)
{
for (auto & pipe : res)
pipe.addSimpleTransform(std::make_shared<ExpressionTransform>(
pipe.getHeader(), result_projection));
}
/// By the way, if a distributed query or query to a Merge table is made, then the `_sample_factor` column can have different values.
if (sample_factor_column_queried)
{
for (auto & pipe : res)
pipe.addSimpleTransform(std::make_shared<AddingConstColumnTransform<Float64>>(
pipe.getHeader(), std::make_shared<DataTypeFloat64>(), used_sample_factor, "_sample_factor"));
}
if (query_info.prewhere_info && query_info.prewhere_info->remove_columns_actions)
{
for (auto & pipe : res)
pipe.addSimpleTransform(std::make_shared<ExpressionTransform>(
pipe.getHeader(), query_info.prewhere_info->remove_columns_actions));
}
return res;
}
namespace
{
size_t roundRowsOrBytesToMarks(
size_t rows_setting,
size_t bytes_setting,
size_t rows_granularity,
size_t bytes_granularity)
{
if (bytes_granularity == 0)
return (rows_setting + rows_granularity - 1) / rows_granularity;
else
return (bytes_setting + bytes_granularity - 1) / bytes_granularity;
}
}
Pipes MergeTreeDataSelectExecutor::spreadMarkRangesAmongStreams(
RangesInDataParts && parts,
size_t num_streams,
const Names & column_names,
UInt64 max_block_size,
bool use_uncompressed_cache,
const SelectQueryInfo & query_info,
const Names & virt_columns,
const Settings & settings,
const MergeTreeReaderSettings & reader_settings) const
{
/// Count marks for each part.
std::vector<size_t> sum_marks_in_parts(parts.size());
size_t sum_marks = 0;
size_t total_rows = 0;
const auto data_settings = data.getSettings();
size_t adaptive_parts = 0;
for (size_t i = 0; i < parts.size(); ++i)
{
total_rows += parts[i].getRowsCount();
sum_marks_in_parts[i] = parts[i].getMarksCount();
sum_marks += sum_marks_in_parts[i];
if (parts[i].data_part->index_granularity_info.is_adaptive)
adaptive_parts++;
}
size_t index_granularity_bytes = 0;
if (adaptive_parts > parts.size() / 2)
index_granularity_bytes = data_settings->index_granularity_bytes;
const size_t max_marks_to_use_cache = roundRowsOrBytesToMarks(
settings.merge_tree_max_rows_to_use_cache,
settings.merge_tree_max_bytes_to_use_cache,
data_settings->index_granularity,
index_granularity_bytes);
const size_t min_marks_for_concurrent_read = roundRowsOrBytesToMarks(
settings.merge_tree_min_rows_for_concurrent_read,
settings.merge_tree_min_bytes_for_concurrent_read,
data_settings->index_granularity,
index_granularity_bytes);
if (sum_marks > max_marks_to_use_cache)
use_uncompressed_cache = false;
Pipes res;
if (0 == sum_marks)
return res;
if (num_streams > 1)
{
/// Parallel query execution.
/// Reduce the number of num_streams if the data is small.
if (sum_marks < num_streams * min_marks_for_concurrent_read && parts.size() < num_streams)
num_streams = std::max((sum_marks + min_marks_for_concurrent_read - 1) / min_marks_for_concurrent_read, parts.size());
MergeTreeReadPoolPtr pool = std::make_shared<MergeTreeReadPool>(
num_streams, sum_marks, min_marks_for_concurrent_read, parts, data, query_info.prewhere_info, true,
column_names, MergeTreeReadPool::BackoffSettings(settings), settings.preferred_block_size_bytes, false);
/// Let's estimate total number of rows for progress bar.
LOG_TRACE(log, "Reading approx. " << total_rows << " rows with " << num_streams << " streams");
for (size_t i = 0; i < num_streams; ++i)
{
auto source = std::make_shared<MergeTreeThreadSelectBlockInputProcessor>(
i, pool, min_marks_for_concurrent_read, max_block_size, settings.preferred_block_size_bytes,
settings.preferred_max_column_in_block_size_bytes, data, use_uncompressed_cache,
query_info.prewhere_info, reader_settings, virt_columns);
if (i == 0)
{
/// Set the approximate number of rows for the first source only
source->addTotalRowsApprox(total_rows);
}
res.emplace_back(std::move(source));
}
}
else
{
/// Sequential query execution.
for (const auto & part : parts)
{
auto source = std::make_shared<MergeTreeSelectProcessor>(
data, part.data_part, max_block_size, settings.preferred_block_size_bytes,
settings.preferred_max_column_in_block_size_bytes, column_names, part.ranges, use_uncompressed_cache,
query_info.prewhere_info, true, reader_settings, virt_columns, part.part_index_in_query);
res.emplace_back(std::move(source));
}
/// Use ConcatProcessor to concat sources together.
/// It is needed to read in parts order (and so in PK order) if single thread is used.
if (res.size() > 1)
{
auto concat = std::make_shared<ConcatProcessor>(res.front().getHeader(), res.size());
Pipe pipe(std::move(res), std::move(concat));
res = Pipes();
res.emplace_back(std::move(pipe));
}
}
return res;
}
static ExpressionActionsPtr createProjection(const Pipe & pipe, const MergeTreeData & data)
{
const auto & header = pipe.getHeader();
auto projection = std::make_shared<ExpressionActions>(header.getNamesAndTypesList(), data.global_context);
projection->add(ExpressionAction::project(header.getNames()));
return projection;
}
Pipes MergeTreeDataSelectExecutor::spreadMarkRangesAmongStreamsWithOrder(
RangesInDataParts && parts,
size_t num_streams,
const Names & column_names,
UInt64 max_block_size,
bool use_uncompressed_cache,
const SelectQueryInfo & query_info,
const ExpressionActionsPtr & sorting_key_prefix_expr,
const Names & virt_columns,
const Settings & settings,
const MergeTreeReaderSettings & reader_settings,
ExpressionActionsPtr & out_projection) const
{
size_t sum_marks = 0;
const InputSortingInfoPtr & input_sorting_info = query_info.input_sorting_info;
size_t adaptive_parts = 0;
std::vector<size_t> sum_marks_in_parts(parts.size());
const auto data_settings = data.getSettings();
for (size_t i = 0; i < parts.size(); ++i)
{
sum_marks_in_parts[i] = parts[i].getMarksCount();
sum_marks += sum_marks_in_parts[i];
if (parts[i].data_part->index_granularity_info.is_adaptive)
adaptive_parts++;
}
size_t index_granularity_bytes = 0;
if (adaptive_parts > parts.size() / 2)
index_granularity_bytes = data_settings->index_granularity_bytes;
const size_t max_marks_to_use_cache = roundRowsOrBytesToMarks(
settings.merge_tree_max_rows_to_use_cache,
settings.merge_tree_max_bytes_to_use_cache,
data_settings->index_granularity,
index_granularity_bytes);
const size_t min_marks_for_concurrent_read = roundRowsOrBytesToMarks(
settings.merge_tree_min_rows_for_concurrent_read,
settings.merge_tree_min_bytes_for_concurrent_read,
data_settings->index_granularity,
index_granularity_bytes);
if (sum_marks > max_marks_to_use_cache)
use_uncompressed_cache = false;
Pipes res;
if (sum_marks == 0)
return res;
/// Let's split ranges to avoid reading much data.
auto split_ranges = [rows_granularity = data_settings->index_granularity, max_block_size](const auto & ranges, int direction)
{
MarkRanges new_ranges;
const size_t max_marks_in_range = (max_block_size + rows_granularity - 1) / rows_granularity;
size_t marks_in_range = 1;
if (direction == 1)
{
/// Split first few ranges to avoid reading much data.
bool splitted = false;
for (auto range : ranges)
{
while (!splitted && range.begin + marks_in_range < range.end)
{
new_ranges.emplace_back(range.begin, range.begin + marks_in_range);
range.begin += marks_in_range;
marks_in_range *= 2;
if (marks_in_range > max_marks_in_range)
splitted = true;
}
new_ranges.emplace_back(range.begin, range.end);
}
}
else
{
/// Split all ranges to avoid reading much data, because we have to
/// store whole range in memory to reverse it.
for (auto it = ranges.rbegin(); it != ranges.rend(); ++it)
{
auto range = *it;
while (range.begin + marks_in_range < range.end)
{
new_ranges.emplace_front(range.end - marks_in_range, range.end);
range.end -= marks_in_range;
marks_in_range = std::min(marks_in_range * 2, max_marks_in_range);
}
new_ranges.emplace_front(range.begin, range.end);
}
}
return new_ranges;
};
const size_t min_marks_per_stream = (sum_marks - 1) / num_streams + 1;
for (size_t i = 0; i < num_streams && !parts.empty(); ++i)
{
size_t need_marks = min_marks_per_stream;
Pipes pipes;
/// Loop over parts.
/// We will iteratively take part or some subrange of a part from the back
/// and assign a stream to read from it.
while (need_marks > 0 && !parts.empty())
{
RangesInDataPart part = parts.back();
parts.pop_back();
size_t & marks_in_part = sum_marks_in_parts.back();
/// We will not take too few rows from a part.
if (marks_in_part >= min_marks_for_concurrent_read &&
need_marks < min_marks_for_concurrent_read)
need_marks = min_marks_for_concurrent_read;
/// Do not leave too few rows in the part.
if (marks_in_part > need_marks &&
marks_in_part - need_marks < min_marks_for_concurrent_read)
need_marks = marks_in_part;
MarkRanges ranges_to_get_from_part;
/// We take the whole part if it is small enough.
if (marks_in_part <= need_marks)
{
ranges_to_get_from_part = part.ranges;
need_marks -= marks_in_part;
sum_marks_in_parts.pop_back();
}
else
{
/// Loop through ranges in part. Take enough ranges to cover "need_marks".
while (need_marks > 0)
{
if (part.ranges.empty())
throw Exception("Unexpected end of ranges while spreading marks among streams", ErrorCodes::LOGICAL_ERROR);
MarkRange & range = part.ranges.front();
const size_t marks_in_range = range.end - range.begin;
const size_t marks_to_get_from_range = std::min(marks_in_range, need_marks);
ranges_to_get_from_part.emplace_back(range.begin, range.begin + marks_to_get_from_range);
range.begin += marks_to_get_from_range;
marks_in_part -= marks_to_get_from_range;
need_marks -= marks_to_get_from_range;
if (range.begin == range.end)
part.ranges.pop_front();
}
parts.emplace_back(part);
}
ranges_to_get_from_part = split_ranges(ranges_to_get_from_part, input_sorting_info->direction);
if (input_sorting_info->direction == 1)
{
pipes.emplace_back(std::make_shared<MergeTreeSelectProcessor>(
data, part.data_part, max_block_size, settings.preferred_block_size_bytes,
settings.preferred_max_column_in_block_size_bytes, column_names, ranges_to_get_from_part,
use_uncompressed_cache, query_info.prewhere_info, true, reader_settings,
virt_columns, part.part_index_in_query));
}
else
{
pipes.emplace_back(std::make_shared<MergeTreeReverseSelectProcessor>(
data, part.data_part, max_block_size, settings.preferred_block_size_bytes,
settings.preferred_max_column_in_block_size_bytes, column_names, ranges_to_get_from_part,
use_uncompressed_cache, query_info.prewhere_info, true, reader_settings,
virt_columns, part.part_index_in_query));
pipes.back().addSimpleTransform(std::make_shared<ReverseTransform>(pipes.back().getHeader()));
}
}
if (pipes.size() > 1)
{
SortDescription sort_description;
for (size_t j = 0; j < input_sorting_info->order_key_prefix_descr.size(); ++j)
sort_description.emplace_back(data.sorting_key_columns[j],
input_sorting_info->direction, 1);
/// Drop temporary columns, added by 'sorting_key_prefix_expr'
out_projection = createProjection(pipes.back(), data);
for (auto & pipe : pipes)
pipe.addSimpleTransform(std::make_shared<ExpressionTransform>(pipe.getHeader(), sorting_key_prefix_expr));
auto merging_sorted = std::make_shared<MergingSortedTransform>(
pipes.back().getHeader(), pipes.size(), sort_description, max_block_size);
res.emplace_back(std::move(pipes), std::move(merging_sorted));
}
else
res.emplace_back(std::move(pipes.front()));
}
return res;
}
Pipes MergeTreeDataSelectExecutor::spreadMarkRangesAmongStreamsFinal(
RangesInDataParts && parts,
size_t num_streams,
const Names & column_names,
UInt64 max_block_size,
bool use_uncompressed_cache,
const SelectQueryInfo & query_info,
const Names & virt_columns,
const Settings & settings,
const MergeTreeReaderSettings & reader_settings,
ExpressionActionsPtr & out_projection) const
{
const auto data_settings = data.getSettings();
size_t sum_marks = 0;
size_t adaptive_parts = 0;
for (const auto & part : parts)
{
for (const auto & range : part.ranges)
sum_marks += range.end - range.begin;
if (part.data_part->index_granularity_info.is_adaptive)
++adaptive_parts;
}
size_t index_granularity_bytes = 0;
if (adaptive_parts >= parts.size() / 2)
index_granularity_bytes = data_settings->index_granularity_bytes;
const size_t max_marks_to_use_cache = roundRowsOrBytesToMarks(
settings.merge_tree_max_rows_to_use_cache,
settings.merge_tree_max_bytes_to_use_cache,
data_settings->index_granularity,
index_granularity_bytes);
if (sum_marks > max_marks_to_use_cache)
use_uncompressed_cache = false;
Pipes pipes;
for (const auto & part : parts)
{
auto source_processor = std::make_shared<MergeTreeSelectProcessor>(
data, part.data_part, max_block_size, settings.preferred_block_size_bytes,
settings.preferred_max_column_in_block_size_bytes, column_names, part.ranges, use_uncompressed_cache,
query_info.prewhere_info, true, reader_settings,
virt_columns, part.part_index_in_query);
Pipe pipe(std::move(source_processor));
/// Drop temporary columns, added by 'sorting_key_expr'
if (!out_projection)
out_projection = createProjection(pipe, data);
pipe.addSimpleTransform(std::make_shared<ExpressionTransform>(pipe.getHeader(), data.sorting_key_expr));
pipes.emplace_back(std::move(pipe));
}
Names sort_columns = data.sorting_key_columns;
SortDescription sort_description;
size_t sort_columns_size = sort_columns.size();
sort_description.reserve(sort_columns_size);
Block header = pipes.at(0).getHeader();
for (size_t i = 0; i < sort_columns_size; ++i)
sort_description.emplace_back(header.getPositionByName(sort_columns[i]), 1, 1);
auto get_merging_processor = [&]() -> MergingTransformPtr
{
switch (data.merging_params.mode)
{
case MergeTreeData::MergingParams::Ordinary:
{
return std::make_shared<MergingSortedTransform>(header, pipes.size(),
sort_description, max_block_size);
}
case MergeTreeData::MergingParams::Collapsing:
return std::make_shared<CollapsingSortedTransform>(header, pipes.size(),
sort_description, data.merging_params.sign_column, true, max_block_size);
case MergeTreeData::MergingParams::Summing:
return std::make_shared<SummingSortedTransform>(header, pipes.size(),
sort_description, data.merging_params.columns_to_sum, max_block_size);
case MergeTreeData::MergingParams::Aggregating:
return std::make_shared<AggregatingSortedTransform>(header, pipes.size(),
sort_description, max_block_size);
case MergeTreeData::MergingParams::Replacing:
return std::make_shared<ReplacingSortedTransform>(header, pipes.size(),
sort_description, data.merging_params.version_column, max_block_size);
case MergeTreeData::MergingParams::VersionedCollapsing:
return std::make_shared<VersionedCollapsingTransform>(header, pipes.size(),
sort_description, data.merging_params.sign_column, max_block_size);
case MergeTreeData::MergingParams::Graphite:
throw Exception("GraphiteMergeTree doesn't support FINAL", ErrorCodes::LOGICAL_ERROR);
}
__builtin_unreachable();
};
if (num_streams > settings.max_final_threads)
num_streams = settings.max_final_threads;
if (num_streams <= 1 || sort_description.empty() || query_info.force_tree_shaped_pipeline)
{
Pipe pipe(std::move(pipes), get_merging_processor());
pipes = Pipes();
pipes.emplace_back(std::move(pipe));
return pipes;
}
ColumnNumbers key_columns;
key_columns.reserve(sort_description.size());
for (auto & desc : sort_description)
{
if (!desc.column_name.empty())
key_columns.push_back(header.getPositionByName(desc.column_name));
else
key_columns.emplace_back(desc.column_number);
}
Processors selectors;
Processors copiers;
selectors.reserve(pipes.size());
for (auto & pipe : pipes)
{
auto selector = std::make_shared<AddingSelectorTransform>(pipe.getHeader(), num_streams, key_columns);
auto copier = std::make_shared<CopyTransform>(pipe.getHeader(), num_streams);
connect(pipe.getPort(), selector->getInputPort());
connect(selector->getOutputPort(), copier->getInputPort());
selectors.emplace_back(std::move(selector));
copiers.emplace_back(std::move(copier));
}
Processors merges;
std::vector<InputPorts::iterator> input_ports;
merges.reserve(num_streams);
input_ports.reserve(num_streams);
for (size_t i = 0; i < num_streams; ++i)
{
auto merge = get_merging_processor();
merge->setSelectorPosition(i);
input_ports.emplace_back(merge->getInputs().begin());
merges.emplace_back(std::move(merge));
}
/// Connect outputs of i-th splitter with i-th input port of every merge.
for (auto & resize : copiers)
{
size_t input_num = 0;
for (auto & output : resize->getOutputs())
{
connect(output, *input_ports[input_num]);
++input_ports[input_num];
++input_num;
}
}
Processors processors;
for (auto & pipe : pipes)
{
auto pipe_processors = std::move(pipe).detachProcessors();
processors.insert(processors.end(), pipe_processors.begin(), pipe_processors.end());
}
pipes.clear();
pipes.reserve(num_streams);
for (auto & merge : merges)
pipes.emplace_back(&merge->getOutputs().front());
pipes.front().addProcessors(processors);
pipes.front().addProcessors(selectors);
pipes.front().addProcessors(copiers);
pipes.front().addProcessors(merges);
return pipes;
}
void MergeTreeDataSelectExecutor::createPositiveSignCondition(
ExpressionActionsPtr & out_expression, String & out_column, const Context & context) const
{
auto function = std::make_shared<ASTFunction>();
auto arguments = std::make_shared<ASTExpressionList>();
auto sign = std::make_shared<ASTIdentifier>(data.merging_params.sign_column);
auto one = std::make_shared<ASTLiteral>(1);
function->name = "equals";
function->arguments = arguments;
function->children.push_back(arguments);
arguments->children.push_back(sign);
arguments->children.push_back(one);
ASTPtr query = function;
auto syntax_result = SyntaxAnalyzer(context).analyze(query, data.getColumns().getAllPhysical());
out_expression = ExpressionAnalyzer(query, syntax_result, context).getActions(false);
out_column = function->getColumnName();
}
/// Calculates a set of mark ranges, that could possibly contain keys, required by condition.
/// In other words, it removes subranges from whole range, that definitely could not contain required keys.
MarkRanges MergeTreeDataSelectExecutor::markRangesFromPKRange(
const MergeTreeData::DataPartPtr & part, const KeyCondition & key_condition, const Settings & settings) const
{
MarkRanges res;
size_t marks_count = part->index_granularity.getMarksCount();
const auto & index = part->index;
if (marks_count == 0)
return res;
bool has_final_mark = part->index_granularity.hasFinalMark();
/// If index is not used.
if (key_condition.alwaysUnknownOrTrue())
{
if (has_final_mark)
res.push_back(MarkRange(0, marks_count - 1));
else
res.push_back(MarkRange(0, marks_count));
}
else
{
size_t used_key_size = key_condition.getMaxKeyColumn() + 1;
size_t min_marks_for_seek = roundRowsOrBytesToMarks(
settings.merge_tree_min_rows_for_seek,
settings.merge_tree_min_bytes_for_seek,
part->index_granularity_info.fixed_index_granularity,
part->index_granularity_info.index_granularity_bytes);
/** There will always be disjoint suspicious segments on the stack, the leftmost one at the top (back).
* At each step, take the left segment and check if it fits.
* If fits, split it into smaller ones and put them on the stack. If not, discard it.
* If the segment is already of one mark length, add it to response and discard it.
*/
std::vector<MarkRange> ranges_stack = { {0, marks_count} };
std::function<void(size_t, size_t, FieldRef &)> create_field_ref;
/// If there are no monotonic functions, there is no need to save block reference.
/// Passing explicit field to FieldRef allows to optimize ranges and shows better performance.
if (key_condition.hasMonotonicFunctionsChain())
{
auto index_block = std::make_shared<Block>();
for (size_t i = 0; i < used_key_size; ++i)
index_block->insert({index[i], data.primary_key_data_types[i], data.primary_key_columns[i]});
create_field_ref = [index_block](size_t row, size_t column, FieldRef & field)
{
field = {index_block.get(), row, column};
};
}
else
{
create_field_ref = [&index](size_t row, size_t column, FieldRef & field)
{
index[column]->get(row, field);
};
}
/// NOTE Creating temporary Field objects to pass to KeyCondition.
std::vector<FieldRef> index_left(used_key_size);
std::vector<FieldRef> index_right(used_key_size);
while (!ranges_stack.empty())
{
MarkRange range = ranges_stack.back();
ranges_stack.pop_back();
bool may_be_true;
if (range.end == marks_count && !has_final_mark)
{
for (size_t i = 0; i < used_key_size; ++i)
create_field_ref(range.begin, i, index_left[i]);
may_be_true = key_condition.mayBeTrueAfter(
used_key_size, index_left.data(), data.primary_key_data_types);
}
else
{
if (has_final_mark && range.end == marks_count)
range.end -= 1; /// Remove final empty mark. It's useful only for primary key condition.
for (size_t i = 0; i < used_key_size; ++i)
{
create_field_ref(range.begin, i, index_left[i]);
create_field_ref(range.end, i, index_right[i]);
}
may_be_true = key_condition.mayBeTrueInRange(
used_key_size, index_left.data(), index_right.data(), data.primary_key_data_types);
}
if (!may_be_true)
continue;
if (range.end == range.begin + 1)
{
/// We saw a useful gap between neighboring marks. Either add it to the last range, or start a new range.
if (res.empty() || range.begin - res.back().end > min_marks_for_seek)
res.push_back(range);
else
res.back().end = range.end;
}
else
{
/// Break the segment and put the result on the stack from right to left.
size_t step = (range.end - range.begin - 1) / settings.merge_tree_coarse_index_granularity + 1;
size_t end;
for (end = range.end; end > range.begin + step; end -= step)
ranges_stack.emplace_back(end - step, end);
ranges_stack.emplace_back(range.begin, end);
}
}
}
return res;
}
MarkRanges MergeTreeDataSelectExecutor::filterMarksUsingIndex(
MergeTreeIndexPtr index,
MergeTreeIndexConditionPtr condition,
MergeTreeData::DataPartPtr part,
const MarkRanges & ranges,
const Settings & settings) const
{
if (!part->volume->getDisk()->exists(part->getFullRelativePath() + index->getFileName() + ".idx"))
{
LOG_DEBUG(log, "File for index " << backQuote(index->name) << " does not exist. Skipping it.");
return ranges;
}
const size_t min_marks_for_seek = roundRowsOrBytesToMarks(
settings.merge_tree_min_rows_for_seek,
settings.merge_tree_min_bytes_for_seek,
part->index_granularity_info.fixed_index_granularity,
part->index_granularity_info.index_granularity_bytes);
size_t granules_dropped = 0;
size_t marks_count = part->getMarksCount();
size_t final_mark = part->index_granularity.hasFinalMark();
size_t index_marks_count = (marks_count - final_mark + index->granularity - 1) / index->granularity;
MergeTreeIndexReader reader(
index, part,
index_marks_count,
ranges);
MarkRanges res;
/// Some granules can cover two or more ranges,
/// this variable is stored to avoid reading the same granule twice.
MergeTreeIndexGranulePtr granule = nullptr;
size_t last_index_mark = 0;
for (const auto & range : ranges)
{
MarkRange index_range(
range.begin / index->granularity,
(range.end + index->granularity - 1) / index->granularity);
if (last_index_mark != index_range.begin || !granule)
reader.seek(index_range.begin);
for (size_t index_mark = index_range.begin; index_mark < index_range.end; ++index_mark)
{
if (index_mark != index_range.begin || !granule || last_index_mark != index_range.begin)
granule = reader.read();
MarkRange data_range(
std::max(range.begin, index_mark * index->granularity),
std::min(range.end, (index_mark + 1) * index->granularity));
if (!condition->mayBeTrueOnGranule(granule))
{
++granules_dropped;
continue;
}
if (res.empty() || res.back().end - data_range.begin > min_marks_for_seek)
res.push_back(data_range);
else
res.back().end = data_range.end;
}
last_index_mark = index_range.end - 1;
}
LOG_DEBUG(log, "Index " << backQuote(index->name) << " has dropped " << granules_dropped << " granules.");
return res;
}
}
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