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  • How would you gather client's data on Google App Engine without using Datastore/Backend Instances too much?

    - by ruslan
    I'm relatively new to StackExchange and not sure if it's appropriate place to ask design question. Site gives me a hint "The question you're asking appears subjective and is likely to be closed". Please let me know. Anyway.. One of the projects I'm working on is online survey engine. It's my first big commercial project on Google App Engine. I need your advice on how to collect stats and efficiently record them in DataStore without bankrupting me. Initial requirements are: After user finishes survey client sends list of pairs [ID (int) + PercentHit (double)]. This list shows how close answers of this user match predefined answers of reference answerers (which identified by IDs). I call them "target IDs". Creator of the survey wants to see aggregated % for given IDs for last hour, particular timeframe or from the beginning of the survey. Some surveys may have thousands of target/reference answerers. So I created entity public class HitsStatsDO implements Serializable { @Id transient private Long id; transient private Long version = (long) 0; transient private Long startDate; @Parent transient private Key parent; // fake parent which contains target id @Transient int targetId; private double avgPercent; private long hitCount; } But writing HitsStatsDO for each target from each user would give a lot of data. For instance I had a survey with 3000 targets which was answered by ~4 million people within one week with 300K people taking survey in first day. Even if we assume they were answering it evenly for 24 hours it would give us ~1040 writes/second. Obviously it hits concurrent writes limit of Datastore. I decided I'll collect data for one hour and save that, that's why there are avgPercent and hitCount in HitsStatsDO. GAE instances are stateless so I had to use dynamic backend instance. There I have something like this: // Contains stats for one hour private class Shard { ReadWriteLock lock = new ReentrantReadWriteLock(); Map<Integer, HitsStatsDO> map = new HashMap<Integer, HitsStatsDO>(); // Key is target ID public void saveToDatastore(); public void updateStats(Long startDate, Map<Integer, Double> hits); } and map with shard for current hour and previous hour (which doesn't stay here for long) private HashMap<Long, Shard> shards = new HashMap<Long, Shard>(); // Key is HitsStatsDO.startDate So once per hour I dump Shard for previous hour to Datastore. Plus I have class LifetimeStats which keeps Map<Integer, HitsStatsDO> in memcached where map-key is target ID. Also in my backend shutdown hook method I dump stats for unfinished hour to Datastore. There is only one major issue here - I have only ONE backend instance :) It raises following questions on which I'd like to hear your opinion: Can I do this without using backend instance ? What if one instance is not enough ? How can I split data between multiple dynamic backend instances? It hard because I don't know how many I have because Google creates new one as load increases. I know I can launch exact number of resident backend instances. But how many ? 2, 5, 10 ? What if I have no load at all for a week. Constantly running 10 backend instances is too expensive. What do I do with data from clients while backend instance is dead/restarting? Thank you very much in advance for your thoughts.

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  • database design help for game / user levels / progress

    - by sprugman
    Sorry this got long and all prose-y. I'm creating my first truly gamified web app and could use some help thinking about how to structure the data. The Set-up Users need to accomplish tasks in each of several categories before they can move up a level. I've got my Users, Tasks, and Categories tables, and a UserTasks table which joins the three. ("User 3 has added Task 42 in Category 8. Now they've completed it.") That's all fine and working wonderfully. The Challenge I'm not sure of the best way to track the progress in the individual categories toward each level. The "business" rules are: You have to achieve a certain number of points in each category to move up. If you get the number of points needed in Cat 8, but still have other work to do to complete the level, any new Cat 8 points count toward your overall score, but don't "roll over" into the next level. The number of Categories is small (five currently) and unlikely to change often, but by no means absolutely fixed. The number of points needed to level-up will vary per level, probably by a formula, or perhaps a lookup table. So the challenge is to track each user's progress toward the next level in each category. I've thought of a few potential approaches: Possible Solutions Add a column to the users table for each category and reset them all to zero each time a user levels-up. Have a separate UserProgress table with a row for each category for each user and the number of points they have. (Basically a Many-to-Many version of #1.) Add a userLevel column to the UserTasks table and use that to derive their progress with some kind of SUM statement. Their current level will be a simple int in the User table. Pros & Cons (1) seems like by far the most straightforward, but it's also the least flexible. Perhaps I could use a naming convention based on the category ids to help overcome some of that. (With code like "select cats; for each cat, get the value from Users.progress_{cat.id}.") It's also the one where I lose the most data -- I won't know which points counted toward leveling up. I don't have a need in mind for that, so maybe I don't care about that. (2) seems complicated: every time I add or subtract a user or a category, I have to maintain the other table. I foresee synchronization challenges. (3) Is somewhere in between -- cleaner than #2, but less intuitive than #1. In order to find out where a user is, I'd have mildly complex SQL like: SELECT categoryId, SUM(points) from UserTasks WHERE userId={user.id} & countsTowardLevel={user.level} groupBy categoryId Hmm... that doesn't seem so bad. I think I'm talking myself into #3 here, but would love any input, advice or other ideas. P.S. Sorry for the cross-post. I wrote this up on SO and then remembered that there was a game dev-focused one. Curious to see if I get different answers one place than the other....

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  • Tessellation Texture Coordinates

    - by Stuart Martin
    Firstly some info - I'm using DirectX 11 , C++ and I'm a fairly good programmer but new to tessellation and not a master graphics programmer. I'm currently implementing a tessellation system for a terrain model, but i have reached a snag. My current system produces a terrain model from a height map complete with multiple texture coordinates, normals, binormals and tangents for rendering. Now when i was using a simple vertex and pixel shader combination everything worked perfectly but since moving to include a hull and domain shader I'm slightly confused and getting strange results. My terrain is a high detail model but the textured results are very large patches of solid colour. My current setup passes the model data into the vertex shader then through the hull into the domain and then finally into the pixel shader for use in rendering. My only thought is that in my hull shader i pass the information into the domain shader per patch and this is producing the large areas of solid colour because each patch has identical information. Lighting and normal data are also slightly off but not as visibly as texturing. Below is a copy of my hull shader that does not work correctly because i think the way that i am passing the data through is incorrect. If anyone can help me out but suggesting an alternative way to get the required data into the pixel shader? or by showing me the correct way to handle the data in the hull shader id be very thankful! cbuffer TessellationBuffer { float tessellationAmount; float3 padding; }; struct HullInputType { float3 position : POSITION; float2 tex : TEXCOORD0; float3 normal : NORMAL; float3 tangent : TANGENT; float3 binormal : BINORMAL; float2 tex2 : TEXCOORD1; }; struct ConstantOutputType { float edges[3] : SV_TessFactor; float inside : SV_InsideTessFactor; }; struct HullOutputType { float3 position : POSITION; float2 tex : TEXCOORD0; float3 normal : NORMAL; float3 tangent : TANGENT; float3 binormal : BINORMAL; float2 tex2 : TEXCOORD1; float4 depthPosition : TEXCOORD2; }; ConstantOutputType ColorPatchConstantFunction(InputPatch<HullInputType, 3> inputPatch, uint patchId : SV_PrimitiveID) { ConstantOutputType output; output.edges[0] = tessellationAmount; output.edges[1] = tessellationAmount; output.edges[2] = tessellationAmount; output.inside = tessellationAmount; return output; } [domain("tri")] [partitioning("integer")] [outputtopology("triangle_cw")] [outputcontrolpoints(3)] [patchconstantfunc("ColorPatchConstantFunction")] HullOutputType ColorHullShader(InputPatch<HullInputType, 3> patch, uint pointId : SV_OutputControlPointID, uint patchId : SV_PrimitiveID) { HullOutputType output; output.position = patch[pointId].position; output.tex = patch[pointId].tex; output.tex2 = patch[pointId].tex2; output.normal = patch[pointId].normal; output.tangent = patch[pointId].tangent; output.binormal = patch[pointId].binormal; return output; } Edited to include the domain shader:- [domain("tri")] PixelInputType ColorDomainShader(ConstantOutputType input, float3 uvwCoord : SV_DomainLocation, const OutputPatch<HullOutputType, 3> patch) { float3 vertexPosition; PixelInputType output; // Determine the position of the new vertex. vertexPosition = uvwCoord.x * patch[0].position + uvwCoord.y * patch[1].position + uvwCoord.z * patch[2].position; output.position = mul(float4(vertexPosition, 1.0f), worldMatrix); output.position = mul(output.position, viewMatrix); output.position = mul(output.position, projectionMatrix); output.depthPosition = output.position; output.tex = patch[0].tex; output.tex2 = patch[0].tex2; output.normal = patch[0].normal; output.tangent = patch[0].tangent; output.binormal = patch[0].binormal; return output; }

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  • Keeping an Eye on Your Storage

    - by Fatherjack
    There are plenty of resources that advise you about looking for signs that your storage hardware is having problems. SQL Server Alerts for 823, 824 and 825 are covered here by Paul Randall of SQL Skills: http://www.sqlskills.com/blogs/paul/a-little-known-sign-of-impending-doom-error-825/ and here by me: https://www.simple-talk.com/blogs/2011/06/27/alerts-are-good-arent-they/. Now until very recently I wasn’t aware that there was a different way to track the 823 + 824 errors. It was by complete chance that I happened to be searching about in the msdb database when I found the suspect_pages table. Running a query against it I got zero rows. This, as it turns out is a good thing. Highlighting the table name and pressing F1 got me nowhere – Is it just me or does Books Online fail to load properly for no obvious reason sometimes? So I typed the table name into the search bar and got my local version of http://msdn.microsoft.com/en-us/library/ms174425.aspx. From that we get the following description: Contains one row per page that failed with a minor 823 error or an 824 error. Pages are listed in this table because they are suspected of being bad, but they might actually be fine. When a suspect page is repaired, its status is updated in the event_type column. So, in the table we would, on healthy hardware, expect to see zero rows but on disks that are having problems the event_type column would show us what is going on. Where there are suspect pages on the disk the rows would have an event_type value of 1, 2 or 3, where those suspect pages have been restored, repaired or deallocated by DBCC then the value would be 4, 5 or 7. Having this table means that we can set up SQL Monitor to check the status of our hardware as we can create a custom metric based on the query below: USE [msdb] go SELECT COUNT(*) FROM [dbo].[suspect_pages] AS sp All we need to do is set the metric to collect this value and set an alert to email when the value is not 1 and we are then able to let SQL Monitor take care of our storage. Note that the suspect_pages table does not have any updates concerning Error 825 which the links at the top of the page cover in more detail. I would suggest that you set SQL Monitor to alert on the suspect_pages table in addition to other taking other measures to look after your storage hardware and not have it as your only precaution. Microsoft actually pass ownership and administration of the suspect_pages table over to the database administrator (Manage the suspect_pages Table (SQL Server)) and in a surprising move (to me at least) advise DBAs to actively update and archive data in it. The table will only ever contain a maximum of 1000 rows and once full, new rows will not be added. Keeping an eye on this table is pretty important, although In my opinion, if you get to 1000 rows in this table and are not already waiting for new disks to be added to your server you are doing something wrong but if you have 1000 rows in there then you need to move data out quickly because you may be missing some important events on your server.

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  • What DX level does my graphics card support? Does it go to 11?

    - by Daniel Moth
    Recently I run into a situation that I have run into quite a few times. Someone encounters a machine and the question arises: "Is there a DirectX 11 card in this machine?". Typically the reason you are interested in that is because cards with DirectX 11 drivers fully support DirectCompute (and by extension C++ AMP) for GPGPU programming. The driver specifically is WDDM (1.1 on Windows 7 and Windows 8 introduces WDDM 1.2 with cool new capabilities). There are many ways for figuring out if you have a DirectX11 card, so here are the approaches that you can use, with a bonus right at the end of the post. Run DxDiag WindowsKey + R, type DxDiag and hit Enter. That is the DirectX diagnostic tool, which unfortunately, only tells you on the "System" tab what is the highest version of DirectX installed on your machine. So if it reports DirectX 11, that doesn't mean you have a DX11 driver! The "Display" tab has a promising "DDI version" label, but unfortunately that doesn't seem to be accurate on the machines I've tested it with (or I may be misinterpreting its use). Either way, this tool is not the one you want for this purpose, although it is good for telling you the WDDM version among other things. Use the Microsoft hardware page There is a Microsoft Windows 7 compatibility center, that lists all hardware (tip: use the advanced search) and you could try and locate your device there… good luck. Use Wikipedia or the hardware vendor's website Use the Wikipedia page for the vendor cards, for both nvidia and amd. Often this information will also be in the specifications for the cards on the IHV site, but is is nice that wikipedia has a single page per vendor that you can search etc. There is a column in the tables for API support where you can see the DirectX version. Check if it is one of these recommended DX11 cards You may not have a DirectX 11 card and are interested in purchasing one. While I am in no position to make recommendations, I will list here some cards from two big IHVs that we know are DirectX 11 capable. Some AMD (aka ATI) cards Low end, inexpensive DX11 hardware: Radeon 5450, 5550, 6450, 6570 Mid range (decent perf, single precision): Radeon 5750, 5770, 6770, 6790 High end (capable of double precision): Radeon 5850, 5870, 6950, 6970 Single precision APUs: AMD E-Series APUs AMD A-Series APUs Some NVIDIA cards Low end, inexpensive DX11 hardware: GeForce GT430, GT 440, GT520, GTS 450 Quadro 400, 600 Mid-range (decent perf, single precision): GeForce GTX 460, GTX 550 Ti, GTX 560, GTX 560 Ti Quadro 2000 High end (capable of double precision): GeForce GTX 480, GTX 570, GTX 580, GTX 590, GTX 595 Quadro 4000, 5000, 6000 Tesla C2050, C2070, C2075 Get the DirectX SDK and run DirectX Caps Viewer Download and install the June 2010 DirectX SDK. As part of that you now have the DirectX Capabilities Viewer utility (find it in your start menu by searching for "DirectX Caps Viewer", the filename is DXCapsViewer.exe). It will list all your devices (emulated, and real hardware ones) under the first node. Expand the hardware entries and then expand again the Direct3D 11 folder. If you see D3D_FEATURE_LEVEL_11_ under that, then your card supports feature level 11 which means it supports DirectCompute and C++ AMP. In the following screenshot of one of my old laptops, the card only goes to feature level 10. Run a utility from the web that just tells you! Of course, writing some C++ AMP code that enumerates accelerators and lists the ones that are capable is trivial. However that requires that you have redistributed the runtime, so a more broadly applicable approach is to use the DX APIs directly to enumerate the DX11 capable cards. That is exactly what the development lead for C++ AMP has done and he describes and shares that utility at this post. Comments about this post by Daniel Moth welcome at the original blog.

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  • SQL Authority News – Secret Tool Box of Successful Bloggers: 52 Tips to Build a High Traffic Top Ranking Blog

    - by Pinal Dave
    When I started this blog, it was meant as a bookmark for myself for helpful tips and tricks.  Gradually, it grew into a blog that others were reading and commenting on.  While SQL and databases are my first love and the reason I started this blog, the side effect was that I discovered I loved writing.  I discovered a secret goal I didn’t even know I wanted – I wanted to become an author.  For a long time, writing this blog satisfied that urge.  Gradually, though, I wanted to see my name in print. 12th Book Over the past few years I have authored and co-authored a number of books – they are all based on my knowledge of SQL Server, and were meant to spread my years of experience into the world, to share what I have learned with my community.  I currently have elevan of these “manuals” available for sale.  As exciting as it was to see my name in print, I still felt that there was more I could do as an author. That is when I realized that I am more than just a SQL expert.  I have been writing this blog now for more than 10 years, and it grew from a personal bookmark to a thriving website with over 2 million views per month.  I thought to myself “I could write a book about how to create a successful blog!”  And that is exactly what I did.  I am extremely excited to share with all of you my new book – “Secret Toolbox of Successful Bloggers.” A Labor of Love This project has been a labor of love for me.  It started out as a series for this blog – I would post one article a week until I felt the topic had been covered.  I found that as I wrote, new topics kept popping up in my mind, and eventually this small blog series grew into a full book.  The blog series was large enough to last a whole year, so I definitely thought that it could be a full book.  Ideas on how to become a successful blogger were so frequent that, I will admit, I feel like there is so much I left out of this book.  I had a lot more to say than I originally thought! I am so excited to be sharing this book with all of you.  I am so passionate about this topic, and I feel like there are so many people who can benefit from this book.  I know that when I started this blog, I did not know what I was doing, and I would have loved a “helping hand” to tell what to do and what not to do.  If this book can act that way to any of my readers, I feel it is a success. Rules of Thumb If you are interested in the topic of becoming a blogger, as you read this book, keep in mind that it is suggestions only.  Blogging is so new to the world that while there are “rules of thumb” about what to do and what not to do, a map of steps (“first, do x, then do y”) is not going to work for every single blogger.  This book is meant to encourage new bloggers to put their content out there in the world, to be brave and create a community like the one I have here at SQL Authority.  I have gained so much from this community, I wanted to give something back, and this book is just one small part. I hope that everyone who reads this books finds at least one helpful tip, and that everyone can experience the joy of blogging.  That is the whole reason I wrote this book, and what I hope everyone takes away from it. Where Can You Get It? You can get the book from following URL: Kindle eBook | Print Book Reference: Pinal Dave (http://blog.SQLAuthority.com)Filed under: About Me, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, T SQL

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  • PASS: International Travels

    - by Bill Graziano
    Nihao!  One of the largest changes PASS is going through is the the expansion outside the US and Canada.  We’ve had international chapters and events in Europe since the early 2000’s.  But nothing on the scale we’re seeing now.  Since January 1st there have been 18 SQL Saturday events outside North America and 19 events in North America.  We hope to have three international SQLRally events outside the US in FY13 (budget willing).  I don’t know the exact percentage of chapters outside the US but it’s got be 50% or higher. We recently started an effort to remake the Board to better reflect the growing global face of PASS.  This involves assigning some Board seats to geographic regions.  You can ask questions about this in our feedback forum, participate in a Twitter chat or ask questions directly of Board members.  You can email me at if you’d like to ask a question directly.  We’re doing this very slowly and deliberately in hopes that a long communication cycle gives us a chance to address all the issues that our members will raise. After the Summit we passed a budget exception allocating an extra $20,000 for Board members to travel to local events.  I think it’s important for Board members to visit new areas and talk to more of our members.  I sent out an email asking where people had attended events outside their home city.  Here’s the list I got back: Albuquerque, Amsterdam, Boston, Brisbane, Chicago, Colorado Springs, Columbus, Dallas, Houston, Jacksonville, Las Vegas, London, Louisville, Minneapolis, New York City, Orange County, Orlando, Pensacola, Perth, Philadelphia, Phoenix, Redmond, Seattle, Silicon Valley, Sydney, Tampa Bay, Vancouver, Washington DC and Wellington.  (Disclaimer: Some of this travel was paid for by employers or Board members themselves.  Some of this travel may have been completed before the Summit.  That’s still one heck of a list!) The last SQL Saturday event this fiscal year is SQL Saturday Shanghai.  And that’s one I’m attending.  This is our first event in China and is being put on in cooperation with the local Microsoft office.  Hopefully this event will be the start of a growing community in China that includes chapters, SQL Saturdays and maybe a SQLRally or two in the future.  I’m excited to speak with people that are just starting down this path and watching this community grow. I encourage you to visit the PASS Global Growth site and read through the material there.  This is the biggest change we’ve made to our governance since I’ve been on the Board.  You need to understand how it affects you and how it affects the organization. And wish me luck on the 15 hour flight to Shanghai on Friday afternoon.  Rob Farley flies from Australia to the US for PASS events multiple times per year and I don’t know how he does it so often.  I think one of these is going to wipe me out.  (And Nihao (knee-how) is Chinese for Hello.)

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  • SQL Server IO handling mechanism can be severely affected by high CPU usage

    - by sqlworkshops
    Are you using SSD or SAN / NAS based storage solution and sporadically observe SQL Server experiencing high IO wait times or from time to time your DAS / HDD becomes very slow according to SQL Server statistics? Read on… I need your help to up vote my connect item – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage. Instead of taking few seconds, queries could take minutes/hours to complete when CPU is busy.In SQL Server when a query / request needs to read data that is not in data cache or when the request has to write to disk, like transaction log records, the request / task will queue up the IO operation and wait for it to complete (task in suspended state, this wait time is the resource wait time). When the IO operation is complete, the task will be queued to run on the CPU. If the CPU is busy executing other tasks, this task will wait (task in runnable state) until other tasks in the queue either complete or get suspended due to waits or exhaust their quantum of 4ms (this is the signal wait time, which along with resource wait time will increase the overall wait time). When the CPU becomes free, the task will finally be run on the CPU (task in running state).The signal wait time can be up to 4ms per runnable task, this is by design. So if a CPU has 5 runnable tasks in the queue, then this query after the resource becomes available might wait up to a maximum of 5 X 4ms = 20ms in the runnable state (normally less as other tasks might not use the full quantum).In case the CPU usage is high, let’s say many CPU intensive queries are running on the instance, there is a possibility that the IO operations that are completed at the Hardware and Operating System level are not yet processed by SQL Server, keeping the task in the resource wait state for longer than necessary. In case of an SSD, the IO operation might even complete in less than a millisecond, but it might take SQL Server 100s of milliseconds, for instance, to process the completed IO operation. For example, let’s say you have a user inserting 500 rows in individual transactions. When the transaction log is on an SSD or battery backed up controller that has write cache enabled, all of these inserts will complete in 100 to 200ms. With a CPU intensive parallel query executing across all CPU cores, the same inserts might take minutes to complete. WRITELOG wait time will be very high in this case (both under sys.dm_io_virtual_file_stats and sys.dm_os_wait_stats). In addition you will notice a large number of WAITELOG waits since log records are written by LOG WRITER and hence very high signal_wait_time_ms leading to more query delays. However, Performance Monitor Counter, PhysicalDisk, Avg. Disk sec/Write will report very low latency times.Such delayed IO handling also occurs to read operations with artificially very high PAGEIOLATCH_SH wait time (with number of PAGEIOLATCH_SH waits remaining the same). This problem will manifest more and more as customers start using SSD based storage for SQL Server, since they drive the CPU usage to the limits with faster IOs. We have a few workarounds for specific scenarios, but we think Microsoft should resolve this issue at the product level. We have a connect item open – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage - (with example scripts) to reproduce this behavior, please up vote the item so the issue will be addressed by the SQL Server product team soon.Thanks for your help and best regards,Ramesh MeyyappanHome: www.sqlworkshops.comLinkedIn: http://at.linkedin.com/in/rmeyyappan

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  • Design pattern for logging changes in parent/child objects saved to database

    - by andrew
    I’ve got a 2 database tables in parent/child relationship as one-many. I’ve got three classes representing the data in these two tables: Parent Class { Public int ID {get; set;} .. other properties } Child Class { Public int ID {get;set;} Public int ParentID {get; set;} .. other properties } TogetherClass { Public Parent Parent; Public List<Child> ChildList; } Lastly I’ve got a client and server application – I’m in control of both ends so can make changes to both programs as I need to. Client makes a request for ParentID and receives a Together Class for the matching parent, and all of the child records. The client app may make changes to the children – add new children, remove or modify existing ones. Client app then sends the Together Class back to the server app. Server app needs to update the parent and child records in the database. In addition I would like to be able to log the changes – I’m doing this by having 2 separate tables one for Parent, one for child; each containing the same columns as the original plus date time modified, by whom and a list of the changes. I’m unsure as to the best approach to detect the changes in records – new records, records to be deleted, records with no fields changed, records with some fields changed. I figure I need to read the parent & children records and compare those to the ones in the Together Class. Strategy A: If Together class’s child record has an ID of say 0, that indicates a new record; insert. Any deleted child records are no longer in the Together Class; see if any of the comparison child records are not found in the Together class and delete if not found (Compare using ID). Check each child record for changes and if changed log. Strategy B: Make a new Updated TogetherClass UpdatedClass { Public Parent Parent {get; set} Public List<Child> ListNewChild {get;set;} Public List<Child> DeletedChild {get;set;} Public List<Child> ExistingChild {get;set;} // used for no changes and modified rows } And then process as per the list. The reason why I’m asking for ideas is that both of these solutions don’t seem optimal to me and I suspect this problem has been solved already – some kind of design pattern ? I am aware of one potential problem in this general approach – that where Client App A requests a record; App B requests same record; A then saves changes; B then saves changes which may overwrite changes A made. This is a separate locking issue which I’ll raise a separate question for if I’ve got trouble implementing. The actual implementation is c#, SQL Server and WCF between client and server - sharing a library containing the class implementations. Apologies if this is a duplicate post – I tried searching various terms without finding a match though.

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  • Running a WebLogic Portal (WLP) 10.3.4 Domain as a Windows Service

    - by user647124
    To start a WLP server as a Windows service it is simplest to make your own script based on the provided standard script located at WL_HOME\server\bin\installSvc.cmd. The standard script works fine for a plain WLS domain, but lacks some classpath and options necessary for WLP.Start by making a copy of the installSvc.cmd script and naming it something specific to your domain.Next, just under SETLOCAL you will find where WL_HOME is defined. Here you will add the definitions you would normally add in a script that later calls installSvc.cmd (as per the standard documentation). set DOMAIN_NAME=gnma_test_domainset USERDOMAIN_HOME=D:\my_test_domainset SERVER_NAME=AdminServerset WLS_USER=weblogicset WLS_PW=gnmaAdmin01set PRODUCTION_MODE=trueset MEM_ARGS=-Xms512m –Xmx512mset MW_HOME=C:\Oracle\Middleware Note: I had heard of people using this approach who had issues with the length of the command line. This may be due to their use of the default domain path. In the example above, I use a shorter path.At this point, edit the DOMAIN_HOME\bin\startWebLogic.cmd and set it to echo both the classpath and the options. Then start the domain and capture the output of those echoes, then shut the domain back down. Now REM out the existing CLASSPATH definition, then use the outputs you captured earlier to set the CLASSPATH and JAVA_OPTIONS like this: REM set CLASSPATH=%WEBLOGIC_CLASSPATH%;%CLASSPATH%; C:\Oracle\Middleware\wlportal_10.3\portal\lib\security\wsrp-security-providers.jarset CLASSPATH=%MW_HOME%\patch_wls1034\profiles\default\sys_manifest_classpath\weblogic_patch.jar;%MW_HOME%\patch_wlp1034\profiles\default\sys_manifest_classpath\weblogic_patch.jar;%MW_HOME%\patch_oepe1111\profiles\default\sys_manifest_classpath\weblogic_patch.jar;%MW_HOME%\patch_ocm1033\profiles\default\sys_manifest_classpath\weblogic_patch.jar;%MW_HOME%\JROCKI~1.1-3\lib\tools.jar;%WL_HOME%\server\lib\weblogic_sp.jar;%WL_HOME%\server\lib\weblogic.jar;%MW_HOME%\modules\features\weblogic.server.modules_10.3.4.0.jar;%WL_HOME%\server\lib\webservices.jar;%MW_HOME%\modules\ORGAPA~1.1/lib/ant-all.jar;%MW_HOME%\modules\NETSFA~1.0_1/lib/ant-contrib.jar;%WL_HOME%\common\derby\lib\derbyclient.jar;%WL_HOME%\server\lib\xqrl.jar;%WL_HOME%\server\lib\xquery.jar;%WL_HOME%\server\lib\binxml.jarset JAVA_OPTIONS= -Xverify:none -ea -da:com.bea... -da:javelin... -da:weblogic... -ea:com.bea.wli... -ea:com.bea.broker... -ea:com.bea.sbconsole... -Dplatform.home=%WL_HOME% -Dwls.home=%WL_HOME%\server -Dweblogic.home=%WL_HOME%\server -Dweblogic.wsee.bind.suppressDeployErrorMessage=true -Dweblogic.wsee.skip.async.response=true -Dweblogic.management.discover=true -Dwlw.iterativeDev=true -Dwlw.testConsole=true -Dwlw.logErrorsToConsole=true -Dweblogic.ext.dirs=%MW_HOME%\patch_wls1034\profiles\default\sysext_manifest_classpath;%MW_HOME%\patch_wlp1034\profiles\default\sysext_manifest_classpath;%MW_HOME%\patch_oepe1111\profiles\default\sysext_manifest_classpath;%MW_HOME%\patch_ocm1033\profiles\default\sysext_manifest_classpath;%MW_HOME%\wlportal_10.3\p13n\lib\system;%MW_HOME%\wlportal_10.3\light-portal\lib\system;%MW_HOME%\wlportal_10.3\portal\lib\system;%MW_HOME%\wlportal_10.3\info-mgmt\lib\system;%MW_HOME%\wlportal_10.3\analytics\lib\system;%MW_HOME%\wlportal_10.3\apps\lib\system;%MW_HOME%\wlportal_10.3\info-mgmt\deprecated\lib\system;%MW_HOME%\wlportal_10.3\content-mgmt\lib\system -Dweblogic.alternateTypesDirectory=%MW_HOME%\wlportal_10.3\portal\lib\securityAnd that's it. Looks really simple, but it took me quite some time to gather all the necessary pieces in order to make it work. Hopefully you find this before you went through half as much research.The example here uses a domain with only the Admin server and no managed servers. For a variety of reasons I only want the Admin server to be run as a service. The standard documentation along with the example above should allow you to expand this to include managed servers should you feel the need.

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  • Best Practices - Core allocation

    - by jsavit
    This post is one of a series of "best practices" notes for Oracle VM Server for SPARC (also called Logical Domains) Introduction SPARC T-series servers currently have up to 4 CPU sockets, each of which has up to 8 or (on SPARC T3) 16 CPU cores, while each CPU core has 8 threads, for a maximum of 512 dispatchable CPUs. The defining feature of Oracle VM Server for SPARC is that each domain is assigned CPU threads or cores for its exclusive use. This avoids the overhead of software-based time-slicing and emulation (or binary rewriting) of system state-changing privileged instructions used in traditional hypervisors. To create a domain, administrators specify either the number of CPU threads or cores that the domain will own, as well as its memory and I/O resources. When CPU resources are assigned at the individual thread level, the logical domains constraint manager attempts to assign threads from the same cores to a domain, and avoid "split core" situations where the same CPU core is used by multiple domains. Sometimes this is unavoidable, especially when domains are allocated and deallocated CPUs in small increments. Why split cores can matter Split core allocations can silenty reduce performance because multiple domains with different address spaces and memory contents are sharing the core's Level 1 cache (L1$). This is called false cache sharing since even identical memory addresses from different domains must point to different locations in RAM. The effect of this is increased contention for the cache, and higher memory latency for each domain using that core. The degree of performance impact can be widely variable. For applications with very small memory working sets, and with I/O bound or low-CPU utilization workloads, it may not matter at all: all machines wait for work at the same speed. If the domains have substantial workloads, or are critical to performance then this can have an important impact: This blog entry was inspired by a customer issue in which one CPU core was split among 3 domains, one of which was the control and service domain. The reported problem was increased I/O latency in guest domains, but the root cause might be higher latency servicing the I/O requests due to the control domain being slowed down. What to do about it Split core situations are easily avoided. In most cases the logical domain constraint manager will avoid it without any administrative action, but it can be entirely prevented by doing one of the several actions: Assign virtual CPUs in multiples of 8 - the number of threads per core. For example: ldm set-vcpu 8 mydomain or ldm add-vcpu 24 mydomain. Each domain will then be allocated on a core boundary. Use the whole core constraint when assigning CPU resources. This allocates CPUs in increments of entire cores instead of virtual CPU threads. The equivalent of the above commands would be ldm set-core 1 mydomain or ldm add-core 3 mydomain. Older syntax does the same thing by adding the -c flag to the add-vcpu, rm-vcpu and set-vcpu commands, but the new syntax is recommended. When whole core allocation is used an attempt to add cores to a domain fails if there aren't enough completely empty cores to satisfy the request. See https://blogs.oracle.com/sharakan/entry/oracle_vm_server_for_sparc4 for an excellent article on this topic by Eric Sharakan. Don't obsess: - if the workloads have minimal CPU requirements and don't need anywhere near a full CPU core, then don't worry about it. If you have low utilization workloads being consolidated from older machines onto a current T-series, then there's no need to worry about this or to assign an entire core to domains that will never use that much capacity. In any case, make sure the most important domains have their own CPU cores, in particular the control domain and any I/O or service domain, and of course any important guests. Summary Split core CPU allocation to domains can potentially have an impact on performance, but the logical domains manager tends to prevent this situation, and it can be completely and simply avoided by allocating virtual CPUs on core boundaries.

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  • Oracle Retail Mobile Point-of-Service

    - by David Dorf
    When most people discuss mobile in retail, they immediately go to shopping applications.  While I agree the consumer side of mobile is huge, I believe its also important to arm store associates with mobile tools.  There are around a dozen major roll-outs of mobile POS to chain retailers, and all have been successful.  This does not, however, signal the demise of traditional registers.  Retailers will adopt mobile POS slowly and reduce the number of fixed registers over time, but there's likely to be a combination of both for the foreseeable future.  Even Apple retains at least one fixed register in every store, you just have to know where to look. The business benefits for mobile POS are pretty straightforward: 1. Faster checkout.  Walmart's CFO recently reported that for every second they shave off the average transaction time, they can potentially save $12M a year in labor.  I think its more likely that labor will be redeployed to enhance the customer experience. 2. Smarter associates.  The sales associates on the floor need the same access to information that consumers have, if not more.  They need ready access to product details, reviews, inventory, etc. to meet consumer expectations.  In a recent study, 40% of consumers said a savvy store associate can impact their final product selection more than a website. 3. Lower costs.  Mobile POS hardware (iPod touch + sled) costs about a fifth of fixed registers, not to mention the reclaimed space that can be used for product displays. But almost all Mobile POS solutions can claim those benefits equally.  Where there's differentiation is on the technical side.  Oracle recently announced availability of the Oracle Retail Mobile Point-of-Service, and it has three big technology advantages in the market: 1. Portable. We used a popular open-source component called PhoneGap that abstracts the app from the underlying OS and hardware so that iOS, Android, and other platforms could be supported.  Further, we used Web technologies such as HTML5 and JavaScript, which are commonly known by many programmers, as opposed to ObjectiveC which is more difficult to find.  The screen can adjust to different form-factors and sizes, just like you see with browsers.  In the future when a new, zippy device gets released, retailers will have the option to move to that device more easily than if they used a native app. 2. Flexible.  Our Mobile POS is free with the Oracle Retail Point-of-Service product.  Retailers can use any combination of fixed and mobile registers, and those ratios can change as required.  Perhaps start with 1 mobile and 4 fixed per store, then transition over time to 4 mobile and 1 fixed without any additional software licenses.  Our scalable solution supports lots of combinations. 3. Consistent.  Because our Mobile POS is fully integrated to our traditional POS, the same business logic is reused.  Third-party Mobile POS solutions often handle pricing, promotions, and tax calculations separately leading to possible inconsistencies within the store.  That won't happen with Oracle's solution. For many retailers, Mobile POS can lower costs, increase customer service, and generally enhance a consumer's in-store experience.  Apple led the way, but lots of other retailers are discovering the many benefits of adding mobile capabilities in their stores.  Just be sure to examine both the business and technology benefits so you get the most value from your solution for the longest period of time.

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  • New spreadsheet accompanying SmartAssembly 6.0 provides statistics for prioritizing bug fixes

    - by Jason Crease
    One problem developers face is how to prioritize the many voices providing input into software bugs. If there is something wrong with a function that is the darling of a particular user, he or she tends to want action - now! The developer's dilemma is how to ascertain that the problem is major or minor, and when it should be addressed. Now there is a new spreadsheet accompanying SmartAssembly that provides exactly that information in an objective manner. This might upset those used to getting their way by being the loudest or pushiest, but ultimately it will ensure that the biggest problems get the priority they deserve. Here's how it works: Feature Usage Reporting (FUR) in SmartAssembly 6.0 provides a wealth of data about how your software is used by its end-users, but in the SmartAssembly UI the data isn't mined to its full extent. The new Excel spreadsheet for FUR extracts statistics from that data and presents them in easy-to-understand forms. I developed the spreadsheet feature in Microsoft Excel, using a fair amount of VBA. The spreadsheet connects directly to the database which stores the feature-usage data, and shows a wide variety of statistics and tables extracted from that data.  You want to know what percentage of users have used the 'Export as XML' button?  No problem.  How popular is v5.3 is compared to v5.1?  There's graphs for that. You need to know whether you have more users in Russia or Brazil? There's a big pie chart for that. I recently witnessed the spreadsheet in use here at Red Gate Software. My bug is exposed as minor While testing new features in .NET Reflector, I found a usability bug in the Refresh button and filed it in the Red Gate bug-tracking system. The bug was labelled "V.NEXT MINOR," which means it would be fixed in the next point release. Although I'm a professional tester, I'm not much different than most software users when they discover a bug that affects them personally: I wanted it fixed immediately. There was an ulterior motive at play here, of course. I would get to see my colleagues put the spreadsheet to work. The Reflector team loaded up the spreadsheet to view the feature-usage statistics that SmartAssembly collected for the refresh button. The resulting statistics showed that only 8% of users have ever pressed the Refresh button, and only 2.6% of sessions involve pressing the button. When Refresh is used, it's only pressed on average 1.6 times a session, with a maximum of 8 times during a session. This was in stark contrast to what I was doing as a conscientious tester: pressing it dozens of times per session. The spreadsheet provides evidence that my bug was a minor one. On to more serious things Based on the solid evidence uncovered by the spreadsheet, the Reflector team concluded that my experience does not represent that of the vast majority of Reflector's recorded users. The Reflector team had ample data to send me back to my desk and keep the bug classified as "V.NEXT MINOR." The team then went back to fixing more serious bugs. If I'm in the shoes of the user, I might not be thoroughly happy, but I cannot deny that the evidence clearly placed me in a very small minority. Next time I'm hoping the spreadsheet will prove that my bug is more important. Find out more about Feature-Usage Reporting here. The spreadsheet is available for free download here.

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  • How the SPARC T4 Processor Optimizes Throughput Capacity: A Case Study

    - by Ruud
    This white paper demonstrates the architected latency hiding features of Oracle’s UltraSPARC T2+ and SPARC T4 processors That is the first sentence from this technical white paper, but what does it exactly mean? Let's consider a very simple example, the computation of a = b + c. This boils down to the following (pseudo-assembler) instructions that need to be executed: load @b, r1 load @c, r2 add r1,r2,r3 store r3, @a The first two instructions load variables b and c from an address in memory (here symbolized by @b and @c respectively). These values go into registers r1 and r2. The third instruction adds the values in r1 and r2. The result goes into register r3. The fourth instruction stores the contents of r3 into the memory address symbolized by @a. If we're lucky, both b and c are in a nearby cache and the load instructions only take a few processor cycles to execute. That is the good case, but what if b or c, or both, have to come from very far away? Perhaps both of them are in the main memory and then it easily takes hundreds of cycles for the values to arrive in the registers. Meanwhile the processor is doing nothing and simply waits for the data to arrive. Actually, it does something. It burns cycles while waiting. That is a waste of time and energy. Why not use these cycles to execute instructions from another application or thread in case of a parallel program? That is exactly what latency hiding on the SPARC T-Series processors does. It is a hardware feature totally transparent to the user and application. As soon as there is a delay in the execution, the hardware uses these otherwise idle cycles to execute instructions from another process. As a result, the throughput capacity of the system improves because idle cycles are no longer wasted and therefore more jobs can be run per unit of time. This feature has been in the SPARC T-series from the beginning, so why this paper? The difference with previous publications on this topic is in the amount of detail given. How this all works under the hood is fully explained using two example programs. Starting from the assembly language instructions, it is demonstrated in what way these programs execute. To really see what is happening we go down to the processor pipeline level, where the gaps in the execution are, and show in what way these idle cycles are filled by other copies of the same program running simultaneously. Both the SPARC T4 as well as the older UltraSPARC T2+ processor are covered. You may wonder why the UltraSPARC T2+ is included. The focus of this work is on the SPARC T4 processor, but to explain the basic concept of latency hiding at this very low level, we start with the UltraSPARC T2+ processor because it is architecturally a much simpler design. From the single issue, in-order pipelines of this processor we then shift gears and cover how this all works on the much more advanced dual issue, out-of-order architecture of the T4. The analysis and performance experiments have been conducted on both processors. The results depend on the processor, but in all cases the theoretical estimates are confirmed by the experiments. If you're interested to read a lot more about this and find out how things really work under the hood, you can download a copy of the paper here. A paper like this could not have been produced without the help of several other people. I want to thank the co-author of this paper, Jared Smolens, for his very valuable contributions and our highly inspiring discussions. I'm also indebted to Thomas Nau (Ulm University, Germany), Shane Sigler and Mark Woodyard (both at Oracle) for their feedback on earlier versions of this paper. Karen Perkins (Perkins Technical Writing and Editing) and Rick Ramsey at Oracle were very helpful in providing editorial and publishing assistance.

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  • New Analytic settings for the new code

    - by Steve Tunstall
    If you have upgraded to the new 2011.1.3.0 code, you may find some very useful settings for the Analytics. If you didn't already know, the analytic datasets have the potential to fill up your OS hard drives. The more datasets you use and create, that faster this can happen. Since they take a measurement every second, forever, some of these metrics can get in the multiple GB size in a matter of weeks. The traditional 'fix' was that you had to go into Analytics -> Datasets about once a month and clean up the largest datasets. You did this by deleting them. Ouch. Now you lost all of that historical data that you might have wanted to check out many months from now. Or, you had to export each metric individually to a CSV file first. Not very easy or fun. You could also suspend a dataset, and have it not collect data at all. Well, that fixed the problem, didn't it? of course you now had no data to go look at. Hmmmm.... All of this is no longer a concern. Check out the new Settings tab under Analytics... Now, I can tell the ZFSSA to keep every second of data for, say, 2 weeks, and then average those 60 seconds of each minute into a single 'minute' value. I can go even further and ask it to average those 60 minutes of data into a single 'hour' value.  This allows me to effectively shrink my older datasets by a factor of 1/3600 !!! Very cool. I can now allow my datasets to go forever, and really never have to worry about them filling up my OS drives. That's great going forward, but what about those huge datasets you already have? No problem. Another new feature in 2011.1.3.0 is the ability to shrink the older datasets in the same way. Check this out. I have here a dataset called "Disk: I/O opps per second" that is about 6.32M on disk (You need not worry so much about the "In Core" value, as that is in RAM, and it fluctuates all the time. Once you stop viewing a particular metric, you will see that shrink over time, just relax).  When one clicks on the trash can icon to the right of the dataset, it used to delete the whole thing, and you would have to re-create it from scratch to get the data collecting again. Now, however, it gives you this prompt: As you can see, this allows you to once again shrink the dataset by averaging the second data into minutes or hours. Here is my new dataset size after I do this. So it shrank from 6.32MB down to 2.87MB, but i can still see my metrics going back to the time I began the dataset. Now, you do understand that once you do this, as you look back in time to the minute or hour data metrics, that you are going to see much larger time values, right? You will need to decide what size of granularity you can live with, and for how long. Check this out. Here is my Disk: Percent utilized from 5-21-2012 2:42 pm to 4:22 pm: After I went through the delete process to change everything older than 1 week to "Minutes", the same date and time looks like this: Just understand what this will do and how you want to use it. Right now, I'm thinking of keeping the last 6 weeks of data as "seconds", and then the last 3 months as "Minutes", and then "Hours" forever after that. I'll check back in six months and see how the sizes look. Steve 

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  • What is the best practice, point of view of well experienced developers

    - by Damien MIRAS
    My manager pushes me to use his self defined best practices. All of these practices are based on is own assumptions. I disagree with them and I would like to have some feedback of well experienced people about these practices. I would prefer answers from people involved in the maintenance of huge products and people whom have maintained the product for years. Developers with 15+ years of experience are preferred because my manager has that much experience himself. I have 7 years of experience. Here are the practices he wants me to use: never extends classes, use composition and interface instead because extending classes are unmaintainable and difficult to debug. What I think about that Extend when needed, respect "Liskov's Substitution Principle" and you'll never be stuck with a problem, but prefer composition and decoration. I don't know any serious project which has banned inheriting, sometimes it's impossible to not use that, i.e. in a UI framework. Design patterns are just unusable. In PHP, for simple use cases (for example a user needs a web interface to view a database table), his "best practice" is: copy some random php code wich we own, paste and modify it, put html and php code in same file, never use classes in PHP, it doesn't work well for small jobs, and in fact it doesn't work well at all, there is no good tool to work with. Copy & paste PHP code is good practice for maintenance because scripts are independent, if you have a bug somewhere you can fix it without side effects. What I think about that: NEVER EVER COPY code or do it because you have five minutes to deliver something, you will do some refactoring after that. Copy & paste code is a beginners error, if you have errors you'll have the error everywhere any time you have pasted it's a nightmare to maintain. If you repsect the "Open Close Principle" you'll rarely get edge effects, use unit test if you are afraid of that. For small jobs in PHP use at least something you get or write the HTML separately from the PHP code and reuse it any time you need it. Classes in PHP are mature, not as mature as other languages like python or java, but they are usable. There is tools to work with classes in PHP like Zend Studio that work very well. The use of classes or not depends not on the language you use but the programming paradigm you have choosen. I'm a OOP developer, I use PHP5, why do I have to shoot myself in the foot? When you find a simple bug in the code, and you can fix it simply, if you are not working on the code where you have found it, never fix it, even if it takes 5 seconds. He says to me his "best practices" are driven by the fact that he has a lot of experience in maintaining software in production (14 years) and he now knows what works and what doesn't work, what the community says is a fad, and the people advocating such principles as never copy & paste code, are not evolved in maintaining applications. What I think about that: If you find a bug fix it if you can do it quickly inform the people who've touched that code before, check if you have not introduced a new bug, ideally add a unit test for it. I currently work on a web commerce project, which serves 15k unique users per day. The code base has to be maintained and has been maintained this way since 2005. Ideally you include a short description of your position and experience in terms of years effectively maintaining an application which has been in production for real.

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  • Roles / Profiles / Perspectives in NetBeans IDE 7.1

    - by Geertjan
    With a check out of main-silver from yesterday, I'm able to use the brand new "role" attribute in @TopComponent.Registration, as you can see below, in the bit in bold: @ConvertAsProperties(dtd = "-//org.role.demo.ui//Admin//EN", autostore = false) @TopComponent.Description(preferredID = "AdminTopComponent", //iconBase="SET/PATH/TO/ICON/HERE", persistenceType = TopComponent.PERSISTENCE_ALWAYS) @TopComponent.Registration(mode = "editor", openAtStartup = true, role="admin") public final class AdminTopComponent extends TopComponent { And here's a window for general users of the application, with the "role" attribute set to "user": @ConvertAsProperties(dtd = "-//org.role.demo.ui//User//EN", autostore = false) @TopComponent.Description(preferredID = "UserTopComponent", //iconBase="SET/PATH/TO/ICON/HERE", persistenceType = TopComponent.PERSISTENCE_ALWAYS) @TopComponent.Registration(mode = "explorer", openAtStartup = true, role="user") public final class UserTopComponent extends TopComponent { So, I have two windows. One is assigned to the "admin" role, the other to the "user" role. In the "ModuleInstall" class, I add a "WindowSystemListener" and set "user" as the application's role: public class Installer extends ModuleInstall implements WindowSystemListener { @Override public void restored() { WindowManager.getDefault().addWindowSystemListener(this); } @Override public void beforeLoad(WindowSystemEvent event) { WindowManager.getDefault().setRole("user"); WindowManager.getDefault().removeWindowSystemListener(this); } @Override public void afterLoad(WindowSystemEvent event) { } @Override public void beforeSave(WindowSystemEvent event) { } @Override public void afterSave(WindowSystemEvent event) { } } So, when the application starts, the "UserTopComponent" is shown, not the "AdminTopComponent". Next, I have two Actions, for switching between the two roles, as shown below: @ActionID(category = "Window", id = "org.role.demo.ui.SwitchToAdminAction") @ActionRegistration(displayName = "#CTL_SwitchToAdminAction") @ActionReferences({ @ActionReference(path = "Menu/Window", position = 250) }) @Messages("CTL_SwitchToAdminAction=Switch To Admin") public final class SwitchToAdminAction extends AbstractAction { @Override public void actionPerformed(ActionEvent e) { WindowManager.getDefault().setRole("admin"); } @Override public boolean isEnabled() { return !WindowManager.getDefault().getRole().equals("admin"); } } @ActionID(category = "Window", id = "org.role.demo.ui.SwitchToUserAction") @ActionRegistration(displayName = "#CTL_SwitchToUserAction") @ActionReferences({ @ActionReference(path = "Menu/Window", position = 250) }) @Messages("CTL_SwitchToUserAction=Switch To User") public final class SwitchToUserAction extends AbstractAction { @Override public void actionPerformed(ActionEvent e) { WindowManager.getDefault().setRole("user"); } @Override public boolean isEnabled() { return !WindowManager.getDefault().getRole().equals("user"); } } When I select one of the above actions, the role changes, and the other window is shown. I could, of course, add a Login dialog to the "SwitchToAdminAction", so that authentication is required in order to switch to the "admin" role. Now, let's say I am now in the "user" role. So, the "UserTopComponent" shown above is now opened. I decide to also open another window, the Properties window, as below... ...and, when I am in the "admin" role, when the "AdminTopComponent" is open, I decide to also open the Output window, as below... Now, when I switch from one role to the other, the additional window/s I opened will also be opened, together with the explicit members of the currently selected role. And, the main window position and size are also persisted across roles. When I look in the "build" folder of my project in development, I see two different Windows2Local folders, one per role, automatically created by the fact that there is something to be persisted for a particular role, e.g., when a switch to a different role is done: And, with that, we now clearly have roles/profiles/perspectives in NetBeans Platform applications from NetBeans Platform 7.1 onwards.

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  • 11.10 desktop alerts (volume change and terminal bell) stopped working but all other audio still works

    - by FlabbergastedPickle
    All, My sound works just fine in 11.10 64-bit install on HP dm1-4050 Sandy Bridge notebook (e.g. audio works in Banshee, flash, games, browser, Thunderbird email notification, etc.), but the core desktop notifications (e.g. pressing a tab in a terminal where there is more than one option should trigger a terminal bell, or changing volume using volume keys should be accompanied with the supporting "quack" that the volume app makes) do not work. I've intentionally disabled login sound as explained here on ask ubuntu but even enabling it back makes no difference. These notifications did work before just fine and I am not sure when did the actually stop working but it must've been fairly recently. Only things I did were trying to install some ppa edge xorg drivers for my intel card (a separate issue) but also reverted them all with ppa-purge once I discovered they did not improve anything. Other thing I did was check volume settings with alsamixer and did alsactl store for the soundcard after I did some experimenting with volume settings for PCM (on my laptop PCM at 100% crackles so I had to lower it and make pulseaudio ignore its setting as per ask ubuntu's page). That said, neither of these should have any bearing on the said notifications since the volume is up and they clearly work everywhere else but the core desktop events. The system ready drum sound when Ubuntu boots and user reaches the login screen also does not work. The guest login behaves exactly same as mine. Audio works (including the login sound since I've not disabled it for the guest account), but no quacks when changing the volume or terminal bell sounds... I've tried copying ubuntu sounds to /usr/share/sounds/ as suggested on ask ubuntu and that did not work. I also tried using dconf-editor to check sound theme settings and tried both freedesktop (which is what it was set to) and ubuntu, as suggested on ask ubuntu. This did not work either. I tried purging the ~/.pulse folder and the /tmp/*pulse* entries, rebooting and restarting pulseaudio with -D flag. While audio came back on and behaved just fine in all aspects (e.g. one can adjust volume levels, play music, games, in-browser sound stuff, and other app alerts) except for the system ready drum sound (at the login screen), and any system event (terminal bell and volume change quack sound). It is interesting that the quack sound works inside system settings-sound when adjusting levels there, but it does not when volume is changed via top bar's volume settings... I do recall that at one point yesterday when I was restarting pulseaudio the quacks that accompany volume change did start working but I have no idea what caused that. This was also when I first realized those alerts were not working. After rebooting it was again gone. I did compile my own 3.0.14-rt31 kernel a little while ago as instructed on one of the wiki's for the 11.10 rt kernel. Everything works as before except for the said sound alerts. I am not sure if this began happening since I started using the rt kernel though and yesterday's momentary ability to hear those quacks while changing the volume make me believe that the kernel is not one responsible for this problem. One more thing I can think of is that I used alsoft-conf tool to configure buffering on the OpenAL (due to TA Spring's choppy audio) and changed in there default audio device to ALSA. I also tried reverting it to Pulseaudio as the only allowed output but the bottom part of the Backend tab always reverts to ALSA even when I select Pulseaudio. The pulseaudio does remain as the only active choice on top. This, however, once again does not make any sense in terms of preventing desktop audio alerts when everything else including OpenAL games plays sound just fine... So, there you have it, as verbose as I could make it :-). I tried all I could find on this issue and had no luck so far... Any ideas?

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  • Reducing Deadlocks - not a DBA issue ?

    - by steveh99999
     As a DBA, I'm involved on an almost daily basis troubleshooting 'SQL Server' performance issues. Often, this troubleshooting soon veers away from a 'its a SQL Server issue' to instead become a wider application/database design/coding issue.One common perception with SQL Server is that deadlocking is an application design issue - and is fixed by recoding...  I see this reinforced by MCP-type questions/scenarios where the answer to prevent deadlocking is simply to change the order in code in which tables are accessed....Whilst this is correct, I do think this has led to a situation where many 'operational' or 'production support' DBAs, when faced with a deadlock, are happy to throw the issue over to developers without analysing the issue further....A couple of 'war stories' on deadlocks which I think are interesting :- Case One , I had an issue recently on a third-party application that I support on SQL 2008.  This particular third-party application has an unusual support agreement where the customer is allowed to change the index design on the third-party provided database.  However, we are not allowed to alter application code or modify table structure..This third-party application is also known to encounter occasional deadlocks – indeed, I have documentation from the vendor that up to 50 deadlocks per day is not unusual !So, as a DBA I have to support an application which in my opinion has too many deadlocks - but, I cannot influence the design of the tables or stored procedures for the application. This should be the classic - blame the third-party developers scenario, and hope this issue gets addressed in a future application release - ie we could wait years for this to be resolved and implemented in our production environment...But, as DBAs  can change the index layout, is there anything I could do still to reduce the deadlocks in the application ?I initially used SQL traceflag 1222 to write deadlock detection output to the SQL Errorlog – using this I was able to identify one table heavily involved in the deadlocks.When I examined the table definition, I was surprised to see it was a heap – ie no clustered index existed on the table.Using SQL profiler to see locking behaviour and plan for the query involved in the deadlock, I was able to confirm a table scan was being performed.By creating an appropriate clustered index - it was possible to produce a more efficient plan and locking behaviour.So, less locks, held for less time = less possibility of deadlocks. I'm still unhappy about the overall number of deadlocks on this system - but that's something to be discussed further with the vendor.Case Two,  a system which hadn't changed for months suddenly started seeing deadlocks on a regular basis. I love the 'nothing's changed' scenario, as it gives me the opportunity to appear wise and say 'nothings changed on this system, except the data'.. This particular deadlock occurred on a table which had been growing rapidly. By using DBCC SHOW_STATISTICS - the DBA team were able to see that the deadlocks seemed to be occurring shortly after auto-update stats had regenerated the table statistics using it's default sampling behaviour.As a quick fix, we were able to schedule a nightly UPDATE STATISTICS WITH FULLSCAN on the table involved in the deadlock - thus, greatly reducing the potential for stats to be updated via auto_update_stats, consequently reducing the potential for a bad plan to be generated based on an unrepresentative sample of the data. This reduced the possibility of a deadlock occurring.  Not a perfect solution by any means, but quick, easy to implement, and needed no application code changes. This fix gave us some 'breathing space'  to properly fix the code during the next scheduled application release.   The moral of this post - don't dismiss deadlocks as issues that can only be fixed by developers...

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  • Good DBAs Do Baselines

    - by Louis Davidson
    One morning, you wake up and feel funny. You can’t quite put your finger on it, but something isn’t quite right. What now? Unless you happen to be a hypochondriac, you likely drag yourself out of bed, get on with the day and gather more “evidence”. You check your symptoms over the next few days; do you feel the same, better, worse? If better, then great, it was some temporal issue, perhaps caused by an allergic reaction to some suspiciously spicy chicken. If the same or worse then you go to the doctor for some health advice, but armed with some data to share, and having ruled out certain possible causes that are fixed with a bit of rest and perhaps an antacid. Whether you realize it or not, in comparing how you feel one day to the next, you have taken baseline measurements. In much the same way, a DBA uses baselines to gauge the gauge health of their database servers. Of course, while SQL Server is very willing to share data regarding its health and activities, it has almost no idea of the difference between good and bad. Over time, experienced DBAs develop “mental” baselines with which they can gauge the health of their servers almost as easily as their own body. They accumulate knowledge of the daily, natural state of each part of their database system, and so know instinctively when one of their databases “feels funny”. Equally, they know when an “issue” is just a passing tremor. They see their SQL Server with all of its four CPU cores running close 100% and don’t panic anymore. Why? It’s 5PM and every day the same thing occurs when the end-of-day reports, which are very CPU intensive, are running. Equally, they know when they need to respond in earnest when it is the first time they have heard about an issue, even if it has been happening every day. Nevertheless, no DBA can retain mental baselines for every characteristic of their systems, so we need to collect physical baselines too. In my experience, surprisingly few DBAs do this very well. Part of the problem is that SQL Server provides a lot of instrumentation. If you look, you will find an almost overwhelming amount of data regarding user activity on your SQL Server instances, and use and abuse of the available CPU, I/O and memory. It seems like a huge task even to work out which data you need to collect, let alone start collecting it on a regular basis, managing its storage over time, and performing detailed comparative analysis. However, without baselines, though, it is very difficult to pinpoint what ails a server, just by looking at a single snapshot of the data, or to spot retrospectively what caused the problem by examining aggregated data for the server, collected over many months. It isn’t as hard as you think to get started. You’ve probably already established some troubleshooting queries of the type SELECT Value FROM SomeSystemTableOrView. Capturing a set of baseline values for such a query can be as easy as changing it as follows: INSERT into BaseLine.SomeSystemTable (value, captureTime) SELECT Value, SYSDATETIME() FROM SomeSystemTableOrView; Of course, there are monitoring tools that will collect and manage this baseline data for you, automatically, and allow you to perform comparison of metrics over different periods. However, to get yourself started and to prove to yourself (or perhaps the person who writes the checks for tools) the value of baselines, stick something similar to the above query into an agent job, running every hour or so, and you are on your way with no excuses! Then, the next time you investigate a slow server, and see x open transactions, y users logged in, and z rows added per hour in the Orders table, compare to your baselines and see immediately what, if anything, has changed!

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  • BizTalk&ndash;Mapping repeating EDI segments using a Table Looping functoid

    - by Bill Osuch
    BizTalk’s HIPAA X12 schemas have several repeating date/time segments in them, where the XML winds up looking something like this: <DTM_StatementDate> <DTM01_DateTimeQualifier>232</DTM01_DateTimeQualifier> <DTM02_ClaimDate>20120301</DTM02_ClaimDate> </DTM_StatementDate> <DTM_StatementDate> <DTM01_DateTimeQualifier>233</DTM01_DateTimeQualifier> <DTM02_ClaimDate>20120302</DTM02_ClaimDate> </DTM_StatementDate> The corresponding EDI segments would look like this: DTM*232*20120301~ DTM*233*20120302~ The DateTimeQualifier element indicates whether it’s the start date or end date – 232 for start, 233 for end. So in this example (an X12 835) we’re saying the statement starts on 3/1/2012 and ends on 3/2/2012. When you’re mapping from some other data format, many times your start and end dates will be within the same node, like this: <StatementDates> <Begin>20120301</Begin> <End>20120302</End> </StatementDates> So how do you map from that and create two repeating segments in your destination map? You could connect both the <Begin> and <End> nodes to a looping functoid, and connect its output to <DTM_StatementDate>, then connect both <Begin> and <End> to <DTM_StatementDate> … this would give you two repeating segments, each with the correct date, but how to add the correct qualifier? The answer is the Table Looping Functoid! To test this, let’s create a simplified schema that just contains the date fields we’re mapping. First, create your input schema: And your output schema: Now create a map that uses these two schemas, and drag a Table Looping functoid onto it. The first input parameter configures the scope (or how many times the records will loop), so drag a link from the StatementDates node over to the functoid. Yes, StatementDates only appears once, so this would make it seem like it would only loop once, but you’ll see in just a minute. The second parameter in the functoid is the number of columns in the output table. We want to fill two fields, so just set this to 2. Now drag the Begin and End nodes over to the functoid. Finally, we want to add the constant values for DateTimeQualifier, so add a value of 232 and another of 233. When all your inputs are configured, it should look like this: Now we’ll configure the output table. Click on the Table Looping Grid, and configure it to look like this: Microsoft’s description of this functoid says “The Table Looping functoid repeats with the looping record it is connected to. Within each iteration, it loops once per row in the table looping grid, producing multiple output loops.” So here we will loop (# of <StatementDates> nodes) * (Rows in the table), or 2 times. Drag two Table Extractor functoids onto the map; these are what are going to pull the data we want out of the table. The first input to each of these will be the output of the TableLooping functoid, and the second input will be the row number to pull from. So the functoid connected to <DTM01_DateTimeQualifier> will look like this: Connect these two functoids to the two nodes we want to populate, and connect another output from the Table Looping functoid to the <DTM_StatementDate> record. You should have a map that looks something like this: Create some sample xml, use it as the TestMap Input Instance, and you should get a result like the XML at the top of this post. Technorati Tags: BizTalk, EDI, Mapping

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  • Doubts about several best practices for rest api + service layer

    - by TheBeefMightBeTough
    I'm going to be starting a project soon that exposes a restful api for business intelligence. It may not be limited to a restful api, so I plan to delegate requests to a service layer that then coordinates multiple domain objects (each of which have business logic local to the object). The api will likely have many calls as it is a long-term project. While thinking about the design, I recalled a few best practices. 1) Use command objects at the controller layer (I'm using Spring MVC). 2) Use DTOs at the service layer. 3) Validate in both the controller and service layer, though for different reasons. I have my doubts about these recommendations. 1) Using command objects adds a lot of extra single-purpose classes (potentially one per request). What exactly is the benefit? Annotation based validation can be done using this approach, sure. What if I have two requests that take the same parameters, but have different validation requirements? I would have to have two different classes with exactly the same members but different annotations? Bleh. 2) I have heard that using DTOs is preferable to parameters because it makes for more maintainable code down the road (say, e.g., requirements change and the service parameters need to be altered). I don't quite understand this. Shouldn't an api be more-or-less set in stone? I would understand that in the early phases of a project (or, especially, an entire company) the domain itself will not be well understood, and thus core domain objects may change along with the apis that manipulate these objects. At this point however the number of api methods should be small and their dependents few, so changes to the methods could easily be tolerated from a maintainability standpoint. In a large api with many methods and a substantial domain model, I would think having a DTO for potentially each domain object would become unwieldy. Am I misunderstanding something here? 3) I see validation in the controller and service layer as redundant in most cases. Why would I validate that parameters are not null and are in general well formed in the controller if the service is going to do exactly the same (and more). Couldn't I just do all the validation in the service and throw a runtime exception with a list of bad parameters then catch that in the controller to make the error messages more presentable? Better yet, couldn't I just make the error messages user-friendly in the service and let the exception trickle up to a global handler (ControllerAdvice in spring, for example)? Is there something wrong with either of these approaches? (I do see a use case for controller validation if the input does not map one-to-one with the service input, but since the controllers are for a rest api and not forms, the api parameters will probably map directly to service parameters.) I do also have a question about unchecked vs checked exceptions. Namely, I'm not really sure why I'd ever want to use a checked exception. Every time I have seen them used they just get wrapped into general exceptions (DomainException, SystemException, ApplicationException, w/e) to reduce the signature length of methods, or devs catch Exception rather than dealing with the App1Exception, App2Exception, Sys1Exception, Sys2Exception. I don't see how either of these practices is very useful. Why not just use unchecked exceptions always and catch the ones you actually do care about? You could just document what unchecked exceptions the method throws.

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  • Taking HRMS to the Cloud to Simplify Human Resources Management

    - by HCM-Oracle
    By Anke Mogannam With human capital management (HCM) a top-of-mind issue for executives in every industry, human resources (HR) organizations are poised to have their day in the sun—proving not just their administrative worth but their strategic value as well.  To make good on that promise, however, HR must modernize. Indeed, if HR is to act as an agent of change—providing the swift reallocation of employees  and the rapid absorption of employee data required for enterprises to shift course on a dime—it must first deal with the disruptive change at its own front door. And increasingly, that means choosing the right technology and human resources management system (HRMS) for managing the entire employee lifecycle. Unfortunately, for most organizations, this task has proved easier said than done. This is because while much has been written about advances in HRMS technology, until recently, most of those advances took the form of disparate on-premises solutions designed to serve very specific purposes. Although this may have resulted in key competencies in certain areas, it also meant that processes for core HR functions like payroll and benefits were being carried out in separate systems from those used for talent management, workforce optimization, training, and so on. With no integration—and no single system of record—processes were disconnected, ease of use was impeded, user experience was diminished, and vital data was left untapped.  Today, however, that scenario has begun to change, and end-to-end cloud-based HCM solutions have moved from wished-for innovations to real-life solutions. Why, then, have HR organizations been so slow in adopting them? The answer—it would seem—is, “It’s complicated.” So complicated, in fact, that 45 percent of the respondents to PwC’s “Annual HR Technology Survey” (for 2013) reported having no formal HR software roadmap, and 40 percent stated that they “did not know” whether their organizations would be increasing their use of cloud or software as a service (SaaS) for HR.  Clearly, HR organizations need help sorting through the morass of HR software options confronting them. But just as clearly, there’s an enormous opportunity awaiting those that do. The trick will come in charting a course that allows HR to leverage existing technology while investing in the cloud-based solutions that will deliver the end-to-end processes, easy-to-understand analytics, and superior adaptability required to simplify—and add value to—every aspect of employee management. The Opportunity therefore is to cut costs, drive Innovation, and increase engagement by moving to cloud-based HCM.  Then you will benefit from one Interface, leverage many access points, and  gain at-a-glance insight across your entire workforce. With many legacy on-premises HR systems not being efficient anymore and cloud-based, integrated systems that span the range of HR functions finally reaching maturity, the time is ripe for moving core HR to the cloud. Indeed, for the first time ever there are more HRMS replacement initiatives than HRMS upgrade initiatives under way, and the majority of them involve moving to the cloud per Cedar Crestone’s 2013-2014 HRMS survey. To learn how you can launch your own cloud HCM initiative and begin using HR to power the enterprise, visit Oracle HRMS in the Cloud and Oracle’s new customer 2 cloud program. Anke Mogannam brings more than 16 years of marketing and human capital management experience in the technology industries to her role at Oracle where she is part of the Human Capital Management applications marketing team. In that role, Anke drives content marketing, messaging, go-to-market activities, integrated marketing campaigns, and field enablement. Prior to joining Oracle, Anke held several roles in communications, marketing, HCM product strategy and product management at PeopleSoft, SAP, Workday and Saba. Follow her on Twitter @amogannam

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  • How can I gather client's data on Google App Engine without using Datastore/Backend Instances too much?

    - by ruslan
    One of the projects I'm working on is online survey engine. It's my first big commercial project on Google App Engine. I need your advice on how to collect stats and efficiently record them in DataStore without bankrupting me. Initial requirements are: After user finishes survey client sends list of pairs [ID (int) + PercentHit (double)]. This list shows how close answers of this user match predefined answers of reference answerers (which identified by IDs). I call them "target IDs". Creator of the survey wants to see aggregated % for given IDs for last hour, particular timeframe or from the beginning of the survey. Some surveys may have thousands of target/reference answerers. So I created entity public class HitsStatsDO implements Serializable { @Id transient private Long id; transient private Long version = (long) 0; transient private Long startDate; @Parent transient private Key parent; // fake parent which contains target id @Transient int targetId; private double avgPercent; private long hitCount; } But writing HitsStatsDO for each target from each user would give a lot of data. For instance I had a survey with 3000 targets which was answered by ~4 million people within one week with 300K people taking survey in first day. Even if we assume they were answering it evenly for 24 hours it would give us ~1040 writes/second. Obviously it hits concurrent writes limit of Datastore. I decided I'll collect data for one hour and save that, that's why there are avgPercent and hitCount in HitsStatsDO. GAE instances are stateless so I had to use dynamic backend instance. There I have something like this: // Contains stats for one hour private class Shard { ReadWriteLock lock = new ReentrantReadWriteLock(); Map<Integer, HitsStatsDO> map = new HashMap<Integer, HitsStatsDO>(); // Key is target ID public void saveToDatastore(); public void updateStats(Long startDate, Map<Integer, Double> hits); } and map with shard for current hour and previous hour (which doesn't stay here for long) private HashMap<Long, Shard> shards = new HashMap<Long, Shard>(); // Key is HitsStatsDO.startDate So once per hour I dump Shard for previous hour to Datastore. Plus I have class LifetimeStats which keeps Map<Integer, HitsStatsDO> in memcached where map-key is target ID. Also in my backend shutdown hook method I dump stats for unfinished hour to Datastore. There is only one major issue here - I have only ONE backend instance :) It raises following questions on which I'd like to hear your opinion: Can I do this without using backend instance ? What if one instance is not enough ? How can I split data between multiple dynamic backend instances? It hard because I don't know how many I have because Google creates new one as load increases. I know I can launch exact number of resident backend instances. But how many ? 2, 5, 10 ? What if I have no load at all for a week. Constantly running 10 backend instances is too expensive. What do I do with data from clients while backend instance is dead/restarting?

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  • XNA Multiplayer Games and Networking

    - by JoshReuben
    ·        XNA communication must by default be lightweight – if you are syncing game state between players from the Game.Update method, you must minimize traffic. That game loop may be firing 60 times a second and player 5 needs to know if his tank has collided with any player 3 and the angle of that gun turret. There are no WCF ServiceContract / DataContract niceties here, but at the same time the XNA networking stack simplifies the details. The payload must be simplistic - just an ordered set of numbers that you would map to meaningful enum values upon deserialization.   Overview ·        XNA allows you to create and join multiplayer game sessions, to manage game state across clients, and to interact with the friends list ·        Dependency on Gamer Services - to receive notifications such as sign-in status changes and game invitations ·        two types of online multiplayer games: system link game sessions (LAN) and LIVE sessions (WAN). ·        Minimum dev requirements: 1 Xbox 360 console + Creators Club membership to test network code - run 1 instance of game on Xbox 360, and 1 on a Windows-based computer   Network Sessions ·        A network session is made up of players in a game + up to 8 arbitrary integer properties describing the session ·        create custom enums – (e.g. GameMode, SkillLevel) as keys in NetworkSessionProperties collection ·        Player state: lobby, in-play   Session Types ·        local session - for split-screen gaming - requires no network traffic. ·        system link session - connects multiple gaming machines over a local subnet. ·        Xbox LIVE multiplayer session - occurs on the Internet. Ranked or unranked   Session Updates ·        NetworkSession class Update method - must be called once per frame. ·        performs the following actions: o   Sends the network packets. o   Changes the session state. o   Raises the managed events for any significant state changes. o   Returns the incoming packet data. ·        synchronize the session à packet-received and state-change events à no threading issues   Session Config ·        Session host - gaming machine that creates the session. XNA handles host migration ·        NetworkSession properties: AllowJoinInProgress , AllowHostMigration ·        NetworkSession groups: AllGamers, LocalGamers, RemoteGamers   Subscribe to NetworkSession events ·        GamerJoined ·        GamerLeft ·        GameStarted ·        GameEnded – use to return to lobby ·        SessionEnded – use to return to title screen   Create a Session session = NetworkSession.Create(         NetworkSessionType.SystemLink,         maximumLocalPlayers,         maximumGamers,         privateGamerSlots,         sessionProperties );   Start a Session if (session.IsHost) {     if (session.IsEveryoneReady)     {        session.StartGame();        foreach (var gamer in SignedInGamer.SignedInGamers)        {             gamer.Presence.PresenceMode =                 GamerPresenceMode.InCombat;   Find a Network Session AvailableNetworkSessionCollection availableSessions = NetworkSession.Find(     NetworkSessionType.SystemLink,       maximumLocalPlayers,     networkSessionProperties); availableSessions.AllowJoinInProgress = true;   Join a Network Session NetworkSession session = NetworkSession.Join(     availableSessions[selectedSessionIndex]);   Sending Network Data var packetWriter = new PacketWriter(); foreach (LocalNetworkGamer gamer in session.LocalGamers) {     // Get the tank associated with this player.     Tank myTank = gamer.Tag as Tank;     // Write the data.     packetWriter.Write(myTank.Position);     packetWriter.Write(myTank.TankRotation);     packetWriter.Write(myTank.TurretRotation);     packetWriter.Write(myTank.IsFiring);     packetWriter.Write(myTank.Health);       // Send it to everyone.     gamer.SendData(packetWriter, SendDataOptions.None);     }   Receiving Network Data foreach (LocalNetworkGamer gamer in session.LocalGamers) {     // Keep reading while packets are available.     while (gamer.IsDataAvailable)     {         NetworkGamer sender;          // Read a single packet.         gamer.ReceiveData(packetReader, out sender);          if (!sender.IsLocal)         {             // Get the tank associated with this packet.             Tank remoteTank = sender.Tag as Tank;              // Read the data and apply it to the tank.             remoteTank.Position = packetReader.ReadVector2();             …   End a Session if (session.AllGamers.Count == 1)         {             session.EndGame();             session.Update();         }   Performance •        Aim to minimize payload, reliable in order messages •        Send Data Options: o   Unreliable, out of order -(SendDataOptions.None) o   Unreliable, in order (SendDataOptions.InOrder) o   Reliable, out of order (SendDataOptions.Reliable) o   Reliable, in order (SendDataOptions.ReliableInOrder) o   Chat data (SendDataOptions.Chat) •        Simulate: NetworkSession.SimulatedLatency , NetworkSession.SimulatedPacketLoss •        Voice support – NetworkGamer properties: HasVoice ,IsTalking , IsMutedByLocalUser

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