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  • Linked List exercise, what am I doing wrong?

    - by Sean Ochoa
    Hey all. I'm doing a linked list exercise that involves dynamic memory allocation, pointers, classes, and exceptions. Would someone be willing to critique it and tell me what I did wrong and what I should have done better both with regards to style and to those subjects I listed above? /* Linked List exercise */ #include <iostream> #include <exception> #include <string> using namespace std; class node{ public: node * next; int * data; node(const int i){ data = new int; *data = i; } node& operator=(node n){ *data = *(n.data); } ~node(){ delete data; } }; class linkedList{ public: node * head; node * tail; int nodeCount; linkedList(){ head = NULL; tail = NULL; } ~linkedList(){ while (head){ node* t = head->next; delete head; if (t) head = t; } } void add(node * n){ if (!head) { head = n; head->next = NULL; tail = head; nodeCount = 0; }else { node * t = head; while (t->next) t = t->next; t->next = n; n->next = NULL; nodeCount++; } } node * operator[](const int &i){ if ((i >= 0) && (i < nodeCount)) throw new exception("ERROR: Invalid index on linked list.", -1); node *t = head; for (int x = i; x < nodeCount; x++) t = t->next; return t; } void print(){ if (!head) return; node * t = head; string collection; cout << "["; int c = 0; if (!t->next) cout << *(t->data); else while (t->next){ cout << *(t->data); c++; if (t->next) t = t->next; if (c < nodeCount) cout << ", "; } cout << "]" << endl; } }; int main (const int & argc, const char * argv[]){ try{ linkedList * myList = new linkedList; for (int x = 0; x < 10; x++) myList->add(new node(x)); myList->print(); }catch(exception &ex){ cout << ex.what() << endl; return -1; } return 0; }

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  • New Feature in ODI 11.1.1.6: ODI for Big Data

    - by Julien Testut
    Normal 0 false false false EN-US X-NONE X-NONE /* 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:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} By Ananth Tirupattur Starting with Oracle Data Integrator 11.1.1.6.0, ODI is offering a solution to process Big Data. This post provides an overview of this feature. With all the buzz around Big Data and before getting into the details of ODI for Big Data, I will provide a brief introduction to Big Data and Oracle Solution for Big Data. So, what is Big Data? Big data includes: structured data (this includes data from relation data stores, xml data stores), semi-structured data (this includes data from weblogs) unstructured data (this includes data from text blob, images) Traditionally, business decisions are based on the information gathered from transactional data. For example, transactional Data from CRM applications is fed to a decision system for analysis and decision making. Products such as ODI play a key role in enabling decision systems. However, with the emergence of massive amounts of semi-structured and unstructured data it is important for decision system to include them in the analysis to achieve better decision making capability. While there is an abundance of opportunities for business for gaining competitive advantages, process of Big Data has challenges. The challenges of processing Big Data include: Volume of data Velocity of data - The high Rate at which data is generated Variety of data In order to address these challenges and convert them into opportunities, we would need an appropriate framework, platform and the right set of tools. Hadoop is an open source framework which is highly scalable, fault tolerant system, for storage and processing large amounts of data. Hadoop provides 2 key services, distributed and reliable storage called Hadoop Distributed File System or HDFS and a framework for parallel data processing called Map-Reduce. Innovations in Hadoop and its related technology continue to rapidly evolve, hence therefore, it is highly recommended to follow information on the web to keep up with latest information. Oracle's vision is to provide a comprehensive solution to address the challenges faced by Big Data. Oracle is providing the necessary Hardware, software and tools for processing Big Data Oracle solution includes: Big Data Appliance Oracle NoSQL Database Cloudera distribution for Hadoop Oracle R Enterprise- R is a statistical package which is very popular among data scientists. ODI solution for Big Data Oracle Loader for Hadoop for loading data from Hadoop to Oracle. Further details can be found here: http://www.oracle.com/us/products/database/big-data-appliance/overview/index.html ODI Solution for Big Data: ODI’s goal is to minimize the need to understand the complexity of Hadoop framework and simplify the adoption of processing Big Data seamlessly in an enterprise. ODI is providing the capabilities for an integrated architecture for processing Big Data. This includes capability to load data in to Hadoop, process data in Hadoop and load data from Hadoop into Oracle. ODI is expanding its support for Big Data by providing the following out of the box Knowledge Modules (KMs). IKM File to Hive (LOAD DATA).Load unstructured data from File (Local file system or HDFS ) into Hive IKM Hive Control AppendTransform and validate structured data on Hive IKM Hive TransformTransform unstructured data on Hive IKM File/Hive to Oracle (OLH)Load processed data in Hive to Oracle RKM HiveReverse engineer Hive tables to generate models Using the Loading KM you can map files (local and HDFS files) to the corresponding Hive tables. For example, you can map weblog files categorized by date into a corresponding partitioned Hive table schema. Normal 0 false false false EN-US X-NONE X-NONE /* 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:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Using the Hive control Append KM you can validate and transform data in Hive. In the below example, two source Hive tables are joined and mapped to a target Hive table. Normal 0 false false false EN-US X-NONE X-NONE /* 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:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} The Hive Transform KM facilitates processing of semi-structured data in Hive. In the below example, the data from weblog is processed using a Perl script and mapped to target Hive table. Normal 0 false false false EN-US X-NONE X-NONE /* 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:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Using the Oracle Loader for Hadoop (OLH) KM you can load data from Hive table or HDFS to a corresponding table in Oracle. OLH is available as a standalone product. ODI greatly enhances OLH capability by generating the configuration and mapping files for OLH based on the configuration provided in the interface and KM options. ODI seamlessly invokes OLH when executing the scenario. In the below example, a HDFS file is mapped to a table in Oracle. Development and Deployment:The following diagram illustrates the development and deployment of ODI solution for Big Data. Using the ODI Studio on your development machine create and develop ODI solution for processing Big Data by connecting to a MySQL DB or Oracle database on a BDA machine or Hadoop cluster. Schedule the ODI scenarios to be executed on the ODI agent deployed on the BDA machine or Hadoop cluster. ODI Solution for Big Data provides several exciting new capabilities to facilitate the adoption of Big Data in an enterprise. You can find more information about the Oracle Big Data connectors on OTN. You can find an overview of all the new features introduced in ODI 11.1.1.6 in the following document: ODI 11.1.1.6 New Features Overview

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  • Linked list example using threads

    - by Carl_1789
    I have read the following code of using CRITICAL_SECTION when working with multiple threads to grow a linked list. what would be the main() part which uses two threads to add to linked list? #include <windows.h> typedef struct _Node { struct _Node *next; int data; } Node; typedef struct _List { Node *head; CRITICAL_SECTION critical_sec; } List; List *CreateList() { List *pList = (List*)malloc(sizeof(pList)); pList->head = NULL; InitializeCriticalSection(&pList->critical_sec); return pList; } void AddHead(List *pList, Node *node) { EnterCriticalSection(&pList->critical_sec); node->next = pList->head; pList->head = node; LeaveCriticalSection(&pList->critical_sec); } void Insert(List *pList, Node *afterNode, Node *newNode) { EnterCriticalSection(&pList->critical_sec); if (afterNode == NULL) { AddHead(pList, newNode); } else { newNode->next = afterNode->next; afterNode->next = newNode; } LeaveCriticalSection(&pList->critical_sec); } Node *Next(List *pList, Node *node) { Node* next; EnterCriticalSection(&pList->critical_sec); next = node->next; LeaveCriticalSection(&pList->critical_sec); return next; }

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  • adding elements in to the doubly linked list

    - by user329820
    Hi this is my code for main class and doubly linked class and node class but when I run the program ,in the concole will show this"datastructureproject.DoublyLinkedList@19ee1ac" instead of the random numbers .please help me thanks! main class: public class Main { public static int getRandomNumber(double min, double max) { Random random = new Random(); return (int) (random.nextDouble() * (max - min) + min); } public static void main(String[] args) { int j; int i = 0; i = getRandomNumber(10, 10000); DoublyLinkedList listOne = new DoublyLinkedList(); for (j = 0; j <= i / 2; j++) { listOne.add(getRandomNumber(10, 10000)); } System.out.println(listOne); } } doubly linked list class: public class DoublyLinkedList { private Node head ; private Node tail; private long size = 0; public DoublyLinkedList() { head= new Node(0, null, null); tail = new Node(0, head, null); } public void add(int i){ head.setValue(i); Node newNode = new Node(); head.setNext(newNode); newNode.setPrev(head); newNode = head; } } and the node class is like the class that you have seen before (Node prev,Node next,int value)

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  • Meaning of NEXT in Linked List creation in perl

    - by seleniumnewbie
    So I am trying to learn Linked Lists using Perl. I am reading "Mastering Algorithms with Perl" by Job Orwant. In the book he explains how to create a linked list I understand most of it, but I just simply fail to understand the command/index/key NEXT in the second last line of the code snippet. $list=undef; $tail=\$list; foreach (1..5){ my $node = [undef, $_ * $_]; $$tail = $node; $tail = \${$node->[NEXT]}; # The NEXT on this line? } What is he trying to do there? Isn $node a scalar, which stores the address of the unnamed array. Also even if we are de-referencing $node, should we not refer to the individual elements by an index number example (0,1). If we do use "NEXT" as a key, is $node a reference to a hash? I am very confused. Something in plain English will be highly appreciated.

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  • Java How to find a value in a linked list iteratively and recursively

    - by Roxy
    Hi I have a method that has a reference to a linked list and a int value. So, this method would count and return how often the value happens in the linked list. So, I decided to make a class, public class ListNode{ public ListNode (int v, ListNode n) {value = v; next = n;) public int value; public ListNode next; } Then, the method would start with a public static int findValue(ListNode x, int valueToCount){ // so would I do it like this?? I don't know how to find the value, // like do I check it? for (int i =0; i< x.length ;i++){ valueToCount += valueToCount; } So, I CHANGED this part, If I did this recursively, then I would have public static int findValue(ListNode x, int valueToCount) { if (x.next != null && x.value == valueToCount { return 1 + findValue(x, valueToCount);} else return new findvalue(x, valueToCount); SO, is the recursive part correct now?

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  • How to implement a Linked List in Java?

    - by nbarraille
    Hello! I am trying to implement a simple HashTable in Java that uses a Linked List for collision resolution, which is pretty easy to do in C, but I don't know how to do it in Java, as you can't use pointers... First, I know that those structures are already implemented in Java, I'm not planning on using it, just training here... So I created an element, which is a string and a pointer to the next Element: public class Element{ private String s; private Element next; public Element(String s){ this.s = s; this.next = null; } public void setNext(Element e){ this.next = e; } public String getString(){ return this.s; } public Element getNext(){ return this.next; } @Override public String toString() { return "[" + s + "] => "; } } Of course, my HashTable has an array of Element to stock the data: public class CustomHashTable { private Element[] data; Here is my problem: For example I want to implement a method that adds an element AT THE END of the linked List (I know it would have been simpler and more efficient to insert the element at the beginning of the list, but again, this is only for training purposes). How do I do that without pointer? Here is my code (which could work if e was a pointer...): public void add(String s){ int index = hash(s) % data.length; System.out.println("Adding at index: " + index); Element e = this.data[index]; while(e != null){ e = e.getNext(); } e = new Element(s); } Thanks!

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  • Having trouble deleting a node from a linked list

    - by Requiem
    I've been working on this code for my shell that I'm creating and for some reason it isn't working. I'm implementing a watchuser function that watch's a user when an argument is given (args[1]). However, when a second argument (args[2]) of "off" is given, the user should be deleted from the linked list and should no longer be watched. struct userList * goList; goList = userInventory; do{ if (strcmp(userInventory->username, args[1]) == 0){ printf("%s\n", args[1]); printf("%s\n",userInventory->username); struct userList * temp2; temp2 = userInventory->next; if (userInventory->next != NULL){ userInventory->next = temp2->next; userInventory->next->prev = userInventory; } free(temp2); } goList = goList->next; }while (goList != userInventory); My global struct is also as follows: struct userList{ char * username; struct userList * prev; struct userList * next; } For reason, this code won't delete the user node from my linked list. The adding works, but this remove function won't and I'm not sure why. The print statements are there just to make sure it's executing the condition, which it is. If anyone could help me find the reasoning behind my error, I'd greatly appreciate it. Till then, I'll be trying to debug this. Thanks.

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  • Data recovery on a data HDD (no OS)

    - by aCuria
    I am helping a family member with a dead hard disk. It is a seagate 200Gb 3.5" HDD in one of those old-school external enclosures. The problem was that windows failed to detect the hard disk when plugged in through USB. I removed the hard disk from its enclosure, and plugged it into my desktop PC. The BIOS does detect it upon POST, but unfortunately windows 7 would refuse to boot. It will get stuck on the loading screen with the glowing windows logo. Safe mode doesn't help either. What options do I have before going for some professional data recovery? edit: Someone modified the Title to something completely different from what I was asking, i just changed it back. 1) 2 HDD drives, DiskA(Dead), DiskB(my OS disk) 2) when B is connected to my system, everything works fine 3) when A AND B is connected, failure to boot. POSTs fine, but windows wont load 4) A has NO OS, its PURE data. It came from an EXTERNAL HDD enclosure which doesnt belong to me, and im trying to do data recovery.

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  • Segmentation fault in a function to reverse a singly linked list recursivley.

    - by Amanda
    I am implementing a function to recursively reverse a linked-list, but getting seg-fault. typedef struct _node { int data; struct _node *next; } Node, *NodeP; NodeP recursiveReverseList(NodeP first){ if(first == NULL) return NULL; if(first->next == NULL) return first; NodeP rest = recursiveReverseList(first->next); rest->next = first; first->next = NULL; return first; } Can you please help? P.S. The iterative version is working fine though. Its not homework. Just practicing C. Thank you all :)

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  • Data Governance 2010 Conference in San Diego

    - by Tony Ouk
    The Data Governance Annual Conference is one of the world's most authoritative and vendor neutral event on Data Governance and Data Quality.  The conference will focus on the "how-tos" from starting a data governance and stewardship program to attaining data governance maturity with specific topics on MDM.  This year's event will be hosted June 7 through June 10 in San Diego, California. For more information, including registration details, visit the Data Governance 2010 Conference website.

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  • How to search for newline or linebreak characters in Excel?

    - by Highly Irregular
    I've imported some data into Excel (from a text file) and it contains some sort of newline characters. It looks like this initially: If I hit F2 (to edit) then Enter (to save changes) on each of the cells with a newline (without actually editing anything), Excel automatically changes the layout to look like this: I don't want these newlines characters here, as it messes up data processing further down the track. How can I do a search for these to detect more of them? The usual search function doesn't accept an enter character as a search character.

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  • Oracle Data Integration 12c: Simplified, Future-Ready, High-Performance Solutions

    - by Thanos Terentes Printzios
    In today’s data-driven business environment, organizations need to cost-effectively manage the ever-growing streams of information originating both inside and outside the firewall and address emerging deployment styles like cloud, big data analytics, and real-time replication. Oracle Data Integration delivers pervasive and continuous access to timely and trusted data across heterogeneous systems. Oracle is enhancing its data integration offering announcing the general availability of 12c release for the key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c, delivering Simplified and High-Performance Solutions for Cloud, Big Data Analytics, and Real-Time Replication. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. With the 12c release Oracle becomes the new leader in the data integration and replication technologies as no other vendor offers such a complete set of data integration capabilities for pervasive, continuous access to trusted data across Oracle platforms as well as third-party systems and applications. Oracle Data Integration 12c release addresses data-driven organizations’ critical and evolving data integration requirements under 3 key themes: Future-Ready Solutions : Supporting Current and Emerging Initiatives Extreme Performance : Even higher performance than ever before Fast Time-to-Value : Higher IT Productivity and Simplified Solutions  With the new capabilities in Oracle Data Integrator 12c, customers can benefit from: Superior developer productivity, ease of use, and rapid time-to-market with the new flow-based mapping model, reusable mappings, and step-by-step debugger. Increased performance when executing data integration processes due to improved parallelism. Improved productivity and monitoring via tighter integration with Oracle GoldenGate 12c and Oracle Enterprise Manager 12c. Improved interoperability with Oracle Warehouse Builder which enables faster and easier migration to Oracle Data Integrator’s strategic data integration offering. Faster implementation of business analytics through Oracle Data Integrator pre-integrated with Oracle BI Applications’ latest release. Oracle Data Integrator also integrates simply and easily with Oracle Business Analytics tools, including OBI-EE and Oracle Hyperion. Support for loading and transforming big and fast data, enabled by integration with big data technologies: Hadoop, Hive, HDFS, and Oracle Big Data Appliance. Only Oracle GoldenGate provides the best-of-breed real-time replication of data in heterogeneous data environments. With the new capabilities in Oracle GoldenGate 12c, customers can benefit from: Simplified setup and management of Oracle GoldenGate 12c when using multiple database delivery processes via a new Coordinated Delivery feature for non-Oracle databases. Expanded heterogeneity through added support for the latest versions of major databases such as Sybase ASE v 15.7, MySQL NDB Clusters 7.2, and MySQL 5.6., as well as integration with Oracle Coherence. Enhanced high availability and data protection via integration with Oracle Data Guard and Fast-Start Failover integration. Enhanced security for credentials and encryption keys using Oracle Wallet. Real-time replication for databases hosted on public cloud environments supported by third-party clouds. Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c and other Oracle technologies, such as Oracle Database 12c and Oracle Applications, provides a number of benefits for organizations: Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c enables developers to leverage Oracle GoldenGate’s low overhead, real-time change data capture completely within the Oracle Data Integrator Studio without additional training. Integration with Oracle Database 12c provides a strong foundation for seamless private cloud deployments. Delivers real-time data for reporting, zero downtime migration, and improved performance and availability for Oracle Applications, such as Oracle E-Business Suite and ATG Web Commerce . Oracle’s data integration offering is optimized for Oracle Engineered Systems and is an integral part of Oracle’s fast data, real-time analytics strategy on Oracle Exadata Database Machine and Oracle Exalytics In-Memory Machine. Oracle Data Integrator 12c and Oracle GoldenGate 12c differentiate the new offering on data integration with these many new features. This is just a quick glimpse into Oracle Data Integrator 12c and Oracle GoldenGate 12c. Find out much more about the new release in the video webcast "Introducing 12c for Oracle Data Integration", where customer and partner speakers, including SolarWorld, BT, Rittman Mead will join us in launching the new release. Resource Kits Meet Oracle Data Integration 12c  Discover what's new with Oracle Goldengate 12c  Oracle EMEA DIS (Data Integration Solutions) Partner Community is available for all your questions, while additional partner focused webcasts will be made available through our blog here, so stay connected. For any questions please contact us at partner.imc-AT-beehiveonline.oracle-DOT-com Stay Connected Oracle Newsletters

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  • Import and Export data from SQL Server 2005 to XL Sheet

    - by SAMIR BHOGAYTA
    For uploading the data from Excel Sheet to SQL Server and viceversa, we need to create a linked server in SQL Server. Expample linked server creation: Before you executing the below command the excel sheet should be created in the specified path and it should contain the name of the columns. EXEC sp_addlinkedserver 'ExcelSource2', 'Jet 4.0', 'Microsoft.Jet.OLEDB.4.0', 'C:\Srinivas\Vdirectory\Testing\Marks.xls', NULL, 'Excel 5.0' Once you executed above query it will crate linked server in SQL Server 2005. The following are the Query from sending the data from Excel sheet to SQL Server 2005. INSERT INTO emp SELECT * from OPENROWSET('Microsoft.Jet.OLEDB.4.0', 'Excel 8.0;Database=C:\text.xls','SELECT * FROM [sheet1$]') The following query is for sending the data from SQL Server 2005 to Excel Sheet. insert into OPENROWSET('Microsoft.Jet.OLEDB.4.0', 'Excel 8.0;Database=c:\text.xls;', 'SELECT * FROM [sheet1$]') select * from emp

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  • Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

    - by Compudicted
    Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Weindows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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  • Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

    - by Compudicted
    Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review-again.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Windows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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  • Internal Mutation of Persistent Data Structures

    - by Greg Ros
    To clarify, when I mean use the terms persistent and immutable on a data structure, I mean that: The state of the data structure remains unchanged for its lifetime. It always holds the same data, and the same operations always produce the same results. The data structure allows Add, Remove, and similar methods that return new objects of its kind, modified as instructed, that may or may not share some of the data of the original object. However, while a data structure may seem to the user as persistent, it may do other things under the hood. To be sure, all data structures are, internally, at least somewhere, based on mutable storage. If I were to base a persistent vector on an array, and copy it whenever Add is invoked, it would still be persistent, as long as I modify only locally created arrays. However, sometimes, you can greatly increase performance by mutating a data structure under the hood. In more, say, insidious, dangerous, and destructive ways. Ways that might leave the abstraction untouched, not letting the user know anything has changed about the data structure, but being critical in the implementation level. For example, let's say that we have a class called ArrayVector implemented using an array. Whenever you invoke Add, you get a ArrayVector build on top of a newly allocated array that has an additional item. A sequence of such updates will involve n array copies and allocations. Here is an illustration: However, let's say we implement a lazy mechanism that stores all sorts of updates -- such as Add, Set, and others in a queue. In this case, each update requires constant time (adding an item to a queue), and no array allocation is involved. When a user tries to get an item in the array, all the queued modifications are applied under the hood, requiring a single array allocation and copy (since we know exactly what data the final array will hold, and how big it will be). Future get operations will be performed on an empty cache, so they will take a single operation. But in order to implement this, we need to 'switch' or mutate the internal array to the new one, and empty the cache -- a very dangerous action. However, considering that in many circumstances (most updates are going to occur in sequence, after all), this can save a lot of time and memory, it might be worth it -- you will need to ensure exclusive access to the internal state, of course. This isn't a question about the efficacy of such a data structure. It's a more general question. Is it ever acceptable to mutate the internal state of a supposedly persistent or immutable object in destructive and dangerous ways? Does performance justify it? Would you still be able to call it immutable? Oh, and could you implement this sort of laziness without mutating the data structure in the specified fashion?

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  • Sabre Manages Fast Data Growth with Oracle Data Integration Products

    - by Irem Radzik
    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-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Last year at OpenWorld we announced Sabre Holding as a winner of the Fusion Middleware Innovation Awards. The Sabre team did an excellent job at leveraging cutting edge technologies for managing rapid data growth and exponential scalability demands they have experienced in the travel industry. Today we announced the details and specific benefits of Sabre’s new real-time data integration solution in a press release. Please take a look if you haven’t seen it yet. Sabre Holdings Deploys Oracle Data Integrator and Oracle GoldenGate to Support Rapid Customer Growth There are 3 different areas of benefits Sabre achieved by using Oracle Data Integration products: Manages 7X increase in data sources for the enterprise data warehouse Reduced infrastructure complexity Decreased time to market for new products and services by 30 percent. This simply shows that using latest technologies helps the companies to innovate robust solutions against today’s key data management challenges. And the benefit of using a next generation data integration technology is not only seen in the IT operations, but also in the business side. A better data integration solution for the enterprise data warehouse delivered the platform they need to accelerate how they service their customers, improving their competitive advantage. Tomorrow I will give another great example of innovation with next generation data integration from Oracle. We will be discussing the Fusion Middleware Innovation Awards 2012 winners and their results with using Oracle’s data integration products.

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  • implementing dynamic query handler on historical data

    - by user2390183
    EDIT : Refined question to focus on the core issue Context: I have historical data about property (house) sales collected from various sources in a centralized/cloud data source (assume info collection is handled by a third party) Planning to develop an application to query and retrieve data from this centralized data source Example Queries: Simple : for given XYZ post code, what is average house price for 3 bed room house? Complex: What is estimated price for an house at "DD,Some Street,XYZ Post Code" (worked out from average values of historic data filtered by various characteristics of the house: house post code, no of bed rooms, total area, and other deeper insights like house building type, year of built, features)? In addition to average price, the application should support other property info ** maximum, or minimum price..etc and trend (graph) on a selected property attribute over a period of time**. Hence, the queries should not enforce the search based on a primary key or few fixed fields In other words, queries can be What is the change in 3 Bed Room house price (irrespective of location) over last 30 days? What kind of properties we can get for X price (irrespective of location or house type) The challenge I have is identifying the domain (BI/ Data Analytical or DB Design or DB Query Interface or DW related or something else) this problem (dynamic query on historic data) belong to, so that I can do further exploration My findings so far I could be wrong on the following, so please correct me if you think so I briefly read about BI/Data Analytics - I think it is heavy weight solution for my problem and has scalability issues. DB Design - As I understand RDBMS works well if you know Data model at design time. I am expecting attributes about property or other entity (user) that am going to bring in, would evolve quickly. hence maintenance would be an issue. As I am going to have multiple users executing query at same time, performance would be a bottleneck Other options like Graph DB (http://www.tinkerpop.com/) seems to be bit complex (they are good. but using those tools meant for generic purpose, make me think like assembly programming to solve my problem ) BigData related solution are to analyse data from multiple unrelated domains So, Any suggestion on the space this problem fit in ? (Especially if you have design/implementation experience of back-end for property listing or similar portals)

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  • AngularJS dealing with large data sets (Strategy)

    - by Brian
    I am working on developing a personal temperature logging viewer based on my rasppi curl'ing data into my web server's api. Temperatures are taken every 2 seconds and I can have several temperature sensors posting data. Needless to say I will have a lot of data to handle even within the scope of an hour. I have implemented a very simple paging api from the server so the server doesn't timeout and is currently only returning data in 1000 units per call, then paging through the data. I had the idea to intially show say the last 20 minutes of data from a sensor (or all sensors depending on user choices), then allowing the user to select other timeframes from which to show data. The issue comes in when you want to view all sensors or an extended time period (say 24 hours). Is there a best practice of handling this large amount of data? Would it be useful to load those first 20 minutes into the live view and then cache into local storage something like the last 24 hours? I haven't been able to find a decent idea of this in use yet even though there are a lot of ways to take this problem. I am just looking for some suggestions as to what might provide a good balance between good performance and not caching the entire data set on the client side (as beyond a week of data this might not be feasible).

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  • I need some help creating a non-binary tree (or some other data structure that will better solve my problem)

    - by EDO
    I have about ten lists of numbers and some strings. Each list has about <= 30K lines. Each line on a list has a distinct number. I need to build an efficient way of finding all the lines in each list that has the same 'control' number (or key for dB guys) and comparing what is in their string parts. I am writing this in Java. I have thought about using trees but my brain cells are about burnt now. I need some help.

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  • replacing data.frame element-wise operations with data.table (that used rowname)

    - by Harold
    So lets say I have the following data.frames: df1 <- data.frame(y = 1:10, z = rnorm(10), row.names = letters[1:10]) df2 <- data.frame(y = c(rep(2, 5), rep(5, 5)), z = rnorm(10), row.names = letters[1:10]) And perhaps the "equivalent" data.tables: dt1 <- data.table(x = rownames(df1), df1, key = 'x') dt2 <- data.table(x = rownames(df2), df2, key = 'x') If I want to do element-wise operations between df1 and df2, they look something like dfRes <- df1 / df2 And rownames() is preserved: R> head(dfRes) y z a 0.5 3.1405463 b 1.0 1.2925200 c 1.5 1.4137930 d 2.0 -0.5532855 e 2.5 -0.0998303 f 1.2 -1.6236294 My poor understanding of data.table says the same operation should look like this: dtRes <- dt1[, !'x', with = F] / dt2[, !'x', with = F] dtRes[, x := dt1[,x,]] setkey(dtRes, x) (setkey optional) Is there a more data.table-esque way of doing this? As a slightly related aside, more generally, I would have other columns such as factors in each data.table and I would like to omit those columns while doing the element-wise operations, but still have them in the result. Does this make sense? Thanks!

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  • Handwritten linked list is segfaulting and I don't understand why

    - by Born2Smile
    Hi I was working on a bit of fun, making an interface to run gnuplot from within c++, and for some reason the my linked list implementation fails. The code below fails on the line plots-append(&plot). Stepping through the code I discovered that for some reason the destructor ~John() is called immediately after the constructor John(), and I cannot seem to figure out why. The code included below is a stripped down version operating only on Plot*. Originally I made the linked list as a template class. And it worked fine as ll<int and ll<char* but for some reason it fails as ll<Plot*. Could youp please help me figure out why it fails? and perhaps help me understand how to make it work? In advance: Thanks a heap! //B2S #include <string.h class Plot{ char title[80]; public: Plot(){ } }; class Link{ Plot* element; Link* next; Link* prev; friend class ll; }; class ll{ Link* head; Link* tail; public: ll(){ head = tail = new Link(); head-prev = tail-prev = head-next = tail-next = head; } ~ll(){ while (head!=tail){ tail = tail-prev; delete tail-next; } delete head; } void append(Plot* element){ tail-element = element; tail-next = new Link(); tail-next-prev = tail; tail-next = tail; } }; class John{ ll* plots; public: John(){ plots= new ll(); } ~John(){ delete plots; } John(Plot* plot){ John(); plots-append(plot); } }; int main(){ Plot p; John k(&p); }

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  • Using triggers to update linked server table

    - by tabouakl
    Can I use triggers to insert or update tables in a linked server? I tried it and got the following error: Unable to start a nested transaction for OLE DB provider 'SQLOLEDB'. A nested transaction was required because the XACT_ABORT option was set to OFF. [OLE/DB provider returned message: Cannot start more transactions on this session.] OLE DB error trace [OLE/DB Provider 'SQLOLEDB' ITransactionLocal::StartTransaction returned 0x8004d013: ISOLEVEL=4096].

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