Abstract: A method for optimizing memory access for database operations is provided. The method may include performing a first database operation by at least executing a first instruction stream associated with the first database operation. The first database operation may be defined as a coroutine to at least enable the execution of the first instruction stream to be interleaved with an execution of a second instruction stream. In response to determining that data required to continue the execution of the first instruction stream is absent from a cache, the execution of the first instruction stream may be suspended and the second instruction stream may be executed instead. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: Techniques and solutions are provided for performing adaptive database table placement in a non-uniform memory access (NUMA) architecture. The adaptive table placement can occur in response to changing workloads on the NUMA nodes. For example, if a particular NUMA node is saturated, a database table may be moved from the memory of the saturated NUMA node to the memory of another NUMA node that is underutilized. In some cases, an entire database table is moved, while in other cases the database table is partitioned and only part of the table is moved.

Abstract: A method for optimizing memory access for database operations is provided. The method may include identifying an access pattern associated with a database operation. The access pattern may include data required to perform the database operation. One or more memory pages may be generated based at least on the access pattern. The one or more memory pages may include at least a portion of the data required to perform the database operation. The one or more memory pages including at least the portion of the data required to perform the database operation may be stored in a main memory. The database operation may be performed by at least loading, from the main memory and into a cache, the one or more memory pages including at least the portion of the data required to perform the database operation. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and underutilization of computing resources by monitoring and controlling the number of active worker threads. The number of active worker threads can be adapted to avoid underutilization of computing resources by giving the OS control of additional worker threads processing blocked application tasks. The task scheduler can dynamically determine a number of parallel operations for a particular task based on the number of available threads. The number of available worker threads can be determined based on the average availability of worker threads in the recent history of the application. Based on the number of available worker threads, the partitionable operation can be partitioned into a number of sub operations and executed in parallel.

Abstract: A method for optimizing memory access for database operations is provided. The method may include identifying an access pattern associated with a database operation. The access pattern may include data required to perform the database operation. One or more memory pages may be generated based at least on the access pattern. The one or more memory pages may include at least a portion of the data required to perform the database operation. The one or more memory pages including at least the portion of the data required to perform the database operation may be stored in a main memory. The database operation may be performed by at least loading, from the main memory and into a cache, the one or more memory pages including at least the portion of the data required to perform the database operation. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: A method for optimizing memory access for database operations is provided. The method may include performing a database operation by at least executing a first instruction stream associated with the first database operation. The first database operation may be defined as a coroutine to at least enable the execution of the first instruction stream to be interleaved with an execution of a second instruction stream. In response to determining that data required to continue the execution of the first instruction stream is absent from a cache, the execution of the first instruction may be suspended and the second instruction stream may be executed instead. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and underutilization of computing resources by monitoring and controlling the number of active worker threads. The number of active worker threads can be adapted to avoid underutilization of computing resources by giving the OS control of additional worker threads processing blocked application tasks. The task scheduler can dynamically determine a number of parallel operations for a particular task based on the number of available threads. The number of available worker threads can be determined based on the average availability of worker threads in the recent history of the application. Based on the number of available worker threads, the partitionable operation can be partitioned into a number of sub operations and executed in parallel.

Abstract: Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and underutilization of computing resources by monitoring and controlling the number of active worker threads. The number of active worker threads can be adapted to avoid underutilization of computing resources by giving the OS control of additional worker threads processing blocked application tasks. The task scheduler can dynamically determine a number of parallel operations for a particular task based on the number of available threads. The number of available worker threads can be determined based on the average availability of worker threads in the recent history of the application. Based on the number of available worker threads, the partitionable operation can be partitioned into a number of sub operations and executed in parallel.

Abstract: Techniques and solutions are provided for performing adaptive database table placement in a non-uniform memory access (NUMA) architecture. The adaptive table placement can occur in response to changing workloads on the NUMA nodes. For example, if a particular NUMA node is saturated, a database table may be moved from the memory of the saturated NUMA node to the memory of another NUMA node that is underutilized. In some cases, an entire database table is moved, while in other cases the database table is partitioned and only part of the table is moved.

Abstract: Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and underutilization of computing resources by monitoring and controlling the number of active worker threads. The number of active worker threads can be adapted to avoid underutilization of computing resources by giving the OS control of additional worker threads processing blocked application tasks. The task scheduler can dynamically determine a number of parallel operations for a particular task based on the number of available threads. The number of available worker threads can be determined based on the average availability of worker threads in the recent history of the application. Based on the number of available worker threads, the partitionable operation can be partitioned into a number of sub operations and executed in parallel.

Abstract: Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and underutilization of computing resources by monitoring and controlling the number of active worker threads. The number of active worker threads can be adapted to avoid underutilization of computing resources by giving the OS control of additional worker threads processing blocked application tasks. The task scheduler can dynamically determine a number of parallel operations for a particular task based on the number of available threads. The number of available worker threads can be determined based on the average availability of worker threads in the recent history of the application. Based on the number of available worker threads, the partitionable operation can be partitioned into a number of sub operations and executed in parallel.

Abstract: A database system maintains a feature set of a modern database system while operating directly on raw data files. Systems may use an adaptive indexing mechanism that maintains positional information to provide efficient access to raw data files, a flexible caching structure, and techniques for selective parsing and selective tokenizing. In doing so, possible performance bottlenecks associated with repeated parsing, tokenizing, and expensive data type conversion costs can be overcome.

Abstract: Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and underutilization of computing resources by monitoring and controlling the number of active worker threads. The number of active worker threads can be adapted to avoid underutilization of computing resources by giving the OS control of additional worker threads processing blocked application tasks. The task scheduler can dynamically determine a number of parallel operations for a particular task based on the number of available threads. The number of available worker threads can be determined based on the average availability of worker threads in the recent history of the application. Based on the number of available worker threads, the partitionable operation can be partitioned into a number of sub operations and executed in parallel.

Abstract: A database system maintains a feature set of a modern database system while operating directly on raw data files. Systems may use an adaptive indexing mechanism that maintains positional information to provide efficient access to raw data files, a flexible caching structure, and techniques for selective parsing and selective tokenizing. In doing so, possible performance bottlenecks associated with repeated parsing, tokenizing, and expensive data type conversion costs can be overcome.