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discord9
12f83828b1
* feat: add Prom remote-write query regression scenario Signed-off-by: discord9 <discord9@163.com> * test: add high-cardinality remote-write query case Signed-off-by: discord9 <discord9@163.com> * feat: chunk remote-write query regression loads Signed-off-by: discord9 <discord9@163.com> * test: use multi-day remote-write regression case Signed-off-by: discord9 <discord9@163.com> * fix: address query regression review comments Signed-off-by: discord9 <discord9@163.com> * ci: allow large query regression comments Signed-off-by: discord9 <discord9@163.com> --------- Signed-off-by: discord9 <discord9@163.com>
102 lines
3.0 KiB
TOML
102 lines
3.0 KiB
TOML
# Query performance regression case for GreptimeDB issue #7913.
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# This is a case config for the generic direct-SST fixture generator. The
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# generator must not hard-code PromQL/#7913 behavior; this file only supplies one
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# schema/layout/query instance.
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[case]
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name = "promql_pushdown_7913"
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description = "PromQL/TQL small-window selectors should stay fast on high-cardinality metric-like fixtures"
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issue = "https://github.com/GreptimeTeam/greptimedb/issues/7913"
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[scenario]
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kind = "direct_readable_sst"
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seed = 7913
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[[scenario.tables]]
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database = "public"
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name = "promql_pushdown_7913"
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engine = "mito"
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append_mode = true
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sst_format = "flat"
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primary_key = ["host", "instance"]
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time_index = "greptime_timestamp"
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[[scenario.tables.columns]]
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name = "host"
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type = "STRING"
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semantic = "tag"
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distribution = { kind = "cardinality", values = 256, prefix = "host" }
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[[scenario.tables.columns]]
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name = "instance"
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type = "STRING"
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semantic = "tag"
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distribution = { kind = "cardinality", values = 4096, prefix = "instance" }
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[[scenario.tables.columns]]
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name = "download_mbs"
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type = "DOUBLE"
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semantic = "field"
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distribution = { kind = "deterministic_wave", min = 0.0, max = 1000.0 }
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[[scenario.tables.columns]]
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name = "greptime_timestamp"
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type = "TIMESTAMP(9)"
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semantic = "timestamp"
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[scenario.layout]
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regions = 1
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sst_count = 1024
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rows_per_sst = 32768
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row_group_size = 8192
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series_count = 4096
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start_unix_nanos = 1_704_067_200_000_000_000 # 2024-01-01T00:00:00Z
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step_nanos = 1_000_000_000
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time_range_layout = "non_overlapping_per_sst"
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series_layout = "timestamp_major"
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[[scenario.queries]]
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name = "selector_5m_high_cardinality"
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kind = "tql"
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# TQL start/end timestamps are epoch seconds. `timestamp_major` layout writes one
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# sample for every series at each scrape timestamp, so short PromQL windows still
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# scan millions of raw samples instead of millisecond-scale synthetic trickles.
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# The default 5-minute lookback means scans start before each query window.
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query = "TQL ANALYZE VERBOSE (1704069000, 1704069300, '15s') promql_pushdown_7913{host=~'host.*'}"
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warmup = 3
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iterations = 9
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[scenario.queries.thresholds]
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max_candidate_latency_regression_pct = 15
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[[scenario.queries]]
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name = "latest_timestamp_equality_subquery"
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kind = "sql"
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query = "SELECT * FROM promql_pushdown_7913 WHERE greptime_timestamp = (SELECT greptime_timestamp FROM promql_pushdown_7913 ORDER BY greptime_timestamp DESC LIMIT 1)"
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warmup = 3
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iterations = 9
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[scenario.queries.thresholds]
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max_candidate_latency_regression_pct = 15
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[[scenario.queries]]
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name = "selector_15m_high_cardinality"
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kind = "tql"
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query = "TQL ANALYZE VERBOSE (1704069000, 1704069900, '15s') promql_pushdown_7913{host=~'host.*'}"
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warmup = 3
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iterations = 9
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[scenario.queries.thresholds]
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max_candidate_latency_regression_pct = 15
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[[scenario.queries]]
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name = "selector_1h_high_cardinality"
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kind = "tql"
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query = "TQL ANALYZE VERBOSE (1704069000, 1704072600, '15s') promql_pushdown_7913{host=~'host.*'}"
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warmup = 3
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iterations = 9
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[scenario.queries.thresholds]
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max_candidate_latency_regression_pct = 15
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