diff --git a/tests/perf/query_cases/promql_rate_dense_resets/case.toml b/tests/perf/query_cases/promql_rate_dense_resets/case.toml
new file mode 100644
index 0000000000..4a03a0854a
--- /dev/null
+++ b/tests/perf/query_cases/promql_rate_dense_resets/case.toml
@@ -0,0 +1,163 @@
+# PromQL rate/increase window-width and evaluation-step benchmark with dense resets.
+#
+# Remote-write `modulo` values use cardinality 15 and step 1. Because 780 is
+# divisible by 15, every one of the 128 series resets from 14 to 0 exactly every
+# 15 local samples (225 seconds) at the 15-second cadence: 51 resets
+# per series in 780 samples. The `resets` HTTP control is manually inspected in
+# its retained response: each aligned one-hour window contains 240 samples and
+# should report 16 resets per series. The runner does not assert numeric values.
+
+[case]
+name = "promql_rate_dense_resets"
+description = "PromQL rate and increase across windows and steps for counters resetting every 15 samples"
+issue = "https://github.com/GreptimeTeam/greptimedb/pull/9089"
+
+[scenario]
+kind = "prom_remote_write_then_query"
+
+[scenario.remote_write]
+database = "public"
+metric = "promql_rate_dense_resets"
+physical_table = "greptime_physical_table"
+series_count = 128
+samples_per_series = 780
+sample_chunk_size = 195
+flush_every_sample_chunks = 1
+start_unix_millis = 1704067200000
+step_millis = 15000
+chunk_series_count = 128
+timeout_seconds = 180
+visibility_timeout_seconds = 120
+
+[scenario.remote_write.value]
+pattern = "modulo"
+base = 0
+step = 1
+cardinality = 15
+
+[scenario.remote_write.prom_store]
+pending_rows_flush_interval = "1s"
+max_batch_rows = 100000
+
+[[scenario.queries]]
+name = "selector_control_2h_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') promql_rate_dense_resets{host=~'host.*'}"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "rate_1m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') rate(promql_rate_dense_resets{host=~'host.*'}[1m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "increase_1m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') increase(promql_rate_dense_resets{host=~'host.*'}[1m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "rate_5m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') rate(promql_rate_dense_resets{host=~'host.*'}[5m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "increase_5m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') increase(promql_rate_dense_resets{host=~'host.*'}[5m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "rate_1h_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') rate(promql_rate_dense_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "increase_1h_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') increase(promql_rate_dense_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+# Twelve evaluations per 1h window: representative larger overlapping step.
+[[scenario.queries]]
+name = "rate_1h_5m_overlapping"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '5m') rate(promql_rate_dense_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+# One evaluation per 1h window: representative non-overlapping step.
+[[scenario.queries]]
+name = "increase_1h_1h_non_overlapping"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '1h') increase(promql_rate_dense_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "resets_1h_1h_expected_sixteen"
+kind = "prom_http"
+query = "resets(promql_rate_dense_resets{host=~\"host.*\"}[1h])"
+start = "1704070800"
+end = "1704078000"
+step = "1h"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+# Manual response check: at 1704070800, 1704074400, and 1704078000, the
+# left-open 1h windows contain samples 1..240, 241..480, and 481..720. Each has
+# 16 resets and extrapolated increase 53520 / 239 = 223.93305439330544. The runner
+# retains but does not assert it.
+
+[[scenario.queries]]
+name = "increase_1h_host0000_manual_response_check"
+kind = "prom_http"
+query = "increase(promql_rate_dense_resets{host=\"host0000\"}[1h])"
+start = "1704070800"
+end = "1704078000"
+step = "1h"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
diff --git a/tests/perf/query_cases/promql_rate_no_resets/case.toml b/tests/perf/query_cases/promql_rate_no_resets/case.toml
new file mode 100644
index 0000000000..0486ced4e8
--- /dev/null
+++ b/tests/perf/query_cases/promql_rate_no_resets/case.toml
@@ -0,0 +1,160 @@
+# PromQL rate/increase window-width and evaluation-step benchmark without resets.
+#
+# Remote-write `linear` values increase by one at every 15-second sample for
+# each series. 128 series × 780 samples = 99,840 rows over 3h14m45s.
+# The `resets` HTTP control below is manually inspected in its retained response:
+# it should report 0 for every series at all three one-hour, non-overlapping
+# evaluations. The runner records the response but does not assert its numeric values.
+
+[case]
+name = "promql_rate_no_resets"
+description = "PromQL rate and increase across windows and steps for monotonic counters without resets"
+issue = "https://github.com/GreptimeTeam/greptimedb/pull/9089"
+
+[scenario]
+kind = "prom_remote_write_then_query"
+
+[scenario.remote_write]
+database = "public"
+metric = "promql_rate_no_resets"
+physical_table = "greptime_physical_table"
+series_count = 128
+samples_per_series = 780
+sample_chunk_size = 195
+flush_every_sample_chunks = 1
+start_unix_millis = 1704067200000
+step_millis = 15000
+chunk_series_count = 128
+timeout_seconds = 180
+visibility_timeout_seconds = 120
+
+[scenario.remote_write.value]
+pattern = "linear"
+base = 0
+step = 1
+
+[scenario.remote_write.prom_store]
+pending_rows_flush_interval = "1s"
+max_batch_rows = 100000
+
+[[scenario.queries]]
+name = "selector_control_2h_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') promql_rate_no_resets{host=~'host.*'}"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "rate_1m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') rate(promql_rate_no_resets{host=~'host.*'}[1m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "increase_1m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') increase(promql_rate_no_resets{host=~'host.*'}[1m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "rate_5m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') rate(promql_rate_no_resets{host=~'host.*'}[5m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "increase_5m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') increase(promql_rate_no_resets{host=~'host.*'}[5m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "rate_1h_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') rate(promql_rate_no_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "increase_1h_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') increase(promql_rate_no_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+# Twelve evaluations per 1h window: representative larger overlapping step.
+[[scenario.queries]]
+name = "rate_1h_5m_overlapping"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '5m') rate(promql_rate_no_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+# One evaluation per 1h window: representative non-overlapping step.
+[[scenario.queries]]
+name = "increase_1h_1h_non_overlapping"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '1h') increase(promql_rate_no_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "resets_1h_1h_expected_zero"
+kind = "prom_http"
+query = "resets(promql_rate_no_resets{host=~\"host.*\"}[1h])"
+start = "1704070800"
+end = "1704078000"
+step = "1h"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+# Manual response check: at 1704070800, 1704074400, and 1704078000, the
+# left-open 1h windows contain samples 1..240, 241..480, and 481..720. Each
+# extrapolated increase is exactly 240. The runner retains but does not assert it.
+
+[[scenario.queries]]
+name = "increase_1h_host0000_manual_response_check"
+kind = "prom_http"
+query = "increase(promql_rate_no_resets{host=\"host0000\"}[1h])"
+start = "1704070800"
+end = "1704078000"
+step = "1h"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
diff --git a/tests/perf/query_cases/promql_rate_sparse_resets/case.toml b/tests/perf/query_cases/promql_rate_sparse_resets/case.toml
new file mode 100644
index 0000000000..110a1e471e
--- /dev/null
+++ b/tests/perf/query_cases/promql_rate_sparse_resets/case.toml
@@ -0,0 +1,163 @@
+# PromQL rate/increase window-width and evaluation-step benchmark with sparse resets.
+#
+# Remote-write `modulo` values use cardinality 195 and step 1. Because 780 is
+# divisible by 195, every one of the 128 series resets from 194 to 0 exactly at
+# local sample indexes 195, 390, and 585 (15-second cadence): three resets per
+# series. The `resets` HTTP control is manually inspected in its retained response:
+# each aligned one-hour window should report 1 reset per series. The runner does
+# not assert numeric response values.
+
+[case]
+name = "promql_rate_sparse_resets"
+description = "PromQL rate and increase across windows and steps for counters resetting every 195 samples"
+issue = "https://github.com/GreptimeTeam/greptimedb/pull/9089"
+
+[scenario]
+kind = "prom_remote_write_then_query"
+
+[scenario.remote_write]
+database = "public"
+metric = "promql_rate_sparse_resets"
+physical_table = "greptime_physical_table"
+series_count = 128
+samples_per_series = 780
+sample_chunk_size = 195
+flush_every_sample_chunks = 1
+start_unix_millis = 1704067200000
+step_millis = 15000
+chunk_series_count = 128
+timeout_seconds = 180
+visibility_timeout_seconds = 120
+
+[scenario.remote_write.value]
+pattern = "modulo"
+base = 0
+step = 1
+cardinality = 195
+
+[scenario.remote_write.prom_store]
+pending_rows_flush_interval = "1s"
+max_batch_rows = 100000
+
+[[scenario.queries]]
+name = "selector_control_2h_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') promql_rate_sparse_resets{host=~'host.*'}"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "rate_1m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') rate(promql_rate_sparse_resets{host=~'host.*'}[1m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "increase_1m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') increase(promql_rate_sparse_resets{host=~'host.*'}[1m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "rate_5m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') rate(promql_rate_sparse_resets{host=~'host.*'}[5m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "increase_5m_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') increase(promql_rate_sparse_resets{host=~'host.*'}[5m])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "rate_1h_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') rate(promql_rate_sparse_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "increase_1h_15s"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '15s') increase(promql_rate_sparse_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+# Twelve evaluations per 1h window: representative larger overlapping step.
+[[scenario.queries]]
+name = "rate_1h_5m_overlapping"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '5m') rate(promql_rate_sparse_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+# One evaluation per 1h window: representative non-overlapping step.
+[[scenario.queries]]
+name = "increase_1h_1h_non_overlapping"
+kind = "tql"
+query = "TQL ANALYZE VERBOSE (1704070800, 1704078000, '1h') increase(promql_rate_sparse_resets{host=~'host.*'}[1h])"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+[[scenario.queries]]
+name = "resets_1h_1h_expected_one"
+kind = "prom_http"
+query = "resets(promql_rate_sparse_resets{host=~\"host.*\"}[1h])"
+start = "1704070800"
+end = "1704078000"
+step = "1h"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10
+
+# Manual response check: at 1704070800, 1704074400, and 1704078000, the
+# left-open 1h windows contain samples 1..240, 241..480, and 481..720. Each has
+# one reset and extrapolated increase 57120 / 239 = 238.9958158995816. The runner
+# retains but does not assert it.
+
+[[scenario.queries]]
+name = "increase_1h_host0000_manual_response_check"
+kind = "prom_http"
+query = "increase(promql_rate_sparse_resets{host=\"host0000\"}[1h])"
+start = "1704070800"
+end = "1704078000"
+step = "1h"
+warmup = 3
+iterations = 9
+
+[scenario.queries.thresholds]
+max_candidate_latency_regression_pct = 10