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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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  • 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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  • Bitmask data insertions in SSDT Post-Deployment scripts

    - by jamiet
    On my current project we are using SQL Server Data Tools (SSDT) to manage our database schema and one of the tasks we need to do often is insert data into that schema once deployed; the typical method employed to do this is to leverage Post-Deployment scripts and that is exactly what we are doing. Our requirement is a little different though, our data is split up into various buckets that we need to selectively deploy on a case-by-case basis. I was going to use a SQLCMD variable for each bucket (defaulted to some value other than “Yes”) to define whether it should be deployed or not so we could use something like this in our Post-Deployment script: IF ($(DeployBucket1Flag) = 'Yes')BEGIN   :r .\Bucket1.data.sqlENDIF ($(DeployBucket2Flag) = 'Yes')BEGIN   :r .\Bucket2.data.sqlENDIF ($(DeployBucket3Flag) = 'Yes')BEGIN   :r .\Bucket3.data.sqlEND That works fine and is, I’m sure, a very common technique for doing this. It is however slightly ugly because we have to litter our deployment with various SQLCMD variables. My colleague James Rowland-Jones (whom I’m sure many of you know) suggested another technique – bitmasks. I won’t go into detail about how this works (James has already done that at Using a Bitmask - a practical example) but I’ll summarise by saying that you can deploy different combinations of the buckets simply by supplying a different numerical value for a single SQLCMD variable. Each bit of that value’s binary representation signifies whether a particular bucket should be deployed or not. This is better demonstrated using the following simple script (which can be easily leveraged inside your Post-Deployment scripts): /* $(DeployData) is a SQLCMD variable that would, if you were using this in SSDT, be declared in the SQLCMD variables section of your project file. It should contain a numerical value, defaulted to 0. In this example I have declared it using a :setvar statement. Test the affect of different values by changing the :setvar statement accordingly. Examples: :setvar DeployData 1 will deploy bucket 1 :setvar DeployData 2 will deploy bucket 2 :setvar DeployData 3   will deploy buckets 1 & 2 :setvar DeployData 6   will deploy buckets 2 & 3 :setvar DeployData 31  will deploy buckets 1, 2, 3, 4 & 5 */ :setvar DeployData 0 DECLARE  @bitmask VARBINARY(MAX) = CONVERT(VARBINARY,$(DeployData)); IF (@bitmask & 1 = 1) BEGIN     PRINT 'Bucket 1 insertions'; END IF (@bitmask & 2 = 2) BEGIN     PRINT 'Bucket 2 insertions'; END IF (@bitmask & 4 = 4) BEGIN     PRINT 'Bucket 3 insertions'; END IF (@bitmask & 8 = 8) BEGIN     PRINT 'Bucket 4 insertions'; END IF (@bitmask & 16 = 16) BEGIN     PRINT 'Bucket 5 insertions'; END An example of running this using DeployData=6 The binary representation of 6 is 110. The second and third significant bits of that binary number are set to 1 and hence buckets 2 and 3 are “activated”. Hope that makes sense and is useful to some of you! @Jamiet P.S. I used the awesome HTML Copy feature of Visual Studio’s Productivity Power Tools in order to format the T-SQL code above for this blog post.

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  • Looking for Cutting-Edge Data Integration: 2014 Excellence Awards

    - by Sandrine Riley
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 It is nomination time!!! This year's Oracle Fusion Middleware Excellence Awards will honor customers and partners who are creatively using various products across Oracle Fusion Middleware. Think you have something unique and innovative with one or a few of our Oracle Data Integration products? We would love to hear from you! Please submit today. The deadline for the nomination is June 20, 2014. What you win: An Oracle Fusion Middleware Innovation trophy One free pass to Oracle OpenWorld 2014 Priority consideration for placement in Profit magazine, Oracle Magazine, or other Oracle publications & press release Oracle Fusion Middleware Innovation logo for inclusion on your own Website and/or press release Let us reminisce a little… For details on the 2013 Data Integration Winners: Royal Bank of Scotland’s Market and International Banking and The Yalumba Wine Company, check out this blog post: 2013 Oracle Excellence Awards for Fusion Middleware Innovation… and the Winners for Data Integration are… and for details on the 2012 Data Integration Winners: Raymond James and Morrisons, check out this blog post: And the Winners of Fusion Middleware Innovation Awards in Data Integration are…  Now to view the 2013 Winners (for all categories). We hope to honor you! Here's what you need to do:  Click here to submit your nomination today.  And just a reminder: the deadline to submit a nomination is 5pm Pacific Time on June 20, 2014. /* 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;}

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  • Coherence Data Guarantees for Data Reads - Basic Terminology

    - by jpurdy
    When integrating Coherence into applications, each application has its own set of requirements with respect to data integrity guarantees. Developers often describe these requirements using expressions like "avoiding dirty reads" or "making sure that updates are transactional", but we often find that even in a small group of people, there may be a wide range of opinions as to what these terms mean. This may simply be due to a lack of familiarity, but given that Coherence sits at an intersection of several (mostly) unrelated fields, it may be a matter of conflicting vocabularies (e.g. "consistency" is similar but different in transaction processing versus multi-threaded programming). Since almost all data read consistency issues are related to the concept of concurrency, it is helpful to start with a definition of that, or rather what it means for two operations to be concurrent. Rather than implying that they occur "at the same time", concurrency is a slightly weaker statement -- it simply means that it can't be proven that one event precedes (or follows) the other. As an example, in a Coherence application, if two client members mutate two different cache entries sitting on two different cache servers at roughly the same time, it is likely that one update will precede the other by a significant amount of time (say 0.1ms). However, since there is no guarantee that all four members have their clocks perfectly synchronized, and there is no way to precisely measure the time it takes to send a given message between any two members (that have differing clocks), we consider these to be concurrent operations since we can not (easily) prove otherwise. So this leads to a question that we hear quite frequently: "Are the contents of the near cache always synchronized with the underlying distributed cache?". It's easy to see that if an update on a cache server results in a message being sent to each near cache, and then that near cache being updated that there is a window where the contents are different. However, this is irrelevant, since even if the application reads directly from the distributed cache, another thread update the cache before the read is returned to the application. Even if no other member modifies a cache entry prior to the local near cache entry being updated (and subsequently read), the purpose of reading a cache entry is to do something with the result, usually either displaying for consumption by a human, or by updating the entry based on the current state of the entry. In the former case, it's clear that if the data is updated faster than a human can perceive, then there is no problem (and in many cases this can be relaxed even further). For the latter case, the application must assume that the value might potentially be updated before it has a chance to update it. This almost aways the case with read-only caches, and the solution is the traditional optimistic transaction pattern, which requires the application to explicitly state what assumptions it made about the old value of the cache entry. If the application doesn't want to bother stating those assumptions, it is free to lock the cache entry prior to reading it, ensuring that no other threads will mutate the entry, a pessimistic approach. The optimistic approach relies on what is sometimes called a "fuzzy read". In other words, the application assumes that the read should be correct, but it also acknowledges that it might not be. (I use the qualifier "sometimes" because in some writings, "fuzzy read" indicates the situation where the application actually sees an original value and then later sees an updated value within the same transaction -- however, both definitions are roughly equivalent from an application design perspective). If the read is not correct it is called a "stale read". Going back to the definition of concurrency, it may seem difficult to precisely define a stale read, but the practical way of detecting a stale read is that is will cause the encompassing transaction to roll back if it tries to update that value. The pessimistic approach relies on a "coherent read", a guarantee that the value returned is not only the same as the primary copy of that value, but also that it will remain that way. In most cases this can be used interchangeably with "repeatable read" (though that term has additional implications when used in the context of a database system). In none of cases above is it possible for the application to perform a "dirty read". A dirty read occurs when the application reads a piece of data that was never committed. In practice the only way this can occur is with multi-phase updates such as transactions, where a value may be temporarily update but then withdrawn when a transaction is rolled back. If another thread sees that value prior to the rollback, it is a dirty read. If an application uses optimistic transactions, dirty reads will merely result in a lack of forward progress (this is actually one of the main risks of dirty reads -- they can be chained and potentially cause cascading rollbacks). The concepts of dirty reads, fuzzy reads, stale reads and coherent reads are able to describe the vast majority of requirements that we see in the field. However, the important thing is to define the terms used to define requirements. A quick web search for each of the terms in this article will show multiple meanings, so I've selected what are generally the most common variations, but it never hurts to state each definition explicitly if they are critical to the success of a project (many applications have sufficiently loose requirements that precise terminology can be avoided).

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

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

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  • Relational database data explorer / visualization?

    - by Ian Boyd
    Is there a tool that can let one browse relational data as a graph of connected nodes? For example, i'm faced with trying to cleanse some anomolous data. i can start with two offending rows. In this particular example, the TransactionID should, by business rules, be unique to the table, but i find a transaction that violates that rule: SELECT * FROM LCTTrans WHERE TransactionID = 1075048 LCTID TransactionID ========= ============= 4358 1075048 4359 1075048 2 row(s) affected But really what i want to begin to hunt down all the related data, to try to see which is right. So this hypothetical software would start by showing me these two rows: Next, i want to see that transaction that is linked into this table: Now that transaction points to an MAL, so show me that: Now lets add those two LCTs, that the transaction is "on". A transaction can be on only one LCT, yet this one is pointing to two: Okay computer, both of those LCTs point to an MAL and the transaction that created them, show me those: Those last two transactions, they also point at an MAL, and they themselves point to an LCT, show me those: Okay, now are there any entries in LCTTrans that point to LCTs 4358 or 4359?... And so on, and so on. Now i did all this manually, running single selects, copying and pasting uniqueidentifier keys and converting them into friendly id numbers so i could easily see the relationships. Is there software that can do this?

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  • How to properly set relationships in Core Data when using setValue and data already exists

    - by ern
    Let's say I have two objects: Articles and Categories. For the sake of this example all relevant categories have already been added to the data store. When looping through data that holds edits for articles, there is category relationship information that needs to be saved. I was planning on using the -setValue method in the Article class in order to set the relationships like so: - (void)setValue:(id)value forUndefinedKey:(NSString *)key { if([key isEqualToString:@"categories"]){ NSLog(@"trying to set categories..."); } } The problem is that value isn't a Category, it is just a string (or array of strings) holding the title of a category. I could certainly do a lookup within this method for each category and assign it, but that seems inefficient when processing a whole bunch of articles at once. Another option is to populate an array of all possible categories and just filter, but my question is where to store that array? Should it be a class method on Article? Is there a way to pass in additional data to the -setValue method? Is there another, better option for setting the relationship I'm not thinking of? Thanks for your help.

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  • Suggested Web Application Framework and Database for Enterprise, “Big-Data” App?

    - by willOEM
    I have a web application that I have been developing for a small group within my company over the past few years, using Pipeline Pilot (plus jQuery and Python scripting) for web development and back-end computation, and Oracle 10g for my RDBMS. Users upload experimental genomic data, which is parsed into a database, and made available for querying, transformation, and reporting. Experimental data sets are large and have many layers of metadata. A given experimental data record might have a foreign key relationship with a table that describes this data point's assay. Assays can cover multiple genes, which can have multiple transcript, which can have multiple mutations, which can affect multiple signaling pathways, etc. Users need to approach this data from any point in those layers in the metadata. Since all data sets for a given data type can run over a billion rows, this results in some large, dynamic queries that are hard to predict. New data sets are added on a weekly basis (~1GB per set). Experimental data is never updated, but the associated metadata can be updated weekly for a few records and yearly for most others. For every data set insert the system sees, there will be between 10 and 100 selects run against it and associated data. It is okay for updates and inserts to run slow, so long as queries run quick and are as up-to-date as possible. The application continues to grow in size and scope and is already starting to run slower than I like. I am worried that we have about outgrown Pipeline Pilot, and perhaps Oracle (as the sole database). Would a NoSQL database or an OLAP system be appropriate here? What web application frameworks work well with systems like this? I'd like the solution to be something scalable, portable and supportable X-years down the road. Here is the current state of the application: Web Server/Data Processing: Pipeline Pilot on Windows Server + IIS Database: Oracle 10g, ~1TB of data, ~180 tables with several billion-plus row tables Network Storage: Isilon, ~50TB of low-priority raw data

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  • Simple ADF page using BAM Data Control

    - by [email protected]
    var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-15829414-1"); pageTracker._trackPageview(); } catch(err) {} Purpose : In this blog I will walk you through very simple steps to create an ADF page using BAM data control connection.Details : Create the projectOpen JDeveloper (make sure you have installed the SOA extension for JDev)Create new Application using "Generic Application" template.Click on "Next"Shuttle  "ADF Faces" to right pane for the project technology.Click "Finish"Create a BAM connectionIn the resource palette click on "Folder->New Connection -> BAM"Enter the connection name and click "Next"Enter Connection details Click on "Test connection" and "Finish"Create the BAM Data Control Open the IDE connection created in above step.Drag and drop "Employees" to "Data controls" palette.Select "Flat Query" and Click "Finish".Create the View Create a new JSF page.From Data control Panel drag and drop "Employees->Query->ADF Read Only table"Right click and Run the page.

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  • Data Aggregation of CSV files java

    - by royB
    I have k csv files (5 csv files for example), each file has m fields which produce a key and n values. I need to produce a single csv file with aggregated data. I'm looking for the most efficient solution for this problem, speed mainly. I don't think by the way that we will have memory issues. Also I would like to know if hashing is really a good solution because we will have to use 64 bit hashing solution to reduce the chance for a collision to less than 1% (we are having around 30000000 rows per aggregation). For example file 1: f1,f2,f3,v1,v2,v3,v4 a1,b1,c1,50,60,70,80 a3,b2,c4,60,60,80,90 file 2: f1,f2,f3,v1,v2,v3,v4 a1,b1,c1,30,50,90,40 a3,b2,c4,30,70,50,90 result: f1,f2,f3,v1,v2,v3,v4 a1,b1,c1,80,110,160,120 a3,b2,c4,90,130,130,180 algorithm that we thought until now: hashing (using concurentHashTable) merge sorting the files DB: using mysql or hadoop or redis. The solution needs to be able to handle Huge amount of data (each file more than two million rows) a better example: file 1 country,city,peopleNum england,london,1000000 england,coventry,500000 file 2: country,city,peopleNum england,london,500000 england,coventry,500000 england,manchester,500000 merged file: country,city,peopleNum england,london,1500000 england,coventry,1000000 england,manchester,500000 The key is: country,city. This is just an example, my real key is of size 6 and the data columns are of size 8 - total of 14 columns. We would like that the solution will be the fastest in regard of data processing.

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  • SQL – Download FREE Book – Data Access for HighlyScalable Solutions: Using SQL, NoSQL, and Polyglot Persistence

    - by Pinal Dave
    Recently I was preparing for Big Data and I ended up on very interesting read for everybody. This is created by Microsoft and it is indeed a fantastic read as per my opinion. It took me some time to read this entire book but it was worth reading this as it tried to answer two of the very interesting questions related to muscle. Here is the abstract from the book: Organizations seeking to use a NoSQL database are therefore faced with a twofold challenge: • Which NoSQL database(s) best meet(s) the needs of the organization? • How does an organization integrate a NoSQL database into its solutions? As I keep on reading the book, I find it very interesting and informative. I suggest if you have time this weekend, download the book and read it. This guide focuses on the most common types of NoSQL database currently available, describes the situations for which they are most suited, and shows examples of how you might incorporate them into a business application. The guide summarizes the experiences of a fictitious organization named Adventure Works, who implemented a solution that comprised an assortment of different databases. Download Data Access for HighlyScalable Solutions:  Using SQL, NoSQL,  and Polyglot Persistence While we are talking about Big Data and NoSQL do not forget to check out my tomorrow’s blog as I am going to talk about the same subject and it will be very interesting. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, NoSQL, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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