TL;DR: Database System Implementation focuses on the implementation of database systems, including storage structures, query processing, and transaction management, and provides extensive coverage of query processing.
Abstract: From the Publisher:
Three well-known computer scientists at Stanford University-Hector Garcia-Molina, Jeffrey D. Ullman, and Jennifer Widom-have written one of the most comprehensive books on database system implementation. Hector Garcia- Molina pioneered this book at Stanford as a second database systems course for computer science majors and industry-based professionals. It focuses on the implementation of database systems, including storage structures, query processing, and transaction management. Database System Implementation is valuable as an academic textbook or a professional reference.
Noteworthy Features
Provides extensive coverage of query processing, including major algorithms for execution of queries and techniques for optimizing queries
Covers information integration, including warehousing and mediators, OLAP, and data-cube systems
Explains error-correction in RAID disks and covers bitmap indexes, data mining, data statistics, and pointer swizzling
Supports additional teaching materials found on the book's Web page at ...
TL;DR: The In-Memory PoInter Chasing Accelerator (IMPICA), which leverages the logic layer within 3D-stacked memory for linked data structure traversal and addresses the key challenges of how to achieve high parallelism in the presence of serial accesses in pointer chasing, and how to effectively perform virtual-to-physical address translation on the memory side without requiring expensive accesses to the CPU's memory management unit.
Abstract: Pointer chasing is a fundamental operation, used by many important data-intensive applications (e.g., databases, key-value stores, graph processing workloads) to traverse linked data structures. This operation is both memory bound and latency sensitive, as it (1) exhibits irregular access patterns that cause frequent cache and TLB misses, and (2) requires the data from every memory access to be sent back to the CPU to determine the next pointer to access. Our goal is to accelerate pointer chasing by performing it inside main memory, thereby avoiding inefficient and high-latency data transfers between main memory and the CPU. To this end, we propose the In-Memory PoInter Chasing Accelerator (IMPICA), which leverages the logic layer within 3D-stacked memory for linked data structure traversal.
TL;DR: A new flow-sensitive pointer analysis algorithm is presented that is an order of magnitude faster than the existing state of the art, enabling for the first time flow-sensitivity pointer analysis for programs with millions of lines of code.
Abstract: Many program analyses benefit, both in precision and performance, from precise pointer analysis. An important dimension of pointer analysis precision is flow-sensitivity, which has been shown to be useful for applications such as program verification and static analysis of binary code, among many others. However, flow-sensitive pointer analysis has historically been unable to scale to programs with millions of lines of code. We present a new flow-sensitive pointer analysis algorithm that is an order of magnitude faster than the existing state of the art, enabling for the first time flow-sensitive pointer analysis for programs with millions of lines of code. Our flow-sensitive algorithm is based on a sparse representation of program code created by a staged, flow-insensitive pointer analysis. We explain how this new algorithm is a member of a new family of pointer analysis algorithms that deserves further study.
TL;DR: In this article, a method and apparatus of displaying contextual help or status information to the user of a computer system in a graphical user interface is presented, and the information is then displayed proximate to the pointer, preferably in a semitransparent window at a predictable offset from the pointer to allow the information presented by the graphical interface to be viewed.
Abstract: A method and apparatus of displaying contextual help or status information to the user of a computer system in a graphical user interface. When a help facility is enabled, the system determines the position of a pointer, such as a mouse pointer, relative to the objects in the graphical user interface. If the pointer is over an object, the system refers to one or more tables which correlate objects with help and/or status information. The information is then displayed proximate to the pointer, preferably in a semitransparent window at a predictable offset from the pointer to allow the information presented by the graphical user interface to be viewed. As the pointer is moved across the graphical user interface, the information text associated with the pointer changes dynamically. In one preferred embodiment, at least one of the tables which correlate objects with the information is updated to reflect details about objects which change dynamically.
TL;DR: In this article, a method for restoring a virtual disk (vdisk) in an active file system to an earlier time is described, where pointers pointing to data represented by the virtual disk are maintained.
Abstract: A method for restoring a virtual disk (vdisk) in an active file system to an earlier time is described. Pointers pointing to data represented by the virtual disk are maintained. The pointers are saved to persistent storage at the earlier time. A pointer at a later time is compared with the pointers saved at the earlier time. If the pointer from the later time matches the pointer saved at the earlier time, the pointer from the later time is kept in the active file system. If the pointer from the later time does not match the pointers saved at the earlier time, a set of pointers associated with the pointer saved at the earlier time is copied to the active file system.