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  • TechEd 2012 - day 3

    - by Stefan Barrett
    The content has got more useful for me as a developer, and I've now seen 2 things which I think will make a big difference: Fake in vs2012 - allows me to stub or fake out libraries making unit testing easier/possible. C++ AMP & auto - auto might get me to start using c++ again (it makes code like for each much nicer/easier to write), while AMP is something I want to play with (moves the processing onto the GPU) The food got a little better, while there was less sign of the snacks.

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  • Webcast: The ART of Migrating and Modernizing IBM Mainframe Applications

    - by todd.little
    Tuxedo provides an excellent platform to migrate mainframe applications to distributed systems. As the only distributed transaction processing monitor that offers quality of service comparable or better than mainframe systems, Tuxedo allows customers to migrate their existing mainframe based applications to a platform with a much lower total cost of ownership. Please join us on Thursday April 29 at 10:00am Pacific Time for this exciting webcast covering the new Oracle Tuxedo Application Runtime for CICS and Batch 11g. Find out how easy it is to migrate your CICS and mainframe batch applications to Tuxedo.

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  • New Release IPM 11g

    - by [email protected]
    This year a new release of Oracle Imaging & Process Management has been released: IPM 11g. IPM is basically a Content Server specialized in images processing. IPM works with UCM and ODC, so the files are stored in the UCM repository and the images are checked in via ODC or OFR. One of the most remarkable changes in this release is the use of WebLogic as Application Server, instead of OC4J.

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  • Community Profile: Steve Blackwell on Fusion Middleware in Avocent's Trellis DCIM Project

    - by OTN ArchBeat
    Steve Blackwell is VP of engineering at Avocent. I had a chance to sit down with Steve during Oracle OpenWorld 2013 to ask him about Avocent's Trellis project, a three-year Data Center Infrastructure Management (DCIM) undertaking built on Oracle Fusion Middleware, including Oracle WebLogic Suite, Oracle Coherence, Oracle Complex Event Processing, and Oracle Service Bus. Steve shares a lot of background and technical detail on the project in this video, so check it out.

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  • Oracle Exadata Resource Kit available

    - by javier.puerta(at)oracle.com
    To learn more about how easy it is to achieve extreme database application performance, we now invite you to access the Oracle Exadata Resource Kit, featuring: The Oracle Exadata Launch Webcast with Mark Hurd, President, Oracle IDC's report on how Oracle Exadata exceeds expectations A technical overview of Oracle Exadata Database Machine Customer case studies, videos, podcasts, and more Don't miss this chance to learn how Oracle Exadata provides extreme performance by combining data warehousing and online transaction processing applications in a single machine. Access the Oracle Exadata Resource Kit today.

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  • Optimizing AES modes on Solaris for Intel Westmere

    - by danx
    Optimizing AES modes on Solaris for Intel Westmere Review AES is a strong method of symmetric (secret-key) encryption. It is a U.S. FIPS-approved cryptographic algorithm (FIPS 197) that operates on 16-byte blocks. AES has been available since 2001 and is widely used. However, AES by itself has a weakness. AES encryption isn't usually used by itself because identical blocks of plaintext are always encrypted into identical blocks of ciphertext. This encryption can be easily attacked with "dictionaries" of common blocks of text and allows one to more-easily discern the content of the unknown cryptotext. This mode of encryption is called "Electronic Code Book" (ECB), because one in theory can keep a "code book" of all known cryptotext and plaintext results to cipher and decipher AES. In practice, a complete "code book" is not practical, even in electronic form, but large dictionaries of common plaintext blocks is still possible. Here's a diagram of encrypting input data using AES ECB mode: Block 1 Block 2 PlainTextInput PlainTextInput | | | | \/ \/ AESKey-->(AES Encryption) AESKey-->(AES Encryption) | | | | \/ \/ CipherTextOutput CipherTextOutput Block 1 Block 2 What's the solution to the same cleartext input producing the same ciphertext output? The solution is to further process the encrypted or decrypted text in such a way that the same text produces different output. This usually involves an Initialization Vector (IV) and XORing the decrypted or encrypted text. As an example, I'll illustrate CBC mode encryption: Block 1 Block 2 PlainTextInput PlainTextInput | | | | \/ \/ IV >----->(XOR) +------------->(XOR) +---> . . . . | | | | | | | | \/ | \/ | AESKey-->(AES Encryption) | AESKey-->(AES Encryption) | | | | | | | | | \/ | \/ | CipherTextOutput ------+ CipherTextOutput -------+ Block 1 Block 2 The steps for CBC encryption are: Start with a 16-byte Initialization Vector (IV), choosen randomly. XOR the IV with the first block of input plaintext Encrypt the result with AES using a user-provided key. The result is the first 16-bytes of output cryptotext. Use the cryptotext (instead of the IV) of the previous block to XOR with the next input block of plaintext Another mode besides CBC is Counter Mode (CTR). As with CBC mode, it also starts with a 16-byte IV. However, for subsequent blocks, the IV is just incremented by one. Also, the IV ix XORed with the AES encryption result (not the plain text input). Here's an illustration: Block 1 Block 2 PlainTextInput PlainTextInput | | | | \/ \/ AESKey-->(AES Encryption) AESKey-->(AES Encryption) | | | | \/ \/ IV >----->(XOR) IV + 1 >---->(XOR) IV + 2 ---> . . . . | | | | \/ \/ CipherTextOutput CipherTextOutput Block 1 Block 2 Optimization Which of these modes can be parallelized? ECB encryption/decryption can be parallelized because it does more than plain AES encryption and decryption, as mentioned above. CBC encryption can't be parallelized because it depends on the output of the previous block. However, CBC decryption can be parallelized because all the encrypted blocks are known at the beginning. CTR encryption and decryption can be parallelized because the input to each block is known--it's just the IV incremented by one for each subsequent block. So, in summary, for ECB, CBC, and CTR modes, encryption and decryption can be parallelized with the exception of CBC encryption. How do we parallelize encryption? By interleaving. Usually when reading and writing data there are pipeline "stalls" (idle processor cycles) that result from waiting for memory to be loaded or stored to or from CPU registers. Since the software is written to encrypt/decrypt the next data block where pipeline stalls usually occurs, we can avoid stalls and crypt with fewer cycles. This software processes 4 blocks at a time, which ensures virtually no waiting ("stalling") for reading or writing data in memory. Other Optimizations Besides interleaving, other optimizations performed are Loading the entire key schedule into the 128-bit %xmm registers. This is done once for per 4-block of data (since 4 blocks of data is processed, when present). The following is loaded: the entire "key schedule" (user input key preprocessed for encryption and decryption). This takes 11, 13, or 15 registers, for AES-128, AES-192, and AES-256, respectively The input data is loaded into another %xmm register The same register contains the output result after encrypting/decrypting Using SSSE 4 instructions (AESNI). Besides the aesenc, aesenclast, aesdec, aesdeclast, aeskeygenassist, and aesimc AESNI instructions, Intel has several other instructions that operate on the 128-bit %xmm registers. Some common instructions for encryption are: pxor exclusive or (very useful), movdqu load/store a %xmm register from/to memory, pshufb shuffle bytes for byte swapping, pclmulqdq carry-less multiply for GCM mode Combining AES encryption/decryption with CBC or CTR modes processing. Instead of loading input data twice (once for AES encryption/decryption, and again for modes (CTR or CBC, for example) processing, the input data is loaded once as both AES and modes operations occur at in the same function Performance Everyone likes pretty color charts, so here they are. I ran these on Solaris 11 running on a Piketon Platform system with a 4-core Intel Clarkdale processor @3.20GHz. Clarkdale which is part of the Westmere processor architecture family. The "before" case is Solaris 11, unmodified. Keep in mind that the "before" case already has been optimized with hand-coded Intel AESNI assembly. The "after" case has combined AES-NI and mode instructions, interleaved 4 blocks at-a-time. « For the first table, lower is better (milliseconds). The first table shows the performance improvement using the Solaris encrypt(1) and decrypt(1) CLI commands. I encrypted and decrypted a 1/2 GByte file on /tmp (swap tmpfs). Encryption improved by about 40% and decryption improved by about 80%. AES-128 is slighty faster than AES-256, as expected. The second table shows more detail timings for CBC, CTR, and ECB modes for the 3 AES key sizes and different data lengths. » The results shown are the percentage improvement as shown by an internal PKCS#11 microbenchmark. And keep in mind the previous baseline code already had optimized AESNI assembly! The keysize (AES-128, 192, or 256) makes little difference in relative percentage improvement (although, of course, AES-128 is faster than AES-256). Larger data sizes show better improvement than 128-byte data. Availability This software is in Solaris 11 FCS. It is available in the 64-bit libcrypto library and the "aes" Solaris kernel module. You must be running hardware that supports AESNI (for example, Intel Westmere and Sandy Bridge, microprocessor architectures). The easiest way to determine if AES-NI is available is with the isainfo(1) command. For example, $ isainfo -v 64-bit amd64 applications pclmulqdq aes sse4.2 sse4.1 ssse3 popcnt tscp ahf cx16 sse3 sse2 sse fxsr mmx cmov amd_sysc cx8 tsc fpu 32-bit i386 applications pclmulqdq aes sse4.2 sse4.1 ssse3 popcnt tscp ahf cx16 sse3 sse2 sse fxsr mmx cmov sep cx8 tsc fpu No special configuration or setup is needed to take advantage of this software. Solaris libraries and kernel automatically determine if it's running on AESNI-capable machines and execute the correctly-tuned software for the current microprocessor. Summary Maximum throughput of AES cipher modes can be achieved by combining AES encryption with modes processing, interleaving encryption of 4 blocks at a time, and using Intel's wide 128-bit %xmm registers and instructions. References "Block cipher modes of operation", Wikipedia Good overview of AES modes (ECB, CBC, CTR, etc.) "Advanced Encryption Standard", Wikipedia "Current Modes" describes NIST-approved block cipher modes (ECB,CBC, CFB, OFB, CCM, GCM)

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  • Improved Performance on PeopleSoft Combined Benchmark using SPARC T4-4

    - by Brian
    Oracle's SPARC T4-4 server running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved a world record 18,000 concurrent users experiencing subsecond response time while executing a PeopleSoft Payroll batch job of 500,000 employees in 32.4 minutes. This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier. The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment. The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 47% (online and batch) leaving significant headroom for additional processing across the three tiers. The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices. Performance Landscape Results are presented for the PeopleSoft HRMS Self-Service and Payroll combined benchmark. The new result with 128 streams shows significant improvement in the payroll batch processing time with little impact on the self-service component response time. PeopleSoft HRMS Self-Service and Payroll Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.988 0.539 32.4 128 SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.944 0.503 43.3 64 The following results are for the PeopleSoft HRMS Self-Service benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the payroll component. PeopleSoft HRMS Self-Service 9.1 Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) 2x SPARC T4-2 (db) 18,000 1.048 0.742 N/A N/A The following results are for the PeopleSoft Payroll benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the self-service component. PeopleSoft Payroll (N.A.) 9.1 - 500K Employees (7 Million SQL PayCalc, Unicode) Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-4 (db) N/A N/A N/A 30.84 96 Configuration Summary Application Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 512 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 PeopleSoft HCM 9.1 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Java Platform, Standard Edition Development Kit 6 Update 32 Database Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 256 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 PeopleTools 8.52 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Micro Focus Server Express (COBOL v 5.1.00) Web Tier Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 Oracle WebLogic Server 10.3.4 Java Platform, Standard Edition Development Kit 6 Update 32 Storage Configuration: 1 x Sun Server X2-4 as a COMSTAR head for data 4 x Intel Xeon X7550, 2.0 GHz 128 GB memory 1 x Sun Storage F5100 Flash Array (80 flash modules) 1 x Sun Storage F5100 Flash Array (40 flash modules) 1 x Sun Fire X4275 as a COMSTAR head for redo logs 12 x 2 TB SAS disks with Niwot Raid controller Benchmark Description This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2. The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published. PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions. All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions. The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes. The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state. Key Points and Best Practices Two PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning. Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads. A total of 128 PeopleSoft streams server processes where used on the database node to complete payroll batch job of 500,000 employees in 32.4 minutes. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN PeopleSoft Enterprise Human Capital Managementoracle.com OTN PeopleSoft Enterprise Human Capital Management (Payroll) oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 8 November 2012.

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  • Is RTD Stateless or Stateful?

    - by [email protected]
    Yes.   A stateless service is one where each request is an independent transaction that can be processed by any of the servers in a cluster.  A stateful service is one where state is kept in a server's memory from transaction to transaction, thus necessitating the proper routing of requests to the right server. The main advantage of stateless systems is simplicity of design. The main advantage of stateful systems is performance. I'm often asked whether RTD is a stateless or stateful service, so I wanted to clarify this issue in depth so that RTD's architecture will be properly understood. The short answer is: "RTD can be configured as a stateless or stateful service." The performance difference between stateless and stateful systems can be very significant, and while in a call center implementation it may be reasonable to use a pure stateless configuration, a web implementation that produces thousands of requests per second is practically impossible with a stateless configuration. RTD's performance is orders of magnitude better than most competing systems. RTD was architected from the ground up to achieve this performance. Features like automatic and dynamic compression of prediction models, automatic translation of metadata to machine code, lack of interpreted languages, and separation of model building from decisioning contribute to achieving this performance level. Because  of this focus on performance we decided to have RTD's default configuration work in a stateful manner. By being stateful RTD requests are typically handled in a few milliseconds when repeated requests come to the same session. Now, those readers that have participated in implementations of RTD know that RTD's architecture is also focused on reducing Total Cost of Ownership (TCO) with features like automatic model building, automatic time windows, automatic maintenance of database tables, automatic evaluation of data mining models, automatic management of models partitioned by channel, geography, etcetera, and hot swapping of configurations. How do you reconcile the need for a low TCO and the need for performance? How do you get the performance of a stateful system with the simplicity of a stateless system? The answer is that you make the system behave like a stateless system to the exterior, but you let it automatically take advantage of situations where being stateful is better. For example, one of the advantages of stateless systems is that you can route a message to any server in a cluster, without worrying about sending it to the same server that was handling the session in previous messages. With an RTD stateful configuration you can still route the message to any server in the cluster, so from the point of view of the configuration of other systems, it is the same as a stateless service. The difference though comes in performance, because if the message arrives to the right server, RTD can serve it without any external access to the session's state, thus tremendously reducing processing time. In typical implementations it is not rare to have high percentages of messages routed directly to the right server, while those that are not, are easily handled by forwarding the messages to the right server. This architecture usually provides the best of both worlds with performance and simplicity of configuration.   Configuring RTD as a pure stateless service A pure stateless configuration requires session data to be persisted at the end of handling each and every message and reloading that data at the beginning of handling any new message. This is of course, the root of the inefficiency of these configurations. This is also the reason why many "stateless" implementations actually do keep state to take advantage of a request coming back to the same server. Nevertheless, if the implementation requires a pure stateless decision service, this is easy to configure in RTD. The way to do it is: Mark every Integration Point to Close the session at the end of processing the message In the Session entity persist the session data on closing the session In the session entity check if a persisted version exists and load it An excellent solution for persisting the session data is Oracle Coherence, which provides a high performance, distributed cache that minimizes the performance impact of persisting and reloading the session. Alternatively, the session can be persisted to a local database. An interesting feature of the RTD stateless configuration is that it can cope with serializing concurrent requests for the same session. For example, if a web page produces two requests to the decision service, these requests could come concurrently to the decision services and be handled by different servers. Most stateless implementation would have the two requests step onto each other when saving the state, or fail one of the messages. When properly configured, RTD will make one message wait for the other before processing.   A Word on Context Using the context of a customer interaction typically significantly increases lift. For example, offer success in a call center could double if the context of the call is taken into account. For this reason, it is important to utilize the contextual information in decision making. To make the contextual information available throughout a session it needs to be persisted. When there is a well defined owner for the information then there is no problem because in case of a session restart, the information can be easily retrieved. If there is no official owner of the information, then RTD can be configured to persist this information.   Once again, RTD provides flexibility to ensure high performance when it is adequate to allow for some loss of state in the rare cases of server failure. For example, in a heavy use web site that serves 1000 pages per second the navigation history may be stored in the in memory session. In such sites it is typical that there is no OLTP that stores all the navigation events, therefore if an RTD server were to fail, it would be possible for the navigation to that point to be lost (note that a new session would be immediately established in one of the other servers). In most cases the loss of this navigation information would be acceptable as it would happen rarely. If it is desired to save this information, RTD would persist it every time the visitor navigates to a new page. Note that this practice is preferred whether RTD is configured in a stateless or stateful manner.  

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  • Service Broker, not ETL

    - by jamiet
    I have been very quiet on this blog of late and one reason for that is I have been very busy on a client project that I would like to talk about a little here. The client that I have been working for has a website that runs on a distributed architecture utilising a messaging infrastructure for communication between different endpoints. My brief was to build a system that could consume these messages and produce analytical information in near-real-time. More specifically I basically had to deliver a data warehouse however it was the real-time aspect of the project that really intrigued me. This real-time requirement meant that using an Extract transformation, Load (ETL) tool was out of the question and so I had no choice but to write T-SQL code (i.e. stored-procedures) to process the incoming messages and load the data into the data warehouse. This concerned me though – I had no way to control the rate at which data would arrive into the system yet we were going to have end-users querying the system at the same time that those messages were arriving; the potential for contention in such a scenario was pretty high and and was something I wanted to minimise as much as possible. Moreover I did not want the processing of data inside the data warehouse to have any impact on the customer-facing website. As you have probably guessed from the title of this blog post this is where Service Broker stepped in! For those that have not heard of it Service Broker is a queuing technology that has been built into SQL Server since SQL Server 2005. It provides a number of features however the one that was of interest to me was the fact that it facilitates asynchronous data processing which, in layman’s terms, means the ability to process some data without requiring the system that supplied the data having to wait for the response. That was a crucial feature because on this project the customer-facing website (in effect an OLTP system) would be calling one of our stored procedures with each message – we did not want to cause the OLTP system to wait on us every time we processed one of those messages. This asynchronous nature also helps to alleviate the contention problem because the asynchronous processing activity is handled just like any other task in the database engine and hence can wait on another task (such as an end-user query). Service Broker it was then! The stored procedure called by the OLTP system would simply put the message onto a queue and we would use a feature called activation to pick each message off the queue in turn and process it into the warehouse. At the time of writing the system is not yet up to full capacity but so far everything seems to be working OK (touch wood) and crucially our users are seeing data in near-real-time. By near-real-time I am talking about latencies of a few minutes at most and to someone like me who is used to building systems that have overnight latencies that is a huge step forward! So then, am I advocating that you all go out and dump your ETL tools? Of course not, no! What this project has taught me though is that in certain scenarios there may be better ways to implement a data warehouse system then the traditional “load data in overnight” approach that we are all used to. Moreover I have really enjoyed getting to grips with a new technology and even if you don’t want to use Service Broker you might want to consider asynchronous messaging architectures for your BI/data warehousing solutions in the future. This has been a very high level overview of my use of Service Broker and I have deliberately left out much of the minutiae of what has been a very challenging implementation. Nonetheless I hope I have caused you to reflect upon your own approaches to BI and question whether other approaches may be more tenable. All comments and questions gratefully received! Lastly, if you have never used Service Broker before and want to kick the tyres I have provided below a very simple “Service Broker Hello World” script that will create all of the objects required to facilitate Service Broker communications and then send the message “Hello World” from one place to anther! This doesn’t represent a “proper” implementation per se because it doesn’t close down down conversation objects (which you should always do in a real-world scenario) but its enough to demonstrate the capabilities! @Jamiet ----------------------------------------------------------------------------------------------- /*This is a basic Service Broker Hello World app. Have fun! -Jamie */ USE MASTER GO CREATE DATABASE SBTest GO --Turn Service Broker on! ALTER DATABASE SBTest SET ENABLE_BROKER GO USE SBTest GO -- 1) we need to create a message type. Note that our message type is -- very simple and allowed any type of content CREATE MESSAGE TYPE HelloMessage VALIDATION = NONE GO -- 2) Once the message type has been created, we need to create a contract -- that specifies who can send what types of messages CREATE CONTRACT HelloContract (HelloMessage SENT BY INITIATOR) GO --We can query the metadata of the objects we just created SELECT * FROM   sys.service_message_types WHERE name = 'HelloMessage'; SELECT * FROM   sys.service_contracts WHERE name = 'HelloContract'; SELECT * FROM   sys.service_contract_message_usages WHERE  service_contract_id IN (SELECT service_contract_id FROM sys.service_contracts WHERE name = 'HelloContract') AND        message_type_id IN (SELECT message_type_id FROM sys.service_message_types WHERE name = 'HelloMessage'); -- 3) The communication is between two endpoints. Thus, we need two queues to -- hold messages CREATE QUEUE SenderQueue CREATE QUEUE ReceiverQueue GO --more querying metatda SELECT * FROM sys.service_queues WHERE name IN ('SenderQueue','ReceiverQueue'); --we can also select from the queues as if they were tables SELECT * FROM SenderQueue   SELECT * FROM ReceiverQueue   -- 4) Create the required services and bind them to be above created queues CREATE SERVICE Sender   ON QUEUE SenderQueue CREATE SERVICE Receiver   ON QUEUE ReceiverQueue (HelloContract) GO --more querying metadata SELECT * FROM sys.services WHERE name IN ('Receiver','Sender'); -- 5) At this point, we can begin the conversation between the two services by -- sending messages DECLARE @conversationHandle UNIQUEIDENTIFIER DECLARE @message NVARCHAR(100) BEGIN   BEGIN TRANSACTION;   BEGIN DIALOG @conversationHandle         FROM SERVICE Sender         TO SERVICE 'Receiver'         ON CONTRACT HelloContract WITH ENCRYPTION=OFF   -- Send a message on the conversation   SET @message = N'Hello, World';   SEND  ON CONVERSATION @conversationHandle         MESSAGE TYPE HelloMessage (@message)   COMMIT TRANSACTION END GO --check contents of queues SELECT * FROM SenderQueue   SELECT * FROM ReceiverQueue   GO -- Receive a message from the queue RECEIVE CONVERT(NVARCHAR(MAX), message_body) AS MESSAGE FROM ReceiverQueue GO --If no messages were received and/or you can't see anything on the queues you may wish to check the following for clues: SELECT * FROM sys.transmission_queue -- Cleanup DROP SERVICE Sender DROP SERVICE Receiver DROP QUEUE SenderQueue DROP QUEUE ReceiverQueue DROP CONTRACT HelloContract DROP MESSAGE TYPE HelloMessage GO USE MASTER GO DROP DATABASE SBTest GO

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  • XNA extending an existing Content type

    - by Maarten
    We are doing a game in XNA that reacts to music. We need to do some offline processing of the music data and therefore we need a custom type containing the Song and some additional data: // Project AudioGameLibrary namespace AudioGameLibrary { public class GameTrack { public Song Song; public string Extra; } } We've added a Content Pipeline extension: // Project GameTrackProcessor namespace GameTrackProcessor { [ContentSerializerRuntimeType("AudioGameLibrary.GameTrack, AudioGameLibrary")] public class GameTrackContent { public SongContent SongContent; public string Extra; } [ContentProcessor(DisplayName = "GameTrack Processor")] public class GameTrackProcessor : ContentProcessor<AudioContent, GameTrackContent> { public GameTrackProcessor(){} public override GameTrackContent Process(AudioContent input, ContentProcessorContext context) { return new GameTrackContent() { SongContent = new SongProcessor().Process(input, context), Extra = "Some extra data" // Here we can do our processing on 'input' }; } } } Both the Library and the Pipeline extension are added to the Game Solution and references are also added. When trying to use this extension to load "gametrack.mp3" we run into problems however: // Project AudioGame protected override void LoadContent() { AudioGameLibrary.GameTrack gameTrack = Content.Load<AudioGameLibrary.GameTrack>("gametrack"); MediaPlayer.Play(gameTrack.Song); } The error message: Error loading "gametrack". File contains Microsoft.Xna.Framework.Media.Song but trying to load as AudioGameLibrary.GameTrack. AudioGame contains references to both AudioGameLibrary and GameTrackProcessor. Are we maybe missing other references? EDIT Selecting the correct content processor helped, it loads the audio file correctly. However, when I try to process some data, e.g: public override GameTrackContent Process(AudioContent input, ContentProcessorContext context) { int count = input.Data.Count; // With this commented out it works fine return new GameTrackContent() { SongContent = new SongProcessor().Process(input, context) }; } It crashes with the following error: Managed Debugging Assistant 'PInvokeStackImbalance' has detected a problem in 'C:\Users\Maarten\Documents\Visual Studio 2010\Projects\AudioGame\DebugPipeline\bin\Debug\DebugPipeline.exe'. Additional Information: A call to PInvoke function 'Microsoft.Xna.Framework.Content.Pipeline!Microsoft.Xna.Framework.Content.Pipeline.UnsafeNativeMethods+AudioHelper::OpenAudioFile' has unbalanced the stack. This is likely because the managed PInvoke signature does not match the unmanaged target signature. Check that the calling convention and parameters of the PInvoke signature match the target unmanaged signature. Information from logger right before crash: Using "BuildContent" task from assembly "Microsoft.Xna.Framework.Content.Pipel ine, Version=4.0.0.0, Culture=neutral, PublicKeyToken=842cf8be1de50553". Task "BuildContent" Building gametrack.mp3 -> bin\x86\Debug\Content\gametrack.xnb Rebuilding because asset is new Importing gametrack.mp3 with Microsoft.Xna.Framework.Content.Pipeline.Mp3Imp orter Im experiencing exactly this: http://forums.create.msdn.com/forums/t/75996.aspx

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  • Core Parking in Ubuntu?

    - by Xxx Xxx
    Core parking is a new feature that introduced in Windows 7 to get better Battery performance . Depending on the resource use of the operating system it may park one or multiple cores of a multi-core cpu to reduce the computer’s power consumption and thermal emissions. Once operations require more processing power, the parked cores are activated again to assist in the tasks So my question is that is there any way i can do it on Ubuntu 12.04 " Core Parking " ?

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  • Oracle ETPM v2.3.1 Examachine Performance Benchmark Data Sheet

    - by Paula Speranza-Hadley
    Oracle Tax is pleased to announce the exceptional results of the Oracle ETPM v2.3.1 Examachine performance benchmark.   The benchmark achieved the following results:  · Processed8M outpayments and 2M payments in  6 hours · Processed 1M forms in 4 hours · Near  linear scalability of batch processing For the complete data sheet, please click on the following link:  https://blogs.oracle.com/tax/resource/OracleETPMv231ExamachinePerformanceBenchmarkDataSheet.pdf

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  • Notepad++ : Guide pratique, une série de tutoriels de Nicolas Liautaud pour découvrir l'éditeur de texte

    Notepad++ est un éditeur de texte très léger, très puissant et libre (licence GPL). Il est parfait pour programmer avec des langages ne nécessitant pas d'environnement de développement (HTML, CSS, JavaScript, PHP%u2026) ou en ayant un peu pratique (Python, processing%u2026), ou pour du traitement de données. Il prend en charge par défaut une cinquantaine de langages différents, et vous laisse libre d'en ajouter d'autres.

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  • apt-get broken + dependencies issue + many software uninstalled

    - by vnc786
    OS=ubuntu 12.04 64bit 3.2.0-29-generic what i did? apt-get purge libre* which i thought will remove LO 3.5 but, which was a big mistake after couple of moments, i realise that its is removing all other software so i did cltl-c which stopped the apt process i restarted my system after that i found that following software were missing apt-get,evince(pdf), cheese etc..here is full list http://pastebin.com/CWHrw10y i managed to install APT deb file through dpkg but now i am not able to do any installation so i just removed /var/lib/dpkg/status and created new but that didnt help apt-get -f install Reading package lists... Done Building dependency tree Reading state information... Done Correcting dependencies... Done The following extra packages will be installed: apt-utils coreutils debconf debconf-i18n dpkg libacl1 libapt-inst1.4 libapt-pkg4.12 libattr1 libbz2-1.0 libdb5.1 libgcc1 liblocale-gettext-perl liblzma5 libselinux1 libstdc++6 libtext-charwidth-perl libtext-iconv-perl libtext-wrapi18n-perl perl-base tar tzdata xz-utils zlib1g Suggested packages: debconf-doc debconf-utils whiptail dialog gnome-utils libterm-readline-gnu-perl libgtk2-perl libnet-ldap-perl libqtgui4-perl libqtcore4-perl apt bzip2 ncompress xz-lzma The following NEW packages will be installed: apt-utils coreutils debconf debconf-i18n dpkg libacl1 libapt-inst1.4 libapt-pkg4.12 libattr1 libbz2-1.0 libdb5.1 libgcc1 liblocale-gettext-perl liblzma5 libselinux1 libstdc++6 libtext-charwidth-perl libtext-iconv-perl libtext-wrapi18n-perl perl-base tar tzdata xz-utils zlib1g 0 upgraded, 24 newly installed, 0 to remove and 0 not upgraded. 2 not fully installed or removed. Need to get 0 B/9,246 kB of archives. After this operation, 29.9 MB of additional disk space will be used. Do you want to continue [Y/n]? y E: Cannot get debconf version. Is debconf installed? debconf: apt-extracttemplates failed: No such file or directory dpkg: regarding .../libgcc1_1%3a4.6.3-1ubuntu5_amd64.deb containing libgcc1, pre-dependency problem: libgcc1 pre-depends on multiarch-support multiarch-support is unpacked, but has never been configured. dpkg: error processing /var/cache/apt/archives/libgcc1_1%3a4.6.3-1ubuntu5_amd64.deb (--unpack): pre-dependency problem - not installing libgcc1 No apport report written because MaxReports is reached already Errors were encountered while processing: /var/cache/apt/archives/libgcc1_1%3a4.6.3-1ubuntu5_amd64.deb E: Internal Error, No file name for libc6 W: Could not perform immediate configuration on 'multiarch-support:amd64'. Please see man 5 apt.conf under APT::Immediate-Configure for details. (2) E: Sub-process /usr/bin/dpkg returned an error code (1) # apt-get -u dist-upgrade Reading package lists... Done Building dependency tree Reading state information... Done You might want to run 'apt-get -f install' to correct these. The following packages have unmet dependencies: libc6 : Depends: libgcc1 but it is not installed Depends: tzdata but it is not installed E: Unmet dependencies. Try using -f. i have tried below link Unable to install due to debconf problem How do I resolve unmet dependencies? but no help... thanks

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  • What are some reputable merchant account providers for high risk payment web sites?

    - by GregH
    I am helping to set up an online cigar web site. However, it has become a real pain to take payments online since tobacco is considered a "high-risk" item and nobody will provide a merchant account to process the payments. It looks like there are companies that specialize in high-risk merchant accounts. I was wondering if anybody could recommend a high-risk merchant account and payment processing provider?

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  • WebCenter Customer Spotlight: College of American Pathologists

    - by me
    Author: Peter Reiser - Social Business Evangelist, Oracle WebCenter  Solution Summary College of American Pathologists Goes Live with OracleWebCenter - Imaging, AP Invoice Automation, and EBS Managed Attachment with Support for Imaging ContentThe College of American Pathologists (CAP), the leading organization of board-certified pathologists serving more then 18,000 physician members, 7,000 laboratories are accredited by the CAP, and approximately 22,000 laboratories are enrolled in the College’s proficiency testing programs. The business objective was to content-enable their Oracle E-Business Suite (EBS) enterprise application by combining the best of Imaging and Manage Attachment functionality providing a unique opportunity for the business to have unprecedented access to both structure and unstructured content from within their enterprise application. The solution improves customer services turnaround time, provides better compliance and improves maintenance and management of the technology infrastructure. Company OverviewThe College of American Pathologists (CAP), celebrating 50 years as the gold standard in laboratory accreditation, is a medical society serving more than 17,000 physician members and the global laboratory community. It is the world’s largest association composed exclusively of board certified pathologists and is the worldwide leader in laboratory quality assurance. The College advocates accountable, high-quality, and cost-effective patient care. The more than 17,000 pathologist members of the College of American Pathologists represent board-certified pathologists and pathologists in training worldwide. More than 7,000 laboratories are accredited by the CAP, and approximately 23,000 laboratories are enrolled in the College’s proficiency testing programs.  Business ChallengesThe CAP business objective was to content-enable their Oracle E-Business Suite (EBS) enterprise application by combining the best of Imaging and Manage Attachment functionality providing a unique opportunity for the business to have unprecedented access to both structure and unstructured content from within their enterprise application.  Bring more flexibility to systems and programs in order to adapt quickly Get a 360 degree view of the customer Reduce cost of running the business Solution DeployedWith the help of Oracle Consulting, the customer implemented Oracle WebCenter Content as the centralized E-Business Suite Document Repository.  The solution enables to capture, present and manage all unstructured content (PDFs,word processing documents, scanned images, etc.) related to Oracle E-Business Suite transactions and exposing the related content using the familiar EBS User Interface. Business ResultsThe CAP achieved following benefits from the implemented solution: Managed Attachment Solution Align with strategic Oracle Fusion Middleware platform Integrate with the CAP existing data capture capabilities Single user interface provided by the Managed Attachment solution for all content Better compliance and improved collaboration  Account Payables Invoice Processing Imaging Solution Automated invoice management eliminating dependency on paper materials and improving compliance, collaboration and accuracy A single repository to house and secure scanned invoices and all supplemental documents Greater management visibility of invoice entry process Additional Information CAP OpenWorld Presentation Oracle WebCenter Content Oracle Webcenter Capture Oracle WebCenter Imaging Oracle  Consulting

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  • How do I prevent tampering with AJAX process page? [closed]

    - by whamsicore
    I am using Ajax for processing with JQUERY. The Data_string is sent to my process.php page, where it is saved. Issue: right now anyone can directly type example.com/process.php to access my process page, or type example.com/process.php/var1=foo1&var2=foo2 to emulate a form submission. How do I prevent this from happening? Also, in the Ajax code I specified POST. What is the difference here between POST and GET?

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  • SQL SERVER – BI Quiz Hint – Performance Tuning Cubes – Hints

    - by pinaldave
    I earlier wrote about SQL BI Quiz over here and here. The details of the quiz is here: Working with huge data is very common when it is about Data Warehousing. It is necessary to create Cubes on the data to make it meaningful and consumable. There are cases when retrieving the data from cube takes lots of the time. Let us assume that your cube is returning you data very quickly. Suddenly on one day it is returning the data very slowly. What are the three things will you to diagnose this. After diagnose what you will do to resolve performance issue. Participate in my question over here I required BI Expert Jason Thomas to help with few hints to blog readers. He is one of the leading SSAS expert and writes a complicated subject in simple words. If queries were executing properly before but now take a long time to return the data, it means that there has been a change in the environment in which it is running. Some possible changes are listed below:-  1) Data factors:- Compare the data size then and now. Increase in data can result in different execution times. Poorly written queries as well as poor design will not start showing issues till the data grows. How to find it out? (Ans : SQL Server profiler and Perfmon Counters can be used for identifying the issues and performance  tuning the MDX queries)  2) Internal Factors:- Is some slow MDX query / multiple mdx queries running at the same time, which was not running when you had tested it before? Is there any locking happening due to proactive caching or processing operations? Are the measure group caches being cleared by processing operations? (Ans : Again, profiler and perfmon counters will help in finding it out. Load testing can be done using AS Performance Workbench (http://asperfwb.codeplex.com/) by running multiple queries at once)  3) External factors:- Is some other application competing for the same resources?  HINT : Read “Identifying and Resolving MDX Query Performance Bottlenecks in SQL Server 2005 Analysis Services” (http://sqlcat.com/whitepapers/archive/2007/12/16/identifying-and-resolving-mdx-query-performance-bottlenecks-in-sql-server-2005-analysis-services.aspx) Well, these are great tips. Now win big prizes by participate in my question over here. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Is sticking to one language a good practice?

    - by Ans
    I'm developing a pipeline for processing text that will go into production. The question I keep asking myself is: should I stick to one language when looking for a tool to do a particular task (e.g. NLTK, PDFMiner, CLD, CRFsuite, etc.)? Or is it OK to mix and match looking for the best tool regardless of what language it's written in (e.g. OpenNLP, ParsCit, poppler, CFR++, etc.) and warp my code around them?

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  • Improve Performance of char.IsWhiteSpace for ASCII inputs in .NET 3.5

    - by Tanzim Saqib
    IsNullOrWhiteSpace is a new method introduced in string class in .NET 4.0. While this is a very useful method in string based processing, I attempted to implement it in .NET 3.5 using char.IsWhiteSpace() . I have found significant performance penalty using this method which I replaced later on, with my version. The following code takes about 20.6074219 seconds in my machine whereas my implementation of char.IsWhiteSpace takes about 1/4 less time 15.8271485 seconds only. In many scenarios ex. string...(read more)

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  • SSAS: Utility to check you have the correct data types and sizes in your cube definition

    - by DrJohn
    This blog describes a tool I developed which allows you to compare the data types and data sizes found in the cube’s data source view with the data types/sizes of the corresponding dimensional attribute.  Why is this important?  Well when creating named queries in a cube’s data source view, it is often necessary to use the SQL CAST or CONVERT operation to change the data type to something more appropriate for SSAS.  This is particularly important when your cube is based on an Oracle data source or using custom SQL queries rather than views in the relational database.   The problem with BIDS is that if you change the underlying SQL query, then the size of the data type in the dimension does not update automatically.  This then causes problems during deployment whereby processing the dimension fails because the data in the relational database is wider than that allowed by the dimensional attribute. In particular, if you use some string manipulation functions provided by SQL Server or Oracle in your queries, you may find that the 10 character string you expect suddenly turns into an 8,000 character monster.  For example, the SQL Server function REPLACE returns column with a width of 8,000 characters.  So if you use this function in the named query in your DSV, you will get a column width of 8,000 characters.  Although the Oracle REPLACE function is far more intelligent, the generated column size could still be way bigger than the maximum length of the data actually in the field. Now this may not be a problem when prototyping, but in your production cubes you really should clean up this kind of thing as these massive strings will add to processing times and storage space. Similarly, you do not want to forget to change the size of the dimension attribute if your database columns increase in size. Introducing CheckCubeDataTypes Utiltity The CheckCubeDataTypes application extracts all the data types and data sizes for all attributes in the cube and compares them to the data types and data sizes in the cube’s data source view.  It then generates an Excel CSV file which contains all this metadata along with a flag indicating if there is a mismatch between the DSV and the dimensional attribute.  Note that the app not only checks all the attribute keys but also the name and value columns for each attribute. Another benefit of having the metadata held in a CSV text file format is that you can place the file under source code control.  This allows you to compare the metadata of the previous cube release with your new release to highlight problems introduced by new development. You can download the C# source code from here: CheckCubeDataTypes.zip A typical example of the output Excel CSV file is shown below - note that the last column shows a data size mismatch by TRUE appearing in the column

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  • Windows Azure Recipe: Big Data

    - by Clint Edmonson
    As the name implies, what we’re talking about here is the explosion of electronic data that comes from huge volumes of transactions, devices, and sensors being captured by businesses today. This data often comes in unstructured formats and/or too fast for us to effectively process in real time. Collectively, we call these the 4 big data V’s: Volume, Velocity, Variety, and Variability. These qualities make this type of data best managed by NoSQL systems like Hadoop, rather than by conventional Relational Database Management System (RDBMS). We know that there are patterns hidden inside this data that might provide competitive insight into market trends.  The key is knowing when and how to leverage these “No SQL” tools combined with traditional business such as SQL-based relational databases and warehouses and other business intelligence tools. Drivers Petabyte scale data collection and storage Business intelligence and insight Solution The sketch below shows one of many big data solutions using Hadoop’s unique highly scalable storage and parallel processing capabilities combined with Microsoft Office’s Business Intelligence Components to access the data in the cluster. Ingredients Hadoop – this big data industry heavyweight provides both large scale data storage infrastructure and a highly parallelized map-reduce processing engine to crunch through the data efficiently. Here are the key pieces of the environment: Pig - a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. Mahout - a machine learning library with algorithms for clustering, classification and batch based collaborative filtering that are implemented on top of Apache Hadoop using the map/reduce paradigm. Hive - data warehouse software built on top of Apache Hadoop that facilitates querying and managing large datasets residing in distributed storage. Directly accessible to Microsoft Office and other consumers via add-ins and the Hive ODBC data driver. Pegasus - a Peta-scale graph mining system that runs in parallel, distributed manner on top of Hadoop and that provides algorithms for important graph mining tasks such as Degree, PageRank, Random Walk with Restart (RWR), Radius, and Connected Components. Sqoop - a tool designed for efficiently transferring bulk data between Apache Hadoop and structured data stores such as relational databases. Flume - a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large log data amounts to HDFS. Database – directly accessible to Hadoop via the Sqoop based Microsoft SQL Server Connector for Apache Hadoop, data can be efficiently transferred to traditional relational data stores for replication, reporting, or other needs. Reporting – provides easily consumable reporting when combined with a database being fed from the Hadoop environment. Training These links point to online Windows Azure training labs where you can learn more about the individual ingredients described above. Hadoop Learning Resources (20+ tutorials and labs) Huge collection of resources for learning about all aspects of Apache Hadoop-based development on Windows Azure and the Hadoop and Windows Azure Ecosystems SQL Azure (7 labs) Microsoft SQL Azure delivers on the Microsoft Data Platform vision of extending the SQL Server capabilities to the cloud as web-based services, enabling you to store structured, semi-structured, and unstructured data. See my Windows Azure Resource Guide for more guidance on how to get started, including links web portals, training kits, samples, and blogs related to Windows Azure.

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  • Ten Problems with XQuery and the SQL/XML Standard

    XQuery and SQL/XML standard are processors for XML. SQL/XML was designed to try to match the capabilities of XQuery as closely as possible and XQuery was designed not only to support XML, but also to support relational processing. Read on to learn why this may have a negative influence on their capabilities.

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  • Using Oracle BPM to Extend Oracle Applications

    - by Michelle Kimihira
    Author: Srikant Subramaniam, Senior Principal Product Manager, Oracle Fusion Middleware Customers often modify applications to meet their specific business needs - varying regulatory requirements, unique business processes, product mix transition, etc. Traditional implementation practices for such modifications are typically invasive in nature and introduce risk into projects, affect time-to-market and ease of use, and ultimately increase the costs of running and maintaining the applications. Another downside of these traditional implementation practices is that they literally cast the application in stone, making it difficult for end-users to tailor their individual work environments to meet specific needs, without getting IT involved. For many businesses, however, IT lacks the capacity to support such rapid business changes. As a result, adopting innovative solutions to change the economics of customization becomes an imperative rather than a choice. Let's look at a banking process in Siebel Financial Services and Oracle Policy Automation (OPA) using Oracle Business Process Management. This approach makes modifications simple, quick to implement and easy to maintain/upgrade. The process model is based on the Loan Origination Process Accelerator, i.e., a set of ready to deploy business solutions developed by Oracle using Business Process Management (BPM) 11g, containing customizable and extensible pre-built processes to fit specific customer requirements. This use case is a branch-based loan origination process. Origination includes a number of steps ranging from accepting a loan application, applicant identity and background verification (Know Your Customer), credit assessment, risk evaluation and the eventual disbursal of funds (or rejection of the application). We use BPM to model all of these individual tasks and integrate (via web services) with: Siebel Financial Services and (simulated) backend applications: FLEXCUBE for loan management, Background Verification and Credit Rating. The process flow starts in Siebel when a customer applies for loan, switches to OPA for eligibility verification and product recommendations, before handing it off to BPM for approvals. OPA Connector for Siebel simplifies integration with Siebel’s web services framework by saving directly into Siebel the results from the self-service interview. This combination of user input and product recommendation invokes the BPM process for loan origination. At the end of the approval process, we update Siebel and the financial app to complete the loop. We use BPM Process Spaces to display role-specific data via dashboards, including the ability to track the status of a given process (flow trace). Loan Underwriters have visibility into the product mix (loan categories), status of loan applications (count of approved/rejected/pending), volume and values of loans approved per processing center, processing times, requested vs. approved amount and other relevant business metrics. Summary Oracle recommends the use of Fusion Middleware as an extensions platform for applications. This approach makes modifications simple, quick to implement and easy to maintain/upgrade applications (by moving customizations away from applications to the process layer). It is also easier to manage processes that span multiple applications by using Oracle BPM. Additional Information Product Information on Oracle.com: Oracle Fusion Middleware Follow us on Twitter and Facebook Subscribe to our regular Fusion Middleware Newsletter

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