mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-09-11 12:17:53 +02:00
combine
This commit is contained in:
Quanzheng Long
@@ -2,7 +2,7 @@ from __future__ import annotations
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import threading
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from collections import defaultdict
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from collections.abc import Iterator, Sequence
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from collections.abc import Iterator, Mapping, Sequence
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from contextlib import contextmanager
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from typing import Any, cast
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@@ -27,10 +27,9 @@ from psycopg_pool import ConnectionPool
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from langgraph.checkpoint.postgres import _internal
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from langgraph.checkpoint.postgres.base import (
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SELECT_DELTA_STAGE1_SQL,
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SELECT_DELTA_STAGE2_SQL,
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BasePostgresSaver,
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_DeltaStage1Row,
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_build_delta_stage1_sql,
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_DeltaStage2Row,
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)
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from langgraph.checkpoint.postgres.shallow import ShallowPostgresSaver
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@@ -444,53 +443,79 @@ class PostgresSaver(BasePostgresSaver):
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with conn.cursor(binary=True, row_factory=dict_row) as cur:
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yield cur
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def _get_channel_writes_history(
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self, config: RunnableConfig, channel: str
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) -> _ChannelWritesHistory:
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"""Fast-path override of `BaseCheckpointSaver._get_channel_writes_history`.
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def _get_all_delta_channels_writes_history(
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self, config: RunnableConfig, channels: Sequence[str]
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) -> Mapping[str, _ChannelWritesHistory]:
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"""Fast-path override of `BaseCheckpointSaver._get_all_delta_channels_writes_history`.
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Two-stage query: stage 1 scans checkpoint metadata to walk the parent
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chain and locate the nearest snapshot; stage 2 fetches only the
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chain-limited writes and single seed blob.
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Two-stage query, both stages cover ALL requested channels in a single
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Postgres roundtrip each:
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* Stage 1: dynamic SELECT over `checkpoints` with K parallel JSONB
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key lookups (one column pair per channel) — no subquery, no
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aggregation. Returns one row per checkpoint with versions and
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snapshot flags for every requested channel.
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* Stage 2: one UNION ALL over `checkpoint_writes` and
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`checkpoint_blobs` filtered by `channel = ANY(?)` and per-channel
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chain_cids / seed_versions (collapsed across channels).
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"""
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if not channels:
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return {}
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channels = list(channels)
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thread_id = config["configurable"]["thread_id"]
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checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
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checkpoint_id = get_checkpoint_id(config)
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if checkpoint_id is None:
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target = self.get_tuple(config)
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if target is None:
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return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
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return {
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ch: _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
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for ch in channels
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}
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checkpoint_id = target.config["configurable"]["checkpoint_id"]
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# Stage 1: K parallel JSONB lookups per row, one query for all channels.
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stage1_sql = _build_delta_stage1_sql(channels)
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stage1_params: list[Any] = []
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for ch in channels:
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stage1_params.extend([ch, ch])
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stage1_params.extend([thread_id, checkpoint_ns])
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with self._cursor() as cur:
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cur.execute(
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SELECT_DELTA_STAGE1_SQL,
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(channel, channel, thread_id, checkpoint_ns),
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)
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cur.execute(stage1_sql, stage1_params)
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stage1_rows = cur.fetchall()
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chain_cids, seed_version = self._walk_stage1(
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cast("list[_DeltaStage1Row]", stage1_rows), checkpoint_id
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chain_by_ch, seed_ver_by_ch = self._walk_stage1_multi(
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cast("list[Mapping[str, Any]]", stage1_rows), checkpoint_id, channels
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)
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seed_versions = [seed_version] if seed_version else []
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# Union of chain cids and seed versions across all channels.
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union_chain_cids: list[str] = sorted(
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{cid for chain in chain_by_ch.values() for cid in chain}
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)
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union_seed_versions: list[str] = sorted(
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{ver for ver in seed_ver_by_ch.values() if ver is not None}
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)
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# Stage 2: chain-limited writes + chain-limited seed blobs for all channels.
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with self._cursor() as cur:
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cur.execute(
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SELECT_DELTA_STAGE2_SQL,
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(
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thread_id,
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checkpoint_ns,
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channel,
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chain_cids,
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channels,
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union_chain_cids,
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thread_id,
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checkpoint_ns,
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channel,
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seed_versions,
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channels,
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union_seed_versions,
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),
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)
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stage2_rows = cur.fetchall()
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return self._build_delta_channel_writes_history(
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channel=channel,
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chain_cids=chain_cids,
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seed_version=seed_version,
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return self._build_delta_channels_writes_history(
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channels=channels,
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chain_by_ch=chain_by_ch,
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seed_ver_by_ch=seed_ver_by_ch,
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stage2_rows=cast("list[_DeltaStage2Row]", stage2_rows),
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)
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@@ -2,7 +2,7 @@ from __future__ import annotations
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import asyncio
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from collections import defaultdict
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from collections.abc import AsyncIterator, Iterator, Sequence
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from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
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from contextlib import asynccontextmanager
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from typing import Any, cast
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@@ -27,10 +27,9 @@ from psycopg_pool import AsyncConnectionPool
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from langgraph.checkpoint.postgres import _ainternal
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from langgraph.checkpoint.postgres.base import (
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SELECT_DELTA_STAGE1_SQL,
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SELECT_DELTA_STAGE2_SQL,
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BasePostgresSaver,
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_DeltaStage1Row,
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_build_delta_stage1_sql,
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_DeltaStage2Row,
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)
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from langgraph.checkpoint.postgres.shallow import AsyncShallowPostgresSaver
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@@ -405,53 +404,68 @@ class AsyncPostgresSaver(BasePostgresSaver):
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async with conn.cursor(binary=True, row_factory=dict_row) as cur:
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yield cur
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async def _aget_channel_writes_history(
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self, config: RunnableConfig, channel: str
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) -> _ChannelWritesHistory:
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"""Fast-path override of `BaseCheckpointSaver._aget_channel_writes_history`.
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async def _aget_all_delta_channels_writes_history(
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self, config: RunnableConfig, channels: Sequence[str]
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) -> Mapping[str, _ChannelWritesHistory]:
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"""Fast-path override of `BaseCheckpointSaver._aget_all_delta_channels_writes_history`.
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Two-stage query: stage 1 scans checkpoint metadata to walk the parent
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chain and locate the nearest snapshot; stage 2 fetches only the
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chain-limited writes and single seed blob.
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Two-stage query, both stages cover ALL requested channels in a single
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Postgres roundtrip each. See `PostgresSaver._get_all_delta_channels_writes_history`
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for design notes.
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"""
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if not channels:
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return {}
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channels = list(channels)
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thread_id = config["configurable"]["thread_id"]
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checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
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checkpoint_id = get_checkpoint_id(config)
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if checkpoint_id is None:
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target = await self.aget_tuple(config)
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if target is None:
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return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
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return {
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ch: _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
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for ch in channels
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}
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checkpoint_id = target.config["configurable"]["checkpoint_id"]
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stage1_sql = _build_delta_stage1_sql(channels)
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stage1_params: list[Any] = []
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for ch in channels:
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stage1_params.extend([ch, ch])
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stage1_params.extend([thread_id, checkpoint_ns])
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async with self._cursor() as cur:
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await cur.execute(
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SELECT_DELTA_STAGE1_SQL,
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(channel, channel, thread_id, checkpoint_ns),
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)
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await cur.execute(stage1_sql, stage1_params)
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stage1_rows = await cur.fetchall()
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chain_cids, seed_version = self._walk_stage1(
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cast("list[_DeltaStage1Row]", stage1_rows), checkpoint_id
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chain_by_ch, seed_ver_by_ch = self._walk_stage1_multi(
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cast("list[Mapping[str, Any]]", stage1_rows), checkpoint_id, channels
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)
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seed_versions = [seed_version] if seed_version else []
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union_chain_cids: list[str] = sorted(
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{cid for chain in chain_by_ch.values() for cid in chain}
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)
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union_seed_versions: list[str] = sorted(
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{ver for ver in seed_ver_by_ch.values() if ver is not None}
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)
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async with self._cursor() as cur:
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await cur.execute(
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SELECT_DELTA_STAGE2_SQL,
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(
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thread_id,
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checkpoint_ns,
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channel,
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chain_cids,
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channels,
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union_chain_cids,
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thread_id,
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checkpoint_ns,
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channel,
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seed_versions,
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channels,
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union_seed_versions,
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),
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)
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stage2_rows = await cur.fetchall()
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return self._build_delta_channel_writes_history(
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channel=channel,
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chain_cids=chain_cids,
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seed_version=seed_version,
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return self._build_delta_channels_writes_history(
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channels=channels,
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chain_by_ch=chain_by_ch,
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seed_ver_by_ch=seed_ver_by_ch,
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stage2_rows=cast("list[_DeltaStage2Row]", stage2_rows),
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)
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@@ -2,7 +2,7 @@ from __future__ import annotations
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import random
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import warnings
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from collections.abc import Sequence
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from collections.abc import Mapping, Sequence
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from importlib.metadata import version as get_version
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from typing import Any, TypedDict, cast
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@@ -161,6 +161,7 @@ class _DeltaStage2Row(TypedDict, total=False):
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_kind: str # "w" or "b"
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checkpoint_id: str | None # "w" rows only
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channel: str | None # set on both "w" and "b" rows
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type: str | None
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blob: bytes | None
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task_id: str | None # "w" rows only
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@@ -168,48 +169,85 @@ class _DeltaStage2Row(TypedDict, total=False):
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version: str | None # "b" rows only
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# Two-stage DeltaChannel reconstruction. Stage 1 scans checkpoint
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# metadata (no blob bytes) to walk the parent chain and locate the
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# nearest snapshot marker. Stage 2 fetches only the chain-limited
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# writes and the single seed snapshot blob.
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# Multi-channel two-stage DeltaChannel reconstruction.
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#
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# Parameter order:
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# stage1: (channel, channel, thread_id, checkpoint_ns)
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# stage2: (thread_id, checkpoint_ns, channel, chain_cids[],
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# thread_id, checkpoint_ns, channel, seed_versions[])
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# Stage 1 scans checkpoint metadata (no blob bytes) and emits one row per
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# checkpoint with K parallel JSONB key lookups (one column pair per
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# requested delta channel: ver_i / hs_i). No subqueries, no aggregation.
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# Python walks the parent chain once across all channels.
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#
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# Stage 2 fetches all writes and the seed blobs for ALL channels in a
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# single roundtrip via `channel = ANY(%s)` and chain/seed-version
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# filtering.
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#
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# Empirical comparison vs an alternative "ship full channel_versions /
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# channel_values JSONB and let Python pick" form (1000 checkpoints,
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# 8 total channels in graph, 3 delta channels requested):
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#
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# Postgres execution: A=0.24ms vs B=0.38ms (both negligible)
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# End-to-end latency: A=6.83ms vs B=2.28ms (B is 3.0x faster)
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# Wire payload: A=836KB vs B=330KB (61% smaller)
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# Buffer hits: identical (167 blocks)
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#
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# B (this dynamic-columns design) wins because it avoids JSONB
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# serialization on the wire and JSONB-to-dict deserialization in
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# psycopg. Even at K=8 (8 delta channels = 16 dynamic columns), B
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# still beats A end-to-end (4.2ms vs 6.8ms).
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def _build_delta_stage1_sql(channels: Sequence[str]) -> str:
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"""Build stage 1 SQL with 2K parallel JSONB key lookups.
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For channels=["messages", "files"] the result is::
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SELECT checkpoint_id, parent_checkpoint_id,
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checkpoint -> 'channel_versions' ->> %s AS ver_0,
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(checkpoint -> 'channel_values' -> %s) IS NOT NULL AS hs_0,
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checkpoint -> 'channel_versions' ->> %s AS ver_1,
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(checkpoint -> 'channel_values' -> %s) IS NOT NULL AS hs_1
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FROM checkpoints
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WHERE thread_id = %s AND checkpoint_ns = %s
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Channel names are passed as `%s` parameters (safe from SQL injection).
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Only the column aliases `ver_i` / `hs_i` are interpolated into the
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SQL string (i is bounded by len(channels) and uses safe identifiers).
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Caller must extend params with `[ch_0, ch_0, ch_1, ch_1, ...,
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thread_id, ns]`.
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"""
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cols = []
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for i in range(len(channels)):
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cols.append(
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f"checkpoint -> 'channel_versions' ->> %s AS ver_{i}, "
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f"(checkpoint -> 'channel_values' -> %s) IS NOT NULL AS hs_{i}"
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)
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return (
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"SELECT checkpoint_id, parent_checkpoint_id, "
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+ ", ".join(cols)
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+ " FROM checkpoints WHERE thread_id = %s AND checkpoint_ns = %s"
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)
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SELECT_DELTA_STAGE1_SQL = """
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SELECT checkpoint_id,
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parent_checkpoint_id,
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checkpoint -> 'channel_versions' ->> %s AS ver,
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(checkpoint -> 'channel_values' -> %s) IS NOT NULL AS has_snapshot
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FROM checkpoints
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WHERE thread_id = %s AND checkpoint_ns = %s
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"""
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SELECT_DELTA_STAGE2_SQL = """
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SELECT 'w'::text AS _kind,
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checkpoint_id,
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checkpoint_id, channel,
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type, blob, task_id, idx, NULL::text AS version
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FROM checkpoint_writes
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WHERE thread_id = %s AND checkpoint_ns = %s AND channel = %s
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WHERE thread_id = %s AND checkpoint_ns = %s AND channel = ANY(%s)
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AND checkpoint_id = ANY(%s)
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UNION ALL
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SELECT 'b', NULL,
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SELECT 'b', NULL, channel,
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type, blob, NULL, NULL, version
|
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FROM checkpoint_blobs
|
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WHERE thread_id = %s AND checkpoint_ns = %s AND channel = %s
|
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WHERE thread_id = %s AND checkpoint_ns = %s AND channel = ANY(%s)
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AND version = ANY(%s)
|
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"""
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class _DeltaStage1Row(TypedDict):
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"""One row from `SELECT_DELTA_STAGE1_SQL`."""
|
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|
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checkpoint_id: str
|
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parent_checkpoint_id: str | None
|
||||
ver: str | None
|
||||
has_snapshot: bool
|
||||
# Stage 1 rows are dynamic-shape dicts: {checkpoint_id, parent_checkpoint_id,
|
||||
# ver_0, hs_0, ver_1, hs_1, ...}. Walking is parameterized by the channel
|
||||
# list to map indices back to channel names — no static TypedDict here.
|
||||
# `dict[str, Any]` is the practical signature.
|
||||
|
||||
|
||||
class BasePostgresSaver(BaseCheckpointSaver[str]):
|
||||
@@ -255,86 +293,119 @@ class BasePostgresSaver(BaseCheckpointSaver[str]):
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _walk_stage1(
|
||||
stage1_rows: Sequence[_DeltaStage1Row],
|
||||
def _walk_stage1_multi(
|
||||
stage1_rows: Sequence[Mapping[str, Any]],
|
||||
target_id: str,
|
||||
) -> tuple[list[str], str | None]:
|
||||
"""Walk the parent chain from stage 1 metadata rows.
|
||||
channels: Sequence[str],
|
||||
) -> tuple[dict[str, list[str]], dict[str, str | None]]:
|
||||
"""Walk the parent chain once for all requested channels.
|
||||
|
||||
Returns (chain_cids, seed_version):
|
||||
chain_cids: ancestor checkpoint IDs from target's parent down to
|
||||
the seed (or root), in newest-first order.
|
||||
seed_version: the channel blob version at the nearest ancestor
|
||||
with has_snapshot=True, or None if pure delta.
|
||||
Each row carries `ver_i` / `hs_i` per channel index. We walk the
|
||||
parent chain from target's parent toward the root; for each
|
||||
channel we stop at the nearest ancestor where `hs_i` is true and
|
||||
record that ancestor's `ver_i` as the seed version. All
|
||||
ancestors visited up to (and including) a channel's seed are in
|
||||
that channel's `chain_cids`.
|
||||
|
||||
Returns:
|
||||
chain_cids_by_channel: per-channel list of ancestor cids in
|
||||
newest-first order.
|
||||
seed_version_by_channel: per-channel seed version (None if
|
||||
walk reached root with no snapshot).
|
||||
"""
|
||||
parent_of: dict[str, str | None] = {}
|
||||
ver_of: dict[str, str | None] = {}
|
||||
snapshot_of: dict[str, bool] = {}
|
||||
# For each channel index, store ver and has_snapshot per cid.
|
||||
ver_by_i_by_cid: list[dict[str, str | None]] = [
|
||||
{} for _ in range(len(channels))
|
||||
]
|
||||
hs_by_i_by_cid: list[dict[str, bool]] = [{} for _ in range(len(channels))]
|
||||
|
||||
for r in stage1_rows:
|
||||
cid = r["checkpoint_id"]
|
||||
parent_of[cid] = r["parent_checkpoint_id"]
|
||||
ver_of[cid] = r["ver"]
|
||||
snapshot_of[cid] = r["has_snapshot"]
|
||||
cid = cast(str, r["checkpoint_id"])
|
||||
parent_of[cid] = cast("str | None", r["parent_checkpoint_id"])
|
||||
for i in range(len(channels)):
|
||||
ver_by_i_by_cid[i][cid] = cast("str | None", r.get(f"ver_{i}"))
|
||||
hs_by_i_by_cid[i][cid] = bool(r.get(f"hs_{i}"))
|
||||
|
||||
chain_cids: list[str] = []
|
||||
seed_version: str | None = None
|
||||
cur_cid: str | None = parent_of.get(target_id)
|
||||
while cur_cid is not None:
|
||||
chain_cids.append(cur_cid)
|
||||
if snapshot_of.get(cur_cid, False):
|
||||
seed_version = ver_of.get(cur_cid)
|
||||
break
|
||||
cur_cid = parent_of.get(cur_cid)
|
||||
return chain_cids, seed_version
|
||||
chain_by_ch: dict[str, list[str]] = {ch: [] for ch in channels}
|
||||
seed_ver_by_ch: dict[str, str | None] = {ch: None for ch in channels}
|
||||
# For each channel, walk from target's parent until we hit a
|
||||
# snapshot or the root. Walks share the parent_of mapping but
|
||||
# are otherwise independent.
|
||||
for i, ch in enumerate(channels):
|
||||
cur_cid: str | None = parent_of.get(target_id)
|
||||
while cur_cid is not None:
|
||||
chain_by_ch[ch].append(cur_cid)
|
||||
if hs_by_i_by_cid[i].get(cur_cid, False):
|
||||
seed_ver_by_ch[ch] = ver_by_i_by_cid[i].get(cur_cid)
|
||||
break
|
||||
cur_cid = parent_of.get(cur_cid)
|
||||
return chain_by_ch, seed_ver_by_ch
|
||||
|
||||
def _build_delta_channel_writes_history(
|
||||
def _build_delta_channels_writes_history(
|
||||
self,
|
||||
*,
|
||||
channel: str,
|
||||
chain_cids: list[str],
|
||||
seed_version: str | None,
|
||||
channels: Sequence[str],
|
||||
chain_by_ch: dict[str, list[str]],
|
||||
seed_ver_by_ch: dict[str, str | None],
|
||||
stage2_rows: Sequence[_DeltaStage2Row],
|
||||
) -> _ChannelWritesHistory:
|
||||
"""Reconstruct delta channel history from two-stage query results.
|
||||
) -> dict[str, _ChannelWritesHistory]:
|
||||
"""Demux stage 2 rows per channel; produce per-channel histories.
|
||||
|
||||
chain_cids are in newest-first order (target's parent first).
|
||||
stage2_rows contain only writes for chain_cids and the single
|
||||
seed blob at seed_version.
|
||||
stage2_rows carry `channel` on every row. We build per-channel
|
||||
`writes_by_cid` and per-channel `seed_blob` dicts, then assemble
|
||||
a `_ChannelWritesHistory` per requested channel.
|
||||
"""
|
||||
writes_by_cid: dict[str, list[tuple[str, bytes, str, int]]] = {}
|
||||
seed_blob: tuple[str, bytes] | None = None
|
||||
# writes_by_ch_by_cid[channel][cid] = list of (type, blob, task_id, idx)
|
||||
writes_by_ch_by_cid: dict[
|
||||
str, dict[str, list[tuple[str, bytes, str, int]]]
|
||||
] = {ch: {} for ch in channels}
|
||||
# seed_blob_by_ver[(channel, version)] = (type, blob)
|
||||
seed_blob_by_ver: dict[tuple[str, str], tuple[str, bytes]] = {}
|
||||
|
||||
for r in stage2_rows:
|
||||
ch = cast(str, r["channel"])
|
||||
kind = r["_kind"]
|
||||
if kind == "w":
|
||||
cid = cast(str, r["checkpoint_id"])
|
||||
writes_by_cid.setdefault(cid, []).append(
|
||||
writes_by_ch_by_cid.setdefault(ch, {}).setdefault(cid, []).append(
|
||||
cast(
|
||||
"tuple[str, bytes, str, int]",
|
||||
(r["type"], r["blob"], r["task_id"], r["idx"]),
|
||||
)
|
||||
)
|
||||
else: # kind == "b"
|
||||
seed_blob = cast("tuple[str, bytes]", (r["type"], r["blob"]))
|
||||
ver = cast(str, r["version"])
|
||||
seed_blob_by_ver[(ch, ver)] = cast(
|
||||
"tuple[str, bytes]", (r["type"], r["blob"])
|
||||
)
|
||||
|
||||
for ws in writes_by_cid.values():
|
||||
ws.sort(key=lambda w: (w[2], w[3]), reverse=True)
|
||||
# Sort writes per (channel, cid) newest-first by (task_id, idx)
|
||||
for cid_map in writes_by_ch_by_cid.values():
|
||||
for ws in cid_map.values():
|
||||
ws.sort(key=lambda w: (w[2], w[3]), reverse=True)
|
||||
|
||||
if not chain_cids:
|
||||
return _ChannelWritesHistory(seed=DELTA_SENTINEL, writes=[])
|
||||
result: dict[str, _ChannelWritesHistory] = {}
|
||||
for ch in channels:
|
||||
chain_cids = chain_by_ch.get(ch, [])
|
||||
seed_version = seed_ver_by_ch.get(ch)
|
||||
|
||||
collected: list[PendingWrite] = []
|
||||
for cid in chain_cids:
|
||||
for type_tag, write_blob, task_id, _idx in writes_by_cid.get(cid, []):
|
||||
val = self.serde.loads_typed((type_tag, write_blob))
|
||||
collected.append((task_id, channel, val))
|
||||
collected: list[PendingWrite] = []
|
||||
cid_writes = writes_by_ch_by_cid.get(ch, {})
|
||||
for cid in chain_cids:
|
||||
for type_tag, write_blob, task_id, _idx in cid_writes.get(cid, []):
|
||||
val = self.serde.loads_typed((type_tag, write_blob))
|
||||
collected.append((task_id, ch, val))
|
||||
|
||||
seed: Any = DELTA_SENTINEL
|
||||
if seed_blob is not None and seed_blob[0] != "empty":
|
||||
seed = self.serde.loads_typed(seed_blob)
|
||||
seed: Any = DELTA_SENTINEL
|
||||
if seed_version is not None:
|
||||
blob = seed_blob_by_ver.get((ch, seed_version))
|
||||
if blob is not None and blob[0] != "empty":
|
||||
seed = self.serde.loads_typed(blob)
|
||||
|
||||
collected.reverse()
|
||||
return _ChannelWritesHistory(seed=seed, writes=collected)
|
||||
collected.reverse()
|
||||
result[ch] = _ChannelWritesHistory(seed=seed, writes=collected)
|
||||
return result
|
||||
|
||||
def _dump_blobs(
|
||||
self,
|
||||
|
||||
Reference in New Issue
Block a user