599bcd6ea7
The classes restriction, restrictions and its children aren't used anywhere now and can be safely removed. Some includes need to be modified for the code to compile. Signed-off-by: Jan Ciolek <jan.ciolek@scylladb.com>
1948 lines
89 KiB
C++
1948 lines
89 KiB
C++
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/*
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* Copyright (C) 2015-present ScyllaDB
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*/
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/*
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* SPDX-License-Identifier: AGPL-3.0-or-later
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*/
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#include <algorithm>
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#include <boost/algorithm/cxx11/all_of.hpp>
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#include <boost/algorithm/cxx11/any_of.hpp>
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#include <boost/range/adaptors.hpp>
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#include <boost/range/algorithm.hpp>
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#include <functional>
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#include <ranges>
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#include <stdexcept>
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#include "cql3/expr/expression.hh"
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#include "query-result-reader.hh"
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#include "statement_restrictions.hh"
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#include "data_dictionary/data_dictionary.hh"
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#include "cartesian_product.hh"
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#include "cql3/cql_config.hh"
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#include "cql3/constants.hh"
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#include "cql3/lists.hh"
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#include "cql3/selection/selection.hh"
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#include "cql3/statements/request_validations.hh"
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#include "types/list.hh"
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#include "types/map.hh"
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#include "types/set.hh"
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namespace cql3 {
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namespace restrictions {
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static logging::logger rlogger("restrictions");
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using boost::adaptors::filtered;
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using boost::adaptors::transformed;
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using statements::request_validations::invalid_request;
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statement_restrictions::statement_restrictions(schema_ptr schema, bool allow_filtering)
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: _schema(schema)
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, _partition_range_is_simple(true)
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{ }
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#if 0
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static const column_definition*
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to_column_definition(const schema_ptr& schema, const ::shared_ptr<column_identifier::raw>& entity) {
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return get_column_definition(schema,
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*entity->prepare_column_identifier(schema));
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}
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#endif
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template <typename Visitor>
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concept visitor_with_binary_operator_context = requires (Visitor v) {
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{ v.current_binary_operator } -> std::convertible_to<const expr::binary_operator*>;
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};
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void with_current_binary_operator(
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visitor_with_binary_operator_context auto& visitor,
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std::invocable<const expr::binary_operator&> auto func) {
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if (!visitor.current_binary_operator) {
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throw std::logic_error("Evaluation expected within binary operator");
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}
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func(*visitor.current_binary_operator);
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}
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/// Every token, or if no tokens, an EQ/IN of every single PK column.
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static std::vector<expr::expression> extract_partition_range(
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const expr::expression& where_clause, schema_ptr schema) {
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using namespace expr;
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struct {
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std::optional<expression> tokens;
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std::unordered_map<const column_definition*, expression> single_column;
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const binary_operator* current_binary_operator = nullptr;
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void operator()(const conjunction& c) {
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std::ranges::for_each(c.children, [this] (const expression& child) { expr::visit(*this, child); });
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}
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void operator()(const binary_operator& b) {
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if (current_binary_operator) {
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throw std::logic_error("Nested binary operators are not supported");
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}
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current_binary_operator = &b;
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expr::visit(*this, b.lhs);
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current_binary_operator = nullptr;
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}
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void operator()(const token&) {
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with_current_binary_operator(*this, [&] (const binary_operator& b) {
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if (tokens) {
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tokens = make_conjunction(std::move(*tokens), b);
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} else {
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tokens = b;
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}
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});
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}
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void operator()(const column_value& cv) {
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auto s = &cv;
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with_current_binary_operator(*this, [&] (const binary_operator& b) {
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if (s->col->is_partition_key() && (b.op == oper_t::EQ || b.op == oper_t::IN)) {
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const auto found = single_column.find(s->col);
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if (found == single_column.end()) {
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single_column[s->col] = b;
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} else {
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found->second = make_conjunction(std::move(found->second), b);
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}
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}
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});
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}
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void operator()(const tuple_constructor& s) {
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// Partition key columns are not legal in tuples, so ignore tuples.
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}
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void operator()(const subscript& sub) {
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const column_value& cval = get_subscripted_column(sub.val);
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with_current_binary_operator(*this, [&] (const binary_operator& b) {
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if (cval.col->is_partition_key() && (b.op == oper_t::EQ || b.op == oper_t::IN)) {
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const auto found = single_column.find(cval.col);
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if (found == single_column.end()) {
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single_column[cval.col] = b;
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} else {
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found->second = make_conjunction(std::move(found->second), b);
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}
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}
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});
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}
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void operator()(const constant&) {}
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void operator()(const unresolved_identifier&) {
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on_internal_error(rlogger, "extract_partition_range(unresolved_identifier)");
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}
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void operator()(const column_mutation_attribute&) {
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on_internal_error(rlogger, "extract_partition_range(column_mutation_attribute)");
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}
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void operator()(const function_call&) {
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on_internal_error(rlogger, "extract_partition_range(function_call)");
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}
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void operator()(const cast&) {
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on_internal_error(rlogger, "extract_partition_range(cast)");
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}
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void operator()(const field_selection&) {
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on_internal_error(rlogger, "extract_partition_range(field_selection)");
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}
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void operator()(const null&) {
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on_internal_error(rlogger, "extract_partition_range(null)");
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}
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void operator()(const bind_variable&) {
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on_internal_error(rlogger, "extract_partition_range(bind_variable)");
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}
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void operator()(const untyped_constant&) {
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on_internal_error(rlogger, "extract_partition_range(untyped_constant)");
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}
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void operator()(const collection_constructor&) {
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on_internal_error(rlogger, "extract_partition_range(collection_constructor)");
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}
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void operator()(const usertype_constructor&) {
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on_internal_error(rlogger, "extract_partition_range(usertype_constructor)");
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}
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} v;
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expr::visit(v, where_clause);
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if (v.tokens) {
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return {std::move(*v.tokens)};
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}
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if (v.single_column.size() == schema->partition_key_size()) {
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return boost::copy_range<std::vector<expression>>(v.single_column | boost::adaptors::map_values);
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}
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return {};
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}
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/// Extracts where_clause atoms with clustering-column LHS and copies them to a vector. These elements define the
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/// boundaries of any clustering slice that can possibly meet where_clause. This vector can be calculated before
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/// binding expression markers, since LHS and operator are always known.
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static std::vector<expr::expression> extract_clustering_prefix_restrictions(
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const expr::expression& where_clause, schema_ptr schema) {
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using namespace expr;
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/// Collects all clustering-column restrictions from an expression. Presumes the expression only uses
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/// conjunction to combine subexpressions.
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struct visitor {
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std::vector<expression> multi; ///< All multi-column restrictions.
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/// All single-clustering-column restrictions, grouped by column. Each value is either an atom or a
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/// conjunction of atoms.
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std::unordered_map<const column_definition*, expression> single;
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const binary_operator* current_binary_operator = nullptr;
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void operator()(const conjunction& c) {
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std::ranges::for_each(c.children, [this] (const expression& child) { expr::visit(*this, child); });
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}
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void operator()(const binary_operator& b) {
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if (current_binary_operator) {
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throw std::logic_error("Nested binary operators are not supported");
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}
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current_binary_operator = &b;
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expr::visit(*this, b.lhs);
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current_binary_operator = nullptr;
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}
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void operator()(const tuple_constructor& tc) {
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for (auto& e : tc.elements) {
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if (!expr::is<column_value>(e)) {
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on_internal_error(rlogger, fmt::format("extract_clustering_prefix_restrictions: tuple of non-column_value: {}", tc));
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}
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}
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with_current_binary_operator(*this, [&] (const binary_operator& b) {
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multi.push_back(b);
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});
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}
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void operator()(const column_value& cv) {
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auto s = &cv;
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with_current_binary_operator(*this, [&] (const binary_operator& b) {
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if (s->col->is_clustering_key()) {
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const auto found = single.find(s->col);
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if (found == single.end()) {
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single[s->col] = b;
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} else {
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found->second = make_conjunction(std::move(found->second), b);
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}
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}
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});
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}
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void operator()(const subscript& sub) {
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const column_value& cval = get_subscripted_column(sub.val);
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with_current_binary_operator(*this, [&] (const binary_operator& b) {
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if (cval.col->is_clustering_key()) {
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const auto found = single.find(cval.col);
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if (found == single.end()) {
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single[cval.col] = b;
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} else {
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found->second = make_conjunction(std::move(found->second), b);
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}
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}
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});
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}
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void operator()(const token&) {
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// A token cannot be a clustering prefix restriction
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}
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void operator()(const constant&) {}
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void operator()(const unresolved_identifier&) {
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on_internal_error(rlogger, "extract_clustering_prefix_restrictions(unresolved_identifier)");
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}
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void operator()(const column_mutation_attribute&) {
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on_internal_error(rlogger, "extract_clustering_prefix_restrictions(column_mutation_attribute)");
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}
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void operator()(const function_call&) {
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on_internal_error(rlogger, "extract_clustering_prefix_restrictions(function_call)");
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}
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void operator()(const cast&) {
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on_internal_error(rlogger, "extract_clustering_prefix_restrictions(cast)");
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}
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void operator()(const field_selection&) {
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on_internal_error(rlogger, "extract_clustering_prefix_restrictions(field_selection)");
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}
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void operator()(const null&) {
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on_internal_error(rlogger, "extract_clustering_prefix_restrictions(null)");
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}
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void operator()(const bind_variable&) {
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on_internal_error(rlogger, "extract_clustering_prefix_restrictions(bind_variable)");
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}
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void operator()(const untyped_constant&) {
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on_internal_error(rlogger, "extract_clustering_prefix_restrictions(untyped_constant)");
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}
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void operator()(const collection_constructor&) {
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on_internal_error(rlogger, "extract_clustering_prefix_restrictions(collection_constructor)");
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}
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void operator()(const usertype_constructor&) {
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on_internal_error(rlogger, "extract_clustering_prefix_restrictions(usertype_constructor)");
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}
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} v;
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expr::visit(v, where_clause);
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if (!v.multi.empty()) {
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return std::move(v.multi);
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}
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std::vector<expression> prefix;
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for (const auto& col : schema->clustering_key_columns()) {
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const auto found = v.single.find(&col);
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if (found == v.single.end()) { // Any further restrictions are skipping the CK order.
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break;
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}
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if (find_needs_filtering(found->second)) { // This column's restriction doesn't define a clear bound.
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// TODO: if this is a conjunction of filtering and non-filtering atoms, we could split them and add the
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// latter to the prefix.
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break;
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}
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prefix.push_back(found->second);
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if (has_slice(found->second)) {
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break;
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}
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}
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return prefix;
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}
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statement_restrictions::statement_restrictions(data_dictionary::database db,
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schema_ptr schema,
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statements::statement_type type,
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const std::vector<expr::expression>& where_clause,
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prepare_context& ctx,
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bool selects_only_static_columns,
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bool for_view,
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bool allow_filtering)
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: statement_restrictions(schema, allow_filtering)
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{
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if (!where_clause.empty()) {
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for (auto&& relation_expr : where_clause) {
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const expr::binary_operator* relation_binop = expr::as_if<expr::binary_operator>(&relation_expr);
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if (relation_binop == nullptr) {
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on_internal_error(rlogger, format("statement_restrictions: where clause has non-binop element: {}", relation_expr));
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}
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expr::binary_operator prepared_restriction = expr::validate_and_prepare_new_restriction(*relation_binop, db, schema, ctx);
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add_restriction(prepared_restriction, schema, allow_filtering, for_view);
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if (prepared_restriction.op != expr::oper_t::IS_NOT) {
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_where = _where.has_value() ? make_conjunction(std::move(*_where), prepared_restriction) : prepared_restriction;
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}
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}
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}
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if (_where.has_value()) {
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if (!has_token(_partition_key_restrictions)) {
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_single_column_partition_key_restrictions = expr::get_single_column_restrictions_map(_partition_key_restrictions);
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}
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if (!expr::contains_multi_column_restriction(_clustering_columns_restrictions)) {
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_single_column_clustering_key_restrictions = expr::get_single_column_restrictions_map(_clustering_columns_restrictions);
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}
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_single_column_nonprimary_key_restrictions = expr::get_single_column_restrictions_map(_nonprimary_key_restrictions);
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_clustering_prefix_restrictions = extract_clustering_prefix_restrictions(*_where, _schema);
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_partition_range_restrictions = extract_partition_range(*_where, _schema);
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}
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auto cf = db.find_column_family(schema);
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auto& sim = cf.get_index_manager();
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const expr::allow_local_index allow_local(
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!has_partition_key_unrestricted_components()
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&& partition_key_restrictions_is_all_eq());
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_has_multi_column = find_binop(_clustering_columns_restrictions, expr::is_multi_column);
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_has_queriable_ck_index = clustering_columns_restrictions_have_supporting_index(sim, allow_local)
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&& !type.is_delete();
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_has_queriable_pk_index = parition_key_restrictions_have_supporting_index(sim, allow_local)
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&& !type.is_delete();
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_has_queriable_regular_index = expr::index_supports_some_column(_nonprimary_key_restrictions, sim, allow_local)
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&& !type.is_delete();
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// At this point, the select statement if fully constructed, but we still have a few things to validate
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process_partition_key_restrictions(for_view, allow_filtering);
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// Some but not all of the partition key columns have been specified;
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// hence we need turn these restrictions into index expressions.
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if (_uses_secondary_indexing || pk_restrictions_need_filtering()) {
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_index_restrictions.push_back(_partition_key_restrictions);
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}
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// If the only updated/deleted columns are static, then we don't need clustering columns.
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// And in fact, unless it is an INSERT, we reject if clustering columns are provided as that
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// suggest something unintended. For instance, given:
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// CREATE TABLE t (k int, v int, s int static, PRIMARY KEY (k, v))
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// it can make sense to do:
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// INSERT INTO t(k, v, s) VALUES (0, 1, 2)
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// but both
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// UPDATE t SET s = 3 WHERE k = 0 AND v = 1
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// DELETE s FROM t WHERE k = 0 AND v = 1
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// sounds like you don't really understand what your are doing.
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if (selects_only_static_columns && has_clustering_columns_restriction()) {
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if (type.is_update() || type.is_delete()) {
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throw exceptions::invalid_request_exception(format("Invalid restrictions on clustering columns since the {} statement modifies only static columns", type));
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}
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if (type.is_select()) {
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throw exceptions::invalid_request_exception(
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"Cannot restrict clustering columns when selecting only static columns");
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}
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}
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process_clustering_columns_restrictions(for_view, allow_filtering);
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// Covers indexes on the first clustering column (among others).
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if (_is_key_range && _has_queriable_ck_index && !_has_multi_column) {
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_uses_secondary_indexing = true;
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}
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if (_uses_secondary_indexing || clustering_key_restrictions_need_filtering()) {
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_index_restrictions.push_back(_clustering_columns_restrictions);
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} else if (find_binop(_clustering_columns_restrictions, expr::is_on_collection)) {
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fail(unimplemented::cause::INDEXES);
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#if 0
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_index_restrictions.push_back(new Forwardingprimary_key_restrictions() {
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@Override
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protected primary_key_restrictions getDelegate()
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{
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return _clustering_columns_restrictions;
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}
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@Override
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public void add_index_expression_to(List<::shared_ptr<index_expression>> expressions, const query_options& options) throws InvalidRequestException
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{
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List<::shared_ptr<index_expression>> list = new ArrayList<>();
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super.add_index_expression_to(list, options);
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for (::shared_ptr<index_expression> expression : list)
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{
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if (expression.is_contains() || expression.is_containsKey())
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expressions.add(expression);
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}
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}
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});
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uses_secondary_indexing = true;
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#endif
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}
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if (!expr::is_empty_restriction(_nonprimary_key_restrictions)) {
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if (_has_queriable_regular_index && _partition_range_is_simple) {
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_uses_secondary_indexing = true;
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} else if (!allow_filtering) {
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throw exceptions::invalid_request_exception("Cannot execute this query as it might involve data filtering and "
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"thus may have unpredictable performance. If you want to execute "
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"this query despite the performance unpredictability, use ALLOW FILTERING");
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}
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_index_restrictions.push_back(_nonprimary_key_restrictions);
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}
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if (_uses_secondary_indexing && !(for_view || allow_filtering)) {
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validate_secondary_index_selections(selects_only_static_columns);
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}
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}
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const std::vector<expr::expression>& statement_restrictions::index_restrictions() const {
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return _index_restrictions;
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}
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// Current score table:
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// local and restrictions include full partition key: 2
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// global: 1
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// local and restrictions does not include full partition key: 0 (do not pick)
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int statement_restrictions::score(const secondary_index::index& index) const {
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if (index.metadata().local()) {
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const bool allow_local = !has_partition_key_unrestricted_components() && partition_key_restrictions_is_all_eq();
|
|
return allow_local ? 2 : 0;
|
|
}
|
|
return 1;
|
|
}
|
|
|
|
std::pair<std::optional<secondary_index::index>, expr::expression> statement_restrictions::find_idx(const secondary_index::secondary_index_manager& sim) const {
|
|
std::optional<secondary_index::index> chosen_index;
|
|
int chosen_index_score = 0;
|
|
expr::expression chosen_index_restrictions;
|
|
|
|
for (const auto& index : sim.list_indexes()) {
|
|
auto cdef = _schema->get_column_definition(to_bytes(index.target_column()));
|
|
for (const expr::expression& restriction : index_restrictions()) {
|
|
if (has_token(restriction) || contains_multi_column_restriction(restriction)) {
|
|
continue;
|
|
}
|
|
|
|
expr::single_column_restrictions_map rmap = expr::get_single_column_restrictions_map(restriction);
|
|
const auto found = rmap.find(cdef);
|
|
if (found != rmap.end() && is_supported_by(found->second, index)
|
|
&& score(index) > chosen_index_score) {
|
|
chosen_index = index;
|
|
chosen_index_score = score(index);
|
|
chosen_index_restrictions = restriction;
|
|
}
|
|
}
|
|
}
|
|
return {chosen_index, chosen_index_restrictions};
|
|
}
|
|
|
|
bool statement_restrictions::has_eq_restriction_on_column(const column_definition& column) const {
|
|
if (!_where.has_value()) {
|
|
return false;
|
|
}
|
|
|
|
return expr::has_eq_restriction_on_column(column, *_where);
|
|
}
|
|
|
|
std::vector<const column_definition*> statement_restrictions::get_column_defs_for_filtering(data_dictionary::database db) const {
|
|
std::vector<const column_definition*> column_defs_for_filtering;
|
|
if (need_filtering()) {
|
|
auto& sim = db.find_column_family(_schema).get_index_manager();
|
|
auto opt_idx = std::get<0>(find_idx(sim));
|
|
auto column_uses_indexing = [&opt_idx] (const column_definition* cdef, const expr::expression* single_col_restr) {
|
|
return opt_idx && single_col_restr && is_supported_by(*single_col_restr, *opt_idx);
|
|
};
|
|
if (pk_restrictions_need_filtering()) {
|
|
for (auto&& cdef : expr::get_sorted_column_defs(_partition_key_restrictions)) {
|
|
const expr::expression* single_col_restr = nullptr;
|
|
auto it = _single_column_partition_key_restrictions.find(cdef);
|
|
if (it != _single_column_partition_key_restrictions.end()) {
|
|
if (is_single_column_restriction(it->second)) {
|
|
single_col_restr = &it->second;
|
|
}
|
|
}
|
|
if (!column_uses_indexing(cdef, single_col_restr)) {
|
|
column_defs_for_filtering.emplace_back(cdef);
|
|
}
|
|
}
|
|
}
|
|
const bool pk_has_unrestricted_components = has_partition_key_unrestricted_components();
|
|
if (pk_has_unrestricted_components || clustering_key_restrictions_need_filtering()) {
|
|
column_id first_filtering_id = pk_has_unrestricted_components ? 0 : _schema->clustering_key_columns().begin()->id +
|
|
num_clustering_prefix_columns_that_need_not_be_filtered();
|
|
for (auto&& cdef : expr::get_sorted_column_defs(_clustering_columns_restrictions)) {
|
|
const expr::expression* single_col_restr = nullptr;
|
|
auto it = _single_column_partition_key_restrictions.find(cdef);
|
|
if (it != _single_column_partition_key_restrictions.end()) {
|
|
single_col_restr = &it->second;
|
|
}
|
|
if (cdef->id >= first_filtering_id && !column_uses_indexing(cdef, single_col_restr)) {
|
|
column_defs_for_filtering.emplace_back(cdef);
|
|
}
|
|
}
|
|
}
|
|
for (auto&& [cdef, cur_restr] : _single_column_nonprimary_key_restrictions) {
|
|
if (!column_uses_indexing(cdef, &cur_restr)) {
|
|
column_defs_for_filtering.emplace_back(cdef);
|
|
}
|
|
}
|
|
}
|
|
return column_defs_for_filtering;
|
|
}
|
|
|
|
void statement_restrictions::add_restriction(const expr::binary_operator& restr, schema_ptr schema, bool allow_filtering, bool for_view) {
|
|
if (restr.op == expr::oper_t::IS_NOT) {
|
|
// Handle IS NOT NULL restrictions seperately
|
|
add_is_not_restriction(restr, schema, for_view);
|
|
} else if (expr::is_multi_column(restr)) {
|
|
// Multi column restrictions are only allowed on clustering columns
|
|
add_multi_column_clustering_key_restriction(restr);
|
|
} else if (has_token(restr)) {
|
|
// Token always restricts the partition key
|
|
add_token_partition_key_restriction(restr);
|
|
} else if (expr::is_single_column_restriction(restr)) {
|
|
const column_definition* def = get_the_only_column(restr).col;
|
|
if (def->is_partition_key()) {
|
|
add_single_column_parition_key_restriction(restr, schema, allow_filtering, for_view);
|
|
} else if (def->is_clustering_key()) {
|
|
add_single_column_clustering_key_restriction(restr, schema, allow_filtering);
|
|
} else {
|
|
add_single_column_nonprimary_key_restriction(restr);
|
|
}
|
|
} else {
|
|
throw exceptions::invalid_request_exception(format("Unhandled restriction: {}", restr));
|
|
}
|
|
}
|
|
|
|
void statement_restrictions::add_is_not_restriction(const expr::binary_operator& restr, schema_ptr schema, bool for_view) {
|
|
const expr::column_value* lhs_col_def = expr::as_if<expr::column_value>(&restr.lhs);
|
|
// The "IS NOT NULL" restriction is only supported (and
|
|
// mandatory) for materialized view creation:
|
|
if (lhs_col_def == nullptr) {
|
|
throw exceptions::invalid_request_exception("IS NOT only supports single column");
|
|
}
|
|
// currently, the grammar only allows the NULL argument to be
|
|
// "IS NOT", so this assertion should not be able to fail
|
|
if (!expr::is<expr::constant>(restr.rhs) || !expr::as<expr::constant>(restr.rhs).is_null()) {
|
|
throw exceptions::invalid_request_exception("Only IS NOT NULL is supported");
|
|
}
|
|
|
|
_not_null_columns.insert(lhs_col_def->col);
|
|
|
|
if (!for_view) {
|
|
throw exceptions::invalid_request_exception(format("restriction '{}' is only supported in materialized view creation", restr));
|
|
}
|
|
}
|
|
|
|
void statement_restrictions::add_single_column_parition_key_restriction(const expr::binary_operator& restr, schema_ptr schema, bool allow_filtering, bool for_view) {
|
|
// View definition allows PK slices, because it's not a performance problem.
|
|
if (restr.op != expr::oper_t::EQ && restr.op != expr::oper_t::IN && !allow_filtering && !for_view) {
|
|
throw exceptions::invalid_request_exception(
|
|
"Only EQ and IN relation are supported on the partition key "
|
|
"(unless you use the token() function or allow filtering)");
|
|
}
|
|
if (has_token(_partition_key_restrictions)) {
|
|
throw exceptions::invalid_request_exception(
|
|
format("Columns \"{}\" cannot be restricted by both a normal relation and a token relation",
|
|
join(", ", expr::get_sorted_column_defs(_partition_key_restrictions))));
|
|
}
|
|
|
|
_partition_key_restrictions = expr::make_conjunction(_partition_key_restrictions, restr);
|
|
_partition_range_is_simple &= !find(restr, expr::oper_t::IN);
|
|
}
|
|
|
|
void statement_restrictions::add_token_partition_key_restriction(const expr::binary_operator& restr) {
|
|
if (!partition_key_restrictions_is_empty() && !has_token(_partition_key_restrictions)) {
|
|
throw exceptions::invalid_request_exception(
|
|
format("Columns \"{}\" cannot be restricted by both a normal relation and a token relation",
|
|
join(", ", expr::get_sorted_column_defs(_partition_key_restrictions))));
|
|
}
|
|
|
|
_partition_key_restrictions = expr::make_conjunction(_partition_key_restrictions, restr);
|
|
}
|
|
|
|
void statement_restrictions::add_single_column_clustering_key_restriction(const expr::binary_operator& restr, schema_ptr schema, bool allow_filtering) {
|
|
if (find_binop(_clustering_columns_restrictions, [] (const expr::binary_operator& b) {
|
|
return expr::is<expr::tuple_constructor>(b.lhs);
|
|
})) {
|
|
throw exceptions::invalid_request_exception(
|
|
"Mixing single column relations and multi column relations on clustering columns is not allowed");
|
|
}
|
|
|
|
const column_definition* new_column = expr::get_the_only_column(restr).col;
|
|
const column_definition* last_column = expr::get_last_column_def(_clustering_columns_restrictions);
|
|
|
|
if (last_column != nullptr && !allow_filtering) {
|
|
if (has_slice(_clustering_columns_restrictions) && schema->position(*new_column) > schema->position(*last_column)) {
|
|
throw exceptions::invalid_request_exception(format("Clustering column \"{}\" cannot be restricted (preceding column \"{}\" is restricted by a non-EQ relation)",
|
|
new_column->name_as_text(), last_column->name_as_text()));
|
|
}
|
|
|
|
if (schema->position(*new_column) < schema->position(*last_column)) {
|
|
if (has_slice(restr)) {
|
|
throw exceptions::invalid_request_exception(format("PRIMARY KEY column \"{}\" cannot be restricted (preceding column \"{}\" is restricted by a non-EQ relation)",
|
|
last_column->name_as_text(), new_column->name_as_text()));
|
|
}
|
|
}
|
|
}
|
|
|
|
_clustering_columns_restrictions = expr::make_conjunction(_clustering_columns_restrictions, restr);
|
|
}
|
|
|
|
void statement_restrictions::add_multi_column_clustering_key_restriction(const expr::binary_operator& restr) {
|
|
if (expr::is_empty_restriction(_clustering_columns_restrictions)) {
|
|
_clustering_columns_restrictions = restr;
|
|
return;
|
|
}
|
|
|
|
if (!find_binop(_clustering_columns_restrictions, [] (const expr::binary_operator& b) {
|
|
return expr::is<expr::tuple_constructor>(b.lhs);
|
|
})) {
|
|
throw exceptions::invalid_request_exception("Mixing single column relations and multi column relations on clustering columns is not allowed");
|
|
}
|
|
|
|
if (restr.op == expr::oper_t::EQ) {
|
|
throw exceptions::invalid_request_exception(format("{} cannot be restricted by more than one relation if it includes an Equal",
|
|
expr::get_columns_in_commons(_clustering_columns_restrictions, restr)));
|
|
} else if (restr.op == expr::oper_t::IN) {
|
|
throw exceptions::invalid_request_exception(format("{} cannot be restricted by more than one relation if it includes a IN",
|
|
expr::get_columns_in_commons(_clustering_columns_restrictions, restr)));
|
|
} else if (is_slice(restr.op)) {
|
|
if (!expr::has_slice(_clustering_columns_restrictions)) {
|
|
throw exceptions::invalid_request_exception(format("Column \"{}\" cannot be restricted by both an equality and an inequality relation",
|
|
expr::get_columns_in_commons(_clustering_columns_restrictions, restr)));
|
|
}
|
|
|
|
const expr::binary_operator* other_slice = expr::find_in_expression<expr::binary_operator>(_clustering_columns_restrictions, [](const expr::binary_operator){return true;});
|
|
if (other_slice == nullptr) {
|
|
on_internal_error(rlogger, "add_multi_column_clustering_key_restriction: _clustering_columns_restrictions is empty!");
|
|
}
|
|
|
|
// Don't allow to mix plain and SCYLLA_CLUSTERING_BOUND bounds
|
|
if (other_slice->order != restr.order) {
|
|
static auto order2str = [](auto o) { return o == expr::comparison_order::cql ? "plain" : "SCYLLA_CLUSTERING_BOUND"; };
|
|
throw exceptions::invalid_request_exception(
|
|
format("Invalid combination of restrictions ({} / {})",
|
|
order2str(other_slice->order), order2str(restr.order)));
|
|
}
|
|
|
|
// Here check that there aren't two < <= or two > and >=
|
|
auto is_greater = [](expr::oper_t op) {return op == expr::oper_t::GT || op == expr::oper_t::GTE; };
|
|
auto is_less = [](expr::oper_t op) {return op == expr::oper_t::LT || op == expr::oper_t::LTE; };
|
|
|
|
if (is_greater(restr.op) && is_greater(other_slice->op)) {
|
|
throw exceptions::invalid_request_exception(format(
|
|
"More than one restriction was found for the start bound on {}",
|
|
expr::get_columns_in_commons(restr, *other_slice)));
|
|
}
|
|
|
|
if (is_less(restr.op) && is_less(other_slice->op)) {
|
|
throw exceptions::invalid_request_exception(format(
|
|
"More than one restriction was found for the end bound on {}",
|
|
expr::get_columns_in_commons(restr, *other_slice)));
|
|
}
|
|
|
|
_clustering_columns_restrictions = expr::make_conjunction(_clustering_columns_restrictions, restr);
|
|
} else {
|
|
throw exceptions::invalid_request_exception(format("Unsupported multi-column relation: ", restr));
|
|
}
|
|
}
|
|
|
|
void statement_restrictions::add_single_column_nonprimary_key_restriction(const expr::binary_operator& restr) {
|
|
_nonprimary_key_restrictions = expr::make_conjunction(_nonprimary_key_restrictions, restr);
|
|
}
|
|
|
|
void statement_restrictions::process_partition_key_restrictions(bool for_view, bool allow_filtering) {
|
|
// If there is a queriable index, no special condition are required on the other restrictions.
|
|
// But we still need to know 2 things:
|
|
// - If we don't have a queriable index, is the query ok
|
|
// - Is it queriable without 2ndary index, which is always more efficient
|
|
// If a component of the partition key is restricted by a relation, all preceding
|
|
// components must have a EQ. Only the last partition key component can be in IN relation.
|
|
if (has_token(_partition_key_restrictions)) {
|
|
_is_key_range = true;
|
|
} else if (expr::is_empty_restriction(_partition_key_restrictions)) {
|
|
_is_key_range = true;
|
|
_uses_secondary_indexing = _has_queriable_pk_index;
|
|
}
|
|
|
|
if (pk_restrictions_need_filtering()) {
|
|
if (!allow_filtering && !for_view && !_has_queriable_pk_index) {
|
|
throw exceptions::invalid_request_exception("Cannot execute this query as it might involve data filtering and "
|
|
"thus may have unpredictable performance. If you want to execute "
|
|
"this query despite the performance unpredictability, use ALLOW FILTERING");
|
|
}
|
|
_is_key_range = true;
|
|
_uses_secondary_indexing = _has_queriable_pk_index;
|
|
}
|
|
|
|
}
|
|
|
|
bool statement_restrictions::has_partition_key_unrestricted_components() const {
|
|
std::vector<const column_definition*> pk_columns = expr::get_sorted_column_defs(_partition_key_restrictions);
|
|
bool all_restricted = pk_columns.size() == _schema->partition_key_size();
|
|
return !all_restricted;
|
|
}
|
|
|
|
bool statement_restrictions::partition_key_restrictions_is_empty() const {
|
|
return expr::is_empty_restriction(_partition_key_restrictions);
|
|
}
|
|
|
|
bool statement_restrictions::partition_key_restrictions_is_all_eq() const {
|
|
return expr::has_only_eq_binops(_partition_key_restrictions);
|
|
}
|
|
|
|
size_t statement_restrictions::partition_key_restrictions_size() const {
|
|
return expr::get_sorted_column_defs(_partition_key_restrictions).size();
|
|
}
|
|
|
|
bool statement_restrictions::pk_restrictions_need_filtering() const {
|
|
return !expr::is_empty_restriction(_partition_key_restrictions)
|
|
&& !has_token(_partition_key_restrictions)
|
|
&& (has_partition_key_unrestricted_components() || expr::has_slice_or_needs_filtering(_partition_key_restrictions));
|
|
}
|
|
|
|
size_t statement_restrictions::clustering_columns_restrictions_size() const {
|
|
return expr::get_sorted_column_defs(_clustering_columns_restrictions).size();
|
|
}
|
|
|
|
bool statement_restrictions::clustering_key_restrictions_need_filtering() const {
|
|
if (expr::contains_multi_column_restriction(_clustering_columns_restrictions)) {
|
|
return false;
|
|
}
|
|
|
|
return num_clustering_prefix_columns_that_need_not_be_filtered() < clustering_columns_restrictions_size();
|
|
}
|
|
|
|
bool statement_restrictions::has_unrestricted_clustering_columns() const {
|
|
return clustering_columns_restrictions_size() < _schema->clustering_key_size();
|
|
}
|
|
|
|
bool statement_restrictions::clustering_columns_restrictions_have_supporting_index(
|
|
const secondary_index::secondary_index_manager& index_manager,
|
|
expr::allow_local_index allow_local) const {
|
|
// Single column restrictions can be handled by the existing code
|
|
if (!expr::contains_multi_column_restriction(_clustering_columns_restrictions)) {
|
|
return expr::index_supports_some_column(_clustering_columns_restrictions, index_manager, allow_local);
|
|
}
|
|
|
|
// Multi column restrictions have to be handled separately
|
|
for (const auto& index : index_manager.list_indexes()) {
|
|
if (!allow_local && index.metadata().local()) {
|
|
continue;
|
|
}
|
|
if (multi_column_clustering_restrictions_are_supported_by(index)) {
|
|
return true;
|
|
}
|
|
}
|
|
return false;
|
|
}
|
|
|
|
bool statement_restrictions::multi_column_clustering_restrictions_are_supported_by(
|
|
const secondary_index::index& index) const {
|
|
// Slice restrictions have to be checked depending on the clustering slice
|
|
if (has_slice(_clustering_columns_restrictions)) {
|
|
bounds_slice clustering_slice = get_clustering_slice();
|
|
|
|
const expr::column_value* supported_column =
|
|
find_in_expression<expr::column_value>(_clustering_columns_restrictions,
|
|
[&](const expr::column_value& cval) -> bool {
|
|
return clustering_slice.is_supported_by(*cval.col, index);
|
|
}
|
|
);
|
|
return supported_column != nullptr;
|
|
}
|
|
|
|
// Otherwise it has to be a singe binary operator with EQ or IN.
|
|
// This is checked earlier during add_restriction.
|
|
const expr::binary_operator* single_binop =
|
|
expr::as_if<expr::binary_operator>(&_clustering_columns_restrictions);
|
|
if (single_binop == nullptr) {
|
|
on_internal_error(rlogger, format(
|
|
"multi_column_clustering_restrictions_are_supported_by more than one non-slice restriction: {}",
|
|
_clustering_columns_restrictions));
|
|
}
|
|
|
|
if (single_binop->op != expr::oper_t::IN && single_binop->op != expr::oper_t::EQ) {
|
|
on_internal_error(rlogger, format("Disallowed multi column restriction: {}", *single_binop));
|
|
}
|
|
|
|
const expr::column_value* supported_column =
|
|
find_in_expression<expr::column_value>(_clustering_columns_restrictions,
|
|
[&](const expr::column_value& cval) -> bool {
|
|
return index.supports_expression(*cval.col, single_binop->op);
|
|
}
|
|
);
|
|
return supported_column != nullptr;
|
|
}
|
|
|
|
bounds_slice statement_restrictions::get_clustering_slice() const {
|
|
std::optional<bounds_slice> result;
|
|
|
|
expr::for_each_expression<expr::binary_operator>(_clustering_columns_restrictions,
|
|
[&](const expr::binary_operator& binop) {
|
|
bounds_slice cur_slice = bounds_slice::from_binary_operator(binop);
|
|
if (!result.has_value()) {
|
|
result = cur_slice;
|
|
} else {
|
|
result->merge(cur_slice);
|
|
}
|
|
}
|
|
);
|
|
|
|
return *result;
|
|
}
|
|
|
|
bool statement_restrictions::parition_key_restrictions_have_supporting_index(const secondary_index::secondary_index_manager& index_manager,
|
|
expr::allow_local_index allow_local) const {
|
|
// Token restrictions can't be supported by an index
|
|
if (has_token(_partition_key_restrictions)) {
|
|
return false;
|
|
}
|
|
|
|
return expr::index_supports_some_column(_partition_key_restrictions, index_manager, allow_local);
|
|
}
|
|
|
|
void statement_restrictions::process_clustering_columns_restrictions(bool for_view, bool allow_filtering) {
|
|
if (!has_clustering_columns_restriction()) {
|
|
return;
|
|
}
|
|
|
|
if (find_binop(_clustering_columns_restrictions, expr::is_on_collection)
|
|
&& !_has_queriable_ck_index && !allow_filtering) {
|
|
throw exceptions::invalid_request_exception(
|
|
"Cannot restrict clustering columns by a CONTAINS relation without a secondary index or filtering");
|
|
}
|
|
|
|
if (has_clustering_columns_restriction() && clustering_key_restrictions_need_filtering()) {
|
|
if (_has_queriable_ck_index) {
|
|
_uses_secondary_indexing = true;
|
|
} else if (!allow_filtering && !for_view) {
|
|
auto clustering_columns_iter = _schema->clustering_key_columns().begin();
|
|
for (auto&& restricted_column : expr::get_sorted_column_defs(_clustering_columns_restrictions)) {
|
|
const column_definition* clustering_column = &(*clustering_columns_iter);
|
|
++clustering_columns_iter;
|
|
if (clustering_column != restricted_column) {
|
|
throw exceptions::invalid_request_exception(format("PRIMARY KEY column \"{}\" cannot be restricted as preceding column \"{}\" is not restricted",
|
|
restricted_column->name_as_text(), clustering_column->name_as_text()));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
namespace {
|
|
|
|
using namespace expr;
|
|
|
|
/// Computes partition-key ranges from token atoms in ex.
|
|
dht::partition_range_vector partition_ranges_from_token(const expr::expression& ex, const query_options& options) {
|
|
auto values = possible_lhs_values(nullptr, ex, options);
|
|
if (values == expr::value_set(expr::value_list{})) {
|
|
return {};
|
|
}
|
|
const auto bounds = expr::to_range(values);
|
|
const auto start_token = bounds.start() ? bounds.start()->value().with_linearized([] (bytes_view bv) { return dht::token::from_bytes(bv); })
|
|
: dht::minimum_token();
|
|
auto end_token = bounds.end() ? bounds.end()->value().with_linearized([] (bytes_view bv) { return dht::token::from_bytes(bv); })
|
|
: dht::maximum_token();
|
|
const bool include_start = bounds.start() && bounds.start()->is_inclusive();
|
|
const auto include_end = bounds.end() && bounds.end()->is_inclusive();
|
|
|
|
auto start = dht::partition_range::bound(include_start
|
|
? dht::ring_position::starting_at(start_token)
|
|
: dht::ring_position::ending_at(start_token));
|
|
auto end = dht::partition_range::bound(include_end
|
|
? dht::ring_position::ending_at(end_token)
|
|
: dht::ring_position::starting_at(end_token));
|
|
|
|
return {{std::move(start), std::move(end)}};
|
|
}
|
|
|
|
/// Turns a partition-key value into a partition_range. \p pk must have elements for all partition columns.
|
|
dht::partition_range range_from_bytes(const schema& schema, const std::vector<managed_bytes>& pk) {
|
|
const auto k = partition_key::from_exploded(pk);
|
|
const auto tok = dht::get_token(schema, k);
|
|
const query::ring_position pos(std::move(tok), std::move(k));
|
|
return dht::partition_range::make_singular(std::move(pos));
|
|
}
|
|
|
|
void error_if_exceeds(size_t size, size_t limit) {
|
|
if (size > limit) {
|
|
throw std::runtime_error(
|
|
fmt::format("clustering-key cartesian product size {} is greater than maximum {}", size, limit));
|
|
}
|
|
}
|
|
|
|
/// Computes partition-key ranges from expressions, which contains EQ/IN for every partition column.
|
|
dht::partition_range_vector partition_ranges_from_singles(
|
|
const std::vector<expr::expression>& expressions, const query_options& options, const schema& schema) {
|
|
const size_t size_limit =
|
|
options.get_cql_config().restrictions.partition_key_restrictions_max_cartesian_product_size;
|
|
// Each element is a vector of that column's possible values:
|
|
std::vector<std::vector<managed_bytes>> column_values(schema.partition_key_size());
|
|
size_t product_size = 1;
|
|
for (const auto& e : expressions) {
|
|
if (const auto arbitrary_binop = find_binop(e, [] (const binary_operator&) { return true; })) {
|
|
if (auto cv = expr::as_if<expr::column_value>(&arbitrary_binop->lhs)) {
|
|
const value_set vals = possible_lhs_values(cv->col, e, options);
|
|
if (auto lst = std::get_if<value_list>(&vals)) {
|
|
if (lst->empty()) {
|
|
return {};
|
|
}
|
|
product_size *= lst->size();
|
|
error_if_exceeds(product_size, size_limit);
|
|
column_values[schema.position(*cv->col)] = std::move(*lst);
|
|
} else {
|
|
throw exceptions::invalid_request_exception(
|
|
"Only EQ and IN relation are supported on the partition key "
|
|
"(unless you use the token() function or allow filtering)");
|
|
}
|
|
}
|
|
}
|
|
}
|
|
cartesian_product cp(column_values);
|
|
dht::partition_range_vector ranges(product_size);
|
|
std::transform(cp.begin(), cp.end(), ranges.begin(), std::bind_front(range_from_bytes, std::ref(schema)));
|
|
return ranges;
|
|
}
|
|
|
|
/// Computes partition-key ranges from EQ restrictions on each partition column. Returns a single singleton range if
|
|
/// the EQ restrictions are not mutually conflicting. Otherwise, returns an empty vector.
|
|
dht::partition_range_vector partition_ranges_from_EQs(
|
|
const std::vector<expr::expression>& eq_expressions, const query_options& options, const schema& schema) {
|
|
std::vector<managed_bytes> pk_value(schema.partition_key_size());
|
|
for (const auto& e : eq_expressions) {
|
|
const auto col = expr::get_subscripted_column(find(e, oper_t::EQ)->lhs).col;
|
|
const auto vals = std::get<value_list>(possible_lhs_values(col, e, options));
|
|
if (vals.empty()) { // Case of C=1 AND C=2.
|
|
return {};
|
|
}
|
|
pk_value[schema.position(*col)] = std::move(vals[0]);
|
|
}
|
|
return {range_from_bytes(schema, pk_value)};
|
|
}
|
|
|
|
} // anonymous namespace
|
|
|
|
dht::partition_range_vector statement_restrictions::get_partition_key_ranges(const query_options& options) const {
|
|
if (_partition_range_restrictions.empty()) {
|
|
return {dht::partition_range::make_open_ended_both_sides()};
|
|
}
|
|
if (has_token(_partition_range_restrictions[0])) {
|
|
if (_partition_range_restrictions.size() != 1) {
|
|
on_internal_error(
|
|
rlogger,
|
|
format("Unexpected size of token restrictions: {}", _partition_range_restrictions.size()));
|
|
}
|
|
return partition_ranges_from_token(_partition_range_restrictions[0], options);
|
|
} else if (_partition_range_is_simple) {
|
|
// Special case to avoid extra allocations required for a Cartesian product.
|
|
return partition_ranges_from_EQs(_partition_range_restrictions, options, *_schema);
|
|
}
|
|
return partition_ranges_from_singles(_partition_range_restrictions, options, *_schema);
|
|
}
|
|
|
|
namespace {
|
|
|
|
using namespace expr;
|
|
|
|
clustering_key_prefix::prefix_equal_tri_compare get_unreversed_tri_compare(const schema& schema) {
|
|
clustering_key_prefix::prefix_equal_tri_compare cmp(schema);
|
|
std::vector<data_type> types = cmp.prefix_type->types();
|
|
for (auto& t : types) {
|
|
if (t->is_reversed()) {
|
|
t = t->underlying_type();
|
|
}
|
|
}
|
|
cmp.prefix_type = make_lw_shared<compound_type<allow_prefixes::yes>>(types);
|
|
return cmp;
|
|
}
|
|
|
|
/// True iff r1 start is strictly before r2 start.
|
|
bool starts_before_start(
|
|
const query::clustering_range& r1,
|
|
const query::clustering_range& r2,
|
|
const clustering_key_prefix::prefix_equal_tri_compare& cmp) {
|
|
if (!r2.start()) {
|
|
return false; // r2 start is -inf, nothing is before that.
|
|
}
|
|
if (!r1.start()) {
|
|
return true; // r1 start is -inf, while r2 start is finite.
|
|
}
|
|
const auto diff = cmp(r1.start()->value(), r2.start()->value());
|
|
if (diff < 0) { // r1 start is strictly before r2 start.
|
|
return true;
|
|
}
|
|
if (diff > 0) { // r1 start is strictly after r2 start.
|
|
return false;
|
|
}
|
|
const auto len1 = r1.start()->value().representation().size();
|
|
const auto len2 = r2.start()->value().representation().size();
|
|
if (len1 == len2) { // The values truly are equal.
|
|
return r1.start()->is_inclusive() && !r2.start()->is_inclusive();
|
|
} else if (len1 < len2) { // r1 start is a prefix of r2 start.
|
|
// (a)>=(1) starts before (a,b)>=(1,1), but (a)>(1) doesn't.
|
|
return r1.start()->is_inclusive();
|
|
} else { // r2 start is a prefix of r1 start.
|
|
// (a,b)>=(1,1) starts before (a)>(1) but after (a)>=(1).
|
|
return r2.start()->is_inclusive();
|
|
}
|
|
}
|
|
|
|
/// True iff r1 start is before (or identical as) r2 end.
|
|
bool starts_before_or_at_end(
|
|
const query::clustering_range& r1,
|
|
const query::clustering_range& r2,
|
|
const clustering_key_prefix::prefix_equal_tri_compare& cmp) {
|
|
if (!r1.start()) {
|
|
return true; // r1 start is -inf, must be before r2 end.
|
|
}
|
|
if (!r2.end()) {
|
|
return true; // r2 end is +inf, everything is before it.
|
|
}
|
|
const auto diff = cmp(r1.start()->value(), r2.end()->value());
|
|
if (diff < 0) { // r1 start is strictly before r2 end.
|
|
return true;
|
|
}
|
|
if (diff > 0) { // r1 start is strictly after r2 end.
|
|
return false;
|
|
}
|
|
const auto len1 = r1.start()->value().representation().size();
|
|
const auto len2 = r2.end()->value().representation().size();
|
|
if (len1 == len2) { // The values truly are equal.
|
|
return r1.start()->is_inclusive() && r2.end()->is_inclusive();
|
|
} else if (len1 < len2) { // r1 start is a prefix of r2 end.
|
|
// a>=(1) starts before (a,b)<=(1,1) ends, but (a)>(1) doesn't.
|
|
return r1.start()->is_inclusive();
|
|
} else { // r2 end is a prefix of r1 start.
|
|
// (a,b)>=(1,1) starts before (a)<=(1) ends but after (a)<(1) ends.
|
|
return r2.end()->is_inclusive();
|
|
}
|
|
}
|
|
|
|
/// True if r1 end is strictly before r2 end.
|
|
bool ends_before_end(
|
|
const query::clustering_range& r1,
|
|
const query::clustering_range& r2,
|
|
const clustering_key_prefix::prefix_equal_tri_compare& cmp) {
|
|
if (!r1.end()) {
|
|
return false; // r1 end is +inf, which is after everything.
|
|
}
|
|
if (!r2.end()) {
|
|
return true; // r2 end is +inf, while r1 end is finite.
|
|
}
|
|
const auto diff = cmp(r1.end()->value(), r2.end()->value());
|
|
if (diff < 0) { // r1 end is strictly before r2 end.
|
|
return true;
|
|
}
|
|
if (diff > 0) { // r1 end is strictly after r2 end.
|
|
return false;
|
|
}
|
|
const auto len1 = r1.end()->value().representation().size();
|
|
const auto len2 = r2.end()->value().representation().size();
|
|
if (len1 == len2) { // The values truly are equal.
|
|
return !r1.end()->is_inclusive() && r2.end()->is_inclusive();
|
|
} else if (len1 < len2) { // r1 end is a prefix of r2 end.
|
|
// (a)<(1) ends before (a,b)<=(1,1), but (a)<=(1) doesn't.
|
|
return !r1.end()->is_inclusive();
|
|
} else { // r2 end is a prefix of r1 end.
|
|
// (a,b)<=(1,1) ends before (a)<=(1) but after (a)<(1).
|
|
return r2.end()->is_inclusive();
|
|
}
|
|
}
|
|
|
|
/// Correct clustering_range intersection. See #8157.
|
|
std::optional<query::clustering_range> intersection(
|
|
const query::clustering_range& r1,
|
|
const query::clustering_range& r2,
|
|
const clustering_key_prefix::prefix_equal_tri_compare& cmp) {
|
|
// Assume r1's start is to the left of r2's start.
|
|
if (starts_before_start(r2, r1, cmp)) {
|
|
return intersection(r2, r1, cmp);
|
|
}
|
|
if (!starts_before_or_at_end(r2, r1, cmp)) {
|
|
return {};
|
|
}
|
|
const auto& intersection_start = r2.start();
|
|
const auto& intersection_end = ends_before_end(r1, r2, cmp) ? r1.end() : r2.end();
|
|
if (intersection_start == intersection_end && intersection_end.has_value()) {
|
|
return query::clustering_range::make_singular(intersection_end->value());
|
|
}
|
|
return query::clustering_range(intersection_start, intersection_end);
|
|
}
|
|
|
|
struct range_less {
|
|
const class schema& s;
|
|
clustering_key_prefix::less_compare cmp = clustering_key_prefix::less_compare(s);
|
|
bool operator()(const query::clustering_range& x, const query::clustering_range& y) const {
|
|
if (!x.start() && !y.start()) {
|
|
return false;
|
|
}
|
|
if (!x.start()) {
|
|
return true;
|
|
}
|
|
if (!y.start()) {
|
|
return false;
|
|
}
|
|
return cmp(x.start()->value(), y.start()->value());
|
|
}
|
|
};
|
|
|
|
/// An expression visitor that translates multi-column atoms into clustering ranges.
|
|
struct multi_column_range_accumulator {
|
|
const query_options& options;
|
|
const schema_ptr schema;
|
|
std::vector<query::clustering_range> ranges{query::clustering_range::make_open_ended_both_sides()};
|
|
const clustering_key_prefix::prefix_equal_tri_compare prefix3cmp = get_unreversed_tri_compare(*schema);
|
|
|
|
void operator()(const binary_operator& binop) {
|
|
if (is_compare(binop.op)) {
|
|
auto opt_values = expr::get_tuple_elements(expr::evaluate(binop.rhs, options), *type_of(binop.rhs));
|
|
auto& lhs = expr::as<tuple_constructor>(binop.lhs);
|
|
std::vector<managed_bytes> values(lhs.elements.size());
|
|
for (size_t i = 0; i < lhs.elements.size(); ++i) {
|
|
auto& col = expr::as<column_value>(lhs.elements.at(i));
|
|
values[i] = *statements::request_validations::check_not_null(
|
|
opt_values[i],
|
|
"Invalid null value in condition for column {}", col.col->name_as_text());
|
|
}
|
|
intersect_all(to_range(binop.op, clustering_key_prefix(std::move(values))));
|
|
} else if (binop.op == oper_t::IN) {
|
|
const cql3::raw_value tup = expr::evaluate(binop.rhs, options);
|
|
statements::request_validations::check_false(tup.is_null(), "Invalid null value for IN restriction");
|
|
process_in_values(expr::get_list_of_tuples_elements(tup, *type_of(binop.rhs)));
|
|
} else {
|
|
on_internal_error(rlogger, format("multi_column_range_accumulator: unexpected atom {}", binop));
|
|
}
|
|
}
|
|
|
|
void operator()(const conjunction& c) {
|
|
std::ranges::for_each(c.children, [this] (const expression& child) { expr::visit(*this, child); });
|
|
}
|
|
|
|
void operator()(const constant& v) {
|
|
std::optional<bool> bool_val = get_bool_value(v);
|
|
if (!bool_val.has_value()) {
|
|
on_internal_error(rlogger, "non-bool constant encountered outside binary operator");
|
|
}
|
|
|
|
if (*bool_val == false) {
|
|
ranges.clear();
|
|
}
|
|
}
|
|
|
|
void operator()(const column_value&) {
|
|
on_internal_error(rlogger, "Column encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const subscript&) {
|
|
on_internal_error(rlogger, "Subscript encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const token&) {
|
|
on_internal_error(rlogger, "Token encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const unresolved_identifier&) {
|
|
on_internal_error(rlogger, "Unresolved identifier encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const column_mutation_attribute&) {
|
|
on_internal_error(rlogger, "writetime/ttl encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const function_call&) {
|
|
on_internal_error(rlogger, "function call encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const cast&) {
|
|
on_internal_error(rlogger, "typecast encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const field_selection&) {
|
|
on_internal_error(rlogger, "field selection encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const null&) {
|
|
on_internal_error(rlogger, "null encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const bind_variable&) {
|
|
on_internal_error(rlogger, "bind variable encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const untyped_constant&) {
|
|
on_internal_error(rlogger, "untyped constant encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const tuple_constructor&) {
|
|
on_internal_error(rlogger, "tuple constructor encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const collection_constructor&) {
|
|
on_internal_error(rlogger, "collection constructor encountered outside binary operator");
|
|
}
|
|
|
|
void operator()(const usertype_constructor&) {
|
|
on_internal_error(rlogger, "collection constructor encountered outside binary operator");
|
|
}
|
|
|
|
/// Intersects each range with v. If any intersection is empty, clears ranges.
|
|
void intersect_all(const query::clustering_range& v) {
|
|
for (auto& r : ranges) {
|
|
auto intrs = intersection(r, v, prefix3cmp);
|
|
if (!intrs) {
|
|
ranges.clear();
|
|
break;
|
|
}
|
|
r = *intrs;
|
|
}
|
|
}
|
|
|
|
template<std::ranges::range Range>
|
|
requires std::convertible_to<typename Range::value_type::value_type, managed_bytes_opt>
|
|
void process_in_values(Range in_values) {
|
|
if (ranges.empty()) {
|
|
return; // Shortcircuit an easy case.
|
|
}
|
|
std::set<query::clustering_range, range_less> new_ranges(range_less{*schema});
|
|
for (const auto& current_tuple : in_values) {
|
|
// Each IN value is like a separate EQ restriction ANDed to the existing state.
|
|
auto current_range = to_range(
|
|
oper_t::EQ, clustering_key_prefix::from_optional_exploded(*schema, current_tuple));
|
|
for (const auto& r : ranges) {
|
|
auto intrs = intersection(r, current_range, prefix3cmp);
|
|
if (intrs) {
|
|
new_ranges.insert(*intrs);
|
|
}
|
|
}
|
|
}
|
|
ranges.assign(new_ranges.cbegin(), new_ranges.cend());
|
|
}
|
|
};
|
|
|
|
/// Calculates clustering bounds for the multi-column case.
|
|
std::vector<query::clustering_range> get_multi_column_clustering_bounds(
|
|
const query_options& options,
|
|
schema_ptr schema,
|
|
const std::vector<expression>& multi_column_restrictions) {
|
|
multi_column_range_accumulator acc{options, schema};
|
|
for (const auto& restr : multi_column_restrictions) {
|
|
expr::visit(acc, restr);
|
|
}
|
|
return acc.ranges;
|
|
}
|
|
|
|
/// Reverses the range if the type is reversed. Why don't we have nonwrapping_interval::reverse()??
|
|
query::clustering_range reverse_if_reqd(query::clustering_range r, const abstract_type& t) {
|
|
return t.is_reversed() ? query::clustering_range(r.end(), r.start()) : std::move(r);
|
|
}
|
|
|
|
constexpr bool inclusive = true;
|
|
|
|
/// Calculates clustering bounds for the single-column case.
|
|
std::vector<query::clustering_range> get_single_column_clustering_bounds(
|
|
const query_options& options,
|
|
const schema& schema,
|
|
const std::vector<expression>& single_column_restrictions) {
|
|
const size_t size_limit =
|
|
options.get_cql_config().restrictions.clustering_key_restrictions_max_cartesian_product_size;
|
|
size_t product_size = 1;
|
|
std::vector<std::vector<managed_bytes>> prior_column_values; // Equality values of columns seen so far.
|
|
for (size_t i = 0; i < single_column_restrictions.size(); ++i) {
|
|
auto values = possible_lhs_values(
|
|
&schema.clustering_column_at(i), // This should be the LHS of restrictions[i].
|
|
single_column_restrictions[i],
|
|
options);
|
|
if (auto list = std::get_if<value_list>(&values)) {
|
|
if (list->empty()) { // Impossible condition -- no rows can possibly match.
|
|
return {};
|
|
}
|
|
product_size *= list->size();
|
|
prior_column_values.push_back(std::move(*list));
|
|
error_if_exceeds(product_size, size_limit);
|
|
} else if (auto last_range = std::get_if<nonwrapping_interval<managed_bytes>>(&values)) {
|
|
// Must be the last column in the prefix, since it's neither EQ nor IN.
|
|
std::vector<query::clustering_range> ck_ranges;
|
|
if (prior_column_values.empty()) {
|
|
// This is the first and last range; just turn it into a clustering_key_prefix.
|
|
ck_ranges.push_back(
|
|
reverse_if_reqd(
|
|
last_range->transform([] (const managed_bytes& val) { return clustering_key_prefix::from_range(std::array<managed_bytes, 1>{val}); }),
|
|
*schema.clustering_column_at(i).type));
|
|
} else {
|
|
// Prior clustering columns are equality-restricted (either via = or IN), producing one or more
|
|
// prior_column_values elements. Now we will turn each such element into a CK range dictated by those
|
|
// equalities and this inequality represented by last_range. Each CK range's upper/lower bound is
|
|
// formed by extending the Cartesian-product element with the corresponding last_range bound, if it
|
|
// exists; if it doesn't, the CK range bound is just the Cartesian-product element, inclusive.
|
|
//
|
|
// For example, the expression `c1=1 AND c2=2 AND c3>3` makes lower CK bound (1,2,3) exclusive and
|
|
// upper CK bound (1,2) inclusive.
|
|
ck_ranges.reserve(product_size);
|
|
const auto extra_lb = last_range->start(), extra_ub = last_range->end();
|
|
for (auto& b : cartesian_product(prior_column_values)) {
|
|
auto new_lb = b, new_ub = b;
|
|
if (extra_lb) {
|
|
new_lb.push_back(extra_lb->value());
|
|
}
|
|
if (extra_ub) {
|
|
new_ub.push_back(extra_ub->value());
|
|
}
|
|
query::clustering_range::bound new_start(new_lb, extra_lb ? extra_lb->is_inclusive() : inclusive);
|
|
query::clustering_range::bound new_end (new_ub, extra_ub ? extra_ub->is_inclusive() : inclusive);
|
|
ck_ranges.push_back(reverse_if_reqd({new_start, new_end}, *schema.clustering_column_at(i).type));
|
|
}
|
|
}
|
|
sort(ck_ranges.begin(), ck_ranges.end(), range_less{schema});
|
|
return ck_ranges;
|
|
}
|
|
}
|
|
// All prefix columns are restricted by EQ or IN. The resulting CK ranges are just singular ranges of corresponding
|
|
// prior_column_values.
|
|
std::vector<query::clustering_range> ck_ranges(product_size);
|
|
cartesian_product cp(prior_column_values);
|
|
std::transform(cp.begin(), cp.end(), ck_ranges.begin(), std::bind_front(query::clustering_range::make_singular));
|
|
sort(ck_ranges.begin(), ck_ranges.end(), range_less{schema});
|
|
return ck_ranges;
|
|
}
|
|
|
|
// In old v1 indexes the token column was of type blob.
|
|
// This causes problems because blobs are sorted differently than the bigint token values that they represent.
|
|
// Tokens are encoded as 8 byte big endian two's complement signed integers,
|
|
// which with blob sorting makes them ordered like this:
|
|
// 0, 1, 2, 3, 4, 5, ..., bigint_max, bigint_min, ...., -5, -4, -3, -2, -1
|
|
// Because of this clustering restrictions like token(p) > -4 and token(p) < 4 need to be translated
|
|
// to two clustering ranges on the old index.
|
|
// All binary_operators in token_restriction must have column_value{token_column} as their LHS.
|
|
static std::vector<query::clustering_range> get_index_v1_token_range_clustering_bounds(
|
|
const query_options& options,
|
|
const column_definition& token_column,
|
|
const expression& token_restriction) {
|
|
|
|
// A workaround in order to make possible_lhs_values work properly.
|
|
// possible_lhs_values looks at the column type and uses this type's comparator.
|
|
// This is a problem because when using blob's comparator, -4 is greater than 4.
|
|
// This makes possible_lhs_values think that an expression like token(p) > -4 and token(p) < 4
|
|
// is impossible to fulfill.
|
|
// Create a fake token column with the type set to bigint, translate the restriction to use this column
|
|
// and use this restriction to calculate possible lhs values.
|
|
column_definition token_column_bigint = token_column;
|
|
token_column_bigint.type = long_type;
|
|
expression new_token_restrictions = replace_column_def(token_restriction, &token_column_bigint);
|
|
|
|
std::variant<value_list, nonwrapping_range<managed_bytes>> values =
|
|
possible_lhs_values(&token_column_bigint, new_token_restrictions, options);
|
|
|
|
return std::visit(overloaded_functor {
|
|
[](const value_list& list) {
|
|
std::vector<query::clustering_range> ck_ranges;
|
|
ck_ranges.reserve(list.size());
|
|
|
|
for (auto&& value : list) {
|
|
ck_ranges.emplace_back(query::clustering_range::make_singular(std::vector<managed_bytes>{value}));
|
|
}
|
|
|
|
return ck_ranges;
|
|
},
|
|
[](const nonwrapping_interval<managed_bytes>& range) {
|
|
auto int64_from_be_bytes = [](const managed_bytes& int_bytes) -> int64_t {
|
|
if (int_bytes.size() != 8) {
|
|
throw std::runtime_error("token restriction value should be 8 bytes");
|
|
}
|
|
|
|
return read_be<int64_t>((const char*)&int_bytes[0]);
|
|
};
|
|
|
|
auto int64_to_be_bytes = [](int64_t int_val) -> managed_bytes {
|
|
managed_bytes int_bytes(managed_bytes::initialized_later{}, 8);
|
|
write_be((char*)&int_bytes[0], int_val);
|
|
return int_bytes;
|
|
};
|
|
|
|
int64_t token_low = std::numeric_limits<int64_t>::min();
|
|
int64_t token_high = std::numeric_limits<int64_t>::max();
|
|
bool low_inclusive = true, high_inclusive = true;
|
|
|
|
const std::optional<interval_bound<managed_bytes>>& start = range.start();
|
|
const std::optional<interval_bound<managed_bytes>>& end = range.end();
|
|
|
|
if (start.has_value()) {
|
|
token_low = int64_from_be_bytes(start->value());
|
|
low_inclusive = start->is_inclusive();
|
|
}
|
|
|
|
if (end.has_value()) {
|
|
token_high = int64_from_be_bytes(end->value());
|
|
high_inclusive = end->is_inclusive();
|
|
}
|
|
|
|
query::clustering_range::bound lower_bound(std::vector({int64_to_be_bytes(token_low)}), low_inclusive);
|
|
query::clustering_range::bound upper_bound(std::vector({int64_to_be_bytes(token_high)}), high_inclusive);
|
|
|
|
std::vector<query::clustering_range> ck_ranges;
|
|
|
|
if (token_high < token_low) {
|
|
// Impossible range, return empty clustering ranges
|
|
return ck_ranges;
|
|
}
|
|
|
|
// Blob encoded tokens are sorted like this:
|
|
// 0, 1, 2, 3, 4, 5, ..., bigint_max, bigint_min, ...., -5, -4, -3, -2, -1
|
|
// This means that in cases where low >= 0 or high < 0 we can simply use the whole range.
|
|
// In other cases we have to take two ranges: (low, -1] and [0, high).
|
|
if (token_low >= 0 || token_high < 0) {
|
|
ck_ranges.emplace_back(std::move(lower_bound), std::move(upper_bound));
|
|
} else {
|
|
query::clustering_range::bound zero_bound(std::vector({int64_to_be_bytes(0)}));
|
|
query::clustering_range::bound min1_bound(std::vector({int64_to_be_bytes(-1)}));
|
|
|
|
ck_ranges.reserve(2);
|
|
|
|
if (!(token_high == 0 && !high_inclusive)) {
|
|
ck_ranges.emplace_back(std::move(zero_bound), std::move(upper_bound));
|
|
}
|
|
|
|
if (!(token_low == -1 && !low_inclusive)) {
|
|
ck_ranges.emplace_back(std::move(lower_bound), std::move(min1_bound));
|
|
}
|
|
}
|
|
|
|
return ck_ranges;
|
|
}
|
|
}, values);
|
|
}
|
|
|
|
using opt_bound = std::optional<query::clustering_range::bound>;
|
|
|
|
/// Makes a partial bound out of whole_bound's prefix. If the partial bound is strictly shorter than the whole, it is
|
|
/// exclusive. Otherwise, it matches the whole_bound's inclusivity.
|
|
opt_bound make_prefix_bound(
|
|
size_t prefix_len, const std::vector<bytes>& whole_bound, bool whole_bound_is_inclusive) {
|
|
if (whole_bound.empty()) {
|
|
return {};
|
|
}
|
|
// Couldn't get std::ranges::subrange(whole_bound, prefix_len) to compile :(
|
|
std::vector<bytes> partial_bound(
|
|
whole_bound.cbegin(), whole_bound.cbegin() + std::min(prefix_len, whole_bound.size()));
|
|
return query::clustering_range::bound(
|
|
clustering_key_prefix(std::move(partial_bound)),
|
|
prefix_len >= whole_bound.size() && whole_bound_is_inclusive);
|
|
}
|
|
|
|
/// Given a multi-column range in CQL order, breaks it into an equivalent union of clustering-order ranges. Returns
|
|
/// those ranges as vector elements.
|
|
///
|
|
/// A difference between CQL order and clustering order means that the right-hand side of a clustering-key comparison is
|
|
/// not necessarily a single (lower or upper) bound on the clustering key in storage. Eg, `WITH CLUSTERING ORDER BY (a
|
|
/// ASC, b DESC)` indicates that "a less than 5" means "a comes before 5 in storage", but "b less than 5" means "b comes
|
|
/// AFTER 5 in storage". Therefore the CQL expression (a,b)<(5,5) cannot be executed by fetching a single range from
|
|
/// the storage layer -- the right-hand side is not a single upper bound from the storage layer's perspective.
|
|
///
|
|
/// When translating the WHERE clause into clustering ranges to fetch, it's natural to first calculate the CQL-order
|
|
/// ranges: comparisons define ranges, the AND operator intersects them, the IN operator makes a Cartesian product. The
|
|
/// result of this is a union of ranges in CQL order that define the clustering slice to fetch. And if the clustering
|
|
/// order is the same as the CQL order, these ranges can be sent to the storage proxy directly to fetch the correct
|
|
/// result. But if the two orders differ, there is some work to be done first. This is simple enough for ranges that
|
|
/// only vary a single column -- see reverse_if_reqd(). Multi-column ranges are more complicated; they are translated
|
|
/// into an equivalent union of clustering-order ranges by get_equivalent_ranges().
|
|
///
|
|
/// Continuing the above example, we can translate the CQL expression (a,b)<(5,5) into a union of several ranges that
|
|
/// are continuous in storage. We begin by observing that (a,b)<(5,5) is the same as a<5 OR (a=5 AND b<5). This is a
|
|
/// union of two ranges: the range corresponding to a<5, plus the range corresponding to (a=5 AND b<5). Note that both
|
|
/// of these ranges are continuous in storage because they only vary a single column:
|
|
///
|
|
/// * a<5 is a range from -inf to clustering_key_prefix(5) exclusive
|
|
///
|
|
/// * (a=5 AND b<5) is a range from clustering_key_prefix(5,5) exclusive to clustering_key_prefix(5) inclusive; note
|
|
/// the clustering order between those start/end bounds
|
|
///
|
|
/// Here is an illustration of those two ranges in storage, with rows represented vertically and clustering-ordered left
|
|
/// to right:
|
|
///
|
|
/// a: 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6
|
|
/// b: 5 4 3 2 1 0 7 6 5 4 3 2 1 0 5 4 3 2 1
|
|
/// 1st range ^^^^^^^^^^^ ^^^^^^^^^ 2nd range
|
|
///
|
|
/// For more examples of this range translation, please see the statement_restrictions unit tests.
|
|
std::vector<query::clustering_range> get_equivalent_ranges(
|
|
const query::clustering_range& cql_order_range, const schema& schema) {
|
|
const auto& cql_lb = cql_order_range.start();
|
|
const auto& cql_ub = cql_order_range.end();
|
|
if (cql_lb == cql_ub && (!cql_lb || cql_lb->is_inclusive())) {
|
|
return {cql_order_range};
|
|
}
|
|
const auto cql_lb_bytes = cql_lb ? cql_lb->value().explode(schema) : std::vector<bytes>{};
|
|
const auto cql_ub_bytes = cql_ub ? cql_ub->value().explode(schema) : std::vector<bytes>{};
|
|
const bool cql_lb_is_inclusive = cql_lb ? cql_lb->is_inclusive() : false;
|
|
const bool cql_ub_is_inclusive = cql_ub ? cql_ub->is_inclusive() : false;
|
|
|
|
size_t common_prefix_len = 0;
|
|
// Skip equal values; they don't contribute to equivalent-range generation.
|
|
while (common_prefix_len < cql_lb_bytes.size() && common_prefix_len < cql_ub_bytes.size() &&
|
|
cql_lb_bytes[common_prefix_len] == cql_ub_bytes[common_prefix_len]) {
|
|
++common_prefix_len;
|
|
}
|
|
|
|
std::vector<query::clustering_range> ranges;
|
|
// First range is special: it has both bounds.
|
|
opt_bound lb1 = make_prefix_bound(
|
|
common_prefix_len + 1, cql_lb_bytes, cql_lb_is_inclusive);
|
|
opt_bound ub1 = make_prefix_bound(
|
|
common_prefix_len + 1, cql_ub_bytes, cql_ub_is_inclusive);
|
|
auto range1 = schema.clustering_column_at(common_prefix_len).type->is_reversed() ?
|
|
query::clustering_range(ub1, lb1) : query::clustering_range(lb1, ub1);
|
|
ranges.push_back(std::move(range1));
|
|
|
|
for (size_t p = common_prefix_len + 2; p <= cql_lb_bytes.size(); ++p) {
|
|
opt_bound lb = make_prefix_bound(p, cql_lb_bytes, cql_lb_is_inclusive);
|
|
opt_bound ub = make_prefix_bound(p - 1, cql_lb_bytes, /*irrelevant:*/true);
|
|
if (ub) {
|
|
ub = query::clustering_range::bound(ub->value(), inclusive);
|
|
}
|
|
auto range = schema.clustering_column_at(p - 1).type->is_reversed() ?
|
|
query::clustering_range(ub, lb) : query::clustering_range(lb, ub);
|
|
ranges.push_back(std::move(range));
|
|
}
|
|
|
|
for (size_t p = common_prefix_len + 2; p <= cql_ub_bytes.size(); ++p) {
|
|
// Note the difference from the cql_lb_bytes case above!
|
|
opt_bound ub = make_prefix_bound(p, cql_ub_bytes, cql_ub_is_inclusive);
|
|
opt_bound lb = make_prefix_bound(p - 1, cql_ub_bytes, /*irrelevant:*/true);
|
|
if (lb) {
|
|
lb = query::clustering_range::bound(lb->value(), inclusive);
|
|
}
|
|
auto range = schema.clustering_column_at(p - 1).type->is_reversed() ?
|
|
query::clustering_range(ub, lb) : query::clustering_range(lb, ub);
|
|
ranges.push_back(std::move(range));
|
|
}
|
|
|
|
return ranges;
|
|
}
|
|
|
|
/// Extracts raw multi-column bounds from exprs; last one wins.
|
|
query::clustering_range range_from_raw_bounds(
|
|
const std::vector<expression>& exprs, const query_options& options, const schema& schema) {
|
|
opt_bound lb, ub;
|
|
for (const auto& e : exprs) {
|
|
if (auto b = find_clustering_order(e)) {
|
|
cql3::raw_value tup_val = expr::evaluate(b->rhs, options);
|
|
if (tup_val.is_null()) {
|
|
on_internal_error(rlogger, format("range_from_raw_bounds: unexpected atom {}", *b));
|
|
}
|
|
|
|
const auto r = to_range(
|
|
b->op, clustering_key_prefix::from_optional_exploded(schema, expr::get_tuple_elements(tup_val, *type_of(b->rhs))));
|
|
if (r.start()) {
|
|
lb = r.start();
|
|
}
|
|
if (r.end()) {
|
|
ub = r.end();
|
|
}
|
|
}
|
|
}
|
|
return {lb, ub};
|
|
}
|
|
|
|
} // anonymous namespace
|
|
|
|
std::vector<query::clustering_range> statement_restrictions::get_clustering_bounds(const query_options& options) const {
|
|
if (_clustering_prefix_restrictions.empty()) {
|
|
return {query::clustering_range::make_open_ended_both_sides()};
|
|
}
|
|
if (find_binop(_clustering_prefix_restrictions[0], expr::is_multi_column)) {
|
|
bool all_natural = true, all_reverse = true; ///< Whether column types are reversed or natural.
|
|
for (auto& r : _clustering_prefix_restrictions) { // TODO: move to constructor, do only once.
|
|
using namespace expr;
|
|
const auto& binop = expr::as<binary_operator>(r);
|
|
if (is_clustering_order(binop)) {
|
|
return {range_from_raw_bounds(_clustering_prefix_restrictions, options, *_schema)};
|
|
}
|
|
for (auto& element : expr::as<tuple_constructor>(binop.lhs).elements) {
|
|
auto& cv = expr::as<column_value>(element);
|
|
if (cv.col->type->is_reversed()) {
|
|
all_natural = false;
|
|
} else {
|
|
all_reverse = false;
|
|
}
|
|
}
|
|
}
|
|
auto bounds = get_multi_column_clustering_bounds(options, _schema, _clustering_prefix_restrictions);
|
|
if (!all_natural && !all_reverse) {
|
|
std::vector<query::clustering_range> bounds_in_clustering_order;
|
|
for (const auto& b : bounds) {
|
|
const auto eqv = get_equivalent_ranges(b, *_schema);
|
|
bounds_in_clustering_order.insert(bounds_in_clustering_order.end(), eqv.cbegin(), eqv.cend());
|
|
}
|
|
return bounds_in_clustering_order;
|
|
}
|
|
if (all_reverse) {
|
|
for (auto& crange : bounds) {
|
|
crange = query::clustering_range(crange.end(), crange.start());
|
|
}
|
|
}
|
|
return bounds;
|
|
} else {
|
|
return get_single_column_clustering_bounds(options, *_schema, _clustering_prefix_restrictions);
|
|
}
|
|
}
|
|
|
|
namespace {
|
|
|
|
/// True iff get_partition_slice_for_global_index_posting_list() will be able to calculate the token value from the
|
|
/// given restrictions. Keep in sync with the get_partition_slice_for_global_index_posting_list() source.
|
|
bool token_known(const statement_restrictions& r) {
|
|
return !r.has_partition_key_unrestricted_components() && r.partition_key_restrictions_is_all_eq();
|
|
}
|
|
|
|
} // anonymous namespace
|
|
|
|
bool statement_restrictions::need_filtering() const {
|
|
using namespace expr;
|
|
|
|
if (_uses_secondary_indexing && has_token(_partition_key_restrictions)) {
|
|
// If there is a token(p1, p2) restriction, no p1, p2 restrictions are allowed in the query.
|
|
// All other restrictions must be on clustering or regular columns.
|
|
int64_t non_pk_restrictions_count = clustering_columns_restrictions_size();
|
|
non_pk_restrictions_count += expr::get_sorted_column_defs(_nonprimary_key_restrictions).size();
|
|
|
|
// We are querying using an index, one restriction goes to the index restriction.
|
|
// If there are some restrictions other than token() and index column then we need to do filtering.
|
|
// p1, p2 can have many different values, so clustering prefix breaks.
|
|
return non_pk_restrictions_count > 1;
|
|
}
|
|
|
|
const auto npart = partition_key_restrictions_size();
|
|
if (npart > 0 && npart < _schema->partition_key_size()) {
|
|
// Can't calculate the token value, so a naive base-table query must be filtered. Same for any index tables,
|
|
// except if there's only one restriction supported by an index.
|
|
return !(npart == 1 && _has_queriable_pk_index &&
|
|
expr::is_empty_restriction(_clustering_columns_restrictions) &&
|
|
expr::is_empty_restriction(_nonprimary_key_restrictions));
|
|
}
|
|
if (pk_restrictions_need_filtering()) {
|
|
// We most likely cannot calculate token(s). Neither base-table nor index-table queries can avoid filtering.
|
|
return true;
|
|
}
|
|
// Now we know the partition key is either unrestricted or fully restricted.
|
|
|
|
const auto nreg = expr::get_sorted_column_defs(_nonprimary_key_restrictions).size();
|
|
if (nreg > 1 || (nreg == 1 && !_has_queriable_regular_index)) {
|
|
return true; // Regular columns are unsorted in storage and no single index suffices.
|
|
}
|
|
if (nreg == 1) { // Single non-key restriction supported by an index.
|
|
// Will the index-table query require filtering? That depends on whether its clustering key is restricted to a
|
|
// continuous range. Recall that this clustering key is (token, pk, ck) of the base table.
|
|
if (npart == 0 && expr::is_empty_restriction(_clustering_columns_restrictions)) {
|
|
return false; // No clustering key restrictions => whole partitions.
|
|
}
|
|
return !token_known(*this) || clustering_key_restrictions_need_filtering()
|
|
// Multi-column restrictions don't require filtering when querying the base table, but the index
|
|
// table has a different clustering key and may require filtering.
|
|
|| _has_multi_column;
|
|
}
|
|
// Now we know there are no nonkey restrictions.
|
|
|
|
if (_has_multi_column) {
|
|
// Multicolumn bounds mean lexicographic order, implying a continuous clustering range. Multicolumn IN means a
|
|
// finite set of continuous ranges. Multicolumn restrictions cannot currently be combined with single-column
|
|
// clustering restrictions. Therefore, a continuous clustering range is guaranteed.
|
|
return false;
|
|
}
|
|
|
|
if (_has_queriable_ck_index && _uses_secondary_indexing) {
|
|
// In cases where we use an index, clustering column restrictions might cause the need for filtering.
|
|
// TODO: This is overly conservative, there are some cases when this returns true but filtering
|
|
// is not needed. Because of that the data_dictionary::database will sometimes perform filtering when it's not actually needed.
|
|
// Query performance shouldn't be affected much, at most we will filter rows that are all correct.
|
|
// Here are some cases to consider:
|
|
// On a table with primary key (p, c1, c2, c3) with an index on c3
|
|
// WHERE c3 = ? - doesn't require filtering
|
|
// WHERE c1 = ? AND c2 = ? AND c3 = ? - requires filtering
|
|
// WHERE p = ? AND c1 = ? AND c3 = ? - doesn't require filtering, but we conservatively report it does
|
|
// WHERE p = ? AND c1 LIKE ? AND c3 = ? - requires filtering
|
|
// WHERE p = ? AND c1 = ? AND c2 LIKE ? AND c3 = ? - requires filtering
|
|
// WHERE p = ? AND c1 = ? AND c2 = ? AND c3 = ? - doesn't use an index
|
|
// WHERE p = ? AND c1 = ? AND c2 < ? AND c3 = ? - doesn't require filtering, but we report it does
|
|
return clustering_columns_restrictions_size() > 1;
|
|
}
|
|
// Now we know that the query doesn't use an index.
|
|
|
|
// The only thing that can cause filtering now are the clustering columns.
|
|
return clustering_key_restrictions_need_filtering();
|
|
}
|
|
|
|
void statement_restrictions::validate_secondary_index_selections(bool selects_only_static_columns) {
|
|
if (key_is_in_relation()) {
|
|
throw exceptions::invalid_request_exception(
|
|
"Index cannot be used if the partition key is restricted with IN clause. This query would require filtering instead.");
|
|
}
|
|
}
|
|
|
|
const expr::single_column_restrictions_map& statement_restrictions::get_single_column_partition_key_restrictions() const {
|
|
return _single_column_partition_key_restrictions;
|
|
}
|
|
|
|
/**
|
|
* @return clustering key restrictions split into single column restrictions (e.g. for filtering support).
|
|
*/
|
|
const expr::single_column_restrictions_map& statement_restrictions::get_single_column_clustering_key_restrictions() const {
|
|
return _single_column_clustering_key_restrictions;
|
|
}
|
|
|
|
void statement_restrictions::prepare_indexed_global(const schema& idx_tbl_schema) {
|
|
if (!_partition_range_is_simple) {
|
|
return;
|
|
}
|
|
|
|
const column_definition* token_column = &idx_tbl_schema.clustering_column_at(0);
|
|
|
|
if (has_token(_partition_key_restrictions)) {
|
|
// When there is a token(p1, p2) >/</= ? restriction, it is not allowed to have restrictions on p1 or p2.
|
|
// This means that p1 and p2 can have many different values (token is a hash, can have collisions).
|
|
// Clustering prefix ends after token_restriction, all further restrictions have to be filtered.
|
|
expr::expression token_restriction = replace_token(_partition_key_restrictions, token_column);
|
|
_idx_tbl_ck_prefix = std::vector{std::move(token_restriction)};
|
|
|
|
return;
|
|
}
|
|
|
|
// If we're here, it means the index cannot be on a partition column: process_partition_key_restrictions()
|
|
// avoids indexing when _partition_range_is_simple. See _idx_tbl_ck_prefix blurb for its composition.
|
|
_idx_tbl_ck_prefix = std::vector<expr::expression>(1 + _schema->partition_key_size());
|
|
_idx_tbl_ck_prefix->reserve(_idx_tbl_ck_prefix->size() + idx_tbl_schema.clustering_key_size());
|
|
for (const auto& e : _partition_range_restrictions) {
|
|
const auto col = expr::as<column_value>(find(e, oper_t::EQ)->lhs).col;
|
|
const auto pos = _schema->position(*col) + 1;
|
|
(*_idx_tbl_ck_prefix)[pos] = replace_column_def(e, &idx_tbl_schema.clustering_column_at(pos));
|
|
}
|
|
|
|
add_clustering_restrictions_to_idx_ck_prefix(idx_tbl_schema);
|
|
|
|
(*_idx_tbl_ck_prefix)[0] = binary_operator(
|
|
column_value(token_column),
|
|
oper_t::EQ,
|
|
// TODO: This should be a unique marker whose value we set at execution time. There is currently no
|
|
// handy mechanism for doing that in query_options.
|
|
expr::constant::make_unset_value(token_column->type));
|
|
}
|
|
|
|
void statement_restrictions::prepare_indexed_local(const schema& idx_tbl_schema) {
|
|
if (!_partition_range_is_simple) {
|
|
return;
|
|
}
|
|
|
|
// Local index clustering key is (indexed column, base clustering key)
|
|
_idx_tbl_ck_prefix = std::vector<expr::expression>();
|
|
_idx_tbl_ck_prefix->reserve(1 + _clustering_prefix_restrictions.size());
|
|
|
|
const column_definition& indexed_column = idx_tbl_schema.column_at(column_kind::clustering_key, 0);
|
|
const column_definition& indexed_column_base_schema = *_schema->get_column_definition(indexed_column.name());
|
|
|
|
// Find index column restrictions in the WHERE clause
|
|
std::vector<expr::expression> idx_col_restrictions =
|
|
extract_single_column_restrictions_for_column(*_where, indexed_column_base_schema);
|
|
expr::expression idx_col_restriction_expr = expr::expression(expr::conjunction{std::move(idx_col_restrictions)});
|
|
|
|
// Translate the restriction to use column from the index schema and add it
|
|
expr::expression replaced_idx_restriction = replace_column_def(idx_col_restriction_expr, &indexed_column);
|
|
_idx_tbl_ck_prefix->push_back(replaced_idx_restriction);
|
|
|
|
// Add restrictions for the clustering key
|
|
add_clustering_restrictions_to_idx_ck_prefix(idx_tbl_schema);
|
|
}
|
|
|
|
void statement_restrictions::add_clustering_restrictions_to_idx_ck_prefix(const schema& idx_tbl_schema) {
|
|
for (const auto& e : _clustering_prefix_restrictions) {
|
|
if (find_binop(_clustering_prefix_restrictions[0], expr::is_multi_column)) {
|
|
// TODO: We could handle single-element tuples, eg. `(c)>=(123)`.
|
|
break;
|
|
}
|
|
const auto any_binop = find_binop(e, [] (auto&&) { return true; });
|
|
if (!any_binop) {
|
|
break;
|
|
}
|
|
const auto col = expr::as<column_value>(any_binop->lhs).col;
|
|
_idx_tbl_ck_prefix->push_back(replace_column_def(e, idx_tbl_schema.get_column_definition(col->name())));
|
|
}
|
|
}
|
|
|
|
// How many of the restrictions (in column order) do not need filtering
|
|
// because they are implemented as a slice (potentially, a contiguous disk
|
|
// read). For example, if we have the filter "c1 < 3 and c2 > 3", c1 does not
|
|
// need filtering but c2 does so num_prefix_columns_that_need_not_be_filtered
|
|
// will be 1.
|
|
unsigned int statement_restrictions::num_clustering_prefix_columns_that_need_not_be_filtered() const {
|
|
if (expr::contains_multi_column_restriction(_clustering_columns_restrictions)) {
|
|
return 0;
|
|
}
|
|
|
|
expr::single_column_restrictions_map column_restrictions =
|
|
expr::get_single_column_restrictions_map(_clustering_columns_restrictions);
|
|
|
|
// Restrictions currently need filtering in three cases:
|
|
// 1. any of them is a CONTAINS restriction
|
|
// 2. restrictions do not form a contiguous prefix (i.e. there are gaps in it)
|
|
// 3. a SLICE restriction isn't on a last place
|
|
column_id position = 0;
|
|
unsigned int count = 0;
|
|
for (const auto& restriction : column_restrictions | boost::adaptors::map_values) {
|
|
if (find_needs_filtering(restriction)
|
|
|| position != get_the_only_column(restriction).col->id) {
|
|
return count;
|
|
}
|
|
if (!has_slice(restriction)) {
|
|
position = get_the_only_column(restriction).col->id + 1;
|
|
}
|
|
count++;
|
|
}
|
|
return count;
|
|
}
|
|
|
|
std::vector<query::clustering_range> statement_restrictions::get_global_index_clustering_ranges(
|
|
const query_options& options,
|
|
const schema& idx_tbl_schema) const {
|
|
if (!_idx_tbl_ck_prefix) {
|
|
on_internal_error(
|
|
rlogger, "statement_restrictions::get_global_index_clustering_ranges called with unprepared index");
|
|
}
|
|
std::vector<managed_bytes> pk_value(_schema->partition_key_size());
|
|
for (const auto& e : _partition_range_restrictions) {
|
|
const auto col = expr::as<column_value>(find(e, oper_t::EQ)->lhs).col;
|
|
const auto vals = std::get<value_list>(possible_lhs_values(col, e, options));
|
|
if (vals.empty()) { // Case of C=1 AND C=2.
|
|
return {};
|
|
}
|
|
pk_value[_schema->position(*col)] = std::move(vals[0]);
|
|
}
|
|
std::vector<bytes> pkv_linearized(pk_value.size());
|
|
std::transform(pk_value.cbegin(), pk_value.cend(), pkv_linearized.begin(),
|
|
[] (const managed_bytes& mb) { return to_bytes(mb); });
|
|
auto& token_column = idx_tbl_schema.clustering_column_at(0);
|
|
bytes_opt token_bytes = token_column.get_computation().compute_value(
|
|
*_schema, pkv_linearized, clustering_row(clustering_key_prefix::make_empty()));
|
|
if (!token_bytes) {
|
|
on_internal_error(rlogger,
|
|
format("null value for token column in indexing table {}",
|
|
token_column.name_as_text()));
|
|
}
|
|
// WARNING: We must not yield to another fiber from here until the function's end, lest this RHS be
|
|
// overwritten.
|
|
const_cast<expr::expression&>(expr::as<binary_operator>((*_idx_tbl_ck_prefix)[0]).rhs) =
|
|
expr::constant(raw_value::make_value(*token_bytes), token_column.type);
|
|
|
|
// Multi column restrictions are not added to _idx_tbl_ck_prefix, they are handled later by filtering.
|
|
return get_single_column_clustering_bounds(options, idx_tbl_schema, *_idx_tbl_ck_prefix);
|
|
}
|
|
|
|
std::vector<query::clustering_range> statement_restrictions::get_global_index_token_clustering_ranges(
|
|
const query_options& options,
|
|
const schema& idx_tbl_schema
|
|
) const {
|
|
if (!_idx_tbl_ck_prefix.has_value()) {
|
|
on_internal_error(
|
|
rlogger, "statement_restrictions::get_global_index_token_clustering_ranges called with unprepared index");
|
|
}
|
|
|
|
const column_definition& token_column = idx_tbl_schema.clustering_column_at(0);
|
|
|
|
// In old indexes the token column was of type blob.
|
|
// This causes problems with sorting and must be handled separately.
|
|
if (token_column.type != long_type) {
|
|
return get_index_v1_token_range_clustering_bounds(options, token_column, _idx_tbl_ck_prefix->at(0));
|
|
}
|
|
|
|
return get_single_column_clustering_bounds(options, idx_tbl_schema, *_idx_tbl_ck_prefix);
|
|
}
|
|
|
|
std::vector<query::clustering_range> statement_restrictions::get_local_index_clustering_ranges(
|
|
const query_options& options,
|
|
const schema& idx_tbl_schema) const {
|
|
if (!_idx_tbl_ck_prefix.has_value()) {
|
|
on_internal_error(
|
|
rlogger, "statement_restrictions::get_local_index_clustering_ranges called with unprepared index");
|
|
}
|
|
|
|
// Multi column restrictions are not added to _idx_tbl_ck_prefix, they are handled later by filtering.
|
|
return get_single_column_clustering_bounds(options, idx_tbl_schema, *_idx_tbl_ck_prefix);
|
|
}
|
|
|
|
sstring statement_restrictions::to_string() const {
|
|
return _where ? expr::to_string(*_where) : "";
|
|
}
|
|
|
|
static bool has_eq_null(const query_options& options, const expression& expr) {
|
|
return find_binop(expr, [&] (const binary_operator& binop) {
|
|
return binop.op == oper_t::EQ && evaluate(binop.rhs, options).is_null();
|
|
});
|
|
}
|
|
|
|
bool statement_restrictions::range_or_slice_eq_null(const query_options& options) const {
|
|
return boost::algorithm::any_of(_partition_range_restrictions, std::bind_front(has_eq_null, std::cref(options)))
|
|
|| boost::algorithm::any_of(_clustering_prefix_restrictions, std::bind_front(has_eq_null, std::cref(options)));
|
|
}
|
|
} // namespace restrictions
|
|
} // namespace cql3
|