Abstract: Each of one or more commit cycles may be associated with a predicted number of updates. A statistics collection time for a database table can be determined by estimating a sum of predicted updates included in one or more commit cycles. Whether the estimated sum of predicted updates is greater than a first threshold may be determined. In addition, a progress point for a first one of the commit cycles can be determined. A time to collect statistics may be selected based on the progress point of the first commit cycle.

Abstract: A structured query language (SQL) query is configured to present a selected portion of a result set to a user interface. The selected portion of the result set can be based on an offset criteria appended to the SQL query. The offset criteria determines a location of a first presented instance of the selected portion of the result set. The offset criteria is configured to determine the location of the first presented instance of the selected portion of the result set independent of a number of instances appearing between a first instance of the result set and the first presented instance of the selected portion of the result set.

Abstract: Techniques for streamlined commit procedures between synchronized nodes are provided. A request to commit a transaction is transmitted from a first node, where the request instructs a second node to retain any locks related to the transaction. A response is received, from the second node, indicating that the transaction was successfully committed. Upon receiving the response, the transaction is committed on the first node. Upon successfully committing the transaction on the first node, first cleanup request is transmitted to the second node, where the cleanup request instructs the second node to release any locks related to the transaction.

Abstract: A blockchain configuration may require constant and large amounts of resources to maintain a growing structure. One example method of operation may include receiving blockchain transactions and creating a blockchain block, identifying miner devices to process the blockchain block, identifying expenses associated with each of the miner devices, selecting an optimal cost miner device among the miner devices based on the identified expenses associated with each of the miner devices, and assigning the optimal cost miner device to solve the blockchain block.

Abstract: Each of one or more commit cycles may be associated with a predicted number of updates. A statistics collection time for a database table can be determined by estimating a sum of predicted updates included in one or more commit cycles. Whether the estimated sum of predicted updates is greater than a first threshold may be determined. In addition, a progress point for a first one of the commit cycles can be determined. A time to collect statistics may be selected based on the progress point of the first commit cycle.

Abstract: Systems and methods for providing automatic fork protection including determining that a transaction having fork protection was included in a first block that was appended to a blockchain, that a hash of the first block was validated, that a consensus decision was made by validator nodes approving the first block for addition to the blockchain, that a second block was appended to the blockchain after the first block, that the second block comprises a hash that is not based on the first block, that the first block was on a first fork and the second block was on a second fork, that the blockchain was resolved in favor of the second fork, and that the transaction failed as a result of the blockchain being resolved in favor of the second fork. The method including compensating a party that submitted the failed transaction based on the fork protection.

Abstract: A computer-implemented method for determining a query execution plan based on transaction state may include determining that a first set of database values in a database table are in a committed transaction state and that a second set of database values in the database table are in an uncommitted transaction state. In response to the determining, the first set of database values may have a first set of statistics generated and the second set of database values may have a second set of statistics generated. The first and second set of statistics may be for use in determining a query execution plan.

Abstract: Techniques for streamlined commit procedures between synchronized nodes are provided. A request to commit a transaction is transmitted from a first node, where the request instructs a second node to retain any locks related to the transaction. A response is received, from the second node, indicating that the transaction was successfully committed. Upon receiving the response, the transaction is committed on the first node. Upon successfully committing the transaction on the first node, first cleanup request is transmitted to the second node, where the cleanup request instructs the second node to release any locks related to the transaction.

Abstract: A journal optimizer in a computer database system with an adaptive journal mechanism. The adaptive journal mechanism dynamically adjusts adaptive parameters of the journal optimizer to optimize the journal based on one or more journal conditions to more efficiently utilize system resources. The adaptive parameters used to adapt the optimization include aggressiveness parameters and the location of the optimizer, where the aggressiveness parameters specify the intensity of optimization of the journal by the journal optimizer. For example, the adaptive journal mechanism may dynamically adjust an adaptive parameter of the optimizer to increase optimization of the journal when the resource utilization indicates the resources are underutilized and decrease optimization of the journal when the resource utilization indicates resources are strained.

Abstract: A journal optimizer in a computer database system with an adaptive journal mechanism. The adaptive journal mechanism dynamically adjusts adaptive parameters of the journal optimizer to optimize the journal based on one or more journal conditions to more efficiently utilize system resources. The adaptive parameters used to adapt the optimization include aggressiveness parameters and the location of the optimizer, where the aggressiveness parameters specify the intensity of optimization of the journal by the journal optimizer. For example, the adaptive journal mechanism may dynamically adjust an adaptive parameter of the optimizer to increase optimization of the journal when the resource utilization indicates the resources are underutilized and decrease optimization of the journal when the resource utilization indicates resources are strained.

Abstract: A structured query language (SQL) query is configured to present a selected portion of a result set to a user interface. The selected portion of the result set can be based on an offset criteria appended to the SQL query. The offset criteria determines a location of a first presented instance of the selected portion of the result set. The offset criteria is configured to determine the location of the first presented instance of the selected portion of the result set independent of a number of instances appearing between a first instance of the result set and the first presented instance of the selected portion of the result set.

Abstract: A structured query language (SQL) query is configured to present a selected portion of a result set to a user interface. The selected portion of the result set can be based on an offset criteria appended to the SQL query. The offset criteria determines a location of a first presented instance of the selected portion of the result set. The offset criteria is configured to determine the location of the first presented instance of the selected portion of the result set independent of a number of instances appearing between a first instance of the result set and the first presented instance of the selected portion of the result set.

Abstract: Aggregating database entry modifications for replay of database changes includes: inserting, in a journal modification table, of database entry modifications, where each database entry is associated with a relative record number; and, for each relative record number: aggregating, in the journal modification table, a plurality of the modifications into a single modification.

Abstract: Aggregating database entry modifications for replay of database changes includes: inserting, in a journal modification table, of database entry modifications, where each database entry is associated with a relative record number; and, for each relative record number: aggregating, in the journal modification table, a plurality of the modifications into a single modification.

Abstract: Each of one or more commit cycles may be associated with a predicted number of updates. A statistics collection time for a database table can be determined by estimating a sum of predicted updates included in one or more commit cycles. Whether the estimated sum of predicted updates is greater than a first threshold may be determined. In addition, a progress point for a first one of the commit cycles can be determined. A time to collect statistics may be selected based on the progress point of the first commit cycle.

Abstract: Each of one or more commit cycles may be associated with a predicted number of updates. A statistics collection time for a database table can be determined by estimating a sum of predicted updates included in one or more commit cycles. Whether the estimated sum of predicted updates is greater than a first threshold may be determined. In addition, a progress point for a first one of the commit cycles can be determined. A time to collect statistics may be selected based on the progress point of the first commit cycle.

Abstract: Each of one or more commit cycles may be associated with a predicted number of updates. A statistics collection time for a database table can be determined by estimating a sum of predicted updates included in one or more commit cycles. Whether the estimated sum of predicted updates is greater than a first threshold may be determined. In addition, a progress point for a first one of the commit cycles can be determined. A time to collect statistics may be selected based on the progress point of the first commit cycle.

Abstract: Each of one or more commit cycles may be associated with a predicted number of updates. A statistics collection time for a database table can be determined by estimating a sum of predicted updates included in one or more commit cycles. Whether the estimated sum of predicted updates is greater than a first threshold may be determined. In addition, a progress point for a first one of the commit cycles can be determined. A time to collect statistics may be selected based on the progress point of the first commit cycle.

Abstract: Systems and methods for providing automatic fork protection including determining that a transaction having fork protection was included in a first block that was appended to a blockchain, that a hash of the first block was validated, that a consensus decision was made by validator nodes approving the first block for addition to the blockchain, that a second block was appended to the blockchain after the first block, that the second block comprises a hash that is not based on the first block, that the first block was on a first fork and the second block was on a second fork, that the blockchain was resolved in favor of the second fork, and that the transaction failed as a result of the blockchain being resolved in favor of the second fork. The method including compensating a party that submitted the failed transaction based on the fork protection.

Abstract: A first database management system (DBMS) running on first computer having a first set of computing resources determines that with respect to the first set of computing resources a first query access plan for executing a query satisfies a set of query optimization criteria. A determination is then made that with respect to a second set of computing resources the first query access plan fails a set of preliminary criteria. In response to this failure determination, a second query access plan for executing the query is generated. Prior to having a second DBMS running on a second computer having the second set of computing resources receive a request to execute the query, a determination is made that with respect to the second set of computing resources the second query access plan satisfies the set query optimization criteria.