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Pull request overview
This PR aims to reduce CPU time and memory usage during schema metadata refresh by avoiding per-row dict allocations and trimming schema column queries, while also shrinking metadata object overhead.
Changes:
- Introduces an internal
_RowView+_row_factoryand routes schema query result handling through it to reduce per-row allocations. - Adds
__slots__to several metadata model classes and replaces someOrderedDictusages with plaindictto reduce memory overhead. - Narrows the
system_schema.columnsquery inSchemaParserV3to only the fields needed by the parser and refactors_build_table_columnsto classify rows in a single pass.
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Pull request overview
This PR optimizes schema metadata refresh by reducing per-row allocations during schema parsing and narrowing the system_schema.columns select list to only the fields needed for building table/column metadata.
Changes:
- Introduces an internal lightweight row representation (
_RowView+_row_factory) and uses it in schema parser result handling to reduce time/memory overhead. - Reduces the
system_schema.columnsquery to fetch only required columns and refactors_build_table_columnsto classify rows in a single pass. - Adds unit tests for
_RowViewand_row_factorybehavior.
Reviewed changes
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| File | Description |
|---|---|
| cassandra/metadata.py | Adds _RowView/_row_factory, switches schema parser row handling away from per-row dicts, tightens system_schema.columns query, and updates metadata classes/docstrings/slots. |
| tests/unit/test_metadata.py | Adds unit tests validating _RowView and _row_factory semantics (getitem/get/contains/read-only/shared index map). |
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mykaul
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mykaul
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Understand this PR’s impact Explore downstream dependencies and potential security impact with Blast Radius. Warning Review limit reachedNext included review available in 5 minutes. View limit detailsLimit details: You’ve used the included review currently available. You've used all free OSS reviews for now. Wait for the free limit to reset to keep reviewing this public repository. Review configuration: ⚙️ Run configurationConfiguration used: Organization UI Review profile: QUIET Plan: Advanced Run ID: 📒 Files selected for processing (5)
📝 WalkthroughWalkthroughThe change adds read-only Sequence Diagram(s)sequenceDiagram
participant DDLResponse
participant ControlConnection
participant Session
participant PeerNodes
DDLResponse->>ControlConnection: Pass response_future.session
ControlConnection->>Session: Check connected-host schema agreement
Session-->>ControlConnection: Return agreement result
ControlConnection->>PeerNodes: Query peers when no connected host is available
PeerNodes-->>ControlConnection: Return schema versions
Priority: ⬇️ Low Change: Refactor Merge Risk: 🔵 Low · up to Automatic session selection during schema refresh lacks direct coverage, so a future change could silently break this path. Add the focused regression test before merging. 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
✨ Finishing Touches 💡 1🛠️ Fix failing CI checks 💡
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🧹 Nitpick comments (2)
cassandra/metadata.py (2)
61-61: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick winSort
__slots__to satisfy Ruff RUF023.Proposed fix
- __slots__ = ("_row", "_index_map") + __slots__ = ("_index_map", "_row")🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@cassandra/metadata.py` at line 61, The __slots__ definition in the metadata class needs to be sorted to satisfy Ruff RUF023. Update the __slots__ tuple in the class that defines _row and _index_map so the slot names are in the expected sorted order and keep the declaration consistent with the rest of the file.Source: Linters/SAST tools
56-58: 🎯 Functional Correctness | 🔵 Trivial | ⚡ Quick winDrop the custom
values()/items()generatorsMappingalready provides reusable view objects here; these overrides turn them into one-shot iterators and lose the usual size/reuse semantics.cassandra/metadata.py:82-85🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@cassandra/metadata.py` around lines 56 - 58, The custom values() and items() generators in the Mapping implementation should be removed so the class can use the default Mapping view behavior. Update the metadata mapping class in cassandra/metadata.py by dropping the overridden values() and items() methods, and rely on the inherited reusable view objects from collections.abc.Mapping instead.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Nitpick comments:
In `@cassandra/metadata.py`:
- Line 61: The __slots__ definition in the metadata class needs to be sorted to
satisfy Ruff RUF023. Update the __slots__ tuple in the class that defines _row
and _index_map so the slot names are in the expected sorted order and keep the
declaration consistent with the rest of the file.
- Around line 56-58: The custom values() and items() generators in the Mapping
implementation should be removed so the class can use the default Mapping view
behavior. Update the metadata mapping class in cassandra/metadata.py by dropping
the overridden values() and items() methods, and rely on the inherited reusable
view objects from collections.abc.Mapping instead.
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Rebased onto latest Notably, this pulls in Self-reviewed the diff against Ran The 3 existing review threads were already resolved/outdated (they were about the earlier |
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Pull request overview
Copilot reviewed 2 out of 2 changed files in this pull request and generated no new comments.
Comments suppressed due to low confidence (2)
cassandra/metadata.py:2630
- This query no longer matches the exact Simulacron prime in
tests/integration/simulacron/test_empty_column.py:161-164, which still only registersSELECT * FROM system_schema.columns. The metadata refresh in that integration test will therefore receive no primed response. Update that prime to this projected query (and keep the legacy schema-table primes) so the existing empty-column regression test continues to exercise V3+ metadata parsing.
_SELECT_COLUMNS = "SELECT keyspace_name, table_name, column_name, clustering_order, kind, position, type FROM system_schema.columns"
cassandra/metadata.py:1388
- The PR description and memory benchmark claim that all metadata classes, including
ColumnMetadata, use pure__slots__, but this patch only adds slots to_RowView;TableMetadata,ColumnMetadata,KeyspaceMetadata, andMaterializedViewMetadatastill have instance__dict__storage. Consequently the stated 264-byte-per-column saving is not delivered. Either implement the promised slots change with compatibility coverage or remove that claim and its benchmark from the PR scope.
self.columns = {} if columns is None else columns
Introduce _RowView, a __slots__-based read-only row wrapper that stores data as tuples with a shared column-name-to-index map, and _row_factory that creates these views. _RowView inherits from collections.abc.Mapping, providing a complete dict-like read interface. This eliminates per-row dict allocation during schema parsing. All rows from the same result set share a single index map object.
Python 3.7+ guarantees dict preserves insertion order, making OrderedDict
unnecessary. Replace OrderedDict() with {} in TableMetadata.columns,
TableMetadata.triggers, and MaterializedViewMetadata.columns. Remove the
now-unused OrderedDict import.
….columns Replace SELECT * with an explicit column list for the system_schema.columns query in SchemaParserV3 (inherited by V4). Only the 7 columns actually consumed by the parser are fetched: keyspace_name, table_name, column_name, clustering_order, kind, position, type. This reduces network transfer and deserialization overhead during schema refresh.
Replace dict_factory in _SchemaParser._handle_results and get_column_from_system_local with _row_factory, eliminating per-row dict allocation during schema parsing. Also refactor SchemaParserV4._build_keyspace_metadata_internal to read from the row without mutating it, since _RowView is read-only. Note: V22-only dict_factory call sites are left unchanged as they do not affect the V3/V4 code path (V3 and V4 fully override _query_all).
Replace three list comprehension passes over col_rows with a single classification loop that sorts columns into partition, clustering, and other buckets. Also use in-place sort() instead of sorted() and reuse the already-built column_meta instead of a redundant dict lookup.
Cover __getitem__, get(), __contains__, __repr__, shared index map, read-only enforcement, empty input, single-column, and multi-row scenarios.
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_RowView.__init__ computed max(index_map.values()) on every row, making construction O(columns) per row instead of O(1). That is the hot path when parsing system_schema results, so the max() defeated the point of the lightweight view. Compute the column count once in _row_factory and validate each row there, leaving _RowView.__init__ as two plain slot assignments. While here, stop materializing every page at once: _handle_results unpacked the entire get_next_pages() generator into itertools.chain, holding all pages and the accumulated rows in memory simultaneously. Extend per page instead.
Schema agreement is typically reached a few ms after a DDL returns, but the peers-view version signal is propagated by gossip (up to a gossip round on both Scylla and Cassandra). The fixed 200ms retry quantizes every wait up to the next interval, adding up to 200ms to a change that was already agreed. Poll at 10ms and double up to the historic 200ms cap on both the session and control-connection loops, so a fast change is noticed promptly while a slow one still converges under the same total timeout.
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Actionable comments posted: 1
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Inline comments:
In `@cassandra/cluster.py`:
- Around line 4068-4069: Add a focused test for refresh_schema() that registers
one connected session in cluster.sessions, invokes refresh_schema() without a
session argument, and asserts _refresh_schema() receives that session. Keep the
existing no-argument test intact unless needed to avoid overlap, and use the
established mocking and session setup patterns.
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The DDL-triggered refresh waited on the control connection's system.peers view, but the schema version there is only propagated by gossip: measured ~0.4-0.7s behind the nodes actually applying the schema (Scylla 2026.3 and Cassandra 5.0), which dominated DDL latency at ~1s on a 2-node cluster. Thread the response's session into _refresh_schema and, when it has connected hosts, ask each of them for system.local directly (the existing session scope check) instead of polling gossip. Peers remain the fallback for callers without a session, such as control-connection startup. Also simplify the fallback _get_schema_mismatches to compare every reachable peer against a single reference version, only building the per-version endpoint breakdown when there is a mismatch to report. On a 2-node Cassandra 5.0 cluster this cuts a CREATE TABLE from ~1.0s to ~0.13s end to end.
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Ran a before/after benchmark isolating this PR's changes from unrelated master drift: built the driver from the merge-base (
~12.5s → ~9.0s, about a 28% reduction in this schema-change test's wall time, with all tests passing on both sides. Matches the PR's claimed mechanism (bypassing gossip-lagged Caveat: this ran on my desktop (16 cores, shared with a normal interactive session — browser/Slack/etc. running), not a quiet benchmarking box, so treat these as directional rather than precise. Occasional single-run outliers up to ~2x showed up on both sides across repeats; the numbers above are from a clean back-to-back set. |
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@gusev-p It looks like this PR fixes the problem we discussed today. |
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I'm concerned that this changes the semantics from "the schema is synced on the alive part of the whole cluster" to "schema is synced on whatever hosts the session happens to be connected to". What if a driver uses My suggestion seems safer:
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Is that an interesting scenario? Can we think of a more realistic one? I think a more realistic scenario is:
How do we determine most cases? with 100 nodes as well? with high latency across DCs? Under load?
Yes, that was the initial set of PRs here, the main change was not to rely on system.peers at all. If that's unsafe, we'll have to re-think this approach. |
Two related improvements:
system.localcheck (the big win).1. DDL schema-agreement latency
Problem
After a DDL, the control connection waited for
system.peersto report the newschema_version. On a node,system.peersonly learns a peer's version on the next gossip round, so every DDL blocked until gossip propagated — even though the change had already been applied.Server-side cause (ScyllaDB):
system.local.schema_versionis written immediately (update_schema_version_and_announce,db/schema_tables.cc), while the version is published to peers as a gossip application state (migration_manager::passive_announce→add_local_application_state(SCHEMA, …)).gossiper::replicateis intra-shard only, and network dissemination happens on the periodic gossip round (gossiper.hh,INTERVAL{1000}).system.peerstherefore lagssystem.localby up to a gossip interval.Change
system.localon the DDL path: when a session is available, the control connection delegates the wait toSession.wait_for_schema_agreement, which queriessystem.localdirectly on the connected hosts in parallel, rather than reading the gossip-laggedsystem.peersview. Thesystem.peersloop is kept as a fallback for callers without a session (e.g. control-connection startup), and the deprecatedControlConnection.wait_for_schema_agreementstill uses it._get_schema_mismatchesback to a single pass (build one version→endpoints set, agreed whenlen(versions) == 1).Results (2-node, measured)
Breakdown on ScyllaDB: replacing the gossip view with a direct
system.localread takes ~0.9 s → ~0.11 s, and the adaptive backoff removes the fixed 200 ms floor (~0.11 s → ~0.04 s).Scope note
The per-host check covers the hosts the session is connected to. With the default load-balancing policy that is the local datacenter (remote DCs are
HostDistance.IGNOREDunlessused_hosts_per_remote_dc > 0), so the round is gated by the slowest connected host — a local cross-AZ hop in the common case. If remote DCs are in use, the round is gated by the cross-DC hop; that is still far below the ~1 s gossip wait.2. Metadata schema parsing (memory / CPU)
system_schema.columns— the biggest network/memory win for large schemas.dict_factorywith_RowView— a lightweight tuple-backedMappingthat shares a single column-name→index map across all rows of a result set.max(index_map.values())on every row (which made construction O(columns) per row on the hot path)._build_table_columns.OrderedDictwithdict(Python 3.7+ guarantees insertion order).Numbers (Python 3.14)
_RowView(new)dict_factory(old)_RowViewimplements the fullcollections.abc.Mappingprotocol (keys(),values(),items(),len(), iteration, membership).Testing
tests/integration/standard/test_concurrent_schema_change_and_node_kill.pypassed against a 3-node ScyllaDB cluster (schema change with a node killed non-gently mid-DDL).Pre-review checklist
./docs/source/.Fixes:annotations to PR description.