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  • Big Data – Buzz Words: What is MapReduce – Day 7 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is Hadoop. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – MapReduce. What is MapReduce? MapReduce was designed by Google as a programming model for processing large data sets with a parallel, distributed algorithm on a cluster. Though, MapReduce was originally Google proprietary technology, it has been quite a generalized term in the recent time. MapReduce comprises a Map() and Reduce() procedures. Procedure Map() performance filtering and sorting operation on data where as procedure Reduce() performs a summary operation of the data. This model is based on modified concepts of the map and reduce functions commonly available in functional programing. The library where procedure Map() and Reduce() belongs is written in many different languages. The most popular free implementation of MapReduce is Apache Hadoop which we will explore tomorrow. Advantages of MapReduce Procedures The MapReduce Framework usually contains distributed servers and it runs various tasks in parallel to each other. There are various components which manages the communications between various nodes of the data and provides the high availability and fault tolerance. Programs written in MapReduce functional styles are automatically parallelized and executed on commodity machines. The MapReduce Framework takes care of the details of partitioning the data and executing the processes on distributed server on run time. During this process if there is any disaster the framework provides high availability and other available modes take care of the responsibility of the failed node. As you can clearly see more this entire MapReduce Frameworks provides much more than just Map() and Reduce() procedures; it provides scalability and fault tolerance as well. A typical implementation of the MapReduce Framework processes many petabytes of data and thousands of the processing machines. How do MapReduce Framework Works? A typical MapReduce Framework contains petabytes of the data and thousands of the nodes. Here is the basic explanation of the MapReduce Procedures which uses this massive commodity of the servers. Map() Procedure There is always a master node in this infrastructure which takes an input. Right after taking input master node divides it into smaller sub-inputs or sub-problems. These sub-problems are distributed to worker nodes. A worker node later processes them and does necessary analysis. Once the worker node completes the process with this sub-problem it returns it back to master node. Reduce() Procedure All the worker nodes return the answer to the sub-problem assigned to them to master node. The master node collects the answer and once again aggregate that in the form of the answer to the original big problem which was assigned master node. The MapReduce Framework does the above Map () and Reduce () procedure in the parallel and independent to each other. All the Map() procedures can run parallel to each other and once each worker node had completed their task they can send it back to master code to compile it with a single answer. This particular procedure can be very effective when it is implemented on a very large amount of data (Big Data). The MapReduce Framework has five different steps: Preparing Map() Input Executing User Provided Map() Code Shuffle Map Output to Reduce Processor Executing User Provided Reduce Code Producing the Final Output Here is the Dataflow of MapReduce Framework: Input Reader Map Function Partition Function Compare Function Reduce Function Output Writer In a future blog post of this 31 day series we will explore various components of MapReduce in Detail. MapReduce in a Single Statement MapReduce is equivalent to SELECT and GROUP BY of a relational database for a very large database. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – HDFS. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL Developer Data Modeler v3.3 Early Adopter: Search

    - by thatjeffsmith
    photo: Stuck in Customs via photopin cc The next version of Oracle SQL Developer Data Modeler is now available as an Early Adopter (read, beta) release. There are many new major feature enhancements to talk about, but today’s focus will be on the brand new Search mechanism. Data, data, data – SO MUCH data Google has made countless billions of dollars around a very efficient and intelligent search business. People have become accustomed to having their data accessible AND searchable. Data models can have thousands of entities or tables, each having dozens of attributes or columns. Imagine how hard it could be to find what you’re looking for here. This is the challenge we have tackled head-on in v3.3. Same location as the Search toolbar in Oracle SQL Developer (and most web browsers) Here’s how it works: Search as you type – wicked fast as the entire model is loaded into memory Supports regular expressions (regex) Results loaded to a new panel below Search across designs, models Search EVERYTHING, or filter by type Save your frequent searches Save your search results as a report Open common properties of object in search results and edit basic properties on-the-fly Want to just watch the video? We have a new Oracle Learning Library resource available now which introduces the new and improved Search mechanism in SQL Developer Data Modeler. Go watch the video and then come back. Some Screenshots This will be a pretty easy feature to pick up. Search is intuitive – we’ve already learned how to do search. Now we just have a better interface for it in SQL Developer Data Modeler. But just in case you need a couple of pointers… The SYS data dictionary in model form with Search Results If I type ‘translation’ in the search dialog, then the results will come up as hits are ‘resolved.’ By default, everything is searched, although I can filter the results after-the-fact. You can see where the search finds a match in the ‘Content’ column Save the Results as a Report If you limit the search results to a category and a model, then you can save the results as a report. All of the usual suspects You can optionally include the search string, which displays in the top of of the report as ‘PATTERN.’ You can save you common reporting setups as a template and reuse those as well. Here’s a sample HTML report: Yes, I like to search my search results report! Two More Ways to Search You can search ‘in context’ by opening the ‘Find’ dialog from an active design. You can do this using the ‘Search’ toolbar button or from a model context menu. Searching a specific model Instead of bringing up the old modal Find dialog, you now get to use the new and improved Search panel. Notice there’s no ‘Model’ drop-down to select and that the active Search form is now in the Search panel versus the search toolbar up top. What else is new in SQL Developer Data Modeler version 3.3? All kinds of goodies. You can send your model to Excel for quick edits/reviews and suck the changes back into your model, you can share objects between models, and much much more. You’ll find new videos and blog posts on the subject in the new few days and weeks. Enjoy! If you have any feedback or want to report bugs, please visit our forums.

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  • Big Data – Operational Databases Supporting Big Data – Key-Value Pair Databases and Document Databases – Day 13 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the Relational Database and NoSQL database in the Big Data Story. In this article we will understand the role of Key-Value Pair Databases and Document Databases Supporting Big Data Story. Now we will see a few of the examples of the operational databases. Relational Databases (Yesterday’s post) NoSQL Databases (Yesterday’s post) Key-Value Pair Databases (This post) Document Databases (This post) Columnar Databases (Tomorrow’s post) Graph Databases (Tomorrow’s post) Spatial Databases (Tomorrow’s post) Key Value Pair Databases Key Value Pair Databases are also known as KVP databases. A key is a field name and attribute, an identifier. The content of that field is its value, the data that is being identified and stored. They have a very simple implementation of NoSQL database concepts. They do not have schema hence they are very flexible as well as scalable. The disadvantages of Key Value Pair (KVP) database are that they do not follow ACID (Atomicity, Consistency, Isolation, Durability) properties. Additionally, it will require data architects to plan for data placement, replication as well as high availability. In KVP databases the data is stored as strings. Here is a simple example of how Key Value Database will look like: Key Value Name Pinal Dave Color Blue Twitter @pinaldave Name Nupur Dave Movie The Hero As the number of users grow in Key Value Pair databases it starts getting difficult to manage the entire database. As there is no specific schema or rules associated with the database, there are chances that database grows exponentially as well. It is very crucial to select the right Key Value Pair Database which offers an additional set of tools to manage the data and provides finer control over various business aspects of the same. Riak Rick is one of the most popular Key Value Database. It is known for its scalability and performance in high volume and velocity database. Additionally, it implements a mechanism for collection key and values which further helps to build manageable system. We will further discuss Riak in future blog posts. Key Value Databases are a good choice for social media, communities, caching layers for connecting other databases. In simpler words, whenever we required flexibility of the data storage keeping scalability in mind – KVP databases are good options to consider. Document Database There are two different kinds of document databases. 1) Full document Content (web pages, word docs etc) and 2) Storing Document Components for storage. The second types of the document database we are talking about over here. They use Javascript Object Notation (JSON) and Binary JSON for the structure of the documents. JSON is very easy to understand language and it is very easy to write for applications. There are two major structures of JSON used for Document Database – 1) Name Value Pairs and 2) Ordered List. MongoDB and CouchDB are two of the most popular Open Source NonRelational Document Database. MongoDB MongoDB databases are called collections. Each collection is build of documents and each document is composed of fields. MongoDB collections can be indexed for optimal performance. MongoDB ecosystem is highly available, supports query services as well as MapReduce. It is often used in high volume content management system. CouchDB CouchDB databases are composed of documents which consists fields and attachments (known as description). It supports ACID properties. The main attraction points of CouchDB are that it will continue to operate even though network connectivity is sketchy. Due to this nature CouchDB prefers local data storage. Document Database is a good choice of the database when users have to generate dynamic reports from elements which are changing very frequently. A good example of document usages is in real time analytics in social networking or content management system. Tomorrow In tomorrow’s blog post we will discuss about various other Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • What happens to the storage capacity when I uninstall Ubuntu?

    - by shole1202
    I used the wubi installer for Ubuntu 12.04. After having trouble with getting the Operating System to boot, I tried uninstalling it with wubi. From 'My Computer' (in Windows 7), I noticed the maximum capacity of my hard drive drop from 256gb to 238gb. I have tried using some methods with the command prompt to locate the missing storage, but Windows now only recognizes that the storage on the disk to have 238gb instead of the original 256. Is there any way to recover that memory?

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  • VMWare ESX, storage over 2TB

    - by Phliplip
    Hi, First of, i'm a webdeveloper and my server experience lies in setting up FreeBSD servers for webserver. I'm working on a project for at photographer, and i'm hired to develop a new online photo ordering system - where user of course can view their photos :) They have a massive need of storage, thus we have bought a HP G6 and 8x1TB SATA HDD. Our plan is to install VMWare ESX 4.0, running multiple virtual machines; FreeBSD 8 for webserver and some windows servers. Allready done that. Then mount one big storage to the BSD, and share it through Samba to the WinServers. The raid is set up with an array of 2x 1TB to handle the VMs. And the rest is setup as 3 2x1TB to handle the photo-data. Thus 2.73TB for photo-data (the raids are 1+0). Now if we add a datastore in the ESX and add the 3 LUNs we can get a datastore of 2.74TB. But i don't se how i can add this datastore direct to the VM. Only the BSD VM needs access to this. Only way is to create a VirtualDisk, with a max of 2TB (8MB blocksize). This is because the datastore where we save the virtualdisk has a maximum filesize of 2TB. Then add it as a harddisk to the BSD VM. In the 'Add Harddisk' pane for the VM, i see an option for Raw Disk Management. I think this is to access the datastore or the raid directly. Only problem is that its greyed out! Can i access the datastorage directly from the BSD? Without creating and adding virtualdisk.

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  • Dedicated server with a lot of storage and good support - and cost-effective

    - by Martin Burger
    Hello, I am from Germany and looking for a dedicated server located in the US with a lot of storage: 750 - 1500 GB. CPU speed and amount of memory are secondary, the server will host large amounts of media files via http and ftp - the basic task is to help people exchange media files. In Germany, there are some good offers, like "Root Server EQ6" at www.hetzner.de. For example, that company provides support of high quality, and their plans are very cost-effective. The plan mentioned above costs about $90 per month and provides two 1500 GB SATA-II HDDs (Software-RAID 1). In the US, I found (amongst others) Go Daddy and rackspace. Go Daddy offers some "Storage Monster" plans that include 2 x 1,000 GB hard drives for about $180 per month - already twice as much as Hetzner above. However, I found some blog and forum entries that complain about the support provided by Go Daddy. Rackspace seems to provide decent support, but they are very "upscale". Their dedicated servers are customizable and start at $419 - thus, about 4.5 times as much as Hetzner. Can anybody recommend a solution / plan that is comparable to the one by Hetzner? Or are prices for dedicated servers in general much higher than in Germany? Regards, Martin

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  • Multi-petabyte scale out storage solution [closed]

    - by Alex Yuriev
    Let's say that I have a need to have a single-name space scale to multi-petabyte object store with a file system-like wrapper. What is currently out there that supports the following: Single name space that can take 1B files. Support for multiple entry points using NFS At least node level replication ( preferably node and file level replication ) Online software upgrades No "magic sauce" on the storage layer The following has been evaluated: Gluster & Lustre - just ick - fundamental lack of understanding of why online upgrades are mandatory. OneFS - we have it. It is smelling more and more like it hides a dead body under the hood. Other than MapR and zfs am I missing anything? P.S. Oh yes, I keep forgetting that the forums are for people to discuss if 2TB drive actually stores 2TB info. May bad. Seriously though - how the heck can "meets the following requirements" can be considered a "debate"? P.P.S. I did not throw an idiotic insult - i pointed out that this is actually an interesting question compared to a conversation about storage capacity of a 2TB hard drive. It is not a question of what works better - it is a question that asks did I miss any of the products that currently exist which fit the criteria where criteria is clearly outline. I got one answer below which included something that I have not looked at in a long time which looks quite a bit grown up compared to the time I briefly look at it before.

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  • The data reader returned by the store data provider does not have enough columns

    - by molgan
    Hello I get the following error when I try to execute a stored procedure: "The data reader returned by the store data provider does not have enough columns" When I in the sql-manager execute it like this: DECLARE @return_value int, @EndDate datetime EXEC @return_value = [dbo].[GetSomeDate] @SomeID = 91, @EndDate = @EndDate OUTPUT SELECT @EndDate as N'@EndDate' SELECT 'Return Value' = @return_value GO It returns the value properly.... @SomeDate = '2010-03-24 09:00' And in my app I have: if (_entities.Connection.State == System.Data.ConnectionState.Closed) _entities.Connection.Open(); using (EntityCommand c = new EntityCommand("MyAppEntities.GetSomeDate", (EntityConnection)this._entities.Connection)) { c.CommandType = System.Data.CommandType.StoredProcedure; EntityParameter paramSomeID = new EntityParameter("SomeID", System.Data.DbType.Int32); paramSomeID.Direction = System.Data.ParameterDirection.Input; paramSomeID.Value = someID; c.Parameters.Add(paramSomeID); EntityParameter paramSomeDate = new EntityParameter("SomeDate", System.Data.DbType.DateTime); SomeDate.Direction = System.Data.ParameterDirection.Output; c.Parameters.Add(paramSomeDate); int retval = c.ExecuteNonQuery(); return (DateTime?)c.Parameters["SomeDate"].Value; Why does it complain about columns? I googled on error and someone said something about removing RETURN in sp, but I dont have any RETURN there. last like is like SELECT @SomeDate = D.SomeDate FROM .... /M

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  • HTML5 web storage: can different websites overwrite each other’s data on a user’s computer?

    - by Deepak Mahalingam
    I have a few questions regarding the concept of HTML5 storage. I went through the w3c specification, books and tutorials on the same, but still I am a bit unclear about certain concepts: Assume that I access Website A. Some JavaScript runs in my browser that sets a key value pair, say ('username','deepak'). Then I access Website B which also adds a key,value pair in the localstorage as ('username','mahalingam'). How will they both be differentiated? Will Website B override the value set by website A in my localstorage? How can we ensure that a website would not erase all of my localstorage?

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  • Help with Perl persistent data storage using Data::Dumper

    - by stephenmm
    I have been trying to figure this out for way to long tonight. I have googled it to death and none of the examples or my hacks of the examples are getting it done. It seems like this should be pretty easy but I just cannot get it. Here is the code: #!/usr/bin/perl -w use strict; use Data::Dumper; my $complex_variable = {}; my $MEMORY = "$ENV{HOME}/data/memory-file"; $complex_variable->{ 'key' } = 'value'; $complex_variable->{ 'key1' } = 'value1'; $complex_variable->{ 'key2' } = 'value2'; $complex_variable->{ 'key3' } = 'value3'; print Dumper($complex_variable)."TEST001\n"; open M, ">$MEMORY" or die; print M Data::Dumper->Dump([$complex_variable], ['$complex_variable']); close M; $complex_variable = {}; print Dumper($complex_variable)."TEST002\n"; # Then later to restore the value, it's simply: do $MEMORY; #eval $MEMORY; print Dumper($complex_variable)."TEST003\n"; And here is my output: $VAR1 = { 'key2' => 'value2', 'key1' => 'value1', 'key3' => 'value3', 'key' => 'value' }; TEST001 $VAR1 = {}; TEST002 $VAR1 = {}; TEST003 Everything that I read says that the TEST003 output should look identical to the TEST001 output which is exactly what I am trying to achieve. What am I missing here? Should I be "do"ing differently or should I be "eval"ing instead and if so how? Thanks for any help...

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  • ASP.NET server data persistence

    - by Wayne Werner
    Hi, I'm not really sure exactly how the question should be phrased, so please be patient if I ask the wrong thing. I'm writing an ASP.NET application using VB as the code behind language. I have a data access class that connects to the DB to run the query (parameterized, of course), and another class to perform the validation tasks - I access this class from my aspx page. What I would like is to be able to store the data server side and wait for the user to choose from a few options based on the validity of the data. But unless my understanding is completely off, having persistent data objects on the server will give problems when multiple users connect? My ultimate goal is that once the data has been validated the end user can't modify it. Currently I'm validating the data, but I still have to retrieve it from the web form AFTER the user says OK, which obviously leaves open the possibility of injecting bad data either accidentally (unlikely) or on purpose (also unlikely for the use, but I'd prefer not to take the chance). So am I completely off in my understanding? If so, can someone point me to a resource that provides some instructions on keeping persistent data on the server, or provide instruction? Thanks!

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  • SQLAuthority News – Best Practices for Data Warehousing with SQL Server 2008 R2

    - by pinaldave
    An integral part of any BI system is the data warehouse—a central repository of data that is regularly refreshed from the source systems. The new data is transferred at regular intervals  by extract, transform, and load (ETL) processes. This whitepaper talks about what are best practices for Data Warehousing. This whitepaper discusses ETL, Analysis, Reporting as well relational database. The main focus of this whitepaper is on mainly ‘architecture’ and ‘performance’. Download Best Practices for Data Warehousing with SQL Server 2008 R2 Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Data Warehousing, PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • DocumentDB - Another Azure NoSQL Storage Service

    - by Shaun
    Originally posted on: http://geekswithblogs.net/shaunxu/archive/2014/08/25/documentdb---another-azure-nosql-storage-service.aspxMicrosoft just released a bunch of new features for Azure on 22nd and one of them I was interested in most is DocumentDB, a document NoSQL database service on the cloud.   Quick Look at DocumentDB We can try DocumentDB from the new azure preview portal. Just click the NEW button and select the item named DocumentDB to create a new account. Specify the name of the DocumentDB, which will be the endpoint we are going to use to connect later. Select the capacity unit, resource group and subscription. In resource group section we can select which region our DocumentDB will be located. Same as other azure services select the same location with your consumers of the DocumentDB, for example the website, web services, etc.. After several minutes the DocumentDB will be ready. Click the KEYS button we can find the URI and primary key, which will be used when connecting. Now let's open Visual Studio and try to use the DocumentDB we had just created. Create a new console application and install the DocumentDB .NET client library from NuGet with the keyword "DocumentDB". You need to select "Include Prerelase" in NuGet Package Manager window since this library was not yet released. Next we will create a new database and document collection under our DocumentDB account. The code below created an instance of DocumentClient with the URI and primary key we just copied from azure portal, and create a database and collection. And it also prints the document and collection link string which will be used later to insert and query documents. 1: static void Main(string[] args) 2: { 3: var endpoint = new Uri("https://shx.documents.azure.com:443/"); 4: var key = "LU2NoyS2fH0131TGxtBE4DW/CjHQBzAaUx/mbuJ1X77C4FWUG129wWk2oyS2odgkFO2Xdif9/ZddintQicF+lA=="; 5:  6: var client = new DocumentClient(endpoint, key); 7: Run(client).Wait(); 8:  9: Console.WriteLine("done"); 10: Console.ReadKey(); 11: } 12:  13: static async Task Run(DocumentClient client) 14: { 15:  16: var database = new Database() { Id = "testdb" }; 17: database = await client.CreateDatabaseAsync(database); 18: Console.WriteLine("database link = {0}", database.SelfLink); 19:  20: var collection = new DocumentCollection() { Id = "testcol" }; 21: collection = await client.CreateDocumentCollectionAsync(database.SelfLink, collection); 22: Console.WriteLine("collection link = {0}", collection.SelfLink); 23: } Below is the result from the console window. We need to copy the collection link string for future usage. Now if we back to the portal we will find a database was listed with the name we specified in the code. Next we will insert a document into the database and collection we had just created. In the code below we pasted the collection link which copied in previous step, create a dynamic object with several properties defined. As you can see we can add some normal properties contains string, integer, we can also add complex property for example an array, a dictionary and an object reference, unless they can be serialized to JSON. 1: static void Main(string[] args) 2: { 3: var endpoint = new Uri("https://shx.documents.azure.com:443/"); 4: var key = "LU2NoyS2fH0131TGxtBE4DW/CjHQBzAaUx/mbuJ1X77C4FWUG129wWk2oyS2odgkFO2Xdif9/ZddintQicF+lA=="; 5:  6: var client = new DocumentClient(endpoint, key); 7:  8: // collection link pasted from the result in previous demo 9: var collectionLink = "dbs/AAk3AA==/colls/AAk3AP6oFgA=/"; 10:  11: // document we are going to insert to database 12: dynamic doc = new ExpandoObject(); 13: doc.firstName = "Shaun"; 14: doc.lastName = "Xu"; 15: doc.roles = new string[] { "developer", "trainer", "presenter", "father" }; 16:  17: // insert the docuemnt 18: InsertADoc(client, collectionLink, doc).Wait(); 19:  20: Console.WriteLine("done"); 21: Console.ReadKey(); 22: } the insert code will be very simple as below, just provide the collection link and the object we are going to insert. 1: static async Task InsertADoc(DocumentClient client, string collectionLink, dynamic doc) 2: { 3: var document = await client.CreateDocumentAsync(collectionLink, doc); 4: Console.WriteLine(await JsonConvert.SerializeObjectAsync(document, Formatting.Indented)); 5: } Below is the result after the object had been inserted. Finally we will query the document from the database and collection. Similar to the insert code, we just need to specify the collection link so that the .NET SDK will help us to retrieve all documents in it. 1: static void Main(string[] args) 2: { 3: var endpoint = new Uri("https://shx.documents.azure.com:443/"); 4: var key = "LU2NoyS2fH0131TGxtBE4DW/CjHQBzAaUx/mbuJ1X77C4FWUG129wWk2oyS2odgkFO2Xdif9/ZddintQicF+lA=="; 5:  6: var client = new DocumentClient(endpoint, key); 7:  8: var collectionLink = "dbs/AAk3AA==/colls/AAk3AP6oFgA=/"; 9:  10: SelectDocs(client, collectionLink); 11:  12: Console.WriteLine("done"); 13: Console.ReadKey(); 14: } 15:  16: static void SelectDocs(DocumentClient client, string collectionLink) 17: { 18: var docs = client.CreateDocumentQuery(collectionLink + "docs/").ToList(); 19: foreach(var doc in docs) 20: { 21: Console.WriteLine(doc); 22: } 23: } Since there's only one document in my collection below is the result when I executed the code. As you can see all properties, includes the array was retrieve at the same time. DocumentDB also attached some properties we didn't specified such as "_rid", "_ts", "_self" etc., which is controlled by the service.   DocumentDB Benefit DocumentDB is a document NoSQL database service. Different from the traditional database, document database is truly schema-free. In a short nut, you can save anything in the same database and collection if it could be serialized to JSON. We you query the document database, all sub documents will be retrieved at the same time. This means you don't need to join other tables when using a traditional database. Document database is very useful when we build some high performance system with hierarchical data structure. For example, assuming we need to build a blog system, there will be many blog posts and each of them contains the content and comments. The comment can be commented as well. If we were using traditional database, let's say SQL Server, the database schema might be defined as below. When we need to display a post we need to load the post content from the Posts table, as well as the comments from the Comments table. We also need to build the comment tree based on the CommentID field. But if were using DocumentDB, what we need to do is to save the post as a document with a list contains all comments. Under a comment all sub comments will be a list in it. When we display this post we just need to to query the post document, the content and all comments will be loaded in proper structure. 1: { 2: "id": "xxxxx-xxxxx-xxxxx-xxxxx", 3: "title": "xxxxx", 4: "content": "xxxxx, xxxxxxxxx. xxxxxx, xx, xxxx.", 5: "postedOn": "08/25/2014 13:55", 6: "comments": 7: [ 8: { 9: "id": "xxxxx-xxxxx-xxxxx-xxxxx", 10: "content": "xxxxx, xxxxxxxxx. xxxxxx, xx, xxxx.", 11: "commentedOn": "08/25/2014 14:00", 12: "commentedBy": "xxx" 13: }, 14: { 15: "id": "xxxxx-xxxxx-xxxxx-xxxxx", 16: "content": "xxxxx, xxxxxxxxx. xxxxxx, xx, xxxx.", 17: "commentedOn": "08/25/2014 14:10", 18: "commentedBy": "xxx", 19: "comments": 20: [ 21: { 22: "id": "xxxxx-xxxxx-xxxxx-xxxxx", 23: "content": "xxxxx, xxxxxxxxx. xxxxxx, xx, xxxx.", 24: "commentedOn": "08/25/2014 14:18", 25: "commentedBy": "xxx", 26: "comments": 27: [ 28: { 29: "id": "xxxxx-xxxxx-xxxxx-xxxxx", 30: "content": "xxxxx, xxxxxxxxx. xxxxxx, xx, xxxx.", 31: "commentedOn": "08/25/2014 18:22", 32: "commentedBy": "xxx", 33: } 34: ] 35: }, 36: { 37: "id": "xxxxx-xxxxx-xxxxx-xxxxx", 38: "content": "xxxxx, xxxxxxxxx. xxxxxx, xx, xxxx.", 39: "commentedOn": "08/25/2014 15:02", 40: "commentedBy": "xxx", 41: } 42: ] 43: }, 44: { 45: "id": "xxxxx-xxxxx-xxxxx-xxxxx", 46: "content": "xxxxx, xxxxxxxxx. xxxxxx, xx, xxxx.", 47: "commentedOn": "08/25/2014 14:30", 48: "commentedBy": "xxx" 49: } 50: ] 51: }   DocumentDB vs. Table Storage DocumentDB and Table Storage are all NoSQL service in Microsoft Azure. One common question is "when we should use DocumentDB rather than Table Storage". Here are some ideas from me and some MVPs. First of all, they are different kind of NoSQL database. DocumentDB is a document database while table storage is a key-value database. Second, table storage is cheaper. DocumentDB supports scale out from one capacity unit to 5 in preview period and each capacity unit provides 10GB local SSD storage. The price is $0.73/day includes 50% discount. For storage service the highest price is $0.061/GB, which is almost 10% of DocumentDB. Third, table storage provides local-replication, geo-replication, read access geo-replication while DocumentDB doesn't support. Fourth, there is local emulator for table storage but none for DocumentDB. We have to connect to the DocumentDB on cloud when developing locally. But, DocumentDB supports some cool features that table storage doesn't have. It supports store procedure, trigger and user-defined-function. It supports rich indexing while table storage only supports indexing against partition key and row key. It supports transaction, table storage supports as well but restricted with Entity Group Transaction scope. And the last, table storage is GA but DocumentDB is still in preview.   Summary In this post I have a quick demonstration and introduction about the new DocumentDB service in Azure. It's very easy to interact through .NET and it also support REST API, Node.js SDK and Python SDK. Then I explained the concept and benefit of  using document database, then compared with table storage.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Nagy dobás készül az Oracle adatányászati felületen, Oracle Data Mining

    - by Fekete Zoltán
    Ahogyan már a tavaly oszi Oracle OpenWorld hírekben és eloadásokban is láthattuk a beharangozót, az Oracle nagy dobásra készül az adatbányászati fronton (Oracle Data Mining), mégpedig a remekül használható adatbányászati motor grafikus felületének a kiterjesztésével. Ha jól megfigyeljük ezt az utóbbi linket, az eddigi grafikus felület már Oracle Data Miner Classic néven fut. Hogyan is lehet használni az Oracle Data Mining-ot? - Oracle Data Miner (ingyenesen letöltheto GUI az OTN-rol) - Java-ból és PL/SQL-bol, Oracle Data Mining JDeveloper and SQL Developer Extensions - Excel felületrol, Oracle Spreadsheet Add-In for Predictive Analytics - ODM Connector for mySAP BW Oracle Data Mining technikai információ.

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  • Article about Sun ZFS Storage Appliances

    - by Owen Allen
    Sun ZFS Storage Appliances are versatile storage systems. Discovering and managing them in Ops Center, though, makes them even more versatile. If you discover a Sun ZFS Storage Appliance in Ops Center 12c, you can create iSCSI and Fibre Channel LUNS, and make the LUNs available to server pools and virtualization hosts as a storage library. Barbara Higgins has written an excellent article that walks you through the process of setting up a Sun ZFS Storage Appliance and discovering and managing it in Ops Center. If you're looking into ways to make a Sun ZFS Storage Appliance work for you, it's worth a look.

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  • Join Our Call: Sun Storage 2500-M2 Announcement

    - by user797911
    Oracle's Sun Storage 2500-M2 array brings together the latest Fibre Channel (FC) and SAS2 technologies with Oracle's Sun Storage Common Array software from Oracle to create a robust solution that’s equally adept in an entry-level storage area network (SAN) for the mid-size business and integrating into an existing storage network within the enterprise. The Sun Storage 2500-M2 replaces Sun's Storage 2500 array product line and is designed so that the customer may have a quick qualification time for fast and easy deployment in the traditional 2500 environments. Jun Jang, Oracle Principal Product Manager will be hosting this 1 hour live call (a recording will be available), please join us to find out more: Event Date: 24-JUN-11 Event Time: 08:00 am PST/PDT/4pm UK time Web Registration and Access: http://oukc.oracle.com/static09/opn/login/?t=livewebcast|c=1031672594 Access for Mobile Devices: http://my.oracle.com/content/web/cnt636926 Call Provider: Intercall International Participant Dial-In Number: 706-634-8508 Additional International Dial-In Numbers Link: http://www.intercall.com/national/oracleuniversity/gdnam.html Dial-In Passcode: 96395

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  • Join Our Call: Sun Storage 2500-M2 Announcement

    - by mseika
    Oracle's Sun Storage 2500-M2 array brings together the latest Fibre Channel (FC) and SAS2 technologies with Oracle's Sun Storage Common Array software from Oracle to create a robust solution that’s equally adept in an ! entry-level storage area network (SAN) for the mid-size business and integrating into an existing storage network within the enterprise. The Sun Storage 2500-M2 replaces Sun's Storage 2500 array product line and is designed so that the customer may have a quick qualification time for fast and easy deployment in the traditional 2500 environments. Jun Jang, Oracle Principal Product Manager will be hosting this 1 hour live call (a recording will be available), please join us to find out more:24. Jun 2011 08:00 am PST/PDT/4pm UK timeWeb Registration and AccessAccess for Mobile DevicesInternational Participant Dial-In Number: 706-634-8508Additional International Dial-In Numbers LinkDial-In Passcode: 6395

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  • Azure Blob storage defrag

    - by kaleidoscope
    The Blob Storage is really handy for storing temporary data structures during a scaled-out distributed processing. Yet, the lifespan of those data structures should not exceed the one of the underlying operation, otherwise clutter and dead data could potentially start filling up your Blob Storage Temporary data in cloud computing is very similar to memory collection in object oriented languages, when it's not done automatically by the framework, temp data tends to leak. In particular, in cloud computing,  it's pretty easy to end up with storage leaks due to: Collection omission. App crash. Service interruption. All those events cause garbage to accumulate into your Blob Storage. Then, it must be noted that for most cloud apps, I/O costs are usually predominant compared to pure storage costs. Enumerating through your whole Blob Storage to clean the garbage is likely to be an expensive solution. Lokesh, M

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  • How to Use Windows 8's Storage Spaces to Mirror & Combine Drives

    - by Chris Hoffman
    “Storage Spaces” is a new feature in Windows 8 that can combine multiple hard drives into a single virtual drive. It can mirror data across multiple drives for redundancy or combine multiple physical drives into a single pool of storage. You can even create pools of storage larger than the amount of physical storage space you have available. When the physical storage fills up, you can plug in another drive and take advantage of it with no additional configuration required. Storage Spaces is similar to RAID or LVM on Linux. The HTG Guide to Hiding Your Data in a TrueCrypt Hidden Volume Make Your Own Windows 8 Start Button with Zero Memory Usage Reader Request: How To Repair Blurry Photos

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  • Oracle OpenWord 2012 - Managing Storage in the Cloud

    - by jwalker
    At Oracle OpenWorld this year attendees will get experience using the Sun ZFS Storage Appliance during the Managing Storage in the Cloud Hands-On-Lab. Using Sun ZFS Storage, we will be provisioning Oracle Enterprise Linux Virtual Machines and filesystem shares that can be used with Oracle Database. We will also be using Oracle DTrace Analytics to analyze I/O workloads and drill down to see how the storage is really being used. Hope you can join us! Session ID: HOL10034 Session Title: Managing Storage in the Cloud Speakers: Brian Haskins, Nagendran J, Paul Johnson, Karlheinz Vogel and Jim Walker Venue and Room: Marriott Marquis - Salon 14/15 Date and Times: Monday October 1 - 3:15-4:15PM, Tuesday October 2 - 5:00-6:00PM Oracle OpenWorld Storage Sessions

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  • Google I/O 2012 - Big Data: Turning Your Data Problem Into a Competitive Advantage

    Google I/O 2012 - Big Data: Turning Your Data Problem Into a Competitive Advantage Ju-kay Kwek, Navneet Joneja Can businesses get practical value from web-scale data without building proprietary web-scale infrastructure? This session will explore how new Google data services can be used to solve key data storage, transformation and analysis challenges. We will look at concrete case studies demonstrating how real life businesses have successfully used these solutions to turn data into a competitive business asset. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 1 0 ratings Time: 52:39 More in Science & Technology

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  • Data-Driven SOA with Oracle Data Integrator

    - by Irem Radzik
    v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Cambria","serif"; mso-fareast-font-family:"MS Mincho";} By Mike Eisterer, Data integration is more than simply moving data in bulk or in real-time, it is also about unifying information for improved business agility and integrating it in today’s service-oriented architectures. SOA enables organizations to easily define services which may then be discovered and leveraged by varying consumers. These consumers may be applications, customer facing portals, or complex business rules which are assembling services to automate process. Data as a foundational service provider is a key component of today’s successful SOA implementations. Oracle offers the broadest and most integrated portfolio of products to help you define, organize, orchestrate and consume data services. If you are attending Oracle OpenWorld next week, you will have ample opportunity to see the latest Oracle Data Integrator live in action and work with it yourself in two offered Hands-on Labs. Visit the hands-on lab to gain experience firsthand: Oracle Data Integrator and Oracle SOA Suite: Hands-on- Lab (HOL10480) Wed Oct 3rd 11:45AM Marriott Marquis- Salon 1/2 To learn more about Oracle Data Integrator, please visit our Introduction Hands-on LAB: Introduction to Oracle Data Integrator (HOL10481) Mon Oct 1st 3:15PM, Marriott Marquis- Salon 1/2 If you are not able to attend OpenWorld, please check out our latest resources for Data Integration.

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  • Subsetting a data frame in a function using another data frame as parameter

    - by lecodesportif
    I would like to submit a data frame to a function and use it to subset another data frame. This is the basic data frame: foo <- data.frame(var1= c('1', '1', '1', '2', '2', '3'), var2=c('A', 'A', 'B', 'B', 'C', 'C')) I use the following function to find out the frequencies of var2 for specified values of var1. foobar <- function(x, y, z){ a <- subset(x, (x$var1 == y)) b <- subset(a, (a$var2 == z)) n=nrow(b) return(n) } Examples: foobar(foo, 1, "A") # returns 2 foobar(foo, 1, "B") # returns 1 foobar(foo, 3, "C") # returns 1 This works. But now I want to submit a data frame of values to foobar. Instead of the above examples, I would like to submit df to foobar and get the same results as above (2, 1, 1) df <- data.frame(var1=c('1','1','3'), var2=c("A", "B", "C")) When I change foobar to accept two arguments like foobar(foo, df) and use y[, c(var1)] and y[, c(var2)] instead of the two parameters x and y it still doesn't work. Which way is there to do this?

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  • Managing Data Dependecies of Java Classes that Load Data from the Classpath at Runtime

    - by Martin Potthast
    What is the simplest way to manage dependencies of Java classes to data files present in the classpath? More specifically: How should data dependencies be annotated? Perhaps using Java annotations (e.g., @Data)? Or rather some build entries in a build script or a properties file? Is there build tool that integrates and evaluates such information (Ant, Scons, ...)? Do you have examples? Consider the following scenario: A few lines of Ant create a Jar from my sources that includes everything found on the classpath. Then jarjar is used to remove all .class files that are not necessary to execute, say, class Foo. The problem is that all the data files that class Bar depends upon are still there in the Jar. The ideal deployment script, however, would recognize that the data files on which only class Bar depends can be removed while data files on which class Foo depends must be retained. Any hints?

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  • Best way to collect and store data daily?

    - by mktb
    I have a bunch of statistics: # of users, # of families, ratio user/family, etc. I'd like to store these daily so I can view this data historically. However, I'm looking for the most effective way to store this data. Should I run a cron job that writes to the database DATE: today USERS: 123 FAMILIES: 456 RATIO: 7.89 or whatever? (or should I write multiple rows like DATE: today DATATYPE: users VALUE: 123?) Or is there another option I can use that is more efficient or more effective? Thanks!

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