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  • Is there a faster way to remove un-referenced controls from a Form's designer file?

    - by Eric
    I started looking into the designer file of one of my Forms and noticed that a lot of the old controls I thought I had deleted are still being instantiated but are not actually used on the form. Is there any easy way to clean up these controls from the designer file that are not being used? Right now I've printed out a list of all the private fields at the bottom of the designer file that reference the controls of the form. I'm going down the list one by one trying to determine if the control is actually used or not, and then deleting those that I find are not on the form. The document outline is useful for figuring out what controls are on the form, but this is still a rather tedious process. Does anyone have a better way?

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  • Is it faster to count down that it is to count up?

    - by Bob
    Our computer science teacher once said that for some reason it is more efficient to count down that count up. For example if you need to use a FOR loop and the loop index is not used somewhere (like printing a line of N * to the screen) I mean that code like this : for (i=N; i>=0; i--) putchar('*'); is better than: for (i=0; i<N; i++) putchar('*'); Is it really true? and if so does anyone know why?

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  • SQL & PHP - Which is faster mysql_num_rows() or 'select count()'?

    - by Joel
    I'm just wondering which method is the most effective if I'm literally just wanting to get the number of rows in a table. $res = mysql_query("SELECT count(*) as `number` FROM `table1`"); $count = mysql_fetch_result($res,0,'number'); or $res = mysql_query("SELECT `ID` FROM `table1`"); $count = mysql_num_rows($res); Anyone done any decent testing on this?

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  • Better to develop Ruby project on server or buy a faster desktop computer? B/c laptop too slow.

    - by user33184
    I have a Linux laptop (Vostro V13) running a Celeron M chip. This is a fine laptop, but running unit tests especially for Rails applications is slow. I want a faster development environment but I don't want to spend too much money. So the choice I have is between $390 for a Linux desktop machine with a Pentium Dual Core Processor E5400 and just paying between $30 and $40 a month to Linode and trying to do development remotely on that server. Can anyone with experience developing server applications using both methods offer any advice?

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  • Is "for(;;)" faster than "while (TRUE)"? If not, why do people use it?

    - by Chris Cooper
    for (;;) { //Something to be done repeatedly } I have seen this sort of thing used a lot, but I think it is rather strange... Wouldn't it be much clearer to say while (TRUE), or something along those lines? I'm guessing that (as is the reason for many-a-programmer to resort to cryptic code) this is a tiny margin faster? Why, and is it REALLY worth it? If so, why not just define it this way: #DEFINE while(TRUE) for(;;)

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  • Internet connectivity

    - by user309281
    Hi All Basically want to know the different factors which will help in having faster Internet experience, ie. faster upload and download. In this, how browsers like IE, mozilla, opera play in enabling faster internet connections ?

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  • Why is preserving the pitch in audio playback (allegedly) less performant?

    - by Markus Unterwaditzer
    In VLC for Android, i discovered an option to preserve the pitch during faster-than-normal playback: The "requires a fast device" obviously implies that faster playback is more performant when the pitch is changed too. Why is that so? What i've tried: Before posting this question i did some shallow research through Google. According to Wikipedia, there are several methods for faster playback of audio, the "simplest" one (Resampling) changes the pitch.

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  • Parallelism in .NET – Introduction

    - by Reed
    Parallel programming is something that every professional developer should understand, but is rarely discussed or taught in detail in a formal manner.  Software users are no longer content with applications that lock up the user interface regularly, or take large amounts of time to process data unnecessarily.  Modern development requires the use of parallelism.  There is no longer any excuses for us as developers. Learning to write parallel software is challenging.  It requires more than reading that one chapter on parallelism in our programming language book of choice… Today’s systems are no longer getting faster with each generation; in many cases, newer computers are actually slower than previous generation systems.  Modern hardware is shifting towards conservation of power, with processing scalability coming from having multiple computer cores, not faster and faster CPUs.  Our CPU frequencies no longer double on a regular basis, but Moore’s Law is still holding strong.  Now, however, instead of scaling transistors in order to make processors faster, hardware manufacturers are scaling the transistors in order to add more discrete hardware processing threads to the system. This changes how we should think about software.  In order to take advantage of modern systems, we need to redesign and rewrite our algorithms to work in parallel.  As with any design domain, it helps tremendously to have a common language, as well as a common set of patterns and tools. For .NET developers, this is an exciting time for parallel programming.  Version 4 of the .NET Framework is adding the Task Parallel Library.  This has been back-ported to .NET 3.5sp1 as part of the Reactive Extensions for .NET, and is available for use today in both .NET 3.5 and .NET 4.0 beta. In order to fully utilize the Task Parallel Library and parallelism, both in .NET 4 and previous versions, we need to understand the proper terminology.  For this series, I will provide an introduction to some of the basic concepts in parallelism, and relate them to the tools available in .NET.

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  • How to Avoid Your Next 12-Month Science Project

    - by constant
    While most customers immediately understand how the magic of Oracle's Hybrid Columnar Compression, intelligent storage servers and flash memory make Exadata uniquely powerful against home-grown database systems, some people think that Exalogic is nothing more than a bunch of x86 servers, a storage appliance and an InfiniBand (IB) network, built into a single rack. After all, isn't this exactly what the High Performance Computing (HPC) world has been doing for decades? On the surface, this may be true. And some people tried exactly that: They tried to put together their own version of Exalogic, but then they discover there's a lot more to building a system than buying hardware and assembling it together. IT is not Ikea. Why is that so? Could it be there's more going on behind the scenes than merely putting together a bunch of servers, a storage array and an InfiniBand network into a rack? Let's explore some of the special sauce that makes Exalogic unique and un-copyable, so you can save yourself from your next 6- to 12-month science project that distracts you from doing real work that adds value to your company. Engineering Systems is Hard Work! The backbone of Exalogic is its InfiniBand network: 4 times better bandwidth than even 10 Gigabit Ethernet, and only about a tenth of its latency. What a potential for increased scalability and throughput across the middleware and database layers! But InfiniBand is a beast that needs to be tamed: It is true that Exalogic uses a standard, open-source Open Fabrics Enterprise Distribution (OFED) InfiniBand driver stack. Unfortunately, this software has been developed by the HPC community with fastest speed in mind (which is good) but, despite the name, not many other enterprise-class requirements are included (which is less good). Here are some of the improvements that Oracle's InfiniBand development team had to add to the OFED stack to make it enterprise-ready, simply because typical HPC users didn't have the need to implement them: More than 100 bug fixes in the pieces that were not related to the Message Passing Interface Protocol (MPI), which is the protocol that HPC users use most of the time, but which is less useful in the enterprise. Performance optimizations and tuning across the whole IB stack: From Switches, Host Channel Adapters (HCAs) and drivers to low-level protocols, middleware and applications. Yes, even the standard HPC IB stack could be improved in terms of performance. Ethernet over IB (EoIB): Exalogic uses InfiniBand internally to reach high performance, but it needs to play nicely with datacenters around it. That's why Oracle added Ethernet over InfiniBand technology to it that allows for creating many virtual 10GBE adapters inside Exalogic's nodes that are aggregated and connected to Exalogic's IB gateway switches. While this is an open standard, it's up to the vendor to implement it. In this case, Oracle integrated the EoIB stack with Oracle's own IB to 10GBE gateway switches, and made it fully virtualized from the beginning. This means that Exalogic customers can completely rewire their server infrastructure inside the rack without having to physically pull or plug a single cable - a must-have for every cloud deployment. Anybody who wants to match this level of integration would need to add an InfiniBand switch development team to their project. Or just buy Oracle's gateway switches, which are conveniently shipped with a whole server infrastructure attached! IPv6 support for InfiniBand's Sockets Direct Protocol (SDP), Reliable Datagram Sockets (RDS), TCP/IP over IB (IPoIB) and EoIB protocols. Because no IPv6 = not very enterprise-class. HA capability for SDP. High Availability is not a big requirement for HPC, but for enterprise-class application servers it is. Every node in Exalogic's InfiniBand network is connected twice for redundancy. If any cable or port or HCA fails, there's always a replacement link ready to take over. This requires extra magic at the protocol level to work. So in addition to Weblogic's failover capabilities, Oracle implemented IB automatic path migration at the SDP level to avoid unnecessary failover operations at the middleware level. Security, for example spoof-protection. Another feature that is less important for traditional users of InfiniBand, but very important for enterprise customers. InfiniBand Partitioning and Quality-of-Service (QoS): One of the first questions we get from customers about Exalogic is: “How can we implement multi-tenancy?” The answer is to partition your IB network, which effectively creates many networks that work independently and that are protected at the lowest networking layer possible. In addition to that, QoS allows administrators to prioritize traffic flow in multi-tenancy environments so they can keep their service levels where it matters most. Resilient IB Fabric Management: InfiniBand is a self-managing network, so a lot of the magic lies in coming up with the right topology and in teaching the subnet manager how to properly discover and manage the network. Oracle's Infiniband switches come with pre-integrated, highly available fabric management with seamless integration into Oracle Enterprise Manager Ops Center. In short: Oracle elevated the OFED InfiniBand stack into an enterprise-class networking infrastructure. Many years and multiple teams of manpower went into the above improvements - this is something you can only get from Oracle, because no other InfiniBand vendor can give you these features across the whole stack! Exabus: Because it's not About the Size of Your Network, it's How You Use it! So let's assume that you somehow were able to get your hands on an enterprise-class IB driver stack. Or maybe you don't care and are just happy with the standard OFED one? Anyway, the next step is to actually leverage that InfiniBand performance. Here are the choices: Use traditional TCP/IP on top of the InfiniBand stack, Develop your own integration between your middleware and the lower-level (but faster) InfiniBand protocols. While more bandwidth is always a good thing, it's actually the low latency that enables superior performance for your applications when running on any networking infrastructure: The lower the latency, the faster the response travels through the network and the more transactions you can close per second. The reason why InfiniBand is such a low latency technology is that it gets rid of most if not all of your traditional networking protocol stack: Data is literally beamed from one region of RAM in one server into another region of RAM in another server with no kernel/drivers/UDP/TCP or other networking stack overhead involved! Which makes option 1 a no-go: Adding TCP/IP on top of InfiniBand is like adding training wheels to your racing bike. It may be ok in the beginning and for development, but it's not quite the performance IB was meant to deliver. Which only leaves option 2: Integrating your middleware with fast, low-level InfiniBand protocols. And this is what Exalogic's "Exabus" technology is all about. Here are a few Exabus features that help applications leverage the performance of InfiniBand in Exalogic: RDMA and SDP integration at the JDBC driver level (SDP), for Oracle Weblogic (SDP), Oracle Coherence (RDMA), Oracle Tuxedo (RDMA) and the new Oracle Traffic Director (RDMA) on Exalogic. Using these protocols, middleware can communicate a lot faster with each other and the Oracle database than by using standard networking protocols, Seamless Integration of Ethernet over InfiniBand from Exalogic's Gateway switches into the OS, Oracle Weblogic optimizations for handling massive amounts of parallel transactions. Because if you have an 8-lane Autobahn, you also need to improve your ramps so you can feed it with many cars in parallel. Integration of Weblogic with Oracle Exadata for faster performance, optimized session management and failover. As you see, “Exabus” is Oracle's word for describing all the InfiniBand enhancements Oracle put into Exalogic: OFED stack enhancements, protocols for faster IB access, and InfiniBand support and optimizations at the virtualization and middleware level. All working together to deliver the full potential of InfiniBand performance. Who else has 100% control over their middleware so they can develop their own low-level protocol integration with InfiniBand? Even if you take an open source approach, you're looking at years of development work to create, test and support a whole new networking technology in your middleware! The Extras: Less Hassle, More Productivity, Faster Time to Market And then there are the other advantages of Engineered Systems that are true for Exalogic the same as they are for every other Engineered System: One simple purchasing process: No headaches due to endless RFPs and no “Will X work with Y?” uncertainties. Everything has been engineered together: All kinds of bugs and problems have been already fixed at the design level that would have only manifested themselves after you have built the system from scratch. Everything is built, tested and integrated at the factory level . Less integration pain for you, faster time to market. Every Exalogic machine world-wide is identical to Oracle's own machines in the lab: Instant replication of any problems you may encounter, faster time to resolution. Simplified patching, management and operations. One throat to choke: Imagine finger-pointing hell for systems that have been put together using several different vendors. Oracle's Engineered Systems have a single phone number that customers can call to get their problems solved. For more business-centric values, read The Business Value of Engineered Systems. Conclusion: Buy Exalogic, or get ready for a 6-12 Month Science Project And here's the reason why it's not easy to "build your own Exalogic": There's a lot of work required to make such a system fly. In fact, anybody who is starting to "just put together a bunch of servers and an InfiniBand network" is really looking at a 6-12 month science project. And the outcome is likely to not be very enterprise-class. And it won't have Exalogic's performance either. Because building an Engineered System is literally rocket science: It takes a lot of time, effort, resources and many iterations of design/test/analyze/fix to build such a system. That's why InfiniBand has been reserved for HPC scientists for such a long time. And only Oracle can bring the power of InfiniBand in an enterprise-class, ready-to use, pre-integrated version to customers, without the develop/integrate/support pain. For more details, check the new Exalogic overview white paper which was updated only recently. P.S.: Thanks to my colleagues Ola, Paul, Don and Andy for helping me put together this article! var flattr_uid = '26528'; var flattr_tle = 'How to Avoid Your Next 12-Month Science Project'; var flattr_dsc = 'While most customers immediately understand how the magic of Oracle's Hybrid Columnar Compression, intelligent storage servers and flash memory make Exadata uniquely powerful against home-grown database systems, some people think that Exalogic is nothing more than a bunch of x86 servers, a storage appliance and an InfiniBand (IB) network, built into a single rack.After all, isn't this exactly what the High Performance Computing (HPC) world has been doing for decades?On the surface, this may be true. And some people tried exactly that: They tried to put together their own version of Exalogic, but then they discover there's a lot more to building a system than buying hardware and assembling it together. IT is not Ikea.Why is that so? Could it be there's more going on behind the scenes than merely putting together a bunch of servers, a storage array and an InfiniBand network into a rack? Let's explore some of the special sauce that makes Exalogic unique and un-copyable, so you can save yourself from your next 6- to 12-month science project that distracts you from doing real work that adds value to your company.'; var flattr_tag = 'Engineered Systems,Engineered Systems,Infiniband,Integration,latency,Oracle,performance'; var flattr_cat = 'text'; var flattr_url = 'http://constantin.glez.de/blog/2012/04/how-avoid-your-next-12-month-science-project'; var flattr_lng = 'en_GB'

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  • Performance Enhancement in Full-Text Search Query

    - by Calvin Sun
    Ever since its first release, we are continuing consolidating and developing InnoDB Full-Text Search feature. There is one recent improvement that worth blogging about. It is an effort with MySQL Optimizer team that simplifies some common queries’ Query Plans and dramatically shorted the query time. I will describe the issue, our solution and the end result by some performance numbers to demonstrate our efforts in continuing enhancement the Full-Text Search capability. The Issue: As we had discussed in previous Blogs, InnoDB implements Full-Text index as reversed auxiliary tables. The query once parsed will be reinterpreted into several queries into related auxiliary tables and then results are merged and consolidated to come up with the final result. So at the end of the query, we’ll have all matching records on hand, sorted by their ranking or by their Doc IDs. Unfortunately, MySQL’s optimizer and query processing had been initially designed for MyISAM Full-Text index, and sometimes did not fully utilize the complete result package from InnoDB. Here are a couple examples: Case 1: Query result ordered by Rank with only top N results: mysql> SELECT FTS_DOC_ID, MATCH (title, body) AGAINST ('database') AS SCORE FROM articles ORDER BY score DESC LIMIT 1; In this query, user tries to retrieve a single record with highest ranking. It should have a quick answer once we have all the matching documents on hand, especially if there are ranked. However, before this change, MySQL would almost retrieve rankings for almost every row in the table, sort them and them come with the top rank result. This whole retrieve and sort is quite unnecessary given the InnoDB already have the answer. In a real life case, user could have millions of rows, so in the old scheme, it would retrieve millions of rows' ranking and sort them, even if our FTS already found there are two 3 matched rows. Apparently, the million ranking retrieve is done in vain. In above case, it should just ask for 3 matched rows' ranking, all other rows' ranking are 0. If it want the top ranking, then it can just get the first record from our already sorted result. Case 2: Select Count(*) on matching records: mysql> SELECT COUNT(*) FROM articles WHERE MATCH (title,body) AGAINST ('database' IN NATURAL LANGUAGE MODE); In this case, InnoDB search can find matching rows quickly and will have all matching rows. However, before our change, in the old scheme, every row in the table was requested by MySQL one by one, just to check whether its ranking is larger than 0, and later comes up a count. In fact, there is no need for MySQL to fetch all rows, instead InnoDB already had all the matching records. The only thing need is to call an InnoDB API to retrieve the count The difference can be huge. Following query output shows how big the difference can be: mysql> select count(*) from searchindex_inno where match(si_title, si_text) against ('people')  +----------+ | count(*) | +----------+ | 666877 | +----------+ 1 row in set (16 min 17.37 sec) So the query took almost 16 minutes. Let’s see how long the InnoDB can come up the result. In InnoDB, you can obtain extra diagnostic printout by turning on “innodb_ft_enable_diag_print”, this will print out extra query info: Error log: keynr=2, 'people' NL search Total docs: 10954826 Total words: 0 UNION: Searching: 'people' Processing time: 2 secs: row(s) 666877: error: 10 ft_init() ft_init_ext() keynr=2, 'people' NL search Total docs: 10954826 Total words: 0 UNION: Searching: 'people' Processing time: 3 secs: row(s) 666877: error: 10 Output shows it only took InnoDB only 3 seconds to get the result, while the whole query took 16 minutes to finish. So large amount of time has been wasted on the un-needed row fetching. The Solution: The solution is obvious. MySQL can skip some of its steps, optimize its plan and obtain useful information directly from InnoDB. Some of savings from doing this include: 1) Avoid redundant sorting. Since InnoDB already sorted the result according to ranking. MySQL Query Processing layer does not need to sort to get top matching results. 2) Avoid row by row fetching to get the matching count. InnoDB provides all the matching records. All those not in the result list should all have ranking of 0, and no need to be retrieved. And InnoDB has a count of total matching records on hand. No need to recount. 3) Covered index scan. InnoDB results always contains the matching records' Document ID and their ranking. So if only the Document ID and ranking is needed, there is no need to go to user table to fetch the record itself. 4) Narrow the search result early, reduce the user table access. If the user wants to get top N matching records, we do not need to fetch all matching records from user table. We should be able to first select TOP N matching DOC IDs, and then only fetch corresponding records with these Doc IDs. Performance Results and comparison with MyISAM The result by this change is very obvious. I includes six testing result performed by Alexander Rubin just to demonstrate how fast the InnoDB query now becomes when comparing MyISAM Full-Text Search. These tests are base on the English Wikipedia data of 5.4 Million rows and approximately 16G table. The test was performed on a machine with 1 CPU Dual Core, SSD drive, 8G of RAM and InnoDB_buffer_pool is set to 8 GB. Table 1: SELECT with LIMIT CLAUSE mysql> SELECT si_title, match(si_title, si_text) against('family') as rel FROM si WHERE match(si_title, si_text) against('family') ORDER BY rel desc LIMIT 10; InnoDB MyISAM Times Faster Time for the query 1.63 sec 3 min 26.31 sec 127 You can see for this particular query (retrieve top 10 records), InnoDB Full-Text Search is now approximately 127 times faster than MyISAM. Table 2: SELECT COUNT QUERY mysql>select count(*) from si where match(si_title, si_text) against('family‘); +----------+ | count(*) | +----------+ | 293955 | +----------+ InnoDB MyISAM Times Faster Time for the query 1.35 sec 28 min 59.59 sec 1289 In this particular case, where there are 293k matching results, InnoDB took only 1.35 second to get all of them, while take MyISAM almost half an hour, that is about 1289 times faster!. Table 3: SELECT ID with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, match(si_title, si_text) against(<TERM>) as rel FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.5 sec 5.05 sec 10.1 family film 0.95 sec 25.39 sec 26.7 Pizza restaurant orange county California 0.93 sec 32.03 sec 34.4 President united states of America 2.5 sec 36.98 sec 14.8 Table 4: SELECT title and text with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, si_title, si_text, ... as rel FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.61 sec 41.65 sec 68.3 family film 1.15 sec 47.17 sec 41.0 Pizza restaurant orange county california 1.03 sec 48.2 sec 46.8 President united states of america 2.49 sec 44.61 sec 17.9 Table 5: SELECT ID with ORDER BY and LIMIT CLAUSE for selected terms mysql> SELECT <ID>, match(si_title, si_text) against(<TERM>) as rel  FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) ORDER BY rel desc LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.5 sec 5.05 sec 10.1 family film 0.95 sec 25.39 sec 26.7 Pizza restaurant orange county califormia 0.93 sec 32.03 sec 34.4 President united states of america 2.5 sec 36.98 sec 14.8 Table 6: SELECT COUNT(*) mysql> SELECT count(*) FROM si_<TB> WHERE match(si_title, si_text) against (<TERM>) LIMIT 10; Term InnoDB (time to execute) MyISAM(time to execute) Times Faster family 0.47 sec 82 sec 174.5 family film 0.83 sec 131 sec 157.8 Pizza restaurant orange county califormia 0.74 sec 106 sec 143.2 President united states of america 1.96 sec 220 sec 112.2  Again, table 3 to table 6 all showing InnoDB consistently outperform MyISAM in these queries by a large margin. It becomes obvious the InnoDB has great advantage over MyISAM in handling large data search. Summary: These results demonstrate the great performance we could achieve by making MySQL optimizer and InnoDB Full-Text Search more tightly coupled. I think there are still many cases that InnoDB’s result info have not been fully taken advantage of, which means we still have great room to improve. And we will continuously explore the area, and get more dramatic results for InnoDB full-text searches. Jimmy Yang, September 29, 2012

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  • Internet Explorer 9 is coming Monday to a web near you

    - by brian_ritchie
    Internet Explorer 9 is finally here...well almost.  Microsoft is releasing their new browser on March 14, 2011. IE9 has a number of improvements, including: Faster, Faster, Faster.  Did I mention it is faster?   With the new browsers coming out from Mozilla, Google, and Microsoft, there have been a flood of speed test coverage.  Chrome has long held the javascript speed crown.  But according to Steven J. Vaughan-Nichols over at ZDNET..."for the moment at least IE9 is actually the fastest browser I’ve tested to date."  He came to this revelation after figuring out that the 32-bit version of IE9 has the new Chakra JIT (the 64-bit version doesn't).  It also has a DirectX-based rendering engine so it can do cool tricks once reserved for desktop applications. Windows 7 Desktop Integration.  Read my post for more details.  Unfortantely, they didn't integrate my ideas...at least not yet :) Hot new UI.  Ok, they "borrowed" some ideas from Chrome...but that is the best form of flattery. Standards Compliance.  A real focus on HTML5 and CSS3.  Definite goodness for developers. So, go get yourself some IE9 on Monday and enjoy! 

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  • What do DBAs do?

    - by Jonathan Conway
    Yes, I know they administrate databases. I asked this question because I'd like to get a further insight into the kind of day-to-day duties a DBA might perform, and the real-world business problems they solve. For example: I optimized a 'products' query so that it ran 25% faster, which made the overall application faster. Is this a typical duty? Or is there more to being a DBA than simply making things faster? In what situations does DBA work involve planning and creativity?

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  • Exadata - Following up on customer deployments

    - by Carlos M. Orozco -Oracle
    Over the last year or so I've been visiting customers who have had Exadata deployed and have been enjoying the benefits the platform has been providing. Benefits include greater performance, consolidating multiple databases, data compression and time to value improvements. Most often I hear my reports run faster. One hospitality company report times that used to take 3 hrs now run in 12 seconds. Another services company reported all their batch reports taking 11hrs now run in 38 mins. Also reported that their transactions post faster, and batch updates run faster. So what does that mean? For most of them it means that now they have a platform that can handle growth. Most are growing 15% organically, but I've also seen 40% growth thru acquisition. Exadata has been keeping up with the additional data demand by customers leveraging compression and the smart storage features.

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  • Notes from AT&T ARO Session at Oredev 2013

    - by Geertjan
    The mobile internet is 12 times bigger than internet was 12 years ago. Explosive growth, faster networks, and more powerful devices. 85% of users prefer mobile apps, while 56% have problems. Almost 60% want less than 2 second mobile app startup. App with poor mobile experience results in not buying stuff, going to competitor, not liking your company. Battery life. Bad mobile app is worse than no app at all because it turns people away from brand, etc. Apps didn't exist 10 years ago, 72 billion dollars a year in 2013, 151 billion in 2017.Testing performance. Mobile is different than regular app. Need to fix issues before customers discover them. ARO is free and open source AT&T tool for identifying mobile app performance problems. Mobile data is different -- radio resource control state machine. Radio resource control -- radio from idle to continuous reception -- drains battery, sends data, packets coming through, after packets come through radio is still on which is tail time, after 10 seconds of no data coming through radio goes off. For example, YouTube, e.g., 10 to 15 seconds after every connection, can be huge drain on battery, app traffic triggers RRC state. Goal. Balance fast network connectivity against battery usage. ARO is free and open source and test any platform and won awards. How do I test my app? pcap or tcdump network. Native collector: Android and iOS. Android rooted device is needed. Test app on phone, background data, idle for ads and analytics. Graded against 25 best practices. See all the processes, all network traffic mapped to processes, stats about trace, can look just at your app, exlude Facebook, etc. Many tests conducted, e.g., file download, HTML (wrapped applications, e.g., cordova). Best Practices. Make stuff smaller. GZIP, smaller files, download faster, best for files larger than 800 bytes, minification -- remove tabs and commenting -- browser doesn't need that, just give processor what it needs remove wheat from chaff. Images -- make images smaller, 1024x1024 image for a checkmark, swish it, make it 33% smaller, ARO records the screen, probably could be 9 times smaller. Download less stuff. 17% of HTTP content on mobile is duplicate data because of caching, reloading from cache is 75% to 99% faster than downloading again, 75% possible savings which means app will start up faster because using cache -- everyone wants app starting up 2 seconds. Make fewer HTTP requests. Inline and combine CSS and JS when possible reduces the number of requests, spread images used often. Fewer connections. Faster and use less battery, for example, download an image every 60 secs, download an add every 60 seconds, send analytics every 60 seconds -- instead of that, use transaction manager, download everything at once, reduce amount of time connected to network by 40% also -- 80% of applications do NOT close connections when they are finished, e.g., download picture, 10 seconds later the radio turns off, if you do not explicitly close, eventually server closes, 38% more tail time, 40% less energy if you close connection right away, background data traffic is 27% of data and 55% of network time, this kills the battery. Look at redirection. Adds 200 to 600 ms on each connection, waterfall diagram to all the requests -- e.g., xyz.com redirect to www.xyz.com redirect to xyz.mobi to www.xyz.com, waterfall visualization of packets, minimize redirects but redirects are fine. HTML best practices. Order matters and hiding code (JS downloading blocks rendering, always do CSS before JS or JS asynchronously, CSS 'display:none' hides images from user but the browser downloads them which adds latency to application. Some apps turn on GPS for no reason. Tell network when down, but maybe some other app is using the radio at the same time. It's all about knowing best practices: everyone wins with ARO (carriers, e.g., AT&T, developers, customers). Faster apps, better battery usage, network traffic better, better app reviews, happier customers. MBTA app, referenced as an example.ARO is free, open source, can test all platforms.

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  • Speeding up procedural texture generation

    - by FalconNL
    Recently I've begun working on a game that takes place in a procedurally generated solar system. After a bit of a learning curve (having neither worked with Scala, OpenGL 2 ES or Libgdx before), I have a basic tech demo going where you spin around a single procedurally textured planet: The problem I'm running into is the performance of the texture generation. A quick overview of what I'm doing: a planet is a cube that has been deformed to a sphere. To each side, a n x n (e.g. 256 x 256) texture is applied, which are bundled in one 8n x n texture that is sent to the fragment shader. The last two spaces are not used, they're only there to make sure the width is a power of 2. The texture is currently generated on the CPU, using the updated 2012 version of the simplex noise algorithm linked to in the paper 'Simplex noise demystified'. The scene I'm using to test the algorithm contains two spheres: the planet and the background. Both use a greyscale texture consisting of six octaves of 3D simplex noise, so for example if we choose 128x128 as the texture size there are 128 x 128 x 6 x 2 x 6 = about 1.2 million calls to the noise function. The closest you will get to the planet is about what's shown in the screenshot and since the game's target resolution is 1280x720 that means I'd prefer to use 512x512 textures. Combine that with the fact the actual textures will of course be more complicated than basic noise (There will be a day and night texture, blended in the fragment shader based on sunlight, and a specular mask. I need noise for continents, terrain color variation, clouds, city lights, etc.) and we're looking at something like 512 x 512 x 6 x 3 x 15 = 70 million noise calls for the planet alone. In the final game, there will be activities when traveling between planets, so a wait of 5 or 10 seconds, possibly 20, would be acceptable since I can calculate the texture in the background while traveling, though obviously the faster the better. Getting back to our test scene, performance on my PC isn't too terrible, though still too slow considering the final result is going to be about 60 times worse: 128x128 : 0.1s 256x256 : 0.4s 512x512 : 1.7s This is after I moved all performance-critical code to Java, since trying to do so in Scala was a lot worse. Running this on my phone (a Samsung Galaxy S3), however, produces a more problematic result: 128x128 : 2s 256x256 : 7s 512x512 : 29s Already far too long, and that's not even factoring in the fact that it'll be minutes instead of seconds in the final version. Clearly something needs to be done. Personally, I see a few potential avenues, though I'm not particularly keen on any of them yet: Don't precalculate the textures, but let the fragment shader calculate everything. Probably not feasible, because at one point I had the background as a fullscreen quad with a pixel shader and I got about 1 fps on my phone. Use the GPU to render the texture once, store it and use the stored texture from then on. Upside: might be faster than doing it on the CPU since the GPU is supposed to be faster at floating point calculations. Downside: effects that cannot (easily) be expressed as functions of simplex noise (e.g. gas planet vortices, moon craters, etc.) are a lot more difficult to code in GLSL than in Scala/Java. Calculate a large amount of noise textures and ship them with the application. I'd like to avoid this if at all possible. Lower the resolution. Buys me a 4x performance gain, which isn't really enough plus I lose a lot of quality. Find a faster noise algorithm. If anyone has one I'm all ears, but simplex is already supposed to be faster than perlin. Adopt a pixel art style, allowing for lower resolution textures and fewer noise octaves. While I originally envisioned the game in this style, I've come to prefer the realistic approach. I'm doing something wrong and the performance should already be one or two orders of magnitude better. If this is the case, please let me know. If anyone has any suggestions, tips, workarounds, or other comments regarding this problem I'd love to hear them.

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  • Have Your Cake and Eat it Too: Industry Best Practices + Flexibility

    - by Oracle Accelerate for Midsize Companies
    By Richard Garraputa, VP of Sales & Marketing, brij Richard joined brij in 1996 after graduating from the University of North Carolina at Greensboro with degrees in Information Systems and Accounting. He directs brij’s overall strategies of both the business development and marketing departments. Companies looking for new ERP systems spend so much time comparing features and functions of software products but too often short change the value of their own processes.  Company managers I meet often claim that they are implementing a new ERP system so they can perform better and faster.  When asked how, the answer is often “by implementing best practices”.  But the term ‘best practices’ is frequently used to mean ‘doing things the way everyone else does them’ rather than a starting point or benchmark to build upon by adding your own value. Of course, implementing standardized processes across an enterprise is an important step in improving operational efficiencies.  But not all companies are alike.  Do you ever tell your customers “We are just like our competition and have no competitive differentiation”?  Probably not.  So why should the implementation of your business processes be just like your competitor’s?  Even within the same industry, companies differentiate themselves by leveraging their unique expertise and approach to business.  These unique aspects—the competitive differentiators that companies use to thrive in a crowded marketplace—can and should be supported by the implementation of business systems like ERP. Modern ERP systems like Oracle’s JD Edwards EnterpriseOne have a broad and deep functional footprint designed to integrate a company’s core operations.  But how can a company take advantage of this footprint without blowing up their implementation budget?  Some ERP vendors claim to solve this challenge by stating that their systems come pre-configured with ‘best practices’.  Too often what they are really saying is that you will have to abandon your key operational differentiators to fit a vendor’s template for your business—or extend your implementation and postpone the realization of any benefits. Thankfully for midsize companies, there is an alternative to the undesirable options of extended implementation projects or abandoning their competitive differentiators.  Oracle Accelerate Solutions speed the time it takes to implement JD Edwards EnterpriseOne solution based on your unique business characteristics, getting your new ERP system up and running faster without forcing your business to fit a cookie-cutter solution. We’ve been a JD Edwards implementation partner since 1986 and we now leverage Oracle Business Accelerators—cloud based rapid implementation tools built and maintained by Oracle. Oracle Business Accelerators deliver the benefits of embedded industry best practices without forcing every customer in to one set of processes like many template or “clone and go” approaches do. You retain the ability to reconfigure your applications—without customization—as your business changes. Wielded by Oracle partners with industry-specific domain expertise, Oracle Accelerate Solution implementations powered by Oracle Business Accelerators help automate the application configuration to fit your business better, faster. For example, on a recent project at a manufacturing company, the project manager told me that Oracle Business Accelerators helped get them to Conference Room Pilot 20% faster than with a traditional approach. Time savings equal cost savings. And if ‘better and faster’ is your goal for your business performance, shouldn’t it be the goal for your ERP implementation as well? Established in 1986, brij has been dedicated solely to helping its customers implement Oracle’s JD Edwards solutions and to maximize the value of those customers’ IT investments. They are a Gold level member in Oracle PartnerNetwork and an Oracle Accelerate Solution provider.

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  • Why increase pointer by two while finding loop in linked list, why not 3,4,5?

    - by GG
    I had a look at question already which talk about algorithm to find loop in a linked list. I have read Floyd's cycle-finding algorithm solution, mentioned at lot of places that we have to take two pointers. One pointer( slower/tortoise ) is increased by one and other pointer( faster/hare ) is increased by 2. When they are equal we find the loop and if faster pointer reaches null there is no loop in the linked list. Now my question is why we increase faster pointer by 2. Why not something else? Increasing by 2 is necessary or we can increase it by X to get the result. Is it necessary that we will find a loop if we increment faster pointer by 2 or there can be the case where we need to increment by 3 or 5 or x.

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  • Is a clear and replace more efficient than a loop checking all records?

    - by Matt
    I have a C# List, that is filled from a database.. So far its only 1400 records, but I expect it to grow a LOT.. Routinely I do a check for new data on the entire list.. What I'm trying to figure out is this, is it faster to simply clear the List and reload all the data from the table, or would checking each record be faster.. Intuition tells me that the dump and load method would be faster, but I thought I should check first...

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  • domain name vs ip address, same server, but different speed

    - by bn
    I have two similar sites: - two of them have almost exactly the same codes, and running on the same server - both sites are the same, they just use different language. - database of the slower site is populated (maybe only the user table) the other tables for site content is the same - the faster uses root to access database one of the sites is not released yet, so it uses IP Address to access the site instead of domain name the site that is using IP address is faster (lot faster) the site that is using domain name is slower do you know why is this happening what could be the reason?

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  • fastest in objC: IsEqualToString:@"" or length > 0?

    - by Cœur
    I'd like to know which one is fastest for testing a non-empty NSString for iOS 4.0+ (iPhone 3G). Note: the strings to test will be 99% of the time from 2 to 100 chars length. if ([foo length] > 0) or if ([foo isEqualToString:@""] == NO && foo != nil) I think it depends if isEqualToString: compares the length first (and in that case first way is faster) or if isEqualToString: compares first character of strings first (and in that case second way might be faster). ps: I already know isEqualToString: is faster than isEqual: which is itself faster than compare:.

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  • Is referencing a selector faster in jquery than actually calling the selector? if so, how much does it make a difference?

    - by anthonypliu
    Hi, I have this code: $(preview-button).click(...) $(preview-button).slide(...) $(preview-button).whatever(...) Is it a better practice to do this: var preview-button = $(preview-button); preview-button.click(...); preview-button.click(...); preview-button).slide(...); preview-button.whatever(...); It probably would be better practice to do this for the sake of keeping code clean and modular, BUT does it make a difference performance wise? Does one take longer to process than the other? Thanks guys.

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