# Default all-group default-versus-BSS storage and warmed-query comparison.

[case]
name = "sst_float_bss"
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"

[scenario]
kind = "prom_remote_write_then_query"

[scenario.remote_write]
database = "public"
metric = "sst_float_bss"
physical_table = "sst_float_bss_physical"
series_count = 1000
samples_per_series = 4320
sample_chunk_size = 1440
flush_every_sample_chunks = 1
start_unix_millis = 1_704_067_200_000 # 2024-01-01T00:00:00Z
step_millis = 60000
chunk_series_count = 128
timeout_seconds = 600
visibility_timeout_seconds = 300

# Omit the default encoding from base setup because older binaries do not recognize it.
# The high shared TWCS trigger avoids compaction changing the three-flush layout.
base_setup_sql = [
  "CREATE TABLE sst_float_bss_physical (greptime_timestamp TIMESTAMP TIME INDEX, greptime_value DOUBLE) ENGINE=metric WITH ('physical_metric_table'='', 'compaction.twcs.trigger_file_num'='100')",
]
candidate_setup_sql = [
  "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')",
]

[scenario.remote_write.value]
# Synthetic, not empirical: 95% integral and 5% nonintegral series vary
# smoothly within deterministic per-series ranges; series are not a global monotonic counter.
pattern = "bounded_mixed"
base = 0
step = 1
cardinality = 1000
seed = 42
mixed_every = 20
run_length = 60

[scenario.remote_write.prom_store]
pending_rows_flush_interval = "1s"
max_batch_rows = 100000

[scenario.remote_write.storage]
root_suffix = "data/greptime/public"
column = "greptime_value"
min_files = 1
min_files_with_column = 1
max_candidate_total_file_size_regression_pct = -5.0

[scenario.remote_write.read_bench]
enabled = true
parquetbench = true
scanbench = true
iterations = 7
projection = ["greptime_value"]
parquet_reader = "direct"
scan_scanner = "seq"
parallelism = 1

[[scenario.queries]]
name = "sum_all_values"
kind = "sql"
query = "SELECT sum(greptime_value) FROM sst_float_bss"
warmup = 3
iterations = 15

[scenario.queries.thresholds]
max_candidate_latency_regression_pct = 25

[[scenario.queries]]
name = "hourly_sum_values"
kind = "sql"
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"
warmup = 3
iterations = 15

[scenario.queries.thresholds]
max_candidate_latency_regression_pct = 25