Skip to main content
Schema: aptos.core Table: fact_transactions_state_checkpoint Type: View

ā€‹
Description

This table contains StateCheckpoint transactions from the Aptos blockchain, which are special system transactions appended at the end of each block to serve as checkpoint milestones. These transactions provide critical state verification data including state checkpoint hashes, accumulator root hashes, and event root hashes that enable the blockchain to maintain data integrity and support efficient state synchronization. StateCheckpoint transactions are essential for the blockchainā€™s consensus mechanism and enable nodes to verify the integrity of the blockchain state at regular intervals.

ā€‹
Key Use Cases

  • Blockchain state integrity verification and checkpoint analysis
  • State synchronization monitoring and node health assessment
  • Consensus mechanism analysis and state verification tracking
  • Block finality analysis and state checkpoint milestone monitoring
  • Network security analysis and state tampering detection
  • State recovery and synchronization efficiency analysis

ā€‹
Important Relationships

  • Provides state verification context for transaction analysis in core.fact_transactions
  • Links to block data in core.fact_blocks for comprehensive block analysis
  • Supports consensus analysis and state integrity verification
  • Enables checkpoint-based analysis across all core models
  • Provides infrastructure context for network security monitoring

ā€‹
Commonly-used Fields

  • block_number: Primary identifier for linking to block-level analysis
  • state_checkpoint_hash: Essential for state integrity verification and checkpoint analysis
  • accumulator_root_hash: Critical for state accumulator verification and data integrity
  • event_root_hash: Important for event tree verification and event integrity
  • vm_status: Transaction execution status for checkpoint health monitoring
  • block_timestamp: Primary field for time-series analysis of checkpoint activity

ā€‹
Columns

Column NameData TypeDescription
BLOCK_NUMBERVARIANTAlso known as block height. The block number indicates the position of a block in the blockchain, increasing sequentially after the addition of each new block.
Data type: Integer Example:
  • 12345678
  • 98765432
Business Context:
  • Primary identifier for ordering and filtering blockchain data chronologically.
  • Essential for block-level analysis and network growth tracking.
  • Enables correlation of transactions, transfers, and events to specific blocks. | | BLOCK_TIMESTAMP | TIMESTAMP_NTZ | The date and time at which the block was produced on the Aptos blockchain.
Data type: Timestamp Example:
  • 2024-01-15 14:30:25.123456
Business Context:
  • Primary field for time-series analysis and temporal filtering of blockchain activity.
  • Essential for trend analysis, volume calculations, and historical comparisons.
  • Enables time-based grouping and aggregation for analytics and reporting. | | VERSION | NUMBER | The version number, also known as the height, represents the sequential position of a transaction in the Aptos blockchain. The first transaction has a version of 0, and each subsequent transaction increments by 1.
Data type: Integer Example:
  • 0 (genesis transaction)
  • 12345678
  • 98765432
Business Context:
  • Unique identifier for ordering transactions chronologically across the entire blockchain.
  • Essential for transaction sequencing and version-based analysis.
  • Enables precise transaction tracking and blockchain state verification. | | TX_HASH | TEXT | Transaction hash is a unique 66-character identifier that is generated when a transaction is executed on the Aptos blockchain.
Data type: String Example:
  • 0x1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef
Business Context:
  • Primary identifier for linking transaction data across all related tables.
  • Essential for transaction verification and blockchain explorer lookups.
  • Enables correlation of transfers, events, and state changes to specific transactions. | | SUCCESS | BOOLEAN | The boolean value indicating whether the transaction was successfully executed on the Aptos blockchain.
Data type: Boolean Example:
  • true (transaction succeeded)
  • false (transaction failed)
Business Context:
  • Essential for filtering successful transactions and analyzing failure rates.
  • Critical for accurate volume calculations and user experience analysis.
  • Enables debugging and error pattern recognition in transaction analysis. | | TX_TYPE | TEXT | The type of transaction executed on the Aptos blockchain, categorizing transactions by their purpose and origin.
Data type: String Example:
  • user_transaction (regular user-initiated transactions)
  • block_metadata_transaction (system transactions for block metadata)
  • state_checkpoint_transaction (system transactions for state checkpoints)
Business Context:
  • Essential for filtering and categorizing different types of blockchain activity.
  • Critical for separating user activity from system operations in analytics.
  • Enables focused analysis on specific transaction categories and use cases. | | VM_STATUS | TEXT | The execution status of a transaction as reported by the Aptos Virtual Machine (VM), providing success confirmation or failure details.
Data type: String Example:
  • Executed successfully
  • OUT_OF_GAS
  • INSUFFICIENT_BALANCE
  • INVALID_ARGUMENT
Business Context:
  • Essential for transaction success rate analysis and failure investigation.
  • Critical for debugging transaction issues and understanding failure patterns.
  • Enables user experience analysis and error pattern recognition. | | STATE_CHECKPOINT_HASH | TEXT | The cryptographic hash of the state checkpoint, providing verification of the blockchain state at a specific point in time.
Data type: String Example:
  • 0x1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef
Business Context:
  • Essential for state checkpoint verification and integrity validation.
  • Critical for blockchain state consistency and checkpoint tracking.
  • Enables checkpoint analytics and state integrity reporting. | | ACCUMULATOR_ROOT_HASH | TEXT | The root hash of the Merkle accumulator, providing cryptographic proof of the blockchainā€™s state at a given point.
Data type: String Example:
  • 0x1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef
Business Context:
  • Essential for blockchain state verification and integrity validation.
  • Critical for consensus mechanism analysis and state synchronization.
  • Enables verification of blockchain state consistency and security. | | EVENT_ROOT_HASH | TEXT | The root hash of the event tree, providing cryptographic proof of all events emitted in the transaction.
Data type: String Example:
  • 0x1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef
Business Context:
  • Essential for event verification and integrity validation.
  • Critical for event-driven analytics and event correlation analysis.
  • Enables verification of event consistency and security. | | FACT_TRANSACTIONS_STATE_CHECKPOINT_ID | TEXT | The 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_TIMESTAMP | TIMESTAMP_NTZ | The 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_TIMESTAMP | TIMESTAMP_NTZ | The 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. |