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• Master Note for Generic Data Warehousing

  - by lajos.varady(at)oracle.com

  ++++++++++++++++++++++++++++++++++++++++++++++++++++ The complete and the most recent version of this article can be viewed from My Oracle Support Knowledge Section. Master Note for Generic Data Warehousing [ID 1269175.1] ++++++++++++++++++++++++++++++++++++++++++++++++++++In this Document   Purpose   Master Note for Generic Data Warehousing      Components covered      Oracle Database Data Warehousing specific documents for recent versions      Technology Network Product Homes      Master Notes available in My Oracle Support      White Papers      Technical Presentations Platforms: 1-914CU; This document is being delivered to you via Oracle Support's Rapid Visibility (RaV) process and therefore has not been subject to an independent technical review. Applies to: Oracle Server - Enterprise Edition - Version: 9.2.0.1 to 11.2.0.2 - Release: 9.2 to 11.2Information in this document applies to any platform. Purpose Provide navigation path Master Note for Generic Data Warehousing Components covered Read Only Materialized ViewsQuery RewriteDatabase Object PartitioningParallel Execution and Parallel QueryDatabase CompressionTransportable TablespacesOracle Online Analytical Processing (OLAP)Oracle Data MiningOracle Database Data Warehousing specific documents for recent versions 11g Release 2 (11.2)11g Release 1 (11.1)10g Release 2 (10.2)10g Release 1 (10.1)9i Release 2 (9.2)9i Release 1 (9.0)Technology Network Product HomesOracle Partitioning Advanced CompressionOracle Data MiningOracle OLAPMaster Notes available in My Oracle SupportThese technical articles have been written by Oracle Support Engineers to provide proactive and top level information and knowledge about the components of thedatabase we handle under the "Database Datawarehousing".Note 1166564.1 Master Note: Transportable Tablespaces (TTS) -- Common Questions and IssuesNote 1087507.1 Master Note for MVIEW 'ORA-' error diagnosis. For Materialized View CREATE or REFRESHNote 1102801.1 Master Note: How to Get a 10046 trace for a Parallel QueryNote 1097154.1 Master Note Parallel Execution Wait Events Note 1107593.1 Master Note for the Oracle OLAP OptionNote 1087643.1 Master Note for Oracle Data MiningNote 1215173.1 Master Note for Query RewriteNote 1223705.1 Master Note for OLTP Compression Note 1269175.1 Master Note for Generic Data WarehousingWhite Papers Transportable Tablespaces white papers Database Upgrade Using Transportable Tablespaces:Oracle Database 11g Release 1 (February 2009) Platform Migration Using Transportable Database Oracle Database 11g and 10g Release 2 (August 2008) Database Upgrade using Transportable Tablespaces: Oracle Database 10g Release 2 (April 2007) Platform Migration using Transportable Tablespaces: Oracle Database 10g Release 2 (April 2007)Parallel Execution and Parallel Query white papers Best Practices for Workload Management of a Data Warehouse on the Sun Oracle Database Machine (June 2010) Effective resource utilization by In-Memory Parallel Execution in Oracle Real Application Clusters 11g Release 2 (Feb 2010) Parallel Execution Fundamentals in Oracle Database 11g Release 2 (November 2009) Parallel Execution with Oracle Database 10g Release 2 (June 2005)Oracle Data Mining white paper Oracle Data Mining 11g Release 2 (March 2010)Partitioning white papers Partitioning with Oracle Database 11g Release 2 (September 2009) Partitioning in Oracle Database 11g (June 2007)Materialized Views and Query Rewrite white papers Oracle Materialized Views  and Query Rewrite (May 2005) Improving Performance using Query Rewrite in Oracle Database 10g (December 2003)Database Compression white papers Advanced Compression with Oracle Database 11g Release 2 (September 2009) Table Compression in Oracle Database 10g Release 2 (May 2005)Oracle OLAP white papers On-line Analytic Processing with Oracle Database 11g Release 2 (September 2009) Using Oracle Business Intelligence Enterprise Edition with the OLAP Option to Oracle Database 11g (July 2008)Generic white papers Enabling Pervasive BI through a Practical Data Warehouse Reference Architecture (February 2010) Optimizing and Protecting Storage with Oracle Database 11g Release 2 (November 2009) Oracle Database 11g for Data Warehousing and Business Intelligence (August 2009) Best practices for a Data Warehouse on Oracle Database 11g (September 2008)Technical PresentationsA selection of ObE - Oracle by Examples documents: Generic Using Basic Database Functionality for Data Warehousing (10g) Partitioning Manipulating Partitions in Oracle Database (11g Release 1) Using High-Speed Data Loading and Rolling Window Operations with Partitioning (11g Release 1) Using Partitioned Outer Join to Fill Gaps in Sparse Data (10g) Materialized View and Query Rewrite Using Materialized Views and Query Rewrite Capabilities (10g) Using the SQLAccess Advisor to Recommend Materialized Views and Indexes (10g) Oracle OLAP Using Microsoft Excel With Oracle 11g Cubes (how to analyze data in Oracle OLAP Cubes using Excel's native capabilities) Using Oracle OLAP 11g With Oracle BI Enterprise Edition (Creating OBIEE Metadata for OLAP 11g Cubes and querying those in BI Answers) Building OLAP 11g Cubes Querying OLAP 11g Cubes Creating Interactive APEX Reports Over OLAP 11g CubesSelection of presentations from the BIWA website:Extreme Data Warehousing With Exadata  by Hermann Baer (July 2010) (slides 2.5MB, recording 54MB)Data Mining Made Easy! Introducing Oracle Data Miner 11g Release 2 New "Work flow" GUI   by Charlie Berger (May 2010) (slides 4.8MB, recording 85MB )Best Practices for Deploying a Data Warehouse on Oracle Database 11g  by Maria Colgan (December 2009)  (slides 3MB, recording 18MB, white paper 3MB )

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• How to give my user permission to add/edit files on local apache server? [duplicate]

  - by Logan

  Possible Duplicate: How to make Apache run as current user I'm setting up my local test server again, and I seem to have forgotten how to successfully set up the LAMP server. I have installed LAMP server via tasksel command and I have configured the /var/www directory according to a guide I've found: After the lamp server installation you will need write permissions to the /var/www directory. Follow these steps to configure permissions. Add your user to the www-data group sudo usermod -a -G www-data <your user name> now add the /var/www folder to the www-data group sudo chgrp -R www-data /var/www now give write permissions to the www-data group sudo chmod -R g+w /var/www So logan user is now part of www-data group and the file/folder permissions look like the output below: logan@computer:/var/www$ ls -lart total 172 -rw-r--r-- 1 www-data www-data 1997 Oct 23 2010 wp-links-opml.php -rw-r--r-- 1 www-data www-data 3177 Nov 1 2010 wp-config-sample.php -rw-r--r-- 1 www-data www-data 3700 Jan 8 2012 wp-trackback.php -rw-r--r-- 1 www-data www-data 271 Jan 8 2012 wp-blog-header.php -rw-r--r-- 1 www-data www-data 395 Jan 8 2012 index.php -rw-r--r-- 1 www-data www-data 3522 Apr 10 2012 wp-comments-post.php -rw-r--r-- 1 www-data www-data 19929 May 6 2012 license.txt -rw-r--r-- 1 www-data www-data 18219 Sep 11 08:27 wp-signup.php -rw-r--r-- 1 www-data www-data 2719 Sep 11 16:11 xmlrpc.php -rw-r--r-- 1 www-data www-data 2718 Sep 23 12:57 wp-cron.php -rw-r--r-- 1 www-data www-data 7723 Sep 25 01:26 wp-mail.php -rw-r--r-- 1 www-data www-data 2408 Oct 26 15:40 wp-load.php -rw-r--r-- 1 www-data www-data 4663 Nov 17 10:11 wp-activate.php -rw-r--r-- 1 www-data www-data 9899 Nov 22 04:52 wp-settings.php -rw-r--r-- 1 www-data www-data 9175 Nov 29 19:57 readme.html -rw-r--r-- 1 www-data www-data 29310 Nov 30 08:40 wp-login.php drwxr-xr-x 14 root root 4096 Dec 24 17:41 .. drwx------ 9 www-data www-data 4096 Dec 26 16:11 wp-admin drwx------ 9 www-data www-data 4096 Dec 26 16:11 wp-includes -rw-rw-rw- 1 www-data www-data 3448 Dec 26 16:14 wp-config.php drwxrwxr-x 5 www-data www-data 4096 Dec 26 16:14 . drwx------ 6 www-data www-data 4096 Dec 26 16:19 wp-content Things work perfectly at http://localhost, I can view the website fine. The thing with this is that I will be working on a plugin for wordpress and I don't want to deal with separate owners under www directory to create or modify files/folders. When I give my user the ownership of /var/www recursively as logan:www-data I can create/modify files but cannot view the http://localhost. I get a Forbidden error. I'm assuming that this is because of the Apache's configuration? Which one is healthier or easier considering this is just a local test website, configuring apache to give user logan to view website and chmod /var/www logan:logan so that I can create files etc. without any sudo commands; or is it easier to configure user groups to get www-data user to act like my logan user? (Idk how that's possible, maybe putting www-data user under logan group?) Please shed some light to this subject. All I want is to be able to create/modifiy files under my user, and yet to be able to successfully view http://localhost I appreciate the help!

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• Oracle Enterprise Data Quality: Ever Integration-ready

  - by Mala Narasimharajan

  It is closing in on a year now since Oracle’s acquisition of Datanomic, and the addition of Oracle Enterprise Data Quality (EDQ) to the Oracle software family. The big move has caused some big shifts in emphasis and some very encouraging excitement from the field.  To give an illustration, combined with a shameless promotion of how EDQ can help to give quick insights into your data, I did a quick Phrase Profile of the subject field of emails to the Global EDQ mailing list since it was set up last September. The results revealed a very clear theme:   Integration, Integration, Integration! As well as the important Siebel and Oracle Data Integrator (ODI) integrations, we have been asked about integration with a huge variety of Oracle applications, including EBS, Peoplesoft, CRM on Demand, Fusion, DRM, Endeca, RightNow, and more - and we have not stood still! While it would not have been possible to develop specific pre-integrations with all of the above within a year, we have developed a package of feature-rich out-of-the-box web services and batch processes that can be plugged into any application or middleware technology with ease. And with Siebel, they work out of the box. Oracle Enterprise Data Quality version 9.0.4 includes the Customer Data Services (CDS) pack – a ready set of standard processes with standard interfaces, to provide integrated: Address verification and cleansing  Individual matching Organization matching The services can are suitable for either Batch or Real-Time processing, and are enabled for international data, with simple configuration options driving the set of locale-specific dictionaries that are used. For example, large dictionaries are provided to support international name transcription and variant matching, including highly specialized handling for Arabic, Japanese, Chinese and Korean data. In total across all locales, CDS includes well over a million dictionary entries.   Excerpt from EDQ’s CDS Individual Name Standardization Dictionary CDS has been developed to replace the OEM of Informatica Identity Resolution (IIR) for attached Data Quality on the Oracle price list, but does this in a way that creates a ‘best of both worlds’ situation for customers, who can harness not only the out-of-the-box functionality of pre-packaged matching and standardization services, but also the flexibility of OEDQ if they want to customize the interfaces or the process logic, without having to learn more than one product. From a competitive point of view, we believe this stands us in good stead against our key competitors, including Informatica, who have separate ‘Identity Resolution’ and general DQ products, and IBM, who provide limited out-of-the-box capabilities (with a steep learning curve) in both their QualityStage data quality and Initiate matching products. Here is a brief guide to the main services provided in the pack: Address Verification and Standardization EDQ’s CDS Address Cleaning Process The Address Verification and Standardization service uses EDQ Address Verification (an OEM of Loqate software) to verify and clean addresses in either real-time or batch. The Address Verification processor is wrapped in an EDQ process – this adds significant capabilities over calling the underlying Address Verification API directly, specifically: Country-specific thresholds to determine when to accept the verification result (and therefore to change the input address) based on the confidence level of the API Optimization of address verification by pre-standardizing data where required Formatting of output addresses into the input address fields normally used by applications Adding descriptions of the address verification and geocoding return codes The process can then be used to provide real-time and batch address cleansing in any application; such as a simple web page calling address cleaning and geocoding as part of a check on individual data.     Duplicate Prevention Unlike Informatica Identity Resolution (IIR), EDQ uses stateless services for duplicate prevention to avoid issues caused by complex replication and synchronization of large volume customer data. When a record is added or updated in an application, the EDQ Cluster Key Generation service is called, and returns a number of key values. These are used to select other records (‘candidates’) that may match in the application data (which has been pre-seeded with keys using the same service). The ‘driving record’ (the new or updated record) is then presented along with all selected candidates to the EDQ Matching Service, which decides which of the candidates are a good match with the driving record, and scores them according to the strength of match. In this model, complex multi-locale EDQ techniques can be used to generate the keys and ensure that the right balance between performance and matching effectiveness is maintained, while ensuring that the application retains control of data integrity and transactional commits. The process is explained below: EDQ Duplicate Prevention Architecture Note that where the integration is with a hub, there may be an additional call to the Cluster Key Generation service if the master record has changed due to merges with other records (and therefore needs to have new key values generated before commit). Batch Matching In order to allow customers to use different match rules in batch to real-time, separate matching templates are provided for batch matching. For example, some customers want to minimize intervention in key user flows (such as adding new customers) in front end applications, but to conduct a more exhaustive match on a regular basis in the back office. The batch matching jobs are also used when migrating data between systems, and in this case normally a more precise (and automated) type of matching is required, in order to minimize the review work performed by Data Stewards.  In batch matching, data is captured into EDQ using its standard interfaces, and records are standardized, clustered and matched in an EDQ job before matches are written out. As with all EDQ jobs, batch matching may be called from Oracle Data Integrator (ODI) if required. When working with Siebel CRM (or master data in Siebel UCM), Siebel’s Data Quality Manager is used to instigate batch jobs, and a shared staging database is used to write records for matching and to consume match results. The CDS batch matching processes automatically adjust to Siebel’s ‘Full Match’ (match all records against each other) and ‘Incremental Match’ (match a subset of records against all of their selected candidates) modes. The Future The Customer Data Services Pack is an important part of the Oracle strategy for EDQ, offering a clear path to making Data Quality Assurance an integral part of enterprise applications, and providing a strong value proposition for adopting EDQ. We are planning various additions and improvements, including: An out-of-the-box Data Quality Dashboard Even more comprehensive international data handling Address search (suggesting multiple results) Integrated address matching The EDQ Customer Data Services Pack is part of the Enterprise Data Quality Media Pack, available for download at http://www.oracle.com/technetwork/middleware/oedq/downloads/index.html.

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• Master Data Management Implementation Styles

  - by david.butler(at)oracle.com

  In any Master Data Management solution deployment, one of the key decisions to be made is the choice of the MDM architecture. Gartner and other analysts describe some different Hub deployment styles, which must be supported by a best of breed MDM solution in order to guarantee the success of the deployment project.   Registry Style: In a Registry Style MDM Hub, the various source systems publish their data and a subscribing Hub stores only the source system IDs, the Foreign Keys (record IDs on source systems) and the key data values needed for matching. The Hub runs the cleansing and matching algorithms and assigns unique global identifiers to the matched records, but does not send any data back to the source systems. The Registry Style MDM Hub uses data federation capabilities to build the "virtual" golden view of the master entity from the connected systems.   Consolidation Style: The Consolidation Style MDM Hub has a physically instantiated, "golden" record stored in the central Hub. The authoring of the data remains distributed across the spoke systems and the master data can be updated based on events, but is not guaranteed to be up to date. The master data in this case is usually not used for transactions, but rather supports reporting; however, it can also be used for reference operationally.   Coexistence Style: The Coexistence Style MDM Hub involves master data that's authored and stored in numerous spoke systems, but includes a physically instantiated golden record in the central Hub and harmonized master data across the application portfolio. The golden record is constructed in the same manner as in the consolidation style, and, in the operational world, Consolidation Style MDM Hubs often evolve into the Coexistence Style. The key difference is that in this architectural style the master data stored in the central MDM system is selectively published out to the subscribing spoke systems.   Transaction Style: In this architecture, the Hub stores, enhances and maintains all the relevant (master) data attributes. It becomes the authoritative source of truth and publishes this valuable information back to the respective source systems. The Hub publishes and writes back the various data elements to the source systems after the linking, cleansing, matching and enriching algorithms have done their work. Upstream, transactional applications can read master data from the MDM Hub, and, potentially, all spoke systems subscribe to updates published from the central system in a form of harmonization. The Hub needs to support merging of master records. Security and visibility policies at the data attribute level need to be supported by the Transaction Style hub, as well.   Adaptive Transaction Style: This is similar to the Transaction Style, but additionally provides the capability to respond to diverse information and process requests across the enterprise. This style emerged most recently to address the limitations of the above approaches. With the Adaptive Transaction Style, the Hub is built as a platform for consolidating data from disparate third party and internal sources and for serving unified master entity views to operational applications, analytical systems or both. This approach delivers a real-time Hub that has a reliable, persistent foundation of master reference and relationship data, along with all the history and lineage of data changes needed for audit and compliance tracking. On top of this persistent master data foundation, the Hub can dynamically aggregate transaction data on demand from different source systems to deliver the unified golden view to downstream systems. Data can also be accessed through batch interfaces, published to a message bus or served through a real-time services layer. New data sources can be readily added in this approach by extending the data model and by configuring the new source mappings and the survivorship rules, meaning that all legacy data hubs can be leveraged to contribute their records/rules into the new transaction hub. Finally, through rich user interfaces for data stewardship, it allows exception handling by business analysts to keep it current with business rules/practices while maintaining the reliability of best-of-breed master records.   Confederation Style: In this architectural style, several Hubs are maintained at departmental and/or agency and/or territorial level, and each of them are connected to the other Hubs either directly or via a central Super-Hub. Each Domain level Hub can be implemented using any of the previously described styles, but normally the Central Super-Hub is a Registry Style one. This is particularly important for Public Sector organizations, where most of the time it is practically or legally impossible to store in a single central hub all the relevant constituent information from all departments.   Oracle MDM Solutions can be deployed according to any of the above MDM architectural styles, and have been specifically designed to fully support the Transaction and Adaptive Transaction styles. Oracle MDM Solutions provide strong data federation and integration capabilities which are key to enabling the use of the Confederated Hub as a possible architectural style approach. Don't lock yourself into a solution that cannot evolve with your needs. With Oracle's support for any type of deployment architecture, its ability to leverage the outstanding capabilities of the Oracle technology stack, and its open interfaces for non-Oracle technology stacks, Oracle MDM Solutions provide a low TCO and a quick ROI by enabling a phased implementation strategy.

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• Best practices for upgrading user data when updating versions of software

  - by Javy

  In my code I check the current version of the software on launch and compare it to the version stored in the user's data file(s). If the version is newer, then I call different methods to update the old data to the newer data version, if necessary. I usually have to make a new method to convert the data with each update that changes user data in some way, and cannot remove the old ones in case there was someone who missed an update. So the app must be able to go through each method call and update their data until they get their data current. With larger data sets, this could be a problem. In addition, I recently had a brief discussion with another StackOverflow user this and he indicated he always appended a date stamp to the filename to manage data versions, although his reasoning as to why this was better than storing the version data in the file itself was unclear. Since I've rarely seen management of user data versions in books I've read, I'm curious what are the best practices for naming user data files and procedures for updating older data to newer versions.

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• How to tackle archived who-is personal data with opt-out?

  - by defaye

  As far as I understand it, it is possible to opt-out (in the UK at least) of having your address details displayed on who-is information of a domain for non-trading individuals. What I want to know is, after opt-out, how do individuals combat archived data? Is there any enforcement of this? How many who-is websites are there which archive data and what rights do we have to force them to remove that data without paying absurd fees? In the case of capitulating to these scoundrels, what point is it in paying for the removal of archived data if that data can presumably resurface on another who-is repository? In other words, what strategy is one supposed to take, besides being wiser after the fact?

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• pure-ftpd debian, can't get www-data user working

  - by lynks

  I'm trying to add FTP access to the apache web files, in the past I have done this with an ftpuser and group arrangement. This time I would like to make it possible to login directly as www-data (the default apache user on debian) to make things a bit cleaner. I have checked and re-checked all the common issues; MinUID is set to 1 (www-data has uid 33) www-data has shell set to /bin/bash in /etc/passwd PAMAuthentication is off UnixAuthentication is on I have restarted pure-ftpd using /etc/init.d/pure-ftpd restart My resulting pure-ftpd run is; /usr/sbin/pure-ftpd -l unix -A -Y 1 -u 1 -E -O clf:/var/log/pure-ftpd/transfer.log -8 UTF-8 -B My syslog contains; Oct 7 19:46:40 Debian-60-squeeze-64 pure-ftpd: ([email protected]) [WARNING] Can't login as [www-data]: account disabled And my ftp client is giving me; 530 Sorry, but I can't trust you Am I missing something obvious?

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• Chef: nested data bag data to template file returns "can't convert String into Integer"

  - by Dalho Park

  I'm creating simple test recipe with a template and data bag. What I'm trying to do is creating a config file from data bag that has simple nested information, but I receive error "can't convert String into Integer" Here are my setting file 1) recipe/default.rb data1 = data_bag_item( 'mytest', 'qa' )['test'] data2 = data_bag_item( 'mytest', 'qa' ) template "/opt/env/test.cfg" do source "test.erb" action :create_if_missing mode 0664 owner "root" group "root" variables({ :pepe1 = data1['part.name'], :pepe2 = data2['transport.tcp.ip2'] }) end 2)my data bag named "mytest" $knife data bag show mytest qa id: qa test: part.name: L12 transport.tcp.ip: 111.111.111.111 transport.tcp.port: 9199 transport.tcp.ip2: 222.222.222.222 3)template file test.erb part.name=<%= @pepe1 % transport.tcp.binding=<%= @pepe2 % Error reurns when I run chef-client on my server, [2013-06-24T19:50:38+00:00] DEBUG: filtered backtrace of compile error: /var/chef/cache/cookbooks/config_test/recipes/default.rb:19:in []',/var/chef/cache/cookbooks/config_test/recipes/default.rb:19:inblock in from_file',/var/chef/cache/cookbooks/config_test/recipes/default.rb:12:in from_file' [2013-06-24T19:50:38+00:00] DEBUG: filtered backtrace of compile error: /var/chef/cache/cookbooks/config_test/recipes/default.rb:19:in[]',/var/chef/cache/cookbooks/config_test/recipes/default.rb:19:in block in from_file',/var/chef/cache/cookbooks/config_test/recipes/default.rb:12:infrom_file' [2013-06-24T19:50:38+00:00] DEBUG: backtrace entry for compile error: '/var/chef/cache/cookbooks/config_test/recipes/default.rb:19:in `[]'' [2013-06-24T19:50:38+00:00] DEBUG: Line number of compile error: '19' Recipe Compile Error in /var/chef/cache/cookbooks/config_test/recipes/default.rb TypeError can't convert String into Integer Cookbook Trace: /var/chef/cache/cookbooks/config_test/recipes/default.rb:19:in []' /var/chef/cache/cookbooks/config_test/recipes/default.rb:19:inblock in from_file' /var/chef/cache/cookbooks/config_test/recipes/default.rb:12:in `from_file' Relevant File Content: /var/chef/cache/cookbooks/config_test/recipes/default.rb: 12: template "/opt/env/test.cfg" do 13: source "test.erb" 14: action :create_if_missing 15: mode 0664 16: owner "root" 17: group "root" 18: variables({ 19 :pepe1 = data1['part.name'], 20: :pepe2 = data2['transport.tcp.ip2'] 21: }) 22: end 23: I tried many things and if I comment out "pepe1 = data1['part.name'],", then :pepe2 = data2['transport.tcp.ip2'] works fine. only nested data "part.name" cannot be set to @pepe1. Does anyone knows why I receive the errors? thanks,

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• Data recovery on a corrupted 3TB disk

  - by Mark K Cowan

  Short version I probably need software to run a deep-scan recovery (ideally on Linux) to find files on NTFS filesystem. The file data is intact, but the references are no longer present. Analogous to recovering data from a "quick-formatted" partition. Hopefully there is a smarter way available than deep-scan, one which would recover filenames and possibly paths. Long version I have a 3TB disk containing a load of backups. Windows 7 SP1 refused to detect the disk when plugged in directly via SATA, so I put it on a USB/SATA adaptor which seemed to work at first. The SATA/USB adaptor probably does not support disks over 2.2TB though. Windows first asked me if I wanted to 'format' the disk, then later showed me most of the contents but some folder were inaccessible. I stupidly decided to run a CHKDSK on my backup disk, which made the folders accessible but also left them empty. I connected this disk via SATA to my main PC (Arch Linux). I tried: testdisk ntfsundelete ntfsfix --no-action (to look for diagnostically relevant faults, disk was "OK" though) to no avail as the files references in the tables had presumably been zeroed out by CHKDSK, rather than using a typical journal'd deletion). If it is useful at all, a majority of the files that I want to recover are JPEG, Photoshop PSD, and MPEG-3/MPEG-4/AVI/MKV files. If worst comes to worst, I'll just design my own sector scanner and use some simple heuristic-driven analysis to recover raw binary blocks of data from the disk which appears to match the structures of the above file types. I am unfamiliar with the exact workings of NTFS but used to be proficient at recovering FAT32 systems with just a hex-editor, so I can provide any useful diagnostic information if you let me know how to find it! My priorities in ascending order of importance for choosing the accepted answer: Restores directory structure Recovers many filenames in addition to the file data Is free / very cheap Runs on Linux Recovers a majority of file data The last point is the most important, but the more of the higher points you match the more rep you'll probably get :)

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• Any "Magic Tricks" For Getting Data Back After Windows 7 Install

  - by user163757

  My old man installed Windows 7 without making a proper backup, and now realizes he left behind some important data. He did a true "clean install", so there is no Windows.old folder in the root directory. However, I believe the format performed on the hard drive was only a quick format, so I am hoping there is some chance at data recovery. I took his hard drive out, and have spent a majority of the weekend researching data recovery options. I paid $70 for the GetDataBack software, but have had little success with it. I can see all of the files I want to restore, however they appear corrupt when I try to open them. With that all being said, does anyone know of a viable way to recover some of this data, or is it a lost cause all together?

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• raid 0 data recovery?

  - by Fred

  HI All, I have two identical seagate 7200.9 500Gb drives confiured as a RAID 0 spanned disk in windows. One of the drives has lost power and wont spin up at all. I know this normally means death for the data on both drives but i have a cunning plan.. DISK 1 - NO POWER RAID 0 DISK DISK 2 - FULLY FUNCTIONAL RAID 0 DISK DISK 3 - FULLY FUNCTIONAL SPARE DISK Copy the working drive (disk 2) data to a third 500GB DISK (disk 3), remove the logic board from the working disk (disk 2) and replace it with the non working logic board on the broken drive (disk 1) , then hopefully recreate the RAID 0 with disk 1 and disk 3, just long enough to get the data off it. Hope this makes sense, here are my questions: Windows disk manager atm recognises disk 2 but wont let me access it in anyway, therefore copying the data off it (or getting a disk image) cant be done in windows. Does anyone know of any software (in linux or self booting) that would allow me to access this disk? Anyone know of any software that will recreate the spanned drive off two disk images Am i missing any key information that means i definitely shouldn't even bother starting this, i know its a long shot anyway but its worth a try unless i definitely cant do it. The irritating thing is that i am sure its a logic board failure on disk 1 as it simply wont power up at all, suddenly no signs of life, so i am sure the data is intact! Any help would be really appreciated! Thanks

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• Summing up spreadsheet data when a column contains “#N/A”

  - by Doris

  I am using Goggle Spreadsheet to work up some historical stock data and I use a Google function (=googlefinance=…) to import the historical closing prices for a stock, then I work with that data further. But, in that list of data generated from the =googlefinance=… function, one of the amounts comes up as #N/A. I don’t know why, but it happens for various symbols that I have tried. When I use a max function on the array, which includes the N/A line, the max function does not come up with anything but an N/A, so the N/A throws off any further functions. I thought I’d create a second column to the right of the imported data in which I can give it an IF function, something like, If ((A1 <0), "0", A1), with the expectation that it would return 0 if cell A1 is the N/A, and the cell value if it is not N/A. However, this still returns N/A. I also tried an IS BLANK function but that resulted in the same NA. Does anyone have any suggestions for a workaround to eliminate the N/A from an array of numbers that I am trying to work with?

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• TDWI World Conference Features Oracle and Big Data

  - by Mandy Ho

  Oracle is a Gold Sponsor at this year's TDWI World Conference Series, held at the Manchester Grand Hyatt in San Diego, California - July 31 to Aug 1. The theme of this event is Big Data Tipping Point: BI Strategies in the Era of Big Data. The conference features an educational look at how data is now being generated so quickly that organizations across all industries need new technologies to stay ahead - to understand customer behavior, detect fraud, improve processes and accelerate performance. Attendees will hear how the internet, social media and streaming data are fundamentally changing business intelligence and data warehousing. Big data is reaching critical mass - the tipping point. Oracle will be conducting the following Evening Workshop. To reserve your space, call 1.800.820.5592 ext 10775. Title...:    Integrating Big Data into Your Data Center (or A Big Data Reference Architecture) Date.:    Wed., August 1, 2012, at 7:00 p.m Venue:: Manchester Grand Hyatt, San Diego, Room Weblogs, Social Media, smart meters, senors and other devices generate high volumes of low density information that isn't readily accessible in enterprise data warehouses and business intelligence applications today. But, this data can have relevant business value, especially when analyzed alongside traditional information sources. In this session, we will outline a reference architecture for big data that will help you maximize the value of your big data implementation. You will learn: The key technologies in a big architecture, and their specific use case The integration point of the various technologies and how they fit into your existing IT environment How effectively leverage analytical sandboxes for data discovery and agile development of data driven solutions   At the end of this session you will understand the reference architecture and have the tools to implement this architecture at your company. Presenter: Jean-Pierre Dijcks, Senior Principal Product Manager Don't miss our booth and the chance to meet with our Big data experts on the exhibition floor at booth #306. 

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• How do you encode Algebraic Data Types in a C#- or Java-like language?

  - by Jörg W Mittag

  There are some problems which are easily solved by Algebraic Data Types, for example a List type can be very succinctly expressed as: data ConsList a = Empty | ConsCell a (ConsList a) consmap f Empty = Empty consmap f (ConsCell a b) = ConsCell (f a) (consmap f b) l = ConsCell 1 (ConsCell 2 (ConsCell 3 Empty)) consmap (+1) l This particular example is in Haskell, but it would be similar in other languages with native support for Algebraic Data Types. It turns out that there is an obvious mapping to OO-style subtyping: the datatype becomes an abstract base class and every data constructor becomes a concrete subclass. Here's an example in Scala: sealed abstract class ConsList[+T] { def map[U](f: T => U): ConsList[U] } object Empty extends ConsList[Nothing] { override def map[U](f: Nothing => U) = this } final class ConsCell[T](first: T, rest: ConsList[T]) extends ConsList[T] { override def map[U](f: T => U) = new ConsCell(f(first), rest.map(f)) } val l = (new ConsCell(1, new ConsCell(2, new ConsCell(3, Empty))) l.map(1+) The only thing needed beyond naive subclassing is a way to seal classes, i.e. a way to make it impossible to add subclasses to a hierarchy. How would you approach this problem in a language like C# or Java? The two stumbling blocks I found when trying to use Algebraic Data Types in C# were: I couldn't figure out what the bottom type is called in C# (i.e. I couldn't figure out what to put into class Empty : ConsList< ??? >) I couldn't figure out a way to seal ConsList so that no subclasses can be added to the hierarchy What would be the most idiomatic way to implement Algebraic Data Types in C# and/or Java? Or, if it isn't possible, what would be the idiomatic replacement?

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• Why is my ServiceOperation method missing from my WCF Data Services client proxy code?

  - by Kev

  I have a simple WCF Data Services service and I want to expose a Service Operation as follows: [System.ServiceModel.ServiceBehavior(IncludeExceptionDetailInFaults = true)] public class ConfigurationData : DataService<ProductRepository> { // This method is called only once to initialize service-wide policies. public static void InitializeService(IDataServiceConfiguration config) { config.SetEntitySetAccessRule("*", EntitySetRights.ReadMultiple | EntitySetRights.ReadSingle); config.SetServiceOperationAccessRule("*", ServiceOperationRights.All); config.UseVerboseErrors = true; } // This operation isn't getting generated client side [WebGet] public IQueryable<Product> GetProducts() { // Simple example for testing return (new ProductRepository()).Product; } Why isn't the GetProducts method visible when I add the service reference on the client?

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• How to Convert multiple sets of Data going from left to right to top to bottom the Pythonic way?

  - by ThinkCode

  Following is a sample of sets of contacts for each company going from left to right. ID Company ContactFirst1 ContactLast1 Title1 Email1 ContactFirst2 ContactLast2 Title2 Email2 1 ABC John Doe CEO [email protected] Steve Bern CIO [email protected] How do I get them to go top to bottom as shown? ID Company Contactfirst ContactLast Title Email 1 ABC John Doe CEO [email protected] 1 ABC Steve Bern CIO [email protected] I am hoping there is a Pythonic way of solving this task. Any pointers or samples are really appreciated! p.s : In the actual file, there are 10 sets of contacts going from left to right and there are few thousand such records. It is a CSV file and I loaded into MySQL to manipulate the data.

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• How to add data manually in core data entity

  - by pankaj

  Hi I am working on core data for the first time. I have just created an entity and attributes for that entity. I want to add some data inside the entity(u can say i want to add data in a table), earlier i when i was using sqlite, i would add data using terminal. But here in core data i am not able to find a place where i can manually add data. I just want to add data in entity and display it in a UITableView. I have gone through the the documentation of core data but it does not explain how to add data manually although it explains how i can add it programmiticaly but i dont need to do it programically. I want to do it manually. Thanks in advance

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• How do I set default values on new properties for existing entities after light weight core data migration?

  - by Moritz

  I've successfully completed light weight migration on my core data model. My custom entity Vehicle received a new property 'tirePressure' which is an optional property of type double with the default value 0.00. When 'old' Vehicles are fetched from the store (Vehicles that were created before the migration took place) the value for their 'tirePressure' property is nil. (Is that expected behavior?) So I thought: "No problem, I'll just do this in the Vehicle class:" - (void)awakeFromFetch { [super awakeFromFetch]; if (nil == self.tirePressure) { [self willChangeValueForKey:@"tirePressure"]; self.tirePressure = [NSNumber numberWithDouble:0.0]; [self didChangeValueForKey:@"tirePressure"]; } } Since "change processing is explicitly disabled around" awakeFromFetch I thought the calls to willChangeValueForKey and didChangeValueForKey would mark 'tirePresure' as dirty. But they don't. Every time these Vehicles are fetched from the store 'tirePressure' continues to be nil despite having saved the context.

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• What is a good approach for a Data Access Layer?

  - by Adil Mughal

  Our software is a customized Human Resource Management System (HRMS) using ASP.NET with Oracle as the database and now we are actually moving to make it a product that supports multiple tenants with their own databases. Our options: Use NHibernate to support Multiple databases and use of OO. But we concern related to NHibernate learning curve and any problem we faced. Make a generalized DAL which will continue working with Oracle using stored procedures and use tools to convert it to other databases such as SQL Server or MySql. There is a risk associated with having to support multiple database-dependent versions of a single script. Provide the software as a Service (SaaS) and maintain the way we conduct business. However there can may be clients who do not want or trust the Cloud or other SaaS business models. With this in mind, what's the best Data access layer technique?

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• How do you verify the correct data is in a data mart?

  - by blockcipher

  I'm working on a data warehouse and I'm trying to figure out how to best verify that data from our data cleansing (normalized) database makes it into our data marts correctly. I've done some searches, but the results so far talk more about ensuring things like constraints are in place and that you need to do data validation during the ETL process (E.g. dates are valid, etc.). The dimensions were pretty easy as I could easily either leverage the primary key or write a very simple and verifiable query to get the data. The fact tables are more complex. Any thoughts? We're trying to make this very easy for a subject matter export to run a couple queries, see some data from both the data cleansing database and the data marts, and visually compare the two to ensure they are correct.

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• Select data from three different tables with null data

  - by user3678972

  I am new in Sql. My question is how to get data from three different tables with null values. I have tried a query as below: SELECT * FROM [USER] JOIN [Location] ON ([Location].UserId = [USER].Id) JOIN [ParentChild] ON ([ParentChild].UserId = [USER].Id) WHERE ParentId=7 which I find from this link. Its working fine but, it not fetches all and each data associated with the ParentId Something like it only fetches data which are available in all tables, but also omits some data which not available in Location tables but it comes under the given ParentId. For example: UserId ParentId 1 7 8 7 For userId 8, there is data available in Location table,so it fetches all data. But there is no data for userId 1 available in Location table, so the query didn't work for this. But I want all and every data. If there is no data for userId then it can return only null columns. Is it possible ?? hope everyone can understand my problem.

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• How does Core Data determine if an NSObjects data can be dropped?

  - by Kevin

  In the app I am working on now I was storing about 500 images in Core Data. I have since pulled those images out and store them in the file system now, but in the process I found that the app would crash on the device if I had an array of 500 objects with image data in them. An array with 500 object ids with the image data in those objects worked fine. The 500 objects without the image data also worked fine. I found that I got the best performance with both an array of object ids and image data stored on the filesystem instead of in core data. The conclusion I came to was that if I had an object in an array that told Core Data I was "using" that object and Core Data would hold on to the data. Is this correct?

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• How to handle encryption key conflicts when synchronizing data?

  - by Rafael

  Assume that there is data that gets synchronized between several devices. The data is protected with a symmetric encryption algorithm and a key. The key is stored on each device and encrypted with a password. When a user changes the password only the key gets re-encrypted. Under normal circumstances, when there is a good network connection to other peers, the current key gets synchronized and all data on the new device gets encrypted with the same key. But how to handle situations where a new device doesn’t have a network connection and e.g. creates its own new, but incompatible key? How to keep the usability as high as possible under such circumstances? The application could detect that there is no network and hence refuse to start. That’s very bad usability in my opinion, because the application isn’t functional at all in this case. I don’t consider this a solution. The application could ignore the missing network connection and create a new key. But what to do when the application gains a network connection? There will be several incompatible keys and some parts of the underlying data could only be encrypted with one key and other parts with another key. The situation would get worse if there would be more keys than just two and the application would’ve to ask every time for a password when another object that should get decrypted with another key would be needed. It is very messy and time consuming to try to re-encrypt all data that is encrypted with another key with a main key. What should be the main key at all in this case? The oldest key? The key with the most encrypted objects? What if the key got synchronized but not all objects that got encrypted with this particular key? How should the user know for which particular password the application asks and why it takes probably very long to re-encrypt the data? It’s very hard to describe encryption “issues” to users. So far I didn’t find an acceptable solution, nor some kind of generic strategy. Do you have some hints about a concrete strategy or some books / papers that describe synchronization of symmetrically encrypted data with keys that could cause conflicts?

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• How to switch from Core Data automatic lightweight migration to manual?

  - by Jaanus

  My situation is similar to this question. I am using lightweight migration with the following code, fairly vanilla from Apple docs and other SO threads. It runs upon app startup when initializing the Core Data stack. NSDictionary *options = [NSDictionary dictionaryWithObjectsAndKeys: [NSNumber numberWithBool:YES], NSMigratePersistentStoresAutomaticallyOption, [NSNumber numberWithBool:YES], NSInferMappingModelAutomaticallyOption, nil]; NSError *error = nil; NSString *storeType = nil; if (USE_SQLITE) { // app configuration storeType = NSSQLiteStoreType; } else { storeType = NSBinaryStoreType; } persistentStoreCoordinator = [[NSPersistentStoreCoordinator alloc] initWithManagedObjectModel:[self managedObjectModel]]; // the following line sometimes crashes on app startup if (![persistentStoreCoordinator addPersistentStoreWithType:storeType configuration:nil URL:[self persistentStoreURL] options:options error:&error]) { // handle the error } For some users, especially with slower devices, I have crashes confirmed by logs at the indicated line. I understand that a fix is to switch this to manual mapping and migration. What is the recipe to do that? The long way for me would be to go through all Apple docs, but I don't recall there being good examples and tutorials specifically for schema migration.

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• Core data migration failing with "Can't find model for source store" but managedObjectModel for source is present

  - by Ira Cooke

  I have a cocoa application using core-data, which is now at the 4th version of its managed object model. My managed object model contains abstract entities but so far I have managed to get migration working by creating appropriate mapping models and creating my persistent store using addPersistentStoreWithType:configuration:options:error and with the NSMigratePersistentStoresAutomaticallyOption set to YES. NSDictionary *optionsDictionary = [NSDictionary dictionaryWithObject:[NSNumber numberWithBool:YES] forKey:NSMigratePersistentStoresAutomaticallyOption]; NSURL *url = [NSURL fileURLWithPath: [applicationSupportFolder stringByAppendingPathComponent: @"MyApp.xml"]]; NSError *error=nil; [theCoordinator addPersistentStoreWithType:NSXMLStoreType configuration:nil URL:url options:optionsDictionary error:&error] This works fine when I migrate from model version 3 to 4, which is a migration that involves adding attributes to several entities. Now when I try to add a new model version (version 5), the call to addPersistentStoreWithType returns nil and the error remains empty. The migration from 4 to 5 involves adding a single attribute. I am struggling to debug the problem and have checked all the following; The source database is in fact at version 4 and the persistentStoreCoordinator's managed object model is at version 5. The 4-5 mapping model as well as managed object models for versions 4 and 5 are present in the resources folder of my built application. I've tried various model upgrade paths. Strangely I find that upgrading from an early version 3 - 5 works .. but upgrading from 4 - 5 fails. I've tried adding a custom entity migration policy for migration of the entity whose attributes are changing ... in this case I overrode the method beginEntityMapping:manager:error: . Interestingly this method does get called when migration works (ie when I migrate from 3 to 4, or from 3 to 5 ), but it does not get called in the case that fails ( 4 to 5 ). I'm pretty much at a loss as to where to proceed. Any ideas to help debug this problem would be much appreciated.

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