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Parent: #3110, checklist items "Establish representative OLTP and storage workload baselines" and "Define rolling-upgrade and rollback requirements before HStore/PD work".
Sibling: apache/hugegraph-toolchain#772 (shared data generator; there the loader is measured as a client, here the server and the storage).
Does not overlap with #3145 (codec fixtures, PoC selection matrix).
Scope
OLTP baseline. A fixed mix on a shared dataset (CI profile 100k vertices / 500k edges, full profile 5M / 25M): point read by id, 1-hop and 2-hop over edges, a secondary-index query, batch insert, batch update with the SUM strategy, Gremlin g.V().has(). For each: p50/p95/p99, throughput, server RSS and heap, on rocksdb (single node) and on hstore (1 PD + 3 Store, Helm chart from feat(helm): add HStore deployment chart hugegraph/hugegraph#221). A Python harness against REST; results as markdown plus raw JSON.
HStore storage baseline. After loading the full profile: size of storage/ split into db, raft log and snapshot; duration and effect of a forced compaction; snapshot duration; time to rebuild a replica after a Store loses its disk; replication lag under writes. Method from hugegraph-store/docs/operations-guide.md and my earlier measurements.
No tuning: the baseline measures the default configuration of the chart and of the distribution; tuning is separate work.
Acceptance criteria
The harness reproduces the CI profile with a single command against a server from the distribution (rocksdb) and against the chart (hstore); the full profile is published with hardware configuration, versions and logs.
Documents in the repo: docs/workload-baselines.md (numbers and method) and docs/upgrade-requirements.md; the harness under hugegraph-server/hugegraph-dist/scripts/baseline/ or wherever review points.
PR plan
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OLTP harness (CI profile) plus the generator shared with toolchain #772, numbers from rocksdb and hstore on the cluster, docs/workload-baselines.md
Parent: #3110, checklist items "Establish representative OLTP and storage workload baselines" and "Define rolling-upgrade and rollback requirements before HStore/PD work".
Sibling: apache/hugegraph-toolchain#772 (shared data generator; there the loader is measured as a client, here the server and the storage).
Does not overlap with #3145 (codec fixtures, PoC selection matrix).
Scope
SUMstrategy, Gremling.V().has(). For each: p50/p95/p99, throughput, server RSS and heap, on rocksdb (single node) and on hstore (1 PD + 3 Store, Helm chart from feat(helm): add HStore deployment chart hugegraph/hugegraph#221). A Python harness against REST; results as markdown plus raw JSON.storage/split into db, raft log and snapshot; duration and effect of a forced compaction; snapshot duration; time to rebuild a replica after a Store loses its disk; replication lag under writes. Method fromhugegraph-store/docs/operations-guide.mdand my earlier measurements.docs/upgrade-requirements.mdinhugegraph-store/docswith a requirement / test / status table.Non-goals
Acceptance criteria
docs/workload-baselines.md(numbers and method) anddocs/upgrade-requirements.md; the harness underhugegraph-server/hugegraph-dist/scripts/baseline/or wherever review points.PR plan
docs/workload-baselines.mddocs/upgrade-requirements.mdwith the upgrade/rollback harness (5 requirements, results on master)