Abstract: Some embodiments provide a program that receives a first set of data and a first greenhouse gas emission value. The program stores, in a cache, the first set of data and the first greenhouse gas emission value. The program receives a second set of data and a second greenhouse gas emission value. The program stores, in the cache, the second set of data and the second greenhouse gas emission value. The program receives a third set of data and a third greenhouse gas emission value. The program determines one of the first and second sets of data to remove from the cache based on the first and second greenhouse gas emission values. The program replaces, in the cache, one of the first and second sets of data and the corresponding first or second greenhouse gas emission value with the third set of data and the third greenhouse gas emission value.

Abstract: A computing system that determines employee and organizational compliance includes one or more databases that store organizational data and one or more processors to execute instructions to perform various operations.

Abstract: An Artificial Intelligence (AI)-based data processing system processes current data to determine if the quality of the current data is adequate to be provided to data consumers and if the quality is adequate, the current data is further analyzed to determine if an impacted load including changes to dimension data of the current data or an incremental load including changes to fact data of the current data is to be provided to the data consumers. Depending on the amount of data to be provided to the data consumers, processing units (PUs) may be determined and assigned to carry out the data upload. Various machine learning (ML) models that are used to provide predictions from the current data are analyzed to determine the quality of predictions and if needed, can be automatically retrained by the data processing system.

Abstract: According to some embodiments, a system, method and non-transitory, computer readable medium are provided comprising a memory storing processor-executable program code; and a processing unit to cause the system to: receive a range of persistent volume disk size values from a cloud service provider; receive a value for an upper bound of a number of persistent volume disks attachable to a virtual machine per the cloud service; determine a number of persistent volume disks based on the upper bound, wherein the number is at least two; generate a plurality of configurations of the determined number of persistent volume disks, wherein a configuration is provided for each persistent volume disk size value, and each configuration divides the persistent volume disk size value between two or more persistent volume disks; and aggregate the generated plurality of configurations in a decision table. Numerous other aspects are provided.

Abstract: A computing system that determines employee and organizational compliance includes one or more databases that store organizational data and one or more processors to execute instructions to perform various operations.

Abstract: A method and a system for providing one or more services to one or more user devices in an IoT network in a scalable M2M (Machine to Machine) framework. The method comprises receiving a connection request from the one or more user devices [202] at a load balance of the IoT network, the connection request comprises at least a username comprising a cluster identifier. The load balancer [204] determines a cluster identifier based on the connection request and identifies at least one target cluster from the one or more clusters [206], said target cluster being associated with the identifier cluster identifier. The load balancer [204] routes the connection request to the at least one target cluster to provide the one or more services to the one or more user devices [202].

Abstract: Some embodiments provide a program that receives a first set of data and a first greenhouse gas emission value. The program stores, in a cache, the first set of data and the first greenhouse gas emission value. The program receives a second set of data and a second greenhouse gas emission value. The program stores, in the cache, the second set of data and the second greenhouse gas emission value. The program receives a third set of data and a third greenhouse gas emission value. The program determines one of the first and second sets of data to remove from the cache based on the first and second greenhouse gas emission values. The program replaces, in the cache, one of the first and second sets of data and the corresponding first or second greenhouse gas emission value with the third set of data and the third greenhouse gas emission value.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program observes a parameter associated with a computing system. Upon receiving a change associated with the parameter, the program further determines a routine definition from a set of routine definitions associated with the parameter. Each routine definition in the set of routine definitions specifies a set of instructions associated with a particular parameter associated with the computing system. The program also executes the set of instructions specified in the determined routine definition.

Abstract: A method and a system for providing one or more services to one or more user devices [202] in an IoT network in a scalable M2M (Machine to Machine) framework. The method comprises receiving a connection request from the one or more user devices [202] at a load balance of the IoT network, the connection request comprises at least a username comprising a cluster identifier. The load balancer [204] determines a cluster identifier based on the connection request and identifies at least one target cluster from the one or more clusters [206], said target cluster being associated with the identifier cluster identifier. The load balancer [204] routes the connection request to the at least one target cluster to provide the one or more services to the one or more user devices [202].

Abstract: Disclosed herein are system, method, and computer program product embodiments for adaptive caching for hybrid columnar databases with heterogeneous page sizes. An embodiment operates by scanning one or more pools comprising one or more pages of the same size in a buffer cache. The embodiment determines an increment of a reuse rate for the pools in the buffer cache within a time interval. The embodiment determines a cumulative reuse rate that is the sum of the increments of the reuse rate over several time intervals. The embodiment determines a gliding average reuse rate of the cumulative reuse rate over several time intervals. The embodiment compares the average reuse rates of the plurality of the pools to a threshold to dynamically determine whether a pool should reuse memory from the existing pages of the same pool or rebalance memory from one or more victim pools.

Abstract: Disclosed herein are system, method, and computer program product embodiments for adaptive caching for hybrid columnar databases with heterogeneous page sizes. An embodiment operates by receiving a request to load a new page of memory from a disk in a buffer cache. The embodiment scans one or more pools comprising one or more pages of the same size in a buffer cache. The embodiment determines an increment of a reuse rate for the pools in the buffer cache within a time interval. The embodiment determines a cumulative reuse rate that is the sum of the increments of the reuse rate over several time intervals. The embodiment determines a gliding average reuse rate of the cumulative reuse rate over several time intervals. The embodiment compares the average reuse rates of the plurality of the pools to a threshold to dynamically determine whether a pool should reuse memory from the existing pages of the same pool or rebalance memory from one or more victim pools.

Abstract: A method and a system for providing one or more services to one or more user devices [202] in an IoT network in a scalable M2M (Machine to Machine) framework. The method comprises receiving a connection request from the one or more user devices [202] at a load balance of the IoT network, the connection request comprises at least a username comprising a cluster identifier. The load balancer [204] determines a cluster identifier based on the connection request and identifies at least one target cluster from the one or more clusters [206], said target cluster being associated with the identifier cluster identifier. The load balancer [204] routes the connection request to the at least one target cluster to provide the one or more services to the one or more user devices [202].

Abstract: A database system provides a non-volatile cache memory layer for caching pages for a set of database from the database system. The non-volatile cache memory layer may include a non-volatile cache for caching pages for a database from the set of database on the database system. The non-volatile cache may be configured through invoking a configuring stored procedure persistent on the database system. A request is received at the non-volatile cache memory layer for performing an operation on a page from the database on the database system. Based on the received request and an identification of the page, a caching operation is performed on the non-volatile cache memory layer. The caching operation is associated with the request. Data associated with the requested operation on the page is stored and organized on the NV cache memory layer.

Abstract: A system, a microfluidic chip and a method are provided for counting desired cells in a body fluid that allows for a reasonable range of error in exchange for fast and cheap diagnosis. The fluid containing the cells to be measured is immobilized on a microfluidic chip and stained and the cell count is determined from optical signals that measure the amount of stain acquired by the immobilized cells.

Abstract: A database system provides a non-volatile cache memory layer for caching pages for a set of database from the database system. The non-volatile cache memory layer may include a non-volatile cache for caching pages for a database from the set of database on the database system. The non-volatile cache may be configured through invoking a configuring stored procedure persistent on the database system. A request is received at the non-volatile cache memory layer for performing an operation on a page from the database on the database system. Based on the received request and an identification of the page, a caching operation is performed on the non-volatile cache memory layer. The caching operation is associated with the request. Data associated with the requested operation on the page is stored and organized on the NV cache memory layer.