Abstract: A computer-implemented method dynamically switches access plans for a query during concurrent query execution. The method includes receiving a first query configured to be processed by a database system. The method also includes generating, for the first query, an access plan for each of identified resource sets. The method includes determining a first set of available resources that represent an available capacity for the database system. The method further includes selecting a first resource set of the one or more resource sets, where the selecting is based on the first set of available resources being closest to the first resource set. The method also includes selecting, based on the first set of available resources, a first access plan of the one or more access plans. The method includes executing the first query and returning results of the first query to a source of the first query.

Abstract: This disclosure provides a method, a computing system, and a computer program product for managing prefetching of pages in a database system. The method comprises obtaining shared information associated with page access, wherein the shared information associated with the page access includes information associated with the page access from a plurality of computing nodes. The method further comprises determining whether to prefetch a number of pages into a global buffer pool based at least on the shared information associated with the page access using a sequential prefetching method.

Abstract: A computer implemented method processes a query. A number of processor units processes the query to identify a result set in response to receiving the query from a first client. The number of processor units stores, the result set in a shared cache assigned to a group of clients, wherein result set stored in the shared cache is accessible by the group of clients. The number of processor units returns the result set to a second client in the group of clients from the shared cache in response to receiving the query from the second client in the group of clients.

Abstract: Computer technology for retrieving data stored in a table that includes the following computer operations: receiving, from persistent storage of a computer, an original Index Tree data structure; storing, in volatile memory, a memory-based Index Tree data structure based on the original Index Tree data structure, with the memory-based Index Tree data structure including: a root node, a set of hierarchically arranged intermediate layer(s) with each intermediate layer including a plurality of non-leaf nodes, and a leaf layer including a plurality of leaf nodes; and retrieving data from a table in a database, with the retrieval including traversing the memory-based Index Tree data structure through a plurality of child lock pointers to locate pages including the data to be retrieved from the table.

Abstract: An embodiment for analyzing and tracking data flow to determine proper schemas for unstructured data. The embodiment may automatically use a sidecar to collect schema discovery rules during conversion of raw data to unstructured data. The embodiment may automatically generate multiple schemas for different tenants using the collected schema discovery rules. The embodiment may automatically use ETL to export unstructured data to SQL databases with the generated multiple schemas for the different tenants. The embodiment may automatically monitor usage data of the SQL databases and collect the usage data. The embodiment may automatically optimize schema discovery using the collected usage data. The embodiment may automatically discover schemas with hot usage and apply the discovered schemas with hot usage to other tenants for consumption and further monitoring.

Abstract: A computer-implemented method, system and computer program product for scaling a resource of a Database as a Service (DBaaS) cluster in a cloud platform. User service requests from a service cluster to be processed by the DBaaS cluster are received. A first set of tracing data is generated by a service mesh, which facilitates service-to-service communication between the service cluster and the DBaaS cluster, from the user service requests. A second set of tracing data is generated by the DBaaS cluster from handling the user service requests. A dependency tree is then generated to discover application relationships to identify potential bottlenecks in nodes of the DBaaS cluster based on these sets of tracing data. The pod(s) of a DBaaS node are then scaled based on the dependency tree, which is used in part, to predict the utilization of the resources of the DBaaS node identified as being a potential bottleneck.

Abstract: This disclosure provides a computer-implemented method, a computer system and a computer program product for database compression oriented to combinations of fields of a database record. One or more combinations of fields of a record of a database are determined that satisfy a frequency criterion indicating that access frequencies of the one or more combinations of fields are higher than an access frequency threshold. The record is reorganized based on the one or more combinations of fields to store fields of each combination of the one or more combinations of fields in a respective contiguous storage space. The reorganized record is compressed by applying a compression scheme to the one or more combinations of fields.

Abstract: A computer-implemented method that includes receiving an ingestion request to ingest data to a database comprising physical shards and detecting that the ingestion request is directed to a first hotspot shard. The first hotspot shard has a contention level over a threshold value. The method also detects context characteristics within the data and generates a first virtual shard based on a first virtual shard key selected from the detected context characteristics. The first virtual shard virtually duplicates at least a portion of the first hotspot shard. The method also includes ingesting the data to the first virtual shard.

Abstract: A method, computer system, and a computer program product is provided for computer log management. In one embodiment, in response to receiving a log request from a user, an input content is analyzed and adjusted according to input contents and user's previous activities. A similarity analysis and a fairness analysis is performed to determine similarities between the input content, as adjusted, and a plurality of log records in an object library. The similarity analysis includes analyzing any patterns and attributes. The attributes have a dimension, and each dimension has a predefined weight (W). The fairness analysis ensures that one type of log is not favored over others. A best possible match is then determined, and one or more logs are presented to the user providing the best possible match.

Abstract: One or more computer processors generate a debug chain from one or more similar resource bound breakpoints, wherein the debug chain provides dynamic code flow. The one or more computer processors distribute the generated debug chain to one or more tenants.

Abstract: A disclosed database system and enhanced methods implement enhanced mini-plans and dynamically changing a query mini-plan with trustworthy Artificial Intelligence (AI) to improve query execution performance in a database system. An AI cost model evaluates candidate mini-plans for executing a query. AI truth monitors evaluate the execution of the mini-plans, such as predicted input factors and adjusted mini-plans of one or more AI running data models. The AI truth monitors provide feedback to adjust the AI cost model based on evaluating the execution of the mini-plans. The AI truth monitors validate adjusted mini-plans, provide feedback to the AI cost model with improved overall prediction accuracy, and enhanced mini-plans to gain query performance.

Abstract: Disclosed are techniques for relational database locks based on columns. Database transactions may be targeted to specific columns of one or more records, instead of the entire row for those records, using primary keys. Column locks on specific keys are stored separately than column locks on ranges of keys, which are both checked when requesting a new column lock for either a single key or a range of keys. When a threshold number of columns for a given record, or range of records/keys, have been locked, the column locks for that record, or range of records, can be combined into a single row level lock to reduce resource costs for maintaining multiple concurrent locks.

Abstract: An embodiment includes generating a partition schema for a distributed database based on historical usage data indicative of usage of the distributed database, where the generating of the partition schema comprises determining a partition range of a partition of the partition schema. The embodiment also includes generating a node identifier for the partition using a hash function and a first weight value assigned to the partition. The embodiment also includes monitoring performance data indicative of a performance of the distributed database, the monitoring comprising detecting a failure of the performance to satisfy a performance threshold. The embodiment also includes initiating, responsive to detecting the failure, a redistribution procedure by changing the node identifier of the partition by replacing the first weight value with a second weight value.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include training a model. The operations may include enhancing the model with reinforcement learning and improving stability of the model with a graph neural network model. The operations may include predicting, with the model, a resource cost of a node and deploying the node.

Abstract: A computer-implemented method for performing an operation in a tree structure is provided according to embodiments of the present disclosure. In the computer-implemented method, an operation to be performed in a tree structure may be received. The tree structure may comprise a plurality of non-leaf nodes and a plurality of leaf nodes. The operation may be associated with a record comprising a pair of key and value. One of the non-leaf nodes may be determined based on the key of the record. Then, the operation may be performed in the determined non-leaf node.

Abstract: Provided are techniques for building and using a sparse Time Series Database (TSDB). Time series records are received from a native TSDB, where each of the time series records includes a timestamp and one or more tags. Timeslots are determined for shards for the sparse TSDB based on the timestamp included in each of the time series records. The sparse TSDB is built by creating the shards for the determined timeslots and storing the time series records in the shards, while filling in empty ranges in the shards. A query that specifies at least one of the one or more tags is received. It is determined whether to execute the query against the sparse TSDB, and, in response to a determination to execute the query against the sparse TSDB, the query is executed against the sparse TSDB to generate results that are returned.

Abstract: A system, program product, and method for enhancing automatic multidimensional query processing. The method includes executing a database query including semi-joining a plurality of dimension tables with a fact table. The method also includes identifying for extraction one or more data values from each dimension table of the plurality of dimension tables. The data values from each dimension table of the plurality of dimension tables are associated with a respective record identification (RID), thereby defining one or more RIDs. The method further includes generating a plurality of RID lists. Each RID list of the plurality of RID lists includes a collection of the one or more RIDs for the respective dimension table. The method also includes merging the plurality of RID lists, sorting, subject to the merging, the plurality of RIDs as a function of data location, and fetching the data values from the fact table.

Abstract: This disclosure provides a method, a computing system, and a computer program product for managing prefetching of pages in a database system. The method comprises obtaining shared information associated with page access, wherein the shared information associated with the page access includes information associated with the page access from a plurality of computing nodes. The method further comprises determining whether to prefetch a number of pages into a global buffer pool based at least on the shared information associated with the page access using a sequential prefetching method.

Abstract: In a computer-implemented method for improving performance of a database, a processor receives batch jobs for a relational database. The batch jobs may include a first member with a first buffer pool, and a second member with a second buffer pool. The processor may also identify a first actual object and an isolation level for the batch jobs, generate related queries based on the first actual object and the isolation level, calculate a cost for the first member and the second member to run the batch jobs based on the related queries, and assign the batch jobs to the first member based on a lower calculated cost.

Abstract: A processor may allocate a first buffer segment from a buffer pool. The first buffer segment may be configured with a first contiguous range of memory for a first data partition of a data table. The first data partition comprising a first plurality of data blocks. A processor may store the first plurality of data blocks in order into the first buffer segment. A processor may retrieve the target data block from the first buffer segment in response to a data access request for a target data block of the first plurality of data blocks.