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.

Abstract: A computer-implemented method for reusing deleted database records includes, receiving, by a database manager executing within a computing device, a first query request to insert, into a database table, a first set of database records. The database manager identifies a first set of entries within a journal log bundle. The database manager also determines, in response to identifying a first set of entries, that there is a third set of deleted database records located on a same page as a second set of database records. The database manager also, in response to determining that there is a third set of deleted database records located on a same page as the second set of database records, inserts into the database table the first set of database records using the third set of deleted database records.

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: 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: 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: 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: 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 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: A computer-implemented method for reusing deleted database records includes, receiving, by a database manager executing within a computing device, a first query request to insert, into a database table, a first set of database records. The database manager identifies a first set of entries within a journal log bundle. The database manager also determines, in response to identifying a first set of entries, that there is a third set of deleted database records located on a same page as a second set of database records. The database manager also, in response to determining that there is a third set of deleted database records located on a same page as the second set of database records, inserts into the database table the first set of database records using the third set of deleted database records.

Abstract: A database management system (DBMS) runs on scalable production system. The DBMS includes a first operating mode, wherein the scalable production system runs on a first set of computing resources, and a second operating mode, wherein the scalable production system runs on a second set of computing resources. The DBMS in the first mode determines that with respect to the first set of resources a first query access plan for executing a query satisfies optimization criteria. A determination is made that with respect to the second set of resources the first plan fails preliminary criteria. In response to this failure determination, a second query access plan for executing the query is generated. Prior to having the DBMS receive a request to execute the query while in the second mode, a determination is made that with respect to the second set of resources the second plan satisfies the optimization criteria.

Abstract: A database management system (DBMS) runs on scalable production system. The DBMS includes a first operating mode, wherein the scalable production system runs on a first set of computing resources, and a second operating mode, wherein the scalable production system runs on a second set of computing resources. The DBMS in the first mode determines that with respect to the first set of resources a first query access plan for executing a query satisfies optimization criteria. A determination is made that with respect to the second set of resources the first plan fails preliminary criteria. In response to this failure determination, a second query access plan for executing the query is generated. Prior to having the DBMS receive a request to execute the query while in the second mode, a determination is made that with respect to the second set of resources the second plan satisfies the optimization criteria.

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: 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: 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: 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 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: 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: 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.