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  • Exporting Master Data from Master Data Services

    This white paper describes how to export master data from Microsoft SQL Server Master Data Services (MDS) using a subscription view, and how to import the master data into an external system using SQL Server Integration Services (SSIS). The white paper provides a step-by-step sample for creating a subscription view and an SSIS package. 12 essential tools for database professionalsThe SQL Developer Bundle contains 12 tools designed with the SQL Server developer and DBA in mind. Try it now.

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  • Google Webmaster Tools Data Highlighter says "Failed to load data, please try again later"

    - by George Garside
    I seem to be unable to access the data highlighter in Google Webmaster Tools since I attempted to start a new highlight on a page. Clicking the red Start Highlighting button to open the tagger did nothing, so I refreshed. Now, the page loads without the middle content section, then a few seconds later shows the following error: Failed to load data, please try again later. I can't get any of the middle section to load, even the list of current pages/page sets that have been highlighted—this error shows. I thought it may be a Google service outage, but other sites' data highlighters work fine. It also seems coincidental that it stopped working after I attempted to start highlighting—I was able to list the existing pages and page sets fine before that, and still am able to access the service on other sites. I've tried clearing browser data and have tried Google Chrome as well—same problem. What's happened?

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  • Big Data – Buzz Words: What is NewSQL – Day 10 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the relational database. In this article we will take a quick look at the what is NewSQL. What is NewSQL? NewSQL stands for new scalable and high performance SQL Database vendors. The products sold by NewSQL vendors are horizontally scalable. NewSQL is not kind of databases but it is about vendors who supports emerging data products with relational database properties (like ACID, Transaction etc.) along with high performance. Products from NewSQL vendors usually follow in memory data for speedy access as well are available immediate scalability. NewSQL term was coined by 451 groups analyst Matthew Aslett in this particular blog post. On the definition of NewSQL, Aslett writes: “NewSQL” is our shorthand for the various new scalable/high performance SQL database vendors. We have previously referred to these products as ‘ScalableSQL‘ to differentiate them from the incumbent relational database products. Since this implies horizontal scalability, which is not necessarily a feature of all the products, we adopted the term ‘NewSQL’ in the new report. And to clarify, like NoSQL, NewSQL is not to be taken too literally: the new thing about the NewSQL vendors is the vendor, not the SQL. In other words - NewSQL incorporates the concepts and principles of Structured Query Language (SQL) and NoSQL languages. It combines reliability of SQL with the speed and performance of NoSQL. Categories of NewSQL There are three major categories of the NewSQL New Architecture – In this framework each node owns a subset of the data and queries are split into smaller query to sent to nodes to process the data. E.g. NuoDB, Clustrix, VoltDB MySQL Engines – Highly Optimized storage engine for SQL with the interface of MySQ Lare the example of such category. E.g. InnoDB, Akiban Transparent Sharding – This system automatically split database across multiple nodes. E.g. Scalearc  Summary In simple words – NewSQL is kind of database following relational database principals and provides scalability like NoSQL. Tomorrow In tomorrow’s blog post we will discuss about the Role of Cloud Computing in 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 Best Articles for Backing Up and Syncing Your Data

    - by Lori Kaufman
    World Backup Day is March 31st and we decided to provide you with some useful information to make backing up your data easier. We’ve published articles about backing up various types of data and settings both offline and online. There’s all kinds of settings on your computer to backup in addition to your personal data, such as Wi-Fi passwords, drivers, and settings for programs like web browsers, Office, and Windows Live Writer. There are also many tools available to help you keep your data and settings backed up. Make Your Own Windows 8 Start Button with Zero Memory Usage Reader Request: How To Repair Blurry Photos HTG Explains: What Can You Find in an Email Header?

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  • Big Data Learning Resources

    - by Lara Rubbelke
    I have recently had several requests from people asking for resources to learn about Big Data and Hadoop. Below is a list of resources that I typically recommend. I'll update this list as I find more resources. Let's crowdsource this... Tell me your favorite resources and I'll get them on the list! Books and Whitepapers Planning for Big Data Free e-book Great primer on the general Big Data space. This is always my recommendation for people who are new to Big Data and are trying to understand it....(read more)

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  • Distortion in format of data in wordpad file when shifted from windows XP to winows 2007

    - by Harpreet
    I have many data files which were set to open in wordpad file in windows XP. Those files have a particular format for data, like following: Name of Data file No. of data columns Name of data in column_1 Name of data in column_2 . . . Name of data in column_n column_1 column_2 column_3 ... column_n Now my computer has been formatted and OS is changed to windows 2007, however when I open my data files in wordpad the above format of data is no more present. The format in wordpad in windows 2007 seems to be distorted. Does anyone knows what to do to restore the format as shown above, which is what the data used to look like in XP? I have attached the snap shot of the new distorted format of data as seen in wordpad in windows 2007. The snap shot shows 100 column names, however the data columns present are only 5 when it should be actually 100 data columns.

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  • Data Loading Issues? Try the new Demantra Data Load Guided Resolution

    - by user702295
    Hello!   Do you have data loading issues?  Perhaps you are trying the new partial schema export tool.   New to Demantra, the Data Load Guided Resolution, document 1461899.1.  This interactive guide will help you locate known solutions to previously discovered issues quickly.  From performance, ORA and ODPM errors to collections related issues that have no known hard number error.   This guide includes the diagnosis of data being imported into Demantra and data being exported from Demantra.  Contact me with any questions or suggestions.   Thank You!

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  • how to recover deleted ntfs patition with data entirely while installing ubuntu 13.04

    - by Anson Varghese
    I've installed ubuntu 13.04 onto my hp 2231tx computer. During installation all of my data was erased. I didn't know all of my three partitions would be deleted. I was shocked after finding out that all of my personal data was erased. I didn't know what to do to resolve this problem so I search google for an answer. I found a program called testdisk and I used it to recover about half of my data. Among this data weren't my personal photos and videos. Is there a way to recover the other half?

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  • E-Book on big data (featuring Analysts, Customers and more)

    - by Jean-Pierre Dijcks
    As we are gearing up for Openworld, here is a nice E-book on big data to start paging through. It contains Gartner's take on big data, customer and partner interviews and a lot more good info. Enjoy the read so you come prepared for Openworld!! Read the E-Book here. For those coming to Oracle Openworld (or the Americas Cup races around the same time), you can find big data sessions via this URL. Enjoy!!

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  • Choices in Architecture, Design, Algorithms, Data Structures for effective RDF Reasoning and Querying in a Big Data Environment [on hold]

    - by user2891213
    As part of my academic project I would like to know what choices in Architecture, Design, Algorithms, Data Structures do we need in order to provide effective and efficient RDF Reasoning and Querying in a Big Data Environment. Basically I want to get info regarding below points: What are the Systems and Software to get appropriate Architecture? What kind of API layer(s) would we need on top of the Big Data stores, to make this possible? The Indexing structures we will need. The appropriate Algorithms, and appropriate Algorithms for Query Planning across Big Data stores. The Performance Analysis and Cost Models we will need to justify the design decisions we have made along the way. Can anyone please provide pointers.. Thanks, David

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  • Data Structure Behind Amazon S3s Keys (Filtering Data Structure)

    - by dimo414
    I'd like to implement a data structure similar to the lookup functionality of Amazon S3. For those of you who don't know what I'm taking about, Amazon S3 stores all files at the root, but allows you to look up groups of files by common prefixes in their names, therefore replicating the power of a directory tree without the complexity of it. The catch is, both lookup and filter operations are O(1) (or close enough that even on very large buckets - S3's disk equivalents - both operations might as well be O(1))). So in short, I'm looking for a data structure that functions like a hash map, with the added benefit of efficient (at the very least not O(n)) filtering. The best I can come up with is extending HashMap so that it also contains a (sorted) list of contents, and doing a binary search for the range that matches the prefix, and returning that set. This seems slow to me, but I can't think of any other way to do it. Does anyone know either how Amazon does it, or a better way to implement this data structure?

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  • Best Data Structure For Time Series Data

    - by TriParkinson
    Hi all, I wonder if someone could take a minute out of their day to give their two cents on my problem. I would like some suggestions on what would be the best data structure for representing, on disk, a large data set of time series data. The main priority is speed of insertion, with other priorities in decreasing order; speed of retrieval, size on disk, size in memory, speed of removal. I have seen that B+ trees are often used in database because of their fast search times, but how about for fast insertion times? Is a linked list really the way to go? Thanks in advance for your time, Tri

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  • MySQL: Blank row in table after LOAD DATA INFILE

    - by Tom
    Hi, I'm uploading a large amount of data from a CSV (I'm doing it via MySQL Workbench): LOAD DATA INFILE 'C:/development/mydoc.csv' INTO TABLE mydatabase.mytable CHARACTER SET utf8 FIELDS TERMINATED BY ',' OPTIONALLY ENCLOSED BY '"' LINES TERMINATED BY '\r'; However, I'm noticing that it keeps adding an empty line full of nulls/zeros after the last record. I'm guessing it's because of the "LINES TERMINATED" command. However, I need that to load the data in correctly. Is there some way around this / some better SQL to avoid the blank row in the table? Thanks

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  • Update tableview instantly as data pushed in core data iphone

    - by user336685
    I need to update the tableview as soon as the content is pushed in core data database. for this AppDelegate.m contains following code NSManagedObjectContext *moc = [self managedObjectContext]; NSFetchRequest *request = [[NSFetchRequest alloc] init]; [request setEntity:[NSEntityDescription entityForName:@"FeedItem" inManagedObjectContext:moc]]; //for loop // push data in code data & then save context [moc save:&error]; ZAssert(error == nil, @"Error saving context: %@", [error localizedDescription]); //for loop ends This code triggers following code from RootviewController.m - (void)controllerWillChangeContent:(NSFetchedResultsController*)controller { [[self tableView] beginUpdates]; } But this updates the tableview only at the end of the for loop ,the table does not get updated after immediate push in db. I tried following code but that didn't work - (void)controllerDidChangeContent:(NSFetchedResultsController *)controller { // In the simplest, most efficient, case, reload the table view. [self.tableView reloadData]; } I have been stuck with this problem for several days.Please help.Thanks in advance for solution.

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  • Core Data data type for just the date - not including time

    - by Jason
    I am new at Core Data, and it seems like it is a great way to manage the data store. However I am also very memory-conscious due to the fact that the iPhone doesn't have that much of it. I was a little surprised to see that the data types are so limited - eg. there is a Date type which includes also the time, but no Date type for just the date! All the time information takes up precious bytes of memory, if I just wanted an attribute with the date (e.g. 2/15/2010 rather than 2/15/2010 02:34:48), how could I do this? Is it possible?

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  • Big DataData Mining with Hive – What is Hive? – What is HiveQL (HQL)? – Day 15 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the operational database in Big Data Story. In this article we will understand what is Hive and HQL in Big Data Story. Yahoo started working on PIG (we will understand that in the next blog post) for their application deployment on Hadoop. The goal of Yahoo to manage their unstructured data. Similarly Facebook started deploying their warehouse solutions on Hadoop which has resulted in HIVE. The reason for going with HIVE is because the traditional warehousing solutions are getting very expensive. What is HIVE? Hive is a datawarehouseing infrastructure for Hadoop. The primary responsibility is to provide data summarization, query and analysis. It  supports analysis of large datasets stored in Hadoop’s HDFS as well as on the Amazon S3 filesystem. The best part of HIVE is that it supports SQL-Like access to structured data which is known as HiveQL (or HQL) as well as big data analysis with the help of MapReduce. Hive is not built to get a quick response to queries but it it is built for data mining applications. Data mining applications can take from several minutes to several hours to analysis the data and HIVE is primarily used there. HIVE Organization The data are organized in three different formats in HIVE. Tables: They are very similar to RDBMS tables and contains rows and tables. Hive is just layered over the Hadoop File System (HDFS), hence tables are directly mapped to directories of the filesystems. It also supports tables stored in other native file systems. Partitions: Hive tables can have more than one partition. They are mapped to subdirectories and file systems as well. Buckets: In Hive data may be divided into buckets. Buckets are stored as files in partition in the underlying file system. Hive also has metastore which stores all the metadata. It is a relational database containing various information related to Hive Schema (column types, owners, key-value data, statistics etc.). We can use MySQL database over here. What is HiveSQL (HQL)? Hive query language provides the basic SQL like operations. Here are few of the tasks which HQL can do easily. Create and manage tables and partitions Support various Relational, Arithmetic and Logical Operators Evaluate functions Download the contents of a table to a local directory or result of queries to HDFS directory Here is the example of the HQL Query: SELECT upper(name), salesprice FROM sales; SELECT category, count(1) FROM products GROUP BY category; When you look at the above query, you can see they are very similar to SQL like queries. Tomorrow In tomorrow’s blog post we will discuss about very important components of the Big Data Ecosystem – Pig. 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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  • Clever ways of implementing different data structures in C & data structures that should be used mor

    - by Yktula
    What are some clever (not ordinary) ways of implementing data structures in C, and what are some data structures that should be used more often? For example, what is the most effective way (generating minimal overhead) to implement a directed and cyclic graph with weighted edges in C? I know that we can store the distances in an array as is done here, but what other ways are there to implement this kind of a graph?

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  • Using GameKit to transfer CoreData data between iPhones, via NSDictionary

    - by OscarTheGrouch
    I have an application where I would like to exchange information, managed via Core Data, between two iPhones. First turning the Core Data object to an NSDictionary (something very simple that gets turned into NSData to be transferred). My CoreData has 3 string attributes, 2 image attributes that are transformables. I have looked through the NSDictionary API but have not had any luck with it, creating or adding the CoreData information to it. Any help or sample code regarding this would be greatly appreciated.

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  • core-data relationships and data structure.

    - by Boaz
    What is the right way to build iPhone core data for this SMS like app (with location)? - I want to represent an entity of conversation with "profile1" "profile2" that heritage from a profile entity, and a message entity with: "to" "from" "body" where the "to" and "from" are equal to "profile1" and/or "profile2" in the conversation entity. How can I make such a relationships? is there a better way to represent the data (other structure)? Thanks

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  • [Visual C++]Forcing memory alignment of variables/data-structures

    - by John
    I'm looking at using SSE and I gather aligning data on 16byte boundaries is recommended. There are two cases to consider: float data[4]; struct myystruct { float x,y,z,w; }; I'm not sure the first case can be done explicitly, though there's perhaps a compiler option I could use? In the second case I remember being able to control packing in old versions of GCC several years back, is this still possible?

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  • SQL SERVER – Data Pages in Buffer Pool – Data Stored in Memory Cache

    - by pinaldave
    This will drop all the clean buffers so we will be able to start again from there. Now, run the following script and check the execution plan of the query. Have you ever wondered what types of data are there in your cache? During SQL Server Trainings, I am usually asked if there is any way one can know how much data in a table is stored in the memory cache? The more detailed question I usually get is if there are multiple indexes on table (and used in a query), were the data of the single table stored multiple times in the memory cache or only for a single time? Here is a query you can run to figure out what kind of data is stored in the cache. USE AdventureWorks GO SELECT COUNT(*) AS cached_pages_count, name AS BaseTableName, IndexName, IndexTypeDesc FROM sys.dm_os_buffer_descriptors AS bd INNER JOIN ( SELECT s_obj.name, s_obj.index_id, s_obj.allocation_unit_id, s_obj.OBJECT_ID, i.name IndexName, i.type_desc IndexTypeDesc FROM ( SELECT OBJECT_NAME(OBJECT_ID) AS name, index_id ,allocation_unit_id, OBJECT_ID FROM sys.allocation_units AS au INNER JOIN sys.partitions AS p ON au.container_id = p.hobt_id AND (au.type = 1 OR au.type = 3) UNION ALL SELECT OBJECT_NAME(OBJECT_ID) AS name, index_id, allocation_unit_id, OBJECT_ID FROM sys.allocation_units AS au INNER JOIN sys.partitions AS p ON au.container_id = p.partition_id AND au.type = 2 ) AS s_obj LEFT JOIN sys.indexes i ON i.index_id = s_obj.index_id AND i.OBJECT_ID = s_obj.OBJECT_ID ) AS obj ON bd.allocation_unit_id = obj.allocation_unit_id WHERE database_id = DB_ID() GROUP BY name, index_id, IndexName, IndexTypeDesc ORDER BY cached_pages_count DESC; GO Now let us run the query above and observe the output of the same. We can see in the above query that there are four columns. Cached_Pages_Count lists the pages cached in the memory. BaseTableName lists the original base table from which data pages are cached. IndexName lists the name of the index from which pages are cached. IndexTypeDesc lists the type of index. Now, let us do one more experience here. Please note that you should not run this test on a production server as it can extremely reduce the performance of the database. DBCC DROPCLEANBUFFERS This will drop all the clean buffers and we will be able to start again from there. Now run following script and check the execution plan for the same. USE AdventureWorks GO SELECT UnitPrice, ModifiedDate FROM Sales.SalesOrderDetail WHERE SalesOrderDetailID BETWEEN 1 AND 100 GO The execution plans contain the usage of two different indexes. Now, let us run the script that checks the pages cached in SQL Server. It will give us the following output. It is clear from the Resultset that when more than one index is used, datapages related to both or all of the indexes are stored in Memory Cache separately. Let me know what you think of this article. I had a great pleasure while writing this article because I was able to write on this subject, which I like the most. In the next article, we will exactly see what data are cached and those that are not cached, using a few undocumented commands. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: DMV, Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL DMV

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