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• Data Flow Diagrams - Difference between Lines and Arrows

  - by Howdy_McGee

  I'm currently working with Visio to create Data Flow Diagrams for a System Analysis and Design class but I'm unsure what the difference between ------ and ------> is. I can connect 2 shapes together with a line (process, entity, data store) but does the single line connecting the two mean data flow? Do I need to explicitly use the data flow arrow to show which way data is flowing? (There doesn't seem to be tags for this topic, maybe im in the wrong place?)

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• Big Data Videos

  - by Jean-Pierre Dijcks

  You can view them all on YouTube using the following links: Overview for the Boss: http://youtu.be/ikJyrmKdJWc Hadoop: http://youtu.be/acWtid-OOWM Acquiring Big Data: http://youtu.be/TfuhuA_uaho Organizing Big Data: http://youtu.be/IC6jVRO2Hq4 Analyzing Big Data: http://youtu.be/2yf_jrBhz5w These videos are a great place to start learning about big data, the value it can bring to your organisation and how Oracle can help you start working with big data today.

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• SQL Server and the XML Data Type : Data Manipulation

  The introduction of the xml data type, with its own set of methods for processing xml data, made it possible for SQL Server developers to create columns and variables of the type xml. Deanna Dicken examines the modify() method, which provides for data manipulation of the XML data stored in the xml data type via XML DML statements.

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• Behavior of <- NULL on lists versus data.frames for removing data

  - by Ananda Mahto

  Many R users eventually figure out lots of ways to remove elements from their data. One way is to use NULL, particularly when you want to do something like drop a column from a data.frame or drop an element from a list. Eventually, a user comes across a situation where they want to drop several columns from a data.frame at once, and they hit upon <- list(NULL) as the solution (since using <- NULL will result in an error). A data.frame is a special type of list, so it wouldn't be too tough to imagine that the approaches for removing items from a list should be the same as removing columns from a data.frame. However, they produce different results, as can be seen in the example below. ## Make some small data--two data.frames and two lists cars1 <- cars2 <- head(mtcars)[1:4] cars3 <- cars4 <- as.list(cars2) ## Demonstration that the `list(NULL)` approach works cars1[c("mpg", "cyl")] <- list(NULL) cars1 # disp hp # Mazda RX4 160 110 # Mazda RX4 Wag 160 110 # Datsun 710 108 93 # Hornet 4 Drive 258 110 # Hornet Sportabout 360 175 # Valiant 225 105 ## Demonstration that simply using `NULL` does not work cars2[c("mpg", "cyl")] <- NULL # Error in `[<-.data.frame`(`*tmp*`, c("mpg", "cyl"), value = NULL) : # replacement has 0 items, need 12 Switch to applying the same concept to a list, and compare the difference in behavior. ## Does not fully drop the items, but sets them to `NULL` cars3[c("mpg", "cyl")] <- list(NULL) # $mpg # NULL # # $cyl # NULL # # $disp # [1] 160 160 108 258 360 225 # # $hp # [1] 110 110 93 110 175 105 ## *Does* drop the `list` items while this would ## have produced an error with a `data.frame` cars4[c("mpg", "cyl")] <- NULL # $disp # [1] 160 160 108 258 360 225 # # $hp # [1] 110 110 93 110 175 105 The main questions I have are, if a data.frame is a list, why does it behave so differently in this scenario? Is there a foolproof way of knowing when an element will be dropped, when it will produce an error, and when it will simply be given a NULL value? Or do we depend on trial-and-error for this?

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• How does jQuery stores data with .data()?

  - by TK

  I am a little confused how jQuery stores data with .data() functions. Is this something called expando? Or is this using HTML5 Web Storage although I think this is very unlikely? The documentation says: The .data() method allows us to attach data of any type to DOM elements in a way that is safe from circular references and therefore from memory leaks. As I read about expando, it seems to have a rick of memory leak. Unfortunately my skills are not enough to read and understand jQuery code itself, but I want to know how jQuery stores such data by using data(). http://api.jquery.com/data/

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• ASP.Net Layered app - Share Entity Data Model amongst layers

  - by Chris Klepeis

  How can I share the auto-generated entity data model (generated object classes) amongst all layers of my C# web app whilst only granting query access in the data layer? This uses the typical 3 layer approach: data, business, presentation. My data layer returns an IEnumerable<T> to my business layer, but I cannot return type T to the presentation layer because I do not want the presentation layer to know of the existence of the data layer - which is where the entity framework auto-generated my classes. It was recommended to have a seperate layer with just the data model, but I'm unsure how to seperate the data model from the query functionality the entity framework provides.

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• How does jQuery store data with .data()?

  - by TK

  I am a little confused how jQuery stores data with .data() functions. Is this something called expando? Or is this using HTML5 Web Storage although I think this is very unlikely? The documentation says: The .data() method allows us to attach data of any type to DOM elements in a way that is safe from circular references and therefore from memory leaks. As I read about expando, it seems to have a rick of memory leak. Unfortunately my skills are not enough to read and understand jQuery code itself, but I want to know how jQuery stores such data by using data(). http://api.jquery.com/data/

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• Accessing and Updating Data in ASP.NET: Filtering Data Using a CheckBoxList

  Filtering Database Data with Parameters, an earlier installment in this article series, showed how to filter the data returned by ASP.NET's data source controls. In a nutshell, the data source controls can include parameterized queries whose parameter values are defined via parameter controls. For example, the SqlDataSource can include a parameterized SelectCommand, such as: SELECT * FROM Books WHERE Price > @Price. Here, @Price is a parameter; the value for a parameter can be defined declaratively using a parameter control. ASP.NET offers a variety of parameter controls, including ones that use hard-coded values, ones that retrieve values from the querystring, and ones that retrieve values from session, and others. Perhaps the most useful parameter control is the ControlParameter, which retrieves its value from a Web control on the page. Using the ControlParameter we can filter the data returned by the data source control based on the end user's input. While the ControlParameter works well with most types of Web controls, it does not work as expected with the CheckBoxList control. The ControlParameter is designed to retrieve a single property value from the specified Web control, but the CheckBoxList control does not have a property that returns all of the values of its selected items in a form that the CheckBoxList control can use. Moreover, if you are using the selected CheckBoxList items to query a database you'll quickly find that SQL does not offer out of the box functionality for filtering results based on a user-supplied list of filter criteria. The good news is that with a little bit of effort it is possible to filter data based on the end user's selections in a CheckBoxList control. This article starts with a look at how to get SQL to filter data based on a user-supplied, comma-delimited list of values. Next, it shows how to programmatically construct a comma-delimited list that represents the selected CheckBoxList values and pass that list into the SQL query. Finally, we'll explore creating a custom parameter control to handle this logic declaratively. Read on to learn more! Read More >

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• SQLAuthority News – Fast Track Data Warehouse 3.0 Reference Guide

  - by pinaldave

  http://msdn.microsoft.com/en-us/library/gg605238.aspx I am very excited that Fast Track Data Warehouse 3.0 reference guide has been announced. As a consultant I have always enjoyed working with Fast Track Data Warehouse project as it truly expresses the potential of the SQL Server Engine. Here is few details of the enhancement of the Fast Track Data Warehouse 3.0 reference architecture. The SQL Server Fast Track Data Warehouse initiative provides a basic methodology and concrete examples for the deployment of balanced hardware and database configuration for a data warehousing workload. Balance is measured across the key components of a SQL Server installation; storage, server, application settings, and configuration settings for each component are evaluated. Description Note FTDW 3.0 Architecture Basic component architecture for FT 3.0 based systems. New Memory Guidelines Minimum and maximum tested memory configurations by server socket count. Additional Startup Options Notes for T-834 and setting for Lock Pages in Memory. Storage Configuration RAID1+0 now standard (RAID1 was used in FT 2.0). Evaluating Fragmentation Query provided for evaluating logical fragmentation. Loading Data Additional options for CI table loads. MCR Additional detail and explanation of FTDW MCR Rating. Read white paper on fast track data warehousing. Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: Business Intelligence, Data Warehousing, PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQL White Papers, SQLAuthority News, T SQL, Technology

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• Accessing and Updating Data in ASP.NET: Filtering Data Using a CheckBoxList

  Filtering Database Data with Parameters, an earlier installment in this article series, showed how to filter the data returned by ASP.NET's data source controls. In a nutshell, the data source controls can include parameterized queries whose parameter values are defined via parameter controls. For example, the SqlDataSource can include a parameterized SelectCommand, such as: SELECT * FROM Books WHERE Price > @Price. Here, @Price is a parameter; the value for a parameter can be defined declaratively using a parameter control. ASP.NET offers a variety of parameter controls, including ones that use hard-coded values, ones that retrieve values from the querystring, and ones that retrieve values from session, and others. Perhaps the most useful parameter control is the ControlParameter, which retrieves its value from a Web control on the page. Using the ControlParameter we can filter the data returned by the data source control based on the end user's input. While the ControlParameter works well with most types of Web controls, it does not work as expected with the CheckBoxList control. The ControlParameter is designed to retrieve a single property value from the specified Web control, but the CheckBoxList control does not have a property that returns all of the values of its selected items in a form that the CheckBoxList control can use. Moreover, if you are using the selected CheckBoxList items to query a database you'll quickly find that SQL does not offer out of the box functionality for filtering results based on a user-supplied list of filter criteria. The good news is that with a little bit of effort it is possible to filter data based on the end user's selections in a CheckBoxList control. This article starts with a look at how to get SQL to filter data based on a user-supplied, comma-delimited list of values. Next, it shows how to programmatically construct a comma-delimited list that represents the selected CheckBoxList values and pass that list into the SQL query. Finally, we'll explore creating a custom parameter control to handle this logic declaratively. Read on to learn more! Read More >

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• C++ : Lack of Standardization at the Binary Level

  - by Nawaz

  Why ISO/ANSI didn't standardize C++ at the binary level? There are many portability issues with C++, which is only because of lack of it's standardization at the binary level. Don Box writes, (quoting from his book Essential COM, chapter COM As A Better C++) C++ and Portability Once the decision is made to distribute a C++ class as a DLL, one is faced with one of the fundamental weaknesses of C++, that is, lack of standardization at the binary level. Although the ISO/ANSI C++ Draft Working Paper attempts to codify which programs will compile and what the semantic effects of running them will be, it makes no attempt to standardize the binary runtime model of C++. The first time this problem will become evident is when a client tries to link against the FastString DLL's import library from a C++ developement environment other than the one used to build the FastString DLL. Are there more benefits Or loss of this lack of binary standardization?

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• C++ : Lack of Standardization at the Binary Level

  - by Nawaz

  Why ISO/ANSI didn't standardize C++ at the binary level? There are many portability issues with C++, which is only because of lack of it's standardization at the binary level. Don Box writes, (quoting from his book Essential COM, chapter COM As A Better C++) C++ and Portability Once the decision is made to distribute a C++ class as a DLL, one is faced with one of the fundamental weaknesses of C++, that is, lack of standardization at the binary level. Although the ISO/ANSI C++ Draft Working Paper attempts to codify which programs will compile and what the semantic effects of running them will be, it makes no attempt to standardize the binary runtime model of C++. The first time this problem will become evident is when a client tries to link against the FastString DLL's import library from a C++ developement environment other than the one used to build the FastString DLL. Are there more benefits Or loss of this lack of binary standardization?

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• Processing Text and Binary (Blob, ArrayBuffer, ArrayBufferView) Payload in WebSocket - (TOTD #185)

  - by arungupta

  The WebSocket API defines different send(xxx) methods that can be used to send text and binary data. This Tip Of The Day (TOTD) will show how to send and receive text and binary data using WebSocket. TOTD #183 explains how to get started with a WebSocket endpoint using GlassFish 4. A simple endpoint from that blog looks like: @WebSocketEndpoint("/endpoint") public class MyEndpoint { public void receiveTextMessage(String message) { . . . } } A message with the first parameter of the type String is invoked when a text payload is received. The payload of the incoming WebSocket frame is mapped to this first parameter. An optional second parameter, Session, can be specified to map to the "other end" of this conversation. For example: public void receiveTextMessage(String message, Session session) {     . . . } The return type is void and that means no response is returned to the client that invoked this endpoint. A response may be returned to the client in two different ways. First, set the return type to the expected type, such as: public String receiveTextMessage(String message) { String response = . . . . . . return response; } In this case a text payload is returned back to the invoking endpoint. The second way to send a response back is to use the mapped session to send response using one of the sendXXX methods in Session, when and if needed. public void receiveTextMessage(String message, Session session) {     . . .     RemoteEndpoint remote = session.getRemote();     remote.sendString(...);     . . .     remote.sendString(...);    . . .    remote.sendString(...); } This shows how duplex and asynchronous communication between the two endpoints can be achieved. This can be used to define different message exchange patterns between the client and server. The WebSocket client can send the message as: websocket.send(myTextField.value); where myTextField is a text field in the web page. Binary payload in the incoming WebSocket frame can be received if ByteBuffer is used as the first parameter of the method signature. The endpoint method signature in that case would look like: public void receiveBinaryMessage(ByteBuffer message) {     . . . } From the client side, the binary data can be sent using Blob, ArrayBuffer, and ArrayBufferView. Blob is a just raw data and the actual interpretation is left to the application. ArrayBuffer and ArrayBufferView are defined in the TypedArray specification and are designed to send binary data using WebSocket. In short, ArrayBuffer is a fixed-length binary buffer with no format and no mechanism for accessing its contents. These buffers are manipulated using one of the views defined by one of the subclasses of ArrayBufferView listed below: Int8Array (signed 8-bit integer or char) Uint8Array (unsigned 8-bit integer or unsigned char) Int16Array (signed 16-bit integer or short) Uint16Array (unsigned 16-bit integer or unsigned short) Int32Array (signed 32-bit integer or int) Uint32Array (unsigned 16-bit integer or unsigned int) Float32Array (signed 32-bit float or float) Float64Array (signed 64-bit float or double) WebSocket can send binary data using ArrayBuffer with a view defined by a subclass of ArrayBufferView or a subclass of ArrayBufferView itself. The WebSocket client can send the message using Blob as: blob = new Blob([myField2.value]);websocket.send(blob); where myField2 is a text field in the web page. The WebSocket client can send the message using ArrayBuffer as: var buffer = new ArrayBuffer(10);var bytes = new Uint8Array(buffer);for (var i=0; i<bytes.length; i++) { bytes[i] = i;}websocket.send(buffer); A concrete implementation of receiving the binary message may look like: @WebSocketMessagepublic void echoBinary(ByteBuffer data, Session session) throws IOException {    System.out.println("echoBinary: " + data);    for (byte b : data.array()) {        System.out.print(b);    }    session.getRemote().sendBytes(data);} This method is just printing the binary data for verification but you may actually be storing it in a database or converting to an image or something more meaningful. Be aware of TYRUS-51 if you are trying to send binary data from server to client using method return type. Here are some references for you: JSR 356: Java API for WebSocket - Specification (Early Draft) and Implementation (already integrated in GlassFish 4 promoted builds) TOTD #183 - Getting Started with WebSocket in GlassFish TOTD #184 - Logging WebSocket Frames using Chrome Developer Tools, Net-internals and Wireshark Subsequent blogs will discuss the following topics (not necessary in that order) ... Error handling Custom payloads using encoder/decoder Interface-driven WebSocket endpoint Java client API Client and Server configuration Security Subprotocols Extensions Other topics from the API

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• Versioning freindly, extendible binary file format

  - by Bas Bossink

  In the project I'm currently working on there is a need to save a sizeable data structure to disk. Being in optimist I thought their must be a standard solution for such a problem however upto now I haven't found a solution that satisfies the following requirements: .net 2.0 support, preferably with a foss implementation version friendly (this should be interpreted as reading an old version of the format should be relatively simple if the changes in the underlying data structure are simple, say adding/dropping fields) ability to do some form of random access where part of the data can be extended after initial creation (think of this as extending intermediate results) space and time efficient (xml has been excluded as option given this requierement) Options considered so far: Protocol Buffers : was turned down by verdict of the documentation about Large Data Sets since this comment suggest adding another layer on top, this would call for additional complexity which I wish to have handled by the file format itself. HDF5,EXI : do not seem to have .net implementations SQLite : the data structure at hand would result in a pretty complex table structure that seems to heavyweight for the intended use BSON : does not appear to support requirement 3. Fast Infoset : only seems to have buyware .net implementations Any recommendations or pointers are greatly appreciated. Furthermore if you believe any of the information above is not true please provide pointers/examples to proove me wrong.

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• Binary Tree in C Insertion Error

  - by Paul

  I'm quite new to C and I'm trying to implement a Binary Tree in C which will store a number and a string and then print them off e.g. 1 : Bread 2 : WashingUpLiquid etc. The code I have so far is: #include <stdio.h> #include <stdlib.h> #define LENGTH 300 struct node { int data; char * definition; struct node *left; struct node *right; }; struct node *node_insert(struct node *p, int value, char * word); void print_preorder(struct node *p); int main(void) { int i = 0; int d = 0; char def[LENGTH]; struct node *root = NULL; for(i = 0; i < 2; i++) { printf("Please enter a number: \n"); scanf("%d", &d); printf("Please enter a definition for this word:\n"); scanf("%s", def); root = node_insert(root, d, def); printf("%s\n", def); } printf("preorder : "); print_preorder(root); printf("\n"); return 0; } struct node *node_insert(struct node *p, int value, char * word) { struct node *tmp_one = NULL; struct node *tmp_two = NULL; if(p == NULL) { p = (struct node *)malloc(sizeof(struct node)); p->data = value; p->definition = word; p->left = p->right = NULL; } else { tmp_one = p; while(tmp_one != NULL) { tmp_two = tmp_one; if(tmp_one->data > value) tmp_one = tmp_one->left; else tmp_one = tmp_one->right; } if(tmp_two->data > value) { tmp_two->left = (struct node *)malloc(sizeof(struct node)); tmp_two = tmp_two->left; tmp_two->data = value; tmp_two->definition = word; tmp_two->left = tmp_two->right = NULL; } else { tmp_two->right = (struct node *)malloc(sizeof(struct node)); tmp_two = tmp_two->right; tmp_two->data = value; tmp_two->definition = word; tmp_two->left = tmp_two->right = NULL; } } return(p); } void print_preorder(struct node *p) { if(p != NULL) { printf("%d : %s\n", p->data, p->definition); print_preorder(p->left); print_preorder(p->right); } } At the moment it seems to work for the ints but the description part only prints out for the last one entered. I assume it has something to do with pointers on the char array but I had no luck getting it to work. Any ideas or advice? Thanks

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• Versioning friendly, extendible binary file format

  - by Bas Bossink

  In the project I'm currently working on there is a need to save a sizable data structure to disk (edit: think dozens of MB's). Being an optimist, I thought that there must be a standard solution for such a problem; however, up to now I haven't found a solution that satisfies the following requirements: .NET 2.0 support, preferably with a FOSS implementation Version friendly (this should be interpreted as: reading an old version of the format should be relatively simple if the changes in the underlying data structure are simple, say adding/dropping fields) Ability to do some form of random access where part of the data can be extended after initial creation (think of this as extending intermediate results) Space and time efficient (XML has been excluded as option given this requirement) Options considered so far: Protocol Buffers: was turned down by verdict of the documentation about Large Data Sets - since this comment suggested adding another layer on top, this would call for additional complexity which I wish to have handled by the file format itself. HDF5,EXI: do not seem to have .net implementations SQLite/SQL Server Compact edition: the data structure at hand would result in a pretty complex table structure that seems too heavyweight for the intended use BSON: does not appear to support requirement 3. Fast Infoset: only seems to have paid .NET implementations. Any recommendations or pointers are greatly appreciated. Furthermore if you believe any of the information above is not true, please provide pointers/examples to prove me wrong.

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• extjs data store load data on fly

  - by CKeven

  I'm trying to create a data store that will load the data schema and records on fly. Here is the current code i have and I'm not sure how to setup the array reader properly since i don't have the schema before query returns. ds = new Ext.data.Store({ url: 'http://10.10.97.83/cgi-bin/cgiip.exe/WService=wsdev/majax/jsbrdgx.p', baseParams: { cr: Ext.util.JSON.encode(omgtobxParms) }, reader: new Ext.data.ArrayReader({ //root:data.value.records }, col_names) }); {"name": "tmp_buy_book", "schema": [ { "name": "a", "type": "C"}, { "name": "b", "type": "C"} "records": [["1", ""], ["1",""]]}

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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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• 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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• C++ design question on traversing binary trees

  - by user231536

  I have a binary tree T which I would like to copy to another tree. Suppose I have a visit method that gets evaluated at every node: struct visit { virtual void operator() (node* n)=0; }; and I have a visitor algorithm void visitor(node* t, visit& v) { //do a preorder traversal using stack or recursion if (!t) return; v(t); visitor(t->left, v); visitor(t->right, v); } I have 2 questions: I settled on using the functor based approach because I see that boost graph does this (vertex visitors). Also I tend to repeat the same code to traverse the tree and do different things at each node. Is this a good design to get rid of duplicated code? What other alternative designs are there? How do I use this to create a new binary tree from an existing one? I can keep a stack on the visit functor if I want, but it gets tied to the algorithm in visitor. How would I incorporate postorder traversals here ? Another functor class?

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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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• 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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