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  • PostgreSQL: Why does this simple query not use the index?

    - by David
    I have a table t with a column c, which is an int and has a btree index on it. Why does the following query not utilize this index? explain select c from t group by c; The result I get is: HashAggregate (cost=1005817.55..1005817.71 rows=16 width=4) -> Seq Scan on t (cost=0.00..946059.84 rows=23903084 width=4) My understanding of indexes is limited, but I thought such queries were the purpose of indexes.

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  • postgresql duplicate table names best practice

    - by veilig
    My company has a handful of apps that we deploy in the websites we build. Recently a very old app needed to be included along side a newer app and there was a conflict w/ a duplicate table name needed to be used by both apps. We are now in the process of updating an old app and there will be some DB updates. I'm curious what people consider best practice (or how do you do it) to help ensure these name collisions don't happen. I've looked at schema's but not sure if thats the right path we want to take. As the documentation prescribes, I don't want to "wire" a particular schema name into an application and if I add schema's to the user search path how would it know which table I was referring to if two schema's have the same table name. although, maybe I'm reading to much into this. Any insights or words of wisdom would be greatly appreciated!

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  • database modeling for google app engine for multiple revison of entity.

    - by iamgopal
    hi, in my application ( kind of wiki clone ) - an article is frequently changing. and i need to track all changes that are done on that article. { text only. } one crude way i have done it, is to add a datetime property and create a new entity everytime something change. which is too much database wasting. { and also un-necessary index waste too. } and also need to re-create parent-child and entity relationships. i also have log which can show changes -- but i want some thing easier , so that jumping from one version to another version could be easier. ideas ? thanks.

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  • Using a user-defined type as a primary key

    - by Chris Kaminski
    Suppose I have a system where I have metadata such as: table: ====== key name address ... Then suppose I have a user-defined type described as so: datasource datasource-key A) are there systems where it's possible to have keys based on user-defined types? B) if so, how do you decompose the keys into a form suitable for querying? C) is this a case where I'm just better off with a composite primary key?

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  • rake db:migrate and rake db:create both work on test database, not development database

    - by geography_guy
    I am new to Stack Overflow and Ruby on Rails. My problem is, when I run the command rake db:create or rake db:migrate, the test database is affected, but the development database is not. rails (3.2.2) my database.yml: # Warning: The database defined as "test" will be erased and # re-generated from your development database when you run "rake". # Do not set this db to the same as development or production. test: &test adapter: postgresql encoding: unicode database: ticketee_test pool: 5 username: ticketee password: my_password_here development: adapter: postgresql encoding: unicode database: ticketee_development pool: 5 username: ticketee password: my_password_here production: adapter: postgresql encoding: unicode database: ticketee_production pool: 5 username: ticketee password: my_password_here cucumber: <<: *test

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  • What db fits me?

    - by afvasd
    Dear Everyone I am currently using mysql. I am finding that my schema is getting incredibly complicated. I seek to find a new db that will suit my needs: Let's assume I am building a news aggregrator (which collects news from multiple website). I then run algorithms to determine if two news from different sites are actually referring to the same topic. I run this algorithm to cluster news together. The relationship is depicted below: cluster \--news1 \--word1 \--word2 \--news2 \--word3 \--news3 \--word1 \--word3 And then I will apply some magic and determine the importance of each word. Summing all the importance of each word gives me the importance of a news article. Summing the importance of each news article gives me the importance of a cluster. Note that above cluster there are also subgroups( like split by region etc), and categories (like sports, etc) which I have to determine the importance of that in a particular day per se. I have used views in the past to do so, but I realized that views are very slow. So i will normally do an insert into an actual table and index them for better performance. As you can see this leads to multiple tables derived like (cluster, importance), (news, importance), (words, importance) etc which can get pretty messy. Also the "importance" metric will change. It has become increasingly difficult to alter tables, update data (which I am using TRUNCATE TABLE) and then inserting from null. I am currently looking into something schemaless like Mongodb. I do not need distributedness. I would very much want something that is reasonably fast (which can be indexed) and something that is a lot more flexible that traditional RDMBS. Also, I need something that has some kind of ORM because I personally like ORM a lot. I am currently using sqlalchemy Please help!

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  • SQL SERVER – Fastest Way to Restore the Database

    - by pinaldave
    A few days ago, I received following email: “Pinal, We are in an emergency situation. We have a large database of around 80+ GB and its backup is of 50+ GB in size. We need to restore this database ASAP and use it; however, restoring the database takes forever. Do you think a compressed backup would solve our problem? Any other ideas you got?” First of all, the asker has already answered his own question. Yes; I have seen that if you are using a compressed backup, it takes lesser time when you try to restore a database. I have previously blogged about the same subject. Here are the links to those blog posts: SQL SERVER – Data and Page Compressions – Data Storage and IO Improvement SQL SERVER – 2008 – Introduction to Row Compression SQL SERVER – 2008 – Introduction to New Feature of Backup Compression However, if your database is very large that it still takes a few minutes to restore the database even though you use any of the features listed above, then it will really take some time to restore the database. If there is urgency and there is no time you can spare for restoring the database, then you can use the wonderful tool developed by Idera called virtual database. This tool restores a certain database in just a few seconds so it will readily be available for usage. I have in depth written my experience with this tool in the article here SQL SERVER – Retrieve and Explore Database Backup without Restoring Database – Idera virtual database. Let me know your experience in this scenario. Have you ever needed your database backup restored very quickly, what did you do in that scenario. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, Readers Question, SQL, SQL Authority, SQL Backup and Restore, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • EM12c Release 4: Database as a Service Enhancements

    - by Adeesh Fulay
    Oracle Enterprise Manager 12.1.0.4 (or simply put EM12c R4) is the latest update to the product. As previous versions, this release provides tons of enhancements and bug fixes, attributing to improved stability and quality. One of the areas that is most exciting and has seen tremendous growth in the last few years is that of Database as a Service. EM12c R4 provides a significant update to Database as a Service. The key themes are: Comprehensive Database Service Catalog (includes single instance, RAC, and Data Guard) Additional Storage Options for Snap Clone (includes support for Database feature CloneDB) Improved Rapid Start Kits Extensible Metering and Chargeback Miscellaneous Enhancements 1. Comprehensive Database Service Catalog Before we get deep into implementation of a service catalog, lets first understand what it is and what benefits it provides. Per ITIL, a service catalog is an exhaustive list of IT services that an organization provides or offers to its employees or customers. Service catalogs have been widely popular in the space of cloud computing, primarily as the medium to provide standardized and pre-approved service definitions. There is already some good collateral out there that talks about Oracle database service catalogs. The two whitepapers i recommend reading are: Service Catalogs: Defining Standardized Database Service High Availability Best Practices for Database Consolidation: The Foundation for Database as a Service [Oracle MAA] EM12c comes with an out-of-the-box service catalog and self service portal since release 1. For the customers, it provides the following benefits: Present a collection of standardized database service definitions, Define standardized pools of hardware and software for provisioning, Role based access to cater to different class of users, Automated procedures to provision the predefined database definitions, Setup chargeback plans based on service tiers and database configuration sizes, etc Starting Release 4, the scope of services offered via the service catalog has been expanded to include databases with varying levels of availability - Single Instance (SI) or Real Application Clusters (RAC) databases with multiple data guard based standby databases. Some salient points of the data guard integration: Standby pools can now be defined across different datacenters or within the same datacenter as the primary (this helps in modelling the concept of near and far DR sites) The standby databases can be single instance, RAC, or RAC One Node databases Multiple standby databases can be provisioned, where the maximum limit is determined by the version of database software The standby databases can be in either mount or read only (requires active data guard option) mode All database versions 10g to 12c supported (as certified with EM 12c) All 3 protection modes can be used - Maximum availability, performance, security Log apply can be set to sync or async along with the required apply lag The different service levels or service tiers are popularly represented using metals - Platinum, Gold, Silver, Bronze, and so on. The Oracle MAA whitepaper (referenced above) calls out the various service tiers as defined by Oracle's best practices, but customers can choose any logical combinations from the table below:  Primary  Standby [1 or more]  EM 12cR4  SI  -  SI  SI  RAC -  RAC SI  RAC RAC  RON -  RON RON where RON = RAC One Node is supported via custom post-scripts in the service template A sample service catalog would look like the image below. Here we have defined 4 service levels, which have been deployed across 2 data centers, and have 3 standardized sizes. Again, it is important to note that this is just an example to get the creative juices flowing. I imagine each customer would come up with their own catalog based on the application requirements, their RTO/RPO goals, and the product licenses they own. In the screenwatch titled 'Build Service Catalog using EM12c DBaaS', I walk through the complete steps required to setup this sample service catalog in EM12c. 2. Additional Storage Options for Snap Clone In my previous blog posts, i have described the snap clone feature in detail. Essentially, it provides a storage agnostic, self service, rapid, and space efficient approach to solving your data cloning problems. The net benefit is that you get incredible amounts of storage savings (on average 90%) all while cloning databases in a matter of minutes. Space and Time, two things enterprises would love to save on. This feature has been designed with the goal of providing data cloning capabilities while protecting your existing investments in server, storage, and software. With this in mind, we have pursued with the dual solution approach of Hardware and Software. In the hardware approach, we connect directly to your storage appliances and perform all low level actions required to rapidly clone your databases. While in the software approach, we use an intermediate software layer to talk to any storage vendor or any storage configuration to perform the same low level actions. Thus delivering the benefits of database thin cloning, without requiring you to drastically changing the infrastructure or IT's operating style. In release 4, we expand the scope of options supported by snap clone with the addition of database CloneDB. While CloneDB is not a new feature, it was first introduced in 11.2.0.2 patchset, it has over the years become more stable and mature. CloneDB leverages a combination of Direct NFS (or dNFS) feature of the database, RMAN image copies, sparse files, and copy-on-write technology to create thin clones of databases from existing backups in a matter of minutes. It essentially has all the traits that we want to present to our customers via the snap clone feature. For more information on cloneDB, i highly recommend reading the following sources: Blog by Tim Hall: Direct NFS (DNFS) CloneDB in Oracle Database 11g Release 2 Oracle OpenWorld Presentation by Cern: Efficient Database Cloning using Direct NFS and CloneDB The advantages of the new CloneDB integration with EM12c Snap Clone are: Space and time savings Ease of setup - no additional software is required other than the Oracle database binary Works on all platforms Reduce the dependence on storage administrators Cloning process fully orchestrated by EM12c, and delivered to developers/DBAs/QA Testers via the self service portal Uses dNFS to delivers better performance, availability, and scalability over kernel NFS Complete lifecycle of the clones managed by EM12c - performance, configuration, etc 3. Improved Rapid Start Kits DBaaS deployments tend to be complex and its setup requires a series of steps. These steps are typically performed across different users and different UIs. The Rapid Start Kit provides a single command solution to setup Database as a Service (DBaaS) and Pluggable Database as a Service (PDBaaS). One command creates all the Cloud artifacts like Roles, Administrators, Credentials, Database Profiles, PaaS Infrastructure Zone, Database Pools and Service Templates. Once the Rapid Start Kit has been successfully executed, requests can be made to provision databases and PDBs from the self service portal. Rapid start kit can create complex topologies involving multiple zones, pools and service templates. It also supports standby databases and use of RMAN image backups. The Rapid Start Kit in reality is a simple emcli script which takes a bunch of xml files as input and executes the complete automation in a matter of seconds. On a full rack Exadata, it took only 40 seconds to setup PDBaaS end-to-end. This kit works for both Oracle's engineered systems like Exadata, SuperCluster, etc and also on commodity hardware. One can draw parallel to the Exadata One Command script, which again takes a bunch of inputs from the administrators and then runs a simple script that configures everything from network to provisioning the DB software. Steps to use the kit: The kit can be found under the SSA plug-in directory on the OMS: EM_BASE/oracle/MW/plugins/oracle.sysman.ssa.oms.plugin_12.1.0.8.0/dbaas/setup It can be run from this default location or from any server which has emcli client installed For most scenarios, you would use the script dbaas/setup/database_cloud_setup.py For Exadata, special integration is provided to reduce the number of inputs even further. The script to use for this scenario would be dbaas/setup/exadata_cloud_setup.py The database_cloud_setup.py script takes two inputs: Cloud boundary xml: This file defines the cloud topology in terms of the zones and pools along with host names, oracle home locations or container database names that would be used as infrastructure for provisioning database services. This file is optional in case of Exadata, as the boundary is well know via the Exadata system target available in EM. Input xml: This file captures inputs for users, roles, profiles, service templates, etc. Essentially, all inputs required to define the DB services and other settings of the self service portal. Once all the xml files have been prepared, invoke the script as follows for PDBaaS: emcli @database_cloud_setup.py -pdbaas -cloud_boundary=/tmp/my_boundary.xml -cloud_input=/tmp/pdb_inputs.xml          The script will prompt for passwords a few times for key users like sysman, cloud admin, SSA admin, etc. Once complete, you can simply log into EM as the self service user and request for databases from the portal. More information available in the Rapid Start Kit chapter in Cloud Administration Guide.  4. Extensible Metering and Chargeback  Last but not the least, Metering and Chargeback in release 4 has been made extensible in all possible regards. The new extensibility features allow customer, partners, system integrators, etc to : Extend chargeback to any target type managed in EM Promote any metric in EM as a chargeback entity Extend list of charge items via metric or configuration extensions Model abstract entities like no. of backup requests, job executions, support requests, etc  A slew of emcli verbs have also been added that allows administrators to create, edit, delete, import/export charge plans, and assign cost centers all via the command line. More information available in the Chargeback API chapter in Cloud Administration Guide. 5. Miscellaneous Enhancements There are other miscellaneous, yet important, enhancements that are worth a mention. These mostly have been asked by customers like you. These are: Custom naming of DB Services Self service users can provide custom names for DB SID, DB service, schemas, and tablespaces Every custom name is validated for uniqueness in EM 'Create like' of Service Templates Now creating variants of a service template is only a click away. This would be vital when you publish service templates to represent different database sizes or service levels. Profile viewer View the details of a profile like datafile, control files, snapshot ids, export/import files, etc prior to its selection in the service template Cleanup automation - for failed and successful requests Single emcli command to cleanup all remnant artifacts of a failed request Cleanup can be performed on a per request bases or by the entire pool As an extension, you can also delete successful requests Improved delete user workflow Allows administrators to reassign cloud resources to another user or delete all of them Support for multiple tablespaces for schema as a service In addition to multiple schemas, user can also specify multiple tablespaces per request I hope this was a good introduction to the new Database as a Service enhancements in EM12c R4. I encourage you to explore many of these new and existing features and give us feedback. Good luck! References: Cloud Management Page on OTN Cloud Administration Guide [Documentation] -- Adeesh Fulay (@adeeshf)

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  • Automated backups for Windows Azure SQL Database

    - by Greg Low
    One of the questions that I've often been asked is about how you can backup databases in Windows Azure SQL Database. What we have had access to was the ability to export a database to a BACPAC. A BACPAC is basically just a zip file that contains a bunch of metadata along with a set of bcp files for each of the tables in the database. Each table in the database is exported one after the other, so this does not produce a transactionally-consistent backup at a specific point in time. To get a transactionally-consistent copy, you need a database that isn't in use.The easiest way to get a database that isn't in use is to use CREATE DATABASE AS COPY OF. This creates a new database as a transactionally-consistent copy of the database that you are copying. You can then use the export options to get a consistent BACPAC created.Previously, I've had to automate this process by myself. Given there was also no SQL Agent in Azure, I used a job in my on-premises SQL Server to do this, using a linked server configuration.Now there's a much simpler way. Windows Azure SQL Database now supports an automated export function. On the Configuration tab for the database, you need to enable the Automated Export function. You can configure how often the operation is performed for you, and which storage account will be used for the backups.It's important to consider the cost impacts of this as well. You are charged for how ever many databases are on your server on a given day. So if you enable a daily backup, you will double your database costs. Do not schedule the backups just before midnight UTC, as that could cause you to have three databases each day instead of one.This is a much needed addition to the capabilities. Scott Guthrie also posted about some other notable changes today, including a preview of a new premium offering for SQL Database. In addition to the Web and Business editions, there will now be a Premium edition that has reserved (rather than shared) resources. You can read about it all in Scott's post here: http://weblogs.asp.net/scottgu/archive/2013/07/23/windows-azure-july-updates-sql-database-traffic-manager-autoscale-virtual-machines.aspx

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  • creating tables on remote database

    - by raj
    I created a database link using database link. create public database link REMOTEDB connect to REMOTEUSER identified by REMOTEPWD using 'REMOTEDB'; then i create a table in remote db like, create table MYTABLE@REMOTEDB (name varchar2(20))); It says, ORA-02021 DDL operations are not allowed on| a remote database.. Will this Not work on any cost, or am i just missing some permissions to create ?

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  • Parsing unicode XML with Python SAX on App Engine

    - by Derek Dahmer
    I'm using xml.sax with unicode strings of XML as input, originally entered in from a web form. On my local machine (python 2.5, using the default xmlreader expat, running through app engine), it works fine. However, the exact same code and input strings on production app engine servers fail with "not well-formed". For example, it happens with the code below: from xml import sax class MyHandler(sax.ContentHandler): pass handler = MyHandler() # Both of these unicode strings return 'not well-formed' # on app engine, but work locally xml.parseString(u"<a>b</a>",handler) xml.parseString(u"<!DOCTYPE a[<!ELEMENT a (#PCDATA)> ]><a>b</a>",handler) # Both of these work, but output unicode xml.parseString("<a>b</a>",handler) xml.parseString("<!DOCTYPE a[<!ELEMENT a (#PCDATA)> ]><a>b</a>",handler) resulting in the error: File "<string>", line 1, in <module> File "/base/python_dist/lib/python2.5/xml/sax/__init__.py", line 49, in parseString parser.parse(inpsrc) File "/base/python_dist/lib/python2.5/xml/sax/expatreader.py", line 107, in parse xmlreader.IncrementalParser.parse(self, source) File "/base/python_dist/lib/python2.5/xml/sax/xmlreader.py", line 123, in parse self.feed(buffer) File "/base/python_dist/lib/python2.5/xml/sax/expatreader.py", line 211, in feed self._err_handler.fatalError(exc) File "/base/python_dist/lib/python2.5/xml/sax/handler.py", line 38, in fatalError raise exception SAXParseException: <unknown>:1:1: not well-formed (invalid token) Any reason why app engine's parser, which also uses python2.5 and expat, would fail when inputting unicode?

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  • Optimising RSS parsing on App Engine to avoid high CPU warnings

    - by Danny Tuppeny
    I'm pulling some RSS feeds into a datastore in App Engine to serve up to an iPhone app. I use cron to schedule updating the RSS every x minutes. Each task only parses one RSS feed (which has 15-20 items). I frequently get warnings about high CPU usage in the App Engine dashboard, so I'm looking for ways to optimise my code. Currently, I use minidom (since it's already there on App Engine), but I suspect it's not very efficient! Here's the code: dom = minidom.parseString(urlfetch.fetch(url).content) if dom: items = [] for node in dom.getElementsByTagName('item'): item = RssItem( key_name = self.getText(node.getElementsByTagName('guid')[0].childNodes), title = self.getText(node.getElementsByTagName('title')[0].childNodes), description = self.getText(node.getElementsByTagName('description')[0].childNodes), modified = datetime.now(), link = self.getText(node.getElementsByTagName('link')[0].childNodes), categories = [self.getText(category.childNodes) for category in node.getElementsByTagName('category')] ); items.append(item); db.put(items); def getText(self, nodelist): rc = '' for node in nodelist: if node.nodeType == node.TEXT_NODE: rc = rc + node.data return rc There isn't much going on, but the scripts often take 2-6 seconds CPU time, which seems a bit excessive for looping through 20ish items and reading a few attributes. What can I do to make this faster? Is there anything particularly bad in the above code, or should I change to another way of parsing? Are there are any libraries (that work on App Engine) that would be better, or would I be better parsing the RSS myself?

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  • Media recommendation engine - Single user system - How to start

    - by Microkernel
    Hi guys, I want to implement a media recommendation engine. I saw a similar posts on this, but I think my requirements are bit different from those, so posting here. Here is the deal. I want to implement a recommendation engine for media players like VLC, which would be an engine that has to care for only single user. Like, it would be embedded in a media player on a PC which is typically used by single user. And it will start learning the likes and dislikes of the user and gradually learns what a user likes. Here it will not be able to find similar users for using their data for recommendation as its a single user system. So how to go about this? Or you can consider it as a recommendation engine that has to be put in say iPods, which has to learn about a single user and recommend music/Movies from the collections it has. I thought of start collecting the genre of music/movies (maybe even artist name) that user watches and recommend movies from the most watched Genre, but it look very crude, isn't it? So is there any algorithms I can use or any resources I can refer up to? Regards, MicroKernel :)

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  • Google App Engine - Caching generated HTML

    - by Alexander
    I have written a Google App Engine application that programatically generates a bunch of HTML code that is really the same output for each user who logs into my system, and I know that this is going to be in-efficient when the code goes into production. So, I am trying to figure out the best way to cache the generated pages. The most probable option is to generate the pages and write them into the database, and then check the time of the database put operation for a given page against the time that the code was last updated. Then, if the code is newer than the last put to the database (for a particular HTML request), new HTML will be generated and served, and cached to the database. If the code is older than the last put to the database, then I will just get the HTML direct from the database and serve it (therefore avoiding all the CPU wastage of generating the HTML). I am not only looking to minimize load times, but to minimize CPU usage. However, one issue that I am having is that I can't figure out how to programatically check when the version of code uploaded to the app engine was updated. I am open to any suggestions on this approach, or other approaches for caching generated html. Note that while memcache could help in this situation, I believe that it is not the final solution since I really only need to re-generate html when the code is updated (as opposed to every time the memcache expires). Kind Regards, and thank you in advance for any suggestions you may be able to offer. -Alex

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  • Deploy GWT Application to Google App Engine using NetBeans

    - by Yan Cheng CHEOK
    Hello, I try to deploy a GWT application, to Google App Engine using NetBeans. I had successful run GWT sample http://code.google.com/webtoolkit/doc/latest/tutorial/create.html using Personal GlassFish v3 Prelude Domain, by 1) Copy generated source code from StockWatcher to C:\Projects\StockWatcherNetbeans\src\java\com\google\ 2) Modify C:\Projects\StockWatcherNetbeans\nbproject\gwt.properties gwt.module=com.google.gwt.stockwatcher.StockWatcher 3) Select Personal GlassFish v3 Prelude Domain, and run. All works fine! Now, I try to select Google App Engine server, and run. However, I get the error "There is no appengine web project opened!" I check... There is file called C:\Projects\StockWatcherNetbeans\war\WEB-INF\appengine-web.xml with content <?xml version="1.0" encoding="UTF-8"?> <appengine-web-app xmlns="http://appengine.google.com/ns/1.0" xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xsi:schemaLocation='http://kenai.com/projects/nbappengine/downloads/download/schema/appengine-web.xsd appengine-web.xsd'> <application>StockWatcherNetbeans</application> <version>1</version> </appengine-web-app> I am using NetBeans 6.7.1 GWT4NB (GWT Plugin for NetBeans) 2.6.12 Google App Engine plugin for NetBeans from http://kenai.com/downloads/nbappengine/1.0_NetBeans671/updates.xml Anything I had missed out? Even when I right click to the project, the Deploy to Google App Engine options is disabled. And yes, please do not ask me why not use Eclipse.

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  • Best Practices For Database Consolidation On Exadata - New Whitepapers

    - by Javier Puerta
     Best Practices For Database Consolidation On Exadata Database Machine (Nov. 2011) Consolidation can minimize idle resources, maximize efficiency, and lower costs when you host multiple schemas, applications or databases on a target system. Consolidation is a core enabler for deploying Oracle database on public and private clouds.This paper provides the Exadata Database Machine (Exadata) consolidation best practices to setup and manage systems and applications for maximum stability and availability:Download here Oracle Exadata Database Machine Consolidation: Segregating Databases and Roles (Sep. 2011) This paper is focused on the aspects of segregating databases from each other in a platform consolidation environment on an Oracle Exadata Database Machine. Platform consolidation is the consolidation of multiple databases on to a single Oracle Exadata Database Machine. When multiple databases are consolidated on a single Database Machine, it may be necessary to isolate certain database components or functions in order to meet business requirements and provide best practices for a secure consolidation. In this paper we outline the use of Oracle Exadata database-scoped security to securely separate database management and provide a detailed case study that illustrates the best practices. Download here

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  • Which design better when use foreign key instead of a string to store a list of id

    - by Kien Thanh
    I'm building online examination system. I have designed to table, Question and GeneralExam. The table GeneralExam contains info about the exam like name, description, duration,... Now I would like to design table GeneralQuestion, it will contain the ids of questions belongs to a general exam. Currently, I have two ideas to design GeneralQuestion table: It will have two columns: general_exam_id, question_id. It will have two columns: general_exam_id, list_question_ids (string/text). I would like to know which designing is better, or pros and cons of each designing. I'm using Postgresql database.

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  • Database-as-a-Service on Exadata Cloud

    - by Gagan Chawla
    Note – Oracle Enterprise Manager 12c DBaaS is platform agnostic and is designed to work on Exadata/non-Exadata, physical/virtual, Oracle/non Oracle platforms and it’s not a mandatory requirement to use Exadata as the base platform. Database-as-a-Service (DBaaS) is an important trend these days and the top business drivers motivating customers towards private database cloud model include constant pressure to reduce IT Costs and Complexity, and also to be able to improve Agility and Quality of Service. The first step many enterprises take in their journey towards cloud computing is to move to a consolidated and standardized environment and Exadata being already a proven best-in-class popular consolidation platform, we are seeing now more and more customers starting to evolve from Exadata based platform into an agile self service driven private database cloud using Oracle Enterprise Manager 12c. Together Exadata Database Machine and Enterprise Manager 12c provides industry’s most comprehensive and integrated solution to transform from a typical silo’ed environment into enterprise class database cloud with self service, rapid elasticity and pay-per-use capabilities.   In today’s post, I’ll list down the important steps to enable DBaaS on Exadata using Enterprise Manager 12c. These steps are chalked down based on a recent DBaaS implementation from a real customer engagement - Project Planning - First step involves defining the scope of implementation, mapping functional requirements and objectives to use cases, defining high availability, network, security requirements, and delivering the project plan. In a Cloud project you plan around technology, business and processes all together so ensure you engage your actual end users and stakeholders early on in the project right from the scoping and planning stage. Setup your EM 12c Cloud Control Site – Once the project plan approval and sign off from stakeholders is achieved, refer to EM 12c Install guide and these are some important tips to follow during the site setup phase - Review the new EM 12c Sizing paper before you get started with install Cloud, Chargeback and Trending, Exadata plug ins should be selected to deploy during install Refer to EM 12c Administrator’s guide for High Availability, Security, Network/Firewall best practices and options Your management and managed infrastructure should not be combined i.e. EM 12c repository should not be hosted on same Exadata where target Database Cloud is to be setup Setup Roles and Users – Cloud Administrator (EM_CLOUD_ADMINISTRATOR), Self Service Administrator (EM_SSA_ADMINISTRATOR), Self Service User (EM_SSA_USER) are the important roles required for cloud lifecycle management. Roles and users are managed by Super Administrator via Setup menu –> Security option. For Self Service/SSA users custom role(s) based on EM_SSA_USER should be created and EM_USER, PUBLIC roles should be revoked during SSA user account creation. Configure Software Library – Cloud Administrator logs in and in this step configures software library via Enterprise menu –> provisioning and patching option and the storage location is OMS shared filesystem. Software Library is the centralized repository that stores all software entities and is often termed as ‘local store’. Setup Self Update – Self Update is one of the most innovative and cool new features in EM 12c framework. Self update can be accessed via Setup -> Extensibility option by Super Administrator and is the unified delivery mechanism to get all new and updated entities (Agent software, plug ins, connectors, gold images, provisioning bundles etc) in EM 12c. Deploy Agents on all Compute nodes, and discover Exadata targets – Refer to Exadata discovery cookbook for detailed walkthrough to ensure successful discovery of Exadata targets. Configure Privilege Delegation Settings – This step involves deployment of privilege setting template on all the nodes by Super Administrator via Setup menu -> Security option with the option to define whether to use sudo or powerbroker for all provisioning and patching operations. Provision Grid Infrastructure with RAC Database on Compute Nodes – Software is provisioned in this step via a provisioning profile using EM 12c database provisioning. In case of Exadata, Grid Infrastructure and RAC Database software is already deployed on compute nodes via OneCommand from Oracle, so SSA Administrator just needs to discover Oracle Homes and Listener as EM targets. Databases will be created as and when users request for databases from cloud. Customize Create Database Deployment Procedure – the actual database creation steps are "templatized" in this step by Self Service Administrator and the newly saved deployment procedure will be used during service template creation in next step. This is an important step and make sure you have locked all the required variables marked as locked as ‘Y’ in this table. Setup Self Service Portal – This step involves setting up of zones, user quotas, service templates, chargeback plan. The SSA portal is setup by Self Service Administrator via Setup menu -> Cloud -> Database option and following guided workflow. Refer to DBaaS cookbook for details. You also have an option to customize SSA login page via steps documented in EM 12c Cloud Administrator’s guide Final Checks – Define and document process guidelines for SSA users and administrators. Get your SSA users trained on Self Service Portal features and overall DBaaS model and SSA administrators should be familiar with Self Service Portal setup pieces, EM 12c database lifecycle management capabilities and overall EM 12c monitoring framework. GO LIVE – Announce rollout of Database-as-a-Service to your SSA users. Users can login to the Self Service Portal and request/monitor/view their databases in Exadata based database cloud. Congratulations! You just delivered a successful database cloud implementation project! In future posts, we will cover these additional useful topics around database cloud – DBaaS Implementation tips and tricks – right from setup to self service to managing the cloud lifecycle ‘How to’ enable real production databases copies in DBaaS with rapid provisioning in database cloud Case study of a customer who recently achieved success with their transformational journey from traditional silo’ed environment on to Exadata based database cloud using Enterprise Manager 12c. More Information – Podcast on Database as a Service using Oracle Enterprise Manager 12c Oracle Enterprise Manager 12c Installation and Administration guide, Cloud Administration guide DBaaS Cookbook Exadata Discovery Cookbook Screenwatch: Private Database Cloud: Set Up the Cloud Self-Service Portal Screenwatch: Private Database Cloud: Use the Cloud Self-Service Portal Stay Connected: Twitter |  Face book |  You Tube |  Linked in |  Newsletter

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  • Design Pattern for Complex Data Modeling

    - by Aaron Hayman
    I'm developing a program that has a SQL database as a backing store. As a very broad description, the program itself allows a user to generate records in any number of user-defined tables and make connections between them. As for specs: Any record generated must be able to be connected to any other record in any other user table (excluding itself...the record, not the table). These "connections" are directional, and the list of connections a record has is user ordered. Moreover, a record must "know" of connections made from it to others as well as connections made to it from others. The connections are kind of the point of this program, so there is a strong possibility that the number of connections made is very high, especially if the user is using the software as intended. A record's field can also include aggregate information from it's connections (like obtaining average, sum, etc) that must be updated on change from another record it's connected to. To conserve memory, only relevant information must be loaded at any one time (can't load the entire database in memory at load and go from there). I cannot assume the backing store is local. Right now it is, but eventually this program will include syncing to a remote db. Neither the user tables, connections or records are known at design time as they are user generated. I've spent a lot of time trying to figure out how to design the backing store and the object model to best fit these specs. In my first design attempt on this, I had one object managing all a table's records and connections. I attempted this first because it kept the memory footprint smaller (records and connections were simple dicts), but maintaining aggregate and link information between tables became....onerous (ie...a huge spaghettified mess). Tracing dependencies using this method almost became impossible. Instead, I've settled on a distributed graph model where each record and connection is 'aware' of what's around it by managing it own data and connections to other records. Doing this increases my memory footprint but also let me create a faulting system so connections/records aren't loaded into memory until they're needed. It's also much easier to code: trace dependencies, eliminate cycling recursive updates, etc. My biggest problem is storing/loading the connections. I'm not happy with any of my current solutions/ideas so I wanted to ask and see if anybody else has any ideas of how this should be structured. Connections are fairly simple. They contain: fromRecordID, fromTableID, fromRecordOrder, toRecordID, toTableID, toRecordOrder. Here's what I've come up with so far: Store all the connections in one big table. If I do this, either I load all connections at once (one big db call) or make a call every time a user table is loaded. The big issue here: the size of the connections table has the potential to be huge, and I'm afraid it would slow things down. Store in separate tables all the outgoing connections for each user table. This is probably the worst idea I've had. Now my connections are 'spread out' over multiple tables (one for each user table), which means I have to make a separate DB called to each table (or make a huge join) just to find all the incoming connections for a particular user table. I've avoided making "one big ass table", but I'm not sure the cost is worth it. Store in separate tables all outgoing AND incoming connections for each user table (using a flag to distinguish between incoming vs outgoing). This is the idea I'm leaning towards, but it will essentially double the total DB storage for all the connections (as each connection will be stored in two tables). It also means I have to make sure connection information is kept in sync in both places. This is obviously not ideal but it does mean that when I load a user table, I only need to load one 'connection' table and have all the information I need. This also presents a separate problem, that of connection object creation. Since each user table has a list of all connections, there are two opportunities for a connection object to be made. However, connections objects (designed to facilitate communication between records) should only be created once. This means I'll have to devise a common caching/factory object to make sure only one connection object is made per connection. Does anybody have any ideas of a better way to do this? Once I've committed to a particular design pattern I'm pretty much stuck with it, so I want to make sure I've come up with the best one possible.

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  • Google I/O 2010 - Testing techniques for Google App Engine

    Google I/O 2010 - Testing techniques for Google App Engine Google I/O 2010 - Testing techniques for Google App Engine App Engine 201 Max Ross We typically write tests assuming that our development stack closely resembles our production stack. What if our target environment only lives in the cloud? We will highlight the key differences between typical testing techniques and Google App Engine testing techniques. We will also present concrete strategies for testing against local and cloud-based implementations of App Engine services. Finally, we will explain how to use App Engine as a highly parallel test harness that runs existing test suites without modification. For all I/O 2010 sessions, please go to code.google.com/events/io/2010/sessions.html From: GoogleDevelopers Views: 6 1 ratings Time: 54:29 More in Science & Technology

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  • Google I/O 2010 - Data migration in App Engine

    Google I/O 2010 - Data migration in App Engine Google I/O 2010 - Data migration in App Engine App Engine 201 Matthew Blain Learn about the App Engine bulk loader and see an example of migrating data from an external data source into the app engine datastore--and back out. Do you have data stored in a traditional, relational DB which you'd like to upload to App Engine? This session will teach you how. For all I/O 2010 sessions, please go to code.google.com From: GoogleDevelopers Views: 6 0 ratings Time: 44:26 More in Science & Technology

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  • What different ways are there to model restitution in a physics engine?

    - by Mikael Högström
    In my physics engine I give a body a value for restitution between 0 and 1. When two bodies collide there seems to be different views on how the restitution of the collision should be calculated. To me the most intuitive seems to be to take the average of the two but some seem to take only the largest one. Are there other ways to do it? Also, could the closing velocity or some other parameter come into effect?

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  • Is the "One Description Table to rule them all" approch good?

    - by DavRob60
    Long ago, I worked (as a client) with a software which use a centralized table for it's codified element. Here, as far as I remember, how the table look like : Table_Name (PK) Field_Name (PK) Code (PK) Sort_Order Description So, instead of creating a table every time they need a codified field, they where just adding row in this table with the new Table_Name and Field_Name. I'm sometime tempted to use this pattern in some database I design, but I have resisted to this as from now, I think there's something wrong with this, but I cannot put the finger on it. It is just because you land with some of the structure logic within the Data or something else?

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  • 24 Hours of PASS

    - by andyleonard
    I am honored to participate in 24 Hours of PASS starting at 8:00 AM 19 May 2010! My presentation is titled Database Development Patterns and is the second session - starting at 9:00 AM EDT 19 May 2010. It's free, but you have to register to attend - register today! :{> Andy Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!...(read more)

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  • Where is a postgresql 9.1 database stored in ubuntu 12.04?

    - by celenius
    I installed and created a Postgresql database on ubuntu. I then created the database using the following command: sudo su postgres createdb mydatabase However, I can't figure out where the database was initialized. I would like to be able to edit the hba.conf file and postgresl.conf files. When I view the database using pgadmin I see the following information: CREATE DATABASE mydatabase WITH OWNER = postgres ENCODING = 'UTF8' TABLESPACE = pg_default LC_COLLATE = 'en_US.UTF-8' LC_CTYPE = 'en_US.UTF-8' CONNECTION LIMIT = -1; Any thoughts on how I can find the database cluster location?

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