--- title: Metrics and analytics description: Query R2 Data Catalog metrics for Iceberg REST API operations and table maintenance jobs via the GraphQL Analytics API. image: https://developers.cloudflare.com/dev-products-preview.png --- > Documentation Index > Fetch the complete documentation index at: https://developers.cloudflare.com/r2/llms.txt > Use this file to discover all available pages before exploring further. [Skip to content](#%5Ftop) # Metrics and analytics R2 Data Catalog exposes metrics that allow you to monitor Iceberg REST API requests and table maintenance jobs (compaction and snapshot expiration) across your warehouses. The metrics displayed in the Cloudflare dashboard are queried from Cloudflare's [GraphQL Analytics API](https://developers.cloudflare.com/analytics/graphql-api/). You can access the metrics [programmatically](#query-via-the-graphql-api) via GraphQL or any HTTP client. ## Metrics ### Data operations metrics R2 Data Catalog exports the below metrics within the `r2CatalogDataOperationsAdaptiveGroups` dataset. These metrics track Iceberg REST API requests made to your catalog, such as loading tables, listing namespaces, and committing updates. | Metric | GraphQL Field Name | Aggregation | Description | | ------------------ | ------------------ | ------------------- | ----------------------------------------- | | Request count | count | count | Total number of Iceberg REST API requests | | Request body bytes | requestBodyBytes | sum | Total bytes sent in request bodies | | Request duration | requestDurationMs | sum, avg, quantiles | Request duration in milliseconds | The `r2CatalogDataOperationsAdaptiveGroups` dataset provides the following dimensions for filtering and grouping queries: * `warehouseName` \- The name of the R2 Data Catalog warehouse * `operation` \- The Iceberg REST API operation name (for example, `load-table`, `list-namespaces`, `commit-table`) * `namespaceName` \- The Iceberg namespace targeted by the request, if applicable * `tableName` \- The Iceberg table targeted by the request, if applicable * `httpStatus` \- HTTP response status code * `datetime` \- Request timestamp * `date` \- Request timestamp, truncated to the start of a day * `datetimeHour` \- Request timestamp, truncated to the start of an hour * `datetimeMinute` \- Request timestamp, truncated to the start of a minute * `datetimeFiveMinutes` \- Request timestamp, truncated to the start of five minutes * `datetimeFifteenMinutes` \- Request timestamp, truncated to the start of fifteen minutes ### Table maintenance metrics R2 Data Catalog exports the below metrics within the `r2CatalogTableMaintenanceAdaptiveGroups` dataset. These metrics track table maintenance jobs including [compaction and snapshot expiration](https://developers.cloudflare.com/r2/data-catalog/table-maintenance/). | Metric | GraphQL Field Name | Aggregation | Description | | --------------- | ------------------ | ------------------- | ----------------------------------------------- | | Job count | count | count | Total number of maintenance jobs executed | | Files processed | filesProcessed | sum | Total input files processed by maintenance jobs | | Files output | filesOutput | sum | Total output files created by maintenance jobs | | Input bytes | inputBytes | sum | Total bytes read or scanned by maintenance jobs | | Output bytes | outputBytes | sum | Total bytes written by maintenance jobs | | Job duration | jobDurationMs | sum, avg, quantiles | Job duration in milliseconds | The `r2CatalogTableMaintenanceAdaptiveGroups` dataset provides the following dimensions for filtering and grouping queries: * `warehouseName` \- The name of the R2 Data Catalog warehouse * `jobType` \- The type of maintenance job (`compaction`, `snapshot-expiration`) * `namespaceName` \- The Iceberg namespace containing the table * `tableName` \- The Iceberg table that was maintained * `success` \- Whether the job succeeded (`1`) or failed (`0`) * `datetime` \- Job timestamp * `date` \- Job timestamp, truncated to the start of a day * `datetimeHour` \- Job timestamp, truncated to the start of an hour * `datetimeMinute` \- Job timestamp, truncated to the start of a minute * `datetimeFiveMinutes` \- Job timestamp, truncated to the start of five minutes * `datetimeFifteenMinutes` \- Job timestamp, truncated to the start of fifteen minutes ## Query via the GraphQL API You can programmatically query analytics for your R2 Data Catalog warehouses via the [GraphQL Analytics API](https://developers.cloudflare.com/analytics/graphql-api/). This API queries the same datasets as the Cloudflare dashboard and supports GraphQL [introspection](https://developers.cloudflare.com/analytics/graphql-api/features/discovery/introspection/). R2 Data Catalog GraphQL datasets require an `accountTag` filter with your Cloudflare account ID. ### Measure data operations over a time period This query returns the total number of Iceberg REST API requests and total request duration, grouped by operation, for a specific warehouse. ``` query CatalogDataOperations( $accountTag: String! $warehouseName: String! $datetimeStart: Time! $datetimeEnd: Time! ) { viewer { accounts(filter: { accountTag: $accountTag }) { r2CatalogDataOperationsAdaptiveGroups( limit: 10000 filter: { warehouseName: $warehouseName datetime_geq: $datetimeStart datetime_leq: $datetimeEnd } ) { count dimensions { operation } sum { requestBodyBytes requestDurationMs } avg { requestDurationMs } } } } } ``` ### Measure request latency percentiles This query returns request duration percentiles for a specific warehouse, which is useful for understanding latency distribution. ``` query CatalogLatencyPercentiles( $accountTag: String! $warehouseName: String! $datetimeStart: Time! $datetimeEnd: Time! ) { viewer { accounts(filter: { accountTag: $accountTag }) { r2CatalogDataOperationsAdaptiveGroups( limit: 10000 filter: { warehouseName: $warehouseName datetime_geq: $datetimeStart datetime_leq: $datetimeEnd } ) { count dimensions { operation } quantiles { requestDurationMsP50 requestDurationMsP90 requestDurationMsP99 } } } } } ``` ### Query table maintenance job metrics This query returns a summary of compaction and snapshot expiration jobs for a specific warehouse, including files processed, bytes read and written, and success or failure status. ``` query CatalogMaintenanceMetrics( $accountTag: String! $warehouseName: String! $datetimeStart: Time! $datetimeEnd: Time! ) { viewer { accounts(filter: { accountTag: $accountTag }) { r2CatalogTableMaintenanceAdaptiveGroups( limit: 10000 filter: { warehouseName: $warehouseName datetime_geq: $datetimeStart datetime_leq: $datetimeEnd } ) { count dimensions { jobType tableName success } sum { filesProcessed filesOutput inputBytes outputBytes jobDurationMs } } } } } ``` ### Filter by operation or table You can narrow results to a specific Iceberg operation or table. For example, to query only `load-table` operations for a specific table: ``` query CatalogFilterByOperation( $accountTag: String! $datetimeStart: Time! $datetimeEnd: Time! ) { viewer { accounts(filter: { accountTag: $accountTag }) { r2CatalogDataOperationsAdaptiveGroups( limit: 10000 filter: { warehouseName: "my-warehouse" operation: "load-table" tableName: "my_table" datetime_geq: $datetimeStart datetime_leq: $datetimeEnd } ) { count sum { requestDurationMs } } } } } ``` To query only failed maintenance jobs: ``` query CatalogFailedMaintenanceJobs( $accountTag: String! $datetimeStart: Time! $datetimeEnd: Time! ) { viewer { accounts(filter: { accountTag: $accountTag }) { r2CatalogTableMaintenanceAdaptiveGroups( limit: 10000 filter: { warehouseName: "my-warehouse" success: 0 datetime_geq: $datetimeStart datetime_leq: $datetimeEnd } ) { count dimensions { jobType tableName } } } } } ``` ### Query across all warehouses To query metrics across all warehouses on an account, omit the `warehouseName` filter and include `warehouseName` in the dimensions: ``` query CatalogAllWarehouses( $accountTag: String! $datetimeStart: Time! $datetimeEnd: Time! ) { viewer { accounts(filter: { accountTag: $accountTag }) { r2CatalogDataOperationsAdaptiveGroups( limit: 10000 filter: { datetime_geq: $datetimeStart, datetime_leq: $datetimeEnd } ) { count dimensions { warehouseName operation } sum { requestDurationMs } } } } } ``` ```json {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"item":{"@id":"/directory/","name":"Directory"}},{"@type":"ListItem","position":2,"item":{"@id":"/r2/","name":"R2"}},{"@type":"ListItem","position":3,"item":{"@id":"/r2/data-catalog/","name":"R2 Data Catalog"}},{"@type":"ListItem","position":4,"item":{"@id":"/r2/data-catalog/observability/","name":"Observability"}},{"@type":"ListItem","position":5,"item":{"@id":"/r2/data-catalog/observability/metrics/","name":"Metrics and analytics"}}]} ```