Bigquery Observability

GoogleOfficialPublished by Google

Skill
Tool integration
Data and AI
Apache-2.0
No issues found

From the author

Provides data-retrieval best practices, tool selection guidance, and performant SQL query syntax for BigQuery telemetry across INFORMATION_SCHEMA, Cloud Monitoring, and the REST API. Use when the telemetry to fetch is already known, selecting telemetry tools, writing performant INFORMATION_SCHEMA queries, retrieving telemetry for diagnosing single-job performance bottlenecks, investigating slot contention, job concurrency and queue latency, analyzing reservation capacity, utilization and autoscaling saturation, or auditing capacity-based and on-demand compute and storage resource billable usage. Don't use for root-cause diagnosis or symptom troubleshooting when the cause is unknown (use bigquery-troubleshooting first), or for writing or optimizing business logic SQL (use bigquery-optimization).

— the description by Google

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

BigQuery Observability offers a structured approach to monitoring and analyzing BigQuery performance and resource usage. It guides users in selecting the right telemetry tools—ranging from INFORMATION_SCHEMA for historical analysis to the REST API for real-time job lookups—and provides optimized SQL templates for auditing compute, storage, and capacity. The skill emphasizes efficient data retrieval, least-privilege access, and performance guardrails to ensure accurate telemetry without unnecessary overhead.

What it does

Provides SQL query templates for INFORMATION_SCHEMA views.
Offers guidance on choosing between INFORMATION_SCHEMA, Cloud Monitoring, and REST APIs.
Includes best practices for performant telemetry retrieval and cost management.
Details schema dictionaries for compute, storage, and capacity metrics.
Defines workflows for diagnosing job bottlenecks and resource contention.
Enforces usage attribution for all Google Cloud CLI and API interactions.

When to use it

When you need to audit billable compute or storage resource usage.
When investigating job performance bottlenecks or slot contention.
When analyzing reservation capacity, utilization, or autoscaling saturation.
When you need to perform historical analysis or cohort comparisons of jobs.
When selecting the appropriate telemetry tool for real-time vs. historical monitoring.

Advantages

Reduces query overhead by providing optimized, partition-filtered SQL patterns.
Ensures least-privilege access by recommending specific view variants.
Standardizes diagnostic workflows across single-job and system-level issues.
Provides clear guidance on avoiding common pitfalls like full metadata scans.

Usage examples

“How do I check for slot contention in my BigQuery project?”: The agent provides a query template using the JOBS_TIMELINE view, filtered by the relevant time window, to identify periods of high slot usage and queue latency.
“I need to audit my on-demand compute spend for the last 30 days.”: The agent provides a structured SQL query using INFORMATION_SCHEMA.JOBS, including logic to deduplicate script wrappers and calculate billable bytes.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/google/bigquery-observability/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip bigquery-observability.zip -d .agents/skills

Documentation by Google

BigQuery Observability

Attribution

MUST READ: Before executing any gcloud, REST API, or MCP command, you MUST read Usage Attribution. For commands executed directly in the terminal (never in generated scripts, Terraform, or user code), prefix gcloud with CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:bigquery-observability)" and append agent-skills/1.0 (skill:bigquery-observability) to User-Agent headers.

Tool Selection

Tool	Primary Use Cases	Strengths & Capabilities	When to Avoid / Limitations
`INFORMATION_SCHEMA` (`I_S`)	Historical analysis, cohort comparison (`normalized_literals`), discovery of fast/slow windows, reservation/project timelines, multi-job aggregates, cost/billing tracing.	Flexible SQL querying across `JOBS`, `JOBS_TIMELINE`, and `RESERVATIONS`; supports custom time windows and grouping.	Avoid for high-frequency real-time polling or single-job point-lookups (can consume slots and take seconds to execute).
REST API (`jobs.api` / `reservation.api`)	Single-job point-lookup, real-time stage bottleneck diagnosis, automated pipeline status checks, reservation/capacity commitment configuration inspection (`reservations.get`, `reservations.list`).	Zero-SQL overhead, fast REST/CLI point-lookups (`bq show -j`, `bq show --reservation`), instant access to `performanceInsights`, `queryPlan`, and structural metadata.	Avoid for aggregate analysis across thousands of jobs, cross-project historical comparison, or system timeline aggregations.
`Cloud Monitoring` (Metrics Explorer / Charts)	Real-time alerting, fleet-wide dashboards, continuous slot utilization tracking, high-level SLA/SLO monitoring.	Out-of-the-box charts for slot utilization, query throughput, `PENDING` queue depth, and execution latency; low-latency alerting without running queries.	Avoid for SQL-level debugging, individual query text inspection, or stage-level execution detail.

Prerequisites & Environment Setup

Before retrieving telemetry or running observability queries, ensure the Google Cloud environment and project are configured:

Google Cloud SDK: Ensure the Google Cloud SDK is installed and configured.
Project Selection: Set the active Google Cloud project:
```
gcloud config set project {project_id}
```
API Enablement: Ensure the BigQuery and Cloud Monitoring APIs are enabled:
```
gcloud services enable bigquery.googleapis.com monitoring.googleapis.com
```
Authentication: Authenticate the environment:
- CLI queries and bq commands: gcloud auth login
- SDKs and automated client tools: gcloud auth application-default login
- Service accounts: Set GOOGLE_APPLICATION_CREDENTIALS="/path/to/key.json"
Billing & IAM Roles:
- Verify an active Google Cloud Billing account is attached to {project_id}.
- Ensure appropriate IAM roles:
  - roles/bigquery.jobUser: Running telemetry queries.
  - roles/bigquery.resourceViewer or roles/bigquery.admin: Organization-level jobs and reservation telemetry.
  - roles/monitoring.viewer: Cloud Monitoring metrics.
Companion Skills Installation: This skill is part of a 3-pillar operations suite (bigquery-observability, bigquery-optimization, bigquery-troubleshooting). If any companion skill is not yet installed in your environment, install the full suite:
```
npx skills add google/skills --skill bigquery-observability --skill bigquery-optimization --skill bigquery-troubleshooting
```

Workflow

Single-Job Point-Lookup (Zero-SQL Overhead): For single-job slowness or inspection, always prioritize the REST API or CLI (bq show -j) first. It provides zero-SQL overhead and fast point-lookups for internal stage bottlenecks (performanceInsights, queryPlan, shuffle spill).
```
bq show --location={location} -j {project_id}:{job_id}
```
Diagnostic Transition Logic: If no job-level issues are found (e.g. no clear internal bottlenecks), the investigation should transition to system-level INFORMATION_SCHEMA queries (such as JOBS_TIMELINE or RESERVATIONS_TIMELINE) to check for broader issues like slot contention, queueing delay, or noisy neighbors.

Best Practices for Writing `INFORMATION_SCHEMA` Queries

Every query against a BigQuery INFORMATION_SCHEMA view must be qualified with either a region qualifier or a dataset qualifier, optionally prefixed by a project qualifier.

Qualification Syntax & Scope Matching

Region-Qualified Syntax:
```
`{project_id}`.`region-{region}`.INFORMATION_SCHEMA.{view}
```
Example: `my-project`.`region-us`.INFORMATION_SCHEMA.JOBS
Applies to: Regional telemetry views (JOBS*, JOBS_TIMELINE*, RESERVATIONS*, CAPACITY_COMMITMENTS*, TABLE_STORAGE*, STREAMING_TIMELINE*). The client query execution location MUST match the region-{region} qualifier (or BigQuery throws: Not found: Table {project_id}:region-{region}.INFORMATION_SCHEMA.{view} was not found in location {location}).
Dataset-Qualified Syntax:
```
`{project_id}`.`{dataset_id}`.INFORMATION_SCHEMA.{view}
```
Example: `my-project`.`analytics`.INFORMATION_SCHEMA.TABLES
Applies to: Dataset-scoped views (PARTITIONS, SEARCH_INDEXES*, ROW_ACCESS_POLICIES). Never use region- with dataset views.
Dual-Scoped Views: Views like TABLES, COLUMNS, COLUMN_FIELD_PATHS, VIEWS, ROUTINES, and VECTOR_INDEXES can be qualified with either {dataset_id} or region-{region} depending on whether dataset or region-wide analysis is required.
Project Qualifier ({project_id}): Optional. If omitted, queries default to the project in which the query is executing. Specifying a project qualifier on organization-level views (e.g. JOBS_BY_ORGANIZATION) has no impact on results.

Principle of Least Privilege & Scope Selection

When constructing INFORMATION_SCHEMA queries, always select the scope and view variant with the least IAM permission requirement that satisfies the analytical need:

User-Level over Project-Level (_BY_USER): When diagnosing queries or sessions executed by the current user, use _BY_USER (e.g. JOBS_BY_USER, SESSIONS_BY_USER). This requires only bigquery.jobs.list (granted via roles/bigquery.user or roles/bigquery.jobUser), avoiding the need for bigquery.jobs.listAll or roles/bigquery.admin.
Dataset-Level over Region/Project-Level: When querying table metadata, columns, or views for a specific dataset, qualify with {dataset_id} rather than region-{region} when project-level metadata access is restricted. Dataset-scoped queries require permissions only on that target dataset.
Project-Level over Org/Folder-Level (_BY_PROJECT): Always start with project-scoped views before escalating to _BY_FOLDER or _BY_ORGANIZATION. Folder and organization queries require broad folder/org IAM permissions (bigquery.jobs.listAll or bigquery.tables.list at the Org/Folder node).
Metadata Roles over Data Roles: For table and storage introspection, prefer roles/bigquery.metadataViewer (which provides bigquery.tables.get and bigquery.tables.list) over roles/bigquery.dataViewer or roles/bigquery.dataOwner when data read access (bigquery.tables.getData) is not needed. (Note: INFORMATION_SCHEMA.PARTITIONS uniquely requires bigquery.tables.getData).

Execution Guardrails & Query Invariants

Mandatory Partition & Time Filtering: Always filter on creation_time (e.g., creation_time >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 3 DAY)) or usage_date to avoid full metadata table scans.
Script Wrapper Exclusion: Add AND (statement_type != 'SCRIPT' OR statement_type IS NULL) when aggregating compute spend to avoid double-counting parent scripts and child jobs.
Column Pruning: Never use SELECT * against INFORMATION_SCHEMA; only project required columns.
Dry Run & Cost Estimation: Use a dry run (bq query --dry_run --use_legacy_sql=false "{query}" or API dryRun=true) before executing complex queries, multi-view joins, or large scans to validate syntax and estimate totalBytesProcessed at zero cost.
Empty Regional Scope (0 Rows): If the execution location matches the qualifier, but the project has no datasets or jobs in that region, the query succeeds and returns 0 rows. Never assume 0 rows means 0 usage—always verify the target dataset locations.
Non-Hierarchical Region Scope: Region qualifiers are not hierarchical. Multi-regions do not encompass single regions (e.g. region-us returns only multi-region US metadata and does not include single regions like region-us-central1).
No Multi-Region Aggregation in SQL: Region qualifiers cannot be joined cross-region in a single query (e.g. region-us cannot join region-eu).
Uncached Execution & Minimum Scan Size: INFORMATION_SCHEMA query results are never cached. On-demand queries incur a minimum of 10 MB of data processing charges per execution.

Domain References & SQL Queries

Telemetry Query Guides

On-Demand Compute: Billed Bytes (references/compute_ondemand_billable.md): Authoritative Golden CTE (bytes_billed_cte), timezone-aligned billing date extraction (PST8PDT), BQML CREATE_MODEL 50x multiplier rules, script wrapper deduplication, and row-level security (RLS) masking checks.
Capacity Compute: Billable Slots & Commitments (references/compute_capacity_billable.md): Query templates for auditing billable capacity hours across 1-Year/3-Year commitments, uncovered baseline PAYG slots, and dynamic autoscaling hours.
Storage Footprints & Usage (Bytes Stored) (references/storage_footprints.md): Storage snapshot queries, compression ratio calculations, Time Travel / Fail-Safe churn, daily average GiB time-integrals, billing model evaluation, and search index coverage.

Performance & Troubleshooting Guides

Job Performance Queries (references/job_performance_queries.md): Queries for evaluating individual and aggregate job performance, stage bottleneck flags, comparable jobs via normalized literals (query_info.query_hashes.normalized_literals), BI Engine acceleration, metadata cache (cmeta) acceleration, search index usage, materialized view rewrite usage, and execution variance outliers.
Resource Contention Queries (references/resource_contention_queries.md): Queries for diagnosing slot contention, queue latency, per-minute concurrency/queue timelines, and 1-second reservation slot saturation.
Capacity & Configuration Queries (references/capacity_and_configuration_queries.md): Queries for evaluating second-by-second baseline/max capacity ceilings, autoscaling saturation timelines, and auditing configuration changes (RESERVATION_CHANGES_BY_PROJECT, ASSIGNMENT_CHANGES_BY_PROJECT).

Schema Dictionaries (Column Definitions & Units)

Compute & Capacity Schema Dictionary (references/schema_compute.md): Complete column dictionary, physical units, and least-privilege IAM roles for all compute, job, session, reservation, capacity commitment, and assignment views (JOBS*, JOBS_TIMELINE*, SESSIONS_BY_USER, SESSIONS_BY_PROJECT, RESERVATIONS*, RESERVATION_CHANGES*, RESERVATIONS_TIMELINE*, CAPACITY_COMMITMENTS*, CAPACITY_COMMITMENT_CHANGES_BY_PROJECT, ASSIGNMENTS*, ASSIGNMENT_CHANGES_BY_PROJECT).
Storage & Data Catalog Schema Dictionary (references/schema_storage.md): Complete column dictionary, physical units, and least-privilege IAM roles for all table storage, partition, column, snapshot, dataset, constraint, and replication views (TABLE_STORAGE*, TABLE_STORAGE_USAGE_TIMELINE*, TABLES*, TABLE_OPTIONS, COLUMNS, COLUMN_FIELD_PATHS, PARTITIONS, VIEWS, MATERIALIZED_VIEWS, TABLE_SNAPSHOTS*, TABLE_CONSTRAINTS, KEY_COLUMN_USAGE, SCHEMATA*, SCHEMATA_OPTIONS, SCHEMATA_REPLICAS*, SCHEMATA_LINKS, SHARED_DATASET_USAGE).
Platform, Governance & Ingestion Schema Dictionary (references/schema_others.md): Complete column dictionary, physical units, and least-privilege IAM roles for all remaining views including Access Control (OBJECT_PRIVILEGES, ROW_ACCESS_POLICIES, ROW_ACCESS_POLICY_OPTIONS), Streaming Ingestion (STREAMING_TIMELINE_BY_PROJECT*, WRITE_API_TIMELINE_BY_PROJECT*), Configuration Options (PROJECT_OPTIONS*, EFFECTIVE_PROJECT_OPTIONS, ORGANIZATION_OPTIONS*, ORGANIZATION_OPTIONS_CHANGES), Insights & Recommendations (RECOMMENDATIONS*, INSIGHTS), and Indexes/BI Engine/Routines (SEARCH_INDEXES*, SEARCH_INDEX_COLUMNS, SEARCH_INDEX_OPTIONS, VECTOR_INDEXES*, VECTOR_INDEX_COLUMNS, VECTOR_INDEX_OPTIONS, BI_CAPACITIES, BI_CAPACITY_CHANGES, ROUTINES*, ROUTINE_OPTIONS, PARAMETERS).

Files

ATTRIBUTION.mdAdded by AutoGineer862 B
LICENSELicence file added by AutoGineer11.1 KiB
SKILL.md14.3 KiB
references/attribution.md1.9 KiB
references/capacity_and_configuration_queries.md6.6 KiB
references/compute_capacity_billable.md6.2 KiB
references/compute_ondemand_billable.md5.7 KiB
references/job_performance_queries.md11.1 KiB
references/resource_contention_queries.md9.3 KiB
references/schema_compute.md40.4 KiB
references/schema_others.md32.0 KiB
references/schema_storage.md34.3 KiB
references/storage_footprints.md10.1 KiB

references/schema_others.md

BigQuery Platform, Governance & Ingestion INFORMATION_SCHEMA Reference

A comprehensive dictionary, column definition guide, and physical unit specification for all remaining BigQuery INFORMATION_SCHEMA views, covering BI Engine Acceleration, Security, Streaming Ingestion, Routines, Search/Vector Indexes, Configurations, and Recommendations.

View Scoping & Qualification Matrix (Lines 61-79)
5. Routines, Functions, Stored Procedures & ML Views (Lines 80-179)
- INFORMATION_SCHEMA.ROUTINES (Lines 82-120)
- INFORMATION_SCHEMA.PARAMETERS (Lines 121-151)
- INFORMATION_SCHEMA.ROUTINE_OPTIONS (Lines 152-179)
6. Streaming & Ingestion Views (Lines 180-249)
- INFORMATION_SCHEMA.STREAMING_TIMELINE_BY_PROJECT (and _BY_ORGANIZATION, _BY_FOLDER) (Lines 182-214)
- INFORMATION_SCHEMA.WRITE_API_TIMELINE_BY_PROJECT (and _BY_ORGANIZATION, _BY_FOLDER) (Lines 215-249)
7. Search, Vector, AI Indexes & BI Engine Views (Lines 250-405)
- INFORMATION_SCHEMA.SEARCH_INDEXES (and _OPTIONS) (Lines 252-290)
- INFORMATION_SCHEMA.SEARCH_INDEX_COLUMNS (Lines 291-316)
- INFORMATION_SCHEMA.VECTOR_INDEXES (and _OPTIONS) (Lines 317-354)
- INFORMATION_SCHEMA.VECTOR_INDEX_COLUMNS (Lines 355-380)
- INFORMATION_SCHEMA.BI_CAPACITIES & BI_CAPACITY_CHANGES (Lines 381-405)
8. Security, Access Control, Governance & Policy Views (Lines 406-459)
- INFORMATION_SCHEMA.OBJECT_PRIVILEGES (Lines 408-433)
- INFORMATION_SCHEMA.ROW_ACCESS_POLICIES & ROW_ACCESS_POLICY_OPTIONS (Lines 434-459)
9. Recommendations & Insights Views (Lines 460-536)
- INFORMATION_SCHEMA.RECOMMENDATIONS (and _BY_PROJECT, _BY_ORGANIZATION) (Lines 462-498)
- INFORMATION_SCHEMA.INSIGHTS (and _BY_PROJECT) (Lines 499-536)
10. Project & Organization Configuration Views (Lines 537-633)
- INFORMATION_SCHEMA.PROJECT_OPTIONS (Lines 539-565)
- INFORMATION_SCHEMA.EFFECTIVE_PROJECT_OPTIONS (Lines 566-591)
- INFORMATION_SCHEMA.ORGANIZATION_OPTIONS (Lines 592-613)
- INFORMATION_SCHEMA.ORGANIZATION_OPTIONS_CHANGES (Lines 614-633)

View Scoping & Qualification Matrix

Platform, acceleration, and governance views fall into Dual-Scoped, Region-Only, and Dataset-Only qualification categories:

View Family	INFORMATION_SCHEMA View(s)	Qualification Scope	Syntax Pattern & Scoping Rules
BI Engine Acceleration	`BI_CAPACITIES`, `BI_CAPACITY_CHANGES`	Region-Only	`{project_id}`.`region-{region}`.INFORMATION_SCHEMA.BI_CAPACITIES*<br>• In-memory RAM capacity and allocation modification logs.
Search Indexes	`SEARCH_INDEXES`, `SEARCH_INDEX_COLUMNS`, `SEARCH_INDEX_OPTIONS`, `SEARCH_INDEX_COLUMN_OPTIONS`<br><br>`SEARCH_INDEXES_BY_ORGANIZATION`	Dataset-Only<br><br><br>Region-Only	• Dataset views require `{dataset_id}`.<br>• Org view requires `region-{region}`.
Vector Indexes	`VECTOR_INDEXES`, `VECTOR_INDEX_COLUMNS`, `VECTOR_INDEX_OPTIONS`	Dual-Scoped	`{project_id}`.`region-{region}`.INFORMATION_SCHEMA.VECTOR_INDEXES<br>OR<br> `{project_id}`.`{dataset_id}`.INFORMATION_SCHEMA.VECTOR_INDEXES
Access Control	`OBJECT_PRIVILEGES`	Region-Only	`{project_id}`.`region-{region}`.INFORMATION_SCHEMA.OBJECT_PRIVILEGES<br>• IAM permissions on datasets, tables, views, and routines.
Row-Level Security	`ROW_ACCESS_POLICIES`, `ROW_ACCESS_POLICY_OPTIONS`	Dataset-Only	`{project_id}`.`{dataset_id}`.INFORMATION_SCHEMA.ROW_ACCESS_POLICIES*<br>• Row access filter expressions and predicate definitions.
Streaming Ingestion	`STREAMING_TIMELINE_BY_PROJECT`, `WRITE_API_TIMELINE_BY_PROJECT`	Region-Only	`{project_id}`.`region-{region}`.INFORMATION_SCHEMA.{view_name}<br>• Streaming buffer and Storage Write API append throughput.
Configurations	`PROJECT_OPTIONS`, `EFFECTIVE_PROJECT_OPTIONS`, `ORGANIZATION_OPTIONS`	Region-Only	`{project_id}`.`region-{region}`.INFORMATION_SCHEMA.{view_name}<br>• Default option settings and audit history.
Insights & Recommendations	`RECOMMENDATIONS*`, `INSIGHTS`	Region-Only	`{project_id}`.`region-{region}`.INFORMATION_SCHEMA.{view_name}<br>• Slot rightsizing and partitioning recommendations.
Routines & Parameters	`ROUTINES`, `PARAMETERS`, `ROUTINE_OPTIONS`	Dual-Scoped	`{project_id}`.`region-{region}`.INFORMATION_SCHEMA.ROUTINES<br>OR<br> `{project_id}`.`{dataset_id}`.INFORMATION_SCHEMA.ROUTINES

5. Routines, Functions, Stored Procedures & ML Views

`INFORMATION_SCHEMA.ROUTINES`

High-Level Description

Defines user-defined functions (UDFs), stored procedures, remote functions, table functions (TVFs), parameter signatures, return types, determinism, and Cloud Function connection endpoints.

Required IAM Permissions & Predefined Roles

Requires bigquery.routines.get and bigquery.routines.list on the target dataset or project.
Predefined Roles: BigQuery Metadata Viewer (roles/bigquery.metadataViewer - Least Privilege), BigQuery Data Viewer (roles/bigquery.dataViewer), or BigQuery Admin (roles/bigquery.admin).

Column Name	Data Type	Physical Unit	Description
`specific_catalog`	`STRING`	Project ID	Project name.
`specific_schema`	`STRING`	Dataset ID	Dataset name.
`specific_name`	`STRING`	Routine ID	Unique routine identifier.
`routine_catalog`	`STRING`	Project ID	Catalog name.
`routine_schema`	`STRING`	Dataset ID	Schema name.
`routine_name`	`STRING`	Name	Function/procedure name.
`routine_type`	`STRING`	Enum	`'FUNCTION'`, `'PROCEDURE'`, `'TABLE FUNCTION'`.
`data_type`	`STRING`	SQL Type	Return data type (or `NULL` for procedures).
`routine_body`	`STRING`	Enum	`'SQL'` or `'EXTERNAL'`.
`routine_definition`	`STRING`	SQL Code	Routine body expression or JavaScript/Python function text.
`external_language`	`STRING`	Enum	`'JAVASCRIPT'`, `'PYTHON'`, `'SQL'`.
`is_deterministic`	`STRING`	`'YES'` / `'NO'`	Indicates whether identical inputs always return identical results.
`security_type`	`STRING`	Enum	Execution security context: `'DEFINER'` or `'INVOKER'`.
`created`	`TIMESTAMP`	UTC Timestamp	Creation timestamp.
`last_altered`	`TIMESTAMP`	UTC Timestamp	Last modification timestamp.
`ddl`	`STRING`	SQL String	DDL statement to recreate the routine.
`connection`	`STRING`	Resource Path	Cloud Resource connection path for BigQuery Remote Functions.

`INFORMATION_SCHEMA.PARAMETERS`

High-Level Description

Defines parameter signatures, modes, positions, and defaults for BigQuery routines.

Required IAM Permissions & Predefined Roles

Requires bigquery.routines.get and bigquery.routines.list on the target dataset or project.
Predefined Roles: BigQuery Metadata Viewer (roles/bigquery.metadataViewer - Least Privilege), BigQuery Data Viewer (roles/bigquery.dataViewer), or BigQuery Admin (roles/bigquery.admin).

Column Name	Data Type	Physical Unit	Description
`specific_catalog`	`STRING`	Project ID	Project name.
`specific_schema`	`STRING`	Dataset ID	Dataset name.
`specific_name`	`STRING`	Routine ID	Unique routine identifier.
`ordinal_position`	`INT64`	Position	1-indexed parameter position (0 = return value).
`parameter_mode`	`STRING`	Enum	`'IN'`, `'OUT'`, `'INOUT'`.
`is_result`	`STRING`	`'YES'` / `'NO'`	`'YES'` if row represents function return value.
`parameter_name`	`STRING`	Param Name	Parameter identifier.
`data_type`	`STRING`	SQL Type	GoogleSQL data type of parameter.
`parameter_default`	`STRING`	SQL Literal	Default value expression.
`is_aggregate`	`STRING`	`'YES'` / `'NO'`	Indicates aggregate parameter status.

`INFORMATION_SCHEMA.ROUTINE_OPTIONS`

High-Level Description

Lists routine-level configuration options defined in OPTIONS(...) clauses.

Required IAM Permissions & Predefined Roles

Requires bigquery.routines.get and bigquery.routines.list on the target dataset or project.
Predefined Roles: BigQuery Metadata Viewer (roles/bigquery.metadataViewer - Least Privilege), BigQuery Data Viewer (roles/bigquery.dataViewer), or BigQuery Admin (roles/bigquery.admin).

Column Name	Data Type	Physical Unit	Description
`specific_catalog`	`STRING`	Project ID	Project name.
`specific_schema`	`STRING`	Dataset ID	Dataset name.
`specific_name`	`STRING`	Routine ID	Unique routine identifier.
`option_name`	`STRING`	Option Name	Option key.
`option_type`	`STRING`	SQL Type	GoogleSQL type of option.
`option_value`	`STRING`	Option Value	Configured option value.

6. Streaming & Ingestion Views

`INFORMATION_SCHEMA.STREAMING_TIMELINE_BY_PROJECT` (and `_BY_ORGANIZATION`, `_BY_FOLDER`)

High-Level Description

Provides 1-minute discrete telemetry for real-time data ingestion via BigQuery Storage Write API and legacy streaming. Tracks ingested payloads, row counts, and streaming error rates.

Required IAM Permissions & Predefined Roles

Project-Level (Least Privilege): Requires bigquery.tables.list on the project. Granted by BigQuery Metadata Viewer (roles/bigquery.metadataViewer), BigQuery Data Viewer (roles/bigquery.dataViewer), or BigQuery Admin (roles/bigquery.admin).
_BY_FOLDER: Requires bigquery.tables.list on the parent folder.
_BY_ORGANIZATION: Requires bigquery.tables.list on the organization.

Column Name	Data Type	Physical Unit	Description & Conversion Formula
`dataset_id`	`STRING`	Dataset ID	Target dataset.
`error_code`	`STRING`	Error Code	Ingestion error classification code.
`folder_numbers`	`ARRAY<INT64>`	Array	Folder hierarchy IDs containing the project (only in `_BY_FOLDER`).
`project_id`	`STRING`	Project ID	Project receiving streamed rows.
`project_number`	`INT64`	Numeric ID	Numeric project identifier.
`start_timestamp`	`TIMESTAMP`	UTC Timestamp	1-minute discrete interval timestamp.
`table_id`	`STRING`	Table ID	Target table.
`total_input_bytes`	`INT64`	Bytes	Raw ingested byte payload.
`total_requests`	`INT64`	Count	Number of streaming append requests.
`total_rows`	`INT64`	Count	Total records ingested.

`INFORMATION_SCHEMA.WRITE_API_TIMELINE_BY_PROJECT` (and `_BY_ORGANIZATION`, `_BY_FOLDER`)

High-Level Description

Monitors BigQuery Storage Write API traffic, throughput, and committed vs. default stream modes.

Required IAM Permissions & Predefined Roles

Project-Level (Least Privilege): Requires bigquery.tables.list on the project. Granted by BigQuery Metadata Viewer (roles/bigquery.metadataViewer), BigQuery Data Viewer (roles/bigquery.dataViewer), or BigQuery Admin (roles/bigquery.admin).
_BY_FOLDER: Requires bigquery.tables.list on the parent folder.
_BY_ORGANIZATION: Requires bigquery.tables.list on the organization.

Column Name	Data Type	Physical Unit	Description
`dataset_id`	`STRING`	Dataset ID	Target dataset ID.
`error_code`	`STRING`	Error Code	Write API error code.
`folder_numbers`	`ARRAY<INT64>`	Array	Folder hierarchy IDs containing the project (only in `_BY_FOLDER`).
`project_id`	`STRING`	Project ID	Project containing the target tables.
`project_number`	`INT64`	Numeric ID	Numeric project identifier.
`start_timestamp`	`TIMESTAMP`	UTC Timestamp	1-minute discrete interval timestamp.
`stream_type`	`STRING`	Enum	`'COMMITTED'`, `'PENDING'`, `'BUFFERED'`, `'DEFAULT'`.
`table_id`	`STRING`	Table ID	Target table ID.
`total_input_bytes`	`INT64`	Bytes	Total bytes processed by the Storage Write API.
`total_requests`	`INT64`	Count	Number of append requests.
`total_rows`	`INT64`	Count	Total rows appended.

7. Search, Vector, AI Indexes & BI Engine Views

`INFORMATION_SCHEMA.SEARCH_INDEXES` (and `_OPTIONS`)

High-Level Description

Monitors BigQuery text Search Indexes, indexing coverage percentages, storage footprints, text analyzers, and unindexed row backlogs.

Required IAM Permissions & Predefined Roles

Dataset/Project Scope (Least Privilege): Requires bigquery.tables.get and bigquery.tables.list on the dataset or project. Granted by BigQuery Metadata Viewer (roles/bigquery.metadataViewer), BigQuery Data Viewer (roles/bigquery.dataViewer), or BigQuery Admin (roles/bigquery.admin).
_BY_ORGANIZATION: Requires bigquery.tables.get and bigquery.tables.list on the organization.

Column Name	Data Type	Physical Unit	Description
`analyzer`	`STRING`	Enum	Text analyzer: `'LOG_ANALYZER'`, `'NO_OP_ANALYZER'`, `'TEXT_ANALYZER'`.
`coverage_percentage`	`INT64`	Percent	Percentage of base table data currently indexed (0–100).
`creation_time`	`TIMESTAMP`	UTC Timestamp	Timestamp when index was created.
`ddl`	`STRING`	SQL String	DDL statement to recreate search index.
`disable_reason`	`STRING`	Reason String	Reason index was disabled.
`disable_time`	`TIMESTAMP`	UTC Timestamp	Timestamp when index was disabled.
`index_catalog`	`STRING`	Project ID	Project name.
`index_name`	`STRING`	Index Name	Search index name.
`index_schema`	`STRING`	Dataset ID	Dataset name.
`index_status`	`STRING`	Enum	`'ACTIVE'`, `'PENDING'`, `'STALE'`, `'DISABLED'`.
`last_index_alteration_info`	`RECORD`	Alteration Struct	Details of latest user-triggered index alteration (`status`, `message`, `new_coverage_percentage`, `start_time`, `end_time`, `ddl`).
`last_modification_time`	`TIMESTAMP`	UTC Timestamp	Last index modification timestamp.
`last_refresh_time`	`TIMESTAMP`	UTC Timestamp	Last completed index build timestamp.
`table_name`	`STRING`	Table ID	Base table identifier.
`total_logical_bytes`	`INT64`	Bytes	Logical storage consumed by search index structures.
`total_storage_bytes`	`INT64`	Bytes	Physical storage consumed by search index structures.
`unindexed_row_count`	`INT64`	Count	Number of base table rows not yet indexed.

`INFORMATION_SCHEMA.SEARCH_INDEX_COLUMNS`

High-Level Description

Defines columns participating in BigQuery text Search Indexes.

Required IAM Permissions & Predefined Roles

Requires bigquery.tables.get and bigquery.tables.list on the dataset or project.
Predefined Roles: BigQuery Metadata Viewer (roles/bigquery.metadataViewer - Least Privilege), BigQuery Data Viewer (roles/bigquery.dataViewer), or BigQuery Admin (roles/bigquery.admin).

Column Name	Data Type	Physical Unit	Description
`index_catalog`	`STRING`	Project ID	Project name.
`index_schema`	`STRING`	Dataset ID	Dataset name.
`table_name`	`STRING`	Table ID	Table name.
`index_name`	`STRING`	Index Name	Search index name.
`index_column_name`	`STRING`	Column Name	Name of indexed column.
`index_field_path`	`STRING`	Field Path	Field path for struct columns.

`INFORMATION_SCHEMA.VECTOR_INDEXES` (and `_OPTIONS`)

High-Level Description

Monitors Vector Indexes (e.g. IVF, HNSW, Tree-AH) for vector similarity search and embedding lookups (VECTOR_SEARCH).

Required IAM Permissions & Predefined Roles

Requires bigquery.tables.get and bigquery.tables.list on the target dataset or project.
Predefined Roles: BigQuery Metadata Viewer (roles/bigquery.metadataViewer - Least Privilege), BigQuery Data Viewer (roles/bigquery.dataViewer), or BigQuery Admin (roles/bigquery.admin).

Column Name	Data Type	Physical Unit	Description
`coverage_percentage`	`INT64`	Percent	Base table vector data indexing coverage percentage (0–100).
`creation_time`	`TIMESTAMP`	UTC Timestamp	Timestamp when vector index was created.
`ddl`	`STRING`	SQL String	DDL statement to recreate vector index.
`disable_reason`	`STRING`	Reason String	Reason index was disabled.
`disable_time`	`TIMESTAMP`	UTC Timestamp	Timestamp when index was disabled.
`index_catalog`	`STRING`	Project ID	Project name.
`index_name`	`STRING`	Index Name	Vector index name.
`index_schema`	`STRING`	Dataset ID	Dataset name.
`index_status`	`STRING`	Enum	`'ACTIVE'`, `'PENDING DISABLEMENT'`, `'TEMPORARILY DISABLED'`, `'PERMANENTLY DISABLED'`.
`last_index_alteration_info`	`RECORD`	Alteration Struct	Details of latest user-triggered index alteration (`status`, `message`, `new_coverage_percentage`, `start_time`, `end_time`, `ddl`).
`last_model_build_time`	`TIMESTAMP`	UTC Timestamp	Timestamp when index model build was initiated.
`last_modification_time`	`TIMESTAMP`	UTC Timestamp	Last index modification timestamp.
`last_refresh_time`	`TIMESTAMP`	UTC Timestamp	Timestamp when index weights were last updated.
`table_name`	`STRING`	Table ID	Base table name.
`total_logical_bytes`	`INT64`	Bytes	Logical index size.
`total_storage_bytes`	`INT64`	Bytes	Physical compressed index size.
`unindexed_row_count`	`INT64`	Count	Number of vectors pending indexing.

`INFORMATION_SCHEMA.VECTOR_INDEX_COLUMNS`

High-Level Description

Defines columns participating in BigQuery Vector Indexes.

Required IAM Permissions & Predefined Roles

Requires bigquery.tables.get and bigquery.tables.list on the target dataset or project.
Predefined Roles: BigQuery Metadata Viewer (roles/bigquery.metadataViewer - Least Privilege), BigQuery Data Viewer (roles/bigquery.dataViewer), or BigQuery Admin (roles/bigquery.admin).

Column Name	Data Type	Physical Unit	Description
`index_catalog`	`STRING`	Project ID	Project name.
`index_column_name`	`STRING`	Column Name	Vector embedding column name.
`index_field_path`	`STRING`	Field Path	Field path for struct columns.
`index_name`	`STRING`	Index Name	Vector index name.
`index_schema`	`STRING`	Dataset ID	Dataset name.
`table_name`	`STRING`	Table ID	Table name.

`INFORMATION_SCHEMA.BI_CAPACITIES` & `BI_CAPACITY_CHANGES`

High-Level Description

Tracks BigQuery BI Engine in-memory acceleration reservations, configured RAM capacities, and capacity alteration events.

Required IAM Permissions & Predefined Roles

Requires bigquery.bireservations.get on the project.
Predefined Roles: BigQuery Resource Viewer (roles/bigquery.resourceViewer), BigQuery Resource Admin (roles/bigquery.resourceAdmin), or BigQuery Admin (roles/bigquery.admin).

Column Name	Data Type	Physical Unit	Description
`bi_capacity_name`	`STRING`	Resource Path	BI Engine capacity identifier.
`preferred_tables`	`ARRAY<RECORD>`	Array	Pinned tables prioritized for memory caching.
`project_id`	`STRING`	Project ID	Project hosting the BI Engine capacity.
`project_number`	`INT64`	Numeric ID	Project number.
`size`	`INT64`	Bytes	Configured in-memory RAM capacity allocation.

8. Security, Access Control, Governance & Policy Views

`INFORMATION_SCHEMA.OBJECT_PRIVILEGES`

High-Level Description

Lists IAM permissions and role grants across datasets, tables, views, routines, and models.

Required IAM Permissions & Predefined Roles

Requires bigquery.datasets.getIamPolicy on datasets or bigquery.tables.getIamPolicy on tables.
Predefined Roles: BigQuery Data Owner (roles/bigquery.dataOwner), BigQuery Admin (roles/bigquery.admin), or Security Admin (roles/iam.securityAdmin).

Column Name	Data Type	Physical Unit	Description
`grantee`	`STRING`	Principal	Grantee identity (`'user:[email protected]'`, `'group:[email protected]'`, `'serviceAccount:[email protected]'`).
`object_catalog`	`STRING`	Project ID	Project containing the resource.
`object_name`	`STRING`	Resource Name	Name of table, view, or dataset.
`object_schema`	`STRING`	Dataset ID	Dataset containing the resource.
`object_type`	`STRING`	Enum	`'SCHEMA'`, `'TABLE'`, `'VIEW'`, `'ROUTINE'`, `'MODEL'`.
`privilege_type`	`STRING`	Role ID	IAM Role ID granted (e.g. `'roles/bigquery.dataViewer'`).

`INFORMATION_SCHEMA.ROW_ACCESS_POLICIES` & `ROW_ACCESS_POLICY_OPTIONS`

High-Level Description

Defines Row-Level Security (RLS) policies and filter predicates on base tables within a dataset.

Required IAM Permissions & Predefined Roles

Requires bigquery.rowAccessPolicies.getFilteredData or bigquery.rowAccessPolicies.getIamPolicy on the target table/dataset.
Predefined Roles: BigQuery Data Owner (roles/bigquery.dataOwner) or BigQuery Admin (roles/bigquery.admin).

Column Name	Data Type	Physical Unit	Description
`creation_time`	`TIMESTAMP`	UTC Timestamp	Timestamp when policy was created.
`filter_predicate`	`STRING`	SQL Boolean	GoogleSQL filter expression applied to restrict row visibility.
`last_modified_time`	`TIMESTAMP`	UTC Timestamp	Timestamp when filter predicate was modified.
`row_access_policy_name`	`STRING`	Policy Name	Unique RLS policy identifier.
`table_catalog`	`STRING`	Project ID	Project name.
`table_name`	`STRING`	Table ID	Table identifier.
`table_schema`	`STRING`	Dataset ID	Dataset identifier.

9. Recommendations & Insights Views

`INFORMATION_SCHEMA.RECOMMENDATIONS` (and `_BY_PROJECT`, `_BY_ORGANIZATION`)

High-Level Description

Surfaces automated BigQuery Recommender recommendations for cost savings, performance optimization, partition/cluster suggestions, and reservation rightsizing.

Required IAM Permissions & Predefined Roles

Project-Level (Least Privilege): Requires recommender.bigqueryCapacityCommitmentsRecommendations.get and recommender.bigqueryCapacityCommitmentsRecommendations.list on the project. Granted by Recommender Viewer (roles/recommender.viewer / roles/recommender.bigqueryViewer) or BigQuery Admin (roles/bigquery.admin).
_BY_ORGANIZATION: Requires recommender permissions at the organization level.

Column Name	Data Type	Physical Unit	Description
`additional_details`	`RECORD`	Struct	JSON details and recommended DDL/CLI operations (`operations.action`, `operations.path`, `operations.value`).
`associated_insight_ids`	`ARRAY<STRING>`	IDs	IDs of `INSIGHTS` supporting this recommendation.
`description`	`STRING`	Text	Human-readable recommendation text and rationale.
`last_updated_time`	`TIMESTAMP`	UTC Timestamp	Timestamp when recommendation was generated or refreshed.
`primary_impact`	`RECORD`	Struct	Cost, performance, or security impact (`category`, `cost_projection.duration_seconds`).
`priority`	`STRING`	Enum	`'P1'`, `'P2'`, `'P3'`, `'P4'`.
`project_id`	`STRING`	Project ID	Project ID.
`project_number`	`INT64`	Numeric ID	Project number.
`recommendation_id`	`STRING`	Base64 ID	Unique recommendation identifier.
`recommender`	`STRING`	String	Recommender type (e.g. `'google.bigquery.table.PartitionClusterRecommender'`).
`state`	`STRING`	Enum	`'ACTIVE'`, `'CLAIMED'`, `'SUCCEEDED'`, `'DISMISSED'`.
`subtype`	`STRING`	String	Subtype classification (e.g. `'PARTITION'`, `'CLUSTER'`).
`target_resources`	`ARRAY<STRING>`	Resource Paths	Fully qualified GCP resources affected by recommendation.

`INFORMATION_SCHEMA.INSIGHTS` (and `_BY_PROJECT`)

High-Level Description

Surfaces underlying workload signals, slot bottlenecks, table scan patterns, and stats that trigger recommender actions.

Required IAM Permissions & Predefined Roles

Project-Level (Least Privilege): Requires recommender.bigqueryCapacityCommitmentsInsights.get/list or recommender.bigqueryPartitionClusterInsights.get/list on the project. Granted by Recommender Viewer (roles/recommender.viewer / roles/recommender.bigqueryViewer) or BigQuery Admin (roles/bigquery.admin).
_BY_ORGANIZATION: Requires insight permissions at the organization level.

Column Name	Data Type	Physical Unit	Description
`additional_details`	`RECORD`	Struct	JSON details and observation period (`observation_period_seconds`).
`associated_recommendation_ids`	`ARRAY<STRING>`	IDs	Full recommendation names/IDs associated with this insight.
`category`	`STRING`	Enum	`'COST'`, `'PERFORMANCE'`, `'SECURITY'`.
`description`	`STRING`	Text	Description of observed performance signal.
`insight_id`	`STRING`	Base64 ID	Unique insight identifier.
`insight_type`	`STRING`	String	Insight type (e.g. `'google.bigquery.table.StatsInsight'`).
`last_updated_time`	`TIMESTAMP`	UTC Timestamp	Generation timestamp.
`project_id`	`STRING`	Project ID	Project ID.
`project_number`	`INT64`	Numeric ID	Project number.
`severity`	`STRING`	Enum	`'LOW'`, `'MEDIUM'`, `'HIGH'`, `'CRITICAL'`.
`state`	`STRING`	Enum	`'ACTIVE'`, `'ACCEPTED'`, `'DISMISSED'`.
`subtype`	`STRING`	String	Subtype classification (`'TABLE_STATS'`).
`target_resources`	`ARRAY<STRING>`	Resource Paths	Targeted GCP resources.

10. Project & Organization Configuration Views

`INFORMATION_SCHEMA.PROJECT_OPTIONS`

High-Level Description

Lists configured project-level default options (e.g. default time travel duration, KMS keys, default query priority, and default reservation assignments).

Required IAM Permissions & Predefined Roles

Requires bigquery.config.get on the project.
Predefined Roles: BigQuery Metadata Viewer (roles/bigquery.metadataViewer - Least Privilege), BigQuery Resource Viewer (roles/bigquery.resourceViewer), or BigQuery Admin (roles/bigquery.admin).

Column Name	Data Type	Physical Unit	Description
`project_number`	`INT64`	Numeric ID	Project number.
`project_id`	`STRING`	Project ID	Project identifier.
`option_name`	`STRING`	Option Name	Option identifier (e.g. `'default_time_travel_hours'`, `'default_query_job_timeout_ms'`).
`option_description`	`STRING`	Text	Description of the option's behavior.
`option_type`	`STRING`	SQL Type	GoogleSQL data type.
`option_value`	`STRING`	Value String	Configured parameter value.

`INFORMATION_SCHEMA.EFFECTIVE_PROJECT_OPTIONS`

High-Level Description

Lists effective project options accounting for organization and folder inheritance hierarchy.

Required IAM Permissions & Predefined Roles

Requires bigquery.config.get on the project.
Predefined Roles: BigQuery Metadata Viewer (roles/bigquery.metadataViewer - Least Privilege), BigQuery Resource Viewer (roles/bigquery.resourceViewer), or BigQuery Admin (roles/bigquery.admin).

Column Name	Data Type	Physical Unit	Description
`project_number`	`INT64`	Numeric ID	Project number.
`project_id`	`STRING`	Project ID	Project identifier.
`option_name`	`STRING`	Option Name	Option identifier.
`option_value`	`STRING`	Value String	Effective option value.
`option_set_level`	`STRING`	Enum	Definition level: `'DEFAULT'`, `'ORGANIZATION'`, `'FOLDER'`, `'PROJECT'`, `'USER'`.
`option_set_on_id`	`STRING`	Resource ID	GCP resource ID where the setting was overridden.

`INFORMATION_SCHEMA.ORGANIZATION_OPTIONS`

High-Level Description

Defines organization-level default configuration settings across BigQuery projects.

Required IAM Permissions & Predefined Roles

Requires bigquery.config.get on the organization.
Predefined Roles: BigQuery Admin (roles/bigquery.admin) on the organization resource.

Column Name	Data Type	Physical Unit	Description
`option_name`	`STRING`	Option Name	Organization setting name.
`option_description`	`STRING`	Text	Option description.
`option_type`	`STRING`	SQL Type	Option data type.
`option_value`	`STRING`	Value String	Configured organization-wide value.

`INFORMATION_SCHEMA.ORGANIZATION_OPTIONS_CHANGES`

High-Level Description

Maintains an audit log of organization-level setting updates.

Required IAM Permissions & Predefined Roles

Requires bigquery.config.get on the organization.
Predefined Roles: BigQuery Admin (roles/bigquery.admin) on the organization resource.

Column Name	Data Type	Physical Unit	Description
`project_id`	`STRING`	Project ID	Project where change originated.
`update_time`	`TIMESTAMP`	UTC Timestamp	Timestamp of option change.
`username`	`STRING`	User Identity	Identity of administrator who committed change.
`updated_options`	`JSON`	JSON Struct	JSON object containing old and new setting values.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs a command-line tool, Needs Node.js

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by

Google

Publisher

Google (Official)

Source

google/skills · skills/cloud/bigquery-observability · commit 2194d3b

Licence

Apache License 2.0 (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Google or Google.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download bigquery-observability.zip

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by Google

BigQuery Observability

Attribution

Tool Selection

Prerequisites & Environment Setup

Workflow

Best Practices for Writing INFORMATION_SCHEMA Queries

Qualification Syntax & Scope Matching

Principle of Least Privilege & Scope Selection

Execution Guardrails & Query Invariants

Domain References & SQL Queries

Telemetry Query Guides

Performance & Troubleshooting Guides

Schema Dictionaries (Column Definitions & Units)

Files

references/schema_others.md

BigQuery Platform, Governance & Ingestion INFORMATION_SCHEMA Reference

Table of Contents

View Scoping & Qualification Matrix

5. Routines, Functions, Stored Procedures & ML Views

INFORMATION_SCHEMA.ROUTINES

High-Level Description

Required IAM Permissions & Predefined Roles

INFORMATION_SCHEMA.PARAMETERS

High-Level Description

Required IAM Permissions & Predefined Roles

INFORMATION_SCHEMA.ROUTINE_OPTIONS

High-Level Description

Required IAM Permissions & Predefined Roles

6. Streaming & Ingestion Views

INFORMATION_SCHEMA.STREAMING_TIMELINE_BY_PROJECT (and _BY_ORGANIZATION, _BY_FOLDER)

High-Level Description

Required IAM Permissions & Predefined Roles

INFORMATION_SCHEMA.WRITE_API_TIMELINE_BY_PROJECT (and _BY_ORGANIZATION, _BY_FOLDER)

High-Level Description

Required IAM Permissions & Predefined Roles

7. Search, Vector, AI Indexes & BI Engine Views

INFORMATION_SCHEMA.SEARCH_INDEXES (and _OPTIONS)

High-Level Description

Required IAM Permissions & Predefined Roles

INFORMATION_SCHEMA.SEARCH_INDEX_COLUMNS

High-Level Description

Required IAM Permissions & Predefined Roles

INFORMATION_SCHEMA.VECTOR_INDEXES (and _OPTIONS)

High-Level Description

Required IAM Permissions & Predefined Roles

INFORMATION_SCHEMA.VECTOR_INDEX_COLUMNS

High-Level Description

Required IAM Permissions & Predefined Roles

INFORMATION_SCHEMA.BI_CAPACITIES & BI_CAPACITY_CHANGES

High-Level Description

Required IAM Permissions & Predefined Roles

8. Security, Access Control, Governance & Policy Views

INFORMATION_SCHEMA.OBJECT_PRIVILEGES

High-Level Description

Required IAM Permissions & Predefined Roles

INFORMATION_SCHEMA.ROW_ACCESS_POLICIES & ROW_ACCESS_POLICY_OPTIONS

High-Level Description

Required IAM Permissions & Predefined Roles

9. Recommendations & Insights Views

INFORMATION_SCHEMA.RECOMMENDATIONS (and _BY_PROJECT, _BY_ORGANIZATION)

High-Level Description

Required IAM Permissions & Predefined Roles

INFORMATION_SCHEMA.INSIGHTS (and _BY_PROJECT)

High-Level Description

Required IAM Permissions & Predefined Roles

10. Project & Organization Configuration Views

INFORMATION_SCHEMA.PROJECT_OPTIONS

High-Level Description

Required IAM Permissions & Predefined Roles

INFORMATION_SCHEMA.EFFECTIVE_PROJECT_OPTIONS

High-Level Description

Required IAM Permissions & Predefined Roles

Best Practices for Writing `INFORMATION_SCHEMA` Queries

`INFORMATION_SCHEMA.ROUTINES`

`INFORMATION_SCHEMA.PARAMETERS`

`INFORMATION_SCHEMA.ROUTINE_OPTIONS`

`INFORMATION_SCHEMA.STREAMING_TIMELINE_BY_PROJECT` (and `_BY_ORGANIZATION`, `_BY_FOLDER`)

`INFORMATION_SCHEMA.WRITE_API_TIMELINE_BY_PROJECT` (and `_BY_ORGANIZATION`, `_BY_FOLDER`)

`INFORMATION_SCHEMA.SEARCH_INDEXES` (and `_OPTIONS`)

`INFORMATION_SCHEMA.SEARCH_INDEX_COLUMNS`

`INFORMATION_SCHEMA.VECTOR_INDEXES` (and `_OPTIONS`)

`INFORMATION_SCHEMA.VECTOR_INDEX_COLUMNS`

`INFORMATION_SCHEMA.BI_CAPACITIES` & `BI_CAPACITY_CHANGES`

`INFORMATION_SCHEMA.OBJECT_PRIVILEGES`

`INFORMATION_SCHEMA.ROW_ACCESS_POLICIES` & `ROW_ACCESS_POLICY_OPTIONS`

`INFORMATION_SCHEMA.RECOMMENDATIONS` (and `_BY_PROJECT`, `_BY_ORGANIZATION`)

`INFORMATION_SCHEMA.INSIGHTS` (and `_BY_PROJECT`)

`INFORMATION_SCHEMA.PROJECT_OPTIONS`

`INFORMATION_SCHEMA.EFFECTIVE_PROJECT_OPTIONS`

`INFORMATION_SCHEMA.ORGANIZATION_OPTIONS`

`INFORMATION_SCHEMA.ORGANIZATION_OPTIONS_CHANGES`