Abstract: A computer implemented system and method allow database performance testing and improvement. The method comprises using a database system (DBS) for embedding a virtual resource simulation system (VRSS) into a node of the DBS, loading a new configuration parameter of a database into the VRSS, receiving, by the VRSS from the DBS, an action control block (ACB), and dynamically activating and assigning a service task by a service task dispatcher of the VRSS to process the ACB. The method further comprises simulating a process of database execution based on a content of the ACB by creating a limited database internal data structure that is based on the ACB and the new configuration parameter, and manipulating the limited database internal structure to produce a simulation result. The method further comprises utilizing a metric associated with the simulation result of the new configuration parameter in the simulated process of database execution.

Abstract: In an approach for improving performance of a batch job running on database servers in an active-active architecture. A processor, responsive to a batch job being ready to be executed on a source database server, sends a first communication to a target database server with a synchronization start point. While executing the batch job, a processor utilizes a pre-lock function, pre-load function, and lock avoidance function to prevent lock conflicts. A processor, responsive to either the source database server or the target database server encountering a commit statement, suspends the respective database server and sends a second communication to ask if the other respective database server is ready to complete the commit statement. A processor, responsive to the other respective database server confirming its ready to complete the commit statement, completes the commit statement on both the source database server and the target database server.

Abstract: A computer-implemented method provides application-based query transformations. The method includes determining an application is initiated. The method includes identifying a set of execution units included in the application. The execution units are based on of a set of queries in the application and a set of actions in the application. The method also includes building a query dependency graph (QDG) comprising a plurality of nodes, wherein each node of the plurality of nodes is correlated to an execution unit, and each node is linked to at least one additional node, the link indicating a relative execution order and a common attribute each node and the additional node. The method includes merging, based on a performance architecture, two or more of the set of execution units into a section. The method includes processing the application according to the QDG.

Abstract: A computer-implemented method to estimate computing cost of database queries. The method includes receiving a query. The method also includes generating one or more access plans for the query. The method further includes dynamically generating a learning model based on each of the generated access plans. The method includes estimating, by the learning model and for each of the one or more access plans, a predicted cost to execute the query. The method includes selecting, based on the predicted cost, a first access path associated with a lowest cost of the predicted costs and executing the query according the selected access path.

Abstract: A computer-implemented method for managing an index table associated with a data table includes obtaining an index entry associated with a key in the data table. The computer-implemented method further includes determining whether an index page associated with the index entry is in a buffer pool, wherein the buffer pool includes a plurality of index pages loaded from the index table and at least one temp index. The computer-implemented method further includes adding, in response to determining that the index page associated with the index entry is not in the buffer pool, the index entry into the at least one temp index. The computer-implemented method further includes consolidating the at least one temp index into the index table.

Abstract: An approach is provided for optimizing a database buffer pool. Based on statistics about read and write operations in a range of pages, the range of pages is determined to be a candidate for a hot read range for which locks and latches are avoided in processing operations in the hot read range. Using an on-time trigger or pre-trigger process, the hot read range is created from the range of pages by marking start and end points in the range of pages. Write operation(s) are determined to be included in the hot read range by marking an object control block. The write operation(s) are added to a write pending list. The read operations in the hot read range are performed without a latch or lock. The write operation(s) are merged from the write pending list to the range of pages and the write operation(s) are performed.

Abstract: Database log writing is based on log pipeline contention. A determination is made as to whether contention in writing data to a log pipeline, which is used in writing data from memory to storage, is at a prespecified level. Based on determining that the contention in writing the data to the log pipeline is at the prespecified level, a split operation is automatically performed to create a new log pipeline.

Abstract: Trace processing in a database system is facilitated by obtaining database trace data collected from database tracing a database system, and data analyzing, by one or more processors, the database trace data to determine one or more field-related rules to, in part, reduce impact on system performance of database tracing in the database system. Trace processing is further facilitated by applying the one or more field-related rules to a database trace in the database system to adjust trace fields of the database trace according to the one or more field-related rules, thereby reducing impact on system performance of the database trace in the database system.

Abstract: An approach is provided for automatically updating a data type of a database column. Based on a database definition, category, and usage, the column is determined to be a candidate for a data type change. For first values in the column values, costs of processing queries using a new data type are determined to be less than other costs of processing the queries using other data types. For exception value(s) in the column values, costs of processing the queries using the original data type are determined to be less than other costs of processing the queries using other data types. The original data type is replaced with the new data type for the first values and the original data type is retained for the exception value(s). The first values are associated with a first schema and the exception value(s) are associated with a second schema.

Abstract: A method, system, and computer program product for recommending an initial database security model. The method may include identifying a plurality of nodes connected to a security network. The method may also include analyzing security characteristics of each node of the plurality of nodes. The method may also include identifying, from the security characteristics, key factors for each node. The method may also include calculating similarities between each node of the plurality of nodes. The method may also include building a self-organized centerless network across the plurality of nodes by grouping nodes with high similarities based on the similarities between each node, where the self-organized centerless network is a centerless network without a central management server, and includes groups of nodes from the plurality of nodes. The method may also include generating federated security models for the groups of nodes.

Abstract: Trace processing in a database system is facilitated by obtaining database trace data collected from database tracing a database system, and data analyzing, by one or more processors, the database trace data to determine one or more field-related rules to, in part, reduce impact on system performance of database tracing in the database system. Trace processing is further facilitated by applying the one or more field-related rules to a database trace in the database system to adjust trace fields of the database trace according to the one or more field-related rules, thereby reducing impact on system performance of the database trace in the database system.

Abstract: Database recovery is based on workload priorities. A database workload is divided into a plurality of workload groups. A workload group of the plurality of workload groups is selected for recovery, in which the selecting is based on a priority of the workload group. One or more recovery actions are performed for the workload group selected for recovery.

Abstract: Systems and methods for pre-allocating and utilizing storage space in a relational database are provided. In embodiments a method includes: obtaining transaction data including data regarding record insertions in a relational database, wherein each record of the record insertions is associated with a key value; identifying a type of each of the record insertions as either a random insertion type or a key range insertion type based on the database transaction data, wherein the random insertion type comprises records associated with respective key values inserted in a random order, and the key range insert type comprises records associated with a range of key values inserted within a certain time period; predicting a new range of key values associated with future record insertions based on the type of each of the record insertions; and pre-allocating page space in one or more pages of the relational database for the future record insertions.

Abstract: A simulated dataset is queried for regression by validating a structured query language (SQL) statement, determining a pattern type of the SQL statement, reconstructing the SQL statement according to a predetermined process for the pattern type, creating a mutated SQL statement for querying a simulated dataset, and validating the mutated SQL statement. The simulated dataset is based on a confidential dataset having the confidential elements removed or replaced.

Abstract: Leveraging the competence of a computing cluster and a storage cluster by dynamically adjusting an SQL (structured query language) execution path to optimize system performance with fast response time under a distributed relational database on a data storage platform. Also, endpoint devices are divided into groups for the purpose of responding to queries and/or query blocks. The most suitable group of endpoint devices is chosen to respond to a given query or query block.

Abstract: A computer-implemented method selects an access path for high cost and/or complex queries. The method includes building a classification model configured to identify a lowest cost access path. The method further includes receiving a query, where the query is configured to retrieve a set of data from a database. The method also includes generating an access map for the query, where the access map includes one or more potential access paths to execute the query. The method includes collecting, for the query, a set of data for each potential access path. The method further includes classifying, by the classification model, the query. The method also includes selecting a first access path of the one or more potential access paths and executing the query.

Abstract: In a computer-implemented method for improving performance of a database optimizer, a processor calculates a first execution time for a database query executing through a first access path of a database system. A processor generates a second access path. A processor determines a second execution time via a simulation of the database query through the second access path. A processor determines that the second execution time is less than the first execution time. A processor, responsive to determining that the second execution time is less than the first execution time, sends the second access path to the database optimizer.

Abstract: A computer-implemented method to estimate an execution time for large query batches. The method includes identifying a batch of queries, where the batch of queries where each query is configured to retrieve data from a database. Selecting a first query and generating an access path for the first query including one or more mini plans. Building a learning model for the one or more mini plans. Estimating an estimated execution time for each of the one or more mini plans. Adding each of the estimated execution times for each of the one or more mini plans to determine a first total estimated time for the first query. Displaying the first total estimated time.

Abstract: Leveraging the competence of a computing cluster and a storage cluster by dynamically adjusting an SQL (structured query language) execution path to optimize system performance with fast response time under a distributed relational database on a data storage platform. Also, endpoint devices are divided into groups for the purpose of responding to queries and/or query blocks. The most suitable group of endpoint devices is chosen to respond to a given query or query block.

Abstract: A method of managing a storage system comprises detecting a reference to a first page in the storage system. The method also comprises creating a first candidate block for the first page based on the detecting. The first candidate block may comprise a continuous series of pages that begins with the first page. The method also comprises monitoring subsequent references to pages within the first candidate block. The method also comprises determining that the first candidate block meets a first set of hot-block requirements. The method also comprises relocating the first candidate block to a hot-block space in a buffer pool based on the determining, resulting in a first hot block.