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  • Microsoft guarantees the performance of SQL Server

    - by simonsabin
    I have recently been informed that Microsoft will be guaranteeing the performance of SQL Server. Yes thats right Microsoft will guarantee that you will get better performance out of SQL Server that any other competitor system. However on the flip side there are also saying that end users also have to guarantee the performance of SQL Server if they want to use the next release of SQL Server targeted for 2011 or 2012. It appears that a recent recruit Mark Smith from Newcastle, England will be heading a new team that will be making sure you are running SQL Server on adequate hardware and making sure you are developing your applications according to best practices. The Performance Enforcement Team (SQLPET) will be a global group headed by mark that will oversee two other groups the existing Customer Advisory Team (SQLCAT) and another new team the Design and Operation Group (SQLDOG). Mark informed me that the team was originally thought out during Yukon and was going to be an independent body that went round to customers making sure they didn’t suffer performance problems. However it was felt that they needed to wait a few releases until SQL Server was really there. The original Yukon Independent Performance Enhancement Team (YIPET) has now become the SQL Performance Enforcement Team (SQLPET). When challenged about the change from enhancement to enforcement Mark was unwilling to comment. An anonymous source suggested that "..Microsoft is sick of the bad press SQL Server gets for performance when the performance problems are normally down to people developing applications badly and using inadequate hardware..." Its true that it is very easy to install and run SQL, unlike other RDMS systems and the flip side is that its also easy to get into performance problems due to under specified hardware and bad design. Its not yet confirmed if this enforcement will apply to all SKUs or just the high end ones. I would personally welcome some level of architectural and hardware advice service that clients would be able to turn to, in order to justify getting the appropriate hardware at the start of a project and not 1 year in when its often too late.

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  • Performance impact: What is the optimal payload for SqlBulkCopy.WriteToServer()?

    - by Linchi Shea
    For many years, I have been using a C# program to generate the TPC-C compliant data for testing. The program relies on the SqlBulkCopy class to load the data generated by the program into the SQL Server tables. In general, the performance of this C# data loader is satisfactory. Lately however, I found myself in a situation where I needed to generate a much larger amount of data than I typically do and the data needed to be loaded within a confined time frame. So I was driven to look into the code...(read more)

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  • SQL Rally Pre-Con: Data Warehouse Modeling – Making the Right Choices

    - by Davide Mauri
    As you may have already learned from my old post or Adam’s or Kalen’s posts, there will be two SQL Rally in North Europe. In the Stockholm SQL Rally, with my friend Thomas Kejser, I’ll be delivering a pre-con on Data Warehouse Modeling: Data warehouses play a central role in any BI solution. It's the back end upon which everything in years to come will be created. For this reason, it must be rock solid and yet flexible at the same time. To develop such a data warehouse, you must have a clear idea of its architecture, a thorough understanding of the concepts of Measures and Dimensions, and a proven engineered way to build it so that quality and stability can go hand-in-hand with cost reduction and scalability. In this workshop, Thomas Kejser and Davide Mauri will share all the information they learned since they started working with data warehouses, giving you the guidance and tips you need to start your BI project in the best way possible?avoiding errors, making implementation effective and efficient, paving the way for a winning Agile approach, and helping you define how your team should work so that your BI solution will stand the test of time. You'll learn: Data warehouse architecture and justification Agile methodology Dimensional modeling, including Kimball vs. Inmon, SCD1/SCD2/SCD3, Junk and Degenerate Dimensions, and Huge Dimensions Best practices, naming conventions, and lessons learned Loading the data warehouse, including loading Dimensions, loading Facts (Full Load, Incremental Load, Partitioned Load) Data warehouses and Big Data (Hadoop) Unit testing Tracking historical changes and managing large sizes With all the Self-Service BI hype, Data Warehouse is become more and more central every day, since if everyone will be able to analyze data using self-service tools, it’s better for him/her to rely on correct, uniform and coherent data. Already 50 people registered from the workshop and seats are limited so don’t miss this unique opportunity to attend to this workshop that is really a unique combination of years and years of experience! http://www.sqlpass.org/sqlrally/2013/nordic/Agenda/PreconferenceSeminars.aspx See you there!

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  • Oracle Financial Analytics for SAP Certified with Oracle Data Integrator EE

    - by denis.gray
    Two days ago Oracle announced the release of Oracle Financial Analytics for SAP.  With the amount of press this has garnered in the past two days, there's a key detail that can't be missed.  This release is certified with Oracle Data Integrator EE - now making the combination of Data Integration and Business Intelligence a force to contend with.  Within the Oracle Press Release there were two important bullets: ·         Oracle Financial Analytics for SAP includes a pre-packaged ABAP code compliant adapter and is certified with Oracle Data Integrator Enterprise Edition to integrate SAP Financial Accounting data directly with the analytic application.  ·         Helping to integrate SAP financial data and disparate third-party data sources is Oracle Data Integrator Enterprise Edition which delivers fast, efficient loading and transformation of timely data into a data warehouse environment through its high-performance Extract Load and Transform (E-LT) technology. This is very exciting news, demonstrating Oracle's overall commitment to Oracle Data Integrator EE.   This is a great way to start off the new year and we look forward to building on this momentum throughout 2011.   The following links contain additional information and media responses about the Oracle Financial Analytics for SAP release. IDG News Service (Also appeared in PC World, Computer World, CIO: "Oracle is moving further into rival SAP's turf with Oracle Financial Analytics for SAP, a new BI (business intelligence) application that can crunch ERP (enterprise resource planning) system financial data for insights." Information Week: "Oracle talks a good game about the appeal of an optimized, all-Oracle stack. But the company also recognizes that we live in a predominantly heterogeneous IT world" CRN: "While some businesses with SAP Financial Accounting already use Oracle BI, those integrations had to be custom developed. The new offering provides pre-built integration capabilities." ECRM Guide:  "Among other features, Oracle Financial Analytics for SAP helps front-line managers improve financial performance and decision-making with what the company says is comprehensive, timely and role-based information on their departments' expenses and revenue contributions."   SAP Getting Started Guide for ODI on OTN: http://www.oracle.com/technetwork/middleware/data-integrator/learnmore/index.html For more information on the ODI and its SAP connectivity please review the Oracle® Fusion Middleware Application Adapters Guide for Oracle Data Integrator11g Release 1 (11.1.1)

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  • Improving VPN performance - stronger encryption = more performance?

    - by Seth
    I have a site-to-site VPN set up with two SonicWall's (a TZ170 and a Pro1260). It was suggested to me that turning off encryption (so the VPN is tunneling only) would improve performance. (I'm not concerned with security, because the VPN is running over a trusted line.) Using FTP and HTTP transfers, I measured my baseline performance at about 130±10 kB/s. The Ipsec (Phase 2) Encryption was set to 3DES, so I set it to "none". However, the effect was opposite -- the performance dropped to 60±30 kB/s, and the transfers stall for about 25 seconds before any data comes down the line. I tried AES-128 and the throughput went UP to 160±5 kB/s. The rated speed of my line is 193 kB/s (it's a T1). Contrary to what I would think, stronger Ipsec encryption seems to improve throughput. Can anyone explain what might be going on here? Why would no encryption cause poor and highly variable performance, and cause transfers to stall? Why does AES-128 improve performance?

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  • Request bursting from web application Load Tests

    - by MaseBase
    I'm migrating our web and database hosting to a new environment on all new machines. I've recently performed a Load Test using WAPT to generate load from multiple distributed clients. The server has plenty of room to handle the traffic load, but I'm seeing an odd pattern of incoming traffic during the load tests. Here is the gist of our setup: Firewall server running MS Forefront TMG 2010 on Win 2k8 server Request routing done by IIS Application Request Routing on firewall machine Web server is a Hyper-V VM on the Database server (which is the host OS) These machines are hefty with dual-CPU's with six cores (12 total procs) Web server running IIS 7.5 Web applications built in ASP.NET 2.0, with 1 ISAPI filter (Url Rewrite) in front What I'm seeing during the load tests is that the requests all come through in bursts. Even though I have 7 different distributed clients sending traffic loads, the requests come through about 300-500 requests at a time. The performance monitor shows nearly all of the counters moving through this pattern, where a burst of requests comes in the req/sec jumps to 70, the queued requests jumps to 500, the current requests jumps up, the CPU jumps up, everything. Then once it's handled that group of requests, it has a lull for nearly 10 seconds where nearly nothing is happening. 0-5 req/sec, 0 queued requests, minimal CPU usage. Then after 10 seconds of inactivity, another burst comes through, spiking all of the counters once again. What I can't figure out is why the requests are coming through in bursts when I know that the load being generated is not sent that way, especially considering the various load-generating clients sending traffic all in different intervals with random think time's between each request. Is there something in the layers between Hyper-V or perhaps in the hardware which might cause this coalesce of requests together? Here is what i'm looking at, the highlighted metric is Requests/sec, but the others critical counter go with it: Requests Queued (which I'd obviously like to keep as close to 0 as possible). Any ideas on this?

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  • What is the definition of "Big Data"?

    - by Ben
    Is there one? All the definitions I can find describe the size, complexity / variety or velocity of the data. Wikipedia's definition is the only one I've found with an actual number Big data sizes are a constantly moving target, as of 2012 ranging from a few dozen terabytes to many petabytes of data in a single data set. However, this seemingly contradicts the MIKE2.0 definition, referenced in the next paragraph, which indicates that "big" data can be small and that 100,000 sensors on an aircraft creating only 3GB of data could be considered big. IBM despite saying that: Big data is more simply than a matter of size. have emphasised size in their definition. O'Reilly has stressed "volume, velocity and variety" as well. Though explained well, and in more depth, the definition seems to be a re-hash of the others - or vice-versa of course. I think that a Computer Weekly article title sums up a number of articles fairly well "What is big data and how can it be used to gain competitive advantage". But ZDNet wins with the following from 2012: “Big Data” is a catch phrase that has been bubbling up from the high performance computing niche of the IT market... If one sits through the presentations from ten suppliers of technology, fifteen or so different definitions are likely to come forward. Each definition, of course, tends to support the need for that supplier’s products and services. Imagine that. Basically "big data" is "big" in some way shape or form. What is "big"? Is it quantifiable at the current time? If "big" is unquantifiable is there a definition that does not rely solely on generalities?

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  • Big Data – Operational Databases Supporting Big Data – Columnar, Graph and Spatial Database – Day 14 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the Key-Value Pair Databases and Document Databases in the Big Data Story. In this article we will understand the role of Columnar, Graph and Spatial Database supporting Big Data Story. Now we will see a few of the examples of the operational databases. Relational Databases (The day before yesterday’s post) NoSQL Databases (The day before yesterday’s post) Key-Value Pair Databases (Yesterday’s post) Document Databases (Yesterday’s post) Columnar Databases (Tomorrow’s post) Graph Databases (Today’s post) Spatial Databases (Today’s post) Columnar Databases  Relational Database is a row store database or a row oriented database. Columnar databases are column oriented or column store databases. As we discussed earlier in Big Data we have different kinds of data and we need to store different kinds of data in the database. When we have columnar database it is very easy to do so as we can just add a new column to the columnar database. HBase is one of the most popular columnar databases. It uses Hadoop file system and MapReduce for its core data storage. However, remember this is not a good solution for every application. This is particularly good for the database where there is high volume incremental data is gathered and processed. Graph Databases For a highly interconnected data it is suitable to use Graph Database. This database has node relationship structure. Nodes and relationships contain a Key Value Pair where data is stored. The major advantage of this database is that it supports faster navigation among various relationships. For example, Facebook uses a graph database to list and demonstrate various relationships between users. Neo4J is one of the most popular open source graph database. One of the major dis-advantage of the Graph Database is that it is not possible to self-reference (self joins in the RDBMS terms) and there might be real world scenarios where this might be required and graph database does not support it. Spatial Databases  We all use Foursquare, Google+ as well Facebook Check-ins for location aware check-ins. All the location aware applications figure out the position of the phone with the help of Global Positioning System (GPS). Think about it, so many different users at different location in the world and checking-in all together. Additionally, the applications now feature reach and users are demanding more and more information from them, for example like movies, coffee shop or places see. They are all running with the help of Spatial Databases. Spatial data are standardize by the Open Geospatial Consortium known as OGC. Spatial data helps answering many interesting questions like “Distance between two locations, area of interesting places etc.” When we think of it, it is very clear that handing spatial data and returning meaningful result is one big task when there are millions of users moving dynamically from one place to another place & requesting various spatial information. PostGIS/OpenGIS suite is very popular spatial database. It runs as a layer implementation on the RDBMS PostgreSQL. This makes it totally unique as it offers best from both the worlds. Courtesy: mushroom network Tomorrow In tomorrow’s blog post we will discuss about very important components of the Big Data Ecosystem – Hive. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Can't save data for a member in a data form

    - by RahulS
    Implied sharing is an old thing everyone knows the reasons and solutions of that, still little theory about that: With Essbase implied sharing, some members are shared even if you do not explicitly set them as shared. These members are implied shared members. When an implied share relationship is created, each implied member assumes the other member’s value. Essbase assumes (or implies) a shared member relationship in these situations: 1. A parent has only one child 2. A parent has only one child that consolidates to the parent In a Planning form that contains members with an implied sharing relationship, when a value is added for the parent, the child assumes the same value after the form is saved. Likewise, if a value is added for the child, the parent usually assumes the same value after a form is saved.For example, when a calculation script or load rule populates an implied share member, the other implied share member assumes the value of the member populated by the calculation script or load rule. The last value calculated or imported takes precedence. The result is the same whether you refer to the parent or the child as a variable in a calculation script. For more information have a look at: http://docs.oracle.com/cd/E17236_01/epm.1112/hp_admin_11122/ch14s11.html Now the issue which we are going to talk about is We loose data on save even when the parent is dynamic calc and has a single child. A dynamic calc parent to a single child:  If we design the form with following selection: In the data form we will find parent below the member and this is by design whenever you make a selection using commands to select all the member below parent, always children will appear before the parent: Lets try to enter data, Save it Now, try to change the way we selected members Here we go: Now the question again why this behavior: 1. Data from Planning data form passes to Essbase row by row, 2. Because in data form the child member appears before the parent, 3. First, data goes to Essbase for child (SingleStoreChild), 4. Then when Planning passes the data for parent there was #Missing or No data,  5. Over writes the data to #missing. PS: As we know that dynamic calc members are calculated on the fly they are not allocated with any memory in the Essbase, here the parent was dynamic calc and it was pointing to same memory as child in the background, when Planning was passing data to Essbase for second row it has updated the child with missing data.(Little confusing, let me know if you need more explanation) 6. As one of the solutions just change the order of appearance of parent and child. Cheers..!!! Rahul S. https://www.facebook.com/pages/HyperionPlanning/117320818374228

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  • Is Data Science “Science”?

    - by BuckWoody
    I hold the term “science” in very high esteem. I grew up on the Space Coast in Florida, and eventually worked at the Kennedy Space Center, surrounded by very intelligent people who worked in various scientific fields. Recently a new term has entered the computing dialog – “Data Scientist”. Since it’s not a standard term, it has a lot of definitions, and in fact has been disputed as a correct term. After all, the reasoning goes, if there’s no such thing as “Data Science” then how can there be a Data Scientist? This argument has been made before, albeit with a different term – “Computer Science”. In Peter Denning’s excellent article “Is Computer Science Science” (April  2005/Vol. 48, No. 4 COMMUNICATIONS OF THE ACM) there are many points that separate “science” from “engineering” and even “art”.  I won’t repeat the content of that article here (I recommend you read it on your own) but will leverage the points he makes there. Definition of Science To ask the question “is data science ‘science’” then we need to start with a definition of terms. Various references put the definition into the same basic areas: Study of the physical world Systematic and/or disciplined study of a subject area ...and then they include the things studied, the bodies of knowledge and so on. The word itself comes from Latin, and means merely “to know” or “to study to know”. Greek divides knowledge further into “truth” (episteme), and practical use or effects (tekhne). Normally computing falls into the second realm. Definition of Data Science And now a more controversial definition: Data Science. This term is so new and perhaps so niche that the major dictionaries haven’t yet picked it up (my OED reference is older – can’t afford to pop for the online registration at present). Researching the term's general use I created an amalgam of the definitions this way: “Studying and applying mathematical and other techniques to derive information from complex data sets.” Using this definition, data science certainly seems to be science - it's learning about and studying some object or area using systematic methods. But implicit within the definition is the word “application”, which makes the process more akin to engineering or even technology than science. In fact, I find that using these techniques – and data itself – part of science, not science itself. I leave out the concept of studying data patterns or algorithms as part of this discipline. That is actually a domain I see within research, mathematics or computer science. That of course is a type of science, but does not seek for practical applications. As part of the argument against calling it “Data Science”, some point to the scientific method of creating a hypothesis, testing with controls, testing results against the hypothesis, and documenting for repeatability.  These are not steps that we often take in working with data. We normally start with a question, and fit patterns and algorithms to predict outcomes and find correlations. In this way Data Science is more akin to statistics (and in fact makes heavy use of them) in the process rather than starting with an assumption and following on with it. So, is Data Science “Science”? I’m uncertain – and I’m uncertain it matters. Even if we are facing rampant “title inflation” these days (does anyone introduce themselves as a secretary or supervisor anymore?) I can tolerate the term at least from the intent that we use data to study problems across a wide spectrum, rather than restricting it to a single domain. And I also understand those who have worked hard to achieve the very honorable title of “scientist” who have issues with those who borrow the term without asking. What do you think? Science, or not? Does it matter?

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  • Load Sharing Regarding Large Websites

    - by JHarley1
    Hello, I have a question regarding Load Sharing for large websites. My Understanding: So if you have a website that has millions of fits a day you will need to have an architecture that can support this sort of pressure. You can either do one or two things: Invest in a single large server that has huge amounts of processing power, memory and storage (such as Microsoft's TerraServer). Spread the load of your website across a number of machines. Let me tackle the second approach, so you have a collection of machines all running Web Server Software and all having access to identical copies of the websites pages. You can either spread the load across these machines using a cyclic pattern in a DNS or you can use a Load Ballancing Switch. The advantages of this approach is: - Redundancy - servers can fail and the others would "pick up the slack" - Incremental - the ability to easily add new machines to this set-up. My Question's Is there a Virtual approach to this issue of load balancing now? If the website runs from a database - is there still only a single copy of the database? If a user had a session running on one Server (e.g. they had gone to www.example.org and had been assigned to Server 2 - were they had created a session) if they refreshed the website (and were allocated Server 3) would they still have their session? What are the other disadvantages associated with Load Balancing? Many Thanks, J

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  • How to limit disk performance?

    - by DrakeES
    I am load-testing a web application and studying the impact of some config tweaks (related to disk i/o) on the overall app performance, i.e. the amount of users that can be handled simultaneously. But the problem is that I hit 100% CPU before I can see any effect of the disk-related config settings. I am therefore wondering if there is a way I could deliberately limit the disk performance so that it becomes the bottleneck and the tweaks I am trying to play with actually start impacting performance. Should I just make the hard disk busy with something else? What would serve the best for this purpose? More details (probably irrelevant, but anyway): PHP/Magento/Apache, studying the impact of apc.stat. Setting it to 0 makes APC not checking PHP scripts for modification which should increase performance where disk is the bottleneck. Using JMeter for benchmarking.

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  • Using BPEL Performance Statistics to Diagnose Performance Bottlenecks

    - by fip
    Tuning performance of Oracle SOA 11G applications could be challenging. Because SOA is a platform for you to build composite applications that connect many applications and "services", when the overall performance is slow, the bottlenecks could be anywhere in the system: the applications/services that SOA connects to, the infrastructure database, or the SOA server itself.How to quickly identify the bottleneck becomes crucial in tuning the overall performance. Fortunately, the BPEL engine in Oracle SOA 11G (and 10G, for that matter) collects BPEL Engine Performance Statistics, which show the latencies of low level BPEL engine activities. The BPEL engine performance statistics can make it a bit easier for you to identify the performance bottleneck. Although the BPEL engine performance statistics are always available, the access to and interpretation of them are somewhat obscure in the early and current (PS5) 11G versions. This blog attempts to offer instructions that help you to enable, retrieve and interpret the performance statistics, before the future versions provides a more pleasant user experience. Overview of BPEL Engine Performance Statistics  SOA BPEL has a feature of collecting some performance statistics and store them in memory. One MBean attribute, StatLastN, configures the size of the memory buffer to store the statistics. This memory buffer is a "moving window", in a way that old statistics will be flushed out by the new if the amount of data exceeds the buffer size. Since the buffer size is limited by StatLastN, impacts of statistics collection on performance is minimal. By default StatLastN=-1, which means no collection of performance data. Once the statistics are collected in the memory buffer, they can be retrieved via another MBean oracle.as.soainfra.bpel:Location=[Server Name],name=BPELEngine,type=BPELEngine.> My friend in Oracle SOA development wrote this simple 'bpelstat' web app that looks up and retrieves the performance data from the MBean and displays it in a human readable form. It does not have beautiful UI but it is fairly useful. Although in Oracle SOA 11.1.1.5 onwards the same statistics can be viewed via a more elegant UI under "request break down" at EM -> SOA Infrastructure -> Service Engines -> BPEL -> Statistics, some unsophisticated minds like mine may still prefer the simplicity of the 'bpelstat' JSP. One thing that simple JSP does do well is that you can save the page and send it to someone to further analyze Follows are the instructions of how to install and invoke the BPEL statistic JSP. My friend in SOA Development will soon blog about interpreting the statistics. Stay tuned. Step1: Enable BPEL Engine Statistics for Each SOA Servers via Enterprise Manager First st you need to set the StatLastN to some number as a way to enable the collection of BPEL Engine Performance Statistics EM Console -> soa-infra(Server Name) -> SOA Infrastructure -> SOA Administration -> BPEL Properties Click on "More BPEL Configuration Properties" Click on attribute "StatLastN", set its value to some integer number. Typically you want to set it 1000 or more. Step 2: Download and Deploy bpelstat.war File to Admin Server, Note: the WAR file contains a JSP that does NOT have any security restriction. You do NOT want to keep in your production server for a long time as it is a security hazard. Deactivate the war once you are done. Download the bpelstat.war to your local PC At WebLogic Console, Go to Deployments -> Install Click on the "upload your file(s)" Click the "Browse" button to upload the deployment to Admin Server Accept the uploaded file as the path, click next Check the default option "Install this deployment as an application" Check "AdminServer" as the target server Finish the rest of the deployment with default settings Console -> Deployments Check the box next to "bpelstat" application Click on the "Start" button. It will change the state of the app from "prepared" to "active" Step 3: Invoke the BPEL Statistic Tool The BPELStat tool merely call the MBean of BPEL server and collects and display the in-memory performance statics. You usually want to do that after some peak loads. Go to http://<admin-server-host>:<admin-server-port>/bpelstat Enter the correct admin hostname, port, username and password Enter the SOA Server Name from which you want to collect the performance statistics. For example, SOA_MS1, etc. Click Submit Keep doing the same for all SOA servers. Step 3: Interpret the BPEL Engine Statistics You will see a few categories of BPEL Statistics from the JSP Page. First it starts with the overall latency of BPEL processes, grouped by synchronous and asynchronous processes. Then it provides the further break down of the measurements through the life time of a BPEL request, which is called the "request break down". 1. Overall latency of BPEL processes The top of the page shows that the elapse time of executing the synchronous process TestSyncBPELProcess from the composite TestComposite averages at about 1543.21ms, while the elapse time of executing the asynchronous process TestAsyncBPELProcess from the composite TestComposite2 averages at about 1765.43ms. The maximum and minimum latency were also shown. Synchronous process statistics <statistics>     <stats key="default/TestComposite!2.0.2-ScopedJMSOSB*soa_bfba2527-a9ba-41a7-95c5-87e49c32f4ff/TestSyncBPELProcess" min="1234" max="4567" average="1543.21" count="1000">     </stats> </statistics> Asynchronous process statistics <statistics>     <stats key="default/TestComposite2!2.0.2-ScopedJMSOSB*soa_bfba2527-a9ba-41a7-95c5-87e49c32f4ff/TestAsyncBPELProcess" min="2234" max="3234" average="1765.43" count="1000">     </stats> </statistics> 2. Request break down Under the overall latency categorized by synchronous and asynchronous processes is the "Request breakdown". Organized by statistic keys, the Request breakdown gives finer grain performance statistics through the life time of the BPEL requests.It uses indention to show the hierarchy of the statistics. Request breakdown <statistics>     <stats key="eng-composite-request" min="0" max="0" average="0.0" count="0">         <stats key="eng-single-request" min="22" max="606" average="258.43" count="277">             <stats key="populate-context" min="0" max="0" average="0.0" count="248"> Please note that in SOA 11.1.1.6, the statistics under Request breakdown is aggregated together cross all the BPEL processes based on statistic keys. It does not differentiate between BPEL processes. If two BPEL processes happen to have the statistic that share same statistic key, the statistics from two BPEL processes will be aggregated together. Keep this in mind when we go through more details below. 2.1 BPEL process activity latencies A very useful measurement in the Request Breakdown is the performance statistics of the BPEL activities you put in your BPEL processes: Assign, Invoke, Receive, etc. The names of the measurement in the JSP page directly come from the names to assign to each BPEL activity. These measurements are under the statistic key "actual-perform" Example 1:  Follows is the measurement for BPEL activity "AssignInvokeCreditProvider_Input", which looks like the Assign activity in a BPEL process that assign an input variable before passing it to the invocation:                                <stats key="AssignInvokeCreditProvider_Input" min="1" max="8" average="1.9" count="153">                                     <stats key="sensor-send-activity-data" min="0" max="1" average="0.0" count="306">                                     </stats>                                     <stats key="sensor-send-variable-data" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="monitor-send-activity-data" min="0" max="0" average="0.0" count="306">                                     </stats>                                 </stats> Note: because as previously mentioned that the statistics cross all BPEL processes are aggregated together based on statistic keys, if two BPEL processes happen to name their Invoke activity the same name, they will show up at one measurement (i.e. statistic key). Example 2: Follows is the measurement of BPEL activity called "InvokeCreditProvider". You can not only see that by average it takes 3.31ms to finish this call (pretty fast) but also you can see from the further break down that most of this 3.31 ms was spent on the "invoke-service".                                  <stats key="InvokeCreditProvider" min="1" max="13" average="3.31" count="153">                                     <stats key="initiate-correlation-set-again" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="invoke-service" min="1" max="13" average="3.08" count="153">                                         <stats key="prep-call" min="0" max="1" average="0.04" count="153">                                         </stats>                                     </stats>                                     <stats key="initiate-correlation-set" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="sensor-send-activity-data" min="0" max="0" average="0.0" count="306">                                     </stats>                                     <stats key="sensor-send-variable-data" min="0" max="0" average="0.0" count="153">                                     </stats>                                     <stats key="monitor-send-activity-data" min="0" max="0" average="0.0" count="306">                                     </stats>                                     <stats key="update-audit-trail" min="0" max="2" average="0.03" count="153">                                     </stats>                                 </stats> 2.2 BPEL engine activity latency Another type of measurements under Request breakdown are the latencies of underlying system level engine activities. These activities are not directly tied to a particular BPEL process or process activity, but they are critical factors in the overall engine performance. These activities include the latency of saving asynchronous requests to database, and latency of process dehydration. My friend Malkit Bhasin is working on providing more information on interpreting the statistics on engine activities on his blog (https://blogs.oracle.com/malkit/). I will update this blog once the information becomes available. Update on 2012-10-02: My friend Malkit Bhasin has published the detail interpretation of the BPEL service engine statistics at his blog http://malkit.blogspot.com/2012/09/oracle-bpel-engine-soa-suite.html.

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  • Data Modeling Resources

    - by Dejan Sarka
    You can find many different data modeling resources. It is impossible to list all of them. I selected only the most valuable ones for me, and, of course, the ones I contributed to. Books Chris J. Date: An Introduction to Database Systems – IMO a “must” to understand the relational model correctly. Terry Halpin, Tony Morgan: Information Modeling and Relational Databases – meet the object-role modeling leaders. Chris J. Date, Nikos Lorentzos and Hugh Darwen: Time and Relational Theory, Second Edition: Temporal Databases in the Relational Model and SQL – all theory needed to manage temporal data. Louis Davidson, Jessica M. Moss: Pro SQL Server 2012 Relational Database Design and Implementation – the best SQL Server focused data modeling book I know by two of my friends. Dejan Sarka, et al.: MCITP Self-Paced Training Kit (Exam 70-441): Designing Database Solutions by Using Microsoft® SQL Server™ 2005 – SQL Server 2005 data modeling training kit. Most of the text is still valid for SQL Server 2008, 2008 R2, 2012 and 2014. Itzik Ben-Gan, Lubor Kollar, Dejan Sarka, Steve Kass: Inside Microsoft SQL Server 2008 T-SQL Querying – Steve wrote a chapter with mathematical background, and I added a chapter with theoretical introduction to the relational model. Itzik Ben-Gan, Dejan Sarka, Roger Wolter, Greg Low, Ed Katibah, Isaac Kunen: Inside Microsoft SQL Server 2008 T-SQL Programming – I added three chapters with theoretical introduction and practical solutions for the user-defined data types, dynamic schema and temporal data. Dejan Sarka, Matija Lah, Grega Jerkic: Training Kit (Exam 70-463): Implementing a Data Warehouse with Microsoft SQL Server 2012 – my first two chapters are about data warehouse design and implementation. Courses Data Modeling Essentials – I wrote a 3-day course for SolidQ. If you are interested in this course, which I could also deliver in a shorter seminar way, you can contact your closes SolidQ subsidiary, or, of course, me directly on addresses [email protected] or [email protected]. This course could also complement the existing courseware portfolio of training providers, which are welcome to contact me as well. Logical and Physical Modeling for Analytical Applications – online course I wrote for Pluralsight. Working with Temporal data in SQL Server – my latest Pluralsight course, where besides theory and implementation I introduce many original ways how to optimize temporal queries. Forthcoming presentations SQL Bits 12, July 17th – 19th, Telford, UK – I have a full-day pre-conference seminar Advanced Data Modeling Topics there.

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  • SQL SERVER – Video – Beginning Performance Tuning with SQL Server Execution Plan

    - by pinaldave
    Traveling can be most interesting or most exhausting experience. However, traveling is always the most enlightening experience one can have. While going to long journey one has to prepare a lot of things. Pack necessary travel gears, clothes and medicines. However, the most essential part of travel is the journey to the destination. There are many variations one prefer but the ultimate goal is to have a delightful experience during the journey. Here is the video available which explains how to begin with SQL Server Execution plans. Performance Tuning is a Journey Performance tuning is just like a long journey. The goal of performance tuning is efficient and least resources consuming query execution with accurate results. Just as maps are the most essential aspect of performance tuning the same way, execution plans are essentially maps for SQL Server to reach to the resultset. The goal of the execution plan is to find the most efficient path which translates the least usage of the resources (CPU, memory, IO etc). Execution Plans are like Maps When online maps were invented (e.g. Bing, Google, Mapquests etc) initially it was not possible to customize them. They were given a single route to reach to the destination. As time evolved now it is possible to give various hints to the maps, for example ‘via public transport’, ‘walking’, ‘fastest route’, ‘shortest route’, ‘avoid highway’. There are places where we manually drag the route and make it appropriate to our needs. The same situation is with SQL Server Execution Plans, if we want to tune the queries, we need to understand the execution plans and execution plans internals. We need to understand the smallest details which relate to execution plan when we our destination is optimal queries. Understanding Execution Plans The biggest challenge with maps are figuring out the optimal path. The same way the  most common challenge with execution plans is where to start from and which precise route to take. Here is a quick list of the frequently asked questions related to execution plans: Should I read the execution plans from bottoms up or top down? Is execution plans are left to right or right to left? What is the relational between actual execution plan and estimated execution plan? When I mouse over operator I see CPU and IO but not memory, why? Sometime I ran the query multiple times and I get different execution plan, why? How to cache the query execution plan and data? I created an optimal index but the query is not using it. What should I change – query, index or provide hints? What are the tools available which helps quickly to debug performance problems? Etc… Honestly the list is quite a big and humanly impossible to write everything in the words. SQL Server Performance:  Introduction to Query Tuning My friend Vinod Kumar and I have created for the same a video learning course for beginning performance tuning. We have covered plethora of the subject in the course. Here is the quick list of the same: Execution Plan Basics Essential Indexing Techniques Query Design for Performance Performance Tuning Tools Tips and Tricks Checklist: Performance Tuning We believe we have covered a lot in this four hour course and we encourage you to go over the video course if you are interested in Beginning SQL Server Performance Tuning and Query Tuning. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Execution Plan

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  • Deploying Data Mining Models using Model Export and Import

    - by [email protected]
    In this post, we'll take a look at how Oracle Data Mining facilitates model deployment. After building and testing models, a next step is often putting your data mining model into a production system -- referred to as model deployment. The ability to move data mining model(s) easily into a production system can greatly speed model deployment, and reduce the overall cost. Since Oracle Data Mining provides models as first class database objects, models can be manipulated using familiar database techniques and technology. For example, one or more models can be exported to a flat file, similar to a database table dump file (.dmp). This file can be moved to a different instance of Oracle Database EE, and then imported. All methods for exporting and importing models are based on Oracle Data Pump technology and found in the DBMS_DATA_MINING package. Before performing the actual export or import, a directory object must be created. A directory object is a logical name in the database for a physical directory on the host computer. Read/write access to a directory object is necessary to access the host computer file system from within Oracle Database. For our example, we'll work in the DMUSER schema. First, DMUSER requires the privilege to create any directory. This is often granted through the sysdba account. grant create any directory to dmuser; Now, DMUSER can create the directory object specifying the path where the exported model file (.dmp) should be placed. In this case, on a linux machine, we have the directory /scratch/oracle. CREATE OR REPLACE DIRECTORY dmdir AS '/scratch/oracle'; If you aren't sure of the exact name of the model or models to export, you can find the list of models using the following query: select model_name from user_mining_models; There are several options when exporting models. We can export a single model, multiple models, or all models in a schema using the following procedure calls: BEGIN   DBMS_DATA_MINING.EXPORT_MODEL ('MY_MODEL.dmp','dmdir','name =''MY_DT_MODEL'''); END; BEGIN   DBMS_DATA_MINING.EXPORT_MODEL ('MY_MODELS.dmp','dmdir',              'name IN (''MY_DT_MODEL'',''MY_KM_MODEL'')'); END; BEGIN   DBMS_DATA_MINING.EXPORT_MODEL ('ALL_DMUSER_MODELS.dmp','dmdir'); END; A .dmp file can be imported into another schema or database using the following procedure call, for example: BEGIN   DBMS_DATA_MINING.IMPORT_MODEL('MY_MODELS.dmp', 'dmdir'); END; As with models from any data mining tool, when moving a model from one environment to another, care needs to be taken to ensure the transformations that prepare the data for model building are matched (with appropriate parameters and statistics) in the system where the model is deployed. Oracle Data Mining provides automatic data preparation (ADP) and embedded data preparation (EDP) to reduce, or possibly eliminate, the need to explicitly transport transformations with the model. In the case of ADP, ODM automatically prepares the data and includes the necessary transformations in the model itself. In the case of EDP, users can associate their own transformations with attributes of a model. These transformations are automatically applied when applying the model to data, i.e., scoring. Exporting and importing a model with ADP or EDP results in these transformations being immediately available with the model in the production system.

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  • SQLAuthority News – SafePeak’s SQL Server Performance Contest – Winners

    - by pinaldave
    SafePeak, the unique automated SQL performance acceleration and performance tuning software vendor, announced the winners of their SQL Performance Contest 2011. The contest quite unique: the writer of the best / most interesting and most community liked “performance story” would win an expensive gadget. The judges were the community DBAs that could participating and Like’ing stories and could also win expensive prizes. Robert Pearl SQL MVP, was the contest supervisor. I liked most of the stories and decided then to contact SafePeak and suggested to participate in the give-away and they have gladly accepted the same. The winner of best story is: Jason Brimhall (USA) with a story about a proc with a fair amount of business logic. Congratulations Jason! The 3 participants won the second prize of $100 gift card on amazon.com are: Michael Corey (USA), Hakim Ali (USA) and Alex Bernal (USA). And 5 participants won a printed copy of a book of mine (Book Reviews of SQL Wait Stats Joes 2 Pros: SQL Performance Tuning Techniques Using Wait Statistics, Types & Queues) are: Patrick Kansa (USA), Wagner Bianchi (USA), Riyas.V.K (India), Farzana Patwa (USA) and Wagner Crivelini (Brazil). The winners are welcome to send safepeak their mail address to receive the prizes (to “info ‘at’ safepeak.com”). Also SafePeak team asked me to welcome you all to continue sending stories, simply because they (and we all) like to read interesting stuff) as well as to send them ideas for future contests. You can do it from here: www.safepeak.com/SQL-Performance-Contest-2011/Submit-Story Congratulations to everybody! I found this very funny video about SafePeak: It looks like someone (maybe the vendor) played with video’s once and created this non-commercial like video: SafePeak dynamic caching is an immediate plug-n-play performance acceleration and scalability solution for cloud, hosted and business SQL server applications. By caching in memory result sets of queries and stored procedures, while keeping all those cache correct and up to date using unique patent pending technology, SafePeak can fix SQL performance problems and bottlenecks of most applications – most importantly: without actual code changes. By the way, I checked their website prior this contest announcement and noticed that they are running these days a special end year promotion giving between 30% to 45% discounts. Since the installation is quick and full testing can be done within couple of days – those have the need (performance problems) and have budget leftovers: I suggest you hurry. A free fully functional trial is here: www.safepeak.com/download, while those that want to start with a quote should ping here www.safepeak.com/quote. Good luck! Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Puzzle, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Webcast Replay Available: Performance Tuning E-Business Suite Concurrent Manager (Performance Series Part 2 of 3)

    - by BillSawyer
    I am pleased to release the replay and presentation for the latest ATG Live Webcast: Performance Tuning E-Business Suite Concurrent Manager (Performance Series Part 2 of 3) (Presentation)Andy Tremayne, Senior Architect, Applications Performance, and co-author of Oracle Applications Performance Tuning Handbook from Oracle Press, and Uday Moogala, Senior Principal Engineer, Applications Performance discussed two major components of E-Business Suite performance tuning:  concurrent management and tracing. They dispel some myths surrounding these topics, and shared with you the recommended best practices that you can use on your own E-Business Suite instance.Finding other recorded ATG webcastsThe catalog of ATG Live Webcast replays, presentations, and all ATG training materials is available in this blog's Webcasts and Training section.

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  • Configuration of Sonicwall Load Balancing

    - by jacke672
    We installed a Sonicwall NSA 240 appliance and have configured it up for our SSL VPN connection and for load balancing with 2 ADSL lines. Over the past week, I have been testing the load balancing options to optimize the connection speeds for our users - but I've run into the following: Round Robin load balancing is the ideal load balancing setting and it's roughly doubling our throughput- but, when it's active users are unable to access any SSL enabled websites such as banking, web-mail, etc. For this reason, I have been using percentage based balancing as it allows me to enable source and destination IP binding, which doesn't 'break' any secure connections but were left with the slow connection speeds we had before adding the second line. I'm looking for a method in which we can take advantage of the round robin connection speeds while allowing users to access sites with SSL certificates, all while still allowing our remote (vpn) users to connect. Any help would be appreciated. Thanks

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  • Coldfusion 8 Application Crashes Under Heavy Load

    - by KM01
    Hello, We have a CF8 app that runs for 20-25 minutes before crashing under heavy load ~ 1200 users. This load is generated by our load testing tool: 1200 users ramped up in 5 mins (approx behavior of our users), running for an hour. We have this app on Solaris 10, Apache 2, JRun 4 and Oracle 10g. Java version is 1.6. During the initial load tests, the thread dumps pointed to monitor deadlocks that pointed to sessions. "jrpp-173": waiting to lock monitor 0x019fdc60 (object 0x6b893530, a java.util.Hashtable), which is held by "scheduler-1" "scheduler-1": waiting to lock monitor 0x026c3ce0 (object 0x6abe2f20, a coldfusion.monitor.memory.SessionMemoryMonitor$TopMemoryUsedSessions), which is held by "jrpp-167" "jrpp-167": waiting to lock monitor 0x019fdc60 (object 0x6b893530, a java.util.Hashtable), which is held by "scheduler-1" We increased the number of sessions relative to the number of CPUs (48 simultaneous threads against 32 CPUs), and the deadlock went away. While varying the simultaneous threads helped a little bit in terms of response time, the CF server still tanked in 20-25 minutes during all of these tests. We ran more thread dumps, and saw a thread locking a monitor, for e.g.: "jrpp-475" prio=3 tid=0x02230800 nid=0x2c5 runnable [0x4397d000] java.lang.Thread.State: RUNNABLE at java.util.HashMap.getEntry(HashMap.java:347) at java.util.HashMap.containsKey(HashMap.java:335) at java.util.HashSet.contains(HashSet.java:184) at coldfusion.monitor.memory.MemoryTracker.onAddObject(MemoryTracker.java:124) at coldfusion.monitor.memory.MemoryTrackerProxy.onReplaceValue(MemoryTrackerProxy.java:598) at coldfusion.monitor.memory.MemoryTrackerProxy.onPut(MemoryTrackerProxy.java:510) at coldfusion.util.CaseInsensitiveMap.put(CaseInsensitiveMap.java:250) at coldfusion.util.FastHashtable.put(FastHashtable.java:43) - locked <0x6f7e1a78> (a coldfusion.runtime.Struct) at coldfusion.runtime.CfJspPage._arrayset(CfJspPage.java:1027) at coldfusion.runtime.CfJspPage._arraySetAt(CfJspPage.java:2117) at cfvalidation2ecfc1052964961$funcSETUSERAUDITDATA.runFunction(/app/docs/apply/cfcs/validation.cfc:377) As you see in the last line above there were several references CFMs and CFCs, and the lines have "cflock" tags, which were scoped to the "application." We (the dev team) then changed them to be scoped to a "name". After more load tests, there is no locking going on and there no deadlocks, but now the application tanks in 7-10 minutes. We've gotten system, network and DB reports from the respective admins, and they are not being taxed; even watched the server stats with server monitor, top, prstat, ran sar reports, etc. So we believe it is an issue with the CF server or maybe the JVM. I am running out of ideas as to what else we can try. Disclaimer: I am not a CF developer or Admin. I am just running the load test, analyzing the reports, threads etc, and sharing the results with the dev and admin teams, and trying the next change, and so on. So far no dice. Has anyone run into something similar? How did you go about diagnosing and troubleshooting? All thoughts and pointers welcome. Thank you for your time! KM

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  • Load testing nginx inside AWS

    - by andy
    I'm trying to load test nginx running on AWS. I need to try to optimise it to handle 1Gbps of inbound traffic. Currently I've got it to peak at 85Mbit/s by running nginx on an m1.large with 4 other machines hitting it by using ab with -i (for head requests) -k (keepalives) -r (ignore failed requests) -n 500000 -c 20000. I'm struggling to generate more than 85 Mbit/s traffic from 4 machines, yet when I do scp a large file I get nearly 0.25Gbit/s of traffic going over the network. Are there any tools or approaches that I could use to load test nginx that might generate more load? I'm only interested in inbound traffic, so perhaps a DoS tool could help if it chucks away responses? I'm hitting a very small (40 byte) static asset, and have peaked at handling 50K concurrent connections and getting 25k reqs/s when just using a single load generator machine.

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  • Why Oracle Data Integrator for Big Data?

    - by Mala Narasimharajan
    Big Data is everywhere these days - but what exactly is it? It’s data that comes from a multitude of sources – not only structured data, but unstructured data as well.  The sheer volume of data is mindboggling – here are a few examples of big data: climate information collected from sensors, social media information, digital pictures, log files, online video files, medical records or online transaction records.  These are just a few examples of what constitutes big data.   Embedded in big data is tremendous value and being able to manipulate, load, transform and analyze big data is key to enhancing productivity and competitiveness.  The value of big data lies in its propensity for greater in-depth analysis and data segmentation -- in turn giving companies detailed information on product performance, customer preferences and inventory.  Furthermore, by being able to store and create more data in digital form, “big data can unlock significant value by making information transparent and usable at much higher frequency." (McKinsey Global Institute, May 2011) Oracle's flagship product for bulk data movement and transformation, Oracle Data Integrator, is a critical component of Oracle’s Big Data strategy. ODI provides automation, bulk loading, and validation and transformation capabilities for Big Data while minimizing the complexities of using Hadoop.  Specifically, the advantages of ODI in a Big Data scenario are due to pre-built Knowledge Modules that drive processing in Hadoop. This leverages the graphical UI to load and unload data from Hadoop, perform data validations and create mapping expressions for transformations.  The Knowledge Modules provide a key jump-start and eliminate a significant amount of Hadoop development.  Using Oracle Data Integrator together with Oracle Big Data Connectors, you can simplify the complexities of mapping, accessing, and loading big data (via NoSQL or HDFS) but also correlating your enterprise data – this correlation may require integrating across heterogeneous and standards-based environments, connecting to Oracle Exadata, or sourcing via a big data platform such as Oracle Big Data Appliance. To learn more about Oracle Data Integration and Big Data, download our resource kit to see the latest in whitepapers, webinars, downloads, and more… or go to our website on www.oracle.com/bigdata

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  • General Policies and Procedures for Maintaining the Value of Data Assets

    Here is a general list for policies and procedures regarding maintaining the value of data assets. Data Backup Policies and Procedures Backups are very important when dealing with data because there is always the chance of losing data due to faulty hardware or a user activity. So the need for a strategic backup system should be mandatory for all companies. This being said, in the real world some companies that I have worked for do not really have a good data backup plan. Typically when companies tend to take this kind of approach in data backups usually the data is not really recoverable.  Unfortunately when companies do not regularly test their backup plans they get a false sense of security because they think that they are covered. However, I can tell you from personal and professional experience that a backup plan/system is never fully implemented until it is regularly tested prior to the time when it actually needs to be used. Disaster Recovery Plan Expanding on Backup Policies and Procedures, a company needs to also have a disaster recovery plan in order to protect its data in case of a catastrophic disaster.  Disaster recovery plans typically encompass how to restore all of a company’s data and infrastructure back to a restored operational status.  Most Disaster recovery plans also include time estimates on how long each step of the disaster recovery plan should take to be executed.  It is important to note that disaster recovery plans are never fully implemented until they have been tested just like backup plans. Disaster recovery plans should be tested regularly so that the business can be confident in not losing any or minimal data due to a catastrophic disaster. Firewall Policies and Content Filters One way companies can protect their data is by using a firewall to separate their internal network from the outside. Firewalls allow for enabling or disabling network access as data passes through it by applying various defined restrictions. Furthermore firewalls can also be used to prevent access from the internal network to the outside by these same factors. Common Firewall Restrictions Destination/Sender IP Address Destination/Sender Host Names Domain Names Network Ports Companies can also desire to restrict what their network user’s view on the internet through things like content filters. Content filters allow a company to track what webpages a person has accessed and can also restrict user’s access based on established rules set up in the content filter. This device and/or software can block access to domains or specific URLs based on a few factors. Common Content Filter Criteria Known malicious sites Specific Page Content Page Content Theme  Anti-Virus/Mal-ware Polices Fortunately, most companies utilize antivirus programs on all computers and servers for good reason, virus have been known to do the following: Corrupt/Invalidate Data, Destroy Data, and Steal Data. Anti-Virus applications are a great way to prevent any malicious application from being able to gain access to a company’s data.  However, anti-virus programs must be constantly updated because new viruses are always being created, and the anti-virus vendors need to distribute updates to their applications so that they can catch and remove them. Data Validation Policies and Procedures Data validation is very important to ensure that only accurate information is stored. The existence of invalid data can cause major problems when businesses attempt to use data for knowledge based decisions and for performance reporting. Data Scrubbing Policies and Procedures Data scrubbing is valuable to companies in one of two ways. The first can be used to clean data prior to being analyzed for report generation. The second is that it allows companies to remove things like personally Identifiable information from its data prior to transmit it between multiple environments or if the information is sent to an external location. An example of this can be seen with medical records in regards to HIPPA laws that prohibit the storage of specific personal and medical information. Additionally, I have professionally run in to a scenario where the Canadian government does not allow any Canadian’s personal information to be stored on a server not located in Canada. Encryption Practices The use of encryption is very valuable when a company needs to any personal information. This allows users with the appropriated access levels to view or confirm the existence or accuracy of data within a system by either decrypting the information or encrypting a piece of data and comparing it to the stored version.  Additionally, if for some unforeseen reason the data got in to the wrong hands then they would have to first decrypt the data before they could even be able to read it. Encryption just adds and additional layer of protection around data itself. Standard Normalization Practices The use of standard data normalization practices is very important when dealing with data because it can prevent allot of potential issues by eliminating the potential for unnecessary data duplication. Issues caused by data duplication include excess use of data storage, increased chance for invalidated data, and over use of data processing. Network and Database Security/Access Policies Every company has some form of network/data access policy even if they have none. These policies help secure data from being seen by inappropriate users along with preventing the data from being updated or deleted by users. In addition, without a good security policy there is a large potential for data to be corrupted by unassuming users or even stolen. Data Storage Policies Data storage polices are very important depending on how they are implemented especially when a company is trying to utilize them in conjunction with other policies like Data Backups. I have worked at companies where all network user folders are constantly backed up, and if a user wanted to ensure the existence of a piece of data in the form of a file then they had to store that file in their network folder. Conversely, I have also worked in places where when a user logs on or off of the network there entire user profile is backed up. Training Policies One of the biggest ways to prevent data loss and ensure that data will remain a company asset is through training. The practice of properly train employees on how to work with in systems that access data is crucial when trying to ensure a company’s data will remain an asset. Users need to be trained on how to manipulate a company’s data in order to perform their tasks to reduce the chances of invalidating data.

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  • How to find virtualization performance bottlenecks?

    - by Martin
    We have recently started moving our C++ build server(s) from real machines into VMs. (MS Hyper-V) We have some performance issues that I've currently no idea how to address. We have: Test-Box - this is a piece of desktop workstation hardware my co-worker used to set up the VM before we moved it to the actual server hardware Srv-Box - this is the server hardware Test-Box-Real - This is Windows running directly on the Test-Box HW Test-Box-VM - This is Windows in a Hyper-V VM on the Test-Box HW Srv-Box-Real- This is Server2008R2 running on the Srv-Box HW. Srv-Box-VM- This is Windows running in a Hyper-V VM on the Srv-Box HW, i.e. on Srv-Box-Real. Now, the problem is that we compared Build times between Test-Box-Real and Test-Box-VM and they were basically equal (within about 2%). Then we moved the VM to the Srv-Box machine and what we saw there is that we have a significant performance degradation between Srv-Box-Real and Srv-Box-VM, that is, where we saw no differences on the Test HW we now do see major differences in performance on the actual Server HW. (Builds about ~~ 50% slower inside the VM.) I should add that both the Test-Box and the Srv-Box are only running this one single VM and doing nothing else. I should also note that the "Real" OS is Win2008R2(64bit) and the VM hosted OS is Wind2003R2(32bit). Hardware specs: Srv-Box: Intel XEON E5640 @ 2.67Ghz (This means 8 cores with hyperthreading on the Real system and "only" 4 cores on the VM, since Hyper-V doesn't allow for hyperthreading, but number of cores doesn't seem to explain the problem here.) 16GB RAM (we have 4GB assigned to the VM) Virtual DELL RAID 1 (2x 450GB HUS156045VLS600 Hitachi 15k SAS drives) Test-Box: Intel XEON E31245 @ 3.3GHz 16GB RAM WD VelociRaptor 600GB 10k RPM SATA Note again that I'm only concerned with the differences between Srv-Box-Real and Srv-Box-VM (high) vs. the differences seen btw. Test-Box-Real and Test-Box-VM (low). Why would one machine have parity when comparing VM vs Real performance and the other (server grade HW no less) would have a large disparity? (Both being XEON CPUs ...)

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  • SQL SERVER – Activity Monitor and Performance Issue

    - by pinaldave
    We had wonderful SQLAuthority News – Community Tech Days – December 11, 2010 event yesterday. After the event, we had meeting among Jacob Sebastian, Vinod Kumar, Rushabh Mehta and myself. We all were sharing our experience about performance tuning consultations. During the conversation, Jacob has shared wonderful story of his recent observation. The story is very small but the moral of the story is very important. The story is about a client, who had continuously performance issues. Client used Activity Monitor (Read More: SQL SERVER – 2008 – Location of Activity Monitor – Where is SQL Serve Activity Monitor Located) to check the performance issues. The pattern of the performance issues was very much common all the time. Every time, after a while the computer stopped responding. After doing in-depth performance analysis, Jacob realized that client once opened activity monitor never closed it. The same activity monitor itself is very expensive process. The tool, which helped to debug the performance issues, also helped (negatively) to bring down the server. After closing the activity monitor which was open for long time, the server did not have performance issues. Moral of the story: Activity Monitor is great tool but use it with care and close it when not needed. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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