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  • Optimizing AES modes on Solaris for Intel Westmere

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

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  • Performance problems loading XML with SSIS, an alternative way!

    - by AtulThakor
    I recently needed to load several thousand XML files into a SQL database, I created an SSIS package which was created as followed: Using a foreach container to loop through a directory and load each file path into a variable, the “Import XML” dataflow would then load each XML file into a SQL table.       Running this, it took approximately 1 second to load each file which seemed a massive amount of time to parse the XML and load the data, speaking to my colleague Martin Croft, he suggested the use of T-SQL Bulk Insert and OpenRowset, so we adjusted the package as followed:     The same foreach container was used but instead the following SQL command was executed (this is an expression):     "INSERT INTO MyTable(FileDate) SELECT   CAST(bulkcolumn AS XML)     FROM OPENROWSET(         BULK         '" + @[User::CurrentFile]  + "',         SINGLE_BLOB ) AS x"     Using this method we managed to load approximately 20 records per second, much faster…for data loading! For what we wanted to achieve this was perfect but I’ll leave you with the following points when making your own decision on which solution you decide to choose!      Openrowset Method Much faster to get the data into SQL You’ll need to parse or create a view over the XML data to allow the data to be more usable(another post on this!) Not able to apply validation/transformation against the data when loading it The SQL Server service account will need permission to the file No schema validation when loading files SSIS Slower (in our case) Schema validation Allows you to apply transformations/joins to the data Permissions should be less of a problem Data can be loaded into the final form through the package When using a schema validation errors can fail the package (I’ll do another post on this)

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  • Book Review (Book 10) - The Information: A History, a Theory, a Flood

    - by BuckWoody
    This is a continuation of the books I challenged myself to read to help my career - one a month, for year. You can read my first book review here, and the entire list is here. The book I chose for March 2012 was: The Information: A History, a Theory, a Flood by James Gleick. I was traveling at the end of last month so I’m a bit late posting this review here. Why I chose this book: My personal belief about computing is this: All computing technology is simply re-arranging data. We take data in, we manipulate it, and we send it back out. That’s computing. I had heard from some folks about this book and it’s treatment of data. I heard that it dealt with the basics of data - and the semantics of data, information and so on. It also deals with the earliest forms of history of information, which fascinates me. It’s similar I was told, to GEB which a favorite book of mine as well, so that was a bonus. Some folks I talked to liked it, some didn’t - so I thought I would check it out. What I learned: I liked the book. It was longer than I thought - took quite a while to read, even though I tend to read quickly. This is the kind of book you take your time with. It does in fact deal with the earliest forms of human interaction and the basics of data. I learned, for instance, that the genesis of the binary communication system is based in the invention of telegraph (far-writing) codes, and that the earliest forms of communication were expensive. In fact, many ciphers were invented not to hide military secrets, but to compress information. A sort of early “lol-speak” to keep the cost of transmitting data low! I think the comparison with GEB is a bit over-reaching. GEB is far more specific, fanciful and so on. In fact, this book felt more like something fro Richard Dawkins, and tended to wander around the subject quite a bit. I imagine the author doing his research and writing each chapter as a book that followed on from the last one. This is what possibly bothered those who tended not to like it, I think. Towards the middle of the book, I think the author tended to be a bit too fragmented even for me. He began to delve into memes, biology and more - I think he might have been better off breaking that off into another work. The existentialism just seemed jarring. All in all, I liked the book. I recommend it to any technical professional, specifically ones involved with data technology in specific. And isn’t that all of us? :)

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  • How one decision can turn web services to hell

    - by DigiMortal
    In this posting I will show you how one stupid decision may turn developers life to hell. There is a project where bunch of complex applications exchange data frequently and it is very hard to change something without additional expenses. Well, one analyst thought that string is silver bullet of web services. Read what happened. Bad bad mistake In the early stages of integration project there was analyst who also established architecture and technical design for web services. There was one very bad mistake this analyst made: All data must be converted to strings before exchange! Yes, that’s correct, this was the requirement. All integers, decimals and dates are coming in and going out as strings. There was also explanation for this requirement: This way we can avoid data type conversion errors! Well, this guy works somewhere else already and I hope he works in some burger restaurant – far away from computers. Consequences If you first look at this requirement it may seem like little annoying piece of crap you can easily survive. But let’s see the real consequences one stupid decision can cause: hell load of data conversions are done by receiving applications and SSIS packages, SSIS packages are not error prone and they depend heavily on strings they get from different services, there are more than one format per type that is used in different services, for larger amounts of data all these conversion tasks slow down the work of integration packages, practically all developers have been in hurry with some SSIS import tasks and some fields that are not used in different calculations in SSAS cube are imported without data conversions (by example, some prices are strings in format “1.021 $”). The most painful problem for developers is the part of data conversions because they don’t expect that there is such a stupid requirement stated and therefore they are not able to estimate the time their tasks take on these web services. Also developers must be prepared for cases when suddenly some service sends data that is not in acceptable format and they must solve the problems ASAP. This puts unexpected load on developers and they are not very happy with it because they can’t understand why they have to live with this horror if it is possible to fix. What to do if you see something like this? Well, explain the problem to customer and demand special tasks to project schedule to get this mess solved before going on with new developments. It is cheaper to solve the problems now that later.

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  • I have an apache process that takes 98% CPU. How can I find what apache call it runs?

    - by Nir
    As you can see below, a single Apache process hangs and takes large amount of CPU resources. How can I find what http call this apache process runs? PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 12554 www-data 20 0 776m 285m 199m R 97 3.7 67:15.84 apache2 14580 www-data 20 0 748m 372m 314m S 4 4.8 0:13.60 apache2 12561 www-data 20 0 784m 416m 322m S 3 5.4 0:58.10 apache2 12592 www-data 20 0 785m 427m 332m S 2 5.6 0:57.06 apache2

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  • Database Security Events in April

    - by Troy Kitch
    Wed, Apr 18, Executive Oracle Database Security Round Table - Tampa, FL Tue, Apr 24, ISC(2) Leadership Regional Event Series - San Diego, CA April 24 - May 17,  Independent Oracle Users Group Enterprise Data at Risk Seminar Series Tue, Apr 24 IOUG Enterprise Data at Risk Seminar Series - Toronto Wed, Apr 25 IOUG Enterprise Data at Risk Seminar Series - New York Thu, Apr 26 IOUG Enterprise Data at Risk Seminar Series - Boston Thu, Apr 26 ISC(2) Leadership Regional Event Series - San Jose, CA

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  • The SPARC SuperCluster

    - by Karoly Vegh
    Oracle has been providing a lead in the Engineered Systems business for quite a while now, in accordance with the motto "Hardware and Software Engineered to Work Together." Indeed it is hard to find a better definition of these systems.  Allow me to summarize the idea. It is:  Build a compute platform optimized to run your technologies Develop application aware, intelligently caching storage components Take an impressively fast network technology interconnecting it with the compute nodes Tune the application to scale with the nodes to yet unseen performance Reduce the amount of data moving via compression Provide this all in a pre-integrated single product with a single-pane management interface All these ideas have been around in IT for quite some time now. The real Oracle advantage is adding the last one to put these all together. Oracle has built quite a portfolio of Engineered Systems, to run its technologies - and run those like they never ran before. In this post I'll focus on one of them that serves as a consolidation demigod, a multi-purpose engineered system.  As you probably have guessed, I am talking about the SPARC SuperCluster. It has many great features inherited from its predecessors, and it adds several new ones. Allow me to pick out and elaborate about some of the most interesting ones from a technological point of view.  I. It is the SPARC SuperCluster T4-4. That is, as compute nodes, it includes SPARC T4-4 servers that we learned to appreciate and respect for their features: The SPARC T4 CPUs: Each CPU has 8 cores, each core runs 8 threads. The SPARC T4-4 servers have 4 sockets. That is, a single compute node can in parallel, simultaneously  execute 256 threads. Now, a full-rack SPARC SuperCluster has 4 of these servers on board. Remember the keyword demigod.  While retaining the forerunner SPARC T3's exceptional throughput, the SPARC T4 CPUs raise the bar with single performance too - a humble 5x better one than their ancestors.  actually, the SPARC T4 CPU cores run in both single-threaded and multi-threaded mode, and switch between these two on-the-fly, fulfilling not only single-threaded OR multi-threaded applications' needs, but even mixed requirements (like in database workloads!). Data security, anyone? Every SPARC T4 CPU core has a built-in encryption engine, that is, encryption algorithms cast into silicon.  A PCI controller right on the chip for customers who need I/O performance.  Built-in, no-cost Virtualization:  Oracle VM for SPARC (the former LDoms or Logical Domains) is not a server-emulation virtualization technology but rather a serverpartitioning one, the hypervisor runs in the server firmware, and all the VMs' HW resources (I/O, CPU, memory) are accessed natively, without performance overhead.  This enables customers to run a number of Solaris 10 and Solaris 11 VMs separated, independent of each other within a physical server II. For Database performance, it includes Exadata Storage Cells - one of the main reasons why the Exadata Database Machine performs at diabolic speed. What makes them important? They provide DB backend storage for your Oracle Databases to run on the SPARC SuperCluster, that is what they are built and tuned for DB performance.  These storage cells are SQL-aware.  That is, if a SPARC T4 database compute node executes a query, it doesn't simply request tons of raw datablocks from the storage, filters the received data, and throws away most of it where the statement doesn't apply, but provides the SQL query to the storage node too. The storage cell software speaks SQL, that is, it is able to prefilter and through that transfer only the relevant data. With this, the traffic between database nodes and storage cells is reduced immensely. Less I/O is a good thing - as they say, all the CPUs of the world do one thing just as fast as any other - and that is waiting for I/O.  They don't only pre-filter, but also provide data preprocessing features - e.g. if a DB-node requests an aggregate of data, they can calculate it, and handover only the results, not the whole set. Again, less data to transfer.  They support the magical HCC, (Hybrid Columnar Compression). That is, data can be stored in a precompressed form on the storage. Less data to transfer.  Of course one can't simply rely on disks for performance, there is Flash Storage included there for caching.  III. The low latency, high-speed backbone network: InfiniBand, that interconnects all the members with: Real High Speed: 40 Gbit/s. Full Duplex, of course. Oh, and a really low latency.  RDMA. Remote Direct Memory Access. This technology allows the DB nodes to do exactly that. Remotely, directly placing SQL commands into the Memory of the storage cells. Dodging all the network-stack bottlenecks, avoiding overhead, placing requests directly into the process queue.  You can also run IP over InfiniBand if you please - that's the way the compute nodes can communicate with each other.  IV. Including a general-purpose storage too: the ZFSSA, which is a unified storage, providing NAS and SAN access too, with the following features:  NFS over RDMA over InfiniBand. Nothing is faster network-filesystem-wise.  All the ZFS features onboard, hybrid storage pools, compression, deduplication, snapshot, replication, NFS and CIFS shares Storageheads in a HA-Cluster configuration providing availability of the data  DTrace Live Analytics in a web-based Administration UI Being a general purpose application data storage for your non-database applications running on the SPARC SuperCluster over whichever protocol they prefer, easily replicating, snapshotting, cloning data for them.  There's a lot of great technology included in Oracle's SPARC SuperCluster, we have talked its interior through. As for external scalability: you can start with a half- of full- rack SPARC SuperCluster, and scale out to several racks - that is, stacking not separate full-rack SPARC SuperClusters, but extending always one large instance of the size of several full-racks. Yes, over InfiniBand network. Add racks as you grow.  What technologies shall run on it? SPARC SuperCluster is a general purpose scaleout consolidation/cloud environment. You can run Oracle Databases with RAC scaling, or Oracle Weblogic (end enjoy the SPARC T4's advantages to run Java). Remember, Oracle technologies have been integrated with the Oracle Engineered Systems - this is the Oracle on Oracle advantage. But you can run other software environments such as SAP if you please too. Run any application that runs on Oracle Solaris 10 or Solaris 11. Separate them in Virtual Machines, or even Oracle Solaris Zones, monitor and manage those from a central UI. Here the key takeaways once again: The SPARC SuperCluster: Is a pre-integrated Engineered System Contains SPARC T4-4 servers with built-in virtualization, cryptography, dynamic threading Contains the Exadata storage cells that intelligently offload the burden of the DB-nodes  Contains a highly available ZFS Storage Appliance, that provides SAN/NAS storage in a unified way Combines all these elements over a high-speed, low-latency backbone network implemented with InfiniBand Can grow from a single half-rack to several full-rack size Supports the consolidation of hundreds of applications To summarize: All these technologies are great by themselves, but the real value is like in every other Oracle Engineered System: Integration. All these technologies are tuned to perform together. Together they are way more than the sum of all - and a careful and actually very time consuming integration process is necessary to orchestrate all these for performance. The SPARC SuperCluster's goal is to enable infrastructure operations and offer a pre-integrated solution that can be architected and delivered in hours instead of months of evaluations and tests. The tedious and most importantly time and resource consuming part of the work - testing and evaluating - has been done.  Now go, provide services.   -- charlie  

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  • Hype and LINQ

    - by Tony Davis
    "Tired of querying in antiquated SQL?" I blinked in astonishment when I saw this headline on the LinqPad site. Warming to its theme, the site suggests that what we need is to "kiss goodbye to SSMS", and instead use LINQ, a modern query language! Elsewhere, there is an article entitled "Why LINQ beats SQL". The designers of LINQ, along with many DBAs, would, I'm sure, cringe with embarrassment at the suggestion that LINQ and SQL are, in any sense, competitive ways of doing the same thing. In fact what LINQ really is, at last, is an efficient, declarative language for C# and VB programmers to access or manipulate data in objects, local data stores, ORMs, web services, data repositories, and, yes, even relational databases. The fact is that LINQ is essentially declarative programming in a .NET language, and so in many ways encourages developers into a "SQL-like" mindset, even though they are not directly writing SQL. In place of imperative logic and loops, it uses various expressions, operators and declarative logic to build up an "expression tree" describing only what data is required, not the operations to be performed to get it. This expression tree is then parsed by the language compiler, and the result, when used against a relational database, is a SQL string that, while perhaps not always perfect, is often correctly parameterized and certainly no less "optimal" than what is achieved when a developer applies blunt, imperative logic to the SQL language. From a developer standpoint, it is a mistake to consider LINQ simply as a substitute means of querying SQL Server. The strength of LINQ is that that can be used to access any data source, for which a LINQ provider exists. Microsoft supplies built-in providers to access not just SQL Server, but also XML documents, .NET objects, ADO.NET datasets, and Entity Framework elements. LINQ-to-Objects is particularly interesting in that it allows a declarative means to access and manipulate arrays, collections and so on. Furthermore, as Michael Sorens points out in his excellent article on LINQ, there a whole host of third-party LINQ providers, that offers a simple way to get at data in Excel, Google, Flickr and much more, without having to learn a new interface or language. Of course, the need to be generic enough to deal with a range of data sources, from something as mundane as a text file to as esoteric as a relational database, means that LINQ is a compromise and so has inherent limitations. However, it is a powerful and beautifully compact language and one that, at least in its "query syntax" guise, is accessible to developers and DBAs alike. Perhaps there is still hope that LINQ can fulfill Phil Factor's lobster-induced fantasy of a language that will allow us to "treat all data objects, whether Word files, Excel files, XML, relational databases, text files, HTML files, registry files, LDAPs, Outlook and so on, in the same logical way, as linked databases, and extract the metadata, create the entities and relationships in the same way, and use the same SQL syntax to interrogate, create, read, write and update them." Cheers, Tony.

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  • Characteristics of a Web service that promote reusability and change

    Characteristics of a Web service that promote reusability and change:  Standardized Data Exchange Formats (XML, JSON) Standardized communication protocols (Soap, Rest) Promotes Loosely Coupled Systems  Standardized Data Exchange Formats (XML, JSON) XML W3.org defines Extensible Markup Language (XML) as a simplistic text format derived from SGML. XML was designed to solve challenges found in large-scale electronic publishing. In addition,  XML is playing an important role in the exchange of data primarily focusing on data exchange on the web. JSON JavaScript Object Notation (JSON) is a human-readable text-based standard designed for data interchange. This format is used for serializing and transmitting data over a network connection in a structured format. The primary use of JSON is to transmit data between a server and web application. JSON is an alternative to XML. Standardized communication protocols (Soap, Rest) Soap W3Scools.com defines SOAP as a simple XML-based protocol. This protocol lets applications exchange data over HTTP.  SOAP provides a way to communicate between applications running on different operating systems, with different technologies and programming languages. Rest In 2007, Stefan Tilkov defines Representational State Transfer (REST) as a set of principles that outlines how Web standards are supposed to be used.  Using REST in an application will ensure that it exploits the Web’s architecture to its benefit. Promotes Loosely Coupled Systems “Loose coupling as an approach to interconnecting the components in a system or network so that those components, also called elements, depend on each other to the least extent practicable. Coupling refers to the degree of direct knowledge that one element has of another.” (TechTarget.com, 2007) “Loosely coupled system can be easily broken down into definable elements. The extent of coupling in a system can be measured by mapping the maximum number of element changes that can occur without adverse effects. Examples of such changes include adding elements, removing elements, renaming elements, reconfiguring elements, modifying internal element characteristics and rearranging the way in which elements are interconnected.” (TechTarget.com, 2007) References: W3C. (2011). Extensible Markup Language (XML). Retrieved from W3.org: http://www.w3.org/XML/ W3Scools.com. (2011). SOAP Introduction. Retrieved from W3Scools.com: http://www.w3schools.com/soap/soap_intro.asp Tilkov, Stefan. (2007). A Brief Introduction to REST. Retrieved from Infoq.com: http://www.infoq.com/articles/rest-introduction TechTarget.com. (2011). loose coupling. Retrieved from TechTarget.com: http://searchnetworking.techtarget.com/definition/loose-coupling

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  • PHP may be executing as a "privileged" group and user, which could be a serious security vulnerability

    - by Martin
    I ran some security tests on a Ubuntu 12.04 Server, and I've got these warnings : PHP may be executing as a "privileged" group, which could be a serious security vulnerability. PHP may be executing as a "privileged" user, which could be a serious security vulnerability. In /etc/apache2/envvars, I have this: export APACHE_RUN_USER=www-data export APACHE_RUN_GROUP=www-data And all files in /var/www are having these user/group: www-data:www-data Am I setting this correctly? What should I do to fix this problem?

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  • Azure Diagnostics: The Bad, The Ugly, and a Better Way

    - by jasont
    If you’re a .Net web developer today, no doubt you’ve enjoyed watching Windows Azure grow up over the past couple of years. The platform has scaled, stabilized (mostly), and added on a slew of great (and sometimes overdue) features. What was once just an endpoint to host a solution, developers today have tremendous flexibility and options in the platform. Organizations are building new solutions and offerings on the platform, and others have, or are in the process of, migrating existing applications out of their own data centers into the Azure cloud. Whether new application development or migrating legacy, every development shop and IT organization needs to monitor their applications in the cloud, the same as they do on premises. Azure Diagnostics has some capabilities, but what I constantly hear from users is that it’s either (a) not enough, or (b) too cumbersome to set up. Today, Stackify is happy to announce that we fully support Azure deployments, just the same as your on-premises deployments. Let’s take a look below and compare and contrast the options. Azure Diagnostics Let’s crack open the Windows Azure documentation on Azure Diagnostics and see just how easy it is to use. The high level steps are:   Step 1: Import the Diagnostics Oh, I’ve already deployed my app without the diagnostics module. Guess I can’t do anything until I do this and re-deploy. Step 2: Configure the Diagnostics (and multiple sub-steps) Do I want it all? Or just pieces of it? Whoops, forgot to include a specific performance counter, I guess I’ll have to deploy again. Wait a minute… I have to specifically code these performance counters into my role’s OnStart() method, compile and deploy again? And query and consume it myself? Step 3: (Optional) Permanently store diagnostic data Lucky for me, Azure storage has gotten pretty cheap. But how often should I move the data into storage? I want to see real-time data, so I guess that’s out now as well. Step 4: (Optional) View stored diagnostic data Optional? Of course I want to see it. Conveniently, Microsoft recommends 3 tools to do this with. Un-conveniently, none of these are web based and they all just give you access to raw data, and very little charting or real-time intelligence. Just….. data. Nevermind that one product seems to have gotten stale since a recent acquisition, and doesn’t even have screenshots!   So, let’s summarize: lots of diagnostics data is available, but think realistically. Think Dev Ops. What happens when you are in the middle of a major production performance issue and you don’t have the diagnostics you need? You are redeploying an application (and thankfully you have a great branching strategy, so you feel perfectly safe just willy-nilly launching code into prod, don’t you?) to get data, then shipping it to storage, and then digging through that data to find a needle in a haystack. Would you like to be able to troubleshoot a performance issue in the middle of the night, or on a weekend, from your iPad or home computer’s web browser? Forget it: the best you get is this spark line in the Azure portal. If it’s real pointy, you probably have an issue; but since there is no alert based on a threshold your customers have likely already let you know. And high CPU, Memory, I/O, or Network doesn’t tell you anything about where the problem is. The Better Way – Stackify Stackify supports application and server monitoring in real time, all through a great web interface. All of the things that Azure Diagnostics provides, Stackify provides for your on-premises deployments, and you don’t need to know ahead of time that you’ll need it. It’s always there, it’s always on. Azure deployments are essentially no different than on-premises. It’s a Windows Server (or Linux) in the cloud. It’s behind a different firewall than your corporate servers. That’s it. Stackify can provide the same powerful tools to your Azure deployments in two simple steps. Step 1 Add a startup task to your web or worker role and deploy. If you can’t deploy and need it right now, no worries! Remote Desktop to the Azure instance and you can execute a Powershell script to download / install Stackify.   Step 2 Log in to your account at www.stackify.com and begin monitoring as much as you want, as often as you want and see the results instantly. WMI? It’s there Event Viewer? You’ve got it. File System Access? Yes, please! Would love to make sure my web.config is correct.   IIS / App Pool Info? Yep. You can even restart it. Running Services? All of them. Start and Stop them to your heart’s content. SQL Database access? You bet’cha. Alerts and Notification? Of course! You should know before your customers let you know. … and so much more.   Conclusion Microsoft has shown, consistently, that they love developers, developers, developers. What every developer needs to realize from this is that they’ve given you a canvas, which is exactly what Azure is. It’s great infrastructure that is readily available, easy to manage, and fairly cost effective. However, the tooling is your responsibility. What you get, at best, is bare bones. App and server diagnostics should be available when you need them. While we, as developers, try to plan for and think of everything ahead of time, there will come times where we need to get data that just isn’t available. And having to go through a lot of cumbersome steps to get that data, and then have to find a friendlier way to consume it…. well, that just doesn’t make a lot of sense to me. I’d rather spend my time writing and developing features and completing bug fixes for my applications, than to be writing code to monitor and diagnose.

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  • Is it important for reflection-based serialization maintain consistent field ordering?

    - by Matchlighter
    I just finished writing a packet builder that dynamically loads data into a data stream for eventual network transmission. Each builder operates by finding fields in a given class (and its superclasses) that are marked with a @data annotation. When I finishing my implementation, I remembered that getFields() does not return results in any specific order. Should reflection-based methods for serializing arbitrary data (like my packets) attempt to preserve a specific field ordering (such as alphabetical), and if so, how?

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  • The need for user-defined index types

    - by Greg Low
    Since the removal of the 8KB limit on serialization, the ability to define new data types using SQL CLR integration is now almost at a usable level, apart from one key omission: indexes. We have no ability to create our own types of index to support our data types. As a good example of this, consider that when Microsoft introduced the geometry and geography (spatial) data types, they did so as system CLR data types but also needed to introduce a spatial index as a new type of index. Those of us that...(read more)

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  • Isn't MVC anti OOP?

    - by m3th0dman
    The main idea behind OOP is to unify data and behavior in a single entity - the object. In procedural programming there is data and separately algorithms modifying the data. In the Model-View-Controller pattern the data and the logic/algorithms are placed in distinct entities, the model and the controller respectively. In an equivalent OOP approach shouldn't the model and the controller be placed in the same logical entity?

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  • logrotate isn't rotating a particular log file (and i think it should be)

    - by Max Williams
    Hi all. For a particular app, i have log files in two places. One of the places has just one log file that i want to use with logrotate, for the other location i want to use logrotate on all log files in that folder. I've set up an entry called millionaire-staging in /etc/logrotate.d and have been testing it by calling logrotate -f millionaire-staging. Here's my entry: #/etc/logrotate.d/millionaire-staging compress rotate 1000 dateext missingok sharedscripts copytruncate /var/www/apps/test.millionaire/log/staging.log { weekly } /var/www/apps/test.millionaire/shared/log/*log { size 40M } So, for the first folder, i want to rotate weekly (this seems to have worked fine). For the other, i want to rotate only when the log files get bigger than 40 meg. When i look in that folder (using the same locator as in the logrotate config), i can see a file in there that's 54M and which hasn't been rotated: $ ls -lh /var/www/apps/test.millionaire/shared/log/*log -rw-r--r-- 1 www-data root 33M 2010-12-29 15:00 /var/www/apps/test.millionaire/shared/log/test.millionaire.charanga.com.access-log -rw-r--r-- 1 www-data root 54M 2010-09-10 16:57 /var/www/apps/test.millionaire/shared/log/test.millionaire.charanga.com.debug-log -rw-r--r-- 1 www-data root 53K 2010-12-14 15:48 /var/www/apps/test.millionaire/shared/log/test.millionaire.charanga.com.error-log -rw-r--r-- 1 www-data root 3.8M 2010-12-29 14:30 /var/www/apps/test.millionaire/shared/log/test.millionaire.charanga.com.ssl.access-log -rw-r--r-- 1 www-data root 16K 2010-12-17 15:00 /var/www/apps/test.millionaire/shared/log/test.millionaire.charanga.com.ssl.error-log -rw-r--r-- 1 deploy deploy 0 2010-12-29 14:49 /var/www/apps/test.millionaire/shared/log/unicorn.stderr.log -rw-r--r-- 1 deploy deploy 0 2010-12-29 14:49 /var/www/apps/test.millionaire/shared/log/unicorn.stdout.log Some of the other log files in that folder have been rotated though: $ ls -lh /var/www/apps/test.millionaire/shared/log total 91M -rw-r--r-- 1 www-data root 33M 2010-12-29 15:05 test.millionaire.charanga.com.access-log -rw-r--r-- 1 www-data root 54M 2010-09-10 16:57 test.millionaire.charanga.com.debug-log -rw-r--r-- 1 www-data root 53K 2010-12-14 15:48 test.millionaire.charanga.com.error-log -rw-r--r-- 1 www-data root 3.8M 2010-12-29 14:30 test.millionaire.charanga.com.ssl.access-log -rw-r--r-- 1 www-data root 16K 2010-12-17 15:00 test.millionaire.charanga.com.ssl.error-log -rw-r--r-- 1 deploy deploy 0 2010-12-29 14:49 unicorn.stderr.log -rw-r--r-- 1 deploy deploy 41K 2010-12-29 11:03 unicorn.stderr.log-20101229.gz -rw-r--r-- 1 deploy deploy 0 2010-12-29 14:49 unicorn.stdout.log -rw-r--r-- 1 deploy deploy 1.1K 2010-10-15 11:05 unicorn.stdout.log-20101229.gz I think what might have happened is that i first ran this config with a pattern matching *.log, and that means it only rotated the two files that ended in .log (as opposed to -log). Then, when i changed the config and ran it again, it won't do any more since it think's its already had its weekly run, or something. Can anyone see what i'm doing wrong? Is it to do with those top folders being owned by root rather than deploy do you think? thanks, max

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  • logrotate isn't rotating a particular log file (and i think it should be)

    - by Max Williams
    Hi all. For a particular app, i have log files in two places. One of the places has just one log file that i want to use with logrotate, for the other location i want to use logrotate on all log files in that folder. I've set up an entry called millionaire-staging in /etc/logrotate.d and have been testing it by calling logrotate -f millionaire-staging. Here's my entry: #/etc/logrotate.d/millionaire-staging compress rotate 1000 dateext missingok sharedscripts copytruncate /var/www/apps/test.millionaire/log/staging.log { weekly } /var/www/apps/test.millionaire/shared/log/*log { size 40M } So, for the first folder, i want to rotate weekly (this seems to have worked fine). For the other, i want to rotate only when the log files get bigger than 40 meg. When i look in that folder (using the same locator as in the logrotate config), i can see a file in there that's 54M and which hasn't been rotated: $ ls -lh /var/www/apps/test.millionaire/shared/log/*log -rw-r--r-- 1 www-data root 33M 2010-12-29 15:00 /var/www/apps/test.millionaire/shared/log/test.millionaire.charanga.com.access-log -rw-r--r-- 1 www-data root 54M 2010-09-10 16:57 /var/www/apps/test.millionaire/shared/log/test.millionaire.charanga.com.debug-log -rw-r--r-- 1 www-data root 53K 2010-12-14 15:48 /var/www/apps/test.millionaire/shared/log/test.millionaire.charanga.com.error-log -rw-r--r-- 1 www-data root 3.8M 2010-12-29 14:30 /var/www/apps/test.millionaire/shared/log/test.millionaire.charanga.com.ssl.access-log -rw-r--r-- 1 www-data root 16K 2010-12-17 15:00 /var/www/apps/test.millionaire/shared/log/test.millionaire.charanga.com.ssl.error-log -rw-r--r-- 1 deploy deploy 0 2010-12-29 14:49 /var/www/apps/test.millionaire/shared/log/unicorn.stderr.log -rw-r--r-- 1 deploy deploy 0 2010-12-29 14:49 /var/www/apps/test.millionaire/shared/log/unicorn.stdout.log Some of the other log files in that folder have been rotated though: $ ls -lh /var/www/apps/test.millionaire/shared/log total 91M -rw-r--r-- 1 www-data root 33M 2010-12-29 15:05 test.millionaire.charanga.com.access-log -rw-r--r-- 1 www-data root 54M 2010-09-10 16:57 test.millionaire.charanga.com.debug-log -rw-r--r-- 1 www-data root 53K 2010-12-14 15:48 test.millionaire.charanga.com.error-log -rw-r--r-- 1 www-data root 3.8M 2010-12-29 14:30 test.millionaire.charanga.com.ssl.access-log -rw-r--r-- 1 www-data root 16K 2010-12-17 15:00 test.millionaire.charanga.com.ssl.error-log -rw-r--r-- 1 deploy deploy 0 2010-12-29 14:49 unicorn.stderr.log -rw-r--r-- 1 deploy deploy 41K 2010-12-29 11:03 unicorn.stderr.log-20101229.gz -rw-r--r-- 1 deploy deploy 0 2010-12-29 14:49 unicorn.stdout.log -rw-r--r-- 1 deploy deploy 1.1K 2010-10-15 11:05 unicorn.stdout.log-20101229.gz I think what might have happened is that i first ran this config with a pattern matching *.log, and that means it only rotated the two files that ended in .log (as opposed to -log). Then, when i changed the config and ran it again, it won't do any more since it think's its already had its weekly run, or something. Can anyone see what i'm doing wrong? Is it to do with those top folders being owned by root rather than deploy do you think? thanks, max

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  • SQL Server Developer Tools &ndash; Codename Juneau vs. Red-Gate SQL Source Control

    - by Ajarn Mark Caldwell
    So how do the new SQL Server Developer Tools (previously code-named Juneau) stack up against SQL Source Control?  Read on to find out. At the PASS Community Summit a couple of weeks ago, it was announced that the previously code-named Juneau software would be released under the name of SQL Server Developer Tools with the release of SQL Server 2012.  This replacement for Database Projects in Visual Studio (also known in a former life as Data Dude) has some great new features.  I won’t attempt to describe them all here, but I will applaud Microsoft for making major improvements.  One of my favorite changes is the way database elements are broken down.  Previously every little thing was in its own file.  For example, indexes were each in their own file.  I always hated that.  Now, SSDT uses a pattern similar to Red-Gate’s and puts the indexes and keys into the same file as the overall table definition. Of course there are really cool features to keep your database model in sync with the actual source scripts, and the rename refactoring feature is now touted as being more than just a search and replace, but rather a “semantic-aware” search and replace.  Funny, it reminds me of SQL Prompt’s Smart Rename feature.  But I’m not writing this just to criticize Microsoft and argue that they are late to the party with this feature set.  Instead, I do see it as a viable alternative for folks who want all of their source code to be version controlled, but there are a couple of key trade-offs that you need to know about when you choose which tool set to use. First, the basics Both tool sets integrate with a wide variety of source control systems including the most popular: Subversion, GIT, Vault, and Team Foundation Server.  Both tools have integrated functionality to produce objects to upgrade your target database when you are ready (DACPACs in SSDT, integration with SQL Compare for SQL Source Control).  If you regularly live in Visual Studio or the Business Intelligence Development Studio (BIDS) then SSDT will likely be comfortable for you.  Like BIDS, SSDT is a Visual Studio Project Type that comes with SQL Server, and if you don’t already have Visual Studio installed, it will install the shell for you.  If you already have Visual Studio 2010 installed, then it will just add this as an available project type.  On the other hand, if you regularly live in SQL Server Management Studio (SSMS) then you will really enjoy the SQL Source Control integration from within SSMS.  Both tool sets store their database model in script files.  In SSDT, these are on your file system like other source files; in SQL Source Control, these are stored in the folder structure in your source control system, and you can always GET them to your file system if you want to browse them directly. For me, the key differentiating factors are 1) a single, unified check-in, and 2) migration scripts.  How you value those two features will likely make your decision for you. Unified Check-In If you do a continuous-integration (CI) style of development that triggers an automated build with unit testing on every check-in of source code, and you use Visual Studio for the rest of your development, then you will want to really consider SSDT.  Because it is just another project in Visual Studio, it can be added to your existing Solution, and you can then do a complete, or unified single check-in of all changes whether they are application or database changes.  This is simply not possible with SQL Source Control because it is in a different development tool (SSMS instead of Visual Studio) and there is no way to do one unified check-in between the two.  You CAN do really fast back-to-back check-ins, but there is the possibility that the automated build that is triggered from the first check-in will cause your unit tests to fail and the CI tool to report that you broke the build.  Of course, the automated build that is triggered from the second check-in which contains the “other half” of your changes should pass and so the amount of time that the build was broken may be very, very short, but if that is very, very important to you, then SQL Source Control just won’t work; you’ll have to use SSDT. Refactoring and Migrations If you work on a mature system, or on a not-so-mature but also not-so-well-designed system, where you want to refactor the database schema as you go along, but you can’t have data suddenly disappearing from your target system, then you’ll probably want to go with SQL Source Control.  As I wrote previously, there are a number of changes which you can make to your database that the comparison tools (both from Microsoft and Red Gate) simply cannot handle without the possibility (or probability) of data loss.  Currently, SSDT only offers you the ability to inject PRE and POST custom deployment scripts.  There is no way to insert your own script in the middle to override the default behavior of the tool.  In version 3.0 of SQL Source Control (Early Access version now available) you have that ability to create your own custom migration script to take the place of the commands that the tool would have done, and ensure the preservation of your data.  Or, even if the default tool behavior would have worked, but you simply know a better way then you can take control and do things your way instead of theirs. You Decide In the environment I work in, our automated builds are not triggered off of check-ins, but off of the clock (currently once per night) and so there is no point at which the automated build and unit tests will be triggered without having both sides of the development effort already checked-in.  Therefore having a unified check-in, while handy, is not critical for us.  As for migration scripts, these are critically important to us.  We do a lot of new development on systems that have already been in production for years, and it is not uncommon for us to need to do a refactoring of the database.  Because of the maturity of the existing system, that often involves data migrations or other additional SQL tasks that the comparison tools just can’t detect on their own.  Therefore, the ability to create a custom migration script to override the tool’s default behavior is very important to us.  And so, you can see why we will continue to use Red Gate SQL Source Control for the foreseeable future.

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  • laptop crashed: why?

    - by sds
    my linux (ubuntu 12.04) laptop crashed, and I am trying to figure out why. # last sds pts/4 :0 Tue Sep 4 10:01 still logged in sds pts/3 :0 Tue Sep 4 10:00 still logged in reboot system boot 3.2.0-29-generic Tue Sep 4 09:43 - 11:23 (01:40) sds pts/8 :0 Mon Sep 3 14:23 - crash (19:19) this seems to indicate a crash at 09:42 (= 14:23+19:19). as per another question, I looked at /var/log: auth.log: Sep 4 09:17:02 t520sds CRON[32744]: pam_unix(cron:session): session closed for user root Sep 4 09:43:17 t520sds lightdm: pam_unix(lightdm:session): session opened for user lightdm by (uid=0) no messages file syslog: Sep 4 09:24:19 t520sds kernel: [219104.819975] CPU0: Package power limit normal Sep 4 09:43:16 t520sds kernel: imklog 5.8.6, log source = /proc/kmsg started. kern.log: Sep 4 09:24:19 t520sds kernel: [219104.819969] CPU1: Package power limit normal Sep 4 09:24:19 t520sds kernel: [219104.819971] CPU2: Package power limit normal Sep 4 09:24:19 t520sds kernel: [219104.819974] CPU3: Package power limit normal Sep 4 09:24:19 t520sds kernel: [219104.819975] CPU0: Package power limit normal Sep 4 09:43:16 t520sds kernel: imklog 5.8.6, log source = /proc/kmsg started. Sep 4 09:43:16 t520sds kernel: [ 0.000000] Initializing cgroup subsys cpuset Sep 4 09:43:16 t520sds kernel: [ 0.000000] Initializing cgroup subsys cpu I had a computation running until 9:24, but the system crashed 18 minutes later! kern.log has many pages of these: Sep 4 09:43:16 t520sds kernel: [ 0.000000] total RAM covered: 8086M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 64K num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 128K num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 256K num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 512K num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 1M num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 2M num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 4M num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 8M num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 16M num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] *BAD*gran_size: 64K chunk_size: 32M num_reg: 10 lose cover RAM: -16M Sep 4 09:43:16 t520sds kernel: [ 0.000000] *BAD*gran_size: 64K chunk_size: 64M num_reg: 10 lose cover RAM: -16M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 128M num_reg: 10 lose cover RAM: 0G Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 256M num_reg: 10 lose cover RAM: 0G Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 512M num_reg: 10 lose cover RAM: 0G Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 1G num_reg: 10 lose cover RAM: 0G Sep 4 09:43:16 t520sds kernel: [ 0.000000] *BAD*gran_size: 64K chunk_size: 2G num_reg: 10 lose cover RAM: -1G does this mean that my RAM is bad?! it also says Sep 4 09:43:16 t520sds kernel: [ 2.944123] EXT4-fs (sda1): INFO: recovery required on readonly filesystem Sep 4 09:43:16 t520sds kernel: [ 2.944126] EXT4-fs (sda1): write access will be enabled during recovery Sep 4 09:43:16 t520sds kernel: [ 3.088001] firewire_core: created device fw0: GUID f0def1ff8fbd7dff, S400 Sep 4 09:43:16 t520sds kernel: [ 8.929243] EXT4-fs (sda1): orphan cleanup on readonly fs Sep 4 09:43:16 t520sds kernel: [ 8.929249] EXT4-fs (sda1): ext4_orphan_cleanup: deleting unreferenced inode 658984 ... Sep 4 09:43:16 t520sds kernel: [ 9.343266] EXT4-fs (sda1): ext4_orphan_cleanup: deleting unreferenced inode 525343 Sep 4 09:43:16 t520sds kernel: [ 9.343270] EXT4-fs (sda1): 56 orphan inodes deleted Sep 4 09:43:16 t520sds kernel: [ 9.343271] EXT4-fs (sda1): recovery complete Sep 4 09:43:16 t520sds kernel: [ 9.645799] EXT4-fs (sda1): mounted filesystem with ordered data mode. Opts: (null) does this mean my HD is bad? As per FaultyHardware, I tried smartctl -l selftest, which uncovered no errors: smartctl 5.41 2011-06-09 r3365 [x86_64-linux-3.2.0-30-generic] (local build) Copyright (C) 2002-11 by Bruce Allen, http://smartmontools.sourceforge.net === START OF INFORMATION SECTION === Model Family: Seagate Momentus 7200.4 Device Model: ST9500420AS Serial Number: 5VJE81YK LU WWN Device Id: 5 000c50 0440defe3 Firmware Version: 0003LVM1 User Capacity: 500,107,862,016 bytes [500 GB] Sector Size: 512 bytes logical/physical Device is: In smartctl database [for details use: -P show] ATA Version is: 8 ATA Standard is: ATA-8-ACS revision 4 Local Time is: Mon Sep 10 16:40:04 2012 EDT SMART support is: Available - device has SMART capability. SMART support is: Enabled === START OF READ SMART DATA SECTION === SMART overall-health self-assessment test result: PASSED See vendor-specific Attribute list for marginal Attributes. General SMART Values: Offline data collection status: (0x82) Offline data collection activity was completed without error. Auto Offline Data Collection: Enabled. Self-test execution status: ( 0) The previous self-test routine completed without error or no self-test has ever been run. Total time to complete Offline data collection: ( 0) seconds. Offline data collection capabilities: (0x7b) SMART execute Offline immediate. Auto Offline data collection on/off support. Suspend Offline collection upon new command. Offline surface scan supported. Self-test supported. Conveyance Self-test supported. Selective Self-test supported. SMART capabilities: (0x0003) Saves SMART data before entering power-saving mode. Supports SMART auto save timer. Error logging capability: (0x01) Error logging supported. General Purpose Logging supported. Short self-test routine recommended polling time: ( 1) minutes. Extended self-test routine recommended polling time: ( 109) minutes. Conveyance self-test routine recommended polling time: ( 2) minutes. SCT capabilities: (0x103b) SCT Status supported. SCT Error Recovery Control supported. SCT Feature Control supported. SCT Data Table supported. SMART Attributes Data Structure revision number: 10 Vendor Specific SMART Attributes with Thresholds: ID# ATTRIBUTE_NAME FLAG VALUE WORST THRESH TYPE UPDATED WHEN_FAILED RAW_VALUE 1 Raw_Read_Error_Rate 0x000f 117 099 034 Pre-fail Always - 162843537 3 Spin_Up_Time 0x0003 100 100 000 Pre-fail Always - 0 4 Start_Stop_Count 0x0032 100 100 020 Old_age Always - 571 5 Reallocated_Sector_Ct 0x0033 100 100 036 Pre-fail Always - 0 7 Seek_Error_Rate 0x000f 069 060 030 Pre-fail Always - 17210154023 9 Power_On_Hours 0x0032 095 095 000 Old_age Always - 174362787320258 10 Spin_Retry_Count 0x0013 100 100 097 Pre-fail Always - 0 12 Power_Cycle_Count 0x0032 100 100 020 Old_age Always - 571 184 End-to-End_Error 0x0032 100 100 099 Old_age Always - 0 187 Reported_Uncorrect 0x0032 100 100 000 Old_age Always - 0 188 Command_Timeout 0x0032 100 100 000 Old_age Always - 1 189 High_Fly_Writes 0x003a 100 100 000 Old_age Always - 0 190 Airflow_Temperature_Cel 0x0022 061 043 045 Old_age Always In_the_past 39 (0 11 44 26) 191 G-Sense_Error_Rate 0x0032 100 100 000 Old_age Always - 84 192 Power-Off_Retract_Count 0x0032 100 100 000 Old_age Always - 20 193 Load_Cycle_Count 0x0032 099 099 000 Old_age Always - 2434 194 Temperature_Celsius 0x0022 039 057 000 Old_age Always - 39 (0 15 0 0) 195 Hardware_ECC_Recovered 0x001a 041 041 000 Old_age Always - 162843537 196 Reallocated_Event_Count 0x000f 095 095 030 Pre-fail Always - 4540 (61955, 0) 197 Current_Pending_Sector 0x0012 100 100 000 Old_age Always - 0 198 Offline_Uncorrectable 0x0010 100 100 000 Old_age Offline - 0 199 UDMA_CRC_Error_Count 0x003e 200 200 000 Old_age Always - 0 254 Free_Fall_Sensor 0x0032 100 100 000 Old_age Always - 0 SMART Error Log Version: 1 No Errors Logged SMART Self-test log structure revision number 1 Num Test_Description Status Remaining LifeTime(hours) LBA_of_first_error # 1 Extended offline Completed without error 00% 4545 - SMART Selective self-test log data structure revision number 1 SPAN MIN_LBA MAX_LBA CURRENT_TEST_STATUS 1 0 0 Not_testing 2 0 0 Not_testing 3 0 0 Not_testing 4 0 0 Not_testing 5 0 0 Not_testing Selective self-test flags (0x0): After scanning selected spans, do NOT read-scan remainder of disk. If Selective self-test is pending on power-up, resume after 0 minute delay. Googling for the messages proved inconclusive, I can't even figure out whether the messages are routine or catastrophic. So, what do I do now?

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  • Building an MVC application using QuickBooks

    - by dataintegration
    RSSBus ADO.NET Providers can be used from many tools and IDEs. In this article we show how to connect to QuickBooks from an MVC3 project using the RSSBus ADO.NET Provider for QuickBooks. Although this example uses the QuickBooks Data Provider, the same process can be used with any of our ADO.NET Providers. Creating the Model Step 1: Download and install the QuickBooks Data Provider from RSSBus. Step 2: Create a new MVC3 project in Visual Studio. Add a data model to the Models folder using the ADO.NET Entity Data Model wizard. Step 3: Create a new RSSBus QuickBooks Data Source by clicking "New Connection", specify the connection string options, and click Next. Step 4: Select all the tables and views you need, and click Finish to create the data model. Step 5: Right click on the entity diagram and select 'Add Code Generation Item'. Choose the 'ADO.NET DbContext Generator'. Creating the Controller and the Views Step 6: Add a new controller to the Controllers folder. Give it a meaningful name, such as ReceivePaymentsController. Also, make sure the template selected is 'Controller with empty read/write actions'. Before adding new methods to the Controller, create views for your model. We will add the List, Create, and Delete views. Step 7: Right click on the Views folder and go to Add -> View. Here create a new view for each: List, Create, and Delete templates. Make sure to also associate your Model with the new views. Step 10: Now that the views are ready, go back and edit the RecievePayment controller. Update your code to handle the Index, Create, and Delete methods. Sample Project We are including a sample project that shows how to use the QuickBooks Data Provider in an MVC3 application. You may download the C# project here or download the VB.NET project here. You will also need to install the QuickBooks ADO.NET Data Provider to run the demo. You can download a free trial here. To use this demo, you will also need to modify the connection string in the 'web.config'.

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  • Function Folding in #PowerQuery

    - by Darren Gosbell
    Originally posted on: http://geekswithblogs.net/darrengosbell/archive/2014/05/16/function-folding-in-powerquery.aspxLooking at a typical Power Query query you will noticed that it's made up of a number of small steps. As an example take a look at the query I did in my previous post about joining a fact table to a slowly changing dimension. It was roughly built up of the following steps: Get all records from the fact table Get all records from the dimension table do an outer join between these two tables on the business key (resulting in an increase in the row count as there are multiple records in the dimension table for each business key) Filter out the excess rows introduced in step 3 remove extra columns that are not required in the final result set. If Power Query was to execute a query like this literally, following the same steps in the same order it would not be overly efficient. Particularly if your two source tables were quite large. However Power Query has a feature called function folding where it can take a number of these small steps and push them down to the data source. The degree of function folding that can be performed depends on the data source, As you might expect, relational data sources like SQL Server, Oracle and Teradata support folding, but so do some of the other sources like OData, Exchange and Active Directory. To explore how this works I took the data from my previous post and loaded it into a SQL database. Then I converted my Power Query expression to source it's data from that database. Below is the resulting Power Query which I edited by hand so that the whole thing can be shown in a single expression: let     SqlSource = Sql.Database("localhost", "PowerQueryTest"),     BU = SqlSource{[Schema="dbo",Item="BU"]}[Data],     Fact = SqlSource{[Schema="dbo",Item="fact"]}[Data],     Source = Table.NestedJoin(Fact,{"BU_Code"},BU,{"BU_Code"},"NewColumn"),     LeftJoin = Table.ExpandTableColumn(Source, "NewColumn"                                   , {"BU_Key", "StartDate", "EndDate"}                                   , {"BU_Key", "StartDate", "EndDate"}),     BetweenFilter = Table.SelectRows(LeftJoin, each (([Date] >= [StartDate]) and ([Date] <= [EndDate])) ),     RemovedColumns = Table.RemoveColumns(BetweenFilter,{"StartDate", "EndDate"}) in     RemovedColumns If the above query was run step by step in a literal fashion you would expect it to run two queries against the SQL database doing "SELECT * …" from both tables. However a profiler trace shows just the following single SQL query: select [_].[BU_Code],     [_].[Date],     [_].[Amount],     [_].[BU_Key] from (     select [$Outer].[BU_Code],         [$Outer].[Date],         [$Outer].[Amount],         [$Inner].[BU_Key],         [$Inner].[StartDate],         [$Inner].[EndDate]     from [dbo].[fact] as [$Outer]     left outer join     (         select [_].[BU_Key] as [BU_Key],             [_].[BU_Code] as [BU_Code2],             [_].[BU_Name] as [BU_Name],             [_].[StartDate] as [StartDate],             [_].[EndDate] as [EndDate]         from [dbo].[BU] as [_]     ) as [$Inner] on ([$Outer].[BU_Code] = [$Inner].[BU_Code2] or [$Outer].[BU_Code] is null and [$Inner].[BU_Code2] is null) ) as [_] where [_].[Date] >= [_].[StartDate] and [_].[Date] <= [_].[EndDate] The resulting query is a little strange, you can probably tell that it was generated programmatically. But if you look closely you'll notice that every single part of the Power Query formula has been pushed down to SQL Server. Power Query itself ends up just constructing the query and passing the results back to Excel, it does not do any of the data transformation steps itself. So now you can feel a bit more comfortable showing Power Query to your less technical Colleagues knowing that the tool will do it's best fold all the  small steps in Power Query down the most efficient query that it can against the source systems.

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  • Medical Devices which supports Direct access through Bluetooth Low Energy [on hold]

    - by Suganthan
    I have went through this link and came to know that we can directly interact with BLE devices to read and write data, so I just want to know some medical device which supports direct access to third-party application (we can directly access the data from the medical device data). Is their any devices which supports direct access to the data Note: I already went through medical devices like Withings and Fitbit

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  • parallel_for_each from amp.h – part 1

    - by Daniel Moth
    This posts assumes that you've read my other C++ AMP posts on index<N> and extent<N>, as well as about the restrict modifier. It also assumes you are familiar with C++ lambdas (if not, follow my links to C++ documentation). Basic structure and parameters Now we are ready for part 1 of the description of the new overload for the concurrency::parallel_for_each function. The basic new parallel_for_each method signature returns void and accepts two parameters: a grid<N> (think of it as an alias to extent) a restrict(direct3d) lambda, whose signature is such that it returns void and accepts an index of the same rank as the grid So it looks something like this (with generous returns for more palatable formatting) assuming we are dealing with a 2-dimensional space: // some_code_A parallel_for_each( g, // g is of type grid<2> [ ](index<2> idx) restrict(direct3d) { // kernel code } ); // some_code_B The parallel_for_each will execute the body of the lambda (which must have the restrict modifier), on the GPU. We also call the lambda body the "kernel". The kernel will be executed multiple times, once per scheduled GPU thread. The only difference in each execution is the value of the index object (aka as the GPU thread ID in this context) that gets passed to your kernel code. The number of GPU threads (and the values of each index) is determined by the grid object you pass, as described next. You know that grid is simply a wrapper on extent. In this context, one way to think about it is that the extent generates a number of index objects. So for the example above, if your grid was setup by some_code_A as follows: extent<2> e(2,3); grid<2> g(e); ...then given that: e.size()==6, e[0]==2, and e[1]=3 ...the six index<2> objects it generates (and hence the values that your lambda would receive) are:    (0,0) (1,0) (0,1) (1,1) (0,2) (1,2) So what the above means is that the lambda body with the algorithm that you wrote will get executed 6 times and the index<2> object you receive each time will have one of the values just listed above (of course, each one will only appear once, the order is indeterminate, and they are likely to call your code at the same exact time). Obviously, in real GPU programming, you'd typically be scheduling thousands if not millions of threads, not just 6. If you've been following along you should be thinking: "that is all fine and makes sense, but what can I do in the kernel since I passed nothing else meaningful to it, and it is not returning any values out to me?" Passing data in and out It is a good question, and in data parallel algorithms indeed you typically want to pass some data in, perform some operation, and then typically return some results out. The way you pass data into the kernel, is by capturing variables in the lambda (again, if you are not familiar with them, follow the links about C++ lambdas), and the way you use data after the kernel is done executing is simply by using those same variables. In the example above, the lambda was written in a fairly useless way with an empty capture list: [ ](index<2> idx) restrict(direct3d), where the empty square brackets means that no variables were captured. If instead I write it like this [&](index<2> idx) restrict(direct3d), then all variables in the some_code_A region are made available to the lambda by reference, but as soon as I try to use any of those variables in the lambda, I will receive a compiler error. This has to do with one of the direct3d restrictions, where only one type can be capture by reference: objects of the new concurrency::array class that I'll introduce in the next post (suffice for now to think of it as a container of data). If I write the lambda line like this [=](index<2> idx) restrict(direct3d), all variables in the some_code_A region are made available to the lambda by value. This works for some types (e.g. an integer), but not for all, as per the restrictions for direct3d. In particular, no useful data classes work except for one new type we introduce with C++ AMP: objects of the new concurrency::array_view class, that I'll introduce in the post after next. Also note that if you capture some variable by value, you could use it as input to your algorithm, but you wouldn’t be able to observe changes to it after the parallel_for_each call (e.g. in some_code_B region since it was passed by value) – the exception to this rule is the array_view since (as we'll see in a future post) it is a wrapper for data, not a container. Finally, for completeness, you can write your lambda, e.g. like this [av, &ar](index<2> idx) restrict(direct3d) where av is a variable of type array_view and ar is a variable of type array - the point being you can be very specific about what variables you capture and how. So it looks like from a large data perspective you can only capture array and array_view objects in the lambda (that is how you pass data to your kernel) and then use the many threads that call your code (each with a unique index) to perform some operation. You can also capture some limited types by value, as input only. When the last thread completes execution of your lambda, the data in the array_view or array are ready to be used in the some_code_B region. We'll talk more about all this in future posts… (a)synchronous Please note that the parallel_for_each executes as if synchronous to the calling code, but in reality, it is asynchronous. I.e. once the parallel_for_each call is made and the kernel has been passed to the runtime, the some_code_B region continues to execute immediately by the CPU thread, while in parallel the kernel is executed by the GPU threads. However, if you try to access the (array or array_view) data that you captured in the lambda in the some_code_B region, your code will block until the results become available. Hence the correct statement: the parallel_for_each is as-if synchronous in terms of visible side-effects, but asynchronous in reality.   That's all for now, we'll revisit the parallel_for_each description, once we introduce properly array and array_view – coming next. Comments about this post by Daniel Moth welcome at the original blog.

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  • How do I start the postgreSQL service upon boot?

    - by Homunculus Reticulli
    I am running PostgreSQL (v 8.4) on Ubuntu 10.0.4. The PG service currently starts on reboot (after I installed PG on my machine), however, I want the service to use a new data directory. Currently, after a reboot, I have to: Stop the currently running PG service manually type: /usr/local/pgsql/bin/pg_ctl start -D /my/preffered/data/directory -l /usr/local/pgsql/data/logfile Which file do I need to edit to ensure that I always have the service using the correct data folder?

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  • Pragmas and exceptions

    - by Darryl Gove
    The compiler pragmas: #pragma no_side_effect(routinename) #pragma does_not_write_global_data(routinename) #pragma does_not_read_global_data(routinename) are used to tell the compiler more about the routine being called, and enable it to do a better job of optimising around the routine. If a routine does not read global data, then global data does not need to be stored to memory before the call to the routine. If the routine does not write global data, then global data does not need to be reloaded after the call. The no side effect directive indicates that the routine does no I/O, does not read or write global data, and the result only depends on the input. However, these pragmas should not be used on routines that throw exceptions. The following example indicates the problem: #include <iostream extern "C" { int exceptional(int); #pragma no_side_effect(exceptional) } int exceptional(int a) { if (a==7) { throw 7; } else { return a+1; } } int a; int c=0; class myclass { public: int routine(); }; int myclass::routine() { for(a=0; a<1000; a++) { c=exceptional(c); } return 0; } int main() { myclass f; try { f.routine(); } catch(...) { std::cout << "Something happened" << a << c << std::endl; } } The routine "exceptional" is declared as having no side effects, however it can throw an exception. The no side effects directive enables the compiler to avoid storing global data back to memory, and retrieving it after the function call, so the loop containing the call to exceptional is quite tight: $ CC -O -S test.cpp ... .L77000061: /* 0x0014 38 */ call exceptional ! params = %o0 ! Result = %o0 /* 0x0018 36 */ add %i1,1,%i1 /* 0x001c */ cmp %i1,999 /* 0x0020 */ ble,pt %icc,.L77000061 /* 0x0024 */ nop However, when the program is run the result is incorrect: $ CC -O t.cpp $ ./a.out Something happend00 If the code had worked correctly, the output would have been "Something happened77" - the exception occurs on the seventh iteration. Yet, the current code produces a message that uses the original values for the variables 'a' and 'c'. The problem is that the exception handler reads global data, and due to the no side effects directive the compiler has not updated the global data before the function call. So these pragmas should not be used on routines that have the potential to throw exceptions.

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  • What types of objects are useful in SQL CLR?

    - by Greg Low
    I've had a number of people over the years ask about whether or not a particular type of object is a good candidate for SQL CLR integration. The rules that I normally apply are as follows: Database Object Transact-SQL Managed Code Scalar UDF Generally poor performance Good option when limited or no data-access Table-valued UDF Good option if data-related Good option when limited or no data-access Stored Procedure Good option Good option when external access is required or limited data access DML...(read more)

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