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  • Extreme Performance and Scale Delivered by SOA on Oracle Exalogic

    - by J Swaroop
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* 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:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Calibri","sans-serif"; mso-ascii- mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi- mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* 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:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Calibri","sans-serif"; mso-ascii- mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi- mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Demands to incorporate internet-scale applications, data, and social media traffic with existing IT infrastructure require extreme availability, reliability, and scalability. In this session on industrial-strength SOA, learn how Oracle Exalogic and Oracle Exadata engineered systems address these requirements. Topics covered: (1) how SOA and BPM benefit from “hardware and software engineered for each other,” (2) how Oracle Exadata provides the data tier with unparalleled scalability and performance for SOA and BPM running on Oracle Exalogic (3) customer case studies (4) best practices and topology guidelines (5) information on tools that help operate, manage, provision, and deploy—to help reduce overall TCO. Extreme engineering at its best! Session details: 10/2/12 (Tuesday) 11:45 AM - Moscone South -308

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  • Would you expect this error ?

    - by GrumpyOldDBA
    Now I know why, but what I'm thinking is that if I create an error should I get valid data returned? To explain, I was browsing through the dmvs for queries which might benefit from tuning and I identified a query with two clustered index scans ( table scans ). I don't know all the schema off by heart and I was looking for a select by a LoginID column. I assumed this would be numeric and promptly entered an integer value to examine the query plan, yeah I should have looked at the table definition...(read more)

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  • Ubuntu 12.10 64 bits not booting on a Dell Inspiron 15z Puissance (French) in UEFI mode

    - by NicoGuich
    When trying to start Ubuntu from my USB key in UEFI mode (it works in Legacy mode, but I have to keep Windows) on a Dell Inspiron 15z , Grub starts, but when I choose any option, I get a black screen and my USB key stop teling me it is being read. EDIT: when using the legacy mode and trying to install Ubuntu, I get a blank partition table with Ubiquity… … and a very strange partition table from GParted (I have a hybrid 32Go SSD + 500Go HDD disk) :

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  • Determining distribution of NULL values

    - by AaronBertrand
    Today on the twitter hash tag #sqlhelp, @leenux_tux asked: How can I figure out the percentage of fields that don't have data ? After further clarification, it turns out he is after what proportion of columns are NULL. Some folks suggested using a data profiling task in SSIS . There may be some validity to that, but I'm still a fan of sticking to T-SQL when I can, so here is how I would approach it: Create a #temp table or @table variable to store the results. Create a cursor that loops through all...(read more)

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  • Increasing deadlocks with NoLock

    - by Dave Ballantyne
    One on my personnel pet issues is with inappropriate use of the NOLOCK hint (and read uncommitted) .  Dont get me wrong, I have used it in exceptional circumstances , but as a general statement it is a bad thing.  Mostly , when NOLOCK, is used the discussion is around a single statement,  “it runs faster with nolock for XYZ reason”,  however ,IMO, this is quite a shorted sighted view.  What about the Transaction ? What about other concurrent users ?  What is good for one statement in isolation , does not mean that it is good for the system as a whole.  I have seen on a number of occasions deadlocks happen, when tasks that would of(and should of) be blocked continue to execute, only for a deadlock to occur at a later data writing (INSERT,UPDATE,DELETE) statement.  Writers will block writers regardless of isolation level. By Way of (fairly contrived ) example , lets generate some dummy tables and populate with some data drop table a go drop table b go Create Table a ( col1 integer ) go insert into a values(1) insert into a values(2) go Create Table b ( col1 integer ) go insert into b values(1) insert into b values(2) go   Now make two connections. In connection one execute set transaction isolation level read committed BEGIN TRAN Select * from a Select * from b delete from a In connection two execute set transaction isolation level read committed BEGIN TRAN Select * from a Select * from b delete from b Right now the ‘select from a’ in connection two is being blocked by the ‘delete from a’ in connection one.  This is ,IMO, quite a healthy and natural thing to be happening , some see this as a ‘slow down’, a drop in performance.  So, lets reach for our ‘NOLOCK’ magic pill.  Cancel the blocked query and ROLLBACK both transactions, then in connection one execute set transaction isolation level read uncommitted BEGIN TRAN Select * from a Select * from b delete from b and then in connection two execute set transaction isolation level read uncommitted BEGIN TRAN Select * from a Select * from b delete from a We have now solved out performance problem , no more blocking.  Lets finish the work required by the transaction, in connection one , execute delete from a Oh, ‘ performance problem’ again , its now being blocked. Still, lets complete the work in connection two…. delete from b DEADLOCK!!  It is important to be clear about the role of the select statements.  They do not participate within the deadlock, but are preventing code executing that would of.   Additionally, without the select readers to block, a deadlock would occur on the deletes with READ COMMITTED. Naturally, other isolation levels will exhibit different behaviour as to where and when they will and wont block,  and I would encourage you to read BOL and satisfy yourself that you really do NEED to NOLOCK.

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  • Is hashing of just "username + password" as safe as salted hashing

    - by randomA
    I want to hash "user + password". EDIT: prehashing "user" would be an improvement, so my question is also for hashing "hash(user) + password". If cross-site same user is a problem then the hashing changed to hashing "hash(serviceName + user) + password" From what I read about salted hash, using "user + password" as input to hash function will help us avoid problem with reverse hash table hacking. The same thing can be said about rainbow table. Any reason why this is not as good as salted hashing?

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  • T4 Performance Counters explained

    - by user13346607
    Now that T4 is out for a few month some people might have wondered what details of the new pipeline you can monitor. A "cpustat -h" lists a lot of events that can be monitored, and only very few are self-explanatory. I will try to give some insight on all of them, some of these "PIC events" require an in-depth knowledge of T4 pipeline. Over time I will try to explain these, for the time being these events should simply be ignored. (Side note: some counters changed from tape-out 1.1 (*only* used in the T4 beta program) to tape-out 1.2 (used in the systems shipping today) The table only lists the tape-out 1.2 counters) 0 0 1 1058 6033 Oracle Microelectronics 50 14 7077 14.0 Normal 0 false false false EN-US JA 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-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:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} pic name (cpustat) Prose Comment Sel-pipe-drain-cycles, Sel-0-[wait|ready], Sel-[1,2] Sel-0-wait counts cycles a strand waits to be selected. Some reasons can be counted in detail; these are: Sel-0-ready: Cycles a strand was ready but not selected, that can signal pipeline oversubscription Sel-1: Cycles only one instruction or µop was selected Sel-2: Cycles two instructions or µops were selected Sel-pipe-drain-cycles: cf. PRM footnote 8 to table 10.2 Pick-any, Pick-[0|1|2|3] Cycles one, two, three, no or at least one instruction or µop is picked Instr_FGU_crypto Number of FGU or crypto instructions executed on that vcpu Instr_ld dto. for load Instr_st dto. for store SPR_ring_ops dto. for SPR ring ops Instr_other dto. for all other instructions not listed above, PRM footnote 7 to table 10.2 lists the instructions Instr_all total number of instructions executed on that vcpu Sw_count_intr Nr of S/W count instructions on that vcpu (sethi %hi(fc000),%g0 (whatever that is))  Atomics nr of atomic ops, which are LDSTUB/a, CASA/XA, and SWAP/A SW_prefetch Nr of PREFETCH or PREFETCHA instructions Block_ld_st Block loads or store on that vcpu IC_miss_nospec, IC_miss_[L2_or_L3|local|remote]\ _hit_nospec Various I$ misses, distinguished by where they hit. All of these count per thread, but only primary events: T4 counts only the first occurence of an I$ miss on a core for a certain instruction. If one strand misses in I$ this miss is counted, but if a second strand on the same core misses while the first miss is being resolved, that second miss is not counted This flavour of I$ misses counts only misses that are caused by instruction that really commit (note the "_nospec") BTC_miss Branch target cache miss ITLB_miss ITLB misses (synchronously counted) ITLB_miss_asynch dto. but asynchronously [I|D]TLB_fill_\ [8KB|64KB|4MB|256MB|2GB|trap] H/W tablewalk events that fill ITLB or DTLB with translation for the corresponding page size. The “_trap” event occurs if the HWTW was not able to fill the corresponding TLB IC_mtag_miss, IC_mtag_miss_\ [ptag_hit|ptag_miss|\ ptag_hit_way_mismatch] I$ micro tag misses, with some options for drill down Fetch-0, Fetch-0-all fetch-0 counts nr of cycles nothing was fetched for this particular strand, fetch-0-all counts cycles nothing was fetched for all strands on a core Instr_buffer_full Cycles the instruction buffer for a strand was full, thereby preventing any fetch BTC_targ_incorrect Counts all occurences of wrongly predicted branch targets from the BTC [PQ|ROB|LB|ROB_LB|SB|\ ROB_SB|LB_SB|RB_LB_SB|\ DTLB_miss]\ _tag_wait ST_q_tag_wait is listed under sl=20. These counters monitor pipeline behaviour therefore they are not strand specific: PQ_...: cycles Rename stage waits for a Pick Queue tag (might signal memory bound workload for single thread mode, cf. Mail from Richard Smith) ROB_...: cycles Select stage waits for a ROB (ReOrderBuffer) tag LB_...: cycles Select stage waits for a Load Buffer tag SB_...: cycles Select stage waits for Store Buffer tag combinations of the above are allowed, although some of these events can overlap, the counter will only be incremented once per cycle if any of these occur DTLB_...: cycles load or store instructions wait at Pick stage for a DTLB miss tag [ID]TLB_HWTW_\ [L2_hit|L3_hit|L3_miss|all] Counters for HWTW accesses caused by either DTLB or ITLB misses. Canbe further detailed by where they hit IC_miss_L2_L3_hit, IC_miss_local_remote_remL3_hit, IC_miss I$ prefetches that were dropped because they either miss in L2$ or L3$ This variant counts misses regardless if the causing instruction commits or not DC_miss_nospec, DC_miss_[L2_L3|local|remote_L3]\ _hit_nospec D$ misses either in general or detailed by where they hit cf. the explanation for the IC_miss in two flavours for an explanation of _nospec and the reasoning for two DC_miss counters DTLB_miss_asynch counts all DTLB misses asynchronously, there is no way to count them synchronously DC_pref_drop_DC_hit, SW_pref_drop_[DC_hit|buffer_full] L1-D$ h/w prefetches that were dropped because of a D$ hit, counted per core. The others count software prefetches per strand [Full|Partial]_RAW_hit_st_[buf|q] Count events where a load wants to get data that has not yet been stored, i. e. it is still inside the pipeline. The data might be either still in the store buffer or in the store queue. If the load's data matches in the SB and in the store queue the data in buffer takes precedence of course since it is younger [IC|DC]_evict_invalid, [IC|DC|L1]_snoop_invalid, [IC|DC|L1]_invalid_all Counter for invalidated cache evictions per core St_q_tag_wait Number of cycles pipeline waits for a store queue tag, of course counted per core Data_pref_[drop_L2|drop_L3|\ hit_L2|hit_L3|\ hit_local|hit_remote] Data prefetches that can be further detailed by either why they were dropped or where they did hit St_hit_[L2|L3], St_L2_[local|remote]_C2C, St_local, St_remote Store events distinguished by where they hit or where they cause a L2 cache-to-cache transfer, i.e. either a transfer from another L2$ on the same die or from a different die DC_miss, DC_miss_\ [L2_L3|local|remote]_hit D$ misses either in general or detailed by where they hit cf. the explanation for the IC_miss in two flavours for an explanation of _nospec and the reasoning for two DC_miss counters L2_[clean|dirty]_evict Per core clean or dirty L2$ evictions L2_fill_buf_full, L2_wb_buf_full, L2_miss_buf_full Per core L2$ buffer events, all count number of cycles that this state was present L2_pipe_stall Per core cycles pipeline stalled because of L2$ Branches Count branches (Tcc, DONE, RETRY, and SIT are not counted as branches) Br_taken Counts taken branches (Tcc, DONE, RETRY, and SIT are not counted as branches) Br_mispred, Br_dir_mispred, Br_trg_mispred, Br_trg_mispred_\ [far_tbl|indir_tbl|ret_stk] Counter for various branch misprediction events.  Cycles_user counts cycles, attribute setting hpriv, nouser, sys controls addess space to count in Commit-[0|1|2], Commit-0-all, Commit-1-or-2 Number of times either no, one, or two µops commit for a strand. Commit-0-all counts number of times no µop commits for the whole core, cf. footnote 11 to table 10.2 in PRM for a more detailed explanation on how this counters interacts with the privilege levels

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  • Sending HTML to Gmail always lands in Spam

    - by cartaysm
    I am having an issue with sending HTML emails to Gmail. I can send them to Yahoo, Hotmail, RR, AOL, etc. with no problem at all, but when I send them to Gmail I get kicked to spam. I have checked my IP with a lot of different list to make sure it is not listed anywhere, which it is not. spamhaus = is not listed in the DBL abuse.net = is not listed in the SBL abuse.net = is not listed in the PBL abuse.net = is not listed in the XBL spamcop = not listed in bl.spamcop.net host 24.172.204.xxx xxx.204.172.24.in-addr.arpa domain name pointer xxxevents.com. host xxxevents.com xxxevents.com has address 24.172.204.xxx xxxevents.com mail is handled by 10 mail.xxxevents.com. I am just trying to send a very VERY basic HTML message (listed below). I use an Ubuntu server, swiftmailer, multipart/alternative (HTML & plain), SPF = pass, and I am going to setup DKIM today to see if that fixes it (but I doubt it will)... For now I will only post the message I sent that gets kicked to spam and can provide any details needed. <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head><title>Triathlon</title></head> <body> <table cellpadding="0" cellspacing="0"> <tr> <td> <p>Thank you for attending our 4th annual Triathlon/Duathlon/5k at Hueston Woods State Park on August 12th. This event is held annually to raise research funding for Crohn's Disease, Ulcerative Colitis, and Muscular Dystrophy diseases.</p> </td> </tr> <tr> <td> <p>As you know the results and pictures have been posted on our home page at since Sunday 8/13/2012. Now we also have updated our Facebook page with those photos and you can start tagging yourself or downloading the pictures now! <br /> our page and tag yourself at </p> <p> test test </p> <p>Race day events is professionally managed by Speedy-Feet</p> </td> </tr> </table> </body> </html> Just plain text works great, I thought maybe wording was messing me up but not the case... I am almost done install opendkim so I will be able to rule that out very soon. Edit: Okay installed opendkim and I am getting passing results so I sent the html I posted above it went through just fine. So now when I start to add a few more lines I am getting kicked back to spam again. Here is updated html code: ` <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head><title>Triathlon</title></head> <body> <table cellpadding="0" cellspacing="0"> <tr> <td> <center><a href='http://xxxevents.com' target="_blank"> <font face="Verdana, Arial, Helvetica, sans-serif" color="#666666" size="2"> <img src="http://xxxevents.com/marketemailimages/xxxlogo.png" alt="xxx It Events | Raising funds for Crohns, Colitis, and Muscular Dystrophy" border="0" /> </font></a></center> </td> <tr> <td> <p>Thank you for attending our 4th annual Triathlon/Duathlon/5k at Hueston Woods State Park on August 12th. This event is held annually to raise research funding for Crohn's Disease, Ulcerative Colitis, and Muscular Dystrophy diseases.</p> </td> </tr> <tr> <td> <p>As you know the results and pictures have been posted on our home page at since Sunday 8/13/2012. Now we also have updated our Facebook page with those photos and you can start tagging yourself or downloading the pictures now! <br /> our page and tag yourself at </p> <p> test test </p> <p>Race day events is professionally managed by Speedy-Feet</p> </td> </tr> </table> <table width="100%" border="0" cellspacing="0" cellpadding="0"> <tr> <td valign="top"> <div align="center" style="font-family:Verdana, Arial, Helvetica, sans-serif; font-size:10px;"><br />PO Box xxx Maineville, OH 45039<br /> <a href="mailto:[email protected]">[email protected]</a> | <a href='http://xxxevents.com' target="_blank">xxxevents.com</a><br /> <br /> </div> </td> </tr> </table> </body> </html>`

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  • SQL SERVER – Reseting Identity Values for All Tables

    - by pinaldave
    Sometime email requesting help generates more questions than the motivation to answer them. Let us go over one of the such examples. I have converted the complete email conversation to chat format for easy consumption. I almost got a headache after around 20 email exchange. I am sure if you can read it and feel my pain. DBA: “I deleted all of the data from my database and now it contains table structure only. However, when I tried to insert new data in my tables I noticed that my identity values starts from the same number where they actually were before I deleted the data.” Pinal: “How did you delete the data?” DBA: “Running Delete in Loop?” Pinal: “What was the need of such need?” DBA: “It was my development server and I needed to repopulate the database.” Pinal: “Oh so why did not you use TRUNCATE which would have reset the identity of your table to the original value when the data got deleted? This will work only if you want your database to reset to the original value. If you want to set any other value this may not work.” DBA: (silence for 2 days) DBA: “I did not realize it. Meanwhile I regenerated every table’s schema and dropped the table and re-created it.” Pinal: “Oh no, that would be extremely long and incorrect way. Very bad solution.” DBA: “I understand, should I just take backup of the database before I insert the data and when I need, I can use the original backup to restore the database. This way I will have identity beginning with 1.” Pinal: “This going totally downhill. It is wrong to do so on multiple levels. Did you even read my earlier email about TRUNCATE.” DBA: “Yeah. I found it in spam folder.” Pinal: (I decided to stay silent) DBA: (After 2 days) “Can you provide me script to reseed identity for all of my tables to value 1 without asking further question.” Pinal: USE DATABASE; EXEC sp_MSForEachTable ' IF OBJECTPROPERTY(object_id(''?''), ''TableHasIdentity'') = 1 DBCC CHECKIDENT (''?'', RESEED, 1)' GO Our conversation ended here. If you have directly jumped to this statement, I encourage you to read the conversation one time. There is difference between reseeding identity value to 1 and reseeding it to original value – I will write an another blog post on this subject in future. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL CE 3.5 and the ‘SELECT TOP’ Query

    - by stevewarren
    Finally! SQL CE 3.5 now supports the ‘TOP’ keyword. However, there is a trick to this: you must surround the number with parenthesis. For example, in regular T-SQL you would write SELECT TOP N [col] FROM [table] However, in SQL CE 3.5 you must write SELECT TOP (N) [col] FROM [table]

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  • Mobile BI Comes of Age

    - by rich.clayton(at)oracle.com
    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:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} 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:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* 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:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} One of the hot topics in the Business Intelligence industry is mobility.  More specifically the question is how business can be transformed by the iPhone and the iPad.  In June 2003, Gartner predicted that Mobile BI would be obsolete and that the technology was headed for the 'trough of disillusionment'.  I agreed with them at that time.  Many vendors like MicroStrategy and Business Objects jumped into the fray attempting to show how PDA's like Palm Pilots could be integrated with BI.  Their investments resulted in interesting demos with no commercial traction.  Why, because wireless networks and mobile operating systems were primitive, immature and slow. In my opinion, Apple's iOS has changed everything in Mobile BI.  Yes Blackberry, Android and Symbian and all the rest have their place in the market but I believe that increasingly consumers (not IT departments) influence BI decision making processes.  Consumers are choosing the iPhone and the iPad. The number of iPads I see in business meetings now is staggering.  Some use it for email and note taking and others are starting to use corporate applications.  The possibilities for Mobile BI are countless and I would expect to see iPads enterprise-wide over the next few years.   These new devices will provide just-in-time access to critical business information.  Front-line managers interacting with customers, suppliers, patients or citizens will have information literally at their fingertips. I've experimented with several mobile BI tools.  They look cool but like their Executive Information System (EIS) predecessors of the 1990's these tools lack a backbone and a plausible integration strategy.  EIS was a viral technology in the early 1990's.  Executives from every industry and job function were showcasing their dashboards to fellow co-workers and colleagues at the country club.  Just like the iPad, every senior manager wanted one.  EIS wasn't a device however, it was a software application.   EIS quickly faded into the software sunset as it lacked integration with corporate information systems.  BI servers  replaced EIS because the technology focused on the heavy data lifting of integrating, normalizing, aggregating and managing large, complex data volumes.  The devices are here to stay. The cute stand-alone mobile BI tools, not so much. If all you're looking to do is put Excel files on your iPad, there are plenty of free tools on the market.  You'll look cool at your next management meeting but after a few weeks, the cool factor will fade away and you'll be wondering how you will ever maintain it.  If however you want secure, consistent, reliable information on your iPad, you need an integration strategy and a way to model the data.  BI Server technologies like the Oracle BI Foundation is a market leading approach to tackle that issue. I liken the BI mobility frenzy to buying classic cars.  Classic Cars have two buying groups - teenagers and middle-age folks looking to tinker.  Teenagers look at the pin-stripes and the paint job while middle-agers (like me)  kick the tires a bit and look under the hood to check out the quality and reliability of the engine.  Mobile BI tools sure look sexy but don't go very far without an engine and a transmission or an integration strategy. The strategic question in Mobile BI is can these startups build a motor and transmission faster than Oracle can re-paint the car?  Oracle has a great engine and a transmission that connects to all enterprise information assets.  We're working on the new paint job and are excited about the possibilities.  Just as vertical integration worked in the automotive business, it too works in the technology industry.

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  • When is a Seek not a Seek?

    - by Paul White
    The following script creates a single-column clustered table containing the integers from 1 to 1,000 inclusive. IF OBJECT_ID(N'tempdb..#Test', N'U') IS NOT NULL DROP TABLE #Test ; GO CREATE TABLE #Test ( id INTEGER PRIMARY KEY CLUSTERED ); ; INSERT #Test (id) SELECT V.number FROM master.dbo.spt_values AS V WHERE V.[type] = N'P' AND V.number BETWEEN 1 AND 1000 ; Let’s say we need to find the rows with values from 100 to 170, excluding any values that divide exactly by 10.  One way to write that query would be: SELECT T.id FROM #Test AS T WHERE T.id IN ( 101,102,103,104,105,106,107,108,109, 111,112,113,114,115,116,117,118,119, 121,122,123,124,125,126,127,128,129, 131,132,133,134,135,136,137,138,139, 141,142,143,144,145,146,147,148,149, 151,152,153,154,155,156,157,158,159, 161,162,163,164,165,166,167,168,169 ) ; That query produces a pretty efficient-looking query plan: Knowing that the source column is defined as an INTEGER, we could also express the query this way: SELECT T.id FROM #Test AS T WHERE T.id >= 101 AND T.id <= 169 AND T.id % 10 > 0 ; We get a similar-looking plan: If you look closely, you might notice that the line connecting the two icons is a little thinner than before.  The first query is estimated to produce 61.9167 rows – very close to the 63 rows we know the query will return.  The second query presents a tougher challenge for SQL Server because it doesn’t know how to predict the selectivity of the modulo expression (T.id % 10 > 0).  Without that last line, the second query is estimated to produce 68.1667 rows – a slight overestimate.  Adding the opaque modulo expression results in SQL Server guessing at the selectivity.  As you may know, the selectivity guess for a greater-than operation is 30%, so the final estimate is 30% of 68.1667, which comes to 20.45 rows. The second difference is that the Clustered Index Seek is costed at 99% of the estimated total for the statement.  For some reason, the final SELECT operator is assigned a small cost of 0.0000484 units; I have absolutely no idea why this is so, or what it models.  Nevertheless, we can compare the total cost for both queries: the first one comes in at 0.0033501 units, and the second at 0.0034054.  The important point is that the second query is costed very slightly higher than the first, even though it is expected to produce many fewer rows (20.45 versus 61.9167). If you run the two queries, they produce exactly the same results, and both complete so quickly that it is impossible to measure CPU usage for a single execution.  We can, however, compare the I/O statistics for a single run by running the queries with STATISTICS IO ON: Table '#Test'. Scan count 63, logical reads 126, physical reads 0. Table '#Test'. Scan count 01, logical reads 002, physical reads 0. The query with the IN list uses 126 logical reads (and has a ‘scan count’ of 63), while the second query form completes with just 2 logical reads (and a ‘scan count’ of 1).  It is no coincidence that 126 = 63 * 2, by the way.  It is almost as if the first query is doing 63 seeks, compared to one for the second query. In fact, that is exactly what it is doing.  There is no indication of this in the graphical plan, or the tool-tip that appears when you hover your mouse over the Clustered Index Seek icon.  To see the 63 seek operations, you have click on the Seek icon and look in the Properties window (press F4, or right-click and choose from the menu): The Seek Predicates list shows a total of 63 seek operations – one for each of the values from the IN list contained in the first query.  I have expanded the first seek node to show the details; it is seeking down the clustered index to find the entry with the value 101.  Each of the other 62 nodes expands similarly, and the same information is contained (even more verbosely) in the XML form of the plan. Each of the 63 seek operations starts at the root of the clustered index B-tree and navigates down to the leaf page that contains the sought key value.  Our table is just large enough to need a separate root page, so each seek incurs 2 logical reads (one for the root, and one for the leaf).  We can see the index depth using the INDEXPROPERTY function, or by using the a DMV: SELECT S.index_type_desc, S.index_depth FROM sys.dm_db_index_physical_stats ( DB_ID(N'tempdb'), OBJECT_ID(N'tempdb..#Test', N'U'), 1, 1, DEFAULT ) AS S ; Let’s look now at the Properties window when the Clustered Index Seek from the second query is selected: There is just one seek operation, which starts at the root of the index and navigates the B-tree looking for the first key that matches the Start range condition (id >= 101).  It then continues to read records at the leaf level of the index (following links between leaf-level pages if necessary) until it finds a row that does not meet the End range condition (id <= 169).  Every row that meets the seek range condition is also tested against the Residual Predicate highlighted above (id % 10 > 0), and is only returned if it matches that as well. You will not be surprised that the single seek (with a range scan and residual predicate) is much more efficient than 63 singleton seeks.  It is not 63 times more efficient (as the logical reads comparison would suggest), but it is around three times faster.  Let’s run both query forms 10,000 times and measure the elapsed time: DECLARE @i INTEGER, @n INTEGER = 10000, @s DATETIME = GETDATE() ; SET NOCOUNT ON; SET STATISTICS XML OFF; ; WHILE @n > 0 BEGIN SELECT @i = T.id FROM #Test AS T WHERE T.id IN ( 101,102,103,104,105,106,107,108,109, 111,112,113,114,115,116,117,118,119, 121,122,123,124,125,126,127,128,129, 131,132,133,134,135,136,137,138,139, 141,142,143,144,145,146,147,148,149, 151,152,153,154,155,156,157,158,159, 161,162,163,164,165,166,167,168,169 ) ; SET @n -= 1; END ; PRINT DATEDIFF(MILLISECOND, @s, GETDATE()) ; GO DECLARE @i INTEGER, @n INTEGER = 10000, @s DATETIME = GETDATE() ; SET NOCOUNT ON ; WHILE @n > 0 BEGIN SELECT @i = T.id FROM #Test AS T WHERE T.id >= 101 AND T.id <= 169 AND T.id % 10 > 0 ; SET @n -= 1; END ; PRINT DATEDIFF(MILLISECOND, @s, GETDATE()) ; On my laptop, running SQL Server 2008 build 4272 (SP2 CU2), the IN form of the query takes around 830ms and the range query about 300ms.  The main point of this post is not performance, however – it is meant as an introduction to the next few parts in this mini-series that will continue to explore scans and seeks in detail. When is a seek not a seek?  When it is 63 seeks © Paul White 2011 email: [email protected] twitter: @SQL_kiwi

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  • Clustered Index

    - by Derek Dieter
    The clustered index on a table can be defined as: the sort order for how the data for the table is actually stored. Being that the clustered index is the actual data itself, you cannot have two clustered indexes. You can however have many non clustered indexes. These non clustered indexes are [...]

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  • SQL Server Add Primary Key

    - by Derek D.
    Adding a primary key can be done either after a table is created, or at the same a table is created. It is important to note, that by default a primary key is clustered. This may or may not be the preferred method of creation. For more information on clustered vs non [...]

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  • 7 Good Reasons to Upgrade E-Business Suite to the cloud

    - by Lisa Schwartz
    v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} As promised here is blog Part 2: Why Upgrade to Oracle E-Business Suite 12 in the cloud? 7 Good Reasons to Upgrade to E-Business Suite 12 in the Cloud: 1)   Take advantage of new and improved features: from global sub-ledger accounting to mobile access for supply chain management to built-in extensions for information search and discovery. If you haven’t checked out the latest features yet, there are over 1000 EBS 12 enhancements. 2) Plan now to address any ongoing Oracle Support considerations and regulatory compliance requirements. EBS Release 11 support is ending soon. Based upon that information alone, you should have an EBS upgrade strategy and planning well underway. 3) Customizations got you worried? Expedite your next Oracle E-Business Suite upgrade – have Oracle identify all customizations, reduce un-needed customizations (EBS 12 has built-in many of your customizations) and during the upgrade keep all necessary customizations to run your business. 4) Migrating EBS to the cloud allows parallel migration and testing. Therefore no extra hardware purchases for the testing and upgrade. Business disruption is minimized. And, by moving to the cloud, this provides for smoother future upgrades that are based on your own timeline. 5) Oracle Experts will upgrade and run your EBS applications for you in the cloud. Free your IT resources to develop new services and work on projects that are critical to business innovation and competitiveness. Your IT resources will not be inundated with upgrade tasks!      6) Reallocate precious IT dollars to other projects, eliminate CapEx costs. 7) Oracle minimizes business risk by having enterprise class cloud services under stringent SLAs designed to run your business applications for you such as: a. Enterprise grade infrastructure b. World-class security and identity management c. Best practices in regulatory compliance: from classified federal gov’t standards, to healthcare HIPPA standards to meeting Financial Services requirements (PCI DSS) 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-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} 7 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-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Next Step: To help you upgrade and get to the cloud in the shortest period of  time, Oracle has a program called Oracle Upgrade Factory for Oracle E-Business Suite 12. It offers a unique approach, seamlessly bundling Managed Cloud Services and Oracle Consulting Services together for an entire Oracle E-Business Suite upgrade and migration to a managed private  cloud. Read the Oracle Upgrade Factory Solution Brief here. Normal 0 false 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-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

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  • Fun with Aggregates

    - by Paul White
    There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

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  • SQL SERVER – Weekly Series – Memory Lane – #031

    - by Pinal Dave
    Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Find Table without Clustered Index – Find Table with no Primary Key Clustered index is very important concept for any table. They impact the performance very heavily. Here is a quick script to find tables without a clustered index. Replace TEXT with VARCHAR(MAX) – Stop using TEXT, NTEXT, IMAGE Data Types Question: “Is VARCHAR (MAX) big enough to store the TEXT field?” Answer: “Yes, VARCHAR(MAX) is big enough to accommodate TEXT field. TEXT, NTEXT and IMAGE data types of SQL Server 2000 will be deprecated in a future version of SQL Server, SQL Server 2005 provides backward compatibility to data types but it is recommended to use new data types which are VARHCAR (MAX), NVARCHAR (MAX) and VARBINARY (MAX).” Limiting Result Sets by Using TABLESAMPLE – Examples Introduced in SQL Server 2005, TABLESAMPLE allows you to extract a sampling of rows from a table in the FROM clause. The rows retrieved are random and they are are not in any order. This sampling can be based on a percentage of number of rows. You can use TABLESAMPLE when only a sampling of rows is necessary for the application instead of a full result set. User Defined Functions (UDF) Limitations UDF have its own advantage and usage but in this article we will see the limitation of UDF. Things UDF can not do and why Stored Procedure are considered as more flexible then UDFs. Stored Procedure are more flexibility then User Defined Functions(UDF). However, this blog post is a good read to know what are the limitations of UDF. Change Database Compatible Level – Backward Compatibility For a long time SQL Server stayed on the compatibility level of 80 which is of SQL Server 2000. However, as soon as SQL Server 2005 introduced the issue of compatibility was quite a major issue. Since that time MS has been releasing the versions at every 2-3 years, changing compatibility is a ever popular topic. In this blog post, we learn how we can do the same using T-SQL. We can also do the same using SSMS and here is the blog post for the same: Change Database Compatible Level – Backward Compatibility – Part 2 – Management Studio. Constraint on VARCHAR(MAX) Field To Limit It Certain Length How can I limit the VARCHAR(MAX) field with maximum length of 12500 characters only. His Question was valid as our application was allowed 12500 characters. First of all – this requirement is bit strange but if someone wants to do the same, they can do it as described in this blog post. 2008 UNPIVOT Table Example Understanding UNPIVOT can be very complicated at times. In this blog post, I have attempted to explain the same concept in very simple words. Create Default Constraint Over Table Column A simple straight to script blog post – I still use this blog quite many times for my own reference. UDF – Get the Day of the Week Function It took me 4 iteration to find this very simple function which can immediately get the day of the week in a single line. 2009 Find Hostname and Current Logged In User Name There are two tricks listed in this blog post where users can find out the hostname and current logged user name immediately and very easily. Interesting Observation of Logon Trigger On All Servers When I was doing a project, I made an interesting observation of executing a logon trigger multiple times. It was absolutely unexpected for me! As I was logging only once, naturally, I was expecting the entry only once. However, it did it multiple times on different threads – indeed an eccentric phenomenon at first sight! Difference Between Candidate Keys and Primary Key One needs to be very careful in selecting the Primary Key as an incorrect selection can adversely impact the database architect and future normalization. For a Candidate Key to qualify as a Primary Key, it should be Non-NULL and unique in any domain. I have observed quite often that Primary Keys are seldom changed. I would like to have your feedback on not changing a Primary Key. Create Multiple Filegroup For Single Database Why should one create multiple file group for any database and what are the advantages of the same. In this blog post, I explain the same in detail. List All Objects Created on All Filegroups in Database In this blog post we discuss the essential question – “How can I find which object belongs to which filegroup. Is there any way to know this?” 2010 DATE and TIME in SQL Server 2008 When DATE is converted to DATETIME it adds the of midnight. When TIME is converted to DATETIME it adds the date of 1900 and it is something one wants to consider if you are going to run scripts from SQL Server 2008 to earlier version with CONVERT. Disabled Index and Update Statistics If you do not need a nonclustered index, I suggest you to drop it as keeping them disabled is an overhead on your system. This is because every time the statistics are updated for system all the statistics for disabled indexes are also updated. Precision of SMALLDATETIME – A 1 Minute Precision The precision of the datatype SMALLDATETIME is 1 minute. It discards the seconds by rounding up or rounding down any seconds greater than zero. 2011 Getting Columns Headers without Result Data – SET FMTONLY ON SET FMTONLY ON returns only metadata to the client. It can be used to test the format of the response without actually running the query. When this setting is ON the resultset only have headers of the results but no data. Copy Database from Instance to Another Instance – Copy Paste in SQL Server SQL Server has a feature which copy database from one database to another database and it can be automated as well using SSIS. Make sure you have SQL Server Agent Turned on as this feature will create a job. Puzzle – SELECT * vs SELECT COUNT(*) If you have ever wondered SELECT * gives error when executed alone but SELECT COUNT(*) does not. Why? in that case, you should read this blog post. Creating All New Database with Full Recovery Model This blog post is very based on very interesting story where the user wants to do something by default for every single new database created. Model database is a secret weapon which should be used very carefully and with proper evalution. If used carefully this can be a very much beneficiary when we need a newly created database behave in certain fashion. 2012 In year 2012 I had two interesting series ran on the blog. If there is no fun in learning, the learning becomes a burden. For the same reason, I had decided to build a three part quiz around SEQUENCE. The quiz was to identify the next value of the sequence. I encourage all of you to take part in this fun quiz. Guess the Next Value – Puzzle 1 Guess the Next Value – Puzzle 2 Guess the Next Value – Puzzle 3 Can anyone remember their final day of schooling?  This is probably a silly question because – of course you can!  Many people mark this as the most exciting, happiest day of their life.  It marks the end of testing, the end of following rules set by teachers, and the beginning of finally being able to earn money and work in your chosen field. Read five part series on developer training subject Developer Training - Importance and Significance - Part 1 Developer Training – Employee Morals and Ethics – Part 2 Developer Training – Difficult Questions and Alternative Perspective - Part 3 Developer Training – Various Options for Developer Training – Part 4 Developer Training – A Conclusive Summary- Part 5 Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Checking who is connected to your server, with PowerShell.

    - by Fatherjack
    There are many occasions when, as a DBA, you want to see who is connected to your SQL Server, along with how they are connecting and what sort of activities they are carrying out. I’m going to look at a couple of ways of getting this information and compare the effort required and the results achieved of each. SQL Server comes with a couple of stored procedures to help with this sort of task – sp_who and its undocumented counterpart sp_who2. There is also the pumped up version of these called sp_whoisactive, written by Adam Machanic which does way more than these procedures. I wholly recommend you try it out if you don’t already know how it works. When it comes to serious interrogation of your SQL Server activity then it is absolutely indispensable. Anyway, back to the point of this blog, we are going to look at getting the information from sp_who2 for a remote server. I wrote this Powershell script a week or so ago and was quietly happy with it for a while. I’m relatively new to Powershell so forgive both my rather low threshold for entertainment and the fact that something so simple is a moderate achievement for me. $Server = 'SERVERNAME' $SMOServer = New-Object Microsoft.SQLServer.Management.SMO.Server $Server # connection and query stuff         $ConnectionStr = "Server=$Server;Database=Master;Integrated Security=True" $Query = "EXEC sp_who2" $Connection = new-object system.Data.SQLClient.SQLConnection $Table = new-object "System.Data.DataTable" $Connection.connectionstring = $ConnectionStr try{ $Connection.open() $Command = $Connection.CreateCommand() $Command.commandtext = $Query $result = $Command.ExecuteReader() $Table.Load($result) } catch{ # Show error $error[0] | format-list -Force } $Title = "Data access processes (" + $Table.Rows.Count + ")" $Table | Out-GridView -Title $Title $Connection.close() So this is pretty straightforward, create an SMO object that represents our chosen server, define a connection to the database and a table object for the results when we get them, execute our query over the connection, load the results into our table object and then, if everything is error free display these results to the PowerShell grid viewer. The query simply gets the results of ‘EXEC sp_who2′ for us. Depending on how many connections there are will influence how long the query runs. The grid viewer lets me sort and search the results so it can be a pretty handy way to locate troublesome connections. Like I say, I was quite pleased with this, it seems a pretty simple script and was working well for me, I have added a few parameters to control the output and give me more specific details but then I see a script that uses the $SMOServer object itself to provide the process information and saves having to define the connection object and query specifications. $Server = 'SERVERNAME' $SMOServer = New-Object Microsoft.SQLServer.Management.SMO.Server $Server $Processes = $SMOServer.EnumProcesses() $Title = "SMO processes (" + $Processes.Rows.Count + ")" $Processes | Out-GridView -Title $Title Create the SMO object of our server and then call the EnumProcesses method to get all the process information from the server. Staggeringly simple! The results are a little different though. Some columns are the same and we can see the same basic information so my first thought was to which runs faster – so that I can get my results more quickly and also so that I place less stress on my server(s). PowerShell comes with a great way of testing this – the Measure-Command function. All you have to do is wrap your piece of code in Measure-Command {[your code here]} and it will spit out the time taken to execute the code. So, I placed both of the above methods of getting SQL Server process connections in two Measure-Command wrappers and pressed F5! The Powershell console goes blank for a while as the code is executed internally when Measure-Command is used but the grid viewer windows appear and the console shows this. You can take the output from Measure-Command and format it for easier reading but in a simple comparison like this we can simply cross refer the TotalMilliseconds values from the two result sets to see how the two methods performed. The query execution method (running EXEC sp_who2 ) is the first set of timings and the SMO EnumProcesses is the second. I have run these on a variety of servers and while the results vary from execution to execution I have never seen the SMO version slower than the other. The difference has varied and the time for both has ranged from sub-second as we see above to almost 5 seconds on other systems. This difference, I would suggest is partly due to the cost overhead of having to construct the data connection and so on where as the SMO EnumProcesses method has the connection to the server already in place and just needs to call back the process information. There is also the difference in the data sets to consider. Let’s take a look at what we get and where the two methods differ Query execution method (sp_who2) SMO EnumProcesses Description - Urn What looks like an XML or JSON representation of the server name and the process ID SPID Spid The process ID Status Status The status of the process Login Login The login name of the user executing the command HostName Host The name of the computer where the  process originated BlkBy BlockingSpid The SPID of a process that is blocking this one DBName Database The database that this process is connected to Command Command The type of command that is executing CPUTime Cpu The CPU activity related to this process DiskIO - The Disk IO activity related to this process LastBatch - The time the last batch was executed from this process. ProgramName Program The application that is facilitating the process connection to the SQL Server. SPID1 - In my experience this is always the same value as SPID. REQUESTID - In my experience this is always 0 - Name In my experience this is always the same value as SPID and so could be seen as analogous to SPID1 from sp_who2 - MemUsage An indication of the memory used by this process but I don’t know what it is measured in (bytes, Kb, Mb…) - IsSystem True or False depending on whether the process is internal to the SQL Server instance or has been created by an external connection requesting data. - ExecutionContextID In my experience this is always 0 so could be analogous to REQUESTID from sp_who2. Please note, these are my own very brief descriptions of these columns, detail can be found from MSDN for columns in the sp_who results here http://msdn.microsoft.com/en-GB/library/ms174313.aspx. Where the columns are common then I would use that description, in other cases then the information returned is purely for interpretation by the reader. Rather annoyingly both result sets have useful information that the other doesn’t. sp_who2 returns Disk IO and LastBatch information which is really useful but the SMO processes method give you IsSystem and MemUsage which have their place in fault diagnosis methods too. So which is better? On reflection I think I prefer to use the sp_who2 method primarily but knowing that the SMO Enumprocesses method is there when I need it is really useful and I’m sure I’ll use it regularly. I’m OK with the fact that it is the slower method because Measure-Command has shown me how close it is to the other option and that it really isn’t a large enough margin to matter.

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  • Hierarchies on Steroids #2: A Replacement for Nested Sets Calculations

    In this sequel to his first "Hierarchies on Steroids" article, SQL Server MVP Jeff Moden shows us how to build a pre-aggregated table that will answer most of the questions that you could ask of a typical hierarchy. Any bets on whether Santa is packin’ a Tally Table in his bag or not? 12 essential tools for database professionalsThe SQL Developer Bundle contains 12 tools designed with the SQL Server developer and DBA in mind. Try it now.

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  • Auditing database source code changes

    - by John Paul Cook
    Auditing changes to database source code can be easily implemented with a database trigger. Here’s a simple implementation of stored procedure auditing using an audit table and a database trigger. It assumes that a schema named Audit already exists. CREATE TABLE Audit . AuditStoredProcedures ( DatabaseName sysname , ObjectName sysname , LoginName sysname , ChangeDate datetime , EventType sysname , EventDataXml xml ); Notice the EventDataXml column. Using an nvarchar column to store the source text...(read more)

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  • More on PHP and Oracle 11gR2 Improvements to Client Result Caching

    - by christopher.jones
    Oracle 11.2 brought several improvements to Client Result Caching. CRC is way for the results of queries to be cached in the database client process for reuse.  In an Oracle OpenWorld presentation "Best Practices for Developing Performant Application" my colleague Luxi Chidambaran had a (non-PHP generated) graph for the Niles benchmark that shows a DB CPU reduction up to 600% and response times up to 22% faster when using CRC. Sometimes CRC is called the "Consistent Client Cache" because Oracle automatically invalidates the cache if table data is changed.  This makes it easy to use without needing application logic rewrites. There are a few simple database settings to turn on and tune CRC, so management is also easy. PHP OCI8 as a "client" of the database can use CRC.  The cache is per-process, so plan carefully before caching large data sets.  Tables that are candidates for caching are look-up tables where the network transfer cost dominates. CRC is really easy in 11.2 - I'll get to that in a moment.  It was also pretty easy in Oracle 11.1 but it needed some tiny application changes.  In PHP it was used like: $s = oci_parse($c, "select /*+ result_cache */ * from employees"); oci_execute($s, OCI_NO_AUTO_COMMIT); // Use OCI_DEFAULT in OCI8 <= 1.3 oci_fetch_all($s, $res); I blogged about this in the past.  The query had to include a specific hint that you wanted the results cached, and you needed to turn off auto committing during execution either with the OCI_DEFAULT flag or its new, better-named alias OCI_NO_AUTO_COMMIT.  The no-commit flag rule didn't seem reasonable to me because most people wouldn't be specific about the commit state for a query. Now in Oracle 11.2, DBAs can now nominate tables for caching, either with CREATE TABLE or ALTER TABLE.  That means you don't need the query hint anymore.  As well, the no-commit flag requirement has been lifted.  Your code can now look like: $s = oci_parse($c, "select * from employees"); oci_execute($s); oci_fetch_all($s, $res); Since your code probably already looks like this, your DBA can find the top queries in the database and simply tune the system by turning on CRC in the database and issuing an ALTER TABLE statement for candidate tables.  Voila. Another CRC improvement in Oracle 11.2 is that it works with DRCP connection pooling. There is some fine print about what is and isn't cached, check the Oracle manuals for details.  If you're using 11.1 or non-DRCP "dedicated servers" then make sure you use oci_pconnect() persistent connections.  Also in PHP don't bind strings in the query, although binding as SQLT_INT is OK.

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  • EXALYTICS - If Oracle BI Server Does Not Fail Over to the TimesTen Instance

    - by Ahmed Awan
    If the BI Server does not fail over to the second TimesTen instance on the scaled-out node, then ensure that the logical table source (LTS) for the repository has mapped both TimesTen physical data sources. This mapping ensures that at the logical table source level, a mapping exists to both TimesTen instances. If one TimesTen instance is not available, then failover logic for the BI Server at the DSN level tries to connect to the other TimesTen instance. Reference: http://docs.oracle.com/cd/E23943_01/bi.1111/e24706/toc.htm

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  • Using ASP.NET Membership Provider with an ACL

    - by geekrutherford
    Up until recently one of my applications has used the membership provider within ASP.NET exclusively. However, it has been proposed that while the currently defined roles are beneficial, security needs to be more granular to restrict both access to certain pages and functionality present within a given page.   Unfortunately, the role based security ASP.NET gives you out of the box falls down in this area. This is not due to a lack of foresight by Microsoft, but rather it was simply not designed for implementing both role based security and any inherent ACL you may define within these roles. Mind you some would say an ACL is independent of the role to which a user belongs and is assigned to the user directly.   The application mentioned here has it's own User object (which encapsulates the membership provider user object as a property) and SQL Server table to store extended information not present in the aspnet_users table. While I could have modified the aspnet membership schema to suit the applications needs, it seemed smarter to simply create a separate table with a foreign key back to the aspnet_users table.   Since I have a separate object to store extended user information, I simply created an ACL object and expose it as a property of my user object.   This is all well and good, but it does not help in regards to the SiteMapProvider and restricting access at the page level based on the users ACL.   The straightforward answer would be to develop some code within the databound event for the menu that checks the page title and has hardcoded logic that dictates a user must have certain permissions turned on. The problem with this approach is that it's HARDCODED!!! If you need to change access to a page you'd need to do a build and go through your normal deployment process....ugh!!!   An alternative method, albeit not perfect, is to utilize the resourceKey property on the SiteMapNodes in the SiteMap file with the name of the required permission to view the page. Within the databound event for your menu you iterate the SiteMapNodes in the menus SiteMapProvider looking for a match at the page level based on title. When a match is detected, you have a switch/case on the SiteMapNodes resourceKey (the name of the ACL permission required). The case for the resourceKey ensures the users ACL permission is turned on and viola!!!   This is noteably not perfect in that it is using the resourceKey in a manner other than intended.  Since the application is not localized, using it in the manner described it not an issue.   Below is a sample SiteMap file with the resourceKey used as the ACL permission identifier:     Below is the ItemDataBound event. This application uses the Telerik Menu control:

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  • SQL Server Max TinyInt Value

    - by Derek Dieter
    The maximum value for a tinyint in SQL Server is: 0 through 255 And the byte size is: 1 byte other maximum values: BigInt: -9223372036854775808 through 9223372036854775807 (8 bytes) Int: -2147483648 through 2147483647 (4 bytes) SmallInt: -32768 through 32767 (2 bytes) Related Posts:»SQL Server Max SmallInt Value»SQL Server Max Int Value»SQL Server Bigint Max Value»Create Date Table»Dynamic Numbers Table

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  • I'm blogging again, and about time too

    - by fatherjack
    No, seriously, this one is about time. I recently had an issue in a work database where a query was giving random results, sometimes the query would return a row and other times it wouldn't. There was quite a bit of work distilling the query down to find the reason for this and I'll try to explain by demonstrating what was happening by using some sample data in a table with rather a contrived use case. Let's assume we have a table that is designed to have a start and end date for something, maybe...(read more)

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