We want the format of query results to be eventually defined in the IDL and be independent of the format we use in memory to represent collections. This change is a step in this direction. The change decouples format of collection cells in query results from our in-memory representation. We currently use collection_mutation_view, after the change we will use CQL binary protocol format. We use that because it requires less transformations on the coordinator side. One complication is that some list operations need to retrieve keys used in list cells, not only values. To satisfy this need, new query option was added called "collections_as_maps" which will cause lists and sets to be reinterpreted as maps matching their underlying representation. This allows the coordinator to generate mutations referencing existing items in lists.
175 lines
5.6 KiB
C++
175 lines
5.6 KiB
C++
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/*
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* Copyright 2015 Cloudius Systems
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*/
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/*
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* This file is part of Scylla.
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*
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* Scylla is free software: you can redistribute it and/or modify
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* it under the terms of the GNU Affero General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Scylla is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Scylla. If not, see <http://www.gnu.org/licenses/>.
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*/
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#pragma once
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#include <experimental/optional>
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#include "keys.hh"
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#include "dht/i_partitioner.hh"
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#include "enum_set.hh"
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#include "range.hh"
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namespace query {
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template <typename T>
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using range = ::range<T>;
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using ring_position = dht::ring_position;
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using partition_range = range<ring_position>;
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using clustering_range = range<clustering_key_prefix>;
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extern const partition_range full_partition_range;
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// FIXME: Move this to i_partitioner.hh after query::range<> is moved to utils/range.hh
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query::partition_range to_partition_range(query::range<dht::token>);
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inline
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bool is_wrap_around(const query::partition_range& range, const schema& s) {
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return range.is_wrap_around(dht::ring_position_comparator(s));
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}
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inline
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bool is_single_partition(const query::partition_range& range) {
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return range.is_singular() && range.start()->value().has_key();
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}
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typedef std::vector<clustering_range> clustering_row_ranges;
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class specific_ranges {
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public:
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specific_ranges(partition_key pk, clustering_row_ranges ranges)
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: _pk(std::move(pk)), _ranges(std::move(ranges)) {
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}
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specific_ranges(const specific_ranges&) = default;
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void add(const schema& s, partition_key pk, clustering_row_ranges ranges) {
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if (!_pk.equal(s, pk)) {
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throw std::runtime_error("Only single specific range supported currently");
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}
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_pk = std::move(pk);
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_ranges = std::move(ranges);
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}
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bool contains(const schema& s, const partition_key& pk) {
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return _pk.equal(s, pk);
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}
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size_t size() const {
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return 1;
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}
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const clustering_row_ranges* range_for(const schema& s, const partition_key& key) const {
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if (_pk.equal(s, key)) {
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return &_ranges;
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}
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return nullptr;
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}
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const partition_key& pk() const {
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return _pk;
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}
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const clustering_row_ranges& ranges() const {
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return _ranges;
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}
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private:
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friend std::ostream& operator<<(std::ostream& out, const specific_ranges& r);
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partition_key _pk;
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clustering_row_ranges _ranges;
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};
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// Specifies subset of rows, columns and cell attributes to be returned in a query.
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// Can be accessed across cores.
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// Schema-dependent.
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class partition_slice {
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public:
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enum class option { send_clustering_key, send_partition_key, send_timestamp, send_expiry, reversed, distinct, collections_as_maps };
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using option_set = enum_set<super_enum<option,
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option::send_clustering_key,
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option::send_partition_key,
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option::send_timestamp,
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option::send_expiry,
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option::reversed,
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option::distinct,
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option::collections_as_maps>>;
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clustering_row_ranges _row_ranges;
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public:
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std::vector<column_id> static_columns; // TODO: consider using bitmap
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std::vector<column_id> regular_columns; // TODO: consider using bitmap
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option_set options;
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private:
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std::unique_ptr<specific_ranges> _specific_ranges;
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cql_serialization_format _cql_format;
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public:
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partition_slice(clustering_row_ranges row_ranges, std::vector<column_id> static_columns,
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std::vector<column_id> regular_columns, option_set options,
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std::unique_ptr<specific_ranges> specific_ranges = nullptr,
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cql_serialization_format = cql_serialization_format::internal());
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partition_slice(const partition_slice&);
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partition_slice(partition_slice&&);
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~partition_slice();
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const clustering_row_ranges& row_ranges(const schema&, const partition_key&) const;
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void set_range(const schema&, const partition_key&, clustering_row_ranges);
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void clear_range(const schema&, const partition_key&);
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const clustering_row_ranges& default_row_ranges() const {
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return _row_ranges;
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}
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const std::unique_ptr<specific_ranges>& get_specific_ranges() const {
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return _specific_ranges;
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}
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const cql_serialization_format& cql_format() const {
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return _cql_format;
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}
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friend std::ostream& operator<<(std::ostream& out, const partition_slice& ps);
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friend std::ostream& operator<<(std::ostream& out, const specific_ranges& ps);
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};
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constexpr auto max_rows = std::numeric_limits<uint32_t>::max();
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// Full specification of a query to the database.
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// Intended for passing across replicas.
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// Can be accessed across cores.
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class read_command {
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public:
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utils::UUID cf_id;
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table_schema_version schema_version; // TODO: This should be enough, drop cf_id
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partition_slice slice;
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uint32_t row_limit;
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gc_clock::time_point timestamp;
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public:
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read_command(utils::UUID cf_id,
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table_schema_version schema_version,
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partition_slice slice,
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uint32_t row_limit = max_rows,
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gc_clock::time_point now = gc_clock::now())
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: cf_id(std::move(cf_id))
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, schema_version(std::move(schema_version))
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, slice(std::move(slice))
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, row_limit(row_limit)
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, timestamp(now)
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{ }
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friend std::ostream& operator<<(std::ostream& out, const read_command& r);
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};
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}
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