Abstract: A distributed storage system includes table controllers collectively storing partitions of a logical table having multiple rows. For each of the partitions, a corresponding table controller stores a subset of the rows of the logical table across individual pages. A management controller updates a schema of the logical table from a first to a second schema definition by, for each of the partitions, sending an update command indicating the second schema definition to the corresponding table controller. The first table controller corresponds to a first partition that includes a first subset of the rows. The first table controller, prior to receiving the update command, includes an identifier of the first schema definition within each page of data for the first subset. Subsequent to receiving the update command, the first table controller, when writing each new page of data for the first subset, includes an identifier of the second schema definition.

Abstract: Methods and systems for addressing malfunction of a medical imaging device are disclosed. The method includes classifying a type of an image artifact in a medical image acquired by the medical imaging device by using a trained machine learning model. The method also includes analyzing system data associated with acquisition of the medical image to identify one or more system parameters that might have contributed to the type of image artifact and providing an action for addressing the image artifact based on the identified one or more system parameters.

Abstract: An execution environment in a computer system provides dynamic data and compute resources elasticity for user code to improve execution efficiency. The execution environment translates the user code into a runtime agnostic representation with a set of tasks. For each task, the execution environment determines a level of concurrency for executing the task based on the size of the set of input data for the task, the amount of compute resources available at the time of invocation of the task, and any context-sensitive heuristics provided by the user code.

Abstract: An execution environment in a computer system supports a declarative programming model where user code is written with a query syntax in a native programming language to express inherent parallelism in terms of data flow. The execution environment translates queries in the user code into a runtime agnostic representation and dynamically selects an execution runtime for executing the runtime agnostic representation.

Abstract: Functionality is described for providing a compiled program that can be executed in a parallel and a distributed manner by any selected runtime environment. The functionality includes a compiler module for producing the compiled program based on a dataflow representation of a program (i.e., a dataflow-expressed program). The dataflow-expressed program, in turn, includes a plurality of tasks that are connected together in a manner specified by a graph (such as a directed acyclic graph). The compiler module also involves performing static type-checking on the dataflow-expressed program to identify the presence of any mismatch errors in the dataflow-expressed program. By virtue of this approach, the above-described functionality can identify any errors in constructing the graph prior to its instantiation and execution in a runtime environment.

Abstract: Methods, systems, apparatuses, and computer program products are provided that enable immediate access to data associated with a source blob. The foregoing is achieved by creating a copy-on-read blob based on the source blob and a link blob based on the copy-on-read blob for each virtual machine to be deployed. When creating the copy-on-read blob, the source blob is not copied. Instead, data from the source blob is copied to the copy-on-read blob upon request by a virtual machine. Subsequent requests for that data are retrieved from the copy-on-read blob. Each link blob stores write data provided by its corresponding virtual machine. When a virtual machine requests data, its corresponding link blob is checked for the data. If the data is not stored therein, the copy-on-read blob is checked for the data. If the copy-on-read blob does not store the data, the data is retrieved from the source blob.

Abstract: Data is replicated between primary and secondary storage systems using a data pulling process or a log shipping process. If data is to be replicated through the log shipping process, a transaction and its associated data get stored in a transaction log in the secondary storage system. Subsequently, when the transaction gets executed, actual data gets persisted from the transaction log to a data log in the secondary storage system. If the data is to be replicated through the data pulling process, the transaction is stored in the transaction log. However, the associated data for the transaction is retrieved from the first primary storage system and stored directly in the data log in the secondary system.

Abstract: Methods for dequeue optimizations in queues are performed by systems and apparatuses. The methods optimize dequeue operations using aggregation of expired messages enqueued in a queue and conditional iteration over enqueued messages based on the aggregation to service dequeue commands. Queues utilize page hierarchies such as root pages, index pages, and data pages. The aggregation of expired messages for pages in the queue determines the latest expired time for messages for a given page, and these latest expired times are stored in their respective pages, including data pages, index pages, and root pages, for use in the conditional iteration. The conditional iteration bypasses pages for which a latest expired time for all messages is prior to the current time when servicing dequeue requests for the queue.

Abstract: Methods, systems, apparatuses, and computer program products are provided that enable immediate access to data associated with a source blob. The foregoing is achieved by creating a copy-on-read blob based on the source blob and a link blob based on the copy-on-read blob for each virtual machine to be deployed. When creating the copy-on-read blob, the source blob is not copied. Instead, data from the source blob is copied to the copy-on-read blob upon request by a virtual machine. Subsequent requests for that data are retrieved from the copy-on-read blob. Each link blob stores write data provided by its corresponding virtual machine. When a virtual machine requests data, its corresponding link blob is checked for the data. If the data is not stored therein, the copy-on-read blob is checked for the data. If the copy-on-read blob does not store the data, the data is retrieved from the source blob.

Abstract: In various embodiments, methods and systems for implementing hash-based partitioning in distributed computing systems are provided. At a high level, a distributed computing system having an underlying range-based partitioning architecture for storage may be configured as a hash-based partitioning system, for example, a hybrid range-hash table storage. An operations engine of the hash-based partitioning system receives a tenant request to provision input/output operations per second (IOPS). The tenant request comprises a requested number of IOPS. Based on the tenant request, a provisioning operation to provision IOPS in a hybrid range-hash table storage with hash-based partitioning is determined. The provisioning operation is selected from one of the following: a table creation provisioning operation, an IOPS increase provisioning operation, and an IOPS decrease provisioning operation. The selected provisioning operation is executed for a corresponding table.

Abstract: Methods, systems, apparatuses, and computer program products are provided that enable immediate access to data associated with a source blob. The foregoing is achieved by creating a copy-on-read blob based on the source blob and a link blob based on the copy-on-read blob for each virtual machine to be deployed. When creating the copy-on-read blob, the source blob is not copied. Instead, data from the source blob is copied to the copy-on-read blob upon request by a virtual machine. Subsequent requests for that data are retrieved from the copy-on-read blob. Each link blob stores write data provided by its corresponding virtual machine. When a virtual machine requests data, its corresponding link blob is checked for the data. If the data is not stored therein, the copy-on-read blob is checked for the data. If the copy-on-read blob does not store the data, the data is retrieved from the source blob.

Abstract: Various methods and systems for implementing request scheduling and processing in a multi-tenant distributed computing environment are provided. Requests to utilize system resources in the distributed computing environment are stored in account queues corresponding to tenant accounts. If storing a request in an account queue would exceed a throttling threshold such as a limit on the number of requests stored per account, the request is dropped to a throttling queue. A scheduler prioritizes processing requests stored in the processing queue before processing requests stored in the account queues. The account queues can be drained using dominant resource scheduling. In some embodiments, a request is not picked up from an account queue if processing the request would exceed a predefined hard limit on system resource utilization for the corresponding tenant account. In some embodiments, the hard limit is defined as a percentage of threads the system has to process requests.

Abstract: Methods for dequeue optimizations in queues are performed by systems and apparatuses. The methods optimize dequeue operations using aggregation of expired messages enqueued in a queue and conditional iteration over enqueued messages based on the aggregation to service dequeue commands. Queues utilize page hierarchies such as root pages, index pages, and data pages. The aggregation of expired messages for pages in the queue determines the latest expired time for messages for a given page, and these latest expired times are stored in their respective pages, including data pages, index pages, and root pages, for use in the conditional iteration. The conditional iteration bypasses pages for which a latest expired time for all messages is prior to the current time when servicing dequeue requests for the queue.

Abstract: A snapshot of data from a table associated with a particular user may be generated. Tree data structures that are distributed across multiple computer systems may be accessed. Each of the tree structures may include data associated with one or more users. At least one tree data structure of the tree data structures that includes data associated with the particular user of the one or more users may be identified. The at least one tree data structure may then be filtered. Filtering may comprise identifying only data that is associated with the particular user. A snapshot of the data associated with the particular user may be generated. Generating the snapshot of the data associated with the particular user comprises generating a data structure that is configured to map to each data page of the at least one tree data structure that includes data associated with the particular user.

Abstract: Embodiments provide a method to collect aggregate information or usage data quickly and efficiently with minimal lag. Additionally, the system can use this aggregate information internally for improved load balancing, better data placement, optimization, and enhanced debugging. The system can quickly look at aggregate information across a huge amount of data and drill down cheaply because the aggregate information is generated using existing processes. Aggregated statistics storage and collection may be built on top of an LSM tree used to store a persistent index for a cloud storage system. The statistics may also represent the result of an operation (e.g., max, min, sum, average) on selected parameter(s) or attribute(s) of stored data. Aggregate statistics values may be efficiently maintained during index merge and garbage collection processes or any other index management. As delta LSM trees are merged into a base LSM tree, the aggregates are updated in delta fashion.

Abstract: Functionality is described for providing a compiled program that can be executed in a parallel and a distributed manner by any selected runtime environment. The functionality includes a compiler module for producing the compiled program based on a dataflow representation of a program (i.e., a dataflow-expressed program). The dataflow-expressed program, in turn, includes a plurality of tasks that are connected together in a manner specified by a graph (such as a directed acyclic graph). The compiler module also involves performing static type-checking on the dataflow-expressed program to identify the presence of any mismatch errors in the dataflow-expressed program. By virtue of this approach, the above-described functionality can identify any errors in constructing the graph prior to its instantiation and execution in a runtime environment.

Abstract: Functionality is described for providing a compiled program that can be executed in a parallel and a distributed manner by any selected runtime environment. The functionality includes a compiler module for producing the compiled program based on a dataflow representation of a program (i.e., a dataflow-expressed program). The dataflow-expressed program, in turn, includes a plurality of tasks that are connected together in a manner specified by a graph (such as a directed acyclic graph). The compiler module also involves performing static type-checking on the dataflow-expressed program to identify the presence of any mismatch errors in the dataflow-expressed program. By virtue of this approach, the above-described functionality can identify any errors in constructing the graph prior to its instantiation and execution in a runtime environment.

Abstract: In various embodiments, methods and systems for implementing multiple transaction logs in a distributed storage system are provided. A log stream component detects performance metrics of a plurality of log streams. The performance metrics are associated with requests from partitions in the distributed storage system. A transaction component receives a request to execute a transaction using a log stream. The request is received from a partition of the distributed storage system. The performance metrics of the plurality of log streams can be referenced, where the performance metrics indicate a performance capacity of a selected log stream to process the request. A log stream for executing the transaction is determined based on the performance capacity. The log stream selected can also factor request attributes of the request. The transaction component communicates the request to be executed, using the log stream to perform the transaction.

Abstract: An execution environment in a computer system provides dynamic data and compute resources elasticity for user code to improve execution efficiency. The execution environment translates the user code into a runtime agnostic representation with a set of tasks. For each task, the execution environment determines a level of concurrency for executing the task based on the size of the set of input data for the task, the amount of compute resources available at the time of invocation of the task, and any context-sensitive heuristics provided by the user code.

Abstract: An execution environment in a computer system supports a declarative programming model where user code is written with a query syntax in a native programming language to express inherent parallelism in terms of data flow. The execution environment translates queries in the user code into a runtime agnostic representation and dynamically selects an execution runtime for executing the runtime agnostic representation.