Learning a Partitioning Advisor with Deep Reinforcement Learning

Commercial data analytics products such as Microsoft Azure SQL Data Warehouse or Amazon Redshift provide ready-to-use scale-out database solutions for OLAP-style workloads in the cloud. While the provisioning of a database cluster is usually fully automated by cloud providers, customers typically still have to make important design decisions which were traditionally made by the database administrator such as selecting the partitioning schemes. In this paper we introduce a learned partitioning advisor for analytical OLAP-style workloads based on Deep Reinforcement Learning (DRL). The main idea is that a DRL agent learns its decisions based on experience by monitoring the rewards for different workloads and partitioning schemes. We evaluate our learned partitioning advisor in an experimental evaluation with different databases schemata and workloads of varying complexity. In the evaluation, we show that our advisor is not only able to find partitionings that outperform existing approaches for automated partitioning design but that it also can easily adjust to different deployments. This is especially important in cloud setups where customers can easily migrate their cluster to a new set of (virtual) machines

The End of a Myth: Distributed Transactions Can Scale

The common wisdom is that distributed transactions do not scale. But what if distributed transactions could be made scalable using the next generation of networks and a redesign of distributed databases? There would be no need for developers anymore to worry about co-partitioning schemes to achieve decent performance. Application development would become easier as data placement would no longer determine how scalable an application is. Hardware provisioning would be simplified as the system administrator can expect a linear scale-out when adding more machines rather than some complex sub-linear function, which is highly application specific. In this paper, we present the design of our novel scalable database system NAM-DB and show that distributed transactions with the very common Snapshot Isolation guarantee can indeed scale using the next generation of RDMA-enabled network technology without any inherent bottlenecks. Our experiments with the TPC-C benchmark show that our system scales linearly to over 6.5 million new-order (14.5 million total) distributed transactions per second on 56 machines.Comment: 12 page

A simple, ultrahigh vacuum compatible scanning tunneling microscope for use at variable temperatures

We present the construction of a very compact scanning tunneling microscope (STM) which can be operated at temperatures between 4 and 350 K. The tip and a tiny tip holder are the only movable parts, whereas the sample and the piezoscanner are rigidly attached to the body of the STM. This leads to an excellent mechanical stability. The coarse approach system relies on the slip-stick principle and is operated by the same piezotube which is used for scanning. As an example of the performance of the device, images of a NbSe2 surface with atomic resolution are obtained

Atomic Force Microscope

The scanning tunneling microscope is proposed as a method to measure forces as small as 10−18 N. As one application for this concept, we introduce a new type of microscope capable of investigating surfaces of insulators on an atomic scale. The atomic force microscope is a combination of the principles of the scanning tunneling microscope and the stylus profilometer. It incorporates a probe that does not damage the surface. Our preliminary results in air demonstrate a lateral resolution of 30 ÅA and a vertical resolution less than 1 Å

Surface molecular dynamics simulation with two orthogonal surface steps: how to beat the particle conservation problem

Due to particle conservation, Canonical Molecular Dynamics (MD) simulations fail in the description of surface phase transitions involving coverage or lateral density changes. However, a step on the surface can act effectively as a source or a sink of atoms, in the simulation as well as in real life. A single surface step can be introduced by suitably modifying planar Periodic Boundary Conditions (PBC), to accommodate the generally inequivalent stacking of two adjacent layers. We discuss here how, through the introduction of two orthogonal surface steps, particle number conservation may no longer represent a fatal constraint for the study of these surface transitions. As an example, we apply the method for estimating temperature-induced lateral density increase of the reconstructed Au (001) surface; the resulting anisotropic cell change is consistent with experimental observations. Moreover, we implement this kind of scheme in conjunction with the variable curvature MD method, recently introduced by our group.Comment: 9 pages, 5 figures, accepted for publication in Surface Science (ECOSS-19

Local field distribution near corrugated interfaces: Green's function formulation

We have developed a Green's function formalism to compute the local field distribution near an interface separating two media of different dielectric constants. The Maxwell's equations are converted into a surface integral equation; thus it greatly simplifies the solutions and yields accurate results for interfaces of arbitrary shape. The integral equation is solved and the local field distribution is obtained for a periodic interface.Comment: Presented at the Conference on Computational Physics (CCP2000), held at Gold Coast, Australia from 3 - 8, December 2000. To be published in Proceedings of CCP200

Reconstructions of Ir (110) and (100): an ab initio study

Prediction criteria for surface reconstructions are discussed, with reference to ab initio calculations of the (110)-$1\times 2$ missing-row and (100)-$5\times 1$ quasi-hexagonal reconstructions of Ir and Rh.Comment: 3 pages RevTeX two-column, to appear in Surface Scienc

Recurrence Tracking Microscope

In order to probe nanostructures on a surface we present a microscope based on the quantum recurrence phenomena. A cloud of atoms bounces off an atomic mirror connected to a cantilever and exhibits quantum recurrences. The times at which the recurrences occur depend on the initial height of the bouncing atoms above the atomic mirror, and vary following the structures on the surface under investigation. The microscope has inherent advantages over existing techniques of scanning tunneling microscope and atomic force microscope. Presently available experimental technology makes it possible to develop the device in the laboratory