data.generated.js

// Generated by agentlogsbench/common/render_dashboard.py.
// Do not edit this file directly.
// Generated at 2026-05-12T04:02:17Z.
const queryCatalog = [{"id":"Q01","title":"Observation list under common filters","category":"retrieval","contract":"Lists observations filtered by tenant, type, status, and time range, ordered by event_time and seq_no.","sql":"SELECT\n  event_time,\n  trace_id,\n  observation_id,\n  seq_no,\n  type,\n  status,\n  model,\n  tool_name,\n  latency_ms\nFROM agent_observations\nWHERE biz_date BETWEEN CAST(:start_date AS DATE) AND CAST(:end_date AS DATE)\n  AND tenant = :tenant\n  AND type IN ('GENERATION', 'TOOL')\n  AND status IN ('ok', 'error')\nORDER BY event_time DESC, seq_no DESC\nLIMIT 50;"},{"id":"Q02","title":"Trace list with failure and cost summaries","category":"analytics","contract":"Aggregates observations by trace_id to produce trace-level counts, failure counts, total cost, and total latency.","sql":"SELECT\n  trace_id,\n  min(event_time) AS started_at,\n  count(*) AS observation_count,\n  sum(CASE WHEN status <> 'ok' THEN 1 ELSE 0 END) AS failure_count,\n  sum(total_cost) AS total_cost,\n  sum(latency_ms) AS total_latency_ms\nFROM agent_observations\nWHERE biz_date BETWEEN CAST(:start_date AS DATE) AND CAST(:end_date AS DATE)\nGROUP BY trace_id\nORDER BY total_cost DESC, total_latency_ms DESC\n  , trace_id ASC\nLIMIT 50;"},{"id":"Q03","title":"Trace replay ordered by seq_no","category":"retrieval","contract":"Returns the ordered observations for one trace replay target from the primary `agent_observations` surface.","sql":"SELECT\n  trace_id,\n  seq_no,\n  type,\n  status,\n  model,\n  tool_name,\n  input,\n  output\nFROM agent_observations\nWHERE trace_id = :trace_id\nORDER BY seq_no ASC;"},{"id":"Q04","title":"Generation and tool chain expansion","category":"retrieval","contract":"Expands parent-child relationships within one trace to show generation-to-tool chains and execution order.","sql":"SELECT\n  child.trace_id,\n  child.seq_no,\n  child.observation_id,\n  child.parent_observation_id,\n  NULLIF(parent.type, '') AS parent_type,\n  child.type AS child_type,\n  child.status,\n  child.tool_name\nFROM agent_observations AS child\nLEFT JOIN agent_observations AS parent\n  ON child.parent_observation_id = parent.observation_id\nWHERE child.trace_id = :trace_id\nORDER BY child.seq_no ASC;"},{"id":"Q05","title":"Tool failure triage with text relevance","category":"retrieval","contract":"Returns failing tool observations with tenant/app filters and aligned token-based relevance over observation text and nested tool diagnostics.","sql":"SELECT\n  event_time,\n  trace_id,\n  observation_id,\n  tool_name,\n  latency_ms,\n  (\n    TEXT_TOKEN_SCORE(input, output, 'unable') +\n    TEXT_TOKEN_SCORE(input, output, 'open')\n  ) AS text_score,\n  payload\nFROM agent_observations\nWHERE type = 'TOOL'\n  AND status = 'error'\n  AND tenant = :tenant\n  AND app = :app\n  AND TEXT_HAS_TOKEN(input, output, 'unable')\n  AND TEXT_HAS_TOKEN(input, output, 'open')\nORDER BY text_score DESC, latency_ms DESC, event_time DESC\nLIMIT 50;"},{"id":"Q06","title":"Token, cost, and latency rollup by model and type","category":"analytics","contract":"Aggregates tokens, cost, and latency by observation type and model.","sql":"SELECT\n  type,\n  model,\n  count(*) AS observations,\n  sum(input_tokens) AS input_tokens,\n  sum(output_tokens) AS output_tokens,\n  sum(total_cost) AS total_cost,\n  avg(latency_ms) AS avg_latency_ms\nFROM agent_observations\nGROUP BY type, model\nORDER BY total_cost DESC, avg_latency_ms DESC\n  , observations DESC, input_tokens DESC, output_tokens DESC\n  , type ASC, model ASC\nLIMIT 50;"},{"id":"Q07","title":"Production-style attr filter across evolving payload","category":"semi_structured","contract":"Filters observations using multiple evolving payload.attr dimensions, matching production-style faceted investigation without helper-table flattening.","sql":"SELECT\n  event_time,\n  trace_id,\n  observation_id,\n  type,\n  status,\n  payload\nFROM agent_observations\nWHERE environment = 'prod'\n  AND type IN ('GENERATION', 'TOOL', 'RETRIEVAL')\n  AND JSON_VALUE(payload, '$.attr.release_ring') IN ('stable', 'canary')\n  AND JSON_VALUE(payload, '$.attr.retrieval_strategy') IN ('hybrid', 'hybrid_rerank')\n  AND JSON_VALUE(payload, '$.attr.surface') IN ('api', 'workflow_runner')\n  AND JSON_VALUE(payload, '$.attr.prompt_template_version') IN ('pt_2026_03_2', 'pt_2026_04_1', 'pt_2026_04_2')\nORDER BY event_time DESC, trace_id DESC, observation_id DESC\nLIMIT 50;"},{"id":"Q08","title":"Structured plus term-based text retrieval over observation payload","category":"semi_structured","contract":"Combines tenant scoping with aligned token retrieval plus a phrase constraint over input/output and nested tool diagnostics, suitable for text-index-backed execution.","sql":"SELECT\n  event_time,\n  trace_id,\n  observation_id,\n  type,\n  status,\n  input,\n  output,\n  TEXT_HAS_PHRASE(input, output, 'unable to open') AS phrase_match,\n  (\n    TEXT_TOKEN_SCORE(input, output, 'unable') +\n    TEXT_TOKEN_SCORE(input, output, 'open')\n  ) AS text_score\nFROM agent_observations\nWHERE tenant = :tenant\n  AND TEXT_HAS_TOKEN(input, output, 'unable')\n  AND TEXT_HAS_TOKEN(input, output, 'open')\n  AND TEXT_HAS_PHRASE(input, output, 'unable to open')\nORDER BY phrase_match DESC, text_score DESC, event_time DESC, trace_id DESC, observation_id DESC\nLIMIT 50;"},{"id":"Q09","title":"Tool usage distribution by name and status","category":"analytics","contract":"Counts tool observations by tool_name and status across the selected time range.","sql":"SELECT\n  tool_name,\n  status,\n  count(*) AS observations,\n  avg(latency_ms) AS avg_latency_ms\nFROM agent_observations\nWHERE type = 'TOOL'\nGROUP BY tool_name, status\nORDER BY observations DESC, avg_latency_ms DESC\n  , tool_name ASC, status ASC\nLIMIT 50;"},{"id":"Q10","title":"Provider stop reason and cache-hit analysis","category":"semi_structured","contract":"Aggregates generation observations by nested payload.provider.stop_reason and payload.provider.cache_hit.","sql":"SELECT\n  JSON_VALUE(payload, '$.provider.stop_reason') AS stop_reason,\n  JSON_VALUE(payload, '$.provider.cache_hit') AS cache_hit,\n  count(*) AS observations,\n  avg(latency_ms) AS avg_latency_ms\nFROM agent_observations\nWHERE type = 'GENERATION'\nGROUP BY JSON_VALUE(payload, '$.provider.stop_reason'), JSON_VALUE(payload, '$.provider.cache_hit')\nORDER BY observations DESC, avg_latency_ms DESC\n  , stop_reason ASC, cache_hit ASC\nLIMIT 50;"},{"id":"Q11","title":"App-Scoped Phrase Retrieval Over Incident Observations","category":"retrieval","contract":"Retrieves incident observations for one tenant/app slice using the same aligned token retrieval and phrase constraint over observation text and nested tool diagnostics.","sql":"SELECT\n  event_time,\n  trace_id,\n  observation_id,\n  type,\n  status,\n  tool_name,\n  latency_ms,\n  TEXT_HAS_PHRASE(input, output, 'unable to open') AS phrase_match,\n  (\n    TEXT_TOKEN_SCORE(input, output, 'unable') +\n    TEXT_TOKEN_SCORE(input, output, 'open')\n  ) AS text_score\nFROM agent_observations\nWHERE tenant = :tenant\n  AND app = :app\n  AND type IN ('GENERATION', 'TOOL', 'RETRIEVAL')\n  AND TEXT_HAS_TOKEN(input, output, 'unable')\n  AND TEXT_HAS_TOKEN(input, output, 'open')\n  AND TEXT_HAS_PHRASE(input, output, 'unable to open')\nORDER BY phrase_match DESC, text_score DESC, latency_ms DESC, event_time DESC, trace_id DESC, observation_id DESC\nLIMIT 50;"},{"id":"Q12","title":"Dynamic field facet aggregation over evolving payload dimensions","category":"semi_structured","contract":"Aggregates observations by selected payload.attr dimensions such as release ring, customer tier, and retrieval strategy.","sql":"SELECT\n  JSON_VALUE(payload, '$.attr.release_ring') AS release_ring,\n  JSON_VALUE(payload, '$.attr.customer_tier') AS customer_tier,\n  JSON_VALUE(payload, '$.attr.retrieval_strategy') AS retrieval_strategy,\n  count(*) AS observations,\n  avg(latency_ms) AS avg_latency_ms,\n  sum(total_cost) AS total_cost\nFROM agent_observations\nWHERE type IN ('GENERATION', 'TOOL', 'RETRIEVAL')\nGROUP BY\n  JSON_VALUE(payload, '$.attr.release_ring'),\n  JSON_VALUE(payload, '$.attr.customer_tier'),\n  JSON_VALUE(payload, '$.attr.retrieval_strategy')\nORDER BY observations DESC, total_cost DESC\n  , release_ring ASC, customer_tier ASC, retrieval_strategy ASC\nLIMIT 50;"},{"id":"Q13","title":"Operational phrase aggregate over tenant-scoped observations","category":"retrieval","contract":"Counts tenant-scoped operational incident observations and distinct traces when text contains operational phrases such as timeout awaiting headers, retry budget depletion, or transient upstream failure.","sql":"SELECT\n  count(*) AS observations,\n  count(DISTINCT trace_id) AS traces,\n  max(event_time) AS last_event_time\nFROM agent_observations\nWHERE biz_date BETWEEN CAST(:start_date AS DATE) AND CAST(:end_date AS DATE)\n  AND tenant = :tenant\n  AND type IN ('GENERATION', 'TOOL', 'RETRIEVAL', 'EVENT')\n  AND (\n    TEXT_HAS_PHRASE(input, output, 'timeout awaiting headers')\n    OR TEXT_HAS_PHRASE(input, output, 'retry budget depleted')\n    OR TEXT_HAS_PHRASE(input, output, 'transient upstream failure')\n  );"},{"id":"Q14","title":"LIKE-based deployment and rollback keyword retrieval","category":"retrieval","contract":"Retrieves recent generation, tool, and event observations for one tenant/app slice using LIKE-style matching over deployment, rollback, and transient incident keywords.","sql":"SELECT\n  event_time,\n  trace_id,\n  observation_id,\n  type,\n  status,\n  tool_name,\n  output\nFROM agent_observations\nWHERE tenant = :tenant\n  AND app = :app\n  AND type IN ('GENERATION', 'TOOL', 'EVENT')\n  AND (\n    LOWER(COALESCE(input, '')) LIKE '%deployment%'\n    OR LOWER(COALESCE(output, '')) LIKE '%deployment%'\n    OR LOWER(COALESCE(input, '')) LIKE '%rollback%'\n    OR LOWER(COALESCE(output, '')) LIKE '%rollback%'\n    OR LOWER(COALESCE(output, '')) LIKE '%transient%'\n  )\nORDER BY event_time DESC, trace_id DESC, observation_id DESC\nLIMIT 50;"},{"id":"Q15","title":"Phrase retrieval over transient failure and timeout incidents","category":"retrieval","contract":"Retrieves tenant-scoped observations containing common operational incident phrases such as transient upstream failure, retry budget depletion, and connector timeout.","sql":"SELECT\n  event_time,\n  trace_id,\n  observation_id,\n  type,\n  status,\n  tool_name,\n  latency_ms\nFROM agent_observations\nWHERE tenant = :tenant\n  AND type IN ('GENERATION', 'TOOL', 'RETRIEVAL', 'EVENT')\n  AND (\n    TEXT_HAS_PHRASE(input, output, 'transient upstream failure')\n    OR TEXT_HAS_PHRASE(input, output, 'retry budget depleted')\n    OR TEXT_HAS_PHRASE(input, output, 'connector timeout')\n  )\nORDER BY latency_ms DESC, event_time DESC, trace_id DESC, observation_id DESC\nLIMIT 50;"},{"id":"Q16","title":"Low-cardinality dynamic field multi-filter","category":"semi_structured","contract":"Filters production observations with low-cardinality payload.attr dimensions such as release ring, customer tier, and traffic cluster.","sql":"SELECT\n  event_time,\n  trace_id,\n  observation_id,\n  type,\n  status,\n  JSON_VALUE(payload, '$.attr.release_ring') AS release_ring,\n  JSON_VALUE(payload, '$.attr.customer_tier') AS customer_tier,\n  JSON_VALUE(payload, '$.attr.traffic_cluster') AS traffic_cluster\nFROM agent_observations\nWHERE tenant = :tenant\n  AND environment = 'prod'\n  AND type IN ('GENERATION', 'TOOL', 'RETRIEVAL')\n  AND JSON_VALUE(payload, '$.attr.release_ring') = :release_ring\n  AND JSON_VALUE(payload, '$.attr.customer_tier') = :customer_tier\n  AND JSON_VALUE(payload, '$.attr.traffic_cluster') = :traffic_cluster\nORDER BY event_time DESC, trace_id DESC, observation_id DESC\nLIMIT 50;"},{"id":"Q17","title":"High-cardinality request-key filter over dynamic payload","category":"semi_structured","contract":"Retrieves one request slice by filtering on the high-cardinality payload.attr.request_key while also checking workflow_variant in the evolving payload.","sql":"SELECT\n  trace_id,\n  observation_id,\n  seq_no,\n  type,\n  status,\n  JSON_VALUE(payload, '$.attr.request_key') AS request_key,\n  JSON_VALUE(payload, '$.attr.workflow_variant') AS workflow_variant\nFROM agent_observations\nWHERE tenant = :tenant\n  AND JSON_VALUE(payload, '$.attr.request_key') = :request_key\n  AND JSON_VALUE(payload, '$.attr.workflow_variant') = :workflow_variant\nORDER BY seq_no ASC, observation_id ASC\nLIMIT 100;"},{"id":"Q18","title":"Prompt template version performance rollup","category":"analytics","contract":"Aggregates observations by payload.attr.prompt_template_version to compare trace coverage, latency, and cost across prompt template revisions.","sql":"SELECT\n  JSON_VALUE(payload, '$.attr.prompt_template_version') AS prompt_template_version,\n  count(*) AS observations,\n  count(DISTINCT trace_id) AS traces,\n  avg(latency_ms) AS avg_latency_ms,\n  sum(total_cost) AS total_cost\nFROM agent_observations\nWHERE type IN ('GENERATION', 'REASONING', 'TOOL')\nGROUP BY JSON_VALUE(payload, '$.attr.prompt_template_version')\nORDER BY observations DESC, total_cost DESC, prompt_template_version ASC\nLIMIT 20;"},{"id":"Q19","title":"Incident rollup by deployment channel and release ring","category":"analytics","contract":"Aggregates error-, timeout-, or retry-like observations by payload.attr.deployment_channel and payload.attr.release_ring.","sql":"SELECT\n  JSON_VALUE(payload, '$.attr.deployment_channel') AS deployment_channel,\n  JSON_VALUE(payload, '$.attr.release_ring') AS release_ring,\n  count(*) AS incident_observations,\n  count(DISTINCT trace_id) AS incident_traces,\n  avg(latency_ms) AS avg_latency_ms\nFROM agent_observations\nWHERE type IN ('GENERATION', 'TOOL', 'RETRIEVAL', 'EVENT')\n  AND (\n    TEXT_HAS_TOKEN(input, output, 'error')\n    OR TEXT_HAS_TOKEN(input, output, 'timeout')\n    OR TEXT_HAS_TOKEN(input, output, 'retry')\n  )\nGROUP BY JSON_VALUE(payload, '$.attr.deployment_channel'), JSON_VALUE(payload, '$.attr.release_ring')\nORDER BY incident_observations DESC, incident_traces DESC, deployment_channel ASC, release_ring ASC\nLIMIT 20;"},{"id":"Q20","title":"Workflow variant and policy pack operational rollup","category":"analytics","contract":"Aggregates observations by payload.attr.workflow_variant and payload.attr.policy_pack to compare tenant breadth, latency, and cost.","sql":"SELECT\n  JSON_VALUE(payload, '$.attr.workflow_variant') AS workflow_variant,\n  JSON_VALUE(payload, '$.attr.policy_pack') AS policy_pack,\n  count(*) AS observations,\n  count(DISTINCT tenant) AS tenants,\n  avg(latency_ms) AS avg_latency_ms,\n  sum(total_cost) AS total_cost\nFROM agent_observations\nWHERE type IN ('GENERATION', 'TOOL', 'RETRIEVAL', 'REASONING')\nGROUP BY JSON_VALUE(payload, '$.attr.workflow_variant'), JSON_VALUE(payload, '$.attr.policy_pack')\nORDER BY observations DESC, total_cost DESC, workflow_variant ASC, policy_pack ASC\nLIMIT 20;"}];
const datasetSizes = [{"value":1000000,"label":"1M"},{"value":10000000,"label":"10M"},{"value":100000000,"label":"100M"}];
const data = [
{"engine":"doris","system":"Apache Doris","machine":"m6i.8xlarge, 991gib root","cluster_size":1,"date":"2026-04-15","dataset_size":1000000,"dataset_label":"1M","load_time":43.222,"storage_bytes":628091781,"data_size":628091781,"index_size":null,"num_loaded_documents":998799,"retains_structure":"yes","proprietary":"no","hardware":"cpu","tuned":"no","comment":"","tags":["sql","column-oriented","full-text","semi-structured"],"version":"5.7.99","os":"Ubuntu 24.04.4 LTS","result":[[0.182,0.033,0.032],[0.22,0.062,0.056],[0.088,0.017,0.017],[0.104,0.032,0.032],[3.298,1.17,1.171],[0.16,0.065,0.053],[1.86,1.27,1.275],[0.141,0.145,0.124],[0.128,0.055,0.055],[0.132,0.068,0.066],[0.11,0.14,0.177],[0.133,0.071,0.074],[0.197,0.032,0.032],[0.735,0.348,0.342],[0.121,0.034,0.032],[0.103,0.036,0.035],[0.091,0.02,0.019],[0.136,0.072,0.074],[0.156,0.074,0.073],[0.151,0.078,0.078]],"source":"https://github.com/velodb/agentlogsbench/blob/main/doris/results/m6i.8xlarge_agentlog_1m.json","query_results_source":"https://github.com/velodb/agentlogsbench/blob/main/doris/results/_query_results/_m6i.8xlarge_agentlog_1m.query_results"}
,{"engine":"clickhouse","system":"ClickHouse","machine":"m6i.8xlarge, 991gib root","cluster_size":1,"date":"2026-04-15","dataset_size":1000000,"dataset_label":"1M","load_time":27.061,"storage_bytes":546115393,"data_size":463842639,"index_size":1920533,"num_loaded_documents":998799,"retains_structure":"yes","proprietary":"no","hardware":"cpu","tuned":"no","comment":"","tags":["sql","column-oriented","full-text","semi-structured"],"version":"ClickHouse local version 26.2.13.2 (official build).","os":"Ubuntu 24.04.4 LTS","result":[[1.726,0.235,0.214],[1.817,0.245,0.233],[1.743,0.239,0.236],[1.847,0.253,0.255],[10.106,0.648,0.637],[1.744,0.25,0.236],[8.784,0.521,0.51],[1.985,0.423,0.369],[1.759,0.248,0.251],[1.751,0.232,0.231],[1.916,0.308,0.31],[1.833,0.25,0.259],[1.964,0.422,0.435],[1.869,0.321,0.313],[1.927,0.398,0.382],[1.826,0.25,0.246],[1.761,0.252,0.233],[1.823,0.256,0.302],[2.343,0.718,0.763],[1.82,0.238,0.246]],"source":"https://github.com/velodb/agentlogsbench/blob/main/clickhouse/results/m6i.8xlarge_agentlog_1m.json","query_results_source":"https://github.com/velodb/agentlogsbench/blob/main/clickhouse/results/_query_results/_m6i.8xlarge_agentlog_1m.query_results"}
,{"engine":"duckdb","system":"DuckDB","machine":"m6i.8xlarge, 991gib root","cluster_size":1,"date":"2026-04-16","dataset_size":1000000,"dataset_label":"1M","load_time":90.26,"storage_bytes":1509437440,"data_size":1509437440,"index_size":0,"num_loaded_documents":998799,"retains_structure":"yes","proprietary":"no","hardware":"cpu","tuned":"no","comment":"","tags":["duckdb"],"version":"1.5.2","os":"Ubuntu 24.04.4 LTS","result":[[0.046,0.007,0.007],[0.03,0.014,0.014],[0.014,0.003,0.002],[0.029,0.01,0.01],[3.148,2.666,2.667],[0.018,0.011,0.011],[23.303,23.453,23.307],[0.537,0.294,0.27],[0.007,0.006,0.006],[42.732,42.608,42.642],[0.18,0.178,0.176],[63.145,63.38,63.286],[0.386,0.382,0.383],[0.167,0.167,0.167],[0.367,0.367,0.371],[23.799,23.583,23.672],[20.647,20.741,20.601],[20.917,20.798,20.775],[44.303,44.473,44.467],[41.93,41.977,42.006]],"source":"https://github.com/velodb/agentlogsbench/blob/main/duckdb/results/m6i.8xlarge_agentlog_1m.json","query_results_source":"https://github.com/velodb/agentlogsbench/blob/main/duckdb/results/_query_results/_m6i.8xlarge_agentlog_1m.query_results"}
,{"engine":"elastic","system":"Elasticsearch","machine":"m6i.8xlarge, 991gib root","cluster_size":1,"date":"2026-04-15","dataset_size":1000000,"dataset_label":"1M","load_time":178.876,"storage_bytes":1854025914,"data_size":1854025914,"index_size":null,"num_loaded_documents":998799,"retains_structure":"yes","proprietary":"no","hardware":"cpu","tuned":"no","comment":"","tags":["search","document","full-text","semi-structured"],"version":"9.3.0","os":"Ubuntu 24.04.4 LTS","result":[[0.123,0.055,0.056],[0.249,0.164,0.167],[0.032,0.029,0.029],[0.028,0.028,0.029],[0.122,0.035,0.035],[0.088,0.099,0.064],[0.187,0.052,0.052],[0.143,0.06,0.059],[0.048,0.037,0.043],[0.061,0.05,0.049],[0.18,0.076,0.075],[0.064,0.067,0.054],[0.161,0.076,0.065],[0.082,0.038,0.038],[0.16,0.063,0.057],[0.074,0.039,0.039],[0.03,0.028,0.029],[2.214,2.219,2.196],[2.811,2.783,2.769],[0.073,0.059,0.058]],"source":"https://github.com/velodb/agentlogsbench/blob/main/elastic/results/m6i.8xlarge_agentlog_1m.json","query_results_source":"https://github.com/velodb/agentlogsbench/blob/main/elastic/results/_query_results/_m6i.8xlarge_agentlog_1m.query_results"}
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