Connecting Microsoft SQL Server Reporting Services to Oracle Autonomous Database
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Oracle Nosql Database
An Oracle White Paper November 2012 Oracle NoSQL Database Oracle NoSQL Database Table of Contents Introduction ........................................................................................ 2 Technical Overview ............................................................................ 4 Data Model ..................................................................................... 4 API ................................................................................................. 5 Create, Remove, Update, and Delete..................................................... 5 Iteration ................................................................................................... 6 Bulk Operation API ................................................................................. 7 Administration .................................................................................... 7 Architecture ........................................................................................ 8 Implementation ................................................................................... 9 Storage Nodes ............................................................................... 9 Client Driver ................................................................................. 10 Performance ..................................................................................... 11 Conclusion ....................................................................................... 12 1 Oracle NoSQL Database Introduction NoSQL databases -
(PI-Net): Facial Image Obfuscation with Manipulable Semantics
Perceptual Indistinguishability-Net (PI-Net): Facial Image Obfuscation with Manipulable Semantics Jia-Wei Chen1,3 Li-Ju Chen3 Chia-Mu Yu2 Chun-Shien Lu1,3 1Institute of Information Science, Academia Sinica 2National Yang Ming Chiao Tung University 3Research Center for Information Technology Innovation, Academia Sinica Abstract Deepfakes [45], if used to replace sensitive semantics, can also mitigate privacy risks for identity disclosure [3, 15]. With the growing use of camera devices, the industry However, all of the above methods share a common has many image datasets that provide more opportunities weakness of syntactic anonymity, or say, lack of formal for collaboration between the machine learning commu- privacy guarantee. Recent studies report that obfuscated nity and industry. However, the sensitive information in faces can be re-identified through machine learning tech- the datasets discourages data owners from releasing these niques [33, 19, 35]. Even worse, the above methods are datasets. Despite recent research devoted to removing sen- not guaranteed to reach the analytical conclusions consis- sitive information from images, they provide neither mean- tent with the one derived from original images, after manip- ingful privacy-utility trade-off nor provable privacy guar- ulating semantics. To overcome the above two weaknesses, antees. In this study, with the consideration of the percep- one might resort to differential privacy (DP) [9], a rigorous tual similarity, we propose perceptual indistinguishability privacy notion with utility preservation. In particular, DP- (PI) as a formal privacy notion particularly for images. We GANs [1, 6, 23, 46] shows a promising solution for both also propose PI-Net, a privacy-preserving mechanism that the provable privacy and perceptual similarity of synthetic achieves image obfuscation with PI guarantee. -
January 2019 Edition
Tunkhannock Area High School Tunkhannock, Pennsylvania The Prowler January 2019 Volume XIV, Issue XLVII Local Subst itute Teacher in Trouble Former TAHS substitute teacher, Zachary Migliori, faces multiple charges. By MADISON NESTOR Former substitute teacher Wyoming County Chief out, that she did not report it originally set for December at Tunkhannock Area High Detective David Ide, started to anyone. 18 was moved to March 18. School, Zachary Migliori, on October 11 when the When Detective Ide asked If he is convicted, he will was charged with three felony parents of a 15-year old Migliori if he knew that one face community service, and counts of distributing obscene student found pornographic of the girls he sent explicit mandatory counseling. material, three misdemeanor images and sexual texts messages to was a 15-year- Tunkhannock Area High counts of open lewdness, and on their daughter’s phone. old, he explained that he School took action right away three misdemeanor counts of The parent then contacted thought she was 18-years-old to ensure students’ safety, unlawful contact with minors. Detective Ide, who found because she hung out with and offers counseling to any This comes after the results after investigating that the many seniors. After being students who need it. of an investigation suspecting substitute teacher was using informed of one victim being Sources:WNEP, lewd contact with students a Snapchat account with the 15-years-old, Migliori said he WCExaminer, CitizensVoice proved to be true. According name ‘Zach Miggs.’ was disgusted with himself. to court documents, Migliori Two 17-year old females Judge Plummer set used Facebook Messenger also came forward, one of Migliori’s bail at $50,000. -
Oracle Database Vault Overview
Oracle Database Vault Oracle Database Vault provides controls to prevent unauthorized privileged users from accessing sensitive data, prevent unauthorized database changes, and helps customers meet industry, regulatory, or corporate security standards. March 23, 2020 Copyright © 2020, Oracle and/or its affiliates Public Purpose Statement This document provides an overview of features and enhancements included in the latest releases of Oracle Database Vault. It is intended solely to help you assess the business benefits of using Oracle Database Vault preventive controls and to plan your Data Security / I.T. projects. Disclaimer This document in any form, software or printed matter, contains proprietary information that is the exclusive property of Oracle. Your access to and use of this confidential material is subject to the terms and conditions of your Oracle software license and service agreement, which has been executed and with which you agree to comply. This document is not part of your license agreement nor can it be incorporated into any contractual agreement with Oracle or its subsidiaries or affiliates. This document is for informational purposes only and is intended solely to assist you in planning for the implementation and upgrade of the product features described. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described in this document remains at the sole discretion of -
S.Ha.R.K. Installation Howto Tools Knoppix Live CD Linux Fdisk HD
S.Ha.R.K. Installation Tools HowTo • Linux fdisk utility • A copy of Linux installation CD • A copy of Windows® installation CD Tullio Facchinetti University of Pavia - Italy • Some FreeDOS utilities • A copy of S.Ha.R.K. S.Ha.R.K. Workshop S.Ha.R.K. Workshop Knoppix live CD Linux fdisk Command action a toggle a bootable flag Download ISO from b edit bsd disklabel c toggle the dos compatibility flag d delete a partition http://www.knoppix.org l list known partition types m print this menu n add a new partition o create a new empty DOS partition table p print the partition table q quit without saving changes • boot from CD s create a new empty Sun disklabel t change a partition's system id • open a command shell u change display/entry units v verify the partition table • type “su” (become root ), password is empty w write table to disk and exit x extra functionality (experts only) • start fdisk (ex. fdisk /dev/hda ) Command (m for help): S.Ha.R.K. Workshop S.Ha.R.K. Workshop HD partitioning HD partitioning 1st FreeDOS FAT32 FreeDOS must be installed Primary 2nd Windows® FAT32 into the first partition of your HD or it may not boot 3rd Linux / extX Data 1 FAT32 format data partitions as ... Extended FAT32, so that you can share Data n FAT32 your data between Linux, last Linux swap swap Windows® and FreeDOS S.Ha.R.K. Workshop S.Ha.R.K. Workshop 1 HD partitioning Windows ® installation FAT32 Windows® partition type Install Windows®.. -
NETSTAT Command
NETSTAT Command | NETSTAT Command | Use the NETSTAT command to display network status of the local host. | | ┌┐────────────── | 55──NETSTAT─────6─┤ Option ├─┴──┬────────────────────────────────── ┬ ─ ─ ─ ────────────────────────────────────────5% | │┌┐───────────────────── │ | └─(──SELect───6─┤ Select_String ├─┴ ─ ┘ | Option: | ┌┐─COnn────── (1, 2) ──────────────── | ├──┼─────────────────────────── ┼ ─ ──────────────────────────────────────────────────────────────────────────────┤ | ├─ALL───(2)──────────────────── ┤ | ├─ALLConn─────(1, 2) ────────────── ┤ | ├─ARp ipaddress───────────── ┤ | ├─CLients─────────────────── ┤ | ├─DEvlinks────────────────── ┤ | ├─Gate───(3)─────────────────── ┤ | ├─┬─Help─ ┬─ ───────────────── ┤ | │└┘─?──── │ | ├─HOme────────────────────── ┤ | │┌┐─2ð────── │ | ├─Interval─────(1, 2) ─┼───────── ┼─ ┤ | │└┘─seconds─ │ | ├─LEVel───────────────────── ┤ | ├─POOLsize────────────────── ┤ | ├─SOCKets─────────────────── ┤ | ├─TCp serverid───(1) ─────────── ┤ | ├─TELnet───(4)───────────────── ┤ | ├─Up──────────────────────── ┤ | └┘─┤ Command ├───(5)──────────── | Command: | ├──┬─CP cp_command───(6) ─ ┬ ────────────────────────────────────────────────────────────────────────────────────────┤ | ├─DELarp ipaddress─ ┤ | ├─DRop conn_num──── ┤ | └─RESETPool──────── ┘ | Select_String: | ├─ ─┬─ipaddress────(3) ┬ ─ ───────────────────────────────────────────────────────────────────────────────────────────┤ | ├─ldev_num─────(4) ┤ | └─userid────(2) ─── ┘ | Notes: | 1 Only ALLCON, CONN and TCP are valid with INTERVAL. | 2 The userid -
Oracle Big Data SQL Release 4.1
ORACLE DATA SHEET Oracle Big Data SQL Release 4.1 The unprecedented explosion in data that can be made useful to enterprises – from the Internet of Things, to the social streams of global customer bases – has created a tremendous opportunity for businesses. However, with the enormous possibilities of Big Data, there can also be enormous complexity. Integrating Big Data systems to leverage these vast new data resources with existing information estates can be challenging. Valuable data may be stored in a system separate from where the majority of business-critical operations take place. Moreover, accessing this data may require significant investment in re-developing code for analysis and reporting - delaying access to data as well as reducing the ultimate value of the data to the business. Oracle Big Data SQL enables organizations to immediately analyze data across Apache Hadoop, Apache Kafka, NoSQL, object stores and Oracle Database leveraging their existing SQL skills, security policies and applications with extreme performance. From simplifying data science efforts to unlocking data lakes, Big Data SQL makes the benefits of Big Data available to the largest group of end users possible. KEY FEATURES Rich SQL Processing on All Data • Seamlessly query data across Oracle Oracle Big Data SQL is a data virtualization innovation from Oracle. It is a new Database, Hadoop, object stores, architecture and solution for SQL and other data APIs (such as REST and Node.js) on Kafka and NoSQL sources disparate data sets, seamlessly integrating data in Apache Hadoop, Apache Kafka, • Runs all Oracle SQL queries without modification – preserving application object stores and a number of NoSQL databases with data stored in Oracle Database. -
Oracle Database Advanced Application Developer's Guide, 11G Release 2 (11.2) E17125-03
Oracle® Database Advanced Application Developer's Guide 11g Release 2 (11.2) E17125-03 August 2010 Oracle Database Advanced Application Developer's Guide, 11g Release 2 (11.2) E17125-03 Copyright © 1996, 2010, Oracle and/or its affiliates. All rights reserved. Primary Author: Sheila Moore Contributing Authors: D. Adams, L. Ashdown, M. Cowan, J. Melnick, R. Moran, E. Paapanen, J. Russell, R. Strohm, R. Ward Contributors: D. Alpern, G. Arora, C. Barclay, D. Bronnikov, T. Chang, L. Chen, B. Cheng, M. Davidson, R. Day, R. Decker, G. Doherty, D. Elson, A. Ganesh, M. Hartstein, Y. Hu, J. Huang, C. Iyer, N. Jain, R. Jenkins Jr., S. Kotsovolos, V. Krishnaswamy, S. Kumar, C. Lei, B. Llewellyn, D. Lorentz, V. Moore, K. Muthukkaruppan, V. Moore, J. Muller, R. Murthy, R. Pang, B. Sinha, S. Vemuri, W. Wang, D. Wong, A. Yalamanchi, Q. Yu This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this software or related documentation is delivered to the U.S. -
Oracle Database Sharding Infographic
Oracle Database Sharding Oracle Sharding : Scale-out Rela7onal Database Sharding = Distributed Par77oning + Replica7on One giant database par66oned into many small databases (shards) Built on shared-nothing hardware architecture • Some web-scale OLTP applicaons use database sharding to avoid • Horizontal par66oning of data using a sharding key (e.g. scalability or availability edge cases of a single large database customer_id) across a farm of independent Oracle Databases • Oracle 12cR2 is the first full-featured RDBMS that provides nave • Shards can be hosted on commodity servers or engineered systems database sharding while suppor6ng enterprise capabili6es • Data automacally replicated with Data Guard or Oracle GoldenGate for high availability and disaster recovery Benefits Linear Scalability Fault Isola7on Geographic Distribuon Flexible Deployment 12,000,000 CPU CA On-Premises Hybrid Cloud 10,000,000 CA CA 8,000,000 … TPS 6,000,000 CA Vector Register 4,000,000 … 2,000,000 0 50 100 150 200 # of Shards Add shards online to Shared-nothing Data Sovereignty - for Flexible On-Premises, Cloud or Hybrid linearly scale - architecture. data privacy regulaons. Deployments. transac6ons, users and Fault of one shard Data Proximity - to bring Supports Cloud bursng database capacity has no impact on data closer to the users other shards Salient Features • Auto deployment of up to 1000 shards • Direct Rou6ng – Supports Data Guard and Oracle GoldenGate – Direct fast path SQL access via sharding key from smart topology- • Mul6ple sharding methods aware -
Oracle Nosql Database EE Data Sheet
Oracle NoSQL Database 21.1 Enterprise Edition (EE) Oracle NoSQL Database is a multi-model, multi-region, multi-cloud, active-active KEY BUSINESS BENEFITS database, designed to provide a highly-available, scalable, performant, flexible, High throughput and reliable data management solution to meet today’s most demanding Bounded latency workloads. It can be deployed in on-premise data centers and cloud. It is well- Linear scalability suited for high volume and velocity workloads, like Internet of Things, 360- High availability degree customer view, online contextual advertising, fraud detection, mobile Fast and easy deployment application, user personalization, and online gaming. Developers can use a single Smart topology management application interface to quickly build applications that run in on-premise and Online elastic configuration cloud environments. Multi-region data replication Enterprise grade software Applications send network requests against an Oracle NoSQL data store to and support perform database operations. With multi-region tables, data can be globally distributed and automatically replicated in real-time across different regions. Data can be modeled as fixed-schema tables, documents, key-value pairs, and large objects. Different data models interoperate with each other through a single programming interface. Oracle NoSQL Database is a sharded, shared-nothing system which distributes data uniformly across multiple shards in a NoSQL database cluster, based on the hashed value of the primary keys. An Oracle NoSQL Database data store is a collection of storage nodes, each of which hosts one or more replication nodes. Data is automatically populated across these replication nodes by internal replication mechanisms to ensure high availability and rapid failover in the event of a storage node failure. -
JES3 Commands
z/OS Version 2 Release 3 JES3 Commands IBM SA32-1008-30 Note Before using this information and the product it supports, read the information in “Notices” on page 431. This edition applies to Version 2 Release 3 of z/OS (5650-ZOS) and to all subsequent releases and modifications until otherwise indicated in new editions. Last updated: 2019-02-16 © Copyright International Business Machines Corporation 1997, 2017. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents List of Figures....................................................................................................... ix List of Tables........................................................................................................ xi About this document...........................................................................................xiii Who should use this document.................................................................................................................xiii Where to find more information................................................................................................................ xiii How to send your comments to IBM......................................................................xv If you have a technical problem.................................................................................................................xv Summary of changes...........................................................................................xvi -
System Analysis and Tuning Guide System Analysis and Tuning Guide SUSE Linux Enterprise Server 15 SP1
SUSE Linux Enterprise Server 15 SP1 System Analysis and Tuning Guide System Analysis and Tuning Guide SUSE Linux Enterprise Server 15 SP1 An administrator's guide for problem detection, resolution and optimization. Find how to inspect and optimize your system by means of monitoring tools and how to eciently manage resources. Also contains an overview of common problems and solutions and of additional help and documentation resources. Publication Date: September 24, 2021 SUSE LLC 1800 South Novell Place Provo, UT 84606 USA https://documentation.suse.com Copyright © 2006– 2021 SUSE LLC and contributors. All rights reserved. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or (at your option) version 1.3; with the Invariant Section being this copyright notice and license. A copy of the license version 1.2 is included in the section entitled “GNU Free Documentation License”. For SUSE trademarks, see https://www.suse.com/company/legal/ . All other third-party trademarks are the property of their respective owners. Trademark symbols (®, ™ etc.) denote trademarks of SUSE and its aliates. Asterisks (*) denote third-party trademarks. All information found in this book has been compiled with utmost attention to detail. However, this does not guarantee complete accuracy. Neither SUSE LLC, its aliates, the authors nor the translators shall be held liable for possible errors or the consequences thereof. Contents About This Guide xii 1 Available Documentation xiii