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  • CLSF & CLK 2013 Trip Report by Jeff Liu

    - by jamesmorris
    This is a contributed post from Jeff Liu, lead XFS developer for the Oracle mainline Linux kernel team. Recently, I attended both the China Linux Storage and Filesystem workshop (CLSF), and the China Linux Kernel conference (CLK), which were held in Shanghai. Here are the highlights for both events. CLSF - 17th October XFS update (led by Jeff Liu) XFS keeps rapid progress with a lot of changes, especially focused on the infrastructure/performance improvements as well as  new feature development.  This can be reflected with a sample statistics among XFS/Ext4+JBD2/Btrfs via: # git diff --stat --minimal -C -M v3.7..v3.12-rc4 -- fs/xfs|fs/ext4+fs/jbd2|fs/btrfs XFS: 141 files changed, 27598 insertions(+), 19113 deletions(-) Ext4+JBD2: 39 files changed, 10487 insertions(+), 5454 deletions(-) Btrfs: 70 files changed, 19875 insertions(+), 8130 deletions(-) What made up those changes in XFS? Self-describing metadata(CRC32c). This is a new feature and it contributed about 70% code changes, it can be enabled via `mkfs.xfs -m crc=1 /dev/xxx` for v5 superblock. Transaction log space reservation improvements. With this change, we can calculate the log space reservation at mount time rather than runtime to reduce the the CPU overhead. User namespace support. So both XFS and USERNS can be enabled on kernel configuration begin from Linux 3.10. Thanks Dwight Engen's efforts for this thing. Split project/group quota inodes. Originally, project quota can not be enabled with group quota at the same time because they were share the same quota file inode, now it works but only for v5 super block. i.e, CRC enabled. CONFIG_XFS_WARN, an new lightweight runtime debugger which can be deployed in production environment. Readahead log object recovery, this change can speed up the log replay progress significantly. Speculative preallocation inode tracking, clearing and throttling. The main purpose is to deal with inodes with post-EOF space due to speculative preallocation, support improved quota management to free up a significant amount of unwritten space when at or near EDQUOT. It support backgroup scanning which occurs on a longish interval(5 mins by default, tunable), and on-demand scanning/trimming via ioctl(2). Bitter arguments ensued from this session, especially for the comparison between Ext4 and Btrfs in different areas, I have to spent a whole morning of the 1st day answering those questions. We basically agreed on XFS is the best choice in Linux nowadays because: Stable, XFS has a good record in stability in the past 10 years. Fengguang Wu who lead the 0-day kernel test project also said that he has observed less error than other filesystems in the past 1+ years, I own it to the XFS upstream code reviewer, they always performing serious code review as well as testing. Good performance for large/small files, XFS does not works very well for small files has already been an old story for years. Best choice (maybe) for distributed PB filesystems. e.g, Ceph recommends delopy OSD daemon on XFS because Ext4 has limited xattr size. Best choice for large storage (>16TB). Ext4 does not support a single file more than around 15.95TB. Scalability, any objection to XFS is best in this point? :) XFS is better to deal with transaction concurrency than Ext4, why? The maximum size of the log in XFS is 2038MB compare to 128MB in Ext4. Misc. Ext4 is widely used and it has been proved fast/stable in various loads and scenarios, XFS just need more customers, and Btrfs is still on the road to be a manhood. Ceph Introduction (Led by Li Wang) This a hot topic.  Li gave us a nice introduction about the design as well as their current works. Actually, Ceph client has been included in Linux kernel since 2.6.34 and supported by Openstack since Folsom but it seems that it has not yet been widely deployment in production environment. Their major work is focus on the inline data support to separate the metadata and data storage, reduce the file access time, i.e, a file access need communication twice, fetch the metadata from MDS and then get data from OSD, and also, the small file access is limited by the network latency. The solution is, for the small files they would like to store the data at metadata so that when accessing a small file, the metadata server can push both metadata and data to the client at the same time. In this way, they can reduce the overhead of calculating the data offset and save the communication to OSD. For this feature, they have only run some small scale testing but really saw noticeable improvements. Test environment: Intel 2 CPU 12 Core, 64GB RAM, Ubuntu 12.04, Ceph 0.56.6 with 200GB SATA disk, 15 OSD, 1 MDS, 1 MON. The sequence read performance for 1K size files improved about 50%. I have asked Li and Zheng Yan (the core developer of Ceph, who also worked on Btrfs) whether Ceph is really stable and can be deployed at production environment for large scale PB level storage, but they can not give a positive answer, looks Ceph even does not spread over Dreamhost (subject to confirmation). From Li, they only deployed Ceph for a small scale storage(32 nodes) although they'd like to try 6000 nodes in the future. Improve Linux swap for Flash storage (led by Shaohua Li) Because of high density, low power and low price, flash storage (SSD) is a good candidate to partially replace DRAM. A quick answer for this is using SSD as swap. But Linux swap is designed for slow hard disk storage, so there are a lot of challenges to efficiently use SSD for swap. SWAPOUT swap_map scan swap_map is the in-memory data structure to track swap disk usage, but it is a slow linear scan. It will become a bottleneck while finding many adjacent pages in the use of SSD. Shaohua Li have changed it to a cluster(128K) list, resulting in O(1) algorithm. However, this apporoach needs restrictive cluster alignment and only enabled for SSD. IO pattern In most cases, the swap io is in interleaved pattern because of mutiple reclaimers or a free cluster is shared by all reclaimers. Even though block layer can merge interleaved IO to some extent, but we cannot count on it completely. Hence the per-cpu cluster is added base on the previous change, it can help reclaimer do sequential IO and the block layer will be easier to merge IO. TLB flush: If we're reclaiming one active page, we should first move the page from active lru list to inactive lru list, and then reclaim the page from inactive lru to swap it out. During the process, we need to clear PTE twice: first is 'A'(ACCESS) bit, second is 'P'(PRESENT) bit. Processors need to send lots of ipi which make the TLB flush really expensive. Some works have been done to improve this, including rework smp_call_functiom_many() or remove the first TLB flush in x86, but there still have some arguments here and only parts of works have been pushed to mainline. SWAPIN: Page fault does iodepth=1 sync io, but it's a little waste if only issue a page size's IO. The obvious solution is doing swap readahead. But the current in-kernel swap readahead is arbitary(always 8 pages), and it always doesn't perform well for both random and sequential access workload. Shaohua introduced a new flag for madvise(MADV_WILLNEED) to do swap prefetch, so the changes happen in userspace API and leave the in-kernel readahead unchanged(but I think some improvement can also be done here). SWAP discard As we know, discard is important for SSD write throughout, but the current swap discard implementation is synchronous. He changed it to async discard which allow discard and write run in the same time. Meanwhile, the unit of discard is also optimized to cluster. Misc: lock contention For many concurrent swapout and swapin , the lock contention such as anon_vma or swap_lock is high, so he changed the swap_lock to a per-swap lock. But there still have some lock contention in very high speed SSD because of swapcache address_space lock. Zproject (led by Bob Liu) Bob gave us a very nice introduction about the current memory compression status. Now there are 3 projects(zswap/zram/zcache) which all aim at smooth swap IO storm and promote performance, but they all have their own pros and cons. ZSWAP It is implemented based on frontswap API and it uses a dynamic allocater named Zbud to allocate free pages. Zbud means pairs of zpages are "buddied" and it can only store at most two compressed pages in one page frame, so the max compress ratio is 50%. Each page frame is lru-linked and can do shink in memory pressure. If the compressed memory pool reach its limitation, shink or reclaim happens. It decompress the page frame into two new allocated pages and then write them to real swap device, but it can fail when allocating the two pages. ZRAM Acts as a compressed ramdisk and used as swap device, and it use zsmalloc as its allocator which has high density but may have fragmentation issues. Besides, page reclaim is hard since it will need more pages to uncompress and free just one page. ZRAM is preferred by embedded system which may not have any real swap device. Now both ZRAM and ZSWAP are in driver/staging tree, and in the mm community there are some disscussions of merging ZRAM into ZSWAP or viceversa, but no agreement yet. ZCACHE Handles file page compression but it is removed out of staging recently. From industry (led by Tang Jie, LSI) An LSI engineer introduced several new produces to us. The first is raid5/6 cards that it use full stripe writes to improve performance. The 2nd one he introduced is SandForce flash controller, who can understand data file types (data entropy) to reduce write amplification (WA) for nearly all writes. It's called DuraWrite and typical WA is 0.5. What's more, if enable its Dynamic Logical Capacity function module, the controller can do data compression which is transparent to upper layer. LSI testing shows that with this virtual capacity enables 1x TB drive can support up to 2x TB capacity, but the application must monitor free flash space to maintain optimal performance and to guard against free flash space exhaustion. He said the most useful application is for datebase. Another thing I think it's worth to mention is that a NV-DRAM memory in NMR/Raptor which is directly exposed to host system. Applications can directly access the NV-DRAM via a memory address - using standard system call mmap(). He said that it is very useful for database logging now. This kind of NVM produces are beginning to appear in recent years, and it is said that Samsung is building a research center in China for related produces. IMHO, NVM will bring an effect to current os layer especially on file system, e.g. its journaling may need to redesign to fully utilize these nonvolatile memory. OCFS2 (led by Canquan Shen) Without a doubt, HuaWei is the biggest contributor to OCFS2 in the past two years. They have posted 46 upstream patches and 39 patches have been merged. Their current project is based on 32/64 nodes cluster, but they also tried 128 nodes at the experimental stage. The major work they are working is to support ATS (atomic test and set), it can be works with DLM at the same time. Looks this idea is inspired by the vmware VMFS locking, i.e, http://blogs.vmware.com/vsphere/2012/05/vmfs-locking-uncovered.html CLK - 18th October 2013 Improving Linux Development with Better Tools (Andi Kleen) This talk focused on how to find/solve bugs along with the Linux complexity growing. Generally, we can do this with the following kind of tools: Static code checkers tools. e.g, sparse, smatch, coccinelle, clang checker, checkpatch, gcc -W/LTO, stanse. This can help check a lot of things, simple mistakes, complex problems, but the challenges are: some are very slow, false positives, may need a concentrated effort to get false positives down. Especially, no static checker I found can follow indirect calls (“OO in C”, common in kernel): struct foo_ops { int (*do_foo)(struct foo *obj); } foo->do_foo(foo); Dynamic runtime checkers, e.g, thread checkers, kmemcheck, lockdep. Ideally all kernel code would come with a test suite, then someone could run all the dynamic checkers. Fuzzers/test suites. e.g, Trinity is a great tool, it finds many bugs, but needs manual model for each syscall. Modern fuzzers around using automatic feedback, but notfor kernel yet: http://taviso.decsystem.org/making_software_dumber.pdf Debuggers/Tracers to understand code, e.g, ftrace, can dump on events/oops/custom triggers, but still too much overhead in many cases to run always during debug. Tools to read/understand source, e.g, grep/cscope work great for many cases, but do not understand indirect pointers (OO in C model used in kernel), give us all “do_foo” instances: struct foo_ops { int (*do_foo)(struct foo *obj); } = { .do_foo = my_foo }; foo>do_foo(foo); That would be great to have a cscope like tool that understands this based on types/initializers XFS: The High Performance Enterprise File System (Jeff Liu) [slides] I gave a talk for introducing the disk layout, unique features, as well as the recent changes.   The slides include some charts to reflect the performances between XFS/Btrfs/Ext4 for small files. About a dozen users raised their hands when I asking who has experienced with XFS. I remembered that when I asked the same question in LinuxCon/Japan, only 3 people raised their hands, but they are Chris Mason, Ric Wheeler, and another attendee. The attendee questions were mainly focused on stability, and comparison with other file systems. Linux Containers (Feng Gao) The speaker introduced us that the purpose for those kind of namespaces, include mount/UTS/IPC/Network/Pid/User, as well as the system API/ABI. For the userspace tools, He mainly focus on the Libvirt LXC rather than us(LXC). Libvirt LXC is another userspace container management tool, implemented as one type of libvirt driver, it can manage containers, create namespace, create private filesystem layout for container, Create devices for container and setup resources controller via cgroup. In this talk, Feng also mentioned another two possible new namespaces in the future, the 1st is the audit, but not sure if it should be assigned to user namespace or not. Another is about syslog, but the question is do we really need it? In-memory Compression (Bob Liu) Same as CLSF, a nice introduction that I have already mentioned above. Misc There were some other talks related to ACPI based memory hotplug, smart wake-affinity in scheduler etc., but my head is not big enough to record all those things. -- Jeff Liu

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  • Oracle OpenWorld Update: Demo Pods and Hands-on Labs

    - by Doug Reid
    0 false 18 pt 18 pt 0 0 false false false /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} Less than one week away until the start of Oracle OpenWorld 2012 and the Data Integration Solutions team is ready to go!  We have an exciting line up for you this year which we have summarized for you in the Oracle OpenWorld Focus on Data Integration Solutions document. In past posts we have discussed session themes and our customer panel, but today I would like to summarize our Hands-on Labs and Demo Pods that we have available for attendees. For Oracle GoldenGate Hands-On Labs we have two labs that we are running this year. Deep Dive into Oracle GoldenGate Thursday October 4th at 11:15AM in the Marriott Marquis Salon 1/2 Oracle GoldenGate provides real-time log-based change data capture and delivery between heterogeneous systems. It enables cost-effective, low-impact, real-time data integration and continuous availability solutions. This session covers Oracle GoldenGate 11g’s internal product architecture and includes a hands-on lab that covers configuration examples for target database instantiation and real-time change data capture and delivery. The participants will configure Oracle GoldenGate to instantiate a secondary database that can be used for disaster recovery or a reporting instance. Come learn how easy it is to use and how this can be a very valuable and easy technology solution for your organization. Introduction to Oracle GoldenGate Veridata Wednesday October 3rd 10:15AM in the Marriott Marquis Sales 1/2 Oracle GoldenGate Veridata compares one set of data with another and identifies data that is out of synchronization. In this hands-on lab, you will be introduced to the key features of this product. Using the Oracle GoldenGate Veridata Web client, you will have the opportunity to configure comparison objects and rules, initiate a comparison, review the status and output of a comparison, and review out-of-sync data. As a bonus this year, we have recorded the labs and made them available on youtube.com/oraclegoldengate. These will be available the day of the labs. Our demo pods are an opportunity for attendees to see our products but more so to meet the product management and development teams. I would like to point out that we have two Oracle GoldenGate 11gR2 demo pods, one in the database camp and the other in the middleware camp. The one in the middleware camp will be focused on all platforms while the one in the database camp will have a focus on the Oracle platform. The other two I would like to point out are the Monitoring Oracle GoldenGate and the Oracle Enterprise Manager demo pods; both of these pods will focus on methods to monitor GoldenGate but the OEM demo pod will have a specific focus on the Oracle GoldenGate Management Pack plug-in for OEM. Below is a list of our demo pods and their locations. Monitoring Oracle GoldenGate for End-to-End Visibility Moscone South, Right - S-241 Oracle Data Integrator and Oracle GoldenGate for Oracle Applications Moscone South, Right - S-240 Oracle GoldenGate 11gR2 New Features Moscone South, Right - S-239 Oracle GoldenGate 11gR2: Real-Time, Transactional Database Replication     Moscone South, Left - S-027 Oracle GoldenGate Veridata and Adapters Moscone South, Right - S-242 Oracle Enterprise Manager Moscone South, Left - S-040 Keep tuned to our blog during the show for news and highlights from the Data Integration Solutions team. See you there.

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  • Why is 0 false?

    - by Morwenn
    This question may sound dumb, but why does 0 evaluates to false and any other [integer] value to true is most of programming languages? String comparison Since the question seems a little bit too simple, I will explain myself a little bit more: first of all, it may seem evident to any programmer, but why wouldn't there be a programming language - there may actually be, but not any I used - where 0 evaluates to true and all the other [integer] values to false? That one remark may seem random, but I have a few examples where it may have been a good idea. First of all, let's take the example of strings three-way comparison, I will take C's strcmp as example: any programmer trying C as his first language may be tempted to write the following code: if (strcmp(str1, str2)) { // Do something... } Since strcmp returns 0 which evaluates to false when the strings are equal, what the beginning programmer tried to do fails miserably and he generally does not understand why at first. Had 0 evaluated to true instead, this function could have been used in its most simple expression - the one above - when comparing for equality, and the proper checks for -1 and 1 would have been done only when needed. We would have considered the return type as bool (in our minds I mean) most of the time. Moreover, let's introduce a new type, sign, that just takes values -1, 0 and 1. That can be pretty handy. Imagine there is a spaceship operator in C++ and we want it for std::string (well, there already is the compare function, but spaceship operator is more fun). The declaration would currently be the following one: sign operator<=>(const std::string& lhs, const std::string& rhs); Had 0 been evaluated to true, the spaceship operator wouldn't even exist, and we could have declared operator== that way: sign operator==(const std::string& lhs, const std::string& rhs); This operator== would have handled three-way comparison at once, and could still be used to perform the following check while still being able to check which string is lexicographically superior to the other when needed: if (str1 == str2) { // Do something... } Old errors handling We now have exceptions, so this part only applies to the old languages where no such thing exist (C for example). If we look at C's standard library (and POSIX one too), we can see for sure that maaaaany functions return 0 when successful and any integer otherwise. I have sadly seen some people do this kind of things: #define TRUE 0 // ... if (some_function() == TRUE) { // Here, TRUE would mean success... // Do something } If we think about how we think in programming, we often have the following reasoning pattern: Do something Did it work? Yes -> That's ok, one case to handle No -> Why? Many cases to handle If we think about it again, it would have made sense to put the only neutral value, 0, to yes (and that's how C's functions work), while all the other values can be there to solve the many cases of the no. However, in all the programming languages I know (except maybe some experimental esotheric languages), that yes evaluates to false in an if condition, while all the no cases evaluate to true. There are many situations when "it works" represents one case while "it does not work" represents many probable causes. If we think about it that way, having 0 evaluate to true and the rest to false would have made much more sense. Conclusion My conclusion is essentially my original question: why did we design languages where 0 is false and the other values are true, taking in account my few examples above and maybe some more I did not think of? Follow-up: It's nice to see there are many answers with many ideas and as many possible reasons for it to be like that. I love how passionate you seem to be about it. I originaly asked this question out of boredom, but since you seem so passionate, I decided to go a little further and ask about the rationale behind the Boolean choice for 0 and 1 on Math.SE :)

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  • Network access lags for Win7 when server network utilization is high

    - by Jeff Miles
    We have a Dell PE2950 file server running Windows 2008, hosting a DFS namespace of ~1.2 TB. This server has two Broadcom 1Gbps NICs teamed together. When there is high traffic going to the server across the network (greater than 200 Mbps), any Windows 7 client accessing a DFS share at the time experiences severe performance problems. For example: Computer A has an AutoCAD drawing opened directly from the DFS share. Performance is normal, not causing any issues. Computer B begins a file transfer, putting a 11GB file onto a different DFS namespace, on the same server Computer A immediately notices lag while using AutoCAD. The cursor momentarily freezes within AutoCAD every 10 seconds or so, and any browsing of the DFS share is extremely slow. Computer B completes file transfer, and performance resumes to normal for Computer A. This is only affecting Windows 7 clients, using a variety of hardware (desktop + laptop). All of our Windows XP clients see no performance impact during the file transfer. Things I have tried with no change: Had Computer A work from an entirely different RAID array from the file transfer destination Updated NIC drivers on clients and server Enabled TCP offload and receive side scaling on the server NIC (previously disabled when the issue began) Antivirus disabled during file transfer I am currently having a user test applications other than AutoCAD when the file transfer occurs, and will update the question with that result. Does anyone have any recommendations for resolution or additional troubleshooting steps?

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  • SSD for swap on Ubuntu server

    - by grs
    Currently I am reading SSD reviews and I wonder how much exactly I will benefit if I move the 24 GB swap from 7200rpm HDD to SSD. Does anyone implemented swap space on SSD? Is this generally good idea? On a side note: I read that ext4 has much better performance if the journal is on SSD. Anyone with such a setup? Thanks! Edit: Here I will answer the questions posted: Occasionally, relatively rare I am hitting the swap. I know what the swap is for and that is better to get more RAM. When the server begins to swap its performance degrades (not a surprise). The idea is if I have few memory hungry processes running, to improve the overall system performance at that time, using SSD for swap, instead of slower rotational media. At the end - I want to be able to login faster and check the server state during swapping, instead of waiting on the login prompt. And of what I see SSD is cheaper per GB than RAM. Would I have better server performance during swapping (as rare it is) using SSD compared to HDD? Where 10k or 15k rpm HDDs would rate in this scenario? Thank you all for your quick and prompt answers!

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  • MysqlTunner and query_cache_size dilemma

    - by wbad
    On a busy mysql server MySQLTuner 1.2.0 always recommends to add query_cache_size no matter how I increase the value (I tried up to 512MB). On the other hand it warns that : Increasing the query_cache size over 128M may reduce performance Here are the last results: >> MySQLTuner 1.2.0 - Major Hayden <[email protected]> >> Bug reports, feature requests, and downloads at http://mysqltuner.com/ >> Run with '--help' for additional options and output filtering -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.5.25-1~dotdeb.0-log [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in InnoDB tables: 6G (Tables: 195) [--] Data in PERFORMANCE_SCHEMA tables: 0B (Tables: 17) [!!] Total fragmented tables: 51 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 1d 19h 17m 8s (254M q [1K qps], 5M conn, TX: 139B, RX: 32B) [--] Reads / Writes: 89% / 11% [--] Total buffers: 24.2G global + 92.2M per thread (1200 max threads) [!!] Maximum possible memory usage: 132.2G (139% of installed RAM) [OK] Slow queries: 0% (2K/254M) [OK] Highest usage of available connections: 32% (391/1200) [OK] Key buffer size / total MyISAM indexes: 128.0M/92.0K [OK] Key buffer hit rate: 100.0% (8B cached / 0 reads) [OK] Query cache efficiency: 79.9% (181M cached / 226M selects) [!!] Query cache prunes per day: 1033203 [OK] Sorts requiring temporary tables: 0% (341 temp sorts / 4M sorts) [OK] Temporary tables created on disk: 14% (760K on disk / 5M total) [OK] Thread cache hit rate: 99% (676 created / 5M connections) [OK] Table cache hit rate: 22% (1K open / 8K opened) [OK] Open file limit used: 0% (49/13K) [OK] Table locks acquired immediately: 99% (64M immediate / 64M locks) [OK] InnoDB data size / buffer pool: 6.1G/19.5G -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance Reduce your overall MySQL memory footprint for system stability Increasing the query_cache size over 128M may reduce performance Variables to adjust: *** MySQL's maximum memory usage is dangerously high *** *** Add RAM before increasing MySQL buffer variables *** query_cache_size (> 192M) [see warning above] The server has 76GB ram and dual E5-2650. The load is usually below 2. I appreciate your hints to interpret the recommendation and optimize the database configs.

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  • Replicated filesystem and EC2 MySQL

    - by El Yobo
    I'm currently investigating migrating our infrastructure over to run on Amazon's EC2 and am trying to figure out the best way to set up a MySQL service. I'm leaning towards running our own MySQL instances, rather than going with Amazon's RDS, but am still considering the best approach for performance and cost on the instance itself. In order to have persistent data, the MySQL data needs to be on an EBS volume (with some form of striped RAID, e.g. RAID0 or RAID10) to improve persistence. However, EBS IO is limited by the network interface (gigabit, so a theoretical maximum of 128 MB/s), while the ephemeral volumes have no such problem. I did see a suggestion for running two MySQL servers on an instance, with a master running on the ephemeral disk (which we would also RAID) and a slave storing changes to an EBS volume, but this has some additional overhead and complexity (two servers). What I was imagining is using some form of replicated file system such that I could have a filesystem on top of a RAID0 of ephemeral volumes to maximise performance all changes from the above immediately replicated to another RAID1 volume backed by multiple EBS volumes to ensure no data loss The advantages of this would be best possible IO performance for the DB server; no network delay in IO decreased IO on EBS volumes (as all read IO will be done on the ephemeral volumes) so decreased cost good data security, as it's backed onto redundant EBS volumes However, I haven't seen an appropriate system to replicate all changes from one volume to the other; is there a filesystem, or any other approach, which will do this? The distributed file systems, e.g. GlusterFS, DRBD etc seem to focus on replicating disks between servers, can they be set up to do what I'm interested in here? I also haven't seen anything about other's taking this approach. Do I have a solution in need of a problem here (i.e. is performance good enough, so this whole idea is redundant)? Is there some flaw in the plan?

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  • RAIDs with a lot of spindles - how to safely put to use the "wasted" space

    - by kubanczyk
    I have a fairly large number of RAID arrays (server controllers as well as midrange SAN storage) that all suffer from the same problem: barely enough spindles to keep the peak I/O performance, and tons of unused disk space. I guess it's a universal issue since vendors offer the smallest drives of 300 GB capacity but the random I/O performance hasn't really grown much since the time when the smallest drives were 36 GB. One example is a database that has 300 GB and needs random performance of 3200 IOPS, so it gets 16 disks (4800 GB minus 300 GB and we have 4.5 TB wasted space). Another common example are redo logs for a OLTP database that is sensitive in terms of response time. The redo logs get their own 300 GB mirror, but take 30 GB: 270 GB wasted. What I would like to see is a systematic approach for both Linux and Windows environment. How to set up the space so sysadmin team would be reminded about the risk of hindering the performance of the main db/app? Or, even better, to be protected from that risk? The typical situation that comes to my mind is "oh, I have this very large zip file, where do I uncompress it? Umm let's see the df -h and we figure something out in no time..." I don't put emphasis on strictness of the security (sysadmins are trusted to act in good faith), but on overall simplicity of the approach. For Linux, it would be great to have a filesystem customized to cap I/O rate to a very low level - is this possible?

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  • Kruskal-Wallis test with details on pairwise comparisons

    - by dalloliogm
    The standard stats::kruskal.test module allows to calculate the kruskal-wallis test on a dataset: >>> data(diamonds) >>> kruskal.test.test(price~carat, data=diamonds) Kruskal-Wallis rank sum test data: price by carat by color Kruskal-Wallis chi-squared = 50570.15, df = 272, p-value < 2.2e-16 this is correct, it is giving me a probability that all the groups in the data have the same mean. However, I would like to have the details for each pair comparison, like if diamonds of colors D and E have the same mean price, as some other softwares do (SPSS) when you ask for a Kruskal test. I have found kruskalmc from the package pgirmess which allows me to do what I want to do: > kruskalmc(diamonds$price, diamonds$color) Multiple comparison test after Kruskal-Wallis p.value: 0.05 Comparisons obs.dif critical.dif difference D-E 571.7459 747.4962 FALSE D-F 2237.4309 751.5684 TRUE D-G 2643.1778 726.9854 TRUE D-H 4539.4392 774.4809 TRUE D-I 6002.6286 862.0150 TRUE D-J 8077.2871 1061.7451 TRUE E-F 2809.1767 680.4144 TRUE E-G 3214.9237 653.1587 TRUE E-H 5111.1851 705.6410 TRUE E-I 6574.3744 800.7362 TRUE E-J 8649.0330 1012.6260 TRUE F-G 405.7470 657.8152 FALSE F-H 2302.0083 709.9533 TRUE F-I 3765.1977 804.5390 TRUE F-J 5839.8562 1015.6357 TRUE G-H 1896.2614 683.8760 TRUE G-I 3359.4507 781.6237 TRUE G-J 5434.1093 997.5813 TRUE H-I 1463.1894 825.9834 TRUE H-J 3537.8479 1032.7058 TRUE I-J 2074.6585 1099.8776 TRUE However, this package only allows for one categoric variable (e.g. I can't study the prices clustered by color and by carat, as I can do with kruskal.test), and I don't know anything about the pgirmess package, whether it is maintained or not, or if it is tested. Can you recommend me a package to execute the Kruskal-Wallis test which returns details for every comparison? How would you handle the problem?

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  • Fast string suffix checking in C# (.NET 4.0)?

    - by ilitirit
    What is the fastest method of checking string suffixes in C#? I need to check each string in a large list (anywhere from 5000 to 100000 items) for a particular term. The term is guaranteed never to be embedded within the string. In other words, if the string contains the term, it will be at the end of the string. The string is also guaranteed to be longer than the suffix. Cultural information is not important. These are how different methods performed against 100000 strings (half of them have the suffix): 1. Substring Comparison - 13.60ms 2. String.Contains - 22.33ms 3. CompareInfo.IsSuffix - 24.60ms 4. String.EndsWith - 29.08ms 5. String.LastIndexOf - 30.68ms These are average times. [Edit] Forgot to mention that the strings also get put into separate lists, but this is not important. It does add to the running time though. On my system substring comparison (extracting the end of the string using the String.Substring method and comparing it to the suffix term) is consistently the fastest when tested against 100000 strings. The problem with using substring comparison though is that Garbage Collection can slow it down considerably (more than the other methods) because String.Substring creates new strings. The effect is not as bad in .NET 4.0 as it was in 3.5 and below, but it is still noticeable. In my tests, String.Substring performed consistently slower on sets of 12000-13000 strings. This will obviously differ between systems and implementations. [EDIT] Benchmark code: http://pastebin.com/smEtYNYN

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  • Can't operator == be applied to generic types in C#?

    - by Hosam Aly
    According to the documentation of the == operator in MSDN, For predefined value types, the equality operator (==) returns true if the values of its operands are equal, false otherwise. For reference types other than string, == returns true if its two operands refer to the same object. For the string type, == compares the values of the strings. User-defined value types can overload the == operator (see operator). So can user-defined reference types, although by default == behaves as described above for both predefined and user-defined reference types. So why does this code snippet fail to compile? void Compare<T>(T x, T y) { return x == y; } I get the error Operator '==' cannot be applied to operands of type 'T' and 'T'. I wonder why, since as far as I understand the == operator is predefined for all types? Edit: Thanks everybody. I didn't notice at first that the statement was about reference types only. I also thought that bit-by-bit comparison is provided for all value types, which I now know is not correct. But, in case I'm using a reference type, would the the == operator use the predefined reference comparison, or would it use the overloaded version of the operator if a type defined one? Edit 2: Through trial and error, we learned that the == operator will use the predefined reference comparison when using an unrestricted generic type. Actually, the compiler will use the best method it can find for the restricted type argument, but will look no further. For example, the code below will always print true, even when Test.test<B>(new B(), new B()) is called: class A { public static bool operator==(A x, A y) { return true; } } class B : A { public static bool operator==(B x, B y) { return false; } } class Test { void test<T>(T a, T b) where T : A { Console.WriteLine(a == b); } }

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  • Which Javascript framework (jQuery vs Dojo vs ... )?

    - by cletus
    There are a few Javascript frameworks/toolets out there, such as: jQuery; Dojo; Prototype; YUI; MooTools; ExtJS; SmartClient; and others I'm sure. It certainly seems that jQuery is ascendant in terms of mindshare at the moment. For example, Microsoft (ASP.NET MVC) and Nokia will use it. I also found this this performance comparison of Dojo, jQuery, MooTools and Prototype (Edit: Updated Comparison), which looks highly favourable to Dojo and jQuery. Now my previous experience with Javascript has been the old school HTML + Javascript most of us have done and RIA frameworks like Google Web Toolkit ("GWT") and Ext-GWT, which were a fairly low-stress entry into the Ajax world for someone from a Java background, such as myself. But, after all this, I find myself leaning towards the more PHP + Ajax type solution, which just seems that much more lightweight. So I've been looking into jQuery and I really like it's use of commands, the use of fluent interfaces and method chaining, it's cross-browser CSS selector superset, the fact that it's lightweight and extensible, the brevity of the syntax, unobtrusive Javascript and the plug-in framework. Now obviously many of these aren't unique to jQuery but on the basis that some things are greater than their sum of parts, it just seems that it all fits together and works well. So jQuery seems to have a lot going for it and it looks to the frontrunner for what I choose to concentrate on. Is there anything else I should be aware of or any particular reasons not to choose it or to choose something else? EDIT: Just wanted to add this trend comparison of Javascript frameworks.

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  • Ignore case in Python strings

    - by Paul Oyster
    What is the easiest way to compare strings in Python, ignoring case? Of course one can do (str1.lower() <= str2.lower()), etc., but this created two additional temporary strings (with the obvious alloc/g-c overheads). I guess I'm looking for an equivalent to C's stricmp(). [Some more context requested, so I'll demonstrate with a trivial example:] Suppose you want to sort a looong list of strings. You simply do theList.sort(). This is O(n * log(n)) string comparisons and no memory management (since all strings and list elements are some sort of smart pointers). You are happy. Now, you want to do the same, but ignore the case (let's simplify and say all strings are ascii, so locale issues can be ignored). You can do theList.sort(key=lambda s: s.lower()), but then you cause two new allocations per comparison, plus burden the garbage-collector with the duplicated (lowered) strings. Each such memory-management noise is orders-of-magnitude slower than simple string comparison. Now, with an in-place stricmp()-like function, you do: theList.sort(cmp=stricmp) and it is as fast and as memory-friendly as theList.sort(). You are happy again. The problem is any Python-based case-insensitive comparison involves implicit string duplications, so I was expecting to find a C-based comparisons (maybe in module string). Could not find anything like that, hence the question here. (Hope this clarifies the question).

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  • Culture Sensitive GetHashCode

    - by user114928
    Hi, I'm writing a c# application that will process some text and provide basic query functions. In order to ensure the best possible support for other languages, I am allowing the users of the application to specify the System.Globalization.CultureInfo (via the "en-GB" style code) and also the full range of collation options using the System.Globalization.CompareOptions flags enum. For regular string comparison I'm then using a combination of: a) String.Compare overload that accepts the culture and options b) For some bulk processes I'm caching the byte data (KeyData) from CompareInfo.GetSortKey (overload that accepts the options) and using a byte-by-byte comparison of the KeyData. This seemed fine (although please comment if you think these two methods shouldn't be mixed), but then I had reason to use the HashSet< class which only has an overload for IEqualityComparer<. MS documentation seems to suggest that I should use StringComparer (which implements both IEqualityComparer< and IComparer<), but this only seems to support the "IgnoreCase" option from CompareOptions and not "IgnoreKanaType", "IgnoreSymbols", "IgnoreWidth" etc. I'm assuming that a StringComparer that ignores these other options could produce different hashcodes for two strings that might be considered the same using my other comparison options. I'd therefore get incorrect results from my application. Only thought at the moment is to create my own IEqualityComparer< that generates a hashcode from the SortKey.KeyData and compares eqality be using the String.Compare overload. Any suggestions?

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  • How to read time from recorded surveillance camera video?

    - by stressed_geek
    I have a problem where I have to read the time of recording from the video recorded by a surveillance camera. The time shows up on the top-left area of the video. Below is a link to screen grab of the area which shows the time. Also, the digit color(white/black) keeps changing during the duration of the video. http://i55.tinypic.com/2j5gca8.png Please guide me in the direction to approach this problem. I am a Java programmer so would prefer an approach through Java. EDIT: Thanks unhillbilly for the comment. I had looked at the Ron Cemer OCR library and its performance is much below our requirement. Since the ocr performance is less than desired, I was planning to build a character set using the screen grabs for all the digits, and using some image/pixel comparison library to compare the frame time with the character-set which will show a probabilistic result after comparison. So I was looking for a good image comparison library(I would be OK with a non-java library which I can run using the command-line). Also any advice on the above approach would be really helpful.

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  • World Record Batch Rate on Oracle JD Edwards Consolidated Workload with SPARC T4-2

    - by Brian
    Oracle produced a World Record batch throughput for single system results on Oracle's JD Edwards EnterpriseOne Day-in-the-Life benchmark using Oracle's SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2. The workload includes both online and batch workload. The SPARC T4-2 server delivered a result of 8,000 online users while concurrently executing a mix of JD Edwards EnterpriseOne Long and Short batch processes at 95.5 UBEs/min (Universal Batch Engines per minute). In order to obtain this record benchmark result, the JD Edwards EnterpriseOne, Oracle WebLogic and Oracle Database 11g Release 2 servers were executed each in separate Oracle Solaris Containers which enabled optimal system resources distribution and performance together with scalable and manageable virtualization. One SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2 utilized only 55% of the available CPU power. The Oracle DB server in a Shared Server configuration allows for optimized CPU resource utilization and significant memory savings on the SPARC T4-2 server without sacrificing performance. This configuration with SPARC T4-2 server has achieved 33% more Users/core, 47% more UBEs/min and 78% more Users/rack unit than the IBM Power 770 server. The SPARC T4-2 server with 2 processors ran the JD Edwards "Day-in-the-Life" benchmark and supported 8,000 concurrent online users while concurrently executing mixed batch workloads at 95.5 UBEs per minute. The IBM Power 770 server with twice as many processors supported only 12,000 concurrent online users while concurrently executing mixed batch workloads at only 65 UBEs per minute. This benchmark demonstrates more than 2x cost savings by consolidating the complete solution in a single SPARC T4-2 server compared to earlier published results of 10,000 users and 67 UBEs per minute on two SPARC T4-2 and SPARC T4-1. The Oracle DB server used mirrored (RAID 1) volumes for the database providing high availability for the data without impacting performance. Performance Landscape JD Edwards EnterpriseOne Day in the Life (DIL) Benchmark Consolidated Online with Batch Workload System Rack Units BatchRate(UBEs/m) Online Users Users /Units Users /Core Version SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 3 95.5 8,000 2,667 500 9.0.2 IBM Power 770 (4 x POWER7, 3.3 GHz, 32 cores) 8 65 12,000 1,500 375 9.0.2 Batch Rate (UBEs/m) — Batch transaction rate in UBEs per minute Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 4 x 300 GB 10K RPM SAS internal disk 2 x 300 GB internal SSD 2 x Sun Storage F5100 Flash Arrays Software Configuration: Oracle Solaris 10 Oracle Solaris Containers JD Edwards EnterpriseOne 9.0.2 JD Edwards EnterpriseOne Tools (8.98.4.2) Oracle WebLogic Server 11g (10.3.4) Oracle HTTP Server 11g Oracle Database 11g Release 2 (11.2.0.1) Benchmark Description JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations. Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company. The workload consists of online transactions and the UBE – Universal Business Engine workload of 61 short and 4 long UBEs. LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time. The UBE processes workload runs from the JD Enterprise Application server. Oracle's UBE processes come as three flavors: Short UBEs < 1 minute engage in Business Report and Summary Analysis, Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address, Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs. The UBE workload generates large numbers of PDF files reports and log files. The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently. Oracle's UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute. Key Points and Best Practices Two JD Edwards EnterpriseOne Application Servers, two Oracle WebLogic Servers 11g Release 1 coupled with two Oracle Web Tier HTTP server instances and one Oracle Database 11g Release 2 database on a single SPARC T4-2 server were hosted in separate Oracle Solaris Containers bound to four processor sets to demonstrate consolidation of multiple applications, web servers and the database with best resource utilizations. Interrupt fencing was configured on all Oracle Solaris Containers to channel the interrupts to processors other than the processor sets used for the JD Edwards Application server, Oracle WebLogic servers and the database server. A Oracle WebLogic vertical cluster was configured on each WebServer Container with twelve managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability. The database log writer was run in the real time RT class and bound to a processor set. The database redo logs were configured on the raw disk partitions. The Oracle Solaris Container running the Enterprise Application server completed 61 Short UBEs, 4 Long UBEs concurrently as the mixed size batch workload. The mixed size UBEs ran concurrently from the Enterprise Application server with the 8,000 online users driven by the LoadRunner. See Also SPARC T4-2 Server oracle.com OTN JD Edwards EnterpriseOne oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Oracle Fusion Middleware oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 09/30/2012.

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  • Verizon Wireless Supports its Mission-Critical Employee Portal with MySQL

    - by Bertrand Matthelié
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Cambria","serif"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} Verizon Wireless, the #1 mobile carrier in the United States, operates the nation’s largest 3G and 4G LTE network, with the most subscribers (109 millions) and the highest revenue ($70.2 Billion in 2011). Verizon Wireless built the first wide-area wireless broadband network and delivered the first wireless consumer 3G multimedia service in the US, and offers global voice and data services in more than 200 destinations around the world. To support 4.2 million daily wireless transactions and 493,000 calls and emails transactions produced by 94.2 million retail customers, Verizon Wireless employs over 78,000 employees with area headquarters across the United States. The Business Challenge Seeing the stupendous rise in social media, video streaming, live broadcasting…etc which redefined the scope of technology, Verizon Wireless, as a technology savvy company, wanted to provide a platform to its employees where they could network socially, view and host microsites, stream live videos, blog and provide the latest news. The IT team at Verizon Wireless had abundant experience with various technology platforms to support the huge number of applications in the company. However, open-source products weren’t yet widely used in the organization and the team had the ambition to adopt such technologies and see if the architecture could meet Verizon Wireless’ rigid requirements. After evaluating a few solutions, the IT team decided to use the LAMP stack for Vzweb, its mission-critical, 24x7 employee portal, with Drupal as the front end and MySQL on Linux as the backend, and for a few other internal websites also on MySQL. The MySQL Solution Verizon Wireless started to support its employee portal, Vzweb, its online streaming website, Vztube, and internal wiki pages, Vzwiki, with MySQL 5.1 in 2010. Vzweb is the main internal communication channel for Verizon Wireless, while Vztube hosts important company-wide webcasts regularly for executive-level announcements, so both channels have to be live and accessible all the time for its 78,000 employees across the United States. However during the initial deployment of the MySQL based Intranet, the application experienced performance issues. High connection spikes occurred causing slow user response time, and the IT team applied workarounds to continue the service. A number of key performance indexes (KPI) for the infrastructure were identified and the operational framework redesigned to support a more robust website and conform to the 99.985% uptime SLA (Service-Level Agreement). The MySQL DBA team made a series of upgrades in MySQL: Step 1: Moved from MyISAM to InnoDB storage engine in 2010 Step 2: Upgraded to the latest MySQL 5.1.54 release in 2010 Step 3: Upgraded from MySQL 5.1 to the latest GA release MySQL 5.5 in 2011, and leveraging MySQL Thread Pool as part of MySQL Enterprise Edition to scale better After making those changes, the team saw a much better response time during high concurrency use cases, and achieved an amazing performance improvement of 1400%! In January 2011, Verizon CEO, Ivan Seidenberg, announced the iPhone launch during the opening keynote at Consumer Electronic Show (CES) in Las Vegas, and that presentation was streamed live to its 78,000 employees. The event was broadcasted flawlessly with MySQL as the database. Later in 2011, Hurricane Irene attacked the East Coast of United States and caused major life and financial damages. During the hurricane, the team directed more traffic to its west coast data center to avoid potential infrastructure damage in the East Coast. Such transition was executed smoothly and even though the geographical distance became longer for the East Coast users, there was no impact in the performance of Vzweb and Vztube, and the SLA goal was achieved. “MySQL is the key component of Verizon Wireless’ mission-critical employee portal application,” said Shivinder Singh, senior DBA at Verizon Wireless. “We achieved 1400% performance improvement by moving from the MyISAM storage engine to InnoDB, upgrading to the latest GA release MySQL 5.5, and using the MySQL Thread Pool to support high concurrent user connections. MySQL has become part of our IT infrastructure, on which potentially more future applications will be built.” To learn more about MySQL Enterprise Edition, Get our Product Guide.

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  • FireFox 6 Super Slow? Cache Settings Corruption

    - by Rick Strahl
    For those of you that follow me on Twitter, you've probably seen some of my tweets regarding major performance problems I've seen with the install of FireFox 6.0. FireFox 6.0 was released a couple of weeks ago and is treated as a 'force feed' update for FireFox 5.0. I'm not sure what the deal is with this braindead versioning that Mozilla is doing with major version releases coming out, what now every other month? Seriously that's retarded especially given the limited number of new features these releases bring, and the upgrade pain for plug-ins that the major version release causes. Anyway, after the FireFox updater bugged me long enough I finally gave in last week and updated to FireFox 6. Immediately after install I noticed terrible performance. Everything was running at a snail's pace with Web pages loading slowly and most content actually slowly 'painting' the page. A typical sign of content downloading slowly. However these are pages that should be mostly cached on my system and even repeated accesses ran just as slow. Just for a reality check I ran the same sites in Chrome (blazing fast) and IE (fast enough :-)) but FireFox - dog on a stick. Why so slow Boss? While complaining lots of people recommended to ditch FireFox - use Chrome, yada yada yada. Yeah, Chrome is fast and getting better but I have a number of plug-ins that I use in FF that I can't easily give up. So I suffered and started looking around more closely at what was happening. The first thing I noticed when accessing pages was that I continually saw accesses to the Google CDN downloading jQuery and jQuery UI. UI especially is pretty heavy in size and currently I'm in a location with a fairly slow IP connection where large files are a bit of an issue. However, seeing the CDN urls pop up repeatedly raised a flag with me. That stuff should be caching and it looked like each and every hit was reloading these scripts and various images over and over again. Fired up FireBug and sure enough I saw something like this on a repeated hit to my blog: Those two highlights are jquery and the main CSS file for the site and both are being loaded fully and taking a while to load. However, since this page had been loaded before, these items should be cached and show 304 requests instead of the full HTTP requests returning 200 result codes. In short it looked like FireFox was not caching ANY content at all and constantly reloading all page resources. No wonder things were running dog slow. Once I realized what the problem was I took a look in the about:config settings and lo and behold a bunch of the cache settings were set to not cache: In my case ALL the main cache flags were set to false for some reason that I can't figure out.  It appears that after the FireFox 6 update these flags somehow mysteriously changed and performance took a nose dive. Switching the .enable flags back to true and resetting all the cache settings tote default reverted performance back to the way it's supposed to be: reasonably fast and snappy as soon as content is cached and accessed again  from cache. I try not to muck with the about:config settings much (other than turning off the IPV6 option) but when there are problems access to these features can be really nice. However, I treat this as a last resort so it took me quite some time before I started looking through ALL the settings. This takes a while, not knowing what I was looking for exactly. If Web load performance is slow it's a good idea to check the cache settings. I have no idea what hosed these settings for me - I certainly didn't explicitly set them in about:config and while in FireFox's Options dialog I didn't see any option that would affect global caching like this, so this remains a mystery to me. Anyway, I hope that this is helpful to some, in case some of you end up running into a similar issue.© Rick Strahl, West Wind Technologies, 2005-2011Posted in FireFox   Tweet (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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  • SQL SERVER – SSMS: Top Object and Batch Execution Statistics Reports

    - by Pinal Dave
    The month of June till mid of July has been the fever of sports. First, it was Wimbledon Tennis and then the Soccer fever was all over. There is a huge number of fan followers and it is great to see the level at which people sometimes worship these sports. Being an Indian, I cannot forget to mention the India tour of England later part of July. Following these sports and as the events unfold to the finals, there are a number of ways the statisticians can slice and dice the numbers. Cue from soccer I can surely say there is a team performance against another team and then there is individual member fairs against a particular opponent. Such statistics give us a fair idea to how a team in the past or in the recent past has fared against each other, head-to-head stats during World cup and during other neutral venue games. All these statistics are just pointers. In reality, they don’t reflect the calibre of the current team because the individuals who performed in each of these games are totally different (Typical example being the Brazil Vs Germany semi-final match in FIFA 2014). So at times these numbers are misleading. It is worth investigating and get the next level information. Similar to these statistics, SQL Server Management studio is also equipped with a number of reports like a) Object Execution Statistics report and b) Batch Execution Statistics reports. As discussed in the example, the team scorecard is like the Batch Execution statistics and individual stats is like Object Level statistics. The analogy can be taken only this far, trust me there is no correlation between SQL Server functioning and playing sports – It is like I think about diet all the time except while I am eating. Performance – Batch Execution Statistics Let us view the first report which can be invoked from Server Node -> Reports -> Standard Reports -> Performance – Batch Execution Statistics. Most of the values that are displayed in this report come from the DMVs sys.dm_exec_query_stats and sys.dm_exec_sql_text(sql_handle). This report contains 3 distinctive sections as outline below.   Section 1: This is a graphical bar graph representation of Average CPU Time, Average Logical reads and Average Logical Writes for individual batches. The Batch numbers are indicative and the details of individual batch is available in section 3 (detailed below). Section 2: This represents a Pie chart of all the batches by Total CPU Time (%) and Total Logical IO (%) by batches. This graphical representation tells us which batch consumed the highest CPU and IO since the server started, provided plan is available in the cache. Section 3: This is the section where we can find the SQL statements associated with each of the batch Numbers. This also gives us the details of Average CPU / Average Logical Reads and Average Logical Writes in the system for the given batch with object details. Expanding the rows, I will also get the # Executions and # Plans Generated for each of the queries. Performance – Object Execution Statistics The second report worth a look is Object Execution statistics. This is a similar report as the previous but turned on its head by SQL Server Objects. The report has 3 areas to look as above. Section 1 gives the Average CPU, Average IO bar charts for specific objects. The section 2 is a graphical representation of Total CPU by objects and Total Logical IO by objects. The final section details the various objects in detail with the Avg. CPU, IO and other details which are self-explanatory. At a high-level both the reports are based on queries on two DMVs (sys.dm_exec_query_stats and sys.dm_exec_sql_text) and it builds values based on calculations using columns in them: SELECT * FROM    sys.dm_exec_query_stats s1 CROSS APPLY sys.dm_exec_sql_text(sql_handle) AS s2 WHERE   s2.objectid IS NOT NULL AND DB_NAME(s2.dbid) IS NOT NULL ORDER BY  s1.sql_handle; This is one of the simplest form of reports and in future blogs we will look at more complex reports. I truly hope that these reports can give DBAs and developers a hint about what is the possible performance tuning area. As a closing point I must emphasize that all above reports pick up data from the plan cache. If a particular query has consumed a lot of resources earlier, but plan is not available in the cache, none of the above reports would show that bad query. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: SQL, SQL Authority, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL Tagged: SQL Reports

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  • How to Use Steam In-Home Streaming

    - by Chris Hoffman
    Steam’s In-Home Streaming is now available to everyone, allowing you to stream PC games from one PC to another PC on the same local network. Use your gaming PC to power your laptops and home theater system. This feature doesn’t allow you to stream games over the Internet, only the same local network. Even if you tricked Steam, you probably wouldn’t get good streaming performance over the Internet. Why Stream? When you use Steam In-Home streaming, one PC sends its video and audio to another PC. The other PC views the video and audio like it’s watching a movie, sending back mouse, keyboard, and controller input to the other PC. This allows you to have a fast gaming PC power your gaming experience on slower PCs. For example, you could play graphically demanding games on a laptop in another room of your house, even if that laptop has slower integrated graphics. You could connect a slower PC to your television and use your gaming PC without hauling it into a different room in your house. Streaming also enables cross-platform compatibility. You could have a Windows gaming PC and stream games to a Mac or Linux system. This will be Valve’s official solution for compatibility with old Windows-only games on the Linux (Steam OS) Steam Machines arriving later this year. NVIDIA offers their own game streaming solution, but it requires certain NVIDIA graphics hardware and can only stream to an NVIDIA Shield device. How to Get Started In-Home Streaming is simple to use and doesn’t require any complex configuration — or any configuration, really. First, log into the Steam program on a Windows PC. This should ideally be a powerful gaming PC with a powerful CPU and fast graphics hardware. Install the games you want to stream if you haven’t already — you’ll be streaming from your PC, not from Valve’s servers. (Valve will eventually allow you to stream games from Mac OS X, Linux, and Steam OS systems, but that feature isn’t yet available. You can still stream games to these other operating systems.) Next, log into Steam on another computer on the same network with the same Steam username. Both computers have to be on the same subnet of the same local network. You’ll see the games installed on your other PC in the Steam client’s library. Click the Stream button to start streaming a game from your other PC. The game will launch on your host PC, and it will send its audio and video to the PC in front of you. Your input on the client will be sent back to the server. Be sure to update Steam on both computers if you don’t see this feature. Use the Steam > Check for Updates option within Steam and install the latest update. Updating to the latest graphics drivers for your computer’s hardware is always a good idea, too. Improving Performance Here’s what Valve recommends for good streaming performance: Host PC: A quad-core CPU for the computer running the game, minimum. The computer needs enough processor power to run the game, compress the video and audio, and send it over the network with low latency. Streaming Client: A GPU that supports hardware-accelerated H.264 decoding on the client PC. This hardware is included on all recent laptops and PCs. Ifyou have an older PC or netbook, it may not be able to decode the video stream quickly enough. Network Hardware: A wired network connection is ideal. You may have success with wireless N or AC networks with good signals, but this isn’t guaranteed. Game Settings: While streaming a game, visit the game’s setting screen and lower the resolution or turn off VSync to speed things up. In-Home Steaming Settings: On the host PC, click Steam > Settings and select In-Home Streaming to view the In-Home Streaming settings. You can modify your streaming settings to improve performance and reduce latency. Feel free to experiment with the options here and see how they affect performance — they should be self-explanatory. Check Valve’s In-Home Streaming documentation for troubleshooting information. You can also try streaming non-Steam games. Click Games > Add a Non-Steam Game to My Library on your host PC and add a PC game you have installed elsewhere on your system. You can then try streaming it from your client PC. Valve says this “may work but is not officially supported.” Image Credit: Robert Couse-Baker on Flickr, Milestoned on Flickr

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  • EPM and Business Analytics Talking-head Videos from Oracle OpenWorld 2013

    - by Mike.Hallett(at)Oracle-BI&EPM
    Normal 0 false false false EN-GB X-NONE X-NONE Here is a selection of 2 to 3 minute video interviews at this year’s Oracle OpenWorld: 1. George Somogyi, Solutions Architect, New Edge Group, talks about the importance of having their integrated Oracle Hyperion Platform consisting of Oracle Hyperion Financial Management, Oracle Hyperion Financial Data Quality Management, Oracle E-Business Suite R12 and Oracle Business Intelligence Extended Edition plus their use of Oracle Managed Cloud Services. Speaker: George Somogyi @ http://youtu.be/kWn0dQxCUy8 2. Gregg Thompson, Director of Financial Systems for ADT, talks about using Oracle Data Relationship Management prior to implementing an Enterprise Performance Management solution. Gregg confirmed that there are big benefits to bringing the full Oracle Hyperion Financial Close suite online with Oracle DRM as the metadata source. Reduced maintenance time and use of external consultants translates into significant time and cost savings and faster implementation times. Speaker: Gregg Thompson @ http://youtu.be/XnFrR9Uk4xk 3. Jeff Spangler, Director Financial Planning and Analysis for Speedy Cash Holdings Corp, talked to us about the benefits achieved through implementing Oracle Hyperion Planning and financial reporting solutions. He also describes how the use of Data Relationship Management will keep the process running smoothly now and in the future. Speaker: Jeff Spangler @ http://youtu.be/kkkuMkgJ22U 4. Marc Seewald, Senior Director of Product Management for Oracle Hyperion Tax Provision at Oracle, talks about Oracle Hyperion Tax Provision, how it is an integral part of the financial close process and that it provides better internal controls and automation of this task. Marc talks about Oracle Partners and customers alike who are seeing great value. Speaker: Marc Seewald @ http://youtu.be/lM_nfvACGuA 5. Matt Bradley, SVP of Product Development for Enterprise Performance Management (EPM) Applications at Oracle, talked to us about different deployment options for Oracle EPM. Cloud services (SaaS), managed services, on-premise, off-premise all have their merits, and organizations need flexibility to easily move between them as their companies evolve. Speaker: Matt Bradley @ http://youtu.be/ATO7Z9dbE-o 6. Neil Sellers, Partner, Qubix International talks about their experience with previewing Oracle’s new Planning and Budgeting Cloud Service. He describes the benefits of the step-by-step task lists, the speed of getting the application up and running, and the huge benefits of not having to manage the software and hardware side of the planning process. Speaker: Neil Sellers @ http://youtu.be/xmosO28e4_I 7. Praveen Pasupuleti, Senior Business Intelligence Development Manager of Citrix Systems Inc., talks about their Oracle Hyperion Planning upgrade and the huge performance improvement now experienced in forecasting. He also talked about the benefits of Oracle Hyperion Workforce Planning achieved by Citrix. Speaker: Praveen Pasupuleti @ http://youtu.be/d1e_4hLqw8c 8. CheckPoint Consulting, talked to us about how Enterprise Performance Management should be viewed as an entire solution, rather than as a bunch of applications in silos, to provide significant benefits; and how Data Relationship Management can tie it all together effectively. Speaker: Ron Dimon @ http://youtu.be/sRwbdbbXvUE 9. Sonal Kulkarni, Enterprise Performance Management Leader, Cummins Inc., talks about their use of Oracle Hyperion Financial Close Management (Account Reconciliation Manager), Oracle Hyperion Financial Management and Oracle Hyperion Financial Data Quality Management and how this is providing efficiency, visibility and compliance benefits. Speaker: Sonal Kulkarni @ http://youtu.be/OEgup5dKyVc 10. Todd Renard, Manager Financial Planning and Business Analytics for B/E Aerospace Inc., talks about the huge benefits that B/E Aerospace is experiencing from Oracle Financial Close Suite. He was extremely excited about Oracle Hyperion Financial Data Quality Management and how this helps them integrate a new business in as little as three weeks. Speaker: Todd Renard @ http://youtu.be/nIfqK46uVI8 11. Peter Smolianski, Chief Technology Officer for the District of Columbia Courts, talked to us about how D.C. Courts is using Oracle Scorecard and Strategy Management to push their 5 year plan forward, to report results to their constituents, and take accountability for process changes to become more efficient. Speaker: Peter Smolianski @ http://www.youtube.com/watch?v=T-DtB5pl-uk 12. Rich Wilkie, Senior Director of Product Management for Financial Close Suite at Oracle, talked to us about Oracle Financial Management Analytics. He told us how the prebuilt dashboards on top of Oracle Hyperion Financial Close Suite make it easy for everyone to see the numbers and understand where they are in the close process, and if there is an issue, they can see where it is. Executives are excited to get this information on mobile devices too. Speaker: Rich Wilkie @ http://www.youtube.com/watch?v=4UHuHgx74Yg 13. Dinesh Balebail, Senior Director of Software Development for Oracle Hyperion Profitability and Cost Management, talked to us about the power and speed of Oracle Hyperion Profitability and Cost Management and how it is being used to do deep costing for Telecoms, Hospitals, Banks and other high transaction volume organizations effectively. Speaker: Dinesh Balebail @ http://youtu.be/ivx5AZCXAfs /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman"; mso-ansi-language:EN-US; mso-fareast-language:EN-US;}

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  • What's New In 11.1.2.1 (Talleyrand SP1)

    - by russ.bishop
    This release is primarily about bug fixes and that's what we spent the most time on, but we also addressed a number of other things: 1. Performance improvements We've done a lot of work to improve the performance of page load and execution times. For example, the View Compare page is about half the size it was previously! We've also done a lot of work on the server to improve performance of queries, exports, action scripts, etc. We implemented some finer-grained locking so fewer operations will block other users while they are in progress. We made some optimizations to improve performance when you have a lot of network or database latency as well. Just a few examples: An Import that previously took 8 GB of memory and hours to complete now runs in about 30 minutes and never takes more than 1 GB of RAM. Searching by exact Node Name now completes within 2 seconds even for a hierarchy with millions of nodes. Another search that was taking 30 seconds to run now completes in less than 5 seconds. 2. Upgrade support This release supports automatic upgrade from previous releases, built right into the console. 3. Console Improvements The Console has been reorganized and made easier to use. It is also much more multi-threaded so it responds quicker without freezing up when you save changes or when it needs to get status. 4. Property Namespaces Properties now have a concept called a Namespace. This is tied into the Application Templates to prevent conflicts with duplicate property names. Right now, if you have an AccountType and you pull in the HFM template, it also has AccountType so you end up creating properties with decorations on the name like "Account Type (HFM)". This is no longer necessary. In addition, properties within a namespace must have unique labels but they can be duplicated across namespaces. So in the Property Grid when you click on the HFM category, you just see "AccountType". When you click on MyCategory, you see "AccountType", but they are different properties with different values. Within formulas, the names are still unique (eg: Custom.AccountType vs HFM.AccountType). I'll write more about this one later. 5. Single Sign On DRM now supports Single Sign-On via HSS. For example, if you are using Oracle's OAM as your SSO solution then you configure HSS to use OAM just like you would before. You also configure DRM to use HSS, again just like before. Then you configure OAM to protect the DRM web app, like you would any other website. However once you do those things, users are no longer prompted to enter their username/password. They simply get redirected to OAM if they don't already have a login token, otherwise they pick their application and sail right into DRM. You can also avoid having to pick an application (see the next item) 6. URL-based navigation You can now specify the application you want to log into via the URL. Combined with SSO and your Intranet, it becomes easy to provide links on our intranet portal that take users directly into a specific DRM application. We also support specifying the Version, Hierarchy, and Node. Again, this can be used on your internal portal, but the scenarios get even more interesting when you are using workflow like Oracle BPEL you can automatically generate links within emails that will take users directly to a specific node in the UI. 7. Job status and cancellation A lot of the jobs now report their status and support true cancellation. Action Scripts also report a progress complete percentage since the amount of work is known ahead of time. 8. Action Script Options Action scripts support Option declarations at the top of the file so a script can self-describe (when specified in the file, the corresponding item in the file is ignored). For example: Option|DetectDelimiter Option|UsePropertyNames|true This will tell DRM to automatically detect the delimiter (a pipe symbol in this case) and that all references to properties are by Name, not by Label. Note that when you load a script in the UI, if you use Labels we automatically try to match them up if they are unique. Any duplicates are indicated and you are presented with a choice to pick which property you actually referred to. This is somewhat similar to Version substitution, but tailored for properties. There are other more minor changes and like I said earlier a lot of bug fixes and performance improvements. Hopefully I will get a chance to dig into some of these things in future blog posts.

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  • Some non-generic collections

    - by Simon Cooper
    Although the collections classes introduced in .NET 2, 3.5 and 4 cover most scenarios, there are still some .NET 1 collections that don't have generic counterparts. In this post, I'll be examining what they do, why you might use them, and some things you'll need to bear in mind when doing so. BitArray System.Collections.BitArray is conceptually the same as a List<bool>, but whereas List<bool> stores each boolean in a single byte (as that's what the backing bool[] does), BitArray uses a single bit to store each value, and uses various bitmasks to access each bit individually. This means that BitArray is eight times smaller than a List<bool>. Furthermore, BitArray has some useful functions for bitmasks, like And, Xor and Not, and it's not limited to 32 or 64 bits; a BitArray can hold as many bits as you need. However, it's not all roses and kittens. There are some fundamental limitations you have to bear in mind when using BitArray: It's a non-generic collection. The enumerator returns object (a boxed boolean), rather than an unboxed bool. This means that if you do this: foreach (bool b in bitArray) { ... } Every single boolean value will be boxed, then unboxed. And if you do this: foreach (var b in bitArray) { ... } you'll have to manually unbox b on every iteration, as it'll come out of the enumerator an object. Instead, you should manually iterate over the collection using a for loop: for (int i=0; i<bitArray.Length; i++) { bool b = bitArray[i]; ... } Following on from that, if you want to use BitArray in the context of an IEnumerable<bool>, ICollection<bool> or IList<bool>, you'll need to write a wrapper class, or use the Enumerable.Cast<bool> extension method (although Cast would box and unbox every value you get out of it). There is no Add or Remove method. You specify the number of bits you need in the constructor, and that's what you get. You can change the length yourself using the Length property setter though. It doesn't implement IList. Although not really important if you're writing a generic wrapper around it, it is something to bear in mind if you're using it with pre-generic code. However, if you use BitArray carefully, it can provide significant gains over a List<bool> for functionality and efficiency of space. OrderedDictionary System.Collections.Specialized.OrderedDictionary does exactly what you would expect - it's an IDictionary that maintains items in the order they are added. It does this by storing key/value pairs in a Hashtable (to get O(1) key lookup) and an ArrayList (to maintain the order). You can access values by key or index, and insert or remove items at a particular index. The enumerator returns items in index order. However, the Keys and Values properties return ICollection, not IList, as you might expect; CopyTo doesn't maintain the same ordering, as it copies from the backing Hashtable, not ArrayList; and any operations that insert or remove items from the middle of the collection are O(n), just like a normal list. In short; don't use this class. If you need some sort of ordered dictionary, it would be better to write your own generic dictionary combining a Dictionary<TKey, TValue> and List<KeyValuePair<TKey, TValue>> or List<TKey> for your specific situation. ListDictionary and HybridDictionary To look at why you might want to use ListDictionary or HybridDictionary, we need to examine the performance of these dictionaries compared to Hashtable and Dictionary<object, object>. For this test, I added n items to each collection, then randomly accessed n/2 items: So, what's going on here? Well, ListDictionary is implemented as a linked list of key/value pairs; all operations on the dictionary require an O(n) search through the list. However, for small n, the constant factor that big-o notation doesn't measure is much lower than the hashing overhead of Hashtable or Dictionary. HybridDictionary combines a Hashtable and ListDictionary; for small n, it uses a backing ListDictionary, but switches to a Hashtable when it gets to 9 items (you can see the point it switches from a ListDictionary to Hashtable in the graph). Apart from that, it's got very similar performance to Hashtable. So why would you want to use either of these? In short, you wouldn't. Any gain in performance by using ListDictionary over Dictionary<TKey, TValue> would be offset by the generic dictionary not having to cast or box the items you store, something the graphs above don't measure. Only if the performance of the dictionary is vital, the dictionary will hold less than 30 items, and you don't need type safety, would you use ListDictionary over the generic Dictionary. And even then, there's probably more useful performance gains you can make elsewhere.

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  • Part 1 - Load Testing In The Cloud

    - by Tarun Arora
    Azure is fascinating, but even more fascinating is the marriage of Azure and TFS! Introduction Recently a client I worked for had 2 major business critical applications being delivered, with very little time budgeted for Performance testing, we immediately hit a bottleneck when the performance testing phase started, the in house infrastructure team could not support the hardware requirements in the short notice. It was suggested that the performance testing be performed on one of the QA environments which was a fraction of the production environment. This didn’t seem right, the team decided to turn to the cloud. The team took advantage of the elasticity offered by Azure, starting with a single test agent which was provisioned and ready for use with in 30 minutes the team scaled up to 17 test agents to perform a very comprehensive performance testing cycle. Issues were identified and resolved but the highlight was that the cost of running the ‘test rig’ proved to be less than if hosted on premise by the infrastructure team. Thank you for taking the time out to read this blog post, in the series of posts, I’ll try and cover the start to end of everything you need to know to use Azure to build your Test Rig in the cloud. But Why Azure? I have my own Data Centre… If the environment is provisioned in your own datacentre, - No matter what level of service agreement you may have with your infrastructure team there will be down time when the environment is patched - How fast can you scale up or down the environments (keeping the enterprise processes in mind) Administration, Cost, Flexibility and Scalability are the areas you would want to think around when taking the decision between your own Data Centre and Azure! How is Microsoft's Public Cloud Offering different from Amazon’s Public Cloud Offering? Microsoft's offering of the Cloud is a hybrid of Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) which distinguishes Microsoft's offering from other providers such as Amazon (Amazon only offers IaaS). PaaS – Platform as a Service IaaS – Infrastructure as a Service Fills the needs of those who want to build and run custom applications as services. Similar to traditional hosting, where a business will use the hosted environment as a logical extension of the on-premises datacentre. A service provider offers a pre-configured, virtualized application server environment to which applications can be deployed by the development staff. Since the service providers manage the hardware (patching, upgrades and so forth), as well as application server uptime, the involvement of IT pros is minimized. On-demand scalability combined with hardware and application server management relieves developers from infrastructure concerns and allows them to focus on building applications. The servers (physical and virtual) are rented on an as-needed basis, and the IT professionals who manage the infrastructure have full control of the software configuration. This kind of flexibility increases the complexity of the IT environment, as customer IT professionals need to maintain the servers as though they are on-premises. The maintenance activities may include patching and upgrades of the OS and the application server, load balancing, failover clustering of database servers, backup and restoration, and any other activities that mitigate the risks of hardware and software failures.   The biggest advantage with PaaS is that you do not have to worry about maintaining the environment, you can focus all your time in solving the business problems with your solution rather than worrying about maintaining the environment. If you decide to use a VM Role on Azure, you are asking for IaaS, more on this later. A nice blog post here on the difference between Saas, PaaS and IaaS. Now that we are convinced why we should be turning to the cloud and why in specific Azure, let’s discuss about the Test Rig. The Load Test Rig – Topology Now the moment of truth, Of course a big part of getting value from cloud computing is identifying the most adequate workloads to take to the cloud, so I’ve decided to try to make a Load Testing rig where the Agents are running on Windows Azure.   I’ll talk you through the above Topology, - User: User kick starts the load test run from the developer workstation on premise. This passes the request to the Test Controller. - Test Controller: The Test Controller is on premise connected to the same domain as the developer workstation. As soon as the Test Controller receives the request it makes use of the Windows Azure Connect service to orchestrate the test responsibilities to all the Test Agents. The Windows Azure Connect endpoint software must be active on all Azure instances and on the Controller machine as well. This allows IP connectivity between them and, given that the firewall is properly configured, allows the Controller to send work loads to the agents. In parallel, the Controller will collect the performance data from the agents, using the traditional WMI mechanisms. - Test Agents: The Test Agents are on the Windows Azure Public Cloud, as soon as the test controller issues instructions to the test agents, the test agents start executing the load tests. The HTTP requests are issued against the web server on premise, the results are captured by the test agents. And finally the results are passed over to the controller. - Servers: The Web Server and DB Server are hosted on premise in the datacentre, this is usually the case with business critical applications, you probably want to manage them your self. Recap and What’s next? So, in the introduction in the series of blog posts on Load Testing in the cloud I highlighted why creating a test rig in the cloud is a good idea, what advantages does Windows Azure offer and the Test Rig topology that I will be using. I would also like to mention that i stumbled upon this [Video] on Azure in a nutshell, great watch if you are new to Windows Azure. In the next post I intend to start setting up the Load Test Environment and discuss pricing with respect to test agent machine types that will be used in the test rig. Hope you enjoyed this post, If you have any recommendations on things that I should consider or any questions or feedback, feel free to add to this blog post. Remember to subscribe to http://feeds.feedburner.com/TarunArora.  See you in Part II.   Share this post : CodeProject

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  • To My 24 Year Old Self, Wherever You Are&hellip;

    - by D'Arcy Lussier
    A decade is a milestone in one’s life, regardless of when it occurs. 2011 might seem like a weird year to mark a decade, but 2001 was a defining year for me. It marked my emergence into the technology industry, an unexpected loss of innocence, and triggered an ongoing struggle with faith and belief. Once you go through a valley, climbing the mountain and looking back over where you travelled, you can take in the entirety of the journey. Over the last 10 years I kept journals, and in this new year I took some time to review them. For those today that are me a decade ago, I share with you what I’ve gleamed from my experiences. Take it for what it’s worth, and safe travels on your own journeys through life. Life is a Performance-Based Sport Have confidence, believe you’re capable, but realize that life is a performance-based sport. Everything you get in life is based on whether you can show that you deserve it. Performance is also your best defense against personal attacks. Just make sure you know what standards you’re expected to hit and if people want to poke holes at you let them do the work of trying to find them. Sometimes performance won’t matter though. Good things will happen to bad people, and bad things to good people. What’s important is that you do the right things and ensure the good and bad even out in your own life. How you finish is just as important as how you start. Start strong, end strong. Respect is Your Most Prized Reward Respect is more important than status or ego. The formula is simple: Performing Well + Building Trust + Showing Dedication = Respect Focus on perfecting your craft and helping your team and respect will come. Life is a Team Sport Whatever aspect of your life, you can’t do it alone. You need to rely on the people around you and ensure you’re a positive aspect of their lives; even those that may be difficult or unpleasant. Avoid criticism and instead find ways to help colleagues and superiors better whatever environment you’re in (work, home, etc.). Don’t just highlight gaps and issues, but also come to the table with solutions. At the same time though, stand up for yourself and hold others accountable for the commitments they make to the team. A healthy team needs accountability. Give feedback early and often, and make it verbal. Issues should be dealt with immediately, and positives should be celebrated as they happen. Life is a Contact Sport Difficult moments will happen. Don’t run from them or shield yourself from experiencing them. Embrace them. They will further mold you and reveal who you will become. Find Your Tribe and Embrace Your Community We all need a tribe: a group of people that we gravitate to for support, guidance, wisdom, and friendship. Discover your tribe and immerse yourself in them. Don’t look for a non-existent tribe just to fill the need of belonging though that will leave you empty and bitter when they don’t meet your unrealistic expectations. Try to associate with people more experienced and more knowledgeable than you. You’ll always learn, and you’ll always remember you have much to learn. Put yourself out there, get involved with the community. Opportunities will present themselves. When we open ourselves up to be vulnerable, we also give others the chance to do the same. This helps us all to grow and help each other, it’s very important. And listen to your wife. (Easter *is* a romantic holiday btw, regardless of what you may think.) Don’t Believe Your Own Press Clippings (and by that I mean the ones you write) Until you have a track record of performance to refer to, any notions of grandeur are just that: notions. You lose your rookie status through trials and tribulations, not by the number of stamps in your passport. Be realistic about your own “experience and leadership” and be honest when you aren’t ready for something. And always remember: nobody really cares about you as much as you think they do. Don’t Let Assholes Get You Down The world isn’t evil, but there is evil in the world. Know the difference and don’t paint all people with the same brush. Do be wary of those that use personal beliefs to describe their business (i.e. “We’re a [religion] company”). What matters is the culture of the organization, and that will tell you the moral compass and what is truly valued. Don’t make someone or something a priority that only makes you an option. Life is unfair and enemies/opponents will succeed when you fail. Don’t waste your energy getting upset at this; the only one that will lose out is you. As mentioned earlier, nobody really cares about you as much as you think they do. Misc Ecclesiastes is bullshit. Everything is certainly *not* meaningless. Software development is about delivery, not the process. Having a great process means nothing if you don’t produce anything. Watch “The Weatherman” (“It’s not easy, but easy doesn’t enter into grownup life.”). Read Tony Dungee’s autobiography, even if you don’t like football, and even if you aren’t a Christian. Say no, don’t feel like you have to commit right away when someone asks you to.

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