Disk

In disk storage, data is recorded on planar, round and rotating surfaces (disks, discs, or platters). A disk drive is a peripheral device of a computer system, connected by some communication medium to a disk controller. The disk controller is a chip, typically connected to the CPU of the computer by the internal communication bus. Main implementations are hard disks, floppy disks and optical discs, of which the first is the usual interpretation. Recently, Solid State Disks have been introduced; though the term ‘disc’ is a misnomer for these devices, as internally they consist of NAND Flash memory chips. Similarly, the term RAM Disk is used for a storage device consisting of volatile DRAM memory. Both offer the same data storage services at the operating system level, though their price, size, performance and persistence characteristics are very different from a hard disk

Letter from the Special Issue Editor

Editorial work for DEBULL on a special issue on data management on Storage Class Memory (SCM) technologies

Main Memory

Primary storage, presently known as main memory, is the largest memory directly accessible to the CPU in the prevalent Von Neumann model and stores both data and instructions (program code). The CPU continuously reads instructions stored there and executes them. It is also called Random Access Memory (RAM), to indicate that load/store instructions can access data at any location at the same cost, is usually implemented using DRAM chips, which are connected to the CPU and other peripherals (disk drive, network) via a bus

Processor Cache

To hide the high latencies of DRAM access, modern computer architecture now features a memory hierarchy that besides DRAM also includes SRAM cache memories, typically located on the CPU chip. Memory access first check these caches, which takes only a few cycles. Only if the needed data is not found, an expensive memory access is needed

Generic and updatable XML value indices covering equality and range lookups

textabstractWe describe a collection of indices for XML text, element, and attribute node values that (i) consume little storage, (ii) have low maintenance overhead, (iii) permit fast equilookup on string values, and (iv) support range-lookup on any XML typed value (e.g., double, dateTime). The equilookup string value index depends on an elaborate hash function and on an associative combination function to facilitate updates on both mixed-content and element nodes. We also present techniques for creating range-lookup indices supporting any ordered XML typed value. These indices rely on a finite state machine that accepts the type specific language, and on a state combination table for combining states to speed-up updates. We evaluate the stability of the hash function, the storage overhead, and the indices creation and maintenance time in the context of the open-source XML database system MonetDB/XQuery

AmbientDB: P2P Data Management Middleware for Ambient Intelligence

The future generation of consumer electronics devices is envisioned to provide automatic cooperation between devices and run applications that are sensitive to people's likings, personalized to their requirements, anticipatory of their behavior and responsive to their presence. We see this `Ambient Intelligence' as a key feature of future pervasive computing. We focus here on one of the challenges in realizing this vision: information management. This entails integrating, querying, synchronizing and evolving structured data, on a heterogeneous and ad-hoc collection of (mobile) devices. Rather than hard-coding data management functionality in each individual application, we argue for adding highlevel data management functionalities to the distributed middleware layer. Our AmbientDB P2P database management system addresses this by providing a global database abstraction over an ad-hoc network of heterogeneous peers

P2P XQuery and the StreetTiVo application

MonetDB/XQuery* is a fully functional publicly available XML DBMS that has been extended with distributed and P2P data management functionality. Our (minimal) XQuery language extension XRPC adds the concept of RPC to XQuery, and we outlined our approach to include the services offered by diverse P2P network structures (such as DHTs), in a way that avoids any further intrusion in the XQuery language and semantics. We also discussed the StreetTiVo application were mxq is being used for data management in a large P2P environment. new construct called XRPC

06472 Abstracts Collection - XQuery Implementation Paradigms

From 19.11.2006 to 22.11.2006, the Dagstuhl Seminar 06472 ``XQuery Implementation Paradigms'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Learned Cardinalities: Estimating Correlated Joins with Deep Learning

We describe a new deep learning approach to cardinality estimation. MSCN is a multi-set convolutional network, tailored to representing relational query plans, that employs set semantics to capture query features and true cardinalities. MSCN builds on sampling-based estimation, addressing its weaknesses when no sampled tuples qualify a predicate, and in capturing join-crossing correlations. Our evaluation of MSCN using a real-world dataset shows that deep learning significantly enhances the quality of cardinality estimation, which is the core problem in query optimization.Comment: CIDR 2019. https://github.com/andreaskipf/learnedcardinalitie

Distributed XQuery and Updates Processing with Heterogeneous XQuery Engines

We demonstrate XRPC, a minimal XQuery extension that enables distributed querying between heterogeneous XQuery engines. The XRPC language extension enhances the existing concept of XQuery functions with the Remote Procedure Call (RPC) paradigm. XRPC is orthogonal to all XQuery features, including the XQuery Update Facility (XQUF). Note that executing xquf updating functions over XRPC leads to the phenomenon of distributed transactions. XRPC achieves heterogeneity by an open SOAP-based network protocol, that can be implemented by any engine, and an XRPC Wrapper that allow