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|**1. Setup**| Connect to system adapter via JSON-RPC (stdio or HTTP). Call `setup(run_id, datasets)` to provision the SUT and return ADBC driver config, then `create_tables(run_id)`. | No |
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|**2. Benchmark (timed)**| Three sequential stages — warm-up (1× query set), baseline (10% of duration, 60s–600s), and load test (full duration with concurrent clients). | Yes |
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|**3. Teardown**| Call `teardown(run_id)` via the adapter to deprovision resources and clean up. | No |
|**1. Setup**| Connect to system adapter via JSON-RPC (stdio or HTTP). Call `setup(run_id, metadata)` to provision the SUT and return ADBC driver config, then `create_tables(run_id, datasets)`. | No |
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|**2. Benchmark (timed)**| Three sequential stages — warm-up (1× query set), baseline (10% of duration, 60s–600s), and load test (full duration with concurrent clients). | Yes |
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|**3. Teardown**| Call `teardown(run_id)` via the adapter to deprovision resources and clean up. | No |
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The **E2E benchmark duration** (phase 2, load test stage) is the primary ranking metric. After the load test, each query's p99 latency is compared against the baseline: >20% increase = FAIL, 10–20% = WARN, ≥3 WARNs = FAIL.
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@@ -215,8 +215,8 @@ Results from every Run are published to [SpiceBench.com](https://spicebench.com)
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To benchmark a new platform, implement the JSON-RPC 2.0 adapter with these methods:
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1.**`setup(run_id, datasets)`** — Provision infrastructure and configure the target system.
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2.**`create_tables(run_id)`** — Create/register destination tables for the benchmark datasets.
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1.**`setup(run_id, metadata)`** — Provision infrastructure and configure the target system.
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2.**`create_tables(run_id, datasets)`** — Create/register destination tables for the benchmark datasets.
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3.**`teardown(run_id)`** — Clean up provisioned resources.
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4.**`metrics(run_id)`***(optional)* — Return current resource usage (CPU, memory, disk, IOPS) and ingestion progress (rows, bytes, rows/s, active connections).
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@@ -243,8 +243,8 @@ The `spicebench` CLI connects to a system adapter using JSON-RPC 2.0 over either
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For each run, SpiceBench calls adapter JSON-RPC methods in this order:
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1.`setup(run_id, datasets, metadata)`
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2.`create_tables(run_id)`
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1.`setup(run_id, metadata)`
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2.`create_tables(run_id, datasets)`
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3. benchmark execution and optional periodic `metrics(run_id)` scraping
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