mirror of
https://github.com/GreptimeTeam/greptimedb.git
synced 2026-10-18 01:42:28 +00:00
85 lines
2.8 KiB
TOML
85 lines
2.8 KiB
TOML
# Explicit-only default-versus-BSS storage and warmed-query comparison. This is
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# intentionally outside the routine default case set.
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[case]
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name = "sst_float_bss"
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description = "Compare default and byte-stream-split floating-point SST bytes and warmed value-scanning query latency with bounded 95/5 per-series DOUBLE values"
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[scenario]
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kind = "prom_remote_write_then_query"
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[scenario.remote_write]
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database = "public"
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metric = "sst_float_bss"
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physical_table = "sst_float_bss_physical"
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series_count = 1000
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samples_per_series = 4320
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sample_chunk_size = 1440
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flush_every_sample_chunks = 1
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start_unix_millis = 1_704_067_200_000 # 2024-01-01T00:00:00Z
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step_millis = 60000
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chunk_series_count = 128
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timeout_seconds = 600
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visibility_timeout_seconds = 300
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# Keep the physical-table definition identical except for float encoding. The
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# high shared TWCS trigger avoids compaction changing the three-flush layout.
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base_setup_sql = [
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"CREATE TABLE sst_float_bss_physical (greptime_timestamp TIMESTAMP TIME INDEX, greptime_value DOUBLE) ENGINE=metric WITH ('physical_metric_table'='', 'experimental_sst_float_field_encoding'='default', 'compaction.twcs.trigger_file_num'='100')",
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]
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candidate_setup_sql = [
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"CREATE TABLE sst_float_bss_physical (greptime_timestamp TIMESTAMP TIME INDEX, greptime_value DOUBLE) ENGINE=metric WITH ('physical_metric_table'='', 'experimental_sst_float_field_encoding'='byte_stream_split', 'compaction.twcs.trigger_file_num'='100')",
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]
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[scenario.remote_write.value]
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# Synthetic, not empirical: 95% integral and 5% nonintegral series vary
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# smoothly within deterministic per-series ranges; series are not a global monotonic counter.
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pattern = "bounded_mixed"
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base = 0
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step = 1
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cardinality = 1000
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seed = 42
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mixed_every = 20
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run_length = 60
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[scenario.remote_write.prom_store]
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pending_rows_flush_interval = "1s"
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max_batch_rows = 100000
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[scenario.remote_write.storage]
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root_suffix = "data/greptime/public"
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column = "greptime_value"
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min_files = 1
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min_files_with_column = 1
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max_candidate_total_file_size_regression_pct = -5.0
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[scenario.remote_write.read_bench]
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enabled = true
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parquetbench = true
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scanbench = true
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iterations = 7
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projection = ["greptime_value"]
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parquet_reader = "direct"
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scan_scanner = "seq"
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parallelism = 1
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[[scenario.queries]]
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name = "sum_all_values"
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kind = "sql"
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query = "SELECT sum(greptime_value) FROM sst_float_bss"
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warmup = 3
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iterations = 15
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[scenario.queries.thresholds]
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max_candidate_latency_regression_pct = 25
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[[scenario.queries]]
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name = "hourly_sum_values"
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kind = "sql"
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query = "SELECT date_bin(INTERVAL '1 hour', greptime_timestamp) AS time_window, sum(greptime_value) FROM sst_float_bss WHERE greptime_timestamp >= TIMESTAMP '2024-01-01 00:00:00' AND greptime_timestamp < TIMESTAMP '2024-01-04 00:00:00' GROUP BY time_window ORDER BY time_window"
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warmup = 3
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iterations = 15
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[scenario.queries.thresholds]
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max_candidate_latency_regression_pct = 25
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