| {"template_id": "tpl_cardinality_distinct_share_profile", "template_name": "Cardinality Distinct Share Profile", "source_workload_id": "subitem_workload_v2", "primary_family": "cardinality_structure", "secondary_family": null, "intent": "New deterministic template for v2.", "sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "required_roles": ["group_col"], "optional_roles": [], "constraints": ["single_table_only", "v2_deterministic_template"], "single_table_portable": "yes", "provenance": {"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_cardinality_distinct_share_profile"}, "provenance_sources": [{"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_cardinality_distinct_share_profile"}], "status": "ready", "notes": "New deterministic template for v2.", "materialization_bucket": "v2_deterministic", "activation_tier": "v2", "dialect_sensitive": false, "family_id": "cardinality_structure", "realization_mode": "deterministic", "binding_roles": ["group_col"], "supported_canonical_subitem_ids": ["support_rank_profile_consistency"], "allowed_variant_roles": ["ranked_signal_view"], "default_facet_ids": ["support_concentration", "value_imbalance_profile"], "gate_priority": "deterministic", "source_catalog": "template_library_v2", "extended_family": true} | |
| {"template_id": "tpl_cardinality_high_card_response_stability", "template_name": "High-Cardinality Response Stability", "source_workload_id": "subitem_workload_v2", "primary_family": "cardinality_structure", "secondary_family": null, "intent": "New deterministic template for v2.", "sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", "required_roles": ["key_col", "target_col"], "optional_roles": [], "constraints": ["single_table_only", "v2_deterministic_template"], "single_table_portable": "yes", "provenance": {"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_cardinality_high_card_response_stability"}, "provenance_sources": [{"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_cardinality_high_card_response_stability"}], "status": "ready", "notes": "New deterministic template for v2.", "materialization_bucket": "v2_deterministic", "activation_tier": "v2", "dialect_sensitive": false, "family_id": "cardinality_structure", "realization_mode": "deterministic", "binding_roles": ["key_col", "target_col"], "supported_canonical_subitem_ids": ["high_cardinality_response_stability"], "allowed_variant_roles": ["focused_target_view"], "default_facet_ids": ["target_cardinality_cross_section"], "gate_priority": "deterministic", "source_catalog": "template_library_v2", "extended_family": true} | |
| {"template_id": "tpl_cardinality_support_rank_profile", "template_name": "Cardinality Support Rank Profile", "source_workload_id": "subitem_workload_v2", "primary_family": "cardinality_structure", "secondary_family": null, "intent": "New deterministic template for v2.", "sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "required_roles": ["group_col"], "optional_roles": [], "constraints": ["single_table_only", "v2_deterministic_template"], "single_table_portable": "yes", "provenance": {"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_cardinality_support_rank_profile"}, "provenance_sources": [{"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_cardinality_support_rank_profile"}], "status": "ready", "notes": "New deterministic template for v2.", "materialization_bucket": "v2_deterministic", "activation_tier": "v2", "dialect_sensitive": false, "family_id": "cardinality_structure", "realization_mode": "deterministic", "binding_roles": ["group_col"], "supported_canonical_subitem_ids": ["support_rank_profile_consistency"], "allowed_variant_roles": ["count_distribution"], "default_facet_ids": ["support_concentration", "value_imbalance_profile"], "gate_priority": "deterministic", "source_catalog": "template_library_v2", "extended_family": true} | |
| {"template_id": "tpl_c2_filtered_group_count_2d", "template_name": "Filtered Two-Dimensional Group Count", "source_workload_id": "car_evaluation_sql_repo", "primary_family": "conditional_dependency_structure", "secondary_family": "subgroup_structure", "intent": "Count rows for a filtered slice across two subgroup dimensions.", "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;", "required_roles": ["group_col", "group_col_2", "predicate_col"], "optional_roles": [], "constraints": ["group_col:groupable", "group_col_2:groupable_distinct_from_group_col", "predicate_col:filterable", "single_table_only"], "single_table_portable": "yes", "provenance": {"url": "https://github.com/nehanawar025/Exploratory-Analysis-of-Car-Evaluation-Dataset-with-SQL/blob/main/Answers.sql", "title": "Answers.sql · Exploratory-Analysis-of-Car-Evaluation-Dataset-with-SQL", "source_query_id": "c2_sql_0008"}, "provenance_sources": [{"url": "https://github.com/nehanawar025/Exploratory-Analysis-of-Car-Evaluation-Dataset-with-SQL/blob/main/Answers.sql", "title": "Answers.sql · Exploratory-Analysis-of-Car-Evaluation-Dataset-with-SQL", "source_query_id": "c2_sql_0008"}], "status": "ready", "notes": "Useful as a general “slice then compare subgroups” template.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["group_col", "group_col_2", "predicate_col"], "supported_canonical_subitem_ids": ["slice_level_consistency"], "allowed_variant_roles": ["count_distribution"], "default_facet_ids": ["conditional_interaction_hotspots"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_c2_two_dim_target_rate", "template_name": "Two-Axis Target Rate Surface", "source_workload_id": "car_evaluation_sql_repo", "primary_family": "conditional_dependency_structure", "secondary_family": "subgroup_structure", "intent": "Measure how a categorical target rate changes across a pair of subgroup axes.", "sql_skeleton": "SELECT {group_col}, {group_col_2},\n AVG(CASE WHEN {target_col} = {target_value} THEN 1 ELSE 0 END) AS target_rate\nFROM {table}\nGROUP BY {group_col}, {group_col_2}\nORDER BY target_rate DESC;", "required_roles": ["group_col", "group_col_2", "target_col"], "optional_roles": [], "constraints": ["group_col:groupable", "group_col_2:groupable_distinct_from_group_col", "target_col:categorical_or_binary", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/nehanawar025/Exploratory-Analysis-of-Car-Evaluation-Dataset-with-SQL/blob/main/Answers.sql", "title": "Answers.sql · Exploratory-Analysis-of-Car-Evaluation-Dataset-with-SQL", "source_query_id": "c2_sql_0007"}, "provenance_sources": [{"url": "https://github.com/nehanawar025/Exploratory-Analysis-of-Car-Evaluation-Dataset-with-SQL/blob/main/Answers.sql", "title": "Answers.sql · Exploratory-Analysis-of-Car-Evaluation-Dataset-with-SQL", "source_query_id": "c2_sql_0007"}], "status": "ready", "notes": "Strong fit for classification-style single-table datasets; partial on regression tasks.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["group_col", "group_col_2", "target_col"], "supported_canonical_subitem_ids": ["dependency_strength_similarity", "direction_consistency"], "allowed_variant_roles": ["within_group_proportion", "ranked_signal_view"], "default_facet_ids": ["pairwise_conditional_dependency", "conditional_rate_shift"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_conditional_group_quantiles", "template_name": "Conditional Group Quantiles", "source_workload_id": "clickhouse_aggregate_docs", "primary_family": "conditional_dependency_structure", "secondary_family": "tail_rarity_structure", "intent": "Report subgroup percentile points only for rows satisfying a low-cardinality condition.", "sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col})\n FILTER (WHERE {condition_col} = {condition_value}) AS conditional_percentile\nFROM {table}\nGROUP BY {group_col}\nORDER BY conditional_percentile DESC;", "required_roles": ["group_col", "measure_col", "condition_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "condition_col:binary_or_low_cardinality_preferred", "single_table_only"], "single_table_portable": "yes", "provenance": {"url": "https://clickhouse.com/docs/examples/aggregate-function-combinators/quantilesTimingIf", "title": "quantilesTimingIf | ClickHouse Docs", "source_query_id": "ClickHouse quantilesTimingIf example"}, "provenance_sources": [{"url": "https://clickhouse.com/docs/examples/aggregate-function-combinators/quantilesTimingIf", "title": "quantilesTimingIf | ClickHouse Docs", "source_query_id": "ClickHouse quantilesTimingIf example"}], "status": "ready", "notes": "Kept optional because it is highly valuable for observability-style tails but more dialect-sensitive than the rest of the core library.", "materialization_bucket": "core", "activation_tier": "optional", "dialect_sensitive": true, "dialect_notes": "Uses percentile syntax plus conditional aggregation/filter semantics. Keep it optional unless the downstream engine supports ordered-set percentiles and FILTER/If-style conditioning.", "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col", "condition_col"], "supported_canonical_subitem_ids": ["slice_level_consistency", "direction_consistency"], "allowed_variant_roles": ["focused_target_view", "filtered_stable_view"], "default_facet_ids": ["conditional_interaction_hotspots", "conditional_rate_shift"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_binned_numeric_group_avg", "template_name": "Binned Numeric Group Average", "source_workload_id": "insurance_sql_analysis_repo", "primary_family": "conditional_dependency_structure", "secondary_family": "subgroup_structure", "intent": "Bin a numeric feature into coarse buckets and compare average outcomes across those bins.", "sql_skeleton": "SELECT CASE\n WHEN {band_col} < {band_cut_1} THEN 'low'\n WHEN {band_col} < {band_cut_2} THEN 'mid'\n ELSE 'high'\n END AS band_bucket,\n AVG({measure_col}) AS avg_measure\nFROM {table}\nGROUP BY band_bucket\nORDER BY avg_measure DESC;", "required_roles": ["band_col", "measure_col"], "optional_roles": [], "constraints": ["band_col:ordered_or_numeric", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/Shagufta-DataAnalyst/insurance-sql-analysis/blob/main/Analysis_queries.sql", "title": "Analysis_queries.sql · insurance-sql-analysis", "source_query_id": "m4_sql_0044"}, "provenance_sources": [{"url": "https://github.com/Shagufta-DataAnalyst/insurance-sql-analysis/blob/main/Analysis_queries.sql", "title": "Analysis_queries.sql · insurance-sql-analysis", "source_query_id": "m4_sql_0044"}], "status": "ready", "notes": "Important for numeric-heavy datasets where raw continuous features must be discretized before subgroup reasoning.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["band_col", "measure_col"], "supported_canonical_subitem_ids": ["slice_level_consistency"], "allowed_variant_roles": ["collapsed_target_view", "filtered_stable_view"], "default_facet_ids": ["conditional_interaction_hotspots"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_group_condition_rate", "template_name": "Grouped Condition Rate", "source_workload_id": "insurance_cost_project_sql_repo", "primary_family": "conditional_dependency_structure", "secondary_family": "subgroup_structure", "intent": "Estimate the proportion of rows meeting a low-cardinality condition within each subgroup.", "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", "required_roles": ["group_col", "condition_col"], "optional_roles": [], "constraints": ["group_col:groupable", "condition_col:binary_or_low_cardinality_preferred", "single_table_only"], "single_table_portable": "yes", "provenance": {"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0016"}, "provenance_sources": [{"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0016"}], "status": "ready", "notes": "Strong analytics template for subgroup-conditional proportions with broad portability.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["group_col", "condition_col"], "supported_canonical_subitem_ids": ["dependency_strength_similarity", "direction_consistency"], "allowed_variant_roles": ["within_group_proportion", "focused_target_view"], "default_facet_ids": ["pairwise_conditional_dependency", "conditional_rate_shift"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_group_dispersion_rank", "template_name": "Grouped Dispersion Rank", "source_workload_id": "insurance_cost_project_sql_repo", "primary_family": "conditional_dependency_structure", "secondary_family": "tail_rarity_structure", "intent": "Rank subgroups by within-group dispersion of a numeric measure.", "sql_skeleton": "SELECT {group_col}, STDDEV({measure_col}) AS measure_stddev\nFROM {table}\nGROUP BY {group_col}\nORDER BY measure_stddev DESC\nLIMIT {top_k};", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0031"}, "provenance_sources": [{"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0031"}], "status": "ready", "notes": "Expands beyond mean-only summaries into spread-sensitive analytics.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["dependency_strength_similarity"], "allowed_variant_roles": ["ranked_signal_view", "focused_target_view"], "default_facet_ids": ["pairwise_conditional_dependency"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_group_ratio_two_conditions", "template_name": "Grouped Ratio of Two Conditions", "source_workload_id": "insurance_cost_project_sql_repo", "primary_family": "conditional_dependency_structure", "secondary_family": "subgroup_structure", "intent": "Contrast two condition counts within each subgroup as a ratio.", "sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "required_roles": ["group_col", "condition_col"], "optional_roles": [], "constraints": ["group_col:groupable", "condition_col:binary_or_low_cardinality_preferred", "single_table_only"], "single_table_portable": "yes", "provenance": {"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0026"}, "provenance_sources": [{"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0026"}], "status": "ready", "notes": "Captures a common dashboard KPI style rather than a benchmark-only artifact.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["group_col", "condition_col"], "supported_canonical_subitem_ids": ["direction_consistency"], "allowed_variant_roles": ["contrastive_conditional_view"], "default_facet_ids": ["conditional_rate_shift"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_median_filtered_numeric", "template_name": "Filtered Median Numeric Slice", "source_workload_id": "insurance_cost_project_sql_repo", "primary_family": "conditional_dependency_structure", "secondary_family": "tail_rarity_structure", "intent": "Compute a median-like robust center for a filtered numeric slice.", "sql_skeleton": "WITH ranked AS (\n SELECT {measure_col},\n ROW_NUMBER() OVER (ORDER BY {measure_col}) AS row_num,\n COUNT(*) OVER () AS total_rows\n FROM {table}\n WHERE {predicate_col} {predicate_op} {predicate_value}\n)\nSELECT AVG({measure_col}) AS median_measure\nFROM ranked\nWHERE row_num BETWEEN (total_rows + 1) / 2 AND (total_rows + 2) / 2;", "required_roles": ["measure_col", "predicate_col"], "optional_roles": [], "constraints": ["measure_col:numeric", "predicate_col:filterable", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0022"}, "provenance_sources": [{"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0022"}], "status": "ready", "notes": "Retained because robust-statistic templates are common in practical analytical workflows even if they are not universal.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["measure_col", "predicate_col"], "supported_canonical_subitem_ids": ["slice_level_consistency"], "allowed_variant_roles": ["focused_target_view", "filtered_stable_view"], "default_facet_ids": ["conditional_interaction_hotspots"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_window_partition_avg", "template_name": "Window Partition Average", "source_workload_id": "insurance_cost_project_sql_repo", "primary_family": "conditional_dependency_structure", "secondary_family": "subgroup_structure", "intent": "Use a window function to report per-group averages without collapsing the row-level relation first.", "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0011"}, "provenance_sources": [{"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0011"}], "status": "ready", "notes": "Adds explicit window-function coverage to the analytics library.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["slice_level_consistency", "direction_consistency"], "allowed_variant_roles": ["filtered_stable_view", "ranked_signal_view"], "default_facet_ids": ["conditional_interaction_hotspots", "conditional_rate_shift"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_rtabench_time_bucket_filtered_count", "template_name": "Time-Bucket Filtered Count", "source_workload_id": "rtabench_order_events", "primary_family": "conditional_dependency_structure", "secondary_family": "subgroup_structure", "intent": "Count events per time bucket within a filtered slice.", "sql_skeleton": "SELECT DATE_TRUNC('{time_grain}', {time_col}) AS time_bucket,\n COUNT(*) AS event_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY time_bucket\nORDER BY time_bucket;", "required_roles": ["time_col", "predicate_col"], "optional_roles": [], "constraints": ["time_col:temporal", "predicate_col:filterable", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/timescale/rtabench/main/postgres/queries/0004_count_delayed_orders_per_day.sql", "title": "postgres/queries/0004_count_delayed_orders_per_day.sql · RTABench", "source_query_id": "RTABench 0004"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/timescale/rtabench/main/postgres/queries/0004_count_delayed_orders_per_day.sql", "title": "postgres/queries/0004_count_delayed_orders_per_day.sql · RTABench", "source_query_id": "RTABench 0004"}], "status": "ready", "notes": "Added as a restrained time-aware extension because time-bucket event counts are one of the most universal temporal dashboard queries.", "materialization_bucket": "extension", "activation_tier": "extension", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["time_col", "predicate_col"], "supported_canonical_subitem_ids": ["slice_level_consistency"], "allowed_variant_roles": ["filtered_stable_view", "count_distribution"], "default_facet_ids": ["conditional_interaction_hotspots"], "gate_priority": "support", "source_catalog": "template_library_extensions_v1", "extended_family": false} | |
| {"template_id": "tpl_rtabench_time_bucket_group_moving_avg", "template_name": "Time-Bucket Group Moving Average", "source_workload_id": "rtabench_order_events", "primary_family": "conditional_dependency_structure", "secondary_family": "tail_rarity_structure", "intent": "Compute a rolling moving average over time-bucketed subgroup counts.", "sql_skeleton": "WITH bucketed AS (\n SELECT DATE_TRUNC('{time_grain}', {time_col}) AS time_bucket,\n {group_col},\n COUNT(*) AS event_count\n FROM {table}\n WHERE {predicate_col} {predicate_op} {predicate_value}\n GROUP BY time_bucket, {group_col}\n)\nSELECT time_bucket,\n {group_col},\n event_count,\n AVG(event_count) OVER (\n PARTITION BY {group_col}\n ORDER BY time_bucket\n ROWS BETWEEN {lookback_rows} PRECEDING AND CURRENT ROW\n ) AS moving_avg_count\nFROM bucketed\nORDER BY {group_col}, time_bucket;", "required_roles": ["time_col", "group_col", "predicate_col"], "optional_roles": [], "constraints": ["time_col:temporal", "group_col:groupable", "predicate_col:filterable", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/timescale/rtabench/main/postgres/queries/0000_terminal_hourly_stats.sql", "title": "postgres/queries/0000_terminal_hourly_stats.sql · RTABench", "source_query_id": "RTABench 0000"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/timescale/rtabench/main/postgres/queries/0000_terminal_hourly_stats.sql", "title": "postgres/queries/0000_terminal_hourly_stats.sql · RTABench", "source_query_id": "RTABench 0000"}], "status": "ready", "notes": "Represents a common dashboard smoothing pattern while staying within a single-table event log structure.", "materialization_bucket": "extension", "activation_tier": "extension", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["time_col", "group_col", "predicate_col"], "supported_canonical_subitem_ids": ["slice_level_consistency", "direction_consistency"], "allowed_variant_roles": ["filtered_stable_view", "ranked_signal_view"], "default_facet_ids": ["conditional_interaction_hotspots", "conditional_rate_shift"], "gate_priority": "support", "source_catalog": "template_library_extensions_v1", "extended_family": false} | |
| {"template_id": "tpl_tail_drift_ratio", "template_name": "Tail Drift Ratio", "source_workload_id": "tpcds_altinity_queries", "primary_family": "conditional_dependency_structure", "secondary_family": "tail_rarity_structure", "intent": "Compare current-period to prior-period subgroup volume and flag material negative drift.", "sql_skeleton": "WITH period_counts AS (\n SELECT {group_col},\n SUM(CASE WHEN {time_col} >= {current_period_start} AND {time_col} < {current_period_end} THEN 1 ELSE 0 END) AS current_count,\n SUM(CASE WHEN {time_col} >= {previous_period_start} AND {time_col} < {previous_period_end} THEN 1 ELSE 0 END) AS previous_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col}, current_count, previous_count,\n CAST(current_count AS FLOAT) / NULLIF(previous_count, 0) AS drift_ratio\nFROM period_counts\nWHERE CAST(current_count AS FLOAT) / NULLIF(previous_count, 0) < {drift_ratio_threshold}\nORDER BY drift_ratio ASC;", "required_roles": ["group_col", "time_col"], "optional_roles": [], "constraints": ["group_col:groupable", "time_col:temporal", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/Altinity/tpc-ds/blob/master/queries/query_75.sql", "title": "query_75.sql · Altinity/tpc-ds", "source_query_id": "TPC-DS Q75"}, "provenance_sources": [{"url": "https://github.com/Altinity/tpc-ds/blob/master/queries/query_75.sql", "title": "query_75.sql · Altinity/tpc-ds", "source_query_id": "TPC-DS Q75"}], "status": "ready", "notes": "Explicitly kept in the extension bucket because most current benchmark datasets lack real temporal semantics.", "materialization_bucket": "extension", "activation_tier": "extension", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["group_col", "time_col"], "supported_canonical_subitem_ids": ["direction_consistency"], "allowed_variant_roles": ["contrastive_conditional_view", "ranked_signal_view"], "default_facet_ids": ["conditional_rate_shift"], "gate_priority": "review", "source_catalog": "template_library_extensions_v1", "extended_family": false} | |
| {"template_id": "tpl_tpcds_baseline_gated_extreme_ranking", "template_name": "Baseline-Gated Extreme Ranking", "source_workload_id": "tpcds_altinity_queries", "primary_family": "conditional_dependency_structure", "secondary_family": "tail_rarity_structure", "intent": "Apply a subgroup baseline gate before ranking entities by an extreme aggregate outcome.", "sql_skeleton": "WITH item_stats AS (\n SELECT {group_col}, {item_col}, AVG({measure_col}) AS avg_measure\n FROM {table}\n GROUP BY {group_col}, {item_col}\n), group_baseline AS (\n SELECT {group_col}, AVG(avg_measure) AS group_avg\n FROM item_stats\n GROUP BY {group_col}\n), eligible AS (\n SELECT i.{group_col}, i.{item_col}, i.avg_measure\n FROM item_stats AS i\n JOIN group_baseline AS g\n ON i.{group_col} = g.{group_col}\n WHERE i.avg_measure > g.group_avg * {baseline_fraction}\n)\nSELECT {group_col}, {item_col}, avg_measure,\n RANK() OVER (PARTITION BY {group_col} ORDER BY avg_measure DESC) AS within_group_rank\nFROM eligible\nORDER BY avg_measure DESC\nLIMIT {top_k};", "required_roles": ["group_col", "item_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "item_col:groupable_or_high_cardinality", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/Altinity/tpc-ds/blob/master/queries/query_44.sql", "title": "query_44.sql · Altinity/tpc-ds", "source_query_id": "TPC-DS Q44"}, "provenance_sources": [{"url": "https://github.com/Altinity/tpc-ds/blob/master/queries/query_44.sql", "title": "query_44.sql · Altinity/tpc-ds", "source_query_id": "TPC-DS Q44"}], "status": "ready", "notes": "Distinct from plain top-k because the ranking only happens after a relative baseline gate is cleared.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["group_col", "item_col", "measure_col"], "supported_canonical_subitem_ids": ["dependency_strength_similarity"], "allowed_variant_roles": ["ranked_signal_view", "focused_target_view"], "default_facet_ids": ["pairwise_conditional_dependency"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_tpcds_within_group_share", "template_name": "Within-Group Share of Total", "source_workload_id": "tpcds_qualification", "primary_family": "conditional_dependency_structure", "secondary_family": "subgroup_structure", "intent": "Measure each item's contribution within a parent subgroup using a windowed share-of-total.", "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", "required_roles": ["group_col", "item_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "item_col:groupable_or_high_cardinality", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/cwida/tpcds-result-reproduction/master/query_qualification/98.sql", "title": "query_qualification/98.sql · tpcds-result-reproduction", "source_query_id": "TPC-DS Q98"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/cwida/tpcds-result-reproduction/master/query_qualification/98.sql", "title": "query_qualification/98.sql · tpcds-result-reproduction", "source_query_id": "TPC-DS Q98"}], "status": "ready", "notes": "One of the strongest workload-grounded window templates retained in v1.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["group_col", "item_col", "measure_col"], "supported_canonical_subitem_ids": ["dependency_strength_similarity"], "allowed_variant_roles": ["within_group_proportion", "focused_target_view"], "default_facet_ids": ["pairwise_conditional_dependency"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_tpch_filtered_sum_band", "template_name": "Filtered Sum in Numeric Band", "source_workload_id": "tpch_qgen", "primary_family": "conditional_dependency_structure", "secondary_family": "tail_rarity_structure", "intent": "Aggregate a numeric measure within a numeric band filter.", "sql_skeleton": "SELECT SUM({measure_col}) AS total_measure\nFROM {table}\nWHERE {band_col} BETWEEN {lower_bound} AND {upper_bound};", "required_roles": ["measure_col", "band_col"], "optional_roles": [], "constraints": ["measure_col:numeric", "band_col:ordered_or_numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/electrum/tpch-dbgen/master/queries/6.sql", "title": "queries/6.sql · tpch-dbgen", "source_query_id": "TPC-H Q6"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/electrum/tpch-dbgen/master/queries/6.sql", "title": "queries/6.sql · tpch-dbgen", "source_query_id": "TPC-H Q6"}], "status": "ready", "notes": "Promoted into the materialized core because the tail review showed this narrow-band threshold slice is a canonical low-support but high-impact pattern rather than a benchmark curiosity.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "conditional_dependency_structure", "realization_mode": "agent", "binding_roles": ["measure_col", "band_col"], "supported_canonical_subitem_ids": ["slice_level_consistency"], "allowed_variant_roles": ["filtered_stable_view", "collapsed_target_view"], "default_facet_ids": ["conditional_interaction_hotspots"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_missing_marginal_rate_profile", "template_name": "Marginal Missing Rate Profile", "source_workload_id": "subitem_workload_v2", "primary_family": "missingness_structure", "secondary_family": null, "intent": "New deterministic template for v2.", "sql_skeleton": "SELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table};", "required_roles": ["missing_col"], "optional_roles": [], "constraints": ["single_table_only", "v2_deterministic_template"], "single_table_portable": "yes", "provenance": {"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_missing_marginal_rate_profile"}, "provenance_sources": [{"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_missing_marginal_rate_profile"}], "status": "ready", "notes": "New deterministic template for v2.", "materialization_bucket": "v2_deterministic", "activation_tier": "v2", "dialect_sensitive": false, "family_id": "missingness_structure", "realization_mode": "deterministic", "binding_roles": ["missing_col"], "supported_canonical_subitem_ids": ["marginal_missing_rate_consistency"], "allowed_variant_roles": ["missing_indicator_view"], "default_facet_ids": ["missing_indicator_distribution"], "gate_priority": "deterministic", "source_catalog": "template_library_v2", "extended_family": false} | |
| {"template_id": "tpl_missing_rate_by_subgroup", "template_name": "Missing Rate by Subgroup", "source_workload_id": "subitem_workload_v2", "primary_family": "missingness_structure", "secondary_family": null, "intent": "New deterministic template for v2.", "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY missing_rate DESC, total_rows DESC;", "required_roles": ["missing_col", "group_col"], "optional_roles": [], "constraints": ["single_table_only", "v2_deterministic_template"], "single_table_portable": "yes", "provenance": {"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_missing_rate_by_subgroup"}, "provenance_sources": [{"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_missing_rate_by_subgroup"}], "status": "ready", "notes": "New deterministic template for v2.", "materialization_bucket": "v2_deterministic", "activation_tier": "v2", "dialect_sensitive": false, "family_id": "missingness_structure", "realization_mode": "deterministic", "binding_roles": ["missing_col", "group_col"], "supported_canonical_subitem_ids": ["co_missingness_pattern_consistency"], "allowed_variant_roles": ["missing_rate_by_subgroup"], "default_facet_ids": ["missing_rate_by_subgroup", "missing_target_interaction"], "gate_priority": "deterministic", "source_catalog": "template_library_v2", "extended_family": false} | |
| {"template_id": "tpl_missing_target_interaction", "template_name": "Missingness-Target Interaction", "source_workload_id": "subitem_workload_v2", "primary_family": "missingness_structure", "secondary_family": null, "intent": "New deterministic template for v2.", "sql_skeleton": "SELECT\n {target_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {target_col}\nORDER BY missing_rate DESC, total_rows DESC;", "required_roles": ["missing_col", "target_col"], "optional_roles": [], "constraints": ["single_table_only", "v2_deterministic_template"], "single_table_portable": "yes", "provenance": {"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_missing_target_interaction"}, "provenance_sources": [{"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_missing_target_interaction"}], "status": "ready", "notes": "New deterministic template for v2.", "materialization_bucket": "v2_deterministic", "activation_tier": "v2", "dialect_sensitive": false, "family_id": "missingness_structure", "realization_mode": "deterministic", "binding_roles": ["missing_col", "target_col"], "supported_canonical_subitem_ids": ["co_missingness_pattern_consistency"], "allowed_variant_roles": ["missing_target_interaction"], "default_facet_ids": ["missing_rate_by_subgroup", "missing_target_interaction"], "gate_priority": "deterministic", "source_catalog": "template_library_v2", "extended_family": false} | |
| {"template_id": "tpl_clickbench_filtered_distinct_topk", "template_name": "Filtered Top-k Distinct Coverage", "source_workload_id": "clickbench_hits", "primary_family": "subgroup_structure", "secondary_family": "conditional_dependency_structure", "intent": "Rank subgroups by distinct-entity coverage within a filtered slice.", "sql_skeleton": "SELECT {group_col}, COUNT(DISTINCT {entity_col}) AS distinct_entities\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}\nORDER BY distinct_entities DESC\nLIMIT {top_k};", "required_roles": ["group_col", "entity_col", "predicate_col"], "optional_roles": [], "constraints": ["group_col:groupable", "entity_col:high_cardinality_preferred", "predicate_col:filterable", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q14"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q14"}], "status": "ready", "notes": "A broadly useful dashboard pattern that combines slicing with distinct-user style coverage ranking.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "entity_col", "predicate_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["filtered_stable_view", "ranked_signal_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_clickbench_filtered_topk_group_count", "template_name": "Filtered Top-k Group Count", "source_workload_id": "clickbench_hits", "primary_family": "subgroup_structure", "secondary_family": "conditional_dependency_structure", "intent": "Rank subgroups by support within a filtered slice.", "sql_skeleton": "SELECT {group_col}, COUNT(*) AS support\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}\nORDER BY support DESC\nLIMIT {top_k};", "required_roles": ["group_col", "predicate_col"], "optional_roles": [], "constraints": ["group_col:groupable", "predicate_col:filterable", "single_table_only"], "single_table_portable": "yes", "provenance": {"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q13"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q13"}], "status": "ready", "notes": "A cleaner heavy-hitter slice than the existing two-dimensional filtered count template.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "predicate_col"], "supported_canonical_subitem_ids": ["subgroup_size_stability"], "allowed_variant_roles": ["count_distribution", "filtered_stable_view"], "default_facet_ids": ["subgroup_distribution_shift"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_clickbench_group_count", "template_name": "Grouped Count by Category", "source_workload_id": "clickbench_hits", "primary_family": "subgroup_structure", "secondary_family": null, "intent": "Count rows by a single subgroup dimension to capture baseline subgroup mass.", "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", "required_roles": ["group_col"], "optional_roles": [], "constraints": ["group_col:groupable", "single_table_only"], "single_table_portable": "yes", "provenance": {"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q08"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q08"}], "status": "ready", "notes": "Closest to dashboard-style subgroup mass queries; deliberately keeps only one group axis for broad portability.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col"], "supported_canonical_subitem_ids": ["subgroup_size_stability"], "allowed_variant_roles": ["count_distribution"], "default_facet_ids": ["subgroup_distribution_shift"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_clickbench_group_distinct_topk", "template_name": "Top-k Groups by Distinct Entity Coverage", "source_workload_id": "clickbench_hits", "primary_family": "subgroup_structure", "secondary_family": "tail_rarity_structure", "intent": "Find the top subgroups by distinct-entity coverage.", "sql_skeleton": "SELECT {group_col}, COUNT(DISTINCT {entity_col}) AS distinct_entities\nFROM {table}\nGROUP BY {group_col}\nORDER BY distinct_entities DESC\nLIMIT {top_k};", "required_roles": ["group_col", "entity_col"], "optional_roles": [], "constraints": ["group_col:groupable", "entity_col:high_cardinality_preferred", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q09"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q09"}], "status": "ready", "notes": "Good proxy for coverage/richness queries seen in web analytics workloads.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "entity_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["ranked_signal_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_clickbench_group_summary_topk", "template_name": "Grouped Summary Top-k", "source_workload_id": "clickbench_hits", "primary_family": "subgroup_structure", "secondary_family": "conditional_dependency_structure", "intent": "Rank subgroups by support while also reporting a numeric mean and distinct-entity coverage.", "sql_skeleton": "SELECT {group_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_measure,\n COUNT(DISTINCT {entity_col}) AS distinct_entities\nFROM {table}\nGROUP BY {group_col}\nORDER BY support DESC\nLIMIT {top_k};", "required_roles": ["group_col", "measure_col", "entity_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "entity_col:high_cardinality_preferred", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q10"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q10"}], "status": "ready", "notes": "Retains the multi-metric dashboard feel of ClickBench without overfitting to web-log column names.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col", "entity_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["ranked_signal_view", "collapsed_target_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_clickbench_two_dimensional_topk_count", "template_name": "Two-Dimensional Top-k Count", "source_workload_id": "clickbench_hits", "primary_family": "subgroup_structure", "secondary_family": "tail_rarity_structure", "intent": "Find the heaviest two-dimensional subgroup combinations by row count.", "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}, {group_col_2}\nORDER BY support DESC\nLIMIT {top_k};", "required_roles": ["group_col", "group_col_2"], "optional_roles": [], "constraints": ["group_col:groupable", "group_col_2:groupable_distinct_from_group_col", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q31"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/ClickHouse/ClickBench/main/clickhouse/queries.sql", "title": "clickhouse/queries.sql · ClickBench", "source_query_id": "ClickBench Q31"}], "status": "ready", "notes": "Useful for interaction-heavy dashboards and joint heavy-hitter analysis.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "group_col_2"], "supported_canonical_subitem_ids": ["subgroup_size_stability"], "allowed_variant_roles": ["count_distribution"], "default_facet_ids": ["subgroup_distribution_shift"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_h2o_group_sum", "template_name": "Grouped Numeric Sum", "source_workload_id": "h2o_db_benchmark", "primary_family": "subgroup_structure", "secondary_family": null, "intent": "Compare total numeric mass across subgroups using a simple grouped sum.", "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/h2oai/db-benchmark/master/duckdb/groupby-duckdb.R", "title": "duckdb/groupby-duckdb.R · h2oai/db-benchmark", "source_query_id": "H2O groupby q1"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/h2oai/db-benchmark/master/duckdb/groupby-duckdb.R", "title": "duckdb/groupby-duckdb.R · h2oai/db-benchmark", "source_query_id": "H2O groupby q1"}], "status": "ready", "notes": "Selected because plain grouped sums are missing from the current library yet are among the most universal single-table analytics queries.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["collapsed_target_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_h2o_two_dimensional_group_sum", "template_name": "Two-Dimensional Group Sum", "source_workload_id": "h2o_db_benchmark", "primary_family": "subgroup_structure", "secondary_family": null, "intent": "Compare total numeric mass across a two-way subgroup grid.", "sql_skeleton": "SELECT {group_col}, {group_col_2}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}, {group_col_2}\nORDER BY total_measure DESC;", "required_roles": ["group_col", "group_col_2", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "group_col_2:groupable_distinct_from_group_col", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/h2oai/db-benchmark/master/duckdb/groupby-duckdb.R", "title": "duckdb/groupby-duckdb.R · h2oai/db-benchmark", "source_query_id": "H2O groupby q2"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/h2oai/db-benchmark/master/duckdb/groupby-duckdb.R", "title": "duckdb/groupby-duckdb.R · h2oai/db-benchmark", "source_query_id": "H2O groupby q2"}], "status": "ready", "notes": "Complements the existing two-dimensional count and average templates with the equally common summed-mass view.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "group_col_2", "measure_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["collapsed_target_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_h2o_two_dimensional_robust_summary", "template_name": "Two-Dimensional Robust Summary", "source_workload_id": "h2o_db_benchmark", "primary_family": "subgroup_structure", "secondary_family": "tail_rarity_structure", "intent": "Compare robust center and spread of a numeric measure across a two-way subgroup grid.", "sql_skeleton": "SELECT {group_col}, {group_col_2},\n PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY {measure_col}) AS median_measure,\n STDDEV({measure_col}) AS measure_stddev\nFROM {table}\nGROUP BY {group_col}, {group_col_2}\nORDER BY median_measure DESC;", "required_roles": ["group_col", "group_col_2", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "group_col_2:groupable_distinct_from_group_col", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/h2oai/db-benchmark/master/duckdb/groupby-duckdb.R", "title": "duckdb/groupby-duckdb.R · h2oai/db-benchmark", "source_query_id": "H2O groupby q6"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/h2oai/db-benchmark/master/duckdb/groupby-duckdb.R", "title": "duckdb/groupby-duckdb.R · h2oai/db-benchmark", "source_query_id": "H2O groupby q6"}], "status": "ready", "notes": "Kept in the core registry as an optional analytics template. It is dialect-sensitive because ordered-set percentile support varies across SQL engines.", "materialization_bucket": "core", "activation_tier": "optional", "dialect_sensitive": true, "dialect_notes": "Uses ordered-set percentile and standard-deviation aggregates. Keep it optional unless the downstream SQL engine supports PERCENTILE_CONT/QUANTILE_CONT-style syntax.", "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "group_col_2", "measure_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["collapsed_target_view", "filtered_stable_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_group_avg_numeric", "template_name": "Grouped Numeric Mean", "source_workload_id": "insurance_cost_project_sql_repo", "primary_family": "subgroup_structure", "secondary_family": null, "intent": "Compare mean numeric outcomes across subgroups.", "sql_skeleton": "SELECT {group_col}, AVG({measure_col}) AS avg_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY avg_measure DESC;", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0012"}, "provenance_sources": [{"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0012"}], "status": "ready", "notes": "One of the most reusable regression-style templates among the public insurance SQL repository exemplars.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["collapsed_target_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_support_guarded_group_avg", "template_name": "Support-Guarded Group Average", "source_workload_id": "insurance_cost_project_sql_repo", "primary_family": "subgroup_structure", "secondary_family": "tail_rarity_structure", "intent": "Compute subgroup averages only when support exceeds a configurable minimum.", "sql_skeleton": "SELECT {group_col}, AVG({measure_col}) AS avg_measure, COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nHAVING COUNT(*) > {min_group_size}\nORDER BY {group_col};", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "support_guard:minimum_group_size", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0025"}, "provenance_sources": [{"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0025"}], "status": "ready", "notes": "Reclassified as analytics because the support guard is part of the query semantics rather than an external evaluation rule.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["collapsed_target_view", "filtered_stable_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_two_dimensional_group_avg", "template_name": "Two-Dimensional Group Average", "source_workload_id": "insurance_sql_analysis_repo", "primary_family": "subgroup_structure", "secondary_family": "conditional_dependency_structure", "intent": "Compare average numeric outcomes across a two-way subgroup grid.", "sql_skeleton": "SELECT {group_col}, {group_col_2}, AVG({measure_col}) AS avg_measure\nFROM {table}\nGROUP BY {group_col}, {group_col_2}\nORDER BY avg_measure DESC;", "required_roles": ["group_col", "group_col_2", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "group_col_2:groupable_distinct_from_group_col", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/Shagufta-DataAnalyst/insurance-sql-analysis/blob/main/Analysis_queries.sql", "title": "Analysis_queries.sql · insurance-sql-analysis", "source_query_id": "m4_sql_0046"}, "provenance_sources": [{"url": "https://github.com/Shagufta-DataAnalyst/insurance-sql-analysis/blob/main/Analysis_queries.sql", "title": "Analysis_queries.sql · insurance-sql-analysis", "source_query_id": "m4_sql_0046"}], "status": "ready", "notes": "Clean public-repo analogue of pairwise interaction reporting.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "group_col_2", "measure_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["collapsed_target_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_tail_weighted_topk_sum", "template_name": "Weighted Top-k Sum", "source_workload_id": "bigquery_approx_aggregate_docs", "primary_family": "subgroup_structure", "secondary_family": "tail_rarity_structure", "intent": "Rank groups by weighted aggregate mass while preserving both support and weighted total.", "sql_skeleton": "SELECT {group_col},\n SUM({measure_col}) AS weighted_total,\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY weighted_total DESC\nLIMIT {top_k};", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "support_guard:minimum_group_size", "single_table_only"], "single_table_portable": "yes", "provenance": {"url": "https://cloud.google.com/bigquery/docs/reference/standard-sql/approximate_aggregate_functions", "title": "Approximate aggregate functions | BigQuery | Google Cloud Documentation", "source_query_id": "BigQuery APPROX_TOP_SUM example"}, "provenance_sources": [{"url": "https://cloud.google.com/bigquery/docs/reference/standard-sql/approximate_aggregate_functions", "title": "Approximate aggregate functions | BigQuery | Google Cloud Documentation", "source_query_id": "BigQuery APPROX_TOP_SUM example"}, {"url": "https://clickhouse.com/docs/sql-reference/aggregate-functions/reference/approxtopsum", "title": "approx_top_sum | ClickHouse Docs", "source_query_id": "ClickHouse approx_top_sum example"}], "status": "ready", "notes": "Materialized as a canonical family rather than an engine-specific function variant, with BigQuery and ClickHouse as independent public evidence sources.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["ranked_signal_view", "filtered_stable_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "review", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_tpcds_topk_group_sum", "template_name": "Top-k Group Sum with Filter", "source_workload_id": "tpcds_qualification", "primary_family": "subgroup_structure", "secondary_family": "conditional_dependency_structure", "intent": "Rank subgroups by total numeric measure under a filter.", "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}\nORDER BY total_measure DESC\nLIMIT {top_k};", "required_roles": ["group_col", "measure_col", "predicate_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "predicate_col:filterable", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/cwida/tpcds-result-reproduction/master/query_qualification/03.sql", "title": "query_qualification/03.sql · tpcds-result-reproduction", "source_query_id": "TPC-DS Q3"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/cwida/tpcds-result-reproduction/master/query_qualification/03.sql", "title": "query_qualification/03.sql · tpcds-result-reproduction", "source_query_id": "TPC-DS Q3"}], "status": "ready", "notes": "A pragmatic single-table reduction of a common sales-ranking pattern.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col", "predicate_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["ranked_signal_view", "filtered_stable_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_tpch_max_aggregate_winner", "template_name": "Max Aggregate Winner Selection", "source_workload_id": "tpch_qgen", "primary_family": "subgroup_structure", "secondary_family": "tail_rarity_structure", "intent": "Aggregate by group and keep only the winner whose aggregate value is maximal.", "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS total_measure\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col}, total_measure\nFROM grouped\nWHERE total_measure = (SELECT MAX(total_measure) FROM grouped)\nORDER BY {group_col};", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/electrum/tpch-dbgen/master/queries/15.sql", "title": "queries/15.sql · electrum/tpch-dbgen", "source_query_id": "TPC-H Q15"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/electrum/tpch-dbgen/master/queries/15.sql", "title": "queries/15.sql · electrum/tpch-dbgen", "source_query_id": "TPC-H Q15"}], "status": "ready", "notes": "Distinct from ordinary top-k because it encodes winner-only selection after grouped aggregation.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["focused_target_view", "ranked_signal_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_tpch_two_dimensional_summary", "template_name": "Two-Dimensional Summary with Filter", "source_workload_id": "tpch_qgen", "primary_family": "subgroup_structure", "secondary_family": "conditional_dependency_structure", "intent": "Summarize a numeric measure across two grouping axes with an additional filter.", "sql_skeleton": "SELECT {group_col}, {group_col_2},\n SUM({measure_col}) AS sum_measure,\n AVG({measure_col}) AS avg_measure,\n COUNT(*) AS support\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY {group_col}, {group_col_2};", "required_roles": ["group_col", "group_col_2", "measure_col", "predicate_col"], "optional_roles": [], "constraints": ["group_col:groupable", "group_col_2:groupable_distinct_from_group_col", "measure_col:numeric", "predicate_col:ordered_or_numeric_preferred", "single_table_only"], "single_table_portable": "yes", "provenance": {"url": "https://raw.githubusercontent.com/electrum/tpch-dbgen/master/queries/1.sql", "title": "queries/1.sql · tpch-dbgen", "source_query_id": "TPC-H Q1"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/electrum/tpch-dbgen/master/queries/1.sql", "title": "queries/1.sql · tpch-dbgen", "source_query_id": "TPC-H Q1"}], "status": "ready", "notes": "Join-free abstraction of a classic TPC-H summary report pattern.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "subgroup_structure", "realization_mode": "agent", "binding_roles": ["group_col", "group_col_2", "measure_col", "predicate_col"], "supported_canonical_subitem_ids": ["internal_profile_stability"], "allowed_variant_roles": ["collapsed_target_view", "filtered_stable_view"], "default_facet_ids": ["subgroup_rank_order", "subgroup_distribution_shift", "subgroup_conditional_contrast"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_grouped_percentile_point", "template_name": "Grouped Percentile Point", "source_workload_id": "bigquery_approx_aggregate_docs", "primary_family": "tail_rarity_structure", "secondary_family": "subgroup_structure", "intent": "Report a percentile point such as p95 or p99 for each subgroup instead of returning the raw tail rows.", "sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "single_table_only"], "single_table_portable": "yes", "provenance": {"url": "https://cloud.google.com/bigquery/docs/reference/standard-sql/approximate_aggregate_functions", "title": "Approximate aggregate functions | BigQuery | Google Cloud Documentation", "source_query_id": "BigQuery APPROX_QUANTILES example"}, "provenance_sources": [{"url": "https://cloud.google.com/bigquery/docs/reference/standard-sql/approximate_aggregate_functions", "title": "Approximate aggregate functions | BigQuery | Google Cloud Documentation", "source_query_id": "BigQuery APPROX_QUANTILES example"}, {"url": "https://trino.io/docs/current/functions/aggregate.html", "title": "Aggregate functions — Trino Documentation", "source_query_id": "Trino approx_percentile"}, {"url": "https://docs.snowflake.com/en/sql-reference/functions/percentile_cont", "title": "PERCENTILE_CONT | Snowflake Documentation", "source_query_id": "Snowflake PERCENTILE_CONT grouped example"}, {"url": "https://clickhouse.com/docs/sql-reference/aggregate-functions/reference/quantile", "title": "quantile | ClickHouse Docs", "source_query_id": "ClickHouse quantile example"}, {"url": "https://druid.apache.org/docs/latest/querying/sql-functions/", "title": "All Druid SQL functions | Apache Druid", "source_query_id": "Druid APPROX_QUANTILE_DS example"}, {"url": "https://docs.pinot.apache.org/functions/aggregation/percentile", "title": "percentile | Apache Pinot Docs", "source_query_id": "Pinot percentile example"}], "status": "ready", "notes": "Canonical percentile-point family added so the library can represent p95/p99 style tail monitoring without returning full quantile slices.", "materialization_bucket": "core", "activation_tier": "optional", "dialect_sensitive": true, "dialect_notes": "Represents a canonical percentile-point family, but concrete SQL differs across engines (for example PERCENTILE_CONT, APPROX_QUANTILES, approx_percentile, or quantile-style syntax).", "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["tail_concentration_consistency"], "allowed_variant_roles": ["focused_target_view", "ranked_signal_view"], "default_facet_ids": ["rare_target_concentration"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_h2o_topn_within_group", "template_name": "Top-N Within Group by Measure", "source_workload_id": "h2o_db_benchmark", "primary_family": "tail_rarity_structure", "secondary_family": "subgroup_structure", "intent": "Retain the top-N numeric values within each subgroup using window ranking.", "sql_skeleton": "WITH ranked AS (\n SELECT {group_col}, {measure_col},\n ROW_NUMBER() OVER (PARTITION BY {group_col} ORDER BY {measure_col} DESC) AS measure_rank\n FROM {table}\n WHERE {measure_col} IS NOT NULL\n)\nSELECT {group_col}, {measure_col}, measure_rank\nFROM ranked\nWHERE measure_rank <= {top_n}\nORDER BY {group_col}, measure_rank;", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/h2oai/db-benchmark/master/duckdb/groupby-duckdb.R", "title": "duckdb/groupby-duckdb.R · h2oai/db-benchmark", "source_query_id": "H2O groupby q8"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/h2oai/db-benchmark/master/duckdb/groupby-duckdb.R", "title": "duckdb/groupby-duckdb.R · h2oai/db-benchmark", "source_query_id": "H2O groupby q8"}], "status": "ready", "notes": "A canonical window-ranking template from an official single-table benchmark and a good fit for agent-side candidate generation.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["tail_set_consistency", "tail_mass_similarity"], "allowed_variant_roles": ["rare_extreme_view", "ranked_signal_view"], "default_facet_ids": ["low_support_extremes", "tail_ranked_signal"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_global_zscore_outliers", "template_name": "Global Z-score Outlier Scan", "source_workload_id": "insurance_cost_project_sql_repo", "primary_family": "tail_rarity_structure", "secondary_family": "conditional_dependency_structure", "intent": "Score a numeric measure globally and surface high-z-score outliers.", "sql_skeleton": "WITH scored AS (\n SELECT *,\n ({measure_col} - AVG({measure_col}) OVER ())\n / NULLIF(STDDEV({measure_col}) OVER (), 0) AS z_score\n FROM {table}\n)\nSELECT *\nFROM scored\nWHERE ABS(z_score) > {z_threshold}\nORDER BY {measure_col} DESC;", "required_roles": ["measure_col"], "optional_roles": [], "constraints": ["measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0032"}, "provenance_sources": [{"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0032"}], "status": "ready", "notes": "Useful for tail-sensitive analytics and anomaly-style reporting.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["measure_col"], "supported_canonical_subitem_ids": ["tail_set_consistency"], "allowed_variant_roles": ["rare_extreme_view"], "default_facet_ids": ["low_support_extremes"], "gate_priority": "support", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_m4_quantile_tail_slice", "template_name": "Quantile Tail Slice", "source_workload_id": "insurance_cost_project_sql_repo", "primary_family": "tail_rarity_structure", "secondary_family": "conditional_dependency_structure", "intent": "Select the highest quantile bucket of a numeric measure using NTILE-style ranking.", "sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", "required_roles": ["measure_col"], "optional_roles": [], "constraints": ["measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0023"}, "provenance_sources": [{"url": "https://github.com/arka420/Insurance-Cost-Project-Using-SQL/blob/main/Insurance%20cost%20%20SQL%20analysis.sql", "title": "Insurance cost SQL analysis.sql · Insurance-Cost-Project-Using-SQL", "source_query_id": "m4_sql_0023"}], "status": "ready", "notes": "A high-value tail template because it expresses rarity through quantile structure rather than an arbitrary threshold.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["measure_col"], "supported_canonical_subitem_ids": ["tail_set_consistency"], "allowed_variant_roles": ["rare_extreme_view"], "default_facet_ids": ["low_support_extremes"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_tail_low_support_group_count_v2", "template_name": "Low-Support Group Count", "source_workload_id": "subitem_workload_v2", "primary_family": "tail_rarity_structure", "secondary_family": null, "intent": "New v2 agent template for count-based tail coverage on non-numeric datasets.", "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", "required_roles": ["group_col"], "optional_roles": [], "constraints": ["single_table_only", "v2_agent_template"], "single_table_portable": "yes", "provenance": {"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_tail_low_support_group_count_v2"}, "provenance_sources": [{"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_tail_low_support_group_count_v2"}], "status": "ready", "notes": "New v2 agent template for count-based tail coverage on non-numeric datasets.", "materialization_bucket": "v2_agent", "activation_tier": "v2", "dialect_sensitive": false, "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["group_col"], "supported_canonical_subitem_ids": ["tail_set_consistency", "tail_mass_similarity"], "allowed_variant_roles": ["rare_extreme_view", "count_distribution"], "default_facet_ids": ["low_support_extremes", "tail_ranked_signal"], "gate_priority": "primary", "source_catalog": "template_library_v2", "extended_family": false} | |
| {"template_id": "tpl_tail_pairwise_sparse_slice_v2", "template_name": "Pairwise Sparse Slice Count", "source_workload_id": "subitem_workload_v2", "primary_family": "tail_rarity_structure", "secondary_family": null, "intent": "New v2 agent template for sparse pairwise tail slices.", "sql_skeleton": "SELECT\n {group_col},\n {group_col_2},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}, {group_col_2}\nORDER BY support ASC, {group_col}, {group_col_2}\nLIMIT {top_k};", "required_roles": ["group_col", "group_col_2"], "optional_roles": [], "constraints": ["single_table_only", "v2_agent_template"], "single_table_portable": "yes", "provenance": {"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_tail_pairwise_sparse_slice_v2"}, "provenance_sources": [{"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_tail_pairwise_sparse_slice_v2"}], "status": "ready", "notes": "New v2 agent template for sparse pairwise tail slices.", "materialization_bucket": "v2_agent", "activation_tier": "v2", "dialect_sensitive": false, "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["group_col", "group_col_2"], "supported_canonical_subitem_ids": ["tail_set_consistency", "tail_mass_similarity"], "allowed_variant_roles": ["rare_extreme_view", "filtered_stable_view"], "default_facet_ids": ["low_support_extremes", "tail_ranked_signal"], "gate_priority": "support", "source_catalog": "template_library_v2", "extended_family": false} | |
| {"template_id": "tpl_tail_target_rate_extremes_v2", "template_name": "Tail Target-Rate Extremes", "source_workload_id": "subitem_workload_v2", "primary_family": "tail_rarity_structure", "secondary_family": null, "intent": "New v2 agent template for classification-style tail concentration coverage.", "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support,\n AVG(CASE WHEN {target_col} = {target_value} THEN 1 ELSE 0 END) AS focus_rate\nFROM {table}\nGROUP BY {group_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY focus_rate DESC, support ASC\nLIMIT {top_k};", "required_roles": ["group_col", "target_col"], "optional_roles": [], "constraints": ["single_table_only", "v2_agent_template"], "single_table_portable": "yes", "provenance": {"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_tail_target_rate_extremes_v2"}, "provenance_sources": [{"url": "local://subitem_workload_v2", "title": "Locally authored v2 template", "source_query_id": "tpl_tail_target_rate_extremes_v2"}], "status": "ready", "notes": "New v2 agent template for classification-style tail concentration coverage.", "materialization_bucket": "v2_agent", "activation_tier": "v2", "dialect_sensitive": false, "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["group_col", "target_col"], "supported_canonical_subitem_ids": ["tail_concentration_consistency"], "allowed_variant_roles": ["focused_target_view", "ranked_signal_view"], "default_facet_ids": ["rare_target_concentration"], "gate_priority": "primary", "source_catalog": "template_library_v2", "extended_family": false} | |
| {"template_id": "tpl_threshold_rarity_cdf", "template_name": "Threshold Rarity CDF", "source_workload_id": "druid_sql_functions", "primary_family": "tail_rarity_structure", "secondary_family": "conditional_dependency_structure", "intent": "Estimate how rare a threshold is by reporting the empirical CDF value at that threshold.", "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", "required_roles": ["measure_col"], "optional_roles": [], "constraints": ["measure_col:numeric", "single_table_only"], "single_table_portable": "yes", "provenance": {"url": "https://druid.apache.org/docs/latest/querying/sql-functions/", "title": "All Druid SQL functions | Apache Druid", "source_query_id": "Druid DS_RANK example"}, "provenance_sources": [{"url": "https://druid.apache.org/docs/latest/querying/sql-functions/", "title": "All Druid SQL functions | Apache Druid", "source_query_id": "Druid DS_RANK example"}], "status": "ready", "notes": "Added because it answers a different question from percentile-point queries: not 'what is p99?' but 'how rare is threshold T?'", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["measure_col"], "supported_canonical_subitem_ids": ["tail_set_consistency"], "allowed_variant_roles": ["rare_extreme_view"], "default_facet_ids": ["low_support_extremes"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_tpcds_subgroup_baseline_outlier", "template_name": "Subgroup Baseline Outlier", "source_workload_id": "tpcds_altinity_queries", "primary_family": "tail_rarity_structure", "secondary_family": "conditional_dependency_structure", "intent": "Find entity-level aggregates that are extreme relative to their own subgroup baseline.", "sql_skeleton": "WITH entity_totals AS (\n SELECT {group_col}, {item_col}, SUM({measure_col}) AS entity_measure\n FROM {table}\n GROUP BY {group_col}, {item_col}\n), subgroup_baseline AS (\n SELECT {group_col}, AVG(entity_measure) AS subgroup_avg\n FROM entity_totals\n GROUP BY {group_col}\n)\nSELECT e.{group_col}, e.{item_col}, e.entity_measure, b.subgroup_avg\nFROM entity_totals AS e\nJOIN subgroup_baseline AS b\n ON e.{group_col} = b.{group_col}\nWHERE e.entity_measure > b.subgroup_avg * {baseline_multiplier}\nORDER BY e.entity_measure DESC;", "required_roles": ["group_col", "item_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "item_col:groupable_or_high_cardinality", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://github.com/Altinity/tpc-ds/blob/master/queries/query_1.sql", "title": "query_1.sql · Altinity/tpc-ds", "source_query_id": "TPC-DS Q1"}, "provenance_sources": [{"url": "https://github.com/Altinity/tpc-ds/blob/master/queries/query_1.sql", "title": "query_1.sql · Altinity/tpc-ds", "source_query_id": "TPC-DS Q1"}], "status": "ready", "notes": "High-value because it captures rarity relative to a local subgroup baseline, not just global magnitude.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["group_col", "item_col", "measure_col"], "supported_canonical_subitem_ids": ["tail_concentration_consistency"], "allowed_variant_roles": ["focused_target_view", "contrastive_conditional_view"], "default_facet_ids": ["rare_target_concentration"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_tpch_relative_total_threshold", "template_name": "Relative-to-Total Extreme Threshold", "source_workload_id": "tpch_qgen", "primary_family": "tail_rarity_structure", "secondary_family": "conditional_dependency_structure", "intent": "Keep only groups whose aggregate value exceeds a configurable fraction of the grand total.", "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/electrum/tpch-dbgen/master/queries/11.sql", "title": "queries/11.sql · electrum/tpch-dbgen", "source_query_id": "TPC-H Q11"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/electrum/tpch-dbgen/master/queries/11.sql", "title": "queries/11.sql · electrum/tpch-dbgen", "source_query_id": "TPC-H Q11"}], "status": "ready", "notes": "Canonical low-support but high-impact segment template: entity value above a tiny fraction of total.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["tail_mass_similarity"], "allowed_variant_roles": ["count_distribution", "filtered_stable_view"], "default_facet_ids": ["tail_ranked_signal"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |
| {"template_id": "tpl_tpch_thresholded_group_ranking", "template_name": "Thresholded Group Ranking", "source_workload_id": "tpch_qgen", "primary_family": "tail_rarity_structure", "secondary_family": "subgroup_structure", "intent": "Rank only those groups whose aggregate value exceeds an explicit threshold.", "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", "required_roles": ["group_col", "measure_col"], "optional_roles": [], "constraints": ["group_col:groupable", "measure_col:numeric", "single_table_only"], "single_table_portable": "partial", "provenance": {"url": "https://raw.githubusercontent.com/electrum/tpch-dbgen/master/queries/18.sql", "title": "queries/18.sql · electrum/tpch-dbgen", "source_query_id": "TPC-H Q18"}, "provenance_sources": [{"url": "https://raw.githubusercontent.com/electrum/tpch-dbgen/master/queries/18.sql", "title": "queries/18.sql · electrum/tpch-dbgen", "source_query_id": "TPC-H Q18"}], "status": "ready", "notes": "Separates true large-segment ranking from ordinary support guards by thresholding the aggregate itself.", "materialization_bucket": "core", "activation_tier": "core", "dialect_sensitive": false, "family_id": "tail_rarity_structure", "realization_mode": "agent", "binding_roles": ["group_col", "measure_col"], "supported_canonical_subitem_ids": ["tail_set_consistency", "tail_mass_similarity"], "allowed_variant_roles": ["rare_extreme_view", "filtered_stable_view"], "default_facet_ids": ["low_support_extremes", "tail_ranked_signal"], "gate_priority": "primary", "source_catalog": "template_library_v1", "extended_family": false} | |