Search Results

Search found 1848 results on 74 pages for 'significant'.

Page 11/74 | < Previous Page | 7 8 9 10 11 12 13 14 15 16 17 18  | Next Page >

• New Features In Bash Version 4.x - Part 4

  <b>LinuxCommand.org:</b> "In this final installment of our series, we will look at perhaps the most significant area of change in bash version 4.x: arrays."

  Read the article

• Backlinks For Your Website

  One of the most significant factors to a successful website is incoming links or backlinks. The more backlinks you have, the more chances that you will attain an increase page rank value.

  Read the article

• Apache log rotation: logrotate vs rotatelogs vs chronolog

  - by Enrico

  I have been researching log rotation for my server which hosts ~5 fairly high traffic sites. From what I can tell, my options are to use logrotate or to use piped logging with either rotatelogs or chronolog. logrotate requires a restart of apache and both SIGHUP and SIGUSR1 restarts are less than ideal on high traffic sites, because either you drop a bunch of connections or you need to delay compressing the old log until all child processes have died naturally. Also, downtime can be quite significant if compression is enabled. Would using logrotate - without compression and with graceful restart - and compressing old logs after the fact be the best way to minimize downtime? chronolog and rotatelogs sound promising, but are not well documented. I couldn't find examples of using either in combination with vhost specific logs. The chronolog website says, "when the expanded filename changes, the current file is closed and a new one opened". Is this globally? Or is that per AccessLog, CustomLog or ErrorLog directive? Is there a significant difference between chronolog and rotatelogs?

  Read the article

• Possible DNS issue after a reinstall of Windows Server 2000 (get off my lawn)

  - by cop1152

  I just replaced a drive on a Win2000 Server that replicates AD and issues out DHCP at one of our offices. I successfully joined it to the domain, setup range of IP's, etc, but am still having issues. I cannot RDC to it with name or IP. I can ping it, browse to it with Windows Explorer, and remote to it with some other software, but not RDC. The other issue is this: Users are unable to authenticate on it. They receive the message 'username or password incorrect' (or something like that). Changes made on the main domain controller seem to take forever to trickle down. The most significant entry in the DNS Server Log is Event ID 7062: The DNS Server Encountered a Packet Addressed to Itself. At least, I think its significant. The Directory Services Log shows numerous Event IDs 1265: The attempt to establish a replication link with parameters failed with the following status: The DSA operation is unable to proceed because of a DNS lookup failure. Does this make any sense to anyone? I feel like its something very simple that I am overlooking. Thanks in advance.

  Read the article

• What is the oldest hardware still in production use? How is it kept running?

  - by sleske

  In the spirit of the question What is your oldest hardware that still works?, I'd like to ask: What is the oldest hardware you know that is still in production use? And what challenges did you (or someone else) face in keeping it running (scarce documentation, no support, no spare parts available...)? Most organizations will retire / upgrade software and hardware after 5-10 years, but sometimes old software is kept running on old boxes, because it "just works". I once worked at a client site that was running a critical piece of (in-house developed) business software on a single server running HP-UX. The server was old (ca. 12-13 years), but fortunately still running without problems; however, getting spares would have been very difficult, and since software installation was undocumented, any significant system changes or even new hardware might have caused significant downtime and data loss. We eventually managed to replace it, but this is not always possible. I also read that many organizations still run decade-old mainframe hardware, particularly for highly customized systems controlling industrial machines or power plants. Which old hardware have you encountered? How did you manage these challenges? Related question: http://serverfault.com/questions/82467/should-old-servers-be-retired

  Read the article

• Linq-to-XML query to select specific sub-element based on additional criteria

  - by BrianLy

  My current LINQ query and example XML are below. What I'd like to do is select the primary email address from the email-addresses element into the User.Email property. The type element under the email-address element is set to primary when this is true. There may be more than one element under the email-addresses but only one will be marked primary. What is the simplest approach to take here? Current Linq Query (User.Email is currently empty): var users = from response in xdoc.Descendants("response") where response.Element("id") != null select new User { Id = (string)response.Element("id"), Name = (string)response.Element("full-name"), Email = (string)response.Element("email-addresses"), JobTitle = (string)response.Element("job-title"), NetworkId = (string)response.Element("network-id"), Type = (string)response.Element("type") }; Example XML: <?xml version="1.0" encoding="UTF-8"?> <response> <response> <contact> <phone-numbers/> <im> <provider></provider> <username></username> </im> <email-addresses> <email-address> <type>primary</type> <address>[email protected]</address> </email-address> </email-addresses> </contact> <job-title>Account Manager</job-title> <type>user</type> <expertise nil="true"></expertise> <summary nil="true"></summary> <kids-names nil="true"></kids-names> <location nil="true"></location> <guid nil="true"></guid> <timezone>Eastern Time (US &amp; Canada)</timezone> <network-name>Domain</network-name> <full-name>Alice</full-name> <network-id>79629</network-id> <stats> <followers>2</followers> <updates>4</updates> <following>3</following> </stats> <mugshot-url> https://assets3.yammer.com/images/no_photo_small.gif</mugshot-url> <previous-companies/> <birth-date></birth-date> <name>alice</name> <web-url>https://www.yammer.com/domain.com/users/alice</web-url> <interests nil="true"></interests> <state>active</state> <external-urls/> <url>https://www.yammer.com/api/v1/users/1089943</url> <network-domains> <network-domain>domain.com</network-domain> </network-domains> <id>1089943</id> <schools/> <hire-date nil="true"></hire-date> <significant-other nil="true"></significant-other> </response> <response> <contact> <phone-numbers/> <im> <provider></provider> <username></username> </im> <email-addresses> <email-address> <type>primary</type> <address>[email protected]</address> </email-address> </email-addresses> </contact> <job-title>Office Manager</job-title> <type>user</type> <expertise nil="true"></expertise> <summary nil="true"></summary> <kids-names nil="true"></kids-names> <location nil="true"></location> <guid nil="true"></guid> <timezone>Eastern Time (US &amp; Canada)</timezone> <network-name>Domain</network-name> <full-name>Bill</full-name> <network-id>79629</network-id> <stats> <followers>3</followers> <updates>1</updates> <following>1</following> </stats> <mugshot-url> https://assets3.yammer.com/images/no_photo_small.gif</mugshot-url> <previous-companies/> <birth-date></birth-date> <name>bill</name> <web-url>https://www.yammer.com/domain.com/users/bill</web-url> <interests nil="true"></interests> <state>active</state> <external-urls/> <url>https://www.yammer.com/api/v1/users/1089920</url> <network-domains> <network-domain>domain.com</network-domain> </network-domains> <id>1089920</id> <schools/> <hire-date nil="true"></hire-date> <significant-other nil="true"></significant-other> </response> </response>

  Read the article

• Standards Corner: OAuth WG Client Registration Problem

  - by Tanu Sood

  Phil Hunt is an active member of multiple industry standards groups and committees (see brief bio at the end of the post) and has spearheaded discussions, creation and ratifications of  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Calibri","sans-serif"; mso-ascii- mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi- mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} industry standards including the Kantara Identity Governance Framework, among others. Being an active voice in the industry standards development world, we have invited him to share his discussions, thoughts, news & updates, and discuss use cases, implementation success stories (and even failures) around industry standards on this monthly column. Author: Phil Hunt This afternoon, the OAuth Working Group will meet at IETF88 in Vancouver to discuss some important topics important to the maturation of OAuth. One of them is the OAuth client registration problem.OAuth (RFC6749) was initially developed with a simple deployment model where there is only monopoly or singleton cloud instance of a web API (e.g. there is one Facebook, one Google, on LinkedIn, and so on). When the API publisher and API deployer are the same monolithic entity, it easy for developers to contact the provider and register their app to obtain a client_id and credential.But what happens when the API is for an open source project where there may be 1000s of deployed copies of the API (e.g. such as wordpress). In these cases, the authors of the API are not the people running the API. In these scenarios, how does the developer obtain a client_id? An example of an "open deployed" API is OpenID Connect. Connect defines an OAuth protected resource API that can provide personal information about an authenticated user -- in effect creating a potentially common API for potential identity providers like Facebook, Google, Microsoft, Salesforce, or Oracle. In Oracle's case, Fusion applications will soon have RESTful APIs that are deployed in many different ways in many different environments. How will developers write apps that can work against an openly deployed API with whom the developer can have no prior relationship?At present, the OAuth Working Group has two proposals two consider: Dynamic RegistrationDynamic Registration was originally developed for OpenID Connect and UMA. It defines a RESTful API in which a prospective client application with no client_id creates a new client registration record with a service provider and is issued a client_id and credential along with a registration token that can be used to update registration over time.As proof of success, the OIDC community has done substantial implementation of this spec and feels committed to its use. Why not approve?Well, the answer is that some of us had some concerns, namely: Recognizing instances of software - dynamic registration treats all clients as unique. It has no defined way to recognize that multiple copies of the same client are being registered other then assuming if the registration parameters are similar it might be the same client. Versioning and Policy Approval of open APIs and clients - many service providers have to worry about change management. They expect to have approval cycles that approve versions of server and client software for use in their environment. In some cases approval might be wide open, but in many cases, approval might be down to the specific class of software and version. Registration updates - when does a client actually need to update its registration? Shouldn't it be never? Is there some characteristic of deployed code that would cause it to change? Options lead to complexity - because each client is treated as unique, it becomes unclear how the clients and servers will agree on what credentials forms are acceptable and what OAuth features are allowed and disallowed. Yet the reality is, developers will write their application to work in a limited number of ways. They can't implement all the permutations and combinations that potential service providers might choose. Stateful registration - if the primary motivation for registration is to obtain a client_id and credential, why can't this be done in a stateless fashion using assertions? Denial of service - With so much stateful registration and the need for multiple tokens to be issued, will this not lead to a denial of service attack / risk of resource depletion? At the very least, because of the information gathered, it would difficult for service providers to clean up "failed" registrations and determine active from inactive or false clients. There has yet to be much wide-scale "production" use of dynamic registration other than in small closed communities. Client Association A second proposal, Client Association, has been put forward by Tony Nadalin of Microsoft and myself. We took at look at existing use patterns to come up with a new proposal. At the Berlin meeting, we considered how WS-STS systems work. More recently, I took a review of how mobile messaging clients work. I looked at how Apple, Google, and Microsoft each handle registration with APNS, GCM, and WNS, and a similar pattern emerges. This pattern is to use an existing credential (mutual TLS auth), or client bearer assertion and swap for a device specific bearer assertion.In the client association proposal, the developer's registration with the API publisher is handled by having the developer register with an API publisher (as opposed to the party deploying the API) and obtaining a software "statement". Or, if there is no "publisher" that can sign a statement, the developer may include their own self-asserted software statement.A software statement is a special type of assertion that serves to lock application registration profile information in a signed assertion. The statement is included with the client application and can then be used by the client to swap for an instance specific client assertion as defined by section 4.2 of the OAuth Assertion draft and profiled in the Client Association draft. The software statement provides a way for service provider to recognize and configure policy to approve classes of software clients, and simplifies the actual registration to a simple assertion swap. Because the registration is an assertion swap, registration is no longer "stateful" - meaning the service provider does not need to store any information to support the client (unless it wants to). Has this been implemented yet? Not directly. We've only delivered draft 00 as an alternate way of solving the problem using well-known patterns whose security characteristics and scale characteristics are well understood. Dynamic Take II At roughly the same time that Client Association and Software Statement were published, the authors of Dynamic Registration published a "split" version of the Dynamic Registration (draft-richer-oauth-dyn-reg-core and draft-richer-oauth-dyn-reg-management). While some of the concerns above are addressed, some differences remain. Registration is now a simple POST request. However it defines a new method for issuing client tokens where as Client Association uses RFC6749's existing extension point. The concern here is whether future client access token formats would be addressed properly. Finally, Dyn-reg-core does not yet support software statements. Conclusion The WG has some interesting discussion to bring this back to a single set of specifications. Dynamic Registration has significant implementation, but Client Association could be a much improved way to simplify implementation of the overall OpenID Connect specification and improve adoption. In fairness, the existing editors have already come a long way. Yet there are those with significant investment in the current draft. There are many that have expressed they don't care. They just want a standard. There is lots of pressure on the working group to reach consensus quickly.And that folks is how the sausage is made.Note: John Bradley and Justin Richer recently published draft-bradley-stateless-oauth-client-00 which on first look are getting closer. Some of the details seem less well defined, but the same could be said of client-assoc and software-statement. I hope we can merge these specs this week. Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Calibri","sans-serif"; mso-ascii- mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi- mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} About the Writer: Phil Hunt joined Oracle as part of the November 2005 acquisition of OctetString Inc. where he headed software development for what is now Oracle Virtual Directory. Since joining Oracle, Phil works as CMTS in the Identity Standards group at Oracle where he developed the Kantara Identity Governance Framework and provided significant input to JSR 351. Phil participates in several standards development organizations such as IETF and OASIS working on federation, authorization (OAuth), and provisioning (SCIM) standards.  Phil blogs at www.independentid.com and a Twitter handle of @independentid.

  Read the article

• Solaris X86 64-bit Assembly Programming

  - by danx

  Solaris X86 64-bit Assembly Programming This is a simple example on writing, compiling, and debugging Solaris 64-bit x86 assembly language with a C program. This is also referred to as "AMD64" assembly. The term "AMD64" is used in an inclusive sense to refer to all X86 64-bit processors, whether AMD Opteron family or Intel 64 processor family. Both run Solaris x86. I'm keeping this example simple mainly to illustrate how everything comes together—compiler, assembler, linker, and debugger when using assembly language. The example I'm using here is a C program that calls an assembly language program passing a C string. The assembly language program takes the C string and calls printf() with it to print the string. AMD64 Register Usage But first let's review the use of AMD64 registers. AMD64 has several 64-bit registers, some special purpose (such as the stack pointer) and others general purpose. By convention, Solaris follows the AMD64 ABI in register usage, which is the same used by Linux, but different from Microsoft Windows in usage (such as which registers are used to pass parameters). This blog will only discuss conventions for Linux and Solaris. The following chart shows how AMD64 registers are used. The first six parameters to a function are passed through registers. If there's more than six parameters, parameter 7 and above are pushed on the stack before calling the function. The stack is also used to save temporary "stack" variables for use by a function. 64-bit Register Usage %rip Instruction Pointer points to the current instruction %rsp Stack Pointer %rbp Frame Pointer (saved stack pointer pointing to parameters on stack) %rdi Function Parameter 1 %rsi Function Parameter 2 %rdx Function Parameter 3 %rcx Function Parameter 4 %r8 Function Parameter 5 %r9 Function Parameter 6 %rax Function return value %r10, %r11 Temporary registers (need not be saved before used) %rbx, %r12, %r13, %r14, %r15 Temporary registers, but must be saved before use and restored before returning from the current function (usually with the push and pop instructions). 32-, 16-, and 8-bit registers To access the lower 32-, 16-, or 8-bits of a 64-bit register use the following: 64-bit register Least significant 32-bits Least significant 16-bits Least significant 8-bits %rax%eax%ax%al %rbx%ebx%bx%bl %rcx%ecx%cx%cl %rdx%edx%dx%dl %rsi%esi%si%sil %rdi%edi%di%axl %rbp%ebp%bp%bp %rsp%esp%sp%spl %r9%r9d%r9w%r9b %r10%r10d%r10w%r10b %r11%r11d%r11w%r11b %r12%r12d%r12w%r12b %r13%r13d%r13w%r13b %r14%r14d%r14w%r14b %r15%r15d%r15w%r15b %r16%r16d%r16w%r16b There's other registers present, such as the 64-bit %mm registers, 128-bit %xmm registers, 256-bit %ymm registers, and 512-bit %zmm registers. Except for %mm registers, these registers may not present on older AMD64 processors. Assembly Source The following is the source for a C program, helloas1.c, that calls an assembly function, hello_asm(). $ cat helloas1.c extern void hello_asm(char *s); int main(void) { hello_asm("Hello, World!"); } The assembly function called above, hello_asm(), is defined below. $ cat helloas2.s /* * helloas2.s * To build: * cc -m64 -o helloas2-cpp.s -D_ASM -E helloas2.s * cc -m64 -c -o helloas2.o helloas2-cpp.s */ #if defined(lint) || defined(__lint) /* ARGSUSED */ void hello_asm(char *s) { } #else /* lint */ #include <sys/asm_linkage.h> .extern printf ENTRY_NP(hello_asm) // Setup printf parameters on stack mov %rdi, %rsi // P2 (%rsi) is string variable lea .printf_string, %rdi // P1 (%rdi) is printf format string call printf ret SET_SIZE(hello_asm) // Read-only data .text .align 16 .type .printf_string, @object .printf_string: .ascii "The string is: %s.\n\0" #endif /* lint || __lint */ In the assembly source above, the C skeleton code under "#if defined(lint)" is optionally used for lint to check the interfaces with your C program--very useful to catch nasty interface bugs. The "asm_linkage.h" file includes some handy macros useful for assembly, such as ENTRY_NP(), used to define a program entry point, and SET_SIZE(), used to set the function size in the symbol table. The function hello_asm calls C function printf() by passing two parameters, Parameter 1 (P1) is a printf format string, and P2 is a string variable. The function begins by moving %rdi, which contains Parameter 1 (P1) passed hello_asm, to printf()'s P2, %rsi. Then it sets printf's P1, the format string, by loading the address the address of the format string in %rdi, P1. Finally it calls printf. After returning from printf, the hello_asm function returns itself. Larger, more complex assembly functions usually do more setup than the example above. If a function is returning a value, it would set %rax to the return value. Also, it's typical for a function to save the %rbp and %rsp registers of the calling function and to restore these registers before returning. %rsp contains the stack pointer and %rbp contains the frame pointer. Here is the typical function setup and return sequence for a function: ENTRY_NP(sample_assembly_function) push %rbp // save frame pointer on stack mov %rsp, %rbp // save stack pointer in frame pointer xor %rax, %r4ax // set function return value to 0. mov %rbp, %rsp // restore stack pointer pop %rbp // restore frame pointer ret // return to calling function SET_SIZE(sample_assembly_function) Compiling and Running Assembly Use the Solaris cc command to compile both C and assembly source, and to pre-process assembly source. You can also use GNU gcc instead of cc to compile, if you prefer. The "-m64" option tells the compiler to compile in 64-bit address mode (instead of 32-bit). $ cc -m64 -o helloas2-cpp.s -D_ASM -E helloas2.s $ cc -m64 -c -o helloas2.o helloas2-cpp.s $ cc -m64 -c helloas1.c $ cc -m64 -o hello-asm helloas1.o helloas2.o $ file hello-asm helloas1.o helloas2.o hello-asm: ELF 64-bit LSB executable AMD64 Version 1 [SSE FXSR FPU], dynamically linked, not stripped helloas1.o: ELF 64-bit LSB relocatable AMD64 Version 1 helloas2.o: ELF 64-bit LSB relocatable AMD64 Version 1 $ hello-asm The string is: Hello, World!. Debugging Assembly with MDB MDB is the Solaris system debugger. It can also be used to debug user programs, including assembly and C. The following example runs the above program, hello-asm, under control of the debugger. In the example below I load the program, set a breakpoint at the assembly function hello_asm, display the registers and the first parameter, step through the assembly function, and continue execution. $ mdb hello-asm # Start the debugger > hello_asm:b # Set a breakpoint > ::run # Run the program under the debugger mdb: stop at hello_asm mdb: target stopped at: hello_asm: movq %rdi,%rsi > $C # display function stack ffff80ffbffff6e0 hello_asm() ffff80ffbffff6f0 0x400adc() > $r # display registers %rax = 0x0000000000000000 %r8 = 0x0000000000000000 %rbx = 0xffff80ffbf7f8e70 %r9 = 0x0000000000000000 %rcx = 0x0000000000000000 %r10 = 0x0000000000000000 %rdx = 0xffff80ffbffff718 %r11 = 0xffff80ffbf537db8 %rsi = 0xffff80ffbffff708 %r12 = 0x0000000000000000 %rdi = 0x0000000000400cf8 %r13 = 0x0000000000000000 %r14 = 0x0000000000000000 %r15 = 0x0000000000000000 %cs = 0x0053 %fs = 0x0000 %gs = 0x0000 %ds = 0x0000 %es = 0x0000 %ss = 0x004b %rip = 0x0000000000400c70 hello_asm %rbp = 0xffff80ffbffff6e0 %rsp = 0xffff80ffbffff6c8 %rflags = 0x00000282 id=0 vip=0 vif=0 ac=0 vm=0 rf=0 nt=0 iopl=0x0 status=<of,df,IF,tf,SF,zf,af,pf,cf> %gsbase = 0x0000000000000000 %fsbase = 0xffff80ffbf782a40 %trapno = 0x3 %err = 0x0 > ::dis # disassemble the current instructions hello_asm: movq %rdi,%rsi hello_asm+3: leaq 0x400c90,%rdi hello_asm+0xb: call -0x220 <PLT:printf> hello_asm+0x10: ret 0x400c81: nop 0x400c85: nop 0x400c88: nop 0x400c8c: nop 0x400c90: pushq %rsp 0x400c91: pushq $0x74732065 0x400c96: jb +0x69 <0x400d01> > 0x0000000000400cf8/S # %rdi contains Parameter 1 0x400cf8: Hello, World! > [ # Step and execute 1 instruction mdb: target stopped at: hello_asm+3: leaq 0x400c90,%rdi > [ mdb: target stopped at: hello_asm+0xb: call -0x220 <PLT:printf> > [ The string is: Hello, World!. mdb: target stopped at: hello_asm+0x10: ret > [ mdb: target stopped at: main+0x19: movl $0x0,-0x4(%rbp) > :c # continue program execution mdb: target has terminated > $q # quit the MDB debugger $ In the example above, at the start of function hello_asm(), I display the stack contents with "$C", display the registers contents with "$r", then disassemble the current function with "::dis". The first function parameter, which is a C string, is passed by reference with the string address in %rdi (see the register usage chart above). The address is 0x400cf8, so I print the value of the string with the "/S" MDB command: "0x0000000000400cf8/S". I can also print the contents at an address in several other formats. Here's a few popular formats. For more, see the mdb(1) man page for details. address/S C string address/C ASCII character (1 byte) address/E unsigned decimal (8 bytes) address/U unsigned decimal (4 bytes) address/D signed decimal (4 bytes) address/J hexadecimal (8 bytes) address/X hexadecimal (4 bytes) address/B hexadecimal (1 bytes) address/K pointer in hexadecimal (4 or 8 bytes) address/I disassembled instruction Finally, I step through each machine instruction with the "[" command, which steps over functions. If I wanted to enter a function, I would use the "]" command. Then I continue program execution with ":c", which continues until the program terminates. MDB Basic Cheat Sheet Here's a brief cheat sheet of some of the more common MDB commands useful for assembly debugging. There's an entire set of macros and more powerful commands, especially some for debugging the Solaris kernel, but that's beyond the scope of this example. $C Display function stack with pointers $c Display function stack $e Display external function names $v Display non-zero variables and registers $r Display registers ::fpregs Display floating point (or "media" registers). Includes %st, %xmm, and %ymm registers. ::status Display program status ::run Run the program (followed by optional command line parameters) $q Quit the debugger address:b Set a breakpoint address:d Delete a breakpoint $b Display breakpoints :c Continue program execution after a breakpoint [ Step 1 instruction, but step over function calls ] Step 1 instruction address::dis Disassemble instructions at an address ::events Display events Further Information "Assembly Language Techniques for Oracle Solaris on x86 Platforms" by Paul Lowik (2004). Good tutorial on Solaris x86 optimization with assembly. The Solaris Operating System on x86 Platforms An excellent, detailed tutorial on X86 architecture, with Solaris specifics. By an ex-Sun employee, Frank Hofmann (2005). "AMD64 ABI Features", Solaris 64-bit Developer's Guide contains rules on data types and register usage for Intel 64/AMD64-class processors. (available at docs.oracle.com) Solaris X86 Assembly Language Reference Manual (available at docs.oracle.com) SPARC Assembly Language Reference Manual (available at docs.oracle.com) System V Application Binary Interface (2003) defines the AMD64 ABI for UNIX-class operating systems, including Solaris, Linux, and BSD. Google for it—the original website is gone. cc(1), gcc(1), and mdb(1) man pages.

  Read the article

• Investigation: Can different combinations of components effect Dataflow performance?

  - by jamiet

  Introduction The Dataflow task is one of the core components (if not the core component) of SQL Server Integration Services (SSIS) and often the most misunderstood. This is not surprising, its an incredibly complicated beast and we’re abstracted away from that complexity via some boxes that go yellow red or green and that have some lines drawn between them. Example dataflow In this blog post I intend to look under that facade and get into some of the nuts and bolts of the Dataflow Task by investigating how the decisions we make when building our packages can affect performance. I will do this by comparing the performance of three dataflows that all have the same input, all produce the same output, but which all operate slightly differently by way of having different transformation components. I also want to use this blog post to challenge a common held opinion that I see perpetuated over and over again on the SSIS forum. That is, that people assume adding components to a dataflow will be detrimental to overall performance. Its not surprising that people think this –it is intuitive to think that more components means more work- however this is not a view that I share. I have always been of the opinion that there are many factors affecting dataflow duration and the number of components is actually one of the less important ones; having said that I have never proven that assertion and that is one reason for this investigation. I have actually seen evidence that some people think dataflow duration is simply a function of number of rows and number of components. I’ll happily call that one out as a myth even without any investigation!  The Setup I have a 2GB datafile which is a list of 4731904 (~4.7million) customer records with various attributes against them and it contains 2 columns that I am going to use for categorisation: [YearlyIncome] [BirthDate] The data file is a SSIS raw format file which I chose to use because it is the quickest way of getting data into a dataflow and given that I am testing the transformations, not the source or destination adapters, I want to minimise external influences as much as possible. In the test I will split the customers according to month of birth (12 of those) and whether or not their yearly income is above or below 50000 (2 of those); in other words I will be splitting them into 24 discrete categories and in order to do it I shall be using different combinations of SSIS’ Conditional Split and Derived Column transformation components. The 24 datapaths that occur will each input to a rowcount component, again because this is the least resource intensive means of terminating a datapath. The test is being carried out on a Dell XPS Studio laptop with a quad core (8 logical Procs) Intel Core i7 at 1.73GHz and Samsung SSD hard drive. Its running SQL Server 2008 R2 on Windows 7. The Variables Here are the three combinations of components that I am going to test:     One Conditional Split - A single Conditional Split component CSPL Split by Month of Birth and income category that will use expressions on [YearlyIncome] & [BirthDate] to send each row to one of 24 outputs. This next screenshot displays the expression logic in use: Derived Column & Conditional Split - A Derived Column component DER Income Category that adds a new column [IncomeCategory] which will contain one of two possible text values {“LessThan50000”,”GreaterThan50000”} and uses [YearlyIncome] to determine which value each row should get. A Conditional Split component CSPL Split by Month of Birth and Income Category then uses that new column in conjunction with [BirthDate] to determine which of the same 24 outputs to send each row to. Put more simply, I am separating the Conditional Split of #1 into a Derived Column and a Conditional Split. The next screenshots display the expression logic in use: DER Income Category         CSPL Split by Month of Birth and Income Category       Three Conditional Splits - A Conditional Split component that produces two outputs based on [YearlyIncome], one for each Income Category. Each of those outputs will go to a further Conditional Split that splits the input into 12 outputs, one for each month of birth (identical logic in each). In this case then I am separating the single Conditional Split of #1 into three Conditional Split components. The next screenshots display the expression logic in use: CSPL Split by Income Category         CSPL Split by Month of Birth 1& 2       Each of these combinations will provide an input to one of the 24 rowcount components, just the same as before. For illustration here is a screenshot of the dataflow containing three Conditional Split components: As you can these dataflows have a fair bit of work to do and remember that they’re doing that work for 4.7million rows. I will execute each dataflow 10 times and use the average for comparison. I foresee three possible outcomes: The dataflow containing just one Conditional Split (i.e. #1) will be quicker There is no significant difference between any of them One of the two dataflows containing multiple transformation components will be quicker Regardless of which of those outcomes come to pass we will have learnt something and that makes this an interesting test to carry out. Note that I will be executing the dataflows using dtexec.exe rather than hitting F5 within BIDS. The Results and Analysis The table below shows all of the executions, 10 for each dataflow. It also shows the average for each along with a standard deviation. All durations are in seconds. I’m pasting a screenshot because I frankly can’t be bothered with the faffing about needed to make a presentable HTML table. It is plain to see from the average that the dataflow containing three conditional splits is significantly faster, the other two taking 43% and 52% longer respectively. This seems strange though, right? Why does the dataflow containing the most components outperform the other two by such a big margin? The answer is actually quite logical when you put some thought into it and I’ll explain that below. Before progressing, a side note. The standard deviation for the “Three Conditional Splits” dataflow is orders of magnitude smaller – indicating that performance for this dataflow can be predicted with much greater confidence too. The Explanation I refer you to the screenshot above that shows how CSPL Split by Month of Birth and salary category in the first dataflow is setup. Observe that there is a case for each combination of Month Of Date and Income Category – 24 in total. These expressions get evaluated in the order that they appear and hence if we assume that Month of Date and Income Category are uniformly distributed in the dataset we can deduce that the expected number of expression evaluations for each row is 12.5 i.e. 1 (the minimum) + 24 (the maximum) divided by 2 = 12.5. Now take a look at the screenshots for the second dataflow. We are doing one expression evaluation in DER Income Category and we have the same 24 cases in CSPL Split by Month of Birth and Income Category as we had before, only the expression differs slightly. In this case then we have 1 + 12.5 = 13.5 expected evaluations for each row – that would account for the slightly longer average execution time for this dataflow. Now onto the third dataflow, the quick one. CSPL Split by Income Category does a maximum of 2 expression evaluations thus the expected number of evaluations per row is 1.5. CSPL Split by Month of Birth 1 & CSPL Split by Month of Birth 2 both have less work to do than the previous Conditional Split components because they only have 12 cases to test for thus the expected number of expression evaluations is 6.5 There are two of them so total expected number of expression evaluations for this dataflow is 6.5 + 6.5 + 1.5 = 14.5. 14.5 is still more than 12.5 & 13.5 though so why is the third dataflow so much quicker? Simple, the conditional expressions in the first two dataflows have two boolean predicates to evaluate – one for Income Category and one for Month of Birth; the expressions in the Conditional Split in the third dataflow however only have one predicate thus they are doing a lot less work. To sum up, the difference in execution times can be attributed to the difference between: MONTH(BirthDate) == 1 && YearlyIncome <= 50000 and MONTH(BirthDate) == 1 In the first two dataflows YearlyIncome <= 50000 gets evaluated an average of 12.5 times for every row whereas in the third dataflow it is evaluated once and once only. Multiply those 11.5 extra operations by 4.7million rows and you get a significant amount of extra CPU cycles – that’s where our duration difference comes from. The Wrap-up The obvious point here is that adding new components to a dataflow isn’t necessarily going to make it go any slower, moreover you may be able to achieve significant improvements by splitting logic over multiple components rather than one. Performance tuning is all about reducing the amount of work that needs to be done and that doesn’t necessarily mean use less components, indeed sometimes you may be able to reduce workload in ways that aren’t immediately obvious as I think I have proven here. Of course there are many variables in play here and your mileage will most definitely vary. I encourage you to download the package and see if you get similar results – let me know in the comments. The package contains all three dataflows plus a fourth dataflow that will create the 2GB raw file for you (you will also need the [AdventureWorksDW2008] sample database from which to source the data); simply disable all dataflows except the one you want to test before executing the package and remember, execute using dtexec, not within BIDS. If you want to explore dataflow performance tuning in more detail then here are some links you might want to check out: Inequality joins, Asynchronous transformations and Lookups Destination Adapter Comparison Don’t turn the dataflow into a cursor SSIS Dataflow – Designing for performance (webinar) Any comments? Let me know! @Jamiet

  Read the article

• Why Are Minimized Programs Often Slow to Open Again?

  - by Jason Fitzpatrick

  It seems particularly counterintuitive: you minimize an application because you plan on returning to it later and wish to skip shutting the application down and restarting it later, but sometimes maximizing it takes even longer than launching it fresh. What gives? Today’s Question & Answer session comes to us courtesy of SuperUser—a subdivision of Stack Exchange, a community-driven grouping of Q&A web sites. The Question SuperUser reader Bart wants to know why he’s not saving any time with application minimization: I’m working in Photoshop CS6 and multiple browsers a lot. I’m not using them all at once, so sometimes some applications are minimized to taskbar for hours or days. The problem is, when I try to maximize them from the taskbar – it sometimes takes longer than starting them! Especially Photoshop feels really weird for many seconds after finally showing up, it’s slow, unresponsive and even sometimes totally freezes for minute or two. It’s not a hardware problem as it’s been like that since always on all on my PCs. Would I also notice it after upgrading my HDD to SDD and adding RAM (my main PC holds 4 GB currently)? Could guys with powerful pcs / macs tell me – does it also happen to you? I guess OSes somehow “focus” on active software and move all the resources away from the ones that run, but are not used. Is it possible to somehow set RAM / CPU / HDD priorities or something, for let’s say, Photoshop, so it won’t slow down after long period of inactivity? So what is the deal? Why does he find himself waiting to maximize a minimized app? The Answer SuperUser contributor Allquixotic explains why: Summary The immediate problem is that the programs that you have minimized are being paged out to the “page file” on your hard disk. This symptom can be improved by installing a Solid State Disk (SSD), adding more RAM to your system, reducing the number of programs you have open, or upgrading to a newer system architecture (for instance, Ivy Bridge or Haswell). Out of these options, adding more RAM is generally the most effective solution. Explanation The default behavior of Windows is to give active applications priority over inactive applications for having a spot in RAM. When there’s significant memory pressure (meaning the system doesn’t have a lot of free RAM if it were to let every program have all the RAM it wants), it starts putting minimized programs into the page file, which means it writes out their contents from RAM to disk, and then makes that area of RAM free. That free RAM helps programs you’re actively using — say, your web browser — run faster, because if they need to claim a new segment of RAM (like when you open a new tab), they can do so. This “free” RAM is also used as page cache, which means that when active programs attempt to read data on your hard disk, that data might be cached in RAM, which prevents your hard disk from being accessed to get that data. By using the majority of your RAM for page cache, and swapping out unused programs to disk, Windows is trying to improve responsiveness of the program(s) you are actively using, by making RAM available to them, and caching the files they access in RAM instead of the hard disk. The downside of this behavior is that minimized programs can take a while to have their contents copied from the page file, on disk, back into RAM. The time increases the larger the program’s footprint in memory. This is why you experience that delay when maximizing Photoshop. RAM is many times faster than a hard disk (depending on the specific hardware, it can be up to several orders of magnitude). An SSD is considerably faster than a hard disk, but it is still slower than RAM by orders of magnitude. Having your page file on an SSD will help, but it will also wear out the SSD more quickly than usual if your page file is heavily utilized due to RAM pressure. Remedies Here is an explanation of the available remedies, and their general effectiveness: Installing more RAM: This is the recommended path. If your system does not support more RAM than you already have installed, you will need to upgrade more of your system: possibly your motherboard, CPU, chassis, power supply, etc. depending on how old it is. If it’s a laptop, chances are you’ll have to buy an entire new laptop that supports more installed RAM. When you install more RAM, you reduce memory pressure, which reduces use of the page file, which is a good thing all around. You also make available more RAM for page cache, which will make all programs that access the hard disk run faster. As of Q4 2013, my personal recommendation is that you have at least 8 GB of RAM for a desktop or laptop whose purpose is anything more complex than web browsing and email. That means photo editing, video editing/viewing, playing computer games, audio editing or recording, programming / development, etc. all should have at least 8 GB of RAM, if not more. Run fewer programs at a time: This will only work if the programs you are running do not use a lot of memory on their own. Unfortunately, Adobe Creative Suite products such as Photoshop CS6 are known for using an enormous amount of memory. This also limits your multitasking ability. It’s a temporary, free remedy, but it can be an inconvenience to close down your web browser or Word every time you start Photoshop, for instance. This also wouldn’t stop Photoshop from being swapped when minimizing it, so it really isn’t a very effective solution. It only helps in some specific situations. Install an SSD: If your page file is on an SSD, the SSD’s improved speed compared to a hard disk will result in generally improved performance when the page file has to be read from or written to. Be aware that SSDs are not designed to withstand a very frequent and constant random stream of writes; they can only be written over a limited number of times before they start to break down. Heavy use of a page file is not a particularly good workload for an SSD. You should install an SSD in combination with a large amount of RAM if you want maximum performance while preserving the longevity of the SSD. Use a newer system architecture: Depending on the age of your system, you may be using an out of date system architecture. The “system architecture” is generally defined as the “generation” (think generations like children, parents, grandparents, etc.) of the motherboard and CPU. Newer generations generally support faster I/O (input/output), better memory bandwidth, lower latency, and less contention over shared resources, instead providing dedicated links between components. For example, starting with the “Nehalem” generation (around 2009), the Front-Side Bus (FSB) was eliminated, which removed a common bottleneck, because almost all system components had to share the same FSB for transmitting data. This was replaced with a “point to point” architecture, meaning that each component gets its own dedicated “lane” to the CPU, which continues to be improved every few years with new generations. You will generally see a more significant improvement in overall system performance depending on the “gap” between your computer’s architecture and the latest one available. For example, a Pentium 4 architecture from 2004 is going to see a much more significant improvement upgrading to “Haswell” (the latest as of Q4 2013) than a “Sandy Bridge” architecture from ~2010. Links Related questions: How to reduce disk thrashing (paging)? Windows Swap (Page File): Enable or Disable? Also, just in case you’re considering it, you really shouldn’t disable the page file, as this will only make matters worse; see here. And, in case you needed extra convincing to leave the Windows Page File alone, see here and here. Have something to add to the explanation? Sound off in the the comments. Want to read more answers from other tech-savvy Stack Exchange users? Check out the full discussion thread here.     

  Read the article

• Effective optimization strategies on modern C++ compilers

  - by user168715

  I'm working on scientific code that is very performance-critical. An initial version of the code has been written and tested, and now, with profiler in hand, it's time to start shaving cycles from the hot spots. It's well-known that some optimizations, e.g. loop unrolling, are handled these days much more effectively by the compiler than by a programmer meddling by hand. Which techniques are still worthwhile? Obviously, I'll run everything I try through a profiler, but if there's conventional wisdom as to what tends to work and what doesn't, it would save me significant time. I know that optimization is very compiler- and architecture- dependent. I'm using Intel's C++ compiler targeting the Core 2 Duo, but I'm also interested in what works well for gcc, or for "any modern compiler." Here are some concrete ideas I'm considering: Is there any benefit to replacing STL containers/algorithms with hand-rolled ones? In particular, my program includes a very large priority queue (currently a std::priority_queue) whose manipulation is taking a lot of total time. Is this something worth looking into, or is the STL implementation already likely the fastest possible? Along similar lines, for std::vectors whose needed sizes are unknown but have a reasonably small upper bound, is it profitable to replace them with statically-allocated arrays? I've found that dynamic memory allocation is often a severe bottleneck, and that eliminating it can lead to significant speedups. As a consequence I'm interesting in the performance tradeoffs of returning large temporary data structures by value vs. returning by pointer vs. passing the result in by reference. Is there a way to reliably determine whether or not the compiler will use RVO for a given method (assuming the caller doesn't need to modify the result, of course)? How cache-aware do compilers tend to be? For example, is it worth looking into reordering nested loops? Given the scientific nature of the program, floating-point numbers are used everywhere. A significant bottleneck in my code used to be conversions from floating point to integers: the compiler would emit code to save the current rounding mode, change it, perform the conversion, then restore the old rounding mode --- even though nothing in the program ever changed the rounding mode! Disabling this behavior significantly sped up my code. Are there any similar floating-point-related gotchas I should be aware of? One consequence of C++ being compiled and linked separately is that the compiler is unable to do what would seem to be very simple optimizations, such as move method calls like strlen() out of the termination conditions of loop. Are there any optimization like this one that I should look out for because they can't be done by the compiler and must be done by hand? On the flip side, are there any techniques I should avoid because they are likely to interfere with the compiler's ability to automatically optimize code? Lastly, to nip certain kinds of answers in the bud: I understand that optimization has a cost in terms of complexity, reliability, and maintainability. For this particular application, increased performance is worth these costs. I understand that the best optimizations are often to improve the high-level algorithms, and this has already been done.

  Read the article

• Making a Job Change That's Easy Why Not Try a Career Change

  - by david.talamelli

  A few nights ago I received a comment on one of our blog posts that reminded me of a statistic that I heard a while back. The statistic reflected the change in our views towards work and showed how while people in past generations would stay in one role for their working career - now with so much choice people not only change jobs often but also change careers 4-5 times in their working life. To differentiate between a job change and a career change: when I say job change this could be an IT Sales person moving from one IT Sales role to another IT Sales role. A Career change for example would be that same IT Sales person moving from IT Sales to something outside the scope of their industry - maybe to something like an Engineer or Scuba Dive Instructor. The reason for Career changes can be as varied as the people who make them. Someone's motivation could be to pursue a passion or maybe there is a change in their personal circumstances forcing the change or it could be any other number of reasons. I think it takes courage to make a Career change - it can be easy to stay in your comfort zone and do what you know, but to really push yourself sometimes you need to try something new, it is a matter of making that career transition as smooth as possible for yourself. The comment that was posted is here below (thanks Dean for the kind words they are appreciated). Hi David, I just wanted to let you know that I work for a company called Milestone Search in Melbourne, Victoria Australia. (www.mstone.com.au) We subscribe to your feed on a daily basis and find your blogs both interesting and insightful. Not to mention extremely entertaining. I wonder if you have missed out on getting in journalism as this seems to be something you'd be great at ?: ) Anyways back to my point about changing careers. This could be anything from going from I.T. to Journalism, Engineering to Teaching or any combination of career you can think of. I don't think there ever has been a time where we have had so many opportunities to do so many different things in our working life. While this idea sounds great in theory, putting it into practice would be much harder to do I think. First, in an increasingly competitive job market, employers tend to look for specialists in their field. You may want to make a change but your options may be limited by the number of employers willing to take a chance on someone new to an industry that will likely require a significant investment in time to get brought up to speed. Also, using myself as an example if I was given the opportunity to move into Journalism/Communication/Marketing career from my career as an IT Recruiter - realistically I would have to take a significant pay cut to make this change as my current salary reflects the expertise I have in my current career. I would not immediately be up to speed moving into a new career and would not be able to justify a similar salary. Yes there are transferable skills in any career change, but even though you may have transferable skills you must realise that you will also have a large amount of learning to do which would take time. These are two initial hurdles that I immediately think of, there may be more but nothing is insurmountable. If you work out what you want to do with your working career whatever that may be, you then need to just need to work out the steps to get to your end goal. This is where utilising the power of your networks and using Social Media can come in handy. If you are interested in working somewhere why not proactively take the opportunity to research the industry or company - find out who it is you need to speak to and get in touch with them. We spend so much time working, we should enjoy the work we do and not be afraid to try new things. Waiting for your dream job to fall into your lap or be handed to you on a silver platter is not likely going to happen, so if there is something you do want to do, work out a plan to make it happen and chase after it. This article was originally posted on David Talamelli's Blog - David's Journal on Tap

  Read the article

• Talking JavaOne with Rock Star Simon Ritter

  - by Janice J. Heiss

  Oracle’s Java Technology Evangelist Simon Ritter is well known at JavaOne for his quirky and fun-loving sessions, which, this year include: CON4644 -- “JavaFX Extreme GUI Makeover” (with Angela Caicedo on how to improve UIs in JavaFX) CON5352 -- “Building JavaFX Interfaces for the Real World” (Kinect gesture tracking and mind reading) CON5348 -- “Do You Like Coffee with Your Dessert?” (Some cool demos of Java of the Raspberry Pi) CON6375 -- “Custom JavaFX Charts: (How to extend JavaFX Chart controls with some interesting things) I recently asked Ritter about the significance of the Raspberry Pi, the topic of one of his sessions that consists of a credit card-sized single-board computer developed in the UK with the intention of stimulating the teaching of basic computer science in schools. “I don't think there's one definitive thing that makes the RP significant,” observed Ritter, “but a combination of things that really makes it stand out. First, it's the cost: $35 for what is effectively a completely usable computer. OK, so you have to add a power supply, SD card for storage and maybe a screen, keyboard and mouse, but this is still way cheaper than a typical PC. The choice of an ARM processor is also significant, as it avoids problems like cooling (no heat sink or fan) and can use a USB power brick.  Combine these two things with the immense groundswell of community support and it provides a fantastic platform for teaching young and old alike about computing, which is the real goal of the project.”He informed me that he’ll be at the Raspberry Pi meetup on Saturday (not part of JavaOne). Check out the details here.JavaFX InterfacesWhen I asked about how JavaFX can interface with the real world, he said that there are many ways. “JavaFX provides you with a simple set of programming interfaces that can create complex, cool and compelling user interfaces,” explained Ritter. “Because it's just Java code you can combine JavaFX with any other Java library to provide data to display and control the interface. What I've done for my session is look at some of the possible ways of doing this using some of the amazing hardware that's available today at very low cost. The Kinect sensor has added a new dimension to gaming in terms of interaction; there's a Java API to access this so you can easily collect skeleton tracking data from it. Some clever people have also written libraries that can track gestures like swipes, circles, pushes, and so on. We use these to control parts of the UI. I've also experimented with a Neurosky EEG sensor that can in some ways ‘read your mind’ (well, at least measure some of the brain functions like attention and meditation).  I've written a Java library for this that I include as a way of controlling the UI. We're not quite at the stage of just thinking a command though!” Here Comes Java EmbeddedAnd what, from Ritter’s perspective, is the most exciting thing happening in the world of Java today? “I think it's seeing just how Java continues to become more and more pervasive,” he said. “One of the areas that is growing rapidly is embedded systems.  We've talked about the ‘Internet of things’ for many years; now it's finally becoming a reality. With the ability of more and more devices to include processing, storage and networking we need an easy way to write code for them that's reliable, has high performance, and is secure. Java fits all these requirements. With Java Embedded being a conference within a conference, I'm very excited about the possibilities of Java in this space.”Check out Ritter’s sessions or say hi if you run into him. Originally published on blogs.oracle.com/javaone.

  Read the article

• Talking JavaOne with Rock Star Simon Ritter

  - by Janice J. Heiss

  Oracle’s Java Technology Evangelist Simon Ritter is well known at JavaOne for his quirky and fun-loving sessions, which, this year include: CON4644 -- “JavaFX Extreme GUI Makeover” (with Angela Caicedo on how to improve UIs in JavaFX) CON5352 -- “Building JavaFX Interfaces for the Real World” (Kinect gesture tracking and mind reading) CON5348 -- “Do You Like Coffee with Your Dessert?” (Some cool demos of Java of the Raspberry Pi) CON6375 -- “Custom JavaFX Charts: (How to extend JavaFX Chart controls with some interesting things) I recently asked Ritter about the significance of the Raspberry Pi, the topic of one of his sessions that consists of a credit card-sized single-board computer developed in the UK with the intention of stimulating the teaching of basic computer science in schools. “I don't think there's one definitive thing that makes the RP significant,” observed Ritter, “but a combination of things that really makes it stand out. First, it's the cost: $35 for what is effectively a completely usable computer. OK, so you have to add a power supply, SD card for storage and maybe a screen, keyboard and mouse, but this is still way cheaper than a typical PC. The choice of an ARM processor is also significant, as it avoids problems like cooling (no heat sink or fan) and can use a USB power brick.  Combine these two things with the immense groundswell of community support and it provides a fantastic platform for teaching young and old alike about computing, which is the real goal of the project.”He informed me that he’ll be at the Raspberry Pi meetup on Saturday (not part of JavaOne). Check out the details here.JavaFX InterfacesWhen I asked about how JavaFX can interface with the real world, he said that there are many ways. “JavaFX provides you with a simple set of programming interfaces that can create complex, cool and compelling user interfaces,” explained Ritter. “Because it's just Java code you can combine JavaFX with any other Java library to provide data to display and control the interface. What I've done for my session is look at some of the possible ways of doing this using some of the amazing hardware that's available today at very low cost. The Kinect sensor has added a new dimension to gaming in terms of interaction; there's a Java API to access this so you can easily collect skeleton tracking data from it. Some clever people have also written libraries that can track gestures like swipes, circles, pushes, and so on. We use these to control parts of the UI. I've also experimented with a Neurosky EEG sensor that can in some ways ‘read your mind’ (well, at least measure some of the brain functions like attention and meditation).  I've written a Java library for this that I include as a way of controlling the UI. We're not quite at the stage of just thinking a command though!” Here Comes Java EmbeddedAnd what, from Ritter’s perspective, is the most exciting thing happening in the world of Java today? “I think it's seeing just how Java continues to become more and more pervasive,” he said. “One of the areas that is growing rapidly is embedded systems.  We've talked about the ‘Internet of things’ for many years; now it's finally becoming a reality. With the ability of more and more devices to include processing, storage and networking we need an easy way to write code for them that's reliable, has high performance, and is secure. Java fits all these requirements. With Java Embedded being a conference within a conference, I'm very excited about the possibilities of Java in this space.”Check out Ritter’s sessions or say hi if you run into him.

  Read the article

• Building vs. Buying a Master Data Management Solution

  - by david.butler(at)oracle.com

  Many organizations prefer to build their own MDM solutions. The argument is that they know their data quality issues and their data better than anyone. Plus a focused solution will cost less in the long run then a vendor supplied general purpose product. This is not unreasonable if you think of MDM as a point solution for a particular data quality problem. But this approach carries significant risk. We now know that organizations achieve significant competitive advantages when they deploy MDM as a strategic enterprise wide solution: with the most common best practice being to deploy a tactical MDM solution and grow it into a full information architecture. A build your own approach most certainly will not scale to a larger architecture unless it is done correctly with the larger solution in mind. It is possible to build a home grown point MDM solution in such a way that it will dovetail into broader MDM architectures. A very good place to start is to use the same basic technologies that Oracle uses to build its own MDM solutions. Start with the Oracle 11g database to create a flexible, extensible and open data model to hold the master data and all needed attributes. The Oracle database is the most flexible, highly available and scalable database system on the market. With its Real Application Clusters (RAC) it can even support the mixed OLTP and BI workloads that represent typical MDM data access profiles. Use Oracle Data Integration (ODI) for batch data movement between applications, MDM data stores, and the BI layer. Use Oracle Golden Gate for more real-time data movement. Use Oracle's SOA Suite for application integration with its: BPEL Process Manager to orchestrate MDM connections to business processes; Identity Management for managing users; WS Manager for managing web services; Business Intelligence Enterprise Edition for analytics; and JDeveloper for creating or extending the MDM management application. Oracle utilizes these technologies to build its MDM Hubs.  Customers who build their own MDM solution using these components will easily migrate to Oracle provided MDM solutions when the home grown solution runs out of gas. But, even with a full stack of open flexible MDM technologies, creating a robust MDM application can be a daunting task. For example, a basic MDM solution will need: a set of data access methods that support master data as a service as well as direct real time access as well as batch loads and extracts; a data migration service for initial loads and periodic updates; a metadata management capability for items such as business entity matrixed relationships and hierarchies; a source system management capability to fully cross-reference business objects and to satisfy seemingly conflicting data ownership requirements; a data quality function that can find and eliminate duplicate data while insuring correct data attribute survivorship; a set of data quality functions that can manage structured and unstructured data; a data quality interface to assist with preventing new errors from entering the system even when data entry is outside the MDM application itself; a continuing data cleansing function to keep the data up to date; an internal triggering mechanism to create and deploy change information to all connected systems; a comprehensive role based data security system to control and monitor data access, update rights, and maintain change history; a flexible business rules engine for managing master data processes such as privacy and data movement; a user interface to support casual users and data stewards; a business intelligence structure to support profiling, compliance, and business performance indicators; and an analytical foundation for directly analyzing master data. Oracle's pre-built MDM Hub solutions are full-featured 3-tier Internet applications designed to participate in the full Oracle technology stack or to run independently in other open IT SOA environments. Building MDM solutions from scratch can take years. Oracle's pre-built MDM solutions can bring quality data to the enterprise in a matter of months. But if you must build, at lease build with the world's best technology stack in a way that simplifies the eventual upgrade to Oracle MDM and to the full enterprise wide information architecture that it enables.

  Read the article

• WebCenter Customer Spotlight: Texas Industries, Inc.

  - by me

  Author: Peter Reiser - Social Business Evangelist, Oracle WebCenter  Solution SummaryTexas Industries, Inc. (TXI) is a leading supplier of cement, aggregate, and consumer product building materials for residential, commercial, and public works projects. TXI is based in Dallas and employs around 2,000 employees. The customer had the challenge of decentralized and manual processes for entering 180,000 vendor invoices annually.  Invoice entry was a time- and resource-intensive process that entailed significant personnel requirements. TXI implemented a centralized solution leveraging Oracle WebCenter Imaging, a smart routing solution that enables users to capture invoices electronically with Oracle WebCenter Capture and Oracle WebCenter Forms Recognition to send  the invoices through to Oracle Financials for approvals and processing.  TXI significantly lowered resource needs for payable processing,  increase productivity by 80% and reduce invoice processing cycle times by 84%—from 20 to 30 days to just 3 to 5 days, on average. Company OverviewTexas Industries, Inc. (TXI) is a leading supplier of cement, aggregate, and consumer product building materials for residential, commercial, and public works projects. With operating subsidiaries in six states, TXI is the largest producer of cement in Texas and a major producer in California. TXI is a major supplier of stone, sand, gravel, and expanded shale and clay products, and one of the largest producers of bagged cement and concrete  products in the Southwest. Business ChallengesTXI had the challenge of decentralized and manual processes for entering 180,000 vendor invoices annually.  Invoice entry was a time- and resource-intensive process that entailed significant personnel requirements. Their business objectives were: Increase the efficiency of core business processes, such as invoice processing, to support the organization’s desire to maintain its role as the Southwest’s leader in delivering high-quality, low-cost products to the construction industry Meet the audit and regulatory requirements for achieving Sarbanes-Oxley (SOX) compliance Streamline entry of 180,000 invoices annually to accelerate processing, reduce errors, cut invoice storage and routing costs, and increase visibility into payables liabilities Solution DeployedTXI replaced a resource-intensive, paper-based, decentralized process for invoice entry with a centralized solution leveraging Oracle WebCenter Imaging 11g. They worked with the Oracle Partner Keste LLC to develop a smart routing solution that enables users to capture invoices electronically with Oracle WebCenter Capture and then uses Oracle WebCenter Forms Recognition and the Oracle WebCenter Imaging workflow to send the invoices through to Oracle Financials for approvals and processing. Business Results Significantly lowered resource needs for payable processing through centralization and improved efficiency  Enabled the company to process invoices faster and pay bills earlier, allowing it to take advantage of additional vendor discounts Tracked to increase productivity by 80% and reduce invoice processing cycle times by 84%—from 20 to 30 days to just 3 to 5 days, on average Achieved a 25% reduction in paper invoice storage costs now that invoices are captured digitally, and enabled a 50% reduction in shipping costs, as the company no longer has to send paper invoices between headquarters and production facilities for approvals “Entering and manually processing more than 180,000 vendor invoices annually was time and labor intensive. With Oracle Imaging and Process Management, we have automated and centralized invoice entry and processing at our corporate office, improving productivity by 80% and reducing invoice processing cycle times by 84%—a very important efficiency gain.” Terry Marshall, Vice President of Information Services, Texas Industries, Inc. Additional Information TXI Customer Snapshot Oracle WebCenter Content Oracle WebCenter Capture Oracle WebCenter Forms Recognition

  Read the article

• Oracle and Partners release CAMP specification for PaaS Management

  - by macoracle

  Cloud Application Management for Platforms The public release of the Cloud Application Management for Platforms (CAMP) specification, an initial draft of what is expected to become an industry standard self service interface specification for Platform as a Service (PaaS) management, represents a significant milestone in cloud standards development. Created by several players in the emerging cloud industry, including Oracle, the specification is being submitted to the OASIS standards organization (draft charter) where it will be finalized in an open development process. CAMP is targeted at application developers and deployers for self service management of their application on a Platform-as-a-Service cloud. It is closely aligned with the application development process where applications are typically developed in an Application Development Environment (ADE) and then deployed into a private or public platform cloud. CAMP standardizes the model behind an application’s dependencies on platform components and provides a standardized format for moving applications between the ADE and the cloud, and if and when desirable, between clouds. Once an application is deployed, CAMP provides users with a standardized self service interface to the PaaS offering, allowing the cloud consumer to manage the lifecycle of the application on that platform and the use of the underlying platform services. The CAMP interface includes a RESTful binding of the CAMP model onto the standard HTTP protocol, using JSON as the encoding for the model resources. The model for CAMP includes resources that represent the Application, its Components and any Platform Components that they depend on. It's important PaaS Cloud consumers understand that for a PaaS cloud, these are the abstractions that the user would prefer to work with, not Virtual Machines and the various resources such as compute power, storage and networking. PaaS cloud consumers would also not like to become system administrators for the infrastructure that is hosting their applications and component services. CAMP works on this more abstract level, and yet still accommodates platforms that are built using an underlying infrastructure cloud. With CAMP, it is up to the cloud provider whether or not this underlying infrastructure is exposed to the consumer. One major challenge addressed by the CAMP specification is that of ensuring that application deployment on a new platform is as seamless and error free as possible. This becomes even more difficult when the application may have been developed for a different platform and is now moving to a new one. In CAMP this is accomplished by matching the requirements of the application and its components to the specific capabilities of the underlying platform. This needs to be done regardless of whether there are existing pools of virtualized platform resources (such as a database pool) which are provisioned(on the basis of a schema for example), or whether the platform component is really just a set of virtual machines drawn from an infrastructure pool. The interoperability between platform clouds that CAMP offers means that a CAMP client such as an ADE can target multiple clouds with a single common interface. Applications can even be spread across multiple platform clouds and then managed without needing to create a specialized adapter to manage the components running in each cloud. The development of CAMP has been an effort by a small set of companies, but there are significant advantages to this approach. For example, the way that each of these companies creates their platforms is different enough, to ensure that CAMP can cover a wide range of actual deployments. CAMP is now entering the next phase of development under the guidance of an open standards organization, OASIS, which will likely broaden it’s capabilities. We hope is to keep it concise and minimal, however, to ease implementation and adoption. Over time there will be many different types of platform components that applications can use and which need management. CAMP at this point only includes one example of this (in an appendix) – DataBase as a Service. I am looking forward to the start of the CAMP Technical Committee in OASIS and will do my best to ensure a successful development process. Hope to see you there.

  Read the article

• Oracle OpenWorld Update: Oracle GoldenGate Customer Panels

  - by Doug Reid

  0 false 18 pt 18 pt 0 0 false false false /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} We are two weeks out from the start of Oracle OpenWorld 2012. The Data Integration team has a solid line-up of product and customer sessions for you to attend this year, plus five hands-on labs, and numerous demonstration pods in Moscone South. On Monday we kick the track off with Brad Adelberg’s Future Strategy, Direction and Roadmap for Oracle’s Data Integration Platform at 10:45AM in Moscone West 3005. Over the rest of the week we have a number of deep dive sessions that build out the themes that Brad discusses in his keynote, but the two that I would like to highlight today are our Oracle GoldenGate customer panels. The first customer panel is on Zero Downtime Operations and is on Monday at 1:45 in Moscone West 3005. The theme of this session is how to reduce downtime for critical must-succeed systems. Here’s a rundown of the session: Bank of America, TALX, and St. Jude Medical all have users communities that expect systems to be available around the clock. In this customer panel session, Bank of America discusses how it will be leveraging Oracle GoldenGate. St. Jude Medical shares how it is using Oracle GoldenGate to achieve a zero-downtime migration for a 5 TB Oracle online transaction processing (OLTP) 24/7 mission-critical database. TALX discusses how Equifax Workforce Information Services used Oracle GoldenGate to move from processing online transactions in a single site to processing concurrently from two geographically disparate data centers, providing a highly available solution with significant burst capacity. On Tuesday at 11:45 in Moscone West 3005 we switch gears and host a customer panel on Operational Reporting. The theme of this customer panel is all around reporting and how Oracle GoldenGate raises the bar on reporting by enabling real-time access to real-time data. Here’s a rundown of the session: Turk Telekom and Comcast are half a world away from each other, but these two powerhouse companies have both drastically improved performance and access to real-time data by using Oracle GoldenGate. During this panel discussion, Turk Telekom will explain its evaluation and implementation of Oracle GoldenGate, how the business has experienced significant improvements in the core database and reporting platform, and how it plans to expand its usage into its SOA architecture and its architecture based on Oracle’s Siebel platform. Comcast will explain its implementation of Oracle GoldenGate and how it moves data in real time from its mission-critical HP NonStop database to a Teradata data warehouse. Join us at our sessions to learn what other customers are doing with our products or stop by our demo pods in Moscone south and meet the product management and development teams.

  Read the article

• What's New in Oracle's EPM System?

  - by jmorourke

  Oracle’s EPM System R11.1.2.2  is now generally available to customers and partners on the download center.  Although the release number doesn’t sound significant, this is a major release of Oracle’s Hyperion EPM Suite with new modules as well as significant enhancements across the suite.  This release was announced back on April 4th as part of Oracle’s Business Analytics Strategy launch, so analytics is a key aspect of the release.  But the three biggest pieces of news in this release are Oracle Hyperion Planning support for the Exalytics In-Memory Machine, the new Project Financial Planning Application and the new Account Reconciliations Manager module. The Oracle Exalytics In-Memory Machine was announced back in October 2011, at Oracle OpenWorld.  It’s the latest installment from Oracle in a line of engineered systems that combine Oracle Sun hardware, with Oracle database and application technologies – in solutions that are designed to provide high scalability and performance for specific tasks.  Exalytics is the first engineered system specifically designed for high performance analytics.  Running in-memory versions of Oracle Essbase, as well as the Oracle TimesTen database and Oracle BI tools, Exalytics provides speed of thought response times for complex analytic processes with advanced visualizations.  Early adopter customers have achieved 5X to 100X faster interactivity and 6X to 10X faster planning cycles.  Hyperion Planning running with Oracle Exalytics will support enterprise-wide planning, budgeting and forecasting with more detailed data, with hundreds to thousands of users across an organization getting speed of thought performance. The new Hyperion Project Financial Planning application delivered with EPM 11.1.2.2 is also great news for Oracle customers.  This application follows on the heels of other special-purpose planning applications that Oracle has delivered for Workforce and Capital Asset planning.  It allows Project Managers to identify project-related expenses and revenues, plan and propose new projects, and track results over time. Finance Managers can evaluate and compare different projects, manage the funding process, monitor and report the actual financial results and impacts of projects and project portfolios. This new application is applicable to capital projects, contract projects and indirect projects like IT and HR projects across all industries.  This application is a great complement to existing Project Management applications, and helps bridge the gap between these applications, and the financial planning and budgeting process. Account reconciliations has to be one of the biggest bottlenecks and risks in the financial close and reporting process, and many organizations rely on spreadsheets and manual processes to perform this critical process.  To help address this problem, Oracle developed an Account Reconciliation Manager module that is being delivered as part of Oracle Hyperion Financial Close Management.   This module helps automate and streamline account reconciliations and eliminates the chances for errors, omissions and fraud.  But unlike standalone account reconciliation packages, it’s integrated with the rest of the Oracle Hyperion Financial Close suite, and can integrate balances from any source system.  This can help alleviate a major bottleneck in the financial close process, increase accuracy and reduce risk, and can complement existing investments in Hyperion Financial Management, as well as Oracle and non-Oracle transaction processing systems. Other enhancements in this release include an enhanced Web 2.0 interface for Hyperion Planning and Hyperion Financial Management (HFM), configurable dimensionality in HFM, new Predictive Planning feature in Hyperion Planning, new Detailed Profitability feature in Hyperion Profitability and Cost Management, new Smart View interface for Hyperion Strategic Finance, and integration of the Hyperion applications with JD Edwards Financials. For more information about Oracle EPM System R11.1.2.2 check out the links below: Press Release:  http://www.oracle.com/us/corporate/press/1575775 Product Information on O.com:  http://www.oracle.com/us/solutions/business-analytics/overview/index.html Product Information on OTN:  http://www.oracle.com/technetwork/middleware/epm/downloads/index.html Webcast Replay:  http://www.oracle.com/us/go/index.html?Src=7317510&Act=65&pcode=WWMK11054701MPP046 Please contact me if you have any questions or need additional information – [email protected]

  Read the article

• SQL SERVER – Partition Parallelism Support in expressor 3.6

  - by pinaldave

  I am very excited to learn that there is a new version of expressor’s data integration platform coming out in March of this year.  It will be version 3.6, and I look forward to using it and telling everyone about it.  Let me describe a little bit more about what will be so great in expressor 3.6: Greatly enhanced user interface Parallel Processing Bulk Artifact Upgrading The User Interface First let me cover the most obvious enhancements. The expressor Studio user interface (UI) has had some significant work done. Kudos to the expressor Engineering team; the entire UI is a visual masterpiece that is very responsive and intuitive. The improvements are more than just eye candy; they provide significant productivity gains when developing expressor Dataflows. Operator shape icons now include a description that identifies the function of each operator, instead of having to guess at the function by the icon. Operator shapes and highlighting depict the current function and status: Disabled, enabled, complete, incomplete, and error. Each status displays an appropriate message in the message panel with correction suggestions. Floating or docking property panels provide descriptive tool tips for each property as well as auto resize when adjusting the canvas, without having to search Help or the need to scroll around to get access to the property. Progress and status indicators let you know when an operation is working. “No limit” canvas with snap-to-grid allows automatic sizing and accurate positioning when you have numerous operators in the Dataflow. The inline tool bar offers quick access to pan, zoom, fit and overview functions. Selecting multiple artifacts with a right click context allows you to easily manage your workspace more efficiently. Partitioning and Parallel Processing Partitioning allows each operator to process multiple subsets of records in parallel as opposed to processing all records that flow through that operator in a single sequential set. This capability allows the user to configure the expressor Dataflow to run in a way that most efficiently utilizes the resources of the hardware where the Dataflow is running. Partitions can exist in most individual operators. Using partitions increases the speed of an expressor data integration application, therefore improving performance and load times. With the expressor 3.6 Enterprise Edition, expressor simplifies enabling parallel processing by adding intuitive partition settings that are easy to configure. Bulk Artifact Upgrading Bulk Artifact Upgrading sounds a bit intimidating, but it actually is not and it is a welcome addition to expressor Studio. In past releases, users were prompted to confirm that they wanted to upgrade their individual artifacts only when opened. This was a cumbersome and repetitive process. Now with bulk artifact upgrading, a user can easily select what artifact or group of artifacts to upgrade all at once. As you can see, there are many new features and upgrade options that will prove to make expressor Studio quicker and more efficient.  I hope I’m not the only one who is excited about all these new upgrades, and that I you try expressor and share your experience with me. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

  Read the article

• Recent improvements in Console Performance

  - by loren.konkus

  Recently, the WebLogic Server development and support organizations have worked with a number of customers to quantify and improve the performance of the Administration Console in large, distributed configurations where there is significant latency in the communications between the administration server and managed servers. These improvements fall into two categories: Constraining the amount of time that the Console stalls waiting for communication Reducing and streamlining the amount of data required for an update A few releases ago, we added support for a configurable domain-wide mbean "Invocation Timeout" value on the Console's configuration: general, advanced section for a domain. The default value for this setting is 0, which means wait indefinitely and was chosen for compatibility with the behavior of previous releases. This configuration setting applies to all mbean communications between the admin server and managed servers, and is the first line of defense against being blocked by a stalled or completely overloaded managed server. Each site should choose an appropriate timeout value for their environment and network latency. In the next release of WebLogic Server, we've added an additional console preference, "Management Operation Timeout", to the Console's shared preference page. This setting further constrains how long certain console pages will wait for slowly responding servers before returning partial results. While not all Console pages support this yet, key pages such as the Servers Configuration and Control table pages and the Deployments Control pages have been updated to support this. For example, if a user requests a Servers Table page and a Management Operation Timeout occurs, the table is displayed with both local configuration and remote runtime information from the responding managed servers and only local configuration information for servers that did not yet respond. This means that a troublesome managed server does not impede your ability to manage your domain using the Console. To support these changes, these Console pages have been re-written to use the Work Management feature of WebLogic Server to interact with each server or deployment concurrently, which further improves the responsiveness of these pages. The basic algorithm for these pages is: For each configuration mbean (ie, Servers) populate rows with configuration attributes from the fast, local mbean server Find a WorkManager For each server, Create a Work instance to obtain runtime mbean attributes for the server Schedule Work instance in the WorkManager Call WorkManager.waitForAll to wait WorkItems to finish, constrained by Management Operation Timeout For each WorkItem, if the runtime information obtained was not complete, add a message indicating which server has incomplete data Display collected data in table In addition to these changes to constrain how long the console waits for communication, a number of other changes have been made to reduce the amount and scope of managed server interactions for key pages. For example, in previous releases the Deployments Control table looked at the status of a deployment on every managed server, even those servers that the deployment was not currently targeted on. (This was done to handle an edge case where a deployment's target configuration was changed while it remained running on previously targeted servers.) We decided supporting that edge case did not warrant the performance impact for all, and instead only look at the status of a deployment on the servers it is targeted to. Comprehensive status continues to be available if a user clicks on the 'status' field for a deployment. Finally, changes have been made to the System Status portlet to reduce its impact on Console page display times. Obtaining health information for this display requires several mbean interactions with managed servers. In previous releases, this mbean interaction occurred with every display, and any delay or impediment in these interactions was reflected in the display time for every page. To reduce this impact, we've made several changes in this portlet: Using Work Management to obtain health concurrently Applying the operation timeout configuration to constrain how long we will wait Caching health information to reduce the cost during rapid navigation from page to page and only obtaining new health information if the previous information is over 30 seconds old. Eliminating heath collection if this portlet is minimized. Together, these Console changes have resulted in significant performance improvements for the customers with large configurations and high latency that we have worked with during their development, and some lesser performance improvements for those with small configurations and very fast networks. These changes will be included in the 11g Rel 1 patch set 2 (10.3.3.0) release of WebLogic Server.

  Read the article

• Drinking Our Own Champagne: Fusion Accounting Hub at Oracle

  - by Di Seghposs

  A guest post by Corey West, Senior Vice President, Oracle's Corporate Controller and Chief Accounting Officer There's no better story to tell than one about Oracle using its own products with blowout success. Here's how this one goes. As you know, Oracle has increased its share of the software market through a number of high-profile acquisitions. Legally combining companies is a very complicated process -- it can take months to complete, especially for the acquisitions with offices in several countries, each with its own unique laws and regulations. It's a mission critical and time sensitive process to roll an acquired company's legacy systems (running vital operations, such as accounts receivable and general ledger (GL)) into the existing systems at Oracle. To date, we've run our primary financial ledgers in E-Business Suite R12 -- and we've successfully met the requirements of the business and closed the books on time every single quarter. But there's always room for improvement and that comes in the form of Fusion Applications. We are now live on Fusion Accounting Hub (FAH), which is the first critical step in moving to a full Fusion Financials instance. We started with FAH so that we could design a global chart of accounts. Eventually, every transaction in every country will originate from this global chart of accounts -- it becomes the structure for managing our business more uniformly. In conjunction, we're using Oracle Hyperion Data Relationship Management (DRM) to centralize and automate governance of our global chart of accounts and related hierarchies, which will help us lower our costs and greatly reduce risk. Each month, we have to consolidate data from our primary general ledgers. We have been able to simplify this process considerably using FAH. We can now submit our primary ledgers running in E-Business Suite (EBS) R12 directly to FAH, eliminating the need for more than 90 redundant consolidation ledgers. Also we can submit incrementally, so if we need to book an adjustment in a primary ledger after close, we can do so without re-opening it and re-submitting. As a result, we have earlier visibility to period-end actuals during the close. A goal of this implementation, and one that we successfully achieved, is that we are able to use FAH globally with no customization. This means we have the ability to fully deploy ledger sets at the consolidation level, plus we can use standard functionality for currency translation and mass allocations. We're able to use account monitoring and drill down functionality from the consolidation level all the way through to EBS primary ledgers and sub-ledgers, which allows someone to click through a transaction appearing at the consolidation level clear through to its original source, a significant productivity enhancement when doing research. We also see a significant improvement in reporting using Essbase cube and Hyperion Smart View. Specifically, "the addition of an Essbase cube on top of the GL gives us tremendous versatility to automate and speed our elimination process," says Claire Sebti, Senior Director of Corporate Accounting at Oracle. A highlight of this story is that FAH is running in a co-existence environment. Our plan is to move to Fusion Financials in steps, starting with FAH. Next, our Oracle Financial Services Software subsidiary will move to a full Fusion Financials instance. Then we'll replace our EBS instance with Fusion Financials. This approach allows us to plan in steps, learn as we go, and not overwhelm our teams. It also reduces the risk that comes with moving the entire instance at once. Maria Smith, Vice President of Global Controller Operations, is confident about how they've positioned themselves to uptake more Fusion functionality and is eager to "continue to drive additional efficiency and cost savings." In this story, the happy customers are Oracle controllers, financial analysts, accounting specialists, and our management team that get earlier access to more flexible reporting. "Fusion Accounting Hub simplifies our processes and gives us more transparency into account activity," raves Alex SanJuan, Senior Director, Record to Report Strategic Process Owner. Overall, the team has been very impressed with the usability and functionality of FAH and are pleased with the quantifiable improvements. Claire Sebti states, "Our WD5 close activities have been reduced by at least four hours of system processing time, just for the consolidation group." Fusion Accounting Hub is an inspiring beginning to our Fusion Financials implementation story. There's no doubt it's going to be an international bestseller! Corey West, Senior Vice President Oracle's Corporate Controller and Chief Accounting Officer

  Read the article

• Create a Remote Git Repository from an Existing XCode Repository

  - by codeWithoutFear

  Introduction Distributed version control systems (VCS’s), like Git, provide a rich set of features for managing source code.  Many development tools, including XCode, provide built-in support for various VCS’s.  These tools provide simple configuration with limited customization to get you up and running quickly while still providing the safety net of basic version control. I hate losing (and re-doing) work.  I have OCD when it comes to saving and versioning source code.  Save early, save often, and commit to the VCS often.  I also hate merging code.  Smaller and more frequent commits enable me to minimize merge time and effort as well. The work flow I prefer even for personal exploratory projects is: Make small local changes to the codebase to create an incrementally improved (and working) system. Commit these changes to the local repository.  Local repositories are quick to access, function even while offline, and provides the confidence to continue making bold changes to the system.  After all, I can easily recover to a recent working state. Repeat 1 & 2 until the codebase contains “significant” functionality and I have connectivity to the remote repository. Push the accumulated changes to the remote repository.  The smaller the change set, the less likely extensive merging will be required.  Smaller is better, IMHO. The remote repository typically has a greater degree of fault tolerance and active management dedicated to it.  This can be as simple as a network share that is backed up nightly or as complex as dedicated hardware with specialized server-side processing and significant administrative monitoring. XCode’s out-of-the-box Git integration enables steps 1 and 2 above.  Time Machine backups of the local repository add an additional degree of fault tolerance, but do not support collaboration or take advantage of managed infrastructure such as on-premises or cloud-based storage. Creating a Remote Repository These are the steps I use to enable the full workflow identified above.  For simplicity the “remote” repository is created on the local file system.  This location could easily be on a mounted network volume. Create a Test Project My project is called HelloGit and is located at /Users/Don/Dev/HelloGit.  Be sure to commit all outstanding changes.  XCode always leaves a single changed file for me after the project is created and the initial commit is submitted. Clone the Local Repository We want to clone the XCode-created Git repository to the location where the remote repository will reside.  In this case it will be /Users/Don/Dev/RemoteHelloGit. Open the Terminal application. Clone the local repository to the remote repository location: git clone /Users/Don/Dev/HelloGit /Users/Don/Dev/RemoteHelloGit Convert the Remote Repository to a Bare Repository The remote repository only needs to contain the Git database.  It does not need a checked out branch or local files. Go to the remote repository folder: cd /Users/Don/Dev/RemoteHelloGit Indicate the repository is “bare”: git config --bool core.bare true Remove files, leaving the .git folder: rm -R * Remove the “origin” remote: git remote rm origin Configure the Local Repository The local repository should reference the remote repository.  The remote name “origin” is used by convention to indicate the originating repository.  This is set automatically when a repository is cloned.  We will use the “origin” name here to reflect that relationship. Go to the local repository folder: cd /Users/Don/Dev/HelloGit Add the remote: git remote add origin /Users/Don/Dev/RemoteHelloGit Test Connectivity Any changes made to the local Git repository can be pushed to the remote repository subject to the merging rules Git enforces. Create a new local file: date > date.txt /li> Add the new file to the local index: git add date.txt Commit the change to the local repository: git commit -m "New file: date.txt" Push the change to the remote repository: git push origin master Now you can save, commit, and push/pull to your OCD hearts’ content! Code without fear! --Don

  Read the article

• Columnstore Case Study #1: MSIT SONAR Aggregations

  - by aspiringgeek

  Preamble This is the first in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in this deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. Why Columnstore? If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. App: MSIT SONAR Aggregations At MSIT, performance & configuration data is captured by SCOM. We archive much of the data in a partitioned data warehouse table in SQL Server 2012 for reporting via an application called SONAR.  By definition, this is a primary use case for columnstore—report queries requiring aggregation over large numbers of rows.  New data is refreshed each night by an automated table partitioning mechanism—a best practices scenario for columnstore. The Win Compared to performance using classic indexing which resulted in the expected query plan selection including partition elimination vs. SQL Server 2012 nonclustered columnstore, query performance increased significantly.  Logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Other than creating the columnstore index, no special modifications or tweaks to the app or databases schema were necessary to achieve the performance improvements.  Existing nonclustered indexes were rendered superfluous & were deleted, thus mitigating maintenance challenges such as defragging as well as conserving disk capacity. Details The table provides the raw data & summarizes the performance deltas. Logical Reads (8K pages) CPU (ms) Durn (ms) Columnstore 160,323 20,360 9,786 Conventional Table & Indexes 9,053,423 549,608 193,903 ? x56 x27 x20 The charts provide additional perspective of this data.  "Conventional vs. Columnstore Metrics" document the raw data.  Note on this linear display the magnitude of the conventional index performance vs. columnstore.  The “Metrics (?)” chart expresses these values as a ratio. Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the first in a series of reports on columnstore implementations, results from an initial implementation at MSIT in which logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Subsequent features in this series document performance enhancements that are even more significant. 

  Read the article

• Columnstore Case Study #1: MSIT SONAR Aggregations

  - by aspiringgeek

  Preamble This is the first in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in this deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. Why Columnstore? If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. App: MSIT SONAR Aggregations At MSIT, performance & configuration data is captured by SCOM. We archive much of the data in a partitioned data warehouse table in SQL Server 2012 for reporting via an application called SONAR.  By definition, this is a primary use case for columnstore—report queries requiring aggregation over large numbers of rows.  New data is refreshed each night by an automated table partitioning mechanism—a best practices scenario for columnstore. The Win Compared to performance using classic indexing which resulted in the expected query plan selection including partition elimination vs. SQL Server 2012 nonclustered columnstore, query performance increased significantly.  Logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Other than creating the columnstore index, no special modifications or tweaks to the app or databases schema were necessary to achieve the performance improvements.  Existing nonclustered indexes were rendered superfluous & were deleted, thus mitigating maintenance challenges such as defragging as well as conserving disk capacity. Details The table provides the raw data & summarizes the performance deltas. Logical Reads (8K pages) CPU (ms) Durn (ms) Columnstore 160,323 20,360 9,786 Conventional Table & Indexes 9,053,423 549,608 193,903 ? x56 x27 x20 The charts provide additional perspective of this data.  "Conventional vs. Columnstore Metrics" document the raw data.  Note on this linear display the magnitude of the conventional index performance vs. columnstore.  The “Metrics (?)” chart expresses these values as a ratio. Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the first in a series of reports on columnstore implementations, results from an initial implementation at MSIT in which logical reads were reduced by over a factor of 50; both CPU & duration improved by factors of 20 or more.  Subsequent features in this series document performance enhancements that are even more significant. 

  Read the article

< Previous Page | 7 8 9 10 11 12 13 14 15 16 17 18  | Next Page >