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ClickHouse/src/Storages/MergeTree/MergeTreeDataSelectExecutor.cpp
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2021-03-02 19:13:36 +03:00

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#include <boost/rational.hpp> /// For calculations related to sampling coefficients.
#include <ext/scope_guard.h>
#include <optional>
#include <unordered_set>
#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/MergeTree/MergeTreeDataPartUUID.h>
#include <Storages/ReadInOrderOptimizer.h>
#include <Parsers/ASTIdentifier.h>
#include <Parsers/ASTLiteral.h>
#include <Parsers/ASTFunction.h>
#include <Parsers/ASTSampleRatio.h>
#include <Parsers/parseIdentifierOrStringLiteral.h>
#include <Interpreters/ExpressionAnalyzer.h>
#include <Interpreters/Context.h>
#include <Processors/ConcatProcessor.h>
#include <Processors/QueryPlan/QueryPlan.h>
#include <Processors/QueryPlan/FilterStep.h>
#include <Processors/QueryPlan/ExpressionStep.h>
#include <Processors/QueryPlan/ReadFromPreparedSource.h>
#include <Processors/QueryPlan/ReverseRowsStep.h>
#include <Processors/QueryPlan/MergingSortedStep.h>
#include <Processors/QueryPlan/UnionStep.h>
#include <Processors/QueryPlan/MergingFinal.h>
#include <Core/UUID.h>
#include <DataTypes/DataTypeDate.h>
#include <DataTypes/DataTypeEnum.h>
#include <DataTypes/DataTypeUUID.h>
#include <DataTypes/DataTypesNumber.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;
extern const int TOO_MANY_ROWS;
extern const int CANNOT_PARSE_TEXT;
extern const int TOO_MANY_PARTITIONS;
extern const int DUPLICATED_PART_UUIDS;
}
MergeTreeDataSelectExecutor::MergeTreeDataSelectExecutor(const MergeTreeData & data_)
: data(data_), log(&Poco::Logger::get(data.getLogName() + " (SelectExecutor)"))
{
}
/// Construct a block consisting only of possible values of virtual columns
static Block getBlockWithVirtualPartColumns(const MergeTreeData::DataPartsVector & parts, bool with_uuid)
{
auto part_column = ColumnString::create();
auto part_uuid_column = ColumnUUID::create();
for (const auto & part : parts)
{
part_column->insert(part->name);
if (with_uuid)
part_uuid_column->insert(part->uuid);
}
if (with_uuid)
{
return Block(std::initializer_list<ColumnWithTypeAndName>{
ColumnWithTypeAndName(std::move(part_column), std::make_shared<DataTypeString>(), "_part"),
ColumnWithTypeAndName(std::move(part_uuid_column), std::make_shared<DataTypeUUID>(), "_part_uuid"),
});
}
return Block{ColumnWithTypeAndName(std::move(part_column), std::make_shared<DataTypeString>(), "_part")};
}
size_t MergeTreeDataSelectExecutor::getApproximateTotalRowsToRead(
const MergeTreeData::DataPartsVector & parts,
const StorageMetadataPtr & metadata_snapshot,
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, metadata_snapshot, key_condition, settings, log);
/** 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));
}
QueryPlanPtr MergeTreeDataSelectExecutor::read(
const Names & column_names_to_return,
const StorageMetadataPtr & metadata_snapshot,
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, metadata_snapshot,
query_info, context, max_block_size, num_streams,
max_block_numbers_to_read);
}
QueryPlanPtr MergeTreeDataSelectExecutor::readFromParts(
MergeTreeData::DataPartsVector parts,
const Names & column_names_to_return,
const StorageMetadataPtr & metadata_snapshot,
const SelectQueryInfo & query_info,
const Context & context,
const UInt64 max_block_size,
const unsigned num_streams,
const PartitionIdToMaxBlock * max_block_numbers_to_read) const
{
/// 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;
size_t total_parts = parts.size();
bool part_column_queried = false;
bool part_uuid_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 == "_part_uuid")
{
part_uuid_column_queried = true;
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 = metadata_snapshot->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` or `_part_uuid` virtual columns are requested, we try to filter out data by them.
Block virtual_columns_block = getBlockWithVirtualPartColumns(parts, part_uuid_column_queried);
if (part_column_queried || part_uuid_column_queried)
VirtualColumnUtils::filterBlockWithQuery(query_info.query, virtual_columns_block, context);
auto part_values = VirtualColumnUtils::extractSingleValueFromBlock<String>(virtual_columns_block, "_part");
metadata_snapshot->check(real_column_names, data.getVirtuals(), data.getStorageID());
const Settings & settings = context.getSettingsRef();
const auto & primary_key = metadata_snapshot->getPrimaryKey();
Names primary_key_columns = primary_key.column_names;
KeyCondition key_condition(query_info, context, primary_key_columns, primary_key.expression);
if (settings.force_primary_key && key_condition.alwaysUnknownOrTrue())
{
throw Exception(ErrorCodes::INDEX_NOT_USED, "Primary key ({}) is not used and setting 'force_primary_key' is set.",
boost::algorithm::join(primary_key_columns, ", "));
}
std::optional<KeyCondition> minmax_idx_condition;
std::optional<PartitionPruner> partition_pruner;
DataTypes minmax_columns_types;
if (metadata_snapshot->hasPartitionKey())
{
const auto & partition_key = metadata_snapshot->getPartitionKey();
auto minmax_columns_names = data.getMinMaxColumnsNames(partition_key);
minmax_columns_types = data.getMinMaxColumnsTypes(partition_key);
minmax_idx_condition.emplace(query_info, context, minmax_columns_names, data.getMinMaxExpr(partition_key));
partition_pruner.emplace(metadata_snapshot->getPartitionKey(), query_info, context, false /* strict */);
if (settings.force_index_by_date && (minmax_idx_condition->alwaysUnknownOrTrue() && partition_pruner->isUseless()))
{
String msg = "Neither MinMax index by columns (";
bool first = true;
for (const String & col : minmax_columns_names)
{
if (first)
first = false;
else
msg += ", ";
msg += col;
}
msg += ") nor partition expr is used and setting 'force_index_by_date' is set";
throw Exception(msg, ErrorCodes::INDEX_NOT_USED);
}
}
const Context & query_context = context.hasQueryContext() ? context.getQueryContext() : context;
if (query_context.getSettingsRef().allow_experimental_query_deduplication)
selectPartsToReadWithUUIDFilter(parts, part_values, minmax_idx_condition, minmax_columns_types, partition_pruner, max_block_numbers_to_read, query_context);
else
selectPartsToRead(parts, part_values, minmax_idx_condition, minmax_columns_types, partition_pruner, max_block_numbers_to_read);
/// Sampling.
Names column_names_to_read = real_column_names;
std::shared_ptr<ASTFunction> filter_function;
ActionsDAGPtr 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, metadata_snapshot, 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.
*/
/// Parallel replicas has been requested but there is no way to sample data.
/// Select all data from first replica and no data from other replicas.
if (settings.parallel_replicas_count > 1 && !data.supportsSampling() && settings.parallel_replica_offset > 0)
{
LOG_DEBUG(log, "Will use no data on this replica because parallel replicas processing has been requested"
" (the setting 'max_parallel_replicas') but the table does not support sampling and this replica is not the first.");
return {};
}
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;
const auto & sampling_key = metadata_snapshot->getSamplingKey();
DataTypePtr sampling_column_type = sampling_key.data_types[0];
if (sampling_key.data_types.size() == 1)
{
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);
}
if (size_of_universum == RelativeSize(0))
throw Exception(
"Invalid sampling column type in storage parameters: " + sampling_column_type->getName()
+ ". Must be one 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 = metadata_snapshot->getSamplingKeyAST();
if (select.final())
{
sampling_key_ast = std::make_shared<ASTIdentifier>(sampling_key.column_names[0]);
/// We do spoil available_real_columns here, but it is not used later.
available_real_columns.emplace_back(sampling_key.column_names[0], std::move(sampling_column_type));
}
if (has_lower_limit)
{
if (!key_condition.addCondition(sampling_key.column_names[0], 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(sampling_key.column_names[0], 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 = TreeRewriter(context).analyze(query, available_real_columns);
filter_expression = ExpressionAnalyzer(filter_function, syntax_result, context).getActionsDAG(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().getNames();
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 std::make_unique<QueryPlan>();
}
LOG_DEBUG(log, "Key condition: {}", key_condition.toString());
if (minmax_idx_condition)
LOG_DEBUG(log, "MinMax index condition: {}", minmax_idx_condition->toString());
MergeTreeReaderSettings reader_settings =
{
.min_bytes_to_use_direct_io = settings.min_bytes_to_use_direct_io,
.min_bytes_to_use_mmap_io = settings.min_bytes_to_use_mmap_io,
.max_read_buffer_size = settings.max_read_buffer_size,
.save_marks_in_cache = true,
.checksum_on_read = settings.checksum_on_read,
};
/// PREWHERE
String prewhere_column;
if (select.prewhere())
prewhere_column = select.prewhere()->getColumnName();
struct DataSkippingIndexAndCondition
{
MergeTreeIndexPtr index;
MergeTreeIndexConditionPtr condition;
std::atomic<size_t> total_granules;
std::atomic<size_t> granules_dropped;
DataSkippingIndexAndCondition(MergeTreeIndexPtr index_, MergeTreeIndexConditionPtr condition_)
: index(index_)
, condition(condition_)
, total_granules(0)
, granules_dropped(0)
{}
};
std::list<DataSkippingIndexAndCondition> useful_indices;
for (const auto & index : metadata_snapshot->getSecondaryIndices())
{
auto index_helper = MergeTreeIndexFactory::instance().get(index);
auto condition = index_helper->createIndexCondition(query_info, context);
if (!condition->alwaysUnknownOrTrue())
useful_indices.emplace_back(index_helper, condition);
}
if (settings.force_data_skipping_indices.changed)
{
const auto & indices = settings.force_data_skipping_indices.toString();
Strings forced_indices;
{
Tokens tokens(&indices[0], &indices[indices.size()], settings.max_query_size);
IParser::Pos pos(tokens, settings.max_parser_depth);
Expected expected;
if (!parseIdentifiersOrStringLiterals(pos, expected, forced_indices))
throw Exception(ErrorCodes::CANNOT_PARSE_TEXT,
"Cannot parse force_data_skipping_indices ('{}')", indices);
}
if (forced_indices.empty())
throw Exception(ErrorCodes::CANNOT_PARSE_TEXT, "No indices parsed from force_data_skipping_indices ('{}')", indices);
std::unordered_set<std::string> useful_indices_names;
for (const auto & useful_index : useful_indices)
useful_indices_names.insert(useful_index.index->index.name);
for (const auto & index_name : forced_indices)
{
if (!useful_indices_names.count(index_name))
{
throw Exception(ErrorCodes::INDEX_NOT_USED,
"Index {} is not used and setting 'force_data_skipping_indices' contains it",
backQuote(index_name));
}
}
}
RangesInDataParts parts_with_ranges(parts.size());
size_t sum_marks = 0;
std::atomic<size_t> sum_marks_pk = 0;
std::atomic<size_t> total_marks_pk = 0;
size_t sum_ranges = 0;
/// Let's find what range to read from each part.
{
std::atomic<size_t> total_rows {0};
SizeLimits limits;
if (settings.read_overflow_mode == OverflowMode::THROW && settings.max_rows_to_read)
limits = SizeLimits(settings.max_rows_to_read, 0, settings.read_overflow_mode);
SizeLimits leaf_limits;
if (settings.read_overflow_mode_leaf == OverflowMode::THROW && settings.max_rows_to_read_leaf)
leaf_limits = SizeLimits(settings.max_rows_to_read_leaf, 0, settings.read_overflow_mode_leaf);
auto process_part = [&](size_t part_index)
{
auto & part = parts[part_index];
RangesInDataPart ranges(part, part_index);
total_marks_pk.fetch_add(part->index_granularity.getMarksCount(), std::memory_order_relaxed);
if (metadata_snapshot->hasPrimaryKey())
ranges.ranges = markRangesFromPKRange(part, metadata_snapshot, key_condition, settings, log);
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}};
}
}
sum_marks_pk.fetch_add(ranges.getMarksCount(), std::memory_order_relaxed);
for (auto & index_and_condition : useful_indices)
{
size_t total_granules = 0;
size_t granules_dropped = 0;
ranges.ranges = filterMarksUsingIndex(
index_and_condition.index, index_and_condition.condition,
part, ranges.ranges,
settings, reader_settings,
total_granules, granules_dropped,
log);
index_and_condition.total_granules.fetch_add(total_granules, std::memory_order_relaxed);
index_and_condition.granules_dropped.fetch_add(granules_dropped, std::memory_order_relaxed);
}
if (!ranges.ranges.empty())
{
if (limits.max_rows || leaf_limits.max_rows)
{
/// Fail fast if estimated number of rows to read exceeds the limit
auto current_rows_estimate = ranges.getRowsCount();
size_t prev_total_rows_estimate = total_rows.fetch_add(current_rows_estimate);
size_t total_rows_estimate = current_rows_estimate + prev_total_rows_estimate;
limits.check(total_rows_estimate, 0, "rows (controlled by 'max_rows_to_read' setting)", ErrorCodes::TOO_MANY_ROWS);
leaf_limits.check(total_rows_estimate, 0, "rows (controlled by 'max_rows_to_read_leaf' setting)", ErrorCodes::TOO_MANY_ROWS);
}
parts_with_ranges[part_index] = std::move(ranges);
}
};
size_t num_threads = std::min(size_t(num_streams), parts.size());
if (num_threads <= 1)
{
for (size_t part_index = 0; part_index < parts.size(); ++part_index)
process_part(part_index);
}
else
{
/// Parallel loading of data parts.
ThreadPool pool(num_threads);
for (size_t part_index = 0; part_index < parts.size(); ++part_index)
pool.scheduleOrThrowOnError([&, part_index, thread_group = CurrentThread::getGroup()] {
SCOPE_EXIT(
if (thread_group)
CurrentThread::detachQueryIfNotDetached();
);
if (thread_group)
CurrentThread::attachTo(thread_group);
process_part(part_index);
});
pool.wait();
}
/// Skip empty ranges.
size_t next_part = 0;
for (size_t part_index = 0; part_index < parts.size(); ++part_index)
{
auto & part = parts_with_ranges[part_index];
if (!part.data_part)
continue;
sum_ranges += part.ranges.size();
sum_marks += part.getMarksCount();
if (next_part != part_index)
std::swap(parts_with_ranges[next_part], part);
++next_part;
}
parts_with_ranges.resize(next_part);
}
for (const auto & index_and_condition : useful_indices)
{
const auto & index_name = index_and_condition.index->index.name;
LOG_DEBUG(log, "Index {} has dropped {}/{} granules.",
backQuote(index_name),
index_and_condition.granules_dropped, index_and_condition.total_granules);
}
LOG_DEBUG(log, "Selected {}/{} parts by partition key, {} parts by primary key, {}/{} marks by primary key, {} marks to read from {} ranges",
parts.size(), total_parts, parts_with_ranges.size(),
sum_marks_pk.load(std::memory_order_relaxed),
total_marks_pk.load(std::memory_order_relaxed),
sum_marks, sum_ranges);
if (parts_with_ranges.empty())
return std::make_unique<QueryPlan>();
const auto data_settings = data.getSettings();
auto max_partitions_to_read
= settings.max_partitions_to_read.changed ? settings.max_partitions_to_read : data_settings->max_partitions_to_read;
if (max_partitions_to_read > 0)
{
std::set<String> partitions;
for (auto & part_with_ranges : parts_with_ranges)
partitions.insert(part_with_ranges.data_part->info.partition_id);
if (partitions.size() > size_t(max_partitions_to_read))
throw Exception(
ErrorCodes::TOO_MANY_PARTITIONS,
"Too many partitions to read. Current {}, max {}",
partitions.size(),
max_partitions_to_read);
}
String query_id;
if (data_settings->max_concurrent_queries > 0)
{
if (data_settings->min_marks_to_honor_max_concurrent_queries > 0
&& sum_marks >= data_settings->min_marks_to_honor_max_concurrent_queries)
{
query_id = context.getCurrentQueryId();
if (!query_id.empty())
data.insertQueryIdOrThrow(query_id, data_settings->max_concurrent_queries);
}
}
ProfileEvents::increment(ProfileEvents::SelectedParts, parts_with_ranges.size());
ProfileEvents::increment(ProfileEvents::SelectedRanges, sum_ranges);
ProfileEvents::increment(ProfileEvents::SelectedMarks, sum_marks);
QueryPlanPtr plan;
/// 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.
ActionsDAGPtr result_projection;
if (select.final())
{
/// Add columns needed to calculate the sorting expression and the sign.
std::vector<String> add_columns = metadata_snapshot->getColumnsRequiredForSortingKey();
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());
plan = spreadMarkRangesAmongStreamsFinal(
std::move(parts_with_ranges),
num_streams,
column_names_to_read,
metadata_snapshot,
max_block_size,
settings.use_uncompressed_cache,
query_info,
virt_column_names,
settings,
reader_settings,
result_projection,
query_id);
}
else if ((settings.optimize_read_in_order || settings.optimize_aggregation_in_order) && query_info.input_order_info)
{
size_t prefix_size = query_info.input_order_info->order_key_prefix_descr.size();
auto order_key_prefix_ast = metadata_snapshot->getSortingKey().expression_list_ast->clone();
order_key_prefix_ast->children.resize(prefix_size);
auto syntax_result = TreeRewriter(context).analyze(order_key_prefix_ast, metadata_snapshot->getColumns().getAllPhysical());
auto sorting_key_prefix_expr = ExpressionAnalyzer(order_key_prefix_ast, syntax_result, context).getActionsDAG(false);
plan = spreadMarkRangesAmongStreamsWithOrder(
std::move(parts_with_ranges),
num_streams,
column_names_to_read,
metadata_snapshot,
max_block_size,
settings.use_uncompressed_cache,
query_info,
sorting_key_prefix_expr,
virt_column_names,
settings,
reader_settings,
result_projection,
query_id);
}
else
{
plan = spreadMarkRangesAmongStreams(
std::move(parts_with_ranges),
num_streams,
column_names_to_read,
metadata_snapshot,
max_block_size,
settings.use_uncompressed_cache,
query_info,
virt_column_names,
settings,
reader_settings,
query_id);
}
if (!plan)
return std::make_unique<QueryPlan>();
if (use_sampling)
{
auto sampling_step = std::make_unique<FilterStep>(
plan->getCurrentDataStream(),
filter_expression,
filter_function->getColumnName(),
false);
sampling_step->setStepDescription("Sampling");
plan->addStep(std::move(sampling_step));
}
if (result_projection)
{
auto projection_step = std::make_unique<ExpressionStep>(plan->getCurrentDataStream(), result_projection);
projection_step->setStepDescription("Remove unused columns after reading from storage");
plan->addStep(std::move(projection_step));
}
/// 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)
{
ColumnWithTypeAndName column;
column.name = "_sample_factor";
column.type = std::make_shared<DataTypeFloat64>();
column.column = column.type->createColumnConst(0, Field(used_sample_factor));
auto adding_column_action = ActionsDAG::makeAddingColumnActions(std::move(column));
auto adding_column = std::make_unique<ExpressionStep>(plan->getCurrentDataStream(), std::move(adding_column_action));
adding_column->setStepDescription("Add _sample_factor column");
plan->addStep(std::move(adding_column));
}
if (query_info.prewhere_info && query_info.prewhere_info->remove_columns_actions)
{
auto expression_step = std::make_unique<ExpressionStep>(
plan->getCurrentDataStream(),
query_info.prewhere_info->remove_columns_actions->getActionsDAG().clone());
expression_step->setStepDescription("Remove unused columns after PREWHERE");
plan->addStep(std::move(expression_step));
}
return plan;
}
namespace
{
/// Marks are placed whenever threshold on rows or bytes is met.
/// So we have to return the number of marks on whatever estimate is higher - by rows or by bytes.
size_t roundRowsOrBytesToMarks(
size_t rows_setting,
size_t bytes_setting,
size_t rows_granularity,
size_t bytes_granularity)
{
size_t res = (rows_setting + rows_granularity - 1) / rows_granularity;
if (bytes_granularity == 0)
return res;
else
return std::max(res, (bytes_setting + bytes_granularity - 1) / bytes_granularity);
}
/// Same as roundRowsOrBytesToMarks() but do not return more then max_marks
size_t minMarksForConcurrentRead(
size_t rows_setting,
size_t bytes_setting,
size_t rows_granularity,
size_t bytes_granularity,
size_t max_marks)
{
size_t marks = 1;
if (rows_setting + rows_granularity <= rows_setting) /// overflow
marks = max_marks;
else if (rows_setting)
marks = (rows_setting + rows_granularity - 1) / rows_granularity;
if (bytes_granularity == 0)
return marks;
else
{
/// Overflow
if (bytes_setting + bytes_granularity <= bytes_setting) /// overflow
return max_marks;
if (bytes_setting)
return std::max(marks, (bytes_setting + bytes_granularity - 1) / bytes_granularity);
else
return marks;
}
}
}
static QueryPlanPtr createPlanFromPipe(Pipe pipe, const String & query_id, const MergeTreeData & data, const std::string & description = "")
{
auto plan = std::make_unique<QueryPlan>();
std::string storage_name = "MergeTree";
if (!description.empty())
storage_name += ' ' + description;
// Attach QueryIdHolder if needed
if (!query_id.empty())
pipe.addQueryIdHolder(std::make_shared<QueryIdHolder>(query_id, data));
auto step = std::make_unique<ReadFromStorageStep>(std::move(pipe), storage_name);
plan->addStep(std::move(step));
return plan;
}
QueryPlanPtr MergeTreeDataSelectExecutor::spreadMarkRangesAmongStreams(
RangesInDataParts && parts,
size_t num_streams,
const Names & column_names,
const StorageMetadataPtr & metadata_snapshot,
UInt64 max_block_size,
bool use_uncompressed_cache,
const SelectQueryInfo & query_info,
const Names & virt_columns,
const Settings & settings,
const MergeTreeReaderSettings & reader_settings,
const String & query_id) 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 = minMarksForConcurrentRead(
settings.merge_tree_min_rows_for_concurrent_read,
settings.merge_tree_min_bytes_for_concurrent_read,
data_settings->index_granularity,
index_granularity_bytes,
sum_marks);
if (sum_marks > max_marks_to_use_cache)
use_uncompressed_cache = false;
if (0 == sum_marks)
return {};
if (num_streams > 1)
{
/// Parallel query execution.
Pipes res;
/// 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,
std::move(parts),
data,
metadata_snapshot,
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. {} rows with {} streams", total_rows, num_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, metadata_snapshot, 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));
}
return createPlanFromPipe(Pipe::unitePipes(std::move(res)), query_id, data);
}
else
{
/// Sequential query execution.
Pipes res;
for (const auto & part : parts)
{
auto source = std::make_shared<MergeTreeSelectProcessor>(
data, metadata_snapshot, 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));
}
auto pipe = Pipe::unitePipes(std::move(res));
/// 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 (pipe.numOutputPorts() > 1)
pipe.addTransform(std::make_shared<ConcatProcessor>(pipe.getHeader(), pipe.numOutputPorts()));
return createPlanFromPipe(std::move(pipe), query_id, data);
}
}
static ActionsDAGPtr createProjection(const Block & header)
{
auto projection = std::make_shared<ActionsDAG>(header.getNamesAndTypesList());
projection->removeUnusedActions(header.getNames());
projection->projectInput();
return projection;
}
QueryPlanPtr MergeTreeDataSelectExecutor::spreadMarkRangesAmongStreamsWithOrder(
RangesInDataParts && parts,
size_t num_streams,
const Names & column_names,
const StorageMetadataPtr & metadata_snapshot,
UInt64 max_block_size,
bool use_uncompressed_cache,
const SelectQueryInfo & query_info,
const ActionsDAGPtr & sorting_key_prefix_expr,
const Names & virt_columns,
const Settings & settings,
const MergeTreeReaderSettings & reader_settings,
ActionsDAGPtr & out_projection,
const String & query_id) const
{
size_t sum_marks = 0;
const InputOrderInfoPtr & input_order_info = query_info.input_order_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 = minMarksForConcurrentRead(
settings.merge_tree_min_rows_for_concurrent_read,
settings.merge_tree_min_bytes_for_concurrent_read,
data_settings->index_granularity,
index_granularity_bytes,
sum_marks);
if (sum_marks > max_marks_to_use_cache)
use_uncompressed_cache = false;
Pipes res;
if (sum_marks == 0)
return {};
/// 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 split = false;
for (auto range : ranges)
{
while (!split && 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)
split = 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;
bool need_preliminary_merge = (parts.size() > settings.read_in_order_two_level_merge_threshold);
std::vector<QueryPlanPtr> plans;
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_order_info->direction);
if (input_order_info->direction == 1)
{
pipes.emplace_back(std::make_shared<MergeTreeSelectProcessor>(
data,
metadata_snapshot,
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,
metadata_snapshot,
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));
}
}
auto plan = createPlanFromPipe(Pipe::unitePipes(std::move(pipes)), query_id, data, "with order");
if (input_order_info->direction != 1)
{
auto reverse_step = std::make_unique<ReverseRowsStep>(plan->getCurrentDataStream());
plan->addStep(std::move(reverse_step));
}
plans.emplace_back(std::move(plan));
}
if (need_preliminary_merge)
{
SortDescription sort_description;
for (size_t j = 0; j < input_order_info->order_key_prefix_descr.size(); ++j)
sort_description.emplace_back(metadata_snapshot->getSortingKey().column_names[j],
input_order_info->direction, 1);
for (auto & plan : plans)
{
/// Drop temporary columns, added by 'sorting_key_prefix_expr'
out_projection = createProjection(plan->getCurrentDataStream().header);
auto expression_step = std::make_unique<ExpressionStep>(
plan->getCurrentDataStream(),
sorting_key_prefix_expr);
expression_step->setStepDescription("Calculate sorting key prefix");
plan->addStep(std::move(expression_step));
auto merging_sorted = std::make_unique<MergingSortedStep>(
plan->getCurrentDataStream(),
sort_description,
max_block_size);
merging_sorted->setStepDescription("Merge sorting mark ranges");
plan->addStep(std::move(merging_sorted));
}
}
if (plans.size() == 1)
return std::move(plans.front());
DataStreams input_streams;
for (const auto & plan : plans)
input_streams.emplace_back(plan->getCurrentDataStream());
const auto & common_header = plans.front()->getCurrentDataStream().header;
auto union_step = std::make_unique<UnionStep>(std::move(input_streams), common_header);
auto plan = std::make_unique<QueryPlan>();
plan->unitePlans(std::move(union_step), std::move(plans));
return plan;
}
QueryPlanPtr MergeTreeDataSelectExecutor::spreadMarkRangesAmongStreamsFinal(
RangesInDataParts && parts,
size_t num_streams,
const Names & column_names,
const StorageMetadataPtr & metadata_snapshot,
UInt64 max_block_size,
bool use_uncompressed_cache,
const SelectQueryInfo & query_info,
const Names & virt_columns,
const Settings & settings,
const MergeTreeReaderSettings & reader_settings,
ActionsDAGPtr & out_projection,
const String & query_id) 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;
if (num_streams > settings.max_final_threads)
num_streams = settings.max_final_threads;
/// If setting do_not_merge_across_partitions_select_final is true than we won't merge parts from different partitions.
/// We have all parts in parts vector, where parts with same partition are nerby.
/// So we will store iterators pointed to the beginning of each partition range (and parts.end()),
/// then we will create a pipe for each partition that will run selecting processor and merging processor
/// for the parts with this partition. In the end we will unite all the pipes.
std::vector<RangesInDataParts::iterator> parts_to_merge_ranges;
auto it = parts.begin();
parts_to_merge_ranges.push_back(it);
if (settings.do_not_merge_across_partitions_select_final)
{
while (it != parts.end())
{
it = std::find_if(
it, parts.end(), [&it](auto & part) { return it->data_part->info.partition_id != part.data_part->info.partition_id; });
parts_to_merge_ranges.push_back(it);
}
/// We divide threads for each partition equally. But we will create at least the number of partitions threads.
/// (So, the total number of threads could be more than initial num_streams.
num_streams /= (parts_to_merge_ranges.size() - 1);
}
else
{
/// If do_not_merge_across_partitions_select_final is false we just merge all the parts.
parts_to_merge_ranges.push_back(parts.end());
}
std::vector<QueryPlanPtr> partition_plans;
/// If do_not_merge_across_partitions_select_final is true and num_streams > 1
/// we will store lonely parts with level > 0 to use parallel select on them.
std::vector<RangesInDataPart> lonely_parts;
size_t total_rows_in_lonely_parts = 0;
size_t sum_marks_in_lonely_parts = 0;
for (size_t range_index = 0; range_index < parts_to_merge_ranges.size() - 1; ++range_index)
{
QueryPlanPtr plan;
{
Pipes pipes;
/// If do_not_merge_across_partitions_select_final is true and there is only one part in partition
/// with level > 0 then we won't postprocess this part and if num_streams > 1 we
/// can use parallel select on such parts. We save such parts in one vector and then use
/// MergeTreeReadPool and MergeTreeThreadSelectBlockInputProcessor for parallel select.
if (num_streams > 1 && settings.do_not_merge_across_partitions_select_final &&
std::distance(parts_to_merge_ranges[range_index], parts_to_merge_ranges[range_index + 1]) == 1 &&
parts_to_merge_ranges[range_index]->data_part->info.level > 0)
{
total_rows_in_lonely_parts += parts_to_merge_ranges[range_index]->getRowsCount();
sum_marks_in_lonely_parts += parts_to_merge_ranges[range_index]->getMarksCount();
lonely_parts.push_back(std::move(*parts_to_merge_ranges[range_index]));
continue;
}
else
{
for (auto part_it = parts_to_merge_ranges[range_index]; part_it != parts_to_merge_ranges[range_index + 1]; ++part_it)
{
auto source_processor = std::make_shared<MergeTreeSelectProcessor>(
data,
metadata_snapshot,
part_it->data_part,
max_block_size,
settings.preferred_block_size_bytes,
settings.preferred_max_column_in_block_size_bytes,
column_names,
part_it->ranges,
use_uncompressed_cache,
query_info.prewhere_info,
true,
reader_settings,
virt_columns,
part_it->part_index_in_query);
pipes.emplace_back(std::move(source_processor));
}
}
if (pipes.empty())
continue;
auto pipe = Pipe::unitePipes(std::move(pipes));
/// Drop temporary columns, added by 'sorting_key_expr'
if (!out_projection)
out_projection = createProjection(pipe.getHeader());
plan = createPlanFromPipe(std::move(pipe), query_id, data, "with final");
}
auto expression_step = std::make_unique<ExpressionStep>(
plan->getCurrentDataStream(),
metadata_snapshot->getSortingKey().expression->getActionsDAG().clone());
expression_step->setStepDescription("Calculate sorting key expression");
plan->addStep(std::move(expression_step));
/// If do_not_merge_across_partitions_select_final is true and there is only one part in partition
/// with level > 0 then we won't postprocess this part
if (settings.do_not_merge_across_partitions_select_final &&
std::distance(parts_to_merge_ranges[range_index], parts_to_merge_ranges[range_index + 1]) == 1 &&
parts_to_merge_ranges[range_index]->data_part->info.level > 0)
{
partition_plans.emplace_back(std::move(plan));
continue;
}
Names sort_columns = metadata_snapshot->getSortingKeyColumns();
SortDescription sort_description;
size_t sort_columns_size = sort_columns.size();
sort_description.reserve(sort_columns_size);
Names partition_key_columns = metadata_snapshot->getPartitionKey().column_names;
const auto & header = plan->getCurrentDataStream().header;
for (size_t i = 0; i < sort_columns_size; ++i)
sort_description.emplace_back(header.getPositionByName(sort_columns[i]), 1, 1);
auto final_step = std::make_unique<MergingFinal>(
plan->getCurrentDataStream(),
std::min<size_t>(num_streams, settings.max_final_threads),
sort_description,
data.merging_params,
partition_key_columns,
max_block_size);
final_step->setStepDescription("Merge rows for FINAL");
plan->addStep(std::move(final_step));
partition_plans.emplace_back(std::move(plan));
}
if (!lonely_parts.empty())
{
Pipes pipes;
size_t num_streams_for_lonely_parts = num_streams * lonely_parts.size();
const size_t min_marks_for_concurrent_read = minMarksForConcurrentRead(
settings.merge_tree_min_rows_for_concurrent_read,
settings.merge_tree_min_bytes_for_concurrent_read,
data_settings->index_granularity,
index_granularity_bytes,
sum_marks_in_lonely_parts);
/// Reduce the number of num_streams_for_lonely_parts if the data is small.
if (sum_marks_in_lonely_parts < num_streams_for_lonely_parts * min_marks_for_concurrent_read && lonely_parts.size() < num_streams_for_lonely_parts)
num_streams_for_lonely_parts = std::max((sum_marks_in_lonely_parts + min_marks_for_concurrent_read - 1) / min_marks_for_concurrent_read, lonely_parts.size());
MergeTreeReadPoolPtr pool = std::make_shared<MergeTreeReadPool>(
num_streams_for_lonely_parts,
sum_marks_in_lonely_parts,
min_marks_for_concurrent_read,
std::move(lonely_parts),
data,
metadata_snapshot,
query_info.prewhere_info,
true,
column_names,
MergeTreeReadPool::BackoffSettings(settings),
settings.preferred_block_size_bytes,
false);
LOG_TRACE(log, "Reading approx. {} rows with {} streams", total_rows_in_lonely_parts, num_streams_for_lonely_parts);
for (size_t i = 0; i < num_streams_for_lonely_parts; ++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, metadata_snapshot, use_uncompressed_cache,
query_info.prewhere_info, reader_settings, virt_columns);
pipes.emplace_back(std::move(source));
}
auto pipe = Pipe::unitePipes(std::move(pipes));
/// Drop temporary columns, added by 'sorting_key_expr'
if (!out_projection)
out_projection = createProjection(pipe.getHeader());
QueryPlanPtr plan = createPlanFromPipe(std::move(pipe), query_id, data, "with final");
auto expression_step = std::make_unique<ExpressionStep>(
plan->getCurrentDataStream(),
metadata_snapshot->getSortingKey().expression->getActionsDAG().clone());
expression_step->setStepDescription("Calculate sorting key expression");
plan->addStep(std::move(expression_step));
partition_plans.emplace_back(std::move(plan));
}
if (partition_plans.empty())
return {};
if (partition_plans.size() == 1)
return std::move(partition_plans.front());
auto result_header = partition_plans.front()->getCurrentDataStream().header;
DataStreams input_streams;
for (const auto & partition_plan : partition_plans)
input_streams.push_back(partition_plan->getCurrentDataStream());
auto union_step = std::make_unique<UnionStep>(std::move(input_streams), result_header);
union_step->setStepDescription("Unite sources after FINAL");
QueryPlanPtr plan = std::make_unique<QueryPlan>();
plan->unitePlans(std::move(union_step), std::move(partition_plans));
return plan;
}
/// 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 StorageMetadataPtr & metadata_snapshot,
const KeyCondition & key_condition,
const Settings & settings,
Poco::Logger * log)
{
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));
return res;
}
size_t used_key_size = key_condition.getMaxKeyColumn() + 1;
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.
const auto & primary_key = metadata_snapshot->getPrimaryKey();
if (key_condition.hasMonotonicFunctionsChain())
{
auto index_columns = std::make_shared<ColumnsWithTypeAndName>();
for (size_t i = 0; i < used_key_size; ++i)
index_columns->emplace_back(ColumnWithTypeAndName{index[i], primary_key.data_types[i], primary_key.column_names[i]});
create_field_ref = [index_columns](size_t row, size_t column, FieldRef & field)
{
field = {index_columns.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);
auto may_be_true_in_range = [&](MarkRange & range)
{
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]);
return key_condition.mayBeTrueAfter(
used_key_size, index_left.data(), primary_key.data_types);
}
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]);
}
return key_condition.mayBeTrueInRange(
used_key_size, index_left.data(), index_right.data(), primary_key.data_types);
};
if (!key_condition.matchesExactContinuousRange())
{
// Do exclusion search, where we drop ranges that do not match
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} };
size_t steps = 0;
while (!ranges_stack.empty())
{
MarkRange range = ranges_stack.back();
ranges_stack.pop_back();
steps++;
if (!may_be_true_in_range(range))
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);
}
}
LOG_TRACE(log, "Used generic exclusion search over index for part {} with {} steps", part->name, steps);
}
else
{
/// In case when SELECT's predicate defines a single continuous interval of keys,
/// we can use binary search algorithm to find the left and right endpoint key marks of such interval.
/// The returned value is the minimum range of marks, containing all keys for which KeyCondition holds
LOG_TRACE(log, "Running binary search on index range for part {} ({} marks)", part->name, marks_count);
size_t steps = 0;
MarkRange result_range;
size_t searched_left = 0;
size_t searched_right = marks_count;
while (searched_left + 1 < searched_right)
{
const size_t middle = (searched_left + searched_right) / 2;
MarkRange range(0, middle);
if (may_be_true_in_range(range))
searched_right = middle;
else
searched_left = middle;
++steps;
}
result_range.begin = searched_left;
LOG_TRACE(log, "Found (LEFT) boundary mark: {}", searched_left);
searched_right = marks_count;
while (searched_left + 1 < searched_right)
{
const size_t middle = (searched_left + searched_right) / 2;
MarkRange range(middle, marks_count);
if (may_be_true_in_range(range))
searched_left = middle;
else
searched_right = middle;
++steps;
}
result_range.end = searched_right;
LOG_TRACE(log, "Found (RIGHT) boundary mark: {}", searched_right);
if (result_range.begin < result_range.end && may_be_true_in_range(result_range))
res.emplace_back(std::move(result_range));
LOG_TRACE(log, "Found {} range in {} steps", res.empty() ? "empty" : "continuous", steps);
}
return res;
}
MarkRanges MergeTreeDataSelectExecutor::filterMarksUsingIndex(
MergeTreeIndexPtr index_helper,
MergeTreeIndexConditionPtr condition,
MergeTreeData::DataPartPtr part,
const MarkRanges & ranges,
const Settings & settings,
const MergeTreeReaderSettings & reader_settings,
size_t & total_granules,
size_t & granules_dropped,
Poco::Logger * log)
{
if (!part->volume->getDisk()->exists(part->getFullRelativePath() + index_helper->getFileName() + ".idx"))
{
LOG_DEBUG(log, "File for index {} does not exist. Skipping it.", backQuote(index_helper->index.name));
return ranges;
}
auto index_granularity = index_helper->index.granularity;
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 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_helper, part,
index_marks_count,
ranges,
reader_settings);
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);
total_granules += index_range.end - 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;
}
return res;
}
void MergeTreeDataSelectExecutor::selectPartsToRead(
MergeTreeData::DataPartsVector & parts,
const std::unordered_set<String> & part_values,
const std::optional<KeyCondition> & minmax_idx_condition,
const DataTypes & minmax_columns_types,
std::optional<PartitionPruner> & partition_pruner,
const PartitionIdToMaxBlock * max_block_numbers_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, minmax_columns_types).can_be_true)
continue;
if (partition_pruner)
{
if (partition_pruner->canBePruned(part))
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);
}
}
void MergeTreeDataSelectExecutor::selectPartsToReadWithUUIDFilter(
MergeTreeData::DataPartsVector & parts,
const std::unordered_set<String> & part_values,
const std::optional<KeyCondition> & minmax_idx_condition,
const DataTypes & minmax_columns_types,
std::optional<PartitionPruner> & partition_pruner,
const PartitionIdToMaxBlock * max_block_numbers_to_read,
const Context & query_context) const
{
/// const_cast to add UUIDs to context. Bad practice.
Context & non_const_context = const_cast<Context &>(query_context);
/// process_parts prepare parts that have to be read for the query,
/// returns false if duplicated parts' UUID have been met
auto select_parts = [&] (MergeTreeData::DataPartsVector & selected_parts) -> bool
{
auto ignored_part_uuids = non_const_context.getIgnoredPartUUIDs();
std::unordered_set<UUID> temp_part_uuids;
auto prev_parts = selected_parts;
selected_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, minmax_columns_types)
.can_be_true)
continue;
if (partition_pruner)
{
if (partition_pruner->canBePruned(part))
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;
}
/// populate UUIDs and exclude ignored parts if enabled
if (part->uuid != UUIDHelpers::Nil)
{
/// Skip the part if its uuid is meant to be excluded
if (ignored_part_uuids->has(part->uuid))
continue;
auto result = temp_part_uuids.insert(part->uuid);
if (!result.second)
throw Exception("Found a part with the same UUID on the same replica.", ErrorCodes::LOGICAL_ERROR);
}
selected_parts.push_back(part);
}
if (!temp_part_uuids.empty())
{
auto duplicates = non_const_context.getPartUUIDs()->add(std::vector<UUID>{temp_part_uuids.begin(), temp_part_uuids.end()});
if (!duplicates.empty())
{
/// on a local replica with prefer_localhost_replica=1 if any duplicates appeared during the first pass,
/// adding them to the exclusion, so they will be skipped on second pass
non_const_context.getIgnoredPartUUIDs()->add(duplicates);
return false;
}
}
return true;
};
/// Process parts that have to be read for a query.
auto needs_retry = !select_parts(parts);
/// If any duplicated part UUIDs met during the first step, try to ignore them in second pass
if (needs_retry)
{
LOG_DEBUG(log, "Found duplicate uuids locally, will retry part selection without them");
/// Second attempt didn't help, throw an exception
if (!select_parts(parts))
throw Exception("Found duplicate UUIDs while processing query.", ErrorCodes::DUPLICATED_PART_UUIDS);
}
}
}
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