Search Results

Search found 74621 results on 2985 pages for 'oracle platform migration data migration'.

Page 248/2985 | < Previous Page | 244 245 246 247 248 249 250 251 252 253 254 255  | Next Page >

  • Performing multiple fetches in Core Data within the same view

    - by yesimarobot
    I have my CD store setup and everything is working. Once my initial fetch is performed, I need to perform several fetches based on calculations using the data from my first fetch. The examples provided from Apple are great, and helped me get everything going but I'm struggling with executing successive fetches. Any suggestions, or tutorial links are appreciated. Table View loads data from CD store. When a user taps a row it pushes a detail view The detail view loads details from CD. [THE ABOVE STEPS ARE ALL WORKING] I perform several calculations on the data fetched in the detail view. I need to then perform several other fetches based on the results of my calculations.

    Read the article

  • How to reduce the number of points in (x,y) data

    - by Gowtham
    I have a set of data points: (x1, y1) (x2, y2) (x3, y3) ... (xn, yn) The number of sample points can be thousands. I want to represent the same curve as accurately as possible with minimal (lets suppose 30) set of points. I want to capture as many inflection points as possible. However, I have a hard limit on the number of allowed points to represent the data. What is the best algorithm to achieve the same? Is there any free software library that can help? PS: I have tried to implement relative slope difference based point elimination, but this does not always result in the best possible data representation. Thanks for your time. -Gowtham

    Read the article

  • Data frame linear fit in R

    - by user1247384
    This is perhaps a simple question, but I am n00b.Say I have a data frame with a bunch of columns. I need to call lm function over the column 1 and 2, 1 and 3, and so on. So basically I need to loop over all columns and store the results of the fit as I build the model. The problem I am running into is that lm(df[1]~df[2], data = df) doesnt work. In this case df is the data frame object and df[1] is the first column. What is a good way to do this in a loop, as in access the columns of df in an iterative fashion. Thanks.

    Read the article

  • Designing a table to store EXIF data

    - by rafale
    I'm looking to get the best performance out of querying a table containing EXIF data. The queries in question will only search the EXIF data for the specified strings and return the row index on a match. With that said, would it better to store the EXIF data in a table with separate columns for each of the tags, or would storing all of the tags in a single column as one long delimited string suit me just as well? There are around 115 EXIF tags I'll be storing, and each record would be around 1500 to 2000 chars in length if concatenated into a single string.

    Read the article

  • tsql sum data and include default values for missing data

    - by markpirvine
    Hi, I would like a query that will shouw a sum of columns with a default value for missing data. For example assume I have a table as follows: type_lookup: id name 1 self 2 manager 3 peer And a table as follows data: id type_lookup_id value 1 1 1 2 1 4 3 2 9 4 2 1 5 2 9 6 1 5 7 2 6 8 1 2 9 1 1 After running a query I would like a result set as follows: type_lookup_id value 1 13 2 25 3 0 I would like all rows in type_lookup table to be included in the result set - even if they don't appear in the data table. Any help would be greatly appreciated, Mark

    Read the article

  • jquery ajax form function(data)

    - by RussP
    Can some one please tell me where I have gone wrong. What ever I do I get the answer "no" JQuery to send data to php query $j.post("logincheck.php",{ username:$j('#username').attr('value'), password:$j('#password').attr('value'), rand:Math.random() } , function(data) { if(data=='yes') {alert('yes');} else {alert('no');} } ); Here is the php query if(isset($_POST['username'])): $username = $_POST['username']; $password = $_POST['password']; $posts = mysql_query("SELECT * FROM users WHERE username='$username'"); $no_rows = mysql_num_rows($posts ); while($row = mysql_fetch_array($posts)): print 'yes'; endwhile; else: print 'no'; //header('location: index.php'); endif; endif; Thank in adance

    Read the article

  • What frameworks exist for data subscription and update?

    - by Timothy Pratley
    There is one server with multiple clients. The clients are viewing subsets of the servers entire data. If the data that a client is viewing changes, the client should be informed of the changes so that it displays the current data. Example: Two clients are viewing a list of users in an administration screen. One client adds a new user to the list and modifies the permissions of another user. The other client sees the changes propagated to their view. In the client side code I would like the users list to be updated by the framework itself, raising changed events such that it will be redrawn - similar to 'cells' or dataflow. I am looking specifically for a .NET or java implementation.

    Read the article

  • JavaScript: how to use data but to hide it so as it cannot be reused

    - by loukote
    Hi all. I've some data that i'd like to publish just on one website, ie. it should not be reused on other websites. The data is a set of numbers that change every day, our journalists work to get hard gather it. Is there any way to hide, crypt, etc. the data in a way that it cannot be reused by others? But to show it in a graph in the same time? I found the ASCII to HEX tool that could be used for (http://utenti.multimania.it/ascii2hex/). I wonder if you can suggest other ways. (Even if I have to completely change the strategy.) Many thanks!

    Read the article

  • Storing data with a stand-alone C++ application

    - by Mike
    I work with Apache, PHP, and MySQL for web development and local applications. For the past couple of years I have slowly been learning C++ and want to build an application this summer. Specifically, I want to make a "library" application in which I can store information about the books, CDs, and records that I own. I know this type of app exists, but I want to learn C++ and this seems like a good way to go about it. Here are a few questions: Is it possible to create a stand-alone application that does not require a database for storing data? If the answer to #1 above is "yes", is it a good idea to do this for an application that could potentially need to manage a lot of data? What data-storage options would you recommend for use with a C++ application? Thanks!

    Read the article

  • Selecting data from mysql table and related data from another to join them

    - by knittledan
    Ive looked at other questions and answers but still dont understand which brings me here. I have one data base two tables. lets say table1 and table2 from database. I'm looking to grab all the information from table1 and only one column from table2 that coincides with the correct row in table1. Example which I know is wrong: SELECT table1.*, table2.time_stamp FROM table1, table2 WHERE table1.ticket_id=$var AND table1.user_id = table2.user_id Basically select data from table1 then use a value from the selected table to grab the related data from table2 and join them to output them as one mysql_query. Im sure its simple and has been asked before. edit: I dont receive an error. SQL just returns noting. log form of this would be: $sqlResults = mysql_query("SELECT table1.* FROM table1 WHERE table1.ticket_id=$var") while($rowResult = mysql_fetch_array( $sqlResults )) { $userID = $rowResult['user_id']; $sqlResults2 = mysql_query("SELECT table2.time_stamp FROM table2 WHERE table2.user_id=$userID") } I want to combine that into one sql statement so i dont have to hit table2 for every row table1 has

    Read the article

  • Best data recovery tools?

    - by Nonick
    So due to a recent act of stupidity and bravado, I uttered the words "backups! who needs backups?!" and what followed was the tragic loss of 260gb of data. This scenario in particular is requiring me to recover a repartitioned hard disk, but I was wondering what tools people here use in general to recover lost data. I'm sure everyone has been there, either accidentally rewriting files, resaving an old version, computer crash, hard disk death, user deletes an important document etc. So was thinking it might be an interesting point of discussion as to what you guys use to recover lost data. I appologise if this is considered irrelevant, but considering there has been a few recovery questions, I think this might be interesting.

    Read the article

  • Ordered Data Structure that allows to efficiently remove duplicate items

    - by devoured elysium
    I need a data structure that Must be ordered (adding elements a, b and c to an empty structure, will make them be at positions 0, 1 and 2). Allows to add repeated items. This is, I can have a list with a, b, c, a, b. Allows removing all ocurrences of a given item (if I do something like delete(1), it will delete all ocurrences of 1 in the structure). I can't really pick what the best data structure could be in here. I thought at first about something like a List(the problem is having an O(n) operation when removing items), but maybe I'm missing something? What about trees/heaps? Hashtables/maps? I'll have to assume I'll do as much adding as removing with this data structure. Thanks

    Read the article

  • Importing data from many excel workbooks and sheets into a single workbook/table

    - by Max Rusalen
    Hi, I have 54 excel files with three sheets each, each sheet has a different amount of data entries but they are set out in a identical format, and I need to import the data from those sheets into a single workbook using VBA. Is there any way I can program it so I can build the loops to import the data, but without having to write in each workbook name for each loop/sheet? I think I can use the call function, but I don't know how to make the loop codes independent of the workbook name they apply to. Thank you so much in advance, Millie

    Read the article

  • Data access layer design

    - by Sam
    I have a web app and a console application accessing a db. The db has 2 tables (A, B) one of which (A) is specific to the web app. When writing a data access layer, what is the best way to do it? Technically data access layer should provide access to all the data accessible. In doing so, methods to interact with A are exposed to the console application if we have single access layer. Does creating 2 access layers to 2 table in the same database makes any sense? What is a good way to do it?

    Read the article

  • How to insert data in mysql data base table

    - by user1289538
    I am inserting data in MySQL data base but in field it does not insert data. I am using following code $providernpi=$_POST['ProviderNPI']; $patienid=$_POST['PatientID']; $fileurl=$_POST['FileURL']; $filetype=$_POST['FileTYPE']; $datasynid=$_POST['DataSynID']; $appointmentlistingsid=$_POST ['AppointmentListingsID']; $query=("INSERT INTO AppointmentDataSync (ProviderNPI,PatientID, FileURL,FileType,DataSyncID,AppointmentListingsID) VALUES ('$providernpi', '$patientid','$fileurl','$filetype','$datasynid','$appointmentlistingid')"); mysql_query($query,$con); printf("Records inserted: %d\n", mysql_affected_rows()); echo($patienid) ?>

    Read the article

  • From Binary to Data Structures

    - by Cédric Menzi
    Table of Contents Introduction PE file format and COFF header COFF file header BaseCoffReader Byte4ByteCoffReader UnsafeCoffReader ManagedCoffReader Conclusion History This article is also available on CodeProject Introduction Sometimes, you want to parse well-formed binary data and bring it into your objects to do some dirty stuff with it. In the Windows world most data structures are stored in special binary format. Either we call a WinApi function or we want to read from special files like images, spool files, executables or may be the previously announced Outlook Personal Folders File. Most specifications for these files can be found on the MSDN Libarary: Open Specification In my example, we are going to get the COFF (Common Object File Format) file header from a PE (Portable Executable). The exact specification can be found here: PECOFF PE file format and COFF header Before we start we need to know how this file is formatted. The following figure shows an overview of the Microsoft PE executable format. Source: Microsoft Our goal is to get the PE header. As we can see, the image starts with a MS-DOS 2.0 header with is not important for us. From the documentation we can read "...After the MS DOS stub, at the file offset specified at offset 0x3c, is a 4-byte...". With this information we know our reader has to jump to location 0x3c and read the offset to the signature. The signature is always 4 bytes that ensures that the image is a PE file. The signature is: PE\0\0. To prove this we first seek to the offset 0x3c, read if the file consist the signature. So we need to declare some constants, because we do not want magic numbers.   private const int PeSignatureOffsetLocation = 0x3c; private const int PeSignatureSize = 4; private const string PeSignatureContent = "PE";   Then a method for moving the reader to the correct location to read the offset of signature. With this method we always move the underlining Stream of the BinaryReader to the start location of the PE signature.   private void SeekToPeSignature(BinaryReader br) { // seek to the offset for the PE signagure br.BaseStream.Seek(PeSignatureOffsetLocation, SeekOrigin.Begin); // read the offset int offsetToPeSig = br.ReadInt32(); // seek to the start of the PE signature br.BaseStream.Seek(offsetToPeSig, SeekOrigin.Begin); }   Now, we can check if it is a valid PE image by reading of the next 4 byte contains the content PE.   private bool IsValidPeSignature(BinaryReader br) { // read 4 bytes to get the PE signature byte[] peSigBytes = br.ReadBytes(PeSignatureSize); // convert it to a string and trim \0 at the end of the content string peContent = Encoding.Default.GetString(peSigBytes).TrimEnd('\0'); // check if PE is in the content return peContent.Equals(PeSignatureContent); }   With this basic functionality we have a good base reader class to try the different methods of parsing the COFF file header. COFF file header The COFF header has the following structure: Offset Size Field 0 2 Machine 2 2 NumberOfSections 4 4 TimeDateStamp 8 4 PointerToSymbolTable 12 4 NumberOfSymbols 16 2 SizeOfOptionalHeader 18 2 Characteristics If we translate this table to code, we get something like this:   [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Unicode)] public struct CoffHeader { public MachineType Machine; public ushort NumberOfSections; public uint TimeDateStamp; public uint PointerToSymbolTable; public uint NumberOfSymbols; public ushort SizeOfOptionalHeader; public Characteristic Characteristics; } BaseCoffReader All readers do the same thing, so we go to the patterns library in our head and see that Strategy pattern or Template method pattern is sticked out in the bookshelf. I have decided to take the template method pattern in this case, because the Parse() should handle the IO for all implementations and the concrete parsing should done in its derived classes.   public CoffHeader Parse() { using (var br = new BinaryReader(File.Open(_fileName, FileMode.Open, FileAccess.Read, FileShare.Read))) { SeekToPeSignature(br); if (!IsValidPeSignature(br)) { throw new BadImageFormatException(); } return ParseInternal(br); } } protected abstract CoffHeader ParseInternal(BinaryReader br);   First we open the BinaryReader, seek to the PE signature then we check if it contains a valid PE signature and rest is done by the derived implementations. Byte4ByteCoffReader The first solution is using the BinaryReader. It is the general way to get the data. We only need to know which order, which data-type and its size. If we read byte for byte we could comment out the first line in the CoffHeader structure, because we have control about the order of the member assignment.   protected override CoffHeader ParseInternal(BinaryReader br) { CoffHeader coff = new CoffHeader(); coff.Machine = (MachineType)br.ReadInt16(); coff.NumberOfSections = (ushort)br.ReadInt16(); coff.TimeDateStamp = br.ReadUInt32(); coff.PointerToSymbolTable = br.ReadUInt32(); coff.NumberOfSymbols = br.ReadUInt32(); coff.SizeOfOptionalHeader = (ushort)br.ReadInt16(); coff.Characteristics = (Characteristic)br.ReadInt16(); return coff; }   If the structure is as short as the COFF header here and the specification will never changed, there is probably no reason to change the strategy. But if a data-type will be changed, a new member will be added or ordering of member will be changed the maintenance costs of this method are very high. UnsafeCoffReader Another way to bring the data into this structure is using a "magically" unsafe trick. As above, we know the layout and order of the data structure. Now, we need the StructLayout attribute, because we have to ensure that the .NET Runtime allocates the structure in the same order as it is specified in the source code. We also need to enable "Allow unsafe code (/unsafe)" in the project's build properties. Then we need to add the following constructor to the CoffHeader structure.   [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Unicode)] public struct CoffHeader { public CoffHeader(byte[] data) { unsafe { fixed (byte* packet = &data[0]) { this = *(CoffHeader*)packet; } } } }   The "magic" trick is in the statement: this = *(CoffHeader*)packet;. What happens here? We have a fixed size of data somewhere in the memory and because a struct in C# is a value-type, the assignment operator = copies the whole data of the structure and not only the reference. To fill the structure with data, we need to pass the data as bytes into the CoffHeader structure. This can be achieved by reading the exact size of the structure from the PE file.   protected override CoffHeader ParseInternal(BinaryReader br) { return new CoffHeader(br.ReadBytes(Marshal.SizeOf(typeof(CoffHeader)))); }   This solution is the fastest way to parse the data and bring it into the structure, but it is unsafe and it could introduce some security and stability risks. ManagedCoffReader In this solution we are using the same approach of the structure assignment as above. But we need to replace the unsafe part in the constructor with the following managed part:   [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Unicode)] public struct CoffHeader { public CoffHeader(byte[] data) { IntPtr coffPtr = IntPtr.Zero; try { int size = Marshal.SizeOf(typeof(CoffHeader)); coffPtr = Marshal.AllocHGlobal(size); Marshal.Copy(data, 0, coffPtr, size); this = (CoffHeader)Marshal.PtrToStructure(coffPtr, typeof(CoffHeader)); } finally { Marshal.FreeHGlobal(coffPtr); } } }     Conclusion We saw that we can parse well-formed binary data to our data structures using different approaches. The first is probably the clearest way, because we know each member and its size and ordering and we have control about the reading the data for each member. But if add member or the structure is going change by some reason, we need to change the reader. The two other solutions use the approach of the structure assignment. In the unsafe implementation we need to compile the project with the /unsafe option. We increase the performance, but we get some security risks.

    Read the article

  • Basics of Join Predicate Pushdown in Oracle

    - by Maria Colgan
    Happy New Year to all of our readers! We hope you all had a great holiday season. We start the new year by continuing our series on Optimizer transformations. This time it is the turn of Predicate Pushdown. I would like to thank Rafi Ahmed for the content of this blog.Normally, a view cannot be joined with an index-based nested loop (i.e., index access) join, since a view, in contrast with a base table, does not have an index defined on it. A view can only be joined with other tables using three methods: hash, nested loop, and sort-merge joins. Introduction The join predicate pushdown (JPPD) transformation allows a view to be joined with index-based nested-loop join method, which may provide a more optimal alternative. In the join predicate pushdown transformation, the view remains a separate query block, but it contains the join predicate, which is pushed down from its containing query block into the view. The view thus becomes correlated and must be evaluated for each row of the outer query block. These pushed-down join predicates, once inside the view, open up new index access paths on the base tables inside the view; this allows the view to be joined with index-based nested-loop join method, thereby enabling the optimizer to select an efficient execution plan. The join predicate pushdown transformation is not always optimal. The join predicate pushed-down view becomes correlated and it must be evaluated for each outer row; if there is a large number of outer rows, the cost of evaluating the view multiple times may make the nested-loop join suboptimal, and therefore joining the view with hash or sort-merge join method may be more efficient. The decision whether to push down join predicates into a view is determined by evaluating the costs of the outer query with and without the join predicate pushdown transformation under Oracle's cost-based query transformation framework. The join predicate pushdown transformation applies to both non-mergeable views and mergeable views and to pre-defined and inline views as well as to views generated internally by the optimizer during various transformations. The following shows the types of views on which join predicate pushdown is currently supported. UNION ALL/UNION view Outer-joined view Anti-joined view Semi-joined view DISTINCT view GROUP-BY view Examples Consider query A, which has an outer-joined view V. The view cannot be merged, as it contains two tables, and the join between these two tables must be performed before the join between the view and the outer table T4. A: SELECT T4.unique1, V.unique3 FROM T_4K T4,            (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3) VWHERE T4.unique3 = V.hundred(+) AND       T4.ten = V.ten(+) AND       T4.thousand = 5; The following shows the non-default plan for query A generated by disabling join predicate pushdown. When query A undergoes join predicate pushdown, it yields query B. Note that query B is expressed in a non-standard SQL and shows an internal representation of the query. B: SELECT T4.unique1, V.unique3 FROM T_4K T4,           (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3             AND T4.unique3 = V.hundred(+)             AND T4.ten = V.ten(+)) V WHERE T4.thousand = 5; The execution plan for query B is shown below. In the execution plan BX, note the keyword 'VIEW PUSHED PREDICATE' indicates that the view has undergone the join predicate pushdown transformation. The join predicates (shown here in red) have been moved into the view V; these join predicates open up index access paths thereby enabling index-based nested-loop join of the view. With join predicate pushdown, the cost of query A has come down from 62 to 32.  As mentioned earlier, the join predicate pushdown transformation is cost-based, and a join predicate pushed-down plan is selected only when it reduces the overall cost. Consider another example of a query C, which contains a view with the UNION ALL set operator.C: SELECT R.unique1, V.unique3 FROM T_5K R,            (SELECT T1.unique3, T2.unique1+T1.unique1             FROM T_5K T1, T_10K T2             WHERE T1.unique1 = T2.unique1             UNION ALL             SELECT T1.unique3, T2.unique2             FROM G_4K T1, T_10K T2             WHERE T1.unique1 = T2.unique1) V WHERE R.unique3 = V.unique3 and R.thousand < 1; The execution plan of query C is shown below. In the above, 'VIEW UNION ALL PUSHED PREDICATE' indicates that the UNION ALL view has undergone the join predicate pushdown transformation. As can be seen, here the join predicate has been replicated and pushed inside every branch of the UNION ALL view. The join predicates (shown here in red) open up index access paths thereby enabling index-based nested loop join of the view. Consider query D as an example of join predicate pushdown into a distinct view. We have the following cardinalities of the tables involved in query D: Sales (1,016,271), Customers (50,000), and Costs (787,766).  D: SELECT C.cust_last_name, C.cust_city FROM customers C,            (SELECT DISTINCT S.cust_id             FROM sales S, costs CT             WHERE S.prod_id = CT.prod_id and CT.unit_price > 70) V WHERE C.cust_state_province = 'CA' and C.cust_id = V.cust_id; The execution plan of query D is shown below. As shown in XD, when query D undergoes join predicate pushdown transformation, the expensive DISTINCT operator is removed and the join is converted into a semi-join; this is possible, since all the SELECT list items of the view participate in an equi-join with the outer tables. Under similar conditions, when a group-by view undergoes join predicate pushdown transformation, the expensive group-by operator can also be removed. With the join predicate pushdown transformation, the elapsed time of query D came down from 63 seconds to 5 seconds. Since distinct and group-by views are mergeable views, the cost-based transformation framework also compares the cost of merging the view with that of join predicate pushdown in selecting the most optimal execution plan. Summary We have tried to illustrate the basic ideas behind join predicate pushdown on different types of views by showing example queries that are quite simple. Oracle can handle far more complex queries and other types of views not shown here in the examples. Again many thanks to Rafi Ahmed for the content of this blog post.

    Read the article

  • SPARC T4-4 Beats 8-CPU IBM POWER7 on TPC-H @3000GB Benchmark

    - by Brian
    Oracle's SPARC T4-4 server delivered a world record TPC-H @3000GB benchmark result for systems with four processors. This result beats eight processor results from IBM (POWER7) and HP (x86). The SPARC T4-4 server also delivered better performance per core than these eight processor systems from IBM and HP. Comparisons below are based upon system to system comparisons, highlighting Oracle's complete software and hardware solution. This database world record result used Oracle's Sun Storage 2540-M2 arrays (rotating disk) connected to a SPARC T4-4 server running Oracle Solaris 11 and Oracle Database 11g Release 2 demonstrating the power of Oracle's integrated hardware and software solution. The SPARC T4-4 server based configuration achieved a TPC-H scale factor 3000 world record for four processor systems of 205,792 QphH@3000GB with price/performance of $4.10/QphH@3000GB. The SPARC T4-4 server with four SPARC T4 processors (total of 32 cores) is 7% faster than the IBM Power 780 server with eight POWER7 processors (total of 32 cores) on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 36% better in price performance compared to the IBM Power 780 server on the TPC-H @3000GB Benchmark. The SPARC T4-4 server is 29% faster than the IBM Power 780 for data loading. The SPARC T4-4 server is up to 3.4 times faster than the IBM Power 780 server for the Refresh Function. The SPARC T4-4 server with four SPARC T4 processors is 27% faster than the HP ProLiant DL980 G7 server with eight x86 processors on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 52% faster than the HP ProLiant DL980 G7 server for data loading. The SPARC T4-4 server is up to 3.2 times faster than the HP ProLiant DL980 G7 for the Refresh Function. The SPARC T4-4 server achieved a peak IO rate from the Oracle database of 17 GB/sec. This rate was independent of the storage used, as demonstrated by the TPC-H @3000TB benchmark which used twelve Sun Storage 2540-M2 arrays (rotating disk) and the TPC-H @1000TB benchmark which used four Sun Storage F5100 Flash Array devices (flash storage). [*] The SPARC T4-4 server showed linear scaling from TPC-H @1000GB to TPC-H @3000GB. This demonstrates that the SPARC T4-4 server can handle the increasingly larger databases required of DSS systems. [*] The SPARC T4-4 server benchmark results demonstrate a complete solution of building Decision Support Systems including data loading, business questions and refreshing data. Each phase usually has a time constraint and the SPARC T4-4 server shows superior performance during each phase. [*] The TPC believes that comparisons of results published with different scale factors are misleading and discourages such comparisons. Performance Landscape The table lists the leading TPC-H @3000GB results for non-clustered systems. TPC-H @3000GB, Non-Clustered Systems System Processor P/C/T – Memory Composite(QphH) $/perf($/QphH) Power(QppH) Throughput(QthH) Database Available SPARC Enterprise M9000 3.0 GHz SPARC64 VII+ 64/256/256 – 1024 GB 386,478.3 $18.19 316,835.8 471,428.6 Oracle 11g R2 09/22/11 SPARC T4-4 3.0 GHz SPARC T4 4/32/256 – 1024 GB 205,792.0 $4.10 190,325.1 222,515.9 Oracle 11g R2 05/31/12 SPARC Enterprise M9000 2.88 GHz SPARC64 VII 32/128/256 – 512 GB 198,907.5 $15.27 182,350.7 216,967.7 Oracle 11g R2 12/09/10 IBM Power 780 4.1 GHz POWER7 8/32/128 – 1024 GB 192,001.1 $6.37 210,368.4 175,237.4 Sybase 15.4 11/30/11 HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 8/64/128 – 512 GB 162,601.7 $2.68 185,297.7 142,685.6 SQL Server 2008 10/13/10 P/C/T = Processors, Cores, Threads QphH = the Composite Metric (bigger is better) $/QphH = the Price/Performance metric in USD (smaller is better) QppH = the Power Numerical Quantity QthH = the Throughput Numerical Quantity The following table lists data load times and refresh function times during the power run. TPC-H @3000GB, Non-Clustered Systems Database Load & Database Refresh System Processor Data Loading(h:m:s) T4Advan RF1(sec) T4Advan RF2(sec) T4Advan SPARC T4-4 3.0 GHz SPARC T4 04:08:29 1.0x 67.1 1.0x 39.5 1.0x IBM Power 780 4.1 GHz POWER7 05:51:50 1.5x 147.3 2.2x 133.2 3.4x HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 08:35:17 2.1x 173.0 2.6x 126.3 3.2x Data Loading = database load time RF1 = power test first refresh transaction RF2 = power test second refresh transaction T4 Advan = the ratio of time to T4 time Complete benchmark results found at the TPC benchmark website http://www.tpc.org. Configuration Summary and Results Hardware Configuration: SPARC T4-4 server 4 x SPARC T4 3.0 GHz processors (total of 32 cores, 128 threads) 1024 GB memory 8 x internal SAS (8 x 300 GB) disk drives External Storage: 12 x Sun Storage 2540-M2 array storage, each with 12 x 15K RPM 300 GB drives, 2 controllers, 2 GB cache Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Enterprise Edition Audited Results: Database Size: 3000 GB (Scale Factor 3000) TPC-H Composite: 205,792.0 QphH@3000GB Price/performance: $4.10/QphH@3000GB Available: 05/31/2012 Total 3 year Cost: $843,656 TPC-H Power: 190,325.1 TPC-H Throughput: 222,515.9 Database Load Time: 4:08:29 Benchmark Description The TPC-H benchmark is a performance benchmark established by the Transaction Processing Council (TPC) to demonstrate Data Warehousing/Decision Support Systems (DSS). TPC-H measurements are produced for customers to evaluate the performance of various DSS systems. These queries and updates are executed against a standard database under controlled conditions. Performance projections and comparisons between different TPC-H Database sizes (100GB, 300GB, 1000GB, 3000GB, 10000GB, 30000GB and 100000GB) are not allowed by the TPC. TPC-H is a data warehousing-oriented, non-industry-specific benchmark that consists of a large number of complex queries typical of decision support applications. It also includes some insert and delete activity that is intended to simulate loading and purging data from a warehouse. TPC-H measures the combined performance of a particular database manager on a specific computer system. The main performance metric reported by TPC-H is called the TPC-H Composite Query-per-Hour Performance Metric (QphH@SF, where SF is the number of GB of raw data, referred to as the scale factor). QphH@SF is intended to summarize the ability of the system to process queries in both single and multiple user modes. The benchmark requires reporting of price/performance, which is the ratio of the total HW/SW cost plus 3 years maintenance to the QphH. A secondary metric is the storage efficiency, which is the ratio of total configured disk space in GB to the scale factor. Key Points and Best Practices Twelve Sun Storage 2540-M2 arrays were used for the benchmark. Each Sun Storage 2540-M2 array contains 12 15K RPM drives and is connected to a single dual port 8Gb FC HBA using 2 ports. Each Sun Storage 2540-M2 array showed 1.5 GB/sec for sequential read operations and showed linear scaling, achieving 18 GB/sec with twelve Sun Storage 2540-M2 arrays. These were stand alone IO tests. The peak IO rate measured from the Oracle database was 17 GB/sec. Oracle Solaris 11 11/11 required very little system tuning. Some vendors try to make the point that storage ratios are of customer concern. However, storage ratio size has more to do with disk layout and the increasing capacities of disks – so this is not an important metric in which to compare systems. The SPARC T4-4 server and Oracle Solaris efficiently managed the system load of over one thousand Oracle Database parallel processes. Six Sun Storage 2540-M2 arrays were mirrored to another six Sun Storage 2540-M2 arrays on which all of the Oracle database files were placed. IO performance was high and balanced across all the arrays. The TPC-H Refresh Function (RF) simulates periodical refresh portion of Data Warehouse by adding new sales and deleting old sales data. Parallel DML (parallel insert and delete in this case) and database log performance are a key for this function and the SPARC T4-4 server outperformed both the IBM POWER7 server and HP ProLiant DL980 G7 server. (See the RF columns above.) See Also Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage 2540-M2 Array oracle.com OTN Disclosure Statement TPC-H, QphH, $/QphH are trademarks of Transaction Processing Performance Council (TPC). For more information, see www.tpc.org. SPARC T4-4 205,792.0 QphH@3000GB, $4.10/QphH@3000GB, available 5/31/12, 4 processors, 32 cores, 256 threads; IBM Power 780 QphH@3000GB, 192,001.1 QphH@3000GB, $6.37/QphH@3000GB, available 11/30/11, 8 processors, 32 cores, 128 threads; HP ProLiant DL980 G7 162,601.7 QphH@3000GB, $2.68/QphH@3000GB available 10/13/10, 8 processors, 64 cores, 128 threads.

    Read the article

  • 5 Best Practices - Laying the Foundation for WebCenter Projects

    - by Kellsey Ruppel
    Today’s guest post comes from Oracle WebCenter expert John Brunswick. John specializes in enterprise portal and content management solutions and actively contributes to the enterprise software business community and has authored a series of articles about optimal business involvement in portal, business process management and SOA development, examining ways of helping organizations move away from monolithic application development. We’re happy to have John join us today! Maximizing success with Oracle WebCenter portal requires a strategic understanding of Oracle WebCenter capabilities.  The following best practices enable the creation of portal solutions with minimal resource overhead, while offering the greatest flexibility for progressive elaboration. They are inherently project agnostic, enabling a strong foundation for future growth and an expedient return on your investment in the platform.  If you are able to embrace even only a few of these practices, you will materially improve your deployment capability with WebCenter. 1. Segment Duties Around 3Cs - Content, Collaboration and Contextual Data "Agility" is one of the most common business benefits touted by modern web platforms.  It sounds good - who doesn't want to be Agile, right?  How exactly IT organizations go about supplying agility to their business counterparts often lacks definition - hamstrung by ambiguity. Ultimately, businesses want to benefit from reduced development time to deliver a solution to a particular constituent, which is augmented by as much self-service as possible to develop and manage the solution directly. All done in the absence of direct IT involvement. With Oracle WebCenter's depth in the areas of content management, pallet of native collaborative services, enterprise mashup capability and delegated administration, it is very possible to execute on this business vision at a technical level. To realize the benefits of the platform depth we can think of Oracle WebCenter's segmentation of duties along the lines of the 3 Cs - Content, Collaboration and Contextual Data.  All three of which can have their foundations developed by IT, then provisioned to the business on a per role basis. Content – Oracle WebCenter benefits from an extremely mature content repository.  Work flow, audit, notification, office integration and conversion capabilities for documents (HTML & PDF) make this a haven for business users to take control of content within external and internal portals, custom applications and web sites.  When deploying WebCenter portal take time to think of areas in which IT can provide the "harness" for content to reside, then allow the business to manage any content items within the site, using the content foundation to ensure compliance with business rules and process.  This frees IT to work on more mission critical challenges and allows the business to respond in short order to emerging market needs. Collaboration – Native collaborative services and WebCenter spaces are a perfect match for business users who are looking to enable document sharing, discussions and social networking.  The ability to deploy the services is granular and on the basis of roles scoped to given areas of the system - much like the first C “content”.  This enables business analysts to design the roles required and IT to provision with peace of mind that users leveraging the collaborative services are only able to do so in explicitly designated areas of a site. Bottom line - business will not need to wait for IT, but cannot go outside of the scope that has been defined based on their roles. Contextual Data – Collaborative capabilities are most powerful when included within the context of business data.  The ability to supply business users with decision shaping data that they can include in various parts of a portal or portals, just as they would with content items, is one of the most powerful aspects of Oracle WebCenter.  Imagine a discussion about new store selection for a retail chain that re-purposes existing information from business intelligence services about various potential locations and or custom backend systems - presenting it directly in the context of the discussion.  If there are some data sources that are preexisting in your enterprise take a look at how they can be made into discrete offerings within the portal, then scoped to given business user roles for inclusion within collaborative activities. 2. Think Generically, Execute Specifically Constructs.  Anyone who has spent much time around me knows that I am obsessed with this word.  Why? Because Constructs offer immense power - more than APIs, Web Services or other technical capability. Constructs offer organizations the ability to leverage a platform's native characteristics to offer substantial business functionality - without writing code.  This concept becomes more powerful with the additional understanding of the concepts from the platform that an organization learns over time.  Let's take a look at an example of where an Oracle WebCenter construct can substantially reduce the time to get a subscription-based site out the door and into the hands of the end consumer. Imagine a site that allows members to subscribe to specific disciplines to access information and application data around that various discipline.  A space is a collection of secured pages within Oracle WebCenter.  Spaces are not only secured, but also default content stored within it to be scoped automatically to that space. Taking this a step further, Oracle WebCenter’s Activity Stream surfaces events, discussions and other activities that are scoped to the given user on the basis of their space affiliations.  In order to have a portal that would allow users to "subscribe" to information around various disciplines - spaces could be used out of the box to achieve this capability and without using any APIs or low level technical work to achieve this. 3. Make Governance Work for You Imagine driving down the street without the painted lines on the road.  The rules of the road are so ingrained in our minds, we often do not think about the process, but seemingly mundane lane markers are critical enablers. Lane markers allow us to travel at speeds that would be impossible if not for the agreed upon direction of flow. Additionally and more importantly, it allows people to act autonomously - going where they please at any given time. The return on the investment for mobility is high enough for people to buy into globally agreed up governance processes. In Oracle WebCenter we can use similar enablers to lane markers.  Our goal should be to enable the flow of information and provide end users with the ability to arrive at business solutions as needed, not on the basis of cumbersome processes that cannot meet the business needs in a timely fashion. How do we do this? Just as with "Segmentation of Duties" Oracle WebCenter technologies offer the opportunity to compartmentalize various business initiatives from each other within the system due to constructs and security that are available to use within the platform. For instance, when a WebCenter space is created, any content added within that space by default will be secured to that particular space and inherits meta data that is associated with a folder created for the space. Oracle WebCenter content uses meta data to support a broad range of rich ECM functionality and can automatically impart retention, workflow and other policies automatically on the basis of what has been defaulted for that space. Depending on your business needs, this paradigm will also extend to sub sections of a space, offering some interesting possibilities to enable automated management around content. An example may be press releases within a particular area of an extranet that require a five year retention period and need to the reviewed by marketing and legal before release.  The underlying content system will transparently take care of this process on the basis of the above rules, enabling peace of mind over unstructured data - which could otherwise become overwhelming. 4. Make Your First Project Your Second Imagine if Michael Phelps was competing in a swimming championship, but told right before his race that he had to use a brand new stroke.  There is no doubt that Michael is an outstanding swimmer, but chances are that he would like to have some time to get acquainted with the new stroke. New technologies should not be treated any differently.  Before jumping into the deep end it helps to take time to get to know the new approach - even though you may have been swimming thousands of times before. To quickly get a handle on Oracle WebCenter capabilities it can be helpful to deploy a sandbox for the team to use to share project documents, discussions and announcements in an effort to help the actual deployment get under way, while increasing everyone’s knowledge of the platform and its functionality that may be helpful down the road. Oracle Technology Network has made a pre-configured virtual machine available for download that can be a great starting point for this exercise. 5. Get to Know the Community If you are reading this blog post you have most certainly faced a software decision or challenge that was solved on the basis of a small piece of missing critical information - which took substantial research to discover.  Chances were also good that somewhere, someone had already come across this information and would have been excited to share it. There is no denying the power of passionate, connected users, sharing key tips around technology.  The Oracle WebCenter brand has a rich heritage that includes industry-leading technology and practitioners.  With the new Oracle WebCenter brand, opportunities to connect with these experts has become easier. Oracle WebCenter Blog Oracle Social Enterprise LinkedIn WebCenter Group Oracle WebCenter Twitter Oracle WebCenter Facebook Oracle User Groups Additionally, there are various Oracle WebCenter related blogs by an excellent grouping of services partners.

    Read the article

  • General Purpose ASP.NET Data Source Control

    - by Ricardo Peres
    OK, you already know about the ObjectDataSource control, so what’s wrong with it? Well, for once, it doesn’t pass any context to the SelectMethod, you only get the parameters supplied on the SelectParameters plus the desired ordering, starting page and maximum number of rows to display. Also, you must have two separate methods, one for actually retrieving the data, and the other for getting the total number of records (SelectCountMethod). Finally, you don’t get a chance to alter the supplied data before you bind it to the target control. I wanted something simple to use, and more similar to ASP.NET 4.5, where you can have the select method on the page itself, so I came up with CustomDataSource. Here’s how to use it (I chose a GridView, but it works equally well with any regular data-bound control): 1: <web:CustomDataSourceControl runat="server" ID="datasource" PageSize="10" OnData="OnData" /> 2: <asp:GridView runat="server" ID="grid" DataSourceID="datasource" DataKeyNames="Id" PageSize="10" AllowPaging="true" AllowSorting="true" /> The OnData event handler receives a DataEventArgs instance, which contains some properties that describe the desired paging location and size, and it’s where you return the data plus the total record count. Here’s a quick example: 1: protected void OnData(object sender, DataEventArgs e) 2: { 3: //just return some data 4: var data = Enumerable.Range(e.StartRowIndex, e.PageSize).Select(x => new { Id = x, Value = x.ToString(), IsPair = ((x % 2) == 0) }); 5: e.Data = data; 6: //the total number of records 7: e.TotalRowCount = 100; 8: } Here’s the code for the DataEventArgs: 1: [Serializable] 2: public class DataEventArgs : EventArgs 3: { 4: public DataEventArgs(Int32 pageSize, Int32 startRowIndex, String sortExpression, IOrderedDictionary parameters) 5: { 6: this.PageSize = pageSize; 7: this.StartRowIndex = startRowIndex; 8: this.SortExpression = sortExpression; 9: this.Parameters = parameters; 10: } 11:  12: public IEnumerable Data 13: { 14: get; 15: set; 16: } 17:  18: public IOrderedDictionary Parameters 19: { 20: get; 21: private set; 22: } 23:  24: public String SortExpression 25: { 26: get; 27: private set; 28: } 29:  30: public Int32 StartRowIndex 31: { 32: get; 33: private set; 34: } 35:  36: public Int32 PageSize 37: { 38: get; 39: private set; 40: } 41:  42: public Int32 TotalRowCount 43: { 44: get; 45: set; 46: } 47: } As you can guess, the StartRowIndex and PageSize receive the starting row and the desired page size, where the page size comes from the PageSize property on the markup. There’s also a SortExpression, which gets passed the sorted-by column and direction (if descending) and a dictionary containing all the values coming from the SelectParameters collection, if any. All of these are read only, and it is your responsibility to fill in the Data and TotalRowCount. The code for the CustomDataSource is very simple: 1: [NonVisualControl] 2: public class CustomDataSourceControl : DataSourceControl 3: { 4: public CustomDataSourceControl() 5: { 6: this.SelectParameters = new ParameterCollection(); 7: } 8:  9: protected override DataSourceView GetView(String viewName) 10: { 11: return (new CustomDataSourceView(this, viewName)); 12: } 13:  14: internal void GetData(DataEventArgs args) 15: { 16: this.OnData(args); 17: } 18:  19: protected virtual void OnData(DataEventArgs args) 20: { 21: EventHandler<DataEventArgs> data = this.Data; 22:  23: if (data != null) 24: { 25: data(this, args); 26: } 27: } 28:  29: [Browsable(false)] 30: [DesignerSerializationVisibility(DesignerSerializationVisibility.Visible)] 31: [PersistenceMode(PersistenceMode.InnerProperty)] 32: public ParameterCollection SelectParameters 33: { 34: get; 35: private set; 36: } 37:  38: public event EventHandler<DataEventArgs> Data; 39:  40: public Int32 PageSize 41: { 42: get; 43: set; 44: } 45: } Also, the code for the accompanying internal – as there is no need to use it from outside of its declaring assembly - data source view: 1: sealed class CustomDataSourceView : DataSourceView 2: { 3: private readonly CustomDataSourceControl dataSourceControl = null; 4:  5: public CustomDataSourceView(CustomDataSourceControl dataSourceControl, String viewName) : base(dataSourceControl, viewName) 6: { 7: this.dataSourceControl = dataSourceControl; 8: } 9:  10: public override Boolean CanPage 11: { 12: get 13: { 14: return (true); 15: } 16: } 17:  18: public override Boolean CanRetrieveTotalRowCount 19: { 20: get 21: { 22: return (true); 23: } 24: } 25:  26: public override Boolean CanSort 27: { 28: get 29: { 30: return (true); 31: } 32: } 33:  34: protected override IEnumerable ExecuteSelect(DataSourceSelectArguments arguments) 35: { 36: IOrderedDictionary parameters = this.dataSourceControl.SelectParameters.GetValues(HttpContext.Current, this.dataSourceControl); 37: DataEventArgs args = new DataEventArgs(this.dataSourceControl.PageSize, arguments.StartRowIndex, arguments.SortExpression, parameters); 38:  39: this.dataSourceControl.GetData(args); 40:  41: arguments.TotalRowCount = args.TotalRowCount; 42: arguments.MaximumRows = this.dataSourceControl.PageSize; 43: arguments.AddSupportedCapabilities(DataSourceCapabilities.Page | DataSourceCapabilities.Sort | DataSourceCapabilities.RetrieveTotalRowCount); 44: arguments.RetrieveTotalRowCount = true; 45:  46: if (!(args.Data is ICollection)) 47: { 48: return (args.Data.OfType<Object>().ToList()); 49: } 50: else 51: { 52: return (args.Data); 53: } 54: } 55: } As always, looking forward to hearing from you!

    Read the article

  • Coherence Special Interest Group: First Meeting in Toronto and Upcoming Events in New York and Calif

    - by [email protected]
    The first meeting of the Toronto Coherence Special Interest Group (TOCSIG). Date: Friday, April 23, 2010 Time: 8:30am-12:00pm Where: Oracle Mississauga Office, Customer Visitation Center, 110 Matheson Blvd. West, Suite 100, Mississauga, ON L5R3P4 Cameron Purdy, Vice President of Development (Oracle), Patrick Peralta, Senior Software Engineer (Oracle), and Noah Arliss, Software Development Manager (Oracle) will be presenting. Further information about this event can be seen here   The New York Coherence SIG is hosting its seventh meeting. Date: Thursday, Apr 15, 2010 Time: 5:30pm-5:45pm ET social and 5:45pm-8:00pm ET presentations Where: Oracle Office, Room 30076, 520 Madison Avenue, 30th Floor, Patrick Peralta, Dr. Gene Gleyzer, and Craig Blitz from Oracle, will be presenting. Further information about this event can be seen here   The Bay Area Coherence SIG is hosting its fifth meeting. Date: Thursday, Apr 29, 2009 Time: 5:30pm-5:45pm PT social and 5:45pm-8:00pm PT presentations Where: Oracle Conference Center, 350 Oracle Parkway, Room 203, Redwood Shores, CA Tom Lubinski from SL Corp., Randy Stafford from the Oracle A-team, and Taylor Gautier from Grid Dynamics will be presenting Further information about this event can be seen here   Great news, aren't they? 

    Read the article

  • Tutorial: Getting Started with the NoSQL JavaScript / Node.js API for MySQL Cluster

    - by Mat Keep
    Tutorial authored by Craig Russell and JD Duncan  The MySQL Cluster team are working on a new NoSQL JavaScript connector for MySQL. The objectives are simplicity and high performance for JavaScript users: - allows end-to-end JavaScript development, from the browser to the server and now to the world's most popular open source database - native "NoSQL" access to the storage layer without going first through SQL transformations and parsing. Node.js is a complete web platform built around JavaScript designed to deliver millions of client connections on commodity hardware. With the MySQL NoSQL Connector for JavaScript, Node.js users can easily add data access and persistence to their web, cloud, social and mobile applications. While the initial implementation is designed to plug and play with Node.js, the actual implementation doesn't depend heavily on Node, potentially enabling wider platform support in the future. Implementation The architecture and user interface of this connector are very different from other MySQL connectors in a major way: it is an asynchronous interface that follows the event model built into Node.js. To make it as easy as possible, we decided to use a domain object model to store the data. This allows for users to query data from the database and have a fully-instantiated object to work with, instead of having to deal with rows and columns of the database. The domain object model can have any user behavior that is desired, with the NoSQL connector providing the data from the database. To make it as fast as possible, we use a direct connection from the user's address space to the database. This approach means that no SQL (pun intended) is needed to get to the data, and no SQL server is between the user and the data. The connector is being developed to be extensible to multiple underlying database technologies, including direct, native access to both the MySQL Cluster "ndb" and InnoDB storage engines. The connector integrates the MySQL Cluster native API library directly within the Node.js platform itself, enabling developers to seamlessly couple their high performance, distributed applications with a high performance, distributed, persistence layer delivering 99.999% availability. The following sections take you through how to connect to MySQL, query the data and how to get started. Connecting to the database A Session is the main user access path to the database. You can get a Session object directly from the connector using the openSession function: var nosql = require("mysql-js"); var dbProperties = {     "implementation" : "ndb",     "database" : "test" }; nosql.openSession(dbProperties, null, onSession); The openSession function calls back into the application upon creating a Session. The Session is then used to create, delete, update, and read objects. Reading data The Session can read data from the database in a number of ways. If you simply want the data from the database, you provide a table name and the key of the row that you want. For example, consider this schema: create table employee (   id int not null primary key,   name varchar(32),   salary float ) ENGINE=ndbcluster; Since the primary key is a number, you can provide the key as a number to the find function. function onSession = function(err, session) {   if (err) {     console.log(err);     ... error handling   }   session.find('employee', 0, onData); }; function onData = function(err, data) {   if (err) {     console.log(err);     ... error handling   }   console.log('Found: ', JSON.stringify(data));   ... use data in application }; If you want to have the data stored in your own domain model, you tell the connector which table your domain model uses, by specifying an annotation, and pass your domain model to the find function. var annotations = new nosql.Annotations(); function Employee = function(id, name, salary) {   this.id = id;   this.name = name;   this.salary = salary;   this.giveRaise = function(percent) {     this.salary *= percent;   } }; annotations.mapClass(Employee, {'table' : 'employee'}); function onSession = function(err, session) {   if (err) {     console.log(err);     ... error handling   }   session.find(Employee, 0, onData); }; Updating data You can update the emp instance in memory, but to make the raise persistent, you need to write it back to the database, using the update function. function onData = function(err, emp) {   if (err) {     console.log(err);     ... error handling   }   console.log('Found: ', JSON.stringify(emp));   emp.giveRaise(0.12); // gee, thanks!   session.update(emp); // oops, session is out of scope here }; Using JavaScript can be tricky because it does not have the concept of block scope for variables. You can create a closure to handle these variables, or use a feature of the connector to remember your variables. The connector api takes a fixed number of parameters and returns a fixed number of result parameters to the callback function. But the connector will keep track of variables for you and return them to the callback. So in the above example, change the onSession function to remember the session variable, and you can refer to it in the onData function: function onSession = function(err, session) {   if (err) {     console.log(err);     ... error handling   }   session.find(Employee, 0, onData, session); }; function onData = function(err, emp, session) {   if (err) {     console.log(err);     ... error handling   }   console.log('Found: ', JSON.stringify(emp));   emp.giveRaise(0.12); // gee, thanks!   session.update(emp, onUpdate); // session is now in scope }; function onUpdate = function(err, emp) {   if (err) {     console.log(err);     ... error handling   } Inserting data Inserting data requires a mapped JavaScript user function (constructor) and a session. Create a variable and persist it: function onSession = function(err, session) {   var data = new Employee(999, 'Mat Keep', 20000000);   session.persist(data, onInsert);   } }; Deleting data To remove data from the database, use the session remove function. You use an instance of the domain object to identify the row you want to remove. Only the key field is relevant. function onSession = function(err, session) {   var key = new Employee(999);   session.remove(Employee, onDelete);   } }; More extensive queries We are working on the implementation of more extensive queries along the lines of the criteria query api. Stay tuned. How to evaluate The MySQL Connector for JavaScript is available for download from labs.mysql.com. Select the build: MySQL-Cluster-NoSQL-Connector-for-Node-js You can also clone the project on GitHub Since it is still early in development, feedback is especially valuable (so don't hesitate to leave comments on this blog, or head to the MySQL Cluster forum). Try it out and see how easy (and fast) it is to integrate MySQL Cluster into your Node.js platforms. You can learn more about other previewed functionality of MySQL Cluster 7.3 here

    Read the article

  • SPARC Solaris Momentum

    - by Mike Mulkey-Oracle
    Following up on the Oracle Solaris 11.2 launch on April 29th, if you were able to watch the launch event, you saw Mark Hurd state that Oracle will be No. 1 in high-end computing systems "in a reasonable time frame”.  "This is not a 3-year vision," he continued.Well, According to IDC's latest 1QCY14 Tracker, Oracle has regained the #1 UNIX Shipments Marketshare! You can see the report and read about it here: Oracle regains the #1 UNIX Shipments Marketshare, but suffice to say that SPARC Solaris is making strong gains on the competition.  If you have seen the public roadmap through 2019 of Oracle's commitment to continue to deliver on this technology, you can see that Mark Hurd’s comment was not to be taken lightly.  We feel the systems tide turning in Oracle's direction and are working hard to show our partner community the value of being a part of the SPARC Solaris momentum.We are now planning for the Solaris 11.2 GA in late summer (11.2 beta is available now), as well as doing early preparations for Oracle OpenWorld 2014 on September 28th.  Stay tuned there!Here is a sampling of the coverage highlights around the Oracle Solaris 11.2 launch:“Solaris is still one of the most advanced platforms in the enterprise.” – ITBusinessEdge“Oracle is serious about clouds now, just as its customers are, whether they are building them in their own datacenters or planning to use public clouds.” – EnterpriseTech"Solaris is more about a layer of an integrated system than an operating system.” — ZDNet

    Read the article

  • How to convince an employer to move to VB.Net for new development?

    - by Dabblernl
    Some history:For the last six months I have been employed at a small firm with just three programmers, my employer among them. The firm maintains two programs written in VB6. I am asssigned as the lead programmer to one of these. In the last six months I did some maintenance and bug hunting, but created some new functionality too. I had an interview last december, which was favorable, and my contract was prolonged. I am very happy with this course of events as I only obtained a .Net certification a year ago and have no other qualifications (in the field of coding, that is). It is my strong opinion that, while migration of the existing program to .Net is advisable, it is paramount that from now on the new functionality should be written in VB.Net class libraries. After some study I found out how simple it is to integrate .Net class libraries into the VB6 development environment and how easy it is to add their functionality to existing installations by using application manifests. So, I have decided that now is the moment to roll up my sleeves and try and convince my employer that he should let me develop new code in VB.Net, using VB6 for maintenance only. We get along quite well, but I think I am going to need all the ammunition I can get to convince him. Any arguments, preferably backed up up ones, are very welcome, even arguments to dissuade me ;-)

    Read the article

  • JAVA image transfer problem

    - by user579098
    Hi, I have a school assignment, to send a jpg image,split it into groups of 100 bytes, corrupt it, use a CRC check to locate the errors and re-transmit until it eventually is built back into its original form. It's practically ready, however when I check out the new images, they appear with errors.. I would really appreciate if someone could look at my code below and maybe locate this logical mistake as I can't understand what the problem is because everything looks ok :S For the file with all the data needed including photos and error patterns one could download it from this link:http://rapidshare.com/#!download|932tl2|443122762|Data.zip|739 Thanks in advance, Stefan p.s dont forget to change the paths in the code for the image and error files package networks; import java.io.*; // for file reader import java.util.zip.CRC32; // CRC32 IEEE (Ethernet) public class Main { /** * Reads a whole file into an array of bytes. * @param file The file in question. * @return Array of bytes containing file data. * @throws IOException Message contains why it failed. */ public static byte[] readFileArray(File file) throws IOException { InputStream is = new FileInputStream(file); byte[] data=new byte[(int)file.length()]; is.read(data); is.close(); return data; } /** * Writes (or overwrites if exists) a file with data from an array of bytes. * @param file The file in question. * @param data Array of bytes containing the new file data. * @throws IOException Message contains why it failed. */ public static void writeFileArray(File file, byte[] data) throws IOException { OutputStream os = new FileOutputStream(file,false); os.write(data); os.close(); } /** * Converts a long value to an array of bytes. * @param data The target variable. * @return Byte array conversion of data. * @see http://www.daniweb.com/code/snippet216874.html */ public static byte[] toByta(long data) { return new byte[] { (byte)((data >> 56) & 0xff), (byte)((data >> 48) & 0xff), (byte)((data >> 40) & 0xff), (byte)((data >> 32) & 0xff), (byte)((data >> 24) & 0xff), (byte)((data >> 16) & 0xff), (byte)((data >> 8) & 0xff), (byte)((data >> 0) & 0xff), }; } /** * Converts a an array of bytes to long value. * @param data The target variable. * @return Long value conversion of data. * @see http://www.daniweb.com/code/snippet216874.html */ public static long toLong(byte[] data) { if (data == null || data.length != 8) return 0x0; return (long)( // (Below) convert to longs before shift because digits // are lost with ints beyond the 32-bit limit (long)(0xff & data[0]) << 56 | (long)(0xff & data[1]) << 48 | (long)(0xff & data[2]) << 40 | (long)(0xff & data[3]) << 32 | (long)(0xff & data[4]) << 24 | (long)(0xff & data[5]) << 16 | (long)(0xff & data[6]) << 8 | (long)(0xff & data[7]) << 0 ); } public static byte[] nextNoise(){ byte[] result=new byte[100]; // copy a frame's worth of data (or remaining data if it is less than frame length) int read=Math.min(err_data.length-err_pstn, 100); System.arraycopy(err_data, err_pstn, result, 0, read); // if read data is less than frame length, reset position and add remaining data if(read<100){ err_pstn=100-read; System.arraycopy(err_data, 0, result, read, err_pstn); }else // otherwise, increase position err_pstn+=100; // return noise segment return result; } /** * Given some original data, it is purposefully corrupted according to a * second data array (which is read from a file). In pseudocode: * corrupt = original xor corruptor * @param data The original data. * @return The new (corrupted) data. */ public static byte[] corruptData(byte[] data){ // get the next noise sequence byte[] noise = nextNoise(); // finally, xor data with noise and return result for(int i=0; i<100; i++)data[i]^=noise[i]; return data; } /** * Given an array of data, a packet is created. In pseudocode: * frame = corrupt(data) + crc(data) * @param data The original frame data. * @return The resulting frame data. */ public static byte[] buildFrame(byte[] data){ // pack = [data]+crc32([data]) byte[] hash = new byte[8]; // calculate crc32 of data and copy it to byte array CRC32 crc = new CRC32(); crc.update(data); hash=toByta(crc.getValue()); // create a byte array holding the final packet byte[] pack = new byte[data.length+hash.length]; // create the corrupted data byte[] crpt = new byte[data.length]; crpt = corruptData(data); // copy corrupted data into pack System.arraycopy(crpt, 0, pack, 0, crpt.length); // copy hash into pack System.arraycopy(hash, 0, pack, data.length, hash.length); // return pack return pack; } /** * Verifies frame contents. * @param frame The frame data (data+crc32). * @return True if frame is valid, false otherwise. */ public static boolean verifyFrame(byte[] frame){ // allocate hash and data variables byte[] hash=new byte[8]; byte[] data=new byte[frame.length-hash.length]; // read frame into hash and data variables System.arraycopy(frame, frame.length-hash.length, hash, 0, hash.length); System.arraycopy(frame, 0, data, 0, frame.length-hash.length); // get crc32 of data CRC32 crc = new CRC32(); crc.update(data); // compare crc32 of data with crc32 of frame return crc.getValue()==toLong(hash); } /** * Transfers a file through a channel in frames and reconstructs it into a new file. * @param jpg_file File name of target file to transfer. * @param err_file The channel noise file used to simulate corruption. * @param out_file The name of the newly-created file. * @throws IOException */ public static void transferFile(String jpg_file, String err_file, String out_file) throws IOException { // read file data into global variables jpg_data = readFileArray(new File(jpg_file)); err_data = readFileArray(new File(err_file)); err_pstn = 0; // variable that will hold the final (transfered) data byte[] out_data = new byte[jpg_data.length]; // holds the current frame data byte[] frame_orig = new byte[100]; byte[] frame_sent = new byte[100]; // send file in chunks (frames) of 100 bytes for(int i=0; i<Math.ceil(jpg_data.length/100); i++){ // copy jpg data into frame and init first-time switch System.arraycopy(jpg_data, i*100, frame_orig, 0, 100); boolean not_first=false; System.out.print("Packet #"+i+": "); // repeat getting same frame until frame crc matches with frame content do { if(not_first)System.out.print("F"); frame_sent=buildFrame(frame_orig); not_first=true; }while(!verifyFrame(frame_sent)); // usually, you'd constrain this by time to prevent infinite loops (in // case the channel is so wacked up it doesn't get a single packet right) // copy frame to image file System.out.println("S"); System.arraycopy(frame_sent, 0, out_data, i*100, 100); } System.out.println("\nDone."); writeFileArray(new File(out_file),out_data); } // global variables for file data and pointer public static byte[] jpg_data; public static byte[] err_data; public static int err_pstn=0; public static void main(String[] args) throws IOException { // list of jpg files String[] jpg_file={ "C:\\Users\\Stefan\\Desktop\\Data\\Images\\photo1.jpg", "C:\\Users\\Stefan\\Desktop\\Data\\Images\\photo2.jpg", "C:\\Users\\Stefan\\Desktop\\Data\\Images\\photo3.jpg", "C:\\Users\\Stefan\\Desktop\\Data\\Images\\photo4.jpg" }; // list of error patterns String[] err_file={ "C:\\Users\\Stefan\\Desktop\\Data\\Error Pattern\\Error Pattern 1.DAT", "C:\\Users\\Stefan\\Desktop\\Data\\Error Pattern\\Error Pattern 2.DAT", "C:\\Users\\Stefan\\Desktop\\Data\\Error Pattern\\Error Pattern 3.DAT", "C:\\Users\\Stefan\\Desktop\\Data\\Error Pattern\\Error Pattern 4.DAT" }; // loop through all jpg/channel combinations and run tests for(int x=0; x<jpg_file.length; x++){ for(int y=0; y<err_file.length; y++){ System.out.println("Transfering photo"+(x+1)+".jpg using Pattern "+(y+1)+"..."); transferFile(jpg_file[x],err_file[y],jpg_file[x].replace("photo","CH#"+y+"_photo")); } } } }

    Read the article

< Previous Page | 244 245 246 247 248 249 250 251 252 253 254 255  | Next Page >