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Schema: aptos.stats Table: ez_core_metrics_hourly Type: View

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What

A convenience table that aggregates block and transaction related metrics using various aggregate functions such as SUM, COUNT, MIN and MAX from the fact_transactions table, on an hourly basis. Stats for the current hour will be updated as new data arrives.

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Columns

Column NameData TypeDescription
BLOCK_TIMESTAMP_HOURTIMESTAMP_NTZThe hour of the timestamp of the block.
BLOCK_NUMBER_MINFLOATThe minimum block number in the hour.
BLOCK_NUMBER_MAXFLOATThe maximum block number in the hour.
BLOCK_COUNTNUMBERThe number of blocks in the hour.
TRANSACTION_COUNTNUMBERThe number of transactions in the hour.
TRANSACTION_COUNT_SUCCESSNUMBERThe number of successful transactions in the hour.
TRANSACTION_COUNT_FAILEDNUMBERThe number of failed transactions in the hour.
UNIQUE_SENDER_COUNTNUMBERThe number of unique sender address in the hour.
UNIQUE_PAYLOAD_FUNCTION_COUNTNUMBERThe number of unique payload functions in the hour.
TOTAL_FEES_NATIVENUMBERThe sum of all fees in the hour, in the native fee currency.
TOTAL_FEES_USDFLOATThe sum of all fees in the hour, in USD.
EZ_CORE_METRICS_HOURLY_IDTEXTThe unique primary key identifier for each row in the table, ensuring data integrity and uniqueness. Data type: String Example: 0x1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef Business Context: Essential for data integrity and unique row identification. Critical for join operations and data relationship management. Enables precise data retrieval and referential integrity maintenance.
INSERTED_TIMESTAMPTIMESTAMP_NTZThe UTC timestamp when the row was inserted into the table, representing when the data was first recorded. Data type: Timestamp Example: 2024-01-15 14:30:25.123456 Business Context: Essential for data lineage tracking and insertion timing analysis. Critical for understanding data freshness and processing delays. Enables data quality analysis and processing performance monitoring.
MODIFIED_TIMESTAMPTIMESTAMP_NTZThe UTC timestamp when the row was last modified, representing when the data was most recently updated. Data type: Timestamp Example: 2024-01-15 14:30:25.123456 Business Context: Essential for data freshness analysis and update tracking. Critical for understanding data modification patterns and change frequency. Enables data quality monitoring and update performance analysis.